United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical Report

RMRS-GTR-30WWW

October 1999

Ecology and

Conservation

of Lynx in the

United States

Leonard F. Ruggiero

Keith B. Aubry

Steven W. Buskirk

Gary M. Koehler

Charles J. Krebs

Kevin S. McKelvey

John R. Squires

World Wide Web version
Abstract

Ruggiero, Leonard F.; Aubry, Keith B.; Buskirk, Steven W.; Koehler, Gary M.; Krebs, Charles J.;

McKelvey, Kevin S.; Squires, John R. Ecology and conservation of lynx in the United States.

General Technical Report RMRS-GTR-30WWW. Fort Collins, CO: U.S. Department of

Agriculture, Forest Service, Rocky Mountain Research Station. Available at:

http://www.fs.fed.us/rm/pubs/rmrs_gtr030.html

Once found throughout the Rocky Mountains and forests of the northern states, the lynx now

hides in pockets of its former range while feeding mostly on small animals like snowshoe

hares. A team of government and university scientists review the newest scientific knowledge

of this unique cat’s history, distribution, and ecology. The chapters on this web site provide

information for current scientific and public debates regarding the fate of the lynx in the United

States. Chapters look at the relationships among lynx, its habitat, and its prey. The attributes

of northern versus southern lynx populations are compared and contrasted. The authors

caution against making decisions without enough knowledge and show where we lack

information. While the authors present the latest preliminary research results on lynx and offer

some qualified insights into lynx management, the book’s intent is to assess the current state

of knowledge regarding lynx.

Hard copies of the report will be available in late 1999 from the University Press of Colorado,

P.O. Box 849, Niwot, CO 80544.

The Authors

Leonard F. Ruggiero is a scientist at the Rocky Mountain Research Station’s Forestry

Sciences Lab in Missoula, MT.

Keith B. Aubry is a scientist at the Pacific Northwest Research Station in Olympia,

WA.

Steven W. Buskirk is professor of zoology and physiology at University of Wyoming in Laramie.

Gary M. Koehler is research biologist with the Washington Department of Fish &

Wildlife in Olympia, WA.

Charles J. Krebs is professor of zoology at the University of British Columbia.

Kevin S. McKelvey is a scientist at the Rocky Mountain Research Station’s Forestry

Sciences Lab in Missoula, MT.

John R. Squires is a research associate at the University of Montana in Missoula.

The use of trade or firm names in this publication is for reader information and does not

imply endorsement by the U.S. Department of Agriculture or any product or service
Contents

Page

Preface Ecology and Conservation of Lynx in the United States ............................. 1

Chapter 1 Toward a Defensible Lynx Conservation Strategy:

A Framework for Planning in the Face of Uncertainty ................................ 5

Leonard F. Ruggiero

Kevin S. McKelvey

Chapter 2 Theoretical Insights into the Population Viability of Lynx .......................... 21

Kevin S. McKelvey

Steven W. Buskirk

Charles J. Krebs

Chapter 3 Disturbance Ecology of North American Boreal Forests

and Associated Northern Mixed/Subalpine Forests .................................. 39

James K. Agee

Chapter 4 Habitat Fragmentation and Interspecific Competition:

Implications for Lynx Conservation ........................................................... 83

Steven W. Buskirk

Chapter 5 Species Conservation and Natural Variation

Among Populations ................................................................................. 101

Leonard F. Ruggiero

Michael K. Schwartz

Keith B. Aubry

Charles J. Krebs

Amanda Stanley

Steven W. Buskirk

Chapter 6 The Ecology of Snowshoe Hares in Northern

Boreal Forests ......................................................................................... 117

Karen E. Hodges

Chapter 7 Ecology of Snowshoe Hares in Southern Boreal and

Montane Forests ..................................................................................... 163

Karen E. Hodges

Chapter 8 History and Distribution of Lynx in the Contiguous

United States .......................................................................................... 207

Kevin S. McKelvey

Chapter 9 Ecology of Lynx in Northern Canada and Alaska ................................... 265

Garth Mowat

Kim G. Poole

Mark O’Donoghue
Chapter 10 Canada Lynx Habitat and Topographic Use Patterns

in North Central Washington: A Reanalysis ............................................ 307

Kevin S. McKelvey

Yvette K. Ortega

Gary M. Koehler

Keith B. Aubry

J. David Brittell

Chapter 11 Lynx Home Range and Movements in Montana

and Wyoming: Preliminary Results ......................................................... 337

John R. Squires

Tom Laurion

Chapter 12 Space-Use, Diet, Demographics, and Topographic

Associations of Lynx in the Southern Canadian

Rocky Mountains: A Study ...................................................................... 351

Clayton D. Apps

Chapter 13 Ecology of Canada Lynx in Southern Boreal Forests ............................. 373

Keith B. Aubry

Gary M. Koehler

John R. Squires

Chapter 14 Comparative Ecology of Lynx in North America ..................................... 397

Steven W. Buskirk

Leonard F. Ruggiero

Keith B. Aubry

Dean E. Pearson

John R. Squires

Kevin S. McKelvey

Chapter 15 Lynx Conservation in an Ecosystem Management

Context .................................................................................................... 419

Kevin S. McKelvey

Keith B. Aubry

James K. Agee

Steven W. Buskirk

Leonard F. Ruggiero

Gary M. Koehler

Chapter 16 The Scientific Basis for Lynx Conservation:

Qualified Insights .................................................................................... 443

Leonard F. Ruggiero

Keith B. Aubry

Steven W. Buskirk

Gary M. Koehler

Charles J. Krebs

Kevin S. McKelvey

John R. Squires
Chapter 17 Conservation of Lynx in the United States: A Systematic

Approach to Closing Critical Knowledge Gaps ....................................... 455

Keith B. Aubry

Leonard F. Ruggiero

John R. Squires

Kevin S. McKelvey

Gary M. Koehler

Steven W. Buskirk

Charles J. Krebs

Chapter 18 Epilogue: The Scientific Basis for Lynx Conservation:

Can We Get There From Here? .............................................................. 471

Leonard F. Ruggiero

Keith B. Aubry

Steven W. Buskirk

Gary M. Koehler

Charles J. Krebs

Kevin S. McKelvey

John R. Squires
1

Preface

Ecology and

Conservation of Lynx

in the United States

When we began the task of elucidating the scientific basis for lynx conservation in June 1998, I had little idea how constrained our time would be. The

request to do this job came from a consortium of federal land management

agencies in response to the U.S. Fish and Wildlife Service’s “proposed rule”

to list the Canada lynx as a threatened or endangered species throughout its

range in the contiguous United States. I underestimated the extent to which

legal mandates and the expectations of information-hungry biologists and

decision-makers would push us. By late February 1999 we had provided

nearly 800 pages of “working drafts” to agency personnel who were responsible for various products associated with the potential listing. But the

situation grew even more urgent later in the spring when the USFWS

decided to delay its final listing decision by six months, from July 1999 to

January 2000, so they could consider the entirety of our final product.

Although unknown to me at the time, this decision necessitated that our

work be made available for public comment in final form far sooner than we
Preface

2

had planned. We were told that if we failed to meet this timeline, legal

constraints would ensure that agency officials and the general public would

not be able to use our findings in decision-making and public involvement

attendant to the listing process. Moreover, we were told that in order for all

this to happen, our work would have to be disseminated via the Internet! To

say the least, it was disconcerting that our “rush job” would be available all

over the globe, and that the prospects for publishing our work in book form

might be compromised. But as scientists interested in the application of our

work, we had little choice.

Two fortunate circumstances helped to mitigate this dilemma. First, the

Rocky Mountain Research Station has a first-class Publishing Services staff

under the direction of Louise Kingsbury. It was the professional capability

and dedication of this group that made it possible for us to get camera-ready

copies of Chapters 1-16 onto the Internet within the allotted time. Published

electronically as USDA Forest Service, General Technical Report RMRS–

GTR-30WWW, this version of our work was made available to agency

personnel as well as to the general public. Thus, all of the most pertinent

information in this book was available for use in the sociopolitical process

defined pursuant to the Endangered Species Act.

The second fortuitous circumstance was that our work caught the attention of Darrin Pratt, Acquisitions Editor of the University of Colorado Press.

Mr. Pratt’s interest and the ultimate acceptance of our book for publication

by the University of Colorado Press has been extremely gratifying. Accordingly, we are deeply grateful to Louise Kingsbury, Darrin Pratt, and to all

those who have been instrumental in the editing, production, and publication of both the electronic and hard copy editions of this book.

In this book, and in our related activities, we have drawn a clear line

between science and policy. Our job as scientists was to summarize the state

of knowledge, articulate meaningful understandings when possible, and

identify important knowledge gaps relative to the information needed for

conservation plans and policy. Perhaps a more difficult job was left to our

land-management colleagues who must use this information as the basis for

complex and controversial judgments about land management actions. In

this regard, we appreciate the efforts of Bill Ruediger and members of his

“Lynx Biology Team” for their efforts to apply the information in this

volume on behalf of the resource. We also offer a special thanks to Kathy

McAllister, Deputy Regional Forester for the Northern Region of the National Forest System and Leader of the Interagency Lynx Steering Committee. Although beset by great pressure to meet procedural deadlines requiring our information, Kathy was patient and understanding, even though

from her perspective the pace of our work was ponderous. Her support, and
3

Preface

the support of Steering Committee “Chief of Staff,” Dr. Martin Prather, has

done much to ensure the incorporation of science into policy and to facilitate

effective working relationships between scientists and managers.

My deepest gratitude is reserved for my colleagues and friends on the

Lynx Science Team. Dr. Keith Aubry’s writing skill, even temperament, and

tireless work was key to our success. Keith was absolutely selfless in his

efforts, and his ability to synthesize and communicate complex material was

central to much of our work. Professor Steven Buskirk lent his well-deserved

credentials as an internationally respected mammalogist and carnivore

ecologist to our team. In addition to his full-time teaching responsibilities,

Steve contributed innumerable hours to this effort; his scientific acumen,

broad expertise, and high standard of scholarship were tremendous assets.

Professor Charles Krebs is one of the most respected ecologists in the world,

as well as one of the premier authorities on lynx and snowshoe hare ecology

in Canada. I am indebted to him for his participation on this committee, for

his dependable good humor, and for his representation of the cadre of

outstanding Canadian researchers of lynx and snowshoe hares. Dr. Gary

Koehler is the most experienced lynx researcher in the United States, and his

work has formed the basis for most of what is known about lynx in this

country. Gary’s open-mindedness, commitment to the resource, first-hand

knowledge of lynx ecology, and impeccable professionalism made him a

great asset to the Team. Dr. Kevin McKelvey contributed expertise as a

modeler, forest ecologist, and experienced analyst of population patterns

and viability. Kevin is an enviably well-rounded and thoughtful scientist

whose analytical skills and keen intellect played a critical role in our work.

Dr. John Squires is currently managing the most ambitious lynx study

undertaken to date. His first-hand knowledge and insights gained from this

work along with his command of the scientific literature and his extensive

field experience with lynx and other wide-ranging carnivores was of great

value to the group. It was an honor for me to lead this team, and

I deeply respect the professional competence and dedication of each of

these men.

Although Lynx Science Team members are officially listed as technical

editors of this volume, this group wrote over two-thirds of the text and

authored 13 of the 18 chapters. In addition, each Team Member served as

editor on multiple chapters for which they were not authors. In this capacity,

they managed the peer review process, presided over chapter revisions, and

worked with me in making final decisions about acceptance of chapters for

publication. As anyone who has served in this capacity knows, peer review

is often a demanding, lengthy, iterative process requiring time and patience

on the part of both authors and editors. This book was no exception, and it
Preface

4

is only through the tremendous efforts of the above mentioned Science Team

members that we were able to complete this process so quickly.

In this context, we extend our gratitude to a cadre of peer reviewers, most

of whom were asked to provide detailed technical reviews in ridiculously

short times. Included here we thank: Fred Allendorf, Clayton Apps, Theodore

Bailey, Christina Hargis, Greg Hayward, Doug Houston, John McKay,

Chuck Meslow, Francois Messier, Scott Mills, Garth Mowat, Erin O’Doherty,

Mark O’Donoghue, Dan Pletscher, Roger Powell, Martin Raphael, Kermit

Ritland, Mike Wisdom, Bill Zielinski, and numerous anonymous reviewers.

We extend a special thanks to Tina Mainey for her invaluable administrative and moral support and for her attention to endless details throughout

this project. For additional administrative support we also thank Lori

Moffatt, Deanna Crawford, Stacey Clark, and Sarah Day. Our special

thanks also goes to Lane Eskew, Lead Editor for this project, who did an

amazing job of correcting countless errors and of bringing consistency to

our presentations. We also thank Madelyn Dillon and Louise Kingsbury

for additional editorial work; Joyce Stoddard and Nancy Chadwick for

their lead production work; Loa Collins and Karen Eason for additional

production work; and to Suzy Stephens for getting all this on the Web.

All of these people sacrificed nights and weekends to get this job done on

schedule, and we are grateful.

Leonard F. Ruggiero

Lynx Science Team Leader
5

Chapter 1

Toward a Defensible

Lynx Conservation

Strategy: A Framework

for Planning in the Face

of Uncertainty

Leonard F. Ruggiero, USDA Forest Service,

Rocky Mountain Research Station, 800 E. Beckwith, Missoula, MT 59801

Kevin S. McKelvey, USDA Forest Service,

Rocky Mountain Research Station, 800 E. Beckwith, Missoula, MT 59801

Background

On April 2, 1993, the incumbent U.S. President traveled to Portland,

Oregon, to intervene in a national political crisis engendered by public concern

over the conservation of native wildlife on public lands. Environmentalists

had successfully used existing statutes, most notably the National Forest

Management Act and pursuant regulations, to shut down timber industry

operations on commercially important federal lands in the Pacific Northwest. Widespread economic dislocations were expected, and the federal

courts showed no signs of reversing the decision to suspend timber-harvesting activities. At the core of this enormously divisive legal controversy was

the effect of timber management on the viability of northern spotted owl

populations—an issue that arguably defined one of the most significant

conservation conflicts of this century.
Chapter 1—Ruggiero

6

The spotted owl controversy catalyzed heightened concern over the

conservation of “sensitive” species on public lands, especially those species

thought to be negatively affected by land management practices such as

timber harvesting. In 1993, the National Forest System (the land management branch of the USDA Forest Service) responded to this concern by

identifying a number of species and species groups with the potential to

become conservation issues. Included were a group of Pacific salmon, the

marbled murrelet, Mexican spotted owl, northern goshawk, two species of

trout, several forest owls, and four forest carnivores—notably including the

lynx. The basis for concern over most of these species was their putative

association with late-successional forests—the stage of forest development

most frequently removed from managed forest landscapes (Thomas et al.

1993). Land managers decided to assess the state of ecological knowledge for

each of these species relative to the information needed for defensible

conservation planning. In late 1993, scientists in the research branch of the

Forest Service were asked to lead these assessments.

The findings of the forest carnivore conservation assessment were published in a report entitled, The Scientific Basis for Conserving Forest Carnivores:

American Marten, Fisher, Lynx and Wolverine in the Western United States

(Ruggiero et al. 1994b). One of the major conclusions of this assessment was

that, “Major information gaps exist for these forest carnivores. A sustained

commitment to research is needed for developing scientifically sound

conservation strategies to ensure the persistence of forest carnivore populations” (Lyon et al. 1994, p. 137). Regarding lynx in the western United States,

the Assessment read, “...there is a need for the most basic information on

habitat relationships, at any spatial or temporal scale and at any level of

measurement. Virtually any new data on habitat relationships involving

lynx in the western conterminous 48 states would be a substantive increase

in knowledge” (Ruggiero et al. 1994a, p. 142). The state of knowledge was

found to be equally inadequate for all other aspects of lynx ecology in the

western United States. Although a considerable amount is known about

lynx ecology in northwestern Canada, the Assessment concluded that (1) the

applicability of this information to ecosystems in the western United States

is unknown, and (2) potential ecotypic variation in lynx populations warns

against the application of this information in the western United States

(southern) portion of the lynx’s range (Ruggiero et al. 1994a).

Knowledge of lynx ecology in the United States has not improved substantially since publication of the Forest Carnivore Conservation Assessment in

1994: there have been no new research findings published on lynx ecology

in the United States. Management agencies were thus poorly prepared to

deal with the July 8, 1998, “proposed rule” by the U.S. Fish and Wildlife

Service (USFWS) to list the lynx as a threatened or endangered species
7

Ruggiero—Chapter 1

throughout its range in the contiguous United States. This action by the

USFWS followed a long history of public concern, petitions to list the lynx,

and lawsuits against the USFWS based on societal responses to perceived

declines in lynx populations (see Table 1.1 for an overview of these events).

The listing process dictates that unless compelling new evidence emerges to

the contrary, the lynx will be designated threatened or endangered in

January 2000, 1.5 years from the publication of the proposed rule in the

Federal Register (U. S. Fish and Wildlife Service 1998).

In response to this situation, representatives of the USFWS, Bureau of Land

Management (BLM), and USDA Forest Service (USFS) met in Salt Lake City,

Utah, several weeks before the proposed rule was published. There they

discussed how land management agencies could best prepare for the potential listing, particularly the consultation provisions of the Endangered

Species Act. If the lynx became a threatened or endangered species, how

could management agencies demonstrate to the USFWS that their actions

did not jeopardize the continued existence of lynx populations? A decision

was made to produce a conservation strategy of sufficient detail to direct the

actions of land managers such that a “jeopardy opinion” by the USFWS

could be avoided. The dilemma, of course, was how to produce a strategy

that could reliably evaluate the effects of various management actions on the

viability of lynx populations given the paucity of existing information on

lynx ecology in the southern portion of its range.

Scientists from the Research Branch of the USFS, including authors of the

1994 Forest Carnivore Conservation Assessment, were asked to address this

dilemma. The course of action these scientists recommended was predicated

on the lack of crucial scientific information and included a provisional

(interim) reassessment of our understanding of lynx ecology. This process

(Fig. 1.1) would build on the 1994 Assessment by: (1) conducting new

analyses of lynx distribution (based on new and old information),

(2) examining all published and unpublished information that may contribute to our understanding of lynx distribution and ecology in the contiguous

United States, (3) reanalyzing existing data using the latest technology,

(4) reviewing relevant ecological theory, and (5) attempting to elucidate new

insights about lynx ecology based on steps 1-4.

A Lynx Science Team was assembled to implement this process and

attempt a useful interpretation of limited information. Through this process,

the scientific basis for conserving lynx would be documented and, to the

extent possible, resulting insights about lynx ecology would be elucidated

for use by land managers. Management biologists and decision-makers

would then use the Science Team’s report to produce an Interim Conservation

Strategy, which would establish and detail management policy. Integral to

this strategy would be an explicit program of studies (Chapter 17), which, if
Chapter 1—Ruggiero

8

Table 1.1—Overview of events leading to the U.S. Fish and Wildlife Service’s proposed rule to list the lynx as a threatened or

endangered species throughout its range in the contiguous United States (McMaster, personal communication).

August 22, 1991 A petition to list the “North American” (Canada) lynx in the No

Cascades ecosystem of Washington as an endangered 

species and to designate critical habitat was received by the 

Fish and Wildlife Service (Service) from the National Audubon

August 26, 1994 The Service published a notice (59 FR 44123) indicating that 

the Service’s administrative 90-day finding found that the 

petition received April 27, 1994, presented substantial 

information indicating the requested action for the contiguous

Society and 11 other organizations. U.S population may be warrented, but there was not substan

information to indicate that an emergency listing of a souther

Rocky Mountain population was warrented.

October 6, 1992 The Service published a notice of a 90-day finding (57 FR 

46007) indicating that the petition to list the “North American”

(Canada) lynx in the North Cascades did not provide substant

information. Region 1 (Portland Regional Office) had the lead

December 27, 1994 The Service published a notice (59 FR 66507) indicating that 

the Service’s 12-month finding was listing the Canada lynx in 

the contiguous U.S. was not warranted. The finding 

represented the Service’s administrative finding as a result of

on the petition because the petitioned area was confined to 

that Region. Region 6 (Denver Regional Office) had the 

national lead for the lynx.

the status review agreed to in the April 28, 1993, lawsuit 

settlement and the administrative 12-month finding for the 

petition received April 27, 1994.

Late 1992 or 1993 The Greater Ecosystem Alliance and other organizations sue

the Service over the negative 90-day finding announced on 

October 6, 1992.

January 30, 1996 The Defenders of Wildlife and 14 other organizations and 

individuals sued the Service in the U.S. District Court, District o

Columbia, over the not-warranted petition finding announced 

in the Federal Register on Dec. 27, 1994.

April 28, 1993 A settlement agreement was reached whereby the Service 

agreed to reevaluate the negative 90-day finding announced

on October 6, 1992, in light of new information that was 

submitted by the petitioners.

March 27, 1997 The court issued an opinion and order setting aside the notwarranted finding and remanded it back to the Service for 

further consideration. The Service was ordered to publish a 1

month finding on the status of the lynx within 60 days.

July 9, 1993 The Service published a notice (58 FR 36924) indicating that 

the negative 90-day finding had been revisited by Region 1, 

but that there still was not substantial information to support t

petitioned action. However, the Service announced in the

May 27, 1997 The Service published a 12-month petition finding (62 FR 

28643) that the Canada lynx population in the contiguous U.S

was warranted for listing under the Endangered Species Act 

but precluded by actions on other species of higher taxonom

notice that it believed that sufficient evidence existed to 

indicate that an in-depth rangewide status review for the lynx 

should be conducted and that the Service intended to 

commence this status review.

status. This warranted but precluded finding automatically 

elevated the Canada lynx to candidate species status.

November 30, 1993 A second settlement agreement was reached. The Service 

agreed to complete and publish the results of a status review

throughout the lower 48 States by November 14, 1994.

September 15, 1997 Defenders of Wildlife, et al., filed suit against the Service in th

U.S. District Court, District of Columbia, arguing that the Servi

violated the Endangered Species Act in finding that listing the

Canada lynx population in the contiguous U.S. was

warranted but precluded (published in the Federal Register, 

May 27, 1997).

February 2, 1994 The Service published a notice (59 FR 4887) indicating that it

was soliciting information for a rangewide status review. The 

Service indicated that it would complete and publish its findin

no later than November 15, 1994. Region 6 was given the 

December 22, 1997 The court denied the plaintiffs’ Motion to Enforce Judgment 

against the Service’s May 1997 finding that listing the Canada

lynx population in the contiguous U.S. was warranted but 

precluded. At the same time, the court set an expedited

schedule and hearing date (March 18, 1998) for the lawsuit 

filed in September, 1997.

April 27, 1994 A petition to list the “North American” (Canada) lynx in the 

contiguous U.S. and to emergency list the southern Rocky 

Mountain population was received from the Biodiversity Lega

Foundation and four individuals. 

February 11, 1998 The Service and the Plaintiffs reached a settlement that calls 

the Service to publish a proposed rule to list the Canada lynx 

the contiguous U.S. by June 30, 1998. The settlement was 

submitted to the U.S. District Court, District of Columbia, for 

July 08, 1998 Proposed rule to list the lynx was published (63 FR 36994).
9

Ruggiero—Chapter 1

Ecological

Theory

Interim

Conservation

Strategy, Part B:

Plan of Action to

Meet Critical

Research Needs

Interim

Conservation

Strategy, Part A:

Plan of Action for

Forest

Management

Critical

Needs

Qualified

Insights

New

Analyses

Update

Knowledge

Current

State of

Knowledge

New Data

Figure 1.1—Process for developing an interim conservation strategy given that current understandings

are extremely limited.

implemented, would provide the information needed for more substantive

and defensible conservation planning. This book is the formal report of the

Lynx Science Team.

Scientific Context

We face the dilemma of conserving lynx without adequate knowledge of

lynx ecology. We do not yet understand many of the factors that determine

lynx distribution and abundance; hence, we do not have a very sophisticated understanding of how human activities affect the persistence of lynx

populations. Indeed, the entirety of published research on lynx in the United

States comes from only seven studies (Chapters 10 and 13). Similarly, there

are few published studies on the ecology of the snowshoe hare, the lynx’s

primary prey, in the contiguous United States (Chapter 7). A substantial

amount of research has been conducted on both species in Canada and

Alaska (Chapters 6 and 9) but, as discussed above, the applicability of these

studies to lynx conservation in the southern portions of its range is unknown.

This situation has three important ramifications for any attempt to elucidate the scientific basis for lynx conservation. First, this book is not a
Chapter 1—Ruggiero

10

substitute for reliable knowledge gained through a sustained commitment

to scientific research. Hence, Chapter 17, “An Action Plan to Fill Critical

Knowledge Gaps,” must be viewed as a critical part of any conservation

strategy based on information contained herein. The second and corollary

ramification is that any management strategy based all or in part on the

information contained in this volume must be clearly identified as interim. A

more enduring strategy is contingent upon the acquisition of additional

knowledge about lynx ecology and greater understanding of factors influencing the persistence of lynx populations. Finally, because the insights

offered here embody a poorly developed “state of the art,” we use the term

qualified insight to remind the reader of this limitation and to stress the need

for cautious, conservative decision-making.

We know some basic things about lynx ecology. For example, we know

lynx are well adapted to living in cold climates with deep snow, they are

closely associated with coniferous forests, and they rely on the snowshoe

hare as a primary source of food. However, we don’t understand why lynx

are not very abundant in some places where these requirements appear to be

met (e.g., southwestern Colorado and western Wyoming). This lack of

understanding underscores the inadequacy of our knowledge about the

factors controlling lynx abundance and distribution.

Similarly, conventional wisdom holds that a landscape dominated by

coniferous forest will support lynx if it: (1) produces adequate numbers of

snowshoe hares, (2) includes a small amount of old forest needed for den

sites, and (3) includes a mixture of forest age classes dominated by early

successional stands. The key ingredient here appears to be snowshoe hares,

and prime hare habitat is described as regenerating, dense young forest. This

paradigm enjoys such broad acceptance that many acres of public land will

be modified to fit this description in the name of lynx conservation (e.g.,

Envriodata Systems Inc. 1993; Washington Department of Natural Resources 1996). Based on this concept of lynx habitat, most timber harvest

activities would be considered beneficial and, given that trapping no longer

occurs in the United States outside Montana, we might expect lynx populations to be stable or increasing throughout their range. It is hard to reconcile

this with the perception that lynx numbers and distribution in the United

States are so sparse as to warrant listing under the Endangered Species Act

(U. S. Fish and Wildlife Service 1998).

We believe it is critically important to recognize the risks associated with

management decisions made in the face of this kind of uncertainty. Management-induced landscape changes, when based on untested hypotheses, can

result in conditions antithetical to their stated purpose. An interim strategy

has special properties in this regard. Interim direction will be altered within
11

Ruggiero—Chapter 1

a specified time period, and actions taken during the interim period must not

foreclose options for future management. Interim management actions must

also be conservative in order to reflect the poorly developed knowledge base

upon which they were developed. Unfortunately, the sociopolitical pressure

to “do something” usually precludes this conservative approach. Rather, in

natural resource management, decisions based upon the best available

knowledge tend to treat that knowledge as if it were complete, even when

it is woefully inadequate. It is within this context that this book seeks to

reexamine existing knowledge, search for new information, and generate

qualified insights that can be used to build an interim conservation strategy

for the lynx.

The need for action in the face of uncertainty is not unique to the lynx. Our

knowledge concerning many organisms is even more limited, and the

processes of habitat destruction continue. The ongoing alteration of the

natural world ensures a large queue of threatened organisms for the legal

machinery of the Endangered Species Act to process. We hope that the

approach embodied in this book will be of value in other conservation

planning efforts.

Conservation Planning and Uncertainty

Our inability to completely understand ecological processes will always

result in varying degrees of uncertainty when planning for species conservation. We are often uncertain about the details of a species’ status even

when conservation action is clearly appropriate. Comparative census data

are usually lacking and, even when such data are present, we are often

uncertain about how to interpret population changes relative to natural

fluctuations. If we decide that a population is in decline, there will often be

uncertainty about the causes of the decline and perhaps additional uncertainty about appropriate restoration efforts. For species with broad historical ranges such as the lynx, these uncertainties increase, as do the consequences of poor decisions. The potential listing of the lynx under the

Endangered Species Act, for instance, could impact 16 States.

In conservation planning there is often a fundamental mismatch between

the state of knowledge, the feasibility of obtaining specific knowledge, and

the actions that society would have land managers take towards species

conservation. Land management agencies are asked difficult and very

specific questions, such as how the construction of a road or a timber sale will

affect the viability of a lynx population. In asking these questions, society

(1) presupposes highly sophisticated ecological knowledge, (2) assumes these

questions have unequivocal answers, and (3) believes that land managers
Chapter 1—Ruggiero

12

can develop plans that will solve the problem. Unfortunately, these suppositions are rarely true, and conservation planning always occurs in the face

of varying degrees of uncertainty.

There is much society can do to reduce uncertainty and thus improve

conservation planning. We have the tools to improve our understanding of

ecological systems in almost all cases—it is the political will to do so that is

often lacking. Nonetheless, the reality of uncertainty has given rise to several

approaches to conservation planning. If uncertainty is limited and quantifiable, a number of stochastic simulation (Noon and McKelvey 1996; Akçakaya

and Raphael 1998; Marshall et al. 1998) or formal fuzzy logic (Todd and

Burgman 1998) approaches can be used. In most cases, however, uncertainty

is addressed less quantitatively. Here, we briefly discuss two widely accepted approaches, then present the alternative approach embodied in

this book.

Burden of Proof Approach to Conservation

Conservation disputes are often resolved in the judicial system, where

legal constraints require that an action must be proved harmful to a species

before the action is precluded; i.e., the “burden of proof” rests with conservationists (Murphy and Noon 1991; Dayton 1998). This results in reactive

conservation, whereby proposed actions become the issue, rather than

species’ conservation. In addition, when little is known about species of

concern, e.g., those that are rare and/or difficult to study, substantial harm

may occur before such proof is possible. It has therefore been suggested that

the burden of proof be shifted so that uncertainty favors, or at least is not

destructive to, conservation (Dayton 1998).

However, shifting the burden of proof in the judicial process is unlikely to

provide sociopolitical solutions to conservation problems. The process is

still flawed, the burden has simply been shifted from one side to the other.

Proving harm or lack of harm in a conservation context is costly, timeconsuming, and often impractical, regardless of where the burden lies.

Because the burden-of-proof approach creates an environment in which one

side or the other benefits from a lack of information, this approach also

devalues the acquisition of new information. Moreover, because decisions

are binary (i.e., an action is either allowed or precluded) knowledge gained

through this process (or the identification of significant knowledge gaps),

may be lost once a decision is made.
13

Ruggiero—Chapter 1

The Delphi Approach to Conservation

A second approach for dealing with conservation in the face of uncertainty

has been to seek consensus rather than knowledge. Commonly called the

“Delphi method” (Ziglio 1996), this approach evolved out of the need to

confront the uncertainties associated with multi-species management

(Cleaves 1994). The formalized Delphi process adopted by the Forest Ecosystem Management Assessment Team (FEMAT 1993), involved more than

70 experts having special knowledge of individual species or species groups.

These experts participated on panels wherein they were given 100 “likelihood points” that were distributed across four outcomes (Meslow et al.

1994). For each species and management plan, the possible outcomes were

that the plan would (1) produce a stable, well distributed population,

(2) produce a stable but restricted distribution, (3) only produce widely

spaced refugia, or (4) lead to extirpation from federal lands (Meslow et al.

1994). The votes from the panel were then summed to represent the group’s

collective opinion regarding the quality of each management option.

The Delphi method, in various forms, has become very popular as a means

of incorporating scientific input into management decisions (Marcot et al.

1997). This method is popular because it is quick, has proven to be robust in

court, and requires no new knowledge. Furthermore, it generally limits

decision-making by scientific experts to evaluation of a pre-established set

of management alternatives rather than incorporating their input directly

into the process of plan development. In short, the value of the Delphi

process as applied to conservation planning lies mostly in its expedience.

From a scientific perspective, Delphi processes are inappropriate as a basis

for conservation decisions. In the FEMAT example, the only data integral to

the Delphi process relates to the opinions of the panel. These data are not

reproducible and, perhaps more importantly, the relationship of these data

to the ecology of the organisms in question is unknown. The subtle fact that

this process results in an assessment of opinion, rather than an assessment

of what is known about species’ ecologies, is inevitably lost. For example, in

the absence of definitive information, if a panel believes strongly that

an organism needs a specific habitat type, conservation planning will

likely proceed based on this belief, and management actions or general

management policy will be set accordingly. The collective opinion of the

group therefore becomes a surrogate for a science-based understanding

even though no new information has been brought to bear on the problem.

This process might be reasonably benign if the expert opinions reflected the
Chapter 1—Ruggiero

14

state of knowledge—that is, if uncertainty in information lead to uncertainty

in conclusions. However, this is seldom the case, and the illusion of knowledge-based understanding is created. For instance in evaluating the results

of the FEMAT process, Meslow et al. (1994) state: “Some species did not

respond to habitat protection on federal lands, i.e., did not fare well under

any option.” (p. 26). In truth, the response of these species to protection is

unknown. There was no species response. A correct statement would be

that in the opinion of the panel, none of the options afforded adequate

protection for some species.

To a certain extent, the Delphi process can be altered so that the judgments

and opinions are more specific and limited. Marcot et al. (1997), for instance,

asked the experts to provide their opinions concerning the basic ecology and

species-environment interactions for those species where they had expertise, rather than to evaluate species viability associated with various management scenarios. We believe that this is an improvement because the

opinions of the experts will be much closer to their areas of expertise and can,

to the extent that these opinions are based on unpublished findings, represent new information. In the final analysis, however, there is no way to

determine which inferences are based on data and which on opinion, and the

distinction will be lost.

History is replete with scientific conventional wisdom, strongly held at the

time, but found by subsequent investigation to be false. Holding strong

beliefs based on minimal data is a human propensity, but one that is

antithetical to the scientific method. Delphi encourages this propensity and,

in the process, suppresses the acknowledgment of uncertainty needed to

qualify all scientific discourse and to inform sociopolitical processes. Additionally, Delphi methods fail to sufficiently elucidate knowledge gaps and

identify the importance and necessity of obtaining new information.

The Inductive Approach: A Science-Based Method

We have chosen an alternative approach that is based on the assumption

that knowledge is never complete and never universal. Some research

findings are strong enough that they can be assumed to be true. Even in such

cases, however, a strict scientific interpretation limits the scope of inference

to the specific study site, the specific population of organisms studied, and

the time of the investigation. We must also acknowledge that sometimes, in

spite of our best sampling efforts, the individuals we study may not be

representative of the population inhabiting the study area, thus further

limiting the utility of our findings. Peer-reviewed scientific publications

generally provide strong local information, but there are limitations to using

such knowledge. Statistical inferences apply only to the populations, places,
15

Ruggiero—Chapter 1

and times actually studied, and neither the most sophisticated mathematical models nor the most impressive computer-mapping technology can

change this.

This scientific reality does not diminish the importance of the information

derived through this process. Indeed, this is the nature of scientific investigation; through a gradual accumulation of limited pieces of knowledge,

more generalizable interpretations emerge and scientific paradigms are

formed. In the interim, if we wish to apply limited knowledge to the solution

of large-scale problems, we do so using subjective methods. However, such

methods rely on a series of untested assumptions concerning the

generalizability of existing knowledge.

These subjective interpretations are an important part of the scientific

process. Indeed, the most difficult and often the most important part of the

scientific process is the interpretation of research findings within the broader

context of “what is known.” This aspect of science is similar to the creative

process that gives rise to insights about appropriate and meaningful research questions. The critical component of both processes is to limit one’s

interpretations to scientifically defensible inferences based on empirical

data. This aspect of the scientific process is evident in thorough research

proposals and in the discussion sections of published manuscripts. In both

cases, limited knowledge is aggregated and synthesized to derive insights

that have scientific merit as judged by the peer-review process.

The qualified insights we are attempting to produce embrace this scientific

tradition. What we seek here is a middle ground between demanding

certainty and embracing opinion. This middle ground is the result of

interpretation, a fundamentally subjective process based on scientific judgment. In taking this approach we acknowledge that judgments are an

essential part of the scientific process, but they must be based on empirical

data and theory, and they must be specific. It is the specificity of the linkage

between data and inference that separates even the most highly qualified of

insights from the opinion-based approaches described above. We can, for

instance, make qualified insights concerning the probable dietary dependence of lynx on snowshoe hares at the southern periphery of their range. In

doing so, we rely on specific data concerning lynx, hares, and the prey

communities in areas such as the Great Lakes States or the Rocky Mountains.

The inference is qualified: we know a great deal about these relationships in

certain areas and we are inferring the degree to which these understandings

are transferrable to areas where we lack local knowledge. We cannot,

however, make qualified insights concerning how well the lynx would

respond to protection on federal lands in the contiguous United States unless

we can find a similar body of information from which valid inferences

concerning lynx viability can be drawn.
Chapter 1—Ruggiero

16

Organization of the Book

Chapters 2 through 5 of this book provide a context for scientific judgments. We review pertinent ecological theory and examine fundamentally

important information about relevant ecological systems. Viewed within

this context, even scant information about lynx ecology may acquire meaning that would otherwise remain obscure. Moreover, placing data into the

context of ecological theory diminishes the data-dependency of the qualified

insights. For instance, an important issue in conservation biology is the

impact of adult mortality, which is often influenced by human behavior, on

population dynamics. Ecological theory tells us that long-lived organisms

with low fecundity are more sensitive to adult mortality than are short-lived

organisms with high fecundity. By knowing something about the life history

of an organism and applying this theoretical understanding, it is possible to

infer that increasing adult survival will have a positive effect on the population.

For reasons discussed above, the process we have chosen incorporates all

the empirical information we could locate. We critically evaluate all such

data; thus, we are free to incorporate data from published as well as

unpublished sources. Data may be weak for a variety of reasons, but even

weak data will contribute to understanding when viewed in a rigorous

analytical framework. We discriminate between weak data and opinions

based on weak data. For instance, a picture of a lynx shot in low-elevation

rangeland would be considered weak in one sense because it is not part of

a representative sample. However, to the extent that we know that a lynx

occurred in that time and place, we have a small but legitimate datum to add

to our knowledge base. Opinions about why the lynx was there, what it was

doing, and whether it may be representative of a population are not based

on additional data and, therefore, are not pertinent. Accordingly, Chapters

6 through 13 are dedicated to the review and assessment of existing information and to the presentation of new data about the ecology of lynx and

snowshoe hares.

Building on the integration of existing information and relevant ecological

theory, Chapters 14 and 15 synthesize existing information and begin to

make interpretations relative to lynx conservation. It is here that we attempt

to place lynx conservation into the larger context of ecosystem management

by considering the needs of diverse vertebrate communities. This synthesis

leads directly to a discussion of qualified insights in Chapter 16, and that, in

turn, to the use of qualified insights to frame an action plan, as outlined in

Chapter 17.
17

Ruggiero—Chapter 1

An Ecological Framework

The questions we address through qualified insights must be pertinent to

lynx conservation. The science of conservation biology provides a conceptual framework that informs us about the kind of information most critical

to this task; these include:

1. Present and historical patterns of lynx distribution.

2. Factors limiting the geographic distribution of lynx.

3. Principal habitat features affecting lynx.

4. Food habits of lynx.

5. Habitat requirements of key prey species.

6. Population dynamics of key prey species.

7. Principal community factors affecting lynx.

8. Principal factors affecting lynx movements and dispersal.

9. Key demographic properties and dynamics of lynx populations.

10. Geographic variation among lynx populations.

11. Direct human influences on lynx.

Our discussion of qualified insights in Chapter 16 is organized according

to this framework, although many of these key areas are not mutually

exclusive. The ecological relationships implicit in this framework are illustrated in Figure 1.2. We know from the outset that much of this information

is unavailable for the lynx, but our task primarily involves developing

qualified insights about lynx ecology in those areas where critical information is lacking. In addition, the process of developing insights in these datapoor areas will serve to highlight important knowledge gaps. Thus, Chapter

16 is both a compilation of knowledge-based inferences and a compendium

of critical information needs for future research.

Because we cannot depend upon the slow accumulation of independent

research findings to provide a foundation for the conservation of lynx, we

need to identify a plan of action that will, if followed, close important

knowledge gaps in a timely manner. The last and probably the most critical

part of our approach to dealing with uncertainty is to use our qualified

insights to frame this action plan, as presented in Chapter 17.
Chapter 1—Ruggiero

18

Literature Cited

Akçakaya, H. R. and M. G. Raphael. 1998. Assessing human impact despite uncertainty:

viability of the northern spotted owl metapopulation in the western USA. Biodiversity

and Conservation 7:875-894.

Cleaves, D. A. 1994. Assessing uncertainty in expert judgment: a rationale and guidelines

for application in ecosystem management. U.S. Department of Agriculture, Forest Service, General Technical Report SO-110.

Dayton, P. K. 1998. Ecology - reversal of the burden of proof in fisheries management.

Science 279:821-822.

Envriodata Systems, Inc. 1993. Meadows integrated resource analysis: a technical report

addressing lynx habitat. in Okanogan National Forest. 1993. Meadows area integrated

resource analysis. Tonasket and Winthrop Ranger Districts, Okanogan National

Forest, WA.

FEMAT. 1993. Forest ecosystem management: and ecological, economic, and social assessment. Report of the Forest Ecosystem Management Assessment Team. USDA Forest

Service; USDC National Oceanographic and Atmospheric Administration and National

Marine Fisheries Service; USDI Bureau of Land Management, Fish and Wildlife Service,

and National Park Service; and U. S. Environmental Protection Agency, Washington, DC.

Figure 1.2—Hierarchical representation of key areas of understanding needed for

conservation planning.

Present and historical distribution

Limiting factors

Physical (too hot, too cold, etc.)

Barriers (simply couldn’t get there)

Lynx movement capability

Competitors

Effects on survival, fecundity, also exclusion

Prey

Lynx diet and variation in diet

Ecological requirements of key prey species

Factors limiting the population

dynamics of prey

Lynx biology

Habitat relationships

Use patterns

Movement patterns

Demographics

Influence of competitors (fecundity, survival)

Influence of prey (fecundity, survival)

Influence of habitat structure (fecundity, survival)—includes snow
19

Ruggiero—Chapter 1

Lyon, L. J., K. B. Aubry, W. J. Zielinski, S. W. Buskirk, and L. F. Ruggiero. 1994. The scientific

basis for conserving carnivores: considerations for management. Pages 128-137 in L. F.

Ruggiero, K. B. Aubry, S. W. Buskirk, L. J. Lyon, and W. J. Zielinski, technical editors. The

scientific basis for conserving forest carnivores: American marten, fisher, lynx, and

wolverine in the Western United States. U.S. Department of Agriculture, Forest Service,

General Technical Report RM-254.

Marcot, B. G, M. A. Castellano, J. A. Christy, L. K. Croft, J. F. Lehmkuhl, R. H. Naney, R. E.

Rosentreter, R. E. Sandquist, E. Zieroth, K. Nelson, C. G. Niwa, and B. C. Wales. 1997.

Pages 1497-1673 in T. M. Quigley and S. J. Arbelbide, technical editors. An assessment of

ecosystem components in the Interior Columbia Basin and portions of the Klamath

and Great Basins: Volume III. U.S. Department of Agriculture, Forest Service, General

Technical Report PNW-GTR-405.

Marshall, E., R. Haight and F. R. Homans. 1998. Incorporating environmental uncertainty

into species management decisions: Kirtland’s warbler habitat management as a case

study. Conservation Biology 12:975-985.

Meslow, E. C., R. S. Holthausen, and D. A. Cleaves. 1994. Assessment of terrestrial species

and ecosystems. Journal of Forestry 92(4):24-27.

Murphy, D. D. and B. R. Noon. 1991. Coping with uncertainty in wildlife biology. Journal

of Wildlife Management 55:773-782.

Noon, B. R. and K. S. McKelvey. 1996. Management of the spotted owl: a case history in

conservation. Annual Review of Ecology and Systematics 27:135-162.

Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, L. J. Lyon, and W. J. Zielinski. 1994a. Information

needs and a research strategy for conserving forest carnivores. Pages 138-152 in L. F.

Ruggiero, K. B. Aubry, S. W. Buskirk, L. J. Lyon, and W. J. Zielinski, technical editors. The

scientific basis for conserving forest carnivores: American marten, fisher, lynx, and

wolverine in the Western United States. U.S. Department of Agriculture, Forest Service,

General Technical Report RM-254.

Ruggiero, L. F., K. B. Aubry, S. W. Buskirk, L. J. Lyon, and W. J. Zielinski, technical editors.

1994b. The scientific basis for conserving forest carnivores: American marten, fisher,

lynx, and wolverine in the Western United States. U.S. Department of Agriculture, Forest

Service, General Technical Report RM-254.

Thomas J. W., et al. 1993. Viability assessments and management considerations for

species associated with late-successional and old-growth forests in the Pacific Northwest.

U.S. Department of Agriculture, Forest Service, Washington, DC.

Todd, C. R. and M. A. Burgman. 1998. Assessment of threat and conservation priorities

under realistic levels of uncertainty and reliability. Conservation Biology 12:966-974.

U.S. Fish and Wildlife Service. 1998. Proposal to list the contiguous United States distinct

population segment of the Canada lynx: proposed rule. Federal Register 63(130):36994-

37013.

Washington Department of Natural Resources. 1996. Lynx habitat management plan for DNR

managed lands. Washington State Department of Natural Resources, Olympia, WA.

Ziglio, E. 1996. The Delphi method and its contribution to decision-making. Pages 4-33 in

M. Adler and E. Ziglio, Editors. Gazing into the Oracle: the Delphi method and its

application to social policy and public health. Jessica Kingsley Publishers, Bristol, PA.
Chapter 1—Ruggiero

20
21

Chapter 2

Theoretical Insights into

the Population Viability

of Lynx

Kevin S. McKelvey, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59801

Steven W. Buskirk, Department of Zoology and Physiology,

Box 3166, University of Wyoming, Laramie, WY 82071

Charles J. Krebs, Department of Zoology, University of British Columbia,

Vancouver, BC V6T 1Z4 Canada

Abstract—We discuss ecological theory and population models pertinent to the

population biology of southern lynx. Fragmented forest cover types, high

vagility of lynx, and linkages in population dynamics suggest that lynx in the

contiguous United States are arranged as metapopulations. Metapopulation stability depends on not only habitat quality but also dispersal rates between habitat

islands. Models indicate that dispersal rates between habitat islands should sharply

decrease as the islands become smaller and more distant and the risks associated

with crossing between islands increase. Southern lynx populations may fluctuate,

which affects both rates of extinction and colonization of habitat islands. Synchronous population fluctuations can decrease the viability of metapopulations. Southern habitat islands probably are source-sink mosaics that shift with disturbance and

succession. Models indicate that temporally transient habitat may be underutilized

by organisms. Lagged synchronous patterns observed in both northern and southern populations suggest broad connectivity between subpopulations, but empirical
22

Chapter 2—McKelvey

data are lacking and some subpopulations may be isolated. Models that combine

dispersal into spatial predator-prey models generate similar patterns, and dispersal

can provide a synchronizing mechanism. We emphasize the dangers associated

with ignoring either local habitat quality or regional connectivity.

Introduction

To conserve lynx we must rely on both applicable ecological theory and

specific information about lynx ecology like that presented in the middle

section of this book. The purpose of this chapter is to review the ecological

concepts and parameters used in evaluating population viability. We identify some of the specific problems associated with applying these concepts

to lynx.

Population Viability

The population, not the species, is the appropriate taxonomic level of focus

for most conservation efforts (Chapter 5, Ruggiero et al. 1994). The National

Forest Management Act of 1976 requires the U.S. Forest Service to maintain

viable populations of all native vertebrate species, and the Endangered

Species Act of 1973 recognizes distinct population segments as appropriate

levels of statutory protection. Biologically, the importance of maintaining

viable populations is based on the idea of ecological dependency (Ruggiero

et al. 1988), which implies a dynamic relationship between a population and

the environment that supports it.

Population viability refers to the probability that a population will persist

for a specified time into the future (Boyce 1992). Formal Population Viability

Analysis (PVA), however, requires information on many variables that are

difficult to estimate for low-density populations (Beissinger and Westphal

1998) like the lynx. For even the simplest deterministic models, information

on age structure, breeding schedule, and survival rates are needed. These

models assume that demographic rates are constant, which certainly is not

true for lynx. Given even this minimal list of parameters, we cannot build

these models for southern populations of lynx given the scarcity and

uncertainty of data on lynx vital rates (Chapter 13). We can, however,

evaluate ecological theory as it pertains to lynx at the southern periphery of

their range and evaluate potential risks to population persistence.
23

McKelvey—Chapter 2

Stochastic Factors That Affect Viability

Small populations are usually thought to have low viability because of

their vulnerability to chance events. The elements of chance that affect

viability are demographic stochasticity, environmental stochasticity, genetic stochasticity, and catastrophe (Shaffer 1981). Demographic and environmental stochasticity are terms generally associated with birth and death

rates. Demographic stochasticity refers to chance events that work at the

level of the individual; environmental stochasticity to chance events that

affect the vital rates of the population such as low reproductive rates during

a drought.

Catastrophes differ substantially from either demographic or environmental stochasticity. Both demographic and environmental stochasticity

affect expected times to extinction and are sensitive to population size.

Catastrophes can eliminate an entire population at a single moment in time

regardless of its size. Many catastrophes are associated with disturbance

processes such as fire, flood, or volcanic eruption and have limited geographic scope. Such processes may kill all of the organisms within the

disturbed area, but populations outside will be unaffected. In species like the

lynx with a broad geographic distribution, catastrophe is not likely to play

a major role in species persistence. However, small southern populations of

lynx could be affected by catastrophic events, with consequences for viability in the contiguous United States.

Genetic stochasticity is similar to demographic stochasticity but operates

at the genetic level and is expressed indirectly through demographic processes (Saccheri et al. 1998). For example, genes associated with diseaseresistance may be lost by chance in matings among closely related individuals, and the resulting progeny would experience increased mortality rates.

In small populations, this can produce a positive feedback between genetic

and demographic processes: genetic losses reduce fitness, which leads to

smaller populations, increased rates of genetic loss, and further fitness

reductions. This process has been called an extinction vortex (Gilpin and

Soulé 1986).

The genetic properties of populations are vital to both short and long

term population persistence and these issues are discussed more fully in

Chapter 5. In this chapter, the models and theory deal strictly with demographic processes and do not address the genetic processes described above.

While ignoring genetic factors is clearly artificial, genetic and demographic

processes tend to happen at very different rates. For instance, demographic

population rescue requires that enough immigrants enter a population on

average to make up the difference between population losses (emigration
24

Chapter 2—McKelvey

and mortality) and birth rates. This rate of immigration is generally several

orders of magnitude greater than is necessary to accomplish genetic rescue,

which entails offsetting the loss of alleles through genetic drift (See Gilpin

1991 for a discussion of genetic drift in small, fragmented populations).

Population Viability Concerns for Southern Lynx Populations

Southern lynx occur at relatively low densities, are found almost exclusively in cool, moist, coniferous forest types (Chapter 8), eat a winter diet

dominated by two species (snowshoe hare and red squirrel; Chapters 9 and

13), and, at least in Canada and Alaska, exhibit strongly cyclic population

dynamics (Chapter 9). In the contiguous United States, forest cover types in

which lynx have occurred are either peninsular extensions of larger habitat

areas in Canada or discrete islands (Chapter 8, Figs. 8.19-8.23, Map Insert).

Given the low densities of lynx in these southern habitats (Chapter 13), many

of these habitat islands will contain relatively few individuals and may

collectively function as metapopulations. Alternatively, many of these habitat islands may function as separate, isolated populations unto themselves,

rendering each isolated population highly vulnerable to extirpation.

In southern boreal forests, hares appear to exist in many areas at densities

close to the lower limits required for lynx reproduction (Chapter 7) and lynx

densities are correspondingly low (Chapter 13). Prey densities vary with

forest type and stand age. For a population at equilibrium (birth rates = death

rates), small changes in habitat quality can produce a sink (birth rates < death

rates). Because southern lynx populations appear to exist close to this

threshold, southern lynx habitat probably is a shifting mosaic of source and

sink areas.

Lynx populations in the taiga exhibit cyclic dynamics with high-amplitude

fluctuations (Elton and Nicholson 1942; Stenseth et al. 1997; Chapters 8, 9).

There is some evidence that hares (Chapter 7) and lynx (Chapter 8) fluctuate

in the south as well. Population fluctuations potentially change the dynamics of local extinction and colonization, and can produce a number of unique

spatio-temporal patterns such as travelling waves (Okubo 1980). These are

population fluctuations that move, like waves, across broad geographic

areas (See Moss et al. in press for a well-documented example). Adjacent

geographic areas experience peaks and troughs that are lagged behind those

at the origin of the wave, producing the “lagged synchrony” referred to in

later chapters.

Based on these understandings, we believe that three areas of ecological

theory are particularly pertinent to southern lynx populations:

metapopulation dynamics, source-sink habitat relationships, and special

properties of cyclic systems.
25

McKelvey—Chapter 2

Metapopulation Dynamics

Metapopulation models view a population as a number of discrete subpopulations within habitat patches or “islands” connected by dispersal.

Through time, subpopulations may go extinct and be recolonized, but the

larger metapopulation persists. The original metapopulation model described a population of equal-sized habitat islands separated by areas that

contained no resident organisms, but which allowed dispersal (Levins 1969,

1970). According to the model, subpopulations were in one of two states:

either populated or extinct. The dynamics of Levins’ model are described by

the differential equation:

 

dp

dt = mp p ep ( – )– 1 (1)

where p is the proportion of habitat islands occupied, m is the colonization

rate, and e is the extinction rate of the subpopulations. The expected

equilibrium proportion of occupied islands is:

 

pˆ – e

m = 1 (2)

Hence, if the extinction rate is less than the colonization rate, the

metapopulation will persist on at least some of the islands. If the subpopulations are completely isolated, (m = 0), then the metapopulation cannot

persist.

An important inference from this model is that when the rate of local

extinction equals that of colonization, all islands are unoccupied and the

entire metapopulation goes extinct. For most of the islands in a

metapopulation to be occupied at a given time, the colonization rate must

greatly exceed that of local extinction. If subpopulations on islands are

extinction-prone, then a stable metapopulation requires a high rate of

dispersal between the islands.

Recently it has been argued that classical metapopulations, consisting of

equal-sized, equidistant islands, are a theoretical construct that rarely exists

in nature; mainland-island systems in which one island is much larger than

the others are more common (Hanski 1982; Harrison 1993). These systems

are not prone to the same kinds of instabilities as classical metapopulations,

because the mainland is large enough that its population is not prone to

extinction. However, Harrison’s (1993) criticism of applying metapopulation

theory to conservation is pertinent only if one is concerned just with the

persistence of the mainland population. For lynx in the contiguous United

States, we are interested in the dynamics of the islands, where population

persistence will be determined by colonization and extinction rates

among habitat islands.
26

Chapter 2—McKelvey

Colonization

The effect of distance—Assuming a habitat island is unoccupied, its

colonization will occur through the dispersal of organisms from either other

islands or the mainland. The probability of colonization will be a function of

the number of dispersers, and the distance to and difficulty of reaching the

islands. Lamberson et al. (1994) modeled dispersal between same-sized

habitat islands by partitioning the probability into two components: the time

it takes to travel to the island (and hence the probability that the organism

will live long enough to reach it), and the likelihood that a dispersing

individual will encounter the island. For an organism to successfully disperse, it needs to survive long enough to reach the island and it needs to

travel in the right direction. Thus, the probability of successful dispersal

rapidly declines with distance. For a single distant island, only a small

proportion of dispersers will travel in the right direction and, if dispersal is

risky, many will die in transit. We illustrate this using the algorithms

presented by Lamberson et al. (1994). If an organism travels in a straight-line

1 km per day and has a 1% chance of mortality per day while dispersing,

13.5% of the dispersers will find a 10-km wide island at a distance of 10 km.

Only 0.7% would find that same island at a distance of 100 km. This estimate

of the decline in probability of successful colonization with distance probably is conservative. Lamberson et al. (1994) assumed a constant probability

of mortality for each time-unit spent dispersing, but it is likely that death

rates increase as dispersals get longer. During dispersal, organisms are

thought not to forage as efficiently as in a home range, and the disperser’s

body condition likely will decline with time. Thus, dispersal across long

distances is risky, and successful colonization will be rare. If a disperser stops

at the first suitable site, this behavior leads to a geometric decline in

dispersals with distance, a pattern observed in a variety of organisms (Waser

1985; Buechner 1987).

Dispersal in spatially heterogeneous, cyclic populations—Levins’

(1969,1970) metapopulation model assumes equal habitat conditions in all

islands and constant rates of dispersal over time. Lynx, at least in the taiga,

display strongly cyclic population dynamics. In non-cyclic populations,

dispersal is thought to be a relatively passive process; a proportion of the

population disperses, and that proportion is determined by the evolutionary consequences to fitness of dispersing and its opposite, philopatry

(Hamilton and May 1977). In temporally stable habitats, dispersal should

generally lead to decreased fitness and therefore should not be favored

(Hastings 1983; Holt 1985). In a temporally unstable environment, however,

dispersal can be favored even if fitness costs are high (Levin et al. 1984; Frank

1986; Cohen and Levin 1991).
27

McKelvey—Chapter 2

Dispersal may be particularly important for regulating cyclic populations,

but the mechanisms are poorly understood. Krebs (1992) described a phenomenon, the “fence effect,” in voles: if a vole population is physically

enclosed (“fenced”), the population will rise to high densities and subsequently crash, a dynamic not seen in adjacent unfenced populations. Here,

dispersal is a pre-saturation phenomenon with a population-regulatory

function. Krebs (1992) speculated that cyclic populations are characterized

by pre-saturation dispersal, whereas non-cyclic populations exhibit saturation dispersal. In general, dispersal is thought to be more critical for cyclic

populations and may help generate or propagate the cycles. In Canada, lynx

are strongly cyclic, but long-range movements are more frequent during

those periods when hares are rapidly declining (Chapter 9), indicating postsaturation dispersal. The extent to which these movements result in

successful dispersal is, however, unknown.

Successful dispersal—Colonization of islands in a metapopulation differs

fundamentally from within-island or within-mainland dispersal, in that the

latter does not require crossing extensive unsuitable habitats. Dispersal, by

definition, describes movement from site of origin to site of next mating, and

successful dispersal to the entire process of movement, subsequent mating,

and production of young (Shields 1987). If dispersal to distant habitat islands

is rare, successful dispersal must be even more so. Early models (e.g.

MacArthur and Wilson 1967; Richter-Dyn and Goel 1972), concerned only

females, and males were assumed to either automatically follow along or to

have impregnated females before dispersal. For most mammals that do not

exhibit embryonic diapause, these assumptions are unrealistic; successful

dispersal requires, at the very least, a male and a female to arrive at the

destination at about the same time. In the example above, if the source island

produced 10 dispersers per year, then about one animal per year would

successfully disperse 10 km. If the organism were fairly long-lived, this

would provide a reasonable probability of a mating pair co-occurring in the

destination island and dispersing successfully. At 100 km, however, a

dispersing animal would find the island only once every 14 years, greatly

reducing the probability of successful dispersal.

These problems are exacerbated if long-range dispersal is sex-biased. It is

widely believed, for example, that dispersal in many mammals is maledominated (Greenwood 1980; Cockburn et al. 1985; Clark et al. 1988),

although for many species the evidence is weak (see Gaines and McClenaghan

1980) and based on questionable methods (Porter and Dueser 1989). Still, if

most long-range dispersal were by males, then simultaneous male-female

occurrences at destinations would be rarer than overall dispersal rates

suggest. Data on lynx in southern Yukon concerning sex-bias in emigration
28

Chapter 2—McKelvey

are equivocal. In general, rates of emigration showed no sex bias, but 14 of

17 detected movements >100 km were males (Chapter 9). Data on rates of

dispersal, successful and otherwise, are few. Dickman and Doncaster (1989)

found that in urban environments wood mice and bank voles recolonized

distant sites (200-400 m) more slowly than close sites (50-140 m).

The previous discussions concerning dispersal only consider animals that

move independently and disperse in random directions. These assumptions

may be inappropriate. Animals may have knowledge acquired through

exploratory movements or may have direct visual clues that allow them to

move directly from one habitat island to the next. Similarly, if an organism

leaves a scent trail during dispersal, then other dispersers can follow it

thereby increasing the number of dispersers that reach a specific location.

We do not know if lynx have dispersal mechanisms that allow them to more

efficiently colonize islands, but exploratory movements appear to be fairly

common in southern populations (Chapters 11, 13).

Introductions and reintroductions of organisms, which are human-facilitated dispersals, are better documented than natural dispersal events.

Introductions allow us to look at the likelihood of success, given dispersal.

Although introductions and dispersal differ in important ways, some of the

factors that lead to failure (animals arriving in poor condition, behaviors

poorly adapted to the destination, importance of stochasticity in small

populations) will be similar. Importantly, introductions are intended to

succeed and designed to that end. Even so, introductions often fail. In desert

bighorn sheep, all introductions in which the initial population was less than

50 individuals failed within 50 years (Berger 1990). Of 353 insect introductions to control exotic weeds, 70% failed, and success was insensitive to

initial population size: 66% of the introductions in which the initial population was ≤20 failed compared with 70% of those with initial populations

>100 (Simberloff 1989). It is reasonable to conclude that even with large

numbers of dispersers, colonization will frequently be unsuccessful.

Pulsed dispersal and colonization—The role of cyclic dispersal in colonization has been little studied. As we have shown, colonization of distant

areas is very unlikely if animals disperse at constant rates over time. If,

however, dispersers are pulsed so that at some times many dispersers are

searching simultaneously, then the probability of distant colonization increases significantly. Assume, as in our earlier example, that each disperser

has a 0.07% chance of successful arrival at a habitat island, that 90% of

those that arrive survive for a year, and that at least two animals cooccurring at the destination will result in colonization. If the source population produces 10 dispersers every year then, on average, the island will

have ≥2 organisms about 3% of the time. If, however, 100 dispersers are
29

McKelvey—Chapter 2

produced once every 10 years, this increases to about 10%. Of course, not all

sets of two organisms will mate; they will be of the same sex about half the

time. If we assume that at least four organisms are needed for colonization, producing 10 dispersers per year will virtually never achieve this

(0.05%), whereas a 10-year pulse of immigrants will put ≥4 organisms on the

island about 8% of the time.

Extinction after successful dispersal—After a habitat island is colonized

by successful dispersal, the risk of extinction should decrease as the population gets larger. But the relation between extinction risk and population

size is critically dependent on the kind of extinction risk. Early models

(MacArthur and Wilson 1967; Richter-Dyn and Goel 1972) considered only

demographic stochasticity. Demographic stochasticity in a very small

population can be viewed as being similar to a series of coin flips: if heads

the population decreases by one, if tails, it increases by one. If population

size = 3, then HHH would cause extinction, as would HHTHH. In very small

populations, random events leading to extinction are likely and extinction

rates are high. As population size increases, even to as few as 20 reproducing

females, the probability of this type of random event leading to extinction

becomes vanishingly small (MacArthur and Wilson 1967; Richter-Dyn and

Goel 1972).

If demographic stochasticity were the only extinction risk, then except for

tiny, isolated populations metapopulation dynamics would be unimportant. However, environmental stochasticity, including weather, affects the

demography of the metapopulation. Harrison and Quinn (1989) included

correlated environmental stochasticity in a model of metapopulation dynamics and found that if the means and variances of subpopulation extinction rates were high, temporal correlation of subpopulation events greatly

reduced the average time to metapopulation extinction. However, if the

extinction rate of subpopulations was low or moderate and consistent

among subpopulations, high environmental correlation among subpopulations did not predispose the metapopulation to go extinct. The largest

differences between correlated and non-correlated systems were seen in

metapopulations with many islands. So, number of islands in a

metapopulation, rate of subpopulation extinction, and environmental correlation among subpopulations are all related to the persistence of

metapopulations.

Source-Sink Dynamics

Southern lynx populations appear to exist at lower densities and to have

lower reproductive rates than northern populations (Chapter 13). Habitat
30

Chapter 2—McKelvey

heterogeneity is also much higher than in the taiga (Chapter 3); therefore,

southern populations likely occur partly in areas which act as “sinks” and

are dependent on immigration from “sources.” Source environments produce surplus animals, which must disperse to have a chance of surviving.

Sink environments do not produce enough animals to sustain themselves

and, in the absence of immigration from source areas, populations living in

sink areas go extinct (Pulliam 1988). To determine whether a particular area

is a source or a sink, we need to know the birth and death rates of the

population (Krebs 1994). We cannot use the surrogate measure of population density to determine source or sink environments; ecologists have

repeatedly pointed out that sink areas may contain high population densities (Van Horne 1983; Hobbs and Hanley 1990).

In source-sink models (Pulliam 1988; Pulliam and Danielson 1991; Howe

et al. 1991) equilibrium dynamics depend on specific rules concerning

habitat selection, as well as the vital rates associated with the source and sink

areas. If, for instance, a few areas were very productive, but in the rest of the

landscape birth and death rates were nearly in balance, a very large population could be supported by a few source areas. Conversely, the loss of a few

important areas could destabilize a very large population that depended on

sources to maintain population viability.

Source-sink dynamics tend to be modeled as spatial rather than temporal;

a given area is assumed to be either a source or a sink environment permanently (Pulliam 1988; Pulliam and Danielson 1991). Source-sink concepts as

they relate to lynx, however, are complicated by strong temporal components. In the North, the same areas that produce excess animals at one phase

in the cycle are strong sinks a few years later. Similarly, because the densities

of prey change as stands undergo succession (Chapters 6, 7, and 14), areas

that are sinks today may be sources in a few decades, or vice-versa. When

evaluating landscape-level changes and their impacts on source-sink dynamics, it is therefore necessary to determine both current and long-term

productivity of a particular area.

Fahrig (1992) modeled habitat change using a simple model in which

habitat was either suitable or not and found that the model was far more

sensitive to turnover rates of habitat than it was to the distance between

habitat islands. While not a source-sink model in a formal sense, it indicated

that temporal changes in habitat quality could have a profound impact on

population stability. To address this question using a source-sink model,

Pulliam et al. (1991) built a more complex simulation model for the Bachman’s

sparrow (BACHMAP; Pulliam et al. 1991) that allowed habitat areas to

change quality over time so as to simulate active forest management.

Bachman’s sparrow, which historically was found in old pine forests, has

declined over much of its range (Pulliam et al. 1991). An interesting aspect
31

McKelvey—Chapter 2

in this decline is that Bachman’s sparrows breed in newly planted pine

fields as well as old-growth areas, but seldom in intermediate-aged stands

(Pulliam et al. 1991). Young stands areas are plentiful in the short-rotation

southern pine plantations, and reproductive rates in these areas are no

different from those in old forests (Haggerty 1988). Source-sink dynamics

were therefore allowed to vary; the highest recruitment rates were in very old

and very young forests. Surprisingly, Pulliam’s (1991) model consistently

showed that population sizes were maximized when the largest amount of

old forest was retained. As with Fahrig’s (1992) model, the rapid turnover

of the source habitat after cutting precluded its effective utilization.

Cyclic and Spatial Dynamics: Synchronizing

Elements and Traveling Waves

Predator-Prey Dynamics

In mathematical models, populations of specialist predators can exhibit

stable, cyclic, or chaotic behavior. These dynamics reflect interactions between the predator and the prey; the predator affects prey densities and is,

in turn, affected by the prey (May 1973; Hanski et al. 1993). The inclusion of

generalist predators, which can switch prey, tends to dampen cyclic behavior and produce more stable systems (Hanski et al. 1991). Because of preyswitching behavior, predator populations tend to become decoupled from

dynamics of a specific prey (Erlinge et al. 1991; Hanski et al. 1991). For

instance, in northern Canada coyotes depend entirely on snowshoe hares

(O’Donoghue 1997, Chapter 4), and their populations cycle much like those

of lynx in response to hare densities. Because they are hare specialists, their

addition to northern ecosystems in the early 20th century would not necessarily change the cyclic behavior of hares or other hare predators. However,

in areas farther south where coyotes switch to ungulate prey when hares are

scarce (Chapter 4), we would expect them to have a very different influence.

This is consistent with the generally stronger appearance of cyclic dynamics

in northern, less species-rich ecological systems. Similarly, microtine rodent

populations in northern Scandinavia are more cyclic than those farther

south, likely because there are more generalist predators in southern areas

(Erlinge et al. 1991; Hanski et al. 1991).

Diffusion-Reaction Models

Simple predator-prey models assume homogeneity in vital rates and the

interactions between predators to prey. These models therefore apply only
32

Chapter 2—McKelvey

to small geographic areas. For larger areas, predator-prey dynamics are

linked through movement. The inclusion of movement into population

models generally changes their dynamics. In many cases, dispersal acts to

stabilize (Doebeli 1995) or synchronize (Blasius et al. 1999) intrinsically

unstable or chaotic systems. These dynamics have been conceptualized as

diffusion-reaction models (Okubo 1980), in which the diffusion is movement

and the reaction is predator-prey dynamics defined in space and time.

Diffusion-reaction models tend to generate traveling waves (Skellam 1951;

Okubo 1980), that resemble the cyclic behavior of lynx populations over

broad geographic areas (Blasius et al. 1999). For instance, in the simple case

where a population originates at a particular point in space and time,

population growth will spread outward from that point in the form of a

wave. The wave travels at a rate defined by the intrinsic growth rate of the

population and the rate of movement (Okubo 1980; Shigesada and Kawasaki

1997). Unless the predator population is zero behind the frontal wave, the

system is characterized by a “wake” of smaller following waves, the magnitude, duration, and character of which depend on characteristics of the

system being modeled (Gurney et al. 1998). The degree to which actual

dispersal behavior is correctly modeled by diffusion is unknown for most

species. Skellam (1951), however, demonstrated that dispersal of muskrats

in Europe closely followed model expectations.

Large-scale synchrony can be achieved through the coupling of cyclic or

chaotic systems through dispersal (Blasius et al. 1999). Of particular interest

to lynx dynamics is “phase synchronization,” characterized by synchronization of periodicity but not of amplitude (Blasius et al. 1999). This pattern,

which appears to describe lynx dynamics in Canada during the 20th century

(Chapter 9 Fig. 9.4, Blasius et al. 1999), occurs at intermediate levels of

diffusive coupling.

Discussion

If a landscape provides small habitat islands, then the system will only be

stable if it functions as a metapopulation. Very small isolated populations

are subject to a variety of risks and are prone to extinction. For a

metapopulation to persist, rates of colonization must greatly exceed rates of

extinction. Colonization rates, in turn, are driven by the number of colonizers produced by the islands and the probability of successful dispersal

between islands. Because metapopulations depend both on population size

within and dispersals between islands, they can easily be destabilized. If, for

instance, adult mortality were increased so that populations on the islands

were generally below carrying capacity, even if these populations appeared
33

McKelvey—Chapter 2

stable, dispersal would be greatly reduced: there would be fewer potential

dispersers and more of these would likely remain on their natal islands.

Similarly, maintaining populations on the islands at carrying capacity, but

reducing between-island dispersal, would also potentially destabilize the

metapopulation.

For lynx, it is likely that rates of dispersal between both the large mainland

population in the North and between other islands in the contiguous United

States are highly variable. Lynx populations therefore may exist as several

smaller but effectively isolated metapopulations. Arguably, the lynx in the

northeastern United States are effectively isolated from the main Canadian

populations by the St. Lawrence Seaway (Chapter 8) and from the Great

Lake States by agricultural conversion and urban development. Similarly,

boreal forests in Colorado and Utah are separated from the larger areas of

boreal forest in Wyoming by at least 100 km (Chapter 8). If these areas have

become effectively isolated, then they represent special areas of concern

and, if they still contain native populations, these populations are particularly endangered.

We know very little about lynx biology in the southern portions of its

range, but the population dynamics we observe are complex and appear to

be spatially interconnected (Chapter 8). We do not know the degree of

connectivity or its role in the viability of the species, but we assume that

connectivity per se is important. We do not know, for example, how

population dynamics in Saskatchewan affect those in Montana. In later

chapters, however, we demonstrate lagged synchronous fluctuations that

resemble the traveling waves produced in predator-prey models that include movement. Thus, we have support for the importance of the connectivity of lynx populations from metapopulation theory, spatial models and,

limited empirical data.

We know very little about the densities of snowshoe hares or red squirrels

in the contiguous United States, but recognize tremendous variability in

these densities among forest types and successional stages. Given this

variability, source-sink modeling suggests that landscape proportions, spatial arrangement, and turnover rates of these successional stages may be

critically important to the stability of lynx subpopulations.

We suspect that competition from other carnivores could mediate lynxprey interactions (Chapter 4), and we know that generalist predators can

alter the cyclic dynamics of prey populations. But we do not know how these

variables are affected by forest fragmentation, nor how they affect lynx

demography; we cannot parameterize the simplest model that we might

construct of a lynx population. Without better empirical knowledge of the

biology of the lynx-prey-vegetation system, these concepts and models can
34

Chapter 2—McKelvey

only guide us in the most general sense. Even so, they provide us with

useful, and in some cases the only, guideposts on the path to scientific

management of lynx.

Our uncertainty about the ecology of lynx, combined with the obviously

complex interactions of cycling populations over an expansive assumed

metapopulation structure, make the lynx-prey-vegetation system a complex

ecological problem. Several recent conceptual developments, like sourcesink and metapopulation theories, clearly have major implications for lynx

populations in the contiguous United States; but without more empirical

data and modeling efforts, we can only guess at what those are. We know

remarkably little about the current status and numbers of lynx in the

contiguous United States (Chapter 8). However, what little we know indicates that the subpopulations are not large. Until we better determine the

current location and sizes of lynx sub-populations, it is unwise to assume

that these populations can be reduced or further isolated without sharply

increasing the risk of their individual and collective extinction.

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38

Chapter 2—McKelvey
39

Chapter 3

Disturbance Ecology of

North American Boreal

Forests and Associated

Northern Mixed/

Subalpine Forests

James K. Agee, College of Forest Resources

Box 352100, University of Washington, Seattle, WA 98195

Abstract—Disturbance dynamics differ in the three subregions of the North

American boreal forest (taiga, western United States, and eastern United States)

where lynx are found, resulting in a range of potential effects on lynx populations.

Fire severity tends to be high in most of the forest types where lynx habitat occurs,

although subsequent succession will differ among the subregions. Other disturbance dynamics involve insects, disease, wind, and human ownership and use, such

as logging, mining, agriculture, and fire suppression. The author addresses three

general lynx management implications based on disturbance dynamics.

Introduction

The distribution of the lynx in North America is closely associated with the

distribution of the North American boreal forest. The range of the lynx

extends south from the classic boreal forest zone, called the taiga, into the
Chapter 3—Agee

40

subalpine forests of the western United States, and the boreal/hardwood

forest ecotone in the eastern United States (Chapter 8). This chapter summarizes the forest ecology of lynx habitat within the boreal zone of North

America,including the effects of a variety of disturbance agents.

Divisions of the North American Boreal Forest

There are few, if any, forest classification schemes that have directly

comparable boundaries for forest biomes. Criteria for classification often

differ, and scientists often apply subjective rules. Even the acceptance of a

zonal versus gradient classification spurs debate: Larsen (1980), in his classic

treatment of the boreal ecosystem, describes the major types but favors a

gradient approach so does not map his types. Yet of all the forest biomes, the

boreal forest probably comes closest to a broadly accepted definition. The

circumpolar boreal forest is commonly perceived as a set of homogeneous

arboreal stands, dominated by conifers during later stages of succession, and

by arboreal members of the birch and willow families in early succession.

Many of the shrub species are circumpolar in distribution, but none of the

tree species are (Solomon 1992). The northern border of the boreal forest is

defined by tundra. While authors disagree slightly on where the boundary

should be drawn along the gradient from closed-canopy forest to treeless

tundra (Solomon 1992), this boundary is from one easily recognized type to

another (Fig. 3.1). In North America, the southern boundary of the boreal

forest is much more contentious, as the boreal forest changes to subalpine

forest in the western continent, to prairie in mid-continent, and to a mixed

coniferous/deciduous temperate forest in the east. These southern transitions are recognized in three broad groups, for the purposes of describing

lynx habitat south of Canada, across an east-west gradient (map insert):

Northeastern and the Great Lakes boreal forests that include eastern hardwoods and temperate conifers, as well as boreal conifers, and Western boreal

forest, that includes subalpine forests similar to boreal forests.

Consistent and broadly recognized terminology is essential to effective

presentation. I have chosen here to refer to the boreal forest as any forest with

boreal features. This includes not only the taiga, but forests to the south such

as the higher elevation portions of the Cascades, Sierra Nevada, and Rocky

Mountains. Tree species are referred to by common name, with an appendix

at the end of the chapter that includes Latin names; shrubs are mentioned by

common and Latin name in the text. I have chosen here to refer to the

northern boreal forest in general as taiga (e.g., Viereck 1983), with closed

forest and the more open lichen-woodland as constituents. Other authors

would disagree: taiga is variously defined as the “boreal forest” (Oechel and

Lawrence 1985; Van Cleve et al. 1983) and “the great northern coniferous
41

Agee—Chapter 3

Figure 3.1—Major divisions of the taiga, patterned after Larsen (1980). Descriptions of each zone are in

Table 3.1. 1 = Alaska; 2 = The Cordillera; 3 = Interior Forest; 4 = Canadian Shield; 5 = Eastern Canada.

biome” (Larsen 1980) but is also defined as only the northern part of the

boreal forest representing that portion from closed forest canopy to the

forest-tundra treeless boundary (Sirois 1992). The closed-canopy boreal

forest has been called the “main boreal forest” (Hare 1969). To delineate

boreal forest to the north from the transitional boreal zones to the south, the

northern zone will be referred to as taiga, with closed and open subdivisions.

The transitional boreal regions will be called, in the west, Western boreal

forests, and in the east, either Great Lakes or Northeastern boreal forests,

recognizing each has elements of boreal character.

The Physical Environment

The physical environment of the boreal forest is similar around the world.

Unlike most other forest biomes, the boreal forest can be defined on the basis

of structure as much as species composition (Hare and Ritchie 1972; Solomon

1992), and these structural characteristics are closely associated with climatic

and edaphic factors (particularly permafrost). Climatic gradients across the

type include decreasing radiation to the north, differing air mass trajectories

that influence cloud cover and precipitation, topography, and maritime/

continental location (Elliott-Fisk 1988). Long, bitterly cold winters, short and
Chapter 3—Agee

42

cool summers, and brief springs and autumns are characteristic of the boreal

climate (Trewartha 1968). Although the growing season is short, unusually

long summer days compensate to some extent for the brief and cool summers. These summer periods include times with low fuel moisture and strong

winds, associated with severe fire behavior (Schroeder and Buck 1970).

The northern limit of treeline in the Arctic generally occurs along the 13°

July isotherm. Boreal forest is bounded on the north by 30 or fewer days with

mean temperature above 10°C, and to the south by 120 days with mean

temperature above 10°C. Mean yearly temperatures increase from a minimum of –6.2°C near the forest tundra ecotone to 2.5°C near the southern

closed boreal forest boundary. Precipitation is concentrated in the summer

months, and snow cover lasts more than half the year. Although North

American boreal winters are not as severe as those of Siberia (due to a smaller

land mass), large parts of the region are permanently frozen, and the depth

of thaw of the permafrost layer during the summer has a great effect on

rooting depth and nutrient availability (Trewartha 1968; Van Cleve et al.

1983).

Western boreal forest is primarily subalpine rather than a classically boreal

climate. Most of these areas border temperate forest at lower elevation and

alpine communities at higher elevation. This is analogous to the much wider

borders of the taiga with tundra to the north and temperate forest to the

south. Western boreal forests are found at elevations above 1,400 m in

Washington (Agee and Kertis 1987), but the rainshadow effect of the coastal

mountains raises the elevations of all the forest zones to the east, so that

boreal forest is found at 2,700 m elevation in the Colorado Front Range (Peet

1981). The elevation of the Western boreal zone may shift with climatic

change or disturbance (Agee and Smith 1984; Rochefort et al. 1994). Western

boreal forests generally receive more solar radiation and have higher diurnal

temperature fluctuations and warmer temperatures, as well as shorter

growing season day lengths, than classic boreal environments of the taiga

(Oechel and Lawrence 1985). Local topographic variation makes climatic

information difficult to generalize for Western boreal environments. Water

stress may affect photosynthesis at some locations, and severe winter winds,

carrying snow and soil particles, have a significant detrimental effect on

plants that emerge above the snow line in timberline environments.

The Great Lakes and Northeastern boreal forests tend to be warmer than

the taiga, with mean annual temperatures from 1.6 to 7.2°C (Rowe 1972).

They tend to have more available moisture than either the taiga or the

Western boreal forests (Rowe 1972).
43

Agee—Chapter 3

Table 3.1—Major forest regions of the taiga, adapted from Larsen (1980) and Elliott-Fisk (1988).

Region and description

1. Alaska

Upland and lowland forests dominated by white spruce, black spruce. Paper birch and quaking aspen are common pioneer species, with balsam

poplar along streams and floodplains. Fire and permafrost important environmental factors.

2. The Cordillera

Mesophytic uplands dominated by white spruce and white birch. North aspects dominated by black spruce, with a different shrub understory.

Southward, into the subalpine forest type, forest dominants are Engelmann spruce, subalpine fir, subalpine larch, and balsam poplar.

3. Interior Forest

This forest is composed of black spruce, white spruce, lodgepole pine, quaking aspen, and balsam poplar, extending from the Cordilleran foothills

to the Canadian Shield. Black spruce is again common on north aspects, with white spruce typically dominant in the floodplains. The eastern portion

of this zone also includes jack and/or lodgepole pine (ridges and sandy soils), and some eastern larch and balsam fir.

4. Canadian Shield

Both east and west of Hudson Bay, this forest is relatively uniform, with richer forests (more species) to the south. In the southerly regions, balsam

fir/white spruce is dominant in valleys, with jack pine on uplands and black spruce in lowlands. To the north, black spruce, white spruce, and jack

pine are common, with black spruce dominant near the northern forest border.

5. Eastern Canada

The Gaspe-Maritime forests are closely related to those of the Great Lakes–St.Lawrence region. Forests are primarily coniferous with balsam

fir playing a prominent role; associated dominants are black spruce, white spruce, and paper birch. In Labrador-Ungava, black spruce and white

spruce are often dominants, but balsam fir, eastern larch, paper birch, and balsam poplar are also found. Quaking aspen, jack pine, and white cedar

are found to the south. Complex topography and geology has produced a complex mosaic of plant communities. Black spruce becomes more

important to the north.

Composition of the Major Boreal Forest Types

The Taiga

Within the broad structural classes of closed boreal forest and lichen

woodland that comprise the taiga are geographic variants. As one travels

east or west, continuous change is present although not obvious over short

distances (Larsen 1980). Larsen classified the taiga into various regions from

west to east (Table 3.1), with each region having a south-north gradient from

the closed boreal forest on the south to lichen woodland to forest tundra

(Fig. 3.1).

Rowe (1972) defined eight major forest regions in Canada: the taiga is by

far the largest. He subdivides the taiga into three parts: a “predominately

forest” type, equivalent to closed boreal forest, a “forest-grass” type which

fringes the plains in southern Alberta, Saskatchewan, and Manitoba, and a

“forest-barren” type, that borders the “predominately forest” type to the

north and is transitional to tundra. He defines roughly 33 geographically

based “forest sections” within the taiga, with white and black spruce

common across the spectrum. Eastern larch, balsam fir, and jack pine are

common in the eastern portions, and subalpine fir and lodgepole pine are

more common in the west, particularly in the transition to subalpine forest.

Although primarily coniferous, the taiga does include white birch and its
Chapter 3—Agee

44

varieties, as well as quaking aspen and balsam poplar. The proportion of

black spruce and eastern larch increases to the north. The eastern portion of

the taiga includes an intermix of species that are summarized below under

Great Lakes and Northeastern boreal forest. Viereck and Dyrness (1980)

extend the taiga forest classification into Alaska and create a wide number

of potential vegetation types aggregated into bottomland, lowland, and

upland forests.

Great Lakes and Northeastern Boreal Forest

The boreal forests of the Great Lakes and Northeast are southern extensions of boreal forest. These forests, as transitional types from boreal to

temperate forest, are not well described in either the boreal forest (ElliottFisk 1988) or the deciduous forest (Greller 1988) descriptions of the North

American terrestrial vegetation (Barbour and Billings 1988). While having

the boreal species, this heterogeneous type also has many elements of the

forests to the south (Pastor and Mladenoff 1992). Balsam fir is an important

species, and appears to replace white spruce in an ecological sense. White

pine, white cedar, and white birch are all more “important” than white

spruce. Three species of Populus and three maples are also important

members of the community. Black spruce and eastern larch are found in

lowlands and nutrient poor sites (Larsen 1980). The distribution of both the

Great Lakes and Northeastern boreal forest (map insert) closely resembles

the range maps for balsam fir and black spruce (Fig. 3.2).

Balsam fir and northern white cedar are more important as soil moisture

increases, with white pine and white spruce decreasing in importance. Sugar

maple is important on mesic sites and jack pine, black spruce, and eastern

hemlock distributions are bimodal, peaking at the extremes of the moisture

gradient (Maycock and Curtis 1960; Pastor and Mladenoff 1992). Many of the

understory species are circumpolar, but for trees, only genera are circumpolar, with significant species differences between the northern and southern

parts of the mixed forest type.

In Wisconsin, the boreal forest can be divided into three somewhat distinct

types: first, old stands of pure conifers with balsam fir and white spruce as

major dominants, along with eastern white pine, red pine, or white cedar;

associated hardwoods are paper birch, mountain ash, red maple, and

mountain maple. Second, in mixed conifer-hardwood stands, found on

inland mesic sites, shade tolerant hardwoods slowly replace the conifers;

and third, dense stands of balsam fir or white spruce replacing a decadent

canopy of white birch or aspen, with occasional balsam poplar (Curtis 1959).

Some of these divisions represent successional sequences more than environmental heterogeneity.
45

Agee—Chapter 3

Figure 3.2—The ranges of balsam fir and black spruce (Little 1971) south of the Canadian border

closely parallel the distribution of boreal forest in the Great Lakes and Northeast.
Chapter 3—Agee

46

Western Boreal Forests

The extension of boreal features into the subalpine forests of the western

United States where lynx are found is a southern modification of the boreal

conifer forests, which are similar floristically and structurally (Peet 1988).

Engelmann spruce, subalpine fir, and lodgepole pine, the primary dominants across the Western boreal forest, are genetically similar to, and

sometimes hybridize with, the northern boreal species white spruce, balsam

fir, and jack pine. Each species of the first group (Peet 1988) is genetically

heterogeneous, and it is thought that the more genetically homogeneous

boreal species of each pair may be derived from the more heterogeneous one

(Taylor 1959; Parker et al. 1981; Critchfield 1985). North of about 54°N

latitude, white spruce replaces Engelmann spruce. As one moves south,

white spruce occurs at lower elevations than Engelmann spruce and hybridizes with it (Peet 1988). Boreal habitat becomes more fragmented to the

south, with the Colorado Rockies separated from similar habitat in Utah and

northwestern Wyoming (Findley and Anderson 1956).

The Western boreal forests where lynx habitat has historically occurred

(map insert) are surprisingly uniform in their tree species composition:

Engelmann spruce, subalpine fir, and lodgepole pine are found across the

range. At the western edge of these relatively cold and dry forests, maritime

influences allow mountain hemlock to be found on protected sites (Arno and

Hammerly 1984; Agee and Kertis 1987). At timberline in the west, whitebark

pine and subalpine larch replace spruce and fir (Arno and Habeck 1972). In

Colorado, limber pine is a timberline species on xeric sites (Peet 1981; Veblen

1986), but across these subalpine forests, both Engelmann spruce and

subalpine fir can be found to the margin of alpine tundra.

Other western boreal forests apparently do not support lynx. The boreal

zones of the western Cascades of Washington and the Olympic Peninsula

contain subalpine fir, but are dominated by Pacific silver fir and mountain

hemlock. Winter snow often exceeds 3 m depth (Franklin and Dyrness 1973).

The Oregon Cascades boreal zone has mountain hemlock and lodgepole

pine mixed with noble fir, and noble fir is replaced by red fir in the southern

Oregon Cascades. In the California Sierra Nevada, lodgepole pine and red

fir constitute the primary boreal forest species. The winter snow accumulation can be quite deep in these areas, too (Barbour and Woodward 1985). In

the southern Rocky Mountains, the boreal zone becomes a series of disjunct

and isolated “islands” of mountaintops separated by wide areas of woodland or nonforest vegetation.
47

Agee—Chapter 3

Boreal Forest Disturbance Dynamics

Disturbance is common in boreal forests. In fact, the taiga has been referred

to as a “disturbance forest” because of the ubiquitous nature of fire (Rowe

1961). Fires and insect epidemics are both major disturbance processes. Fire

frequencies can range from 50 to 250 years (Viereck 1973; Heinselman 1981).

Fire return intervals are longer (up to 500 years) in the Northeastern boreal

forest (Foster 1983) and in some of the Western boreal forests (Romme and

Knight 1981). Spruce beetles have killed white spruce across wide areas of

south-central Alaska (Werner and Holsten 1983) and Engelmann spruce in

the subalpine forests of the lower 48 states. Spruce budworm has been a

major defoliating disturbance in eastern Canada and the northeastern

United States (Blais 1968).

Forests are dynamic systems, and within a forest ecosystem, the only

constant is change. For forest trees, change occurs through tree growth and

death, and for boreal forest trees, natural disturbance has been a major factor

in terminating the life of trees. There are a number of natural disturbance

factors, including insects, wind, disease, and fire, but it is generally recognized that fire and insects were the most important disturbances across the

boreal landscape. The process of disturbance creates variability in forest

pattern, and it clearly varies in frequency by forest type. Landscape pattern

over time will depend on whether the processes are cyclic or stochastic, and

whether equilibrium or non-equilibrium systems result.

Cyclic and Stochastic Properties of Disturbance

Editor’s note: Elements of the following disussion were drawn from a fire

training lesson plan written by Kevin McKelvey, USDA Forest Service,

Missoula, MT.

Any forest stand has a probability that a disturbance will enter and kill the

trees in the stand. The nature of the probabilistic process can either be cyclic

or stochastic, independent of the actual probability of disturbance. Consider

a coin with heads (H) and tails (T) as the only possible outcomes. If it is turned

alternatively from side to side, it will create a pattern of HTHTHT, etc. The

probability, p, is 0.5 for a head or a tail. This is a cyclic process, as it is very

regular and predictable. If the coin is flipped in the air, the probability for a

head or tail remains 0.5, but the pattern might be HHTTTH, so that subsequent tosses might produce runs of heads or tails. This is a stochastic process,

even though the probability of head or tail is exactly the same as the cyclic

process.

Now consider the distribution of forest stand ages as a cyclic or deterministic process (Fig. 3.3). The even-aged, area-regulated managed forest is a
Chapter 3—Agee

48

1.0

.9

.8

.7

.6

.5

.4

.3

.2

.1

% By 1-year Classes

0 50 100 150 200 250 300

Age - Years

Negative Exponential Distribution

Average Age 100

Rectangular Distribution

Average Age 50

350

Figure 3.3—Comparison of a cyclic age class distribution (the regulated

forest) with a stochastic age class distribution (the negative exponential)

(from Van Wagner 1978).

prime example of a cyclic system (assuming that natural disturbances are

eliminated). The probability of age class x moving to age class x + 1 is one

(p = 1.0), and the probability of being “recycled” to age 0 is zero (p = 0,

assuming that all disturbances are controlled), until the rotation age is

reached, at which time the stand is cut and it moves to age class 0 with p = 1.

Forest stands operating under a cyclic process will have a rectangular age

class distribution, truncated at the rotation age (R). The average stand age is

R/2, and there are no stands older than R.

Forests can also be “regulated” by stochastic processes. Boreal forests are

the classic example of a natural forest regulated by fire acting in a stochastic

manner (Van Wagner 1978; Johnson and Van Wagner 1985). The probability

of any stand being burned in a given year is low, described by p. The

probability of a stand of age x moving to age x + 1 is then (1 –p). If this process

is carried out for a long time, then a negative exponential distribution like

that shown in Figure 3.3 will result. The frequency of any age class x is

f(x) = pe–px

This distribution assumes that the ignition pattern is random, that the area

burned per year is roughly constant, and that stands of all ages are equally

likely to burn (constant flammability). The average stand age is

1/p, or C, and this is commonly called the fire cycle. Roughly one-third of the

stands are older than the average stand age, and there is no maximum age

for a stand, in contrast to the distribution created by cyclic processes. Of

course, the number of older stands is small, and they are likely to be affected

by disease or insects if protected from fire, but this disturbance is usually at
49

Agee—Chapter 3

a finer grain than the landscape effects of fire. Another useful feature of this

distribution is that if the proportion of the landscape above or below a certain

age x is known, the entire age-class distribution can be defined:

∑ f(x) = 1 - e

–px

where ∑ f(x) is the proportion of all age classes up to age x. The negative

exponential model is simple and has a number of appealing characteristics

(Rowe 1983). For example, about one-third of the stands are older than the

mean age, or fire cycle, so that if structural characters by stand age are

known, then habitat character can be inferred, although non-spatially, just

by knowing the fire cycle.

The major criticism of the negative exponential model is its assumption of

equal flammability of stands over time. Johnson and Van Wagner (1985)

show that the negative exponential model is a simple case of the Weibull

distribution where flammability, the shape parameter of the model, c, is

constant at c = 1. Other options for flammability in the Weibull model are

monotonic increases (c >1) or decreases (c <1) of flammability with stand age.

Stochastic models have become popular for describing fire history in a

variety of forest types (Table 3.2; also, Lesica 1996). There is an implicit

assumption that the fire regime is constant over time such that the age class

data represent an ecosystem in equilibrium. Attempts have been made to

disaggregate the age class data to analyze changes in fire frequency over

time, and these are discussed below. The notions of stochasticity and

equilibrium are relevant to the stability of adequate habitat over time for

both lynx and its prey.

Landscape Equilibria

If a given cyclic or stochastic process remains constant over time, then an

equilibrium landscape is eventually produced, and the shape of the ageclass distribution will remain constant over time, although quite different

between the cyclic and stochastic models. However, if the probabilities of

disturbance change over time, then a non-equilibrium state is introduced

which may “ripple” through the age class distribution as a “blip,” or if the

probabilities of disturbance are continually changing, there may be no

predictable range of variability for any age class or the age class distribution

as a whole. Assumptions about disturbance probabilities will have major

implications for the management of lynx habitat.

Equilibrium is in part a function of scale, that in a cartographic sense

decreases as the considered area increases. As scale decreases, the total area

becomes larger, more fires will occur, and the average fire size as a proportion

of the total landscape declines. As this occurs, the assumptions necessary to
Chapter 3—Agee

50

Table 3.2—Fire frequency in the boreal forest. Each set is arranged west to east.

Fire

Biome and return

forest type interval Locationa Type of recordb

Yrs - - - Citation - - -

Taiga (closed forest only)

Black spruce 49 Porcupine River, AK (1) Stand ages - NE, W

(Yarie 1979)

Black spruce 200 Alaska (1) Fire records

(Viereck 1983)

Black spruce 100 N. British Columbia (2) Stand ages

(Smith and Henderson 1970)

Subboreal black/white spruce 125 N. British Columbia (2) BC Forest Service

Subboreal pine-spruce 150 (Bunnell 1995) estimates

Subboreal spruce 125

Spruce willow-birch 175

Jack pine 30-70 Mackenzie River (2-3) Stand ages

Black spruce 80-90 (Rowe et al. 1974)

White spruce 300+

Black spruce and 130 S. Quebec (5)

others (Cogbill 1985)

Black spruce 500 SE Labrador (5) Fire scars, reports,

(Foster 1983) air photos

Western boreal forest

Subalpine fir 109-137 North Cascades Stand ages - NFR

(Agee et al. 1990)

Subalpine fir 250 Pasayten, WA Stand ages

(Fahnestock 1976)

Spruce-fir 250 British Columbia Stand ages

(Bunnell 1995)

Whitebark pine 30-300 N. Rocky Mtns. Fire scars

(Arno 1980, 1986)

(Arno and Peterson 1983)

(Morgan and Bunting 1990)

Spruce-fir 300-350 Yellowstone Stand ages

(Romme 1982)

Spruce-fir/upland 300 Medicine Bow, WY Stand ages

Spruce-fir/drainages 300+ (Romme and Knight 1981)

Spruce-fir 202 Colorado Stand ages-NFR

(Veblen et al. 1994)

Great Lakes boreal forest

Northern pines 22 Itasca State Park, MN Fire scars

Frissell (1973)

Northern pines 100 BWCA Minnesota Stand ages-NFR

(Heinselman 1973)

Northern pines 50 BWCA, Minnesotac Stand ages - NE

(Van Wagner 1978)

Mixed forest 50-100 S. Ontario Stand ages

(Alexander and Euler 1981)

Northeastern boreal forest

Red spruce/hemlock/pine 230 New Brunswick —

(Wein and Moore 1977)

 Mixed Forest 200 Nova Scotia —

(Wein and Moore 1979)

 Mixed forest 800 NE Maine Land survey records

(Lorimer 1977)

a

 Numbers 1-5 at taiga locations refer to Larsen’s (1980) general subdivisions of the taiga summarized in Table 3.1 and Figure 3.1. b

 NFR = natural fire rotation method; NE = negative exponential; W = Weibull; blank = estimate that may or may not be quantitative. c

 The Heinselman and Van Wagner estimates use the same data but different techniques.
51

Agee—Chapter 3

apply a model such as the negative exponential become more reasonable,

and equilibrium landscape conditions are therefore more plausible. What is

an appropriate scale? The scale must be such that fire is not “episodic” and

individual fires do not burn “large” proportions of the landscape. Because

individual fires can burn thousands of hectares, the total area necessary to

consider can be quite large. The minimum equilibrium landscape size, called

the “minimum dynamic area” (Pickett and Thompson 1978), contains representative age classes of the major stages of succession and will depend on the

historic fire size distribution. The Yellowstone National Park, USA, landscape (2+ million acres) is a good example of a non-equilibrium landscape.

It is a broad subalpine plateau that rarely burns, but much of it burned in the

early 1700s (Romme 1982). The forest age classes created by those early fires

created a very large age class that moved as a “wave” through the age class

distribution over time, so that much of the park’s forest became old growth

by the late 20th century, with lodgepole pine being replaced by subalpine fir

on many sites. In 1988, the large fires that burned the national park killed

much of the old growth age class, as well as stands of younger ages, too, and

much of the park forest is now (1999) in the 10-year-old age class, which may

move as a similar age class “wave” in the future or be broken up by other

non-equilibrium fires. Obviously, for the past 300 years, and now for

centuries to come, the Yellowstone forests have not and will not possess any

equilibrium age class structure. If larger subalpine areas of the Rockies are

considered, fire may well be more an equilibrium-maintaining process at

that scale, particularly if topography is broken so that individual fires cannot

burn large proportions of the landscape in any year.

Attempts to quantify changes in fire regimes using stochastic models is a

work in progress. Johnson and Larsen (1991) developed a graphical technique to evaluate changes in slope of cumulative age class distributions over

time. It has been criticized on three grounds: (1) different analysts would

draw the subjectively placed “breaks in slope” of the lines in different places;

(2) the use of empirical, sampled age class data effectively “censors” the

oldest age classes and this “missing tail” of the distribution imparts a false

trend to the graphical technique (Finney 1995); and (3) the actual standing

age distribution, rather than the cumulative age class distributions, should

be used to estimate the time-since-fire (survivorship) distribution (Huggard

and Arnesault, in review). Most studies have incorrectly used the former

rather than the latter distribution. The use of stochastic models remains a

technique in development yet will remain important in analyzing disturbance in the boreal forest. For example, Ratz (1995) built a spatial simulation

model and tested the flammability assumptions of the Weibull model. He

found that an increasing flammability with time (c >1) fit real data sets from
Chapter 3—Agee

52

Alberta (Eberhart and Woodard 1987) better than a constant flammability

assumption.

Equilibrium models have been criticized on the basis that past climate

change, in the presence of long-lived conifers, results in no single “natural”

cycle expressed by age-class distributions on a landscape. The landscape

mosaic is a reflection of a dynamic fire cycle and carries the memory of

different past fire cycles (Johnson et al. 1998). Yet time-since-fire distributions necessary to draw such inference are rare, and the influence of climate

change on disturbance frequency is difficult to estimate. These criticisms

apply to setting the parameters, or form, of the models over time, more than

a rejection of the models. Although climate change is likely to affect fire

activity, the direction of the change is uncertain. Flannigan and Van Wagner

(1991) projected an increase in fire activity across boreal landscapes with

future global warming, while Flannigan et al. (1998) now suggest less fire

activity in these landscapes with global warming.

The application of a concept such as landscape equilibrium implies that

within limits, the forest landscape does possess equilibrium properties at

some scale, yet we should be using such models to consider alternative states

that might be more realistic. Such models might be best thought of as

operational than actual, a way to conceptualize approaches to managing a

landscape more than prescribing a precise equilibrium landscape as a

desired future condition.

Forest Fire Regimes

A fire regime is a generalized picture of the role fire plays in an ecosystem

(Agee 1993). It is often simpler to describe the fire regime than to infer its

effects on stand or landscape attributes, but the fire regime is clearly the

starting point. Most of what we know about the fire regime of the boreal

forest has been published in the last 25 years.

Fire Frequency and Variability—The fire frequency in forests where lynx

habitat occurs varies by over an order of magnitude. Average fire return

intervals using a variety of methods have been estimated for the taiga, as well

as the Western, Great Lakes, and Northeastern boreal forests (Table 3.2).

Variation is partly due to the method employed; for example, in the Great

Lakes boreal forest, the Boundary Water Canoe Area estimates of 50 and 100

years use the same data but different analysis techniques. Nevertheless,

useful trends emerge from these studies.

In the taiga, there is a trend of increasing fire return intervals (FRI) from

west to east. The drier, continental portions of the closed forests have shorter

FRIs than the more mesic eastern maritime boreal forests. Within local areas,

ridgetops or sandy soil areas tend to have shorter FRI than bottomlands. The
53

Agee—Chapter 3

Western boreal forests, with FRI ranging from 150-300 years, have generally

longer FRI than the taiga, where FRIs tend to range from 50-150 years.

Western boreal timberline variants such as whitebark pine, or isolated boreal

“islands” surrounded by lower elevation types (Agee et al. 1990), may have

shorter FRI. The Great Lakes boreal forest FRIs appear to be similar to the

boreal forest to the north. The Northeastern boreal forest, with a greater

maritime influence, tends to have longer FRIs, with fire becoming less

important than wind and insects in coastal areas (Heinselman 1981) and to

the north (Payette et al. 1989).

Fire Spread and Intensity—Fire intensity tends to be high in most of the

forest types where lynx habitat is found. This creates conditions for extensive

even-aged patches of regenerating conifer forest to occur. In boreal forest,

fast-spreading, high-intensity fires are the ones that burn most of the area

(Van Wagner 1983). Sustained fire spread rates over a day of 100 m/min with

intensities of 50,000-100,000 kW/m (flame lengths of 13-18 m) have been

measured (Kiil and Grigel 1969). Van Wagner (1983) summarizes the fire

behavior in northern mixed and boreal forests. These fires spread during

unusual weather conditions (e.g., Johnson and Wowchuck 1993) and under

those conditions are essentially unmanageable. In the Great Lakes and

Northeastern boreal forest, and portions of the Western boreal forests, fire

behavior also tends to be intense (Lorimer 1977; Romme 1982; Agee 1993).

The portions of southern boreal forests where lynx have not historically been

found tend to have a more mixed fire intensity and a moderate-severity fire

regime (Agee 1993). These may be more open timberline environments, such

as the western boreal forest with whitebark pine, or lower elevation forest

with more fire-tolerant conifers.

Although crown fires are common, fires of lower intensity do occur in

boreal forests where lynx historically occurred, although they typically are

a small proportion of the total fire area. Where trees with tall crowns or

sufficiently thick bark occur (such as red, white, or jack pine), some residual

trees may be expected (Johnson 1992). In areas where fuels are limited due

to site conditions, moderate intensity fires may occur and multi-aged stands

may result (Heinselman 1981; Gauthier et al. 1993; Roberts and Mallik 1994).

Some isolated stands on poor soils may have non-serotinous forms of jack

pine and all-aged pine structure (Conkey et al. 1995). Generally, fires in the

taiga, Great Lakes and Northeastern boreal forests and the Western boreal

forests are stand replacement events, either because of typically severe fire

behavior or the inability of the trees to survive even moderate intensity

events; these fires set the stage for open-grown regeneration. The successional dynamics of post-fire seres are discussed in this chapter in section

“Successional Patterns After Disturbance.”
Chapter 3—Agee

54

Different forest types have differing propensities to burn (Van Wagner

1983): jack and lodgepole pines have high flammability throughout the

season; black spruce forest is less prone to surface fire but supports crown

fire when weather conditions are severe; aspen and birch are highly flammable in spring when their litter layers are exposed and can dry quickly, but

all hardwood stands are less flammable in summer because their shaded

litter layers are compact and their crowns do not support crown fire; and

lowland forests require a longer drought to become flammable than upland

forests of pine or spruce.

Fire Extent and Patchiness—Fires in the taiga, as with most high-severity

fire regimes (Agee 1998b), can become quite large. A typical pattern is to

have the frequency of fire sizes skewed to the smaller fires while area burned

is skewed to the larger fires (Fig. 3.4) (Foster 1983; Payette et al. 1989; Hunter

1993). A small number of fires is associated with the majority of the area

burned; therefore, while average patch size created by fires is small, the

landscape area is dominated by the less frequent but much larger patches.

Topographic barriers in the taiga are often absent and severe weather

conditions may drive the fires for days or weeks. Many fires may reach

50,000 ha, and fires of >200,000 ha are possible (Viereck 1983). In the

maritime region of Northeastern boreal forests, fires of 80,000 ha have been

recorded (Lorimer 1977). Where terrain is more heterogeneous, either because of mountains or lakes, fire spread may be interrupted (Bergeron 1991;

Dansereau and Bergeron 1993; Bergeron et al. 1997). Average fire size in the

Great Lakes boreal forest is about 360 ha (Baker 1994), but the average is a

poor descriptor of the distribution. Heinselman’s (1973) fire maps of the

Boundary Waters Canoe Area in Minnesota show many fires that appear to

have been stopped at lake edges. In Western boreal forests, fires may be quite

large where few fire barriers are present (e.g., the Yellowstone Plateau) but

in many areas the boreal zone abuts rock, alpine vegetation, ridgetops, or

other barriers to limit fire size (Agee 1993).

Most fire studies have concentrated on disturbed areas, so that little is

known about residual vegetation around and within the fires that may

contribute substantial patchiness to the burn. Eberhart and Woodard’s

(1987) study of large fires in Alberta evaluated fires more than 20 ha in size

and found that the unburned island area, shape index, and edge index

increased with fire size (Table 3.3). Although the number of islands per 100

ha declined for the largest fires (E3), the unburned island area of this fire size

class was much larger than for the other fire size classes. These islands

covered less than 5% of the interior area of the fire. In interior Alaska, a 1985

fire had about 6% of its area in unburned islands (Paragi et al. 1997).

Unburned area may occur because of higher foliar moisture, terrain, or
55

Agee—Chapter 3

30

25

20

15

10

5

0 <100

Number

Quebec

N = 48

<1,000 <10,000 <100,000 >100,000

Fire Size (ha)

A.

30

25

20

15

10

5

0 <100

Labrador

N = 80

<1,000 <10,000 <100,000 >100,000

600

500

400

300

200

100

0 <100

Total Area of Fires

(Thousands of ha)

Quebec

N = 48

<1,000 <10,000 <100,000 >100,000

B.

600

500

400

300

200

100

0 <100

Labrador

N = 80

<1,000 <10,000 <100,000 >100,000

Fire Size (ha)

Figure 3.4—Typical patterns of frequencies of boreal fire sizes and area burned by fire

size. A. Size-frequency distributions of fires in Quebec and Labrador. B. Total area of fires

in each size class shown in A (from Hunter 1993).

Table 3.3—Mean values of percent disturbed area, median island area, number of islands per

100 ha, fire shape index, and edge index by fire size class for large fires in northern

Alberta, 1970-83 (Eberhart and Woodard 1987). No similar data are available south

of the Canadian border.

Fire size classa

Variable C D E1 E2 E3

% disturbed area 100.0 99.3 96.3 96.6 94.8

No. of islands/100 ha 0.0 0.38 0.96 0.87 0.39

Median island area (ha) — 2.29 2.50 2.59 9.39

Fire shape indexb 1.79 2.40 2.36 2.96 3.78

Edge indexb 2.17 3.29 3.48 5.11 7.47

a

 Fire size class: C = 20-40 ha; D = 41-200 ha; E1 = 201-400 ha; E2 = 401-2,000 ha; E3 = 2,001-20,000 ha. b Shape index is calculated as total exterior fire perimeter divided by the perimeter of a circle of equal area to the fire. Edge

index is similarly calculated but perimeters of all islands are added to the exterior fire perimeter.
Chapter 3—Agee

56

changes in fire weather such as a major wind shift. These unburned areas are

also known as stringers (Quirk and Sykes 1971) or fire skips (Hunter 1993).

In the boreal forests south of the Canadian border, little is known of the

distribution of residual patches. Because lynx may be able to den in small

patches of old growth, the presence of small fire skips may be critical for lynx

habitat. In British Columbia, DeLong (1998) showed for the “dry cool boreal”

and “moist very cold subalpine” forest types, transitional between taiga and

Western boreal forest, that 40-60% of the area burned is in patches greater

than 1,000 ha, and 60-85% in patches greater than 250 ha in size.

Fire Seasonality and Synergistic Effects—The major fire seasons vary

across the boreal forest. In Alaska taiga, May, June, and July are the major fire

months (Viereck 1983), with the latter part of June and early July the critical

time (Barney 1971). Throughout much of the rest of the boreal forest,

including the Western boreal forest, July and August are the months with the

largest area burned (Johnson and Wowchuck 1993). Some fires that begin

early in the season have the potential to burn into September, although most

do not (Johnson 1992; Despain 1990).

Synergistic disturbance effects are defined as increased probability of one

disturbance given the occurrence of another. A number of authors have

suggested that spruce budworm-killed balsam fir may increase fire hazard,

and refer to the Miramachi fire of 1825 in New Brunswick (Furyaev et al.

1983). Although most hurricanes lose strength before reaching the Northeastern boreal forest, these eastern seaboard hurricanes clearly create excessive fuel hazards from the creation of dead fuel from the windblown trees.

Lorimer (1977) suggests a large fire in 1803 in northern Maine was fueled by

a large blowdown that occurred within the previous decade. Surface fuels,

and therefore fire hazard, will accumulate any time there is canopy mortality, but the hazard may exist for a short window of time. In Western boreal

forest, Veblen et al. (1994) suggest that fires essentially “block out” spruce

beetles for many decades until the trees in the recovering stands reach a size

suitable for the beetles to attack. Conversely, Bergeron and Leduc (1998)

suggested that when fire return intervals lengthen, basal area loss due to

spruce budworm will increase because of the proportional increase in

budworm-susceptible balsam fir in these stands.

Other Natural Forest Disturbances

Forest Insects—The history of major insect outbreaks in the boreal forest

is more difficult to track than the history of forest fire. Insects may kill only

one species in a mixed stand, and they may remove either early successional

(pine beetle on pines) or late successional (budworms on firs) species. While
57

Agee—Chapter 3

fires usually thin a stand from below (kill smallest trees first, with the largest,

thickest barked trees left), insects often take the largest trees and thin the

stand from above. There are clearly some boreal forest areas where insects

have a significant history as a disturbance agent, primarily where fire return

intervals either are very long on average or an unusually long fire-free

period has occurred. In Alaska taiga, spruce beetles have killed substantial

white spruce (Werner and Holsten 1983). Spruce budworm appears to have

a major effect on white spruce in the southern taiga, reducing the importance

of spruce in late successional forests (Bergeron and Dubuc 1989). During the

1910-1920s outbreak, it is estimated that 40-50% of the total balsam fir

volume in eastern Canada was killed (Furyaev et al. 1983).

In the Northeastern boreal forest, spruce budworm has defoliated balsam

fir in outbreaks that have traced back over previous centuries (Blais 1968;

Lorimer 1977). The most recent outbreak has occurred from 1970 to the early

1980s (Kettela 1983). Once a local outbreak exceeds a certain size, it can

become self-propagating and spread much like a wildfire but more slowly

(Holling 1992). Occasional spruce beetle epidemics have caused considerable mortality in red spruce stands (Hopkins 1901). In 1985, the boreal forest

types of the northeastern United States had about 45% of the area in “light”

damage (less than 10% dead trees), 28% of the area in “moderate” damage

(11-30% dead trees), and 27% of the area in “heavy” (more than 30% dead

trees) damage classes (Miller-Weeks and Smoronk 1993).

Significant insects of Western boreal forests are those that attack lodgepole

pine (mountain pine beetle), Engelmann spruce (spruce beetle), and subalpine fir. While spruce budworm can become epidemic on lower elevation

firs (Douglas-fir, grand fir) in the West (Swetnam and Lynch 1993; Despain

1990), it is less important in the subalpine zone, although it does attack

subalpine fir and white spruce in the boreal zone (Van Sickle 1995). Lodgepole pine becomes more susceptible to mountain pine beetle as it ages, and

a beetle attack will allow understory spruce and fir to release ingrowth (Agee

1993; Veblen et al. 1994). Where recent beetle attack has occurred, surface

fuels will increase, but a fire is not necessarily guaranteed. Despain (1990)

suggests that the loss of crown fuels reduces crown fire risk at the same time

that surface fuels increase.

The spruce beetle attacks Engelmann spruce, and the additional surface

fuels from this mortality have been implicated in severe fires in riparian

zones (Agee 1998b). In Colorado, the return interval for spruce beetle is

estimated at 116 years (Veblen et al. 1994). Attacks were dated by analyzing

growth releases on firs and spruces too small to be attacked, indicating that

beetle attacks in mixed species stands are usually not stand-destroying

events like intense wildfires.
Chapter 3—Agee

58

The dynamics of insect outbreaks are very complex. Although we may

predict that older stands with target species of minimum size are more at risk

than younger stands, the triggers for outbreaks are not well understood. Pine

beetles often become epidemic during drought periods (Despain 1990), but

western spruce budworm often irrupts during periods of above-normal

precipitation (Swetnam and Lynch 1993).

Disease and Wind—Forest ecosystems are affected by a wide variety of

natural disturbances. We typically concentrate on the most important ones

for a given forest type, such as fire or insects. Diseases are often ignored

because they generally operate at long timeframes, and mortality may be

gradual or associated with crown dieback (Hawksworth and Shigo 1980).

Agents such as wind often remove the trees before they break or fall over

from stem or root rot. Windsnap and windthrow can be important disturbances (Coutts and Grace 1995), but severe events are often widely spaced

in time and not easily reconstructed. In boreal forests, wind as a disturbance

event is poorly understood. There is little evidence that windthrow is a

significant disturbance in the mature taiga.

In the Northeastern and Great Lakes boreal forest, wind can be a significant

disturbance, especially for those types that burn infrequently (Canham and

Loucks 1984; Seymour and Hunter 1992). Most frequently, small gaps are

created in the Great Lakes boreal forest, with an annual gap creation rate of

1% of the forest area per year (Runkle 1982; Mladenoff 1987). Although

catastrophic events may occur only once a millennium, these extreme events

can alter forest dynamics over wide areas. In July 1977, about 15,000 ha of

forest in eastern Minnesota and northern Wisconsin were devastated by a

windstorm (Loucks 1983). The historic (1834-1873 era) forest patch blowdown

size distribution in hemlock-hardwood forest of Wisconsin (excluding the

southern, mature forests of the state) ranged from 1 to 6,000 ha with a mean

size of 160 ha and median size of 30 ha (Loucks 1983). In these mature

hemlock-hardwood forests, wind may be a more significant disturbance

factor than fire (Canham and Loucks 1984). At least one large windthrow

event occurred in northern Maine early in the 19th century (Lorimer 1977),

but its effects were variable and localized. In New England, high-elevation

balsam fir forests have a wave-like pattern largely due to persistent effects

of wind on the forest (Sprugel 1976).

In the Western boreal forest, however, wind has profound physiological

effects across open areas. Severe winter winds can retard succession above

the winter snow line by abrading and desiccating foliage that emerges

(Hadley and Smith 1983). In contrast to this annual disturbance, less frequent

but powerful windstorms can result in large blowdown patches in western

boreal forests, occasionally greater than 5,000 ha (Knight 1994).
59

Agee—Chapter 3

Land Ownership and Land Use History

Land ownership patterns and the history of land use vary considerably

over the boreal forest, and particularly in the three areas of potential lynx

habitat south of the Canadian border. This affects not only the condition of the

land today but a variety of challenges in terms of future habitat management.

The Taiga—Much of the northern boreal forest habitat has been less

affected by modern human influence than boreal forests to the south

(Johnson et al. 1998). Low timber productivity, difficult access, and distance

from markets has kept much of the boreal forest from being logged in the

past, except around settlements. Fire suppression has been of limited effectiveness for the same reasons: values protected have been low, access for

firefighters and equipment is poor, and even fire-detection capability is

limited. The southern taiga has likely been affected more than the northerly

parts, but in general, less modern human influence is detectable in the taiga

than in the boreal forest types of the contiguous United States.

The Northeast Boreal Forest—European settlement in the Northeastern

forest began in the early 1600s, and white pine was selectively harvested

soon thereafter (Ferguson and Longwood 1960). Eastern hemlock was cut,

its bark stripped for tanning purposes, and the logs left behind. Spruce was

also selectively removed, and the pine and spruce harvest peaked in the

1850-1900 period (Ferguson and Longwood 1960). Pulp markets for hardwoods developed after 1900. The history of selective harvest for favored

species (Barrett 1962) to some extent mirrored the pattern of natural disturbances by insects (particularly spruce budworm and spruce beetle) and

wind. Stand-replacing harvests, like stand-replacing natural disturbances,

were not the most common event (Seymour and Hunter 1992).

Forest lands were also cleared for agriculture. Land clearing and farming

reached a peak in the mid-1800s. By 1880, forest covered only 27% of

Connecticut, 74% of Maine, 40% of Massachusetts, 50% of New Hampshire,

34% of Rhode Island, and 35% of Vermont (Barrett 1962). Since that time,

there has been a gradual increase in forest land in all of these states. Maine

is now 87% forested (Ferguson and Longwood 1960) and Vermont is now

70% forested (Klyza and Trombulak 1994), in various stages of succession.

The forest today is somewhat different in character than it once was.

Seymour and Hunter (1992) suggest at least three major differences. First,

there appears to be less old growth, and in this boreal forest type old growth

was more common than to the north because of extended natural disturbance intervals. Once-favored species such as eastern white pine and red

spruce are less common, and recent land-use practices such as clearcutting
Chapter 3—Agee

60

are imprinting a new landscape pattern. These land use practices are

symptomatic of concerns about the future of what is locally called the

“Northern Forest.”

The Northeastern forest area has the least amount of publicly owned forest

of the three boreal forest areas south of the Canadian border. In Maine, for

example, only 1-2% of the forest land is publicly owned, with 38% in forest

industry ownership and about 60% in non-industrial ownership (Ferguson

and Longwood 1960). The percentage of industrial forest ownership in

Maine is the highest of the Northeastern states. In the Northeast, timberland

area has continued to increase (about 9% since 1952), but ownership patterns

suggest that fragmentation is also occurring. In 1958, about 25% of the land

base of Maine was in ownerships less than 40 ha, 25% in ownerships of

40-20,000 ha, and 50% in ownerships greater than 20,000 ha. None of these

were necessarily contiguous blocks of land. Changes over the past 25 years

have resulted in further fragmentation of the ownership pattern (NRC 1998).

Today, almost 32% of forestland area nationally, and 36% in the New

England states exclusive of Maine (Brooks and Birch 1988), are in ownerships of less than 40 ha.

Recent concern has centered on changing forest industry ownership and

management (Reidel 1994; Seymour and Hunter 1992). Industrial forest land

began to be marketed for its development value in the 1980s, and the

northern states affected were concerned enough to form a Northern Forest

Lands Council (NFLC 1994). The intent was to stabilize the land ownership

and management patterns that had characterized the region for decades,

rather than to replace them with public ownership. Industrial forest management, particularly in Maine, was evolving to greater reliance on clearcuts, with a first pass providing landscape diversity and second one within

several years liquidating the remaining mature forest (Seymour and Hunter

1992).

The Great Lakes Forest—The Great Lakes area was the second major area

of the boreal forest south of Canada to be settled by Europeans. Land clearing

there relieved the pressure to farm the marginal lands of the Northeast

forest, and as deforestation occurred in the Great Lakes, it was coincident

with the process of reforestation in the Northeastern forest. Land settlement

first began in the southern portions of Michigan, Wisconsin, and Minnesota

and gradually moved northward (Barlowe 1983). Widespread, unregulated

cutting and indiscriminate slash burning and clearing was rampant during

the mid- to late-1800s. Some of the largest and most destructive forest fires

in the lower 48 states occurred during this time, including the Peshtigo

(Michigan, 1871) and Hinckley (Minnesota, 1884) fires.
61

Agee—Chapter 3

Early logging was focused on pine, with large quantities of northern whitecedar also harvested (Sandberg 1983). By 1920, other species became dominant in the timber economy, and many of the hardwood species began to be

utilized to produce charcoal. The charcoal industry was largely gone by 1930

and was replaced by a pulp industry with less exacting standards for size.

Much of the new forest that replaced the early logged forest was aspen, and

it remains a staple of the pulpwood industry. Jack pine and balsam fir are

also used for pulp. Much of the Great Lakes forest is in an early successional

state because of timber harvesting and farming over the past century

(Curtis 1959).

Substantial public ownership exists for the Great Lakes boreal forest.

National forests began to be reserved in 1908 (later than in the West), and

new national forests were created in the 1920s and 1930s. Lands added

between then and 1948 almost tripled the size of national forest ownership,

from about 800,000 ha to 2,500,000 ha (Barlowe 1983). National Park system

lands were added (Pictured Rocks and Sleeping Dunes National Lakeshores),

among the over 400,000 ha that has been added to public ownership since

World War II. The north-central region of the United States has the largest

absolute area, and greatest percentage, of State and County/Municipal

timberland in the country. This is primarily due to reversion of tax-delinquent land, almost 7,000,000 ha by 1950 (Barlowe 1951). In the eastern area

of the Great Lakes boreal forest, in northern Michigan, about 20-40% of the

land base is now publicly owned, and this percentage increases to about

40-60% in northern Wisconsin and more than 60% in northern Minnesota

(Barlowe 1983).

Continued fire suppression has allowed development of more complex

forest structure in previously farmed/logged areas but has also disrupted

the fire regime in unlogged areas. Baker (1989, 1994) suggests that restoration of the natural fire regime, where desired, will restore natural pattern

without additional restoration measures. Continuation of current suppression policies has significant implications for the boreal forest, discussed in

section “Successional Patterns After Disturbance” (Frelich and Reich 1995).

The Western Boreal Forest—The western boreal forest region has never

had the human-created forestland impact experienced by the other two

boreal forest regions south of the Canadian border. This region was the last

settled by Europeans in the expansion to the Pacific Coast, and development

and exploitation occurred around the fringe of these areas or along narrow

corridors passing through them. These areas were the focus of the first land

reservations for forest reserves, and today much of the National Park System

and National Wilderness System is centered on these western boreal forests.

The distribution of these boreal forests is patchier than in the other two
Chapter 3—Agee

62

boreal regions described in this chapter, so that land use in the intervening

lands can affect lynx migration, but the human history of land use that

changed area of forestland, disturbance patterns, and dominant tree species

is much less prevalent in the West than in the Great Lakes or the Northeast

boreal forest.

Mining was the first large-scale land use practice to affect the western

boreal forest, and it had significant impacts on a local scale. Where mining

occurred, not only was there surface soil disruption, but extensive humancaused forest fires were set to provide easier access to local timber for

firewood, mining timbers, etc. Larger scale timber harvest practices did not

begin until after World War II, and the boreal forest areas were cut only when

the more accessible lands were cutover. The carving of national parks from

the forest reserves, and later from national forests, preserved much of this

land from cutting, and the creation of the Wilderness Act in 1964 further

preserved much of the western boreal forest. Of all the western forest types,

it has the highest proportion of reserved land, largely because it is primarily

in public ownership and is the least productive timberland, making the landuse tradeoffs between preservation and extraction less controversial than for

other public lands. In the Western boreal forest zone, fire suppression has

been in effect for much of this century, but the long natural fire return

intervals (Table 3.2) suggest that removal of fire has not been as significant

as in the lower severity fire regimes of the West (Agee 1998b).

Successional Patterns After Disturbance

Across much of the range of the lynx in North America, a high severity fire

regime occurs, and succession follows a series of paths from early- to latesuccessional communities. Within a given forest type, many potential sequences may be possible: a function of fire duration and soil heating, species

composition at the time of the fire, post-fire climate, biotic interactions, and

other factors. The rate of succession will also vary depending on site

conditions. In this section, the common successional sequences in each of the

four major boreal forest divisions (taiga, Northeast, Great Lakes, and Western) are summarized.

After a stand replacement event, the post-fire sere will include a herbaceous stage, a shrub/sapling stage, a dense, small tree stage, a transition

stage (in many cases a hardwood to conifer transition, but in others just a

shift in conifer species), and a mature/old growth stage. Depending on the

fire return interval, the mature stage may never develop far before it is

disturbed. The timing of these stages will depend on the adaptations of the

species that will possibly grow on the site (Table 3.4). Where a tree or shrub
63

Agee—Chapter 3

Table 3.4—Responses of common tree species of the boreal forests to disturbance. The “Rowe Class” is a set of life

history characters associated with response to disturbance (Rowe 1983), and the specific adaptations are

listed for each of the species.

Rowe Thick Cone Light

Tree species classa bark serotiny Sprouter seeds

Black spruce Evader X

White spruce Avoider

Aspen Endurer, Invader X X

Paper birch Endurer, Invader X X

Balsam poplar Endurer, Invader X X

Jack pine Evader, Resister X

Red pine Resister X

Eastern white pine Resister X

Balsam fir Avoider

Red spruce Avoider

Lodgepole pine Evader X

Engelmann spruce Avoider

Subalpine fir Avoider

a

Invaders = highly dispersive pioneering species with short-lived disseminules

Evaders = species with long-lived propagules stored in soil or canopy

Resisters = shade-intolerant species whose adult stages can survive low-severity fires

Endurers = sprouting species with shallow or deep buried perennating buds

Avoiders = shade tolerant, late successional species that slowly reinvade burned areas

species is able to sprout or develop new plants from a soil or canopy seed

bank, succession is likely to progress more rapidly. Most of the species listed

in Table 3.4 are well-adapted to disturbance. A simple collation of the lifehistory strategies of the common species of a site will give an indication of

the likely rate of recovery. Where evaders and endurers are common, the

post-fire sere will likely begin with those same species. Where avoiders are

the norm, transformation to non-forest vegetation is likely until tree reestablishment is eventually successful, a function of seed source and post-fire

climate (Agee and Smith 1984).

Where the disturbance removes the overstory but leaves the understory

relatively intact, as in a typical blowdown, the successional sequence will be

similar but the species composition will be heavily weighted to the shadetolerant understory trees, either conifers or hardwoods, that were able to

persist in the shade of the overstory trees. Because of the high-severity fire

regime, the live trees on the site become snags and eventually logs as the

snags fall. In a typical post-fire sequence of this nature, there will be (1) a

large post-fire increase in coarse woody debris, (2) a mid-seral decline as the

initial input is over, existing coarse woody debris decays, and the new stand

is not yet large enough to produce more coarse woody debris, and then

(3) a slow increase in late succession as large trees occasionally die or are

killed by insect outbreaks (Harmon et al. 1986).
Chapter 3—Agee

64

The Taiga

The taiga has two major environmental gradients that affect species

composition and successional patterns. The first is a set of local gradients

from dry/warm to wet/cold, and the second is an east/west continental

gradient that affects both climate and the biogeography of species mixes. In

the Alaskan taiga, the local gradients create a complex mix of successional

pathways (Fig. 3.5A) (Viereck 1973; Lutz 1956; Rowe and Scotter 1973). One

of the common themes in taiga forest ecology is that the species mixes are

relatively stable, replacing themselves after disturbance, so the major successional stages are structural in nature. In most cases the disturbance

intervals by fire are short enough that the later successional sequences,

shown at the top of the diagram, are rarely reached. Tree colonization occurs

rapidly, but tree dominance may take 50+ yrs due to early dominance by

shrubs and generally low productivity.

In Alaska, Foote (1983) summarized the major stages on closed-forest

white spruce and black spruce sites. Many of the species are common to both

white and black spruce sites, although relative dominance will differ. On

white spruce sites, the newly burned stage lasts only a few weeks, and

sprouts of rose, highbush cranberry, and willow emerge, along with fireweed. Sprouts of aspen emerge as well, with seedlings of both aspen and

paper birch. White spruce is rarely present immediately after the fire. Within

one to five years post-fire, these plants expand cover and several species of

mosses dominate the ground layer at the site (up to 30% cover). Tall shrubs

and tree saplings dominate the tall shrub-sapling stage (three to 30 years

post-fire). The dense tree stage (26-45 years post-fire) is dominated by the

young trees that initially established, rose, highbush cranberry, mountaincranberry, and Labrador-tea. Lichens are best developed at this time, and

feathermosses are now established. Willows, herbs, and the seral mosses are

no longer important. The hardwood stage is a further development of the

hardwood tree layer, with similar understory shrubs to the dense tree stage

and Hylocomium splendens on the forest floor. As the hardwood trees die

(150+ years), white spruce, which has persisted (but rarely as a dominant),

becomes the dominant overstory species. It will persist until the next

disturbance.

On mesic black spruce sites, the initial patterns are similar (Foote 1983) but

bog blueberry and Labrador-tea are dominant shrubs in early succession,

and black spruce is present rather than white spruce. Black spruce may

average 18,000 stems ha–1, and quaking aspen 11,000 stems ha–1. Hardwood

dominance is usually less than on white spruce sites. In the tall shrub-sapling

stage, willows dominate at densities up to 15,000 stems ha–1, herbaceous
65

Agee—Chapter 3

Figure 3.5—Successional sequences in the (A) Alaska taiga and (B) eastern taiga

(Viereck 1973, 1983).
Chapter 3—Agee

66

species decline, and the tree layer continues to expand. The dense tree stage

(30-55 years post-fire) is dominated by trees, with low shrubs, feathermosses,

and lichens below. Black spruce density averages 2,500 stems ha–1. A mixed

hardwood-spruce stage occurs 56-90 years post-fire, but hardwoods usually

are not dominant. In the spruce stage (90 years post-fire +), a thick feathermossSpaghnum ground cover allows permafrost to increase from 80+ cm depth to

about 60 cm. Fire usually burns these sites before they reach 200 years old.

The first three successional stages (newly-burned, moss-herb, and tall

shrub-sapling) last about 20-25 years on white spruce sites and 30-35 years

on black spruce sites. The hardwood stage is better defined and lasts longer

on white spruce sites. Vegetative and in situ seed (such as serotinous cones)

is greater on black spruce sites (Black and Bliss 1978; Foote 1983). Succession

on lichen-woodland sites is similar to the closed-forest black spruce, except

that crown closure rarely occurs and the sequence of stages is usually

prolonged (130+ years for mature woodland [Maikawa and Kershaw 1976]).

In the central and eastern taiga, a similar set of successional sequences is

postulated (Fig. 3.5B) (Viereck 1983). Balsam poplar, although present, is less

a component of the sere, jack pine is added, and balsam fir appears where fire

return intervals are longer. To the north, jack pine is the first species to

disappear, followed by balsam poplar, eastern larch, and black spruce

(Payette et al. 1989), a pattern supported by the rooting depth of the species

and shallower permafrost (Larsen 1980). Balsam fir and white spruce are the

late successional species on mesic sites, while succession toward black

spruce is the trend on more xeric sites (Bergeron and Dubuc 1989). A majority

of the post-fire seedlings become established in a three- to 10-year period

(Lavoie and Sirois 1998). On the xeric sites, low productivity and the

presence of species like red pine, jack pine, or white pine can result in multiaged stands, although this appears to be most common in the transitional

mixed northern forest (Heinselman 1981). On more mesic sites without these

pines, quaking aspen and paper birch are common early successional species

(Bergeron and Dubuc 1989) after stand-replacing disturbances, particularly

if the fire exposes substantial areas of bare ground (Payette 1992). The

succession of black spruce stands to balsam fir occurs in some stands

(Dammon 1964) but does not appear to happen on other sites (Carleton and

Maycock 1978).

Coarse woody debris trends differ between white and black spruce stands.

Black spruce sites are poor, and large stems will never be found on these sites.

In Alaska, the average diameter at breast height for 51-year-old upland and

lowland stands was 2-3 cm, and there were no logs greater than 5 cm

diameter on the forest floor (Barney and Van Cleve 1973). If these stands

burned, there would be almost no snags or logs created that would be more
67

Agee—Chapter 3

than 5 cm. More productive black spruce sites of greater age (130 years old)

had five to 10 times the mass of live stem wood (Van Cleve 1981) that would

become coarse woody debris if the site burned. By 25 years post-fire, all snags

had been converted to logs in a black spruce stand (Paragi et al. 1997). In

white spruce stands, the same post-fire increase will be seen, but generally

more significant. Coarse woody debris cover in black spruce sites ranged

from 2 to 6% compared to 5 to 16% for a white spruce sere (Foote 1983).

Because more of the coarse woody debris in white spruce stands will be

hardwoods, decay rates are more rapid for coarse woody debris in white

spruce stands (Harmon et al. 1986).

Northeastern and Great Lakes Boreal Forests

Successional sequences after disturbance in the Northeastern and Great

Lakes boreal forests represent a mix of species common to the deciduous

forest and boreal biomes and a mix of disturbances common to both.

Therefore, the successional dynamics are covered together here. As noted

earlier, fire tends to be more important in the Great Lakes boreal forest than

the Northeastern boreal forest. In the Great Lakes, windthrow and insects

may become locally as important as fire, creating a complex series of

successional pathways (Fig. 3.6) (Pastor and Mladenoff 1992). In the Northeastern boreal forest, longer fire return intervals (Lorimer 1977) and higher

frequencies of insect outbreak (spruce budworm) and wind (Seymour 1992)

resulted in many disturbances that were less than stand-replacing in severity. The Northeastern forest, also called the Acadian forest, had greater

potential diversity and age structure as a result (Seymour and Hunter 1992).

Boreal conifers are more frequent on cooler sites or at the extremes of the

moisture gradient (Larsen 1980), while northern hardwoods follow the early

successional species on more mesic and warmer sites (Maycock and Curtis

1960). Like the more northerly boreal forest, tree establishment on stand

replacement burns is rapid. The hardwoods sprout, some like paper birch

have light seeds that disperse widely, and jack pine reproduces from a seed

bank in serotinous cones. On poorly drained sites, black spruce reproduces

from semi-serotinous cones that retain at least part of the seed production.

Jack pine is a common dominant on drier sites where morainal, coarsetextured soils predominate (Conkey et al. 1995). After fire, jack pine and

quaking aspen form dense stands. In the 5-15 year period, jack pine may

reach 10,000-30,000 stems ha–1, with 500-13,000 stems ha–1 of aspen (Roe and

Stoeckler 1950; Cayford and McRae 1983; Agee 1998a). At 40+ years, the

pine-aspen overstory has a black spruce, balsam fir, and shade tolerant

hardwood understory (sugar maple and paper birch). By age 75, the overstory begins a decline, with subsequent release of the understory species,
Chapter 3—Agee

68

Beaver

Fire after

windthrow

Faster decomposition:

Higher N availability

1. Faster decomposition: Higher N availability, lower fuel loads

2. Greater soil water capacity

3. Warmer temperatures

Windthrow

Northern

Hardwoods

Shrubs

Spruce

Budworm

Jack Pine

Fire w/ residual

seed source Fire w/o residual

seed source

Spruce-Fir

Aspen-Birch

Saplings

Moose,

Snowshoe

hare

Birch

Mature

Aspen-Birch

Figure 3.6—Multiple successional sequences in the Great Lakes boreal forest (Pastor

and Mladenoff 1992).

and by age 165, the jack pine and aspen are largely replaced by a multistoried black spruce-balsam fir-hardwood forest, unless an intervening fire

creates another even-aged pine-aspen stand. Heinselman (1973) projected

that spruce would become more dominant over time but found remnant jack

pines to live more than 200 yrs. Mixed pine stands (red pine, eastern white

pine, jack pine) are often indicative of the limited boreal forest area in a

moderate-severity fire regime. These sites will commonly have fire-scarred

pines and represent a succession of multi-aged stands on poor sites. Where

the fire thins few trees, more shade-tolerant species will regenerate, while

hotter fires that kill more trees may create another age class of shadeintolerant pines.

Fire suppression in the Great Lakes area has changed the dominant

successional pathways (Frelich and Reich 1995). Many stands are undergoing a transition from even-aged stands of catastrophic origin to uneven-aged

stands due to small scale openings. Jack or red pine or aspen stands are

moving toward an old-growth mix of black spruce, balsam fir, paper birch,

and white cedar, in patches of 10-30 m created by wind, insects, and disease

(Frelich and Reich 1995). At scales of 1-16 ha, succession leads to a convergence on a mixture of species. It is not clear whether reintroduction of
69

Agee—Chapter 3

catastrophic disturbance will lead back to the original landscape character of

this region. In the heavily altered landscapes at the southern edge of the

boreal forest, the historic landscape character is probably permanently

altered. Second-growth forest landscapes caused by harvest have generally

smaller forest patches and are significantly simpler in shape; important

ecosystem juxtapositions (such as old-growth hemlock adjacent to lowland

conifers) have been largely eliminated (Mladenoff et al. 1993).

While the jack pine type is of interest to fire ecologists, many of the forests

of the Great Lakes and Northeastern boreal forest burn less frequently. On

mesic sites, with longer fire intervals (Table 3.2), hardwoods typically

occupy a more important niche, and as the conifer component decreases, so

does the flammability of the forest (Van Wagner 1983). Other disturbances

such as wind (Pastor and Mladenoff 1992) or insects (Baskerville 1975)

become more important disturbance agents. Replacement of resinous, multiyear evergreen foliage with deciduous foliage that maintains a higher

average foliar moisture content reduces the probability of intense fire. Seed

source for jack pine may be gone by the time a site burns. In Maine, a search

of old records showed pine to be a minor component of the forest in most

areas (Lorimer 1977). In these areas, aspen and birch tend to be the dominant

early successional species. White and gray birch composed >70% of early

successional (younger than 25-year-old) stands, at densities of 1,500-7,600

stems ha–1 (Lorimer 1977). Wet sites tend to be dominated by black spruce

and eastern larch boreal species. Successional trends tend to follow those of

the more classical boreal forest (Damman 1964).

Coarse woody debris loads are significantly greater in the Great Lakes and

Northeastern boreal forest than the taiga, due to higher productivity, longer

disturbance intervals, and minor disturbances such as gap-creating wind

events that periodically replenish the log supply. Unburned stands up to 250

years old had bole mass of 190 to 344 t ha–1 (Gordon 1981), while young jack

pine stands (younger than 60 years old) had less than 20 t ha–1 of stem

biomass (Green and Grigal 1979). Young balsam fir stands from 12 to 52 years

old had coarse woody debris mass decreasing from 35 to 13 t ha–1 (Lambert

et al. 1980). Snag biomass decreased from 27 to 0.25 t ha–1 over the same

sequence.

Western Boreal Forests

The Western boreal forests within the range of the lynx are dominated by

three tree species: lodgepole pine, Engelmann spruce, and subalpine fir. Like

the remainder of the forests with boreal features, these ecosystems are

subjected to disturbance by fire on a periodic basis. Yet there are numerous

characteristics of the subalpine forests that distinguish them from their more
Chapter 3—Agee

70

northerly boreal neighbors: longer intervals between major disturbances

(Table 3.2); species that are less fire-adapted (Table 3.4), implying a longer

post-fire recovery period; absence of a tall shrub component following

disturbance, except where aspen is present; and more post-fire coarse

woody debris.

Many of the forest types below the boreal zone in western forests have

more frequent disturbance by fire than the boreal zone (Agee 1993) and

contain the serotinous-coned lodgepole pine allowing dense, young lodgepole stands to develop after severe fire. However, these stands have occasional lower intensity fires or more representation of fire-tolerant species

more typical of lower elevations (western larch and Douglas-fir). These

species may be representative of a moderate-severity fire regime (Agee

1993), and multiple age classes may occur in these stands (Arno 1976; Arno

1980; Arno et al. 1993). Where residual density is high, post-fire regeneration

is likely to be sparse and dominated by shade-tolerant species. Where

residuals are absent, the dense lodgepole pine stands common to higher

elevations will be found in a mosaic with the residual-dominated stands.

Across the range of western boreal forests, many fire return intervals are

long enough that relatively short-lived lodgepole pine may be removed

from the stands by mountain pine beetles before another fire event occurs.

In such cases, the old-growth dominants Engelmann spruce and subalpine

fir may compose the dominant tree component, but when burned, the spruce

and fir are killed and the species do not quickly re-establish. The seeds of

both species are large, so they are not easily dispersed by wind, and they do

not easily establish on freshly burned sites. Tree colonization may take

decades to centuries (Stahelin 1943, Agee 1993), although occasionally

spruce or fir will immediately regenerate (Loope and Gruell 1973; Habeck

and Mutch 1973; Doyle et al. 1998). During the interim period, vegetation

cover is a herbaceous-low shrub meadow (Stahelin 1943). Near timberline

the trees may return in a “ribbon forest” pattern (Billings 1969), where linear

strips of forest are interspersed with meadow as a result of snow accumulation patterns.

Seventeen years after the Waterfalls Canyon fire in Wyoming, sedges

provided the most vegetative cover, with total shrub cover at 4-6% and a

seedling-sapling density of 2,000-5,000 ha–1, dominated by Engelmann

spruce (Doyle et al. 1998). On the Yellowstone Plateau, on the less productive

end of the western subalpine forest productivity gradient, Romme (1982)

simulated forest succession after fire in two plant associations (Table 3.5) and

estimated the longevity of each stage as a function of plant association,

restocking rate, and lodgepole pine mortality from bark beetles. The immature pine stage (closed canopy) in all cases began at a minimum age of 40

years post-fire.
71

Agee—Chapter 3

Table 3.5—Postfire successional stages (years) in the Yellowstone Plateau area of northwestern Wyoming (adapted from

Romme 1982).

Lodgepole pine/sedge Subalpine fir/huckleberry

Early Late Early Late

pine pine pine Pine

Successional “Typical” Slow canopy canopy “Typical” canopy canopy

stage stands restocking mortality mortality stands mortality mortality

Herbaceous 0-20 0-40 0-20 0-20 0-20 0-20 0-20

Seedling-sapling 20-40 40-80 20-40 20-40 20-40 20-40 20-40

Immature pine 40-150 80-200 40-150 40-150 40-150 40-150 40-150

Mature pine 150-200 200-250 150-170 150-300 150-300 150-180 150-350

Transitional 200-300 250-350 170-240 300-400 300-400 180-280 350-450

Climax foresta 300+ 350+ 240+ 400+ 400+ 280+ 450+

a

Climax forest is defined as the potential vegetation on the sites. For the lodgepole pine/sedge plant association (infertile sites) it is lodgepole pine, and for the subalpine

fir/huckleberry plant association it is subalpine fir and Engelmann spruce.

Where wind is the disturbance agent, or bark beetles remove an overstory

of lodgepole pine or whitebark pine, Engelmann spruce and/or subalpine

fir, released from the understory, are likely to be the post-disturbance

dominants (Morgan and Bunting 1990; Agee 1993). They may or may not

develop as dense stands of small (and usually not young) conifers.

Coarse woody debris in western subalpine forests follows a U-shaped

trend after stand-replacing disturbances, with snags and logs most common

in the young stands, declining to a low in mid-succession (Clark et al. 1998).

Not all the pre-fire log biomass is consumed, and post-fire log biomass is fed

by the fall of snags created by the fire. Unburned spruce-fir forests in

Colorado had 120-135 t ha–1 of stem mass (Landis and Mogren 1975) that

would become coarse woody debris if the stand burned. On old-growth

spruce-fir sites, where lodgepole pine mortality adds a new cohort of coarse

woody debris, log biomass may exceed 100 t ha–1 (Brown and See 1981), and

much of that will remain after fire passes through the stand. In these

environments, decay is slow, so that 50-100 years after the fire, some snags

and many logs still reflect the fire evidence (Agee and Smith 1984). During

the successional stages, there is clearly a substantial mass of coarse woody

debris on site (Huff et al. 1989).

Landscape Management Implications

The natural landscapes of the boreal forest within which the lynx has

successfully existed have been profoundly affected by disturbance, primarily by fire. Although most of the lynx range is included in the high-severity

fire regime, there is considerable range in the frequency with which fire

occurred on these landscapes, and because of that a wide variation in
Chapter 3—Agee

72

successional stages present. Further variation has occurred due to local site

conditions, intensity and duration of the fire, forest age at the time of fire, and

post-fire climate. Mimicking this pattern of natural disturbance has been

suggested as a way to maintain biodiversity in managed forests (Hunter

1990; Bunnell 1995).

For the boreal forest, there are several general principles that must be

addressed in landscape management plans if harvesting or fire disturbance

is to be incorporated:

1. The habitat will be a product of the cumulative effect of all disturbances.

The substitution of logging for fire, for example, is only meaningful if fire can

be successfully removed from the environment, and even then, logging will

not totally mimic fire as a disturbance process because of roading and coarse

woody debris differences.

2. Typical models used for fire history studies suggest that fire selected a

range of stand ages to burn. Harvesting only the oldest ages will decrease the

average stand age of the landscape and will remove the complex boreal

stand structure that may be critical for lynx denning. Young and old stands

need to be part of any landscape disturbance plan.

3. Size and juxtaposition of stands is critical. Most fires are small. Most of

the landscape, however, is affected by larger fire patches, with unburned

areas inside the fire perimeter (stringers, islands, fire skips).

There are a range of prescriptions for lynx or lynx habitat that have quite

different implications for management. Koehler and Aubry (1994), addressing the “southern latitude” habitat (equivalent to Western boreal forest),

suggest that although approximating the natural disturbance frequency and

spatial patterns will provide the best habitat for lynx, large openings (greater

than 100 m across) may create barriers to lynx movement and travel

corridors are needed for cover for lynx. Typical spatial patterns of historic

fires in this type suggest much larger patches were the norm in boreal forests

and that there are no guaranteed “travel corridors” or connectivity between

fire patches or among unburned islands within fires. The discrepancies

within Koehler and Aubry’s (1994) recommendations probably represent

the difference between what is “natural” and what may be optimum for one

species that occupies this natural environment. An example of problems

caused by openings smaller than the natural scale is discussed by Hunter

(1993). Small openings by cutting in boreal forest were ideal for moose but

less so for caribou; wolf populations increased and thereby depressed

caribou populations, a result of creating openings smaller than what historic

fires had done.
73

Agee—Chapter 3

Summary

It is clear that boreal forests, in addition to covering a wide geographic

area, contain many unusual combinations of species and disturbance regimes. Few generalizations beyond broad climatic conditions apply over the

large geographic range of boreal forests. Fire has been the primary natural

disturbance in boreal forests, although its influence decreases in the eastern

boreal region. Stand replacement disturbances are common and are often

large with few islands. Across much of the boreal forest, insects and other

disturbances generate small scale heterogeneity, although spruce budworm

can create widespread epidemic mortality in the eastern boreal forest region.

Fire disturbances tend to fit stochastic models well, although the specific

parameters of the models may be difficult to fit. These models suggest that

large proportions of young forest were characteristic of the boreal region but

that fair amounts of quite old forest were part of the mosaic as well. These

natural landscapes diverged significantly from even-aged silvicultural systems: fewer roads, more coarse woody debris, older age structures, and

complex juxtaposition of different-aged stands. Post-fire successional sequences are very different in the taiga, eastern, midwest, and western forest

types, particularly in the proportion of deciduous vegetation.

Ecology is a science of place, and scientific recommendations for lynx will

have to take the natural and cultural features and history of each boreal

subregion into account.

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83

Chapter 4

Habitat Fragmentation

and Interspecific

Competition: Implications

for Lynx Conservation

Steven W. Buskirk, Department of Zoology and Physiology,

University of Wyoming, P.O. Box 3166, Laramie, WY 82071

Leonard F. Ruggiero, Rocky Mountain Research Station,

800 E. Beckwith, P.O. Box 8089, Missoula, MT 59807

Charles J. Krebs, Department of Zoology, University of British Columbia,

6270 University Blvd., Vancouver, BC V6T 1Z4 Canada

Abstract—Habitat fragmentation and interspecific competition are two important

forces that potentially affect lynx populations. Fragmentation operates by various

mechanisms, including direct habitat loss, vehicle collisions and behavioral disturbance from roads, and changes in landscape features such as edges. Competition

takes two forms: Exploitation competition involves potential competitors, such as

coyotes and raptors, for food with lynx. Interference competition involves aggressive acts, almost always by a larger animal, that can include attacking and killing.

Habitat fragmentation tends to facilitate competition by generalist predators, of

which the most likely beneficiary is the coyote. Other potential interference

competitors with lynx include cougars and bobcats. Of these three carnivores, all

are more widespread and more abundant within the southern distribution of the

lynx than 50 years ago.
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Chapter 4—Buskirk

Introduction

Fragmentation (Dayan et al. 1989) and competition (Rosenzweig 1966) are

major forces shaping the evolution, composition, and function of carnivore

communities (“carnivorans” is a more precise term referring to members of

the Order Carnivora; we use “carnivoran” and “carnivore” synonymously).

In human-dominated landscapes, fragmentation and competition are strongly

linked because vegetation mosaics in landscapes provide high quality

environments for generalist species such as the coyote and great-horned owl

(Goodrich and Buskirk 1995). Under such conditions, generalist predators

are favored over habitat specialists such as the spotted owl and American

marten. As humans change the patterns of natural landscapes through

timber harvest, construction of roads and buildings, and conversion of land

to other uses, ecological processes such as competition, dispersal, and

predation are affected in various ways (Wilcove 1985). Although many of

these effects are poorly understood, it is clear that the structure and function

of animal communities can be dramatically altered (Wilcove et al. 1986;

Yahner 1988; Oehler and Litvaitis 1996). Here, we discuss how interspecific

competition affects carnivores in general, how habitat fragmentation may

mediate this process, and how lynx populations in particular may be

affected.

Habitat Fragmentation

The term “fragmentation” is used widely to describe human alterations of

natural landscapes (Knight et al., in press). Lord and Norton (1990) defined

this process as the disruption of continuity, especially as it relates to

ecosystem processes. Forman (1995) discussed how fragmentation affects

the area, size, shape, and configuration of landscape elements, in an overall

process of land transformation that has major implications for conservation

(Lord and Norton 1990; Wilcove et al. 1986). Fragmentation has been

variously defined to describe a reduction of total area, increased isolation of

patches, and reduced connectedness among patches of natural vegetation

(Rolstad 1991). Fragmentation tends to reduce habitat area and to isolate

patches of native vegetation (especially in late seral stages) from each other,

both of which can lead to local species extirpations (Wilcox 1980; Wilcox and

Murphy 1985). Moreover, the loss of some species in this way can lead to

multiple extinctions through community-level secondary effects (Wilcox

and Murphy 1985).

Fragmentation has been applied to both natural (Andrén 1994) and humancaused alterations of landscape patterns. Here, we use the term “patchiness”
85

Buskirk—Chapter 4

when referring to natural processes (Buskirk et al., in press) and “fragmentation” to anthropogenic disruption of natural patterns and the secondary

effects of such disruption (e.g., behavioral disturbance to wildlife), and the

effects of cars, pets, garbage, and other human accoutrements (Buskirk et al.,

in press).

Although appropriate to any landscape, fragmentation has been preferentially applied to forests (Simberloff 1994; Lehmkuhl and Ruggiero 1991;

Harris 1984). In this context, some have argued that the negative effects of

forest fragmentation are ameliorated in areas like the Rocky Mountains

because of naturally patchy landscapes. This contention is unlikely to be true

given that, by definition, fragmentation disrupts the natural landscape

pattern regardless of the scale of the undisturbed pattern. That is, fragmentation is not scale-limited (Lord and Norton 1990). Moreover, natural landscape pattern is a complex function of topography with its associated (e.g.,

edaphic, microclimatic) gradients and natural disturbance processes, the

most important of which is fire. Clearly, the kinds, amounts, and arrangements of forested environments differ markedly between natural and

anthropogenic disturbances (Harris 1984; Ruggiero et al. 1991).

Fragmentation has been shown to affect a fairly wide range of birds and

mammals (reviewed by Harris 1984, Bright 1993, Andrén 1994, and Oehler

and Litvaitis 1996). This is not surprising, considering the wide range of

mechanisms whereby vertebrates can be impacted—for example, loss of area,

isolation of patches, vehicle collisions, increased predation by edge-preferring

predators, changes in boundary conditions including altered moisture regimes near stand edges, and changes in the habitat matrix or context within

which undisturbed habitats exist. Several of these mechanisms can mediate

competitive relationships by permitting generalist predators such as coyotes

access to landscapes occupied by specialist species that are ecologically

separated in natural landscapes (Hunter 1990). Moreover, our considerable understanding of ecological systems and mechanisms of competition

provides a plausible basis for believing habitat-mediated competition is an

important factor in population persistence. Finally, as clearly stated by

Wilcox and Murphy (1985:884), “That current ecological theory is inadequate for resolving many of the details should not detract from what is

obvious and accepted by most ecologists: habitat fragmentation is the most

serious threat to biological diversity and is the primary cause of the present

extinction crisis.”

Direct habitat effects of fragmentation of most concern in lynx conservation are (1) reduction of area and patch size of late-successional forest and

of optimal snowshoe hare habitat; (2) creation of openings that facilitate

access by potentially competing carnivores; (3) increased densities of edges
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Chapter 4—Buskirk

between early successional and other forest types; and (4) changes in the

amounts and structural complexity of seral forest stands within landscapes.

Although landscape-level studies have not determined how fragmentation

affects lynx ecology and population persistence (Koehler and Aubry 1994),

rare species associated with wilderness, such as the lynx, generally are

considered most susceptible to fragmentation (Bright 1993). Likewise,

habitat specialists with large individual spatial needs, including the lynx

(Quinn and Parker 1987; O’Donoghue et al. 1998), are likely to be impacted

by habitat fragmentation (Andrén 1994). This is so because generalist

predators tend to dominate the predator guild in fragmented landscapes

(Oehler and Litvaitis 1996).

Competition

Keddy (1989:2) defined competition as “the negative effects which one

organism has upon another by consuming, or controlling access to, a

resource that is limited in availability.” Two qualitatively different kinds of

interspecific competition can be illustrated by examples involving the lynx

(Fig. 4.1).

Exploitation (resource) competition (Litvaitis 1992) occurs when other

species, such as the northern goshawk, bobcat, or coyote, use resources that

limit the fitness of a lynx. Thus, if northern goshawks exploit snowshoe hares

in an area so thoroughly that lynx die sooner (from starvation or while

dispersing to a new place), breed less (from females failing to mate or give

birth), or produce smaller litters of kittens than they would otherwise, we say

that northern goshawks competed (exploitatively) with lynx. Although the

competition might have been reciprocal, that issue is academic from our

perspective here.

Interference competition (Case and Gilpin 1974) occurs when one species

acts aggressively toward another, denying it access to a resource (Fig. 4.1).

For example, if a cougar were to chase a lynx away from a hare carcass, or kill

one of its kittens, or scent mark an area so that lynx were deterred from

foraging there, this would constitute interference competition. Exploitation

competition is not particularly affected by the relative body sizes of the

participants, as in the hypothetical example of the smaller goshawk and the

larger-bodied lynx. Interference competition, by contrast, is almost invariably inflicted by a larger carnivore on a smaller one (Fig. 4.2). Further, the

likelihood of interference competition among carnivores seems to be greatest when two species are similar in body form and size (Buskirk in press);

for example, wolves are more likely to exert interference competition on

coyotes than on red foxes (similar shape but different size: Johnson and

Sargeant 1977) or on badgers (different shape).
87

Buskirk—Chapter 4

Vegetation

Prey

Lynx Competitors

Trophic level

Herbivory

Interference

competitionExploitation

competition

Direct habitat

associations

Direct habitat

associations

Exploitation

competition

Body weight (kg)

1

10

100

Wolf

Coyote

Red fox

Lynx

Cougar

Bobcat

Arctic fox

Brown bear

Black bear

Marten

Fisher

Weasels

Figure 4.1—Competitive, trophic, and habitat relationships involving lynx.

Interference competition, when it involves killing, can include ingestion. Direct

habitat associations refer to needs of animals and constraints imposed by

physical structure such as live vegetation, coarse woody debris, and snow.

Figure 4.2—Interference competitive interactions among North American carnivores. Arrows

point from dominant to subordinate participant and in all cases point downward on the bodyweight axis. Interactions are documented in Litvaitis (1992), Buskirk (1999), and this chapter.
88

Chapter 4—Buskirk

Interference competition appears to be capable of influencing carnivore

populations to remarkable degrees. Although exploitation competition can

reduce prey abundance and thus cause predators to become rare (the

numerical response: Taylor 1984), interference competition can drive them

to local or regional extinction. For example, Ashbrook and Walker (1925)

described how one red fox eradicated all (at least six) of the arctic foxes on

Chowiet Island, Alaska (56° 2' N., 156° 40' W., 0.8 km2

 in area) in less than

three years. Similarly, wolves on Isle Royale, Michigan (Krefting 1969) and

the Kenai Peninsula, Alaska (Thurber et al. 1992) have been credited with

eradicating coyotes upon arrival in the former area and with preventing

their sympatry before the extinction of wolves of the latter area. The

potentially high importance of interference competition, compared with

exploitation competition, is surprising unless one considers the prey-switching ability that is a common adaptation of carnivores (Taylor 1984). Alternate

prey can allow carnivores to persist when preferred prey are scarce, but an

effective interference competitor can pursue its enemy to scarcity or extinction. Thus, interference competition and prey availability are both critically

important issues in the distribution and abundance of mesocarnivores,

including the lynx.

The effects of fragmentation on predator-prey interactions (and thus

perhaps interference competition) depend on the specific behaviors of the

species in question (Kareiva 1987) and its environment. Thus, predation and

competition are highly context-specific phenomena. Various biotic and

abiotic factors can mediate competitive interactions (direct habitat associations, Fig. 4.1), so that a dominant competitor in one setting coexists or is

subordinate in another (Sargeant et al. 1987). Many such mediated relationships have been reported. In carnivores, for example, Paquet (1991) reported

that coyotes did not avoid wolves during winter, and Gese et al. (1996)

concluded that coyotes tolerated red foxes in Yellowstone National Park

during a high prey year, but not at other times. A strong abiotic affect on

interactions between another pair of forest-dwelling carnivores, the marten

and fisher, has been described by Krohn et al. (1995). Martens, with their

proportionally larger feet, can travel in deeper, softer snow than can fishers,

and martens predominate in parts of Maine with deep soft snow. But, fishers

are competitively (interference) dominant over martens, and therefore are

the more common species where snow is shallow or crusted.

We summarize possible relationships between lynx and potential competitors in Table 4.1 and Figure 4.2. As discussed earlier, direct evidence of

competition is very difficult to collect and therefore scarce. The fact that there

have been very few intensive studies of lynx in the United States contributes

to the lack of empirical information. In some cases, exploitation of a common
89

Buskirk—Chapter 4

prey species (e.g., snowshoe hares) and numerical (great-horned owl -

Rohner and Krebs 1996, 1998) or functional (red-tailed hawk - Adamcik et al.

1979) responses to increasing hare abundance serves to indicate potentially

important competitive relationships. For predators such as the great-horned

owl, a functional response to hare abundance could lead to owl predation on

lynx kittens, although this has not been reported (C. Rohner, personal

communication). Thus, functional responses to increased prey abundance

may have the primary effect of increased exploitation competition and a

secondary or indirect effect of increased interference competition.

Competition With Cougars

Interference competition between cougars and bobcats was reported by

Koehler and Hornocker (1991), who found that cougars killed bobcats when

both species were forced to lower elevations in winter. Squires and Lorean

(Chapter 11) document two lynx killed by cougars in western Montana

during fall and early winter. Based on these observations and because

cougars are larger than lynx and have become more abundant in the western

United States in recent years (Green 1991), cougars may be significant

interference competitors with lynx. Deep snow, however, is a hindrance to

cougar movements (Fig. 4.3), and should spatially separate lynx and cougars

under normal winter conditions. Strong demographic consequences of

interference have been reported for another pair of felids, the cheetah and

African lion. Caro and Laurenson (1994) reported that lions killed entire

cheetah litters, contributing to a survival rate at age two months of 29%.

Such killing of litters has not been reported for lynx. Other carnivores,

Table 4.1—Possible competitive impacts to lynx, mediating factors, and our evaluation of the

likely importance of the causes in the decline of lynx in the contiguous United States.

Possible impact Potential competitors Likely importance

Exploitation (food)Birds of prey Minimal impact

(goshawk and great-horned owl)

Coyote Locally or regionally important

Wolf Minimal impact

Cougar Minimal impact

Interference Coyote Possible

Bobcat Possible where bobcats occupy

high-elevation habitats

Wolverine Documented, but likely rare

Cougar Likely in summer or where lynx

venture out of deep snow areas
90

Chapter 4—Buskirk

including wolverines and feral dogs (reviewed by McCord and Cordoza

1982 and Quinn and Parker 1987), occasionally kill or take food from lynx.

Competition With Bobcats

Bobcats attain larger body size than lynx (Hall 1981) and may be larger

than sympatric lynx in some areas. Among a small sample of sympatric

bobcats and lynx in western Wyoming, the largest male bobcat was 2-4 kg

larger than the largest male lynx (T. Lorean, personal communication). Such

a body-size difference would set the stage for interference competition

dominated by bobcats. Further, the diets of both species (reviewed by Rolley

1987 and Quinn and Parker 1987) tend to be dominated by leporids, creating

the potential for exploitation competition. Where bobcats attain high densities and body sizes larger than those of sympatric lynx, competitive impacts

upon lynx should be suspected. Although bobcats and lynx are generally

thought to be ecologically separated by deep snow, interactions between

0

100

200

300

400

500

600

700

800

900

1,000

Hare

Redsquirrel

Marten

Fisher

Lynx

Redfox

Wolverine

Bobcat

Coyote

Wolf

Cougar

Loading (g/cm )2 Figure 4.3—Foot loadings of North American mammals important as prey and

community associates of Canada lynx. Weights were taken from Chapman and

Feldhamer (1982) and Silva and Downing (1995). Foot surface areas were

estimated for the larger foot of each species by first enlarging the drawings of tracks

in snow depicted in Forrest (1988) so that their length was the mid-range reported

by Forrest (1988). The area of the track (cm2) was then measured by digital

planimetry (Tamaya Digital Planimeter). Foot loading is an approximation of the

pressure exerted by the animal walking on snow, and therefore its sinking depth.

High sinking depth suggests that, other factors being equal, an animal exerts more

energy to traverse snow while walking. The snowshoe hare has the lowest foot

loading of any mammal considered, the cougar the highest.
91

Buskirk—Chapter 4

these two species under other conditions are poorly understood. For example, in Montana, Smith (1984) reported that bobcat home ranges during

winter were located at significantly lower elevations than were lynx home

ranges, but that this difference disappeared during spring and autumn.

Similarly, in western Maine, Major (1983) found that snowshoe hares ranked

first or second in frequency of occurrence in bobcat diets during all seasons

over a three-year period. Toweill (1986) found that bobcats in the western

Oregon Cascades ate snowshoe hares regularly. These findings indicate that

bobcats may be significant competitors with lynx under some conditions.

That lynx can be excluded by bobcats is suggested by Parker et al. (1983), who

believed that bobcats, recent immigrants to Cape Breton Island, caused the

displacement of lynx from low areas. These accounts suggest the potentially

important influence of bobcats on lynx.

Competition With Coyotes and Wolves

The coyote, because of its wide habitat niche, heavy predation on snowshoe hares (O’Donoghue et al. 1998), high reproductive rate (Quinn and

Parker 1987), great behavioral plasticity (Murray and Boutin 1991), and high

tolerance of humans (Litvaitis 1992), must be considered a potentially

formidable competitor with mesocarnivores, including the lynx. Indeed,

coyotes are suspected in various declines of mesocarnivores, as evidenced

by documented cases of coyotes competing with or preying on sensitive and

endangered species (reviewed by Litvaitis 1992 and Goodrich and Buskirk

1995).

The distribution of coyotes has expanded dramatically during the past

few decades, especially to the northeast (Fuller and Kittredge 1996), but

also to the northwest. Coyote numbers have increased dramatically in

New England, as indexed by numbers of coyotes caught by trappers in

New Hampshire (Fig. 4.4). Virtually no coyotes were trapped in New

Hampshire before 1970, but coyotes were common by the mid-1970s and

continued to increase through the mid-1990s. Pelt price, a strong predictor

of harvest of many furbearers, explains little of the increase in coyote

harvests in New Hampshire over this period (Fig. 4.4). Similarly, coyote

harvests from Washington increased from the five -year period ending 1964-

1965 (mean = 362/year) to the five years ending 1983-1984 (mean = 16,250/

year; Novak et al. 1987). Consistent with this, coyotes were rare or nonexistent in coniferous forests of the Oregon and Washington Cascades until

timber wolves were extirpated around 1930 (Ozoga and Harger 1966).

The ecology of coyotes suggests further that they should be potent competitors. Coyotes at times kill lynx (O’Donoghue et al. 1995), probably most

often when lynx are young or in poor condition. O’Donoghue (1997) also
92

Chapter 4—Buskirk

showed that, comparing densities of lynx, hares, and coyotes between his

Yukon study area and that of Keith et al. (1977) in central Alberta, lynx were

more abundant where coyotes were less dense, rather than where hares were

more dense. Thus, interactions with coyotes appear to influence lynx more

than availability of snowshoe hares, generally considered to be the limiting

factor for lynx numbers. Similarly, coyotes compete with bobcats in various

settings (Nunley 1978; Litvaitis and Harrison 1989). Interference competition (direct killing) of bobcats by coyotes has been documented by Anderson

(1986), Jackson (1986), and Toweill (1986), and coyotes have been implicated

in bobcat declines in some areas. Considering that bobcats can be larger and

are more aggressive than lynx, coyote predation on bobcats suggests the

potential for strong interference competition between coyotes and lynx. As

with cougars and lynx, this potential likely is the greatest during low-snow

periods—the season for which our understanding of lynx ecology is the

weakest. Further, coyotes prey primarily on leporids (Voigt and Berg 1987);

50

100

150

200

250

300

350

400

Coyotes reported killed

Mean pelt price ($)

197219741976197819801982198419861988199019921994

Year

Coyotes

Mean pelt price ($)

0

Figure 4.4—Abundance of coyotes in New Hampshire, as indexed

by numbers killed in the State and sealed by the State of New

Hampshire Game and Fish Department (unpublished data) and

mean price paid per pelt to trappers for coyote pelts, as indexed

by the same agency (unpublished data). Price is plotted because

of the strong influence of price on harvest effort. The year - coyote

correlation was r (Pearson) = 0.77, whereas the price - coyote

correlation was r = 0.03. Therefore, we conclude that the strong

upward linear trend in coyotes killed is the result of their increased

abundance.
93

Buskirk—Chapter 4

within the range of the lynx, coyotes prey heavily on snowshoe hares (Todd

et al. 1981; Todd and Keith 1983; Parker 1986; O’Donoghue et al. 1998), and

attain high densities (up to 0.44/km2

; Todd et al. 1981) when snowshoe hare

populations are high. O’Donoghue et al. (1998) found that in Yukon Territory coyotes preyed on snowshoe hares during snowshoe hare highs at a

higher rate than the lynx predation, suggesting potentially important exploitation competition with lynx. Further, coyote abundance tracked that of

snowshoe hares through the cycle much as did lynx, enough that coyotes

contributed to the cyclic dynamics of snowshoe hare populations

(O’Donoghue et al. 1997). In a similar way, coyote densities have tracked

those of snowshoe hares in forest habitats in the contiguous United States

during the 1990s (Montana Department of Fish, Wildlife and Parks, unpublished data; Fig. 4.5), which probably is attributable to switching of habitats

and prey by coyotes, corresponding with hare population changes. This

illustrates the strong prey- and habitat-switching abilities of the coyote

(reviewed by Patterson et al., in press), which contribute to its success as a

competitor.

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Relative track density

1991 1992 1993 1994 1995 1996

Year

Hares

Coyotes

0

Figure 4.5—Relative abundance of coyotes and snowshoe

hares on transects in Montana, 1991 to 1996. The correlation

between hare and coyote track densities, without any time lag,

is significant (r = 0.81, df = 4, P = 0.05). The absence of a lag in

the correlation suggests that the relationship is at least partially

due to habitat and prey switching by coyotes in response to

fluctuating hare densities.
94

Chapter 4—Buskirk

Numerous reports describe coyotes accessing high-elevation, deep snow

areas by moving along paths, roads, and snowshoe hare trails (Bider 1962;

Ozoga and Harger 1966; Murray et al. 1995). Unpublished data from Oregon

(USDA Forest Service, unpublished report) and Colorado (Byrne 1998,

unpublished) also suggest that coyotes use high elevation areas, although

their means of access is not known. Byrne (1998, unpublished) conducted

track surveys for snowshoe hares and recorded other species’ tracks on 1,160

km of snow transects within presumed snowshoe hare habitat (7,500-11,800

feet elevation) in winter. Coyotes were the second most common carnivore

taxon (after weasels) encountered, with 628 tracks recorded. The elevation

zone with the highest frequency of coyote tracks was 8,000-9,000 feet but

coyote tracks were fairly common (about 0.45/km of transect) in the 9,000-

10,000 and 10,000-11,000 foot elevation zones. These results indicate that

coyotes are much more common in high elevation, deep snow areas of

western mountains than generally has been believed to be the case.

Nevertheless, some basis exists to believe that coyotes and lynx are

spatially segregated in winter by deep snow. In central Alberta, Todd et al.

(1981) found that coyote use of open habitats increased from November to

March, which they attributed to snow accumulation in forest and the greater

compactness and load-bearing strength of snow in openings. This intolerance of deep snow resulted in a diet shift from snowshoe hares to ungulate

carrion in winter. Also in Alberta, Murray et al. (1994) found that coyotes

were more selective of hard or shallow snow conditions than were lynx. In

the western (Murray and Boutin 1991) and northeastern United States

(Litvaitis 1992), this morphological difference causes coyotes and lynx to be

spatially segregated by snow conditions. In the West, this occurs along an

elevational gradient. Such separation should minimize competition between the two species. However, this separation may break down where

human modifications to the environment increase access by coyotes to deep

snow areas. Such modifications include expanded forest openings throughout the range of the lynx in which snow may be drifted, and increased

snowmobile use in deep snow areas of western mountains. Recreational

snowmobile use has expanded dramatically in the contiguous United States

in the past 25 years, with hundreds of thousands of km of trails (>19,000 km

of groomed trails in Maine alone) within the pre-settlement range of the lynx

(Maine Snowmobile Association, World Wide Web site, Zesiger 1997).

Various unpublished accounts describe snowmobile and snowshoe trails

facilitating access by coyotes to areas used by hares and lynx. In the Yukon,

coyotes use both snowshoe and snowmobile trails (O’Donoghue, personal

communication). This facilitation of travel, in general, could help explain
95

Buskirk—Chapter 4

possible lynx reductions in the West via human-facilitated competition

from coyotes and other generalist predators. Better understanding of this

postulated relationship is critical.

Although wolves have been reported to kill lynx, only for Fennoscandia is

there evidence that wolves exert population-level interference competition

with lynx (Pulliainen 1965). We suspect that a more likely effect of wolves on

lynx is by reducing numbers of coyotes, one of the strongest examples of

fierce interference competition among carnivores (Buskirk 1999). In a few

areas of the contiguous United States, wolves are becoming more common

and coyotes more scarce. Lynx should fare better with sympatric wolves

than with sympatric coyotes, because wolves prey little on leporids (Mech

1970) and are marginally too large to be interference competitors with lynx

(Fig. 4.2). We predict that the Greater Yellowstone Area and northern

Montana, with expanding wolf and shrinking coyote populations, will

increase their suitability for occupancy by lynx in coming years.

Conclusions

Fragmentation of habitats occupied by lynx (including increased openings, higher road densities, exurban residential development, and wider

use of snowmobiles and devices that compact snow in areas with deep,

soft snow) is a plausible mechanism for the questionable conservation

status of the lynx in the contiguous United States. Competition could take

the form of exploitation by other predators of snowshoe hares, particularly

the coyote, or involve interference competition, with larger-bodied carnivores acting aggressively toward lynx, even killing them. The coyote,

because of its broad niche tolerances, high reproductive rate, and expanding range in the contiguous United States, is particularly suspect in

competition. In spite of this evidence suggesting that coyotes may

exploitatively compete with lynx, we suspect that, at least where hare

populations cycle, exploitative competition impacting lynx is unlikely.

Competitive systems involving cycling snowshoe hares never come to

equilibrium and the primary impact of the competition should be overwhelmed by the large changes in prey availability. Even so, in the southern

part of the range of lynx, if hares fluctuate less dramatically than they do

in the North, exploitation competition inflicted by coyotes may reduce

lynx numbers. Overall, we suspect that interference competition is more

likely to be the critical form of competition that needs to be evaluated for

lynx in the contiguous United States. Cougars, in particular, appear to be

effective interference competitors with lynx.
96

Chapter 4—Buskirk

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Taylor, R. J. 1984. Predation. Chapman and Hall, New York, NY.

Thurber, J. M., R. O. Peterson, J. D. Wollington, and J. A. Vucetich. 1992. Coyote coexistence

with wolves on the Kenai Peninsula, Alaska. Canadian Journal of Zoology 70:2494-2498.

Todd, A. W., L. B. Keith, and C. A. Fischer. 1981. Population ecology of coyotes during a

fluctuation of snowshoe hares. Journal of Wildlife Management 45:629-640.

Todd, A. W. and L. B. Keith. 1983. Coyote demography during a snowshoe hare decline in

Alberta. Journal of Wildlife Management 47:394-404.

Toweill, D. E. 1986. Resource partitioning by bobcats and coyotes in a coniferous forest.

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Voigt, D. R. and W. E. Berg. 1987. Coyote. Pages 344-357 in M. Novak, J. A. Baker, M. E.

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Wilcove, D. S. 1985. Nest predation in forest tracts and the decline of migratory songbirds.

Ecology 66:1211-1214.

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Temperate Zone. Pages 237-256 in M. E. Soulé, editor. Conservation biology: the science

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Wilcox, eds. Conservation biology: an evolutionary-ecological perspective. Sinauer,

Sunderland, MA.

Wilcox, B. A. and D. D. Murphy. 1985. Conservation strategy: the effects of fragmentation

on extinction. American Naturalist 125:879-887.

Yahner, R. H. 1988. Changes in wildlife communities near edges. Conservation Biology

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Zesiger, S. 1997. Zero to sixty in three seconds (cold). Fortune 135(6):178.
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Chapter 5

Species Conservation

and Natural Variation

Among Populations

Leonard F. Ruggiero, USDA Forest Service, Rocky Mountain Research Station,

815 E. Beckwith, Missoula, MT 59801

Michael K. Schwartz, Wildlife Biology Program, University of Montana,

Missoula, MT 59812

Keith B. Aubry, USDA Forest Service, Pacific Northwest Research Station,

3625 93rd Ave. SW, Olympia, WA 98512

Charles J. Krebs, Department of Zoology, University of British Columbia,

Vancouver, BC V6T 1Z4, Canada

Amanda Stanley, Department of Zoology, University of Washington,

Seattle, WA 98195

Steven W. Buskirk, Department of Zoology and Physiology,

University of Wyoming, P.O. Box 3166, Laramie, WY 82071
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Introduction

In conservation planning, the importance of natural variation is often

given inadequate consideration. However, ignoring the implications of

variation within species may result in conservation strategies that jeopardize, rather than conserve, target species (see Grieg 1979; Turcek 1951;

Storfer 1999). Natural variation in the traits of individuals and populations

is the product of the genetic composition of the individual and the environment to which the individual is exposed. Inherited traits are those that are

largely genetically determined, whereas non-inherited traits result primarily from environmental influences and are not under direct genetic control.

Inherited and non-inherited traits are an oversimplification of a complex

phenomenon and represent two ends of a gradient of variation.

Natural variation exists within and among populations. It is unwise to

assume that behavioral or genetic attributes exhibited by one population are

within the range of behavioral or genetic potential of another (Ruggiero et al.

1988). When this assumption is false, it can result in failed reintroduction

efforts or a net loss of genetic or behavioral variability(e.g., Halloran and Glass

1959 and examples provided in Storfer 1999). Similarly, problems can also

result from applying ecological knowledge from one population to the conservation needs of other populations inhabiting substantially different habitats.

In this chapter, we review fundamental concepts related to patterns of

natural variation in populations and discuss their relevance to the process of

species conservation. First, we define some of the terms used in this chapter

and discuss how geographic variation in environmental conditions may

lead to variation among populations. We then discuss differences between

inherited and non-inherited variation and the role each may play in structuring populations within species. Lastly, we discuss the implications of natural

variation among populations to lynx conservation.

We use the following terms and concepts: genotype refers to a particular set

of genes possessed by an individual, and phenotype is the outward appearance and behavior of the individual (Ricklefs 1990), which is determined by

interactions between the genotype and the environment. Phenotypic plasticity is the capacity for a single genotype to produce multiple phenotypes,

Modifications of the phenotype that do not involve genetic changes

have long been considered...to lack evolutionary significance.

This view is not correct.

- Ernst Mayr
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often as the result of varying environmental influences (Falconer and

Mackay 1996). Adaptation is a trait that permits an organism to function well

in its environment and endows it with capabilities especially appropriate for

its particular environment (Roughgarden 1979).

Within- and Among-Population Variation

Populations and Species

Natural variation exists between individuals in a population and between

populations of a species. A population is a group of conspecific organisms

living near enough to one another that both ecological and reproductive

interactions occur more frequently within the group than with members of

other populations (Futuyma 1986). Populations are composed of unique

individuals possessing varying behavioral and physical traits, and can only

be characterized by the range of variation in these traits. Variation also exists

among populations within a species (Endler 1986; Lott 1991). Differences

among populations generally increase with distance and/or isolation.

In general, the aggregation of these populations comprises a species (for

more specific definitions of the species see reviews in Futuyma 1998; Mallet

1995). Therefore, a species encompasses variation occurring both within and

among populations. Species are not composed of uniform, interchangeable

populations; they are more like jigsaw puzzles with many unique pieces.

Species Range and Dispersal Capability

Diversity among populations can be reduced when a species’ dispersal

capability is great relative to the spatial extent of its range, and when barriers

do not impede dispersal or gene flow (Mills and Allendorf 1996; Wright

1969). However, in widely distributed species, such as the lynx, distance

alone can function as a barrier to genetic exchange among populations, even

when individuals are capable of long-distance movements. This is known as

isolation by distance (see Britten et al. 1995; Hartl and Clark 1989; Wright 1943).

Physical features of geography and habitat may also act as both absolute and

psychological barriers to movements and dispersal (e.g., Buskirk and

Ruggiero 1994; Diamond 1975; Mayr 1970) and impede gene flow. Thus,

dispersal and gene flow are not simply mechanical processes governed

by a species’ movement capabilities, they are also affected by geographic

influences on the movements of individuals, behavioral responses to perceived barriers, and the probability of successful reproduction in new

environments.
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Central vs. Peripheral Populations

Central populations are usually large, continuous, and occupy favorable

habitats. Peripheral populations, by contrast, can be more or less isolated,

fragmented, and subject to a more variable physical environment (Carson

1959; Lesica and Allendorf 1995). Accordingly, peripheral populations will

often experience different selection pressures than central populations,

which may lead to genetic divergence (but see Kirkpatrick and Barton 1997).

Differences in genotype and phenotype are most likely to occur in populations that have become isolated at the periphery of the range (Lesica and

Allendorf 1995; Mayr 1970; Safriel et al. 1994). Isolated populations lack or

have greatly reduced levels of immigration and, consequently, may diverge

from central populations due to genetic drift and natural selection. Peripheral populations often have reduced levels of genetic variability relative to

central populations (Lesica and Allendorf 1995)

Genes vs. Environment: A False Dichotomy

Assessments of natural variation among populations are generally focused on traits that have a direct genetic basis (i.e., inherited traits), with little

emphasis on those that do not (e.g., Vogler and DeSalle 1994). The prevailing

view seems to be that because only genetic material is inherited, it represents

the essential element of natural variation, selection, and adaptation. In

contrast, a phenotype for which no direct genetic basis is known is thought

to be of less evolutionary significance and of only minor importance in

conservation planning (see Pennock and Dimmick 1997; Rohlf 1994). However, we believe this view to be fundamentally incorrect because phenotypic

plasticity (which is itself a genetic trait) and its effects on individual fitness

can play a key role in evolutionary processes (Mayr 1970; Pianka 1994).

Natural Selection and Inherited vs. Non-inherited Traits

Evolutionary theory states that populations contain inherited variation

that arises by random mutation and recombination and which is acted upon

by random genetic drift and natural selection. Natural selection is the

differential reproductive success of different phenotypes, a process which

slowly changes gene frequencies in populations. Those individuals with

phenotypes that are selected against are less successful than others and,

eventually, their genes are eliminated from the population.

Traits that are largely influenced by the environment are considered noninherited. This does not mean that these traits are non-genetic. Most noninherited traits are under “indirect” genetic control, as it is ultimately the
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genes of the individual that allow the phenotype to be shaped by the

environment. When natural selection acts upon these phenotypes, gene

frequencies do not immediately change because there is no direct correlation

between the genotype and the phenotype. However, non-genetic

modifications of the phenotype that occur in the absence of genetic change

can be adaptive, can influence fitness, and may be preserved by indirect

genetic mechanisms and learned behaviors (Falconer and Mackay 1996;

Grant 1963; Mayr 1970).

The evolutionary significance of phenotypic plasticity has been discussed

in many contexts (Baldwin 1896; see also Ancel 1999 and Simpson 1953).

Baldwin argued that such responses might permit a population to inhabit an

environment to which it is poorly adapted. Through this mechanism, the

population may gain the time necessary to acquire, through mutation,

genotypes with an adaptive advantage (Grant 1963).

Discriminating between inherited and non-inherited traits is extremely

difficult. To determine if a behavioral, physiological, morphological, or

biochemical trait is strongly influenced by the environment requires careful

laboratory study (e.g., common garden and reciprocal transplant experiments). Such studies are nearly impossible with large, highly mobile organisms like the lynx.

Examples of Strong Environmental Influences on

Phenotypic Traits

There are many classic examples of natural selection acting upon heritable

traits (e.g., Boag and Grant 1981; Reznick et al. 1990). There appear to be

fewer instances where the local environment has been shown to determine

a phenotype. In this section, we review several cases where environment

plays a large role in shaping the phenotype.

Rhymer (1992) conducted both a reciprocal transplant and a commongarden experiment with mallards from California and Manitoba to see if size

variations were inherited. She found that while some differences in the size

and morphology of mallards persisted regardless of environment, most of

the variation in size was under environmental control. Growth in ducks is

not locally adapted as was previously suggested (Lightbody and Ankeny

1984), but was determined by local environmental conditions at the time of

rearing (Rhymer 1992).

Red-winged blackbirds show large clinal variation in size and shape.

James (1983) conducted a reciprocal transplant experiment with red-winged

blackbird eggs from northern and southern Florida and a single transplant

experiment from Colorado to Minnesota. She concluded that regional variation in the shape of red-winged blackbirds was largely non-genetic because
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transplanted eggs produced birds more like the phenotypes typical of their

adopted area.

Geist (1991) discussed the taxonomic status of wood bison that were

previously thought to be a subspecies distinct from the plains bison. He

concluded that observed differences between plains and wood bison were

not genetically determined, but were phenotypic differences associated

with diet. Thus, differences between wood bison populations appear to be

based on phenotypic plasticity.

Learned behaviors also demonstrate the strong influence of the local

environment on a trait. Both within and among populations, individuals can

exhibit a wide range of learned behaviors. The inheritance of learned

behavior is termed cultural inheritance (Cavalli-Sforza and Feldman 1973). A

well-known example is the learned ability of several species of British birds

to open milk bottles. This behavior was first reported in the 1920s and Hinde

and Fisher (1951) have subsequently mapped its spread over an extensive

area. Recent work by Lefebvre (1995a) indicates that the spread of milkbottle opening by birds has been accelerating across the United Kingdom

(U.K.). However, the behavior is still not found in some U.K. populations,

even though it is prevalent in others.

Cultural inheritance has also been reported in primates (see Lefebvre

1995b). Kawamura (1954)noted that neighboring troops of Japanese macaques

differed in feeding habits, and others began feeding the macaques to observe

their social behavior. One of the foods they provided was wheat grains

spread on a sandy beach, a food source that was difficult for the monkeys to

handle. One female macaque separated out the wheat grains, which floated,

by placing handfuls of sand into puddles of water on the beach. Shortly

thereafter, researchers saw other troop members imitate the separation

technique (Kawai 1965). Soon, it became a technique unique to members of

this troop and not found in other troops.

The key point is that non-inherited traits are often adaptive and therefore

can influence fitness and evolution. Accordingly, phenotypic variety must

be carefully considered by conservationists regardless of the mechanism by

which it was created.

Considerations for Conservation Planning

Reintroductions, Augmentations, and Translocations

Reintroduction entails moving individuals from one or more wild populations to parts of the species’ range where local populations no longer exist.

Population augmentation is the process of moving individuals from one or
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more wild populations to a different part or parts of the species’ range

where local populations are precariously small. We refer to any relocation

of individuals from an existing wild population into a new environment

as a translocation.

Augmenting populations with captive-bred animals, or introducing captive-bred individuals into the wild, is generally problematic. Captive-bred

animals usually have lower survival rates, a reduced fright response to

predators, and may lack other behaviors necessary to survive in the wild

(Reinert 1991; Stahl 1981). In addition, adaptation to captivity can occur

allowing those genotypes best suited for surviving and reproducing in

captivity to increase in frequency, while those genotypes best suited for

surviving and reproducing in the wild dwindle (Kohane and Parsons 1988;

Allendorf 1993).

When appropriate behaviors are absent in captive-bred individuals, it

may mean that those behaviors are learned. Learned behaviors, such as

predator avoidance, probably depend on exposure to specific predators

which may not occur in the natal ranges of translocated animals. However,

the lack of a “hard-wired” genetic basis for these behaviors renders them no

less critical with regard to successful reproduction and, ultimately, to fitness

(see Bekoff 1989 for a discussion of behavioral development in carnivores).

Translocations may fail for many reasons, including non-inherited differences among populations, limits to phenotypic plasticity, and detrimental

stochastic events. Several examples illustrate the problems inherent in

translocating animals from one ecosystem to another.

Evans and Williamson (1976) described an attempted introduction of wild

turkeys from an arid region of Texas to the wetter areas of eastern Texas.

Although the dry-adapted birds survived, high humidity prevented them

from nesting successfully, and the introduction failed.

Woodland caribou from two British Columbia (B.C.) populations (westcentral and east-central) were transplanted into northern Idaho to augment

a small remnant population (Warren 1990; Warren et al. 1996). Transplanted

individuals had a tendency to retain the movement and feeding behavior of

their original stocks. Caribou from west-central B.C. eat mainly terrestrial

lichens in winter, whereas caribou from east-central B.C. eat arboreal lichens

because the snow is too deep to dig through. After translocation, more eastcentral caribou emigrated from the transplant area, in keeping with the

tendency of the parent population to emigrate more frequently than westcentral caribou. Most west-central caribou died, and apparently starved

while digging for lichens in winter, ignoring abundant arboreal lichens in

the transplant area.
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Lynx translocations have also proven to be problematic. Eighty-three lynx

were translocated from the Yukon Territory into the Adirondack Mountains

of New York in the late 1980s (Chapter 13). Nearly half the animals died

within two years of being released and, in spite of considerable search

effort, there is no recent evidence of lynx occurrence in the Adirondacks

(K. Gustafson, personal communication). An ongoing lynx reintroduction

effort involving the translocation of animals from Yukon and Alaska into

Colorado has been fraught with problems, including the starvation of

several individuals (Kloor 1999). Translocations are most likely to succeed

between populations whose environments and ecological relationships are

similar, especially with regard to climate, habitat, and community composition. We believe that translocation of closely related populations, with

similar local adaptations, will have the highest probability of success.

Furthermore, we believe that relocation from the core to the periphery of a

species range will usually entail significant risk.

Outbreeding Depression

Interbreeding between two populations may result in a reduction in

number, viability, or fitness of offspring, a phenomenon known as outbreeding depression (Templeton 1986; Waser and Price 1994). There are two

mechanisms responsible for outbreeding depression: mixing of locally

adapted populations, and disruption of co- adapted gene complexes, which are

sets of genes that increase fitness when all are present in the individual

(Templeton et al. 1986).

The first mechanism, interbreeding of animals from two locally adapted

populations, produces offspring that may not be adapted to either location.

There are several examples of translocation failures resulting from mixing

locally adapted populations (Grieg 1979; Templeton 1986; Turcek 1951).

Populations of the Tatra Mountain ibex in central Europe were supplemented with ibex from Turkey and the Sinai during the 1960s. The hybrids

of these ibex rutted in early autumn instead of in winter (as the native ibex

did), and the females gave birth in February in Czechoslovakia during the

coldest time of the winter. The entire population went extinct because of the

mixing of these groups (Grieg 1979).

A second mechanism that can cause outbreeding depression is the disruption of co-adapted gene complexes. The mixing of gene pools (e.g., by

translocation of individuals with one set of co-adapted gene complexes to

another population with a different set) can break down these gene complexes and cause a reduction in fitness (Dobzhansky 1948).
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Natural Variation and Lynx Conservation

Resource managers have the complex task of applying the concepts

discussed in this chapter within a legal context. The Endangered Species Act

(ESA) will allow listing of “any subspecies of fish or wildlife or plants, and

any distinct population segment of any species of vertebrate fish or wildlife

which interbreeds when mature.” Only two subspecies of lynx have been

described in North America: one in Newfoundland (L.c. subsolanus), and the

other throughout the remainder of Canada, Alaska, and the contiguous

United States (L.c. canadensis; Werdelin 1981). Thus, determining whether

distinct population segments occur within this region is a critical conservation issue.

Evolutionarily Significant Units

The first U.S. management agency that comprehensively addressed the

problem of defining distinct population segments was the National Marine

Fisheries Service (NMFS). One of the missions of NMFS is to manage Pacific

salmon, a species group with high levels of phenotypic variation (Allendorf

et al. 1997). Waples (1991) proposed that a population be considered “distinct” if it represents an Evolutionarily Significant Unit (ESU) of the species

(a term first coined by Ryder in 1986 with regard to prioritizing species for

captive propagation efforts). To be considered an ESU, a population must be

reproductively isolated from conspecific populations, and it must represent

an important component of the evolutionary legacy of the species. According to Waples (1995) the evolutionary legacy of the species is “the genetic

variability that is a product of past evolutionary events and that represents

the reservoir upon which future evolutionary potential depends.”

When NMFS was asked to evaluate the status of spring-, summer-, and

fall-run chinook salmon in the Snake River, they applied the ESU concept

(USDC 1991; USDI and USDC 1996; Waples 1995). Large genetic differences

separated fall from spring and summer fish, but it was unclear what the

contribution of the Snake River fall-run chinook was to the “ecologicalgenetic diversity” of the species (Waples 1995). Water characteristics such as

temperature and turbidity differ dramatically between the Snake River and

the adjoining Columbia River, and it was believed that Snake River fall-run

chinook had developed either physiological or behavioral adaptations to its

river environment. These data, along with different oceanic distributions of

the Columbia and Snake River fish, were used to classify Snake River fall-run

chinook as an ESU. The spring and summer runs were distinct from the

Columbia River chinook. However, the timing of the run (spring versus
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summer) explained less than 10% of the genetic variation in the sample.

Consequently, spring and summer runs were classified as one ESU.

In 1994, the U.S. Fish and Wildlife Service (USFWS) drafted a policy

regarding the recognition of distinct vertebrate population segments under

the ESA (USDI and USDC 1994). The goal was to use criteria similar to NMFS

for defining a distinct population segment (i.e., an ESU). The USFWS

proposed that distinct population segments would be defined according to

the discreteness and significance of the population segment relative to the

remainder of the species (USDI and USDC 1994, 1996). This policy has only

recently been adopted (USDC 1996).

The ESU approach has been criticized from both biological and legal

perspectives as being not biologically meaningful, too subjective, too specific to salmon, and relying too heavily on genetics (Rohlf 1994; Vogler and

DeSalle 1994; see Waples 1995, 1998 for responses). A wide range of solutions

have been proposed to address both the problem of subjectivity (see Moritz

1994) and reliance on DNA-based analyses (see Vogler and DeSalle 1994). All

participants in this debate appear to agree that understanding observable

variation in nature is critical to identifying distinct population segments for

conservation.

Because we are often unable to tell if adaptive traits are inherited, an ESU

policy that focuses only on inherited traits will fail to identify potentially

important distinct population segments. We recommend that all aspects of

the natural history of lynx be considered when evaluating potential ESUs for

lynx. This includes not only data on neutral genetic markers (e.g., microsatellite

DNA), but also potentially adaptive traits inferred from physiological,

behavioral, morphological, and ecological studies.

Implications for Lynx Conservation

We know virtually nothing about levels of natural variation in lynx

populations. However, we do know that the geographic range of lynx covers

a broad range of environmental conditions, especially with regard to habitat

structure, habitat ecology, and predator/prey communities (Chapter 14).

Additionally, the environment at the core of the lynx range is very different

ecologically from the environment at the southern periphery of the species

range (Chapter 3). We also know, however, that individual lynx are capable

of long-range movements, and that all populations are restricted to boreal

forest habitats and appear to rely on snowshoe hares as prey.

Understanding the nature of variation among lynx populations and its

implications for conservation will require studies of the genetic structure

of subpopulations, estimates of historical and current gene flow between

peripheral and core populations, and studies of comparative ecology
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throughout the range of lynx. Until we understand the nature of geographic

variation in lynx populations, it would seem prudent to assume the existence

of important genetic and non-genetic differences among populations, especially those that are distant and/or relatively isolated.

Conclusions

In this review, we have attempted to show that (1) natural variation among

populations is prevalent in nature, (2) conservation assessments and plans

need to explicitly address patterns of natural variation among populations,

whether it is inherited or not and (3) such assessments need to be concerned

not only with genotypes, but also with the plasticity of those genotypes to

produce different phenotypes. The preservation of natural variation will, in

part, be concerned with the conservation of genetic diversity and genetic

adaptations to local environments. Protection of this type of diversity is

mandated by the ESA and can be addressed through the Evolutionarily

Significant Unit (ESU) policy recently adopted by the Departments of

Interior and Commerce. However, implementation of this policy should

include explicit consideration of both inherited and non-inherited variation.

Some non-inherited traits that vary between populations are ultimately

under genetic control. Traits such as phenotypic plasticity allow species to

respond to changing environments and to potentially different environmental conditions found at the periphery of a species’ range. Phenotypes which

are products of specific environments become endangered if we lose or

modify those environments. It would be naive to think that we could recreate an extinct phenotype by taking a similar genotype and subjecting it to

comparable environmental conditions. Similarly, we may disrupt adaptive

phenotypic responses by introducing individuals to the population that lack

the genetic potential to make appropriate phenotypic adjustments. And

finally, culturally inherited behaviors are likely to be especially important in

higher vertebrates having complex behavioral patterns and socially or

parentally facilitated behavioral development.

Traits that are genetically determined and those that are largely determined by the environment are part of a continuum and, in many cases, it

may be impossible to distinguish between the two. Does it matter if differences are genetic, if such differences improve fitness and convey a selective

advantage by improving reproductive success? The answer is a qualified

“no.” In the case of genetic adaptations, this advantage is more or less fixed

over intermediate time periods (e.g., hundreds of years given a more or less

stable environment), thus contributing to the long-term evolutionary potential of the species. In the case of non-genetic differences, the potential for
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change over the short term may mediate survival rates leading to long-term

change. For example, new behaviors learned in response to new environmental challenges could result in improved survival, allowing populations

to persist and acclimate to changing conditions. In this scenario, if environments change quickly and dramatically, as is often the case when translocating animals, a lack of behavioral plasticity could lead to increased mortality

rates and, eventually, local extirpation.

Similarly, management decisions made on the basis of observed habitat

relationships in one population could result in detrimental effects on another population occupying a substantially different environment. For

example, forest management practices determined to be beneficial to lynx in

the taiga may not be appropriate in southern boreal forests of the western

montane region, where ecological conditions are dramatically different. In

other words, the translocation of scientific knowledge from one population

to another can be as risky as the physical translocation of animals. In either

case, the risk of undesirable results will increase with ecosystem dissimilarities and/or geographic distance.

Implications for Management

Because translocations and reintroductions are inherently risky even

under optimal conditions, they should be used only when other management options have failed. Conservation objectives are more likely to be met

by maintaining and/or enhancing habitat conditions for lynx to provide

opportunities for them to recolonize former portions of their range. If

deemed necessary, reintroductions into peripheral populations should be

done with lynx from other peripheral populations, neighboring populations, or genetically similar populations. It is risky to use individuals from

captive, distant, or ecologically dissimilar populations.

Neutral genetic markers can detect the structuring of populations and aid

in the identification of source populations for translocated individuals.

However, we caution that analyses of neutral markers cannot detect differences in adaptive traits between populations. Thus, even if no subdivision of

populations is detected with such analyses, adaptive genetic differences

may still exist between populations.

Lastly, it is critical to consider both inherited and non-inherited variation

when manipulating lynx populations or managing their habitat. We recommend that managers assume the existence of important genetic and nongenetic differences between distant and/or relatively isolated lynx populations until proven otherwise.
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Acknowledgments

We thank Kevin McKelvey, Kermit Ritland, John McKay, Fred Allendorf,

and Scott Mills for helpful suggestions on previous versions of this

manuscript.

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117

Chapter 6

The Ecology of

Snowshoe Hares in

Northern Boreal Forests

Karen E. Hodges, Centre for Biodiversity Research,

University of British Columbia, 6270 University Boulevard,

Vancouver, BC V6T 1Z4, Canada

Abstract—Snowshoe hares exhibit eight to 11 year population fluctuations across

boreal North America, typically with an amplitude of 10 to 25 fold. These fluctuations are synchronous across the continent, with the most recent peak densities

occurring in 1990 and 1991. The numeric cycle is driven by changes in survival and

reproduction, with annual survival of adults ranging from approximately five to

30% and annual natality ranging from approximately six to 20 leverets/female.

These parameters show cyclic changes because of functional and numerical responses of predators and changes in food supply. Predator densities show approximately two to 10 fold fluctuations during the hare cycle. The cyclicity of hares may

be partly explained by regular behavioral shifts, with repercussions on their

physiology, availability to predators, reproduction, and survival. However, this

hypothesis needs more empirical support before it can be accepted.
Chapter 6—Hodges

118

Introduction

In this chapter, I discuss the ecology of cyclic populations of snowshoe

hares in the boreal forests of North America. I emphasize the demographic

changes leading to changes in numbers of hares, the habitats that hares use,

the impacts of nutrition, physiology, and parasite loads on hares’ susceptibility to predation, and the effects of disturbance (fire, logging, fragmentation, and regeneration) on snowshoe hares’ behavior and demography. I

address what is known about the causes of the cycle and cyclic synchrony

among regions. For demographic data, I focus on data sets that show

variation through a cycle in one location; I use demographic results from

shorter studies to examine the factors that influence demography, rather

than trying to infer cyclic or geographic patterns from them.

Magnitude and Synchrony of Northern Hare Cycles

Snowshoe hares show cyclic fluctuations in density across northern North

America, with peak densities every eight to 11 years. It was thought that only

northern populations of hares cycle (Green and Evans 1940; Finerty 1980; Smith

1983; Keith 1990), but recent evidence suggests that hare in their southern

range—through the Cascades, Rockies, and Alleghenies to California, New

Mexico, and Virginia—may also cycle (Chapter 7). Hares were introduced into

Newfoundland in the 1860s and 1870s. Their numbers increased rapidly,

crashed, and have since shown a 10-year cycle (Bergerud 1983).

During the last four decades, the cycle has been largely synchronous across

Canada and into Alaska (Table 6.1). Cyclic peaks have occurred roughly at

the turn of each decade (1960 to 1961, 1970 to 1971, 1980 to 1981, 1990 to 1991),

with lowest densities typically occurring three years later (1963 to 1964, 1973

to 1974, 1983 to 1984, 1993 to 1994). These patterns support previous surveys

that concluded that the cycle is synchronous (MacLulich 1937; Keith 1963;

Finerty 1980; Smith 1983; Sinclair et al. 1993; Sinclair and Gosline 1997). In the

last four decades, peak and low density years have been synchronous across

the continent, whereas cycles in the early and middle parts of the century

were synchronous at peak densities but not necessarily at low densities

(Sinclair and Gosline 1997). There have also been debates about whether

hares in the central part of Canada (i.e., Alberta, Saskatchewan, and Manitoba)

reach peak densities earlier than in other locations, followed by a wave of

peaks that extends north, west, and east (Bulmer 1974; Smith 1983; Ranta

et al. 1997). The data from the last three cycles do not support this idea.

There are a few areas in which hares may not cycle in synchrony. The

hunting data from Newfoundland suggest that cyclic peaks are asynchronous with those in mainland Canada (S. Mahoney, unpublished). Harvest
119

Hodges—Chapter 6

Table 6.1—The snowshoe hare cycle: synchrony, densities, and amplitude. Peak or low years coinciding with the beginning or termination of a study should be viewed with skepticism because

of the inability to see what the hare population did in the previous or subsequent years. Density estimates are not comparable because of different field and statistical techniques

applied to their generation; they and cyclic amplitude are presented to give an order of magnitude. Cyclic amplitude is rounded to the nearest 5. The data collated into this table

are roughly post-1960 and most are within the taiga provinces of the polar domain (Bailey 1997). (S) is spring enumeration. (F) is fall enumeration. No data are indicated by —.

Peak

density Low density

Location Years of study Peak Low (hares/ha) (hares/ha) Amplitude Methods Reference

Newfoundland 1990-1993 1990 1993 — — — Track counts Thompson & Curran 1995

Newfoundland 1954-1998 1960, 1969, — — — — Harvest recordsa Dodds 1965;

1976, 1983, S. Mahoney, unpublished

1998a

Manitouwadge, Ontario 1980-1985 1980 1984 — — — Track counts Thompson & Colgan 1987;

Thompson et al. 1989

Narcisse Wildlife Mgmt 1991-1993 — — — 0.3-0.4 — Live-trapping Murray et al. 1998

Area, Manitoba

Narcisse Wildlife Mgmt 1971-1973 — 1973 (S) — — — Sightings along Rusch et al. 1978

Area, Manitoba transects

Long Point Peninsula, 1971-1987 1971 (F) 1974 (F) 4.4 0.2 25 Live-trapping Koonz 1988, unpublished

 Manitoba 1980 (F) 1985 (F)

Saskatchewan 1958-1987 1960 1963 — — — Observationb Houston 1987;

1970 1973 Houston & Francis 1995

1980 1984

Rochester, Alberta 1961-1984 1962 (S) 1966 (S) 5.9-11.8 0.13-0.26 25 (S) Live-trapping Keith & Windberg 1978;

1971 (S) 1975 (S) (F) (S) Keith 1983;

1981 (S) Keith et al. 1984

Westlock, Alberta 1970-1974 1970 (F) 1973 (F) 5.6 (F) 0.8 (F) 5 Live-trapping Windberg & Keith 1978

woodlot fragments

Prince George, B.C. 1979-1983 1979 (F) — 16.4 (F) — — Live-trapping Sullivan & Sullivan 1988b;

1988-1991 1990 (F) 4.2-5.2 (F) Sullivan 1994

Mackenzie Bison 1989-1996 1989-1990 1992-1993 4.6 0.34 15 Pellet plotsc Poole 1994;

Sanctuary, NWT Track counts K. Poole, unpublished

Ft. Simpson, NWT 1993-1996 — 1994-1995 — 0.17 — Pellet plotsc Poole & Graf 1996;

K. Poole, unpublished

Ft. Smith, NWT 1989-1996 1989-1990 1992-1993 2.0 0.09 20 Pellet plotsc Poole & Graf 1996;

K. Poole, unpublished

Norman Wells, NWT 1989-1997 1989-1990 1992-1993 1.9 0.14 15 Pellet plotsc Poole & Graf 1996;

K. Poole, unpublished

Yellowknife, NWT 1989-1996 1989-1990 1993-1994 3.4 0.28 10 Pellet plotsc Poole & Graf 1996;

K. Poole, unpublished

(con.)
Chapter 6—Hodges

120

Inuvik, NWT 1989-1996 1995-1996 1988-1989 2.0 0.43 5 Pellet plotsc K. Poole, unpublished

Dawson, Yukon 1988-1991 1989-1990 — 1.3-4.3d — — Pellet plotsc Mowat et al. 1997, unpublished

Track counts

Whitehorse, Yukon 1988-1991 1990-1991 — 0.9-4.4d — — Pellet plotsc Mowat et al. 1997, unpublished

Track counts

Snafu Lake, Yukon 1988-1993 1990-1991 1986-1987 7.5 0.8-1.1 5-10 Pellet plotsc Mowat et al. 1997, unpublished;

1993-1994 Slough & Mowat 1996

Kluane Lake, Yukon 1976-1998 1980-1981 1984-1985 2.9 (S) 0.16 (S) 20 Live-trapping Krebs et al. 1986b;

1989-1990 1993-1994 1.5 (S) 0.08 (S) Krebs et al. 1995;

Hodges et al., in press;

C. J. Krebs, unpublished

Tanana Valley & s. 1995-1998 —e 1994-1995e — — — Aerial surveys M. McNay, unpublishede

of Fairbanks, Alaska

Wrangell-St. Elias, Alaska 1991-1998 1990-1991 1993-1994 2.9-5.5f 0.12-0.43f 20-25f Pellet plotsc C. D. Mitchell, unpublished

Fairbanks, Alaska 1986-1996 1988-1989 1992-1993 0.5 0.02 25 Pellet plotsc L.A. Viereck & P.C. Adams

Bonanza Creek LTER,

unpublished

Fairbanks, Alaska 1971-1977 1971 (F) 1975 (F) ~5.9g 0.12 50g Live-trapping Wolff 1980

Pellet plots

Fairbanks, Alaska 1955-1961 1961 1955 — — — Live-trapping Trapp 1962;

Pellet plots O’Farrell 1965

Fairbanks, Alaska 1970-1973 1971 — 6.0-6.5 — — Live-trapping Ernest 1974

Kenai Peninsula, Alaska 1971-1974 1973-1974 — — — — Observations Oldemeyer 1983

Kenai Peninsula, Alaska 1983-1998 1984-1985 1989-1992 0.8-3.0h 0-0.4h 5-25h Live-trappingh Bailey et al. 1986;

Staples 1995;

T. Bailey, unpublished

aThere does not appear to have been a distinct peak in the late 1980s. Lows are difficult to infer from the data because of variation in hunter effort. (M. O’Donoghue, personal communication). bPeaks are from Houston 1987 and generally correspond to the next to the last year of “high” densities in Houston & Francis (1995). Low values are the 4th of the “low” years from Houston & Francis (1995). cDensities from pellet plots are calculated using a regression equation derived from hare density information from 1976 to 1996 (C.J. Krebs, unpublished): ln(hares/ha) = 0.888962*ln(pellets)-1.203391, corrected for bias by multiplying with 1.57 following

Sprugel (1983). Pellets is pellets/0.155m2 . The methodology and rationale were derived in Krebs et al. (1987). The current equation uses more information. dThe range of values is the range that occurred in five different habitat types.

eM. McNay also reports that hare populations were highest in 1988 to 1989 or 1989 to 1990, and may have been at their lowest densities in 1993 to 1994. fFor most years, four sites were surveyed and ranges of values indicate sites. In 1991, only two sites were surveyed.

gThe peak density was inferred from 1971 peak densities in similar habitats in interior Alaska by Ernest (1974).

hDensity estimates are for adult hares only, trapped in summer. Ranges indicate the extreme values for the five study sites.

Table 6.1—Con.

Peak

density Low density

Location Years of study Peak Low (hares/ha) (hares/ha) Amplitude Methods Reference
121

Hodges—Chapter 6

data and observations suggest that there may not have been a cyclic peak in

the late 1980s or early 1990s (M. O’Donoghue, personal communication),

although track surveys in western Newfoundland showed a pronounced

decline from 1990 to 1993 (Thompson and Curran 1995). Human impacts on

hares are severe in Newfoundland and probably influence hare dynamics

(M. O’Donoghue and T. Joyce, personal communication).

The hare population around Inuvik, NWT, is asynchronous. The highest

densities were in 1995 and 1996 and the lowest densities were in 1988 and

1989 (out of eight years of collecting pellet-plot data) (K. Poole, unpublished). The Kenai Peninsula in Alaska also is asynchronous, with hares

reaching peak densities in 1984 and 1985 with low densities from 1989 to 1992

(Oldemeyer 1983; Bailey et al. 1986; Staples 1995; T. Bailey, unpublished).

There has been speculation that hare populations are out of phase throughout Alaska, which allows predators to travel the state in search of locally

abundant hares. The available data suggest that is not the case. With the

exception of the Kenai Peninsula, hares cycle in synchrony in Alaska (H.

Golden, unpublished; Chapter 9).

It has been hypothesized that synchrony is modulated by sunspot activity

(Sinclair et al. 1993; Sinclair and Gosline 1997). Sunspot activity is correlated

with weather patterns, fire, snowfall, and, potentially, plant growth. Regular

changes in one or several of these patterns at a continental scale could

synchronize population cycles that are occurring because of biological

interactions (Meslow and Keith 1971; Fox 1978; Finerty 1980). The Inuvik and

Kenai populations of hares are at the edges of snowshoe hare distribution,

and both are coastal. The coastal influence has pronounced effects on the

weather patterns, which may change the synchrony in these populations.

The question of whether there is geographic variation in peak and low

densities is more difficult to answer because of the array of field and

statistical methodologies used for density estimation and the problem of

determining what area of land was sampled. There is no obvious northsouth or east-west gradient in densities; indeed, during the 1990 to 1991

peak, Yukon had the lowest (1.4 hares/ha at Kluane Lake) (Krebs et al. 1995)

and the second-highest (7.3 hares/ha at Snafu Lake) (Slough and Mowat

1996) recorded peak densities. Estimates of low densities range from <0.1 to

1.0 hares/ha. Most estimates of amplitude are five to 25 fold, which is

somewhat lower than those inferred by Keith (1990). Hare densities vary

within different habitat types (Fuller and Heisey 1986; Koonz 1988, unpublished; Mowat et al. 1997, unpublished; Chapter 7), so estimates may also

reflect sampling effort in different habitats.
Chapter 6—Hodges

122

Natural History of Snowshoe Hares

Adult snowshoe hares range in weight from approximately 1,200 to 1,800 g

(Rowan and Keith 1959; Newson and de Vos 1964; C. J. Krebs, unpublished).

Sex ratios are fairly even at all ages (Dodds 1965; Keith 1990; Hodges et al.,

in press). Hares do not breed until the summer following their birth, with

very rare exceptions (Keith and Meslow 1967; Vaughan and Keith 1980).

Breeding is restricted to the summer, and each female has one to four litters

per summer (Keith et al. 1966; Cary and Keith 1979). Anywhere from one to

14 leverets are born per litter; the first litter of the summer has a mean of

approximately three leverets, the second litter is largest with a mean of five

to six, and the later litters are intermediate in numbers (Cary and Keith 1979;

O’Donoghue and Krebs 1992; Jardine 1995; Stefan 1998). Females breed

synchronously, perhaps to reduce leveret mortality (O’Donoghue and Boutin

1995). Mating occurs immediately post-partum and gestation lasts 35 to 37

days (Meslow and Keith 1968; Stefan 1998). The early litters are weaned at

about 24 to 28 days of age, but the last litter of the season may be nursed for

up to 40 days (O’Donoghue and Bergman 1992). The young are precocial;

they hide together under deadfall, at the base of a bush, in tangled grasses,

or under lupines for the first three to five days, and then hide separately,

coming together for their once-a-day nursing (Rongstad and Tester 1971;

Graf and Sinclair 1987; O’Donoghue and Bergman 1992; O’Donoghue 1994).

Most North American predators eat snowshoe hares, and most hares die

of predation (Keith 1990; Hodges et al., in press). Boreal predators display

size selection for hares. Small predators, such as Harlan’s hawks, hawk owls,

kestrels, and weasels, eat leverets and small juveniles (Stefan 1998; Rohner

et al. 1995; F. I. Doyle, unpublished), while larger predators, such as lynx and

coyotes, eat large juveniles and adult hares (Keith 1990; Hodges et al., in

press). Great horned owls and goshawks eat hares of all sizes (Hodges et al.,

in press). Most mortality occurs before hares reach breeding age, and leveret

survival is lower than juvenile survival. Although wild hares can reach five

to six years of age, typically over 70% of the spring breeding population is

composed of yearlings (Keith 1990; Hodges et al., in press).

In summer, hares eat forbs, grasses, leaves of shrubs, and some woody

browse (Wolff 1978; Grisley 1991; P. Seccombe-Hett, unpublished). In winter, they mainly eat twigs and some bark of bushes and trees (de Vos 1964;

Wolff 1978; Keith 1990), but they will also dig through shallow snow for forbs

and grasses (Gilbert 1990; Hodges 1998). Hares usually select smaller twigs

and are selective about which species they browse (Wolff 1978; Pease et al.

1979; Rogowitz 1988; Smith et al. 1988). Diet selection may be based on protein

or fibre content, secondary compounds, energy content, or digestibility

(Bryant 1981a; Schmitz et al. 1992; Rodgers and Sinclair 1997; Hodges 1998).
123

Hodges—Chapter 6

The Community Cycle

Many snowshoe hare predators also display cyclic dynamics, often with a

lag of one to three years behind the hare cycle (Keith et al. 1977; Keith 1990;

Royama 1992; Boutin et al. 1995). Lynx, coyotes, goshawks, and great horned

owls display numerical and functional responses to the changes in hare

densities, with numeric responses of two to 10 fold (Brand et al. 1976;

Adamcik et al. 1978; Brand and Keith 1979; Todd et al. 1981; Parker et al. 1983;

Poole 1994; Doyle and Smith 1994; Houston and Francis 1995; Slough and

Mowat 1996; Rohner 1996; O’Donoghue et al. 1997, 1998). Other predators,

such as red foxes, marten, fisher, eagles, wolverine, wolves, bobcats, hawk

owls, and Harlan’s hawks, may show functional responses to hare densities

(Keith 1963; Bulmer 1974; Litvaitis et al. 1986; Raine 1987; Kuehn 1989;

Theberge and Wedeles 1989; Dibello et al. 1990; Rohner et al. 1995; Hodges

et al., in press; F. I. Doyle, unpublished). Foxes, wolverine, marten, and fisher

may also exhibit numeric responses to the snowshoe hare cycle (Bulmer

1975; Thompson and Colgan 1987; Kuehn 1989; Slough et al. 1989; Poole and

Graf 1996).

Other small herbivores in the boreal forest also demonstrate cyclic dynamics, perhaps resulting from competition with hares for limited food or from

being the alternate prey when hares densities are low (Keith 1963; Boutin et

al. 1995). Spruce grouse and ruffed grouse show a 10-year fluctuation (Rusch

et al. 1978; Keith and Rusch 1988; Boutin et al. 1995), while red squirrels do

not (Keith and Cary 1991; Boutin et al. 1995; Boonstra et al., in press), and

Arctic ground squirrels may cycle in part of the boreal forest (Boonstra et al.,

in press). Mice and voles do not have regular 10-year fluctuations (Krebs and

Wingate 1985; Boutin et al. 1995), even though several predators prey more

heavily on small mammals when hares are scarce (Raine 1987; Giuliano et al.

1989; O’Donoghue et al. 1998).

Hares affect their woody browse species in several ways through the cycle.

At peak densities, hares may eat a large proportion of the standing shrub

biomass (Pease et al. 1979; Keith 1983; Smith et al. 1988), which will not

necessarily kill the plants. Hares also girdle the woody stems of trees and

shrubs (Sullivan and Sullivan 1982a; Hodges 1998), which will kill the trees.

However, some shrubs resprout from the ground, and girdling may stimulate new growth (Smith et al. 1988). Browsing by hares may affect successional dynamics (Bryant 1987; Rossow et al. 1997), disrupt attempts at

reforestation (Sullivan and Moses 1986; Radvanyi 1987, unpublished), and

influence the amount of secondary compounds that plants produce and their

palatability to hares (Bryant 1981a, 1981b; Fox and Bryant 1984; Bryant et al.

1985).
Chapter 6—Hodges

124

Demographic Changes Through the Cycle

The numeric hare cycle results from demographic changes. The main

demographic changes in order of importance are post-weaning juvenile

survival, adult survival, and leveret survival (Krebs 1996; Haydon et al. 1999;

Hodges et al., in press). Leveret survival and dispersal contribute the least to

cyclic dynamics (Haydon et al. 1999), even though they also vary through the

cycle (Boutin et al. 1985; Keith 1990; Stefan 1998).

Reproduction

Two long-term studies in Yukon and Alberta have shown that snowshoe

hares have the highest reproductive output during the early increase phase

of the cycle (16 to 19 leverets/female) and the lowest reproductive output

during the decline phase (six to eight leverets/female), with maximum

annual reproductive output about 2.5 fold higher than the lowest reproductive output (Fig. 6.1a,b) (Cary and Keith 1979; O’Donoghue and Krebs 1992;

Krebs et al. 1995; Stefan 1998). This pattern is the result of changes in the

proportion of females pregnant for each litter group, the number of litters

that females have in the summer, and the number of leverets per litter (Table

6.2). In Yukon, hares had only two litters during the decline phase, but had

four in the early increase phase (Stefan 1998). In Alberta, in contrast, at least

a few hares had a fourth litter in every year of the cycle, but during decline

years most hares had only three litters (Keith and Windberg 1978; Cary and

Keith 1979). Hares in Alaska had a higher pregnancy rate for the third litter

during the peak than during the decline (Ernest 1974). In both Yukon and

Alberta, litter size varied more for litters two to four than for litter one; mean

size for the first litter varied by approximately 0.5 leverets per litter through

the cycle. Means for later litter groups varied by one to two leverets per litter

through the different phases.

The factors influencing hares’ reproductive output are not well known.

Snowshoe hares exhibit cyclic changes in stress levels, indexed by several

blood chemistry traits such as cortisol and testosterone concentrations

(Boonstra and Singleton 1993; Boonstra et al. 1998a). Stress might cause

reproductive changes either by affecting females’ reproductive output directly or through maternal effects on the offspring (Boonstra et al. 1998b).

Reproduction does not seem to be affected by levels of parasitic infestation

(Bloomer et al. 1995; Sovell and Holmes 1996; Murray et al. 1998). Physically,

mass, skeletal size, and body condition (indexed by mass corrected for

skeletal size) do not appear to affect number of litters or litter size (Hodges

et al. 2000, in press; Hodges et al., in press). Older, heavier individuals may

have higher ovulation rates than younger, lighter hares (Newson 1964), but
125

Hodges—Chapter 6

reproductive output (leverets/female)

0

2

4

6

8

10

12

14

16

18

20

196219631964196519661967196819691970197119721973197419751976

0

2

4

6

8

10

12

spring density

leverets/female

spring density

Figure 6.1—Reproductive output in two cyclic populations of hares:

Alberta (1A) (Keith & Windberg 1978; Cary & Keith 1979) and Yukon

(1B) (Stefan 1998). Total annual natalities were calculated by summing

pregnancy rates x mean litter sizes for each litter.

0

2

4

6

8

10

12

14

16

18

20

1989 1990 1991 1992 1993 1994 1995 1996

0

2

4

6

8

10

12

reproductive output (leverets/female)

spring density

leverets/female

spring density

this difference cannot account for the cyclic changes because the lowest

reproduction occurs in the decline phase of the cycle when the proportion of

adults is highest and average body mass is also high (Hodges et al. 1999;

Hodges et al., in press).

Hares regularly lose mass overwinter (Newson and de Vos 1964). Keith

(1981, 1990; Keith et al. 1984; Vaughan and Keith 1981) has argued that food

shortage leads to the overwinter mass loss and negatively affects total

natality in the subsequent summer. However, there is no clear link between

A.

B.
Chapter 6—Hodges

126

Table 6.2—Reproductive attributes of snowshoe hares from two cyclic populations.

Low Peak Decline

1964-1966 Increase 1961 1962-1963

Albertaa 1975-1976 1967-1969 1970-1971 1972-1974

Number of litters 4 4 3 to 4b 3 to 4b

Litter 1

Range of parturition dates 30 April-15 May 29 April-15 May 4 May-20 May 15 May-20 May

Pregnancy rate 87.2 96.2 92.1 82.3

Mean litter size 3.0 2.8 2.6 2.7

Litter 2

Range of parturition dates 4 June-19 June 3 June-19 June 8 June-24 June 19 June-24 June

Pregnancy rate 95.7 94.0 85.6 89.8

Mean litter size 5.7 5.3 4.8 4.4

Litter 3

Range of parturition dates 9 July-24 July 8 July-24 July 13 July-29 July 24 July-29 July

Pregnancy rate 88.0 91.9 72.2 71.0

Litter size 5.1 5.6 4.6 3.7

Litter 4

Range of parturition dates 13 Aug- 28 Aug 12 Aug-28 Aug 17 Aug-2 Sept 28 Aug-2 Sept

Pregnancy rate 77.3 63.9 14.5 5.7

Litter size 3.7 4.8 4.2 4.0

Low Increase Peak Decline

Yukonc 1993-1994d 1995-1996 1989-1990 1991-1992

Number of litters 3 to 4d 3 to 4d 3 2

Litter 1

Range of parturition dates 9 May-17 May 16 May-2 June 20 May-29 May 27 May-11 June

Pregnancy rate 100 100 89.9 87.5

Mean litter size 3.2 3.4 3.8 3.3

Litter 2

Range of parturition dates 14 June-24 June 13 June-4 July 21 June-7 July 26 June-11 July

Pregnancy rate 100 100 96.4 90.1

Mean litter size 5.9 6.2 5.9 4.2

Litter 3

Range of parturition dates 20 July-2 Aug 28 July-5 Aug 28 July-13 Aug —

Pregnancy rate 100 100 84.5 0

Mean litter size 6.4 5.9 4.3 —

a

Data are from Cary & Keith (1979) and Keith & Windberg (1978). Parturition dates are the range of mean dates for the years given and were calculated by adding

35 days per litter to the conception dates presented in Keith & Windberg (1978). Pregnancy rates were calculated from necropsies and palpation of live hares; litter sizes

from necropsies. b

In 1971, 1972, and 1974, hares had only three litters. Average fourth litter pregnancy rates are calculated including these years. c

Data are from O’Donoghue & Krebs (1992) and Stefan (1998). Parturition dates are the range of dates from individual hares held in captivity for each litter. Pregnancy

rates were calculated by palpation and litter sizes from hares held in captivity until birthing. d

Although there were four litters in Yukon during some years, no data were collected on the fourth litter or in 1993.

mass loss and total annual natality. Changes in total annual natality come

from changes in pregnancy rates and litter sizes for later litters, whereas the

effects of overwinter mass loss might be expected to be most pronounced for

the first litter of the season. Hares do not store fat readily and are most

nutritionally stressed when food is limited rather than showing delayed

effects (Whittaker and Thomas 1983; Thomas 1987). Additionally, studies in

the Yukon have not been able to demonstrate a relationship between either
127

Hodges—Chapter 6

mass or mass loss and total annual reproductive output (O’Donoghue and

Krebs 1992; Stefan 1998; C. I. Stefan and K. E. Hodges, unpublished). Neither

the Yukon studies nor an Alberta study (Vaughan and Keith 1981) found an

effect of mass loss on the size of the first litter.

Across both the cycle and the continent, the consistent patterns in reproductive output are: (1) The percentage of females pregnant declines with

each successive litter group. Most females have at least two litters, but

pregnancy rates for the third and fourth litters are highly variable. (2) Litter

two is usually the largest and litter one the smallest. (3) Total annual natality

is highest in the low phase, followed by increase, peak, and decline phases.

The magnitude of variation is around 2.5 fold. (4) Reproductive output does

not appear to be affected by the mother’s skeletal size, mass, or parasite load.

Age of the mother may affect ovulation rates. Stress levels are correlated

temporally with and may contribute to reproductive changes. Overwinter

mass loss and limited winter food supplies may reduce reproductive output

through reductions in pregnancy rates and litter sizes, but the data are

contradictory.

Survival and Causes of Death

Almost all hares die of predation. During the 1990 cycle in Yukon, 95% of

the hares for whom cause of death could be positively identified were killed

by predators, with approximately half of all deaths due to mammalian

predators (Table 6.3) (Hodges et al., in press). Slightly lower estimates of

predation were derived from previous cycles in Yukon (Table 6.4) (Boutin et

al. 1986) and Alberta (Keith et al. 1977), but these analyses incorporated hares

for whom cause of death could not be determined, which would lower the

predation estimate. The 1980 and 1990 Yukon cycles showed that starvation

and other non-predation deaths occurred during the late increase and peak

and into the decline phases, counter to observations in Alberta that most

starvation deaths occurred during the decline phase (Keith et al. 1984; Keith

1990). Most leverets that die are killed by predators (81% through a cycle)

(O’Donoghue 1994; Stefan 1998), with deaths from exposure or maternal

abandonment (starvation) occurring mainly during the decline phase.

The main predators of adult hares are coyotes, lynx, goshawks, and great

horned owls (Table 6.3) (Keith et al. 1977; O’Donoghue et al. 1997; Gillis 1997,

1998; Hodges et al., in press). In contrast, leverets are predominantly preyed

upon by small raptors (boreal owls, Harlan’s hawks, kestrels, hawk owls)

and small mammals (red squirrels, ground squirrels, weasels). No leveret

kills by lynx or coyotes were observed during a cycle in Yukon (O’Donoghue

1994; Stefan 1998).
Chapter 6—Hodges

128

Table 6.3—Causes of death for hares near Kluane Lake, Yukon, 1988 through 1996. Years are counted from 1 April through

31 March. Values are percentages of the deaths of radiocollared juvenile and adult hares for which the cause was

identifiable (and non-human caused) attributable to each mortality source. The mammalian, avian, and predation

categories include kills by marten, weasels, wolves, eagles, hawk-owls, Harlan’s hawks, and kills for which predation

was certain but the predator species could not be identified. Non-predation deaths are hares that died of starvation,

injury, or some other non-predation cause. Data are from C. J. Krebs, unpublished, and Hodges et al., in press.

1988-89 1989-90 1990-91 1991-92 1992-93 1993-94 1994-95 1995-96

increase peak decline decline decline low low increase

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 

Coyote 20 27 6 51 18 57 48 26

Lynx 0 14 13 17 25 21 7 17

Goshawk 13 14 19 5 14 7 10 14

Great horned owl 0 5 15 12 11 0 2 6

Mammalian 7 0 2 0 11 0 10 14

Avian 20 5 22 4 4 7 5 6

Predation 13 23 9 11 18 7 19 14

Non-predation 27 14 15 0 0 0 0 3

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 

% predation 73 86 85 100 100 100 100 97

n dead 15 22 54 107 28 14 42 35

Table 6.4—Snowshoe hare mortality data from 1978-1988, Kluane Lake, Yukon. Predator species were not identified for hare

kills. Winter (November-April) 1986-1987 and summer (May-October) 1987-1988 data are from Krebs et al. 1992.

The remaining data are from Trostel et al. 1987 (winter, December-May; summer, June-November). Data were

recalculated to exclude hares for which the cause of death was unidentifiable. Values are the percentage of hares

dead of each cause.

1978 1979 1980 1981 1984 1985 1987 1988

Summer increase increase peak peak low low increase increase

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 

Mammalian 14 0 23 20 13 0 50 19

Avian 29 33 11 12 38 50 13 16

Predation 57 50 54 64 25 50 13 53

Non-predation 0 17 11 4 25 0 25 13

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 

% predation 100 83 89 96 75 100 75 87

n dead 7 6 35 25 8 6 8 32

1978 1979 1980 1981 1984 1985 1986 1987

Winter increase increase peak peak low low increase increase

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Percent - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 

Mammalian 8 7 26 17 47 45 60 47

Avian 15 20 9 10 0 18 40 27

Predation 62 40 55 40 33 27 0 13

Non-predation 15 33 9 33 20 9 0 13

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - 

% predation 85 67 91 67 80 91 100 87

n dead 13 30 53 30 15 11 5 15
129

Hodges—Chapter 6

Hare survival rates have been measured from either trapping or radiotelemetry data. The trapping data yields less reliable estimates (Boutin and

Krebs 1986). This method typically underestimates survival rates because

hares are hard to trap (Trapp 1962; Boulanger 1993; Sullivan 1994) and have

variable and sometimes high dispersal rates (Boutin et al. 1985; O’Donoghue

and Bergman 1992; Gillis 1997; Hodges 1998). Survival estimates from

trapping may also be biased by different amounts through the cycle, especially when comparing adult to juvenile survival or when estimating seasonal survival. These biases occur because dispersal and trapability vary

seasonally, cyclically, and with age (Boutin et al. 1985, 1986; Krebs et al.

1986b; Boulanger 1993; Hodges 1998).

Snowshoe hare survival estimates from trapping suggest that survival is

higher in the increase and peak phases than in the decline and low phases

(Fig. 6.2a,b) (Krebs et al. 1986b; see also Keith and Windberg 1978). These

data indicate that juvenile hares have lower survival than adults, and that

whereas adult hares have lower overwinter survival than summer survival,

juveniles may have lower survival during the summer. Snowshoe hare

survival data from radiotelemetry only partially confirm these patterns (Fig.

6.3) (Krebs et al. 1995; Hodges et al., in press). Adult survival is indeed lower

in the decline phase than at other times, but survival in the low phase is not

noticeably different than survival in the increase and peak phases (Hodges

et al. 1999). The survival estimates from radiotelemetry are much higher and

more biologically reasonable; positive growth rates essentially cannot occur

when 30-day survival is lower than 0.90 (corresponding to 25% survival

through the year) (Hodges et al., in press), and the estimates from trapping

therefore do not come close to an accurate estimation. Furthermore, even

radiotelemetry estimates may be biased low (Haydon et al. 1999; C. J. Krebs

and W. Hochachka, unpublished).

Survival of leverets to weaning is higher in the increase phase than in the

decline phase (Stefan 1998). Post-weaning juvenile survival seems to depend

on the litter group: in one year of an increase phase, juveniles in litters one

and two survived as well as adults, whereas juveniles from litters three and

four fared much worse (Gillis 1997, 1998). In this instance, most of the deaths

occurred in the fall, when hares from later litters were simultaneously

growing, changing coat color, and switching from forbs to woody browse.

Snowshoe hare survival rates and causes of death are typically seasonal

(Tables 6.3 and 6.4; Fig. 6.2) (Gillis 1998; Hodges et al., in press). Of the adult

hares killed by lynx during a cycle in Yukon, 80% were killed between

November and March (Hodges et al., in press). Most coyote predation

occurred in October and November, and non-predation deaths occurred

most often in late winter.
Chapter 6—Hodges

130

0.5

0.6

0.7

0.8

0.9

1.0

1977

low

1978

increase

1979 1980

peak

1981 1982

decline

1983

30-day mean survival value

summer

autumn

winter

low

Figure 6.2—Snowshoe hare survival in Yukon, indexed by trapping.

These data are mean survival values (2A) from four control areas,

calculated from Jolly-Seber estimates using data in Krebs et al. 1986b.

For adults, summer is April-September and winter is October-March;

juvenile survival (2B) is broken into May-September (summer), OctoberDecember (autumn), and January-March (winter).

0.5

0.6

0.7

0.8

0.9

1.0

1977

low

1978

increase

1979 1980

peak

1981 1982

decline

1983 1984

low

30-day mean survival value

summer

winter

30 day survival 30 day survival

A.

B.
131

Hodges—Chapter 6

There are anecdotal reports of massive overwinter die-offs, typically

during the winter following peak fall densities (Severaid 1942; Keith 1963;

C. Silver, unpublished; E. Hofer, personal communication; D. Henry, personal communication). Unfortunately, these reports are non-numeric, but

they suggest that starvation or deaths due to disease are prevalent during

that initial winter of decline. In some cases, dying hares had infections, some

of which were due to Staphylococcus aureus (MacLulich 1937). There are hints

that these die-offs occur following particularly high cyclic peaks. If such a

pattern does exist, these cyclic declines may not be initiated by predation.

In addition to the cyclic patterns of survival, which are largely due to the

numerical and functional responses of predators (Keith et al. 1977; Royama

1992; O’Donoghue et al. 1997, 1998), several other factors have been considered for their effects on the survival of hares (Table 6.5). The data on the effect

of habitat type on hare survival are equivocal. In several studies, no effect of

habitat on hare survival has been detected (Keith and Bloomer 1993; Cox

et al. 1997), but other studies have observed lower survival in more open

habitat types (Dolbeer and Clark 1975; Sievert and Keith 1985). Small patch

size is associated with reduced survival in Wisconsin (Keith et al. 1993).

Avian predators kill hares in open areas more often than expected from the

distribution of habitat types (Table 6.5) (Rohner and Krebs 1996; Cox et al.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

88-89

increase

89-90

peak

90-91 91-92

decline

92-93 93-94

low

94-95 95-96

increase

96-97

30-day mean survival value

adults

litter1

litter2

litter3

Figure 6.3—Radiotelemetry estimates of snowshoe hare survival in

Yukon. Adult 30-day survival is based on the full year, whereas leveret

survival is from birth to 30 days. The data are from Stefan 1998 and

Hodges et al., in press. 30 day survival
Chapter 6—Hodges

132

Table 6.5—Correlates of snowshoe hare mortality. The following studies examined snowshoe hare survival or causes of death

with respect to an individual factor to test whether the factor affected hare survival.

Factor and test Effect of factor Location Reference

Habitat

Deciduous vs. No statistical effect on survival; potentially lower Wisconsin Keith & Bloomer 1993

coniferous forest survival in deciduous habitat in Nov.-Dec.

Percent of hares killed by lynx in No effect relative to habitat use by lynx Yukon Murray et al. 1994

4 densities of spruce, deciduous,

and shrub habitats

Percent of hares killed by coyotes No effect relative to habitat use by coyotes in 2 yr;Yukon Murray et al. 1994

in 4 densities of spruce, deciduous, in 1 yr, more kills than expected in dense spruce

and shrub habitats

Percent of hare kills in closed More kills in shrub habitats with low canopy Yukon Hik 1994, 1995

spruce, open spruce, and shrub cover relative to availability

habitats

Percent hares killed by owls in More owl kills in open habitats relative to availability Yukon Rohner & Krebs 1996

5 densities of spruce

Lynx hunting success in 4 No effect Yukon Murray et al. 1995

densities of spruce, deciduous, (see also Murray et al. 1994)

and shrub habitats (kills/chase)

Coyote hunting success in 4 More successful in dense spruce than in Yukon Murray et al. 1995

densities of spruce, deciduous, open spruce (see also Murray et al. 1994)

and shrub habitats (kills/chase)

Dense vs. sparse understory cover Lower survival in areas with low understory cover Wisconsin Sievert & Keith 1985

Patch size (7 areas, 5-28 ha) Lower survival in smaller patches Wisconsin Keith et al. 1993

Microhabitat: ≥2 brush piles/ No effect on hare survival rates Wisconsin Cox et al. 1997

ha added to sites

Vertical foliage density Coyote kill sites similar to habitat availability;Wisconsin Cox et al. 1997

raptor kill sites had lower foliage density

Food addition

Ad lib. Rabbit Chow added No effect on post-weaning juvenile survival Yukon Gillis 1997

year-round to 36 ha areas

Ad lib. Rabbit Chow added No effect on leveret or adult survival Yukon O’Donoghue 1994;

year-round to 36 ha areas Hodges et al., in press

Ad lib. Rabbit Chow added Survival higher in increase & peak, Yukon Krebs et al. 1986b

year-round to 9 ha areas but lower in decline

Downed spruce trees added No effect on survival Yukon Krebs et al. 1986a

to a 9 ha area

Ad lib. Rabbit Chow added to No effect in 3 time periods; higher survival Manitoba Murray et al. 1997

25 ha areas over winter of fed hares in 1 time period

2.9-5.8 ha pens stocked Higher overwinter survival in pens Alberta Vaughan & Keith 1981

with hares; 4/8 had food added; with food added

avian predators had access

Reproductive synchrony

Days away from mean Leverets near mean survived better Yukon O’Donoghue & Boutin 1995

parturition date

Parasite load

Hares given Ivermectin (anti- No effect on survival in 3 time periods; higher Manitoba Murray et al. 1997

nematode) vs. control hares survival of parasite-reduced hares in 1 time period

(con.)
133

Hodges—Chapter 6

Hares given Ivermectin & Droncit No effect on survival Wisconsin Bloomer et al. 1995

(anti-cestode) vs. control hares

Hares given Ivermectin No effect on survival Yukon Sovell 1993

vs. control hares

Other hares

2.9-5.8 ha pens stocked with Survival lower at higher densities Alberta Vaughan & Keith 1981

hares; 4/8 had food added;

avian predators had access

Adults and 1st litter juveniles Removal of adults improved juvenile Yukon Boutin 1984a

removed from 9 ha grids survival in summer & fall

Body condition

Condition and foot size smaller Lower survival of poor condition Wisconsin Sievert & Keith 1985

than mean for population and smaller hares

Bone marrow of hares killed Owl killed hares were in better Yukon Rohner & Krebs 1996

by owls vs. shot hares condition

Age

2.9-5.8 ha pens stocked with Juveniles survived less well than adults Alberta Vaughan & Keith 1981

hares; 4/8 had food added;

avian predators had access

% of the hares killed by owls Owls preferred juvenile hares over adults Yukon Rohner & Krebs 1996

in each age class relative to age structure in population

Season

May-August, Sept-Dec, No effect of season on survival Yukon Hodges 1998

Jan-April in low phase

April-September, Adult survival higher in summer Yukon Krebs et al. 1986b

October-March than in winter

Table 6.5—Con.

Factor and test Effect of factor Location Reference

1997; Hodges 1998). Coyotes and lynx have kill rates comparable to the

amount of time they spend in each habitat (Murray et al. 1994; O’Donoghue

1997), and their hunting success rates may vary with cover type (Murray et al.

1995). These predators select habitats, but it is unclear whether they select

habitats that have the highest prey densities (Ward and Krebs 1985; Theberge

and Wedeles 1989; Koehler 1990a; Murray et al. 1994; Poole et al. 1996) or

habitats that are easier for them to traverse or hunt in (Murray and Boutin

1991; Murray et al. 1995; O’Donoghue 1997). Although these analyses suggest

that hare survival may vary among habitat types, the definitive test for hares

is per capita survival in each habitat. Hare survival in each habitat depends

on hare density, predator presence, and the hunting success of predators

within each habitat. Evaluating these parameters simultaneously will address the question of per capita hare survival as a function of habitat type.
Chapter 6—Hodges

134

The effect of food supply on hare survival has been studied by adding

supplemental food to areas and comparing hare survival on these areas to

survival of hares on non-supplemented areas (Table 6.5). Relative to control

populations, hare populations on food-supplemented sites have shown

reduced survival (Krebs et al. 1986b; Hodges et al., in press), similar survival

(Krebs et al. 1986a; O’Donoghue 1994; Gillis 1998; Hodges et al., in press),

and increased survival (Vaughan and Keith 1981; Krebs et al. 1986b; Murray

et al. 1997). The potential effects of food supply on survival are two-fold: the

distribution of food affects feeding locations and hare availability to predators, while the quality and abundance of the food affect physiology and

starvation. The effects of food supply on hare survival may therefore depend

upon the predation pressure. Starvation deaths mainly occur during and just

after peak densities (Boutin et al. 1986; Keith 1990; Hodges et al., in press),

which corresponds to the time when there is the least browse available

(Smith et al. 1988; Keith 1990), but it is unclear whether starvation deaths are

compensatory or additive to predation deaths. If the distribution of food

forces hares into habitats that are riskier (as argued by Wolff 1980, 1981; Hik

1994, 1995), survival rates could be reduced, but there is a lack of consensus

on the safety of various habitats for hares.

Snowshoe hare mortality patterns are: (1) Most hares of all ages are killed

by predators, predominantly coyotes, goshawks, lynx, and great horned

owls. (2) Starvation is most prevalent during high densities and into the

decline phase. Anecdotal evidence of die-offs indicate that some declines

involve more non-predation deaths than others; these die-offs may be linked

to especially high cyclic peaks. (3) Survival is lowest during the decline phase

and is typically lower in winter than in summer. Mortality rates are highest

for leverets, intermediate for juveniles, and lowest for adults. Post-weaning

juveniles from early litters may survive as well as adults. (4) Predators’

hunting patterns and hunting success vary with habitat type, but few if any

studies have shown clearly that per capita survival of hares varies among

habitat types.

Dispersal

Snowshoe hares are known to disperse for distances up to 20 km (O’Farrell

1965; Keith et al. 1993; Gillis 1997; Hodges 1998). Assuming a home range

size of 10 ha, a hare that relocated to an adjacent area would have to travel

only 350 to 400 m from the center of the original range. This definition is

probably inadequate because both juvenile and adult hares have been

observed traveling >500 m a night but later returning to their home ranges.

These forays away from home ranges last anywhere from overnight up to
135

Hodges—Chapter 6

four to five weeks. It is unknown whether these trips are for mating, are

precursors to dispersal, or are for some other purpose (O’Donoghue and

Bergman 1992; Chu 1996; Gillis 1997; Hodges 1998). Given this range of types

of long-distance movements, defining dispersal for hares is problematic.

Estimates of hare dispersal rates (movement greater than a given distance,

or movement into trapping and/or removal grids) suggest that there may

not be much difference in dispersal rate through the cycle (Table 6.6).

Although immigration indices are biased because they may sample animals

that were present but previously untrapped and because removal grids may

attract animals (Dobson 1981; Boutin et al. 1985; Koenig et al. 1996), neither

capture-recapture data nor the more reliable radiotelemetry data show a

clear cyclic pattern in dispersal. Snowshoe hares have no clear season nor age

of dispersal. The youngest recorded dispersers were 31 and 32 days old

(respectively, Gillis 1997; O’Donoghue and Bergman 1992), and adults as old

as three and four years have also dispersed (K. E. Hodges, unpublished).

Both juveniles and adults disperse throughout the year, and there does not

appear to be a sex bias in dispersal (Windberg and Keith 1976; Boutin 1979;

Boutin et al. 1985; Keith et al. 1984, 1993; Hodges 1998). Hares that disperse

appear to survive as well as hares that remain resident (Boutin 1984a; Keith

1990; Gillis 1997), but in an experiment transplanting hares to simulate

dispersal, survival was lower for the first week following transplantation

(Sievert and Keith 1985).

Table 6.6—Indices of dispersal rates of snowshoe hares. The trapping data may include animals that were resident but

previously untrapped. The radiotelemetry data include animals that moved more than two home-range diameters

and animals that died outside their observed home ranges.

Location Method Low Increase Peak Decline Reference

Alberta Net ingressa 0-21 0-37 0-35 0-41 Keith & Windberg 1978

(% of hares trapped new at

time t & present at t + 1)

Yukon % of hares new in 52 40 42 40 Hodges et al., in press

spring population

Yukon % of radiocollared —b 4.0 2.8 2.7 Boutin et al. 1985

hares dispersing

Yukon % of radiocollared 4.7 (m);Hodges 1998

hares dispersing 8.4 (f)

Yukon % of radiocollared post- —b 50 —b —b Gillis 1997

weaning juveniles dispersing

a

Ranges are for multiple years within each phase.

b

No data.
Chapter 6—Hodges

136

The proximate causes of hare dispersal are unknown, but several potential

correlates have been examined. Keith et al. (1993) found little effect of habitat

patch size on dispersal rates. Food addition treatments tend to attract

immigrants, but there is no indication that hares on control areas disperse at

a greater rate than do hares on food addition areas (Boutin 1984b; Hodges et

al., in press). Hares that disperse may be lighter than hares that do not

disperse (Windberg and Keith 1976; Boutin et al. 1985). That pattern could

arise due to sampling (i.e., if juveniles and adults are not readily distinguished morphologically and more juveniles disperse), or it could indicate

that lighter hares move to find better food resources or to avoid aggressive

encounters (see also Graf 1985; Sinclair 1986; Ferron 1993). Settling rates of

dispersing hares are higher when residents are few or have been removed,

which could be due to aggression or through hares’ assessment of resource

availability (Keith and Surrendi 1971; Windberg and Keith 1976; Boutin

1984a).

Snowshoe Hare Behavior

Habitat Use Patterns

Because snowshoe hares eat conifers, they have been studied by foresters

to minimize hare damage to naturally regenerating stands or plantations

(Aldous and Aldous 1944; Cook and Robeson 1945; Borrecco 1976, unpublished; Radvanyi 1987, unpublished). Other studies have considered how to

manage for snowshoe hares as a game species or as food for forest carnivores

(Brocke 1975; Carreker 1985, unpublished; Thompson 1988; Koehler and

Brittell 1990). These studies often have not considered the availability of

different habitat types, thus making it impossible to determine hare habitat

selection.

Most studies of hare habitat use have used fecal pellet plots, but some have

used numbers per plot and others have used presence/absence per plot; the

bias in the latter method may depend on the phase of the cycle. Additionally,

hares excrete their pellets while they are active (Hodges 1998), so fecal pellet

plots do not sample the resting habitats of hares, even though hares may

spend approximately one-third of their time resting (Keith 1964; Hodges

1998). Other studies have used track transects and live trapping as indices of

hares’ habitat use patterns. Track transects assume that distance traveled is

correlated with time spent, which may not be true if hares are traveling

through certain habitats and spending time eating (and not creating tracks)

in other habitats. Trapping may create a bias by attracting hares to baits. The

three methods describe similar patterns of habitat use by hares (Litvaitis

et al. 1985a), but the numeric estimates vary with the technique used.
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Hodges—Chapter 6

Radiotelemetry may allow a more accurate estimation of hares’ habitat use

patterns, because it samples locations of active and inactive hares. However,

triangulation does not allow fine-scale analysis of habitat use and walking

to find hares visually may be slightly biased by startling hares into particular

types of habitat (but see Hodges 1998).

Nonetheless, a fairly consistent picture of hare habitat use emerges from

the various techniques (Table 6.7). Snowshoe hares typically use coniferous

forests and often use areas with dense understory cover (Wolff 1980; Orr and

Dodds 1982; Parker 1984, 1986; Thompson et al. 1989; Hik 1994; St-Georges

et al. 1995). Hares’ use of different stand types appears to be based primarily

on the cover afforded by the stand, which varies with species composition

and age, and secondarily on the palatability of the species present in the

stand (Wolff 1980; Hik 1994). Hares essentially avoid clear-cuts, young

stands of regrowth, and open areas. Hares also are more likely to use

Table 6.7—Snowshoe hares’ use of regenerating forests. < and > indicate significance of p < 0.05.

Location Measure Species Results Reference

Stand age

Ontario Track transects Picea spp. Use of 20 and 30 yr old stands >10 yr old & Thompson et al. 1989;

Betula papyrifera uncut stands > clearcuts and stands younger Thompson 1988

Populus tremuloides than 5 yr

Abies balsamea

New Brunswick Pellet plots Picea mariana Jack pine: use in 8 yr old stands > 13 yr old Parker 1986

Browsed twigs Pinus banksiana Black spruce: use in 13 yr old stands > 8 yr old

Pinus resinosa

New Brunswick Live-trapping Picea spp. Use of 10-17 yr old stands >uncut Parker 1984

Pellet plots stands and stands younger than 10 yr

Newfoundland Track transects Abies balsamea Use of 40 yr stands >60 yr stands Thompson & Curran 1995

and uncut

Species

New Brunswick Pellet plots Picea mariana Use of jack pine >black spruce >red pine Parker 1986

Browsed twigs Pinus banksiana (8 yr-old stands)

Pinus resinosa Use of black spruce >jack pine

(13 yr-old stands)

Stand density

Nova Scotia Damage to trees Abies balsamea Use of dense stand (~32,000 stems/ha) Lloyd-Smith & Piene 1981,

>use of open stand (7,000 stems/ha) unpublished

British Columbia Live-trapping Pinus contorta More hares caught & more trees Sullivan & Sullivan 1983;

Damage to trees damaged in heavily stocked stands Sullivan & Sullivan 1988

(regressions, p < 0.05 for both)

British Columbia % of trees damaged Pinus contorta Higher % damaged and more Sullivan & Sullivan 1982a,b

Number of wounds wounds/tree with increasing stocking

density (regressions p < 0.05 for both)
Chapter 6—Hodges

138

regrowing stands with dense understory cover than uncut or even-aged

stands with little understory cover (Monthey 1986; Thompson 1988; Thompson et al. 1989; Koehler 1990a,b). Conroy et al. (1979) suggested that habitat

interspersion increased hares use of areas. Studies that have compared the

distribution of hares to the availability of the various habitat types have

found that hares actively select habitats with dense cover and avoid open

habitats (O’Donoghue 1983; Litvaitis et al. 1985b; Hik 1994; St-Georges et al.

1995; Hodges 1998).

Several other factors may influence habitat use by hares. Hares may be

more likely to use deciduous cover in summer than in winter because the

presence of leaves helps to protect them from detection (Wolff 1980;

O’Donoghue 1983; Litvaitis et al. 1985b). Similarly, hares are more likely to

use areas of sparse cover when it is dark and moonless (Gilbert and Boutin

1991). Hares appear to use roughly the same habitats when active as when

resting, although resting hares often use denser microhabitats (e.g., brushpiles, deadfall) (Ferron and Ouellet 1992; Cox et al. 1997; Hodges 1998). A few

studies have found limited differences in habitat use between the sexes

(Litvaitis 1990; Hik 1994). Several authors have suggested that juveniles use

more open habitats than adults do (Dolbeer and Clark 1975; Boutin 1984a).

This pattern could result from social interactions because juveniles are

subordinate to adults (Graf 1985; Graf and Sinclair 1987).

Several authors have suggested that the densest habitats provide hares

with refuges that protect them from predators during the low phase (leading

to relatively dense pockets of hares) and that hares then disperse into more

open habitats as their densities increase (Keith 1966; Wolff 1980, 1981; Hik

1994, 1995). The spatial scale of this phenomenon has not been well articulated, and studies of multi-annual patterns of habitat use have typically

focused on small scale habitat shifts (i.e., m2

 rather than ha or km2). That

approach could be problematic if refugia are at a larger scale such as the

patchiness that results from fires (Fox 1978; Finerty 1980).

The current evidence about refugia is equivocal. Several studies over three

to five years have shown shifts in hare habitat use, typically with hares using

more dense habitats as the population moves from the peak into decline

years (Keith 1966; Wolff 1980; Hik 1994; Mowat et al. 1996). Two longer

studies, however, although showing interannual variation, did not show

regular cyclic patterns in hare habitat use (Fuller and Heisey 1986; Koonz

1988, unpublished). In Manitoba, very different proportions of hares were

caught in each of four habitats through 16 years (Fig. 6.4) (Koonz 1988,

unpublished), but neither the two low phases nor the two decline phases

showed the same pattern of hare habitat use. Furthermore, the refugium

hypothesis predicts that open habitats will not be used when hare densities
139

Hodges—Chapter 6

are low, but several studies have shown that hares do use open habitats

during population lows (Fuller and Heisey 1986; Hodges 1998). The refugium hypothesis also suggests that hare habitat shifts arise either through

predation on hares in open habitats (Keith 1966) or through behavioral shifts

by the hares (Wolff 1980). Yet experimental reduction of predation (and

consequently predation risk) did not lead to differential habitat use or

selection by hares during the low phase (Hodges 1998).

Only a few studies have explicitly considered hare demography within

different habitat types or fragments of habitat. Hare survival may be higher

in coniferous than in deciduous cover, especially in winter when deciduous

trees lose their leaves (Keith and Bloomer 1993). Similarly, hares may have

lower survival in habitats with little understory cover (Sievert and Keith

1985; Sullivan and Moses 1986), but spraying herbicides to reduce the cover

of shrubs and ground vegetation and to encourage coniferous growth does

not appear to affect hare densities, survival, or reproduction (Sullivan 1994,

1996). In Alberta, hares in fragmented woodlots displayed a numeric decline

of reduced amplitude and had slightly higher total annual natalities than

hares in nearby contiguous forest in two of four years, but both adult and

juvenile survival showed no consistent differences between the fragmented

0

10

20

30

40

50

60

70

80

90

100

1971

P

72

D

73 74

L

75 76 77

IN

78 79 80

P

81

D

82 83 84 85

L

86 1987

% of trapped hares

Mature jack pine

Mature black spruce

Immature jack pine

Immature black spruce

Year

Figure 6.4—Snowshoe hare habitat use through the cycle. Koonz

(1988 unpublished) trapped four grids in Manitoba, one in each habitat

type; each grid was four ha. The y-axis gives the percentage of hares

trapped in each habitat in each year, P = peak, D = decline, L = low, IN

= increase.
Chapter 6—Hodges

140

and non-fragmented areas (Windberg and Keith 1978). In another study,

Keith et al. (1993) examined demography in fragments of different sizes (5 to

28 ha); hare density and reproduction were unrelated to patch size, whereas

survival was lower on small fragments. In all of these studies, predation was

the main cause of death.

In summary: (1) Hares’ habitat use is linked to dense understory cover

rather than to canopy closure. (2) Hares appear to select habitats for cover

rather than for food, but cover and food often covary. (3) Predator abundance does not appear to affect the habitat selection patterns of hares.

(4) There is no clear shift of habitat use or selection through the cycle, counter

to the suggestion that hares may concentrate in refugia during the low phase.

Determining the appropriate scale for measuring refugia would help to

substantiate this conclusion. (5) There is limited evidence to suggest that

hares’ survival and reproduction vary among different habitats, but the

evidence is so patchy that this idea needs corroboration and further testing.

Diets and Food Limitation

Snowshoe hares eat a variety of coniferous and deciduous woody plants

through the winter (Table 6.8) (see also Chapter 7). Regional studies have

determined preferences of hares for certain plant species (Bryant and Kuropat

1980; Parker 1984; Bergeron and Tardif 1988; Smith et al. 1988; Hodges 1998),

but because hares are distributed across the continent, their preferences vary

with the local plant community. Studies on the diet selection of snowshoe

hares indicate that hares choose species and twig sizes by responding to

some combination of the nutritive and defensive chemistry of the twigs.

Protein, fibre, secondary compounds, digestibility, and specific nutrients

have all been suggested as arbiters of choice, and hares may be able to

balance negative and positive attributes of the various food plants (Bryant

and Kuropat 1980; Bryant 1981a,b; Belovsky 1984; Fox and Bryant 1984;

Sinclair and Smith 1984b; Reichardt et al. 1984; Schmitz et al. 1992; Rodgers

and Sinclair 1997; Hodges 1998).

Snowshoe hares survive on low-protein browse by eating a lot of it,

passing it through the digestive system quickly, excreting fibrous pellets,

and reingesting soft pellets to extract additional protein and other nutrients

(Cheeke 1983, 1987; Sinclair and Smith 1984a). A corollary to this strategy is

that hares tend to eat the same amount of food daily (Holter et al. 1974; Pease

et al. 1979; Sinclair et al. 1982), and reductions in dietary energy or digestibility therefore lead to mass loss (Rodgers and Sinclair 1997). Additionally,

hares have small fat reserves that are capable of maintaining them for only

four to six days without eating (Whittaker and Thomas 1983), so mass loss

occurs soon after hares start eating inadequate diets. Hares appear to need
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Hodges—Chapter 6

Table 6.8—Diet of snowshoe hares and diameters of browsed twigs through the population cycle.

Index Location Species Low Increase Peak Decline Reference

Mean diameter (mm) of Yukon Salix glauca 2.4 2.0-2.7 3.3-3.6 1.5-2.8 Smith et al. 1988

browsed twigsa Betula glandulosa 1.7-2.4 1.8-2.1 2.3-2.5 1.7

Picea glauca 2.1 2.2 1.8-2.9 2.1

Mean diameter (mm) of Yukon Salix glauca 2.0-3.5 Hodges 1998

browsed twigsa Betula glandulosa 2.0-2.2

Picea glauca 2.6-3.7

Mean diameter (mm) of Alaska Shrubs, mainly yr 1: 2.7-4.8 yr 1: 2.7-3.2 — yr 1: 8.6-13.6 Wolff 1980

browsed twigsb Alnus crispa, Salix yr 2: 2.7-3.3 yr 2: 6.2-11.9

spp., Betula spp. yr 3: 2.6-7.5

% surveyed twigs that Alaska Shrubs, mainly yr 1: 0-99;— — yr 1: 100 Wolff 1980

were browsed over- Alnus crispa, Salix 7/11 sites 0-4 yr 2: 91-100

winter on 11 sitesb spp., Betula spp. yr 2: 0-50;yr 3: 3-99

7/11 sites 0-3

% of tagged twigs eaten Yukon Betula glandulosa — 7-36 71-82 4 Smith et al. 1988

by hares overwintera Salix glauca 10-24 27 2

Picea glauca 4-21 8-13 3

Shepherdia canadensis 5-17 23-26 1

% of trees with damagea British Pinus contorta 35 57-69 25-54 Sullivan & Sullivan 1988

Columbia

aRanges are for years within each phase. bRanges are for sites within each year; yr 1, yr 2, yr 3 refer to the first, second, and third year within each phase.
Chapter 6—Hodges

142

about 300 g of browse daily, and are better able to maintain their mass on 300 g

of small rather than large twigs (Pease et al. 1979). Diets in which the mean

twig diameter is >3 mm lead to mass loss, while diets composed of twigs with

a mean diameter ≤ 3 mm are thought to be sufficient for hares to maintain

their mass (Pease et al. 1979).

Despite this apparent threshold for identifying adequate food for hares,

determining food availability is next to impossible (Sinclair et al. 1982, 1988).

Hares’ dietary composition fluctuates through the cycle (Table 6.8) and

classifying food availability is difficult because twigs that a hare would not

eat in the low phase are readily consumed during the peak phase. Snowshoe

hares can maintain themselves for extended periods of time on sub-optimal

foods (Sinclair et al. 1982) and overwinter mass loss is common (Newson and

de Vos 1964; Keith 1990), so dietary stress is difficult to measure. Another

problem is that hares may not use foods in habitats with high predation risk

(Hik 1994), and many food plants show cyclic changes in secondary compound content, with high levels deterring hares from eating those twigs

(Bryant 1981a; Fox and Bryant 1984; Sinclair et al. 1988). It is therefore

difficult to define food for hares, let alone measure it.

When consistent food indices are applied across a cycle at any one site,

most studies show cyclic fluctuations with food least abundant during the

peak and early decline phases and becoming abundant during the low phase

(Pease et al. 1979; Wolff 1980; Smith et al. 1988; Keith 1990). Some researchers

have used such data coupled with estimates of hares’ dietary needs to infer

absolute food shortage at peak densities (Pease et al. 1979; Keith 1990), while

other researchers have not found absolute food shortage (Smith et al. 1988;

Sinclair et al. 1988). It is difficult to interpret the results of such studies

because of the large error associated with browse estimation and the underlying problem of what food requirements are for hares. A similar difficulty

applies to the question of whether hares might be relatively food limited

during particular phases of the cycle.

An alternative to the food estimation problems has been to examine hares’

dietary intake, physiology, or starvation rates as measures that might

indicate nutritional stress. Hare diets do show cyclic fluctuations, with hares

eating more large twigs during cyclic peaks (Table 6.8). Hares seldom eat

bark at low densities, but will eat it when densities are high; most girdling

of trees in conifer plantations occurs when hare densities are high (Radvanyi

1987, unpublished; Hodges 1998). There are also cyclic changes in hare mass

losses overwinter (Keith and Windberg 1978; Keith 1990), but it is unclear

whether overwinter mass loss is a regular facet of snowshoe hare biology or

a sensitive reflection of food shortage. Neither the dietary shifts nor the mass

loss patterns necessarily indicate food shortage of a magnitude that would
143

Hodges—Chapter 6

affect demography. The strongest indication of potential food shortage is

that starvation rates are higher at high hare densities and into the decline

phase, but starvation deaths typically are a small proportion of total mortality and it is unknown if they are additive to or compensatory with predation

deaths (Tables 6.3 and 6.4) (Keith et al. 1984; Trostel et al. 1987; Keith 1990;

Krebs et al. 1992; Hodges et al., in press).

Food addition experiments circumvent some of these interpretation problems by artificially creating areas of abundant food. These studies have

shown little to no effect of food addition on hare survival, reproduction, or

cyclic dynamics, leading to the conclusion that food shortage is not a

necessary component of cyclic declines (O’Donoghue and Krebs 1992; Stefan

1998; Krebs et al. 1986a,b, 1995; Hodges et al., in press; but see Vaughan and

Keith 1981). It is possible that food addition treatments may attract hares

(Boutin 1984b; Hodges et al., in press), thus leading to higher hare densities;

it is therefore possible that the per capita food supply is still limiting.

Assessing per capita food supply and the effects of food limitation are

difficult for snowshoe hares but overall the following patterns seem to hold:

(1) Hares eat most woody species, selecting smaller twigs and twigs with

fewer chemical defenses. There is a clear cycle in the size of twigs in hare

diets, with the largest twigs eaten during high hare densities. (2) Hares at

peak densities are capable of consuming a large proportion of the available

browse, and hares may girdle trees when densities are high. (3) Food

supplementation experiments have been unable to stop cyclic declines, and

hare survival and reproduction are similar between food-supplemented and

control sites. (4) Absolute food shortage does not appear to occur during hare

cycles, but relative food shortage and changes in food quality may occur. (5)

Starvation deaths do not seem to occur during the low and increase phases

of the cycle, but starvation deaths may reflect either relative or absolute food

shortage.

Movements, Home Ranges, and Activity

Snowshoe hares’ home range sizes cannot be compared directly among

studies because data have been collected differently. Locations have been

obtained from trapping records (O’Farrell 1965; Tompkins and Woehr 1979;

Wolff 1980), flushing hares repeatedly (Keith et al. 1993), triangulating on

radiocollared animals (Boutin 1979, 1984c; Boulanger 1993; Hik 1994), and

walking in to observe radiocollared hares (Ferron and Ouellet 1992; Allcock

1994; Chu 1996; Jekielek 1996; Hodges 1998). Additionally, researchers have

used varying numbers of locations and time periods for estimating home

ranges, the statistical methods of calculating home ranges are not comparable (Worton 1987; Harris et al. 1990), and different software packages may
Chapter 6—Hodges

144

have different algorithms for the “same” statistical method (Lawson and

Rodgers 1997). The following generalizations are therefore based on conclusions derived in each paper rather than on a reappraisal of numeric estimates.

Most home range estimates for snowshoe hares indicate that they use areas

that are five to 10 ha, and often hares are located within a small subset of their

total range (O’Farrell 1965; Wolff 1980; Hodges 1998). Males, but not females,

appear to choose resting spots within a smaller area than the area in which

they feed, but for both sexes there is a high degree of overlap between areas

used for these different activities (Ferron and Ouellet 1992). Hares do not

have territories and overlapping home ranges are common, but they may try

to avoid encountering each other (Adams 1959; Boutin 1980, 1984c).

Female hares have smaller home ranges than males (Bider 1961; Ferron

and Ouellet 1992; Hik 1994; Hodges 1998). Some authors have concluded

that the sexes have similar home range sizes, but typically this conclusion is

based on trapping data (O’Farrell 1965; Tompkins and Woehr 1979; Wolff

1980; see also Keith et al. 1993; Boulanger 1993). However, males appear to

use much more area (assessed by radiotelemetry) than their trapping records

indicate, whereas females are more likely to be trapped throughout their

observed radiotelemetry ranges (Hodges, in press). The equal home range

sizes in the trapping studies are therefore probably the result of a methodological bias that reduces the observed home range size of males.

Snowshoe hares may modify their home range sizes in response to

breeding, food supply, population density, and predators. Females constrict

the areas they use when they have very young litters (Bider 1961; Graf and

Sinclair 1987; O’Donoghue and Bergman 1992; Allcock 1994; Jekielek 1996).

Because mating is usually within 24 hours post-partum and females are

synchronous breeders (O’Donoghue and Boutin 1995), males increase their

movements and the area covered (about 5 fold) around the time when

females are oestrous (Bider 1961; Chu 1996). Hares may have smaller home

ranges at higher densities (Boutin 1984c; Hik 1994), but hares on sites with

supplemental food do not appear to have smaller home ranges than hares on

unsupplemented sites, despite higher densities (Boutin 1984b; Hodges 1998)

and contrary to the typical pattern for other small mammals (Boutin 1990).

Hares in predator exclosures may have smaller home ranges than unprotected hares (Hodges 1998), but Small and Keith (1992) found no differences

in hares’ home range sizes before and after red foxes were introduced to

islands.

Hares are mostly active in twilight, although during summer in high

latitudes they are active in daylight (Keith 1964; Boulanger 1993; Boulanger

and Krebs 1996; Hodges 1998). Movement rates are high in summer, which

may be related to breeding. Winter movement rates are low, possibly to
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Hodges—Chapter 6

minimize exposure to the cold (Hodges 1998). In both winter and summer,

foraging movements do not appear to be related to hare density, and males

have higher movement rates than females (Boulanger 1993; Hik 1994;

Hodges 1998). Hares on food addition sites have movement patterns similar

to hares on control sites, whereas hares protected from predators may

respond by decreasing movements (Hodges 1998).

In summary: (1) Home ranges for hares are not well defined; hares often

make extra-range movements, especially during the breeding season, and

home-range overlap is high among hares. (2) Male hares move more and use

larger areas than do females. (3) Neither food supply nor predator abundance

have clear effects on hares’ movement patterns and home ranges. (4) Hare

density does not appear to have a strong effect on hares’ movements.

Physiological Changes Through the Cycle

Several authors have argued that cyclic changes in hares’ physiology

(parasitic infestation, mass or mass loss, hematology, immunochemistry, fat

reserves) might be partially causal of cyclic reproductive or survival changes

(Keith et al. 1985; Boonstra et al. 1998a). For any of these factors to be causal,

it must demonstrate the appropriate cyclicity and its impact on reproduction

or survival should be of a magnitude comparable to the observed changes in

these parameters.

Hares exhibit cycles in mass, overwinter mass loss, and mass-based

condition indices (Newson and de Vos 1964; Keith and Windberg 1978;

Hodges et al. 2000, in press). Mean spring mass of hares varied by approximately 200 g through the 1990 cycle in Yukon (K. E. Hodges and C. J. Krebs,

unpublished). The lowest average mass was during the low phase and

highest average mass was during the peak and early decline phases (see also

Keith and Windberg 1978; Cary and Keith 1979). Keith and Windberg (1978)

suggested that survival was lower for lower-mass individuals, but their use

of trapping data for this point does not allow them to distinguish among

dispersal, death, and low trapability. Elsewhere, lower-mass individuals

were thought to have higher dispersal rates (Windberg and Keith 1976).

Keith (1990) has suggested that hares with high overwinter mass loss have

reduced reproductive output, but studies in Yukon have failed to find an

impact of mass (or mass corrected for skeletal size) on reproductive output

(Hodges et al. 2000, in press; C. I. Stefan and K. E. Hodges, unpublished).

Bone marrow fat content may be a more sensitive indicator of body

condition, but it can only be ascertained after death. Hares dying of starvation have low marrow fat relative to hares in the rest of the population (Keith

et al. 1984; Murray et al. 1997), and hares killed by predators may have lower
Chapter 6—Hodges

146

marrow fat than hares in the population at large (Keith et al. 1984), but in

some cases their marrow fat content is similar (Murray et al. 1997). Hares

killed by great horned owls in Yukon had a slightly higher marrow fat

content than did hares in the rest of the population (Rohner and Krebs 1996).

Furthermore, food addition does not necessarily lead to higher marrow fat,

despite the presumably better nutrition of hares on food-added sites (Murray

et al. 1998). Other fat indices, such as kidney fat, may be better indicators of

body condition than bone marrow fat content if they respond continuously

to hare body condition rather than having some maximum value as bone

marrow appears to.

Hares that are stressed might have reduced reproduction or survival rates.

Chronic exposure to predators, nutritional limitation, or aggressive interactions potentially may lead to deleterious feedbacks in the hypothalamicpituitary-adrenal system (Feist 1980; Boonstra and Singleton 1993; Boonstra

et al. 1998a). Adrenal hypertrophy could index such stress, but the mass of

adrenals show neither a cyclic pattern nor a clear relationship with hare

density (Windberg and Keith 1976; Höhn and Stelfox 1977; Cary and Keith

1979), although food shortage can lead to lighter adrenals (Vaughan and

Keith 1981). More sensitive examinations of the biochemistry (e.g., free

cortisol levels, leucocyte counts, testosterone levels) indicate that hares are

more stressed during the peak and decline phases than during the low phase

(Dieterich and Feist 1980; Boonstra and Singleton 1993; Boonstra et al. 1998a).

These biochemical responses have yet to be shown to be causally linked to

changes in reproductive output or survival rates of hares.

Snowshoe hares are parasitized by many nematode and cestode species.

Trichuris leporis, Obeliscoides cuniculi, Dirofilaria scapiceps, Trichostrongylus

spp., Nematodirus triangularis, Passalurus nonanulatus, Taenia pisiformis, and

Eimeria spp. can have relatively high infestation rates and/or show cyclic

fluctuations (Erickson 1944; Bookhout 1971; Cary and Keith 1979; Keith et al.

1985; Sovell 1993). Juvenile hares often have heavier parasite infestations

than adults (Maltais and Ouellette 1983; Keith et al. 1985; Keith et al. 1986; but

see Erickson 1944). Theoretically, the presence of a cycle in parasite abundance can enhance the hare population cycle through sublethal effects (Ives

and Murray 1997). Empirically, however, both correlative analyses and

experimental manipulations of parasite load have failed to link parasite

infestation levels and reproductive output (Cary and Keith 1979; Sovell 1993;

Bloomer et al. 1995; Murray et al. 1998) or survival (Sovell 1993; Bloomer

et al. 1995; but see Murray et al. 1997).
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Hodges—Chapter 6

Explanations for the Cycle

Given the variety of physiological and demographic cycles that occur

during the numeric hare cycle, not to mention the plant and predator cycles,

it is no surprise that many explanations exist to explain the hare cycle. There

are two basic tiers of explanation: (1) Describing the regular changes in

reproduction, survival, and dispersal that contribute to the numeric cycle.

(2) Explaining the factors that lead to changes in each of these demographic

parameters. This second class of explanation is broadly divided into trophic

interactions and behavioral and physiological effects.

Most of the numeric change is driven by changes in juvenile survival,

followed by changes in adult survival and leveret survival (Keith 1990; Krebs

1996; Haydon et al. 1999). Adult survival is more important than juvenile

survival during the decline phase, when juvenile survival is so low that small

changes in it have little impact on the dynamics (Haydon et al. 1999).

Changes in reproductive output and dispersal do not have a very large effect

on numeric changes because hares are short-lived and have high fecundity.

The breeding population is therefore determined more by recruitment than

by adult survival (see also Lebreton and Clobert 1991). Because the young

hares have to survive for six to nine months before breeding, their survival

rates have more impact on the population than do their starting numbers.

Explaining the changes in each of the demographic parameters is the next

step of explaining the numeric hare cycle, and it is here that many different

stories are told (for reviews, see Finerty 1980; Keith 1990; Krebs et al. 1992;

Boonstra et al. 1998b). Although hypotheses invoking intrinsic regulation,

hare-plant interactions, or hare-predator interactions have been proposed

(Chitty 1967; Krebs 1978; Finerty 1980; Bryant 1981a; Fox and Bryant 1984;

Trostel et al. 1987), available evidence suggests that hares’ interactions with

both food plants and predators are integral to demographic changes (Keith

1963; Krebs et al. 1992, 1995, 1996; Hodges et al., in press). Keith (1974, 1981,

1990) has proposed that food shortage at peak densities initiates the decline

through an increase in starvation rates, and that the high mortality that

characterizes the decline phase is then largely imposed by predators. Recent

experimental work in the Yukon does not substantiate the argument that

food shortage initiates the decline, but shows instead that the cycle is most

likely due to interactions of food plants, hares, and predators throughout the

cycle (Smith et al. 1988; Sinclair et al. 1988; Krebs et al. 1986b, 1995; Hodges

et al., in press). In Yukon, single factor manipulations of food and predators

increased hare densities but failed to alter either the numeric cycle or the

cyclic changes in survival and natality. However, the simultaneous addition

of food and reduction of predators resulted in a hare population with higher
Chapter 6—Hodges

148

survival, higher annual natality, and higher densities than control populations (Krebs et al. 1995; Hodges et al., in press).

Recent models have attempted to unify behavior, physiology, trophic

interactions, and demographic changes. Hik (1994, 1995) proposed that

hares change habitat types when faced with high predation risk, with safer

habitats also being poorer in food. Under this scenario, the combination of

high predation risk and voluntary dietary restriction cause low survival and

poor reproduction during the decline phase. When risk is reduced and hares

again use better habitats, survival and reproduction rebound (see also Keith

1966; Wolff 1980). Boonstra et al. (1998a) have expanded this model to

suggest that hares also experience physiological stress (that may or may not

be food linked) as a result of high predation risk, and that the stress can

impact reproduction directly and through maternal effects. These models

putatively explain the prolonged low phase of the cycle: hare densities stay

low for several years, even after food plants have regrown and predator

numbers have declined (Smith et al. 1988; Boonstra et al. 1998b; Hodges et al.

1999). If hares affect their nutrition and stress by behavioral changes, or if

they experience maternal effects from mothers who were stressed during the

decline phase, both reproduction and survival could be depressed (Hik 1994;

Boonstra et al. 1998b). Another scenario invokes the sub-lethal impacts of

parasites, suggesting that cyclic changes in parasite infestation rates and

loads impact hare survival and reproduction (Ives and Murray 1997; Murray

et al. 1997). These scenarios are worth testing; at present they are based

mostly on chains of correlation and linking population level analyses

together. To substantiate these arguments, it is critical to examine individual

hares to determine the impacts of predation risk, nutrition, stress, and

parasite load on hare survival and reproduction.

Conclusion

In the north, snowshoe hares undergo regular population cycles of five to

25 fold amplitude. Survival and reproductive changes are responsible for the

numeric changes, but there is uncertainty about the relative impacts of the

factors (food supply, stress, habitats, parasites) affecting these survival and

reproductive changes. Differences in amplitude and duration of the cycle

could possibly be due to variation in hare behavior or habitat characteristics,

if these do affect demography. It would be valuable to develop models that

show how much and what kinds of demographic variation are necessary to

create cycles of different amplitudes and durations. Field studies that can

explain patterns of demographic variation would also be useful.
149

Hodges—Chapter 6

Acknowledgments

I have enjoyed the opportunity to delve into the snowshoe hare, boreal

ecology, and population cycle literatures more thoroughly. I am indebted to

the Lynx Science Team for giving me the opportunity to do so. This chapter

has benefited greatly from discussion with and comments from C. J. Krebs,

A. R. E. Sinclair, J. L. Ruesink, and G. Koehler. Three anonymous reviewers

offered helpful suggestions. I am indebted to the following people, who have

graciously and generously allowed me access to unpublished data and

observations: T. Bailey, F. I. Doyle, H. Golden, D. Henry, W. Hochachka,

C. J. Krebs, S. Mahoney, M. McNay, C. D. Mitchell, G. Mowat, K. Poole,

P. Seccombe-Hett, C. I. Stefan, L. A. Viereck, and P. C. Adams. T. Karels

provided technical assistance.

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Chapter 6—Hodges

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159

Hodges—Chapter 6

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Chapter 6—Hodges

160

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161

Hodges—Chapter 6

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Chapter 6—Hodges

162
163

Chapter 7

Ecology of Snowshoe

Hares in Southern Boreal

and Montane Forests

Karen E. Hodges, Centre for Biodiversity Research, University of British

Columbia 6270 University Boulevard, Vancouver, BC V6T 1Z4 Canada

Abstract—Snowshoe hares occur in many of the montane and sub-boreal forests of

the continental United States, as well as throughout the boreal forests of Canada and

Alaska. Population dynamics in their southern range were previously thought to

be noncyclic, in contrast to the strong 10-year fluctuation that typifies boreal

populations of snowshoe hares. Time series data and studies of hare demography

indicate that northern and southern populations of hares may instead have similar

population dynamics. Hares in southern areas appear to experience two- to 25-fold

fluctuations in numbers with peaks eight to 11 years apart. Peak and low densities

may be lower in southern areas than in northern ones; in the south, peak densities

are commonly one to two hares/ha, whereas northern hare populations commonly

have peak densities up to four to six hares/ha. Demographically, survival estimates

(30-day) range from approximately 0.65-0.95 in Wisconsin, with lowest survival

occurring as populations decline; these values parallel those of cyclic hares in

Yukon. Annual reproductive output may vary regionally, but interpretation of this

pattern is hindered by noncomparable methodologies.
164

Chapter 7—Hodges

The southern range of snowshoe hares is roughly delineated by the range of

suitable forested habitats. Along the eastern seaboard, hares use spruce/fir and

deciduous forests as far south as Tennessee and the Virginias. Around the Great

Lakes, hares occur throughout the sub-boreal coniferous forests. In the Rockies and

westward, hares mainly use the coniferous forests that extend along the mountains

down into New Mexico and California. Throughout their range, hares are predominantly associated with forests that have a well-developed understory that provides

protection from predation and supplies them with food. Such habitat structure is

common in early seral stages but may also occur in coniferous forests with mature

but relatively open overstories or in eastern deciduous forests.

Introduction

Snowshoe hares occur throughout much of North America and have a

regular 10-year population cycle in the northern part of their range. Dynamics of southern hare populations, in contrast, have been described as cyclic,

cyclic with reduced amplitude, noncyclic but fluctuating, and noncyclic

(Howell 1923; Chitty 1950; Finerty 1980; Bittner and Rongstad 1982; Smith

1983; Keith 1990). During the northern hare cycle, hares have both regular

numeric changes and regular changes in survival, reproduction, and possibly dispersal (Cary and Keith 1979; Bittner and Rongstad 1982; Keith 1990;

Krebs et al. 1995; Hodges et al. in press). The habitats in which hares occur

in northern and southern forests vary in terms of species composition, stand

structure, and amount of disturbance (from fire or from harvest), leading to

speculation that hare dynamics are related to habitat structure and degree of

interspersion of different habitat types (Dolbeer and Clark 1975; Wolff 1980,

1981; Buehler and Keith 1982; Sievert and Keith 1985; Keith 1990).

In this chapter, I therefore examine the demography and numeric patterns

of southern hare populations, describe patterns of habitat use by hares in

southern areas, and discuss the linkages between hare demography and

habitat. Throughout, I compare results from southern areas to patterns in

northern hare populations. I compile the information with explicit reference

to methodology, to ensure that comparisons among regions are made using

comparable data. I ask first whether hares display numeric cycles in the

southern parts of their range. Second, I examine demographic parameters

(reproduction, survival, and dispersal) to see if they show cyclic fluctuations

in southern hare populations. Third, I address the dietary and habitat

associations of snowshoe hares. I conclude with a discussion of the relationship of hare population dynamics to habitats, and whether refugia, habitat

fragmentation, and increases in numbers of facultative (multiple-prey)
165

Hodges—Chapter 7

predators can explain the variation in demographic parameters observed

among hare populations.

Distribution and Population Trends

Hares in “the south” occur in four general areas—through the western

mountains of Washington and Oregon down into California, through the

Rockies into New Mexico, around the Great Lakes, and from the Maritimes

down through the Alleghenies and Appalachians into Virginia and West

Virginia (Bittner and Rongstad 1982; Fies 1993, unpublished; Hoefler and

Duke 1996, unpublished; G. Schmidt, personal communication; J.

Rieffenberger, personal communication) These four areas are biologically

and climactically diverse (Bailey 1997), so there is good reason to expect that

hares might display differing dynamics in each of these regions. With the

exception of the mixed deciduous and coniferous forests that cover the

nonmountainous areas from the Great Lakes eastward through the Maritimes,

most areas containing snowshoe hares in the United States are montane. In

contrast, the boreal forests—where hares display a clear population cycle—

provide a more contiguous and less mountainous swath of hare habitat

(Keith 1990; Bailey 1997).

We have extremely limited knowledge about hares in many of the states

where they occur. Distribution records exist for hares in Maryland, Rhode

Island, New Jersey, Delaware, Virginia, Tennessee, North Carolina, Ohio,

Oregon, California, and New Mexico (Keith 1963; Godin 1977; Bittner and

Rongstad 1982; Nagorsen 1985), but I am not aware of any harvest or other

time series data for these states. The status and distribution of hares in these

states are not well known (Bailey 1971; Godin 1977; Verts and Carraway

1998; G. Schmidt, personal communication), but snowshoe hares are thought

to be extirpated from Ohio (D. Scott, personal communication), and in

Virginia and California snowshoe hares are a species of special management

concern (Handley 1978; Williams 1986, unpublished; Fies 1991; Hoefler and

Duke 1996, unpublished; Brylski et al. 1997).

In areas for which time series exist, it is possible to address the issue of

cyclicity. There are four possibilities for hare population dynamics: cyclic,

like northern populations, which display cycles with amplitudes of five

to 25 and eight to 11 years between peak populations (Chapter 6); reducedamplitude cyclic, demonstrating the eight- to 11-year periodicity but with

amplitudes lower than five-fold; fluctuating, with amplitudes similar to

those in northern populations, but lacking an eight- to 11-year periodicity;

or noncyclic, lacking both high-amplitude fluctuations and the eight- to

11-year periodicity in numeric change.
166

Chapter 7—Hodges

Empirically, applying these definitions requires arbitrary decisions, such

as defining the amplitudes at which cyclic populations become cyclic with

reduced amplitude or fluctuating populations become noncyclic. It is similarly difficult to know what to do with interpeak durations of less than

eight or greater than 11 years, especially in time series recording only two or

three peaks. Because even long time series record only a few potential cycles,

the power to determine differences in amplitude and duration among time

series is low. This difficulty is compounded by the use of indices of abundance (tracks, sightings, harvest records) for which the relationship to actual

hare densities is unknown. Because of these problems, I simply present the

time series and describe the observed amplitude and interpeak durations of

each, but I do not analyze these values statistically (Table 7.1). I consider

peaks to be local maxima separated by at least two years and lows are

similarly local minima. I calculated amplitudes by dividing each peak value

by the subsequent low value, and I present the range of these amplitudes.

Table 7.1—Snowshoe hare population trends in southern parts of their range. Amplitude is rounded to the nearest whole number.

Amplitude was calculated by dividing peaks by subsequent lows. I also present the total amplitude for the entire

series (max/min) because some series show large overall fluctuations. If only amplitude is given, max/min was the

same; if only max/min is given, it was impossible to match peaks and lows. Peak years are given only for series

>5 years long, but peaks for series <10 years long should be regarded with suspicion, as should peak years

that occur at the beginning or end of a study. Most of these rubrics indicate overwinter estimates; for peak year, I

indicate the year that started the winter (e.g., 1990 implies winter 1990-1991).

Years

Survey period Amplitude between

Location (# of years) (max/min) peaks Peak years Reference

Fecal pellet plots (n/plot)a

Montana 1986-1998 (13) 2 7 1990 J. Malloy, unpublished

1997

Utahb 1974-1978 (5) 2 — — Wolfe et al. 1982

Washington 1986-1989 (3) 2c — — Koehler 1990a, 1990b

West Virginia 1942-1953 (12) 10 9 1942 Brooks 1955

1951

Quebec (southern) 1991-1996 (6) 4 — 1991 Ferron et al. 1998

(% plots with pellets)

Minnesota 1969-1984 (16) 3 — 1978 Fuller & Heisey 1986

Live trapping

Minnesota 1932-1942 (11) 15 — 1933 Green & Evans 1940a

Keith 1963

New Brunswick 1967-1970 (4) 7 — — Wood & Munroe 1977

Harvest records

Nova Scotia 1950-1964 (14) 4 9 1951 Dodds & Thurber 1965

 (Long Island) 1960

Nova Scotia 1990-1998 (8) (4) — 1996 M. Boudreau, unpublished

New Brunswick 1984-1990 (7) (40) — 1984 K. Eagle, unpublished (con.)
167

Hodges—Chapter 7

Maine 1955-1983 (29) 2 (4) 7 to 9 1948 C. McLaughlin, unpublished

1957 Keith 1963

1966

1973 (1972)d

1981 (1982)d

New York 1932-1951 (19) 2-6 8 to 13 1932 Keith 1963

1960-1968 (7) (24) 1940 G. Batchelar & A. Jacobson, unpublished

1982-1998 (16) 1950

1963

(no data)

1982

1995

Massachusetts 1958-1986 (15) (12) —e —e J. Cardoza, unpublished

Pennsylvania 1930-1997 (64) 4-12 7 to 11 1931 Diefenbach 1998, unpublished

(48) 1942

1949

1959

 (1967)f

1982

 (1992)f

Connecticut 1923-1955 (32) 2-3 9 to 10 (1933)g Sondrini 1950

(3) 1942 Keith 1963

1952

Ontario (southern, 1931-1943 (13) (17) 9 1933 Hess 1954

 one trapline) 1942

Michigan 1937-1997 (61) 1.5-4 5 to 12 1939 G. Karasek, unpublished

(7) 1949 Keith 1963

 (1954)h

1959

1964

1976

1988

Harvest records

Wisconsin 1931-1997 (57) 3-11 8 to 10 1932 B. Dhuey, unpublished

(30) 1941

1949

1957

(no data)

1978

1988

Minnesota 1941-1997 (56) 2-24 8 to 11 1941 Berg 1998, unpublished

(29) 1952

1960

1971

1980

1991

Colorado 1955-1960 (2) — 1956 Dolbeer 1972a, 1972b

1968-1970 (9)

Washington 1988-1997 (9) (6) — 1988 D. Ware, unpublished

Idaho 1986-1992 (7) (5) — 1988 C. Harris, unpublished

Harvest/area

Quebec 1979-1997 (19) 3-9 7 to 9 1980 R. Lafond, unpublished

(14) 1989 Fortin and Huot 1995, unpublished

(con.)

Table 7.1—(Con.)

Years

Survey period Amplitude between

Location (# of years) (max/min) peaks Peak years Reference
168

Chapter 7—Hodges

The most reliable time series are from live-trapping data or counts of

fecal pellets, because density estimates can be derived from these methods

(Table 7.1). Based on short time series (three to 13 years), fecal pellet

plots have shown density differences of two-fold in Montana, Utah,

and Washington (J. Malloy, unpublished; Wolfe et al. 1982; Koehler

1990a,b), four-fold in southern Quebec (Ferron et al. 1998), and 10-fold in

West Virginia (Brooks 1955). These surveys indicate peak hare densities

of approximately 1-2 hares/ha (see also Table 7.5), which is considerably

Harvest/hunter

Prince Edward Island 1971-1984 2 — 1978 R. Dibblee, unpublished

1993-1997 (19) (4)

Harvest/hunter-day

Utah 1975-1996 (22) 3 (5) 12 1978 D. Mitchell, unpublished

1990

Hare sighting indices

Minnesota 1974-1996 (23) 14-70 9 1980 B. Berg 1998, unpublished

(70)i 1989

Minnesota 1946-1959 (13) (75) — 1950 Marshall 1954

Keith 1963

Michigan (Isle Royale) 1974-1997 (24) 9-27 8 1980 Peterson 1998, unpublished

(38)i 1988

Ontario (Manitoulin Island) 1959-1962 — — 1959 Newson & de Vos 1964

Manitoba (southeastern) 1974-1979 (5) 9 — 1978 Leonard 1980; Raine 1987

Track transectsj

Wisconsin (%) 1977-1998 (21) 2-17 12 1977 Glenzinski & Dhuey 1998, unpublished

(17) 1989

Maine (%) 1994-1997 (4) 2 — — C. McLaughlin, unpublished

Montana (#) 1992-1998 (7) 10 — 1991 D. Dziak, unpublished

Wyoming (#) 1987-1996 (10)k (45)k — — L. Ruggiero, unpublished

a

Densities from pellet plots were calculated using a regression equation derived from hare density information from 1976 to 1996 (C.J. Krebs unpublished):

ln(hares/ha)=0.888962*ln(pellets)-1.203391, corrected for bias by multiplying with 1.57 following Sprugel (1983). Pellets is pellets/0.155m2

. The methodology and

rationale were derived in Krebs et al. (1987), and the current equation simply uses more information. b

This time series is for pellet counts in Douglas-fir stands.

c

Values are based on pellet counts in fall; values for fall 1997 were calculated by summing values for two sampling periods within the year. d

From 1972 through 1983, there were also estimates of numbers of hunters. Harvest per hunter indicates the peak years given in parentheses. e

The years that have data are sporadic, making it impossible to determine peak years.

f

Harvest estimates from 1967-1970 were 6,000, 4,000, 5,000, 5,000; although I’ve given the peak as 1967, it could have been later. From 1982 through 1997, hare

harvests have generally declined, with a higher harvest in 1992 than in the preceding two years or subsequent five years. g

The early peak is not as clear as the others; for several years, high and low values alternated.

h

One method of harvest estimation was used from 1937 to 1953, and another from 1954 forward. Although the 1954 harvest estimate represents a local peak, it is

difficult to interpret because it lies on the cusp of the two methods. i

The amplitudes and max/min ignore one 0 value.

j

Each track transect methodology is somewhat different; I present them in two broad classes: counts of number of tracks (#) and proportions of transect segments

containing any hare tracks (%). k

These numbers were derived from transect J, including only years when the transect was run ≥2 times; the amplitude reflects just maximum/minimum rather than

trying to match a low to its preceding peak.

Table 7.1—(Con.)

Years

Survey period Amplitude between

Location (# of years) (max/min) peaks Peak years Reference
169

Hodges—Chapter 7

lower than observed peak densities of approximately 4-6 and sometimes

higher in northern areas (Chapter 6). The two longest pellet plot time series

showed nine years between peaks in West Virginia (Brooks 1955) and seven

years in Montana (J. Malloy, unpublished). Live-trapping in Minnesota and

New Brunswick have indicated fluctuations of seven- to 15-fold, with peak

densities of approximately 1.6 hares/ha (Green and Evans 1940a; Wood

and Munroe 1977).

Most southern time series for snowshoe hares are harvest data. Harvest

data are unlikely to indicate either amplitude or peak and low density years

accurately. Harvest data provide a true reflection of population dynamics if

and only if the same proportion of hares are caught in each year, which

almost certainly does not occur because of socioeconomic as well as biological reasons. Furthermore, the harvest data we have reflect various survey

techniques (phone and mail surveys, hunter licensing, pelt or carcass sales)

and are often based on a small proportion of the hunters (e.g., 5-10%), hence

calling into question the ability of the data to record the actual harvest.

As an additional complication, several of the harvest time series show an

overall fluctuation of approximately 20-50-fold, but have distinct periods of

low or high average harvest. For example, in Pennsylvania, harvests ranged

between 8,600-26,200 from 1930 to 1935; 550 to 6,000 from 1937 to 1979; and

1,400-21,800 from 1980 to 1997 (Diefenbach 1998, unpublished). The entire

time series has an amplitude of 48, but matching lows to their previous peaks

yields amplitudes of four- to 12-fold. It is difficult to partition that variation

into anthropogenic versus hare demographic changes without additional

information such as area exploited or hunter effort. As an example of the

effect of knowing hunter effort: 22 years of Utah harvest data showed a high

correlation between total hare harvest and hares per hunter (r = 0.87 p <0.05),

but the magnitude of difference over the entire time series for total harvest

was 20-fold whereas for hares per hunter it was only 4.3-fold (D. Mitchell,

unpublished). Furthermore, these two indices showed the same peak year,

but were off by a year for their lows. Harvest data should therefore not be

relied upon for determining the population dynamics of hares. Regular 10-

year cycles are unlikely to arise in the harvest data solely because of

anthropogenic factors, however; so if harvest data show cycles, they probably reflect hare population dynamics even if absolute duration and amplitude cannot be correctly inferred.

Harvest records from New England, southeastern Canada (Quebec eastward through the Maritimes), and the eastern seaboard show amplitudes

ranging from two to 12, with 78% of the interpeak lengths between eight

and 10 years (Table 7.1, Fig. 7.1A-D). These data may be confounded by

programs of stocking hares for hunters, which has occurred in at least

Connecticut, New York, Massachusetts, Pennsylvania, West Virginia, and
170

Chapter 7—Hodges

Figure 7.1—Records of snowshoe hare population trends. All records are

from sources cited in Table 7.1. (A) Hare harvests from the Maritimes and

Maine. (B) Hares per hunter and hares killed per unit area from Prince Edward

Island and Quebec. (C) Hare harvests from New York. (D) Hare harvests from

Massachusetts and Pennsylvania. (E) Hare harvests in the Midwest. (F) Hare

sighting indices in the Midwest. (G) Pellet and track records of hares in the

Midwest. (H) Hare harvests and hares per hunter-day in the western states.

10

0

20

30

40

50

60

70

1960 1970 1980 1990 2000

Hare harvest (10,000s)

Nova Scotia

Maine

New Brunswick

A

10

15

0

5

20

25

30

1960 1970 1980 1990 2000

Hare index

Hares/hunter PEI

Hares/10km2 Quebec

B

New York

0

10

20

30

40

1960 1970 1980 1990 2000

Hare harvest (in 10,000s)

C

0

10,000

20,000

30,000

40,000

50,000

1960 1970 1980 1990 2000

Hare harvest

Massachusetts

Pennsylvania

D
171

Hodges—Chapter 7

Figure 7.1 (Con.)

0

20

40

60

80

100

Hare harvests (in 10,000s)

Wisconsin

Minnesota

Michigan

1960 1970 1980 1990 2000

E Harvests

0

5

10

15

Hares seen per 100 km

Minnesota

Michigan

1960 1970 1980 1990 2000

F Sightings

20

100

0

80

% of surveyed area with hare sign

1960 1970 1980 1990 2000

Pellets Minnesota

Tracks Wisconsin

G Surveys

60

40

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

1960 1970 1980 1990 2000

Hare harvest (ID, WA)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Harvest/hunter-day (UT)

Idaho

Washington

Utah

H
172

Chapter 7—Hodges

Virginia (Brooks 1955; Boyle 1955; Fitzpatrick 1957; Behrend 1960, unpublished; August 1974; Richmond and Chien 1976; Schultz 1980; Brown 1984).

Analyses of these programs indicate that <10% of the stocked hares are

actually killed by hunters (Fitzpatrick 1957; Schultz 1980), but it is unknown

what demographic effects the stocking programs have had.

Around the Great Lakes, harvest data show eight- to 10-year fluctuations of two- to 25-fold amplitude (Table 7.1, Fig. 7.1E-G; see also Keith

1990). These cyclic patterns are confirmed by records of hare sightings in

Minnesota (B. Berg, unpublished) and Michigan (Peterson 1998, unpublished; see also Johnson 1969). Pellet plots in Minnesota (Fuller and Heisey

1986) and tracking surveys in Wisconsin (Glenzinski and Dhuey 1998,

unpublished) show roughly the same pattern of highs and lows as the

harvest data do. Keith (1963, 1990; Buehler and Keith 1982; Sievert and Keith

1985) has argued that hares have become noncyclic in Wisconsin since the

1950s, but the tracking surveys and harvest records are equally suggestive

that the cycles have continued.

Population trends of hares from the Rockies westward are not well

known (Fig. 7.1H). The harvest records from Idaho, Colorado, and

Washington are short compared to the 10-year cycle (i.e., seven to nine

years of records), making it difficult to tell if the harvests have the typical

10-year periodicity (Dolbeer 1972b; D. Ware, unpublished; C. Harris, unpublished). Within those years, the amplitudes of fluctuation are two- to

six-fold. In Utah, harvest per hunter-day had an amplitude of three-fold and

an interpeak duration of 12 years through 22 years of data (D. Mitchell,

unpublished). Pellet plots in Utah, Montana, and Washington show twofold fluctuations in hare density (J. Malloy, unpublished; Wolfe et al. 1982;

Koehler 1990a, b). In Wyoming, track counts showed 45-fold variation

(L. Ruggiero, unpublished), while Montana track counts showed four- to

10-fold variation (D. Dziak, unpublished; Giddings 1998, unpublished).

The existing time series do not show a strong synchrony. For example,

five time series showed a peak in 1988, three in 1989, two in 1990, and two in

1991 (Table 7.1). Throughout the century, there tend to be three- to four-year

clusters of peak densities, typically close to the turn of each decade. There are

occasional time series that miss peaks or show peaks in years that no other

series matches (e.g., New York, which shows a peak in 1995). Southern hare

populations may therefore be genuinely asynchronous or the synchrony

may only be at a scale of three to four years. As another possibility, the

harvest data in particular may be off a year or two relative to the actual hare

densities, which would make detection of synchrony difficult.

There are likely to be differences of opinion about how deviant hare

populations have to be in amplitude and interpeak duration in order to

disqualify them as cyclic or to class them as reduced-amplitude cyclic. In my
173

Hodges—Chapter 7

opinion, the existing evidence is strongly suggestive that southern hare

populations are cyclic—amplitudes in the various indices vary from two to

70, and in the longer time series (>10 years) approximately 75% of interpeak

intervals are between eight and 11 years. At a minimum, these patterns

suggest that studies of hares in southern areas should explicitly address

population dynamics. Additional analyses of the existing time series data

are unlikely to resolve the cyclicity debate because of the methodological

difficulties; we require more time series that are density estimates rather

than harvests or other indices.

Snowshoe Hare Demography

Reproduction

Female snowshoe hares can have up to four litters in a season, with one to

14 young per litter; they breed synchronously, leading to distinct litter

groups (Cary and Keith 1979; O’Donoghue and Boutin 1995; Stefan 1998).

Regionally, there has been some suggestion that hares in southern populations have more but smaller litters than do hares in northern populations,

leading to a lower total annual natality (Rowan and Keith 1956; Keith et al.

1966; Ernest 1974; Keith 1981, 1990). Many of the data used to infer this

latitudinal pattern were derived using Green and Evans’ (1940c) method—

calculating average number of litters from the number of females observed

to be pregnant throughout the summer corrected for days of observable

pregnancy, and calculating mean litter size from all litters combined (often

with uneven sampling effort across litter groups). This method has three

problems: the average number of litters has often been calculated on a multiyear basis thus conflating cyclic phase, and both pregnancy rates and litter

sizes are not calculated independently for each litter group. A much more

reliable approach derives pregnancy rate and litter size estimates for each

litter group separately, and then sums the litter groups for total annual

natality (e.g., Dolbeer and Clark 1975; O’Donoghue and Krebs 1992).

Much of the variation in total annual natality actually seems to be better

explained by cyclic phase than by latitude, especially when methodological

issues are considered. In Figure 7.2, the dark symbols indicate estimates

derived from assessment of each litter group; these show a strong effect of

cyclic phase on hares’ natality. Data collected using Green and Evans’

(1940c) method (open symbols and crosses) do not pick up this cyclic pattern,

except in short-term studies, which are less biased by conflation of years.

Additionally, this method is likely to bias estimated annual natality downward, because first litters are smaller than later litters (Keith 1990; Stefan
174

Chapter 7—Hodges

1998). Thus the smaller and less cyclic annual natalities shown for southern

populations are probably due to methodological biases rather than to a

true latitudinal gradient. The two strongest data sets, from Alberta and

Yukon (symbols with lines) (Cary and Keith 1979; Stefan 1998), offer weak

support to the latitudinal pattern, in that Alberta hares tended to have four

litters whereas Yukon hares had two to four, but larger litter sizes in Yukon

yielded slightly larger total annual natalities in all phases except the

decline. Hares in Alaska show trends similar to those of Yukon hares (Ernest

1974). The largest annual natality is approximately 2.5 times greater than the

lowest for hares in Yukon and Alberta. The southern hare studies that have

calculated annual natality on a per litter basis have been too short to assess

Figure 7.2—Annual reproductive output of snowshoe hares at different phases of the population cycle.

Filled symbols are for natalities analyzed as percent pregnant x mean litter size, summed for each litter

group. Open symbols are for natalities calculated by Green & Evan’s (1940c) method, as mean litter size

(litter groups not distinguished) x average litter number (often calculated from many years of data, with

phase not distinguished). The first method is much more reliable. When a study had more than one year

of data for a phase, annual values were averaged. The number given with each region indicates the

maximum number of litter groups observed in that area; ? indicates that the number of litters was not

specified in the reference. Wisconsin and Michigan data were assigned to cyclic phases based on trend

data from Glenzinski and Dhuey (1998, unpublished) and Karasek (unpublished), while the other

references provided information on the population trends in different years. The unknown cyclicities are

from Montana, Utah, and Colorado. Sources: YK, Stefan 1998, Hodges et al. in press; AB, Keith &

Windberg 1978, Cary & Keith 1979; AK, Ernest 1974; AB 2, Rowan & Keith 1956; ONT, Newson 1964;

WI, Kuvlesky & Keith 1983; NF, Dodds 1965; MN, Green & Evans 1940b; MT, Adams 1959; CO & UT,

Dolbeer & Clark 1975; MI, Bookhout 1965a.

0

2

4

6

8

10

12

14

16

18

20

Low Increase Peak Decline Unknown

Total annual natality (leverets/female)

YK (4)

AB (4)

AK (3)

AB2 (3)

ONT (4)

NF (3?)

MN (3?)

MT (3?)

MI (3?)

WI (4)

CO (3)

UT (3)
175

Hodges—Chapter 7

the range of reproductive values through a cycle (Newson 1964; Dolbeer and

Clark 1975), but three six- to seven-year studies using Green and Evans’

(1940c) method show approximately 1.5-fold fluctuation in annual natality

(Green and Evans 1940c; Bookhout 1965a; Dodds 1965).

The Alberta and Yukon data sets (Cary and Keith 1979; Stefan 1998) also

show that hares consistently have smaller first litters than later litters, and

that first litters have a smaller range of variation through the cycle (approximately 0.5 leverets/litter; Chapter 6). If regional differences in litter size

exist, they may therefore be easier to detect in the first litter than in later

litters, especially if the variation among regions is higher than 0.5 leverets/

litter. Additionally, we currently have more data on first litters than on later

litter groups. For populations that are known to be cyclic, there does appear

to be a latitudinal gradient in the size of the first litter (Fig. 7.3). Within each

phase of the cycle, hares in southern populations have smaller first litters (by

up to approximately 1.5 leverets) than do hares in northern populations.

Hares in Utah and Colorado do not fit this pattern, however; their first litter

sizes of approximately 3-4 (Dolbeer and Clark 1975) are comparable to those

of hares in Yukon, Alaska, and central Alberta (Ernest 1974; Windberg and

Keith 1978, Stefan 1998).

There is a weak latitudinal difference in the dates when hares have their

litters (Keith 1981). The onset of hare reproduction is affected by gonadotropin levels, which are affected by daylength (Davis and Meyer 1972, 1973).

The beginning of reproduction is also affected by the beginning of spring

(Meslow and Keith 1971; Keith 1990), so hares in northern latitudes begin

breeding somewhat later than do hares in more southerly latitudes. Nonetheless, most hares have their first litter of the season in May (Keith 1981;

Keith 1990; Hodges et al. in press), and the number of litters per season does

not seem to depend on when the first litter is born (Stefan 1998; Hodges et al.

in press). Additionally, within a region, parturition dates can vary by two to

three weeks among years (Cary and Keith 1979; Stefan 1998), which is as

great as the purported difference among regions (Keith 1981, 1990).

Survival and Causes of Death

Our estimates of snowshoe hare survival have come from trapping and

radiotelemetry, and both of these types of data have been analyzed using

various statistical methods (Fig. 7.4). Inferring patterns of regional and even

cyclic differences in survival is therefore complicated because the data are

not truly comparable. Boutin and Krebs (1986) compared two trapping and

two radiotelemetry estimates of 28-day survival using five years of Yukon

hare data and found that the radiotelemetry estimates were consistently

higher than both trapping estimates, sometimes by as much as 30%. Radio-
176

Chapter 7—Hodges

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

35 40 45 50 55 60 65

Latitude

Number of leverets in first litter

low

increase

peak

unknown

A

Cyclic phase:

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

35 40 45 50 55 60 65

Latitude

Number of leverets in first litter

decline

B

Cyclic phase:

Figure 7.3—The correlation between size of first litter and latitude. Each

point represents mean first litter size in one year. Cyclic phases are

shown separately because of evidence from Alberta and Yukon that

litter size varies through the cycle (Cary and Keith 1979; Stefan 1998).

Wisconsin data were assigned to cyclic phases based on trend data

from Glenzinski and Dhuey (1998, unpublished) and Karasek

(unpublished), and the other references provided information on the

population trends in different years; the “unknown” points are for

Colorado and Utah (Dolbeer and Clark 1975). Sources: AB, Keith &

Windberg 1978, Windberg & Keith 1978, Cary & Keith 1979, Keith et al.

1984; MB, Criddle 1938; ONT, Newson 1964; NB, Wood and Munroe

1977; YK, O’Donoghue and Krebs 1992, Stefan 1998; AK, Ernest 1974;

WI, Kuvlesky and Keith 1983; UT, Dolbeer & Clark 1975; and CO,

Dolbeer & Clark 1975. The regression of litter size during the decline

phase on latitude is highly significant (F1,23 = 71.4, p < 0.001, r

2

 = 0.76).
177

Hodges—Chapter 7

Figure 7.4—Snowshoe hare survival estimates. Wisconsin data were assigned to cyclic

phases based on trend data from Glenzinski and Dhuey (1998, unpublished), and the

other references provided information on the population trends in different years. Panel

A shows studies in which juvenile survival (from birth through the following spring, or

overwinter) was contrasted with adult annual (or overwinter) survival. The diagonal line

indicates identical 30-day survival rates. Each point represents one overwinter or annual

period. Sources: AB, Keith & Windberg 1978; YK, Krebs et al. 1986; MT, Adams 1959;

MN, Green & Evans 1940b; NB, Wood and Munroe 1977; and WI, Keith et al. 1993.

Panels B (radiotelemetry) and C (trapping) show adult overwinter or annual survival

broken down regionally and methodologically. Lines are given at 0.85 for comparative

purposes. Kaplan-Meier and Trent-Rongstad refer to survival calculated following

methodologies in Pollock et al. (1989) and Trent & Rongstad (1974) respectively. JollySeber estimation is described in Krebs (1989), recatch estimation in Keith & Windberg

(1978), and age ratios in Green and Evans (1940b). Minimum estimation simply

calculates individuals caught at time t that are recaught at time t+1. Sources for panel

B: YK, Hodges et al. in press; AB, Keith et al. 1984; and WI, Sievert & Keith 1985. Data

for panel C: YK, Krebs et al. 1986; AB, Keith & Windberg 1978; BC, Sullivan & Moses

1986, Sullivan 1996; MN, Green & Evans 1940b; MT, Adams 1959; NB, Wood & Munroe

1977; WI, Kuvlesky & Keith 1983; CO, Dolbeer 1972a; and OR, Black 1965.

0.6

0.7

0.8

0.9

1.0

0.6 0.7 0.8 0.9 1.0

Juvenile survival (30-day)

Adult survival (30-day)

AB

YK

MT

MN

NB

WI

A.

0.6

0.7

0.8

0.9

1.0

Cyclic phase

Survival rate (30-day)

YK--Kaplan Meier

AB--Trent-Rongstad

WI--Trent-Rongstad

B. Radios

decline low increase peak unknown

(con.)
178

Chapter 7—Hodges

telemetry estimates are more likely to be accurate (Chapter 6); survival

estimates based on trapping are hampered by the low trappability and

potentially high dispersal rates of hares, both of which vary with season, sex,

age, phase of cycle, and possibly region and habitat (Trapp 1962; Boutin et

al. 1985; Boulanger 1993; Sullivan 1994; Gillis 1997; Hodges 1998).

Trapping studies suggest that juvenile survival is lower than adult survival (Fig. 7.4). This pattern may not be always true, however; using

radiocollars, Gillis (1997) found that post-weaning juveniles survived as

well as adults during an increase year in Yukon, and Keith et al. (1993) found

that juvenile survival was comparable to or higher than adult survival

during winter in Wisconsin. Within any given locality, both adult and

juvenile survival are lower during population declines (Green and Evans

1940b; Keith and Windberg 1978; Krebs et al. 1986; Hodges et al. in press).

For regional comparisons, I consider only radiotelemetry estimates because of methodological concerns with the trapping data (Table 7.2). Hares

Table 7.2—Survival rates of hares, assessed from radiotelemetry. Where several values are given, they indicate

the range among study sites and/or years.

Location Phase & years 30-day survival rate Reference

Virginiaa unknown 0.63 (>14 daysa

) Fies 1993 unpublished

1989-1990 0.86 (>60 daysa

)

Wisconsin decline 0.66-0.95 Keith et al. 1993b

1988-1991 Keith & Bloomer 1993b

Bloomer et al. 1995b

Wisconsin decline (Dec-Feb) 0.93 Cox et al. 1997

1994-1995

Wisconsin decline 0.86 Sievert & Keith 1985

1982-1983

a

Hares were released in a reintroduction program. Estimates are for days post-release.

b

Approximately half of these hares were treated with antihelminthic drugs, and hares were distributed among seven patches of habitat ranging in

size from five to 28 ha. I present survival rates recalculated from Table 5 of Keith et al. 1993.

0.6

0.7

0.8

0.9

1.0

Cyclic phase

Survival rate (30-day)

YK--Jolly-Seber

BC--Jolly-Seber

AB--recatch

MN--age ratio

MT--age ratio

NB--age ratio

WI--age ratio

CO--minimum

OR--minimum

BC--minimum

C. Trapping

decline peak low increase unknown

Figure 7.4 (Con.)
179

Hodges—Chapter 7

in Wisconsin had 30-day survival rates ranging between 0.66 and 0.95, with

lowest survival occurring as the population declined (Sievert and Keith

1985; Keith et al. 1993; Cox. et al. 1997). These 30-day survival estimates are

similar to those from a cyclic population of hares in Yukon, where the lowest

monthly survival (0.64) occurred during the decline phase and highest

survival (0.91) occurred as the population increased (Hodges et al. in press).

In Virginia, imported hares were released in a restocking program; their

survival in the first two weeks was low (17 of 26 died), but their survival rates

thereafter were similar to those of hares in Wisconsin and Yukon (Fies 1993,

unpublished). These results are comparable to those of Sievert and Keith

(1985) and evaluations of stocking programs for hunters (Fitzpatrick 1957;

Schultz 1980), all of which conclude that transplanted hares have much

higher mortality rates within the first several weeks after release.

Most hares in southern populations are killed by predators (Table 7.3)

(Fies 1993, unpublished; Sievert and Keith 1985; Keith et al. 1993; Cox et

al. 1997; Murray et al. 1997). These studies indicate that predation is

responsible for >90% of all hare deaths, a figure comparable to the predation

rates found for northern hare populations (Boutin et al. 1986; Krebs et al.

1995; Hodges et al. in press). Both studies of hare mortality patterns and

studies of predators indicate that southern hares are preyed upon by lynx,

coyotes, bobcat, grey fox, great-horned owls, red fox, weasels, mink, marten,

fisher, and goshawks (Zielinski et al. 1983; Litvaitis 1986; Halpin and

Bissonette 1988; Giuliano et al. 1989; Kuehn 1989; Dibello et al. 1990; Koehler

1990a; Erdman et al. 1998). Southern forests also contain predators such as

raccoons, skunks, feral cats and dogs, and snakes, but the extent to which

these predators prey upon hares is unknown. In boreal forests, very young

hares are also susceptible to predation by small predators such as red and

ground squirrels and some of the smaller hawks (O’Donoghue 1994; Rohner

et al. 1995; Stefan 1998; F. Doyle, unpublished), but the southern predators

on young hares are unknown.

Dispersal

Radiotelemetry provides the most reliable assessment of dispersal rates

(Boutin et al. 1985; Gillis 1997; Chapter 6). There are few such estimates for

southern hare populations, but during a population decline in Wisconsin,

2.6% of the hares dispersed and another 5.2% were found dead far enough

away from their original locations to suggest possible dispersal (Keith et al.

1993). During a decline in Yukon, 2.7% of hares dispersed (Boutin et al. 1985).

Keith et al. (1993) argue that the dispersal rate is higher from smaller habitat

patches, but their sample size of dispersers is small (five known dispersers

plus 10 animals found dead).
180

Chapter 7—Hodges

Table 7.3—Causes of mortality for snowshoe hares. Values are % of deaths due to each cause.

Phase & Unknown Non- Observed

Location years Avian Mammalian predator predation Unknown n dead predators References

Virginiaa unknown 8.3 41.7 33.3 16.7a 0 24 bobcat Fies 1993, unpublished

1989 & 1990 grey fox

great-horned owl

Manitoba decline 32.3 33.3 29.2 5.0 0 318 — Murray et al. 1997

(southern) 1991-1993

Wisconsin decline 26.7 48.3 16.7 8.3 0 60b red fox Sievert & Keith 1985

1982-1983 coyote

long-tailed weasel

mink

great-horned owl

goshawk

Wisconsin decline 10 55 31 4 0 122 — Keith et al. 1993c

1988-1991 Keith & Bloomer 1993c

Bloomer et al. 1995c

Wisconsin decline 14 64 0 7 14 14 coyote Cox et al. 1997

1994-1995

aHares were relocated from West Virginia into Virginia during January-April in each year. Most died within two weeks of release, and deaths in this period are thought to be related to handling and release into unfamiliar habitat. bI excluded deaths from handling, hunting, and dogs.

cApproximately half of these hares were treated with antihelminthic drugs, and hares were distributed among seven patches of habitat ranging in size from five to 28 ha.
181

Hodges—Chapter 7

Experiments in which hares are transplanted show that hares have reduced survival immediately following release (Schultz 1980; Sievert and

Keith 1985; Fies 1993, unpublished), which Sievert and Keith (1985) interpreted to mean that dispersers suffer higher mortality than non-dispersers.

Although both transplanting and dispersal lead to habitat unfamiliarity, the

process of catching, transporting, and releasing hares is very different than

what occurs as hares disperse naturally, making it hard to judge from these

experiments what factors lead to the higher mortality rate.

Comparative Demography Between Northern and Southern

Hare Populations

The available evidence suggests that demographic patterns are largely

similar between hares in northern and southern areas. Most hares are killed

by predators and the limited data we have on survival in southern areas

(Sievert and Keith 1985; Keith et al. 1993; Fies 1993, unpublished; Cox et al.

1997) suggest that northern and southern hares have similar survival.

Because the southern regions potentially have a larger suite of predators,

particularly for young hares, it is possible that there are regional differences

in leveret and juvenile survival rates. Although there appear to be differences in reproduction, with northern hares having larger litters but sometimes not as many litters in a season, it is unclear what effect this variation

has on the cycle. Analyses of snowshoe hare population dynamics suggest

that juvenile and adult survival have more impact on the numeric change

than does natality (Keith 1990; Krebs 1996; Haydon et al. 1999). More longterm studies of demography and modeling of the effects of variable survival

and reproductive rates would help in our understanding of why hare

populations display different lengths and amplitudes of fluctuation.

Snowshoe Hare Behavior

Diets

Hares eat many plant species (Table 7.4). The variability in number of

species eaten in the different regions is an amalgam of how speciose the

different areas are, hares’ likings for the different species, and sampling

effort.The short list for the north reflects fewer species in boreal forests than

in temperate ones, whereas the relatively short western list may be due

instead to less intensive sampling. Although many species preferences

have been identified (e.g., Telfer 1972; Bryant and Kuropat 1980; Scott and

Yahner 1989; Thomas et al. 1997, unpublished), these depend on the plant
182

Chapter 7—Hodges

Table 7.4—Food plants used by snowshoe hares in different regions. Because of the variety of analytic techniques and the

different floristic communities, I have not attempted to separate species into degrees of utilization or preference.

Conifers Deciduous trees Shrubs References

Maritimes & Maine

Abies balsamea Acer pensylvanicum Corylus cornuta Telfer 1972 (NB)

Picea spp. Acer rubrum Gaylussaccia baccata Litvaitis 1984 (ME)

Picea rubens Acer saccharum Hamamelis virginiana

Pinus strobus Acer spicatum Kalmia spp.

Thuja occidentalis Alnus rugosa Myrica gale

Tsuga canadensis Alnus crispa Nemopanthus mucronata

Betula alleghaniensis Rhododendron canadense

Betula papyrifera Vaccinium spp.

Betula populifolia Viburnum spp.

Comptonia peregrina

Fagus grandifolia

Quercus rubra

Eastern: Appalachians & Alleghanies

Picea glauca Acer pensylvanicum Juniperus communis Rogowitz 1988 (NY)

Picea rubens Acer rubrum Kalmia latifolia Cook & Robeson 1945 (NY)

Pinus resinosa Acer saccharum Rhododendron lapponicum Brooks 1955 (VA)

Pinus strobus Betula alleghaniensis Rubus alleghaniensis Scott & Yahner 1989 (PA)

Pinus sylvestris Betula lenta Rubus hispidus Walski & Mautz 1977 (NH)

Thuja occidentalis Betula lutea Vaccinium erythrocarpum Brown 1984 (PA)

Tsuga canadensis Betula papyrifera Viburnum dentatum

Fagus grandifolia

Fraxinus americana

Populus tremuloides

Midwest: Great Lakes

Abies balsamea Acer pensylvanicum Amelanchier spp. Bider 1961 (Que)

Larix laricina Acer rubrum Chamaedaphne calyculata Grange 1932 (WI)

Picea abies Acer saccharum Corylus cornuta Bookhout 1965b (MI)

Picea glauca Acer spicatum Juniperus communis Conroy et al. 1979 (MI)

Picea mariana Alnus crispa Ledum groenlandicus De Vos 1964 (ONT)

Pinus banksiana Alnus rugosa Lonicera spp. Grigal & Moody 1980 (MN)

Pinus divaricata Betula alba Rhamnus alnifolia Johnson 1969 (MI)

Pinus resinosa Betula papyrifera Rosa spp. Bergeron & Tardif 1988 (Que)

Pinus strobus Betula pumila Rubus spp.

Thuja occidentalis Fagus grandifolia Salix spp.

Tsuga canadensis Ostrya virginiana Shepherdia canadensis

Populus grandidentata Viburnum spp.

Populus pensylvanica

Populus tremuloides

Populus virginiana

Prunus pensylvanica

Prunus serotina

Prunus virginiana

Pyrus malus

Quercus rubra

Sorbus americana

Ulmus americana

Western: Rockies, Cascades & Intermountain West

Pinus contorta Amelanchier alnifolia Adams 1959 (MT)

Pinus ponderosa Arctostaphylus uva-ursi Koehler 1990a (WA)

Pseudotsuga menziesii Ceanothus spp. Radwan & Campbell 1968 (WA)

Tsuga heterophylla Juniperus scopulorum Thomas et al. 1997, unpublished (WA)

Mahonia repens Sullivan and Sullivan 1983 (BC)

Rosa spp. Borrecco 1976 (WA)

Rubus spp. Black 1965 (OR)

Salix coulteri

Symphoricarpus albus

Vaccinium spp.

North: Boreal Forests

Picea glauca Alnus crispa Amelanchier alnifolia Smith et al. 1988 (YK)

Picea mariana Alnus rugosa Betula glandulosa Wolff 1978 (AK)

Betula papyrifera Corylus cornuta Bryant 1981 (AK)

Populus balsamifera Ledum decumbens

Populus tremuloides Rosa spp.

Salix spp.

Shepherdia canadensis
183

Hodges—Chapter 7

community where each study is conducted. Hares also eat many nonwoody

species (Adams 1959; Radwan and Campbell 1968; Thomas et al. 1997,

unpublished; Hodges 1998).

Browse damage by hares can slow regeneration of conifers after logging,

especially if hares eat the bark of the young trees (Cook and Robeson 1945;

Borrecco 1976; Krefting 1975, unpublished; Sullivan and Sullivan 1986;

Bergeron and Tardif 1988). When hares are at high density, they are more

likely to eat bark and large twigs than during years when hare densities are

lower (de Vos 1964; Lloyd-Smith and Piene 1981, unpublished; Fox and

Bryant 1984). Hares can affect young trees by slowing their growth rate,

destroying the apical meristem, and even killing them (Corson and Cheyney

1928; Cook and Robeson 1945; Krefting 1975, unpublished; Black et al. 1979).

In the north, food availability has been addressed because of its potential

role in the generation of cycles (Vowles 1972; Pease et al. 1979; Bryant 1981;

Keith 1983; Smith et al. 1988). In the south, more effort has been placed on

describing potential competition for food between hares and deer or

moose (Dodds 1960; Dodds 1962, unpublished; Bookhout 1965b; Telfer

1972; Krefting 1975, unpublished). These studies have generally agreed

that these herbivores often eat the same plants but do not appear to be

limiting each other’s numbers, although this pattern has not been thoroughly examined. There is at present no evidence suggesting food limitation in southern hare populations.

Analyzing Snowshoe Hare Habitat Use

In the following discussion, I focus on describing the habitats hares use.

I avoid using the terms “habitat needs” and “habitat requirements.” These

terms are designed to address whether particular habitats are so critical to a

species that without them the species cannot survive (these may be “source”

habitats [sensu Pulliam 1988] or they may be habitats critical to a particular

life-stage, such as habitat for lambing). For a species like the snowshoe hare

that uses many habitat types, it is difficult to know what criteria to employ

to designate a habitat as “required.” Density may not be a good index

because in some cases higher densities can occur in “sink” habitats (Van

Horne 1983), and hares have no obvious need for particular habitats for

reproduction. I similarly avoid discussing “habitat quality” because this

phrase does not have a precise definition. In all of these cases, it is more

valuable to discuss and to quantify habitat-specific demography.

Hare habitat use patterns have been measured by estimates of density

(from trapping or from pellet counts; e.g., Litvaitis et al. 1985b; Krebs et al.

1987; Eaton 1995), direct estimates of relative use (from trapping or radiotelemetry locations of marked hares; e.g., Dolbeer and Clark 1975; Ferron
184

Chapter 7—Hodges

and Ouellet 1992), and indirect estimates of relative use (from browsing

intensity or hare tracks; e.g., Monthey 1986; Rogowitz 1988). Of these,

density estimates are the most informative, because they can indicate

amplitude of change through time or magnitude of difference among

habitats. Direct estimates of relative use can be valuable for showing how

individuals split their time among different habitats (Manly et al. 1993).

Indirect estimates of relative use (indices) are difficult to interpret, because

the amplitudes of difference among habitats or years have an unknown

relationship to the actual differences in hare densities (Hartman 1960;

Thomas et al. 1997, unpublished). Additionally, different protocols (e.g.,

how to count hare runways) make it difficult to compare results from

different studies.

Patterns of Habitat Use by Snowshoe Hares

Density estimates show that hares use certain seral stages more than

others, and this pattern appears to be most correlated with horizontal

understory cover from approximately 1 to 3 m (Table 7.5). Newly clear-cut

areas are essentially not used (Ferron et al. 1998). In Washington, younger

lodgepole pine stands support higher densities of hares than do older stands,

which is associated with the higher stocking density of the younger stands

(Koehler 1990a, b). Typically, forest stands that are densely stocked support

higher hare densities than do lightly stocked stands (Litvaitis et al. 1985b;

Brocke et al. 1993, unpublished). Similarly, stands with dense understory

cover tend to be used more by hares than are stands with little understory

cover (Orr and Dodds 1982; Wolfe et al. 1982). Deciduous forests can support

reasonable densities of hares, especially if they have well-developed understories (Orr and Dodds 1982; Wolfe et al. 1982; Reed et al. 1999, unpublished).

These patterns of habitat use by hares are supported by studies that

employed direct or indirect estimates of relative use (Tables 7.6 and 7.7). The

most consistent finding is that hares’ use of habitats is correlated with

understory cover—stands with shrubs, stands that are densely stocked, and

stands at ages where branches have more lateral cover are more heavily used

by hares (Black 1965; Dolbeer and Clark 1975; Wolfe et al. 1982; Litvaitis et

al. 1985a, b; Monthey 1986; Parker et al. 1983; Koehler 1990a; Swayze 1994,

unpublished; Thomas et al. 1997, unpublished). Overstory cover is sometimes correlated with hare habitat use patterns, but typically in cases

where it is also significantly correlated with understory cover (Richmond

and Chien 1976; Orr and Dodds 1982; Parker et al. 1983; Rogowitz 1988). The

species composition in a stand appears to be less correlated with hare habitat

use than is understory structure (Ferron and Ouellet 1992; Thomas et al.

1997, unpublished). Stand age per se does not appear to be critical, again
185

Hodges—Chapter 7

Table 7.5—Snowshoe hare densities in different habitat types. Density estimates are derived either from pellet plotsa or from

live-trapping data.

Hare density

Location Year/season Method Habitat type (hares/ha) Reference

Stand age/height

Nova Scotia 1976 pellet plots forests with ≥50% spruce-fir. Orr & Dodds 1982

height classes (m):

4.5-9.2 0.59

4.5-15 0.52

9.4-12.3 0.60

12.5-15.2 0.36

Quebec (southern) 1993-1996 pellet plots uncut black spruce forest 0.12-0.25 Ferron et al. 1998

clear-cut black spruce forest 0.01-0.02

Washington 1986-1989 pellet plotsb 1986 /1987 /1989 Koehler 1990a, b

~25-yr-old lodgepole pine 1.04 /1.79 / 0.99

~45-yr-old lodgepole pine 0.86 /0.45 / 0.39

>80-yr-old lodgepole pine 0.43 /— / 0.22

>100-yr-old Englemann fir- 0.09 /0.27 / 0.12

subalpine spruce

Species Composition

Nova Scotia 1976 pellet plots spruce-fir 0.49 Orr & Dodds 1982

maple/birch 0.22

alder 0.69

Utah 1976-1978c pellet plots aspen—sparse understory 0.01 Wolfe et al. 1982

aspen—dense understory 0.22

aspen-conifer edge 0.17

Douglas-fir 0.57

subalpine fir 0.99

Engelmann spruce 0.19

Utah 1976-1978 live-trapping Englemann spruce-subalpine fir Andersen et al. 1980

July 1976 1.0

July 1977 1.8

May 1978 2.7

Colorado 1998 pellet plotsd aspen 0.26 Reed et al. 1999,

Douglas-fir 0.37 unpublished

subalpine fir 0.37

lodgepole pine 0.35

Gambel oak 0.05

Ponderosa pine 0.18

Engelmann spruce 0.46

% cover

Nova Scotia 1976 pellet plots forests with ≥50% spruce-fir. Orr & Dodds 1982

canopy cover classes:

10-40 0.62

41-60 0.49

61-100 0.38

New Hampshire 1990 pellet plotse spruce-fir-birch-ash-maple Brocke et al. 1993,

9,221 stems/ha (90% conifer) 1.34 unpublished

26,028 stems/ha (99% conifer) 1.27

8,512 stems/ha (82% conifer) 0.74

6,533 stems/ha (90% conifer) 0.40

Maine 1982-1983 live-trapping total understory stems/ha 1982 / 1983 Litvaitis et al. 1985b

spring (total conifer stems/ha):

31,490 (2,580) 0.4 / 0.6

20,350 (16,150) 1.2 / 1.7

18,980 (8,580) 0.6 / 0.5

16,440 (4,360) 0.2 / 0.1

a

Densities from pellet plots were recalculated from the original papers using a regression equation derived from hare density information from 1976 to 1996 (C.J. Krebs,

unpublished): ln(hares/ha)=0.888962*ln(pellets)-1.203391, corrected for bias by multiplying with 1.57 following Sprugel (1983). Pellets is pellets/0.155m2. The

methodology and rationale were derived in Krebs et al. (1987), and the current equation simply uses more information. b

Fall 1987 pellet values were calculated from Koehler 1990a by adding the winter and summer counts.

c

Values are from the three years in which all habitats were sampled; the values given are averages across years.

d

Only cover types with >15 pellet plots are shown here.

e

Pellet counts were transformed to hare densities using the Krebs (1998, unpublished) equation rather than reporting the densities in this reference, which were

calculated according to another formula.
186

Chapter 7—Hodges

Table 7.6—Proportional occurrence of snowshoe hares in different habitat types. The data in this table show the proportion

of locations of hares in each habitat type, from locations gathered via radiotelemetry or live-trapping. Livetrapping data are included here instead of in Table 7.5 if the data were presented as number of captures of animals

in each habitat type.

Proportional use

Location Year/season Method Habitat type by hares Reference

Species composition

Quebec 1987 radiotelemetry overstory composition: Ferron and Ouellet 1992

(southeastern) summer (feeding and conifer 19

resting deciduous 37

observations mixed 29

combined) none 15

understory composition:

conifer or none 4

deciduous 80

mixed 16

Oregon 1960-1962 trappinga ~15-yr Douglas-fir stands 78.3 / 74.4a Black 1965

open (clear-cut and fire) 21.7 / 25.6

% cover

Nova Scotia 1977-1979 trappingb fir/spruce/birch forests: Parker et al. 1983

(Cape Breton open mature 47.2

Island) closed mature 9.3

regeneration (16-30 yr) 22.3

regeneration (5-15 yr) 21.2

Maine 1981-1983 trappingc understory density: Litvaitis 1984

October-May < 700 stems/ha 0 / 6.8c Litvaitis et al. 1985a

700-7,000 stems/ha 13.7 / 15.6

7,000-20,000 stems/ha 30.1 / 27.9

>20,000 stems/ha 56.3 / 49.7

Colorado 1969-1971 trapping open (scattered trees) 9.7 (A) / 25.5 (J)d Dolbeer 1972a

July-August forested (spruce-fir-pine) 90.3 (A) / 74.5 (J) Dolbeer & Clark 1975

a

Values are for the same sites but for periods with different numbers of traps.

b

Values are % of live captures/1,000 trap nights.

c

Values are for two sites.

d

A refers to adults, J to juveniles.

because of the importance of stand structure, but several studies have

indicated that younger stands may support more hares than do older

mature stands (C. Grove, unpublished; Johnson 1969; Koehler 1990a,b;

Byrne 1998, unpublished).

Fires and harvesting both return land to early seral stages but may differ

in their effects on hares. Spatial scale of the two disturbances may differ,

and whereas fire often leaves some standing trees, both dead and alive,

clear-cuts and even some selective cuts remove much of the overstory and

often understory as well (Chapter 3). Several authors have argued that fire

contributes to the cyclicity of hares, by providing regenerating areas rich in

food and cover (Howell 1923; Grange 1965; Fox 1978), but there are

comparatively few studies of hares’ use of burned stands of various ages.

In Colorado, pellet plots showed that hares used an eight-year-old burn

of lodgepole pine forest much less than the adjacent unburned forest

(Roppe and Hein 1978). In Michigan, hares used a 30-year-old burned site
187

Hodges—Chapter 7

Table 7.7—Indices of relative use by hares of different habitat types. Statistical significance (at p < 0.05) is taken directly from the analyses performed by the authors: > shows statistical

significance, ≥ shows a trend but no statistical significance, = shows no trend and no statistical significance. In cases where no statistics were performed, the comparable

symbols ⊃, ⊃, and ≈ are used to indicate trends. (0) indicates little or no sign of hares in the habitat.

Location Year/season Methodsa Snowshoe hare habitat use Reference

Stand age/height

Maine 1974-1977 tracks (%) conifer regrowth: 12-15 yr > 7-9 yr > 1-3 yr Monthey 1986

winter

Vermont winter tracks deciduous: stands younger than 60 yr ⊃ stands older than 60 yrb C. Grove, unpublished

New York 1972-1974 tracks (#) saw timber ⊃ seedling/sapling ⊃ pole timber ⊃ old field (0) Richmond and Chien 1976

March

Pennsylvania 1984-1985 tracks (%) successful deciduous regeneration > unsuccessful deciduous regenerationc Scott & Yahner 1989

winter

Colorado 1997-1998 tracks (#) mature ⊃ sapling/pole ⊃ old-growth ⊃ shrub/seedling ⊃ open Byrne 1998, unpublished

winter

Stand composition

Maine 1974-1977 tracks (%) spruce/fir > mixed > maple/beech/birch Monthey 1986

Maine 1981 tracks (#) deciduous > spruce/fir > mixed O’Donoghue 1983

pellets

Vermont winter tracks conifer ≈ deciduous ≈ mixed ≈ opend C. Grove, unpublished

Connecticut 1958-1959 tracks conifer plantation = deciduous > mixed > old field Behrend 1960, unpublished

winter trappinge

New York 1972-1974 tracks (#) Norway spruce ≈ white pine ⊃ stands without these species Richmond and Chien 1976

March

New York 1980 food offerings spruce > pine-shrub, spruce-shrub > deciduous (0), open (0) Rogowitz 1988

January/March pellets

Pennsylvania 1977 tracks (#) deciduous regeneration (8 yrs old) ⊃ laurel ⊃ hemlock Brown 1984

Feb-March

Michigan 1976 browsing cedar/fir ⊃ ash/elm ⊃ alder ⊃ oak/pine ⊃ clear-cut Conroy et al. 1979

Jan-March intensity

Michigan (Isle 1963-1968 pellets 1936 burn > conifer, deciduous > 100-yr-old burn (0)f Johnson 1969

Royale)

(con.)
188

Chapter 7—Hodges Table 7.7 (Con.)

Location Year/season Methodsa Snowshoe hare habitat use Reference

Stand composition

Wisconsin 1978-1979 tracks (#) spruce-cedar-tamarack > pine-oak, alder, aspen-birch, pine-maple, maple-basswood (0) Buehler & Keith 1982

winter spruce-pine plantations > pine-oak, alder, maple-basswood (0)

spruce-pine plantations ≥ aspen-birch, pine-maple

Utah 1972-1973 pellets spruce/fir ≥ lodgepole pine > aspen Clark 1973

June-July

Montana 1977 tracks (#) lodgepole ⊃ grass islands in lodgepole stands ⊃ subalpine fir-Engelmann spruce ⊃ Koehler et al. 1979

conifer islands in grassland

Colorado 1974 pellets unburned lodgepole > 8-yr-old burned lodgepole Roppe & Hein 1978

Colorado 1997-1998 tracks (#) lodgepole ≈ white fir ≈ limber pine ⊃ Douglas-fir ⊃ Engelmann spruce ≈ ponderosa Byrne 1998, unpublished

winter pine ⊃ aspen ⊃ willow ⊃ oak ⊃ open

% cover

Maine 1981-1983 tracks (%) understory density: Litvaitis 1984

pellets 20,000+ stems/ha > 7,000-20,000 > 700-7,000 > below 700 stems/ha Litvaitis et al. 1985a

Maine 1981 tracks (#) understory density: dense > moderate > open > sparse O’Donoghue 1983

pellets

New York 1970-1974 tracks (#) fir/spruce: 20,900 stems/ha ⊃ 5,900 stems/ha Brocke 1975

fall-winter trapping

Connecticut 1958-1959 tracks understory cover from 0-6 ft: 61-100% > 21-60% Behrend 1960, unpublished

winter trappinge

Washington 1994 pellet plots 23-yr-old lodgepole pine regeneration

stand density: ~100,000 stems/ha > ~20,000 stems/ha = ~1000 stems/ha Swayze 1994, unpublished

Washington 1974-1975 damage to sites with Douglas-fir regeneration: Borrecco 1976

seedlings clearcuts > clear-cuts treated with herbicides to eliminate herbaceous growth

(live-trapping)

aFor methods, tracks (%) means track counts where the proportion of transect segments with tracks was calculated, tracks (#) means tracks were actually counted along transects, pellets indicates pellet plots where the collection design or

the presentation do not allow for conversion to density estimates, and browsing intensity and food offerings indicate observations of browse use. bStands were evaluated for presence/absence of hares only. For this analysis, I excluded stands containing trees of ages overlapping these two groups.

cSuccessful regeneration: >70% of 20 1.83-m radius plots containing ≥2 stems that are ≥1.5 m tall. dStands were evaluated for presence/absence of hares only. 82-86% of deciduous, mixed, and coniferous stands contained hare sign; 100% of open sites did as well, but only four open sites were sampled compared to 37-99 stands of the

other types.

eBehrend presented tracks and live captures together in the analysis of habitat use. fThe 1936 burn had a variety of habitat types within it, including alder, jack pine, white birch, aspen.
189

Hodges—Chapter 7

more than a 100-year-old burned site (Johnson 1969). In the Northwest

Territories, hares used a burned site during the first winter post-fire, to eat

the bark of the burned black spruce trees (Stephenson 1985).

Hares may show seasonal shifts in habitat use, using more or denser

coniferous cover in winter than in summer, which suggests that winter

cover may be more important than summer cover (O’Donoghue 1983;

Parker et al. 1983; Litvaitis et al. 1985b; Swayze 1994, unpublished). Additionally, hare habitat use may vary with regional density; in Minnesota,

hares’ use of areas with little cover was higher when population densities

were high, even though the rank order of hare habitat use remained basically

the same as at low densities (Fuller and Heisey 1986). Juvenile hares may

use more open habitats than do adult hares (Dolbeer and Clark 1975),

and there may be differences in habitat use between males and females

(Litvaitis 1990).

Regionally, hares appear more likely to use deciduous forests in the east

than in the west (Tables 7.5 through 7.8). On the east coast, where both

deciduous and coniferous stands are present, hares may use the coniferous

stands more (Richmond and Chien 1976; Orr and Dodds 1982; Rogowitz

1988), but in some cases hares make equal or more use of the deciduous

Table 7.8—Habitat survey results. Forest managers were requested to indicate the top two habitats in

which they would find hares. The numbers indicate responses for different national

forests; in some cases, one forest manager responded for multiple forests. Clearly, some

forest types occur only in one of the regions; the more valuable comparison is within a

region to see which habitat types managers consider to contain more hares.

Oregon & Intermountain Great Lakes

Forest type Washington West & eastern U.S.

Engelmann spruce-subalpine fir 2 15 —

Interior Douglas-fir 6 4 —

Western larch 1 3 —

Grand fir 5 3 —

White fir 3 — —

Balsam fir — — 5

Mountain hemlock 3 — —

Coastal fir-hemlock 2 — —

Red cedar-hemlock 2 1 —

Western red cedar — 1 —

White cedar — — 2

Lodgepole pine 7 14 —

Whitebark pine — 1 —

Red pine — — 2

Jack pine — — 1

Ponderosa pine 1 — —

Red spruce — — 1

White spruce — — 1

Spruce-tamarack — — 1

Spruce-birch — — 1

Cottonwood/willow 1 1 —

Aspen 1 4 2

Birch — — 2
190

Chapter 7—Hodges

stands (Behrend 1960, unpublished; O’Donoghue 1983; Brown 1984; Litvaitis

et al. 1985b). On the east coast, many deciduous forests have dense understories of shrubs and immature trees and these forest types are commonly used

by hares (Tompkins and Woehr 1979; O’Donoghue 1983; Brown 1984; Scott

and Yahner 1989; Ferron and Ouellet 1992). Western deciduous forests—

such as aspen or poplar stands—may lack this understory growth, and these

stands do not show as much use by hares (Clark 1973; Wolfe et al. 1982; Byrne

1998, unpublished; Reed et al. 1999, unpublished). This pattern again highlights the association between hares and understory cover. On the west

coast, lodgepole pine, Douglas-fir, and Englemann-spruce/subalpine fir

stands are common habitats for hares. On the east coast, the common cover

types for hares are spruce/fir, pine, and deciduous.

Habitat interspersion may be valuable to hares by providing them

access to habitats with different protective abilities and food availabilities

(Conroy et al. 1979; Krenz 1988; Koehler and Brittell 1990; Beauvais 1997;

Thomas et al. 1997). Krenz (1988) found that hares in Minnesota were more

likely to use deciduous shrub cover if it was clumped (at a scale of circles

of 168 m radius), whereas hares were more likely to use coniferous cover

that was more evenly distributed. Additionally, the size of habitat patches

can affect hare densities. In Washington, stands ≥32 ha had roughly double

the number of hare pellets as occurred in stands <16 ha (Thomas et al. 1997),

and in Wisconsin there was a trend for larger forest stands to be more likely

to have hares present within them (Buehler and Keith 1982). Thomas et al.

(1997, unpublished) also found that the amount of disturbed habitat (talus,

meadows, or heavily thinned mature forest) in a 600 m strip around each

habitat patch was negatively correlated with the number of hare pellets

within the patch. In Maine, an area managed with clear-cutting had higher

track counts than did areas that were partially harvested or entirely uncut,

suggesting that the habitat matrix affects hare abundance (Monthey 1986).

In Minnesota, hare habitat use was more correlated with habitat interspersion than with stand type, and hares used the edges more than centers of the

heavily used stand types (Conroy et al. 1979). In Wyoming, snowshoe hare

presence in stands was correlated with the degree of interspersion with

clear-cuts and riparian areas (Beauvais 1997).

The bulk of evidence suggests that habitats affect hares’ survival rates

because vulnerability to predation and predator density vary among habitats (O’Donoghue 1997; Murray et al. 1994, 1995). Fecundity may possibly

vary with habitat as well, perhaps mediated by dietary differences (Hik

1994) or the effects of predation risk on stress levels (Boonstra et al. 1998).

At a stand level, then, demography is likely to vary with cover and food

availability. At the level of multiple stands, however, hares may be able to

switch back and forth between different types of stands (Conroy et al. 1979;
191

Hodges—Chapter 7

Krenz 1988; Hik 1994), or different age classes of hares may use different

stand types (Dolbeer and Clark 1975; Boutin 1984). Hare dynamics within

the set of stands will therefore depend on the densities of hares within each

stand as well as the survival and fecundity rates typical of each stand type.

The size of each stand and the degree of interspersion are likely to affect hare

dynamics as well—an array of large stands may have different overall

dynamics than a quilt of small stands because the movement of hares

between stands is easier when each stand is smaller. Additionally, if

certain predators require large stands of particular habitat types, they

may not occur in landscapes where the same amount of habitat is dispersed

in smaller patches.

The habitat use patterns of southern snowshoe hares are similar to those

of hares in northern boreal forests. Hares in northern forests also are often

associated with early seral forests, again with understory cover or stand

density as good correlates with hare habitat use patterns (Wolff 1980;

Sullivan and Sullivan 1982a,b, 1983; Hik 1994, 1995; O’Donoghue 1997).

Northern forests are predominantly coniferous, and the deciduous aspen

and poplar stands typically do not support a thick shrub understory;

hares in northern forests do not use these deciduous stands extensively

(Hodges 1998).

Discussion

The predominant snowshoe hare story in this century has been that

snowshoe hares are strongly cyclic in the north but show reduced or no

cycles in their southern distribution (Howell 1923; MacLulich 1937; Criddle

1938; Keith 1963, 1990; Grange 1965; Finerty 1980; Bittner and Rongstad

1982; Smith 1983). This paradigm has arisen from two main fronts: analyses

of time series data (mainly harvest records) and comparisons of demographic patterns among regions. I have so far presented time series that

support the possibility that hares are cyclic in southern areas, although with

peak and low densities lower than those in northern areas. I have similarly

argued that the comparable data we have from southern and northern hare

populations indicate similar demography among regions. In this final

section, I argue that it is time to emphasize analyses that address why

snowshoe hare fluctuations vary in amplitude, maximum density, and

duration both within and among regions. There is an extensive literature

discussing the linkages of hare behavior, habitats, and demography, and

this framework may prove useful for evaluating the mechanisms leading

to different dynamics and densities in different times or areas.

The dominant model of the effect of hare habitat use patterns on their

demography has been used to explain both cyclic dynamics and the previ-
192

Chapter 7—Hodges

ously hypothesized noncyclicity in the southern range of hares (Keith 1966,

1990; Dolbeer and Clark 1975; Wolff 1980, 1981; Buehler and Keith 1982;

Sievert and Keith 1985; Hik 1994, 1995). The refugium model was most

clearly articulated by Wolff (1980, 1981) as follows: hares selectively use

dense, safe habitats until high hare densities force some hares into poor

habitats, which exposes them to higher predation risk, thus contributing to

the numeric and functional responses of predators and the cyclic decline.

The habitats with densest cover, meanwhile, provide refugia to hares, thus

allowing a source population during the low phase. In this model, reproductive declines are thought to originate because food supply in the densest

habitats is lower, or poorer quality, leaving hares with a trade-off between

nutrition and survival (Hik 1994, 1995). Alternatively, recent evidence

suggests that reproductive declines may be due to the stress of encounters

with predators, which is highest as hare populations decline (Boonstra and

Singleton 1993; Boonstra et al. 1998).

The refugium model has also been used to explain the putative lack of

cycles in the south (Dolbeer and Clark 1975; Wolff 1980, 1981). In this case,

the basic argument is that southern habitats are more patchy due to being

montane (and with greater human impacts). The implication is that hares

that disperse from refugia are even less likely to survive, especially since

there are noncyclic facultative predators able to prey on the hares. Within

each southern habitat patch, therefore, cyclic dynamics are liable to be

subdued because of the smallness of the patch and the survival sink awaiting

dispersers from the patch.

This refugium model can be broken down into a number of testable

components:

(1) refuge habitats exist, in which hares have higher survival than in other

habitat types;

(2) the distribution of hares relative to habitats changes through the cycle,

with a higher proportion of hares in refugia during the low phase;

(3) hare reproduction varies with habitat, with hares in refugia showing

the lowest reproductive output.

If hares in southern populations have dynamics that differ from those

of hares in northern populations, then two additional propositions are

relevant:

(4) hares in southern populations have lower survival in non-refuge

habitats than do hares in northern non-refuge habitats (or in the north

refugia comprise a larger proportion of the habitat available than in the

south); and

(5) hares in southern populations have lower survival overall than do

hares in northern populations, thus stabilizing the cycle.
193

Hodges—Chapter 7

A similar model has been proposed for Fennoscandian microtine cycles

that emphasizes the role of facultative predators in the southern noncyclic

range of microtine rodents (Erlinge et al. 1983; Hansson and Henttonen 1985;

Hansson 1987; Erlinge 1987; Hanski et al. 1991; Lindström 1994). This model

is similar to the refugium model in that a critical element is the increased

mortality that occurs in noncyclic prey populations relative to cyclic ones.

Habitat is invoked more in the role of enabling facultative predators and

alternative prey to be present, rather than in the role of changing the

accessibility of the cyclic prey species to the predators. The same argumentation could be applied to the snowshoe hares: if the facultative predation

model is true, we would expect to see (A) overall higher mortality rates of

snowshoe hares in their southern range, and (B) a higher proportion of

deaths by facultative predators in southern populations than in northern

populations. Although both models need higher hare mortality in the

southern populations (requirements 5 and A), it is possible that hares could

have higher mortality rates in the south without the other requirements of

either model being upheld, in which case other hypotheses would need to

be constructed to explain why the mortality rates differed. It is also possible

that per capita predation rates on hares may be similar among regions, but

that the predators are compensatory with each other (Stenseth et al. 1997;

Hodges et al. in press), thus making the proportion of kills due to each

predator interesting from a community organization perspective but irrelevant to the dynamics of hares.

At present, our evaluation of these two predation models can be little

more than conjectural (Table 7.9). We have limited data that address only

requirements 1 and 2 of the refugium model. A few studies have indicated

small differences in hare survival (measured with radiotelemetry) among

habitats (Sievert and Keith 1985; Keith and Bloomer 1993), and predators

choose particular habitat types and may have differential success rates in

each type (Hik 1994; Murray et al. 1994, 1995; Rohner and Krebs 1996; Cox

et al. 1997). There is, however, no clear cyclic pattern in snowshoe hares’ use

of the available habitat types (Fuller and Heisey 1986; Chapter 6), counter to

the refugium hypothesis. Experimental work in Yukon has shown that

hares protected from predators still prefer dense cover and do not show

much greater use of open cover than unprotected hares (Hik 1994; Hodges

1998), which argues against the idea that high predation pressure forces

hares into dense habitats.

To evaluate the roles of habitat structure and predation on hare cycles

among regions properly, we need precise definitions of refugia and nonrefugia and our data from hare populations in different regions need to be

comparable. Given the evidence from Alberta and Yukon that shows that

both food and predation are necessary components of the cycle (Keith 1990;
194

Chapter 7—Hodges

Table 7.9—Evaluation of the refugium and facultative predation hypotheses for snowshoe hare cycles. Requirements

1-5 belong to the refugium hypothesis, and A-B to the facultative predation hypothesis. Support for any of 4a-4c

would be adequate; only one is needed to support that requirement of the refugium model. If requirements 1 & 2

are met, but 4 & 5 are not, refugia can help explain northern cyclicity but cannot explain dynamics in southern

populations. Requirement 3 is not strictly necessary, but would support the argument that habitat affects hare

demography.

Model requirements Evidence Questions that need to be resolved

1. differential survival in different habitat types see chapter 6; 2 Wisconsin What magnitude of difference is necessary?

studies found differential survival

2. hare distribution in habitats varies cyclically see chapter 6; no clear What magnitude of difference is necessary?

(higher % of hares in refuges during low phase) cyclicity in hare habitat use Does the % of mortalities/hare/habitat vary?

(is a refugium a physical place?)

3. differential reproduction in different habitat types no data available Is habitat a proxy for nutrition or maternal stress?

4a. survival in southern non-refuges < survival in no comparable data available Critical to define well and make comparable

northern non-refuges between regions.

4b. survival in southern refuges < survival in no comparable data available Critical to define well and make comparable

northern refuges between regions. Can “refuge” habitats be

defined by vegetation type and/or structure

or are they defined by having higher survival

within them?

4c. lower % of refuge habitat in south than in north “refuge” habitat needs definition Critical to define well and make comparable

first between regions. Can “refuge” habitats be

defined by vegetation and/or structure or are

they defined by having higher survival within

them?

5 & A. lower survival rate in south than in north comparable data suggest similar What period of the cycle should be used for

survival rates comparison? What magnitude of difference is

necessary? Is it sufficient if survival differs in

only one age class or season?

B. higher % of deaths by facultative predators in no comparable data available Definitions needed of facultative vs. obligate

south than in north for N. American predators of hares. Is it

sufficient if this requirement applies to only

one age class? What magnitude of difference

is necessary?

Krebs et al. 1995), it is distressing that the dominant models for explaining

cycles and potential regional differences in cycles focus on predation.

Reproductive changes occur cyclically and possibly regionally yet are

given only minor attention in these models of hare dynamics. Even though

hare survival appears to have more effect on numeric changes, explicit

hypotheses should be developed that incorporate hares’ food supply and

reproductive changes. Furthermore, the degree of interspersion and the size

of each habitat patch may matter as much to hare demography as does

the actual proportion of each habitat type, so spatially explicit analyses

need to be conducted.
195

Hodges—Chapter 7

Conclusions

Currently, our knowledge of snowshoe hares in their southern range is

dominated by information on distribution and habitat use patterns. Our

knowledge of hare numeric patterns is derived mainly from harvest

records, and our knowledge of hare demographic patterns in their southern

range tend to come from short-term studies (<5 years). All of these data

sets are stronger in the northeast and around the Great Lakes than in the

southern and western range of snowshoe hares. Time series of snowshoe

hare density will be valuable throughout the range of snowshoe hares, but

especially in the western and southern regions where few time series exist.

The existing demographic studies suggest that patterns may be similar

from north to south, but southern records tend to be shorter in duration;

it will be valuable to assess the range of variation in demography in

southern sites across a range of densities and population trends. The

consensus of many studies from north to south is that hares utilize habitats

with dense understories and many overstory species, but we do not yet have

a complete understanding of how the degree of interspersion or spatial scale

of fragmentation affect hare densities and population dynamics. Our future

research should emphasize the interrelationship between habitats—at multiple scales and in various spatial arrays—and snowshoe hare population

dynamics.

Acknowledgments

I wish I had more space to acknowledge the consistent and patient support

of G. Koehler and C.J. Krebs; this chapter is much better than it would have

been sans their support and their insightful comments. Three anonymous

reviewers and members of the Lynx Science Team offered comments on the

manuscript that have greatly strengthened it. S. Clark was indispensible: she

was incredibly useful in contacting people and acquiring references for me,

an effort that L. Moffatt additionally aided. This chapter relies on the generosity of many people who were willing to provide me with their unpublished, reports, and observations. I am extremely grateful to the following people for doing so: M. Boudreau, C. McLaughlin, K. Eagle, D. Dziak,

G. Batchelar, A. Jacobson, J. Cardoza, G. Karasek, D. Ware, R. Lafond,

R. Dibblee, D. Mitchell, J. Malloy, L. Ruggiero, G. Schmidt, C. Harris,

J. Rieffenberger, C. Krebs, and D. Scott. I additionally benefitted from

seeing an unpublished manuscript by D. Murray.
196

Chapter 7—Hodges

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204

Chapter 7—Hodges

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205

Hodges—Chapter 7

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Chapter 7—Hodges

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207

Chapter 8

History and Distribution

of Lynx in the Contiguous

United States

Kevin S. McKelvey, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59807

Keith B. Aubry, USDA Forest Service, Pacific Northwest Research Station,

3625 93rd Ave. SW, Olympia, WA 98512

Yvette K. Ortega, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59807

Abstract—Using written accounts, trapping records, and spatially referenced

occurrence data, the authors reconstructed the history and distribution of lynx in

the contiguous United States from the 1800s to the present. Records show lynx

occurrence in 24 states. Data over broad scales of space and time show lynx

distribution relative to topography and vegetation. For all three study regions

(Northeastern states, Great Lakes and North-Central states, and Western

Mountain states), high frequencies of occurrence were in cool, coniferous forests,

with occurrences at primarily higher elevations in the West.

Introduction

Understanding the geographic distribution of an organism can provide

important insights into its ecology. In this chapter we compile and analyze
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Chapter 8—McKelvey

occurrence data for lynx in the contiguous United States. We’ve organized

our analyses into three sections. In the first, we evaluate available information on the history of lynx occurrence. Because data were generally collected

independently by each state, this analysis is presented state-by-state. In

the second, we evaluate the extent to which population dynamics of lynx in

the states adjacent to Canada are associated with Canadian population

dynamics and investigate the nature of observed relationships. In the third

section, we identify the broadly defined vegetation cover types and elevation zones that encompass the majority of lynx occurrence records and

examine the spatial relationships of records occurring outside these core

areas.

The Nature of the Data

The analyses and discussion presented in this chapter are based on a

variety of data from many sources. We believe they represent most of what

is known concerning where and when lynx have occurred within the contiguous United States. We divide these data into three types. The first type

is written accounts describing the occurrence patterns of lynx. For many of

these accounts, and particularly the older ones, data are not presented to

support the written statements. Because of the paucity of other information,

our understandings of the historical distribution of lynx prior to the 20th

century rely heavily on these accounts.

The second type of data are state- and province-level trapping records.

These data are recorded in Novak et al. (1987) for all states and Canadian

provinces that maintained records. The strength of trapping data is that it

has been collected annually for many years using similar methods. These

data have been used to analyze time trends (Elton and Nicholson 1942;

Ranta et al. 1997), but there are several problems associated with using

these data in this manner. A general problem with trapping data is that they

do not represent constant effort: More lynx trapped could be due to more

trapper effort rather than more lynx. A particular problem associated with

lynx is confusion with bobcats, especially large, pale bobcats that were often

referred to as “lynx-cats” (Novak et al. 1987). For these reasons, we limit our

analysis of trapping data to those states for which we could confirm that lynx

and bobcat harvest records were tabulated separately.

Lastly we have spatially referenced occurrence data. These data come from

many sources: the primary literature, unpublished reports, museum specimens, state survey efforts, and casual observations (See Appendix 8.1).

These data, because of their sources and types, have varying reliability.

Although these data carry a reliability index, the index is not constant
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McKelvey—Chapter 8

across data sets. Even if it were, reliability at the level of the individual

observation does not necessarily infer overall reliability for a data set.

Reliability of the data set depends not only on the intrinsic reliability of

each datum, but also on the rarity of the organism. That is, as an organism

becomes more rare, the proportion of false positives increases. For example,

we know that bobcats are sometimes misidentified as lynx. If lynx were

correctly identified 100% of the time and bobcats correctly identified 99%

of the time, we have very reliable identification at the level of the individual

observation. However, if 1,000 bobcats are seen for every lynx, then for

every 1,000 wildcat identifications 10 will be classified as lynx, but on

average only one will actually be a lynx. Even if lynx were extirpated from

the area in question, these data would still include 10 “lynx.” While we note

the number of “reliable” points by type for each state (Table 8.1), we do no

formal analyses based on these designations. Rather, for analyses where

high reliability for each occurrence is essential, we used a subset of these

data we call “verified records.” We considered a record to be verified only

if it was represented by a museum specimen or a written account in which

a lynx was either in someone’s possession or observed closely, i.e., where a

lynx was killed, photographed, trapped and released, or treed by dogs.

Information obtained from snow-tracking surveys conducted by trained

individuals are discussed where appropriate, but neither tracks nor sighting

reports were considered to represent a verified record.

Data quantity and quality vary greatly from state to state (Table 8.1).

Because none of these data, with the possible exception of trapping records,

represent anything like a census, using numbers of occurrences to infer

numbers of lynx in an area during a specific time period or to make

comparisons between states is not appropriate. Assessing changes in occurrence at the state level can be attempted from the verified records, but we

caution that inferences derived from those data are potentially unreliable.

We know, for instance, that a lynx was killed in New Hampshire in 1992. This

does not, however, lead to any conclusions concerning the current status of

lynx populations in New Hampshire. Similarly, simply because we have

no verified records for lynx in Michigan after 1985 does not mean that lynx

are currently absent from Michigan.

In most states, the majority of the data consist of physical remains or track

data collected by state agencies. In the West, however, Colorado and Oregon

have a high proportion of visual data (Table 8.1), and the patterns in these

states should be considered to be less reliable. In the Great Lakes states,

Wisconsin has a high proportion of visual sightings, but the areas in which

they occur also contain physical specimens and particularly tracks.
210

Chapter 8—McKelvey Table 8.1—Lynx occurrence data used in this chapter. R means reliable, U means of unknown reliability. See text for a discussion of data types and reliability.

Unknown occurrences were often older records in existing databases where data other than the location were not retained. In the western states,

many records of unknown reliability are associated with locations reported by Maj and Garton (1994) that are not duplicated in other databases.

Spatially referenced occurrencesa

Physicalb Tracks Visual Trappingc Verified recordsd

State R U R U R U Unknown Total Time period Number Time period Number

Colorado 33 0 25 25 26 45 42 196 1878-1974 17

Connecticut 0 0 0 0 0 0 0 0 1839 1

Idaho 96 0 74 1 58 4 1 234 1874-1991 74

Illinois 0 0 0 0 0 0 0 0 1842 1

Indiana 0 0 0 0 0 0 0 0 1832 1

Iowa 1 0 0 0 0 0 0 1 1869-1963 6

Maine 15 4 6 1 0 2 0 28 1862-1999 35

Massachusetts 0 0 0 0 0 0 0 0 1855-1918 5

Michigan 32 23 8 5 2 2 9 81 1842-1983 44

Minnesota 179 6 7 4 4 6 81 287 1930-1983 5,585 1892-1993 76

Montana 588 0 518 24 63 7 342 1,542 1950-1997 3,012 1887-1999 84

North Dakota 7 0 0 0 0 0 1 8 1850-1963 16

Nebraska 4 0 0 0 0 0 4 8 1890-1983 13

New Hampshire 40 1 7 5 3 6 0 62 1928-1964 139 1860-1992 5

Nevada 2 0 0 0 0 0 0 2 1916 2

New York 13 2 0 0 1 0 1 17 1877-1973 24

Oregon 15 5 0 1 9 27 15 72 1897-1993 12

Pennsylvania 1 1 0 0 0 0 0 2 1903-1926 4

South Dakota 3 0 0 0 0 0 3 6 1875-1973 10

Utah 11 1 2 0 4 4 5 27 1916-1991 10

Vermont 4 0 0 0 0 0 0 4 1928-1965 4

Washington 144 7 384 107 43 23 57 765 1960-1989 215 1896-1999 134

Wisconsin 12 32 7 42 4 65 0 162 1870-1992 29

Wyoming 83 5 92 7 113 18 43 361 1856-1999 30

aOnly data spatially referenced to at least the county level are included in these totals.

bPhysical remains data also include photographs, radiotelemetry collared animals, and recent hair samples. These other occurrence types generally make up a tiny proportion of the total. cTrapping data are presented for those states where we confirmed the reliability of these data.

dVerified records are spatially referenced to the state and in some cases contain additional records not in the spatially referenced occurrence data.
211

McKelvey—Chapter 8

History of Lynx Occurrence in the Contiguous

United States

In previously published distribution maps for lynx in North America, the

lynx’s range in the United States is depicted as marginal or peninsular

extensions of the northern taiga into the western mountains, Great Lakes

region, and Northeast (Burt 1946; Seton 1929; Hall 1981; McCord and

Cardoza 1982). As explained in Chapter 3, these regions represent southern

extensions of boreal forest in the United States, each of which has unique

tree species composition, natural disturbance regimes, and histories of

human-mediated changes in the composition, extent, and juxtaposition of

available habitats. In the next section, we review the history of lynx

occurrence and abundance in each of these three regions on a state-by-state

basis. Although state boundaries generally do not correspond to ecological

ones, lynx populations are managed by individual state wildlife or game

agencies, and published literature is often limited to reporting or summarizing information from a particular state.

To evaluate the history of lynx occurrence in the contiguous United States,

we compiled verified records from each state by obtaining data on museum

specimens and reviewing published literature and unpublished state agency

reports and harvest records. If there was a discrepancy between published

tabulations of harvest data (Novak et al. 1987) and records obtained directly

from state or provincial agencies, we assumed the latter to be more reliable

and used those data in our analyses. To obtain museum specimen records of

lynx in the contiguous United States, we contacted 88 museums or private

collections in North America, including all mammal collections with >10,000

specimens, any museum from which lynx specimens had been reported, and

at least one major museum from each state in which lynx have been

reported to occur. We located 343 museum records of lynx in the contiguous United States from 41 museums or private collections, dating from

1842 to 1993.

Northeastern States

Maine—We located 35 museum specimens from Maine: 15 have no date

associated with them and 12 were collected between 1862 and 1897. Only

eight were obtained during this century: one in 1903, four in 1948, two in

1954, and one in 1993. Among these specimens, seven are kittens that either

have no date of collection or were collected in the 1860s, verifying that a

breeding population of lynx occurred in Maine during historical times.

Reproduction of lynx in Maine during recent times was verified in 1964,
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Chapter 8—McKelvey

when three kittens were presented to the state for bounty; additional

verified records are known from 1966, 1973 (2 lynx), 1987, 1989, 1990, 1993,

and 1998 (Hunt 1974; Jakubus 1997; Maine Dept. of Inland Fisheries and

Wildlife, unpublished). Anecdotal evidence suggests that lynx were also

breeding in the state during the 1970s; Chief Warden Alanson Noble reported seeing an adult lynx and kitten on the Southwest Branch of the St.

John River in March 1976 (Jakubus 1997). Snow-tracking surveys have

been conducted by the Maine Dept. of Inland Fisheries and Wildlife in

areas with historical lynx records each winter since 1994-1995. Lynx tracks

were found in all years to date except 1995-1996 and 1996-1997 (Jakubus

1997; C. McLaughlin, personal communication). Radiotelemetry research

on lynx was initiated by the state in 1999; to date (September 1999), one

female and one male lynx have been trapped and radio-collared. In June

1999, radiotelemetry monitoring of the female led researchers to a den with

2 kittens, verifying reproduction of lynx in Maine for the first time since

1964 (C. McLaughlin, personal communication).

Written records of Manly Hardy, a trapper and fur buyer in northern and

eastern Maine during the late 1800s, indicate that during this time lynx

occurred only in the northern portion of the state, and were not abundant;

Manly also noted that lynx numbers varied greatly in different years,

suggesting that population fluctuations may have occurred historically

(Jakubus 1997, unpublished). According to Palmer (1937, unpublished),

lynx had not been found in extreme southwestern Maine since the time of

European colonization; by the 1930s, lynx only occurred in the northern

half of the state. By the mid-1960s, lynx were reportedly absent from all

but the north and northwestern portion of the state, where they were

considered scarce (Hunt 1964). In 1967, the Maine legislature repealed the

lynx bounty payment and gave the species complete protection from hunting or trapping.

New Hampshire—New Hampshire is the only state in the Northeast

with a long and detailed history of commercial lynx harvest: From 1928 to

1964, 139 lynx were harvested in New Hampshire (Orff 1985, unpublished).

In the 10-year period from 1928 to 1939, 114 lynx were harvested (mean = 10.4

per year, range 1-20), but the population appears to have declined significantly in the late 1930s; only 25 lynx were taken from 1940 to 1964 (mean =

1.0 per year, range 0-3), when trapping of lynx in the White Mountain

National Forest was prohibited (Fig. 8.1). According to data compiled by

Clark Stevens of the University of New Hampshire, 97% of lynx bountied

from 1931 to 1954 were killed in the White Mountains of northern New

Hampshire in Coos, Grafton, and Carroll Counties (Silver 1974). In 1965, the

bounty was repealed by the State legislature but was reinstituted outside the
213

McKelvey—Chapter 8

White Mountains in 1967 (Siegler 1971). In 1971, the lynx was protected

from all harvest in New Hampshire; in 1980 it was listed as a state endangered species (Orff 1985, unpublished).

Except for harvest data, there are few verified records of lynx from New

Hampshire; only four museum specimens are known: one undated and one

each from 1860, 1947, and 1948. Only two recent verified records are known

from New Hampshire; both were adult males that were road-killed in 1966

and 1992 (Litvaitis 1994; E. Orff, personal communication). From January

to March 1986, Litvaitis et al. (1991) surveyed approximately 100 km2

 of

the White Mountain National Forest on snowshoes (20 transects 2.5-10.0 km

long) 24-96 hours after snowfall but found no lynx tracks. They concluded that their failure to find tracks and the scarcity of recent verified

detections indicated that a viable population of lynx did not occur in

New Hampshire at that time. We found no direct evidence of lynx breeding

in New Hampshire in either historic or recent times.

No

data

0

5

10

15

20

25

30

Number of pelts

1919\20

1925\26

1931\32

1937\38

1943\44

1949\50

1955\56

1961\62

1967\68

1973\74

1979\80

1985\86

1991\92

1997\98

Season

closed

Figure 8.1—Lynx harvest data from New Hampshire, 1928-1964.
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Chapter 8—McKelvey

The history of lynx in New Hampshire has been summarized in detail by

several authors (Litvaitis et al. 1991; Siegler 1971; Silver 1974). Information

on lynx occurrence and population status prior to the early 1900s is fragmentary and difficult to interpret because lynx and bobcat were typically

considered together as “wildcat” in early records and reports (Silver 1974).

From the late 1920s through the 1930s, lynx harvests in New Hampshire

were relatively high (from 1934 to 1937, ≥15 lynx were trapped/year) and

fluctuated strongly in number, reaching a peak in the mid-1930s that was

coincident with a population peak recorded in Quebec (Figs. 8.1 and 8.2;

Litvaitis et al. 1991). After 1940, lynx harvests remained low (0-3 trapped/

year) until the trapping season was closed in 1965 (Fig. 8.1). Based on these

records, Litvaitis et al. (1991) argued that historic populations of lynx in

New Hampshire (and, probably, Maine) and Quebec were continuous at one

time, and that immigrating lynx entered New Hampshire on a regular

basis. They further speculated that large-scale timber harvesting for agricultural and residential development north of the Saint Lawrence Seaway in

southern Quebec resulted in the isolation of lynx populations in New

England, which were unable to remain viable without occasional immigrations of lynx from the north.

0

5,000

10,000

15,000

20,000

25,000

30,000

Number of pelts

1919\20

1925\26

1931\32

1937\38

1943\44

1949\50

1955\56

1961\62

1967\68

1973\74

1979\80

1985\86

1991\92

1997\98

Mean = 2,012

SD = 1,405

CV = 0.70

10.9

1926 10.5

1935 6.2

1945 2.2

1954

4.3

1964

3.9

1973

1.5

1981

1.4

1992

Figure 8.2—Lynx harvest data for Quebec, 1919-1997; peak years are

indicated, as well as a measure of amplitude calculated by dividing the peak

harvest value by the previous low harvest value.
215

McKelvey—Chapter 8

Vermont—Published distribution maps for lynx in New England include

Vermont within the range of lynx (Hamilton 1943; Godin 1977), but only four

records verifying their occurrence at any time in the state could be found.

Only one museum specimen is known from Vermont, a lynx collected in

1965 from Royalton in northern Windsor County. A lynx was reportedly

killed in 1928 in Windam, Windam County (Osgood 1938); another was

taken in Ripton, Addison County in 1937 (Hamilton and Whittaker 1979),

and a third was trapped in the town of St. Albans, Franklin County in 1968

(Anonymous 1987, unpublished). In 1987, the Vermont Agency of Natural

Resources classified the lynx as a state endangered species.

Massachusetts and Connecticut—No museum specimens of lynx could

be found from Massachusetts or Connecticut, and verified records of lynx

occurrence in these states are extremely rare. Parker (1939) describes a

mounted specimen in the Worcester Museum of Natural History taken in

Princeton in the winter of 1884-1885, but we were unable to locate this

specimen. A lynx was reportedly killed in Concord, Middlesex County

about 1855 (F.C.B. 1878), one was trapped about 1865 in Goshen, Hampshire

County (Barrus 1881), one was killed in 1905 in Lanesborough, Berkshire

County (Central 1905), and another was captured in 1918 near Mt. Greylock,

also in Berkshire County (Eaton 1919). Crane (1931) considered the lynx to

be “very rare” in western Massachusetts and quoted a report from 1840 that

stated, “[The lynx] was once common in the State, but appears now only in

the depth of winter, and as a straggler.” The lynx is now considered

extirpated from Massachusetts (Cardoza, in press). Only one verified record

of lynx in Connecticut was found: one was shot at Southington, Hartford

County in 1839 (Goodwin 1935). Goodwin (1935) concluded that the “lynx

is now a very rare animal in Connecticut, and it probably never was very

common.”

New York—The history of lynx in New York was described in detail by

Bergstrom (1977, unpublished) and Brocke (1982, unpublished), and much

of the following account comes from these sources. Historical records

suggest that the lynx was once relatively common in New York, but that its

range retreated northeastward as early as the mid- to late-1800s. Rafinesque

(1817) observed lynx in the Catskill, Allegheny, and Adirondack Mountains,

and a lynx was killed near Rhineback on the Hudson River in the eastern

foothills of the Catskill Mountains in southeastern New York during the

winter of 1877-1878 (Mearns 1899). A report on the zoology of New York in

1842, however, failed to note the lynx’s presence in the southern portion of

the state, describing its range as “not uncommon in the northern districts of

the state [presumably the Adirondack Mountains]” (DeKay 1842). Anecdotal reports gathered by Harper (1929) indicated that the lynx was fairly
216

Chapter 8—McKelvey

common in the Adirondacks in the 1880s and 1890s, but a report on the

mammals of the Adirondack region in 1884 described the lynx as rare and

occurring mostly in the eastern portions of the region (Merriam 1884). By the

turn of the century, Miller (1899) speculated that, although the lynx still

occurred in the Adirondacks and may still occur in the Catskills, the species

was rapidly approaching extinction in New York.

Verified evidence of the occurrence of lynx in New York after 1900 consists

of 23 records scattered in time from 1907 to 1973 (Table 8.2). All but four

of these records are from the Adirondack Mountains, an area of boreal

forest adjacent to the Green Mountains of Vermont and the White Mountains of New Hampshire. These high-elevation boreal zones may have

served as a corridor of suitable habitat, providing connectivity among areas

occupied by lynx in the northeastern United States with those in southeastern Canada (see map in Bailey 1998). Until 1970, the lynx was an unprotected

species in New York and bounty payments were made for their pelts. The

bounty was removed in 1970, but the lynx remained unprotected until 1976,

when it was declared a game animal with closed hunting and trapping

seasons. The New York Department of Environmental Conservation considers the lynx to be extirpated as a breeding species in the State, and has

recommended that it be listed as a state endangered species (Bergstrom 1977,

unpublished).

In response to a lack of evidence for the continued presence of lynx in the

State, a program to reintroduce lynx to the Adirondack Mountains was

initiated in the late 1970s (Brocke et al. 1990). A feasibility study (Brocke 1982,

Table 8.2—Verified records of lynx in New York.

Date Record Reference

Unknown 1 specimen from Jefferson County (western Adirondacks) Academy of Natural Sciences of

Philadelphia

1877-88 1 killed near Rhinebeck on the Hudson River (southeastern New York) Mearns 1899

1907 2 killed in Willseyville, Tioga County (south-central New York) Seagers 1948

1908 1 killed in Nine Mile Swamp, near North Brookfield (Adirondacks) Whish 1919

1908 3 killed in the Quaker Bridge region (Adirondacks) Whish 1919

1909 5 killed near Lowville, Lewis County (western Adirondacks) Whish 1919

1916 1 killed in Oneida County (southwestern Adirondacks) Anonymous 1952

1918 1 trapped near Upper Jay, Essex County (northeastern Adirondacks) Anonymous 1918

1928 1 killed on Hogback Mountain, Essex County (northeastern Adirondacks) Anonymous 1952

1930 1 taken alive near Elizabethtown, Essex County (northeastern Adirondacks) Seagers 1948

Late 1930s 1 killed near Azure Mountain, Waverly, Franklin County (northern Adirondacks) Bergstrom 1977, unpublished

1951 1 shot on Battle Hill, Washington County (eastern New York) Seagers 1951

1961 1 shot near Sherman Lake, Crown Point, Essex County (northeastern Adirondacks) Bergstrom 1977, unpublished

1962 1 trapped on Black Cat Mountain in Arietta, Hamilton County (central Adirondacks) Anonymous 1963

1964 1 killed near Croghan, Lewis County (western Adirondacks) Fountain 1976

Winter 1965-66 1 trapped on Pine Mountain, near Wells, Hamilton County (central Adirondacks) Anonymous 1966

1968 1 specimen from Catskill, Delaware County (southeastern New York) American Museum of Natural

History

1973 1 trapped in Altona, Clinton County (northeastern Adirondacks) Bergstrom 1977, unpublished
217

McKelvey—Chapter 8

unpublished) indicated that a suitable colonization area for lynx existed in

the Adirondacks above 800 m where bobcats (a potential competitor) were

rare and where snowshoe hare populations were dense enough to support

lynx. Between 1989 and 1991, after about 10 years of planning and public

input, 83 lynx ranging in age from <1 to 10.5 years were translocated from

the Whitehorse area of the Yukon Territory in Canada, radio-collared, and

released in the High Peaks area of the Adirondack Mountains (Brocke et al.

1991; K. Gustafson, personal communication). These animals were monitored for two years until the transmitter batteries failed; recorded mortality

was high: 37 of 83 were known to have died, 16 of which were road-killed.

Available evidence indicates that the reintroduction was unsuccessful; since

the last radiotracking season in the winter of 1992-1993, there have been no

verified records of lynx in the Adirondacks and no indication that any

reintroduced lynx bred after they were released (K. Gustafson, personal

communication).

Pennsylvania—A comprehensive review of paleontological, historical,

and specimen records of lynx in Pennsylvania was conducted by Williams

et al. (1985). Surprisingly, they report 26 records of lynx being killed in

Pennsylvania from 1790 to 1900. Bobcats and lynx were often confused in

reports from the 18th and 19th centuries, however, so we view these records

with caution. Recent records are extremely scarce: Only one museum

specimen exists, a lynx collected near Antrium, Tioga County in 1923. A lynx

was reportedly killed in 1903 in Clinton County and two others in 1926 in

Monroe County (Shoemaker 1929; Grimm and Whitebread 1952, unpublished). The majority of records reported by Williams et al. (1985) are from

the northern counties where unbroken, mature boreal forest existed prior to

extensive logging of Pennsylvania forests in the latter half of the 19th

century. This area also represents the southwestern-most extension of mixed

deciduous-coniferous forest in the northeastern United States (Bailey 1998).

Great Lakes and North-Central States

Michigan—Historical accounts of varying reliability, summarized by

Burt (1946) and Baker (1983), suggest that in the 1800s lynx may have been

widely distributed in both the Lower and Upper Peninsulas of Michigan.

However, six of seven verified records from the 1800s are from the Upper

Peninsula near the Wisconsin border; a lynx killed in Washtenaw County in

1842 and five lynx trapped along the Au Sable River in Oscoda County in

1917 represent the only verified records of lynx from the Lower Peninsula

(Table 8.3). Verified records of lynx occurrence in Michigan in the early 1900s

are extremely scarce: five specimens were collected on Isle Royale in 1904
218

Chapter 8—McKelvey

and 1905, and mortality records from the Upper Peninsula are known only

from 1910, 1912, 1923, and 1928 (Table 8.3). By 1928, the Michigan Department of Conservation reported the lynx to be extirpated from the Lower

Peninsula and nearly so from the Upper Peninsula; by 1938, the lynx was

declared on the verge of extinction throughout Michigan and, in later

reports, was not even mentioned (Harger 1965).

Table 8.3—Verified records of lynx in Michigan.

Date Record Reference

Unknown 1 specimen from Michigan. Zoology Museum, University of Michigan

(1842)a 1 taken near Petersburg, Monroe County (LP)b Wood and Dice 1924

1842 1 killed in Washtenaw County (LP) Wood 1922

(1844)a 1 killed along the Au Sable River, Oscoda County (LP) Wood and Dice 1924

Prior to 1874 3 specimens from Marquette, Marquette County (UP)c Peabody Museum, Yale University

1874 1 specimen from Gogebic County (UP) Milwaukee Public Museum

(1875)a Several caught at headwaters of Manistique River,

Schoolcraft County (UP) Wood and Dice 1924

1889 1 specimen from Ishpening, Marquette County (UP) Milwaukee Public Museum

1890-91 1 taken near Gogebic Lake, Gogebic County (UP) Dice and Sherman 1922

(1894)a 1 taken 18 miles east of Cadillac, Wexford County (LP) Wood and Dice 1924

(1894-95)a 34 killed in Mackinac County (UP) Wood and Dice 1924

(1903)a 1 trapped at Big Creek, Oscoda County (LP) Wood and Dice 1924

1904-05 5 collected on Isle Royale, Keneenaw County (UP) Zoology Museum, University of Michigan

1910 1 taken at Rudyar, Chippewa County (UP) Wood and Dice 1924

1912 1 taken near Sault Ste. Marie, Chippewa County (UP) Wood and Dice 1924

1917 5 trapped along the Au Sable River near Luzerne,

Oscoda County (LP) Harger 1965

1923 1 specimen from Mackinac County (UP) National Museum of Natural History

1928 1 trapped in Ontonagon County (UP) Baker 1983

1940 1 trapped on Bois Blanc Island, Mackinac County (UP) Harger 1965

1949 1 trapped at Engadine, Mackinac County (UP) Harger 1965

1953 1 specimen from Dunbar, Marquette County (UP) Erickson 1955; Zoology Museum, University of Michigan

1955 1 specimen from Marquette County (UP) Grand Rapids Public Museum

1958 1 specimen from Rockview, Chippewa County (UP) Michigan State University Museum

1960 1 shot near Rockview, Chippewa County (UP) Harger 1965

1960 1 specimen from Trout Lake, Chippewa County (UP) Michigan State University Museum

1961 1 specimen from Pickford, Chippewa County (UP) Zoology Museum, University of Michigan

1961 1 shot near Dafter, Chippewa County (UP) Harger 1965

1962 1 shot near Pickford, Chippewa County (UP) Harger 1965

1962 1 shot near Nun’s Creek, Mackinac County (UP) Harger 1965

1962 1 trapped near Channing, Dickinson County (UP) Harger 1965

1962 1 shot 7 mi. N of Iron Mountain, Dickinson County (UP) Harger 1965

1962 1 specimen from Dunbar, Chippewa County (UP) Michigan State University Museum

1962 1 shot in Ontonagon County (UP) Harger 1965

1962 1 shot near Sagola, Dickinson County (UP) Harger 1965

1962 1 shot near Trout Lake, Chippewa County (UP) Harger 1965

1962 1 shot near Manistique, Schoolcraft County (UP) Harger 1965

1962 1 shot between Topaz and Matchwood, Ontonagon County (UP) Harger 1965

1962 1 specimen from Sault Ste. Marie, Chippewa County (UP) Michigan State University Museum

1962 1 shot near Dafter, Chippewa County (UP) Harger 1965

1966 1 specimen from Schoolcraft County (UP) Michigan State University Museum

1983 1 killed in Mackinac County (UP) Michigan Dept. of Natural Resources

a

Wood and Dice (1924) caution that there is a strong possibility that some of these records may be of bobcats; we therefore consider these records to be probable,

but not verified, records of lynx in Michigan. b

LP = Lower Peninsula.

c

UP = Upper Peninsula.
219

McKelvey—Chapter 8

By the mid-1940s, Burt (1946) considered the lynx to be “probably

gone from the fauna of Michigan,” but there are verified records from

1940, 1949, 1953, 1955, and 1958 (Table 8.3). From 1960 to 1962, 16 lynx were

killed on the Upper Peninsula, including 12 in 1962, following an unusually

large irruption of lynx in south-central Canada during the early 1960s

(Adams 1963; Gunderson 1978). Harvest records from Ontario, Manitoba,

and Saskatchewan clearly depict the irruption of lynx during this time and

its unusually high amplitude (Fig. 8.3), which was several times greater

than during previous peaks recorded this century. Since the early 1960s,

however, only two verified records of lynx in Michigan could be found: one

in 1966 and another in 1983 (Table 8.3). The lynx has been fully protected in

Michigan since 1983, when it was classified as a threatened species; it was

reclassified as a state endangered species in 1987.

Wisconsin—The history of lynx in Wisconsin was reviewed in detail by

Thiel (1987), including a comprehensive compilation of specimen and

mortality records. Only 11 verified records of lynx in Wisconsin prior to

0

5,000

10,000

15,000

20,000

25,000

30,000

Number of pelts

1919\20

1925\26

1931\32

1937\38

1943\44

1949\50

1955\56

1961\62

1967\68

1973\74

1979\80

1985\86

1991\92

1997\98

Mean = 5,280

SD = 5,214

CV = 0.9

5.4

1923

3.1

1934

1.1

1943

4.8

1952

11.2

1959

5.3

1969

3.0

1979

2.5

1991

Figure 8.3—Lynx harvest data for Saskatchewan, Manitoba, and Ontario combined,

1919-1997; peak years are indicated, as well as a measure of amplitude calculated by

dividing the peak harvest value by the previous low harvest value.
220

Chapter 8—McKelvey

1962 are known, including eight records dating from 1870 to 1926 and three

specimens collected in 1946, 1954, and 1955 (Table 8.4). The lynx is reported

to have always occurred most frequently in the northern portion of Wisconsin (Jackson 1961), and the distribution of verified records supports this

assertion. Only three records are known from the southernmost counties

near the Illinois border; the last of these was in 1946. The last known

occurrence of the lynx in central Wisconsin was in 1972, and all but a few

records since 1965 are from counties located near the borders of northern

Minnesota and the Upper Peninsula of Michigan (Table 8.4). An unusual

increase in lynx mortalities occurred in Wisconsin during the 1960s and early

1970s (Table 8.4; Thiel 1987). The number of verified records of lynx being

killed (16) in Wisconsin during this time period exceeded those from the

previous 100 years (Table 8.4). Similar increases in lynx mortalities during

these same time periods have been reported for Minnesota, North Dakota,

and Montana (Adams 1963; Gunderson 1978; Mech 1973, 1980).

Table 8.4—Verified records of lynx in Wisconsin.

Date Record Reference

1870 1 specimen from Jefferson County Zoological Museum, University of Wisconsin, Madison

1899 2 specimens from Iron County Zoological Museum, University of Wisconsin, Madison

1901 1 specimen from Gordon, Douglas County Zoological Museum, University of Wisconsin, Madison

1907 1 killed in Middleton, Dane County Schorger 1947

1908 1 specimen from Edson, Chippewa County Museum of Natural History, Wisconsin State

University, Stevens Point

1917 1 trapped in La Crosse, La Crosse County Milwaukee Public Museum

1926 1 shot in Shell Lake, Washburn County Stouffer 1961 (cited in Thiel 1987)

1946 1 specimen from Spring Green, Sauk County Zoological Museum, University of Wisconsin, Madison

1954 1 specimen from Hurley, Iron County Zoological Museum, University of Wisconsin, Madison

1955 1 specimen from Richland, Rusk County Zoological Museum, University of Wisconsin, Madison

1962 1 shot in Rusk County Thiel 1987

1963 1 shot in Douglas County Thiel 1987

1964 1 killed in Jackson County Thiel 1987

1965 or 1968 1 killed in Pierce County Thiel 1987

1965 1 killed in Green Lake County Thiel 1987

1965 1 killed by a train near Viroqua, Pierce County Thiel 1987

1965 1 specimen shot while swimming at the mouth of the

St. Louis River, Douglas County University of Wisconsin, Superior

1971 1 shot in Trempealeau County Thiel 1987

1972 1 shot in Trempealeau County Thiel 1987

1972 1 specimen from Woodruff, Vilas County Zoological Museum, University of Wisconsin, Madison

1972 1 killed by car in Oneida County Thiel 1987

1972 1 trapped in Price County Thiel 1987

1972 1 specimen from Lake Noquebay, Marinette County Technical Center, University of Wisconsin, Marinette

1972 1 shot in Tomahawk, Lincoln County Thiel 1987

1973 1 trapped in Iron County Thiel 1987

Winter 1972-1973 1 specimen from Oneida or Vilas County Zoological Museum, University of Wisconsin, Madison

1992 1 specimen from Burnette County Museum of Natural History, Wisconsin State

University, Stevens Point

1992 1 specimen from St. Croix County Museum of Natural History, Wisconsin State

University, Stevens Point
221

McKelvey—Chapter 8

Since that time, only two records of lynx being killed in Wisconsin are

known; both were in 1992. Lynx tracks were detected by the Wisconsin

Department of Natural Resources during wolf surveys from 1993 to 1997,

but all were within six to seven miles of each other, suggesting that they may

represent the same individual (Wydeven 1998, unpublished). Lynx have

been completely protected in Wisconsin since 1957, when harvest seasons

and bounty payments were eliminated; in 1972, the lynx was placed on the

state endangered species list.

Indiana, Illinois, Ohio, and Iowa—Lyon (1936) reviewed published

reports of lynx from Indiana in the 1800s and concluded that none could be

considered verified records, given the confusion over terms used for cougar,

bobcat, and lynx in these sources. Mumford (1969) believed that some of

these records might be authentic, however, and cited a report of a lynx being

killed at Bicknell, Knox County in southwestern Indiana in 1832. Records

from Illinois are similarly scanty; Kennicott (1855) included the lynx in his

list of mammals occurring in Cook County (now metropolitan Chicago),

and specimen records of the Academy of Natural Sciences of Philadelphia

include a lynx collected in Illinois that was obtained by the museum in

June 1842 (this specimen is now missing from the collection). No verified

records of lynx from Ohio could be found, but Smith et al. (1973) included the

species in a list of mammals that once bred in Ohio but which have now been

extirpated. Historical records of lynx in Iowa are more prevalent; Spurrell

(1917) reported that three lynx were trapped in Sac County in northwestern

Iowa in 1869 and one in 1875; another lynx was apparently killed in Iowa in

1906 (Gunderson 1978). In July 1963, a lynx was shot in Shelby County in

west-central Iowa (Rasmussen 1969); none has been reported since that time.

Minnesota—Published historical information on lynx in Minnesota is

virtually nonexistent. In an early monograph on the mammals of

Minnesota, Herrick (1892) was uncertain if the lynx was even a member of

the state’s fauna at that time. Hunters consistently told him that two species

of wildcats occupied the state but all specimens he examined, including

those presented to him as “lynx,” proved to be bobcats. Although lynx were

apparently not common at that time, their presence in Minnesota during the

late 1800s is confirmed by the existence of eight museum specimens dating

from 1892 to 1900. Two of these specimens are from Sherbourne County in

south-central Minnesota and the remainder are from Itaska County in the

north-central portion of the state. Verified records prior to the south-central

Canadian population peak of 1959 are scarce: a lynx was collected in

Sherbourne County in 1927, one in Morrison County in 1928, one in St. Louis

County in 1951, one in Aitkin County in 1953, and one in Lake of the Woods

County in 1955.
222

Chapter 8—McKelvey

The only other documented information on lynx in Minnesota prior to

1960 are harvest records published by the state Department of Natural

Resources (Fig. 8.4; Henderson 1978). However, these records should be

considered with caution; data from 1930 to 1976 do not represent reports of

catch or carcass records obtained during the year of harvest but, rather, are

estimates of harvest obtained in later years by mail survey. These records

indicate, however, that lynx have been harvested in relatively high numbers

in Minnesota in most years since 1930 (mean = 103 per year, range = 0-400).

Peaks in the harvest record that occurred in 1962 and 1973 are also reflected

in museum specimen records. All other specimens from Minnesota are from

the early 1960s and early 1970s: one from 1960, one from 1961, four from

1962, 14 from 1963, one from 1964, 25 from 1972, and one from 1973. During

this time, Mech (1980) trapped 14 lynx in northeastern Minnesota: five in

1972, three in 1973, four in 1974, and two in 1975.

0

100

200

300

400

500

Number of pelts

1919\20

1925\26

1931\32

1937\38

1943\44

1949\50

1955\56

1961\62

1967\68

1973\74

1979\80

1985\86

1991\92

1997\98

1930

1940

1952

1962 1973

No

data

Season

closed

Figure 8.4—Lynx harvest data from Minnesota, 1930-1983; years of peak harvest values are

indicated.
223

McKelvey—Chapter 8

The continued occurrence of lynx in Minnesota in the late 1970s and early

1980s is verified by state records dating from 1977 to 1983, which represent

reports of catch from hunters and trappers at the close of each trapping

season. Altogether, 161 lynx were harvested in Minnesota during this

period (mean = 23, range = 9-42). When expected increases in lynx numbers

failed to occur in the early 1980s, the state closed the harvest season for lynx;

it has not been reopened. Since the closure of lynx harvests, only three

verified lynx records are known: one trapped in Cook County in 1992, and

one illegal possession in Anoka County and one road-kill in St. Louis County

in 1993 (DonCarlos 1994, unpublished). The only documented records of

lynx breeding in Minnesota are two females that gave birth to kittens in the

spring of 1972 (Mech 1973).

North Dakota—The northern Great Plains are generally not included in

the range of lynx (Burt 1946; McCord and Cardoza 1982; Quinn and Parker

1987; Seton 1929), yet there are a surprising number of historical specimen

records from this region. Bailey (1926) reports numerous anecdotal accounts

of lynx being trapped in North Dakota in the 1800s and lists three specimen

records: one collected at Fort Union (now Buford, North Dakota, on the

Montana border) in 1850, one at Arrowhead Lake in east-central North

Dakota in 1907, and one at Cannonball near the south-central border in 1915.

Other reports include several lynx that were killed in the northeastern

portion of the state, including one at Lakota in 1915 and two near Grafton in

1909 and 1911. Bailey (1926) makes several references to periodic increases

in lynx numbers in this region, noting that “in some years, the lynx is

common over the northern portion of North Dakota,” and that many lynx

were captured in north-central North Dakota and brought into taxidermists’

shops in 1908 and 1909, when they were apparently “wandering in search of

new hunting fields.” Two lynx were bountied during the winter of 1954-1955

in the northeastern corner of North Dakota (Adams 1963; Gunderson 1978).

In addition, many lynx apparently were killed in North Dakota during the

lynx irruptions of the 1960s and 1970s (Adams 1963). According to records

of the North Dakota Game and Fish Department, 53 lynx were harvested

from 1962 to 1965 and another 24 from 1972 to 1973. With the exception of

eight museum specimens collected in 1962 and 1963, no other verified lynx

records from North Dakota could be found.

South Dakota and Nebraska—The earliest records of lynx in South

Dakota are both from the southeastern corner of the state, near the borders

of Minnesota and Iowa: One lynx was taken above Sioux City in 1875 and a

museum specimen was collected at Bullhead, Corson County in 1925. Other

reports include one killed in Meade County and two in Pennington County

in 1944; one near Briton, Chamberlain County in 1962; one near Marindahl,
224

Chapter 8—McKelvey

Yankton County in 1962; one near Chamberlain, Brule County in 1963

(Gunderson 1978; Turner 1974); a museum specimen collected in northeastern South Dakota in 1965; and, according to federal Animal Damage

Control records, one killed in 1973 on the Cheyenne River in Pennington

County. Records from Nebraska are of a similar nature: a museum specimen was collected in 1890 near Norfolk in Madison County, and Jones

(1964) reports that a lynx was killed in 1915 near Bassett in north-central

Nebraska, another along the North Platte River near Keystone in 1917, and

a third near Ewing in 1958. All other verified records are associated with

mid-continent lynx irruptions in the early 1960s, 1970s, and 1980s: five from

1963 to 1964; three from 1972 to 1974; and a specimen collected near Herman,

Washington County in 1983 (Nebraska Game and Parks records).

Western Mountain States

Montana—Available information on the history of lynx in Montana in the

late 1800s and early 1900s consists of 12 museum specimens collected

between 1887 and 1921; published information on the recent or historical

status of Montana mammals is limited (Hoffmann et al. 1969). Four specimens were collected in Rosebud and Musselshell Counties in southeastern

Montana in 1887, one in 1895 at upper St. Mary Lake in Glacier National Park,

three in the Bitterroot Mountains in 1910 (two at Bass Creek and one at Elk

Lake), two in 1916 (one without a specific collecting locality and another at

Deer Lodge, Powell County in west-central Montana), one in 1918 at Kintla

Lake in Glacier National Park, and one in 1921 in northwestern Montana

near Plains, Sanders County. The status of lynx in the Glacier Park area of

northwestern Montana during the early 1900s was reviewed by Bailey

(1918), who considered the lynx “more or less common throughout the

Glacier Park region.” He noted, however, that “during years when rabbits

are abundant, [lynx] too, become abundant, and when there are few rabbits,

they are correspondingly scarce.” Five specimens were collected in northwestern Montana in the 1940s and 1950s: one in Lincoln County in 1941, two

in Flathead County in 1954 and 1956, one in Missoula County in 1958, and

one from an unknown locality in the late 1950s.

As in the Great Lakes and north-central States, most later specimen

records are associated with lynx irruptions in the early 1960s and 1970s.

The remaining 19 specimens include 14 obtained from 1962 to 1966 and

five from 1971 to 1976. Data on lynx harvests in the state have been kept

since 1950, however, and show continuous presence of lynx in the state

(Fig. 8.5); since 1977, over 475 lynx were harvested in Montana. Smith (1984,

unpublished) and Brainerd (1985, unpublished) captured 10 lynx during

radiotelemetry studies in western Montana in the 1980s, and an ongoing
225

McKelvey—Chapter 8

study begun in 1998 in the area around Seeley Lake (Chapter 11) has

captured 18 lynx to date (June 1999). Although reliable data on lynx reproduction in Montana are scarce, Brainerd (1985, unpublished) examined 20

trapper-killed lynx carcasses, including several kittens, and found a pregnancy rate for all ages of 70.6%. As was noted for New Hampshire, lynx

harvest data from Montana is cyclic in nature, with peaks corresponding

closely in time and magnitude with those occurring in western Canada,

especially for 1963 and 1971 (Figs. 8.5 and 8.6).

Idaho—Specimen records of lynx in Idaho during the early 1900s are

relatively common; there are 22 museum specimens dating from 1874 to

1917, all of which were collected in the northern and central montane regions

of Idaho north of the Snake River Plain. Specimens were later collected in

central Idaho in 1939 on the Payette National Forest in Valley County and in

1940 in Idaho County. The only other museum records are both from the

northern panhandle region: one from Bonner County in 1954 and one from

0

100

200

300

400

500

Number of pelts

1919\20

1925\26

1931\32

1937\38

1943\44

1949\50

1955\56

1961\62

1967\68

1973\74

1979\80

1985\86

1991\92

1997\98

1963

1971

Quotas 135

120

100

55

40

5 2

No

data

Figure 8.5—Lynx harvest data from Montana, 1950-1997; years of peak harvest

values are indicated.
226

Chapter 8—McKelvey

Shoshone County in 1955. Other verified records prior to 1960 include one

from Shoshone County in 1901, one from Boundary County in 1919, one

from Idaho County in 1936, one from northwest Idaho in 1939, one from

Clearwater County in 1942, five from Caribou County in 1947, two from

Bonneville County in 1955, and one from Idaho County in 1947 (Anonymous

1999, unpublished; Dalquest 1948). With the exception of Caribou and

Bonneville Counties, which are located along the Wyoming border, all of

these records are from the north-central and northern regions of the state.

In an early account of the mammals of Idaho, Davis (1939) described lynx

occurring “in the mountainous regions north and east of the Snake River

Plain.” Rust’s (1946) assessment of the status of lynx in northern Idaho is

similar: “While nowhere abundant in northern Idaho, the Canadian lynx is

fairly well distributed throughout the wooded areas of eight of the 10

northern counties, largely in the Canadian and Hudsonian zones.” He noted

that 25-30 lynx are usually taken by local trappers in addition to those killed

by predator control agents.

0

5,000

10,000

15,000

20,000

25,000

30,000

Number of pelts

1919\20

1925\26

1931\32

1937\38

1943\44

1949\50

1955\56

1961\62

1967\68

1973\74

1979\80

1985\86

1991\92

1997\98

Mean = 6,207

SD = 6,417

CV = 0.96

8.3

1924

2.3

1934 2.2

1944

7.0

1954

11.9

1962

8.0

1971

4.4

1981

2.5

1991

Figure 8.6—Lynx harvest data for British Columbia and Alberta combined, 1919-

1997; peak years are indicated, as well as a measure of amplitude calculated by

dividing the peak harvest value by the previous low harvest value.
227

McKelvey—Chapter 8

There are 35 verified records from 1960 to 1991: four from 1962 to 1969,

18 from 1970 to 1979, 10 from 1982 to 1989, and three from 1990 to 1991;

there are no verified records of lynx in Idaho since 1991 (Anonymous 1999,

unpublished). Although most of these records are from the northern and

central regions of Idaho where lynx occurred historically, six are from

counties in the Snake River Plain, in areas where forest types occupied by

lynx are absent or very fragmentary in extent (see “Lynx Associations with

Broad Cover Types”). These include records from Blaine, Butte, Jerome, and

Twin Falls Counties in 1972; one from Blaine County in 1984; and one from

Power County in 1990. As in other western and midwestern states, there are

a number of anecdotal accounts of lynx being killed or captured in anomalous, low-elevation habitats during lynx irruptions in the 1960s and 1970s

(Lewis and Wenger 1998). These accounts are derived from interviews

initiated in 1997, however, and the lack of similar reports from the 1980s or

1990s suggests that these records represent transient lynx.

Lynx harvest records for Idaho from 1934 to 1981 are available (Novak

et al. 1987), but state biologists consider these data to be unreliable prior

to the late 1980s due to the inclusion of large, pale bobcats in these totals. This

concern appears to be valid; after 1981, when a mandatory pelt-tagging

program was instituted, no lynx was harvested for the next seven trapping

seasons (Anonymous 1999, unpublished). The lynx was unprotected in

Idaho before 1977, when it was classified as a furbearer and harvest was

restricted to a one-month trapping season and a three-month pursuit season.

In 1990, a state-wide quota of three lynx per year was imposed; the season

was closed in 1996.

Washington—Verified records of lynx in Washington are numerous and

well-distributed since the late 1800s. There are 78 museum specimens of

lynx from Washington—more than any other state in the contiguous United

States. The earliest records are represented by 10 specimens collected in

1896 and 1897 on Mt. Adams in the southern Cascade Range near the

border of Oregon. All but a few subsequent specimen records, however, are

from the north-central and northeastern portions of the state near the

Canadian border, including 32 from 1916 to 1920, three from 1928 to 1930,

four from 1939 to 1940, eight from 1951 to 1959, one in 1965, and 17 from

1976 to 1983. In addition, there are three specimens from southeastern

Washington: one from the Blue Mountains in 1931 and two from arid

grassland habitats in 1962 and 1963. A lynx was reportedly trapped near

the southern boundary of Mt. Rainier National Park “some years” prior to

1927 (Taylor and Shaw 1927) and nine lynx were trapped west of Oroville

in Okanogan County in 1938 (photo in Dalquest 1948). According to

Dalquest (1948), each of several trappers regularly took a dozen or more
228

Chapter 8—McKelvey

lynx from remote areas of northeastern Washington each year. No verified

records of lynx are known from coastal areas west of the Cascade Range.

Lynx populations in Washington have been studied in the field more than

anywhere else in the contiguous United States, and most of what is known

of lynx ecology in southern boreal forests comes from these studies (Chapter

13; Koehler and Aubry 1994). Thirty lynx were studied with radiotelemetry

in north-central Washington from 1981 to 1988 (Brittell et al. 1989, unpublished; Koehler 1990), including two radio-collared females that each gave

birth to kittens in 1986 and 1987; snow-tracking indicated that a third,

uncollared female also had a litter of kittens in 1986 (Koehler 1990). From

1995 to 1999, 16 remote-camera photographs of lynx were taken at bait

stations in north-central Washington (J. Rohrer and M. Skatrud, personal

communication).

Management of lynx in Washington began in 1933, when the Washington

Department of Game was established and the lynx was classified as a furbearer that could only be harvested by trapping; the first lynx trapping

season was in the winter of 1934-1935. Monitoring of the lynx harvest did

not begin until 1961, however, at which time trappers were required to

submit reports of catch to the Department of Game. In 1978, the state initiated

mandatory tagging of lynx pelts within 10 days of the close of each trapping

season (Brittell et al. 1989, unpublished). Washington harvest data from

1961 to 1984 (Fig. 8.7) suggests that Washington lynx populations may also

exhibit cyclic patterns of abundance. During the peak harvest of 1969, 26 of

the 31 lynx taken were from the Kettle Range in Ferry County. Only a few

were harvested in this area from 1970 to 1974, but 14 of 19 lynx taken in

Washington in 1975 and 17 of 39 taken in 1976 came from this area. Of the

25 lynx harvested since that time, only two were from Ferry County.

Although trapper effort and pelt prices undoubtedly influence these data,

the lynx population in the Kettle Range appears to have undergone several

dramatic increases and decreases in number from 1961 to 1977. Snowtracking surveys conducted from 1992 to 1996 in the Kettle Range resulted

in only two sets of tracks: one in 1991-1992 and one in 1995-1996 (Washington

Dept. of Fish and Wildlife, unpublished data). Trapping seasons lasted

2-2.5 months from 1961 to 1977 but were shortened to about one month

beginning in 1978; in 1987, a restricted permit system was implemented.

Thus, harvest data after 1977 are not directly comparable to previous data.

A statewide closure of the lynx trapping season was implemented in 1990,

and the lynx was classified as a threatened species in Washington in 1993.

Oregon—The presence of lynx in Oregon in the late 1800s and early 1900s

is documented by nine museum specimens collected from 1897 to 1927.

Verified records after that time, however, are extremely rare. Only three
229

McKelvey—Chapter 8

recent specimens are known, and all were collected in anomalous habitats

within several years of lynx population peaks in western Canada (see “Lynx

Associations With Broad Cover Types”): one in bunchgrass-rimrock habitat in

Wallowa County in 1964, one in a suburban residential area in Benton County

in 1974 (Verts and Carraway 1998), and a third in Harney County in

southeastern Oregon in 1993, where there are only small fragments of

forest types associated with lynx occurrence (see “Lynx Associations With

Broad Cover Types”). Although Bailey (1936) describes early anecdotal

reports of lynx in western Oregon, the 1974 specimen is the only verified

record of lynx west of the Cascade Crest in Oregon.

Wyoming—Reeve et al. (1986, unpublished) conducted a thorough and

comprehensive review of existing information on lynx in Wyoming, including verified records and information obtained through a mail and

telephone survey of knowledgeable individuals in the state. The only verified

record not located by these authors was a museum specimen obtained at

Fort Frederick Steele in Carbon County in southeastern Wyoming

sometime prior to 1872. There are three specimen records from the 1800s,

Figure 8.7—Lynx harvest data from Washington, 1960-1989; years of peak

harvest values are indicated.

0

10

20

30

40

50

Number of pelts

1919\20

1925\26

1931\32

1937\38

1943\44

1949\50

1955\56

1961\62

1967\68

1973\74

1979\80

1985\86

1991\92

1997\98

1964

1969

1976

1984

No data

2Quotas

3

4

Season

closed
230

Chapter 8—McKelvey

including another from southeastern Wyoming in 1856 and one collected

near the headwaters of the Wind River in northwestern Wyoming in 1893.

All other early specimens were from the northwestern portion of the state:

one from the Big Horn Mountains in 1919, two from the Wind River Range

in 1908 and 1919, and seven collected from 1904 to 1920 in the area in and

around Yellowstone National Park in what is now referred to as the “Greater

Yellowstone Ecosystem” (GYE). In an early monograph on the animal life of

Yellowstone Park, Bailey (1930) wrote that lynx “were said to be common

and generally distributed throughout the timbered region.” There are no

recent verified records from the GYE.

Verified records of lynx in Wyoming after 1920 are rare; there are nine

verified records from 1940 to 1957, and all were lynx killed near the westcentral border of the state. A lynx was collected in 1940 at Hoback Rim in

northwestern Sublette County and another in 1949 near Afton, Lincoln

County. The remaining seven records are described by Halloran and

Blanchard (1959) and include five lynx trapped by state predator control

agents in northern Lincoln County from 1952 to 1955, a specimen collected

in northwestern Sublette County in 1954, and a kitten collected in southwestern Teton County in 1957. The only other verified records are a lynx taken in

Albany County in the Laramie Range of southeastern Wyoming in 1963

(Long 1965), and one from an anomalous locality near Douglas, Converse

County in east-central Wyoming in 1983 (Reeve et al. 1986). A radiotelemetry

study was initiated in western Wyoming in 1996, resulting in the capture of

two lynx: a male in December 1996 and a female in March 1997; the female

produced a litter of four kittens in May 1998 (Chapter 11). Prior to 1973, when

the lynx was given full protection in Wyoming, it was considered a predator

that could be harvested legally anytime of year without a license; consequently, no reliable harvest records are available from Wyoming.

Colorado—A thorough review of the history of documented lynx records

in Colorado was conducted by Halfpenny et al. (1989, unpublished) and, except

for the discovery of several more historical specimen records, little new

information has become available since their analysis. Unlike other western

montane regions considered thus far, boreal forest habitat in Colorado is

insular in nature and isolated from similar habitat in Utah and Wyoming by

more than 150 km of lower elevation habitats in the Green River Valley and

Wyoming Basin (Findley and Anderson 1956). All but a few specimen

records are from the center of this island of boreal forest habitat in westcentral Colorado. There are four specimens from the late 1800s: one without

a specific collecting locality, one from Cumbres County near the New

Mexico border, one from Breckenridge, Summit County, and one from

Colorado Springs, El Paso County. Halfpenny et al. (1989, unpublished)
231

McKelvey—Chapter 8

reported that Edwin Carter’s taxidermy notes in the Denver Museum of

Natural History included a lynx trapped in Soda Gulch, Clear Creek County

in 1878. Museum specimens were also found from Grand Lake, Grand

County in 1904-1905; Jefferson, Park County in 1912; and southwestern

Gunnison County in 1925. Terrell (1971) reported one lynx trapped at Red

Cliff, Eagle County in 1929 and one at Marble, Gunnison County in 1931.

Through interviews with trappers, Halfpenny et al. concluded that reports

of three lynx being trapped in Eagle County in 1930 and 1936 were reliable.

After 1936, no lynx specimens or reports of kills are known until 1969,

when a specimen was trapped near Leadville, Lake County, and others were

reportedly shot on the Frying Pan River, Pitkin County (Terrell 1971) and on

the south side of Vail Mountain, Eagle County (Halfpenny et al. 1989,

unpublished). In 1972, a lynx specimen was trapped on Guanella Pass, Clear

Creek County and, in 1974, two were trapped (one is preserved as a

specimen) on the north side of Vail Mountain, Eagle County. Since that time,

only tracks have been found, including three sets on the Frying Pan River,

Eagle and Pitkin Counties and five sets near Mt. Evans, Clear Creek County

(Halfpenny et al. 1989, unpublished). There are no verified records of lynx

in Colorado since 1974, despite large-scale snow-tracking efforts (Carney

1993, unpublished). The management history of lynx in Colorado is similar

to that reported for Wyoming: The lynx was designated an unprotected

predator until 1970, when all harvest of lynx was prohibited; in 1973, it was

classified as a state endangered species.

Utah—Our understanding of the distribution and status of lynx in Utah

comes entirely from scattered mortality records. Barnes (1927) reported that

103 lynx were trapped in a number of counties in Utah in 1915 and 1916, but

Durrant (1952) questioned the validity of these records and believed that

most were actually large bobcats. The relative scarcity of early specimen

records supports this conclusion. Only three specimens of lynx from Utah

in the early 1900s were found in museums, including one collected in 1916

from Wasatch County, one in 1931 from Sanpete County, and one in 1937

from Daggett County. Later records are all from the northwestern portion of

Utah near the southern borders of Wyoming and Idaho. Those records

include one museum specimen collected in 1957 from Daggett County,

mortality reports from Uintah County in 1958 and Summit County in 1958

and 1962 (McKay 1991, unpublished), one specimen from Summit County in

1963, a mortality report from the north slope of the Uinta Mountains in 1972

(McKay 1991, unpublished) and a lynx trapped in Cache County in 1991

(R. McKay, personal communication). No verified records are known after

this time. The lynx is listed as a sensitive species in Utah and has been

protected from all intentional harvest since 1974.
232

Chapter 8—McKelvey

Nevada—There are two museum specimens from Nevada; both were

collected in 1916 in Elko County in north-central Nevada near the Oregon

border (Schantz 1947). These specimens represent the southernmost records

of lynx occurrence west of the Rocky Mountains and are the only verified

records of lynx from Nevada. Three of the 12 specimens from Oregon were

also collected in 1916, suggesting that this may have been a year during

which lynx were dispersing south of their primary range; peaks in lynx

pelt returns from British Columbia and southern Alberta were recorded in

1915 and 1916, respectively (Elton and Nicholson 1942; p. 229).

Synchrony Between United States and Canadian

Trapping Data

Lynx populations in the contiguous United States occur at the southern

margin of a large, interconnected distribution whose geographic center lies

in the northern taiga (McCord and Cardoza 1982; Quinn and Parker 1987).

It has been suggested that the persistence of some lynx populations in the

contiguous United States may be dependent upon the periodic immigration

of lynx into the United States during the crash of northern lynx populations

(Thiel 1987). In the following section, we analyze harvest data, occurrence

data, and verified records from the United States in relation to lynx cycles in

Canada to address the following questions: (1) Are lynx records in the

contiguous United States associated with cyclic population highs in Canada?

and (2) If so, do similar patterns occur repeatedly across time and space?

In southern boreal forests, lynx are believed to occur at relatively low

population densities (Koehler and Aubry 1994), and throughout the 20th

century, harvest records for lynx in Canada have been two to three orders of

magnitude larger than those for the contiguous United States (Novak et al.

1987). In the taiga, long-range emigrations from core populations are associated with the crash of snowshoe hare populations; when prey becomes

scarce, home ranges dissolve and lynx become nomadic (Chapter 9). Thus,

it is possible that periodic immigrations of lynx into the United States

from southern Canadian provinces may occur during such events.

Thiel (1987) argues that periodic immigrations of lynx into the United

States from Canada will produce large increases in lynx records in the United

States occurring several years after cyclic highs in Canada, the lag being the

immigration time. Additionally, we would expect many of these records to

occur in cover types generally not used by lynx and in geographic areas in

which lynx records are generally scarce. However, lagged dynamics and

unusual occurrence patterns, while suggestive, do not necessarily mean

that such occurrences are directly attributable to transients. Complex
233

McKelvey—Chapter 8

asynchronous dynamics are predicted by predator/prey diffusion reaction

models (see Hastings and Harrison 1994 for a review) and occur due to the

interactions between local population dynamics and changes due to dispersal. Mowat et al. (Chapter 9), for instance, suggest that lynx dynamics in

the taiga exhibit lagged synchrony and that the lynx cycle in Canada

“emanates” from central Canada with the patterns in Yukon, Alaska, and

Quebec lagged several years behind those of Saskatchewan and Manitoba.

Correlation analyses of Canadian trapping data (Ranta et al. 1997) also

indicate that, on a continental scale, patterns are least synchronous at

intermediate distances and most synchronous when comparing locations

that are either very close or very far.

Methods

We evaluated Mowat et al.’s (Chapter 9) hypothesis by comparing data

from the central provinces of Alberta and Saskatchewan with data from

areas to the northwest (Alberta + Saskatchewan ➔ Yukon ➔ Alaska) and the

east (Alberta + Saskatchewan ➔ Manitoba ➔ Ontario ➔ Quebec). We

computed correlation coefficients between trapping data for the provinces

of Alberta and Saskatchewan and the other provinces and Alaska incrementally shifted back in time 0-5 years, noted the time lag associated with

the highest correlation, and tested whether lagging the data caused significant changes in correlation coefficients (Zar 1996, pp. 384-386).

For states with reliable and long-term lynx harvest data (New Hampshire,

Minnesota, Montana, and Washington), we repeated the correlation analyses (above) to determine the extent to which these data were correlated with

harvest data from Canadian provinces and whether these data were lagged.

For these analyses we correlated state trapping data with those Canadian

provinces which, due to their proximity, were most likely to contribute to the

local populations. For each state, we visually examined the data using the

most correlated lag time to determine if the patterns appeared synchronous.

Because our primary data are trapping records, which may show patterns and synchrony that result solely from social and economic factors,

we looked to other data to provide a check on the trapping records as well

as to provide information for times and places where trapping data were

absent. Occurrence data and the verified records are not directly associated

with trapping activity and are available for states such as Michigan and

Wisconsin where we have no state-level trapping data. For comparisons of

Canadian trapping data with verified records and general occurrence data,

we used the most correlated lag times for the Canadian data from the

analyses of trapping data described above. Because occurrence data are

often sparse and erratic, we used visual methods to identify potential
234

Chapter 8—McKelvey

associations between these data sets. For Michigan and Wisconsin, where we

lacked trapping data, we compared patterns in the occurrence of verified

lynx records to peaks in harvest data from the Canadian provinces using

the lag time that was most correlated with the Minnesota trapping data. For

the Great Lakes region we estimated the degree to which general occurrence

patterns in data other than harvest records were correlated with Canadian

harvest data lagged as indicated by correlation with Minnesota trapping

records.

Another line of inquiry concerns the degree to which patterns in the lynx

data are correlated with local patterns of hare abundance. For the Great

Lakes region, hare data were available and were highly correlated within the

region (Chapter 7). For Minnesota, we were able to check these data against

independently collected hare occurrence data and the relationship was

strong (r = 0.89, Fig. 8.8). Local lynx populations should respond to changes

in local hare abundances, and the resultant patterns, therefore, may allow

separation of local and dispersal dynamics. We compared lynx trapping and

50

100

150

200

250

300

Hares trapped (thousands)

Hares on grouse routes (max = 14/100km)

1941

1947

1953

1959

1965

1971

1977

1983

1989

1995

Hares trapped

Hares seen

0

Figure 8.8—A comparison between snowshoe hare trapping data and

numbers of hares observed on grouse drumming routes in Minnesota.

Unpublished data provided by the Minnesota Department of Natural Resources.
235

McKelvey—Chapter 8

occurrence data in the Great Lakes region with local patterns of hare

abundance for the period in which hare-trapping was recorded. We used

hare-trapping data from Minnesota because it is complete, is highly correlated with data from Wisconsin and Michigan, and has been independently verified for the last 22 years. Additionally we could compare it

directly to lynx harvest records in Minnesota. Specifically, we were looking

for local increases in hare harvest associated with the peak lynx harvests in

the 1960s and 1970s and a response in lynx occurrence data to a large increase

in hare abundance between 1975 and 1983 (Fig. 8.8). This increase was

thought to be unusually large, perhaps representing the highest densities of

hares in that region during the 20th century (Fig. 8.8; B. Berg, personal

communication); thus, if resident lynx populations were present, they

should have responded numerically to this large irruption in primary prey

populations.

Results

Trapping data—Lagging provincial and Alaskan trapping data 0-2 years

produced the highest correlations when compared with the central provinces of Alberta and Saskatchewan (Table 8.5). With the exception of Yukon,

Table 8.5—Pearson correlation coefficients (r) between trapping data from central Canada and states in the United States

and provinces to the northwest and east. Correlations are to central Canadian data shifted 0-5 years. The best fit

for each state or province is indicated in bold type. In the contiguous United States, correlation coefficients are only

significantly different (Zar 1996, pp. 384-386) for Montana.

Time Shifted

Comparison period 0 years 1 year 2 years 3 years 4 years 5 years Significance

Contiguous U.S.

New Hampshire with 1928-1964 0.23 0.20 0.02 –0.13 –0.20 –0.18 0.273

Quebec

Minnesota with Ontario + 1930-1983 –0.10 0.12 0.22 0.32 0.24 0.00 0.240

Manitoba + Saskatchewan

Montana with Alberta + 1950-1989 0.35 0.69 0.74 0.62 0.35 0.05 <0.001

British Columbia

Washington with Alberta + 1961-1977 –0.24 –0.29 –0.05 0.17 0.25 0.21 0.538

British Columbia

Northwest

Yukon with Alberta + 1934-1996 0.08 0.28 0.36 0.26 0.06 –0.12 0.070

Saskatchewan

Alaska with Alberta + 1934-1996 0.30 0.63 0.79 0.77 0.60 0.31 <0.001

Saskatchewan

East

Manitoba with Alberta + 1924-1997 0.92 0.68 0.38 0.11 –0.04 –0.01 <0.001

Saskatchewan

Ontario with Alberta + 1924-1997 0.74 0.77 0.64 0.39 0.12 –0.06 <0.001

Saskatchewan

Quebec with Alberta + 1924-1997 0.38 0.60 0.71 0.68 0.53 0.33 <0.001

Saskatchewan
236

Chapter 8—McKelvey

lagging the data caused significant (p < 0.05) changes in the correlation

coefficients. The correlation patterns to the east were consistent with Mowat

et al.’s “emanation” hypothesis. Manitoba was synchronous with Alberta

and Saskatchewan, Ontario lagged one year, and Quebec lagged two years

(Table 8.5). Patterns to the northwest were not as clear. Both Yukon and

Alaska had the highest correlations when lagged two years, and Alaska was

much more highly correlated than was Yukon (Table 8.5).

For those states and years for which reliable annual trapping data were

recorded, correlations between harvest totals from the United States and

adjacent Canadian provinces were generally modest (Table 8.5), Montana

being the exception. New Hampshire was the only state for which nonlagged data provided the strongest correlation. Correlations between United

States and Canadian harvest data for the other three states were all improved

by shifting the Canadian data back in time: two years gave the best fit for

Montana, three years for Minnesota, and four years for Washington. Visual

inspection of these data suggests that increases in correlation coefficients

were due to improved alignment of the oscillations in numbers of lynx

trapped (Figs. 8.9-8.12).

0.2

0.4

0.6

0.8

1

Proportion of maximum

1928

1932

1936

1940

1944

1948

1952

1956

1960

1964

New Hampshire

Quebec

0

Figure 8.9—Lynx trapping data from New Hampshire (Fig. 8.1) overlaid

on lynx trapping data from Quebec (Fig. 8.2). The strongest correlation

between these data sets was with no lag between New Hampshire and

Quebec.
237

McKelvey—Chapter 8

Central provinces shifted 3 years

Minnesota

0.2

0.4

0.6

0.8

1

Proportion of maximum

1930

1936

1942

1948

1954

1960

1966

1972

1978

0

0.2

0.4

0.6

0.8

1

Proportion of maximum

1950 1956 1962 1968 1974 1980 1986

Montana

B.C. and Alberta shifted 2 years

0

Figure 8.10—Lynx trapping data from Minnesota (Fig. 8.4) overlaid

on lynx trapping data from Ontario, Manitoba, and Saskatchewan

combined (Fig. 8.3). The strongest correlation between these data

sets was with a three-year lag between Minnesota and south-central

Canada.

Figure 8.11—Lynx trapping data from Montana (Fig. 8.5) overlaid on lynx

trapping data from Alberta and British Columbia combined (Fig. 8.6). The

strongest correlation between these data sets was with a two-year lag

between Montana and southwestern Canada.
238

Chapter 8—McKelvey

One reason that the correlations were not stronger between states and

adjacent provinces was that the patterns were not constant over time. For

example, in New Hampshire, raw data for the first 12 years (1928-1939) are

highly correlated with populations in Quebec (r = 0.76), when an average

of 10 lynx were harvested each year; after this period, however, harvest

records declined to only 0-3 lynx per year and the data become erratic and

difficult to interpret (Fig. 8.9). In Minnesota, a three-year lag with data

from the south-central Canadian provinces resulted in a strong correlation

for the most recent period (r = 0.73, 1960-1983) but the pattern is out of

phase in the previous 26 years (Fig. 8.10).

Occurrence data—Trapping data were removed from the general lynx

occurrence database (Table 8.1) to produce as independent a data set as

possible. Visual inspection of occurrence data from the Great Lakes region

suggest that these fluctuations were aligned with trapping data from the

south-central Canadian provinces with a three-year lag (Fig. 8.13). The

verified lynx occurrences for Michigan and Wisconsin (Tables 8.3 and 8.4),

for the period 1934-1997, are a subset of the occurrence data presented

above and, in some years, make up the bulk of these data. These data are also

0.2

0.4

0.6

0.8

1

Proportion of maximum

1961 1967 1973

Washington

B.C. and Alberta shifted 4 years

0

Figure 8.12—Lynx trapping data from Washington (Fig. 8.7) overlaid on lynx

trapping data from Alberta and British Columbia combined (Fig. 8.6). The

strongest correlation between these data sets was with a four-year lag between

Washington and southwestern Canada.
239

McKelvey—Chapter 8

concordant with the general occurrence data and are aligned with trapping

data from the south-central provinces with a three-year time lag (Fig. 8.14).

Hare densities—To look for responses to the regional increase in hare

populations in the Great Lakes states during the late 1970s and early 1980s

(Fig. 8.8), we compared hare harvest data from Minnesota with general

occurrence data from the Great Lakes region. Based on these data, there

appears to be no relationship between this recent increase in hare density

and numbers of lynx observed (Fig. 8.15). We also compared hare and lynx

harvest data for the state of Minnesota (Fig. 8.16). The large peaks in lynx

harvest in the 1960s and 1970s, which occurred three years after similar

irruptive dynamics in central Canada, do not appear to be associated with

increases in local hare harvest.

Discussion

The idea that lynx population dynamics emanate from the center of the

taiga outward toward the periphery is supported by these analyses.

20

40

60

80

100

120

Number of lynx occurrences

Lynx trapped in Canada

1934

1940

1946

1952

1958

1964

1970

1976

1982

1988

1994

Lake states

Central provinces shifted 3 years 50,000

0 0

Figure 8.13—Lynx occurrence data, with trapping records removed (see

Table 8.1), for the states of Wisconsin, Minnesota, and Michigan combined

overlaid on lynx trapping data from Saskatchewan, Manitoba, and Ontario

combined (Fig. 8.3). Canadian data were lagged three years based on the

best fit to Minnesota trapping data (Table 8.5, Fig. 8.10).
240

Chapter 8—McKelvey

2

4

6

8

10

12

14

Number of lynx occurrences

Lynx trapped in Canada

1934

1940

1946

1952

1958

1964

1970

1976

1982

1988

1994

Michigan and Wisconsin

Central provinces shifted 3 years 50,000

0 0

Hares trapped in Minnesota

Lynx occurrences in the Lake States

20

40

60

80

100

120

Lynx occurrences

Hares trapped in Minnesota

1941

1947

1953

1959

1965

1971

1977

1983

1989

1995

350,000

0 0

Figure 8.14—Verified lynx records for Wisconsin and Michigan

combined (Tables 8.3 and 8.4) overlaid on lynx trapping data from

Saskatchewan, Manitoba, and Ontario combined (Fig. 8.3).

Canadian data were lagged three years based on the best fit to

Minnesota trapping records (Table 8.5, Fig. 8.10). Note that verified

records for these states are weak, with a maximum number per

year of 13 in 1962.

Figure 8.15—Lynx occurrence data for the Great Lakes

region (Fig. 8.13) overlaid on snowshoe hare harvest data for

Minnesota.
241

McKelvey—Chapter 8

Patterns in the contiguous United States, while weaker, are consistent

with the patterns observed within Canada and between Canada and

Alaska. With the exception of the northeastern United States, both correlation metrics (for those data where we applied them) and visual inspection suggested that lagging the Canadian data forward by two to four

years improved the correlation with United States data. While there are

several nonbiological factors that could lead to these patterns, the consistency of lagged correlations between the trapping data and the occurrence

data and across various states and regions suggests that these patterns are

biologically based.

For the Canadian provinces and Alaska, correlation patterns were generally very strong and were consistent across the entire time series (>60 years

in all cases). In the United States, correlations were generally weak and, with

the exception of New Hampshire, were primarily associated with the large

irruptive peaks in the 1960s and 1970s.

If we assume that observed patterns indicate general changes in numbers

of lynx, then there are several hypotheses that could explain these patterns.

One is the immigration hypothesis presented above, another is that local

populations are responding to the same factors that are controlling northern

populations and, hence, are in synchrony, and a third is that the dynamics

are some combination of the two.

Lynx

100

200

300

400

Lynx harvested

Hares harvested (thousands)

1941

1946

1951

1956

1961

1966

1971

1976

1981

Hares

0

Figure 8.16—Lynx and hare harvest data for Minnesota.
242

Chapter 8—McKelvey

In the Canadian provinces, Alaska, Montana, and Washington, we know

that there are local reproductive populations, knowledge that invalidates a

pure immigration hypothesis. For these areas, we can only state that they

appear to be a part of a population in which lagged synchronous dynamics

occur. Because we do not know why these dynamics occur, we cannot say to

what extent they are affected by changes in local dynamics and the role

that immigration might play.

For the most recent decades, dynamics in the Great Lakes region may be

strongly driven by immigration. Though the data are weak, the lack of a

response in the occurrence data to an extremely large regional increase in

hares that peaked in 1980 coupled with low hare densities during the lynx

peaks in the 1960s and 1970s suggest these irruptive dynamics may not be

local in origin. This does not tell us whether or not there are local populations

present, however; it merely indicates that the large “spikes” that dominate

recent temporal patterns of lynx occurrence in the Lake States are at least

partially Canadian in origin.

Given this, we find puzzling the lack of lynx occurrence records associated

with a large population peak occurring in the central provinces during the

early 1980s. This population peak was higher than any recorded in the 20th

century prior to 1959, but there was no evidence from museum specimens,

verified mortality records, or anecdotal observations that unusual numbers

of lynx occurred in any portion of its range in the contiguous United States.

In 1984, after the expected increase in lynx numbers in Minnesota failed to

occur, the state closed the lynx harvest (DonCarlos 1994, unpublished).

The “explosions” of lynx in the early 1960s and 1970s were unprecedented

events in the 20th century (Fig. 8.3). Many lynx observed during these

“explosions” were found in anomalous habitats and geographic regions,

exhibited abnormal behavior, and suffered high mortality (Gunderson 1978;

Thiel 1987). Mech (1980) reported that lynx numbers declined dramatically

in Minnesota after the 1972 influx; trapping records also indicate that postirruptive populations were low: 215 were trapped in 1972, 691 in 1973, 88 in

1974, and 0 in 1975 and 1976. Lynx occurrence records in Michigan and

Wisconsin similarly declined to very low levels within a few years after the

peak irruptive periods (Thiel 1987; Fig. 8.14). It may be that the correlations

which we observed between lynx occurrences in the northern United States

and Canada following these irruptions are historically unusual as well.

Lynx Associations With Broad Cover Types

By considering lynx occurrence data over broad scales of space and time,

we can describe patterns in the distribution of occurrences relative to
243

McKelvey—Chapter 8

topography and vegetation to elucidate the nature of their range in the

contiguous United States (Fig. 8.17). Because of the irregularities in the data,

we do not use the data themselves to define the bounding polygons as one

would for home range data (White and Garrott 1990). Instead, we simply

ask: Which cover types and elevation zones contain most of the occurrences?

To examine the distribution of lynx occurrences by elevation, we used data

from a Digital Elevation Model (1,040 m/pixel) re-coded into 250-m elevation classes. For the Northeast and Great Lakes states, we used provinces

from Bailey’s (1998) ecoregion classification to describe vegetation at the

broader scale, and subsection-level “potential dominant vegetation-1” (Keys

et al. 1995) at the finer scale. For western states, Bailey’s ecoregions were overly

broad, and we lacked a subsection-level map. We therefore characterized

western vegetation using Küchler (1964), with the form classification representing a large-scale cover class, and “vegetation type” representing a finerscale class of potential vegetation.

All occurrences with at least county-level resolution within the three

regions (Table 8.1) were included in these habitat analyses. In the Northeast

and Great Lakes states, where most of the data were at county-level resolution, counties were assigned to vegetation and elevation classes using a

majority-area rule, and occurrences with county-level resolution were then

assigned to these county-level classes. To describe the distribution of

occurrences by habitat type, we emphasized the classes of vegetation and

elevation which encompassed at least 75% of the occurrences in a region and

referred to them as “primary” types. The distribution of occurrences was

also compared to the areal distribution of the types within each region.

Because elevational relationships are likely to vary among states along

ecological gradients, we also considered elevation distributions on a stateby-state basis.

Habitat Patterns Associated With Lynx Occurrences

West—Elevations in the West are variable, ranging from 0 to 4,180 m. Lynx

occurrences generally occurred at higher elevations than is reflected by the

areal distribution of elevation zones: 70% of occurrences fell within the

1,500-2,000-m class, which comprised only 42% of the area. This pattern is

highly influenced by variation among states in the number of occurrences:

95% of the occurrences in the 1,250-2,000-m range are from Montana and

Washington. However, frequency distributions for the individual states

continue to demonstrate peak numbers of occurrences at mid-elevations

that deviate from the areal distribution of elevation classes (Fig. 8.18).

Additional patterns emerge from the state-by-state distributions. Examining elevation patterns across the region, both point and area distributions
244

Chapter 8—McKelvey

Figure 8.17—Spatial distribution of lynx occurrence data from 1842 to 1998 (Table 8.1).
245

McKelvey—Chapter 8

0

5

10

15

20

25

30

35

750 1,000 1,250 1,500* 1,750* 2,000* 2,250* 2,500 2,750 3,000 3,250 3,500 3,750

Elevation class (250-m intervals)

Percent

points

area

Montana

0

5

10

15

20

25

30

35

1,000 1,250 1,500 1,750 2,000 2,250* 2,500*2,750* 3,000* 3,250 3,500 3,750 >3,750

Wyoming

Percent

Elevation class (250-m intervals)

0

5

10

15

20

25

30

1,250 1,500 1,750 2,000 2,250 2,500 2,750* 3,000* 3,250* 3,500* 3,750 >3,750

Percent

Colorado

Elevation class (250-m intervals)

Figure 8.18—Relationships between lynx occurrence and elevation

for Montana, Wyoming, and Colorado. Elevation zones marked with

a (★) were included in the definition of primary areas of occurrence.
246

Chapter 8—McKelvey

shift to increasingly higher elevations as one moves southward from

Idaho and Montana to Wyoming, Utah, and Colorado (Fig. 8.18).

Vegetation types are also effective in characterizing the distribution of

occurrences. At the larger vegetation scale, Rocky Mountain Conifer Forest

contains 83% of the occurrences but represents only 27% of the area in the

region (Fig. 8.19). The other conifer-dominated class in the region, PNW

Conifer Forest, had the second highest point frequency (7%), which was

generally equivalent to its areal frequency, but occurrences were located

only in areas adjacent to Rocky Mountain Conifer Forest. Less than 3% of the

occurrences were located in each of the remaining classes, with decreasing

frequencies of occurrences with greater distance from areas of Rocky Mountain Conifer Forest (Fig. 8.19). On the finer scale of vegetation classification,

the distribution of occurrences also differed significantly from the areal

distribution of types. The primary types, Douglas-fir and western spruce/

fir forests of the Rocky Mountain Conifer class, and fir/hemlock of the

PNW Conifer class, encompass 79% of the occurrences but only 15% of

the area. Occurrences are rare within the remaining vegetation types, which

include both non-forest and drier forest types.

Areas that encompass primary classes of both elevation and vegetation

contain 67% of the occurrences, including a majority of the occurrences

within most states (Fig. 8.20). The area within this combined habitat type

generally increases from south to north. From Montana southeast to Utah

and Colorado, clusters of this combined habitat type become increasingly

isolated. From Washington to Oregon, the width of the strip representing

primary habitat narrows as one moves southward.

Great Lakes region—Elevations in this region are low and of low

variability, ranging from 170 to 660 m. The distribution of occurrences

parallels the areal distribution of elevations in the region, with 80% of

occurrences falling in the mid-elevation zone of 250-500 m, which represents 78% of the total area. This relationship also holds within the individual

states; thus, elevation was not important in characterizing the distribution of

occurrences in this region.

The locations of lynx records in these states were associated with vegetation type, however. At the coarser vegetation scale, 88% of occurrences are

within Mixed Deciduous-Coniferous Forest, which accounts for <50% of

the area (Fig. 8.21). The remaining 12% of occurrences were located in

Broadleaved Continental Forests and Forest-Steppes and Prairies. At the

finer vegetation scale, the seven vegetation types containing occurrences

encompassed 73% of occurrences but only 32% of the area; of the seven

types, sugar maple-basswood, jack pine, and white pine-red pine forest

types had the highest frequencies of occurrences (each >15%). All of these
247

McKelvey—Chapter 8

Nonforest

Other Forest

PNW Conifer

Rocky Mountain Conifer

100 KM

Nonforest

Other Forest

PNW Conifer

Area Per State

(square km)

OR 6,400

WA 15,100

ID 26,300

MT 63,500

WY 37,800

CO 23,700

UT 11,400

100 KM

Figure 8.19—Lynx occurrence data overlaid on Küchler (1964) vegetation classes in the western

United States. The Rocky Mountain Conifer cover-type enclosed 83% of lynx occurrences.

Figure 8.20—Areas of primary lynx occurrence are those areas that (1) consist of a cover type

associated with at least 75% of lynx occurrences and (2) lie within an elevation zone enclosing

at least 75% of lynx occurrences in each state; 67% of lynx records fell within this area.
248

Chapter 8—McKelvey

Forest-Steppes and Praires

Broadleaved Continental Forest

Mixed Deciduous Forest

100 KM

Figure 8.21—Lynx occurrence data overlaid on Bailey (1998) vegetation classes in the Great

Lakes region. The Mixed Deciduous-Coniferous Forest type enclosed 88% of lynx records.

primary types are classified as Mixed Deciduous-Coniferous Forest, except

for the sugar maple-basswood type which falls into Broadleaved Continental Forest. The distribution of these primary vegetation types occurs primarily in northern Wisconsin and Minnesota, with <15% within Michigan

(Fig. 8.22). Conversely, areas lacking occurrences are found in southern

areas and represent mostly non-conifer or unforested types.

Northeast—Elevations in the Northeast range from 0 to 1,745 m. The distribution of occurrences by elevation is shifted toward higher elevations

compared to the areal distribution of elevations in the region: 77% of

occurrences were at mid-elevations ranging from 250 to 750 m, which

comprises 59% of the total area. The 0-250-m class has the greatest difference

between occurrences and area with only 20% of occurrences compared to

39% of the area. These patterns also hold within Maine, New Hampshire,

and New York, but Vermont, Massachusetts, and Pennsylvania had too

few occurrences to allow comparison (Table 8.1).

Vegetation also serves to describe the distribution of lynx occurrences in

the region (Fig. 8.23). At the broader scale, the most northerly and mountainous class in the region, Mixed Forest-Coniferous Forest-Tundra, encompasses 88% of the occurrences compared to only 29% of the area, and the

remaining occurrences fell into five other provinces. At the finer scale,
249

McKelvey—Chapter 8

100 KM

Area Per State

(square km)

MN 48,000

WI 72,000

MI 17,600

Figure 8.22—Areas of primary lynx occurrence in the Great Lakes region are those

areas that enclose 73% of lynx records based on potential dominant vegetation

types (Keys et al. 1995). Elevation was not used to define areas of primary

occurrence in this region.

100 KM

Area Per State

(square km)

ME 28,500

NH 9,800

VT 8,000

NY 27,400

MA 1,000

PA 8,000

Figure 8.23—Areas of primary lynx occurrence in the northeastern states based on

potential dominant vegetation types (Keys et al. 1995) and elevations >250 m; 70% of

lynx records fell within these areas.
250

Chapter 8—McKelvey

occurrences are located within 10 vegetation types, with the highest frequency in red spruce-balsam fir/sugar maple-birch-beech forest (53%).

The primary types also include sugar maple-birch-beech forest and red

spruce-balsam fir forest; the three types together comprise 84% of occurrences compared to 29% of the area and are found within Mixed ForestConiferous Forest-Tundra. The types that include spruce-fir are absent

south of Vermont and the northern Adirondack Mountains. In general, lynx

occurrences were rare within areas typed as dry forest or non-forest.

Intersecting the primary vegetation classes with the primary elevation

classes left an area that is primarily contained within Mixed ForestConiferous Forest-Tundra, includes 70% of the occurrences, and encompasses a majority of the occurrences within each state (Fig. 8.23). More than

60% of this area occurs in Maine and New York, followed by Vermont,

New Hampshire and Pennsylvania, with trace amounts in Massachusetts.

From Maine south to Pennsylvania, areas of primary occurrence become

increasingly disjunct.

Implications of Habitat Relationships

Because our analyses of habitat associations were conducted with data that

varied greatly among states (Table 8.1), observed patterns within a region

are heavily weighted by those states with the most occurrences. However,

even in states with relatively few occurrences, the locations generally fell

within the predicted habitat classes. In the Northeast, most of the occurrences were in the White Mountains of New Hampshire; but predicted

vegetation associations that were based largely on these data include most

of the locations in New York and Maine (Fig. 8.23). Thus, broad-scale

patterns in vegetation and elevation effectively capture regional patterns in

the distribution of lynx occurrences. The consistency across states within a

region adds support to the idea that these patterns reflect general habitat

use patterns of lynx.

For all three regions, high frequencies of occurrence records correspond to

cool, coniferous forests in northern areas. For the western and northeastern

regions, these forests occur at mid-elevations in montane areas; frequencies

of occurrences decrease from these areas toward the more maritime zones.

In all three regions, areas of primary occurrence become increasingly rare

and fragmented as one moves away from these northerly concentrations

of coniferous forests and, in the West, primary forest types also occur at

higher elevations along this gradient. The range of the snowshoe hare, the

primary prey of lynx, is also coincident with montane areas in the West and

Northeast and northern areas in the Great Lakes region (Chapter 7).
251

McKelvey—Chapter 8

Ephemeral locations and dispersal potential—Although the primary

vegetation classes encompassed the majority of occurrences, many occurrences fell into other vegetation classes. Occurrences could be associated

with these types because of location or vegetation classification errors or

dispersal movements, or they could be indicative of small resident populations. While we cannot differentiate between these causes in an absolute

sense, we can use the spatial distributions of these locations to explore the

most likely explanations.

For those 349 occurrences in the focal states of the West that were located

outside of the Rocky Mountain or PNW Conifer classes (Fig. 8.19), we

calculated the nearest straight-line distance to a conifer-type polygon. We

compared these distances to those of random locations placed within the

non-conifer types using a X2

 homogeneity test. Data from the northeastern

and Great Lakes regions were not analyzed because of their limited spatial

resolution (generally only at county level).

Both error and dispersal occurrences should be close to source types,

whereas occurrences from resident populations may be distributed randomly with respect to source areas. Occurrences representing errors are

generally concentrated in a narrow “epsilon band” around the source type

(Blakemore 1984; Dunn et al. 1990) due to granularity along the boundary.

Such an error distribution should decline very quickly with distance from

the source. In contrast, a simple dispersal model of constant probability of

detection with distance (usually through mortality) should show exponential decline with distance.

Points located in non-conifer types are significantly closer to conifer

forest types than expectation (p < 0.001), indicating that they are associated

with conifer forests. Most of the occurrences are extremely close to a conifer

type (Fig. 8.24), and 79% (274 of 349) are within 10 km of conifer forest.

Undoubtedly, many of these occurrences actually occurred within conifer

forests and lie outside of these types due to errors in location and vegetation mapping, while others may be associated with normal within-home

range or short-range exploratory movements. Assuming that many of the

non-conifer locations within 10 km of conifer types may be due to

mapping error, we are left with 75 locations >10 km from conifer forest

whose distance distribution generally declines exponentially with distance

from conifer forests (Fig. 8.25).

These remaining occurrences are reasonably distant from the nearest area

typed as conifer forest, at an average distance of 39 km and maximum

distance of 259 km, and are probably in non-conifer, and generally nonforested types. In addition, because most of the non-conifer types in the

region are non-forest (Fig. 8.19), these distances represent conservative
252

Chapter 8—McKelvey

Figure 8.24—Distances to the nearest conifer forest for those lynx

occurrences in non-conifer cover types in the West. Lynx

occurrences were significantly closer to conifer types than would

be expected based on random placement within non-conifer types.

50

100

150

200

250

300

Number of observations

10 20 30 40 50 60 70 80 90 >90

Distance from conifer forest (km)

Lynx observations

Expected

1

1.5

2

2.5

3

3.5

Lynx occurrences (ln)

10 20 30 40 50 60

Distance from conifer forest (km)

Lynx occurrences

Regression

Y = 3.71-0.044X

r2= 0.87

Figure 8.25—Lynx occurrences in areas that are >10 km

from a conifer type decline exponentially with distance. An

exponential distribution is transformed to a linear relationship

by taking the log of the dependent variable.
253

McKelvey—Chapter 8

estimates of the amount of non-forested landscape crossed by lynx prior to

detection. We also have 20 records of lynx locations in Nevada and the

Plains states (Table 8.1) that probably represent much longer dispersals

across open lands. However, our data suggest that long-distance dispersals

are relatively rare, as only four of 3,803 occurrences in the Western region

were >100 km from conifer forest.

Conclusions

There are records of lynx occurrence in 24 states. Generally, verified

records extend to the mid 1800s, and, due to confusion with bobcats, earlier

accounts are often suspect. For four of these states—Minnesota, Montana,

New Hampshire, and Washington—we have reliable trapping data, and

for Minnesota and Montana, fairly large numbers of lynx were trapped in

the 20th century (5,585 and 3,012, respectively). For most states, data are

too fragmentary to infer much concerning lynx beyond simple occurrence.

In the states where we have trapping data, dynamics appear to be associated with patterns of lagged synchrony that occur across Canada and

Alaska, but the mechanisms that underlie these dynamics are unknown.

Given our current lack of understanding of these dynamics, their presence

increases our uncertainty concerning the meaning of an occurrence, or even

many occurrences. In Minnesota, for instance, the 5,585 lynx trapped in the

20th century could have been produced by a local population, or as some

researchers have hypothesized, be mostly immigrants or any combination of

local lynx and dispersers.

Lynx occurrences in the 20th century are closely associated with conifer

forest types associated with the southern extensions of the boreal forest, a

pattern that conforms to our biological understandings of lynx habitat

(Chapter 13). There is little evidence of occurrence in other types such as pure

deciduous forests in the East or shrub-steppe types in the West. Where

occurrences are in unusual types, most of the locations are immediately

adjacent to the conifer cover types containing most of the occurrences.

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records of selected Pennsylvania mammals. Annals of Carnegie Museum 54:77-188.

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the Museum of Zoology, University of Michigan, Ann Arbor, No. 123.

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Papers of the Michigan Academy of Science, Arts, and Letters 3:425-445.

Wydeven, A. P. 1998. Lynx status in Wisconsin, 1998. Unpublished, Wisconsin Department

of Natural Resources, Madison, WI.

Zar, J. H. 1996. Biostatistical analysis. Prentice Hall, Upper Saddle River, NJ.
260

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Appendix 8.1

Sources for Lynx Occurrence Data in the United States

Colorado: The Colorado Natural Heritage Program maintains a state

database that is a compilation of museum records, Colorado Division of

Wildlife harvest records, sightings reported to the Division, and published

reports. The White River National Forest reported five visual observations

and Rocky Mountain National Park reported one. Museum specimen

records were obtained from the Denver Museum of Natural History,

Academy of Natural Sciences of Philadelphia, Milwaukee Public Museum,

and the National Museum of Natural History. Records from the database

compiled by O.S. Garton and Mary Maj and previously published in Ruggiero

et al. (1994) are also included.

Idaho: The state database for Idaho is maintained by the Idaho Fish

Conservation Data Center (IDFG CDC) and is a compilation of museum

records, IDFG harvest records, sightings of animals and tracks reported to

the CDC and interviews of knowledgeable hound hunters and trappers.

Visual observations and/or tracks were reported by the following National

Forests: Beaverhead-Deerlodge, Bitterroot, Idaho Panhandle, Nez Perce,

and Sawtooth. Museum specimen records were obtained from Harvard

Museum of Comparative Zoology, National Museum of Natural History,

University of Colorado Museum, and the Slater Museum of Natural History

at the University of Puget Sound. Records from the database compiled by

O.S. Garton and Mary Maj and previously published in Ruggiero et al.

(1994) are also included.

Illinois: We have only one record for the state of Illinois and that is of a

mounted skin from the Academy of Natural Sciences of Philadelphia.

Iowa: The one Iowa record we have is from a mounted skin belonging to

the private collection of Jerry L. Rasmussen of Rock Island, Illinois.

Maine: Museum specimen records were obtained from the Harvard

Museum of Comparative Zoology, the Museum of Zoology at the University

of Michigan, and the National Museum of Natural History. Also included

are harvest records as published in Ontario’s Ministry of Natural Resources

“Furbearer harvests in North America 1600-1984” by Milan Novak et al.

Winter track counts were conducted from 1994 to 1997 by the State of

Maine Department of Inland Fisheries and Wildlife, and track observations

during the winter of 1994-1995 are reflected here. This same agency compiled records of incidental takings and historical observations.
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Massachusetts: The only records for Massachusetts are from state harvest reports and bounty records kept by the Massachusetts Division of

Fisheries and Wildlife.

Michigan: Museum specimen records were obtained from the following:

Michigan State University Museum, Peabody Museum at Yale, Grand

Rapids Public Museum, Milwaukee Public Museum, Museum of Zoology

at the University of Michigan, and the National Museum of Natural History.

Various sightings compiled by both the Michigan Department of Natural

Resources and the Michigan Natural Heritage Natural Features Inventory are reported here as well as historical data from two articles,

Elsworth M. Harger’s 1965 “The Status of the Canada Lynx in Michigan”

and “Michigan Mammals” by Rollin H. Baker, published in 1983. Dean

Beyer (University of Northern Michigan) compiled a database of approximately 45 lynx records that includes sightings, tracks, and museum

specimen records from various sources. One visual observation was reported by the Ottawa National Forest.

Minnesota: Data points for Minnesota include harvest records and

records of confiscated carcasses and accidental lynx mortalities obtained

from the Minnesota Department of Natural Resources (MNDNR). The

MNDNR also provided us with records they had compiled of personal

reports of sightings and tracks, reports from newspaper articles, and

shootings. Two surveys were done by the MNDNR that yielded data points,

a winter track survey conducted 1991 through 1997 (one observation of

tracks), and a predator and furbearer scent post census 1975 through 1997

(four detections). L. David Mech trapped and radio-collared a number of

lynx from 1972 through 1978 and published the results in “Age, Sex,

Reproduction, and Spatial Organization of Lynxes Colonizing Northeastern

Minnesota” in 1980. The capture points of those lynx are reflected here.

Additionally, Mech kept autopsy records for lynx trapped, shot, or otherwise killed from 1972 to 1974, and those data points are included in our

database. Museum specimen records were reported by the following: Bell

Museum of Natural History; National Museum of Natural History; the Bird

and Mammals Collection at University of California, Los Angeles; the

Illinois State Museum, the University of Wisconsin Zoological Museum; and

the Los Angeles County Museum.

Montana: The Montana state database is maintained by the Montana

Department of Fish, Wildlife and Parks (MDFWP). Occurrence records for

this database were obtained from MDFWP harvest records, logbooks, occurrence reports by individuals, and winter track surveys. A number of National Forests reported visual observations, tracks, and physical remains.
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These forests include Flathead, Beaverhead-Deerlodge, Gallatin, Kootenai,

Lewis and Clark, and Lolo National Forests. Glacier National Park also

reported visual observations and tracks. Museum specimen records were

obtained from the following: American Museum of Natural History, The

Glacier Collection at Glacier National Park, University of Nebraska State

Museum, University of North Dakota, Illinois State Museum, National

Museum of Natural History, and the Philip Wright Zoological Museum.

Records from the database compiled by O.S. Garton and Mary Maj and

previously published in Ruggiero et al. (1994) are also included.

Nebraska: The U.S. Fish and Game, South Dakota Field Office provided

seven confirmed lynx records. Museum specimen records were obtained

from the University of Nebraska State Museum.

Nevada: Nevada has only two records; both were obtained from the

National Museum of Natural History.

New Hampshire: The New Hampshire Fish and Game provided harvest/

bounty reports as well as a compilation of records from various sources

such as personal accounts of observations and newspaper articles. From

the White Mountain National Forest we obtained a compilation of records

from personal reports and responses to questionnaires. The Audubon

Society of New Hampshire provided points from their Endangered Species

Program database. Museum specimen records were obtained from the

Museum of Comparative Zoology at Harvard, Cornell University Vertebrate Collections, and the University of Maine.

New York: The majority of the data points for New York came from the

U.S. Fish and Wildlife Service report, “The Status of the Lynx in New York

(Lynx canadensis)” by A.S. Bergstrom (1977, unpublished). The New York

State Department of Environmental Conservation reported two rather recent lynx occurrences, one shot and one sighted. Museum specimen records

were obtained from the American Museum of Natural History and the

Academy of Natural Sciences of Philadelphia.

North Dakota: Most of the North Dakota points are from museum

specimen records from the Los Angeles County Museum, University of

North Dakota, the Museum of Southwestern Biology at the University of

New Mexico, and the National Museum of Natural History. The North

Dakota Game and Fish Department reported the total number of lynx taken

for two time periods, 1962-65 and 1972-73, on a statewide basis.

Oregon: The Oregon Department of Fish and Wildlife (ODFW) maintains

a state database made up of ODFW harvest records, published reports, and

sightings reported to the ODFW. Three National Forests reported visual
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McKelvey—Chapter 8

observations: Malheur, Umatilla, and Willamette. Museum specimen

records in the database are from the following museums: National Museum

of Natural History, Oregon State University, the private collection of Wendell

Weaver, the University of Kansas Museum of Natural History, and the

Slater Museum of Natural History at University of Puget Sound. Records

from the database compiled by O.S. Garton and Mary Maj and previously

published in Ruggiero et al. (1994) are also included.

Pennsylvania: The Nature Conservancy’s Pennsylvania Science Office

reported the “last known record” of naturally occurring lynx. One museum

specimen record was obtained from the Reading Public Museum and Art

Gallery.

South Dakota: Six records of lynx observations were obtained from the

South Dakota Department of Game, Fish and Parks, which manages the

South Dakota Natural Heritage Data Base. Museum specimen records were

obtained from South Dakota State University and the National Museum of

Natural History.

Utah: Records were obtained from the Utah Division of Wildlife Resources

(UDWR) Rare Mammal Sighting Program, UDWR harvest records, other

UDWR records, published reports, and interviews with various organizations and private individuals. These records make up the state database that

is maintained by the UDWR Utah Natural Heritage Program. Museum

specimen records were obtained from the Carnegie Museum of Natural

History, Utah Museum of Natural History, and the National Museum of

Natural History. Ashley National Forest reported five visual observations.

Records from the database compiled by O.S. Garton and Mary Maj and

previously published in Ruggiero et al. (1994) are also included.

Vermont: The points for Vermont come from two sources: the Vermont

Department of Fish and Wildlife (historical records of lynx taken) and the

Dartmouth College Museum.

Washington: Details of the Washington state database are lacking and as

such, many of the sources are listed as “unknown.” Sources that are listed

include the U.S. Forest Service, U.S. Bureau of Land Management, the

Washington Department of Natural Resources, and data from local counties.

We received point data directly from the Okanogan National Forest. These

observations were from winter track surveys and camera/bait stations

during 1981-1988. Other survey data included here are from a telemetry

study done by the Washington Department of Fish and Game, 1981-1988.

The Idaho Panhandle and Mount Baker-Snoqualmie National Forests and

North Cascades National Park reported a variety of visual observations,
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Chapter 8—McKelvey

tracks, and physical remains. A number of museums contained specimens, including the Conner Museum at Washington State University,

National Museum of Natural History, University of Washington Burke

Museum, the Museum of Vertebrate Zoology at Berkeley, the University of

Massachusetts, and the Slater Museum of Natural History at the University

of Puget Sound. Records from the database compiled by O.S. Garton and

Mary Maj and previously published in Ruggiero et al. (1994) are included.

Wisconsin: The Wisconsin Department of Natural Resources (WIDNR)

provided data points from harvest records, trapper questionnaires, and

confirmed personal accounts. Richard Thiel (Bureau of Endangered Resources, WIDNR) compiled quite an extensive collection of lynx/lynx

sign observations from sources such as newspaper articles, huntertrapper questionnaires, museum records, and personal accounts. This

“raw data” is summarized in Thiel’s 1987 publication “The Status of

Canada Lynx in Wisconsin, 1865-1980.” Another report by the WIDNR

from which data points were taken is Adrian Wydeven’s 1998 report,

“Lynx Status in Wisconsin.” The Nicolet National Forest ran winter track

surveys 1993 through 1998, and track observations from that study are

included here. Lastly, museum specimen records were obtained from the

following: University of Wisconsin at Madison Zoological Museum,

Museum of Natural History at the University of Wisconsin at Stevens

Point, the Milwaukee Public Museum, the University of Wisconsin at

Superior, and the University of Wisconsin Tech Center at Marinette.

Wyoming: The Wyoming state database is maintained by the Wyoming

Department of Game and Fish (WDGF) and is a compilation of data from the

following sources: WDGF records, publications, federal agency records,

interviews with trappers, and a lynx research project in the Wyoming

Range of southwestern Wyoming. A number of records were compiled by

Reeve et al. (1986, unpublished) and some of the more recent records were

compiled by Tom Laurion (WDGF). Three visual observations were reported by Yellowstone National Park. Museum specimen records were

obtained from Harvard Museum of Comparative Zoology, University of

Kansas Museum of Natural History, National Museum of Natural History,

University of Wyoming Museum of Zoology, and the Carnegie Museum of

Natural History. Records from the database compiled by O.S. Garton and

Mary Maj and previously published in Ruggiero et al. (1994) are included.
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Chapter 9

Ecology of Lynx in

Northern Canada and

Alaska

1

Garth Mowat, Fish and Wildlife Division, Timberland Consultants Ltd.,

P. O. Box 171, Nelson, British Columbia V1L 5P9 Canada

1

Kim G. Poole, Fish and Wildlife Division, Timberland Consultants Ltd.,

P. O. Box 171, Nelson, British Columbia V1L 5P9 Canada

Mark O’Donoghue, Fish and Wildlife Branch, Dept. of Renewable Resources,

Box 310, Mayo, Yukon Territory Y0B 1MO Canada

1

Order of the first two authors decided by the toss of a coin

Abstract—We review the ecology of lynx in the northern part of its range, drawing

heavily on the results of recent research from that region. Snowshoe hares form

the bulk of prey items in essentially all studies and at all periods in the cycle, but

use of alternative prey, often red squirrel, increases as hares become scarce.

Caching of freshly killed prey is rare, although carrion is consumed, primarily

during periods of food shortage. Habitat use by lynx varies geographically, but

tends to track that of snowshoe hares. Lynx prefer older (>20 years old) regenerating

forest stands. Mature forest stands are often used but rarely selected. Most lynx dens

found to date have been associated with blowdown or deadfall trees in regenerating stands. Lynx maintain mostly exclusive intrasexual territories, based on social

intolerance and mutual avoidance. Male home ranges tend to be larger than female

ranges. There appears to be no linear relationship between hare abundance and lynx

home range size, although lynx do increase their home range size dramatically

following the cyclic hare crash. Male and female home ranges generally overlap

completely while within-sex overlap is usually modest; related females may
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Chapter 9—Mowat

tolerate greater overlap. Lynx numbers fluctuate in synchrony over vast areas

and generally lag behind the snowshoe hare cycle by about one year. Peak densities

of 30-45 lynx/100 km2

 have been observed in regenerating stands, and 8-20/100 km2

in mature forest and more southern ranges. Population densities during the low

are <3 lynx/100 km2

. Growth in lynx populations is a result of high fecundity,

high kit survival, and low adult mortality. The decline is due to increased dispersal,

high natural mortality, and a collapse in recruitment. During hare abundance, adult

fecundity is high, litter size averages four to five, and yearling lynx give birth.

During the cyclic low, recruitment essentially fails for about two years, and is

followed by several years of modest recovery. Although trapping is an important

mortality source in many areas, natural causes (primarily starvation and predation)

account for most detected mortality during the first two years after the hare decline.

Fifteen straight-line dispersal distances of 500-1,100 km have been recorded from

recent studies in the two northern territories. Dispersal of adults was highest during

and following the decline in hare densities. Trapping can reduce lynx populations

and can have the greatest impact during the cyclic low, but the long-term impact of

trapping on subsequent cycles is unclear. Despite reduced harvests in all jurisdictions and localized overharvest in some areas, no permanent decrease in range

has been detected in contiguous northern populations.

Introduction

The primary purpose of this chapter is to synthesize relevant information on lynx ecology in northern Canada and Alaska. We have followed the

ecoregion domains of Bailey (1998) to divide work covered in this chapter

from work conducted in “southern boreal forests” (Chapter 13); here we

review research conducted in the polar domain (Bailey 1998). Our intention

was to review studies done in a northern boreal environment, as opposed to

those done in more southern forests (reviewed by Koehler and Aubry 1994).

Much new research on lynx has been conducted over the past decade,

most of it from the northern boreal region. This chapter will emphasize

these recent studies and will update previous reviews of lynx ecology

(e.g., McCord and Cardoza 1982; Tumlison 1987; Quinn and Parker 1987;

Hatler 1988, unpublished; Koehler and Aubry 1994). We refer briefly to

snowshoe hare ecology primarily as it directly relates to lynx; more comprehensive examinations of the ecology of both northern and southern

hare populations are provided in Chapters 6 and 7.

There has been much casual discussion among lynx researchers and

managers regarding the similarity of ecological dynamics, processes, and

relationships of northern populations of lynx to those residing in montane
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Mowat—Chapter 9

environments. We make limited comparisons between northern and

southern populations here; this will be covered in greater detail in

Chapter 13. Here we review lynx behavior in terms of prey selection,

foraging patterns, habitat selection, and social organization. We summarize

information regarding population dynamics including recruitment, survival, dispersal, and population densities. All topics are presented with

respect to the relationship between lynx and snowshoe hare population

dynamics. The relationship between lynx and other carnivores of the

boreal community are presented elsewhere (Chapter 4).

Description

The Canada lynx is a medium-sized cat with a flared facial ruff, black ear

tufts, large padded feet, and a short, black-tipped tail (Banfield 1974; Quinn

and Parker 1987). Lynx show mild sexual dimorphism in size, males (averaging 80-90 cm long and 9-10.5 kg in weight) being 13-25% larger than

females (76-84 cm long and 8-9 kg; Quinn and Parker 1987). In the north, lynx

are found to the northern limit of trees in Alaska, Yukon, and mainland

Northwest Territories (NWT). Lynx are widespread and cyclically abundant in the North and the lynx harvest is an important source of income

for many northern residents. In recent times lynx, along with marten,

have provided the principal source of income for northern trappers

(Slough et al. 1987).

Food Habits

Snowshoe hares form most of the diet of lynx across North America.

Hares comprise from one-third to nearly all of prey items identified for

lynx (for food habits summaries see Quinn and Parker 1987:686; Koehler

and Aubry 1994:75; O’Donoghue et al. 1998b). Other common prey items

include red squirrels, mice and voles, flying squirrels, ground squirrels,

beaver, muskrat, grouse and ptarmigan , and other birds. Ungulates, including deer, caribou, moose, Dall’s sheep, and bison, are eaten as carrion and

occasionally, excluding bison and moose, as prey (Saunders 1963a; Bergerud

1971; Parker et al. 1983; Stephenson et al. 1991; K. Poole, unpublished).

Predation on ungulates is generally restricted to calves, although adults are

taken (Stephenson et al. 1991). Use of ungulates appears to be greater

during winter and during cyclic low hare abundance. Predation by lynx on

red fox and other lynx also occurs, again mostly during periods of low hare

numbers (Stephenson et al. 1991; O’Donoghue et al. 1995).

Several trends are evident when examining data on lynx diets. In lynx

populations reliant on highly cyclic populations of snowshoe hares, the
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Chapter 9—Mowat

proportion of hares in the diet generally declines and use of alternative

prey increases as hares become scarce (Brand et al. 1976; Stephenson et al.

1991; O’Donoghue et al. 1998b; K. Poole, unpublished). In southwestern

Yukon, red squirrels became increasingly important (20-44% biomass) during the years of lowest hare density compared to almost no use (0-4%

biomass) during years of high hare densities (O’Donoghue et al. 1998b).

Similarly, during years of hare scarcity, use of carrion, red squirrel, ruffed

grouse, and other birds increased in central Alberta (Brand et al. 1976), and

in southwestern NWT, red squirrels and birds were found more frequently

(K. Poole, unpublished data). Red squirrels in particular appear to be an

important alternative food source for lynx throughout the North during

periods of low hare abundance.

Lynx diets in summer generally have less snowshoe hare and more

alternative prey than in winter (Quinn and Parker 1987; Koehler and Aubry

1994). On the Kenai Peninsula in Alaska, Staples (1995) found 64% and 38%

hare and 11% and 28% red squirrel in winter and summer lynx scats,

respectively. In the Gaspé region of Québec, Fortin and Huot (1995) found

hares formed 58% of the diet of lynx during the snow-free period and 85%

during winter, with small mammals and red squirrels being important

secondary prey during both periods. The lynx diet in southwest Yukon in

summer contained a greater diversity of prey, primarily because of the

addition of ground squirrels (O’Donoghue et al. 1998c). Other common

alternative prey used by lynx during summer include ducks, passerines and

other birds, ungulates, and carrion (Saunders 1963a; van Zyll de Jong 1966;

Nellis et al. 1972; Brand et al. 1976; Parker et al. 1983). It is unclear whether

the greater abundance of alternative prey in lynx diets during summer is a

result of decreased hunting success on hares or an increase in the availability

of alternative prey.

To our knowledge, differences in diets of lynx by age and sex class have

not been reported. At high hare densities, when lynx eat almost solely hares,

few inter-class differences in diet would be expected. At lower hare densities, however, some partitioning in resources might be expected. Pulliainen

et al. (1995) found no differences in diet between sexes or age categories of

European lynx in east Finland where hares dominated the diet. However, in

southwest Finland, where hares and white-tailed deer were consumed

equally, male lynx consumed more deer and fewer hares than females.

Foraging Ecology and Hunting Behavior

Due to their heavy dependence on hares for food, morphological adaptations to hunting hares (Murray and Boutin 1991), and almost complete
269

Mowat—Chapter 9

overlap of geographic range with hares (Banfield 1974), lynx are usually

considered hare specialists. Accordingly, their foraging behavior is characterized by hunting tactics and movement patterns appropriate for hunting

hares.

Lynx hunt by either stalking and rushing at their prey, or ambushing

them from “ambush beds” established near the trails of prey (Murray et al.

1995; O’Donoghue et al. 1998a). In the southwest Yukon, the frequency of

ambush beds along lynx trails increased nine-fold from the cyclic peak to

the low (O’Donoghue et al. 1998a). This corresponded to a switch in diet

(sensu Murdoch 1969) from hares to red squirrels and the establishment of

more ambush beds near squirrel middens. During this period, lynx also

initiated progressively more chases of hares from ambush beds (from about

4% to 36% of all chases), although their hunting success was about the same

as from stalks for hares, and slightly lower for squirrels (O’Donoghue et al.

1998a). Frequent use of ambush beds by lynx has been noted in one other

study (Saunders 1963a, 1963b), but elsewhere lynx seldom ambushed

hares (Nellis and Keith 1968; Parker 1981). The costs and benefits of ambushing rather than stalking prey likely depend on prey abundance and

behavior as well as the physiological state of the predator (see, for example,

Davies 1977 and Formanowicz and Bradley 1987). Ambushing prey when

their availability is low may be more energetically efficient for lynx than

actively searching for them (O’Donoghue et al. 1998a).

Lynx typically prefer feeding on freshly killed prey over scavenging

(Parker 1981; O’Donoghue et al. 1998b). In the southwest Yukon, lynx cached

the whole carcasses of only 1.6% of the radio-collared hares they killed,

compared to 37.0% of those killed by coyotes (O’Donoghue et al. 1998b).

Lynx caches were formed on the surface of the snow by the lynx pulling snow

over them. All of the caches that were monitored and retrieved by lynx were

consumed in less than two days. Observations of lynx scavenging hares

(Nellis and Keith 1968; Parker 1981) and the carcasses of ungulates (see Food

Habits) have been made as well, but this appears to occur most often during

times of food shortage.

While typically solitary, lynx regularly hunt in mother-kit family groups.

Families usually spread out while hunting hares in good habitat, and hares

flushed by one animal are often killed by another (Saunders 1963a; Parker

1981; Mowat and Slough 1998; O’Donoghue et al. 1998a). This behavior

undoubtedly increases the foraging efficiency of family groups, but likely

due to the inexperience of kits, calculated per-individual kill rates of lynx

hunting as families were 50-60% lower than those of adults hunting alone

(O’Donoghue et al. 1998a). Groups of two or three adult lynx foraging

together were recorded in the southwest Yukon during the cyclic decline

and low (O’Donoghue et al. 1998a). Very limited data from the latter study
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Chapter 9—Mowat

suggest that the kill rates of animals in these groups may have been equal to

or higher than those of lynx foraging by themselves. Several other authors

have recorded small groups of adult lynx together (Carbyn and Patriquin

1983; Poole 1995; Staples 1995; Mowat and Slough 1998), and Barash (1971)

recorded adult lynx hunting and feeding together. Aldama and Delibes

(1991) recorded similar behavior in Iberian lynx.

Lynx-Prey Relationships

Although the boreal forest has relatively low species diversity, the food

web of boreal vertebrates appears to be more complex than was once

recognized (Krebs and Boutin 1998, unpublished). The close relationship

between population fluctuations of lynx and snowshoe hares is well documented. Lynx respond both numerically, through changes in their rates of

survival, recruitment, and movements, and functionally, through changes

in their kill rates, to the hare cycle. The lags in these responses, and in the

combined “total response” (which expresses changes in the proportion of

the prey population killed relative to prey density), contribute to the cyclic

behavior of the system by introducing a delayed density dependent effect

(May 1981; Korpimäki and Krebs 1996; Sinclair and Pech 1996).

Numbers of lynx may vary from three to 17-fold during a cyclic fluctuation

(Keith et al. 1977; Poole 1994; Slough and Mowat 1996; O’Donoghue et al.

1997). Peak densities are typically reached one year after the cyclic peak

for hares, thus the numerical responses of lynx to changing densities of

hare show delayed density dependence (Sinclair and Pech 1996;

O’Donoghue et al. 1997).

The functional responses of lynx to the hare cycle have only been estimated

in two studies. In Alberta, lynx killed about three times as many hares at

cyclic peaks as they did when the abundance of hares was low; maximum

kill rates were estimated to be about 0.8 hares per day (Keith et al. 1977).

Based on their data from snow-tracking, these authors estimated that lynx

showed a Type-2 functional response (sensu Holling 1959b), or one in which

kill rates increase at a monotonically decreasing rate to an asymptotic

maximum. Kill rates of hares by lynx varied four to five-fold in the

southwest Yukon during a hare cycle, and the estimated maximum kill

rates were higher than those in Alberta at about 1.6 hares per day (O’Donoghue

et al. 1998b, 1998c). A Type-2 functional response also fit the observed data

well for this study. The calculated kill rates in Alberta may have been

underestimates, due to the assumptions made that lynx only rested once per

day (Brand et al. 1976; Keith et al. 1977), which is questionable (Parker 1981;

O’Donoghue et al. 1998b).
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Changes in the kill rates of hares by lynx are accompanied by behavioral

changes that likely change the “components” (Holling 1959a, 1966) of the

functional responses. Lynx chased hares for longer distances when hares

were rare than when they were abundant in the southwest Yukon, so

“reactive distances” of lynx may have changed as well (O’Donoghue et al.

1998b). The reported success of lynx in catching hares once they had

initiated chases has varied from 19% to 57% (Saunders 1963a; Brand et al.

1976; Parker 1981; Major 1989; O’Donoghue et al. 1998b), but it does not

seem to be directly related to density of hares (Brand et al. 1976; O’Donoghue

et al. 1998b). In the southwest Yukon, the travel rates and total activity time

also varied little over the course of the cycle (O’Donoghue et al. 1998b), while

activity rates did seem to increase with lower densities of hares densities in

the NWT (K. Poole, unpublished). However, switches in prey selection

(from hares to red squirrels) and hunting tactics at low hare numbers both

likely contributed to the functional responses in the southwest Yukon. Kill

rates by lynx and other predators may only decline once hares are concentrated in largely inaccessible habitats, or “refugia” (Wolff 1980; Hik 1995).

Refugia for prey species typically act to stabilize predator-prey relationships (Taylor 1984), and a relatively invulnerable subpopulation of hares

in very dense cover likely allows them to persist at higher densities

through cyclic lows.

The total impact of predation by lynx on the dynamics of hare populations is determined by combining their numerical and functional responses

(Solomon 1949; Messier 1995). Based on their calculated responses, Keith

et al. (1977) estimated that lynx killed from 2 to 13% of the hares present

each winter in Alberta, with peak predation rates occurring two to four years

after the hare cyclic high. Likewise, lynx killed an estimated 4 to 32% of

hares over winter in the southwest Yukon, with the highest predation rates

one to three years after the cyclic peak (O’Donoghue et al. 1998c). Again, the

lag in the effect of predation on numbers of hares would contribute to the

cyclic dynamics, and throughout the cycle in abundance of hares, lynx are

one of the most important predators of hares. Exclusion of lynx and coyotes

from experimental areas in the southwest Yukon, when combined with

food addition, resulted in densities of hares approximately 11 times higher

than those on control areas, and this effect was most pronounced during the

cyclic low (Krebs et al. 1995; Krebs and Boutin 1998).

While the effects of predation by lynx on hares may be considerable,

lynx likely have little impact on other alternative prey in the boreal forest.

Grouse were the main alternative prey of lynx in Alberta (Brand et al. 1976),

but they never represented more than an estimated 12% of the total

biomass in the diets of lynx. Keith et al. (1977) attributed synchronous
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Chapter 9—Mowat

fluctuations in numbers of grouse and hares to changes in predation rates on

grouse by raptors. In the southwest Yukon, red squirrels were the most

important alternative prey for lynx during years of low abundance of hares

(O’Donoghue et al. 1998b). However, even when squirrels represented 79%

of kills by lynx during winter, the total impact of predation by lynx was less

than 4% of the estimated population of squirrels (O’Donoghue et al. 1998c).

The negligible impact of predation by all terrestrial predators on red

squirrels was also confirmed experimentally in the Yukon (Stuart-Smith

and Boutin 1995). Throughout their range, lynx appear unable to persist at

high densities when numbers of snowshoe hares are low. This both limits

the effect of their predation on alternative prey, and allows numbers of

hares to recover from cyclic lows.

Habitat Selection and Use

At the largest spatial scale, lynx occupy the boreal, subboreal and western

montane forests of North America (McCord and Cardoza 1982; Quinn and

Parker 1987). They occur in many forest types that are not truly boreal,

although all of the forests they occupy are relatively simple in terms of

physical structure and species composition (Koehler and Aubry 1994). Lynx

are absent or uncommon in the wet coastal forests of western Canada and

Alaska. Lynx are more or less ubiquitous residents of northern forests,

with their distribution becoming more discontinuous toward the south.

Legendre et al. (1978) demonstrated that lynx were most abundant in the

boreal forest of their northeast Québec study area, and that lynx distribution

was associated with the distribution of the hare. Lynx were also found in

the sub-arctic forest, which was dominated by balsam fir and paper birch.

Lynx were not found in the more open subarctic forests and tundra to the

north. Dwyer et al. (1989) concluded that lynx in central Ontario were

primarily associated with upland boreal forest and, to a lesser extent,

marshlands with black spruce, alder and willow. Lynx avoided wetlands

with cattails, oak, maple, and hemlock. Quinn and Thompson (1987) found

that lynx were abundant in both the boreal and mixed-wood boreal zones

in central Ontario; these authors compared several population parameters

among the two zones and found no strong indication to suggest differences

in fitness or density. In western Canada, Hatler (1988) reported that the

majority of the lynx harvest in British Columbia (B.C.) came from the only

area of true boreal forest in the province.

At the stand level, lynx prefer regenerating forest stands like those of its

main prey, the snowshoe hare (Thompson 1988; Koehler and Aubry 1994).

Throughout the north, lynx select older regenerating stands (greater than

about 20 years of age) both of human and fire origin at all points in the hare
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Mowat—Chapter 9

cycle (Kesterson 1988; Thompson et al. 1989; Major 1989; Perham 1995;

Staples 1995). Lynx do not frequently use younger regenerating stands

(Thompson et al. 1989; Golden 1993; Perham 1995; Staples 1995). It appears

climax shrub stands are also avoided (Staples 1995), even when they contain

sizeable hare populations (Murray et al. 1994), although the work of Major

(1989) suggests these stands may receive greater use in summer. Many

authors have demonstrated use (though not selection) of mature forest

stands, and indeed one study team (Murray et al. 1994 and O’Donoghue et

al. 1998a) worked where all forested stands were mature. It is interesting to

note that these authors reported a persistent lynx population in this area,

even during a cyclic population low (O’Donoghue et al. 1997). Kesterson

(1988) and Staples (1995) both demonstrated strong selection for mature

stands included within a mid-seral burn, but they demonstrated strong

selection against mature forest when it was the matrix habitat. We conclude

that mature coniferous habitat can support lynx in the North, although the

quality of mature habitat may vary regionally. Major (1989) and Mowat et al.

(1998, unpublished) demonstrated that mature aspen, white spruce, and

black spruce stands in three areas of Yukon contained significant quantities

of browse and horizontal cover, and contained modest numbers of hares

during all phases of the cycle.

Do lynx and hares show similar patterns of habitat selection? We suggest

yes, with two exceptions. First, hares appear to select more dense stands

than lynx (O’Donoghue et al. 1998a). Presumably lynx are unable to hunt

in the densest stands and are hence excluded. This suggestion is consistent

with the observations of many researchers (e.g., Wolff 1980) that hares

survive in pockets of dense habitat during the cyclic low. Second, hares

appear to select dense shrubs with little aerial cover, at least during periods

of reasonable abundance, whereas lynx rarely use such stands. Keith (1990)

suggested that hares need dense understory cover but that “overstory

characteristics are of doubtful significance in habitat selection.” It is unclear,

however, whether lynx avoid some shrub stands because they lack aerial

cover or because they are simply too dense to hunt in successfully. Based on

observations of hares using denser cover than lynx in forested stands, we

suggest that the latter explanation is correct.

Only one study has measured lynx and hare habitat use over the course of

a cyclic fluctuation (O’Donoghue et al. 1998a). In the southwest Yukon

study, the pattern of habitat selection by lynx roughly followed that of hares

though, on average, hares used denser stands in all years. Lynx and hares

used habitats with the densest vegetative cover during the cyclic decline,

while both used more open habitats when hares were abundant (O’Donoghue

et al. 1998a). This study was conducted in a mature forest matrix and it is

unclear whether lynx also move to denser habitats in regenerating stands
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Chapter 9—Mowat

when hares are scarce. Within years, lynx may demonstrate broader habitat

choice during summer when alternative foods are more abundant (Major

1989; Fortin and Huot 1995).

Kesterson (1988) and Staples (1995) both demonstrated selection for a

relatively rare habitat, which they describe as mature stands within a burned

forest matrix. Both these authors suggested that lynx tend to hunt along the

edge of this habitat. Major (1989) also suggested that lynx hunted edge

habitats—in this case, the edge of dense riparian willow stands. The use of

habitat edges may be an important hunting strategy for lynx, which may

allow them to hunt hares that live in habitats that are normally too dense to

hunt effectively. Several authors have shown that lynx select against openings such as water or open meadows, although some use of terrestrial

openings was always detected (Murray et al. 1994; Fortin and Huot 1995;

Poole et al. 1996). Most openings have few if any resident hares, so this result

is not surprising, especially in winter. This does not indicate that lynx will

not cross openings; indeed the fact that lynx were occasionally located in

openings, including farmland (Fortin and Huot 1995), suggests they are not

against entering them. We found lynx regularly crossed several hundred

meter wide openings during our work in NWT and Yukon; occasionally,

lynx crossed frozen lakes and rivers >1 km across (K. Poole and G. Mowat,

personal observation).

While relatively few lynx dens have been described in the North, all had

similar structural aspects regardless of their stand types. Berrie (1974)

described three dens located in central Alaska; two were in tangles of spruce

blowdown, and the other was in a tangle of spruce roots washed up on the

bank of a creek. Stephenson (1986) located one den site in a mature sprucebirch stand, with the den located in an area of numerous deadfall trees.

Kesterson (1988) stated that “lynx seemed to select den sites in or near

mature habitats dominated by large quantities of wind-felled trees.” Hatler

(1988) described a den found in logging debris and blowdown on the edge

of a six to eight-year-old cut-block in northern B.C. Slough (in press) located

39 lynx dens in south-central Yukon. One of these den sites was in a mature

spruce stand, one was in a mature subalpine fir stand, and 37 were in

regenerating stands about 30 years in age. Three dens were under

young, bushy subalpine fir trees, two were in dense copses of mature

willow, and 34 were under blowdown, usually dense tangles of trees. Poole

(1992) located five lynx den sites in southwestern NWT. Den sites were

characterized as areas of moderate to heavy deadfall located in mature

conifer or regenerating mixed conifer and deciduous stands. In summary,

female lynx appear to select den sites in a number of forest types in the

North. Lynx do not appear constrained to select specific stand types;

rather, the feature that was consistently chosen was the structure at the site
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itself. Wind-felled trees were the most common form of protection selected

by female lynx, although other structures such as roots and dense live

vegetation were also used. The importance of proximity to areas with high

prey density to den site selection has not been examined.

Wildfire, which is the most important factor in the dynamics of the

northern boreal forest ecosystem (Kelsall et al. 1977; Viereck 1983), is a major

habitat modifier (Johnson et al. 1995). Johnson et al. (1995) and Paragi et al.

(1997) suggest that optimum habitat for hare and lynx can be achieved in

interior Alaska by frequent and numerous but relatively small fires, or large

patchy fires with abundant unburned inclusions. However, the effects of

spatial heterogeneity and juxtaposition of habitats on behavior and population dynamics of lynx are unstudied.

Logging, which is also an important factor in the dynamics of many

boreal forests, restarts the succession necessary to create optimum hare

and lynx habitat, but often removes the structure needed for denning by

lynx. Whether the regrowth on a logged area becomes usable hare habitat

will depend on site level factors and silviculture treatment post-harvest

(Thompson 1988; Koehler and Brittell 1990). Thompson (1988) suggested

that planted and tended boreal sites are used less by hares and lynx than

naturally regenerating sites. Thompson (1988) further suggested that increased hare and lynx populations would occur with logging plans that

incorporate numerous small stands of mature forest, hence increasing the

amount of uncut forest-successional edge. There may be a limit to the benefit

of edges for hares because predation on hares may increase in small habitat

patches (Chapter 6); very small patches may present predation risks that are

not sustainable for hares. We conclude that logging will only provide quality

lynx habitat if a dense understory of coniferous or deciduous vegetation

results. Because hares select habitat based more on understory cover than

browse (Chapter 6), plant species appear to be of secondary importance.

Except for extremely dense stands, silvicultural prescriptions such as precommercial thinning or herbicide application that thin or remove the understory probably reduce habitat quality for lynx (but see Sullivan 1994, 1996).

Leaving groups of standing and downed trees may allow for denning

opportunities within the cutting area and not force female lynx to search out

den sites in mature forest, as suggested by Koehler and Brittell (1990).

Denning structure must be scattered about the landscape because female

lynx probably establish temporary dens throughout their home range

during the period when kittens are old enough to travel but not hunt (Bailey

1981). Several of the above authors have suggested that good lynx habitat

includes both late and early seral components; we conclude that lynx can

survive in single habitat types, such as early seral or mature forests, as long

as the features to support both hares and denning by lynx exist.
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Chapter 9—Mowat

Spatial Organization, Social Behavior

The lynx spacing mechanism is functionally similar to that of other

Carnivora such as mustelids and ursids. Brittell et al. (1989) suggested that

lynx have a social organization similar to that of bobcats and cougars,

consisting of social intolerance and mutual avoidance (Seidensticker et al.

1973; Bailey 1974). Powell (1979) described this land tenure system as

“intrasexual territories” and Kesterson (1988) also used this description for

lynx. In this system, resident individuals maintain intra-sexually exclusive

territories, and males may or may not have larger home ranges than

females. Lynx are territorial, but not according to the strictest definitions

(see Hornocker et al. 1983 for a related discussion of this topic). Scentmarking using feces, sprayed urine, or anal secretions may be used to mark

home ranges and to provide both spatial and temporal information that may

reduce confrontations (Saunders 1963b; Mellen 1993; Staples 1995). Lynx

also show strong range fidelity, often over many years (Poole 1995;

O’Donoghue et al. 1998c), have core range areas that seldom overlap (Poole

1995; O’Donoghue et al. 1998c), and appear to avoid contact among individuals (Poole 1995) and violent encounters (Poole 1995; Mowat and Slough

1998). Poole’s (1995) work suggests that some sort of spacing mechanism

was operating to keep same-sex animals separated in time and space.

However, the tendency toward neutral indices of dynamic interactions (the

degree to which two animals avoid, ignore, or attract each other [Macdonald

et al. 1980]) indicated little or no active avoidance or overt defense of areas

between overlapping or adjacent pairs, suggesting that this spacing was

upheld by relatively passive means. Conflict among individuals is rare in

lynx (Poole 1995; Mowat and Slough 1998) and perhaps in other solitary

felids as well (Hornocker and Bailey 1986). Aggressive lynx-lynx encounters

do occur, however, and occasionally result in cannibalism, primarily during

years of food shortage (Poole 1994; O’Donoghue et al. 1995; Mowat and

Slough 1998).

Lynx home range sizes vary among areas, sexes, seasons, and cyclical

phases. It is difficult to compare home range sizes among studies because of

differing methods of data collection, sample sizes, and analysis techniques.

Many studies did not determine the ages of the individuals tracked and

could not identify subadults. Further, the home range size of breeding lynx

may increase (Kesterson 1988), hence yearly home ranges may vary depending on when the data were collected, especially when sample sizes are small.

Koehler and Aubry (1994) summarized home range sizes for lynx. Dramatic variation in home range size has been reported for lynx across their

North American range (8-738 km2

), not all of which can be explained by

differences in measurement and analysis techniques. Male home range
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Mowat—Chapter 9

sizes are usually larger than female ranges (Kesterson 1988; Koehler and

Aubry 1994; Fortin and Huot 1995; Perham 1995; Slough and Mowat 1996;

O’Donoghue et al. 1998c, but see Ward and Krebs 1985 and Poole 1994). In

the south-central Yukon, yearling lynx had similar home range sizes to

adults (Slough and Mowat 1996), while Noiseux and Doucet (1987) found

that yearling home ranges were generally smaller than adult home ranges in

southern Québec. Philopatry to home ranges has been reported among

individuals of both sexes resident over several years, but home range shifts

and abandonment are also common (Breitenmoser et al. 1993b; Poole 1994;

Perham 1995; Slough and Mowat 1996; O’Donoghue et al. 1998c).

Poole (1994), Slough and Mowat (1996), and O’Donoghue et al. (1998c)

showed that lynx range size increased dramatically after the sudden decrease in hare abundance in the North. Perham (1995) studied lynx after a

hare decrease in Alaska and found great variation in home range size of

males, several of which had ranges >200 km2

. Poole (1994) and Slough and

Mowat (1996) presented data for several years before the hare decrease and

home range size changed little during this period. Ward and Krebs (1985)

suggested lynx home range size changed with hare abundance; however,

they used a categorical analysis (with three categories of hare abundance) to

test this relationship, and only the largest and the smallest categories

differed significantly from one another (p <0.05). Therefore, their data could

also be interpreted to show similar home range sizes through the lynx cycle

followed by an increase after the sudden hare population decrease. The

only researchers to empirically test for a linear relationship between lynx

home range size and hare abundance were Brand et al. (1976) and Slough

and Mowat (1996). Brand et al. (1976) used only eight home range sizes

across five different winters and were further forced to pool the sexes for

their analysis; these limitations aside, they did not find a linear relationship between lynx home range size and hare abundance. Slough and Mowat

(1996) had larger sample sizes across eight years and found no liner relationship for either sex.

It may be more appropriate to test lynx home range size against hare

abundance the previous year because there appears to be a one year lag in

the numeric response of lynx to hares (Krebs et al. 1995; O’Donoghue et al.

1997). We used correlation analysis and published data from Poole (1994)

and Slough and Mowat (1996) to test for a linear relationship between

lynx home range size and hare density the previous year. We used mean

yearly home range sizes for each sex because of the large variation in sample

size among years (n = 1-15 individuals per year). These conservative tests

suggest there was no linear relationship between lynx home range size and

hare density the previous year for both sexes and study areas (p >0.3, df

3-7 in all cases; Fig. 9.1a,b).
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Chapter 9—Mowat

Lynx did increase their home range sizes dramatically following the hare

crash, and as mentioned above, it would further appear that home range size

changes relatively little during years of high hare abundance. There appears

to be a threshold hare density below which lynx home range size increases

(Fig. 9.1a,b). We did not compare yearly changes in home range size for

individual lynx; perhaps some individuals do alter their home range size

with hare abundance in a more linear fashion.

Home ranges vary seasonally in lynx. Females hunt alone while the kittens

are young, making solitary forays from the den site. As kittens get older they

begin to travel with the female, although it is assumed they are cached at

temporary den sites when she is hunting (Kesterson 1988), as has been

recorded for bobcats (Bailey 1979). Kesterson (1988) and Mowat and Slough

(1998) observed that female home ranges were very small during the

denning period; range size increased appreciably in mid-summer once the

kittens were large enough to begin leaving the den site. By early fall, female

home range size expands to reoccupy the area used before birth, and we

assume that the kittens travel with the female, even while hunting (Bailey

1979; Winegarner and Winegarner 1982; Kesterson 1988). Kittens remain

with the mother throughout the winter. Family groups begin to break-up in

early March (Saunders 1963b; Brand et al. 1976; Parker et al. 1983; Poole 1995;

Mowat et al. 1996b). Kittens appear to be closely associated with their

10

20

30

40

50

60

70

km

1 2 3 4 5

Hares/ha

Male home range size

Female home range size

2

100

200

300

400

500

600

1 2 3 4 5 6 7 8

km

Hares/ha

Male home range size

Female home range size

2

Figure 9.1—The relationship between lynx home range size (n = 1-15) and hare density the previous

year across: (a) eight years of a hare cycle in south-central Yukon (Slough and Mowat 1996), and (b) four

years of a hare cycle in southwest NWT (Poole 1994; K. Poole, unpublished).

a b
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Mowat—Chapter 9

mothers until February or early March, when the association weakens;

natal dispersal begins in late April and early May (Poole 1995; Mowat et al.

1996b). Some juvenile kittens disperse immediately (Poole 1995; Slough and

Mowat 1996), while others remain in the natal area for up to one year after

their first winter (Kesterson 1988; Slough and Mowat 1996). Similar behavior has been recorded for bobcats (McCord and Cardoza 1982) and

Iberian lynx (Aldama and Delibes 1991). Dispersal from the mother’s home

range can be sudden or it can be a more gradual process (Kesterson 1988;

Poole 1994; Mowat and Slough 1998). Separation of the kittens and mother

may be hastened by the subsequent breeding of the adult female (McCord

and Cardoza 1982); however, Mowat and Slough (1998) documented a

female and male lynx together for several days in the company of the

female’s 10-month-old kittens. Kesterson (1988) noted no strong trend

toward increased home range size of males during the breeding season in his

study population, though a few individuals did appear to increase their

range size while breeding.

Home range overlap is often used to assess social patterns in mammals.

This parameter is probably measured even more inaccurately than home

range size because it is affected by all the constraints mentioned above for

home range and is further complicated by the fact that errors can be made

during interpretation of the measurement when relatedness of individuals

is unknown. Unfortunately, relatedness of individuals is rarely known in

field studies. Given the above constraints, it is not surprising great variation

in overlap has been shown for both sexes (Ward and Krebs 1985). In the

NWT, Poole (1995) recorded variable amounts of overlap among lynx

during peak and declining densities of snowshoe hares. Much of the overlap

was among females and was attributed to several pairs of females that

showed large overlap in home range, often for several years. These females

were assumed to have been related. This observation shows the weakness in

measuring range overlap when individual relationships are unknown.

Researchers working on other species of lynx have also recorded variable

home range overlap within sexes (Breitenmoser et al. 1993a; Jedrzejewski et

al. 1996; Ferreras et al. 1997). Generally, male and female home ranges

overlap completely while within-sex overlap is usually modest or may be

confined to one or two pairs of individuals per study (e.g., Poole 1995).

Home range exclusiveness may be a function of degree; some overlap may

occur at the 90 or 95% home range contour level, but, as noted in Poole (1995),

little may occur among the 50% contour core areas.

Felids are said to have a social system based on matrilineal descent

(Kleiman and Eisenberg 1973; Kerby and Macdonald 1988). This theory

would suggest that pair bonds between females, either mother-daughter or

sibling pairs, persist and that these relationships form the basis for the
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Chapter 9—Mowat

organization of social structure. This theory is difficult to test in solitary

species, but there is evidence suggesting that female pair bonds do persist in

Canada lynx and other lynx. Female kittens sometimes establish home

ranges within those of their mothers (Kesterson 1988; Breitenmoser et al.

1993b; Slough and Mowat 1996). Kesterson (1988) found that three female

kittens remained in or near their natal ranges during the entire period for

which they were monitored. This trend has been noted in other solitary

felids (Eisenberg 1981; Sundquist 1981; Ross and Jalkotzy 1992) and suggested by Poole (1994) and Staples (1995) for Canada lynx. Secondly, adult

females may retain amicable contact with their female offspring throughout

their life. Barash (1971) witnessed a group of two adult and one yearling

lynx hunt and share a ground squirrel. Carbyn and Patriquin (1983)

located two different female and kit groups together five times over a 30-day

period. Staples (1995) recorded two different adult females together, each

with a single yearling female offspring, a total of 15 times. O’Donoghue et al.

(1998a) witnessed several adult animals hunting together through three

winters during the cyclic hare decline and low. Mowat and Slough (1998)

often recorded related adult females together during their study of lynx in

south-central Yukon, even when both females had accompanying kittens.

Mowat and Slough (1998) also reported an incident where an adult female

and her yearling offspring gave birth within 800 m of each other. Both Poole

(1995) and O’Donoghue et al. (1997) found female home ranges with large

overlap, although this was not the norm on either study area; both groups

felt that these females were likely related.

The persistence of female bonds has important implications for lynx

conservation. Matrilineal groups may confer greater fitness on their members by allowing group hunting at certain times (O’Donoghue et al. 1998a),

the possibility of adoption of orphaned kittens (Carbyn and Patriquin 1983;

Mowat and Slough 1998), and a reduction in the investment in territorial

defense. In addition, populations with related individuals may attain

higher density because territoriality may be relaxed among relatives.

Behavioral Responses of Lynx to Humans

Staples (1995) presented data on lynx responses to close encounters with

humans. As suggested by earlier authors, he found that lynx were generally

tolerant of humans. The work of Staples (1995) and other anecdotal

accounts of lynx behavior suggests that lynx can tolerate human disturbance

and even continued presence. Trappers will relate that lynx are relatively

easy to capture; they appear to have little fear of human scent, they respond

to baits and lures, and can be attracted using visual attractants.
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Humans may exert potentially negative influences on lynx by building

residences and roads in and through lynx habitat, by altering and modifying

existing habitats, and by direct disturbance through recreation or travel in

areas inhabited by lynx. Our anecdotal experiences suggest that lynx will

tolerate moderate levels of snowmobile traffic through their home ranges.

We could not detect changes in lynx movement patterns or home range in

our northern studies despite constant, repetitive and daily travelling through

the study areas to check traps and locate animals. Lynx appeared to readily

cross highways, and several animals in southwestern NWT established

home ranges adjacent to roads. Lynx are also regularly sighted sitting along

roadsides in the North. Lynx tracks were regularly observed adjacent to

residential areas in both Yukon and NWT, although we do not know if these

animals were residents. Lynx may tend to avoid areas with higher levels of

disturbance or greater fragmentation of habitat from development, although this has not been rigorously tested. Several studies of lynx have

occurred in areas with reasonably dense rural human populations and

interspersed agricultural areas, which further suggests lynx can tolerate

daily human use and presence in an area (Brand and Keith 1979; Fortin

and Huot 1995). Both these studies demonstrated resident lynx populations of about 10/100 km2

.

Although lynx will generally flee when closely approached, they appear

to become bolder and less wary of people during periods of low prey

abundance. Anecdotal observations include a lynx eyeing a dog on the edge

of a mid-summer wedding celebration in the NWT, another killing a dog

outside a trapline cabin while the trapper was present, and a third defending

a fox caught in a trap while the trapper approached. Several incidences of

lynx stalking domestic animals throughout the Yukon during low prey

abundance have been recorded (Mowat and Slough 1998).

Population Dynamics

Lynx numbers fluctuate in response to population levels of snowshoe

hare, and the decline in lynx numbers generally lags one year behind the

decline in hare numbers (Elton and Nicholson 1942; Butler 1953; Keith 1963;

Brand and Keith 1979; Boutin et al. 1995). Lynx populations, as indexed by

harvest data, (Fig. 9.2) fluctuate in synchrony over vast geographic areas,

showing roughly similar trends in timing and amplitude of cyclic peaks and

lows across the continent (Ranta et al. 1997). The lynx cycle appears to

initiate and emanate from central Canada, following similar trends in the

hare cycle (Smith 1983), such that peak lynx harvests in Saskatchewan and

Manitoba from 1960 to 1980 occurred around the turn of the decade, and two

to four years later in Yukon, Alaska, and Québec. Long-distance dispersal of
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Figure 9.2—Lynx harvest from 1920 to 1997 for eight Canadian territories and provinces and Alaska. Data from 1920 to

1983 were primarily from Novak et al. (1987). Data from 1984 to 1997 were obtained from the individual provinces and

territories and from the State of Alaska.

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Mowat—Chapter 9

lynx and other predators during cyclic declines could act as a synchronizing

element of the hare cycle (Butler 1953; Lack 1954; Korpimäki and Krebs

1996). In a recent analysis of time series data for hare and lynx, Stenseth et al.

(1997) suggest that the dominant community linkages are three dimensional

for the hare cycles, and two dimensional for the lynx cycles. The hare appears

to be regulated from below and above (thus both the vegetation-hare and

hare-predator interactions must be considered to understand hare dynamics), whereas the lynx seems to be regulated only from below (thus, for the

lynx, the hare-lynx interaction dominates). This lack of a third dimension

suggests that lynx social structure is not a major factor limiting lynx population growth.

Akçakaya (1992) built a mathematical prey-predator model such that

trophic functions are modeled as functions of prey-to-predator ratios rather

than as functions of prey density only (functions of per capita resources).

This model developed limit cycles consistent with changes in a south to

north gradient and predicted a periodicity of around 10 years. Both of

these patterns are consistent with the true dynamics of the cycle. This

paper demonstrates the need to consider both lynx and hare population

size when considering lynx population dynamics.

The cycle in lynx and hare numbers is often broken into phases. The low

period typically lasts three to five years and is denoted by low population

density and a mild decline and recovery in numbers through the period

(Poole 1994; Slough and Mowat 1996; O’Donoghue et al. 1997). During the

increase phase, about three years in duration, lynx numbers increase quickly

(Poole 1994; Slough and Mowat 1996; O’Donoghue et al. 1997). The peak

phase is usually a two-year period of high lynx density with modest or no

population growth (Poole 1994; Slough and Mowat 1996; O’Donoghue et al.

1997). The decline or crash phase of the hare cycle is one to two years in

duration; lynx numbers decline dramatically during this phase of the cycle.

Quinn and Parker (1987) and Koehler and Aubry (1994) have summarized

lynx densities. More recent work suggests that peak densities in lightly or

unharvested areas in the North may range between 30-45 lynx/100 km2

 in

recent burns (Poole 1994; Slough and Mowat 1996). Peak densities in a

mature forest matrix in the North or in the more southern part of the lynx’s

range are typically lower, at 8-20 lynx/100 km2

 (Parker et al. 1983; Banville

1986; Kesterson 1988; Noiseux and Doucet 1987; Fortin and Huot 1995;

O’Donoghue et al. 1997). Brand et al. (1976) estimated 10 lynx/100 km2

during a hare peak in central Alberta in a mixed forest matrix with

inclusions of agriculture. Population densities during the low are typically

less than 3 lynx/100 km2

, regardless of habitat quality (Brand et al. 1976;

Poole 1994; Staples 1995; Slough and Mowat 1996; O’Donoghue et al. 1997).

In south-central Yukon, Slough and Mowat (1996) calculated a finite rate of
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Chapter 9—Mowat

increase (λ) of 2.03 to the peak, stable numbers during the first year of

declining hare populations (λ = 1.01), and λ = 0.01 during the decline. It

should be noted that all densities presented here are rough figures, and

although they are adequate to demonstrate general temporal and spatial

trends, they combine several different methods, none of which are based on

a sampling methodology or present confidence intervals.

As may be expected, age structure changes with population size in lynx.

Lynx populations are dominated by young animals during the late increase,

peak, and early decline phases of the cycle, leaving an aging adult cohort

through the low phase (Nellis et al. 1972; Brand et al. 1976; Poole 1994; Slough

and Mowat 1996; O’Donoghue et al. 1997). Average age increases through

the low phase due to lack of recruitment, and the oldest age structure is in the

first part of the increase phase, before new recruits are added (Slough and

Mowat 1996). There is less evidence for cyclic variation in sex ratios. Sex

ratios of kittens do not differ from equality (Poole 1994; Slough and Mowat

1996). Sex ratios of adults and yearlings did not differ from unity in any year

in south-central Yukon (Slough and Mowat 1996), but in southwestern NWT

there appeared to be a shift in sex ratio from greater numbers of males at peak

population levels to more females during low levels (Poole 1994). Lembeck

(1986) also documented a shift from predominantly males to more females

in an unharvested bobcat population during a population decrease, and

suggested this resulted from a population control mechanism linked to

females. Smaller individuals may be better able to survive under conditions

of low food abundance, hence the shift to a population composed of more

females during low levels. Trapping also tends to remove males in greater

proportion to their abundance because they have larger home ranges and

may disperse more often.

Most lynx harvests are biased toward males (Berrie 1974; Quinn and

Thompson 1987), but even sex ratios (Brand and Keith 1979) or proportionately more females (Bailey et al. 1986) have been observed. The observation

of more females in the harvest by Bailey et al. (1986) was coupled with a

harvest that exceeded replacement. Age structure of untrapped populations

would presumably be composed of older-aged animals compared to harvested populations (Knick 1990; Poole 1994; Slough and Mowat 1996).

Harvests of lynx in the area surrounding an untrapped study area in southcentral Yukon had 36% fewer kits, 40% more yearlings, and 4% fewer adults

than were present on the study area (Slough and Mowat 1996). Yearlings

were greatly over-represented and kits under-represented in the harvest, as

suggested in other areas (Brand and Keith 1979; Quinn and Thompson 1985).

Lynx dispersal, immigration, survival, and recruitment are closely linked

throughout the snowshoe hare cycle. Population growth in lynx is a result of

a high percentage of breeding females, large litters, high kit survival, low
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Mowat—Chapter 9

mortality, and immigration rates that balance or even exceeded losses to

emigration. The lynx population decline is due to increased dispersal, high

natural mortality, and a collapse in recruitment and immigration. In lynx

studies in southwestern Yukon and southwestern NWT, all collared lynx

resident prior to or during the decline in hare abundance dispersed or died

by the end of the first winter of low hare densities (Poole 1994, 1997;

O’Donoghue et al. 1995, 1997). In south-central Yukon, only two previously

resident lynx remained after the hare decline from a population peak of over

130 animals (including residents, non-residents and all age classes; Slough

and Mowat 1996).

Recruitment

Canada lynx breed through March and April in the North (Quinn and

Parker 1987). Breeding pairs may remain together for several days (Poole

1994; Mowat and Slough 1998) and it is assumed females only breed with one

male, but this assumption has not been tested (McCord and Cardoza 1982).

It is unclear whether female lynx are induced or spontaneous ovulators

(Quinn and Parker 1987). Gestation is approximately 70 days (Crowe 1975;

Quinn and Parker 1987). In south-central Yukon, the mean date of birth for

litters to adult females was 26 May (range 12 May-7 June) and did not differ

among years (Mowat et al. 1996b; Slough and Mowat 1996). In southwestern

NWT, date of birth appeared to be predominantly in the last 10-12 days of

May (K. G. Poole 1992, unpublished). Kittens are born altricial; their eyes

open at 10-14 days of age, though their vision is significantly impaired by

large cataracts for several weeks thereafter (McCord and Cardoza 1982;

G. Mowat, personal observation). Den sites are usually surface scrapes; the

female usually scrapes back the ground cover and places the kittens on dry

ground (Mowat 1993; Slough, in press).

During the period when hares are most abundant, yearling lynx give birth

(Brand and Keith 1979; Quinn and Thompson 1987; Slough and Mowat

1996). In one study, yearling females gave birth approximately two to three

weeks later than adults (Mowat et al. 1996b; Slough and Mowat 1996). Male

lynx are thought to be incapable of breeding in their first year (McCord and

Cardoza 1982; Quinn and Parker 1987).

During the cyclic hare low, lynx pregnancy rates vary from 0 to 100% (see

review in Koehler and Aubry 1994), but sample sizes are often very small

during this period, hence estimates tend to be unreliable. Adult in utero litter

size averages three to four during the low period (Brand and Keith 1979;

O’Connor 1984; Slough and Mowat 1996). Birth rate, the proportion of

females that give birth, has been measured twice during the first year of the

low phase and Poole (1994) and Slough and Mowat (1996) suggested, on the
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Chapter 9—Mowat

basis of few observations, that live births were few or nonexistent. Few

yearling females conceive during the low phase (Brand and Keith 1979;

O’Connor 1984), and Mowat et al. (1996b) argued that few or no yearlings

successfully give birth. All studies report no kittens present during the

second winter following the hare crash (Brand et al. 1976; Poole 1994; Slough

and Mowat 1996; O’Donoghue et al. 1997); the few kittens born generally

have little chance of survival. However, kittens have been reported throughout the cycle in the Klondike Valley in southwestern Yukon (J. Fraser,

personal communication) and in the Mackenzie River Delta in northwestern

NWT (K. Poole, unpublished); these exceptions may point to areas of

optimum hare and lynx habitat. It is unclear how long the period of no or low

recruitment continues; many authors have argued that recruitment fails for

three to five years (Brand and Keith 1979; Parker et al. 1983; Mowat et al.

1996b). In southwestern NWT, no kittens were present among collected

carcasses (n = 69) during the two years following the hare decline (Poole

1994). In south-central Yukon, Slough and Mowat (1996) found no kittens in

a sample of seven carcasses during the first year of low hare numbers;

however, Slough (1996) analyzed pelts (n = 45) collected from a broader area

for the same year and found 13% kittens. Slough (1996) believed that this

overestimate was caused by a decline in lynx body size (and hence pelt

length) during the crash.

Female lynx may begin to give birth before hare densities start to

increase. Brand et al. (1976) saw live litters in summer during two different

years of the cyclic low in hare abundance in central Alberta. Slough and

Mowat (1996) found that three females gave birth to litters during the latter

part of the low phase on their study area. The authors suggested that two

other females may have done so as well. Perhaps the most convincing

evidence of recruitment during the latter part of the low phase comes from

the analysis of trapper samples. Slough and Mowat (1996) found 13 (n = 33)

and 25% (n = 29) kittens in a carcass collection during the last two years of

low hare and lynx densities before the hare increase. Clearly, some young

lynx are recruited to the trappable population during the hare low, especially in the latter years of the low (Slough and Mowat 1996).

As hare numbers increase, yearling females begin to breed and adult litter

sizes increase (Brand and Keith 1979; O’Connor 1984; Slough and Mowat

1996). Pregnancy and birth rates range from 73 to 100% for adults and 33 to

100% for yearlings during this period (Poole 1994; Mowat et al. 1996b; and see

Table 3 in Mowat et al. 1996a:438). Adult litter size averages four to five

during periods of hare abundance (Mowat et al. 1996a:438). Kitten survival

is high (50-83%) during the increase and peak phase of hare cycle

(Brand et al. 1976; Poole 1994; Slough and Mowat 1996). However,
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Mowat—Chapter 9

survival of kittens of yearling mothers was low (<26%) even in high

quality habitat at all times of the hare cycle in south-central Yukon

(Mowat et al. 1996b; Slough and Mowat 1996). These authors suggest

yearlings contribute little to recruitment but the generality of this pattern is

unclear. Lynx have large litters in comparison to other carnivores of their

size (Mowat et al. 1996b) and this, combined with high kitten survival,

generates rapid population growth during the increase and peak phases of

the cycle (Slough and Mowat 1996).

The birth rate of adults and yearlings is reduced the spring following the

hare decline (Poole 1994; Slough and Mowat 1996). Kitten survival also

declines to near zero the year after hare numbers crash (Brand et al. 1976;

Parker et al. 1983; Poole 1994); this decline was delayed one year in southcentral Yukon (Slough and Mowat 1996). Here, most adult females gave

birth to large litters while densities of hares were declining precipitously,

but their birth rate declined to zero one year after the hare crash (Slough

and Mowat 1996). In utero pregnancy rates and litter sizes declined little

during the first year of the lynx crash and continued to overestimate reproduction and recruitment during the decline and low (Mowat et al. 1996a),

making these measurements weak estimators of recruitment and poor

predictors of the lynx decline.

In summary, lynx reproduction is closely tied to hare abundance in

northern populations. Kitten survival declines to zero shortly after the hare

crash, although some lynx continue to breed and possibly give birth for one

more year (Poole 1994; Mowat and Slough 1998). Conception by adults

continues through the low phase but very few live litters are born, especially

during the two years following the lynx decline. In utero litter size declines

through the low, which results in lower litter sizes early in the increase

phase. Lynx may begin to recruit juveniles at least two years before appreciable recovery in hare numbers. We suggest the perception that lynx

recruitment is zero during hare lows is overstated, at least in the far North.

Northern lynx populations do recruit some individuals when hares are

scarce and these individuals may be important in maintaining lynx populations through a hare low phase.

Mortality and Survival

Survival rates of lynx vary tremendously as snowshoe hare abundance

changes through the cycle. Not surprisingly, the level of trapping in and

around the population under study influences survival rates. Annual survival rates of adults during the increase and peak phase of the hare cycle

were >0.70 in a lightly trapped population in southwestern Yukon
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Chapter 9—Mowat

(O’Donoghue et al. 1997), and >0.89 in largely untrapped populations in

southwestern NWT and south-central Yukon (Poole 1994; Slough and

Mowat 1996). Annual survival rates of adult lynx remained high (0.78-0.95)

(Poole 1994; Slough and Mowat 1996) or declined slightly (0.45-0.63)

(O’Donoghue et al. 1997) through the one- or two-year hare decline. The

first year of very low hare numbers was characterized by low adult survival

(0.09-0.40), followed by higher survival in the one to two subsequent years

of low hare densities (0.63-0.82) (Poole 1994; Slough and Mowat 1996,;

O’Donoghue et al. 1997). A similar decline in the annual survival of bobcats

was observed during a decline in jackrabbit density in Idaho (Knick 1990).

Survival tends to be lowest in winter. In southwestern NWT, cumulative

survival summed over four years was higher during summer than during

winter (0.91 vs. 0.08; Poole 1994). Most mortality during low hare abundance

occurred during mid-December to mid-February, and most natural mortality (primarily starvation) appeared to coincide with <-35 °C temperatures,

when metabolic requirements would be greatest (Poole 1994; O’Donoghue

et al. 1995).

Causes of lynx mortality vary greatly across studies. Brand et al. (1976)

noted that starvation of adult lynx seemed unlikely in all but the most

pristine areas, suggesting that nutritionally stressed lynx are first predisposed to mortality related to humans. Ward and Krebs (1985) summarized studies to the mid-1980s of tagged lynx (n = 36) and found 95% of all

lynx deaths were human related (mostly from fur-trapping), and only 5% of

deaths were from natural causes. However, this result is probably biased by

the fact that trappers provided their principal mode of recovery of dead

animals. In interior Alaska, Stephenson (1986) estimated that annual

mortality rates from trapping ranged from 55-100% of radio-marked lynx.

On the Kenai Peninsula in Alaska, Bailey et al. (1986) suggested trapping was

directly or indirectly involved in all nine lynx deaths on their study area

during two years of high hare density, with trapping removing 80% of

individuals over one year of age. On the same study area during a trapping

closure, Staples (1995) observed that no adult male lynx died of natural

causes during periods of low hare densities. Trapping mortality rates

appear to be related to trapping pressure (generally driven by fur prices);

seasonal trapping mortality in central Alberta increased two- to four-fold

with a doubling of pelt prices (Brand and Keith 1979).

Earlier studies showed high trap-related mortality and essentially no

natural mortality in lynx populations. On the basis of modeling population

changes from combined harvest and field data, Brand and Keith (1979)

concluded that trapping mortality of lynx tended to be additive. However,

the authors’ field samples were relatively small, and they could not
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Mowat—Chapter 9

distinguish between undetected mortality and dispersal (Hatler 1988). The

recent Yukon (O’Donoghue et al. 1995, 1997; Slough and Mowat 1996) and

NWT (Poole 1994) studies have documented significant natural mortality

(primarily starvation) of lynx during the first two winters of hare scarcity (or

second or third year of hare decline), which suggests that, at this period in

the cycle, trapping mortality may be primarily compensatory to natural

mortality at least in lightly or untrapped areas. The annual death rate from

trapping (0.08) was higher than from natural causes (0.02) during peak

and declining hare numbers in southwestern NWT (Poole 1994). However,

during low hare numbers the death rate was far higher from natural causes

(0.48) than trapping (0.20). In south-central Yukon, the annual survival rate

on the study area was 0.40 in the first full year of low hare densities, with all

detected mortality from natural causes (Slough and Mowat 1996). However,

20 marked lynx (27% of all emigrants) were trapped after dispersal, and 92%

(n = 25) of known emigrant deaths were human-caused, primarily by

trappers (Slough and Mowat 1996). Comparing survival rates among

studies can be problematic because rates can be affected by how researchers dealt with emigrants. Trapping returns alone will bias mortality rates,

since little natural lynx mortality is detected (e.g., Ward and Krebs 1985).

Causes of natural mortality of lynx are difficult to determine; a radiocollar

and tufts of hair provide little basis for inference. Ideally, mortality factors

should also be identified as proximate or ultimate causes. Starvation (and

related conditions) and cases of cannibalism of lynx have been recorded,

primarily during periods of low prey abundance (Poole 1994; O’Donoghue

et al. 1995; Slough and Mowat 1996). Predation on lynx by wolverine, wolf

and coyote have also been confirmed (Slough and Mowat 1996; O’Donoghue

et al. 1995; 1997; Chapter 4). Lynx host a diverse parasitic fauna, including

nematodes, cestodes, trematodes, lice, and fleas (van Zyll de Jong 1966;

McCord and Cardoza 1982; Smith et al. 1986; Quinn and Parker 1987), but

parasite influence on lynx health and survival is unknown.

In summary, northern lynx populations subject to cyclic hare densities

and differing trapping pressures exhibit large differences in mortality

rates and causes. In lightly trapped or untrapped populations, population

growth is characterized by high kit and adult survival that extends into the

decline in hare numbers, followed by an increase in natural mortality

(starvation, predation, and cannibalism) coupled with high dispersal (see

next section) (Poole 1994; Slough and Mowat 1996; O’Donoghue et al.

1997). This pattern may be disrupted in areas with heavier and consistent

trapping pressure, resulting in natality rates insufficient to maintain

normal cyclic changes in populations through an entire cycle (Bailey et al.

1986).
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Chapter 9—Mowat

Movements and Dispersal

Daily movements of lynx within their range vary greatly and appear to

be affected by environmental conditions, primarily prey densities and

snow characteristics (Nellis and Keith 1968; Ward and Krebs 1985). Daily

travel distances are generally calculated by three methods: (1) snowtracking to determine cumulative distance moved over a 24-hour period

(e.g., Brand et al. 1976; O’Donoghue et al. 1998b); (2) radiotelemetry to

determine either straight-line distances between midday locations in

successive days (e.g., Ward and Krebs 1985; Poole 1994); or (3) between

paired fixes separated by 0.25-2 hours (Parker et al. 1983; Breitenmoser et al.

1991). Based on snow-tracking, average daily cruising distance ranges from

5-9 km (study means from Saunders 1963b; Nellis and Keith 1968; Parker

1981). Daily cruising distances provided by sequential (one to two hours)

telemetry locations from a study on Cape Breton Island, Nova Scotia,

were slightly greater in summer (about 9 km) than in winter (8 km;

Parker et al. 1983). However, daily travel distances of lynx of 12.9-13.5 km

in summer and 20.5 km in winter were measured during one year of the

cyclic decline in the southwest Yukon (Breitenmoser et al. 1991). It may be

assumed that females with young kittens have more restricted movements

(Kesterson 1988; Mowat and Slough 1998).

The causes of changes to or differences in movement patterns of lynx are

unclear. Studies in Alberta found increases in daily movements with increased hare density; Nellis and Keith (1968) speculated that the observed

differences were due to differences in snow characteristics. However, Ward

and Krebs (1985) documented a doubling of daily cruising radius (straightline distance between successive 24-hour locations) from 2.7 to 5.4 km

during moderate to high and low hare densities (<0.5 hares/ha), respectively, which they interpreted as increased foraging effort with decreased

prey abundance. Similar conclusions can be drawn in southwestern NWT;

daily travel distances as determined by radiotelemetry (24-hour locations)

generally were greater (p <0.001) after the decline in hare numbers (Poole

1994). Standardized track counts conducted daily on the same trails provide

additional support; track counts tripled between years of similar lynx

densities but from peak to declining hare densities (K. Poole, unpublished).

However, studies in the southwest Yukon detected no significant changes in

the percent time spent active by lynx during a cyclic decline (O’Donoghue

et al. 1998b), highlighting the inconsistency of results among studies.

Most information on long-distance movements by lynx comes from animals caught by trappers. The number and locations of returns from trappers

are affected by the density and distribution of trapping around study areas,

and by behavioral differences in trap vulnerability among age and sex
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Mowat—Chapter 9

classes of lynx (Bailey et al. 1986; Quinn and Thompson 1987; Slough and

Mowat 1996; Poole 1997). Therefore, all dispersal rates and distances reported must be considered potentially biased.

Long distance (>100 km) movements of lynx were once thought of as

anomalies (Nellis and Wetmore 1969; Mech 1977), but are now considered

characteristic (Ward and Krebs 1985; Brittell et al. 1989; Perham et al. 1993;

O’Donoghue et al. 1995, 1997; Slough and Mowat 1996; Poole 1997).

Documented straight-line dispersal distances range up to 1,100 km, with

15 documented cases of dispersal >500 km (Ward and Krebs 1985; Slough

and Mowat 1996; O’Donoghue et al. 1997; Poole 1997; Fig. 9.3). Relatively

intensive radiotelemetry efforts up to 200 km from the NWT study area

center detected a uniform dispersal direction for female lynx, and a male

dispersal favoring south and west (Poole 1997). Dispersing lynx crossed

roads and large rivers and lakes, sometimes during the snow-free season.

The minimum daily travel rate during dispersal averaged 4.6 km/day

Figure 9.3—Dispersal of lynx >100 km from three areas in the NWT and Yukon.

Data are taken from: ■ = Ward and Krebs (1985) (3) and O’Donoghue et al. (1997)

(8); ● = Slough and Mowat (1996) (17); and ★ = Poole (1997) (19). Hollow symbols

denote study area centers.

★

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★ ★

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■ ■

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500 km

ALASKA

Y.T.

B.C.

AB

N.W.T.
292

Chapter 9—Mowat

(range 1.7-8.3; n = 3; Ward and Krebs 1985), 4.2 km/day (0.3-23.6; n = 8;

Slough and Mowat 1996), and 2.7 km/day (range 1.0-8.4, n = 10, Poole 1997)

in three studies in the Yukon and NWT. These data suggest that dispersing

lynx do not travel any farther per day than resident lynx.

Although emigration and immigration of lynx occurs throughout the hare

cycle (Slough and Mowat 1996; O’Donoghue et al. 1997), a cyclic pattern is

apparent. The rapid increase phase in lynx populations in south-central

Yukon was at least partially due to immigration rates (21-38%) balancing or

exceeding losses to emigration (0-33%; Slough and Mowat 1996). Emigration

rates (52-79%) increased and exceeded immigration (12-50%) during the

two-year decline in hare abundance and the first full year of low hare

densities. In southwestern NWT, annual probability of dispersal for adult

lynx was low (<24%) at peak hare densities and up to the spring after the hare

crash (Poole 1997). Dispersal of adults primarily occurred in the spring after

the rapid decline in hare abundance and during the first two winters of

low hare numbers (78-100%; n = 9-16), and then stabilized during the

third and fourth winters of low hare densities (<20%; n = 10) (Poole 1997).

In southwestern Yukon, all three long-distance dispersals of resident adults

occurred at the end of the snowshoe hare decline, with movements stabilizing during the subsequent winter (Ward and Krebs 1985). During a study of

the same population a decade later, six of 15 collared lynx dispersed during

the first year of a two-year snowshoe hare decline (O’Donoghue et al. 1995).

Similar patterns of dispersal have been observed in bobcats (Hornocker

and Bailey 1986; Knick 1990).

Annual timing of dispersal varies. Timing of dispersal may be related to

the type of dispersal being observed. One type is juveniles dispersing from

natal areas (“innate dispersal”: a spontaneous movement related to the

genetics of the dispersing individual). Another type is adults dispersing in

response to an environmental “catastrophy” (“environmental dispersal”:

a behavioral response to unfavorable conditions; Howard 1960), such as the

hare decline faced by northern lynx populations every 10 years. Juveniles

would tend to disperse primarily in the spring, soon after independence. In

lynx populations, we would expect most environmental dispersal to occur

during the period of greatest nutritional stress, generally mid-winter. The

period of greatest dispersal was March-June in south-central Yukon (Slough

and Mowat 1996), and during mid-winter of the second year of the hare

decline in southwestern Yukon (O’Donoghue et al. 1995). In southwestern

NWT, most dispersal took place during March-June after the winter hare

decline and during mid-winter of the subsequent two winters (Poole 1997).

Known immigrants to the south-central Yukon study area were more

often adult males (Slough and Mowat 1996). During increasing, peak, and

the initial decline in hare abundance, independent kittens 10-12 months of
293

Mowat—Chapter 9

age and yearlings form the bulk of emigrants. Adults are most of dispersers during the latter portion of the decline and initial years of low hare

densities (Slough and Mowat 1996; Poole 1997). Although male lynx have

larger home ranges and hence increased mobility, male-biased dispersal

rates in adult lynx have not been documented (Slough and Mowat 1996;

Poole 1997). In addition, there were no differences in dispersal distances

between sexes, or between kitten/yearling and adult age classes (Poole

1997). We do not feel we can conclude juvenile dispersal is even among the

sexes due to lack of data.

Although emigration was apparently not sex-biased in the south-central

Yukon study, 14 of 17 detected dispersals >100 km were by males (Slough

and Mowat 1996). Most of these samples were from trapping returns, which

are inherently biased toward males (Bailey et al. 1986; Quinn and Thompson

1987). Dispersal rates or distances are generally greater for males than

females of most mammalian species (Greenwood 1980; Wolff 1994).

Annual survival rates did not differ for dispersing vs. non-dispersing

lynx in southwestern NWT for any interval between the peak and the fourth

year of low hare densities (Poole 1997). Survival of dispersing lynx was high

(85-91%) during the peak and initial decline in hare abundance and the

second to fourth years of low hare densities, and poor (29%) during the first

full year of low hare densities (Poole 1997). Natural causes (largely starvation) accounted for over twice as many deaths of dispersing lynx than

human-related causes (13 vs. six). Many lynx apparently died of natural

causes en route, shortly after initiating dispersal, which suggests that the

strategy used by lynx was to maintain residency until a critical starvation

“stress point” was reached and then seek to disperse (O’Donoghue et al.

1995; Poole 1997). Initiation of dispersal often appeared to coincide with

temperatures <-35 °C, a period when metabolic requirements would be

greatest and prey diversity would be minimal, thereby increasing nutritional stress (O’Donoghue et al. 1995; Poole 1997). Given the regional extent

of low snowshoe hare densities (Keith 1990; Poole and Graf 1996) many lynx

never reached areas of higher prey density.

Some dispersing lynx survived the hare population low and re-established

home ranges some distance from their point of dispersal (verified at 65-85

km, potentially up to 1,000 km; Slough and Mowat 1996, O’Donoghue et al.

1997; Poole 1997). These successful re-establishments of home ranges are

difficult to detect using conventional study methods and are likely underreported. Long-distance dispersal of lynx and other predators during cyclic

declines could act as a synchronizing element of the hare cycle (Butler 1953;

Lack 1954; Korpimäki and Krebs 1996; O’Donoghue et al. 1997).

Recent studies have documented the dispersal patterns of adult lynx

during much of the cycle. More research is needed to examine dispersal of
294

Chapter 9—Mowat

juveniles, which likely occurs throughout the cycle, but peaks when both

hare and lynx numbers are increasing or high (Hatler 1988; Slough and

Mowat 1996; Poole 1997). Further understanding of the factors affecting

juvenile dispersal, such as the influence of sex and matrilineal relationships

and prey density, will have implications for harvest management and the

expansion and maintenance of more southern, non-cyclic lynx populations.

Similarly, an understanding of the influence of habitat availability and

connectivity (including forest fragmentation caused by timber harvest) on

both juvenile and adult lynx dispersal will aid in management of southern

populations.

Harvest Management

Trapping mortality may be primarily compensatory to natural mortality

during the first two years of lynx decline when natural mortality rates are

high, but not during other periods of the cycle (Poole 1994; O’Donoghue et

al. 1995, 1997; Slough and Mowat 1996). While the effects of harvest during

the cyclic low could be severe, sustainable harvests can be high during the

later cyclic increase and peak phases because growth rates are large (Poole

1994; Mowat et al. 1996b; Slough and Mowat 1996).

Lynx harvest records show a harvest cycle that varied dramatically in

pattern over the past two centuries (Fig. 9.4). The harvest cycle can be

Figure 9.4—Lynx harvest in Canada from 1825 to 1997. Data prior

to 1919 are from the Hudson’s Bay Company and therefore do not

represent the entire lynx harvest for Canada. After 1919, data were

collected for each province and territory. (Data for 1827-1908;

1919-1983 from Novak et al. 1987. Data for 1910-1918 from Elton

and Nicholson 1942. Data for 1984-1997, unpublished.)

20000

0

40000

60000

80000

Lynx harvested

1825 1875 1925 1975

Hudson's Bay Company Records

Canadian Provincial Data
295

Mowat—Chapter 9

characterized as having uniform high amplitude through to the early 1900s,

declining amplitude from the 1920s to the 1950s, three fairly “normal”

harvest cycles from the late 1950s to the early 1980s, and reduced amplitude

during the 1990s peak. The cyclic pattern through the 20th century was

relatively similar among jurisdictions, although the two northern territories

had a slightly more distinct 1990 cyclic peak (Fig. 9.2).

Citing declining harvest returns and anecdotal information, De Vos and

Matel (1952) noted a decrease in lynx numbers and distribution in Canada

between 1920 and 1950. They cited overtrapping and ecological changes in

habitat, primarily as a result of forest harvesting, as the main factors

responsible for the decrease. We believe overtrapping may be the more

probable explanation because forest harvesting as conducted in the early

part of the century (high-grading) was unlikely to have caused a widespread

decline in lynx numbers and distribution. Similarly, several authors have

suggested local populations were overexploited during the cyclic low of the

1980s (Todd 1985; Bailey et al. 1986; Hatler 1988). There is little doubt that

trapping can reduce lynx populations. Todd (1985) argued that recovery

from low population levels may be prolonged, and that it took more than one

hare cycle for lynx to recover from the suspected over-harvest during the

1920s and 1930s. However, harvest returns are affected by the host of factors

influencing trapper effort and success, including changes in socioeconomic

conditions, season length, quota and trap type restrictions, fur prices,

subsidies, mode of transportation, and ease of access. Fur prices likely affect

harvest effort over the short term (Brand and Keith 1979), but it may not be

valid to compare and contrast inflation-adjusted prices and harvests that

occurred decades apart. Harvest returns, therefore, may be roughly indicative of, but do not directly represent, real population changes.

There remains considerable debate whether lynx were significantly overharvested during the 1980s and early 1990s (Todd 1985; Hatler 1988; Nowell

and Jackson 1996). Interestingly, this period came after three cycles from

1960 to 1980 characterized by relatively high peak harvests, and, possibly

more importantly, relatively high harvest levels during the cyclic lows

(Fig. 9.4). Peak harvests (summing the five-year harvest around each peak)

from 1960 to 1980 were similar to peak harvests during the classic cycles of

the late 1800s, but the five-year harvest during the lows of 1960 to 1980 were

about 25% higher than the lows of the late 1800s. Snowmobiles became

readily available in the late 1950s and early 1960s, likely influencing trapper

coverage, access, and attitudes. Whether or not these increased harvest

levels during the cyclic lows had a significant cumulative impact on subsequent population levels is unknown. Harvest levels during the 1990 peak

were significantly below earlier peaks observed during the 1960s and 1970s,

which, in our opinion, is not unexpected given the 10-fold decrease in pelt
296

Chapter 9—Mowat

prices over the last half of the 1980’s, and hence lower trapper effort. This

decrease in trapper effort was real; for example, NWT trappers told us that

they were not interested in spending money on gas and equipment for a

$60 lynx pelt when they received over $600 per pelt only a few years earlier.

Many turned to wage jobs rather than trapping; the number of trappers in

the NWT dropped from about 3,200 in the mid-1980s to 1,400 in the early

1990s (NWT Department of Renewable Resources, unpublished). Thus the

decrease in harvest was at least partially due to decreased trapper effort in

an area where lynx numbers appeared to be cycling normally (Poole 1994).

In addition, based on community fur returns and local knowledge, no

decrease in range has been detected in the two northern territories or Alaska

through the 1990s (K. Poole, B. Slough, H. Golden, unpublished). Although

we acknowledge that the amplitude of lynx abundance may have been

decreased somewhat through the 1980s and 1990s, based on this coarse

analysis we have no evidence to conclude that there was a long-term impact

to contiguous northern lynx populations due to over-harvest during the low

of the 1980s.

The long-term impact of high harvest pressure during the mid-1980s low

phase in the lynx cycle on more southerly populations or where trapping

intensity was severe may have been more significant (Todd 1985; Bailey et

al. 1986; Hatler 1988). Ease of access in some areas (such as seismic lines

spaced at one kilometer intervals blanketing parts of central and northern

Alberta and British Columbia) coupled with extreme trapping pressure

driven by high pelt prices during low lynx abundance may have reduced or

eliminated lynx from some areas. In response to concerns about overharvest

of lynx during the 1980s low, most Canadian provinces and Alaska implemented season reductions, reduced quotas, or harvest closures in at least

portions of their jurisdictions in the late 1980s. The reduced harvest levels

observed during the lynx cyclic peak of the early 1990s (Figs. 9.2, 9.4) were

likely due to a combination of decreased trapper effort resulting from

reduced pelt prices, and harvest restrictions that remained in place through

much of the early 1990s; overharvest during the 1980 cyclic low may also

have been a contributing factor. Given continuing low lynx pelt prices and

trapper effort, we contend that in time, dispersal by lynx from adjacent

healthy populations will likely repopulate many depopulated areas. However, the amplitude of the recovery to normal cyclic populations may be

reduced for more than one cycle.

Although lynx populations in some areas have been over-harvested, we

suggest that despite limited harvest management over the past half century, normal cycles have persisted throughout much of their northern

range. This observation does not negate the need for more intensive
297

Mowat—Chapter 9

harvest management in areas of high trapping pressure or marginal

habitat, especially during the cyclic low. Harvest management options

include implementation of a tracking harvest strategy (Caughley 1977;

Brand and Keith 1979) where trapping is curtailed or eliminated for three to

four years following the lynx decline; maintenance of permanent untrapped

habitat or refugia (Slough and Mowat 1996); and season or quota restrictions

(Parker et al. 1983; Todd 1985; Bailey et al. 1986; Poole 1994; Slough and

Mowat 1996).

A tracking harvest strategy has management appeal because the only

information required to implement the system is crude knowledge of the

timing of the lynx decline. This information can be inferred from harvest

records. However, measuring pelt length is relatively cheap and yields

information on juvenile recruitment leading to greater certainty in the

timing of cyclic events (Slough 1996). In healthy populations, we recommend managers consider curtailing harvest beginning two years after lynx

populations begin to decline. In areas where distribution is more constrained or harvest more intense, managers may prefer to restrict harvest

starting one year after lynx numbers begin to decline. Harvest should be

restricted for three to four years or until there is evidence of significant

juvenile recruitment and population increase; track counts may be a costeffective monitoring method (Thompson et al. 1989).

A refugia management strategy has less utility where harvest pressure is

fairly continuous throughout the landscape. Large movements and home

ranges by lynx during low hare densities dictate that individual traplines

are often not large enough to support even one lynx, and therefore management activities must be prescribed on a regional basis. Protecting a viable

population in a refuge would require planning at the scale of thousands of

square kilometers because lynx persist at such low densities during the low

phase, and trapping effort on the edge of a refuge could remove lynx that

reside tens of kilometers inside the refuge (Carbyn and Patriquin 1983). We

suggest that attempting to conserve lynx by establishing permanently

untrapped refugia is only advisable where very large reserves currently

exist; even then lynx may be overharvested from substantial areas outside

the reserve if harvest effort is intense. Further, establishing a network of

reserves is politically difficult.

Season restrictions are necessary in all areas for the traditional reasons of

avoiding harvest during breeding activities and timing harvest to the

period when pelts are prime. Further, restricting trapping for lynx until

December or even January may reduce the chance that orphaned juveniles

die after their mother is trapped, providing greater sustainable harvests

and less risk to the population (Bailey 1981; Parker et al. 1983; Mowat 1993).
298

Chapter 9—Mowat

This effort may be particularly important in low-density populations. In

heavily harvested areas or where lynx are at low densities or discontinuous

distributions, quotas may be the only means to adequately limit harvest.

Because of the ease with which lynx are trapped, even very short seasons

such as one month will not necessarily ensure appropriate harvest levels.

Quotas give the managers the greatest control over harvest levels; however,

setting reasonable quotas requires information about population size and

habitat quality. Few managers have this kind of information for an entire

management jurisdiction. For most managers in the northern part of the

range of Canada lynx some sort of tracking harvest strategy will offer

adequate protection to lynx populations at an achievable cost. However, the

most effective management option will depend upon a host of factors

specific to each region, including the spatial distribution of trapping effort,

lynx density and cyclic dynamics, habitat quality and distribution, and

socio-political factors.

Acknowledgments

We thank the many researchers, technicians, government personnel,

and harvesters who have helped advance our knowledge of lynx in the

northern boreal forest over the past decade. The NWT Department of

Renewable Resources, the Yukon Department of Renewable Resources, and

the Natural Sciences and Engineering Research Council of Canada provided

the bulk of funding for much of the recent research from the two northern

territories summarized here. Research from Kluane, Yukon, was conducted

as a part of the Kluane Boreal Forest Ecosystem Project headed by C. J. Krebs.

We thank B. G. Slough for providing his data on lynx den site characteristics. Lastly, we thank L. Ruggiero for inviting us to write this paper.

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307

Chapter 10

Canada Lynx Habitat

and Topographic Use

Patterns in North Central

Washington: A

Reanalysis

Kevin S. McKelvey, USDA Forest Service, Rocky Mountain Research

Station, Forestry Science Lab, 800 E. Beckwith, Missoula, MT 59807

Yvette K. Ortega, USDA Forest Service, Rocky Mountain Research Station,

Forestry Science Lab, 800 E. Beckwith, Missoula, MT 59807

Gary M. Koehler, Washington Department of Fish and Wildlife,

600 Capitol Way N., Olympia, WA 98501

Keith B. Aubry, USDA Forest Service, Pacific Northwest Research Station,

3625 93rd Ave. SW, Olympia, WA 98512

J. David Brittell, Washington Department of Fish and Wildlife,

600 Capitol Way N., Olympia, WA 98501

Abstract—We examined habitat selection by 22 lynx on the Okanogan National

Forest in Washington, analyzing radiotelemetry data collected during two previous studies, 1981 through 1988. At a coarse scale, lynx showed little use of areas

below 1,400 m or above 2,150 m. Within the zone between 1,400 and 2,150 m, lynx

used areas with slopes <10% and moderate stream densities in winter. Selection

for combinations of physical variables and vegetation types was stronger in winter

versus summer, and lynx showed strong selection for lodgepole pine cover
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types in winter. Relative abundance of snowshoe hares measured from pellet

counts on plots within the study area were highest within lodgepole pine and lowest

within Douglas-fir cover types, and winter selectivity may have been influenced by

abundance and distribution of hares. In summer, lynx avoided Douglas-fir cover

types and selected northeast aspects; Douglas-fir tended to occur on southwest

aspects, especially at higher elevations. Road densities in the study area did not have

a significant effect on habitat selection, and lynx crossed roads at frequencies that

did not differ from random expectation.

Introduction

Little is known about habitat use patterns of Canada lynx at the southern

periphery of their range, and relevant telemetry studies are particularly

limited. Koehler et al. (1979) found that two radio-tracked lynx in Montana

used densely stocked stands of lodgepole pine almost exclusively, but

results were based on only 29 telemetry locations. Smith (1984) found that

approximately 80% of locations obtained from four lynx radio-tracked for

two years in Montana were within areas classified in the subalpine fir series

(Pfister et al. 1977). Neither Koehler et al. (1979) nor Smith (1984) compared

use patterns to the distribution of available forest types. Other telemetrybased studies in the contiguous United States include Mech (1980), who

monitored 14 lynx in Minnesota, and Brainerd (1985), who tracked seven

lynx in Montana, but neither reported habitat use. Three telemetry-based

studies of lynx are in progress in the western United States and Southwest

Canada (see Chapters 11, 12).

Most information on habitat relationships of lynx in the contiguous

United States has been derived from two telemetry studies conducted on

the Okanogan National Forest, Washington. Brittell et al. (1989) obtained

540 locations for 17 lynx between 1981 and 1983, and Koehler (1990)

recorded 302 locations for seven lynx between 1984 and 1988 (Table 10.1).

Koehler (1990) reported that home ranges contained a higher proportion of

lodgepole pine and a lower proportion of Douglas-fir cover types than the

overall study area (a zone surrounding the lynx locations and confined to

elevations above 750 m). He also found more pellets of snowshoe hares

within lodgepole pine forests than within other cover types used by lynx and

concluded that lynx selected habitat based on hare densities. Additionally,

Koehler (1990) found that cover types associated with low-elevation grasslands or alpine areas were rare within home ranges and that the average

elevation of telemetry locations in winter was lower than that in summer. In

contrast, Brittell et al. (1989) reported that lynx home ranges did not differ
309

McKelvey—Chapter 10

Table 10.1—Telemetry data for the 22 lynx sampled by Brittell et al. (1989) and Koehler (1990). Two lynx were monitored during both studies.

Avg. days

Lynx Start Stop Duration between Locations by month

ID Sex n (mo/yr) (mo/yr) (days) locations J F M A M J J A S O N D Studya Sampledb

1 M 23 10/81 7/82 274 12 423325200110 B B

3 F 31 10/81 8/82 298 10 524335420111 B B

4 M 19 8/82 3/83 227 12 2 2 4 0 0 0 0 4 0 3 2 2 B W

6 M 64 4/82 9/83 534 8 2 2 4 7 7 10 6 8 9 4 2 3 B B

7 M 47 11/81 3/83 483 10 447245443334 B B

11 M 60 4/82 9/83 534 9 2 2 4 7 5 10 5 8 9 3 2 3 B B

14 F 47 5/82 9/83 506 11 1 2 3 1 4 8 4 6 9 4 2 3 B B

16 M 49 7/82 9/83 431 9 2 2 4 4 4 5 4 9 9 3 0 3 B B

17 F 18 7/82 1/83 177 10 2 0 0 0 0 0 2 2 3 4 2 3 B B

18 F 18 7/82 1/83 169 9 2 0 0 0 0 0 1 4 3 3 2 3 B B

20 F 41 10/82 9/83 338 8 224445346223 B B

21 M 25 4/83 9/83 169 7 0 0 0 2 4 5 3 5 6 0 0 0 B S

24 F 12 7/83 9/83 65 5 0 0 0 0 0 0 1 5 6 0 0 0 B S

31 M 11 7/83 9/83 65 6 0 0 0 0 0 0 1 5 5 0 0 0 B S

33 F 16 5/82 6/82 53 3 0 0 0 0 6 10 0 0 0 0 0 0 B S

55087 M 28 2/87 2/88 345 12 059064201100 K B

59011 M 28 6/85 6/86 384 14 354126051001 K B

104090 M 88 7/82;6/86 9/83;9/87 883 10 7 8 9 4 4 15 8 10 12 3 4 4 B,K B

109062 M 37 2/86 10/87 721 19 187216314121 K B

111167 F 103 8/83;6/85 9/83;10/87 927 9 6 1 4 6 2 3 21 13 12 17 3 5 1 B,K B

112071 F 33 3/86 10/87 595 18 132237603141 K B

195058 M 44 11/84 7/86 606 14 014233789232 K B

Total 842 46 51 72 46 65 130 79 102 115 42 37 38

aB = Brittell et al.; K = Koehler.

bSampled in both (B) seasons, or exclusively in winter (W) or summer (S).
310

Chapter 10—McKelvey

significantly from the study area in terms of slope, aspect, elevation, and

vegetation type.

Considering the scarcity of information on habitat use by lynx and the

conflicting results described above, we reexamined data from Brittell et al.

(1989) and Koehler (1990). Because these two studies occurred in the same

area and used the same methods, they represent a continuum of data

collection amounting to 842 locations for 22 lynx (Table 10.1). By combining

these data, and by taking advantage of current GIS and statistical technologies, we were able to evaluate habitat relationships in greater detail than had

been possible in the past.

Using the combined telemetry locations of Brittell et al. (1989) and Koehler

(1990) as well as spatial data describing vegetation, topography, roads and

streams, we evaluated habitat selection by lynx in the study area considering

multiple spatial scales. Additionally, we considered location data from

road-based track and camera surveys recently conducted by the State of

Washington and the Okanogan National Forest. Because lynx locations

derived from such surveys are sometimes used to infer lynx habitat

relationships, we assessed the concordance between these locations and the

telemetry data. We also used hare data from Koehler (1990) to examine the

relationship between habitat use by lynx and hare densities.

Methods

Study Area

Lynx studies were conducted by Brittell et al. (1989) and Koehler (1990)

in a 1,800-km2

 area of Okanogan County in the northeastern Cascade

Range of Washington (48° 15' to 49° N., 119° 45' to 120° 15' W.) where

elevations range from 750 to 2,540 m. Road densities averaged 800 m/km2

(±STD of 870 m/km2; range 0-3,400 m/km2), and >90% of the length

consisted of narrow, unpaved roads. Annual precipitation averaged 51 cm

at 660 m, and snow depth exceeded 1 m above 1,980 m during November

through March (Koehler 1990). Douglas-fir and ponderosa pine dominated

forests below 1,370 m and southern aspects at higher elevations. High

elevation forests above 1,370 m were dominated by Engelmann spruce,

subalpine fir, and lodgepole pine (Koehler 1990).

Available Data

Telemetry locations were obtained by Brittell et al. (1989) and Koehler

(1990) for 13 adult male and nine adult female lynx from 1982 to 1988

(Table 10.1). Lynx were captured in leg-hold and box-type live traps.
311

McKelvey—Chapter 10

Under ketamine hydrochloride anesthesia, lynx were marked with ear

tags, and fitted with activity-sensitive transmitter collars (Telonics, Mesa,

AZ). Movements of radio-collared animals were monitored from aircraft at

seven to 15 day intervals, depending on weather, and at one to five day

intervals from the ground. Lynx were approached to within 200 m for

ground monitoring and attempts were made to obtain ≥2 locations at ~90°

direction from the animal. Locations were plotted on 1:62,500 U.S. Geological Survey topographic maps to the nearest 50 m. Telemetry error averaged

200 m for data collected 1982 through 1986 (Koehler 1990) but was not

estimated for other years.

For examination of habitat selection by lynx, we obtained three GIS

vegetation layers: one used by Koehler (1990) that was designed to model

areas of equivalent fuel loading (Fuels), another generated for the Okanogan

National Forest by Pacific Meridian Resources, Inc. (PMR), and a third

resulting from the North Cascades Grizzly Bear Ecosystem Evaluation

(NCGBEE) (Almack et al. 1993). The maps were derived from various

LANDSAT images dating from the early to mid-1980s and had similar

resolution (pixel size ~50 m). Because the maps were classified with differing

methods into different vegetation classes (Table 10.2), their depiction of

vegetation in the study area also varied. Labeling of vegetation classes

must be considered primarily nominal: it is unknown to what extent class

label reflects actual vegetation in a given area. For these reasons, we

considered each vegetation coverage separately in examinations of habitat

selection, describing our results in terms of the classes in each coverage. In

the discussion, we look for common patterns among these analyses, making

inferences about the types of vegetation selected by lynx (Table 10.2).

Our analyses of habitat selection by lynx also incorporated physical

variables including road and stream densities, elevation, slope, and aspect.

Coverages of roads and streams developed from 1:24,000-scale data were

converted to density maps by rasterizing the lines and using Arc/INFO’s

FOCALSUM function (ESRI 1997) to index densities. Densities were computed within a fixed neighborhood extending 2.3 km, equivalent to the

average radius of the 50% adaptive kernel home range estimate for lynx with

>50 locations (Table 10.1). Used in this way, FOCALSUM produces a

raster-map in which the value of each raster is the sum of the number of

“road” or “stream” rasters within 2.3 km.

One problem with using this approach to calculate densities is that all

roads or streams within the 2.3 km neighborhood contribute equally

regardless of distance from the “focal” raster. Not only is it likely that roads

or streams close to a location influence habitat use more than distant ones,

but the area within the neighborhood is concentrated at the edge, away

from the focal raster. Unless this is corrected, the road or stream densities
312

Chapter 10—McKelvey Table 10.2—Vegetation classes within the study area as defined by the Fuels (A), PMR (B), and NCGBEE (C) layers (see text for explanation). Also listed are labels for vegetation types used in the text Discussion section to refer to important classes. Species names are: subalpine fir (Abies lasiocarpa), subalpine larch (Larix lyallii), lodgepole pine (Pinus contorta), whitebark pine (Pinus albicaulis), Engelmann spruce (Picea engelmannii), ponderosa pine (Pinus ponderosa), Douglas-fir (Psuedotsuga menziesii),

western larch (Larix occidentalis), PUTR (Purshia tridentata), VACA (Vaccinium caespitosum), VADE (Vaccinium deliciosum), VASC (Vaccinium scoparium).

Mean elevation STD elevation

Original class label Class definitions for meso-scale analyses Vegetation type Area (%) (meters) (meters)

A

Lodgepole pine Lodgepole pine Lodegepole pine 32.6 1,705 209.8

Engelmann spruce Engelmann spruce Spruce-fir 8.9 1,840 151.1

Engelmann spruce/subalpine fir/other Engelmann spruce/subalpine fir/other 9.6 1,780 161.5

Ponderosa pine/Douglas-fir/western larch Ponderosa pine/Douglas-fir/western larch Douglas-fir 13.0 1,388 199.6

Lodgepole pine/other Lodgepole pine/other 7.4 1,780 221.8

Douglas-fir/ponderosa pine Douglas-fir/ponderosa pine 6.9 1,307 205.6

Grass, rock Grass, rock 8.0 1,835 368.7

Hardwood/hardwood conifer Other 1.9 1,294 257.3

Subalpine larch Other 4.7 2,085 100.5

Mountain hemlock/silver fir Other 1.2 1,934 132.7

Whitebark pine Other 1.3 2,125 140.8

Ponderosa pine Other 2.7 1,047 252.7

Shrub, grass/conifer Other 1.8 1,453 332.0

B

Douglas-fir Douglas-fir Douglas-fir 6.1 1,382 307.8

Douglas-fir/mix conifer Douglas-fir/mix conifer 9.5 1,504 243.7

Lodgepole pine Lodgepole pine Lodgepole pine 20.4 1,776 230.1

Mix-various conifer species Mix-various conifer species 10.8 1,503 310.7

Subalpine fir Subalpine fir 17.7 1,782 220.1

Subalpine fir/Engelmann spruce Subalpine fir/Engelmann spruce 5.1 1,668 219.1

Subalpine fir/Douglas-fir Subalpine fir/other 0.7 1,558 231.7

Subalpine fir/lodgepole pine Subalpine fir/other 2.6 1,854 248.8

Subalpine fir/mix conifer Subalpine fir/other 1.8 1,835 177.4

Grass Grass 9.0 1,662 435.6

Douglas-fir/lodgepole pine Other 0.5 1,557 305.3

Engelmann spruce/mix conifer Other 1.0 1,775 227.6

Less than 25% any species Other 6.2 1,508 391.5

Lodgepole pine/mix conifer Other 0.8 1,788 196.9

Pacific silver fir Other 1.2 1,865 195.6

Pacific silver fir/mix conifer Other 0.1 1,949 66.2

Ponderosa pine Other 1.5 1,325 274.6

Shrub Other 3.9 1,684 418.6

(con.)
313

McKelvey—Chapter 10

Subalpine larch/mix conifer Other 0.0 2,115 0.0

Various hardwood species Other 0.1 1,480 96.9

Western larch/mix conifer Other 0.6 1,472 148.1

Whitebark pine/mix conifer Other 0.3 1,853 183.6

Agriculture and developed Absent <0.1 380 0.0

Ponderosa pine/Douglas-fir Absent 0.2 967 192.1

C

Subalpine fir-Engelmann spruce-lodgepole pine—east Subalpine fir-Engelmann spruce-lodgepole pine Lodgepole pine 60.3 1,751 172.9

Douglas-fir-mixed conifer—east Douglas-fir-mixed conifer 14.7 1,396 252.5

Subalpine larch Other forest 2.3 2,128 65.5

Non-riparian deciduous—east Other forest 0.8 1,730 179.9

Whitebark pine Other forest 1.5 2,130 57.3

Engelmann spruce riparian Other forest 1.8 1,540 361.5

Riparian deciduous forest—east Other forest 0.2 1,273 406.6

Subalpine - alpine VASC - VACA meadow Subalpine meadow 2.8 2,028 177.2

Subalpine heather-VADE meadow Subalpine meadow 0.4 2,192 200.8

Subalpine lush meadow—southwest Subalpine meadow 0.5 2,102 138.0

Subalpine meadow -messic to dry—east Subalpine meadow 1.2 1,708 143.9

Subalpine mosaic—east Subalpine meadow 0.9 1,653 98.9

Alpine meadow—east Other open 0.7 2,244 89.0

Bare and rock Other open 0.5 1,964 365.7

Montane herbaceous—east Other open 2.7 1,315 149.9

Montane mosaic—east Other open 1.6 1,263 151.8

Montane shrub—east Other open 0.2 1,708 372.3

Agriculture - fallow and dry pasture Absent 0.1 433 73.3

Lush shrub elev. herbaceous—east Absent 0.1 813 281.0

Ponderosa pine Absent 0.5 756 111.4

Ponderosa pine-Douglas-fir Absent 5.1 1,046 139.0

Shrub steppe - herbaceous Absent 0.7 987 163.5

Shrub steppe - PUTR Absent 0.5 888 175.5

Table 10.2

Wet soil and gravel Absent 0.0 2,152 0.0

 (Con.)

Mean elevation STD elevation

Original class label Class definitions for meso-scale analyses Vegetation type Area (%) (meters) (meters)

B (con.)
314

Chapter 10—McKelvey

computed for a location using FOCALSUM will be dominated by land

conditions 2 km away and will be relatively insensitive to adjacent roads

or streams. We therefore applied a linear distance-weighting function to

the neighborhood: adjacent road or stream rasters contributed 3.0 to the

FOCALSUM, and roads or streams at distances of 1.15 and 2.3 km contributed 1.5 and 0.0, respectively.

The digital elevation model (pixel size ~32 m) that we obtained contained

systematic errors, or bands, which produced ridges and trenches along the

cardinal directions. We removed the bands using Arc/INFO’s

FOCALMEAN function (Brown and Barra 1994) and used the resultant grid

to obtain elevation, slope, and aspect data (ESRI 1997). Because aspect may

be most relevant to the biology of the lynx through its influence on

temperature and moisture gradients, we transformed aspect from a circular statistic into a measure of angular distance from northeast. Redefined

aspect values ranged from 0 on the coldest, wettest slopes (due northeast) to

180 on the warmest, driest slopes (due southwest). We also assigned flat

areas a value of 180 because they receive high radiant energy loads.

Evaluating Habitat Use

Methods developed to evaluate habitat selection for populations compare the distribution of animal locations relative to that of available

habitat types. When a habitat type is used at a proportion significantly

greater than its availability, we state that it is selected, while we infer that

the opposite inequality indicates avoidance of the type (White and Garrott

1990). However, the definition of available habitat is problematic: whether

or not analysis indicates that a particular type is selected depends, in part,

on the degree to which underused types are included in the definition of

available habitat, and results are therefore somewhat arbitrary (Johnson

1980; White and Garrott 1990; Rosenberg and McKelvey 1999).

Established methods for evaluating population-level habitat selection

include two approaches that view the population and available universe

differently (Manly et al. 1993). In one approach, data from all individuals

are pooled, and available habitat is generally defined as the study area

(e.g., Neu et al. 1974). However, given that lynx in our data set were

sampled unevenly, with the number of locations per individual ranging

from 11 to 103 (Table 10.1), simple pooling would give unsatisfactory results

because depiction of habitat selection for the population would be skewed

toward those heavily sampled individuals. Pooling may also suppress

habitat selection patterns of individuals or classes of individuals (White and

Garrott 1990). An alternate approach is to compute resource use functions

for individuals and then combine these into a population-level statistic.
315

McKelvey—Chapter 10

In this case, available habitat is defined by the home range (Manly et al.

1993; White and Garrott 1990). However, these methods are only meaningful when applied to well-sampled individuals. Of the 22 lynx for which

we had data, most had too few points for meaningful calculation of individual use patterns, and only four had >50 locations (Table 10.1).

Given the nature of our sample and the problems associated with established methods, we developed an approach for evaluating habitat selection that combined principles of the approaches described above. Because

habitat use may vary by season, we first split the location data into winter

(October-March) and summer (April-September) periods for which we

conducted separate analyses. We chose these six-month seasons because of

convenience and because they distinguished the period of significant snow

cover (winter) from that of breeding activity (summer). For each season, we

pooled data across individuals, but used sub-sampling to obtain an equivalent number of points per animal so that habitat choices of each could be

equally represented. A subset of points was generated by randomly picking

five points per animal. By picking a relatively small number of points per

individual, we could incorporate lynx with few points and minimize sequential autocorrelation and potential pseudo-replication (Swihardt and

Slade 1985). We generated multiple subsets (n = 20) of points for which we

conducted separate analyses of habitat selection, allowing us to consider the

robustness of derived habitat relationships among potential subsamples.

Rather than limiting the analysis to one definition of availability, we

evaluated habitat selection at multiple spatial scales, clearly defining available habitat at each scale such that statements concerning selection could be

qualified. We began analyses at a coarse scale to consider patterns within the

study area that we defined as the 100% minimum convex polygon for all the

locations buffered by the diameter (4.8 km) of the average 50% adaptive

kernel home range (Fig. 10.1). Because most habitat variables were highly

correlated with elevation, we limited analysis at this scale to evaluation of

selection among broad elevation classes. We used resultant understandings

to delineate a more restricted zone of available habitat that excluded those

elevation classes with little or no use, allowing us to examine meso-scale

habitat selection.

For categorical data describing elevation and vegetation, we compared

use to availability for each subset by computing χ2

 goodness-of-fit statistics

and Bonferroni confidence intervals (Neu et al. 1974). We assessed the overall

significance of results as follows: if χ2

 tests for at least 75% of subsets

showed that use of a class significantly exceeded availability (p <0.05), then

we inferred strong selection for that class; if analysis showed that at least

50% of subsets demonstrated use that was significantly greater than
316

Chapter 10—McKelvey

5 KM

Redefined Available Zone

MCP and buffer 300-m Contours

Winter location Summer location

Figure 10.1—The study area on the Okanogan National Forest in north-central

Washington showing the distribution of 836 lynx telemetry locations collected 1981

through 1988. Also pictured are zones of availability used for coarse and mesoscale analyses of habitat selection.
317

McKelvey—Chapter 10

availability, we inferred marginal selection for the class. Avoidance was

assessed in the same manner.

To incorporate continuous physical variables into analyses of meso-scale

selection, we developed logistic regression models for each subset that

compared lynx locations to random points within the available zone. Vegetation patterns are correlated to physical variables: drier forests are

typically located on lower, south-facing slopes. To assess the degree to

which lynx selection patterns indicated by the physical models reflected

selection for vegetation types, we developed combined models that included vegetation class as a design variable to consider whether vegetation was an important indicator of use when physical features were

accounted for.

Overall significance of regression results was assessed as follows: if a

variable was statistically significant (Wald χ2

 test, p <0.05) in logistic regression models derived for at least 75% of the subsets, then we described

the variable as either strongly selected or strongly avoided, depending on

the sign of its coefficient. Statistical significance of models was evaluated

with the Score test (p <0.05), and models were compared using Akiake’s

Information Criterion (AIC), with lower AIC scores indicating better

models (SAS 1990).

To consider patterns that may have been masked by pooling the data, we

used χ2

 tests of homogeneity to compare use of vegetation classes between

sexes. Similarly, we tested for differences in use of vegetation classes

between the two time periods of study, 1981 through 1983 (Brittell et al. 1989)

and 1984 through 1988 (Koehler 1990), and descriptive statistics were used

to assess similarity of use patterns among the 22 lynx. When we found

significant differences between sexes or time periods, we repeated the χ2

analyses (above) on these subsets.

For evaluation of fine-scale habitat selection, we examined use within

home ranges of lynx with >50 locations. For each of these lynx, the distribution of available types was defined by a 100% minimum convex polygon

that surrounded its locations. We evaluated selection of vegetation classes

using χ2

- goodness-of-fit statistics and Bonferroni confidence intervals.

To examine whether roads may have had direct affects on fine-scale

habitat use, we considered the degree to which lynx crossed roads. Sequential telemetry locations on opposite sides of a road should indicate that the

road was crossed unless the road ended within the home range, thereby

enabling the animal to move between the points without crossing the road.

Most roads in the study area passed through lynx home ranges rather

than ending within them (Fig. 10.2). For each individual with >50 locations, we tested whether line segments defined by sequential telemetry
318

Chapter 10—McKelvey

2 KM

Winter location Summer location Home Range

Potential Movement Road

A

Figure 10.2—Methodology used to evaluate rates at which lynx crossed roads. The frequency of road

intersections for lines between sequential telemetry locations (A) was compared to that for randomly

generated lines (B, page 319).
319

McKelvey—Chapter 10

2 KM

Home Range Potential Movement Road

B
320

Chapter 10—McKelvey

locations intersected roads more or less than expected. To generate the

null expectation for each lynx, we first computed the distances between

successive telemetry locations. Line segments of length chosen randomly

from this set of distances were placed at random locations and azimuths

within the home range so that they fit entirely within its boundary (Fig. 10.2).

Because we generated a large number of random lines per lynx (n = 8,000),

we treated the proportion that intersected roads as a known expectation

(no variance) and used χ2

-goodness-of-fit statistics for comparison to the

proportion of road intersections indicated by telemetry locations.

Okanogan National Forest Road Surveys

For comparison to telemetry-based findings, we considered the types of

habitat where lynx were detected by remote camera and track surveys

conducted on the Okanogan National Forest 1994-1998 (J. Rohrer, unpublished). These detections were obtained at baited stations located at nonrandom points along roads. Still, because lynx are not thought to be drawn

long distances to baits (Robert Naney personal communication; John Weaver

personal communication), we reasoned that lynx may have been detected in

habitat types similar to those used by radio-tracked lynx. We therefore

examined the distribution of detections among elevation and vegetation

classes, but limited our analyses to descriptive statistics.

Hares

Koehler (1990) sampled pellets of snowshoe hares within the study area to

consider the distribution of hares among habitat types used by lynx. Transects

(n = 68) were partitioned among cover types in proportion to their abundance within the study area (Koehler 1990). However, because transects

were placed perpendicular to roads, they did not constitute a representative

sample of the study area. To allow data to be independent among transects,

transects were spaced ≥325 m apart based on the assumption that home

range sizes for hares were <8.8 ha (Wolff 1980; Chapters 6 and 7). Pellets were

counted within 10, 1-m-radius circular plots spaced at 10 m intervals along

each transect, and counts were summed per transect. Pellets were counted

and cleared from plots during September 1986 and counted again on

cleared plots in May and June 1987. Habitat measurements were also

taken on the sample plots (Koehler 1990), allowing us to examine relative

abundance of hares among forest cover types and elevation classes. Because

pellet samples were non-representative, we confined analyses to descriptive statistics.
321

McKelvey—Chapter 10

Results

For the combined data set, most lynx were sampled across several

seasons, and in some cases several years (Table 10.1). Locations were

distributed through time such that the average interval between sampling

was >2 days for all 22 lynx, but more locations were recorded in summer

than winter.

Coarse-Scale Habitat Selection

Six telemetry locations fell beyond our maps of habitat features, leaving

836 telemetry locations (n = 305 and 531 for winter and summer, respectively) for analyses of habitat selection. When buffered, the minimum

convex polygon formed by these points defined an area of available habitat

of 166,620 ha (Fig. 10.1). The majority of telemetry locations fell at elevations

between 1,700 and 2,000 m (Fig. 10.3). Lynx strongly avoided (100% of

subsets) areas <1,100 m, 1,100-1,250 m, and 1,250-1,400 m in both seasons

(Fig. 10.3). Seasonal differences in habitat selection were apparent for

**

-20

-7

* +7 +10

** ** -20 -20 **

-20

*

-10

+4

** +16

*

-13

** ** -20 -20 **

-20 0.00

0.10

0.20

0.30

0.40

<1100 1100-1250 1250-1400 1400-1550 1550-1700 1700-1850 1850-2000 2000-2150 >2150

Elevation (meters)

Proportion

Available

Winter

Summer

Figure 10.3—Coarse-scale use of elevation classes summarized across locations for 22 lynx. Above

each bar is the number of subsets for which use was greater (+) or less (–) than availability (p <0.05).

Classes with marginal (*) or strong (**) selection patterns (see text) are marked accordingly.
322

Chapter 10—McKelvey

higher elevations: use of the 1,400-1,550-m class did not differ from

availability in winter, but lynx showed marginal avoidance of this zone in

summer (65% of subsets; Fig. 10.3). Similarly, avoidance of the >2,150-m

class was strong in the winter (100% of subsets), but marginal in the

summer (50% of subsets; Fig. 10.3).

Meso-Scale Habitat Selection

Based on coarse-scale patterns of habitat use, we redefined available

habitat to exclude elevation classes that were avoided in both seasons

(Fig. 10.3). Removal of zones <1,400 m and >2,150 m reduced the available

area by 25% (Fig. 10.1), eliminated several vegetation classes (Table 10.2),

and left 98.6% of the locations (301 and 523 for winter and summer,

respectively).

Vegetation classes—Selection of vegetation classes within the redefined

area was similar for the three vegetation layers. Using the Fuels map, the

majority of telemetry locations fell within the lodgepole pine class: 53%

in winter and 48% in summer, compared to 39% of the available area

(Fig. 10.4A). Each of seven remaining classes had ≤15% of locations. Lynx

showed strong selection for the lodgepole pine class in winter (85% of

subsets), and strong avoidance of the ponderosa pine/Douglas-fir/western

larch class in summer (85% of subsets; Fig. 10.4A).

Using the PMR classification, the majority of lynx points fell into the

lodgepole pine class: 39% in winter and 33% in summer, compared to an

availability of 24% (Fig. 10.4B). The subalpine fir class contained 25% of

locations, and each of the remaining seven classes had <15%. Lynx showed

marginal selection for the lodgepole pine class in winter (55% of subsets),

avoidance of the Douglas-fir class in both winter (100% of subsets) and

summer (50% of subsets), and strong avoidance of the Douglas-fir/

mixed conifer class in both seasons (≥95% of subsets; Fig. 10.4B).

More than 80% of lynx locations fell into the subalpine fir-Engelmann

spruce-lodgepole pine class of the NCGBEE map, with <10% in each of the

four remaining classes (Douglas-fir-mixed conifer, other forest, subalpine

meadow, other open). Lynx showed marginal selection for the subalpine

fir-Engelmann spruce-lodgepole pine class in summer (65% of subsets).

However, the NCGBEE map was coarse at this scale, with 78% of the

available area falling into this class, and we did not include this map in

subsequent analyses.

Physical variables—Correlation among pairs of physical variables (road

and stream densities, elevation, aspect, and slope) was low (Pearson r <0.5).

Logistic regression models that included all five variables were significant
323

McKelvey—Chapter 10

Figures 10.4—Meso-scale use of vegetation classes summarized across locations for 22 lynx using the

Fuels (A) and PMR (B) vegetation layers (see Table 10.2 and text for explanation). Above each bar is the

number of subsets for which use was greater (+) or less (-) than availability (p <0.05). Classes with

marginal (*) or strong (**) selection patterns (see text) are marked accordingly.

*

-11

-8

-1

-7

**

+17

** -5 -17

-3

+2

0.00

0.10

0.20

0.30

0.40

0.50

Lodgepole pine Lodgepole pine/

other

Engelmann

spruce

Engelmann

spruce/white bark/

pine/other

Ponderosa pine/

Douglas-fir/

western larch

Douglas-fir/

ponderosa pine

Grass, rock Other

Proportion

Available

Winter

Summer

A

-4

-2 -3

-1

*

+11

**-19

**

-20 -9

+2

-1

+1

**-18 *

-10

0.00

0.10

0.20

0.30

0.40

Douglas-fir Douglas-fir/

mix conifer

Lodgepole pine Mix/

various conifer

Subalpine fir Subalpine fir/

Engelmann spruce

Subalpine fir/

other

Grass Other

Proportion

Available

Winter

Summer

B
324

Chapter 10—McKelvey

for all subsets (χ2 >11.5, df = 5, p <0.05), with better models in winter

(AIC = 766-792) compared to summer (AIC = 848-876). In winter, selection

patterns were strong for slope and stream density: probability of lynx use

increased significantly with decreasing slope (χ2

 >4.2, df = 1, p <0.04 for

80% of subsets; Fig. 10.5A) and increasing stream density (χ2

 >4.2, df = 1,

p <0.04 for 80% of subsets; Fig. 10.5B). In summer, selection patterns were

strong for elevation and aspect: probability of lynx use increased significantly with increasing elevation (χ2

 >4.4, df = 1, p <0.04 for 70% of subsets;

Fig. 10.5C) and decreasing aspect (χ2

 >5.1, df = 1, p <0.025 for 85% of subsets;

Fig. 10.5D). However, for stream density and elevation, selection did not

follow a linear pattern: use deviated most from availability at intermediate

values of these variables (Fig. 10.5B, C). Use also deviated from availability

at low to intermediate road densities (Fig. 10.5E), although selection

patterns were weak (winter: χ2

 <3.4, df = 1, p >0.06 for 100% of subsets;

summer: χ2

 <3.8, df = 1, p >0.05 for 55% of subsets).

Combined models of vegetation and physical variables—Vegetation

class was a significant predictor of probability of lynx use, even when

physical variables were accounted for within logistic regression models.

Using the Fuels map, models that included vegetation class were better

(χ2

 >21.8, df = 12, p <0.05) than models with only physical variables for

80% of winter subsets (AIC = 764-790) and 60% of summer subsets

(AIC = 837-877). The lodgepole pine class was strongly selected in the

winter (χ2

 >4.3, df = 1, p <0.04 for 80% of subsets) and marginally selected in

the summer (χ2

 >5.3, df = 1, p<0.03 for 50% of subsets). The addition of

vegetation to the model did not significantly change relationships between

habitat use and the physical variables described above: in winter, flatter

slopes were strongly selected (χ2

 >4.7, df = 1, p <0.04 for 80% of subsets), as

were areas with higher stream densities (χ2

 >5.0, df = 1, p <0.03 for 90%

of subsets). In summer, northern aspects were strongly selected (χ2

 >4.1,

df = 1, p <0.05 for 85% of subsets), but elevation was significant for only 40%

of subsets (χ2

 >4.0, df = 1, p <0.05).

Logistic regression models that included vegetation classes from the

PMR layer (χ2

 >23.0, df = 13, p <0.04) were better (χ2 >23.0, df = 13, p <0.04)

than models with only physical variables for 100% of winter subsets

(AIC = 741-786) and 10% of summer subsets (AIC = 850-873). Selection for

the lodgepole pine class was strong in the winter (χ2

 >4.0, df = 1, p <0.05 for

100% of subsets) and marginal in the summer (χ2

 >4.0, df = 1, p <0.05 for

60% of subsets). As with the Fuels map, relationships between habitat use

and physical variables generally did not change with the addition of

vegetation class to the model: in winter, flatter slopes were marginally

selected (χ2

 >4.5, df = 1, p <0.04 for 50% of subsets), and selection was
325

McKelvey—Chapter 10

-0.04

-0.02

0.00

0.02

0.04

0.06

0.08

Deviation from availability

0-10 10-20 20-30 30+

Slope (degrees)

A

Winter

Summer

-0.10

-0.05

0.00

0.05

0.10

0.15

0.20

Deviation from availability

1000 2000 3000 4000 5000 6000

Stream Density (index)

B

Winter

Summer

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

Deviation from availability

1400-1550 1550-1700 1700-1850 1850-2000 2000-2150

Elevation (m)

Winter

Summer

C

-0.06

-0.04

-0.02

0.00

0.02

0.04

0.06

Deviation from availability

0-30 30-60 60-90 90-120 120-150 150-180

Aspect (degrees from NE)

D

Winter

Summer

Figures 10.5—Meso-scale use as a function of

physical variables, expressed as deviation from the

proportion available. Slope (A) and stream density

(B) were significant in winter, while elevation (C) and

aspect (D) were significant in summer. Road density

(E) was associated with use in winter models that

included PMR vegetation classes as design variables.

-0.20

-0.10

0.00

0.10

0.20

0.30

Deviation from availability

0 2000 4000 6000 8000 10000+

Road Density (index)

E

Winter

Summer
326

Chapter 10—McKelvey

strong (χ2 >5.0, df = 1, p <0.03 for 80% of subsets) for areas with higher

stream densities. Road density also showed a strong association (χ2 >4.1, df

= 1, p <0.05 for 80% of subsets) with lynx use in winter. In summer, northern

aspects were strongly selected (χ2

 >5.5, df = 1, p <0.02 for 80% of subsets),

but elevation was significant for only 30% of subsets (χ2

 >3.9, df = 1, p

<0.05).

To examine the degree to which selection for physical variables by lynx

was associated with specific vegetation classes, we built logistic regression

models that used physical variables to predict the occurrence of vegetation

classes that were strongly selected or avoided. Because selection patterns

were similar for the two vegetation layers, we limited these analyses to the

Fuels map. Occurrence of the lodgepole pine type decreased along slope and

aspect gradients, and increased with stream density (χ2

 >4.1, df = 1, p <0.05)

for each parameter; model χ2

 = 35.0, df = 5, p = 0.0001, AIC = 3485). Therefore,

this class tended to occur in flatter areas with northeast aspects and higher

stream densities. Occurrence of the ponderosa pine/Douglas-fir/western

larch class increased with aspect and decreased with elevation and road

density (χ2

 >6.4, df = 1, p <0.02 for each parameter; model χ2 = 475.0, df = 5,

p = 0.0001, AIC = 1262). Therefore, this class tended to occur within lower

elevation areas with southwest aspects and lower road densities.

Additional factors—To examine whether patterns in habitat use for the

combined population were consistent within various subgroups, we compared the distribution of locations among vegetation classes defined by the

Fuels map for the two time periods of study, 1981 through 1983 and 1984

through 1988. Annual and summer use patterns between time periods

were significantly different (χ2

 = 14.6, df = 7, p = 0.04 andχ2 = 18.5, df = 7,

p = 0.01, respectively), but winter patterns did not differ (χ2

 = 9.6, df = 7,

p = 0.21; Fig. 10.6).

Because use of vegetation classes differed significantly between time

periods, we split the locations by time period and repeated tests for mesoscale selection for each period separately. Tests for winter selection showed

stronger patterns in 1984 through 1988 compared to 1981 through 1983.

Lynx selected the lodgepole pine class marginally (65% of subsets) in 1984

through 1988 but did not show selection (10% of the subsets) in 1981

through 1983. Similarly, avoidance of Douglas-fir classes in winter was

stronger in 1984 through 1988 versus 1981 through 1983 (ponderosa pine/

Douglas-fir/western larch: 25% versus 0%; Douglas-fir/ponderosa pine:

100% versus 45%). Results for summer were comparable between time

periods with selection for lodgepole pine shown for 5% (1981 through 1983)

and 0% (1984 through 1988) of subsets, and avoidance of ponderosa pine/

Douglas-fir/western larch shown for 60% and 50% of subsets.
327

McKelvey—Chapter 10

Distribution of locations among vegetation classes also differed by sex

(χ2

 = 19.8, df = 7, p = 0.006), and this difference applied to winter (χ2 = 19.7,

df = 7, p = 0.006) but not summer (χ2

 = 8.2, df = 7, p = 0.31; Fig.10.7). To assess

whether these differences in use between sexes indicated differences in

habitat selection, we split the subsets by sex and repeated tests for mesoscale selection. Selection by season for each sex followed results obtained

for the combined population (Fig. 10.4A). Both sexes showed selection for

the lodgepole pine class and avoidance of the ponderosa pine/Douglas-fir/

western larch class: in winter, selection for lodgepole pine was shown for

50% of subsets for females compared to 10% for males; avoidance of

ponderosa pine/Douglas-fir/western larch was shown for 10% of subsets

for females versus 0% for males and avoidance of Douglas-fir/ponderosa

pine for 45% versus 100%. In summer, selection for lodgepole pine was

shown for 5% of subsets for females compared to 10% for males; avoidance

of ponderosa pine/Douglas-fir/western larch was shown for 85% of

subsets for females versus 40% for males.

Proportions of locations in each vegetation class defined by the Fuels map

were similar across the 22 lynx (Fig. 10.8). Use of lodgepole pine by the

group was relatively high (49 ± STD of 13.0%), and 19 lynx had a higher

proportion of locations in this class than the proportion available. Use of

0.00

0.10

0.20

0.30

0.40

0.50

0.60

Lodgepole pine Lodgepole pine/

other

Engelmann

spruce

Engelmann

spruce/subalpine

fir/other

Ponderosa pine/

Douglas-fir/

western larch

Douglas-fir/

ponderosa pine

Grass, rock Other

Proportion

1981-1983 (winter)

1984-1988 (winter)

1981-1983 (summer)

1984-1988 (summer)

Figure 10.6—Use of vegetation classes of the Fuels layer for each time period of study and season.
328

Chapter 10—McKelvey

0.00

0.10

0.20

0.30

0.40

0.50

0.60

Lodgepole pine Lodgepole pine/

other

Engelmann

spruce

Engelmann

spruce/subalpine

fir/other

Ponderosa pine/

Douglas-fir/

westernlarch

Douglas-fir/

ponderosa pine

Grass, rock Other

Proportion

Females (winter)

Males (winter)

Females (summer)

Males (summer)

Figure 10.7—Use of vegetation classes of the Fuels layer for each sex and season.

Figure 10.8—The average (± STD) proportion of locations in each vegetation class defined by the Fuels

layer for 22 lynx. Availability of each class is shown for comparison.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

Lodgepole pine Lodgepole pine/

other

Engelmann

spruce

Engelmann

spruce/whitebark

pine/other

Ponderosa pine/

Douglas-fir/

western larch

Douglas-fir/

ponderosapine

Grass, rock Other

Proportion

Observed

Available
329

McKelvey—Chapter 10

ponderosa pine/Douglas-fir/western larch was relatively low (6 ± STD

of 3.9%), and 18 lynx had a lower proportion of locations in this class than the

proportion available.

Fine-Scale Selection Patterns

Four lynx had >50 locations distributed across seasons and covering

>500 days (Table 10.1). Only one of these lynx showed use of vegetation

classes that differed significantly from availability within its home range:

lynx 104090 selected the lodgepole pine class (Fuels map) in winter (χ2

 = 6.0,

df = 1, p <0.02) and avoided the subalpine fir class (PMR map) in

summer (χ2

 = 4.5, df = 1, p <0.04). However, relatively few classes (2-6 and

2-7 classes for the Fuels and PMR maps, respectively) could be tested for

selection because of their low representation within home ranges of individual lynx. For each of the four lynx, frequency of road crossings did not

differ from random expectation (χ2

 = 0.4, 0.7, 1.6, and 3.2; df = 1; p = 0.08, 0.21,

0.39, and 0.55).

Okanogan National Forest Road Surveys

Lynx detections from road surveys were in different habitat types than

predicted by telemetry data. The majority (48%) of detections occurred at

lower elevations (1,400 to 1,700 m). Although 28% of detections were

within the lodgepole pine class, 34% fell into the ponderosa pine/Douglasfir/western larch and Douglas-fir/ponderosa pine classes of the Fuels

layer. Similarly, 43% of detections occurred in Douglas-fir classes of the

PMR layer with 10% in the lodgepole pine class. To further examine these

patterns, we compared the vegetation classes occurring along survey roads

to those of the surrounding landscape. Roads tended to pass through

Douglas-fir classes while the landscape was dominated by lodgepole pine

classes. For example, in the southwest portion of the Okanogan National

Forest (Fig. 10.9), the lodgepole pine class of the Fuels layer covered 41%

of the area and the ponderosa pine/Douglas-fir/western larch and

Douglas-fir/ponderosa pine classes covered 21%. In contrast, only 20% of

the road’s length passed through the lodgepole class and 21% passed

through Douglas-fir classes. Similarly, 21% of lynx detections in this area

fell within lodgepole pine and 36% within the Douglas-fir classes. However, those detections that fell within non-lodgepole pine classes were

generally adjacent and proximal to patches of the lodgepole pine class

(Fig. 10.9).
330

Chapter 10—McKelvey

Figure 10.9—Locations within the southwestern portion of the Okanogan National Forest where

lynx were detected during road surveys. Lynx locations are not distributed uniformly along the road, but

conform more to the habitat characteristics of the road than of the surrounding landscape.

1 KM

Lynx detection Lodgepole pine Road 30-m Contours
331

McKelvey—Chapter 10

Hares

Hare abundance broadly followed patterns of selection by lynx. Forest

types and elevation zones with the highest densities of hares corresponded

to those classes strongly selected by lynx (Fig. 10.10A,B). However, only

Figure 10.10—Standardized abundance of hare pellets

(bars) and use by lynx (lines) as a function of cover type

(A) and elevation (B). Pellet counts from the first (unswept)

sample were averaged across the number of transects

shown above each bar. Use of cover types by lynx,

expressed as deviation from the proportion available,

was defined by the distribution of locations across

corresponding vegetation classes of the Fuels layer.

-0.10

-0.05

0.00

0.05

0.10

Deviation from availability

Lodgepole Spruce/subalpine fir Douglas-fir

Cover type

Summer

Winter

16

11

32 A

Hare pellet index

-0.15

-0.10

-0.05

0.00

0.05

0.10

0.15

Deviation from availability

1400-1550 1550-1700 1700-1850 1850-2000 2000-2150

Elevation (m)

4

9

16

34

1

B

Hare pellet index

Summer

Winter
332

Chapter 10—McKelvey

four hare samples were taken between 1,250 and 1,550 m, and they were all

within Douglas-fir cover types that had lower hare densities across elevation zones. In addition, only 36% of the available area between 1,400 and

1,550 m consisted of Douglas-fir classes (Fuels map), whereas lodgepole

pine classes composed 26% of the area. Douglas-fir was similarly overrepresented in pellet samples taken in the 1,550 to 1,800-m zone.

Discussion

Our multi-scale analyses of habitat selection provide strong support for

Koehler’s (1990) original findings that lynx use lodgepole pine more than

expected and Douglas-fir less than expected. Even when our models were

limited to the elevation zone used by lynx, and we accounted for the

physical attributes of the landscape, selection for lodgepole pine was still

statistically significant. Vegetation classes defined by lodgepole pine were

important in meso-scale comparisons of use to availability using all three

vegetation layers (Table 10.2), and the inclusion of lodgepole classes as

design variables significantly improved models of habitat use derived

from physical variables. Lynx avoided areas defined by Douglas-fir

(Table 10.2), although Douglas-fir classes were not important in models of

habitat use that included other habitat variables. Physical features associated with occurrence of lodgepole pine and Douglas-fir were the same

features associated with habitat selection by lynx, suggesting that these

physical features were primarily indicators of selection for vegetation types.

Selection of northeast aspects in the summer, however, may have been

independent of selection for vegetation. In winter, the proportional use of

northeast aspects was greater than availability (Fig. 10.5D), but aspect was

not significant when considered along with the other habitat variables.

However, in summer, models combining physical and vegetation variables

indicated that northeast aspects were strongly selected. Douglas-fir was

associated with southwest aspects in a logistic regression model, and avoidance of Douglas-fir in summer was the most strong and consistent pattern

among analyses of selection for the combined population, and for sex and

time periods separately, with at least 45% of subsets demonstrating avoidance in each case. Therefore, avoidance of Douglas-fir in summer may have

been associated with the tendency of lynx to select areas with northeast

aspects. Preliminary summer telemetry data for lynx in the Seeley Lake area

in Montana also suggest selection of north-facing aspects where 80% of

locations fell (John Squires personal communication). Lynx habitat in the

Seeley Lake area differs significantly from that on the Okanogan National

Forest, and it is unlikely that topographic correlates to vegetation would be
333

McKelvey—Chapter 10

the same for the two areas. Thermoregulation provides a plausible explanation for the apparent selection of aspects with wetter, cooler conditions in the summer.

Use of lower elevations in the winter described by Koehler (1990) was

also apparent for the broader population of 22 lynx. We detected a seasonal

elevation shift: decreased use of the 2,000 to 2,150-m zone and increased use

of areas 1,400 to 1,550 m in winter. Selection for vegetation types also varied

with season. Lynx showed stronger selection for lodgepole pine in winter

compared to summer for the combined population, and for both sexes and

time periods. These shifts also translated into an increased proportion of

locations on flatter slopes with higher road densities (Figs. 10.5A, E). Use of

Douglas-fir also increased in winter, although only according to the Fuels

map. This pattern may have related to increased adjacency of lodgepole

and Douglas-fir classes at lower elevations where the latter type becomes

more prevalent and less associated with southwest aspects. Overall, comparisons of logistic regression models indicated that selection for combinations of physical and vegetation variables was stronger in winter than in

summer.

Patterns in habitat use by lynx also corresponded to relative abundance of

snowshoe hares as measured by pellet counts. The elevation zones and cover

type with the highest hare indices were those selected by lynx. This association was evident despite the high variability in the hare data (Table 3 in

Koehler 1990) and that cover types representing hare habitat were based on

ground-based assessments (Koehler 1990) whereas lynx habitat was represented by broad vegetation classes defined from LANDSAT imagery. Because the hare data were derived from non-representative samples, caution

must be exercised when interpreting the apparent relationship between

elevation and hare density. However, given the strong use patterns that

Koehler (1979) observed in Montana, we suspect that the observed correlation between lynx and hare patterns indicates a strong causal relationship.

A review of studies of lynx at northern latitudes (Chapter 10.9) shows similar

patterns of lynx selecting habitats where hares are more plentiful. From

snow tracking studies of lynx among white spruce forests in the Yukon,

Murray et al. (1994) found that lynx selected densely stocked stands of white

spruce where hares were most abundant during one year, but used spruce

stands according to availability the next year, when hare numbers were

similar among habitats.

Given the variability of hare densities in time and space and the apparent

sensitivity of lynx to these fluctuations, the overall difference in habitat use

observed between the periods of study is not surprising. Lynx showed

relatively high use of lodgepole pine and low use of Douglas-fir in both 1981
334

Chapter 10—McKelvey

through 1983 and 1984 through 1988. However, use was more skewed

toward lodgepole pine and away from Douglas-fir in winter 1984 through

1988 versus winter 1981 through 1983 (Fig. 10.6). Similarly, comparisons of

use to availability indicated that selection for lodgepole pine was much

stronger for winter 1984 through 1988 versus winter 1981 through 1983, as

was avoidance of Douglas-fir classes. Selection patterns for summer were

similar between time periods.

Koehler (1990) characterized hare densities measured during his study as

low, and these data also indicated that hares were concentrated within

areas of lodgepole pine. Lower hare densities may lead to a more patchy

distribution of hares and subsequent stronger habitat selection by lynx

(Murray et al. 1994), particularly in winter when lynx have fewer opportunities to use alternate prey (Chapter 13).

Our analyses also indicated a neutral relationship between habitat selection and roads. A significant positive association between road density and

habitat use was observed for winter locations, but only when the vegetation

classes of the PMR layer were combined in models with physical variables.

We suspect that this statistical relationship reflects a correlation between the

classification of vegetation and the prevalence of roads. Therefore, road

density, as computed within home-range-sized areas, did not appear to have

significant effects on habitat selection for the combined population. Our

analysis of habitat use at a finer scale indicated that frequency of road

crossing for each of four lynx did not differ from expected. We acknowledge

that our results are based on a small number of lynx within a limited

geographic area, but can state that we found no evidence that habitat use

by lynx was affected by narrow, forest roads at the relatively low densities

that characterized the study area. However, we caution that our analyses

did not address potential indirect effects of roads on habitat quality for

lynx (Chapter 4).

Road-based surveys did not provide a representative sample of the surrounding landscape, and patterns of use appear to have been influenced

by composition of adjacent habitat types (i.e., prevalence of lodgepole).

We therefore believe simple examination of the distribution of the resulting detections—including comparisons to the surrounding landscape, to

areas along survey roads, or to surveyed locations where lynx were not

detected—should not be used to make inferences about habitat use.

Overall, our results suggest that habitat selection by lynx may be driven by

differing mechanisms in summer compared to winter. In summer, lynx

showed more general use of cover types but consistently avoided warm, dry

slopes: behavior that may have been associated with thermoregulation.

Although habitat selection was stronger in winter for all sets of analyses, use
335

McKelvey—Chapter 10

of vegetation in this season was not constant across time periods. Habitat

selection in winter may be more influenced by hares and therefore more

sensitive to variability in hare distribution and abundance. To develop

understandings of mechanisms that underlie habitat requirements for

lynx in the contiguous United States, further examination of habitat

selection that includes consideration of fluctuations in availability of

snowshoe hares is needed.

Literature Cited

Almack, J. A., W. L. Gaines, R. H. Naney, P. H. Morrison, J. R. Eby, G. F. Wooten, M. C.

Snyder, S. H. Fitkin, and E. R. Garcia. 1993. North Cascades grizzly bear ecosystem

evaluation. Report to Interagency Grizzly Bear Committee. Denver, CO.

Brainerd, S. M. 1985. Reproductive ecology of bobcats and lynx in western Montana.

Missoula, MT: University of Montana M.S. Thesis.

Brittell, J. D., R. J. Poelker, S. J. Sweeney, and G. M. Koehler. 1989. Native cats of Washington.

Unpublished. Olympia, WA, Washington Department of Wildlife.

Brown, D. G. and T. J. Barra. 1994. Recognition and reduction of systematic error in elevation

and derivative surfaces from 7 1/2-minute DEMs. Photogrammetric Engineering and

Remote Sensing 60:189-194.

Environmental Systems Research Institute, Inc. (ESRI) 1997. ARC/INFO version 7.1.2.

Redlands, CA.

Johnson, D. H. 1980. The comparison of usage and availability measurements of evaluating

resource preferences. Ecology 61:65-71.

Koehler, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hares in

north central Washington. Canadian Journal of Zoology 68:845-851.

Koehler, G. M., M. G. Hornocker, and H. S. Hash. 1979. Lynx movements and habitat use in

Montana. Canadian Field-Naturalist 93(4):441-442.

Manly, B. F. J., L. L. McDonald, and D. L. Thomas. 1993. Resource selection by animals.

Chapman and Hall, New York.

Mech. L. 1980. Age, sex reproduction, and spatial organization of lynxes colonizing

northeastern Minnesota. Journal of Mammalogy 61: 261-267.

Murray, D. L., S. Boutin, and M. O’Donoghue. 1994. Winter habitat selection by lynx

and coyotes in relation to snowshoe hare abundance. Canadian Journal of Zoology

72:1444-1451.

Neu, C. W., C. R. Byers, and J. M. Peek. 1974. A technique for analysis of utilizationavailability data. Journal of Wildlife Management 38:541-545.

Pfister, R. D., B. L. Kovalchik, S. F. Arno, and R. C. Presby. 1977. Forest habitat types of

Montana. Intermountain Forest and Range Experiment Station, USDA Forest Service,

General Technical Report INT-34.
336

Chapter 10—McKelvey

Rosenberg, D. K. and K. S. McKelvey. 1999. Estimation of habitat selection for central place

organisms. Journal of Wildlife Management 63:1028-1038.

SAS Institute. 1990. SAS/STAT user’s guide. Version 6. 4th edition. SAS Institute Inc.,

Cary, NC.

Smith, D. S. 1984. Habitat use, home range, and movements of bobcats in western Montana.

Missoula, MT: University of Montana. M.S. Thesis.

Swihardt, R. K. and N. A. Slade. 1985. Testing for independence of observations in animal

movement. Ecology 66:4 1176-1184.

White, G. C. and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic

Press, New York.

Wolff, J. O. 1980. The role of habitat patchiness in the population dynamics of snowshoe

hares. Ecological Monographs 50: 111-130.
337

Chapter 11

Lynx Home Range and

Movements in Montana

and Wyoming: Preliminary

Results

John R. Squires, University of Montana, Forestry Science Laboratory,

800 E. Beckwith, Missoula, MT 59807

Tom Laurion, Wyoming Game and Fish Dept.,

260 Buena Vista, Lander, WY 82520

Abstract—Preliminary telemetry data suggest that lynx in Montana and

Wyoming have large home ranges; this result supports the Koehler and Aubry

(1994) contention that lynx from southern lynx populations have large spatial-use

areas. Annual home ranges of males were larger than females. Straight-line,

daily travel distance averaged 2 to 4 km, which is similar to northern populations. Four males in Montana, and the male and female in Wyoming, made

exploratory movements of 20 to 30 km. The extent of these movements may be

underestimated because we could not locate all lynx that traveled extensively.

We do not know if these movements were exploratory or if the home ranges of

these animals include widely dispersed use-areas. The female in Wyoming

denned in a mature subalpine fir forest with high horizontal cover from coarse

woody debris.
338

Chapter 11—Squires

Introduction

Our knowledge of lynx ecology for southern populations is limited to

only seven studies (Koehler et al. 1979; Mech 1980; Smith 1984; Brainerd

1985; Brittell et al. 1989; Koehler 1990; Chapter 12), two of which focused

primarily on bobcats (Smith 1984; Brainerd 1985). Thus, land managers are

in the difficult position of having to manage lynx habitat based on little

data. In this chapter, we present preliminary data from ongoing studies in

western Montana and northwestern Wyoming. Research objectives for

the Montana study are to determine habitat use of lynx at multiple spatial

scales, to describe dispersal and movements, to investigate population vital

rates to the extent possible given a limited sample size, and to document

seasonal food habits.

In Wyoming, the initial research goal was to determine the distribution

of lynx in the state. Surveys confirmed earlier reports that lynx were present

in the Wyoming Range located in western Wyoming; trappers, in 1971-1972,

harvested 18 lynx in a small portion of the Wyoming Range (B. Neely and

J. Welch, personal communication). In 1996, the Wyoming Game and Fish

Department intensified its research efforts to address the following objectives: to quantify hare population trends from 1997 to 2001, to describe lynx

movements in the Wyoming Range, and to obtain genetic and demographic

data to the extent possible, given the small populations. Understanding the

ecology of lynx in Wyoming is critical to conservation planning because

these animals represent the southernmost known population.

In this chapter, we describe the spatial-use patterns of lynx based on

preliminary data. We acknowledge that home range sizes, by themselves,

are difficult to interpret and have limited utility (White and Garrott 1990).

However, these data facilitate conservation planning in at least two ways.

First, monitoring southern populations of lynx requires a basic understanding of spatial-use patterns. For example, the number and placement of

monitoring stations within landscapes depend on the spatial-use patterns

of lynx. Second, given the lack of existing data, any additional information

that describes the movements of lynx from southern populations may help

identify ecological differences between northern and southern populations.

Understanding the ecology of southern lynx populations is especially important, given the species’ proposed listing under the Endangered Species Act

(Federal Register vol. 63:36994-37013).

Study Areas

The study area in Montana is located in the Clearwater River drainage,

near the town of Seeley Lake. This area is about 1,800 km2

, extending east
339

Squires—Chapter 11

to west from the Swan Range to the Mission Mountains, and north to south

from Lindbergh Lake to Salmon Lake. Lynx harvests (1977-1994) and track

surveys suggest this area may support the highest density of lynx in

Montana (Brian Giddings, personal communication). The study area includes state, federal, and private lands that support intensive commercial

forestry. An extensive road network associated with timber harvest, and a

high snow pack, attract private and commercial snowmobile operators.

The Bob Marshall and Mission Mountain Wilderness areas flank the east

and west sides of the study area, respectively. Elevations on the Seeley Lake

study area are about 1,200 to 2,100 m.

The warm and dry forests at lower elevations are dominated by Douglasfir, western larch, lodgepole pine, and ponderosa pine on south to west

aspects—usually as mixed forests—although Douglas-fir may form pure

stands (U.S. Forest Service 1997). Low-elevation forests are open or parklike, but dense stands occur where fire has been absent. Frequent, lowintensity fire is the primary natural disturbance (average = 42 years,

Fischer and Bradley 1987). Fires eliminate small-diameter trees, producing

a park-like structure. Based on 1930 photos, forest patches with moderately open overstories were several hundred to thousands of hectares in

size (U.S. Forest Service 1997). Timber harvest and fire suppression have

shifted the open mature forests that were once most prevalent on lowelevation sites to forests of small-diameter, densely stocked stands. Lowelevation sites are usually less than 35% slope.

Mid-elevations support primarily cool and moist to dry conifer forests.

Dominant tree species include seral Douglas-fir, western larch, and lodgepole pine in mixed to single-species forest stands. Low frequency, standreplacing fires create even-aged stands that form a mosaic of early seral to

old-growth forests (Fischer and Bradley 1987). Slopes at mid-elevations are

often greater than 35%.

Upper elevation forests are mostly subalpine fir, whitebark pine, and

Engelmann spruce with lesser components of lodgepole pine, Douglas-fir,

and western larch. Subalpine forests are multi-storied and multi-aged, often

with a dense shrub understory. Fire disturbances are infrequent and vary

from small spot to large stand-replacement fires depending on climatic

conditions. Riparian vegetation varies from riparian grasses and sedges to

communities composed of dogwood, willow, alder, and mixed conifer

forests. Forested riparian areas are primarily subalpine fir, Engelmann

spruce, Douglas-fir and black cottonwood.

In Wyoming, the study area is located in the Wyoming Range, near Big

Piney. Topography is steep to rolling and elevations are about 2,400 to

3,100 m. Forest cover on drier sites is primarily homogeneous stands of

lodgepole pine. Spruce-fir forests are generally restricted to north
340

Chapter 11—Squires

aspects and compose 19% of vegetative cover. About 9% of forests are

aspen, which are declining from encroachment by conifers. Vegetation on

south slopes is mainly sagebrush and wheatgrasses with patches of aspen

and conifer; the area is about 20% non-forest and 8% riparian. During the

late 19th century, forests in the Wyoming Range were harvested for railroad

ties. Road densities are high; the density of roads open to public travel is

about 0.3 km/km2

.

Methods

In Montana, lynx were captured using VictorTM #3 soft-catch traps and

Fremont snares placed near tracks. Sets were baited with carrion or one of

several scent compounds (beaver castor, Pacific CallTM, Cat PassionTM). Most

“cubby” sets were constructed from small branches so that trapped lynx

could knock them down without injury (G. Mowat, personal communication). Some traps were placed in large, permanent “cubbies” that were large

enough to prevent trapped animals from entangling the trap on the sides of

the set. We checked traps daily and stopped trapping in mid-April to avoid

capturing pregnant females. In Wyoming, lynx were captured using Walker

hounds that pursued and treed lynx after being released on tracks.

In Montana, immobilization drugs (10 mg/kg body wt. Ketaset®

, concentration 100mg/mL; and Xylazine, 1mg/kg body wt., concentration

100mg/mL) were administered from pressurized syringe-darts using either

a TelinjectTM CO2-powered blow tube or syringe pole. This dose produced

predictable immobilization periods (20-30 minutes) and stable vital signs.

Animals were weighed, sexed, ear tagged, and fitted with LotekTM radio

collars (175 g). After processing, we placed lynx inside a large, hard-sided

box to recover fully from drug effects before release. Treed lynx, in

Wyoming, were immobilized (5 mg/kg Telazol®, Fort Dodge Labs,

Poole et al. 1993) using a pressurized syringe-dart fired from an air rifle

(Dan-InjectTM, Denmark). Drugged lynx were then either caught as they fell

from the tree with a large net held by two or three people (T. Bailey, personal

communication), or lowered with a rope. Lynx were fitted with transmitters

(TelonicsTM, Mesa, AZ), were weighed, were measured, and had blood and

hair samples taken.

We monitored the movements of radio-collared lynx in Montana using

both aerial and ground telemetry. Aerial locations were taken weekly using

a Cessna 185 with wing-mounted “H” antennas. Aerial locations were

determined using a non-differentially correctable GPS on board the aircraft.

In addition, two two-person teams located up to four lynx per day to

augment aerial locations. A “priority” lynx was selected for each monitoring day to reduce variation across animals. Transmitters were equipped
341

Squires—Chapter 11

with activity switches so that observers could monitor the animal’s behavior

to minimize disturbance. Ground tracking was coordinated using handheld radios to ensure bearings crossed at about 90°. Antenna locations were

determined using a differentially correctable GPS (Trimble Corporation®).

Relocations were taken from 5:00 to 22:00 to ensure that locations were taken

throughout the day; lynx were not tracked at night. We used aerial telemetry

to track two males that moved to the Bob Marshall Wilderness Area; these

animals received less monitoring effort compared to lynx that remained on

the study area. During May, females were located almost daily to check for

denning activity. In Wyoming, radio-collared lynx were located one or two

times weekly, mostly from the ground with limited use of aircraft.

On the Seeley Lake study area, hare abundance during summer (May to

August) was estimated on two trap grids established in four general cover

types. These types included: (1) open young, <50% canopy closure, tree dbh

<23 cm; (2) open older, <50% canopy closure, dbh >23 cm; (3) closed young,

>50% canopy closure, dbh <23 cm; and (4) closed older, >50% canopy

closure, dbh >23 cm. Each grid consisted of 50 traps (24 x 24 x 66 cm,

TomahawkTM) in a 10 x 5 array with 50-m spacing. Traps were baited with

apple and alfalfa pellets. Hare density was estimated using mark-recapture

methods (Pollock 1982; Pollock et al. 1990). In Wyoming, hare abundance

was estimated from fecal counts on five 600-m transects located within

lynx home ranges (Krebs et al. 1987). As a comparison to the Wyoming

Range, hare abundance was also estimated near Dubois, WY (four, 750-m

transects) and in the Beartooth Mountains (four, 700-m transects) in areas

believed suitable for lynx. Quadrats (5.08 x 305 cm, n = 300 total) were spaced

at 30-m intervals. All quadrats were cleared of hare feces when transects

were established and then were counted and cleared once per year in June.

For both study areas, we used the computer program Ranges V (Kenward

and Hodder 1996) to estimate home range using 95%, 90% and 50% minimum convex polygons (MCP, Hayne 1949). We used MCP home ranges

because this method was most appropriate given the limited number of

lynx relocations and for comparability with the literature. However, home

range estimates using minimum convex polygons are sensitive to sample

size (White and Garrott 1990:148). Incremental-area plots suggest the

area of most (five of six lynx >30 relocations) home ranges was asymptotic when estimated with greater than 30 locations; Poole (1994) found

>20 points were adequate for lynx in Northwest Territories, Canada.

Core-use areas within home-ranges were defined as the 50% MCP (Ackerman

et al. 1989). Home range overlap was calculated according to Poole (1995).

We calculated straight-line travel distances for animals located on consecutive days as an index to hunting effort for comparison with other

populations (Brand et al. 1976; Ward and Krebs 1985; Poole 1994).
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Chapter 11—Squires

Results

Trapping Success

In Montana, we captured 13 lynx (four females, nine males) from

January through April 1998; trap success averaged 0.5 lynx/100 trap

nights. Two additional lynx escaped from traps. From 15 December 1998 to

15 March 1999, we captured five additional lynx (two males, one female, one

male kitten) and recaptured three from the previous winter. Trap success

was 0.6 lynx/100 trap nights for all captures and 0.4 captures/100 trap

nights, for new captures. The only non-target forest carnivore we captured

was a female wolverine; a second wolverine escaped from the trap.

In Wyoming, one male and one female lynx were captured on 7 December

1996 and 15 March 1997, respectively. The female was recaptured on

19 November 1997 to replace the collar and the male was recaptured on

20 December 1997 but was injured in the process. This animal received

veterinary care until 4 February 1998, when it was released.

Daily Movements

In Montana, the mean daily straight-line distance traveled by male lynx

averaged 2.8 km (SD = 0.4, range = 2.5-3.3 km, n = 4, Table 11.1) during

summer (mid-May to August 1998). The mean of two females without

young during the same period averaged 3.2 km per day (SD = 1.0, range = 2.5-

3.9 km, Table 11.1). In Wyoming, the mean daily-travel distance of the

male averaged 4.1 km during summer (range = 1.3-7.2 km, n = nine consecutive travel days, Table 11.2) compared to 2.7 km during winter

(SD = 1.9, range = 0.7-9.5 km, n = 22). The daily travel distance of the

Wyoming female was similar during both summer (mean = 2.4 km, SD = 1.9,

range = 0.3-5.2 km, n = 8) and winter (mean = 2.2 km, SD = 1.4, range = 0.2-

3.8 km, n = 7).

Table 11.1—Straight-line daily travel distances of lynx during the summer (MayAugust, 1998); n = number of days consecutive locations were obtained.

Lynx ID Average distance SD Range

km km

Male 4 (n = 9) 3.3 1.2 1.5-5.7

Male 6 (n = 13) 2.5 2.0 0.8-7.0

Male 26 (n = 13) 2.7 1.5 0.2-5.5

Male 28 (n = 8) 2.6 1.4 0.9-4.4

Average male (n = 4 males) 2.8 0.4 2.5-3.3

Female 10 (n = 11) 3.9 2.2 1.2-7.7

Female 14 (n = 25) 2.5 1.7 0.1-6.5

Average female (n = 2 females) 3.2 1.0 2.5, 3.9
343

Squires—Chapter 11

Home Ranges

In Montana, annual home ranges (90% convex polygon) averaged 220 km2

(SE = 95, n = 4) for males and 90 km2 (SE = 32, n = 2) for females (Table 11.3).

Seasonal ranges of males were 127 km2 (SE = 54, n = 4) during winter and

125 km2

 (SE = 42, n = 6) during summer (Table 11.3). Seasonal ranges of

females were approximately half the size of males; home ranges of females

averaged 51 km2

 (SE = 22, n = 4) during winter and 42 km2 (SE = 9, n = 2)

during summer.

In Wyoming, the male’s 90% MCP home range from December 1996 to

May 1999 was 116 km2

 (n = 279 relocations) compared to 105 km2 (n = 149)

for the female from March 1997 to May 1999 (Table 11.4). During winter, the

male’s 90% MCP home range averaged 63 km2

 (n = three winters) compared

to 50 km2

 for the female (n = two winters). During summer, the male’s

90% MCP home range averaged 81 km2

 (n = two summers) compared to

57 km2

 for the female (n = 2 summers).

In Montana, seasonal home ranges (90% MCP) of females overlapped 62%

(SE = 26, n = 2) between winter and summer and males overlapped 56%

(SE = 6, n = 4, Table 11.5). Core-use areas of females as delineated by 50%

MCP overlapped extensively (68%, SE = 1, n = 2) between winter and

summer, but males shifted their core-use areas between seasons with little

overlap (17%, SE = 5, n = 4). In Wyoming, the female’s annual home range

(1997-1998) overlapped the male’s by about 88%; the degree of overlap

varied from 85% in winter to 43% in summer.

Exploratory Movements

In Montana, four males engaged in exploratory movements outside

their established home ranges, mostly during mid-summer. Male 4 (four

to six years old based on tooth wear and staining) left its home range on

Table 11.2—Straight-line daily travel distances of a single male and female

lynx in western Wyoming during summer (May-August) and

winter (December-April); n = number of days consecutive

locations were obtained.

Lynx ID Average distance SD Range

km km

Male

(summer, n = 9) 4.1 1.9 1.3-7.2

Male

(winter, n = 22) 2.7 1.9 0.7-9.5

Female

(summer, n = 8) 2.4 1.9 0.3-5.2

Female

(winter, n = 7) 2.2 1.4 0.2-3.8
344

Chapter 11—Squires

Table 11.3—Seasonal home range size of lynx, Seeley Lake, March 1998 to March

1999.

Number of Minimum convex polygon (km2)

 Lynx ID relocations 95% 90% 50%

Winter, female

F01 15 15 15 2

F10 27 56 52 19

F14 27 129 114 16

F18 23 26 23 8

Average (SE) 57 (26) 51 (22) 11 (4)

Winter, malea

M02 28 190 137 80

M04 27 84 67 24

M06 29 283 275 36

M26 23 33 30 12

Average (SE) 148 (56) 127 (54) 38 (15)

Summer, female

F10 40 53 50 17

F14 54 52 33 12

Average (SE) 53 (1) 42 (9) 15 (3)

Summer, male

M02 23 318 189 53

M04 38 66 64 33

M06 40 178 173 117

M20 18 534 274 41

M26 41 20 19 11

M28 36 38 32 10

Average (SE) 192 (82) 125 (42) 44 (16)

Annual, femaleb

F10 67 65 58 24

F14 81 164 121 16

Average (SE) 115 (50) 90 (32) 20 (4)

Annual, malec

M02 51 483 448 114

M04 65 132 102 33

M06 69 303 299 157

M26 64 32 29 11

Average (SE) 238 (99) 220 (95) 79 (34)

a

M20 excluded, <10 relocations.

b

F09 excluded, <10 relocations.

c

M03, M05, M07, M08, M12, M16, and M22 excluded, <10 relocations.

Table 11.4—Seasonal home ranges of a single male and female lynx in western

Wyoming.

Number of Minimum convex polygon (km2)

Lynx ID relocations 95% 90% 50%

Winter

Male (10/1996-3/1997) 39 71 64 17

Male (10/1997-3/1998) 20 66 64 19

Male (10/1998-3/1999) 26 134 60 11

Female (10/1997-3/1998) 23 66 38 6

Female (10/1998-3/1999) 30 66 62 29

Summer

Male (4/1996-9/1996) 40 88 68 17

Male (4/1997-9/1997) 15 94 94 21

Female (4/1997-9/1997) 41 69 68 11

Female (4/1998-9/1998) 22 67 45 16

Annual

Male (12/1996-5/1999) 279 137 116 54

Female (3/1997-5/1999) 149 114 105 59
345

Squires—Chapter 11

21 July and traveled 28 km southwest. After about four days, it returned to

its home range on 28 July. Male 6 (two to four years old) left its home range

on 29 July and traveled south for 24 km and remained on the new area for

the summer. The daily travel speed of this male while traveling averaged

5.8 km/day (n = three travel days). Male 20 (one to two years old) moved

extensively throughout the spring and summer. On 18 March, this male

traveled west 22 km and was back near the center of its activity area by

2 April. On 21 July, Male 20 was located in the Bob Marshall Wilderness.

By 28 July, this male had traveled a straight-line distance of 39 km to a site

near Ovando, MT. He had to cross a two-lane highway and the Blackfoot

River (about 30-40 m wide) during the movement. Male 20 remained near

Ovando for two days before it moved again and could no longer be located

from an aircraft. On 12 August, we relocated Male 20 47 km north of Ovando

and by 20 August the animal moved 17 km back to the center of its home

range. Male 28 (three to five years old) left its home range on about 6 July and

was not relocated, even with extensive aerial searching. He returned to his

home range on 3 August where he remained throughout the summer.

In Wyoming, both the male and female made exploratory movements

during summer 1998. The male left his home range on about 19 June and

remained away until 4 September when he was relocated back on his home

range. The female left her home range on about 4 July and returned on about

10 August. Neither animal was located during an extensive aerial search,

so their exploratory movements remain unknown. Between 15 May and

15 June 1999, the male made two exploratory movements to the same

general area about 30 km northeast of his home range; he returned to his

home range in late June.

Table 11.5—Percent overlap between winter (October 1998 to

March 1999) and summer (April 1998 to September

1998) home ranges.

Minimum convex polygon:

95% 90% 50%

Female overlap

F10 84 88 67

F14 35 36 68

Average (SE) 60 (25) 62 (26) 68(1)

Male overlap

M02 40 48 6

M04 39 42 14

M06 71 70 15

M26 69 63 31

Average (SE) 55 (9) 56 (6) 17 (5)
346

Chapter 11—Squires

Hare Density

In Montana, preliminary estimates of summer snowshoe hare density

averaged 0.9 hares/ha in closed old forests, 1.9/ha in closed young forests,

0.6/ha in open old forests, and 0.7/ha in open-young forests (S. Mills and

C. Henderson, personal communication). Hare densities in the Wyoming

Range were 0.8 hares/ha in 1997 and 1.4/ha in 1998. This compared to 0.9

(1997) and 1.0/ha (1998) near Dubois, WY, and 0.6/ha in the Beartooth

Mountains (1998).

Mortality

In Montana, we documented six deaths (necropsies conducted by Montana Department of Fish, Wildlife, and Parks); three animals died of starvation, two were killed by mountain lions, and one died of unknown causes.

Denning

In Montana, two females failed to centralize their activities with home

ranges during May 1998, suggesting they did not give birth. We were unable

to relocate a third female from when she was captured during the winter

until 22 September when we located her near the original trap site. This

female had two kittens but we do not know whether the radio failed

temporarily or she moved off the study area to den. During May 1999, three

of four females centralized their movements within home ranges. Two

females produced two kittens each that we ear-tagged at four weeks of age.

The third female selected a den, but she failed to give birth or her kittens

died before we visited the site when the kittens would have been one month

old. The female that produced kittens the year before failed to den in 1999.

In Wyoming, the female produced a litter of four kittens (two males, two

females) on about 27 May 1998; all kittens were alive on 14 June 1998 when

they were ear-tagged. However, based on snow tracking, the kittens were

not with the female in November and presumably had died. In May 1999 the

same female produced two additional kittens.

The natal den in Wyoming was located in a mature subalpine fir forest

with co-dominant lodgepole pine. The den site was on a moderately steep

slope (36%) with a west aspect (282°). The den was located in a cave-like tree

well 1.5 m wide, 2.5 m long and 0.5 m deep. Three downed logs crisscrossed

above the opening to 1.5 m in height. Trees surrounding the den (n = 4)

averaged 32 cm dbh and 22 m in height. Canopy closure was 48%. Coarse

woody debris (downed logs) was abundant around the den, covering 28%

of the forest floor. Sapling subalpine firs (<7.5 cm dbh) were abundant

(sapling <1.4 m in height = 2,800 stems/ha; saplings >1.4 m = 800/ha). The
347

Squires—Chapter 11

abundant woody debris and high sapling density provided high horizontal

cover, averaging (four cover-board readings at 10 m) 78% between 0-1.5 m.

Shrubs were sparse on the site.

Immediately after the kittens were marked in mid-June, the female

moved her litter to a maternal den located approximately 200 m from the

natal den. This den was located in a depression (0.5 m x 0.5 m wide, 0.3 m

deep) beside a fallen tree. Trees surrounding the den (n = 3) averaged 50 cm

dbh and 30 m in height. Canopy closure was 54%. Coarse woody debris

(logs) also was high, covering 13% of the forest floor. Sapling (<7.5 cm dbh)

density was high, averaging 5,800 stems/ha (sapling <1.4 m in height =

5,000/ha; saplings >1.4 m = 780/ha). Horizontal cover was also high at this

den averaging 86% cover between 0-1.5 m.

We have not rigorously quantified the habitat characteristics of dens

(n = 4) located in 1999. However, we can say that all dens were associated

with coarse woody debris.

Discussion

Our findings generally support Koehler and Aubry’s (1994:93) contention

that lynx living at the southern extent of the species’ range have large

home ranges. In Montana, annual 95% MCP home ranges of males averaged

238 km2

 (SE = 99, n = 4) and 115 km2 (SE = 50, n = 2) for females; the sizes of

these home ranges are similar to those of males (277 km2

, SD = 71, n = 3)

and females (135 km2

, SD = 124, n = 3) in the southern Canadian Rocky

Mountains (Chapter 12). Similarly, the annual home ranges of the male

(110 km2

) and female (90 km2) lynx in Wyoming were also large compared

to northern populations (Chapter 13). The home range sizes we report are

probably underestimates given that we could not locate some animals

during a portion of the summer. As with most populations (Brainerd 1985;

Koehler 1990; Poole 1994; Slough and Mowat 1996), males in Montana and

Wyoming tend to have much larger home ranges than females.

Parker et al. (1983) found that daily activity and travel patterns of lynx

are primarily a function of hunting succes. Given that lynx in Montana and

Wyoming have relatively large home ranges, daily movement patterns of

lynx in Montana and Wyoming should be large relative to northern populations, especially since hare densities are low. However, daily-travel distances of lynx in Montana and Wyoming (about 2-4 km/day) were generally

similar to those in Alaska (Kesterson 1988) and southwest Yukon (about 2-

4 km) when hare density was above 0.5 hares/ha (Ward and Krebs 1985),

but appear greater than lynx in Washington (about 1 km, Brittell et al. 1989).

Although travel distances (i.e., foraging effort) are partially a function of

prey density, daily movements tend to be insensitive to changing prey
348

Chapter 11—Squires

abundance as long as hare densities remain above 1.0 hares/ha (Ward and

Krebs 1985). For example, in southwest Yukon, daily-travel distances of

lynx were similar whether hares were abundant (at 15 hares/ha, daily travel

of lynx = 2.7 km, 95% CI 1.8-3.7) or relatively scarce (at 1.0 hares/ha, daily

travel of lynx = 2.4 km, 95% CI 2.0-2.9; Ward and Krebs 1985). However,

when hare densities declined to 0.5 hares/ha daily, travel distance increased

to 3.3 km (95% CI 2.8-3.7); at 0.2 hares/ha lynx traveled 5.4 km (95% CI 3.9-

7.0) per day. Thus, if southern and northern populations are comparable,

daily movements of lynx in Wyoming and Montana suggest that prey are

above the threshold where movements greatly expand.

Lynx in Montana and Wyoming engaged in exploratory movements of

20 to 30 km; exploratory distances are probably underestimated given our

inability to locate all lynx that traveled extensively. We do not know if these

movements were truly exploratory or if the home ranges of these individuals

include use-areas that are very widely dispersed. It is interesting that all four

lynx in Montana that engaged in exploratory movements did so at about the

same time; all animals moved in late July. In Wyoming, the male initiated its

exploratory movement on about 19 June and the female on 4 July. Lynx in

northern populations become nomadic when prey are scarce (Ward and

Krebs 1985; Slough and Mowat 1996). This explanation seems unlikely during

the summer in Montana and Wyoming, given the seasonal abundance of

young hares and ground squirrels.

The natal den in Wyoming was located in a mature subalpine fir forest

with high horizontal cover from coarse woody debris and saplings. In

Washington, Koehler (1990) described the habitat associated with four dens

(of two females) as mature (≥250 years) forests of Engelmann spruce,

subalpine fir, and lodgepole pine. These dens were in sites with high

woody debris (40 downfall logs/50 m) that the kittens were using as escape

cover. The structural components—mature forests and high woody debris—associated with the natal den in Wyoming were similar to those

associated with dens in Washington.

Literature Cited

Ackerman, B. B., F. A. Leban, E. O. Garton, and M. D. Samuel. 1989. User’s manual for

program HOME RANGE. 2nd ed. Tech. Rep. No. 15. Forestry, Wildlife, and Range

Experiment Station, University of Idaho, Moscow.

Brainerd, S. M. 1985. Reproductive ecology of bobcats and lynx in western Montana.

University of Montana, Missoula.

Brand, C. J., L. B. Keith, and C. A. Fischer. 1976. Lynx responses to changing snowshoe

hare densities in central Alberta. Journal of Wildlife Management 40:416-28.
349

Squires—Chapter 11

Brittell, J. D., R. J. Poelker, S. J. Sweeney, and G. M. Koehler. 1989. Native cats of

Washington. Olympia, WA: Washington Department of Wildlife (unpublished).

Fischer, W. C. and A. F. Bradley. 1987. Fire ecology of western Montana forest habitat types.

Gen. Tech. Rep. INT-223. Ogden, UT: U.S. Department of Agriculture, Forest Service,

Intermountain Research Station.

Hayne, D. W. 1949. Calculation of size of home range. Journal of Mammalogy 30:1-18.

Kenward, R. E. and K. H. Hodder. 1996. Ranges V: an analysis system for biological location

data. Institute of Terrestrial Ecology, Furzebrook Research Station, Wareham, Dorset UK.

Kesterson, M. B. 1988. Lynx home range and spatial organization in relation to population

density and prey abundance. University of Alaska, Fairbanks.

Koehler, G. M., K. B. Aubry. 1994. Lynx. Pages 74-98 In L. F. Ruggiero, K. B. Aubry, S. W.

Buskirk, J. L. Lyon, W. J. Zielinski, tech. eds. The scientific basis for conserving forest

carnivores: American marten, fisher, lynx and wolverine in the Western United States.

Gen. Tech. Rep. RM-254. Fort Collins, CO: U.S. Department of Agriculture, Forest Service,

Rocky Mountain Forest and Range Experiment Station.

Koehler, G. M., M. G. Hornocker, and H. S. Hash. 1979. Lynx movements and habitat use in

Montana. Canadian Field-Naturalist 93:441-2.

Koehler, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hares in

north central Washington. Canadian Journal of Zoology 68:845-51.

Krebs, C. J., G. S. Gilbert, S. Boutin, and R. Boonstra. 1987. Estimation of snowshoe hare

population density from turd transects. Canadian Journal of Zoology 65:565-7.

Mech, L. D. 1980. Age, sex, reproduction, and spatial organization of lynxes colonizing

northeastern Minnesota. Journal of Mammalogy 61:261-7.

Pollock, K. H. 1982. A capture-recapture design robust to unequal probability of capture.

Journal of Wildlife Management 46:752-757.

Pollock, K. H., J. D. Nichols, C. Brownie, and J. E. Hines. 1990. Statistical inference for

capture-recapture experiments. Wildlife Monographs 100:1-97.

Parker, G. R., J. W. Maxwell, and L. D. Morton. 1983. The ecology of the lynx (Lynx canadensis)

in Cape Breton Island. Canadian Journal of Zoology 61:770-86.

Poole, K. G. 1994. Characteristics of an unharvested lynx populations during a snowshoe

hare decline. Journal of Wildlife Management 58:608-18.

Poole K. G. 1995. Spatial organization of a lynx population. Canadian Journal of Zoology

73(4):632-41.

Slough, B. G. and G. Mowat. 1996. Lynx population dynamics in an untrapped refugium.

Journal of Wildlife Management 60:946-61.

Smith, D. S. 1984. Habitat use, home range, and movements of bobcats in western

Montana. University of Montana, Missoula.

Ward, R. M .P and C. J. Krebs. 1985. Behavioural responses of lynx to declining snowshoe

hare abundance. Canadian Journal of Zoology 63:2817-24.

White, G. C. and R. A. Garrott. 1990. Analysis of wildlife radio-tracking data. Academic

Press, Inc., New York.

U.S. Forest Service. 1997. Rice Ridge ecosystem management area and watershed analysis

vegetation report. U.S. Forest Service, Lolo National Forest, Seeley Lake, MT (unpublished).
350

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351

Chapter 12

Space-Use, Diet,

Demographics, and

Topographic Associations

of Lynx in the Southern

Canadian Rocky

Mountains: A Study

Clayton D. Apps, Aspen Wildlife Research

2331 – 7th Ave. N.W., Calgary, Alberta, T2N 1A1, Canada

Abstract—Snowshoe hares are considered the primary prey of Canada lynx

throughout their range. Relative to northern populations, hares occurring in mountainous regions at southern latitudes are thought to remain at low and stable

densities through time. Hence, the ecology of associated southern lynx populations

is expected to resemble that of northern populations during the low phase of the hare

population cycle. The space use, diet, and demographics of lynx in the Rocky

Mountains of southeastern British Columbia and southwestern Alberta are consistent with this hypothesis, based on data collected from 10 lynx, including six (three

males, three females) resident adults, during two years of an assumed increase

phase of a hare cycle. Mean hare densities were low, ranging from 0.01 to 0.47/ha

among cover types and landscapes. Lynx winter diet (n = 137 kills) was diverse and

included hares (52%), red squirrels (30%), northern flying squirrels (5%), grouse

(3%), martens (3%), and voles (3%). Kitten recruitment to winter was zero among

adult females for four lynx-years. Family groups that did occur in the study area

during winter were associated with small litters of two. Survival among resident
Chapter 12—Apps

352

adults was 100%, but three of four subadults monitored during winter did not

survive to mid-May. Home ranges were large, with annual 95% adaptive kernel

utilization distributions averaging 381 and 239 km2

 for resident males and females

respectively. Minimum daily movements averaged 3.8 and 3.0 km respectively.

Two juvenile dispersals were short (44 and 17 km) and ended in starvation.

Space use by lynx may also relate to physiography, the influence of which may

vary seasonally in mountainous landscapes. Most lynx selected mid elevations

(1,550-1,850 m) and moderate to gentle slopes (<40%) within home ranges. Residents

used higher elevations, and some used steeper slopes during summer than during

winter. Highways were crossed less than random expectation within home ranges,

suggesting that they influenced lynx movements. Sexual differences in home range

size were not significant, but daily movements of males were greater than those of

females, indicating that they used space more extensively.

Introduction

The ecology of northern Canada lynx populations varies temporally with

snowshoe hare densities, as demonstrated with respect to population characteristics (Brand et al. 1976; Brand and Keith 1979; Poole 1994; Mowat et al.

1996; Slough and Mowat 1996; O’Donoghue et al. 1997), food habits and

foraging behavior (Brand et al. 1976; O’Donoghue et al. 1998a; O’Donoghue

et al. 1998b), space-use and movements (Ward and Krebs 1985; Poole 1994;

Slough and Mowat 1996), and dispersal (Poole 1997). However, it appears

that hare populations of southern latitudes and mountainous regions remain at relatively low and stable densities through time, possibly a result of

a more patchy habitat distribution, greater competition, and a greater suite

of predators (Dolbeer and Clark 1975; Wolff 1980). Hence, Koehler (1990)

theorized that the ecology of southern lynx populations resembles that of

northern populations during cyclic hare lows. Assuming that any variation

of hare density will be synchronous throughout their range (Smith and

Davis 1981), it follows that several hypotheses would hold true during the

increase and high phase of the cycle. Relative to results reported for northern

populations during hare lows, southern lynx populations should be associated with: (1) hare densities that are as low, (2) diet of as much alternate prey,

(3) resident home ranges that are as large, (4) daily foraging movements that

are as long, (5) reproduction and survival that are as low, and

(6) dispersal rates that are as great.
353

Apps—Chapter 12

Space use by lynx may also relate to physiography (Koehler and Aubry

1994), the influence of which may vary seasonally in mountainous landscapes. For example, open habitats that occur in conjunction with higher

elevations and rugged topography are associated with several prey species

that would be available only during snow-free months (Scotter and Ulrich

1995). Snow conditions that may restrict lynx movements and/or increase

expended energy (Murray and Boutin 1991) are also more likely at higher

elevations. Thus, individuals occurring in mountainous terrain can be

expected to use lower elevations and gentler slopes, make shorter daily

movements, and use smaller home ranges when snow is present. Near

southern range extents, lynx can also be expected to use cooler, north and

east aspects more often during snow-free months. This assumes that they are

more susceptible to heat stress during summer because the species is better

adapted physiologically to northern regions more central to its geographic

range. Finally, just as physiography may affect space use of resident lynx,

landscape features may also influence dispersal, and in highly mountainous

terrain, movements can be expected to align with major valleys. Lynx

movements may also be negatively influenced by highways due to habitat

fragmentation and direct avoidance, an important consideration for their

conservation (B. Ruediger 1996, unpublished). If highways restrict lynx

movements, they should be crossed less than random expectation where

they occur within home ranges.

Among solitary carnivores, it is assumed that female spacing patterns will

reflect the distribution of resources, whereas space use by males also will

conform to the distribution of females (Sandell 1989). Accordingly, home

ranges of female lynx are generally smaller than those of males, and spatial

overlap between sexes is extensive (Koehler and Aubry 1994; Poole 1995;

Slough and Mowat 1996). Because social tolerance is expected among

solitary foragers where resources are dispersed (Carr and McDonald 1986),

these relationships should also hold true among southern lynx populations

persisting in mountainous regions, where habitat is patchy and female home

ranges are not necessarily contiguous. The more extensive space use expected from males also should be reflected in daily movements greater than

those of females.

In this paper, I examine the hypotheses outlined above with research

conducted in the southern Canadian Rocky Mountains between November

1996 and October 1998. Results are of an unexploited, southern lynx population, occurring in a highly mountainous region, during the increase phase of

a snowshoe hare cycle in other regions (C. J. Krebs, personal communication).
Chapter 12—Apps

354

Study Area

The study area (>3,000 km2) is centrally located within the Shining Mountains ecoprovince (Demarchi 1994), and most of it lies within the East

Kootenay Wildlife Management Sub-region of southeastern British Columbia. It is defined by the Beaverfoot and upper Kootenay drainages on

provincial land and straddles the Continental Divide of British Columbia

and Alberta to include the Vermilion, Middle Bow, and Kicking Horse

valleys within Kootenay, Banff, and Yoho National Parks.

Characteristic of the Canadian Rockies, much of the area is rock, ice, and

other inherently unsuitable lynx habitat, and high peaks separate broad

valleys incised by narrow tributary valleys. Elevations (1,200 to over 3,000 m)

span three biogeoclimatic zones (Meidinger and Pojar 1991). Below 1,500 m,

the Montane Spruce Zone is characterized by a climax overstory of hybrid

Engelmann/white spruce and subalpine fir. The Engelmann Spruce-Subalpine Fir Zone occurs at higher elevations but below 2,300 m, where Engelmann spruce and subalpine fir dominate the climax overstory up to the

Alpine Tundra Zone at highest elevations. Sub-climax stands throughout

the study area are dominated by lodgepole pine. The macroclimate is

continental, with mean temperatures ranging from –18°C (January) to 23°C

(July) and 42-63% of the 51-81 cm mean annual precipitation falling as snow

(Achuff et al. 1984). Natural and human conditions vary throughout the

study area, and linear features include two- to four-lane paved highways

with annual (1994) average daily traffic volumes of 1,119-8,322 vehicles per

day (A. Clevenger, personal communication, Banff, AB), as well as industrial

road networks, a twin-tracked railway, and trail systems.

Other predators and potential competitors with lynx include coyote, wolf,

black bear, grizzly bear, marten, wolverine, cougar, at least three hawk

species, golden eagle, and the great-horned owl. Fishers and red fox are rare,

and bobcats are not resident (Poll et al. 1984). Potential lynx prey include

snowshoe hares, red squirrels, northern flying squirrels, gallinaceous

birds, microtine rodents, hoary marmots, ground squirrels, bushy-tailed

woodrats, and beavers. Potential ungulate prey include moose, elk, bighorn

sheep, mountain goat, mule deer, and white-tailed deer.

Despite a limited season in British Columbia, lynx have not been legally

harvested on the provincial section of the study area for at least 15 years.

Based on this, and the 68 years of protection that lynx have received in the

national parks (Poll et al. 1984), I consider the resident population in the

study area to be unexploited.
355

Apps—Chapter 12

Methods

Hare Densities

I determined a range of snowshoe hare densities by counting fecal pellets

during September 1998 in established 305 x 5.1 cm quadrats (Krebs et al.

1987). Ten quadrats were spaced at 30.5 m intervals along each of 61

transects. Transects were placed randomly among early- (20-60 years), mid-

(60-120 years), and late- (>120 years) successional stands but were spaced by

≥500 m. Sampling was further stratified among three landscapes within the

study area, representing geographically distinct areas where I consider

terrain conditions conducive to supporting lynx. Hare densities were calculated with a modified version of the Krebs et al. (1987) regression equation,

using the HARETURD program (C. J. Krebs, personal communication).

Lynx Capture

Study animals were captured during the winters of 1996-1997 and 1997-

1998, with efforts focused in landscapes where lynx signs had been reported

in recent years. Hounds trained to pursue felids were used to tree lynx,

following methods described for cougars and bobcats (Hornocker 1970;

Apps 1996). Live trapping was also carried out using Soft Catch®

(Woodstream Corp., Litiz, PA.) #3 padded foot-hold traps in cubby sets

(Hawbaker 1974) with modifications (Mowat et al. 1994). Captured lynx

were immobilized with ketamine hydrochloride and xylazine hydrochloride at 10.0 and 2.5 mg/kg estimated body mass (Woodbury 1996), administered intramuscularly with an extendable pole-syringe or a

Cap-chur® (Palmer Chemical and Equipment Co. Inc., Douglasville, GA.)

Powder Projector dart gun. Anesthesia was occasionally maintained with an

additional ketamine injection of 6.0 mg/kg. Immobilized lynx were sexed,

and age was subjectively classed (adult: >2 years; juvenile: 1-2 years; kitten:

<1 year) based on skeletal measurements and tooth wear. Study animals

were fitted with motion/mortality sensing whip antennae radiocollars

(Lotek Eng. Inc., Newmarket, ON.) and allowed to recover before release.

Recovery was expedited on three occasions using atipamezole hydrochloride to reverse xylazine at twice the dosage of the latter (Woodbury 1996).

Radiotelemetry

Radiolocations were obtained throughout the year, at least weekly for all

animals, and at least four days per week for most animals. Radiotelemetry

was conducted from the ground and fixed-wing aircraft using standard
Chapter 12—Apps

356

techniques (Samuel and Fuller 1996). Ground locations were estimated from

three bearings taken within 1.5 hours, with origins located using hand-held

Eagle Explorer® GPS receivers (Eagle Electronics, Catoosa, OK). Bearings

were taken <2 km from the animal’s estimated location 69% of the time. Two

azimuths intersected at 70-110° for 88% of error polygons, and 89% of error

polygons were <25 ha. Lynx were mostly inactive during 71% of ground

locations, and I expect that time delays between bearings had a negligible

effect on accuracy. Universal Transverse Mercator coordinates of radiolocations were referenced to ±50 m from 1:20,000 orthophoto or 1:50,000 National

Topographic System (NTS) maps. Positional error associated with 95% of

aircraft radiolocations was considered to be ±150 m (M. Gibeau, personal

communication).

Food Habits

Study animals were snow-tracked during both years when possible, and

kills and scavenging were documented over 759 km of trails. Prey remains

were sufficient for positive species identification in most cases, although

some kills may have been missed due to recent snow or for small prey. Tracks

were directly observed wherever possible to minimize missed kills.

Population Attributes

Lynx carcasses and/or radiocollars were retrieved as soon as possible after

mortality. Probable cause of death was determined from necropsies (Shury

Veterinary Services, Canmore, AB) and field evidence. Female study animals were snow-tracked pre- and post-capture to determine whether kittens

were present. When encountered, family groups of uncollared lynx were

also snow-tracked to count kittens. The movements of females exhibiting

strong site fidelity during May through July were radiotracked daily.

Space Use and Movements

I defined resident lynx as those associated with one activity center subjectively determined over at least three months. Home ranges of resident adults

were estimated seasonally and annually over both years using the program

CALHOME (Kie et al. 1996). I defined summer and winter seasons by the

typical six-month snow and snow-free periods beginning and ending

1 November and 1 May. The late-February to early-April breeding period

(Koehler and Aubry 1994) occurred in winter. To facilitate comparison with

other research, I calculated the 100% and 95% minimum convex polygon

(MCP) (Hayne 1949) and 95%, 75%, and 55% adaptive kernel utilization
357

Apps—Chapter 12

distributions (UD) using optimal smoothing parameters (Worton 1989).

Lynx movements indicated that home ranges could be traversed within 24

hours, thus only radiolocations that were temporally independent by this

interval were used (sensu Swihart and Slade 1985). Among all animals, the

95% UD area appeared to asymptote at 43 to 55 radiolocations (Apps,

unpublished). I compared UD levels between sexes and seasons using

multivariate analysis of variance (MANOVA; α = 0.05). Static interaction

between lynx known to have neighboring or contiguous home ranges was

inferred from spatial home range overlap (Macdonald et al. 1980).

I defined minimum daily movements (MDM) as the distance between

sequential radiolocations separated by 18-36 hours ( x = 24 hours). Mean

MDM were compared among resident lynx of each sex using analysis of

variance (ANOVA; α = 0.05), and between seasons and sexes using unpaired

Student’s t-tests (α = 0.025). I assumed that lynx exhibiting consistent, linear

movements were transient or dispersing animals. Where possible, I summarized the movements of these animals with respect to timing of dispersal,

direction, distance, MDM, and proximate outcome.

Topographic Selection and Highway Influence

For each resident lynx, I assessed seasonal selection for elevation, slope,

and aspect within respective annual home ranges. This corresponds to

Johnson’s (1980) third-order resource selection and Thomas and Taylor’s

(1990) Study Design 3, with inferences relevant at the individual level.

Digital elevation, slope, and aspect models were derived in a GIS from

1:50,000 NTS elevation contours. Aspect was described by two ratio-scale

(0→1) variables depicting south→north and west→east aspects. The raster

resolution of each variable was set to 25 ha, roughly corresponding to the

maximum spatial error of lynx radiolocations. Topographic attributes used

by each animal were estimated from radiolocations temporally independent

by at least 24 hours, following rationale described for home range analysis.

Available attributes were estimated from an equivalent sample of systematic

random locations within each animal’s 95% UD. Variables were screened for

multicollinearity using Pearson correlation coefficients (Tabachnick and

Fidell 1989), and non-redundant (r <0.8) variables were entered into

multiple logistic regression to derive probabilistic resource selection functions (Manly et al. 1993). Box-Tidwell transformations (Box and Tidwell

1962) of elevation and slope were significant in some initial models,

indicating that lynx selection for these attributes was non-linear (Hosmer

and Lemeshow 1989). To facilitate comparisons among animals, I grouped

elevation and slope data into three classes for each variable, roughly
Chapter 12—Apps

358

corresponding to average 0.33 percentile groupings of available habitat

among all animals. I tested the improvement of fitted models over null

models by evaluating the reduction in (–2) log-likelihood ratios against a

Chi-square distribution (Hosmer and Lemeshow 1989; α = 0.05), and I

assessed the explanatory power of each model by regressing actual use

against predicted use probabilities to derive coefficients of determination

(r 2

). The significance of variable coefficients was evaluated using Chi-square

tests of Wald statistics (α = 0.05), and the contributions of each variable were

assessed from the sign and strength of their partial correlations (r) with each

model (Hosmer and Lemeshow 1989; Norusis 1994). From r statistics, I

inferred preference where positive, and avoidance where negative. I evaluated differences in seasonal use of each variable using unpaired Student’s ttests (α = 0.0125). I used SPSS 7.0 (SPSS Inc., Chicago, IL) software for

statistical analyses.

Paved highways dissected all lynx home ranges relatively linearly. I

therefore assumed that a crossing occurred if sequential radiolocations were

obtained on opposite sides of a highway (Chapter 10). This facilitated tests

of the null hypothesis that lynx movements within home ranges were

random with respect to highways. Movements of resident lynx were defined

as the minimum distance between sequential radiolocations, and for each, a

movement vector of the same length but random location and azimuth was

generated within respective 95% UD isopleths. Lynx and random movements were then coded according to their intersection with highways, and

differences in lynx vs. random crossing frequencies were evaluated using

Chi-square tests (α = 0.05).

Results

Hare Densities

For early-, mid-, and late-successional stands respectively, mean hare

densities by landscape were 0.16/ha (95% CI = 0.11-0.24), 0.08/ha (95% CI =

0.05-0.11), and 0.01/ha (95% CI = 0 -0.02) in the upper Kootenay Valley; 0.25/

ha (95% CI = 0.19-0.35), 0.06/ha (95% CI = 0.04-0.10), and 0.10/ha (95% CI =

0.07-0.15) in the Beaverfoot Valley; and 0.47/ha (95% CI = 0.36-0.62), 0.39/

ha (95% CI = 0.26-0.57), and 0.32/ha (95% CI = 0.22-0.46) in the Vermilion

Pass.

Food Habits and Population Attributes

Ten lynx, comprising three adult males, three adult females, one juvenile

male, two kitten/juvenile females, and one kitten male, were radiocollared,
359

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monitored and snow-tracked for 1-23 months between November 1996 and

October 1998. Lynx kills (n = 137) documented over both years were

composed of snowshoe hares (52%), red squirrels (30%), northern flying

squirrels (5%), grouse (3%), martens (3%), voles (3%), a northern flicker

(<1%), and unknown species (3%). One case of scavenging on an intact mule

deer, presumed to have died from a vehicle collision, occurred for 2-4 days

before it was usurped by wolves.

None of the three adult females in the study sample were traveling with

kittens at the time of their capture in November 1997 or 1998. One uncollared

family group was detected in the study area during March 1997, and three

uncollared family groups were detected during November and December

1997. I assumed the latter groups were different individuals because each

group was separated by a linear distance >30 km, beyond the maximum

exploratory movement of radiocollared females (personal observations).

Each group contained an adult and two kittens. Both kittens (M/04, F/03)

from one family group were subsequently radiocollared, but neither survived to May. Two females that were monitored through March of 1997

(F/01) and 1998 (F/02) were snow-tracked while traveling with males, and

F/02 was also directly observed during copulation with an uncollared male

on 13 March. Daily radiolocations of F/01 were within 250 m of an activity

center between 20 May and 1 June 1997, after which she resumed normal

movements and did not revisit the presumed den site. From this, I inferred

that she lost or abandoned her litter at or just after parturition. Kittens were

also not detected with her during snow-tracking early in the following

winter. Radiolocations of F/02 were within 500 m of an activity center on

82% of days between 22 May and 14 July 1998, and she was observed with

one kitten in August of that year.

Known survival of resident adults was 100% over both years. A dispersing

female kitten (F/03) and a transient, juvenile male (M/05) died of starvation

on 15 April and 3 May 1998 respectively. A male kitten (M/04) likely was

killed by an uncollared adult male lynx in December 1997 while traveling

with his family group and within his natal range. A female kitten (F/05)

released to her natal area in April 1998 after four months in captivity due to

a capture injury survived at least the following six months.

Space Use and Movements

The mean number of radiolocations used for summer and winter home

range estimates was 96 (range = 63-183) and 149 (range = 72-265) respectively. Mean 95, 75, and 55% UD estimates did not significantly differ

between seasons for males (F = 3.66, 3 df, p = 0.222) or females (F = 1.34, 3 df,

p = 0.548). Mean annual UD estimates (Table 12.1) also did not significantly
Chapter 12—Apps

360

differ between sex (F = 2.92, 3 df, p = 0.266). Spatial overlap between the

annual 95, 75, and 55% UD areas of M/01 and F/01 was 36, 63, and 60%,

respectively. Of their 183 concurrent daily radiolocations, 78% were separated by >3 km. A second adult female was known to occur also within the

50% UD area of these two lynx, as inferred from snow-tracking and radiolocations of her dependent kitten (M/04). In addition, unmarked adult lynx

were detected within the 70% UD of all other study animals between

1 November and 15 February 1998.

Minimum daily movement (MDM) (Table 12.2) differed among resident

females during summer (F = 9.81; 2, 163 df; p <0.001) but not winter (F = 0.43;

2, 235 df; p = 0.65). MDM differed among resident males during both summer

(F = 3.67; 2, 182 df; p = 0.027) and winter (F = 4.62; 2, 349 df; p = 0.010).

Movements were greater during summer for M/01 (t = 3.48, 278 df, p <0.001)

and were greater during winter for F/02 (t = 2.72, 125 df, p = 0.007), while

seasonal differences were not significant among other residents (t <1.77, 26-

110 df, p >0.082). Male movements were greater than those of females during

both summer (t = 5.01, 347 df, p <0.001) and winter (t = 3.05, 584 df, p = 0.002).

Dispersal

Dispersal movements were documented for three subadult lynx. After he

was radiocollared on 19 March 1998, a juvenile male (M/05) made a 44 km

southeast movement over 11 days (MDM: x = 3.7 km, SD = 1.9). He then used

one meadow complex intensively (MDM: x = 1.3 km, SD = 0.9) for the next

31 days before his death on 3 May. After she was radiocollared within her

natal range, a female kitten (F/03) rejoined her mother for three days, then

moved independently for three days before 28 March when she initiated a

Table 12.1—Annual minimum convex polygon (MCP) and adaptive kernel utilization distribution (UD) home range estimates

(km2

) for resident lynx in the southern Canadian Rocky Mountains, British Columbia and Alberta, 1996-1998.

Lynx sex/ID Period monitored (m/y) n 100% MCP 95% MCP 95% UD 75% UD 55% UD

M/01 11/96 – 10/98 448 559 357 337 117 45

M/02 03/97 – 10/98 189 346 224 330 49 24

M/03 03/97 – 06/98 141 388 249 477 150 51

Male mean 3 431 277 381 105 40

Male SD 113 71 83 52 14

F/01 11/96 – 09/97 200 408 276 505 85 31

F/02 11/97 – 10/98 254 133 85 94 25 11

F/04 04/98 – 10/98 103 77 44 87 30 13

Female mean 3 206 135 229 47 18

Female SD 177 124 239 33 11
361

Apps—Chapter 12

southeast linear movement of 17 km over three days (MDM: x = 5.6 km, SD =

0.4). She then used one area intensively (MDM: x = 0.9 km, SD = 0.5) for the

next 15 days before her death. The movements of both animals followed the

major valley in which they occurred and paralleled but did not cross the

Trans-Canada Highway. After her 30 April release, a kitten/juvenile female

(F/05) used a 75% UD home range of 53 km2

 for five months, after which she

made two separate exploratory movements of a minimum 74 km and 55 km

over 24 and 11 days respectively. The second movement continued in a

southward dispersal.

Topographic Selection and Highway Influence

Topographic selection within home ranges was apparent among all six

resident lynx during summer (χ2

 >21.6, 5-6 df, p <0.002), and among five

during winter (χ2

 >35.6, 5-6 df, p <0.001). Among animals, models explained

variation (r 2

) ranging from 12 to 36% during summer and 19 to 36% during

winter. Lynx either avoided or did not select highest (>1,850 m) elevations,

preferred or did not avoid mid (1,550-1,850 m) elevations, and although

lowest (<1,550 m) elevations were not avoided during winter, two animals

did avoid them during summer (Table 12.3). All males and one female used

mean elevations 90-133 m higher during summer than during winter

(t >2.72, 131-434 df, p <0.008). However, seasonal use of elevations did not

differ for two females (t <1.19, 97-237 df, p >0.240). Most lynx avoided or did

not select steeper (>40%) slopes, and preferred or did not avoid moderate

(20-40%) or gentle (<20%) slopes (Table 12.3). Mean slopes used were 4-9%

steeper during summer than during winter for two males and two females

(t >2.65, 131-237 df, p <0.009), whereas slope use did not differ between

seasons for one male and one female (t <0.95, 97-434 df, p >0.344). Selection

for aspect varied among animals (Table 12.3). Among all six lynx, there were

Table 12.2—Minimum daily movements (MDM; km) for resident lynx during summer (1 May–31 October), winter (1 November–

30 April), and annually in the southern Canadian Rocky Mountains, British Columbia and Alberta, 1996-1998.

Lynx Summer Winter Annual

sex/ID n Range Mean SD n Range Mean SD Mean SD

M/01 124 0.1 – 14.3 4.8 3.2 212 0.5 – 19.3 3.5 3.5 3.9 3.5

M/02 27 0.4 – 13.7 3.3 3.1 45 0.8 – 23.2 5.0 5.2 4.3 4.6

M/03 34 0.4 – 10.9 3.7 2.3 95 0.1 – 19.8 3.0 2.9 3.2 2.7

Males 3 3.9 0.8 3 3.8 1.1 3.8 0.6

F/01 53 0.0 – 10.3 3.0 2.4 101 0.1 – 12.0 2.7 2.5 2.9 2.5

F/02 64 0.0 – 10.9 1.9 2.2 125 0.1 – 10.4 2.8 2.1 2.5 2.2

F/04 49 0.5 – 13.7 3.9 2.8 12 0.8 – 6.1 3.4 1.8 3.9 2.6

Females 3 2.9 1.0 3 3.0 0.4 3.0 0.7
Chapter 12—Apps

362

no significant seasonal differences in the use of northward aspects (t <2.26,

97-434 df, p >0.025), and although one male used eastward aspects greater

during summer than during winter (t = 2.56, 434 df, p = 0.011), seasonal

differences were not significant among the other five lynx (t <1.93, 97-237 df,

p >0.055). All six resident lynx crossed highways less than random expectation within their home ranges (x 2

 >139.9, 1 df, p <0.001).

Discussion

Hare Densities

Hare densities (range = 0.01-0.47/ha) observed in the southern Canadian

Rockies during 1996-1998 are comparable to those reported in northern lynx

study areas during cyclic hare population lows. Hare densities in the

southwest Yukon declined from 8.0 to 10.7/ha to 0.2 to 0.5/ha during one

cycle (Ward and Krebs 1985), and another population fell from 7.5/ha to 1.3/

ha during the next cycle (Slough and Mowat 1996). Similarly, a population

in the Northwest Territories fell from 7 to 9/ha to 0.4 to 1.0/ha during the

early 1990s (Poole 1994), and a northern Alberta population declined drastically from about 17/ha to 0.34/ha during the early 1970s (Brand et al. 1976).

Because my study period coincided with the increase phase of a hare cycle

(C. J. Krebs, personal communication), assuming goegraphic synchrony, my

results are consistent with suggestions that hare densities remain relatively

Table 12.3—Significance (p) and partial correlations (r) of variables considered within multiple logistic regression models

of topographic selection within home ranges. Results are given for summer (1 May-31 October) and winter

(1 November-30 April) for resident lynx in the southern Canadian Rocky Mountains, British Columbia and Alberta,

1996-1998. Preference (+) or avoidance (–) is inferred from r statistics where p < 0.05.

Lynx sex/ID: summer Lynx sex/ID: winter

Variable M/01 M/02 M/03 F/01 F/02 F/04 M/01 M/02 M/03 F/01 F/02 F/04

Elevation (m) p <0.001 0.006 0.049 <0.001 0.511 0.196 <0.001 0.071 <0.001 <0.001 0.773 0.547

<1,550 r –0.20 +0.11 +0.13 –0.20 — 0.00 0.00 +0.12 +0.22 0.00 — 0.0

1,550 – 1,850 r +0.30 +0.10 0.00 +0.29 0.00 +0.06 +0.26 0.00 0.00 +0.27 0.00 0.00

>1,850 r 0.00 –0.21 –0.11 0.00 0.00 0.00 –0.21 –0.13 –0.20 –0.21 0.00 0.00

Slope (%) p <0.001 0.163 0.025 0.038 0.890 0.859 0.018 0.465 0.192 0.015 0.008 0.931

<20 r +0.07 0.00 –0.18 +0.15 0.00 0.00 +0.09 0.00 0.00 +0.12 0.00 0.00

20 – 40 r +0.12 +0.09 +0.04 0.00 0.00 0.00 0.00 0.00 0.00 +0.05 +0.13 0.00

>40 r –0.19 0.00 +0.07 –0.07 0.00 0.00 –0.07 0.00 +0.06 –0.14 –0.11 0.00

S→N aspect p 0.358 0.002 0.100 0.513 0.333 0.024 0.050 0.345 0.711 0.914 0.057 0.723

r 0.00 –0.19 –0.06 0.00 0.00 –0.12 –0.051 0.00 0.00 0.00 –0.06 0.00

W→E aspect p 0.001 0.071 <0.001 0.323 <0.001 0.020 0.973 0.265 <0.001 0.119 <0.001 0.466

r +0.13 –0.08 +0.30 0.00 –0.29 –0.123 0.00 0.00 +0.27 +0.04 –0.22 0.00
363

Apps—Chapter 12

low in southern British Columbia and the northwestern United States

(Chitty 1950; Dolbeer and Clark 1975; Wolff 1980).

Food Habits

The large proportion (47%) of prey other than snowshoe hares documented during winter in this study to date generally is consistent with

observations of opportunistic lynx food habits during hare lows (Koehler

and Aubry 1994; Staples 1995; O’Donoghue et al. 1998b). The 35% combined

proportion of red squirrel and flying squirrel kills also is roughly consistent

with Koehler’s (1990) reported 24% occurrence of tree squirrels in lynx scats

collected year-round in Washington. Lynx predation on marten has not been

previously reported and likely is opportunistic. Despite the substantial

numeric quantity of alternate prey in the diet of lynx in this study, hares

clearly represent the most important food source when biomass ratios are

considered (e.g., 1:5 squirrel:hare; Nellis and Keith 1968), as is consistent

with other lynx populations (Koehler and Aubry 1994; Staples 1995;

O’Donoghue et al. 1998b). My results, however, may underestimate the

diversity of prey used due to missed kills of small species during snowtracking, as was found by O’Donoghue et al. (1998b) in a comparison of killsite with scat data. Although lynx in the Yukon cached partially consumed

hares (O’Donoghue et al. 1998b), this behavior was not observed in the

southern Canadian Rockies.

Reproduction and Recruitment

Kitten production and survival were low during the study period. The

apparent lack of recruitment to early winter among study animals is consistent with northern populations after a hare decline, when winter litter sizes

were zero (Brand et al. 1976; Poole 1994; Mowat et al. 1996). O’Donoghue et

al. (1997) also did not detect family groups in their Yukon study area after the

hare decline. Among the four uncollared family groups, litter sizes also were

low in comparison to northern populations in the year preceding the hare

decline, when mean winter litter sizes were 3.0 (n = 3; Poole 1994) and 3.3 (n =

12; Mowat et al. 1996). However, the occurrence of some kittens suggests that

habitat quality varied among female home ranges within the study area.

Among southern populations, Koehler (1990) also reported low (12%) kitten

survival to winter from three litters in north-central Washington, and three

adult females monitored in Montana from 1982 through 1984 did not

produce kittens (Brainerd 1985). Evidence of breeding and den site abandonment of F/01 is consistent with the suggestion by Mowat et al. (1996) that

breeding and implantation continues to occur regardless of prey densities.
Chapter 12—Apps

364

Survival

Survival of resident adults was high over both years, as was found in

another population refugium (Slough and Mowat 1996). During hare lows

in northern populations, most natural mortality is due to starvation and is

preceded by nomadic movements (Ward and Krebs 1985; Poole 1994; Slough

and Mowat 1996), as observed for two lynx in this study. These two deaths

occurred during spring, in contrast to Poole’s (1994) observation that most

natural mortality in his Northwest Territories study area occurred during

mid-winter. Evidence of cannibalism that I report has been documented

before (Elsey 1954; Nellis et al. 1972; Brittell et al. 1989; Poole 1994; O’Donoghue

et al. 1995; Slough and Mowat 1996).

Space Use and Movements

Annual home ranges of resident lynx in the southern Canadian Rockies

were considerably larger than those reported for most other studies employing the same estimators, regardless of prey density or geographic locale

(Koehler and Aubry 1994; Poole 1994; Slough and Mowat 1996). Minimum

convex polygon (MCP) home ranges in my study area were roughly 5-10

times larger than previously reported (Ibid.), although the influence of

sample size on this estimator may confound comparisons (White and Garrot

1990). An exception to this was reported for the year after a hare decline in

the Yukon, when four female and two male resident lynx maintained larger

mean home ranges with high variability (Slough and Mowat 1996). Similarly, MDM mostly were higher than in other studies of comparable methods

(Ward and Krebs 1985; Poole 1994), implying greater foraging effort. One

exception to this was documented by Ward and Krebs (1985) during a hare

decline in the Yukon, when lynx increased their daily movements from 2.4

to 3.3 to 5.4 km/day as hares declined from 1.0 to 0.5 to 0.2/ha, respectively.

However, another Yukon study did not find that lynx increased their active

time in response to declining hare numbers (O’Donoghue et al. 1998b).

Differences between 100 and 95% MCP home ranges reflect exploratory

movements that were made throughout the year by all resident study

animals. Physiography and the distribution of potential habitat may partially account for lynx home range size differences between geographic areas

(Koehler and Aubry 1994). In comparison to other study areas, space use and

movements by lynx in the southern Canadian Rocky Mountains therefore

may be disproportionately greater relative to prey densities.

Few studies have examined seasonal variation in space-use by lynx.

Although I found no significant seasonal differences in UD areas for either

sex, tests were based on a low sample size. More extensive space-use during
365

Apps—Chapter 12

summer was apparent for only one male; however, inclusion of the breeding

period within the winter season may have masked seasonal differences

among other lynx. Although not statistically tested, in Nova Scotia, individuals of both sexes used areas during summer that were larger than those

used during winter (Parker et al. 1983), and two females with young used

smaller areas during summer in Alaska (Bailey et al. 1986). In accordance

with the latter observation, the only lynx that made smaller daily movements during summer was a female with kittens.

Relative to other study animals, the noticeably smaller UD areas that I

report for two females (F/02, F/04) may reflect the distribution and configuration of potential habitat in the landscape where they occur. Still, although

samples were small, home range comparisons between sex did not reveal

more intensive space use by females as has generally been observed (Koehler

and Aubry 1994), perhaps because females were mostly without kittens

during the monitoring period. Smaller female home ranges were reported in the Yukon only during years of high kitten survival to 1 March

(Slough and Mowat 1996). Poole (1994), however, did not detect home range

differences between sexes over four years of variable kitten survival in the

Northwest Territories. Regardless of home range comparisons, differences

in daily movements suggest that females used space more intensively than

males during both seasons.

Differential space use within home ranges may be influenced by habitat

features and social interactions (Samuel et al. 1985). Obvious differences

between annual UD levels indicate that lynx home ranges were not used

homogenously but were associated with distinct core use areas. Poole (1994)

also reported the use of obvious core home ranges by lynx (50% vs. 95%

MCP). Evidence of intersexual spatial overlap that I report is consistent with

most other populations (Koehler and Aubry 1994; Poole 1995). Sharing of

home ranges between sexes or related females observed elsewhere also

would be expected in the southern Canadian Rockies, considering the

heterogeneous distribution of potential lynx habitat (Sandell 1989).

Topographic Selection

Lynx exhibited variable selection for topographic attributes, which may

relate to differing associations of topography with habitat, human, and snow

conditions; however, there was some consistency in pattern. Avoidance of

highest elevations and steepest slopes by lynx in this study area likely is due

to unsuitable habitat associations and energetic costs of accessing any

habitat that is suitable. Lynx may also use topography to help partition

themselves from competing species. Although they used higher mean

elevations than coyotes during winter in the Yukon (Murray and Boutin
Chapter 12—Apps

366

1991), lynx may not avoid lowest elevations within home ranges if habitat

and terrain conditions are otherwise unsuitable for canids. During summer,

they may further minimize interference competition with canids by using

higher elevations and steeper slopes. The seasonal shift in elevation use that

I found is similar to that reported by Koehler (1990) among lynx in the

mountains of north-central Washington. Within their home ranges, bobcats

occurring sympatric with coyotes in southeast British Columbia preferred

mid elevations, avoided slopes <10°, and selected distances <0.75 km from

slopes associated with rock outcrops (Apps 1996). Terrain was also a factor

in habitat partitioning between bobcats and coyotes in Idaho (Koehler and

Hornocker 1991). Regardless of interspecific relationships, the open habitats

associated with higher elevations in my study area contain additional prey

species not available during winter (Scotter and Ulrich 1995), and snow

conditions may increase the energetic cost of travel at higher elevations

during much of the winter.

I found no obvious pattern of aspect selection by lynx within home ranges,

and use did not differ seasonally among most animals. However, McKelvey

et al. (Chapter 10) detected preference for northeast aspects at the scale of

their Washington study area. If lynx exhibit aspect preferences in the

southern Canadian Rockies, they may occur at broader or finer spatial scales

than I considered. Moreover, finer-scale selection for this variable may relate

to solar insolation, which will vary greatly within and among days. The

individual selection for aspect that did occur may be an artifact of

covariation with other habitat and human conditions.

Highway Influence

The likelihood of highway crossings by resident lynx can be expected to

vary among home ranges according to proximal habitat conditions, width of

road allowance and traffic volume, and perhaps by the animal’s sex and

reproductive status. Although my analysis did not account for these factors,

all lynx crossed highways less than random expectation within their 95% UD

home ranges, suggesting that highways influenced lynx movements. Although my analysis only considered the influence of highways within home

ranges, they may also influence home range selection just as dominant

natural features can (Koehler and Aubry 1994), and this would decrease the

substantive influence apparent within home ranges. Although there have

been no other reports to date of lynx space use and movements relative to

human linear disturbance, four lynx in Washington did not cross logging

roads differently from random within home ranges (Chapter 10). However,

bobcats in Wisconsin selected home ranges with lower densities of secondary roads and crossed paved highways less than expected, a function of
367

Apps—Chapter 12

vehicle traffic levels and juxtaposition of preferred habitat to roads (Lovallo

and Anderson 1996).

Dispersal

The timing of F/03’s dispersal is within the March-June emigration peak

observed by Slough and Mowat (1996) in the Yukon but occurred nine days

before their earliest female kitten dispersal. The linear movements by this

lynx and M/05 are in the lower extremes of those reported for lynx emigrating from northern populations (Slough and Mowat 1996; Poole 1997);

however most reported lynx dispersals have been of adults. The orientation

of movements relative to terrain and the Trans-Canada Highway suggests

that dominant natural and human features may constrain dispersal options

in the southern Canadian Rockies. The intensive use of one area exhibited by

both lynx before their deaths does not imply residency because

dispersing felids have exhibited short-term use of temporary home ranges

(Beier 1995; Apps 1996).

Conclusions

Although results are based on limited data, several conclusions specific to

the southern Canadian Rocky Mountains can be made. Hare densities, and

the diet, space-use and movements, reproduction, subadult survival, and

dispersal of lynx were consistent with those of northern populations during

hare lows. However, assuming geographic synchrony, the study period

coincided with the increase phase of a snowshoe hare cycle, suggesting that

lynx populations in the southern Canadian Rocky Mountains are not subject

to the dramatic, cyclic pulses in productivity reported for northern populations. The following are also apparent: lynx spacing patterns suggest that

resource distribution is patchy; males use space more extensively than

females; topography influences habitat potential, with seasonal differences;

and highways may negatively influence lynx movements.

Acknowledgments

These first two years of this ongoing study were funded by the British

Columbia Habitat Conservation Trust Fund, Parks Canada, the Columbia

Basin Fish and Wildlife Compensation Program, and the Habitat and

Silviculture Assistance Fund. Field assistance was capably provided by

R. Owchar, B. Bertch, S. Stevens, P. Wandeler, S. Hawes, D. Quinn, B. Baxter,

C. Darimont, M. Vassal, J. Weaver, J. Bryan, D. Ghekas, and D. Poszig.

J. Weaver and G. Mowat also contributed helpful advice on study design
Chapter 12—Apps

368

and methods. Project administration and in-kind contributions were provided by A. Dibb of Parks Canada, A. Fontana and R. Neil of the BC Ministry

of Environment, Lands and Parks, and J. Krebs of the Columbia Basin Fish

and Wildlife Compensation Program. Veterinary services were provided by

T. Shury and M. Zehnder. Temporary animal holding and care were facilitated by T. Kinley and N. Newhouse. Constructive input to this manuscript

was provided by S. Buskirk and two anonymous reviewers.

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Chapter 12—Apps

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373

Chapter 13

Ecology of Canada Lynx

in Southern Boreal

Forests

Keith B. Aubry, USDA Forest Service, Pacific Northwest Research Station,

3625 93rd Ave. SW, Olympia, WA 98512

Gary M. Koehler, Washington Department of Fish and Wildlife,

600 Capitol Way N, Olympia, WA 98501

John R. Squires, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59807

Abstract—Canada lynx occur throughout boreal forests of North America, but

ecological conditions in southern regions differ in many respects from those in

Canada and Alaska. To evaluate the extent to which lynx ecology and population

biology may differ between these regions, we review existing information from

southern boreal forests and compare our findings to information presented in

Chapter 9 on lynx in the taiga. Throughout North America, lynx diets in both winter

and summer are dominated by snowshoe hares. In southern boreal forests, alternative prey, especially red squirrels, are important constituents of the diet. This

reliance on alternative prey may reflect a response to low-density hare populations

in southern regions, because alternative prey are also important in the taiga during

lows in the snowshoe hare cycle. In addition, limited information on lynx diets

during snow-free months indicates that alternative prey are important during

summer in both northern and southern populations, regardless of the status of local

hare populations. As in the taiga, lynx in southern regions are associated with boreal

and sub-boreal forest conditions, including upper elevation, coniferous forests in
Chapter 13—Aubry

374

the western mountains and mixed coniferous-deciduous forests in the Northeast.

Throughout their range, lynx are absent or uncommon in dense, wet forests along

the Pacific coast. In both northern and southern regions, lynx occur predominantly

in habitats where snowshoe hares are abundant, especially early successional stands

with high stem densities. However, in southern boreal forests, such habitats appear

to be used primarily for hunting; all known den sites in southern regions were

located in mature forest stands with large woody debris. As in the taiga during times

of hare scarcity, relatively large home ranges appear to be characteristic of lynx in

southern boreal forests. Lynx dispersal movements are similar to those reported

from the taiga. However, only lynx in southern forests are known to make exploratory movements prior to dispersal. We speculate that such explorations may reflect

a more heterogeneous habitat mosaic, and a correspondingly lower probability of

successful dispersal in southern regions. Demographic characteristics of southern

lynx populations, including low densities, low pregnancy rates, low litter sizes, and

high kitten mortality rates are similar to those reported from the taiga during times

of hare scarcity. As in the taiga, we found little evidence that roads represented a

significant disturbance or mortality factor for lynx. Roads into lynx habitat may,

however, provide access to generalist competitors, such as coyotes and bobcats.

Although there is little evidence that competition with other predators negatively

influences lynx populations, this aspect of their ecology has not been studied in

southern boreal forests. In summary, differences in lynx ecology between populations in southern boreal forests and those in the taiga appear to be related primarily

to the use of alternative prey species; the effect of habitat patchiness on movements,

reproduction, and survival; and the potential effects of different communities of

predators and competitors on lynx populations.

Introduction

Canada lynx occur in most boreal forest habitats in North America,

including the classic boreal forests or taiga of northern Canada and Alaska,

upper elevation coniferous forests of the Rocky Mountains and Cascade

Range, and mixed coniferous-deciduous forests of southeastern Canada,

New England, and the Great Lakes states (Chapters 3 and 8; McCord and

Cardoza 1984; Quinn and Parker 1987). Most of the geographic range of lynx

in North America occurs in the taiga, however, where Canada lynx ecology

has been studied in greatest detail (Chapter 9). Lynx reach their highest

densities in the taiga, where populations undergo dramatic 10-year cycles in

delayed synchrony with snowshoe hare populations (Elton and Nicholson

1942; Keith 1963; Chapter 9).
375

Aubry—Chapter 13

Some authors have argued that lynx populations in the southern portion of

their range in the contiguous United States do not cycle in abundance, but

occur at relatively stable densities comparable to those found during cyclic

lows in the taiga (Keith 1963; Koehler and Aubry 1994). This hypothesis is

based largely on the observation that snowshoe hare populations in the

southern portions of their range are either stable or have cycles of very low

amplitude (Adams 1959; Keith 1963; Dolbeer and Clark 1975; Wolff 1980,

1982). However, Hodges (Chapter 7) has compiled new information on

snowshoe hare populations in southern boreal forests that indicates that

hares may fluctuate in number more than previously thought, but at much

lower amplitudes than those recorded in the taiga. Ecological conditions in

southern boreal forests occupied by lynx differ in many ways from those in

the taiga (Chapter 3). Thus, the ecology of lynx in southern boreal forests

may differ in important ways from that described for populations in the

North (see also Chapter 5). If so, such differences would have important

implications for lynx conservation in the contiguous United States.

In this chapter, we review existing information on lynx ecology in boreal

forests south of the Polar ecoregions (Bailey 1998) and compare and contrast

these findings to those presented in Chapter 9 on lynx ecology in northern

boreal forests. Information considered here includes all studies of lynx

ecology in the contiguous United States, as well as those conducted in

Humid Temperate and Dry ecoregions in the southern Canadian Rocky

Mountains (Chapter 12) and on Cape Breton Island in Nova Scotia (Parker

1981; Parker et al. 1983).

Food Habits and Relationships With Prey

Throughout North America, the distribution of lynx is virtually coincident

with the distribution of snowshoe hares (McCord and Cardoza 1984; Bittner

and Rongstad 1984) and, within that range, lynx tend to occur in habitats

where snowshoe hares are most abundant (Koehler and Aubry 1994; Chapter

9). In northern regions, lynx prey almost exclusively on snowshoe hares

during winter; however, during snow-free seasons or when hares are at low

abundances, alternative prey, especially red squirrels, are taken in higher

proportions (Chapter 9). Although limited information from studies in the

western mountains indicates a similar predominance of snowshoe hares in the

diet of lynx (Koehler and Aubry 1994), hare densities are typically low in

southern boreal forests compared to northern regions (Chapters 6 and 7).

There have been few studies of lynx food habits in southern boreal forests

(Table 13.1). Among 29 lynx scats collected in north-central Washington

during winter and summer from 1985 to 1987, 23 (79%) contained snowshoe
Chapter 13—Aubry

376

Table 13.1—Frequency of occurrence (%) of prey items in diets of Canada lynx in North America. Contents of scats, stomachs, and

digestive tracts may contain more than one prey item; thus, total percentages for these analyses may exceed 100%.

Other Grouse

Snowshoe Red small and Other

Study area hare squirrel mammals ptarmigan birds Ungulates Other

Southern boreal forests

North-central Washington; annual 79 24 3 7

(n = 29 scats)a

Southern Canadian Rocky Mountains; winter 52 30 8 3 1 6

(n = 137 kills found during snow tracking)b

Cape Breton Island, Nova Scotia; winter 97 1 3 3 5

(n = 75 stomachs)c

Cape Breton Island, Nova Scotia; winter 93 7425

(n = 55 scats)c

Cape Breton Island, Nova Scotia; summer 70 4 4-5 1 6-7 9 <1

(n = 441 scats)c

Northern boreal forests during low snowshoe hare densities

Central Alberta; winter 35 12 33 6637

(n = 338 items found in stomachs)d

Central Alberta; winter 56 7 15 22

(n = 54 kills found during snow tracking)e

Southwestern Yukon; winter 20 64 13 1 1

(n = 280 kills found during snow tracking)f

Southwestern Yukon; winter 79 50 21 7

(n = 101 scats)f

Kenai Peninsula, Alaska; winter 91 15 13 10 1 7 6

(n = 161 scats)g

Kenai Peninsula, Alaska; winter 63 19 13 6

(n = 16 kills found during snow tracking)g

Kenai Peninsula, Alaska; summer 67 50 29 12 10 10

(n = 42 scats)g

Northern boreal forests during high snowshoe hare densities

Central Alberta; winter 90 5 3 1

(n = 72 items found in stomachs)d

Central Alberta; winter 86 3 6 6

(n = 35 kills found during snow tracking)e

Southwestern Yukon; winter 89 3 3 4 1

(n = 222 kills found during snow tracking)f

Southwestern Yukon; winter 92 5 16 20

(n = 239 scats)f

Kenai Peninsula, Alaska; winter 100 5 7 10

(n = 41 scats)h

Alberta and Northwest Territories; winter 79 2 10 10 13 12 2

(n = 52 digestive tracts)i

Alberta and Northwest Territories; summer 52 9 39 8 26

(n = 23 digestive tracts)i

a

Koehler 1990; bApps Chapter 12; cParker et al. 1983; dBrand and Keith 1979; eBrand et al. 1976; fO’Donoghue et al. 1998 (data on frequency of occurrence in scats

provided by M. O’Donoghue); g

Staples 1995, unpublished; hKesterson 1988, unpublished; ivan Zyll de Jong 1966
377

Aubry—Chapter 13

hare and seven (24%) contained red squirrels; remains of both species were

also found at den sites (Koehler 1990). Using Koehler’s (1990) pellet plot data,

Hodges (Chapter 7) estimated fall snowshoe hare densities on the study area

at 0.09-1.79 hares/ha. Snow tracking along 20.5 km of lynx trails detected

eight chases of prey by lynx; snowshoe hares were chased six times and

captured twice, whereas red squirrels were unsuccessfully chased twice. Lynx

had been observed capturing red squirrels in the study area previously,

however (Brittell et al. 1989, unpublished). Other prey items, including

remains of a deer fawn, adult deer, and white-footed mouse, were each

found in only one scat.

During snow-tracking studies from 1996 to 1998, Apps (Chapter 12)

documented 137 lynx kills during winter in the southern Canadian Rocky

Mountains. Prey species included 71 (52%) snowshoe hares, 41 (30%) red

squirrels, nine (5%) northern flying squirrels, five (3%) martens, voles, and

grouse, one northern flicker, and five “unknown.” Snowshoe hare densities

in the study area were estimated at 0.01-0.47 hares/ha. A radio-marked male

lynx scavenged a road-killed mule deer for several days before being driven

off by wolves. The only food habits information collected during snow-free

months was the observation that a radio-marked juvenile male hunted

meadow voles on seven occasions. There are several reported observations

of lynx hunting ground squirrels in southern boreal forests. In Wyoming, a

male lynx was seen hunting Wyoming ground squirrels in sagebrush habitat

in late April, and a female was observed hunting similarly in early July

(Chapter 11). Barash (1971) observed two adult and one juvenile lynx

cooperatively hunting Columbian ground squirrels during summer in

Glacier National Park, Montana.

In contrast to findings from western montane regions, studies in Nova

Scotia (Parker 1981; Parker et al. 1983) indicated that alternative prey were

relatively unimportant in lynx diets during winter. However, snowshoe

hares occurred in the study area at densities higher than most recorded in the

taiga (5.8-10 hares/ha; see Chapter 6), suggesting that food habits of lynx in

Nova Scotia may not be comparable to those of other lynx populations in

southern boreal forests, where hares occur at substantially lower densities

(Chapter 7). In addition, although southern red-backed voles, masked

shrews, ruffed grouse, and spruce grouse were all considered to be common

in the study area, red squirrels were relatively rare. In “advanced” successional stages (16-30 years after cutting), hare densities declined from 10

hares/ha in 1977 to 1.7 hares/ha in 1979. Nevertheless, for all years combined, snowshoe hares were present in 97% of stomachs examined (n = 75)

and 93% of scats (n = 55) collected during winter; red squirrels were found

in only one stomach (Parker et al. 1983). Among 200 chases detected during
Chapter 13—Aubry

378

snow tracking in the winter of 1977-1978, 198 were of snowshoe hares that

resulted in 34 kills; the remaining two chases were of ruffed grouse (Parker

1981). During summer, however, alternative prey were more important in the

diet; only 70% of scats examined (n = 441) contained remains of snowshoe hare.

Other foods of lynx during summer included birds, small mammals, and carrion.

Very few studies of lynx food habits during snow-free periods have been

conducted in North America (Table 13.1; Chapter 9). Based on available

information, however, there appear to be few essential differences in the

food habits of the lynx throughout its range. Regardless of geographic

location, lynx diets are dominated by snowshoe hares during all seasons of

the year. If hares are abundant, lynx subsist almost exclusively on them

during winter. In the taiga, alternative prey are important in the winter

during lows in the snowshoe hare cycle (Table 13.1; Chapter 9). During

summer in northern boreal forests, alternative prey are more abundant in

lynx diets regardless of the status of local snowshoe hare populations (Table

13.1). It is unclear, however, whether this shift is related to increased

availability of alternative prey or to decreased hunting success on hares

during snow-free periods (Chapter 9). Although data are scarce, the red

squirrel appears to be the most important alternative prey species throughout the range of lynx, with grouse, small mammals, and carrion of lesser

importance in the diet. In southern boreal forests, limited data suggest that

because snowshoe hares typically occur at low densities (Chapter 7), alternative prey may always be important components of lynx diets, especially

in the western mountains.

Habitat Relationships

Historical and current records show that lynx occur primarily within

Douglas-fir, spruce-fir, and fir-hemlock forests at elevations ranging from

1,500 to 2,000 m in the western mountains, boreal forest types at 250-500 m in

the Great Lakes region, and mixed forest-coniferous forest-high tundra vegetation types at 250-750 m in the northeastern United States (Chapter 8).

However, lynx habitat relationships within these forest types have been

studied in only a few locations. Studies that documented habitat use with

radiotelemetry have monitored relatively few animals: three lynx in Nova

Scotia (Parker et al. 1983), five and two in Montana (Smith 1984, unpublished;

Koehler et al. 1979, respectively), and seven in Washington (Koehler 1990).

Brittell et al. (1989, unpublished) reported forest cover type and topographic

attributes for home range areas of 23 radio-marked lynx in Washington, but

such analyses do not provide reliable information on habitat selection.

However, McKelvey et al.’s (Chapter 10) reanalysis of telemetry data from
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Aubry—Chapter 13

Washington (Brittell et al. 1989, unpublished; Koehler 1990) has provided

new information on selection of forest habitats and topographic features by

lynx in that region. Intensive snow-tracking studies comparing habitat use

with availability have only been conducted in Nova Scotia (Parker 1981;

192 km of trails).

Associations With Forest Types

In the western mountains, Canada lynx occur predominantly within

boreal forests (Chapter 8; Koehler and Aubry 1994); elevational zones for

these forests vary with latitude, ranging from an average of about 1,400 m in

Washington to 2,700 m in Colorado (Chapter 3). The lynx study area in the

southern Canadian Rockies (Chapter 12) is dominated by Engelmann sprucewhite spruce and subalpine fir forests occurring at elevations between 1,200

and 3,000 m; lodgepole pine is present as a seral species. The area where lynx

are being studied in western Montana (Chapter 11) ranges from 1,200 to

2,100 m in elevation and is dominated by Douglas-fir, western larch, and

lodgepole pine at lower elevations, and subalpine fir, whitebark pine, and

Engelmann spruce at upper elevations. Habitat used by five radio-marked

lynx in Montana was described by Smith (1984, unpublished) as occurring

within subalpine fir forest associations. The lynx study area in western

Wyoming (Chapter 11) is located at 2,600-2,750 m in elevation, where pure

stands of lodgepole pine occur on drier sites and spruce-fir is generally

restricted to north-facing slopes; south-facing slopes are dominated by

sagebrush and wheat grass communities. Halfpenny et al. (1989, unpublished) reported lynx above 2,700 m along edges of dense spruce-fir stands

near parklands and aspen stands in Colorado.

Forest cover types selected by lynx in the Cascade Range of north-central

Washington (Chapter 10) are similar to those used by lynx in the Rocky

Mountains. In the Cascades, lynx selected lodgepole pine cover types at

elevations ranging from 1,370 to 2,130 m. During winter, however, lynx

shifted their activities to elevations below 1,520 m, avoiding those above

1,980 m. During summer, lynx selected northeast aspects, but whether lynx

selected these sites for thermal or other features is not known (Chapter 10).

Douglas-fir, ponderosa pine, and western larch stands were used less than

expected by lynx.

Lynx are forest dwellers, but historical records (Chapter 8) and recent

studies (Chapter 11) show that lynx occur occasionally in non-forested areas,

such as shrub-steppe habitats in eastern Montana, Wyoming, and Idaho.

However, such observations appear to represent either transient individuals

or resident animals searching opportunistically for prey.
Chapter 13—Aubry

380

Associations of lynx occurrences and forest cover types in the Northeast

described in Chapter 8 fit closely with published descriptions of lynx habitat.

On Cape Breton Island in Nova Scotia, lynx occupied forested habitats at

elevations from 360 to 390 m, where the climax vegetation consisted of

balsam fir and black spruce bogs, and alder-bordered streams. Lynx also

frequented open spruce-dominated bogs, where multiple tracks and evidence

of play activity suggested that such sites may be used for resting and

socializing (Parker 1981). Most trapping records from the White Mountains

of New Hampshire during the 1960s were from elevations over 1,000 m in

forest types dominated by hardwoods and spruce-balsam fir (Litvaitis et al.

1991). Brocke (1982) speculated that the historic distribution of lynx in the

Adirondack Mountains of northern New York was associated with sprucefir forest receiving heavy snowfall at elevations over 900 m. Descriptions of

habitat used by lynx in the Great Lakes states are generally anecdotal in

nature and provide few insights about lynx ecology in that region.

Forest types occupied by lynx in the taiga are described as boreal, subboreal, and montane forests containing snowshoe hares; lynx are absent or

uncommon, however, in wet, coastal forests of western Canada and Alaska

(Chapter 9). These descriptions of broad forest associations are similar to

those reported from southern boreal forests. In the contiguous United States,

the range of lynx is essentially coincident with the distribution of boreal

forest in the western mountains and northeastern United States (Chapters 3

and 8; McCord and Cardoza 1984); as in Canada and Alaska, lynx are absent

from the dense, wet forests along the Pacific coast.

Stand-Scale Habitat Associations

Habitat use by lynx at the stand scale has been studied with both snow

tracking and radiotelemetry in many areas of the taiga (Chapter 9), but there

are few studies of this kind in southern boreal forests. In Montana, Koehler

et al. (1979) reported that 26 of 29 lynx locations for two radio-marked lynx

were in densely stocked lodgepole pine stands where hares were abundant;

the remainder were in Douglas-fir and western larch stands. Selection by

lynx of dense lodgepole pine stands containing high numbers of snowshoe

hares has also been demonstrated in north-central Washington (Koehler

1990). Lodgepole pine is a seral, fire-dependent species in boreal forests of

the western mountains (Chapter 3) and appears to be preferred by lynx in

northern portions of the Cascade Range and Rocky Mountains (Koehler et al.

1979; Koehler 1990; Chapter 10). Average fire frequency in the North

Cascades of Washington is 109-137 years (Chapter 3); but within the 1,800

km2

 study area in north-central Washington, fires burned areas >2,500 ha

(more than half of an average female’s home range) at more frequent
381

Aubry—Chapter 13

intervals (late 1800s, 1929, 1972, and 1994; Okanogan National Forest,

unpublished). However, whether the persistence of lynx populations in this

area (Chapter 8) is related to relatively short fire-return intervals is not

known. Differences in fire ecology between northern and southern boreal

forests and resulting implications for management of lynx habitat are

discussed in detail in Chapters 3 and 15.

Early successional forests appear to be important for lynx in Nova Scotia.

Snow tracking (Parker 1981) and radiotelemetry (Parker et al. 1983) studies

on Cape Breton Island indicated that lynx selected early (5-15 years old) and

advanced (16-30 years old) successional forests, followed by open mature

conifer and open black spruce bog habitat types. Closed mature forests (both

conifer and mixed conifer-hardwood), open mature mixed forests, riparian

alder swales, and frozen lakes were used less than expected. During summer, use of successional habitat decreased and use of mature conifer habitat

increased (Parker et al. 1983).

Parker (1981) found that lynx most strongly selected advanced successional forests, where hares were most abundant. However, among other

habitat types, he found no consistent correlation between habitat selection

and the relative abundance of snowshoe hares. Mature, mixed coniferhardwood forests with relatively high hare populations were selected

against, whereas open, mature coniferous forests with relatively few hares

were used more often than expected. Parker speculated that factors other

than prey abundance may influence habitat selection by lynx and suggested

that lynx use open mature conifer forests, where hares are relatively scarce,

for cover and travel. Parker also speculated that lynx use early and advanced

successional stages, where hares are abundant, for hunting.

Koehler and Brittell (1990) described similar habitat use in north-central

Washington; snow tracking revealed that lynx generally traveled in straight,

non-meandering paths in mature forest stands with sparse understory

cover, indicating that lynx were using stands where hares were scarce but

not actively hunting in them. Such forest conditions were identified as

“travel habitat” that provided security cover when lynx move between

foraging or den sites (Koehler and Brittell 1990). From snow tracking,

Koehler (1990) found that lynx traveled the edges of meadows but only

crossed meadows where openings were less than 100 m wide. During

winter, lynx were also observed traveling through silviculturally thinned

stands with 420-640 trees/ha (Koehler 1990). From these observations,

Koehler and Brittell (1990) speculated that lynx avoid open areas where

security cover is lacking but that 420-640 trees/ha could provide adequate

travel cover; during snow-free periods, shrub habitats may also be used for

travel by lynx.
Chapter 13—Aubry

382

Koehler (1990) located four maternal den sites used by two females in

north-central Washington, all of which were located on north-facing slopes

in mature (>250 years) forest stands with an overstory of spruce, subalpine

fir, and lodgepole pine that contained an average of 40 logs/50 m. A

maternal den in Wyoming was located in a mature subalpine fir stand that

had relatively dense understory cover from large woody debris and saplings

(Chapter 11).

In the taiga, lynx typically prefer forested stands containing the densest

populations of snowshoe hares; such habitats are generally represented by

older (>20 years) regenerating stands of both natural and human origin, or

mature stands with a dense understory (Chapter 9). However, even if hares

are abundant, lynx generally do not occur in forested stands with extremely

dense understories or in shrub-dominated sites, probably because lynx

cannot hunt effectively in such stands (Chapter 9). Tangles of blowdown in

mature forests are used for den sites, but recent work in the Yukon demonstrates that lynx may den in younger, regenerating stands (30 years old)

containing blowdown or structures that provide similar cover, such as roots

and dense vegetation (Chapter 9). The critical habitat component for maternal

dens appears to be understory structure that provides security and thermal

cover for kittens. Suitable understory structures are generally found in

unmanaged, mature forest stands, but may also occur in early successional

forests where windthrow and snags are present.

Although lynx in southern boreal regions generally select forested stands

having abundant snowshoe hare populations, they also occasionally use

habitats with relatively low numbers of hares. In contrast to findings from

the taiga, habitats used by lynx in the southern portion of their range may

include those that are used primarily for traveling between foraging sites

and others that are used primarily for hunting (Koehler and Brittell 1990;

Parker 1981). Although these speculations are based on relatively few data,

habitats that contain abundant snowshoe hare populations in southern

boreal forests may be more patchy and disjunct in distribution (Dolbeer and

Clark 1975; Wolff 1980, 1982), forcing lynx to travel among foraging patches

to find adequate prey. Further research on habitat use relative to the

abundance of snowshoe hares is needed to evaluate this hypothesis.

Spatial Organization

Home Range

Ten studies (Brainerd 1985, unpublished; Brittell et al. 1989, unpublished;

Koehler et al. 1979; Koehler 1990; Mech 1980; Parker et al. 1983; Smith 1984,

unpublished; Chapters 11 [two studies] and 12) have documented spatial
383

Aubry—Chapter 13

Table 13.2—Mean home range sizes of Canada lynx in North America.

Mean home Calculation method

Location range size (km2) and season Source

Southern boreal forests

Southern Canadian 277 + 71a

 (male; n = 3) 95% Minimum Convex Chapter 12

Rocky Mountains 135 + 124 (female; n = 3) Polygon (MCP), annual

North-central Washington 49 + 25 (male; n = 8) 100% MCP, annual Brittell et al. 1989,

37 + 26 (female; n = 7) unpublished

North-central Washington 69 + 28 (male; n = 5) 100% MCP, annual Koehler 1990

39 + 2 (female; n = 2)

North-central Montana 36 (male; n = 1) 100% MCP, Koehler et al. 1979

March-October

North-central Montana 133 (male and female; n = 4) 100% MCP, annual Smith 1984, unpublished

North-central Montana 122 (male; n = 6) 100% MCP, annual Brainerd 1985, unpublished

43 (female; n = 3)

North-central Montana 238 + 99 (male; n = 4) 95% MCP, annual Chapter 11

115 + 50 (female; n = 2)

West-central Wyoming 90 (male; n = 1) 95% MCP, winter Chapter 11

66 (female; n = 1)

West-central Wyoming 91 (male; n = 1) 95% MCP, summer Chapter 11

68 (female; n = 1)

Northeastern Minnesota 194 (n = 2) 100% MCP, annual Mech 1980

87 (n = 2)

Cape Breton Island, 26 (male; n = 1) 100% MCPb

, summer Parker et al. 1983

Nova Scotia 32 (female; n = 1)

Cape Breton Island, 12 (male; n = 1) 100% MCPb

, winter Parker et al. 1983

Nova Scotia 19 (female; n = 1)

Northern boreal forests during low snowshoe hare densities

Southwestern Manitoba 221 (male; n = 1) 100% MCPb

, annual Carbyn and Patriquin 1983

158 (female; n = 2)

South-central Northwest 26 + 5 (male; n = 8) 95% MCP, annual, 1991-92 Poole 1994

Territories 44 + 14 (male; n = 2) 95% MCP, annual, 1992-93

25 + 5 (female; n = 8) 95% MCP, annual, 1991-92

63 + 28 (female; n = 2) 95% MCP, annual, 1992-93 (con.)

organization of resident lynx populations in southern regions using radiotelemetry, but most were short-duration studies involving relatively few

individuals (n = 1-8; Table 13.2). Home range studies vary considerably in

design, implementation, and analysis resulting in many potential sources of

bias. These include differences in the sex, age, and reproductive status of

study animals, the status of prey populations, season of study, duration of

study, sample size, sampling technique, and analytical approach, among

others. Consequently, comparisons among studies are problematic and

results should be interpreted cautiously.
Chapter 13—Aubry

384

South-central Yukon 119 + 189 (male; n = 6) 95% MCP, annual, 1992-93 Slough and Mowat 1996

266 + 106 (male; n = 2) 95% MCP, annual, 1993-94

23 + 7 (female; n = 10) 95% MCP, annual, 1992-93

507 + 297 (female; n = 4) 95% MCP, annual, 1993-94

Southwestern Yukon 28 + 5 (male; n = 4) 95% MCP, annual, 1992-93 M. O’Donoghue,

35 (male; n = 1) 95% MCP, annual, 1993-94 personal communication

40 + 11 (male; n = 2) 95% MCP, annual, 1994-95

24 + 16 (female; n = 3) 95% MCP, annual, 1992-93

34 (female; n = 1) 95% MCP, annual, 1993-94

45 (female; n = 2) 95% MCP, annual, 1994-95

Interior Alaska 160 + 38 (male; n = 5) 95% MCP, annual, 1991-92 Perham 1995, unpublished

183 + 66 (male; n = 6) 95% MCP, annual, 1992-93

30 + 9 (female; n = 3) 95% MCP, annual, 1991-92

47 + 23 (female; n = 23) 95% MCP, annual, 1992-93

Northern boreal forests during high snowshoe hare densities

South-central Northwest 36 + 8 (male; n = 7) 95% MCP, annual, 1989-90 Poole 1994

Territories 17 + 2 (male; n = 13) 95% MCP, annual, 1990-91

21 + 6 (female; n = 4) 95% MCP, annual, 1989-90

18 + 3 (female; n = 10) 95% MCP, annual, 1990-91

Southwestern Yukon 14 + 1 (male; n = 2) 90% MCP, annual Ward and Krebs 1985

13 + 7 (female; n = 2)

South-central Yukon 48 + 26 (male; n = 7) 95% MCP, annual, 1989-90 Slough and Mowat 1996

44 + 23 (male; n = 12) 95% MCP, annual, 1990-91

20 + 9 (female; n = 4) 95% MCP, annual, 1989-90

13 + 4 (female; n = 13) 95% MCP, annual, 1990-91

Southwestern Yukon 24 + 9 (male; n = 7) 95% MCP, annual, 1990-91 M. O’Donoghue,

39 + 51 (male; n = 7) 95% MCP, annual, 1991-92 personal communication

17 + 14 (female; n = 4) 95% MCP, annual, 1990-91

17 + 7 (female; n = 4) 95% MCP, annual, 1991-92

Kenai Peninsula, Alaska 225 + 220 (male; n = 6) 100% MCPb

, annual Kesterson 1988,

107 + 53 (female; n = 8) unpublished

a

Standard deviation, if available from source.

b

Proportion of points used not specified; assumed to be 100%.

Table 13.2—(Con.)

Mean home Calculation method

Location range size (km2) and season Source

In general, lynx home ranges in southern boreal forests are large compared

to those reported from the taiga during times of high snowshoe hare densities

(Table 13.2). Using only annual home range estimates from studies with

sample sizes >3 listed in Table 13.2, the average mean home range size for

males is 151 km2

 in southern boreal forests, 103 km2 in the taiga during low

hare densities, and 62 km2

 in the taiga during high hare densities. The

average mean home range size for females in southern boreal forests is

72 km2

, whereas in the taiga, it is 109 km2 during hare population lows and

30 km2

 during hare highs.
385

Aubry—Chapter 13

Use of centrally located “core” home ranges, where activities were concentrated, was reported from north-central Washington and Nova Scotia (Brittell

et al. 1989, unpublished; Parker et al. 1983). In most studies, males used

vacated territories when a neighboring male died or emigrated, and male

ranges overlapped extensively with those of one to three females (Brittell et

al. 1989, unpublished; Koehler 1990; Parker et al. 1983; Chapter 11). In

Montana, home ranges of juveniles overlapped those of adults regardless of

sex (Brainerd 1985, unpublished) but, in Nova Scotia, the home range of a

juvenile female was adjacent to those of an adult male and an adult female

during both winter and summer (Parker et al. 1983). Although factors

affecting the selection of home ranges at the landscape scale are largely

unknown, home range boundaries in Washington generally occurred along

ridges and major rivers (G. Koehler, unpublished); major highways may also

define home range boundaries (Chapter 12).

Few studies have investigated seasonal changes in home range use, and

results are inconsistent (Table 13.2). In Wyoming, home ranges for both the

male and female lynx were similar in size during winter and summer. In

Montana, Brainerd (1985, unpublished) suggested that summer home ranges

were much smaller than annual home ranges for both males and females,

and Smith (1984, unpublished) reported the largest home ranges during the

spring breeding season. However, home ranges for both the male and female

lynx studied in Nova Scotia were smaller during winter than in summer, and

Koehler (1990) reported that lynx in north-central Washington occupied the

same home ranges for two or more consecutive years.

As reported for lynx populations in the taiga (Chapter 9), estimated home

range sizes for lynx in southern boreal forests vary substantially and appear

to be determined by numerous factors. However, relatively large home

ranges appear to be characteristic of southern lynx populations, especially in

the western mountains (Table 13.2). Both male and female home ranges in

southern boreal forests are comparable to those occurring in the taiga during

times of hare scarcity, and are substantially larger than those reported from

the taiga during high snowshoe hare densities. In the north, lynx maintain

similar-sized home ranges during most phases of the hare cycle but will

expand home ranges when hare populations decline to low levels (Chapter 9).

In most southern boreal forests, reported hare densities are similar to those

occurring during population lows in the north (Chapters 6 and 7; but see

Parker et al. 1983). Thus, as in the north after hare populations have crashed,

lynx in southern boreal regions probably occupy relatively large home

ranges in response to low-density hare populations.
Chapter 13—Aubry

386

Exploratory Movements

Occasionally, lynx in southern populations make what appear to be

“exploratory” movements in which they make long-distance movements

beyond their normal home range boundaries and subsequently return to

their home range. Among eight lynx (six males, two females) studied in

Montana, one juvenile and three adult males made exploratory movements

ranging from 17 to 38 km in straight-line distance (Chapter 11). The duration

of exploratory movements varied from one week to several months. All

adult movements were initiated in July, but the juvenile made two exploratory movements; one between 18 March and 2 April and a second from

about 21 July to 20 August. In the Wyoming study, an adult male left his

home range in mid-June and returned in early September and an adult

female left hers in early July and returned by early August; the geographic

extent of these movements is unknown, however (Chapter 11). In the

southern Canadian Rockies, a juvenile female made an exploratory movement of 38 km in straight-line distance in the fall prior to dispersing (C. Apps,

personal communication).

Exploratory movements of this kind have not been reported from the taiga

(Chapter 9). We speculate that in montane boreal forests, the distribution of

high-quality lynx habitat is patchy and fragmented due to high amounts of

topographic relief and variation in habitat conditions resulting from natural

disturbance processes (Chapter 3). Under such conditions, dispersal in

different directions would be expected to have varying probabilities of

success. Thus, in montane systems with high amounts of spatial heterogeneity, dispersal success may be enhanced by exploratory movements to locate

suitable habitat.

Dispersal

Dispersal is the movement of a organism (either juvenile or adult) from a

place of residence to its first or subsequent breeding site (Shields 1987). Data

on lynx dispersal in southern boreal forests are scanty and anecdotal in

nature, and no successful dispersals (i.e., where a lynx has bred after moving

to a new location) have been reported from southern boreal forests. Consequently, presumed dispersals may simply represent long-distance movements that were cut short when the animal died. Between late April and

November, a female lynx dispersed a distance of 325 km from Montana to

British Columbia, where it was trapped (Brainerd 1985, unpublished). A

male lynx dispersed 97 km in Montana before it was trapped (Smith 1984,

unpublished). In north-central Washington, an adult male and female lynx

that were both resident in the study area for at least a year dispersed north
387

Aubry—Chapter 13

into British Columbia, where they were trapped 616 and 80 km north of the

study area, respectively (Brittell et al. 1989, unpublished; J. Brittell, personal

communication). Apps (Chapter 12) described three dispersal movements

in the southern Canadian Rockies, including a juvenile male that dispersed

44 km in March and then remained in the new location for 31 days before his

death; a juvenile female that moved 17 km over three days in March and

occupied the new area for 15 days before her death; and a juvenile female that

dispersed 55 km before contact was lost. Mech (1977) reported a 483-km

movement by a female lynx that was radio-marked in northeastern Minnesota in 1974 and trapped in western Ontario in 1977.

Dispersal distances reported from southern boreal forests are comparable

to those in the taiga, where movements >100 km are considered typical

(Chapter 9). Apps (Chapter 12) suggested that steep terrain and the

Trans-Canada Highway may affect dispersal movements. However, four of

five lynx that dispersed in Montana, Washington, and Minnesota (Brainerd

1985, unpublished; Brittell et al. 1989, unpublished; Mech 1980; Smith 1984,

unpublished) crossed either two- or four-lane highways and major rivers

before they were trapped. Mowat et al. (Chapter 9) also reported that

dispersing lynx in northern forests often crossed roads and large rivers and

lakes, even during the snow-free season.

Demographic Characteristics

The most reliable information available on demographic characteristics

for southern lynx populations comes from the successive field studies

conducted by Brittell et al. (1989, unpublished) and Koehler (1990) in northcentral Washington in the 1980s. Brittell et al. (1989, unpublished) monitored

a total of 23 lynx with radiotelemetry in north-central Washington from 1980

to 1983. Among 12 resident females, none were known to have given birth

to kittens during the course of the study. However, snow tracking indicated

that an unmarked female was accompanied by two kittens in the winter of

1980-1981 and again in 1982-1983; no tracks of kittens were found in 1981-

1982. Snow tracking was not conducted in the winter of 1983-1984 but, in

August 1984 after field work was terminated, kittens were observed on two

separate occasions: one radio-marked and one unmarked female were each

accompanied by two kittens in or near the study area. Thus, from 1980 to

1984 at least eight kittens (mean litter size = two) were produced in a

population estimated to contain 23 resident lynx each year of the three-year

study. The study area was 1,161 km2 in extent, resulting in an estimated

density of 2.0 lynx/100 km2

. Among radio-marked lynx, 12% were identified

as transients; thus, total lynx density, including kittens and transients, was
Chapter 13—Aubry

388

estimated at 2.4 lynx/100 km2. During the course of this study, three females

and one male died from natural causes; the mean annual mortality rate for

radio-marked lynx was estimated at 11% (range = 0-29%).

Koehler (1990) continued radiotelemetry work on Brittell et al.’s study area

from 1985 to 1987, monitoring a total of seven lynx (five males, two females).

During both years of the study, 15 adults were known to occupy the central

portion of the study area (648 km2

), at an estimated density of 2.3 adults/100

km2

. No kittens were observed in the study area during winter 1985-1986,

but in 1986-1987, snow tracking indicated that four kittens were present in

the study area, resulting in an estimated mean annual density for adults and

kittens of 2.6 lynx/100 km2

. In 1986, both radio-marked females had litters

of three and four kittens each. Both females gave birth again in 1987, one to

a single kitten and the other to at least one kitten (actual litter size could not

be determined); thus, mean litter size over both years of the study was at least

2.7 kittens. In addition, an uncollared female was accompanied by three

kittens in the winter of 1986-1987. From snow tracking in the winters of 1986-

1987 and 1987-1988, Koehler determined that only one of eight kittens from

the three litters of known size survived to the following winter, resulting in

an estimated kitten mortality rate of 88%. Two radio-marked adult males

died during the course of the study, one from predation and another from

unknown causes. Annual mortality rates for radio-marked adult lynx were

27% in 1986 and 0% in 1987. Thus, the estimated mortality rate for kittens

was six to seven times higher than the mean mortality rate for radio-marked

adults.

Both reproductive rates and kitten survival rates appear to be similarly low

in other regions of the southern boreal forest where lynx have been studied.

None of three adult female lynx captured by Apps (Chapter 12) in the

southern Canadian Rockies in November of 1997 or 1998 were travelling

with kittens; however, one radio-marked female was observed with a kitten

in August 1998. Four unmarked family groups were detected in the study

area (>3,000 km2

) in 1997, each of which contained two kittens. Both kittens

(one male, one female) from one of the family groups were subsequently

radio-marked, but neither survived to the spring of 1998. All resident adults

survived through both years of the study, but a dispersing female kitten and

a transient juvenile male died of starvation in the spring of 1998; a male kitten

was killed by a predator in December 1997. None of the three adult female

lynx monitored with radiotelemetry by Brainerd (1985, unpublished) in

Montana from 1982 to 1984 gave birth to kittens. Only one out of four female

lynx monitored during 1998 in Montana was known to have given birth

(Chapter 11); after radio contact with this female was lost during the

breeding season, she was relocated in late September 1998 with two kittens.

The adult female radio-marked in Wyoming (Chapter 11) gave birth to a
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Aubry—Chapter 13

litter of four kittens (two males, two females) on about 27 May; all four were

still alive on 14 June when they were ear-tagged, but none survived into the

winter.

Other information on productivity in lynx populations in southern boreal

forests comes from carcass studies. Brainerd (1985, unpublished) examined

placental scars and corpora lutea in 18 female lynx carcasses from Montana

ranging in age from 1.5 to 9.5 years. Based on placental scars, the average

litter size increased with age: yearlings had a mean litter size of 1.75 (range =

1-3), whereas mean litter size for adults was 3.25 (range = 1-5). Ovulation rates

were also higher for adults, increasing from 3.22 (range = 2-5) for yearlings,

to 5.33 (range = 2-9) for adults. The pregnancy rate for adults was 100%,

whereas only 44.4% of uteri from yearlings contained placental scars.

Parker et al. (1983) examined 154 lynx carcasses obtained from trappers in

Nova Scotia over three winters: 1977-1978 (n = 42), 1978-1979 (n = 57), and

1979-1980 (n = 55). The oldest lynx were 11 years old, but <6% of the sample

was older than six years in any year. Over the three years of the study, the

percentage of kittens in the sample declined from 29% to 9%, and 2%. Based

on counts of placental scars, mean litter size was 3.2 for yearlings and 3.6 for

adults; neither differed significantly among years. Overall pregnancy rates

were 68% for adults and 27% for yearlings. However, yearling pregnancy

rates declined from 67% in 1977-1978 to 29% in 1978-1979 and 0% in 1979-

1980, whereas adult pregnancy rates only declined from 75% to 64%.

Declines in the overall breeding and recruitment rates, as well as the

reproductive success of yearlings, was attributed to a dramatic decrease

(about six-fold in the best habitats) in the abundance of snowshoe hares over

the course of the study (Parker et al. 1983).

With few exceptions, demographic parameters reported from southern

boreal forests are comparable to those occurring in the taiga during times of

hare scarcity. The low in-utero litter sizes (3.25-3.6), low yearling pregnancy

rates (27-44.4%), low yearling litter sizes (1.75-3.2), low kitten production,

high kitten mortality rate (88%), and low lynx densities (Table 13.3) reported

from southern populations are all characteristic of northern populations

during hare lows. In the North, peak lynx densities vary from eight to

45 lynx/100 km2

 depending on habitat conditions, but drop to <3 lynx/100

km2

 during hare population lows, regardless of habitat quality (Chapter 9).

Density estimates for lynx in north-central Washington ranged from 2.0 to

2.6 lynx/100 km2

 and remained relatively constant over the course of the

seven-year study (Brittell et al. 1989, unpublished; Koehler 1990). The

apparent stability of this low-density population has led to speculation that,

because hare populations also occur at low levels in most southern boreal

forests, lynx populations in the western mountains may not exhibit the

cyclic fluctuations characterisitic of northern populations (Koehler and
Chapter 13—Aubry

390

Aubry 1994). However, we caution that data bearing on this hypothesis are

extremely limited; furthermore, a recent review of snowshoe hare density

data in southern boreal regions (Chapter 7) and lynx trapping records

from Washington, Montana, and New Hampshire (Chapter 8) suggest

that both snowshoe hare and lynx populations may fluctuate more in

number in the south than believed previously. Whether observed patterns reflect changes in resident lynx populations or immigrations from

other areas, however, is unknown (Chapter 8). Understanding the nature of

lynx population dynamics in southern boreal forests is a critical research

need.

Human Impacts

Trapping

Little is known about the effects of trapping or shooting mortality on lynx

populations in southern boreal forests. However, in recent years, concern

over the conservation status of lynx throughout the contiguous United

Table 13.3—Densities of Canada lynx populations in North America.

Lynx density

Study area (lynx/100 km2) Source

Southern boreal forests

North-central Washington 2 Brittell et al. 1989, unpublished

North-central Washington 3 Koehler 1990

Cape Breton Island, Nova Scotia 20a Parker et al. 1983

Northern boreal forests during low snowshoe hare densities

Central Alberta 2 Nellis et al. 1972,

Brand et al. 1976

South-central Northwest Territories 3 Poole 1994

South-central Yukon 3 Slough and Mowat 1996

Southwestern Yukon 2 O’Donoghue et al. 1997

Kenai Peninsula, Alaska 4b Kesterson 1988, unpublished

Interior Alaska 2-6 Stephenson 1986, unpublished

Northern boreal forests during high snowshoe hare densities

Central Alberta 10 Nellis et al. 1972,

Brand et al. 1976

South-central Northwest Territories 30 Poole 1994

South-central Yukon 45 Slough and Mowat 1996

Southwestern Yukon 17 O’Donoghue et al. 1997

Kenai Peninsula, Alaska 18 Kesterson 1988, unpublished

a

Snowshoe hare densities were comparable to those occurring during population highs in northern boreal forests.

b

Calculated from author’s description of lynx abundance.
391

Aubry—Chapter 13

States has resulted in severe restrictions on legal harvest; all states except

Montana have either given lynx complete protection or closed their trapping

season. In Montana, a statewide quota of 135 lynx was imposed in 1982; this

quota was lowered steadily until 1991, when it was reduced to two lynx per

year. Although legal harvest is no longer a conservation concern, humancaused mortality is believed to be additive in the low-density lynx populations characteristic of southern boreal forests (Koehler 1990; Table 13.3). If so,

illegal or incidental harvest could significantly reduce population numbers

of lynx in southern regions.

Roads and Trails

Roads into areas occupied by lynx may pose a threat to lynx from

incidental harvest or poaching (Koehler and Brittell 1990), increased access

during winter for competing carnivores, especially coyotes (Chapter 4),

disturbance or mortality from vehicles, and loss of habitat. Although we

know little about the indirect effects of roads or trails on lynx, none of the 89

lynx studied with radiotelemetry in Washington (Brittell et al. 1989, unpublished; Koehler 1990), Montana (Brainerd 1985, unpublished; Koehler et al.

1979; Smith 1984, unpublished; Chapter 11), Wyoming (Chapter 11), the

southern Canadian Rockies (Chapter 12), Minnesota (Mech 1980), or Nova

Scotia (Parker et al. 1983) were killed in vehicle collisions. Among 37 radiomarked animals that died during these studies, 19 were shot or trapped,

eight died of starvation, six from predation, and four from unknown natural

causes. Vehicle collisions were a significant mortality factor among 83 lynx

translocated into the Adirondack Mountains of New York from the Yukon

between 1989 and 1991; in the two years that translocated lynx were

monitored with radiotelemetry, 16 were road-killed (K. Gustafson, personal

communication). However, because translocated lynx may be especially

vulnerable to vehicle collisions (Brocke et al. 1991), the high incidence of

road-kills among lynx in this reintroduction effort is probably not representative of resident lynx populations in southern boreal forests.

In Nova Scotia, Parker (1981) found from snow tracking that road edges

and forest trails were often followed by lynx for considerable distances, and

similar observations were made during winter in Washington for roads less

than 15 m wide (Koehler and Brittell 1990). From analysis of sequential

telemetry locations for lynx in Washington, McKelvey et al. (Chapter 10)

concluded that selection or avoidance of roads could not be inferred. Roads

in the study area were of primitive standards that received little use in

summer but were frequently used by snowmobilers in winter. Ongoing research by Apps (Chapter 12) in the southern Canadian Rockies suggests,

however, that paved roads may have an influence on lynx spatial organization.
Chapter 13—Aubry

392

The 70% adaptive kernel home-range contour for two males and two

females coincided with the Trans-Canada Highway; for another male, it

coincided with a secondary highway.

Mowat et al. (Chapter 9) reported similar observations concerning roads

in northern boreal forests; lynx appeared to tolerate moderate levels of

snowmobile traffic, readily crossed highways, and established home ranges

in proximity to roads. Several studies of lynx in the taiga have been

conducted in areas of relatively dense rural human populations and agricultural development, suggesting that lynx can tolerate moderate levels of

human disturbance.

Predation and Competition

Only a few instances of predation on lynx have been reported from

southern boreal forests, but all are believed to have been by felids. Two of six

mortalities reported from ongoing radiotelemetry studies in Montana were

predation by mountain lions; both occurred during the snow-free period,

including an adult male killed in May and a juvenile male killed in October

(Chapter 11). An adult female lynx found dead in Montana in late January

during an earlier study was believed to have been killed by a mountain lion

(Koehler et al. 1979). A juvenile female lynx found dead in November in northcentral Washington was believed to have died from a bite on the top of her skull

by either a bobcat or a lynx (Brittell et al. 1989, unpublished), and an adult male

was apparently killed by an unknown predator in January (Koehler 1990). In the

southern Canadian Rockies, a male kitten was apparently killed by an unmarked male lynx in December (Chapter 12).

Cannibalism has also been reported from the taiga and generally occurs

during periods of low hare abundance. In the north, wolverine, wolves, and

coyotes have also been reported to prey on lynx (Chapter 9). Because

mountain lions do not occur in most portions of the northern boreal forest or

eastern United States (Dixon 1984), the potential effects of predation or

competition from mountain lions are unique to lynx populations in the

western mountains. Mountain lions are known to occupy high-elevation

lynx habitats during both summer and winter. In a comparative study of

habitat use by mountain lions, bobcats, and coyotes in central Idaho, Koehler

and Hornocker (1991) found that a larger proportion of mountain lion

locations (28%) were in high-elevation subalpine fir-whitebark pine habitats

during summer than either bobcat (10%) or coyote (3%) locations. They also

noted that, because of their body size, mountain lions could negotiate deeper

snows than could other predators, enabling the mountain lions to better

exploit higher elevations and mesic habitats where deep snows accumulated.
393

Aubry—Chapter 13

Mountain lions are present in lynx summer home ranges in Montana

(Chapter 11), but interactions between them have not been studied.

Lynx and bobcats are generally believed to be spatially separated by snow

depth, but several cases of these two species occupying the same area and

presumably competing with one another for food and space have been

documented in the western mountains (Smith 1984, unpublished; Brittell et

al. 1989, unpublished). Parker et al. (1983) reported that the contraction of

lynx range on Cape Breton Island in Nova Scotia was coincident with

colonization of the lowlands by bobcats; in 1983, lynx only occurred in the

highest elevation areas where bobcats had not established themselves.

However, this appears to represent the authors’ speculations only; no data

to support this statement are presented. Although coyotes are potentially

significant competitors of lynx (Chapter 4), evidence indicating that coyotes

have negatively affected lynx populations in southern boreal forests is

lacking.

Competition between lynx and other mammalian or avian predators does

not appear to strongly influence lynx populations in the taiga (Chapter 9),

probably because of the cyclic nature of snowshoe hare populations (which

mediates the effects of exploitation competition), and the relative scarcity of

many of the mammalian predators likely to compete strongly with lynx

(Chapter 4). Buskirk et al. (Chapter 4) have discussed the potential for

detrimental effects on lynx populations from increased competition with

generalist predators in landscapes disturbed and/or fragmented by human

activities. If such competition can have a significant effect on lynx populations, we speculate that it may be of particular concern in western montane

regions of the southern boreal forest. In that area, lynx are sympatric with the

three potentially strongest competitors: mountain lions (interference competition), bobcats, and coyotes (exploitation competition), all of which are

generally increasing in number (Chapter 4). However, this concern is largely

conjectural; data on the effects of sympatric carnivores on lynx populations

in southern boreal forests are rare.

Conclusions

In this chapter, we considered all lynx studies conducted south of the Polar

Ecoregions in North America (Bailey 1998), including those in Nova Scotia,

Minnesota, and the western montane regions. However, results from Nova

Scotia differed strongly in many ways from studies conducted in other

southern boreal forests (see Tables 13.1, 13.2, 13.3), and were most similar to

studies conducted in the taiga during snowshoe hare population peaks.

Results from western montane regions, where snowshoe hare populations
Chapter 13—Aubry

394

generally occurred at relatively low densities, were similar among studies,

and generally comparable to those reported from the taiga during hare

population lows. For these reasons, results from lynx studies in Nova Scotia

are probably more representative of taiga populations than those in the

western montane regions.

In general, southern lynx populations appear to be distinguished from

those in the taiga primarily by differences in the quality and distribution of

available habitat: their primary prey, the snowshoe hare, typically occurs at

very low densities and, because of differences in topography and natural

disturbance regimes, habitats containing abundant snowshoe hare populations are more patchily distributed than in the taiga. As a result, their food

habits, home range sizes, densities, and reproductive characteristics are

generally comparable to those reported for northern lynx populations

during times of hare scarcity. Differences in lynx ecology between populations in the taiga and those occurring in southern boreal forests appear to be

related primarily to the use of alternative prey species, the effect of habitat

patchiness on movements, reproduction and survival, and the potential

effects of different communities of predators and competitors on lynx

populations.

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Barash, D. P. 1971. Cooperative hunting in the lynx. Journal of Mammalogy 52:480.

Bittner, S. L. and O. J. Rongstad. 1984. Snowshoe hare and allies. Pages 146-163 in J. A.

Chapman and G. A. Feldhamer, eds. Wild mammals of North America. Johns Hopkins

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Brainerd, S. M. 1985. Reproductive ecology of bobcats and lynx in western Montana.

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Brand, C. J., L. B. Keith, and C. A. Fischer. 1976. Lynx responses to changing snowshoe hare

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Brittell, J. D., R. J. Poelker, S. J. Sweeney, and G. M. Koehler. 1989. Native cats of Washington,

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Brocke, R. H., K. A. Gustafson, and L. B. Fox. 1991. Restoration of large predators: potentials

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Carbyn, L. N. and D. Patriquin. 1983. Observations of home range sizes, movements and

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Elton, C. and M. Nicholson. 1942. The ten-year cycle in numbers of the lynx in Canada.

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Kesterson, B. A. 1988. Lynx home range and spatial organization in relation to population

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Koehler, G. M. 1990. Population and habitat characteristics of lynx and snowshoe hares in

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carnivores: american marten, fisher, lynx and wolverine in the Western United States.

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Koehler, G. M. and J. D. Brittell. 1990. Managing spruce-fir habitat for lynx and snowshoe

hares. Journal of Forestry 88:10-14.

Koehler, G. M. and M. G. Hornocker. 1991. Seasonal resource use among mountain lions,

bobcats, and coyotes. Journal of Mammalogy 72:391-396.

Koehler, G. M., M. G. Hornocker, and H. S. Hash. 1979. Lynx movements and habitat use in

Montana. Canadian Field-Naturalist 93:441-442.

Litvaitis, J. A., D. Kingman, Jr., J. Lanier, and E. Orff. 1991. Status of lynx in New Hampshire.

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G. A. Feldhamer, eds. Wild Mammals of North America. Johns Hopkins University Press,

Baltimore, MD.

Mech, L. D. 1977. Record movement of a Canadian lynx. Journal of Mammalogy 58:676-677.

Mech, L. D. 1980. Age, sex, reproduction, and spatial organization of lynxes colonizing

northeastern Minnesota. Journal of Mammalogy 61:261-267.

Nellis, C. H., S. P. Wetmore, and L. B. Keith. 1972. Lynx-prey interactions in central Alberta.

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O’Donoghue, M., S. Boutin, C. J. Krebs, and E. J. Hofer. 1997. Numerical response of coyotes

and lynx to the snowshoe hare cycle. Oikos 80:150-162.

O’Donoghue, M., S. Boutin, C. J. Krebs, G. Zuleta, D. L. Murray, and E. J. Hofer. 1998.

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1208.

Parker, G. R. 1981. Winter habitat use and hunting activities of lynx (Lynx canadensis) on

Cape Breton Island, Nova Scotia. Pages 221-248 in Worldwide Furbearer Conference

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Parker, G. R., J. W. Maxwell, and L. D. Morton. 1983. The ecology of the lynx (Lynx

canadensis) on Cape Breton Island. Canadian Journal of Zoology 61:770-786.

Perham, C. T. 1995. Home range, habitat selection, and movements of lynx in eastern interior

Alaska. Unpublished M.S. Thesis, University of Alaska, Fairbanks, AK.

Poole, K. G. 1994. Characteristics of an unharvested lynx population during a snowshoe

hare decline. Journal of Wildlife Management 58:608-618.

Quinn, N. W. S. and G. Parker. 1987. Lynx. Pages 682-695 in Wild furbearer management and

conservation in NorthAmerica. M. Novak, J. A. Baker, M. E. Obbard, and B. Malloch, eds.

Ministry of Natural Resources, Ontario, Canada.

Shields, W. M. 1987. Dispersal and mating systems: investigating their causal connections.

Pages 3-24 in Mammalian dispersal patterns: the effects of social structure on population

genetics. B. D. Chepko-Sade and Z. T. Halpin, eds. University of Chicago Press, Chicago.

Slough, B. G. and G. Mowat. 1996. Population dynamics of lynx in a refuge and interactions

between harvested and unharvested populations. Journal of Wildlife Management

60:946-961.

Smith, D. S. 1984. Habitat use, home range, and movements of bobcats in western Montana.

Unpublished M.S. Thesis, University of Montana, Missoula, MT.

Staples, W. R. 1995. Lynx and coyote diet and habitat relationships during a low hare

population on the Kenai Peninsula, Alaska. Unpublished M.S. Thesis, University of

Alaska, Fairbanks, AK.

Stephenson, R. O. 1986. Development of lynx population estimation techniques. Unpublished, Alaska Department of Fish and Game, Federal Aid in Wildlife Restoration, Final

Report, Project W-22-5, Job 7.12R, Juneau, AK.

van Zyll de Jong, C. G. 1966. Food habits of the lynx in Alberta and the Mackenzie District,

N.W.T. Canadian Field-Naturalist 80:18-23.

Ward, R. M. P. and C. J. Krebs. 1985. Behavioural responses of lynx to declining snowshoe

hare abundance. Canadian Journal of Zoology 63:2817-2824.

Wolff, J. O. 1980. The role of habitat patchiness in the population dynamics of snowshoe

hares. Ecological Monographs 50:111-130.

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cycles. Pages 441-449 in K. Myers and C. D. MacInnes, eds. Proceedings of the World

Lagomorph Conference, University of Guelph, Guelph, Ontario.
397

Chapter 14

Comparative Ecology of

Lynx in North America

Steven W. Buskirk, Department of Zoology and Physiology,

University of Wyoming, P.O. Box 3166, Laramie, WY 82071

Leonard F. Ruggiero, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59801

Keith B. Aubry, USDA Forest Service, Pacific Northwest Research Station,

3625 93rd Ave. SW, Olympia, WA 98512

Dean E. Pearson, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59801

John R. Squires, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59801

Kevin S. McKelvey, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59801

Abstract—Lynx occur across a large geographic area, but have only been

studied in a few locations, and this has led to extrapolation of understandings into areas with very divergent ecologies. We discuss ecological differences across the range of lynx, contrasting the patterns of climate, vegetation,

disturbance dynamics and succession, and predator/prey relationships. In

all these particulars, areas where lynx occur within the contiguous United

States diverge from the well-studied areas of the taiga. We caution against

uncritical application of ecological understandings derived from the North

to southern lynx and we emphasize the potential importance of late-successional forests as habitat for hares, red squirrels, and lynx in the southern part

of the range of the lynx.
Chapter 14—Buskirk

398

Introduction

Our limited knowledge of lynx ecology in North America comes from only

a few areas across a broad geographic range (Table 14.1). For example, we

have much greater knowledge of lynx ecology in the taiga (Chapters 6, 9)

than in southern boreal forests (Chapters 7, 13). Similarly, most of what is

known about habitats of snowshoe hares comes from the north-central and

northeastern United States. Understandings are therefore extrapolated to

other sites that have different climatic, topographic, and vegetative conditions. Such extrapolations may be inappropriate in some cases and result in

negative consequences for lynx conservation (Chapter 5). The comparative

assessment of lynx ecology presented here explores this potential problem

and identifies solutions. Although most extrapolations at issue are along a

several thousand-kilometer ecological gradient from north to south, we also

address extrapolations along the potentially more complex west-east gradient (for example from northeastern Washington to Colorado or from

Montana to Maine).

Table 14.1—Frequently cited lynx studies according to topic and geographic area. Quality code describes the emphasis of the

study: 1) primary topic of study, 2) major component of study, 3) minor component of study.

Northeastern and

Yukon, NWT Rocky Mountain Northcentral U. S.,

Topic Alaska Pacific Northwest Alberta, Manitoba Region and eastern Canada

Habitat Perham 1995 - 2 Koehler 1990 - 2 Murray et al. 1994 - 1 Koehler et al. 1979 - 3 Parker et al. 1983 - 3

relationships Paragi et al. 1997 - 1 Poole et al. 1996 - 1 Smith 1984 - 3

Population O’Connor 1984 - 1 Elton and Nicholson Brainerd 1985 – 2 Parker et al. 1983 - 2

dynamics and 1942 - 1

reproduction Nellis et al. 1972 - 1

Brand and Keith 1979 - 1

Quinn and Thompson

1987 - 1

Poole 1994 - 1

Boutin et al. 1995 - 1

Slough and Mowat

1996 - 1

Mowat et al. 1996 - 1

O’Donoghue et al.

1997 - 1

Ranta et al. 1997 - 1

O’Donoghue et al.

1998b - 1

Movements and Kesterson 1988 - 1 Brittell et al. Carbyn and Patriquin Smith 1984 - 3 Saunders 1963b - 1

home range Perham 1995 - 1 1989 - 2 1983 - 1 Brainerd 1985 - 2 Mech 1980 - 1

Bailey et al. 1986 - 3 Koehler 1990 - 1 Ward and Krebs 1985 - 1 Chapter 11 - 2 Parker et al. 1983 - 2

Poole 1994 - 2 Chapter 12 - 1

Slough and Mowat

1996 - 2 (con.)
399

Buskirk—Chapter 14

Habitat Bailey et al. 1986 Black 1965 Adams 1959 Conroy et al. 1979

relationships of Sullivan and Sullivan Dolbeer and Clark Orr and Dodds 1982

snowshoe hares 1982, 1983, 1988 1975 Buehler and Keith

Koehler 1990, 1991 Wolfe et al. 1982 1982

Parker 1984

Litvaitis et al. 1985

Parker 1986

Fuller and Heisey

1986

Monthey 1986

Rogowitz 1988

Scott and Yahner 1989

Thompson et al. 1989

Thompson and Curran

1995

Ferron and Ouellet 1992

St-Georges et al. 1995

Foraging Stephenson et al. Nellis and Keith 1968

behavior 1991 - 1 Brand et al. 1976 - 2

Ward and Krebs 1985

Murray et al. 1995

O’Donoghue et al.

1998a

Food habits Kesterson 1988 - 2 Koehler 1990 - 2 van Zyll de Jong Chapter 12 - 2 Saunders 1963a - 1

Staples 1995 - 2 1966 - 1 Parker et al. 1983 - 2

Brand et al. 1976 - 1

Brand and Keith 1979 - 2

O’Donoghue et al.

1998a,b - 2

Dispersal Brittell et al. 1989 - 3 Ward and Krebs Mech 1977 - 3

1985 - 2 Brainerd 1985 - 3

O’Donoghue et al.

1995 - 3

Slough and Mowat

1996 - 2

Poole 1997 - 1

Predator and Koehler et al. Murray and Boutin Chapter 11 - 3

competitor 1979 - 3 1991 - 1

interactions O’Donoghue et al.

1995 - (observations)

Table 14.1—Con.

Northeastern and

Yukon, NWT Rocky Mountain Northcentral U. S.,

Topic Alaska Pacific Northwest Alberta, Manitoba Region and eastern Canada
Chapter 14—Buskirk

400

As the chapters in this book show, the ecological relationships and population dynamics of the lynx show similarities across its range (Chapters 8,

13). However, they also reflect significant differences in the environments

occupied by lynx (Chapters 3, 9, 13), suggesting that there may be important

geographical differences in lynx ecology. Therefore, we assess the nature

and extent of regional variation in key biotic and abiotic gradients that

appear to affect the lynx and its prey. We divide the chapter into five sections:

1. Direct climatic effects

2. Natural disturbance regimes, topography, and resulting landscape

patterns

3. Forest successional pathways

4. Patterns of snowshoe hare and red squirrel abundance

5. Predator-prey communities

Direct Climatic Effects

Temperature and moisture regimes appear to limit the distribution of lynx

at coarse and fine scales via differential effects on snowfall and habitat

structure. In the North (Bailey’s [1998] Polar Domain), frozen soils and

permafrost generally hold water near the soil surface, favoring high densities of shrubs and young trees. Also, cold air holds relatively little moisture,

so that snow is only moderately deep and very dry. These conditions are

favorable for lynx and snowshoe hares. However, to the south, soil moisture

in summer is lower, higher elevation forests experience higher evaporation

rates, and mountain ranges cause patterns of soil moisture and snow

deposition to be much more localized. Areas of boreal forest are therefore

more patchily distributed in the southern part of the species’ range (Chapters 3, 8). This may also mean that lynx favor more mesic north-facing aspects

farther south, as was found on the Okanogan Plateau of Washington

(Chapter 10).

Snow depths in boreal forests and their southern extensions generally

increase from north to south, with the deepest snows generally found in

southern Colorado. This is because colder northern air holds relatively less

moisture than the warmer air farther south (Pruppacher and Klett 1978, Fig.

4.6). On the other hand, snow in southern lynx habitats may undergo more

winter thaws, with subsequent formation of crusts, than snow in the taiga.

Crusted snow would tend to remove the competitive advantage held by

lynx, with their long limbs and low foot loadings (Chapter 4). Such an

advantage or the lack thereof may contribute importantly to the success or

failure of lynx populations in some parts of their range. Because of the
401

Buskirk—Chapter 14

fragmented nature of landscapes and heterogeneous distribution of topographic, climatic, and vegetative conditions in western forests, lynx and

snowshoe hare habitats there are more prone to a metapopulation structure,

which has important implications for their population ecology (Chapter 2).

This condition is exacerbated by the presumably greater human-caused

fragmentation of lynx habitat in the south.

In the East, the climax forest condition of deciduous or mixed deciduous/

coniferous trees differs sharply from conditions in the West where succession tends toward coniferous trees. This difference is due to variable influences of climate, specifically the frequency of precipitation and the effects of

elevation. But, in eastern North America, human influences have been

pervasive so that few eastern forests at temperate latitudes are in a climax

condition. As a result, many of the eastern forests that were lynx habitat in

presettlement times are younger and mostly deciduous-dominated today.

Natural Disturbance Regimes, Topography, and

Resulting Landscape Patterns

Successional stage is commonly regarded as a correlate of habitat quality

for snowshoe hares and strongly reflects natural disturbance regimes. The

taiga is extensive, has fairly homogeneous climate and physiognomy, and

exhibits little topographic relief (Elliot-Fisk 1988). Kelsall et al. (1977) described the remarkably uniform snow depths (mean annual total snowfall =

102 -127 cm) across the vast northern boreal forest of Canada. Climax forests

of the taiga are dominated by three coniferous tree species: white spruce on

well-drained sites, black spruce on sites underlain by permafrost, and, east

of the Cordillera, balsam fir (Viereck and Little 1972, Hosie 1973). Trees are

relatively short and have crowns that can extend to the ground. Because

none of the three tree dominants is thick-barked, climax vegetation in the

taiga has little resistance to fire, which is almost always stand-replacing.

These trees also are prone to insect outbreaks, which can defoliate large

areas. Because of the homogeneous moisture conditions and topography,

and because of even-aged stands created by stand-replacing fires, large areas

become flammable simultaneously and, when ignition occurs, fires tend to

burn until the weather changes (Johnson 1992). In Alaska during the period

1893-1937, over 2.4 million ha of forest were reported burned by just

19 individual fires (Barney 1971), a mean of 128,000 ha per fire. In the taiga,

therefore, snow characteristics, disturbance regimes, and resulting vegetation conditions are homogeneous over large areas.

In the Rocky Mountain West, by contrast, site conditions and forest types

vary at small scales. Traveling 10 km from plains to mountaintop, one
Chapter 14—Buskirk

402

encounters habitats from dry desert or steppe, through montane and subalpine forests, to tundra, rock, and permanent snow. Across this gradient,

natural fire-return intervals can vary from less than 10 years in drier types

to over 400 years in moist subalpine stands (Chapter 3). In such settings, fires

often start at low elevation, then slow and die as they ascend mountains into

moister types. Although Rocky Mountain forests have experienced some

very large fires (Gruell 1985, Turner et al. 1997), most fires are topographically limited and smaller than those in the North. Even when comparing

areas with similar fire regimes (i.e., similar fire-return periods, stand replacing fires, and forest age structures fitting the negative exponential model,

Chapters 3, 15), fires in the Rocky Mountain West are generally smaller, with

more complex shapes, due to more complex topography and a wider range

of forest types per unit area. For example, wet concave areas dominated by

Engelmann spruce tend to burn with less frequency and intensity than

adjacent dry convex ones dominated by lodgepole pine. Likewise, post-fire

succession tends to be strongly affected by local topography: north aspects

will tend toward different post-disturbance trajectories than south-facing

slopes. All of these factors tend to produce more heterogeneity within fires

and post-fire seres in Rocky Mountain forests of the contiguous United

States than in the taiga. Some subalpine forests in the West are so moist and

dissected by areas of rock that fire is virtually excluded.

Relative to lynx-prey relationships, the heterogeneity of Rocky Mountain

forests results in higher densities of edges, possibly of ecotones, and the

relatively fine-scaled juxtaposition of forests of various ages. (See Chapter 9

for a discussion of the potential importance of edge in lynx–hare relationships.) Few forested areas in the Rocky Mountain West the size of a lynx

home range (about 75 km2 ) contain homogeneous vegetation. Rather, such

areas tend to feature many stands comprised of several tree and shrub

species having a wide range of stem densities and ages. In contrast, a large

burn in the taiga could easily homogenize a landscape as large as several

lynx home ranges.

The frequency and kinds of disturbance in forested systems generally vary

more strongly along east-west than north-south gradients. This is true at

both continental and smaller scales: the eastern Cascades are more fireprone than the western Cascades, and conifer forests of Montana are more

fire-prone than those in New England (Chapter 3). By contrast, disturbance

events, including fire and avalanches, occur at the northern and southern

edges of the distribution of lynx with remarkably similar frequencies (Chapter 3). In the northeastern United States, broad-scale natural disturbance

appears to have been infrequent and most forests would have been in climax

condition at the time of European contact (Lorimer 1977). However, today
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Buskirk—Chapter 14

those patterns are virtually irrelevant; the disturbance dynamics of these

forests are driven mostly by humans, and forests are much younger. In many

places this has resulted in a reduced conifer component, so that what were

mixed deciduous-coniferous forests 300 years ago are deciduous forests

today. The replacement of mixed stands with pure deciduous stands been

accelerated in recent years in the Great Lakes States by the increasing

importance of aspen as a crop tree (Chapter 3).

Forest Successional Pathways

In boreal forests, succession generally progresses from herbs and cryptogams soon after disturbance to shrubs, seedlings, saplings, mature trees, and

finally to climax forest (Kelsall et al. 1977, Kimmins 1987; Chapter 3).

Commonly, after a stand-replacing disturbance, the initial cohort of trees is

densely stocked, resulting in self-thinning and low levels of light at the forest

floor. Gradually, closed canopies give way to gaps as insect infestation,

disease and windthrow kill individual and small groups of trees, allowing

light to reach the forest floor. Light gaps encourage shade-intolerant trees,

shrubs, and herbs, greatly increasing understory diversity (Pickett and

White 1985, Spies et al. 1990, Valverde and Silvertown 1997). However,

details of successional pathways will vary according to the nature of local

disturbance regimes, tree species composition, and position along major

ecological gradients.

Within the taiga, regenerating seres exhibit high stem densities for trees

and shrubs for 20-35 years (Foote 1983). The young tree stage that follows

features dense deciduous trees with an understory of low shrubs for another

25 years (30-55 years post-fire). This is followed by a conifer-hardwood stage

that also maintains an understory shrub component, followed by the climax

spruce stage, around 90-150 years post-fire. At this climax stage, understory

vegetation is reduced to cryptogams, a few shrubs, and low tree branches.

Successional sequences in the taiga, therefore, support understory shrubs

and small trees for a long time, perhaps over 60 years. Although understory

shrubs mostly disappear in climax spruce forests (Foote 1983), gaps will

allow some trees and shrubs to grow, providing some low cover.

In northeastern and Great Lakes boreal forests, successional pathways

reflect the strong adaptations of deciduous trees. Hardwoods may dominate

entire seral sequences, including climax communities on warm, mesic sites.

Here, insects and wind, rather than fire, play important roles in disturbance

(Baskerville 1975, Lorimer 1977, Pastor and Mladenoff 1992). Cooler sites, or

sites at the extremes of the moisture gradient, follow successional pathways

similar to spruce in taiga forests (Dammon 1964, Larsen 1980). The shrub
Chapter 14—Buskirk

404

stage often is dominated by dense jack pine and quaking aspen for 5-15 years

post-disturbance. After reaching the young tree stage, aspen and pine

develop understories of shade-tolerant spruce, fir, maple, and birch until

about 40 years post-disturbance. The multistoried climax spruce-fir-mixed

hardwood stage is not reached until about 165 years after disturbance

(Chapter 3). So, in cooler sites, understory cover will be dense during early

shrub stages (5-20 years post-disturbance), then decline and emerge again

about 40 years post-disturbance, as climax species grow through the understory. Understory cover then declines again as climax species reach overstory proportions. In hardwood-dominated climax forests, understory cover

may be sparse away from canopy gaps, whereas in conifer-dominated

climax forests, understory cover tends to be more abundant.

Successional pathways in western montane boreal forests vary dramatically along gradients of moisture and soil nutrients. Climate during the

growing season, an important determinant of vegetation, is remarkably

similar across the lodgepole pine zone of western forests (Lotan and Perry

1983, table 2). Although total precipitation decreases from west to east across

the western contiguous United States, the proportion that falls during the

growing season increases so that lodgepole pine forests in Colorado receive

about as much summer precipitation as those in the Cascades, which are

generally considered more mesic (Lotan and Perry 1983). Of course, sites

farther south receive higher incident radiation during the growing season

and occur higher on mountains where lower atmospheric pressure causes

faster evaporation than near sea level (Knight 1994). Boreal forests with

equivalent precipitation will therefore become more xeric farther south.

Soil moisture during the growing season strongly influences shrub and

seedling abundance in western coniferous forests. Alexander et al. (1986)

described the poor regeneration of lodgepole pine in the Medicine Bow

Mountains of southern Wyoming following disturbance on dry sites. However, on some sites, lodgepole pine formed dog-hair stands that persisted for

hundreds of years (Alexander et al. 1986:10). In eastern Washington and

western Montana, the shrub and young tree stages are distinct but brief

(about 5-30 years post-fire), and shrub stem densities are low (Stickney 1981,

1986; Zamora 1982) compared with the taiga (Foote 1983). This pattern

becomes more pronounced farther south and east (Colorado and Wyoming),

where early seral lodgepole pine tends not to develop a shrub component

and tree stem densities can be very low, depending on cone serotiny, fire

intensity, elevation, and soils (Alexander et al. 1986).

In subalpine fir climax types in the Pacific Northwest, sapling densities

through time are often bimodal ( Fig. 14.1, Agee 1993) with peaks occurring

in the shrub-sapling stage and again after canopy gaps develop (Spies et al.
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Buskirk—Chapter 14

1990). Spies and Franklin (1989) reported mean densities of shade-tolerant

saplings in moist Douglas-fir forests of Oregon and Washington consistent

with this bimodal pattern: 228/ha in young stands, 84/ha in mature stands,

and 335/ha in old growth. For understory cover of deciduous shrubs, they

reported increasing densities as succession progressed: 6.8% in young

stands, 8.9% in mature stands, and 12% in old growth. This bimodal pattern

is probably the norm on moist sites. After disturbance, the site will be fully

revegetated with deciduous or coniferous tree species and tall deciduous

brush. Because moist sites support high leaf areas (Gholz 1982), overstory

canopies will be dense, leading to a relative lack of vegetation under the

mature canopy and, when the stand is old enough that mortality in the

overstory is significant, forest gaps are rapidly colonized. These patterns,

however, are far less general on dry sites. On dry sites, tree regeneration after

disturbance is extremely variable (Arno et al 1985, Alexander et al. 1986), and

these sites often lack tall brush components. As a result, open areas are

colonized by grasses or short brush species. Despain (1990), for example,

illustrates the small amount of shrub and small tree understory in all but the

moistest conifer forest sequences in Yellowstone National Park.

Figure 1—Densities (no./ha) of conifer seedling (< 4 cm dbh) stems in

relation to stand age after fire in the Pasayten Wilderness, Washington.

Data are from Fahnestock (1976).

0

500

1000

1500

2000

2500

3000

3500

0-50 50-100 100-200 200-400

Stand age (yr)

Seedlings/ha

Subalpine fir

Engelmann spruce

Lodgepole pine
Chapter 14—Buskirk

406

Patterns of Snowshoe Hare and Red Squirrel

Abundance

Understanding the successional correlates of wildlife abundance is particularly relevant because many species can be linked to specific seres via

forest structure and composition. Forest management alters successional

sequences, either by reducing disturbance (fire suppression) or increasing it

(timber harvest). However, successional pathways vary greatly in rate,

species composition, and physical structure (Pfister et al. 1977, Steele et al.

1981, Moir and Ludwig 1979). Therefore, understanding habitat associations

of lynx and their prey must be framed in terms of specific, regional successional trajectories.

Wherever they have been studied, hare densities are positively correlated

with densities of small-diameter woody stems (Brock 1975, Wolfe et al. 1982,

Pearson 1999, Chapters 6, 7). Density appears to be more important than

composition largely because hares consume a wide variety of plant species

(Chapter 7). Thus, in general, dense small-diameter stems simultaneously

provide both food and cover. Based on these understandings, and lacking

site-specific hare density data, we hypothesize that hare densities can be

inferred from sapling and tall shrub densities for those forest types known

to support hares. In mesic forests, therefore, we argue that hare densities

should be bimodal with stand age: highest in early seral conditions, minimal

in closed-canopy mature forests, and reaching moderate densities in extremely old gap-phase forests. We do not, however, expect this pattern to be

common on dry sites where erratic regeneration and the lack of tall deciduous brush often lead to very open conditions for extensive periods after

disturbance. In these stands, hare habitat will only be produced in later seres.

This bimodal association between brushy vegetation and population

density has been shown in northwestern California for the shrub-associated

dusky-footed woodrat, an important prey of the northern spotted owl. This

species is most abundant in dense understory following disturbance, absent

from mature forest with scarce shrubs and young trees, and intermediate in

abundance in old growth, where increased understory cover accompanies

gap succession (Sakai and Noon 1993). Data for snowshoe hares along entire

successional sequences are scanty; hares tend to be rare immediately after

disturbance, abundant in the shrub-sapling stage, and uncommon in closedcanopy forest (Litvaitis et al. 1985; Koehler 1990a,b; Ferron et al. 1998;

Chapters 6,7). In Ontario, Thompson et al. (1989) counted hare tracks on 2 km

transects for 5 years. The transects intersected logged stands <30 years old

and uncut forest 150-200 years old. Average track counts were highest in
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Buskirk—Chapter 14

20-year-old stands, and abundant and approximately equal numbers of

tracks were located in 30-year-old stands and areas of uncut forests. Thompson et al. (1989) attributed the relatively high levels of hare tracks in the old

forests to the presence of brush in canopy gaps. Mills and Henderson

(unpubl. data) found hares relatively abundant in old-growth forest in

northwestern Montana, and Beauvais (1997) found track densities of hares

to be positively correlated with variables indicative of late-seral stages in

northern Wyoming. Powell (1991 unpubl. data cited in Powell and Zielinski

1994) described a bimodal distribution of snowshoe hare abundance along

a successional sequence on the Olympic Peninsula of Washington. These

pieces of evidence, while weak, suggest that hares may be relatively abundant in climax conifer forests of the western contiguous United States, and

bimodally distributed along successional gradients on mesic sites.

However, in the drier areas within lynx range, including areas in the

southern Rocky Mountains of Colorado where regenerating stands develop

no shrub stage, suitable hare habitat may only occur in old-growth forests

and riparian areas (Lawrence 1955, Dolbeer and Clark 1975). In these areas,

snowshoe hare abundance may follow a unimodal distribution that peaks

under old-growth conditions with the development of canopy gaps. Two

years of snow tracking in a range of stands from young to old growth in

northern Wyoming (Beauvais 1997) showed that snowshoe hare tracks were

negatively correlated with indices typical of highly fragmented landscapes,

such as density of clearcut edge, and positively correlated with indices such

as percent of forest cover and percent of spruce-fir cover. Snowshoe hares

were also positively correlated with maximum diameters of trees, and with

total number of stems within 5 m of sampling points.

Although it is generally acknowledged that early seral stages resulting in

dense understory cover provide important habitat for snowshoe hares

(Chapters 6, 7), little research has examined the relative importance of gap

succession in climax forests for hare habitat. However, the process of gap

development, which produces the habitat conditions associated with hares,

varies among regions. For instance, gap succession in the Pacific Northwest

is driven primarily by single tree mortality, which results in smaller gaps

that compose a smaller proportion of the overall forest (Spies et al. 1990). In

contrast, in eastern North America wind and insects play larger roles,

thereby generating more group-tree mortality, which results in larger gaps

and affects a larger proportion of the forest (Kneeshaw and Bergeron 1998).

These processes may affect the spatial scales of usable habitat for snowshoe

hares within climax or old-growth forests in different regions of North

America.
Chapter 14—Buskirk

408

Understanding red squirrel abundances in the context of succession is also

important given the role of squirrels as alternative prey for lynx (O’Donoghue

et al. 1998b, Chapters 9, 13). Because squirrels eat primarily conifer seeds, in

the West their abundance over successional time is linked to cone-producing

ages, usually mature (Smith 1970, Obbard 1987) or older (Kemp and Keith

1970, Rusch and Reeder 1978), conifers. Thus, late-successional forest provides habitat within which two prey species important to lynx occur sympatrically and are relatively abundant.

Predator-Prey Communities

The North American distributions of lynx and their two most important

prey, snowshoe hares and red squirrels, roughly coincide (Hall 1981). Other

potential prey species occupy much smaller geographic ranges, so the

availability of alternative prey varies regionally for lynx. In the taiga, these

include mice and voles, northern flying squirrels, arctic ground squirrels,

beavers, muskrats, grouse and ptarmigan, and a variety of ungulates (Chapter 9). Arctic hares and Alaska hares are tundra dwellers that penetrate forest

edges slightly (Hall 1981) and may be eaten in a few areas. In southern boreal

forests, however, potential prey communities differ substantially. Mediumsized birds (grouse and ptarmigan), small mammals, and ungulates are

relatively abundant throughout the range of lynx, but medium-sized mammal assemblages in southern boreal forests contain many more species than

those in the taiga. In montane Colorado, for example, there are four species

of leporids: snowshoe hare, white-tailed jackrabbit, mountain cottontail,

and desert cottontail (Hall 1981). The coyote, a generalized leporid predator,

exploits only snowshoe hares in the North but can switch among various

leporids, even those not sympatric in distribution, in southern regions.

Although prey-switching by coyotes may seem to ease the competitive

pressure on lynx in the southern part of its range, it probably does the

opposite. It allows coyotes to switch among leporid species, including

snowshoe hares, as seasons, weather, and prey populations change. There is

no evidence to suggest that lynx are effective at this kind of prey switching.

The greater dietary options available to coyotes in the southern part of the

range of lynx may provide a buffer to coyote populations during population

lows of hares that is not readily available to lynx and may make coyotes more

effective competitors with lynx through time.

Similarly, southern boreal forests during the snow-free season feature

diverse medium-sized rodents not present in the taiga, including woodrats,
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Buskirk—Chapter 14

marmots, ground squirrels, fox and eastern gray squirrels, and chipmunks.

Although available evidence indicates that snowshoe hares and red squirrels are the most important lynx foods during winter in all portions of their

range (Chapters 9, 13), summer diets have scarcely been studied. The

influence of this diverse array of alternative prey in the southern portion of

the range of lynx is largely unknown.

Lynx also have more potential competitors in the southern part of their

range than in the North. In the North, the interference competitors that are

likely to be dominant are the wolf and coyote, but coyotes are largely

restricted to areas without wolves (Buskirk 1999). In southern boreal forests,

by contrast, potential interference competitors of lynx include the coyote,

cougar, and bobcat. Data from Montana show that cougars kill lynx and may

be a substantial source of mortality (Chapter 13). In the taiga, however,

cougars are absent or rare. Coyotes, cougars, and bobcats have expanded

their ranges and increased their populations in the contiguous United States

within the last 20 years (Chapter 4). Therefore, regional and temporal

variation in carnivore communities may contribute to the differential success of lynx populations across North America.

In a few areas of the contiguous United States, wolves are increasing in

distribution and numbers, while coyotes are decreasing in response (Crabtree

and Sheldon 1999). Lynx should be better able to co-exist with wolves than

coyotes, because wolves prey more on ungulates than leporids and are

probably too large to be effective interference competitors with lynx (Chapter 4). Accordingly, community conditions for lynx in the Greater Yellowstone

Area, where wolf populations are expanding and coyote populations contracting, should improve in coming years.

Broad regional variation in forested landscapes, especially the extent and

connectivity of mesic forest types, may mediate competitive interactions

involving lynx. Because suitable habitat areas are generally smaller in the

southern part of the range, competitors, including those not highly adapted

to snow, may be better able to occupy lynx habitat than those in the North

(Chapter 4). This process may also be facilitated by human activities, which

produce dense systems of roads and trails that probably enable coyotes and

other predators to gain access to areas with soft, deep snow (Chapter 4). In

general, intensive forest management and concomitant fragmentation of

habitat via timber harvesting and road systems are more prevalent in

southern boreal forests compared to the taiga. Thus, human-mediated

increases in potential competitors and predators may present a more serious

threat to lynx populations in southern boreal forests than in the taiga.
Chapter 14—Buskirk

410

Conclusions

Across the vast geographic area occupied by lynx in North America, we

observe strong gradients in climate, topography, elevation, soil conditions,

snow conditions, plant dominants, disturbance regimes, and successional

trajectories. On top of these are added the highly variable influences of

humans. Extrapolating information gathered in one part of this region to

others must be done with the greatest of care and would be facilitated by

additional research. The likelihood of important among-population differences increases with geographical and ecological distances between populations (Chapter 5). This chapter identifies some potentially important

ecological differences over the range of lynx and suggests that variation

among populations is a key issue for lynx conservation in the contiguous

United States.

In the southern range of lynx, the communities of both competitors and

prey are more diverse than those in the North. Not only are lynx in the South

subject to a different suite of interference competitors, including mountain

lions, but exploitation competition with generalists such as coyotes will

likely be more significant due to the ability of these predators to prey-switch.

The interactions between lynx and competitors in the south is unstudied and

represents a major research need.

We question the generalization that the best way to provide habitat for

lynx prey, including hares, is to create early-successional forest. On mesic

sites, the highest hare densities are generally found in sapling-stage forests

after disturbance, but squirrels are absent from these sites. We believe the

data, though sparse, also suggest that old gap-phase forests provide a

combination of high numbers of squirrels and moderate densites of hares on

many sites. Additionally, site moisture appears to be an important correlate

of shrub and sapling densities in the early stages following disturbance and,

in dry areas of the West where post-disturbance regeneration is erratic, gapphase old-growth forests may provide relatively higher densities of smalldiameter woody stems compared to earlier stages of succession on the same

sites.

In areas where boreal forests are highly fragmented, older forests may be

an important stabilizing element. Because small areas of boreal forest can be

highly altered by single disturbance events, such as fire, hare dynamics

associated with post-disturbance conditions will be transient. Older forests

are temporally stable, will produce hares in lower but more reliable numbers, and provide squirrels as alternative prey. On dry sites, where young

forests do not reliably produce hare habitat, older forests may provide a

critical source of hare habitat.
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Buskirk—Chapter 14

We are cautious in reaching these conclusions because data are so limited.

However, the relationship between forest succession and prey abundance is

an area of utmost importance to southern lynx conservation. We believe that

a well-designed, geographically extensive study to further examine these

relationships should be given the highest priority for research. Failure to

carefully consider successional trajectories and their structural habitat correlates on a regional and site-specific basis can produce the opposite of

intended results, especially with regard to the habitat needs of snowshoe

hares. Ultimately, lynx management must take into account unique regional

attributes and site conditions relative to disturbance regimes and successional pathways that follow natural disturbance and management events.

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418
419

Chapter 15

Lynx Conservation in an

Ecosystem Management

Context

Kevin S. McKelvey, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59801

Keith B. Aubry, USDA Forest Service, Pacific Northwest Research Station,

3625 93rd Ave. SW, Olympia, WA 98512

James K. Agee, College of Forest Resources, University of Washington,

Box 352100, Seattle, WA 98195

Steven W. Buskirk, Department of Zoology and Physiology, University of

Wyoming, P.O. Box 3166, Laramie, WY 82071

Leonard F. Ruggiero, USDA Forest Service, Rocky Mountain Research

Station, 800 E. Beckwith, Missoula, MT 59801

Gary M. Koehler, Washington Department of Fish and Wildlife,

600 Capitol Way N., Olympia, WA 98501

Abstract—In an ecosystem management context, management for lynx must

occur in the context of the needs of other species, watershed health, and a variety

of products, outputs, and uses. This chapter presents a management model based

on the restoration of historical patterns and processes. We argue that this model is

sustainable in a formal sense, practical, and likely to provide for the needs of a

variety of species, including lynx. Because our knowledge of lynx biology and

disturbance ecology is limited, implementation of this model will be experimental

and must be accompanied by a well-planned monitoring program.
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Introduction

Our knowledge of lynx ecology and population dynamics in southern

boreal forests is limited and based on information obtained at only a few

geographic localities (Chapter 13). Because of these information gaps, the

conservation of lynx populations in this region must proceed initially with

limited knowledge about their habitat relationships and, consequently,

with a limited understanding of how to design forest management strategies

that will provide for the persistence of lynx populations in the contiguous

United States. However, even if we possessed perfect knowledge, management aimed solely at maintaining or improving habitat conditions for a

single species across such a broad geographic area would conflict with many

other resource management objectives. Managing habitat for lynx may not

provide for the needs of other species of conservation concern, or for

biodiversity, watershed health, recreation, grazing, mining, timber, or wilderness uses, yet each has a statutory or regulatory basis and a constituency

on public lands.

In addition, the scale at which forest management strategies are defined

will be a critical consideration for lynx conservation. Because lynx occupy

large home ranges and occur at low densities (about one lynx/50 km2

;

Chapter 13), the long-term viability of lynx populations cannot be achieved

at the spatial scale of relatively small parcels of public land, or even larger

units such as individual National Forests or National Parks. Consequently,

we believe that lynx conservation in the contiguous United States can only

succeed as part of an ecosystem management strategy that is designed to

address the needs of a variety of potentially conflicting resource uses over

long periods of time and broad spatial scales. In this chapter, we discuss

ways in which lynx conservation could be approached within the context

of ecosystem management.

The Concept of Ecosystem Management

The concept of ecosystem management dates back to at least 1988

(Agee and Johnson 1988) and, since that time, a variety of definitions

have been published (Grumbine 1994), many of which reflect contrasting

areas of emphasis. To various constituencies, ecosystem management

represents an emphasis on landscape-scale analysis, on science-based management, on adaptive management, on interagency cooperation, or on

ecological integrity (Franklin 1997).

The Ecological Society of America defined ecosystem management as

“management driven by explicit goals, executed by policies, protocols, and
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practices, and made adaptable by monitoring and research based on our

best understanding of the ecological interactions and processes necessary

to sustain ecosystem structure and function (Christensen et al. 1996).” The

central goal or value of ecosystem management is sustainability. We consider the eight components of ecosystem management presented by

Christensen et al. (1996) to represent the most useful framework for discussing this concept:

1. Long-term sustainability as a fundamental objective

2. Clear, operational goals

3. Sound ecological models

4. An understanding of complexity and inter-connectedness

5. Recognition of the dynamic nature of ecosystems

6. Attention to context and scale

7. Acknowledgment of humans as ecosystem components

8. A commitment to adaptability and accountability

Sustainability

Long-term ecological, social, and economic sustainability are the central

goals of ecosystem management (Christensen et al. 1996). To achieve these

goals, management must ensure that ecological resources and processes will

be maintained in perpetuity, so that future options for management are not

compromised. Operationally, this means keeping all the “pieces” of ecosystem structure, function, and composition, while addressing productivity of

wood, water, livestock, minerals, and other resource outputs expected

from public lands (Franklin 1993). For example, a forested landscape will

only provide a sustainable output of timber if the rate of timber harvest is

low enough that the first stands harvested have re-grown to rotation age

before the last stand is harvested. It is this aspect of sustainability that is

embodied in the ideals of even-aged silviculture and maximum sustained yield. Yet sustainability includes more than timber; it requires

maintaining the productivity of the soil (for timber, forage, and other

resources) and, more broadly, sustaining ecological function so that native

species are perpetuated. Sustainability was once narrowly defined in terms

of resource outputs, but the concept now encompasses both the state of the

ecosystem and associated resource outputs. The foundation of sustainability

is ecological; only by sustaining ecological function can social and economic

sustainability be achieved (Committee of Scientists 1999).

Applying a sustainable management model will not necessarily produce

a sustainable system, however. Most sustainability paradigms are based

on maintaining a state of equilibrium. This is possible in a deterministic
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world, but seldom occurs at small spatial scales in a stochastic system prone

to disturbance, such as in the boreal or subalpine forests typical of lynx

habitat. In high-severity fire regimes (Agee 1993), for example, the majority

of the land base is burned by only a few large, catastrophic fires (McKelvey

and Busse 1996; Minnich 1983). For a system prone to such disturbances to

be sustainable, it must be resilient. Resiliency in this context is created by

scale; ecosystems are more resilient and, hence, more stable when considered at very large spatial scales. In other words, maintaining ecosystem

stability will be most attainable if the size of the extreme events is small in

relation to the total area.

Ecosystem Context

One of the primary causes for the loss of ecosystem resiliency (i.e., loss of

sustainable character) is loss of context resulting from management activities (Allen and Hoekstra 1992). By this, the authors mean a disparity between

the spatial and temporal scales of critical ecosystem processes in the natural

system, and the area and planning horizon of management activities. For

example, cutthroat trout populations were stable in the western United

States during historical times, despite the periodic occurrence of large

disturbances within the range of the cutthroat, such as the 1910 fire in

northern Idaho and western Montana that burned over 1 million ha. Because

this fire occurred in only a portion of the species’ range, rivers and streams

in disturbed areas that lost cutthroat trout habitat eventually recovered

and were recolonized by cutthroat trout. Rivers provided connectivity

between disturbed and undisturbed areas. Although trout populations in

individual streams were prone to local extirpation from such natural disturbances, they were embedded in the larger context of the western United

States cutthroat metapopulation. Thus, even catastrophic disturbances had

little impact on the long-term sustainability of this system for cutthroat trout.

The situation is similar for lynx, except that the spatial scale that must be

considered is much larger. In southern boreal forests, male and female lynx

occupy home ranges that average about 150 km2

 and 75 km2, respectively

(Chapter 13), and interbreeding populations occupy an area many times that

size. Throughout most of Canada and Alaska, lynx numbers cycle in abundance every 10 years in a pattern of lagged synchrony within the species’

range; population peaks in the center of the continent occur approximately

two years before they occur in Alaska or Quebec (Chapter 8; see also Ranta

et al. 1997). While it is possible that these patterns are independent of one

another and driven by exogenous synchronizing factors, such as climate

(Elton and Nicholson 1942), the lagged pattern of synchrony in population
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McKelvey—Chapter 15

dynamics suggests some degree of connectivity through dispersal among

northern populations (Chapter 2). At least in the 1960s and 1970s, when

Canadian population peaks were unusually high, these patterns of lagged

synchrony also appeared in trapping records from Minnesota, Montana,

and, more weakly, Washington state (Chapter 8). Thus, it is possible that

lynx population dynamics in northern tier states of the contiguous United

States are linked to those occurring in Canada.

The potential geographic scope of ecosystem context for lynx populations in the contiguous United States is suggested by the historical analysis of

lynx distribution presented in Chapter 8. In Washington, lynx populations

have persisted only in relatively large blocks of habitat in north-central

and northeastern Washington that are adjacent to lynx habitat in southwestern Canada. Similarly, lynx populations in the Clearwater drainage in

western Montana occur in the context of the Bob Marshall Wilderness and

direct connections to larger habitat areas in Canada. In addition, the documented decline of lynx in New Hampshire is believed to have resulted more

from the loss of large-scale habitat connectivity with Quebec than with the

loss or alteration of local habitat conditions (Chapter 8; Litvaitis et al. 1991).

Thus, for reasons we do not yet fully understand, ecosystem context for

lynx appears to occur at least at the scale of ecoprovinces (Bailey 1998;

Chapter 8).

Diversity and Complexity

In natural systems, the age distribution of forest stands varies dramatically

from that produced under most forest management models. In natural

landscapes, stand age distributions produced by large-scale stochastic events,

such as forest fires, are more complex than those that result from deterministic, even-aged models of forest management. In most boreal

forest systems, the constant-probability stochastic process model (hereafter referred to as the negative exponential model) results in a distribution of stand ages that approximates a negative exponential curve

(Fig. 15.1a). For boreal forests with long fire-return intervals, this model

approximates natural stand-age distributions, or at least one that is much

closer to natural conditions than the truncated distribution produced by

even-aged cutting practices (Fig. 15.1c; see also Chapter 3). By maintaining

old-growth forests in the landscape, the negative exponential model also

retains mature forests, the most temporally stable element on the landscape.

Older forests provide a stabilizing influence that is likely to increase ecosystem resiliency. Resulting landscapes have greater levels of complexity and

diversity because all age classes are maintained within the landscape.
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Figure 15.1—A comparison of negative exponential (a, b) and even-aged (c, d) planning paradigms.

Graphs on the left depict the stand age distributions, and hypothetical landscape views on the right

depict examples of how stands of varying ages, sizes, and shapes could be distributed across the

landscape under each planning paradigm. Relative stand age is indicated by increasingly darker

shading in the polygons.

Humans as Ecosystem Components

The evaluation of humans as ecosystem components includes both the

effects of human perturbations and the needs of society for ecosystem

goods and services. Unquestionably, much of the context-based stability

that characterized pre-settlement North American ecosystems has been

lost. Urbanization and agriculture have increased the isolation and fragmentation of natural areas and reduced the resilience of some parts of

those systems to extreme disturbance events; further, this loss of ecosystem

context is unlikely to be reversed. We do not believe that a system of reserves

maintained by policy or regulation, embedded in a increasingly fragmented

and non-natural matrix, can provide for sustainable lynx populations.

Inevitable large-scale catastrophes preclude this being a sustainable system

from the standpoint of lynx conservation; catastrophes will remove reserves,

and there is no mechanism for their replacement or restoration in a

b

0 100 200 300 400

Stand Age - Years

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

% by 1-year Age Classes

Rectangular Distribution

Rotation Age = 100 years

c d

0 100 200 300 400

Stand Age - Years

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

% by 1-year Age Classes

Negative Exponential Distribution

Average Stand Age = 100 years

a
425

McKelvey—Chapter 15

reserve/matrix approach. Allen and Hoekstra (1992) have argued that one

role of management in sustainable ecosystems is to replace functions that are

generally provided in the natural context, but have been lost due to human

influences. For this reason, we argue for a system of active management in

those land designations where it is permitted. Management of these lands

must be cognisant of and limited by the dependency of various species on

the condition of these areas given the likelihood of divergent management

in adjacent private lands, as well as inevitable natural disturbances.

Simple and rigid prescriptions cannot succeed when the management

goals are as complex as maintaining multiple species of wide-ranging

vertebrates in natural ecosystems. We simply do not have the knowledge to

prescribe procedures that will always achieve these objectives, and we

probably never will. Hence, managers cannot be simply technicians; they

must be creative thinkers and explorers who use adaptive management to

achieve complex and shifting resource management objectives (Walters

1986). We need to build into the system the mechanisms to learn as we go,

and the system must be flexible; managers must be able to react quickly to

new information to minimize ecosystem damage and maximize conservation opportunities. The necessary regulatory framework must also be in

place to allow managers to do so.

Single-Species Habitat Management

Several of the single species-based habitat management models used in

the past embodied some of the concepts of ecosystem management because the goal of these approaches was to provide for a broad array of

ecological values by ensuring that the habitat needs of key species were met.

The National Forest Management Act (NFMA) of 1976, with its attendant

planning regulations, included the concept of “indicator” species as a means

of maintaining biological diversity on National Forest lands. Most indicator

species were chosen on the basis of their presumed sensitivity to ecological

changes resulting from management actions. However, the concept was

widely criticized as being of little value for monitoring and responding to

changes in ecological conditions resulting from management (Patton 1987;

Landres et al. 1988), and its use was largely abandoned. “Umbrella” species

are conceptually similar to indicators, but their use is based on the assumption that protecting habitat for rare species with large spatial needs will

provide for the needs of a variety of more common species with smaller

spatial requirements (Berger 1997). Another link between single species with

higher levels of biological organization is the concept of “keystone” species

(Paine 1969). Keystones are species that make disproportionately large
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Chapter 15—McKelvey

contributions to community or ecosystem function relative to their

abundance (Mills et al. 1993).

The Endangered Species Act (ESA) acknowledges the importance of

ecosystems, but conservation efforts mandated by the ESA typically have

focused on restoring populations of individual species (Christensen et al.

1996). Recently, however, conservation strategies for certain listed species,

including the northern spotted owl (USDA and USDI 1994a), bull trout

(Rieman and McIntyre 1993), and Pacific salmon stocks (USDA and USDI

1994b), have adopted multi-species habitat conservation approaches.

These efforts exemplify the ongoing transformation of endangered species

conservation from a focus on individual species, to one that more closely

reflects the concepts embodied in ecosystem management. While singlespecies or “fine-filter” conservation will continue to be mandated by law, we

believe that the long-term viability of multiple species will best be addressed

with a combination of ecosystem-scale or “coarse-filter” strategies (Haufler

et al. 1996; Hunter et al. 1988) and fine-filter strategies for sensitive or rare

species whose persistence may require special management actions.

Application of Ecosystem Management to Lynx

Conservation

The coarse-filter strategy involves the analysis of pattern and process at

large spatial scales. The overall goal is the retention of most biotic diversity

and ecological functions through the restoration of ecosystem processes.

In this strategy, fine-filter approaches, such as the maintenance of indicator, umbrella, or keystone species, serve as a check on the efficacy of the

coarse filter. They also provide insights into modifications that may be

necessary to meet the needs of rare or sensitive species not met with a coarsefilter approach. Applying both a coarse and fine filter to the process of

ecosystem management increases the probability that key species will be

retained, while generating a dynamic and sustainable landscape. For species

of concern, such as the lynx, fine-filter measures are mandated by law. The

ecosystem management paradigm, when applied to the conservation of

lynx, incorporates these species-oriented measures into broad, coarse-filter

landscape planning.

Broad-Scale Patterns of Lynx Occurrence

Our analysis of the current and historic distribution of lynx populations

in the United States indicates that large, contiguous areas of suitable

habitat are necessary for population persistence (Chapter 8). All lynx
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populations that have long histories of commercial trapping in the

contiguous Unites States are those whose geographic range is contiguous

with or adjacent to larger areas of suitable habitat north of the Canadian

border, including populations in Washington, Montana, and Minnesota.

Because individual lynx may disperse >500 km in straight-line distance

(Chapter 9), lynx populations in southern boreal forests may be augmented

at various times by immigrations from the Canadian taiga. However, the

degree to which the persistence of southern populations depends on the

rescue effect of immigrations from Canada is unknown (Chapter 8).

We cannot assume that lynx populations in the contiguous United States

will be maintained by dispersal of lynx from Canada, nor that connectivity

with larger habitat areas in Canada will be maintained in perpetuity.

Although cooperative conservation efforts with Canadian land management agencies should be explored in all areas of adjacent lynx habitat, we

believe that lynx conservation efforts in the contiguous United States

should be addressed at geographic scales that will provide for the persistence of resident populations of lynx, regardless of periodic augmentations that may occur from other areas. Clearly, ecoprovince-wide planning

is necessary to provide the broad-scale information necessary for effective

conservation of lynx.

The following calculation (included here for illustrative purposes only)

provides a sense of the smallest scale at which conservation planning will

need to be addressed. The estimated density of a local population of 25

resident lynx in north-central Washington studied with radiotelemetry

from 1980 to 1987, was about one lynx per 50 km2

 (Chapter 13; Brittell et al.

1989, unpublished; Koehler 1990). Thus, conservation of this small group of

animals, which is probably not viable as a geographically closed population

(see Chapter 2), would require a planning area at least 1,250 km2

 in size

(25 x 50 km2

). However, this estimate represents a minimum area requirement over a relatively short period of time; to provide sufficient habitat

for the population size to fluctuate around a long-term mean of 25 animals,

the actual conservation area would need to be considerably larger.

Broad-Scale Habitat Management

Unlike organisms that are tightly linked to a particular forest condition,

lynx use a variety of forest age and structural classes (Chapter 13). Preferred

prey for lynx are also associated with a variety of forest types. Red squirrels

are closely tied to mature, cone-producing forests, whereas snowshoe

hares generally reach highest abundance in younger seral stages. Dense

horizontal structure appears to be important for snowshoe hares, but such
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Chapter 15—McKelvey

conditions develop at different stages in different forest types (Chapters 6

and 7). These observations suggest that forests managed for lynx should

contain a mixture of age classes and structural conditions. How such

habitats should be interspersed to benefit lynx, and how to maintain this

interspersion in space and time, therefore become central issues in habitat

management.

Existing lynx habitat management plans in the contiguous United States

are generally focused at relatively small spatial scales, and emphasize the

production of young forest to provide foraging habitat, and the maintenance

of a few, small patches of older forest to provide denning habitat (e.g.,

Washington State Department of Natural Resources 1996). These plans are

based on the premise that if a few small areas of old-growth forest are

provided within the matrix for denning habitat, landscapes managed primarily for a spatial and temporal mosaic of high-quality snowshoe hare

habitat will provide for the long-term persistence of lynx populations

(Koehler and Brittell 1990). However, this approach is based on untested

hypotheses and does not address the divergent needs of other species that

inhabit these landscapes. When faced with uncertainty concerning the

biological requirements of an organism or of a group of organisms, land

management plans must be conservative in their retention of habitat

components. Because we know little of the details of lynx habitat relationships at the stand scale or the necessary juxtaposition of stand types,

landscape-scale habitat management strategies should provide for a continuum of stand ages in a variety of spatial configurations.

The maintenance of all age classes in commercial forests has been

viewed as problematic because even-aged forest management removes all

stands older than the rotation age, eliminating both habitat and future

management options for organisms associated with late-successional forests. On the other hand, removing all disturbance from a site by suppressing

fire and refraining from cutting will, in most areas, preclude stand replacement and impact organisms associated with younger forest conditions. Our

challenge, from the perspective of maintaining lynx and their prey in the

context of ecosystem management, is to design management strategies that

result in dynamic, sustainable landscapes that approximate the composition

of natural systems.

Natural Disturbance as a Management Template

Natural disturbance in boreal forests, due to its stochastic nature,

tends to generate forests composed of widely varying ages and conditions (Chapter 3). These conditions emerge as a direct consequence of
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McKelvey—Chapter 15

disturbance stochasticity; one drainage may burn frequently, whereas an

adjacent drainage may avoid fire for centuries. For example, within a

burned drainage variation in wind patterns may leave unburned patches,

and diurnal variation in moisture and temperature during a fire may result

in some areas having high tree survival, whereas others do not. This

stochastic process leads to a landscape with a mosaic of conditions at various

spatial scales. A very large, stand-replacing fire has little mosaic within its

boundaries (Eberhart and Woodard 1987), but viewed at the spatial scale of

the region and the temporal scale of 100 years, it represents a patch in a fire

mosaic on the landscape. Such an event produces a large, contiguous area of

young forest but, in the larger context, there will be areas of very old forest

as well.

Johnson et al. (1995) and Agee (Chapter 3) argue that naturally occurring age distributions in forested landscapes, especially landscapes composed of boreal and subalpine forests (Johnson et al. 1995), often fit negative

exponential functions, indicating a constant-probability stochastic process.

While this model may not always produce the best fit (Chapter 3), all

stochastic processes produce a characteristic signature in the resulting age

distribution, including asymptotic “tails” in the older age classes (Fig. 15.1a;

Van Wagner 1978; McKelvey and Lamberson 1994). In contrast, cyclic

processes, such as even-aged rotation forestry, truncate the age distribution

(Fig. 15.1c). In a cyclic system, there is no formal mechanism to generate

stands or elements older than rotation age. However, in a forested landscape

with a negative exponential stand-age distribution, about 36% of the landscape will be older than the average stand age, about 13% older than twice

the average stand age, and about 5% older than three times the average

stand age (Table 15.1). Although there is no maximum stand age in this

system (Finney 1994), old stands that have not burned will be subject to

other sources of mortality, such as insects and disease.

Table 15.1—Equilibrium time since disturbance for forests with a negative exponential stand age

distribution. Where time since disturbance exceeds the longevity of individual trees,

the stand ages will be younger than are indicated in this table, and the forests will be

characterized by “gap” processes due to overstory mortality.

 Fire return interval Percent of area (by age class)

(average stand age) <50 50-100 100-200 200-300 >300

100 years 40 24 23 9 4

150 years 29 20 25 13 13

200 years 23 17 24 14 22

300 years 16 13 20 15 36
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Chapter 15—McKelvey

The retention of older stands essentially mimics the process of ecological “escape” in systems characterized by large-scale disturbances. In a

catastrophic fire, variation in fire intensities and the vagaries of weather

allow forest elements at many scales to survive, including individual

trees, small groups of trees, stands, or entire watersheds. As multiple

fires overlap over many years, there will be small areas embedded in larger

areas of younger forest that have, by chance or location, survived multiple

fires. This escape of older elements is not effectively mimicked by embedding fixed reserves in a landscape of cyclic management. In a stochastic

system, with each new disturbance event, older forests may be destroyed or

altered, or they may be left intact; thus, late-successional stands are not

spatially assigned and maintained, but emerge dynamically within the

disturbance process. A variety of other differences, some of them dramatic, also distinguish fixed-rotation from stochastic systems. For example, if a natural fire-return interval is 100 years, and a 100-year clearcut

rotation is implemented to mimic natural rates of disturbance, the average

stand age in the managed forest will be 50 years. In a stochastic system

with a negative exponential stand-age distribution, however, the same

landscape would have an average stand age equal to the fire-return interval,

or 100 years.

Assuming that the scale of disturbance corresponds with the movement

capabilities of individual lynx, landscapes generated through these stochastic processes would provide an amenable environment for lynx by

producing areas of young, dense forest without removing the older elements. If the natural fire regime can be estimated for an area that is to be

managed for lynx, then it is logical to use this rate to design management

strategies. The overall rate of disturbance would be an aggregate of the

cumulative effects of timber harvest, fire, and other natural disturbances

(catastrophic windthrow or insect epidemics) on age structure. Therefore,

in areas subjected to large wildland fires, or where inholdings are managed

for short-rotation timber yield using even-aged management, timber harvest (including salvage) may be inappropriate for decades. In some regions,

significant amounts of wilderness or National Park land will be part of the

planning area, and management of natural fires must be incorporated into

planning. We assume here that fire and timber harvest are similar processes

in their capacity to initiate secondary succession. In addition, we would

argue for a planned rate of disturbance somewhat less than the historically

derived estimate. It is easy to increase the disturbance rate if desirable, but

much harder to recover old-growth forests removed through overly aggressive management.
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McKelvey—Chapter 15

Spatial Patterns Resulting from Natural

Disturbance Processes

Applying the negative exponential model has been suggested as an

ecosystem management approach (Johnson et al. 1995), and does conform

to many of Christensen et al.’s (1996) required properties: it produces

sustainable patterns, maintains ecosystem complexity, and is primarily

derived from an analysis of natural processes, specifically fire. It does not,

however, directly address the larger scale issues of landscape pattern and

connectivity. In these regards the model is neutral; it can be applied in a

variety of configurations.

In even-aged timber management systems employing clearcutting, harvest units are generally similar in size (Fig. 15.1d). For example, a maximum

clearcut size of 40 ac (16 ha) has been mandated on Forest Service lands for

many years. Fires come in many sizes, however. In most forested landscapes, the majority of fires are small, whereas the majority of acreage

burned has resulted from a few, very large fires (Chapter 3). Although this

pattern is probably not feasible or even desirable as a management goal

outside of wilderness, there are many advantages associated with producing fewer, larger cutting units. A disturbance pattern characterized by a few

large blocks (Fig. 15.1b) is desirable if large areas of interior forest habitat

are a management goal, or if processes associated with high edge densities,

such as predation, competition, or nest parasitism, are potentially serious

problems. It also vastly decreases the number of roads that need to be built.

Lower road densities mean less sediment and mass failure into streams,

reduced interactions between people and native biota, and slower invasion

by exotic weed species. Costs of road construction and maintenance are

decreased and, if a site is to be broadcast burned, the cost per acre declines

as the area to be burned increases.

Juxtaposition of Habitat

The application of a fixed rotation age, in addition to the negative consequences of truncating the forest age distribution, also produces fixed

landscape geometries (Fig. 15.1d). Once an area is cut, it is not scheduled to

be re-entered (except for thinning) until it is again at rotation age. Because the

adjacent areas will be younger than the rotation age, the next cut will

conform to the original boundaries. Even if protected reserves are embedded

within an even-aged rotation system, only a relatively small number of

age juxtapositions and geometries are possible within each landscape.
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Chapter 15—McKelvey

However, the juxtaposition of stand ages in a variety of configurations and

the edge habitats that result may provide essential ecological complexity at

the landscape scale. A predator that needs thermal cover and nest sites in

large snags or down logs typically found in old-growth forests, may forage

in herbivore-rich early seral stands if they are nearby. For example, northern

spotted owls use edge areas between old and young forest preferentially in

those areas where young forests contain high concentrations of woodrats

(Zabel et al. 1995). Additionally, most organisms have habitat requirements

that change seasonally or stochastically; what is optimal in the summer may

not be optimal in the winter, and what is optimal in a mild winter may not

be useful during extreme conditions. By developing forests with a mixture

of young and old stands in a variety of spatial combinations, we are likely to

provide habitat requirements for a broad array of organisms.

Stand selection by fire in the taiga is not truly random, but it is more so than

in the southern boreal forest types of the contiguous United States. In more

southern areas, natural barriers and topographic features such as slope and

aspect may provide locations where older forest is more likely to be found.

These “refugia” (e.g., Camp et al. 1997) are not permanently fixed on the

landscape, but tend to be located in areas that are infrequently disturbed,

such as moist sites with topographic protection from wind. Northern

aspects and areas near stream confluences are likely to become refuges

from fire, whereas steep south- and west-facing slopes are likely to be

burned more often. Locally-defined habitat conditions, such as these, should

be used to develop spatially explicit landscape configurations.

Heterogeneity at the Local Scale

Although individual lynx may respond to landscape conditions at the

scale of 50-100 km2

, their primary prey species respond to much smaller

scale patterns, on the order of 1-10 ha. A landscape-scale management

strategy that emphasizes stochastic models does not prescribe the size or

location of treatments on the landscape, nor does it foreclose options

concerning the types of treatments involved; treatments can include either

timber harvest or prescribed fire. Additionally, activities on private lands,

and naturally occurring events such as lightning fires, wind-throw, insectinduced mortality, etc., also need to be factored into landscape planning.

Some of these events and activities may be predictable, while others will be

surprises. Accordingly, management strategies must be flexible at several

spatial scales.

Snowshoe hares generally occur in areas of dense forest cover, including

shrubs and “doghair” thickets of small trees (Chapters 6 and 7). These

structures are common in naturally regenerating areas after fire, but do not
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McKelvey—Chapter 15

result from standard, even-aged forestry practices (Daniel et al. 1979). Thus,

we believe that natural regeneration and stand development will likely

benefit hares and, ultimately, lynx. Creative silviculture is required when

management goals extend beyond wood production. This might translate to

heavier reliance on natural regeneration after wildland fires. Where harvest

mandates artificial regeneration in a short time frame, the planting might be

clustered such that the time of early seral dominance will be spatially

variable across a unit. If pre-commercial thinning is considered, it should be

recognized that the usual objective of increasing the diameter growth of

residual trees may be inappropriate for lynx. Leaving some doghair stands

may be good for lynx; thinning others so heavily that additional conifer

regeneration occurs in the unit may also be appropriate. Because fires leave

large amounts of woody material standing and down, management should

also leave substantial amounts of woody material in representative size

classes, regardless of treatment.

The planning area also needs to encompass transitional areas between

what is considered suitable habitat for lynx. Although the role of such

areas in maintaining lynx populations is poorly understood, the condition

of these areas will likely affect movement and survival during dispersal.

For example, in lower elevation zones with mixed-severity fire regimes

and fire-resistant trees, such as western larch, it may be appropriate to

leave green trees on site. Large units may contain a variety of silvicultural

treatments (e.g., clearcuts, as well as areas of green-tree retention at

various stem densities) that grade into one another. In these transitional

areas, some proportion should be treated with overstory removal significant enough that dense conifer regeneration will result, unless such areas

already exist.

Minimum Area and Age-Class Requirements for

Applying the Negative Exponential Model

We have argued that effective management of wide-ranging species, such

as the lynx, requires planning at large spatial scales. In this context, it is

important to note that stochastic disturbance processes only approach

equilibrium at large spatial scales. With a negative exponential age distribution, very old forests, which make up a relatively small proportion of the

landscape, will be lost by chance alone if planning is done at too small a scale.

Johnson et al. (1995) provide equations for estimating the appropriate scale

based on fire-return interval, projected age of oldest patch, average patch

size, and size of the management unit. Because historic fire-return intervals

vary substantially among southern boreal forests (Chapter 3), spatial planning should be based on sub-regional fire-return intervals.
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Knowledge of historic patch sizes will enable some rough ideas of minimum area. If stand ages are distributed according to the negative exponential model, the largest patch should be a small proportion of the total

landscape. Assuming 10% as the maximum size for a “small” proportion,

and applying this to the north-central Washington landscape discussed

earlier in this chapter where fires of 20,000 ha have occurred (e.g., the 1988

White Mountain fires), the minimum planning area might be 200,000 ha

(2,000 km2

). If we were less conservative and chose 20%, the minimum

area would be 1,000 km2

. This range of 1,000 to 2,000 km2 compares

favorably with the minimum estimate of 1,250 km2

 derived from lynx

studies conducted in that area. The size of planning areas need to be based

on local conditions and must be linked at broader scales, but these estimates

provide a general sense of the scale at which planning would need to take

place.

The management approach we have suggested for the conservation of

lynx is to imitate the stochastic process of fire by managing for a stand age

distribution that approximates the negative exponential model (Fig. 15.1a

and 15.1b). Because this model results in an equilibrium distribution of

forest age classes, standard methods can be used to estimate sustainable

value and volume (McKelvey and Lamberson 1994). This management

model is not as difficult to implement as it may seem. The stochastic process

being modeled does not need to be randomized in the formal sense; deterministic processes can achieve the same patterns. In fact, within the overall

planning area, there is a great deal of freedom concerning the placement

and size of management units and the timing of management activities.

Any stand can be disturbed at any time as long as the proportions associated

with that stand type within the planning area are not exceeded. Accordingly, this strategy is much more spatially flexible than a fixed-rotation

system, but it requires larger spatial and temporal frames than have been

used historically.

Compatibility of Lynx Conservation with Other

Resource Management Objectives

Both the regulatory requirements of state and federal resource management agencies and the concepts embodied in ecosystem management preclude the implementation of a lynx conservation strategy across a broad

geographic area that fails to adequately address other resource values,

especially the habitat needs of threatened or sensitive species. We propose

that other resource management objectives, even those that may conflict in

various ways with the needs of lynx, can be accomplished within the context
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McKelvey—Chapter 15

of a habitat management strategy that mimics large-scale stochastic disturbance regimes. A key component of the negative exponential model is that

it represents an adaptable and flexible management system, not one with

rigid constraints on management options. On the contrary, the dynamic

nature of the negative exponential age distribution in both time and space,

provides a variety of opportunities for adjusting management actions to

meet alternative objectives.

In southern boreal forests, other forest carnivores, including the marten,

fisher, and wolverine, are also of conservation concern, but have habitat

requirements that differ in many ways from those of the lynx (Ruggiero et

al. 1994). Although providing for the habitat needs of these species may

conflict with management of lynx habitat at the stand scale, the flexibility

inherent in the negative exponential model should enable the attainment of

multiple management objectives. In the remainder of this section, we use

these three species to present examples of how applying this model to

lynx conservation can be compatible with management for species having

divergent habitat requirements.

American martens occupy mesic coniferous forests throughout boreal

regions of North America, but generally attain their highest densities in

late-successional stands with high levels of structural heterogeneity

(Buskirk and Powell 1994). In addition, recent work by Hargis et al. (1999)

in Utah suggests that interior forest conditions may provide essential

breeding habitat for martens. Both martens and lynx occupy habitats characterized by snowy winters, and their ranges overlap extensively in northern portions of the Rocky Mountains, Cascade Range, and northeastern

United States. Thus, management of habitat for lynx, especially the creation

of early successional stands for snowshoe hare habitat, will impact martens

in these regions. Under a stochastic disturbance regime, the resulting successional landscape would provide islands of old-growth habitat nested within

an area managed for lynx. However, when applying the negative exponential model, the areal distribution of stand ages is flexible; within the conservation area, a given forest age class could be dispersed, clumped, or a

combination of both. Thus, if a primary management objective was to

provide habitat for a resident population of martens, or other species closely

associated with late-seral forest conditions, older age classes could be

clumped so that one or several areas contained high proportions of old

growth and interior forest habitat.

Habitats occupied by fishers are similar to martens, but fishers are not as

strongly associated with late-successional forests or deep snowpacks (Powell

and Zielinski 1994). Fishers occupy a variety of stand ages but prefer forests

with high canopy closure and complex structures near the ground. Unlike

martens, fishers are not well adapted for traveling or hunting in snow and
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Chapter 15—McKelvey

generally occupy low to mid-elevation forests where deep, soft snow does

not accumulate. Although fishers are sympatric with lynx in much of

Canada and in some portions of the northeastern United States, historical

and current records indicate little overlap in habitats used by these species

in the western mountains. Thus, it is unlikely that management of highelevation boreal forest habitats for lynx will have adverse effects on fisher

populations. Because lynx may use lower elevation habitats to move between patches of boreal forest, however, lower elevation zones may

contain fisher habitat. Thus, if a management objective was to provide

habitat for fishers, a manager might restrict clearcutting or other timber

harvest activities designed to create snowshoe hare habitat to upper elevations, where lynx are most likely to occur, but maintain stands at lower

elevations in older age classes having high levels of canopy closure. In

addition, silvicultural prescriptions designed to provide a diversity of large

forest structures in areas of potential fisher habitat would provide den and

rest sites and increase prey availability for both martens and fishers.

Wolverines occupy a broader range of vegetation zones than other

forest carnivores, including boreal forest, alpine, and tundra habitats. It

has been argued that good wolverine habitat is best defined in terms of an

adequate food supply in areas of low human density; however, the habitat

ecology of wolverines in western montane boreal forests has been studied at

only a few localities (Banci 1994; Copeland 1996, unpublished). Because the

spatial requirements of wolverine exceed those of lynx (Ruggiero et al. 1994),

areas managed for lynx would be smaller than those required for the

conservation of wolverine populations. However, because these areas will

likely contain components of subalpine and alpine habitats, relatively extensive areas of potential wolverine habitat would be included within areas

managed for lynx. Wolverines generally scavenge for ungulates along valley

bottoms and forage and den in remote, high-elevation areas (Hornocker and

Hash 1981; Magoun and Copeland 1998). Thus, if managers wished to

provide habitat for wolverines, they could pay particular attention in the

planning process to ungulate winter range and other aspects of habitat

quality for ungulates to provide a consistent supply of carcasses for wolverine to scavenge. In addition, wolverines generally avoid areas of human

activity. To limit the threat of human-caused disturbance or mortality,

managers could also restrict access to portions of the landscape where

wolverines are most likely to occur.

Monitoring

The management model we have presented in this chapter represents

a conservative approach, but is largely untested. Consequently, the
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McKelvey—Chapter 15

implementation of these ideas should be considered experimental in

nature. Because we are relatively ignorant of the ecological and social

consequences of this type of approach, a comprehensive monitoring plan

must also be established to assess the current status of vegetation and target

species within the planning area and to monitor changes to the landscape

and the biota that result from the implementation of this management

strategy. Unfortunately, most environmental monitoring programs on public lands have not been carried out as planned, nor have they contributed to

decision-making by resource managers or the aversion of biological crises

(Noon et al. 1999). The primary reasons given by Noon et al. (1999) for the

widespread failure of monitoring programs include: a minimal foundation

in ecological theory or knowledge, little logical basis for the selection of

target species, no required understanding of cause-and-effect, no determination of the magnitude of change that would result in a management

response, and no connection between the results of monitoring and decisionmaking. Lynx conservation in the context of ecosystem management cannot

succeed without a scientifically based monitoring strategy that overcomes

the shortcomings of previous monitoring efforts.

An important aspect of our suggested approach to lynx conservation in the

context of ecosystem management is the resultant flexibility in planning

landscape features (i.e., the kinds, amounts, and arrangements of landscape

elements) based on outputs of the negative exponential model. As discussed

throughout this chapter, these outputs include information about patch

sizes and the vegetative composition of modeled landscapes. In many, if not

most, instances the appropriate spatial scale for modeling will subsume

more than one administrative unit. Thus, model outputs will have to be disaggregated across administrative boundaries. To accomplish this, highly

innovative and integrated planning processes will be needed. Innovative

approaches to monitoring the consequences of planning decisions will also

be required. Indeed, the success of this approach will depend on monitoring

the proportions, patch sizes, and arrangements of the vegetation types and

successional stages in each planning area. Given the fundamental importance of pattern as an ecological feature, spatially explicit monitoring to

ensure conformity to desired patterns will be essential.

Within this framework, more traditional monitoring activities will also

need to be performed. Much has been written on this subject (e.g., Goldsmith

1990; Mulder et al. 1999), but the details are beyond the scope of this chapter.

Because a primary objective of management actions will be to enhance

habitat conditions for both lynx and snowshoe hares, monitoring of hare

populations with pellet transects (e.g., Krebs et al. 1987) and lynx populations with snowtracking or other techniques (e.g., Thompson et al. 1981),

will likely be critical components of monitoring strategies. Lastly, we
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Chapter 15—McKelvey

emphasize that effective monitoring programs must include pre-defined

criteria for determining how to interpret monitoring results, and what

actions to take when monitoring indicates the need to modify management

direction.

Conclusions

We believe this approach to conserving lynx populations is compatible

with the need to provide for other sensitive species and with the coarse-filter

approach suggested by ecosystem management. We do not present a detailed template for the implementation of these ideas, because the specific

components of management planning will depend on the natural disturbance regime, current conditions within the landscape, the plant and animal

species that inhabit it, and other management objectives. In all of the

applications of lynx management, however, we recommend the following:

1. Use natural disturbance patterns, in terms of size, frequency, intensity,

and stochasticity for guidance concerning the design and management of

landscapes.

2. Engage in spatially explicit landscape planning within very large

management areas. Lynx metapopulation dynamics operate at regional

scales.

3. Manage for landscapes that contain a continuum of age classes, including both very young and very old forest. Not only is this reflected in patterns

that result from fire and other natural disturbances, but it represents a

prudent conservation policy in the face of uncertainty. In this regard, be

especially cautious with older forests and carefully consider the replacement

time for each forest type and forest element. A large-diameter log may take

hundreds of years to decay; a small clearing can be created in a few weeks.

4. Provide for a variety of regeneration conditions; some areas should be

dense and some more open. Treatments that depend on natural regeneration

will be more likely to produce these patterns than will planting. Leave

individual trees and variable-sized groups of residual elements if natural

disturbance processes suggest these structures are appropriate.

5. Practice adaptive management and consider every action on the landscape to be an experiment. Monitor the efficacy of management actions and

adapt strategies if desired conditions are not being achieved.

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443

Chapter 16

The Scientific Basis for

Lynx Conservation:

Qualified Insights

Leonard F. Ruggiero, USDA Forest Service, Rocky Mountain Research

Station, 800 E. Beckwith, Missoula, MT 59807

Keith B. Aubry, USDA Forest Service, Pacific Northwest Research Station,

3625 93rd Ave. SW, Olympia, WA 98512

Steven W. Buskirk, Department of Physiology and Zoology, University of

Wyoming, P.O. Box 3166, Laramie, WY 82071

Gary M. Koehler, Washington Dept. of Fish and Wildlife,

600 Capitol Way N., Olympia, WA 98501

Charles J. Krebs, University of British Columbia, 6271 University of British

Columbia, 6270 University Blvd., Vancouver, BC V6T 1Z4

Kevin S. McKelvey, USDA Forest Service, Rocky Mountain Research

Station, 800 E. Beckwith, Missoula, MT 59807

John R. Squires, Wildlife Biology Program, University of Montana,

Missoula, MT 59812

Introduction

The information presented in this chapter is based on (1) extant knowledge of lynx ecology, (2) the pertinence of this knowledge to lynx conservation in the contiguous United States, (3) the ecological concepts discussed

in the first section of this book, and (4) the collective interpretation and

judgment of the authors. We have chosen the term “qualified insights” to
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indicate that we know very little about lynx ecology in the United States

and that understandings based on this state of knowledge are necessarily

incomplete. The application of science results in a gradual accretion of

understanding as relatively small increments of knowledge are added to

existing scientific paradigms. This is not to say that the scientific process is

always linear, that intuition and creativity are not crucial aspects of the

process, or that paradigm-changing flashes of insight do not occur. All of

these are elements of the scientific process, but scientific understandings are

generally constructed bit by bit as the result of a sustained commitment to

research. It follows that scientists generally ask questions that are tractable

given the normal tools of scientific investigation, and that large, complex

problems are broken down into manageable pieces. As a corollary to this, it

is inappropriate to expect scientists to solve complex problems in a single

stroke. Yet this is often what ecologists are called upon to do when land

managers and decision-makers find that they lack sufficient understanding

to meet legal mandates for environmental protection. For example, understanding how the viability of lynx populations is affected by human

actions is an extremely complex problem and, because there has not been

a sustained commitment to research, the scientific basis for answering this

question is inadequate. No amount of socio-political clamoring for reliable

answers will change this; uncertainty will prevail.

In the following pages, we have attempted to distill the state of knowledge regarding lynx ecology along with our interpretations about the kind

and quality of understandings that this knowledge conveys. Because the

state of the art is poorly developed for lynx ecology, the first section of this

book was devoted to a presentation of salient ecological concepts. These

concepts provide a partial basis for the scientific interpretations discussed

in Chapter 1. Until additional data are collected, we must assume that

insights based on well-established concepts are valid.

The eleven topics presented below represent crucial areas of ecological

understanding relative to species conservation (Chapter 1). Although we

attempted to offer substantive interpretations in each of these areas, a

lack of information often prevented us from doing so. We elaborate on

these information needs in Chapter 17.

1. Present and Historical Patterns of Lynx

Distribution

During the 1800s and early 1900s, lynx occurred in Colorado, Idaho,

Maine, Michigan, Minnesota, Montana, New Hampshire, New York, Utah,

Washington, Wisconsin, and Wyoming. Relatively few records occur in
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other states. Based on an extensive review of historical information,

including trapping records, New Hampshire, Minnesota, Montana, and

Washington appear to have supported the most lynx. A dramatic decline in

lynx numbers appears to have occurred in New Hampshire, where recent

records are scarce. Although records from New York, Colorado, and Utah

have always been scarce, the lack of recent verified records suggest that lynx

may have been extirpated from these states (Chapter 8). The status of

lynx in the remaining states is unknown.

Extant lynx populations in Washington, Montana, and perhaps Maine

occupy habitats that are contiguous with habitats in Canada. It is likely that

prior to extensive human development adjacent to the St. Lawrence Seaway,

lynx populations in New Hampshire also occurred in habitats that were

contiguous with similar habitats in Canada (Litvaitis et al. 1991). In

addition, trapping records indicate that lynx populations in Montana,

Minnesota, and Washington appear to have cycled in lagged synchrony

with lynx populations in Canada during the population highs of the

1960s and 1970s (Chapter 8). The only other known population of lynx is in

Wyoming (Chapter 11). This population is thought to be small, is adjacent to

extensive park and wilderness areas, and is located within the Greater

Yellowstone Ecosystem.

We conclude that extensive areas of contiguous suitable habitat are needed to

ensure viable lynx populations. All areas in the contiguous United States where we

can state with certainty that lynx currently occur are directly connected to

larger habitat areas. Apparently, lynx are unlikely to persist in relatively small,

isolated refugia of suitable habitat. In saying this, we acknowledge a very

incomplete understanding of what constitutes suitable lynx and hare habitat in

the contiguous United States.

2. Factors Limiting the Geographic Distribution

of Lynx

Most lynx records in North America are found in boreal forests

(Chapter 8). In the Great Lakes states, most records are in the Mixed

Deciduous-Coniferous Province, and, in the northeastern states, most

records are in the Mixed Forest-Coniferous Forest-Tundra Province

(provinces after Bailey 1998). In the western mountains of the United States,

most records are in the Douglas-fir, western spruce/fir, and fir/hemlock

vegetation types (Kuchler 1964). All of these types can be characterized as

mesic coniferous forests with cold snowy winters. Lynx have morphological adaptations for moving and hunting in snow as exemplified by

significantly lower foot loadings than most carnivores (Chapter 4). Records
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from Washington, Wyoming, and Utah/Colorado show that lynx occur at

higher elevations as one moves south, with modal elevations of 2,000 m,

2,700 m, and 3000 m, respectively (Chapter 8). In addition, it is generally

agreed that lynx distributions are limited by the availability of snowshoe

hares (Chapter 9).

Other than cool, snowy, conifer forests and snowshoe hares, we have not

identified additional factors that limit the distribution of lynx. However, this

does not mean that additional factors do not exist. Indeed, there are geographic areas that appear to have the necessary features to support lynx, yet

lynx occurrence records are scarce or absent from these areas. Three such

areas are the Cascade and Coast Ranges in the western United States, the

southern Rocky Mountains, and the Great Lake States (except for the

extreme northeast corner of Minnesota). Assuming that adequate densities

of snowshoe hares exist in these areas, the lack of lynx records indicates

that there are factors controlling the distribution of lynx that we do not

understand.

We conclude that at the broadest geographic scale, lynx distribution is limited to

moist, cool boreal forests that support some minimum density of snowshoe hares

(e.g., at least 0.5 hares/ha in northwestern Canada but unknown farther south).

Lynx are also limited to areas with snowy winters, likely because of their coadaptation with hares and because snow gives lynx a competitive advantage over other

carnivores. In the West, lynx are uncommon or absent in coastal forests, possibly due

to limiting abiotic factors.

3. Principal Habitat Features Affecting Lynx

At the stand level, lynx use a variety of forest types and a broad range of

stand ages. Our limited understanding of lynx in the southern part of

their range suggests that, as in the North, lynx use habitats with abundant

snowshoe hares. However, hare density alone may not be the most crucial

factor in lynx hunting success or in habitat selection by lynx. It is unclear how

habitat structure affects the vulnerability of hares to capture by lynx.

Northern studies suggest that lynx require hare densities of 0.5-1.0 hares/ha

to persist, but farther south this relationship may differ. In the North, when

hare densities fall below this threshold, lynx expand their home ranges,

increase daily travel distances, suffer increased adult mortality, and stop

reproducing (Chapter 9). Additional information on this relationship is a

critical research need for southern populations.

Limited evidence for the southern part of the range suggests that lynx

are associated with mesic forest types, and that dry forest types (e.g.,
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ponderosa pine) are used mostly to move among mesic stands. These

mesic forest types are southern extensions of boreal forests, commonly

dominated by spruce and fir, Douglas-fir, and lodgepole pine. In the

southern part of the range, these types occur as islands and peninsulas

within a matrix of drier, montane forest, typically dominated by lower

elevation conifers (Chapter 8).

Dense, small-diameter woody vegetation supports high hare densities

and, thus, is important for lynx. Such conditions are created by natural

disturbances of varying sizes, including gap-phase processes found in lateseral forests (Chapter 14). The successional processes responsible for the

creation of the structural features associated with hare habitat are controlled by complex moisture/temperature gradients. Thus, the availability,

abundance, and community association of these habitats is spatially variable. However, in the drier portions of lynx range, hare habitat may be

increasingly associated with more mesic late-seral forests and riparian areas

(Chapter 14). Although areas of regenerating forest created by natural or

human-made disturbances can provide important hare habitat, such areas

are temporally transient. On the other hand, late-seral forest appears to be

moderately productive for hares, very productive for red squirrels, and

temporally more stable. The pattern of hare habitat that is optimal for lynx

is unknown and represents a critical information need. The negative exponential forest model provides a range of stand ages (Chapter 15) and holds

potential as a basis for ensuring persistent populations of hares and lynx.

Limited data for southern areas suggest that lynx den in forested sites with

relatively large, complex physical structure near the ground, primarily in the

form of coarse woody debris. The optimal size and arrangement of such

sites is unknown and constitutes another critical information need.

We conclude that a snowshoe hare density greater than 0.5 hares/ha is likely

required for lynx persistence. Hare habitat occurs in a range of stand ages, including

regenerating disturbed stands and late-seral forest. Regenerating stands can be

highly productive for hares, but such stands are temporally transient. Late-seral

forests tend to be moderately productive for hares but also produce red squirrels and

are temporally stable. For lynx to persist, a range of stand ages may be necessary to

provide adequate habitat for hares and for denning. However, on drier sites where

regeneration is sparse, the value of regenerating stands as hare habitat may be

diminished relative to the value of late-seral stands. The negative exponential forest

model provides a range of stand ages and thus provides a possible template for

landscape management. Our generally poor understanding of lynx-habitat relationships at all spatial scales hampers the development of specific habitat-management

prescriptions.
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4. Food Habits of Lynx

Snowshoe hares are the primary prey of lynx throughout its range; in

studies conducted to date, hares comprised 33-100% of lynx diets. However,

when hares are scarce, red squirrels are an important alternative prey

(Chapters 9 and 13). In addition to hares and red squirrels, lynx diets include

ground squirrels, voles, grouse, ungulates, and carrion. However, a predominance of hares in the diet is believed to be an important determinant of

reproduction and recruitment in the taiga, where studies have shown that

when lynx diets were composed primarily of species other than hares,

productivity approached zero (Chapter 9). Very little is known about lynx

diets during snow-free periods, yet foraging ecology during these periods

may be an important determinant of habitat use and survival during

dispersal and of survival through the critical period of food shortage in the

spring. Hence, a more comprehensive understanding of seasonal diets

represents an important research need.

We conclude that snowshoe hares are the dominant prey of lynx throughout its

range, but that red squirrels are an important alternative prey, especially if hares are

scarce. However, available evidence suggests that lynx populations are not likely to

persist where snowshoe hares do not predominate in the diet. Research is critically

needed on lynx food habits in southern boreal forests during both snow and snowfree periods.

5. Habitat Requirements of Key Prey Species

Two key prey species for Canada lynx are snowshoe hares and red

squirrels. Snowshoe hares are limited to forested landscapes in snowy

climates. Hares are closely associated with low, woody vegetation and are

most abundant in stands with high densities of small-diameter stems.

Hares are most likely to occur in coniferous stands or mixed coniferousdeciduous stands, but in some areas pure stands of deciduous forest are

occupied (Scott and Yahner 1989). The critical habitat element for hares is

horizontal structure, which serves as both food and cover (Chapter 7).

Given the appropriate environmental conditions, this dense vegetation is

associated with early seral conditions (e.g., regenerating young stands).

This vegetation structure is also associated with late-seral conditions

(e.g., in gaps that are part of the natural heterogeneity of old-growth stands

- see discussion under item 3 above). Cover for protection from predation

is more important than cover as a food source for hares in northern

populations (Chapter 6). Reducing dense horizontal structure through

silvicultural thinning will likely reduce an area’s carrying capacity for

snowshoe hares.
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Red squirrels are closely associated with mature, cone-bearing coniferous

forest for food and shelter (Klenner and Krebs 1991; Larsen and Boutin 1995).

Densities of pine squirrels, including both red squirrels and the closely

related Douglas’ squirrel, tend to be highest in late-successional forests with

relatively high amounts of coarse woody debris (Buchanan et al. 1990; Kemp

and Keith 1970; Rusch and Reeder 1978). Red squirrels are generally absent

in regenerating forests that lack cone production.

We conclude that to support abundant snowshoe hare and red squirrel populations, landscapes must contain forested areas with low, dense horizontal structure

and late-successional areas with cone-bearing trees and coarse woody debris. The

optimal amounts and arrangement of these elements relative to lynx persistence is

unknown and represents a critical research need (see Chapter 15 for additional

discussion).

6. Population Dynamics of Key Prey Species

A key assumption about southern snowshoe hare populations has been

that they are relatively stable, in contrast to the dramatic fluctuations seen in

northern hare populations (Keith 1990). However, available evidence suggests that southern hare populations may be less stable than previously

thought (Chapter 7). Some populations in the Lake States show strong

fluctuations over relatively long time intervals, including some evidence of

synchrony with northern hare populations. Very limited evidence from

hare populations in the western United States is suggestive of fluctuations, but hare populations in the West have been insufficiently studied and

their dynamics remain largely unknown. In northern hare populations,

predation and food interact to drive changes in numbers (Krebs et al. 1995).

The causes of population fluctuations in southern hares are unknown, and

we do not know how the fragmentation of hare habitat in the south may

influence hare dynamics.

Red squirrel populations throughout their geographic range appear to be

food-limited, with conifer cone crops driving their population changes.

Predation appears to be relatively unimportant to northern red squirrel

populations (Stuart-Smith and Boutin 1995), but the impact of predation on

southern red squirrel populations is unknown.

Red squirrel populations fluctuate but they likely do so independently of

snowshoe hare populations. Since red squirrels are important alternative

prey when and where hares are scarce, a coincidence of low hare and low

squirrel numbers would likely be a significant cause of mortality in foodstressed lynx populations.

We conclude that some southern snowshoe hare populations fluctuate strongly

and that, in general, southern populations are likely not as stable as previously
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thought. Depending on the strength and ubiquity of such fluctuations, southern

lynx populations may also be less stable than previously believed. Red squirrel

populations fluctuate with conifer cone crops in both the North and the South. The

fact that populations of these two key prey species exhibit strong population

fluctuations has potentially important implications, i.e., such fluctuations could

result in local extirpations of lynx if prey populations bottom-out simultaneously.

7. Principal Community Features Affecting Lynx

Various mammals and birds, including coyotes, cougars, bobcats, fishers,

great-horned owls, and goshawks may compete with lynx. This competition may reduce available food for lynx and may also result in their

displacement or death (Chapter 4). The number of generalist competitors

with lynx increases from the northern part of the range to its southern

periphery. Moreover, the increased fragmentation of habitats near the

southern periphery of the range, and habitat fragmentation in general,

may give generalist predators a competitive advantage over lynx. Cougars are locally sympatric with lynx in the western United States during

snow-free periods and available evidence suggests they may be an important source of lynx mortality. Coyotes appear to be especially effective

competitors with lynx in human-dominated landscapes. Coyotes have

expanded their range into the northeastern United States since 1970 and

appear to represent an important factor in lynx ecology there. Based on

research in the North, humans facilitate coyote access into areas occupied by

lynx by compacting snow with snowmobiles, snowshoes, or skis. However,

in the southern part of the range few data address competition between

coyotes and lynx.

We conclude that, in the contiguous United States, competitors, especially the

cougar and coyote, likely influence lynx recruitment and survival. Factors that

facilitate movement of generalist predators into areas occupied by lynx should be

considered a conservation risk. However, data addressing these relationships are

very few, and a better understanding of community interactions, and the ways in

which landscape pattern may mediate these interactions, is a key research need.

8. Principal Factors Affecting Lynx Movements

and Dispersal

Knowledge of a species’ movements and dispersal capabilities is critical to

the conservation of fragmented, peripheral populations. In northern populations, lynx movements up to 1,000 km have been recorded (Chapter 9), and

limited data from southern lynx populations documents movements in
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excess of 100 km (Chapter 13). However, even though long-distance movements may be characteristic of lynx populations, we have no empirical basis

for tying such movements to successful dispersal (i.e., establishment of a

home range and subsequent reproduction). Understanding the basis for

successful lynx dispersal is therefore a key research need with important

implications for conservation (Chapters 2 and 8).

Lynx readily move across landscapes fragmented by conventional industrial forestry (Chapter 11). Documented lynx movements have involved

crossing open valley bottoms and large rivers (Chapter 13); thus, these

landscape features are not absolute barriers to dispersal. Although the effect

of roads on lynx movements, dispersal, and demographics has not been

studied, we have anecdotal accounts of lynx crossing roads of various types.

Additionally, we have reliable lynx occurrence records (mostly from trapping) in areas very distant from forested zones (Chapter 8). Assuming these

lynx were dispersing from the nearest forested areas, highways were

crossed prior to their capture. Although 16 of 83 lynx translocated into

New York were killed by vehicles, none of the 89 resident lynx that have

been studied with radiotelemetry in southern boreal forests were roadkilled (Chapter 13). Although limited, these observations do not support the

hypothesis that roads represent a significant mortality factor for lynx.

We conclude that lynx can move long distances, but we do not know if these

movements result in successful dispersal or the augmentation of distant populations. Existing data, though sparse, do not indicate that roads are a major mortality

factor for lynx. However, the indirect effects of roads on lynx populations, including

the effects of urbanization along highway corridors, are unknown.

9. Key Demographic Properties and Dynamics of

Lynx Populations

Northern lynx populations cycle with hares and dispersal is highest

after hare populations start to decline (Chapter 9); we do not know if

southern populations behave similarly (Chapter 13). We know little about

lynx densities in the southern part of the range, but evidence suggests that

they are comparable to those at cyclic lows in the North. In the North, lynx

are highly fecund and can double their population size every year under

optimal conditions, but the reproductive potential and factors affecting

fecundity in southern populations are unknown.

Theory suggests that the risk of local extinction increases due to spatially

and temporally correlated population fluctuations. Lynx populations in the

southern part of the range appear to be small (Chapter 8). Small population

size, particularly in combination with population fluctuations, predisposes
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these populations to the risk of local extinction (Chapter 2). The probability

that such populations will persist depends on many factors, including the

degree to which they interact with other populations within a metapopulation

structure. However, metapopulation structure per se does little to ensure

persistence when colonization rates are low and population sizes are very

small.

Occupancy of habitat islands in a metapopulation will be governed by

rates of colonization and extinction (Chapter 2). For most of the islands to be

occupied most of the time, rates of colonization need to greatly exceed rates

of local extinction. Dispersal to distant islands from other islands with small

populations is unlikely, and even successful dispersal frequently will not

result in successful colonization. Population size, distance, and barriers to

dispersal between islands are therefore critically important to the stability

of the metapopulation. Reductions in population size on the islands

simultaneously increases extinction rates and decreases rates of colonization. The removal of habitat islands through land conversion or through

large disturbances increases the distance between the remaining islands,

and therefore also decreases colonization rates. To maintain a stable

metapopulation, it is therefore critically important to maintain or increase

the carrying capacity of all areas capable of supporting lynx.

We conclude southern lynx habitat must provide for local recruitment and

survival. Additionally, southern lynx populations may require immigration from

larger contiguous habitat areas. In cases where local populations are relatively small,

dispersal rates must be sustained and, in some cases, substantial in order to be

effective (from a demographic vs. a genetic standpoint). We know virtually nothing

about the vital rates of southern lynx populations, thus assessments of population

viability via demographic modeling are not possible. Additional information regarding the influence of prey abundance on lynx population dynamics is critically

needed.

10. Geographic Variation Among Lynx Populations

All widespread species show some degree of geographic variation

among populations. Variation may be primarily inherited or it may be

largely based on the responses of individuals to local environments.

Regardless of the mechanism, variation among populations can influence

fitness and is often adaptive, meaning that populations within species are

usually not interchangeable parts (Chapter 5). Knowledge of geographic

variation among populations is therefore important for conservation, yet we

know little about how much geographic variation exists among lynx populations. Conventional wisdom suggests that highly mobile species may
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show little geographic variation, but we cannot assume this for lynx without

data, especially considering the broad range of environments occupied by

lynx (Chapter 14). In general, variation among populations has important

ramifications for conservation, including identification of distinct population segments, the consequences of translocations, and the degree to which

ecological understandings apply from one population to another.

We conclude that we know little about geographic variation in lynx, and thus the

transfer of either knowledge or animals from northern to southern populations

entails significant conservation risks. Moreover, this knowledge gap hampers the

identification of potentially distinct population segments for conservation purposes.

Understanding the range of genetic, ecological, and behavioral variation among

lynx populations is a high research priority.

11. Direct Human Influences on Lynx

Direct human influences on lynx include trapping and shooting, vehicle

collisions, and behavioral disturbance. Except in Montana, lynx trapping

seasons are closed throughout the contiguous United States but lynx may be

trapped incidentally or illegally. Evidence from northern areas indicates that

when lynx densities are low, human-caused mortality adds to natural

mortality (Chapter 9). This means that incidental or illegal killing can

significantly affect lynx population dynamics under some circumstances.

The effects of recreational activities on lynx populations have not been

studied. However, limited anecdotal observations do not support the hypotheses that snowmobiling, ski touring, or hiking result in significant

behavioral disturbance to lynx. Winter trails may impact lynx indirectly

by providing increased access to competitors, especially coyotes (Chapter 4).

It seems likely that disturbance at den sites could increase the vulnerability

of kittens to a variety of threats. Lynx exhibit some indifference or curiosity

toward humans, which may predispose them to hunting or trapping

deaths. Although there is no empirical basis for concluding that roads

represent a major mortality source for lynx (Chapter 13), fenced roads and

highways or development along transportation corridors may impede lynx

movements (Chapter 12).

We conclude that there is little empirical information on the direct effects of

humans on lynx in southern boreal forests. However, trapping for other large

furbearers in areas occupied by lynx may pose a risk. Lynx appear to be extremely

susceptible to trapping, and where trapping is permitted it can be (and has been) a

significant source of mortality. We cannot extrapolate conclusions about the

minimal effects of trapping on northern lynx populations to the historical or

potential effects of trapping in southern boreal forests.
454

Chapter 16—Ruggiero

Conclusions

In this Chapter, we have addressed 11 areas of knowledge that are

fundamentally important when planning the management or conservation

of any species. In many instances, we were quite tentative in putting

forth even “qualified insights” due to a lack of empirical information. When

this happened in areas of particular importance, we explicitly included

statements of research need as part of our conclusions. In the following

chapter we build on these conclusions and present a program of research for

closing critical gaps in our knowledge of lynx ecology and natural history.

Literature Cited

Bailey, R. G. 1998. Ecoregions map of North America; explanatory note. USDA Forest

Service, Miscellaneous Publication 1548, Washington, DC.

Buchanan, J. B., R. W. Lundquist, and K. B. Aubry. 1990. Winter populations of Douglas’

squirrels in different-aged Douglas-fir forests. Journal of Wildlife Management

54:577-581.

Kemp, G. A. and L. B. Keith. 1970. Dynamics and regulation of red squirrel (Tamiasciurus

hudsonicus) populations. Ecology 51:763-779.

Keith, L. B. 1990. Dynamics of snowshoe hare populations. Pages 119-195 in H. H. Genoways,

editor. Current mammalogy. Plenum Press, New York.

Klenner, W. and Krebs, C. J. 1991. Red squirrel population dynamics. I. The effect of

supplemental food on demography. Journal of Animal Ecology 60:961-978.

Krebs, C. J., Boutin, S., Boonstra, R., Sinclair, A. R. E., Smith, J. N. M., Dale, M. R. T., Martin,

K., and Turkington, R. 1995. Estimation of snowshoe hare population density from turd

transects. Canadian Journal of Zoology 65:565-567.

Kuchler, A. W. 1964. Potential natural vegetation of the conterminous United States (map

and manual). American Geographical Society Special Publication 36. 116 p.

Larsen, K. W. and Boutin, S. 1995. Exploring territory quality in the North American red

squirrel through removal experiments. Canadian Journal of Zoology 73:1115-1122.

Litvaitis, J. A., Kingman, D., Lanier, J., and Orff, E. 1991. Status of lynx in New Hampshire.

Transactions of the Northeast Section of the Wildlife Society 48:70-75

Rusch, D. A. and W. G. Reeder. 1978. Population ecology of Alberta red squirrels.

Ecology 59:400-420.

Scott, D. P. and Yahner, R. H. 1989. Winter habitat and browse use by snowshoe hares,

Lepus americanus, in a marginal habitat in Pennsylvania. Canadian Field-Naturalist

103:560-563.

Stuart-Smith, A. K. and Boutin, S. 1995. Predation on red squirrels during a snowshoe hare

decline. Canadian Journal of Zoology 73:713-1722.
455

Chapter 17

Conservation of Lynx

in the United States:

A Systematic Approach

to Closing Critical

Knowledge Gaps

Keith B. Aubry, USDA Forest Service, Pacific Northwest Research Station,

3625 93rd Ave. SW, Olympia, WA 98512

Leonard F. Ruggiero, USDA Forest Service, Rocky Mountain Research

Station, 800 E. Beckwith, Missoula, MT 59807

John R. Squires, Wildlife Biology Program, University of Montana,

Missoula, MT 59807

Kevin S. McKelvey, USDA Forest Service, Rocky Mountain Research

Station, 800 E. Beckwith, Missoula, MT 59807

Gary M. Koehler, Washington Department of Fish and Wildlife,

600 Capitol Way N, Olympia, WA 98501

Steven W. Buskirk, Department of Physiology and Zoology, University of

Wyoming, P.O. Box 3166, Laramie, WY 82071

Charles J. Krebs, University of British Columbia, 6270 University Blvd.,

Vancouver, BC V6T 1Z4 Canada
Chapter 17—Aubry

456

Introduction

Large-scale ecological studies and assessments are often implemented

only after the focus of study generates substantial social, political, or legal

pressure to take action (e.g., Thomas et al. 1990; Ruggiero et al. 1991; FEMAT

1993). In such a funding environment, the coordinated planning of research

may suffer as the pressure to produce results escalates. To avoid haphazard

research and to maximize the benefits to lynx conservation with limited

research funds, a carefully coordinated approach to lynx research is needed.

The purpose of this chapter is to provide a systematic framework and

rationale for conducting future research in ways that will maximize the

applicability and utility of new information.

Research on the ecology of rare and sparsely distributed vertebrates, such

as the lynx, is often opportunistic because research must be conducted on

populations that are large enough to allow rigorous scientific investigation.

Even an intensive, long-term study of a few individuals results in anecdotal

information that may or may not represent the population of interest.

Consequently, populations are often selected for study simply because their

existence and relative abundance is known, and because they are logistically

feasible to study. This opportunistic impetus must be tempered, however,

with the knowledge that the value of such research will be limited if there is

no larger context in which to evaluate study results. Without this context,

there will be no scientific basis for applying results beyond the geographic

or ecological scope of each study.

To avoid these problems, wildlife scientists must expand the scope of

inference by designing research to be representative. To generate reliable

inferences about the biology and ecology of lynx in the contiguous United

States (U.S.), we must conduct multiple studies that encompass the range of

variation in habitats occupied by lynx. The program of research contained in

this chapter is predicated upon such an approach. Throughout this book, we

have stressed that we know relatively little about lynx biology and ecology

in the U.S. (Table 17.1), and we have cautioned against overgeneralization or

inappropriate extrapolation of existing information. We believe the lack of

representative data on lynx in the U.S. to be a significant impediment to

science-based conservation and management.

New research on lynx in the U.S. must address multiple spatial scales and

multiple levels of biological organization. In both cases, studies at lower

strata are logically nested within higher strata. One of the most useful

outcomes of such a hierarchical research approach is that new efforts are

facilitated and augmented by results from studies at both lower and higher

strata. For example, the results of a survey designed to determine lynx
457

Aubry—Chapter 17

Table 17.1—Published and unpublished studies on lynx in the contiguous United States by subject. Studies are listed under all appropriate headings but are indicated with an asterisk (*) the

first time they are listed in the table.

Topic and author Location Method Duration Sample size and summary of results

Distribution and relative abundance

* McKelvey et al. (Chapter 8) Contiguous United States Museum and historical records, trapping N/A 3,865 occurrence records: historical distribution

data, track surveys, questionnaires

Habitat relationships

McKelvey et al. (Chapter 8) Contiguous United States Museum and historical records, trapping N/A 3,865 occurrence records: patterns of association with

data, track surveys, questionnaires broad vegetation types and elevation zones

* Brittell et al. (1989, unpublished) North-central Washington Radiotelemetry 34 months 23 lynx: patterns of association with forest types

* Koehler (1990) North-central Washington Radiotelemetry 25 months 7 lynx: patterns of association with forest

types; 4 maternal dens described

McKelvey et al. (Chapter 10)a North-central Washington Radiotelemetry 76 months 22 lynx: patterns of association with forest types and

topographic features

* Koehler et al. (1979) Western Montana Radiotelemetry 8 months 2 lynx: patterns of association with forest types

* Smith (1984, unpublished) Western Montana Radiotelemetry 23 months 5 lynx: patterns of association with forest types

Squires and Laurion (Chapter 11)b Western Montana Radiotelemetry Montana = 22 months, Montana = 18 lynx, Wyoming = 2 lynx:

and Wyoming Wyoming = 34 months 1 maternal den described in Wyoming

Movements and dispersal

Brittell et al. (1989, unpublished) North-central Washington Radiotelemetry 34 months 23 lynx: 2 long-distance movements documented

Squires and Laurion (Chapter 11) Western Montana Radiotelemetry Montana = 22 months, Montana = 18 lynx: 4 exploratory movements

and Wyoming Wyoming = 34 months documented; Wyoming = 2 lynx: 2 exploratory

movements documented

Smith (1984, unpublished) Western Montana Radiotelemetry 23 months 5 lynx: 1 long-distance movement documented

* Brainerd (1985, unpublished) Western Montana Radiotelemetry 25 months 2 lynx: 1 long-distance movement documented

* Mech (1977) Northern Minnesota Radiotelemetry 25 months 14 lynx: 1 long-distance movement documented

(con.)
Chapter 17—Aubry

458

Demography and population dynamics

Brittell et al. (1989, unpublished) North-central Washington Radiotelemetry and snowtracking 34 months 23 lynx: mean density = 2.0/100 km2; 4 litters: mean

litter size = 2.0; mean annual adult mortality rate = 11%

Koehler (1990) North-central Washington Radiotelemetry and snowtracking 25 months 7 lynx: mean density = 2.3/100 km2; 3 litters:

 mean litter size = 2.7; mean kitten mortality rate = 88%

Brainerd (1985, unpublished) Western Montana Carcasses N/A 18 females: mean litter size = 3.3

Squires and Laurion (Chapter 11) Western Montana Radiotelemetry and snowtracking Montana = 22 months, Montana = 3 litters: mean litter size = 2;

and Wyoming Wyoming = 34 months Wyoming = 2 litters: mean litter size = 3

Relationships with prey

Koehler (1990) North-central Washington Scat analysis 25 months 29 scats: 79% snowshoe hare, 24% red squirrel,

7% deer, 3% white-footed mouse

Community interactions

Brittell et al. (1989, unpublished) North-central Washington Radiotelemetry 34 months 23 lynx: 1 bobcat or lynx kill

Koehler et al. (1979) Western Montana Radiotelemetry 8 months 2 lynx: 1 mountain lion kill

Squires and Laurion (Chapter 11) Western Montana Radiotelemetry Montana = 22 months, Montana = 18 lynx, Wyoming = 2 lynx:

Wyoming = 34 months 2 mountain lion kills in Montana

Human impacts

McKelvey et al. (Chapter 10) North-central Washington Radiotelemetry 76 months 22 lynx: no evidence of road avoidance

Brocke et al. (1991) and K. Gustafson New York Radiotelemetry 24 months 83 lynx translocated from

(personal communication) Yukon: 16 road-killed

aMcKelvey et al. (Chapter 10) is a reanalysis of data collected by Brittell et al. (1989, unpublished) and Koehler (1990). bData presented by Squires and Laurion (Chapter 11) represent preliminary results of ongoing studies.

Table 17.1—Con.

Topic and author Location Method Duration Sample size and summary of results
459

Aubry—Chapter 17

presence or absence at a broad spatial scale (e.g., the western U.S.) provide

the basis for selecting study areas for more intensive research on lynx at

smaller spatial scales (e.g., northeastern Washington). Conversely, habitat

and topographic use patterns derived from intensive studies can help

delineate forest types where lynx surveys should be conducted.

We must know where lynx are before we can identify geographic areas

where more intensive research should be conducted. Some research questions, such as determining the potential metapopulation structure of lynx in

the U.S., cannot be addressed until we adequately describe broad-scale

patterns of habitat occupancy. However, the urgency of ongoing lynx

conservation efforts precludes us from waiting until we have a more

complete understanding of the current distribution of lynx before initiating

new research. We must support and expand lynx research in the U.S. while

comprehensively delineating current lynx range and describing patterns of

relative abundance to provide a framework for planning future research.

Information Needs

We have identified critical knowledge gaps in many of the previous

chapters and emphasized the most important of these in the Qualified

Insights (QIs) presented in Chapter 16. Here, we summarize key information

needs for the conservation of lynx in the U.S.

Distribution and Relative Abundance

We have documented the historical distribution of lynx to the extent

possible with existing information, but we lack a clear understanding of the

distribution or relative abundance of extant populations in the U.S. (Chapter

16 - QI 1). This research need must be addressed before new intensive studies

are initiated. Knowledge of lynx distribution will also provide a framework

for investigating geographic variation among southern lynx populations.

This information is essential for assessing the potential impacts of translocating lynx among populations (Chapter 16 - QI 10).

Habitat Relationships

We have a very limited understanding of lynx habitat relationships at any

spatial scale (Chapter 16 - QIs 2 and 3). Our current understanding of habitat

selection for southern populations comes mostly from research conducted

on a single, relatively small population in north-central Washington. However, populations occupying more xeric coniferous forests or mixed coniferous-deciduous forests may have very different habitat relationships. In
Chapter 17—Aubry

460

southern boreal forests, only a few natal dens have been described, but all

were in late-successional stands with relatively dense understory cover from

large woody debris and other complex structures near the forest floor.

However, timber harvesting designed to improve habitat conditions for

snowshoe hares by creating dense, young stands may eliminate such structures. Management of forest habitats for lynx will be severely constrained

until new information is obtained on their habitat relationships at both small

and large spatial scales.

Movements and Dispersal

Dispersal processes will strongly influence conservation planning for

lynx, especially for small, isolated populations at the southern extent of their

range (Chapter 16 - QI 8). Southern lynx populations may exist in a metapopulation structure maintained by the dispersal of individuals among

“islands” of suitable habitat at varying distances from one another. Although long-distance exploratory movements have been documented in

several southern populations, successful dispersal (i.e., reproducing in an

established home range) has not. Thus, we have no empirical information on

success rates for dispersal, dispersal distances, responses to anthropogenic

and natural barriers, or the use of corridors.

Demography and Population Dynamics

Assessments of the population viability of southern lynx populations will

not be possible without new information on densities, birth rates, adult and

kitten survival rates, and population dynamics (Chapter 16 - QI 9). Limited

data from north-central Washington suggest that lynx populations in southern boreal forests may not exhibit the strong cyclic fluctuations characteristic

of lynx populations in the taiga; however, trapping data from several states

suggest otherwise. High-amplitude fluctuations may have a strong influence on dispersal and connectivity among isolated populations. Thus,

conservation planning for southern lynx populations will be influenced

strongly by the nature of their population dynamics.

Relationships With Prey

Limited data indicate that lynx in southern boreal forests depend on

snowshoe hares as their primary prey, with red squirrels as important

secondary prey (Chapter 16 - QI 4). Management of habitat for snowshoe

hares in southern regions must consider how hare abundances vary along

both ecological and successional gradients. However, patterns of hare
461

Aubry—Chapter 17

abundance in southern boreal forests are not well understood. We do not

know how differences in habitat structure may influence the vulnerability of

snowshoe hares and other prey species to lynx predation.

Community Interactions

Many species potentially compete with lynx for prey (Chapter 16 - QI 7).

Exploitation competition may reduce prey availability and result in displacement of lynx, whereas interference competition may affect lynx habitat

selection and, in extreme cases, lead to intraguild predation. Mountain lions

are absent from the taiga but co-occur with southern lynx populations,

and limited data suggest that they may be an important source of lynx

mortality. Coyotes are very effective predators of snowshoe hares, are

capable of killing lynx, and have recently expanded their range in southern

boreal forests. We do not know if predation affects the population dynamics

of lynx, nor do we understand the nature and extent of competition with

generalist predators or how changes in landscape pattern may mediate these

processes.

Human Impacts

Lynx often appear indifferent toward humans, which may predispose

them to direct, human-caused mortality. The indirect impacts of human

activity may exert a stronger influence on lynx populations but are difficult

to quantify (Chapter 16 - QI 11). The effects of outdoor recreation on lynx

populations have not been studied. Observations suggest that some carnivores, especially coyotes, use compacted snow from snowmobiling, skiing,

or snowshoeing as travel routes. However, we do not know if snow compaction increases predation rates or competition from generalist predators.

Snowshoe Hare Habitat Relationships

In Montana and Washington, limited data suggest that hares may have a

bimodal pattern of abundance, whereby they reach highest abundances in

young, dense stands and old, gap-phase forests. High stem densities in

regenerating forests provide dense horizontal cover that is important for

hares (Chapter 16 - QI 5), and old forests have similar cover in gaps formed

from the death of one or several trees. However, in drier forest types in the

northern Rocky Mountains, where regenerating stands often lack high levels

of horizontal cover, hares may be most abundant in older forests. We do not

understand how patterns of hare abundance change according to forest

type, moisture regime, or successional stage.
Chapter 17—Aubry

462

Snowshoe Hare Population Dynamics

In the taiga, population dynamics of lynx are closely tied to those of

snowshoe hares, and lynx populations fluctuate in lagged synchrony with

hare population cycles. We do not know if this model fits southern lynx

populations. Limited data suggest that southern hare populations are not as

stable as previously believed (Chapter 16 - QI 6), but whether their populations cycle as they do in the taiga, or simply fluctuate stochastically, is

unknown.

A Research Framework

Where Do Lynx Occur?

As of 1999, we have only a general idea of the current distribution of lynx

in the U.S. (Chapters 8, 11, 13). We have documented at least one verified

record of occurrence since 1990 in Washington, Oregon, Idaho, Montana,

Wyoming, Utah, Minnesota, Wisconsin, New Hampshire, and Maine. If we

include track data collected by knowledgeable individuals as evidence of

occurrence, we can add Colorado and Michigan to this list. We also know

there is at least one reproductive female lynx in both western Wyoming and

northern Maine. However, strong evidence of the presence of established

populations is limited to western Montana and north-central Washington.

In most areas of historical lynx occurrence, we need to determine if populations of lynx are present before we can select new study locations or assess

the representativeness of resident populations occurring in Washington

and Montana. This information gap must be addressed initially with broadscale, presence/absence surveys conducted throughout the historical range

of lynx.

Do Lynx Detections Represent a Researchable Population?

Although broad-scale surveys may demonstrate the presence of at least

one lynx at a given locality, an intensive radiotelemetry study should not be

implemented until surveys conducted at a finer spatial scale have verified

the presence of a sufficiently large and established (i.e., “researchable”)

population. For example, we know that there are at least two lynx (a male

and female) in the Wyoming Range in western Wyoming, and that the

female had kittens in 1998 and 1999. These lynx occur farther south than any
463

Aubry—Chapter 17

known native population and are therefore of special interest. Before committing research funds to intensive study, however, we must determine if

these lynx are an isolated pair or are part of a larger population occupying

contiguous portions of the Greater Yellowstone Ecosystem.

How Do We Prioritize the Implementation of Intensive Studies?

Simply locating a researchable population does not mean that knowledge

gained from an intensive study would be worth the cost. Additional and

more useful benefits to lynx conservation may be realized by using research

funds in other ways or at other locations. We prioritize intensive studies in

locations where researchable populations are identified according to the

following three criteria:

Would an intensive study increase the representativeness of existing

information? For lynx, a representative sample of populations to study

should be selected from all known populations within the geographic area

of interest. At this time, however, such an approach is impractical because

we do not know the locations of extant populations. We therefore need to

apply simple criteria that are likely to increase the representativeness of

current information on lynx, such as maximizing the geographic extent or

variability in major climatic and ecological gradients among lynx studies

within the geographic area of interest.

What will the value of new information be to lynx management and

conservation? New research on lynx in the U.S. must make a significant

contribution to lynx management and conservation. Throughout this book,

we have identified critical gaps in our knowledge of lynx biology and

ecology. Examples include the ecology and population dynamics of principal prey species, competitive interactions with other carnivores, and human

impacts. Thus, we would give high priority to potential study areas where

assemblages of alternative prey or potential competitors differ markedly

from those of previous lynx studies, or where unique opportunities exist to

study human impacts on lynx populations, such as adjacent landscapes with

and without snowmobile use.

How feasible is the study and what are the costs? The cost of lynx research

increases with the difficulty of access. In addition, certain types of studies

may be infeasible in particular localities, such as snowtracking in areas with

significant avalanche danger. Consequently, logistical constraints on research and resulting unit costs for generating new information must be

considered when setting research priorities.
Chapter 17—Aubry

464

A Research Approach

Broad-Scale Surveys

Broad-scale surveys are intended to provide information about lynx at

large spatial scales (e.g., physiographic regions, ecological provinces, or

states). These surveys are most useful when the objective is to document the

presence of lynx (Fig. 17.1). Such a survey is currently underway nationally

and is designed to provide reliable and representative information about

lynx presence/absence and genetic variation. The detection device used is a

modification of a rubbing-pad technique for collecting hair samples originally developed by J. Weaver (personal communication; see also Weaver

and Amato 1999, unpublished). Survey implementation is based on a

protocol developed and tested by the USDA Forest Service’s Rocky Mountain Research Station (McKelvey et al. 1999, unpublished). Genetic evaluation will be based on analysis of DNA taken from hair samples.

The first year of the survey (1999) represents a pilot study designed to

assess the feasibility of meeting survey objectives, which include determining where lynx occur and where they do not, the pattern of lynx detections

Are lynx

present?

Information on lynx

occurrence relative to

forest cover types and

broad landscape features

Locations currently identified

for fine-scale surveys:

Kettle Range and Selkirk Mountains, WA

Pioneer Mountains, MT

Anaconda and Flint Ranges, MT

Northern Bitterroot Mountains, MT

Kootenai NationalForest, MT

Wyoming Range, WY

Northern Maine 

yes

yes

Broad-scale survey

no unknown Fine-scale survey

no

Apply

selection criteria:

is the population

a priority for

study?

no

yes

Intensive study

unknown

Is the

population

large enough

to study?

Locations currently

identified for intensive study:

Clearwater Drainage, MT

Okanogan Plateau, WA

Figure 17.1—A schematic representation of the process for identifying potential study areas and

implementing intensive research on lynx in the contiguous United States.
465

Aubry—Chapter 17

relative to broad-scale environmental features, and the degree of genetic

structuring among lynx in different geographic areas.

Fine-Scale Surveys

Fine-scale surveys are conducted in areas where lynx are known to be

present. Because these surveys are intended to determine if lynx occur in

sufficient numbers to support intensive research (Fig. 17.1), they will most

likely employ a combination of detection methods, with snowtracking

surveys being the primary means of assessing the relative abundance of

lynx. Although most fine-scale surveys will be based on information obtained from broad-scale surveys, there are a number of areas that have

already been identified where fine-scale surveys would be appropriate

(Fig. 17.1).

Intensive surveys of snowshoe hare distribution and abundance using

pellet plots and live-trapping will be used to determine how differences in

forest composition and structure (including thinning of young forests) and

forest succession along complex moisture/temperature gradients influence

patterns of hare abundance.

Intensive Studies

Intensive studies will be necessary to address most of the information

needs we have identified (Fig. 17.1). These studies will employ a variety of

research techniques, with radiotelemetry being the primary methodology.

Radiotelemetry involves intensive monitoring of the activities of individual

animals, enabling data to be gathered on a broad range of research questions

including habitat relationships, movements, demography, community relationships, and responses to natural and human-caused disturbance. Radiotelemetry also facilitates the study of snowshoe hare habitat relationships,

especially with regard to demographic responses and source-sink phenomena. Accordingly, intensive studies address many objectives at multiple

spatial scales and are central to our proposed research program.

Currently, there are three radiotelemetry studies of lynx being conducted

in the U.S. These include an intensive study in the Clearwater drainage of

western Montana involving 18 radio-collared lynx (Chapter 11), radiotelemetry monitoring of two adult lynx in the Wyoming Range of western

Wyoming (Chapter 11), and radiotelemetry monitoring of two adult lynx in

northern Maine (Chapter 8). We do not know, however, if radio-collared

lynx in Wyoming and Maine are part of more extensive populations.

Although all three of these studies will contribute to our understanding of

lynx biology and ecology in the U.S., only the western Montana study

represents an intensive study of a researchable population (Fig. 17.1).
Chapter 17—Aubry

466

Our current inability to identify all researchable lynx populations in the

U.S. is a critical constraint on the establishment of new intensive studies. The

failure of broad- and fine-scale surveys to identify additional populations

for intensive study would be significant, as it would provide strong evidence

that extant lynx populations in the U.S. are severely restricted. However,

until ongoing and proposed surveys identify additional populations for

study, we must proceed with intensive studies on known populations.

A Program of Intensive Research

At the present time, there are only two places in the U.S. where we can state

with confidence that intensive lynx studies should be conducted: the

Clearwater drainage in western Montana and the Okanogan Plateau in

north-central Washington (Table 17.2; Fig. 17.1). Because virtually all of the

research needs identified here are most efficiently addressed through intensive studies, we must increase the number of these studies in regions where

lynx conservation and related management activities are at issue. For

opportunistic reasons, and because the only intensive study currently ongoing is the Clearwater study in Montana, new intensive research should be

implemented on the Okanogan Plateau in north-central Washington. Although lynx were studied recently (1980-1988) in this area (see Chapters 10,

13), a number of important landscape-scale habitat changes have occurred

on the Plateau since the earlier study, including a major fire. Furthermore,

many of the important information needs identified in Table 17.2 were not

adequately addressed in previous studies (Chapter 13).

In addition, ongoing research in Montana must be continued and expanded. The Clearwater study area provides a unique opportunity to study

the effects of winter recreation, forest fragmentation, and roads on lynx

behavior and on competition with generalist predators. The primary study

area is located in a relatively low-elevation, intensively managed landscape.

However, radio-collared lynx have been moving in and out of the adjacent

Bob Marshall Wilderness, which has very different landscape characteristics. Ongoing studies need to be expanded to understand how adjacent

wilderness areas are used by lynx. The inclusion of such areas in the study

would also increase the representativeness of this research.

Although expanding the Clearwater study and renewing research activity

on the Okanogan Plateau are clearly high priorities, it is important to initiate

new studies in areas that are ecologically distinct from previous and ongoing

studies. To identify such areas, fine-scale surveys to determine the spatial

extent and relative abundance of local populations need to be conducted

immediately in areas where we know lynx occur. These include several
467

Aubry—Chapter 17

Table 17.2—Studies by location indicating information needs to be addressed.

Pacific Northwest Rocky Mountains

Within the Kettle Range Kootenai Northern

historic Okanogan and Selkirk National Clearwater Pioneer Anaconda and Bitterroot Wyoming North- Northeastern

range of Plateau, Mountains, Forest, Drainage, Mountains, Flint Ranges, Mountains, Range, Central U.S. U.S.

Research approach lynx Washington Washington Montana Montana Montana Montana Montana Wyoming Unknown Northern Maine

Broad-scale surveys to

determine presence

Lynx X

Fine-scale surveys to assess

relative abundance

Lynx X X XXXX X

Snowshoe hare X

Intensive studies—lynx

Habitat relationships X X Limiteda Limited

Movements and dispersal X X Limited Limited

Demography and population X X

dynamics

Relationships with prey X X

Community interactions X X

Human impacts X X

Intensive studies—

snowshoe hares

Habitat relationships X X

Population dynamics X X

aRadiotelemetry monitoring of several individuals dooes not constitute intensive research but will contribute limited information on habitat relatiionships and movements.
Chapter 17—Aubry

468

locations in western Montana, western Wyoming, northeastern Washington, and northern Maine (Table 17.2; Fig. 17.1). If additional researchable

populations are located in the Rocky Mountains, we would give highest

priority to studies in cold, dry forest types, such as the Pioneer Mountains in

Montana and the Wyoming Range in Wyoming. New studies in these forest

types would contribute more to our understanding of lynx ecology in the

U.S. than additional studies in mesic forest types.

Recommendations for intensive research in the southern Rocky Mountains and north-central and northeastern U.S. must await the findings of both

broad- and fine-scale surveys. Lynx have never been studied intensively in

these regions, where habitat conditions vary substantially from those in the

Pacific Northwest and northern Rocky Mountains. For these reasons, ongoing radiotelemetry monitoring of several lynx in Maine and Wyoming will

contribute useful information. However, fine-scale surveys to determine

whether to expand research efforts in these areas should be given the highest

priority.

Hare studies are an important component of our proposed research

program. Key conservation issues, including reintroduction efforts and the

potential natural range expansion by lynx, will be strongly influenced by

patterns of hare abundance. To study differences in hare abundance along

successional and moisture gradients and to understand the nature of their

population fluctuations, we need to quantify hare abundance over time

among different forest types and seral stages. A fine-scale survey program

involving cooperative efforts with management agencies will be implemented in representative areas within the historical range of lynx. It is

essential, however, that these surveys be conducted in a coordinated fashion

using sampling protocols that will generate reliable information about hare

habitat relationships and patterns of abundance.

Conclusions

This research program will proceed on several fronts simultaneously.

Broad-scale lynx surveys are underway and by the spring of 2000, we will

know more about the efficacy of the survey protocol and, hopefully, patterns

of lynx occurrence in the U.S. Fine-scale surveys and intensive studies of lynx

and hares should proceed in Washington, Montana, Wyoming, and Maine.

And, if we are able to locate other researchable lynx populations, new

intensive studies should be implemented to increase the representativeness

of our sample, especially in the southern Rocky Mountains and north-central

and northeastern United States. Furthermore, as argued previously by

Ruggiero et al. (1994), new lynx studies should be integrated within a
469

Aubry—Chapter 17

broader program of research on forest carnivores and other species of

concern so that we can develop the information needed to implement

ecosystem management in boreal forest landscapes. We must become more

proactive in our research programs if we are to effectively address conservation issues before options for conserving sensitive species have become

irrevocably limited.

Literature Cited

Brainerd, S. M. 1985. Reproductive ecology of bobcats and lynx in western Montana.

Unpublished M.S. Thesis, University of Montana, Missoula, MT.

Brittell, J. D., R. J. Poelker, S. J. Sweeney, and G.M. Koehler. 1989. Native cats of Washington,

Section III: lynx. Unpublished, Washington Department of Wildlife, Olympia, WA.

Brocke, R. H., K. A. Gustafson, and L. B. Fox. 1991. Restoration of large predators: potentials

and problems. Pages 303-315 in Challenges in the conservation of biological resources. A

practitioner’s guide. D. J. Decker, M. E. Krasny, G. R. Goff, C. R. Smith, and D. W. Gross,

eds. Westview Press, Boulder, CO.

FEMAT. 1993. Forest ecosystem management: an ecological, economic, and social assessment. Report of the Forest Ecosystem Management Assessment Team. USDA Forest

Service; USDC National Oceanographic and Atmospheric Administration and National

Marine Fisheries Service; USDI Bureau of Land Management, Fish and Wildlife Service,

and National Park Service; and U.S. Environmental Protection Agency, Washington, DC.

Koehler, G.M. 1990. Population and habitat characteristics of lynx and snowshoe hares in

north central Washington. Canadian Journal of Zoology 68:845-851.

Koehler, G. M., M. G. Hornocker, and H.S. Hash. 1979. Lynx movements and habitat use in

Montana. Canadian Field-Naturalist 93:441-442.

McKelvey, K. S., J. J. Claar, G. W. McDaniel, and G. Hanvey. 1999. National lynx detection

protocol. Unpublished, USDA Forest Service, Rocky Mountain Research Station,

Missoula, MT.

Mech, L. D. 1977. Record movement of a Canadian lynx. Journal of Mammalogy 58:676-677.

Ruggiero, L. F., K. B. Aubry, A. B. Carey, and M. H. Huff, tech. coords. 1991. Wildlife and

vegetation of unmanaged Douglas-fir forests. USDA Forest Service, General Technical

Report PNW-GTR-285.

Ruggiero, L. F., S. W. Buskirk, K. B. Aubry, L. J. Lyon, and W. J. Zielinski. 1994. Information

needs and a research strategy for conserving forest carnivores. Pages 138-152 in L.F.

Ruggiero, K. B. Aubry, S. W. Buskirk, L. J. Lyon, and W. J. Zielinski, tech. eds. The scientific

basis for conserving forest carnivores in the Western United States: American marten,

fisher, lynx, and wolverine. USDA Forest Service, General Technical Report RM-254.

Smith, D. S. 1984. Habitat use, home range, and movements of bobcats in western Montana.

Unpublished M.S. Thesis, University of Montana, Missoula, MT.
Chapter 17—Aubry

470

Thomas, J. W., E. D. Forsman, J. B. Lint, E. C. Meslow, B. R. Noon, and J. Verner. 1990. A

conservation strategy for the northern spotted owl. Report of the Interagency Scientific

Committee to address the conservation of the northern spotted owl. USDA Forest Service,

USDI Bureau of Land Management, U.S. Fish and Wildlife Service, and National Park

Service, Portland, OR.

U.S. Fish and Wildlife Service. 1998. Proposal to list the contiguous United States distinct

population segment of the Canada lynx: proposed rule. Federal Register 63(130):

36994-37013.

Weaver, J. L. and G. Amato. 1999. Lynx surveys in the Cascade Range: Washington and

Oregon. Unpublished, Wildlife Conservation Society, Bronx, NY.
471

Chapter 18

Epilogue

The Scientific Basis for

Lynx Conservation: Can

We Get There From Here?

Leonard F. Ruggiero, USDA Forest Service, Rocky Mountain Research

Station, 800 E. Beckwith, Missoula, MT 59801

Keith B. Aubry, USDA Forest Service, Pacific Northwest Research Station,

3625 93rd Ave. SW, Olympia, WA 98512

Steven W. Buskirk, Department of Zoology and Physiology,

University of Wyoming, P.O. Box 3166, Laramie, WY 82071

Gary M. Koehler, Washington Department of Fish and Wildlife,

600 Capitol Way N., Olympia, WA 98501

Charles J. Krebs, Department of Zoology, University of British Columbia,

6270 University Blvd., Vancouver, BC V6T 1Z4 Canada

Kevin S. McKelvey, USDA Forest Service, Rocky Mountain Research Station,

800 E. Beckwith, Missoula, MT 59801

John R. Squires, University of Montana, Forestry Sciences Laboratory,

800 E. Beckwith, Missoula, MT 59801
472

Chapter 18—Ruggiero

As we emphasized in the Preface, this book was written under very

unusual circumstances. We began the book shortly after the lynx was

proposed for listing as threatened or endangered under the Endangered

Species Act (ESA). Our purpose was to elucidate the scientific basis for

conserving lynx for use in listing deliberations and in establishing land

management policy, including a strategy for lynx conservation. The listing

decision was delayed by six months so that our findings could be considered. Authors, editors, and production staff worked overtime and weekends to produce camera-ready copies of each chapter, and these were posted

on the Internet for public comment during a specified time period. Draft

copies of the chapters were provided to the U.S. Fish and Wildlife Service

and land management agencies prior to publication so they could begin to

consider our findings in their ongoing assessments and planning processes.

We have, therefore, been in the unusual position of seeing some of the

sociopolitical implications of our findings even as we wrote them.

The areas of primary lynx occurrence identified in Chapter 8 cover about

100 million acres (40.5 million ha). This number grows much larger if one

considers all the land within the putative range of the lynx in the contiguous

United States. Thus, land management policy and related decisions influenced by some or all of the information in this book could affect a vast area.

Because much of this land is dedicated to multiple uses, a wide range of

activities including timber and range management, outdoor recreation, and

the production of other goods and services associated with public lands will

potentially be affected. Through its affect on listing deliberations and

agency conservation planning, the information in this book may have farreaching implications. The question is, Is this an adequate basis for such

deliberations and decisions? In other words, given the state of knowledge

embodied in this book, is there a defensible set of answers to lynx conservation questions?

In answering this question, there are several important considerations.

This book illustrates the kind of scientific analysis that we believe should

form the basis for conservation strategies and listing decisions. We feel that

most of what is currently known, and much of what can reasonably be

inferred, has been incorporated into the text. The information we have

provided is as reliable as it can be, and we believe it is substantive. In short,

although our analyses were severely constrained by the scarcity of reliable

scientific information, we have provided a measure of new information and

scientific insight that surpassed our expectations given the significant

knowledge gaps that exist. We believe this was made possible in part by our

approach to the problem, as outlined in our introductory chapter. Perhaps

the most important aspect of this approach was an interpretation of existing
473

Ruggiero—Chapter 13

information based on the explicit application of accepted ecological concepts. In this context, it is very important to discriminate between subjective

opinions and carefully constructed interpretations of scientific information

made in the context of generally accepted conceptual understandings.

Although such interpretations may be inconclusive in the sense of lacking

proof, their reliability is more easily assessed, and interpretations are open

for further review.

Can we get to a defensible set of answers to lynx conservation questions

based on these analyses and interpretations? The answer is yes, but only on

an interim basis. Answers will come in the form of judgments based in part

on what we have presented here. Not everyone will agree with those

judgments, but our work provides a reasonable basis for developing a

rationale for and evaluating the quality of such judgments. However,

although we may be able to get to an interim position, we are still a long way

from understanding many essential aspects of lynx ecology, and thus from

essential understandings necessary to conserve lynx. As emphasized

throughout this book and as summarized in Chapter 17, there is a great deal

of information that we need to acquire before we can develop precise longterm land management plans that will ensure the persistence of lynx. Our

lack of knowledge necessitates a less precise, and thus very conservative,

approach to interim conservation measures.

The key point here is that although we believe our effort provides an

adequate basis for interim conservation planning, our work must not be

viewed as a surrogate for a well-developed body of reliable scientific data.

In matters of conservation planning, the interpretation of limited information by even the most qualified scientists is no substitute for the organized

acquisition of pertinent data. As a basis for making policy decisions, there

is no reliable surrogate for a sustained commitment to scientific research,

especially when the effects of human activities on species persistence are at

issue. If the decision is made to list the lynx under the ESA, the current state

of knowledge, including the information we have presented here, will not

provide an adequate basis for a reliable recovery plan. Only with a determined and sustained commitment to a comprehensive program of research

(Chapter 17) can we obtain the information needed to effectively manage

and conserve lynx populations in the United States.
474

Chapter 18—Ruggiero
1

Appendix A: Common and Scientific Names

Plants

Common Name Scientific Name

Alder Alnus spp.

Alder, speckled Alnus rugosa

Alder, Sitka Alnus crispa

Antelope-brush; bitter-brush Purshia tridentata

Apple, common Pyrus malus

Ash Fraxinus spp.

Ash, mountain Sorbus americana

Ash, white Fraxinus americana

Aspen Populus tremuloides

Aspen, bigtooth Populus grandidentata

Aspen, quaking Populus tremuloides

Basswood Tilia spp.

Bearberry Arctostaphylos uva-ursi

Beech Fagus spp.

Beech, American Fagus grandifolia

Birch Betula spp.

Birch, bog Betula glandulosa

Birch, gray Betula populifolia

Birch, low Betula pumila

Birch, paper Betula papyrifera

Birch, sweet Betula lenta

Birch, white Betula alba

Birch, yellow Betula lutea

Birch, yellow Betula alleghaniensis

Blackberry, Allegheny Rubus alleghaniensis

Blackberry; dewberry; raspberry; bramble Rubus spp.

Blueberry Vaccinium spp.

Blueberry, dwarf Vaccinium caespitosum

Bogmyrtle, sweetgale Myrica gale

Buckthorn, alderleaf Rhamnus alnifolia

Buffaloberry, russet Shepherdia canadensis

Cattail Typha latifolia

Ceanothus Ceanothus spp.

Cedar, northern white Thuja occidentalis

Cedar, western red Thuja plicata

Cedar, white Thuja occidentalis

Cherry, black Prunus serotina

Cherry, pin Prunus pensylvanica

Chokecherry, common Prunus virginiana
2

Appendix A

Plants

Common Name Scientific Name

Cottonwood Populus spp.

Cottonwood, black Populus trichocarpa

Cranberry, highbush Viburnum edule

Cranberry, mountain Vaccinium vitis-idaea

Cranberry, southern mountain Vaccinium erythrocarpum

Dewberry, bristly Rubus hispidus

Dogwood Cornus spp.

Elm Ulmus spp.

Elm, American Ulmus americana

Filbert, beaked Corylus cornuta

Fir Abies spp.

Fir, balsam Abies balsamifera

Fir, balsam Abies balsamea

Fir, Douglas- Pseudotsuga menziesii

Fir, grand Abies grandis

Fir, noble Abies procera

Fir, Pacific silver Abies amabilis

Fir, red Abies magnifica

Fir, silver Abies amabilis

Fir, subalpine Abies lasiocarpa

Fir, white Abies concolor

Fireweed Epilobium angustifolium

Grape, Oregon Mahonia repens

Hemlock Tsuga spp.

Hemlock, eastern Tsuga canadensis

Hemlock, mountain Tsuga mertensiana

Hemlock, western Tsuga heterophylla

Honeysuckle Lonicera spp.

Hophornbeam, American Ostrya virginiana

Huckleberry, black Gaylussacia baccata

Huckleberry, blueleaved or Cascade Vaccinium deliciosum

Juniper, common Juniperus communis

Juniper, Rocky Mountain Juniperus scopulorum

Kalmia Kalmia spp.

Kalmia; mountain-laurel Kalmia latifolia

Labrador-tea Ledum groenlandicum

Larch, eastern (tamarack) Larix laricina

Larch, subalpine Larix lyallii

Larch, western Larix occidentalis

Leatherleaf, Cassandra Chamaedaphne calyculata

Ledum, crystal-tea Ledum decumbens

Lupine Lupinus spp.

Maple Acer spp.

Maple, mountain Acer spicatum
3

Appendix A

Plants

Common Name Scientific Name

Maple, mountain Acer glabrum

Maple, red Acer rubrum

Maple, striped Acer pensylvanicum

Maple, sugar Acer saccharum

Oak Quercus spp.

Oak, Gambel Quercus gambelii

Oak, northern red Quercus rubra

Pine Pinus spp.

Pine, eastern white Pinus strobus

Pine, gray or jack Pinus divaricata

Pine, jack Pinus banksiana

Pine, limber Pinus flexilis

Pine, lodgepole Pinus contorta

Pine, ponderosa Pinus ponderosa

Pine, red Pinus resinosa

Pine, Scotch Pinus sylvestris

Pine, southern Pinus taeda, P. elliottii, P. palustris

Pine, white Pinus strobus

Pine, whitebark Pinus albicaulis

Poplar, balsam Populus balsamifera

Poplar, necklace Populus virginiana

Poplar, Pensylvanian Populus pensylvanica

Rhododendron, Canadian Rhododendron canadense

Rhododendron, Lapland; rosebay, Lapland Rhododendron lapponicum

Rose Rosa spp.

Sagebrush Artemesia spp.

Serviceberry Amelanchier spp.

Serviceberry, Saskatoon Amelanchier alnifolia

Snowberry, common Symphoricarpos albus

Spruce Picea spp.

Spruce, black Picea mariana

Spruce, Engelmann Picea engelmannii

Spruce, Norway Picea abies

Spruce, red Picea rubens

Spruce, white Picea glauca

Sweetfern, alien Comptonia peregrina

Viburnum Viburnum spp.

Viburnum; arrowwood Viburnum dentatum

Wheatgrass Agropyron spp.

Whortleberry, grouse Vaccinium scoparium

Willow Salix spp.

Willow, scouler Salix scouleriana

Willow, grayleaf Salix glauca

Witchhazel, common Hamamelis virginiana
4

Appendix A

Animals

Common Name Scientific Name

Bachman’s sparrow Aimophila aestivalis

Badger Taxidea taxus

Bear, black Ursus americanus

Bear, brown Ursus arctos

Bear, grizzly (brown) Ursus arctos

Bear, polar Ursus maritimus

Beaver Castor canadensis

Bison Bos bison

Bison, plains Bos bison

Bison, wood Bos bison

Blackbird, red-winged Agelaius phoeniceus

Bobcat Lynx rufus

Caribou Rangifer tarandus

Caribou, woodland Rangifer tarandus

Cheetah Acinonyx jubatus

Cottontail, dessert Sylvilagus audubonii

Cottontail, mountain Sylvilagus nuttallii

Cougar Felis concolor

Coyote Canis latrans

Deer Odocoileus spp.

Deer, mule Odocoileus hemionus

Deer, white-tailed Odocoileus virginianus

Eagle Haliaeetus spp.

Eagle, golden Aquila chrysaetos

Elk Cervus elaphus

Feral cat Felis catus

Feral dog Canis familiaris

Ferret, black-footed Mustela nigripes

Fisher Martes pennanti

Flicker, northern Colaptes aurantus

Fox, arctic Alopex lagopus

Fox, gray Urocyon cinereoargenteus

Fox, red Vulpes vulpes

Goat, mountain Oreamnos americanus

Goshawk, northern Accipiter gentilis

Grouse Dendragapus spp., Bonasa spp.

Grouse, ruffed Bonasa umbellus

Grouse, spruce Dendragapus canadensis

Hare, east Finland Lepus timidus, L. europaeus

Hawk, Harlan’s (red-tailed) Buteo jamaicensis

Hawk, red-tailed Buteo jamaicensis

Ibex, Tatra Mountain Capra ibex

Jackrabbit, black-tailed Lepus californicus
5

Appendix A

Animals

Common Name Scientific Name

Jackrabbit, white-tailed Lepus townsendii

Kestrel Falco sparverius

Lion, African Panthera leo

Lion, mountain Felis concolor

Lynx Lynx canadensis

Lynx, Canada Lynx canadensis

Lynx, european Lynx lynx

Lynx, Iberian Lynx pardinus

Lynx, Newfoundland Lynx canadensis subsolanus

Macaque, Japanese Macaca fuscata

Marmot, hoary Marmota caligata

Marten, American Martes americana

Mink Mustela vison

Mink, sea Mustela macrodon

Moose Alces alces

Mouse, white-footed Peromyscus leucopus

Mouse, wood Apodemus sylvaticus

Murrelet, marbled Brachyramphus marmoratus

Muskrat Ondatra zibethicus

Owl, boreal Aegolius funereus

Owl, great-horned Bubo viginianus

Owl, hawk Surnia ulula

Owl, Mexican spotted Strix occidentalis

Owl, northern spotted Strix occidentalis

Owl, spotted Strix occidentalis

Pine beetle Dendroctonus spp.

Pine beetle, mountain Dendroctonus ponderosae

Pine beetle (western) Dendroctonus brevicomis

Ptarmigan Lagopus spp.

Raccoon Procyon lotor

Salmon, Chinook Oncorhynchus tshawytscha

Salmon, Pacific Onchorhynchus spp.

Sheep, bighorn Ovis canadensis

Sheep, Dall’s Ovis dalli

Sheep, desert bighorn Ovis canadensis

Shrew, masked Sorex cinereeus

Skunk Mephitis spp.

Snowshoe hare Lepus americanus

Spruce beetle Dendroctonus rufipennis

Spruce budworm, western Choristoneura fumiferana

Squirrel, arctic ground Spermophilus parryii

Squirrel, Columbian ground Spermophilus columbianus

Squirrel, eastern gray Sciurus carolinensis
6

Appendix A

Animals

Common Name Scientific Name

Squirrel, fox Sciurus niger

Squirrel, ground Spermophilus parryii

Squirrel, northern flying Glaucomys sabrinus

Squirrel, red Tamiasciurus hudsonicus

Timberwolf Canus lupus

Trout, bull Salvelinus confluentus

Trout, cutthroat Oncorhynchus clarki

Turkeys, wild Meleagris gallopavo

Vole Microtus spp.

Vole, bank Clethrionomys glareolus

Vole, southern red-backed Clethrionomys gapperi

Weasel Mustela spp.

Weasel, long-tailed Mustela frenata

Wolf, gray Canis lupus

Wolverine Gulo gulo

Woodrat Neotoma spp.

Woodrat, bushy-tailed Neotoma cinerea

Woodrat, dusky-footed Neotoma fuscipes