U.S Fish & Wildlife Service

Neonatal Mortality 

of Elk in Wyoming: 

Environmental, 

Population, and 

Predator Effects

Biological Technical Publication

BTP-R6007-2006

U.S Fish & Wildlife Service

Neonatal Mortality 

of Elk in Wyoming: 

Environmental, 

Population, and 

Predator Effects

Biological Technical Publication

BTP-R6007-2006

Bruce L. Smith1, 7

Elizabeth S. Williams2, 8

Katherine C. McFarland3, 9 

Trent L. McDonald4 

Guiming Wang5, 10

Tommy D. Moore6, 11

1 U.S. Fish and Wildlife Service, National Elk Refuge, Jackson, WY 

2 Wyoming State Veterinary Laboratory, University of Wyoming, Laramie, WY 

3 U.S. Fish and Wildlife Service, National Elk Refuge, Jackson, WY 

4 Western Ecosystems Technology, Cheyenne, WY

5 Arkansas Tech University, Russellville, AR 

6 Wyoming Game and Fish Department Laboratory, University of Wyoming, 

Laramie, WY 

7 Current Address: Sheridan, MT 59749

8 Current Address: deceased

9 Current Address: National Park Service, Grand Teton National Park, Moose, WY

10 Current Address: Department of Wildlife and Fisheries, Mississippi State 

University, Mississippi State, MS 

11 Current Address: Laramie, WY

Cover image: Elk calf 

Photo credit: Bruce Smith/USFWS
ii Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

Author Contact information:

Bruce L. Smith, (Current address) 44 Duncan District Road, Sheridan, MT 59749. Phone: (406) 842-5995, 

e-mail: elkmail@3rivers.net

Katherine C. McFarland, (Current address) National Park Service, Grand Teton National Park, Drawer 170, 

Moose, WY, 83012. Phone: (307) 733-3484, e-mail: katherine_mcfarland@nps.gov

Trent L. McDonald, Western Ecosystems Technology, 2003 Central Avenue, Cheyenne, WY 82001. Phone: 

(307) 755-9717, e-mail: tmcdonald@west-inc.com

Guiming Wang, Current Address: Thompson Hall, Room 273, Department of Wildlife and Fisheries, 

Mississippi State University, Mississippi State, MS 39762. Phone: (662) 325-0414, 

email: gwang@cfr.msstate.edu

Tommy D. Moore, PO Box 2421, Laramie, WY 82073. Phone: (307) 742-6057

Recommended citation:

Smith, B.L., E.S. Williams, K.C. McFarland, T.L. McDonald, G. Wang, and T.D. Moore. 2006. Neonatal 

mortality of elk in Wyoming: environmental, population, and predator effects. U.S. Department of Interior, 

U.S. Fish and Wildlife Service, Biological Technical Publication, BTP-R6007-2006, Washington, D.C.

For additional copies or information, contact: 

Wayne J. King

USFWS Region 6

Regional Refuge Biologist

P.O. Box 25486 

Denver Federal Center 

Denver, Colorado 80225-0486

Phone: (303) 236-8102

Fax: (303) 236-4792

E-mail: wayne_j_king@fws.gov 

Series Senior Technical Editor:

Stephanie L. Jones

USFWS, Region 6

Nongame Migratory Bird Coordinator

P.O. Box 25486

Denver Federal Center

Denver, Colorado 80225-0486
 iii

Table of Contents

Table of Contents. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

List of Figures. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

List of Tables. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Executive Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi

Acknowledgments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

Study Area. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Capture and Monitoring of Elk. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Estimated Birth Weights and Rates of Gain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Forensics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Bear Distribution. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Survival and Mortality Analyses. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Population Size and Recruitment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Population Modeling. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Harvestable Surplus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Annual Population Growth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Birth Weights. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Growth and Physiological Status of Calves. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Predator Abundance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Mortality Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

Weather Effects on Survival. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Recruitment. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Rate of Increase and Harvestable Surplus. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Predisposing Mortality Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Physiological Status. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Rate of Gain. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Weather. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Recruitment and Density Dependence. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Predation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Reliability of Mortality Evaluation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Compensation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21

Conclusion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

Future Research. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Literature Cited. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Appendix A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29

Frequency of visitation (proportion of weeks visited during the sampling period) of black and grizzly bears 

at hair collection corrals in the East and West study areas during 1997 - 1999. We monitored all corrals 

weekly from approximately 1 June through 31 July 1998 and 1999 (8 weeks). In 1997, we monitored all hair 

collection corrals 1 June through the third week of July (7 weeks) except Granite Creek and Death Canyon, 

which we monitored only during July (4 weeks). 

Table of Contents
iv Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

Appendix B.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Cause-specific mortality of neonatal elk that died during 1990 - 1992 (n = 22 of 145 calves) 

and 1997 - 1999 (n = 42 of 153 calves). 

Appendix C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31

Causes and dates of death of 22 of 145 elk neonates that died during 1990 - 1992 and 42 of

 153 neonates that died during 1997 - 1999 in the East (E) and West (W) study areas.
 v

List of Figures

Figure 1. Area occupied by the Jackson elk herd showing hair collection corrals in the East and West 

study areas in which elk calves were captured during 1990 - 1992 and 1997 - 1999.. . . . . . . . . . . . . . . . . . . . . . . 2

Figure 2. Weights of elk calves captured during 1990 - 1992 and 1997 - 1999 regressed on age of 

the calves at birth. Weights of calves ≤ 1 day old were considered birth weights. Slopes of the equations 

are estimated cohort daily rates of gain for males and females during the first week of life . . . . . . . . . . . . . . .10

Figure 3. Neonatal mortality (birth through 31 July of the birth year) of radioed elk calves captured in 

the East (East SA) and West (West SA) study areas during 1990 - 1992 and 1997 - 1999.. . . . . . . . . . . . . . . . . 11

Figure 4. Survival of elk (sexes combined) from birth to approximately 60 days of age during 1990 - 1992 

and 1997 - 1999. Log-rank test of difference was significant (P = 0.01).. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

Figure 5. Relationship of birth weight of male and female calves of the Jackson elk herd to probability 

of survival from birth to 31 July of their birth year during 1990 - 1992 and 1997 - 1999. We estimated 

survival curves from the stratified Cox proportional hazards model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 

Figure 6. Elk calf survival by birth weight categories (sexes combined) during 1990 - 1992 and 1997 - 

1999 (see Table 6 for sample sizes).. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 

Figure 7. Estimated probability of an elk calf (sexes combined) of average birth weight (15.7 kg) not 

being killed by a predator during 1990 - 1992 and 1997 - 1999. Probability of death by predation is 1.0 

minus the height of the curves. Tick marks indicate elk censored when transmitters were cast (n = 19 

in 1990 - 1992 and n = 1 in 1997 - 1999) or calves surviving to 31 July of their birth year. . . . . . . . . . . . . . . . . 13

Figure 8. Relationship of mean monthly April temperature (0C) to annual probability of survival from 

birth to 31 July of Jackson elk herd neonates, and to normalized difference vegetation index normalized 

difference vegetation index (NDVI) during the second and third weeks of April 1990 - 1992 and 1997 - 

1999.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Figure 9. Predation by black bears and combined predation by black and grizzly bears on elk neonates 

of the Jackson herd, 1990 - 1992 and 1997 - 1999, related to mean monthly April temperature (A), and 

to normalized difference vegetation index (NDVI) during the second and third weeks of April (B).. . . . . . . .15

Figure 10. Calf:100 cow ratios at the National Elk Refuge during winters 1983-1999 regressed on 

number of elk counted on the National Elk Refuge the previous winter (A), and summer calf:100 

cow ratios in Grand Teton National Park regressed on number of elk counted during summers 

1991 - 1999 (B).. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

List of Figures
vi Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

List of Tables

Table 1. Numbers of female grizzly bears with cubs of the year and total estimated grizzly bear

population in the Greater Yellowstone Ecosystem, 1989 - 1999. ............................................................................. 4

Table 2. Estimated birth weights and daily rates of gain of newborn elk calves captured in northwest 

Wyoming. Test statistics compare daily rates of gain between the 2 time periods for males and 

females. ........................................................................................................................................................................... 9

Table 3. Blood serum chemistries of 84 elk calves captured during 1997 - 1999 in the Jackson herd. 

We used Student’s t tests to compare means of calves that survived (n = 67) and those that died 

(n = 17) during the neonatal period (birth to 31 July)............................................................................................ 11

Table 4. Sex-specific neonatal mortality of elk during 1990 - 1992 and 1997 - 1999............................................. 12

Table 5. Predation on neonatal elk (sexes combined) by black bears and by black and grizzly bears

combined during 1990 - 1992 and 1997 - 1999 in the East and West Study Areas............................................... 12

Table 6. Estimated survival probabilities from birth to 60 days of age for elk calves of different birth 

weights during 1990 - 1992 and 1997 - 1999. We computed estimates from the stratified Cox

proportional hazards model. ...................................................................................................................................... 13

Table 7. Environmental and population characteristics of the two periods during which neonatal 

mortality of elk calves was studied in the Jackson herd......................................................................................... 14

Table 8. Estimated annual recruitment rates (calves observed per 100 cows > 1 year old) from two 

periods during which neonatal mortality of elk calves was studied in the Jackson herd of 11,000 

individuals prior to parturition. ................................................................................................................................. 14

Table 9. Sensitivity analyses of Leslie matrices of the Jackson elk herd constructed for the early 

1990s and late 1990s. Here, is the sensitivity of the finite rate of increase to changes in element 

aij of the Leslie matrix. ............................................................................................................................................... 15

∂λ

∂αij
 vii

Executive Summary

Public concerns over large losses of wild ungulates 

to predators arise when restoring large carnivore 

species to former locations or population densities. 

During the 1990s, mountain lion (Felis concolor) 

and grizzly bear (Ursus arctos) numbers increased 

in Jackson Hole, Wyoming, and gray wolves 

(Canis lupus) were reintroduced to the Greater 

Yellowstone Ecosystem. We investigated effects 

of these predators, as well as black bears (Ursus 

americanus) and coyotes (Canis latrans), on 

mortality of an abundant and increasing prey 

species, elk (Cervus elaphus). We captured, radioinstrumented, and monitored survival of 145 elk 

neonates from 3 cohorts during 1990 - 1992, and 153 

neonates from 3 cohorts during 1997 - 1999 when 

grizzly bears and lions were likely more common 

than during the earlier period of study. Neonatal 

(birth through 31 July) mortality of elk due to 

predation, disease, and accidents increased from 

15.2 % to 27.5% (P = 0.01). Sixty-eight percent 

of all mortality during 1990 - 1992 resulted from 

predation by black bears and coyotes, compared 

to 76% during 1997-1999 by black bears, coyotes, 

grizzly bears, and mountain lions, a non-significant 

difference (P = 0.49). Weight gains of calves during 

the first week, but not birth weights, declined from 

1990 - 1992 to 1997 - 1999. April temperatures were 

cooler, delaying spring green-up, and elk numbers 

were larger during 1997 - 1999 when weight gains 

and survival of calves declined. Calves that died 

were more likely to be male, below average birth 

weight, and had inferior serum nutritional indices. 

The change in neonatal calf survival reduced the 

annual growth rate of the Jackson elk herd from 1.26 

to 1.23, yielding a decline in the annual increment 

of approximately 500 animals in a preparturition 

herd of 11,000 elk. Changes in mid-summer calf:100 

cow ratios indicated a 39 - 45% greater decline in 

neonatal survival than measured among the radioed 

calves. We suggest increasing predation during the 

study was partially compensatory, given predator 

selection of inferior calves and increased mortality 

of cohorts with reduced first week growth rates. 

Reduced rate of first week weight gains of elk calves 

extended the duration of neonatal mortality by one 

month during 1997 - 1999, and may be as important 

in predisposing calves to predation and other 

mortality as low birth weights. Consequently, we 

conclude that increased predation was a proximate 

not an ultimate cause of declining neonatal survival 

during the 1990s. We recommend careful evaluation 

and hypothesis testing of predator effects on elk as 

restoration of large carnivores continues.

Executive Summary
viii Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

Acknowledgments

This work was generously supported by the 

Community Foundation of Jackson Hole, Grand 

Teton National Park, Rocky Mountain Elk 

Foundation, National Elk Refuge, University of 

Wyoming–National Park Service Research Center, 

Wildlife Forever, Wyoming Cooperative Fish and 

Wildlife Research Unit, Wyoming Game and Fish 

Department, National Rifle Association, Safari Club 

International, and the Wyoming State Veterinary 

Laboratory. Among those who provided field 

assistance, special thanks are due E. K. Bentley, 

A. N. Bethe, W. D. Helprin, D. D. Katnik, K. E. 

McGinley, A. E. Parker, S. M. Patla, A. M. Strassler, 

and S. G. Wolff. R. J. Hawkins of Hawkins and 

Powers Aviation safely and efficiently piloted our 

capture helicopter. G. L. Lust of Mountain Air 

Research piloted fixed-wing telemetry missions. 

C. R. Anderson, R. G. Grogan, and L. S. Mills 

helped identify predator species from hair samples. 

J. G. Cook and T. J. Roffe provided insights into 

blood chemistry results. R. W. Klaver provided 

NDVI metrics. We thank S. H. Anderson, S. L. 

Cain, D. S. Moody, B. G. Reiswig, and T. L. Toman 

for administrative assistance. R. A. Garrott, 

B. K. Johnson, D. S. Moody, and T. K. Fuller 

provided helpful reviews and improvements of the 

manuscript. Finally, without the encouragement 

and support of R. J. Schiller, the second phase of this 

project may never have been initiated, much less 

completed. The use of trade names or commercial 

products in this publication are solely for the 

purpose of providing specific information and does 

not imply recommendation or endorsement by the 

U.S. Government.
 1

Introduction

Large carnivores are considered keystone species 

that are vital to the integrity of many ecosystems 

(Estes 1996, Power et al. 1996). However, restoration 

and recovery of large North American carnivores 

has been met with skepticism and resistance by 

some Americans, particularly those that live closest 

to recovery areas and feel threatened by their 

presence (Bath 1991, Fisher 1995, U.S. Fish and 

Wildlife Service 1998). The most prevalent concerns 

are livestock depredations, financial loss to ranchers, 

human safety, and large losses of wild ungulate 

populations (Bath 1991, Braun 1991, Linnell et al. 

1995, Pate et al. 1996, U.S. Fish and Wildlife Service 

1998). Mech (1996) noted that the debate is not 

about whether predators affect their prey; they 

do. Rather, debate continues about the degree to 

which predation is compensatory, regulates prey 

populations in combination with other factors, and 

how predators may shape behavior and structure of 

prey populations. 

Gaillard et al. (1998) in their review of population 

dynamics of large herbivores found that recruitment 

is the main target of limiting factors, both densitydependent and density-independent. Variation in 

recruitment is more often a consequence of changes 

in juvenile survival than fecundity (Sæther 1997). 

The rate of juvenile mortality often varies widely 

among populations of the same species (Geist 

1971) which can significantly affect recruitment 

and the rate of increase of cervid populations 

(Caughley 1977). High neonatal losses can result 

from predation, adverse weather conditions, 

low birth weights and growth rates, altered 

immunocompetence of neonates, and inbreeding 

depression (Ralls et al. 1979, Clutton-Brock et al. 

1992, Kunkel and Mech 1994, Sams et al. 1996, 

Sæther 1997, Singer et al. 1997, Gaillard et al. 1998). 

Large terrestrial predators, for example, appear 

capable of limiting prey populations to varying 

degrees (Gasaway 1992) and removal, addition, or 

changes in abundance of keystone predators can 

produce trophic cascades (Sinclair and NortonGriffiths 1979, McNaughton 1985).

To elucidate predator effects on prey populations, 

Estes (1996) and Gaillard et al. (1998) advocated 

hypothesis testing in manipulative experiments 

that remove or add predators and compare 

results to unmanipulated controls. Yet scientists 

seldom have the opportunity to conduct such 

experiments with wild populations of large, 

valuable mammals. Documentation of predatory 

effects during fortuitous fluctuations in predator 

abundance, resulting from natural variation, overexploitation or protection from exploitation by man, 

or reintroductions offer important opportunities 

for scientists to understand the role of predators 

in ecosystems (Estes 1996, Mech 1996). Such an 

opportunity presented itself to us with regard to 

predation on elk (Cervus elaphus). 

In the Greater Yellowstone Ecosystem (GYE), 

grizzly bear (Ursus arctos) and mountain lion 

(Felis concolor) populations, following restriction 

of human exploitation, are recovering (Berger et 

al. 2001a, Clark et al. 1999, Murphy 1998, Schwartz 

et al. 2002), and gray wolves (Canis lupus) were 

successfully reintroduced in 1995 and 1996 (Bangs 

and Fritts 1996). Concerns about effects of predators 

on prey are nowhere more prevalent than in the 

GYE (Clark et al. 1999). The GYE supports eight 

species of wild ungulates, totaling some 164,000 

animals, plus 230,000 cattle (Bos taurus) and 60,000 

domestic sheep (Ovis aires) (Souvigney et al. 1997). 

Among the wild ungulates in the GYE, elk are most 

abundant, numbering 120,000 wintering animals 

in 25 herds (Toman et al. 1997). Among these, the 

Jackson herd is one of the largest elk herds in North 

America and one of the most widely known and 

studied (Boyce 1989, Lubow and Smith 2004). 

Smith and Anderson (1996) documented causespecific mortality of neonatal elk, including 

predation by black bears (Ursus americanus) and 

coyotes (Canis latrans), during an investigation of 

the Jackson elk herd in the early 1990s. The second 

phase of our study was prompted, in part, by a 

controversy surrounding grizzly bear depredation 

on two cattle grazing allotments in GTNP and 

adjacent Bridger-Teton National Forest south and 

east of Moran, Wyoming (Figure 1). Several hundred 

elk calved annually on those lands before cattle were 

turned out in late June and July. During the mid1990s, grizzly bears began preying on bovine calves 

in these cattle grazing allotments (Anderson et al. 

2002). We hypothesized that bears were attracted to 

the allotments to prey on elk calves then switched 

to bovines when most elk calves became difficult to 

capture. 

Mountain lion numbers also appeared to increase 

during the 1990s in Jackson Hole (D. Brimeyer, 

pers. commun.). Because lions and grizzly bears 

are known to prey on elk neonates (Schlegel 1976, 

Singer et al. 1997), we endeavored to measure 

Introduction
2 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

changes in neonatal mortality of the Jackson elk 

herd and measure allocation of this prey species 

among several species of carnivores. 

Our objectives were to determine 1) the rate of 

predation by grizzly bears and mountain lions on elk 

calves, 2) whether such mortality was compensatory 

or additive to other sources of mortality, 3) any 

influence of environmental factors, calf physiological 

status, or population density on survival of elk 

neonates, and 4) if changes in neonatal mortality 

altered the surplus of elk from the Jackson herd 

available to hunters. We predicted the following:

1) Higher mortality would occur among elk neonates 

of lower birth weights and inferior nutritional 

status as indicated by blood serum chemistry.

2) Neonatal mortality would increase between study 

periods as predator populations increased.

3) Neonatal mortality would increase in our study 

area colonized by grizzly bears, compared to our 

grizzly-free study area, if grizzly bear predation 

is additive to other sources of mortality.

4) If predation represented additive mortality, it 

may be an important limiting influence on population growth and would reduce the harvestable 

surplus of elk available to hunters.

5) Calf mortality may show density dependence if 

it covaried with periods of different population 

sizes.

6) Calf mortality would vary in a density-independent way with cohort birth weight and with 

cohort weight gain, which covary with spring 

temperatures or foraging conditions.

7) Calf mortality would be partially or completely 

compensatory if spring weather conditions or inferior physiological condition predisposed calves 

to increased predation.

Figure 1. Area occupied by the Jackson elk herd showing hair collection corrals in the East and West study 

areas in which elk calves were captured during 1990 - 1992 and 1997 - 1999.
 3

Study Area

Cole (1969), Boyce (1989), and Smith and Robbins 

(1994) described the boundaries, topography, 

climate, and vegetation communities of the Jackson 

elk herd unit, which encompasses 5,195 km2 in the 

Snake River watershed of northwest Wyoming 

(Figure 1). Elk of the Jackson herd migrate 10 - 90 

km between seasonal ranges (Smith and Anderson 

2001). Between 13,000 and 16,200 elk were counted 

in the Jackson elk herd each winter during the 

1990s, when population modeling indicated a herd 

size of 14,000 - 18,000 elk (Lubow and Smith 2004). 

About 70% of the herd is food supplemented in 

winter on the National Elk Refuge (NER) or on 

feedgrounds operated by the state of Wyoming in 

the Gros Ventre drainage. Elk typically arrive at 

feedgrounds during November and December and 

remain on and adjacent to feedgrounds through 

April or early May (Smith and Robbins 1994). They 

forage on new vegetative growth for several weeks 

following the termination of winter feeding about 1 

April and then migrate to calving areas (Smith and 

Robbins 1994, Smith et al. 1997).

Our study was conducted in the Jackson Hole valley 

and foothills lying between the Teton Mountains 

on the west, the Gros Ventre Mountains and Mount 

Leidy Highlands on the east, and the Pinyon Peak 

Highlands on the north (Boyce 1989). Our two 

adjacent study areas, one east of the Snake River 

and Jackson Lake in both Grand Teton National 

Park (GTNP) and the Bridger-Teton National 

Forest (East SA), and one west of the Snake River 

in the Central Valley of GTNP (West SA, Figure 

1), are important calving areas of the Jackson elk 

herd (Smith and Robbins 1994, Smith et al. 1997). 

Elevations range from 1950 to 2450 m. Vegetation 

communities include sagebrush (Artemesia spp.) 

grasslands, and aspen (Populus tremuloides) 

woodlands, interspersed with cottonwood (Populus 

angustifolia) and willow (Salix spp.) riparian zones, 

and coniferous forests of lodgepole pine (Pinus 

contorta), Douglas fir (Pseudotsuga menziesii), and 

Engelman spruce (Picea engelmannii). The climate 

is characterized by long cold winters and warm 

short summers. The reporting station in Moran, 

Wyoming (2069 m), is centrally located in the calving 

areas where we captured elk, and receives 617 mm 

of precipitation annually. January and July monthly 

temperatures at Moran average -10.2oC and 15.7oC, 

respectively (National Oceanic and Atmospheric 

Administration 1992).

Coyotes occupied both the East SA and West SA 

used by elk for calving (Smith and Anderson 1996). 

During an investigation of coyote populations, 

Weaver (1977) found that coyotes were more 

abundant east of the Snake River than west of the 

River in 1973, but of similar abundance during the 

following two years, based on scat and scent station 

indices. 

Black bears were common in both study areas 

(Smith and Anderson 1996). From genetic 

fingerprinting of hair collected at hair collection 

corrals in the East SA, a density of 6 - 10 black bears 

per 100 km2 was estimated during the late 1990s (R. 

Grogan, pers. commun.). Density in the West SA 

was likely higher based on habitat differences and 

protection from hunting (S. L. Cain, pers. commun.).

An established mountain lion population inhabiting 

Jackson Hole probably increased during the course 

of our investigation. Hunters harvested three lions 

during 1972 - 1992 in Jackson Hole compared to 

26 harvested, four natural mortalities, and four 

killed on highways during 1994 - 1999 (D. Brimeyer, 

pers. commun.). Mountain lion hunting seasons 

were similar during the 1990s (D. Brimeyer, pers. 

commun.). An ongoing ecological investigation 

of mountain lions in Jackson Hole indicated 4 - 5 

resident adult lions inhabited the East SA, and 

another three lions likely inhabited the West SA 

(H. Quigley, pers. commun.).

Our study areas were located in the southern portion 

of the GYE. Grizzly bear numbers approximately 

doubled throughout the ecosystem during the 

1990s (Table 1). Schwartz et al. (2002) noted that 

range expansion of grizzly bears was particularly 

evident during the 1990s in the southern portion 

of the ecosystem, including previously unoccupied 

areas of Wyoming. During the 1990s, grizzly bears 

began recolonizing former range and killing bovine 

calves in two cattle grazing allotments, the Elk 

Ranch East (in GTNP) and the Blackrock-Spread 

Creek (Bridger-Teton National Forest), which 

covered 450 km2 south and east of Moran, Wyoming 

(Anderson et al. 2002). West SA (220 km2) lay south 

and west of those allotments, whereas our East SA 

(260 km2) was > 50% encompassed by those two 

grazing allotments (Figure 1). Anderson et al. (2002) 

reported that few sightings or grizzly bear conflicts 

and no documented livestock deaths associated with 

grizzly bears occurred from 1985 - 1991 in those 

grazing allotments. However, State of Wyoming 

personnel attributed deaths of six bovine calves and 

26 additional cattle (25 calves, one cow) in 1993 to 

grizzly bear predation on those grazing allotments 

Study Area
4 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

(Anderson et al. 2002). These depredations 

prompted a 3-year study of the situation by the 

Wyoming Game and Fish Department. During 

summers 1994 - 1996, 18 grizzly bears and 24 black 

bears were captured in snares and culvert traps on 

the allotments and 17 of each species were fitted 

with radio transmitters. Cattle losses continued 

and a grizzly bear documented killing cattle was 

captured and euthanized in GTNP in 1996 (Anderson 

et al. 2002). 

Holm (1998) estimated that at least 15 grizzly bears 

and 21 - 25 black bears in 1995 and at least 16 grizzly 

bears and 19 - 21 black bears in 1996 used the two 

cattle allotments. Estimates of the number of grizzly 

bears frequenting East SA during 1997 - 1999 are 

unavailable and probably varied annually, based 

upon results of bear monitoring during 1994 - 1996 

(Holm 1998, Anderson et al. 2002). Observations 

and radio telemetry locations of grizzly bears were 

uncommon in West SA during the 1990s (Schwartz 

et al. 2002, S. L. Cain, pers. commun.), allowing this 

area to serve as a comparative “grizzly-free” study 

site. 

Gray wolves were reintroduced into Yellowstone 

National Park in 1995 and 1996. Wolves began 

dispersing into Jackson Hole in late 1998 (Smith et 

al. 1999). A pair of wolves, named the Teton Pack, 

denned near the center of East SA in early 1999 

and whelped 5 pups. The adult male was killed in a 

vehicle collision in July 1999.

Grizzly bear in Yellowstone National Park. USFWS

Table 1. Numbers of female grizzly bears with cubs of the year and total estimated grizzly bear population in 

the Greater Yellowstone Ecosystem, 1989 - 1999.

Year Females with cubs of the yeara Total number Estimated total

Unduplicated no. Total sightings of cubsa populationb

1989 16 33 29 214

1990 25 53 58 238

1991 24 62 43 287

1992 25 39 60 377

1993 20 32 41 374

1994 20 34 47 341

1995 17 25 37 364

1996 33 56 72 425

1997 31 80 62 480

1998 35 86 70 427

1999 33 108 63 407

a Schwartz and Haroldson 2002

b

 U. S. Fish and Wildlife Service 2003
 5

Capture and Monitoring of Elk

During 1997 - 1999, we replicated the methodology 

and experimental design for capture and monitoring 

of elk used in a 1990 - 1992 investigation of causespecific mortality of elk neonates (Smith and 

Anderson 1996). Each study used a Hiller 12-E 

helicopter to capture calves during late May and 

June of each year. During the 4 - 10 minutes we 

handled each calf, it was manually restrained, 

blindfolded, hobbled, sexed, and weighed to the 

nearest 0.25 kg. We aged calves according to 

Johnson (1951). We followed animal welfare protocol 

guidelines of the University of Wyoming and the 

U.S. Fish and Wildlife Service at the time of the 

study (Title 9 Code of Federal Regulations, Chapter 

1, Subchapter A, Section 2.31).

Capture weights of 70 calves < 1 day old were 

considered birth weights. We estimated birth 

weights of 248 calves > 1 day old by regressing 

capture weight on age (Smith et al. 1997). The 

regression slopes provided the sex-specific daily 

rates of gain of males and females. 

Methods varied in two respects between the study 

periods. During 1990 - 1992, we instrumented 

each calf with an expandable radio collar (Telonics 

Inc.) weighing 230 g, 1.5% of an elk’s birth weight 

(Smith et al. 1998). Batteries were configured and 

collars were designed to transmit pulse signals 

for > 26 months. A mortality sensor with a 5-hour 

delay switch was integrated into each transmitter’s 

circuitry. During 1997–1999, we fitted each calf with 

a 22-g ear tag transmitter (Advanced Telemetry 

Systems, Inc.). The transmitters remained silent 

while the calves were alive and active. When a 

transmitter remained immobile for > 4 hours, a 

mortality switch initiated transmission of a pulse 

signal. Garrott et al. (1985) found no difference in 

mortality rates and predation rates of mule deer 

(Odocoileus hemionus) fawns in Colorado, half of 

which were instrumented with radio collars and half 

instrumented with eartag transmitters. Survival was 

not affected by capture and radio-instrumenting of 

neonatal ungulates in previous studies (Ozoga and 

Clute 1988, Larsen and Gauthier 1989). 

In addition, during 1997 - 1999, we drew 10 cc 

of blood from most calves by venipuncture of 

the jugular vein. We chilled and centrifuged the 

blood, then collected and froze the sera at –20o

C. We submitted frozen sera to the Wyoming 

State Veterinary Laboratory within 1 month of 

collection for evaluation of physiological status and 

immunocompetence of calves. We used an automated 

analyzer for serum chemistry and electrolyte 

determinations (VetTest 8008 and VetLyte, Idexx). 

We analyzed levels of albumin, alkaline phophatase, 

aspartate aminotransferase, blood urea nitrogen, 

calcium, creatine kinase, gamma glutamylamin 

transferase (GGT), globulin, glucose, lactate 

dehydrogenase (LDH), magnesium, phosphorus, 

and total protein.

We employed null-peak telemetry systems at four 

fixed towers to monitor transmitter frequencies 

twice daily from capture of calves through 31 July, 

and once daily during August (Smith and Anderson 

1996). We also monitored transmitter frequencies 2 

- 3 times weekly from aircraft in areas beyond the 

reception range of telemetry towers.

Estimated Birth Weights and Rates of Gain

We estimated cohort daily rate of gain by regressing 

capture weights on capture age and using capture 

weights of calves < 1 day old as birth weights (Smith 

et al. 1997). Slopes of regression lines were cohort 

daily rates of gain, which we compared for each sex 

between study periods using analysis of covariance. 

We estimated birth weight of each calf > 1 day old 

using the sex-specific daily rate of gain for the study 

period in which it was born. We used Student’s 

t tests to compare mean monthly temperatures 

and precipitation during spring to identify factors 

influencing postpartum weight gain of calves during 

the two study periods. 

In addition to measurements of monthly 

temperature and precipitation, we explored how 

climate and vegetation phenological changes 

potentially influenced weight gains and survival 

of calves by using satellite-derived normalized 

difference vegetation index (NDVI) data. The NDVI, 

derived from the National Oceanic and Atmospheric 

Administration’s Advanced Very High Resolution 

Radiometer satellite sensor, have a 1 km x 1 km 

nominal spatial resolution and daily global coverage. 

NDVI metrics offer an efficient and objective 

means of evaluating phenological characteristics of 

vegetation on a broad scale (Reed et al. 1994). Due 

to the size of pixels, Advanced Very High Resolution 

Radiometer data are linked more to landscape 

processes than to individual plant communities 

(Malingreau and Belward 1992). Thus, we expected 

NDVI values to best correlate with our empirical 

forage measurements averaged over all plant 

communities sampled. 

Methods

Methods
6 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

The NDVI has shown consistent correlation 

with vegetation biomass and dynamics in many 

ecosystems, and their response to climatic changes. 

The NDVI thus represents the first useful tool with 

which to couple climate, vegetation, and animal 

distribution and performances on broad spatial and 

temporal scales (Pettorelli et al. 2005). Metrics of 

interest to us were NDVI greeness values for the 8th

(second and third weeks of April) and 9th (4th week 

of April and first week of May) composite periods 

of the year. We also calculated the rate of greenup 

as the straight line slope from 8th to the 12th (second 

and third weeks of June) composite period, based 

upon the NDVI values of each period. We assumed 

that each of these 3 metrics represented relative 

green forage quantity available each year (Reed et 

al. 1994).

Forensics

Upon detection of a mortality signal, we located 

and assessed the disposition of each calf as soon 

as possible (x =0.6 days in 1990, x= 0.5 days in 

1991, x= 0.4 days in 1992, x = 2.3 days in 1997, 

x= 0.5 days in 1998, and x= 1.0 days in 1999). At 

mortality sites, we conducted a thorough search for 

predator hair, feathers, tracks and scat, evidence of 

struggle and details of attack, and all remains of the 

carcass (Smith and Anderson 1996). We performed 

field necropsies on partially consumed carcasses, 

recording locations and measurements of canine 

punctures associated with attacks and noting feeding 

patterns. We collected and submitted tissue samples, 

and froze and sent intact carcasses to the Wyoming 

State Veterinary Lab for necropsy and diagnostic 

tests. We identified hair samples to species under 

a microscope, based on color, texture, and scale 

patterns of the medulla and cuticle (Moore et al. 

1974). To identify species of ambiguous hair samples, 

we subjected them to microsatellite analysis of 

mitochondrial DNA at the University of Montana’s 

Carnivore Conservation Genetics Laboratory (Mills 

et al. 2000).

Bear Distribution

To document presence of grizzly bears in both 

the West SA and East SA, we constructed 12 hair 

collection corrals (HCCs) (Woods et al. 1999) (Figure 

1). Seven were located in the West SA and five in 

the East SA. A 3.8-l plastic milk jug, nearly filled 

with bovine blood, was suspended by rope between 

two trees over the center of each HCC and beyond 

the reach of a tall bear (Wyoming Game and Fish 

Department 1996). We replaced jugs of bovine blood 

with fresh blood every three weeks.

We visited HCCs weekly from approximately 1 

June through 31 July 1997 - 1999. We removed, 

individually bagged, and submitted hair samples 

captured by the barbed wire for microscopic 

identification of species as described above.

Survival and Mortality Analyses

We monitored calf survival from birth through 31 

August each year but report neonatal survival from 

birth through 31 July, after which date mortality 

ceased. Variables measured during both studies 

that may affect survival included sex of the animal, 

birth weight, period of study (1990 - 1992 or 1997 

- 1999), study area where the elk was captured (East 

SA or West SA), and birth period. Birth period 

categorized the birth date of each elk among the 

first, middle, or last third of all captures. Because 

the temporal distribution of captures varied annually 

with parturition chronology and flying conditions 

(27 May - 25 June 1990, 26 May - 9 June 1991, 27 

May - 6 June 1992, 28 May - 7 June 1997, 26 May - 6 

June 1998, and 26 May - 13 June 1999), we adjusted 

the dates encompassed by the first, middle, and last 

third of the calving season somewhat annually to 

equalize sample sizes by birth period.

We investigated factors influencing the survival of 

elk during their first summer of life using a Cox 

proportional hazards (PH) model (Cox and Oakes 

1984, Collett 1994). Birth was time zero, t

0

, in the 

PH model. Assuming hi(t) is the instantaneous 

probability of death for individual i at time t (called 

the hazard function), and that the i-th individual is 

associated with a measured covariate vector xI = (xi1, 

xi2, ..., xip), the Cox PH model is

hi(t) = h0(t) exp(β1xi1 + β2xi2 + ...+ βpxip)

where h0(t) is called the baseline hazard and 

corresponds to the hazard function of an individual 

with covariate vector xI = (0, 0, ..., 0). 

The Cox PH model has been called semi-parametric 

because the distribution of lifetimes and the baseline 

hazard function are unspecified. The PH model 

derives its name from the fact that if hi(t) and hj(t) 

differ only because xi1 = xj1 + 1, the hazard ratio, 

hi(t)/ hj(t) = exp(β1), does not depend upon time. 

Hence, hi(t) and hj(t) are proportional through 

time and differ only by a multiplicative constant. 

This proportionality of hazard functions is a basic 

assumption of the Cox PH model, the violation of 

which can lead to errant results. The proportional 

hazards assumption was assessed by plotting scaled 

Schoenfeld residuals versus survival times, and 

computing a chi-square significance test for the 

resulting correlation (Grambsch and Therneau 1994)

If the proportional hazards assumption of the Cox 

PH model was not satisfied, a stratified Cox PH 

model was estimated that assumed a different 

baseline hazard function for individuals in different 

strata. Under the stratified Cox PH model, 

proportionality of hazard functions was assumed 

among individuals in the same stratum. A drawback 

of the stratified Cox PH model was that the 

relationship between hazard and the variable used to 

define the strata could not be estimated directly. In 

this case, Kaplan-Meier curves (Cox and Oakes 1984, 

Collett 1994) were computed for each stratum and 

the difference in survival among strata was tested 

using the log-rank test (Collett 1994). 

Hypotheses of the form H0: β1= 0 were tested using 

likelihood ratio tests (Collett 1994). We computed 

likelihood ratio tests as –2ln(L1) + 2ln(L2), where 

  ̄  ̄

  ̄  ̄

 ̄  ̄
 7

L1 represents the statistical likelihood of a Cox PH 

model that does not contain β1 and L2 represents the 

statistical likelihood of a Cox PH model that does 

contain β1. We then compared the resulting value to a 

chi-square distribution. We computed tests of factors 

involving more than two levels (and hence more than 

one βi) using L1 and L2 that differed by two or more 

coefficients. All two-way interactions of variables 

were initially considered in the Cox PH model. We 

removed any variables that were not significant in 

the Cox PH model one-at-a-time in a backward stepwise fashion to arrive at a final Cox PH model.

We classified each mortality as either predation 

mortality or not. For this analysis, we retained nonpredation mortalities in the analysis because like 

animals that survived the entire neonatal period 

(until 31 July each year), they did not succumb 

to predation. We censored the non-predation 

mortalities at the date of death. We investigated 

the instantaneous probability of death by predation 

using a Cox PH model applied to predation 

mortalities. Due to the small number of predation 

mortalities, we categorized birth weight as either 

< 16.0 kg (the average birth weight), or > 16.0 kg. 

We checked the proportional hazards assumption at 

each stage of the analysis. We eliminated terms in 

the Cox PH model that were non-significant. 

Population Size and Recruitment 

Each February, observers riding on feeding vehicles 

systematically counted the number of elk wintering 

on the NER and on three feeding grounds in the 

Gros Ventre drainage and classified them as calves, 

females (> 1 year old), yearling males, and mature 

males (Figure 1; Boyce 1989, Smith and McDonald 

2002). Elk wintering at other locations were 

surveyed and classified from a Bell B1 helicopter 

(Wyoming Game and Fish Department 2000, Lubow 

and Smith 2004). We used the Wyoming Game and 

Fish Department (2000) survey results and other 

data to model the winter population size with POP 

II software program (Bartholow 1997). We tested 

for difference in the mean number of elk in the 

Jackson herd during the 5-year interval (1985-1989 

and 1992-1996) preceding each of our two study 

periods (1990 - 1992 and 1997 - 1999) to assess lag 

effects in population influences on recruitment. We 

chose a 5-year interval because ungulate species 

can experience time lags of 3 - 10 years in densitydependent population responses (Saether 1997). 

We annually counted and classified elk that 

summered in our study areas in GTNP during the 

first week of August 1991 - 1999 from a Bell Jet 

Ranger helicopter (Smith and Anderson 1996). 

Recruitment rates during winter and summer are 

expressed as number of calves:100 females > 1 year 

old. We compared calf:100 cow ratios in August to 

expected reproduction from pregnancy rates (Smith 

and Robbins 1994). This provided a second measure 

of calf survival from birth through July that we 

compared to survival of radioed calves.

We assessed pregnancy rate of 159 > 2-year-old 

elk captured in a corral trap on the NER during 

February 1998 - 2002 from serum assays of 

pregnancy-specific protein-B (Noyes et al. 1997). 

We compared results to pregnancy estimates of a 

group of 318 > 2-year-old elk captured on NER 

during 1978 - 1982 (Smith and Robbins 1994). This 

comparison served to evaluate if fecundity of females 

had changed over time, which could influence 

recruitment and our population modeling efforts. 

We also compared pregnancy status of 52 yearling 

females during 1978 - 1982 to 42 yearlings captured 

and tested during 1998 - 2002.

Population Modeling

We built an individual based model to project the 

effects of increased neonatal mortality on the 

population growth rate of the Jackson elk herd. 

From the average of winter population classification 

counts obtained during the 1990s, we partitioned the 

elk population into six age-sex classes: male and 

female calves (each sex constituting 7.5% of the 

herd), yearling males (males > 1 but < 2 years old, 

5.6%), yearling females (5.6%), bulls (14.5%), and 

cows (59.3%). We assumed a 1:1 sex ratio at birth 

(Smith et al. 1996). We estimated 1% prehunting 

season mortality (1 August - 10 September) for each 

age-sex class (Smith and Robbins 1994, Smith and 

Anderson 1998). We estimated a herd pregnancy 

rate of 63% (17% for yearlings and 87% for 2+ 

year-old elk, reduced by 7% to account for brucellosiscaused fetal losses, Oldemeyer et al. 1993, Smith and 

Robbins 1994). To isolate the influence of change 

in neonatal survival on population growth, we held

constant over the two study periods all population 

parameters except neonatal survival. We considered 

how change in neonatal survival from the early 1990s 

to the late 1990s would alter the annual harvestable 

surplus of a preparturition population size of 11,000 

elk. We used 11,000 elk as that is the population 

objective established by the Wyoming Game and Fish 

Commission for the Jackson herd (Wyoming Game 

and Fish Department 2000).

Harvestable Surplus— We sought to estimate 

how a change in neonatal survival between study 

periods would change the number of elk available to 

hunters. To do so, we used Monte Carlo simulations 

to estimate the number of elk surviving and 

reproducing during the time period 20 May (onset 

of parturition) to 10 September (start of hunting 

season). The number of surviving elk represented 

the population size on 10 September. In the 

simulations, we generated random numbers and 

compared them with survival rates of each age-sex 

group, as reported by Smith and Anderson (1998) 

for radioed elk older than calves, to determine 

fate (death or survival) of each individual in the 

group. The fate of newborn calves was decided by 

comparing the random numbers with measured 

mortality of radioed calves from birth to 10 

September. We used the observed sex-specific 

neonatal mortality during each study period in the 

simulations. We determined reproductive status of 

each yearling and adult female from a separate set of 

random numbers. 

Methods
8 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

From 1,000 Monte Carlo simulations, we generated 

estimates of mean herd size in September and mean 

population growth rate for a pre-parturition herd 

size of 11,000 elk for 1990 - 1992 and for 1997 - 1999. 

We computed the finite rate of increase of the elk 

population from May to September for each iteration 

of the simulations, from the equation

r = (Nt+1-Nt)/Nt. 

The increase in the population size from 19 May 

to 10 September was considered equivalent to the 

harvestable surplus.

Annual Population Growth—We constructed 

Lefkovitch transmission matrices (Lefkovitch 

1965) of survival of 3 age classes of female elk for 

the early 1990s and the late 1990s. Annual survival 

rates of yearling and adult females reported by 

Smith and Anderson (1998) during 1990 - 1992 were 

used for both study periods. Likewise, Smith and 

Anderson (1998) reported annual survival of calves 

during 1990 - 1992 as the sum of neonatal, fall, and 

winter survival. For 1997 - 1999, we used the same 

estimates of calf fall and winter survival. Annual 

survival of female calves (s1)in the late 1990s was 

thus determined as the product of the seasonal 

survival rates 

s1 = sneo sf sw

where sneo = neonatal survival, sf = survival during

the fall, and sw = over-winter survival. We derived 

rates of neonatal survival (sneo) for each study period 

from radioed animals as measured in the present 

investigation. Fall (sf) and winter (sw) survival of 

calves reported by Smith and Anderson (1998) 

during 1990 - 1992 were applied to both study 

periods. Consequently, only neonatal survival was 

permitted to differ between 1990 - 1992 and 1997 

- 1999.

The Lefkovitch matrix for 1990 - 1992 is

2 3

1

2 3

0 0 0.17 0.81

0 0 0.66 0 0

0 0 0.89 0.94

f f

s

s s

        =            

The Lefkovitch matrix for 1997 - 1999 is

2 3

1

2 3

0 0 0.17 0.81

0 0 0.56 0 0

0 0 0.89 0.94

f f

s

s s

        =            

where f

2

 and f

3 are the fecundity of yearling and 

adult females, respectively; s1, s2, and s3 are the 

survival rates of calves, yearlings and adults, 

respectively. The dominant eigenvalues of the above 

Lefkovitch matrices were the annual finite rates of 

increase (λ) of the elk populations (Caswell 2001).

We conducted sensitivity analyses to determine 

how sensitive the finite rates of increase of the elk 

population were to the change in each nonzero 

element (or vital rate of elk) in the transmission 

matrices. The sensitivity of λ to a vital rate is 

determined by (Caswell 2001)

,

i j

ij

v w

a

∂λ = ∂ w v

Where aij

∂λ

∂ is the sensitivity of the finite rate of 

increase to changes in element aij of the Lefkovitch 

matrix; vi is the ith element of the left eigenvector of 

the Lefkovitch matrix, wj the jth element of the right 

eigenvector of the Lefkovitch matrix; and w v, is 

the scalar product of the right and left eigenvectors 

(Caswell 2001). The larger the sensitivity index 

the more sensitive λ was to the vital rate. 

Acquiring large, unbiased samples of newborn 

ungulates in wildland settings to assess survival 

and correlates with survival is difficult. We chose 

P < 0.10 as significant for statistical tests rather 

than a smaller P value, due to the biological and 

management importance of any such findings 

regarding survival rates. We used P < 0.05 when 

addressing differences in physical traits of calves 

between study periods and between the sexes.

ij a

∂λ

∂
 9

Birth Weights

We captured and radio-tagged 318 neonatal elk 

(Table 2). We censored from survival analyses 19 of 

164 calves captured (53 in 1990, 62 in 1991, and 49 in 

1992) during the early 1990s that cast their radios 

prior to 31 July of their birth year. We also censored 

1 of 154 elk captured (46 in 1997, 51 in 1998, and 57 in 

1999) during the late 1990s. Calves captured during 

1990-1992 were similar in age (x= 3.3 days + 0.16 

SE; t = 1.77, 317 df, P = 0.08) to those captured 

during 1997-1999 (x= 3.0 + 0.15 SE).

Capture weights of males (t = 1.96, 163 df, P = 

0.048) and females (t = 3.29, 152 df, P = 0.001) were 

heavier during 1990 - 1992 than during 1997 - 1999. 

However, capture weights of calves < 1-day-old 

(considered birth weights) were similar during the 

early 1990s (22 males, 11 females) and late 1990s 

(16 males, 21 females) (males: t = 0.09, P = 0.93; 

females: t = 1.3, P = 0.2). When capture weights 

of calves > 1-day-old were age-corrected, using 

daily rates of gain calculated for each study period, 

estimated birth weights were no different between 

the two time periods for males (t = 0.29, 163 df, P

= 0.77 and females (t = 1.29, 152 df, P = 0.2; Table 

2). Within study periods, estimated birth weights 

differed by sex (Table 2). Estimated birth weights 

for males (P > 0.6) and females (P > 0.8) were 

similar in the East and West study areas during 1990 

- 1992 and during 1997 - 1999 (Table 2). 

Growth and Physiological Status of Calves

Mean daily rate of gain increased linearly in all 6 

years (P < 0.001), but was more variable during 1997 

- 1999 (male: r2 = 0.25–0.50; female: r2 = 0.28–0.49) 

compared to 1990 - 1992 (male: r2 = 0.59–0.63; 

female: r2 = 0.41–0.59). Mean daily rate of gain of 

males exceeded that of females during the early 

Results

  ̄ 

  ̄ 

Results

Table 2. Estimated birth weights and daily rates of gain (kg/day) of newborn elk calves captured in the 

Jackson elk herd, northwest Wyoming. All captured neonates are represented, including those that later cast 

their radio transmitters. Birth weights were no different (P = 0.16 - 0.8) for either sex between study periods or 

between study areas. 

 Birth weight (kg) Rate of gain 

Study period Study area Sex n x SE x SE

1990 - 1992 Both Male 88 16.8 a 0.27 1.64 c 0.14

1997 - 1999 Both Male 76 16.6 b 0.29 1.18 c 0.18

1990 - 1992 Both Female 76 15.8 a 0.26 1.31d 0.14

1997 - 1999 Both Female 78 15.2 b 0.31 1.09 d 0.18

1990 - 1992 Both Both 164 16.3 0.19 1.39 e 0.11

1997 - 1999 Both Both 154 15.9 0.22 1.17 e 0.13

 

1990 - 1992 East Male 44 16.7 0.38 

1990 - 1992 West Male 45 16.8 0.39 

1990 - 1992 East Female 23 15.9 0.44 

1990 - 1992 West Female 53 15.7 0.32 

1997 - 1999 East Male 37 16.5 0.43 

1997 - 1999 West Male 39 16.8 0.40 

1997 - 1999 East Female 27 15.3 0.56 

1997 - 1999 West Female 51 15.2 0.37

a

 Birth weights of males and females were different (t = 2.72, 163 df, P = 0.007)

b Birth weights of males and females were different (t = 3.32, 152 df, P = 0.001)

c

 Rates of gain for males were different (F1,87 = 10.09, P = 0.002) between study periods.

d

 Rates of gain for females were not different (F1,76 = 1.44, P = 0.23).

e

 Rates of gain for all calves were different (F1,163 = 3.93, P = 0.049).

– –
10 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

1990s (F1,74= 4.45, P = 0.037), but not during the 

late 1990s (F1,76= 0.11, P = 0.7; Figure 2). Estimated 

daily rates of gain during the late 1990s declined 

from the early 1990s in both sexes, significantly so 

for males and sexes combined (Table 2).

We drew blood for serum assays from 84 of 

154 calves (67 that survived and 17 that died) 

captured during 1997 – 1999. Analyses of passive 

transfer of immunoglobulins showed no significant 

differences in gamma-globulin (t = 1.6, P = 0.12) 

or gamma-glutamyl transferase (t = 1.7, P = 0.1) 

concentrations between 67 neonates that survived 

and 17 that died. There were also no differences 

in these immunological attributes between study 

areas or sex (P > 0.7 for all tests). We also assessed 

exposure to leptospirosis and bovine viral diarrhea I 

and bovine viral diarrhea II and found no differences 

between calves that survived and those that died, 

between sexes, and between study areas (P = 0.22 

– 0.6 for all tests). However, surviving calves had 

higher total serum protein, phosphorus, alkaline 

phosphatase, and glucose and lower levels of blood 

urea nitrogen and lactate dehydrogenase compared 

to mortalities (Table 3). Serum attributes were not 

related to estimated calf birth weights.

Predator Abundance

We collected 537 hair samples from black bears 

and 8 hair samples from grizzly bears at 12 HCCs. 

Based on HCC visitations, black bears were twice 

as abundant in the West SA as the East SA during 

1997 – 1999 (Appendix A). Frequency of grizzly bear 

visitation at HCCs averaged 0.02 compared to 0.18 

and 0.37 for black bears in the East and West SA, 

respectively (Appendix A). 

Mortality Factors

Twenty-two of 145 (15.2%) elk captured and radioinstrumented during 1990 - 1992 died between birth 

and 31 July of their birth year compared to 42 of 153 

(27.5%; X2 = 0.6.7, P = 0.01) that died during 1997 - 

1999 (Table 4, Appendix B). Likewise the number of 

predator-caused deaths increased from 1990 - 1992 

[15 of 145 (10.3%)] to 1997 - 1999 [32 of 153 (20.9%); 

X2 = 0.6.3, P = 0.012]. However, the proportion of 

all mortalities per study period due to predation was 

similar between periods (68% vs. 76%, X2 = 0.48, P = 

0.49), whereas the proportion of deaths from disease 

declined (27% vs. 14%, Fisher’s exact test P = 0.034) 

(Figure 3, Appendix B). Bears of both species were 

responsible for 11 of 15 (73%) and 23 of 32 (72%) 

predator kills during 1990 - 1992 and 1997 - 1999, 

respectively. The proportion of marked calves killed 

by bears increased (Fisher’s exact test P = 0.038) 

from 1990 - 1992 to 1997 - 1999 in the grizzly bear 

occupied East SA, but not in the West SA (P = 0.61; 

Table 5). 

Grizzly bears killed 6 radioed calves (all during 

1997 - 1999), 5 in the East SA and 1 calf just west of 

the Snake River that separated the West and East 

study areas (Table 5, Appendix C). However, the 

proportion of calves killed by both species of bears 

did not differ between study areas during 1997 - 

1999 (Fisher’s exact test P = 0.17), nor did mortality 

from all causes differ (Fisher’s exact test P = 0.22, 

Figure 3).

We considered sex, birth period, estimated birth 

weight, study period, and study area as variables 

that may have contributed to mortality. No two-way 

interactions of these variables were significant in the 

Cox PH model. Among main effects, neither study 

area (P = 0.81) nor birth period (P = 0.28) 

Figure 2. Weights of elk calves captured during 1990 - 1992 and 1997 - 1999 regressed on age of the calves at 

birth. Weights of calves ≤ 1 day old were considered birth weights. Slopes of the equations are estimated 

cohort daily rates of gain for males and females during the first week of life.
 11

Table 3. Serum chemistries of 84 elk calves captured during 1997 - 1999 in the Jackson elk herd, northwest 

Wyoming. We used Student’s t tests to compare means of calves that survived (n = 67) and those that died 

(n = 17) during the neonatal period (birth to 31 July) and present results of each test producing a P value < 0.10.

Calves that survived Calves that died 

Serum attribute x SD x SD P value

Alkaline phosphatase (U/L) 903 531 654 336 0.022

Lactate dehydrogenase (U/L) 1168 350 1784 1149 0.052

Glucose (mg/dl) 148.8 27.0 130.4 40.5 0.092

Blood urea nitrogen (mg/dL) 16.4 5.8 24.3 16.3 0.063

Total protein (g/dL) 6.46 0.89 5.95 0.95 0.057

Phosphorus (mg/dL) 9.54 1.41 8.37 1.52 0.009

– –

Figure 3. Neonatal mortality (birth through 31 July of 

the birth year) of radioed elk calves captured in 

the East (East SA) and West (West SA) study areas 

during 1990 - 1992 and 1997 - 1999.

contributed significantly to mortality. Of the 

remaining 3 variables, we could not reject the 

assumption of proportional hazards for sex (P = 

0.33) and birth weight (P = 0.45), but we did reject 

proportional hazards for study period (P = 0.03). 

The test of the proportional hazards assumption 

implied that the elk survival curve’s shape changed 

significantly between 1990 - 1992 and 1997 - 1999. 

A log-rank test of the Kaplan-Meier survival 

curves confirmed that survival of elk declined from 

1990 - 1992 to 1997 - 1999 (P = 0.01). A plot of the 

estimated Kaplan-Meier curves for each study 

period revealed that survival of calves during 1990 

- 1992 “flattened” at approximately 30 days, while 

survival of calves during 1997 - 1999 continued to fall 

until approximately 60 days postpartum (Figure 4). 

We fit a stratified Cox PH model that satisfied the 

proportionality assumption within strata, with 

study period defining the strata. In the stratified 

model, both sex (P = 0.02) and birth weight (P = 

0.001) were significant factors. When we combined 

the early 1990s and late 1990s study periods, the 

instantaneous probability of survival was estimated 

Figure 4. Survival of elk (sexes combined) from birth 

to approximately 60 days of age during 1990 - 1992 

and 1997 - 1999. Log-rank test of difference was 

significant (P = 0.01).

Results
12 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

Table 4. Sex-specific neonatal mortality of radioed elk from the Jackson elk herd, northwest Wyoming, during 

1990 - 1992 and 1997 - 1999. Chi-square tests were used to compare the proportion of calves of each sex that 

died between study periods.

Number of males Number of females

Year Marked Died (%) Marked Died (%)

1990 26 2 24 3

1991 29 9 25 3

1992 22 5 19 0

1997 23 9 23 6

1998 24 5 27 7

1999 29 8 27 7

1990 - 1992 77 16 (20.8)a 68 6 (8.8)b

1997 - 1999 76 22 (28.9)a 77 20 (26.0)b

a X 2 = 1.4, Fisher’s exact test P = 0.27 b X 2 = 7.2, Fisher’s exact test P = 0.009

Table 5. Predation on neonatal elk (sexes combined) by black bears and by black and grizzly bears combined 

during 1990 - 1992 and 1997 - 1999 in the East and West Study Areas of the Jackson elk herd, northwest 

Wyoming. 

1990- 1997-

1990 - 1992 1997 - 1999 All years 1992 1999

Variable East West East West East West Both Both

No. captured 67 97 64 90 131 187 164 154

No. cast radios 9 10 1 9 11 19 1

Black bear kills 4 7 7 9 11 16 11 16

% black bear predation 6.9 8.0 10.9 10.1 9.0 9.1 7.6 10.4 

Black and grizzly bear kills 4 7 13a 10 17 17 11 23

% black and grizzly predation 6.9 8.0 20.3 11.2 13.9 9.7 7.6 15.0

a Includes one predation by a bear of undetermined species.

to be 83% (approximate 95% CI = 9.6% to 205%) 

greater for females than it was for males. The 

instantaneous probability of survival increased by 

15.4% (approximate 95% CI = 7.2% to 22.8%) for

every additional kilogram of weight at birth (Figure 

5). The effect of birth weight on survival was greater 

at lower birth weights (Figure 6, Table 6). Contrary 

to no difference in the early 1990s (P = 0.11 and 

0.42), capture weights (t = 3.0, 151 df, P = 0.003) and 

estimated birth weights (t = 3.5, 151 df, P = 0.001) of 

surviving calves were greater than weights of dying 

calves during the late 1990s by 1.8 kg and 1.7 kg, 

respectively. Elk that died from predation (14.6 kg 

± 0.5 SE), disease (14.7 kg ± 1.0 SE), and accidents 

(14.7 kg ± 1.3 SE ) were of similar birth weights 

(F2, 60 = 0.003, P = 0.99).

The instantaneous probability of death by predation 

was greater in the later study period (P = 0.012, 

log-rank test), but was not related to sex of the 

animal (P = 0.12). The probability of death by 

predation during 1990 - 1992 peaked at 9.5% for elk 

calves that were approximately 15 days old (Figure 

7). The probability of death by predation during 

1997 - 1999 peaked at 21.2% for elk calves that were 

approximately 55 days old (Figure 7). Predation by 

black bears and by black and grizzly bears combined 

increased during the 1990s (Table 5). 

Weather Effects on Survival

Although birth weights were the same, daily cohort 

rate of weight gain (sexes combined) declined from 

the early 1990s to the late 1990s (r2 = 0.49, F1, 163 = 

3.93, P = 0.049; Table 2). Lower weight gains of 

calves during the late 1990s coincided with cooler 

April temperatures (t = 2.8, 4 df, P = 0.05) and with 

higher elk numbers in the Jackson herd during the 

5 years preceding each study period (t = 2.57, 8 df, 

P = 0.033, Table 7). Neither the daily ration 

(t = 0.59, 4 df, P = 0.59) nor number of days elk were 

fed at the NER (t = 0.07, 4 df, P = 0.95) differed 

between the early 1990s and late 1990s study periods 

(Table 7). The proportion of female calves that died 

increased from the early 1990s to the late 1990s 
Results 13

Figure 5. Relationship of birth weight of male and 

female calves of the Jackson elk herd to probability 

of survival from birth to 31 July of their birth year 

during 1990 - 1992 and 1997 - 1999. We estimated 

survival curves from the stratified Cox proportional 

hazards model.

Table 6. Estimated survival probabilities (95% confidence intervals) from birth to 60 days of age for radioed elk 

calves of different birth weights during 1990 - 1992 and 1997 - 1999. We computed estimates from the stratified 

Cox proportional hazards model.

1990 - 1992 1997 - 1999

Sex Birth weight (kg) n Survival n Survival

Female >8 to 12 4 0.57 (0.38 - 0.86) 11 0.39 (0.22 - 0.67)

Female >12 to 16 36 0.75 (0.65 - 0.87) 41 0.61 (0.51 - 0.74)

Female >16 to 20 35 0.86 (0.80 - 0.93) 22 0.78 (0.69 - 0.88)

Female >20 to 24 1 0.93 (0.88 - 0.98) 3 0.88 (0.80 - 0.97)

Male >8 to 12 3 0.36 (0.13 - 1) 8 0.18 (0.04 - 0.89)

Male >12 to 16 19 0.60 (0.38 - 0.93) 30 0.41 (0.21 - 0.83)

Male >16 to 20 51 0.77 (0.62 - 0.96) 36 0.64 (0.44 - 0.91)

Male >20 to 24 15 0.87 (0.77 - 0.99) 2 0.79 (0.64 - 0.99)

(X2 = 7.2, df = 1, P < 0.01, Table 4). Annual survival 

of female calves positively correlated with their 

mean cohort weight gains (r2 = 0.71, F1, 4  = 9.9, 

P = 0.035). Annual survival of all calves positively 

correlated with mean monthly April temperature 

(r2 = 0.89, F1, 4= 34.0, P < 0.01; Figure 8). Annual 

predation by black bears (F1, 4 = 11.1, P = 0.029) 

and by both species of bears (F1, 4 = 651.7, P < 

0.002) varied inversely with mean monthly April 

temperature (Figure 9), and with NDVI during 

the second and third weeks of April (F1, 4= 42.6, P 

< 0.003 and F1,4 = 23.7, P < 0.008 , respectively, 

Figure 9). April is the month during which ambient 

temperatures are generally sufficient to produce 

abundant spring green-up in Jackson Hole (Figure 

8). Other NDVI metrics did not produce significant 

relationships to elk survival.

Figure 6. Elk calf survival by birth weight categories 

(sexes combined) during 1990 - 1992 and 1997 - 1999 

(see Table 6 for sample sizes).

Figure 7. Estimated probability of an elk calf (sexes 

combined) of average birth weight (15.7 kg) not 

being killed by a predator during 1990 - 1992 and 

1997 - 1999. Probability of death by predation is 1.0 

minus the height of the curves. Tick marks indicate 

elk censored when transmitters were cast (n = 19 

in 1990 - 1992 and n = 1 in 1997 - 1999) or calves 

surviving to 31 July of their birth year. 
14 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

Recruitment

Pregnancy rate of elk > 2 years old sampled during 

1998 - 2002 (86.2% of 159 elk) did not differ (X2 = 

0.03, 1 df, P = 0.8) from 1978 - 1982 (87.1% of 318 

elk). Likewise, pregnancy of yearlings was similar 

(X2 = 0.16, 1 df, P = 0.69) during 1998 - 2002 (14.3% 

of 42 elk) and 1978 - 1982 (17.3% of 52 elk). 

Summer and winter recruitment declined from the 

early 1990s to the late 1990s (Table 8). Early August 

calf:100 cow ratios in our study areas correlated 

with annual neonatal survival of radioed calves (r2

= 0.64, F1, 4= 7.06, P = 0.057). Likewise, mid-winter 

calf:100 cow ratios (prior to when most winter 

mortality occurs) of elk wintering on the NER 

correlated with neonatal survival (r2 = 0.62, F1, 4= 

6.64, P = 0.062). Calf:100 cow ratios during August 

in GTNP inversely correlated with population size 

(Figure 10). Calf:100 cow ratios on the NER during 

mid-winter also inversely correlated (r2 = 0.47, 

F1, 15= 13.1, P = 0.003) with population size the 

previous winter (Figure 10). The inverse relationship 

between calf:100 cow ratios and the winter NER elk 

population strengthened (r2 = 0.58, F1, 15= 19.6, P

= 0.001) when a 2-year lag effect (t-2) was used to 

reflect the true recruitment from adult cows rather 

than adult cows plus yearling cows. 

Table 7. Environmental and population characteristics of the two periods during which neonatal mortality of 

elk calves was studied in the Jackson herd.

Study period (x + SE)

Variable 1990 - 1992 1997 - 1999 Test result

Mean April temperature (o C) 5.1 + 0.7 3.1 + 0.2 P = 0.05

Mean number of days elk were fed on NER 66 + 2.1 65.3 + 9.1 P = 0.95

Mean daily ration fed to elk on NER (kg) 3.4 + 0.3 3.3 + 0.01 P = 0.59

Previous 5-year number of elk on and 

 adjacent to National Elk Refuge in wintera 8,681 + 567 10,558 + 360 P = 0.02

Previous 5-year Jackson herd sizea 12,445 + 949 15,025 + 330 P = 0.03

a Numbers of elk counted during mid-winter population surveys (Wyoming Game and Fish Department 2000), averaged for the five 

winters prior to the study period.

–

Table 8. Estimated annual recruitment rates (calves observed per 100 cows > 1 year old) from two periods 

during which neonatal mortality of elk calves was studied in the Jackson herd. A hypothetical preparturition 

herd size of 11,000 elk (the state of Wyoming’s herd management objective), pregnancy rate, and potential 

natality were held constant during the two study periods to evaluate the observed change in neonatal mortality 

on herd recruitment.

Study period (x + SE)

Variable 1990 - 1992 1997 - 1999 Test result

Herd pregnancy rate of females >1 year olda 63 63

Potential natality 4,498 4,498

% cohort mortality measured in radioed neonates 15.2 27.5

Expected August recruitmentb 53.4 45.7

Observed August recruitmentc 45.3 + 1.7 34.7 + 1.0 P = 0.02

Difference in observed and expected August recruitment 8.1 11.0

% underestimation of mortalityd 12.9 17.4

Estimated neonatal mortalitiese 1,264 2,020

Observed mid-winter recruitmentf 26.6 + 1.7 20.6 + 0.7 P = 0.03

a From Smith and Robbins (1994); pregnancy rate during 1998 - 2001 did not differ from the earlier period (see Results, Recruitment)

b Expected recruitment is the pregnancy rate reduced by the calculated neonatal mortality of radioed calves

c Observed recruitment is the number of calves:100 cows observed during August in the East and West study areas: 1990 - 1992 (Smith 

and Anderson 1996), 1997 - 1999 (BLS).

d This unaccounted for mortality largely is presumed to be perinatal mortality.

e Calf mortalities calculated as the difference between potential natality (63 calves:100 cows) in a herd of 11,000 elk and observed 

recruitment in August.

f Calves:100 cows observed in February on and adjacent to National Elk Refuge (Smith and McDonald 2002).

–
 15

Rate of Increase and Harvestable Surplus

Increased neonatal mortality reduced the finite 

rate of increase of the elk population from May 

(beginning of parturition) to September (beginning 

of the elk hunting season) each year from 1.39 ± 

0.004 during 1990 - 1992 to 1.34 ± 0.004 during 

1997 - 1999 (mean ± 1 SD; Fisher’s least significant 

difference, P < 0.05). Starting with a hypothetical 

preparturition herd size of 11,000 elk in May during 

both time periods, we simulated a September 

population of 15,274 ± 40 (x± 1 SD) in the early 

1990s compared to 14,786 ± 43 in the late 1990s. 

Therefore, the increased neonatal mortality 

observed during the late 1990s might lower the 

harvestable surplus by 486 elk if the population were 

at the state of Wyoming’s management objective of 

11,000 elk (Fisher’s least significance difference, 

P < 0.05).

The annual finite rate of increase (λ) of the elk 

population declined slightly from 1.26 in the early 

1990s to 1.23 in the late 1990s. The λ primarily 

was sensitive to adult female survival rate, and 

secondarily to calf survival rate in both the early and 

late 1990s (Table 9). 

Figure 8. Relationship of mean monthly April 

temperature (0C) to annual probability of survival 

from birth to 31 July of Jackson elk herd neonates, 

and to normalized difference vegetation index 

(NDVI) during the second and third weeks of April

1990 - 1992 and 1997 - 1999.

ij

λ

α

∂

∂

Table 9. Sensitivity analyses of Lefkovitch matrices 

of the Jackson elk herd, northwest Wyoming, 

constructed for the early 1990s and late 1990s. Here, 

 is the sensitivity of the finite rate of increase (λ) 

to changes in element aij of the Lefkovitch matrix. The 

larger the sensitivity index, , the more sensitive λ 

was to the vital rate.

Vital rate 1990 - 1992 1997 - 1999

Calf survival 0.34 0.36

Yearling female survival 0.23 0.22

Adult female survival 0.65 0.67

Yearling fecundity 0.09 0.08

Adult fecundity 0.26 0.24

ij

λ

α

∂

∂

ij

λ

α

∂

∂

ij

λ

α

∂

∂

Figure 9. Predation by black bears and combined 

predation by black and grizzly bears on elk neonates 

of the Jackson herd, 1990 - 1992 and 1997 - 1999, 

related to mean monthly April temperature (A), and 

to normalized difference vegetation index (NDVI) 

during the second and third weeks of April (B).

A 

B

Results
16 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

Figure 10. Calf:100 cow ratios at the National Elk Refuge during winters 1983 - 1999 regressed on number of 

elk counted on the National Elk Refuge the previous winter (A), and summer calf:100 cow ratios in Grand 

Teton National Park regressed on number of elk counted during summers 1991 - 1999 (B).

A B

Elk calf in Wyoming. Bruce Smith/USFWS.
 17

Discussion

Predisposing Mortality Factors

Birth weight strongly influenced survival of 

individual elk calves as in other studies of ungulates 

(Clutton-Brock et al. 1982, 1992, Clutton-Brock 

and Albon 1989, Kunkel and Mech 1994, Sams et 

al. 1996, Singer et al. 1997). Light-born calves were 

more vulnerable to all types of mortality, including 

predation. Male calves experienced higher mortality 

than females during the 6 years. As Smith and 

Anderson (1996) suggested, males may have been 

more rambunctious than females and consequently 

more subject to detection and mortality by predators 

than females during the early 1990s. Their faster 

growth rates and greater demand for milk may have 

prompted increased solicitations of nursing from 

their mothers, increasing exposure to predation. 

However, during the late 1990s, when growth rates 

were significantly reduced, predation was not sexbiased.

We unfortunately cannot compare blood chemistries 

between study periods, but we found several 

differences in serum values between calves that 

survived and calves that died during the late 1990s. 

Normal values and kinetics of serum enzymes 

and electrolytes from birth through weaning are 

not published for elk but have been examined for 

bovine calves (Knowles et al. 2000). Cross species 

comparisons must be made with care but the general 

pattern of increase and decline in ruminants is 

probably similar. 

Physiological Status—Alkaline phosphatase is an 

enzyme widespread in the body in various isoforms. 

Our assays did not differentiate between isoenzymes 

derived from liver or bone. Serum alkaline 

phosphatase values are typically high in neonates 

compared to adults but considerable individual 

variation occurs. The mean values found in both 

groups of elk calves were within normal ranges 

determined for neonatal bovine calves suggesting 

that the values detected did not indicate disease 

(Knowles et al. 2000). Increased levels of alkaline 

phosphatase in the calves that survived may have 

been due to increased activity of osteoblasts and 

bone formation and thus reflect more active growth 

than the calves that did not survive. 

Higher mean levels of serum glucose may indicate 

that calves that survived had more recently nursed 

and thus had better maternal care than the calves 

that did not survive. However, serum glucose is 

quite labile in whole blood samples and differences 

could reflect handling of the sample. Similarly, 

lactate dehydrogenase values may be influenced 

by handling including hemolysis and freezing of 

samples (Kaneko 1989), although struggling and 

increased muscle activity during capture could also 

result in increased levels of lactate dehydrogenase. 

Higher phosphorus levels in surviving calves may 

be related to skeletal mobilization and construction. 

Hemolysis may also influence levels of serum 

phosphorus.

Total protein typically decreases due to nutritional 

problems. Although surviving calves had higher 

total protein than those that died, the difference we 

measured in total protein between those groups was 

small. 

Serum glutamyltransferase (GGT) is correlated with 

passive transfer of immunoglobulins in neonatal 

bovine calves. It is produced in the mammary gland 

and is present at high levels in colostrum and thus 

serum levels in neonates may serve as a marker for 

ingestion of colostrum. Higher levels of GGT were 

found in neonatal white-tailed deer (Odocoileus 

virginianus) that survived compared to fawns that 

died (Sams et al. 1996) and ingestion of colostrum 

was suggested as a factor improving survival. 

Colostrum contains immunoglobulins and ingestion 

thus provides neonates with passive immunity 

to pathogens in their environment. The levels of 

GGT found in our elk calves were similar to wellnourished white-tailed deer fawns but considerably 

lower than levels found in bovine neonates (Knowles 

et al. 2000), which may reflect species differences in 

mammary enzyme production. Levels of GGT did 

not differ between elk calves that survived and died.

Blood urea nitrogen (BUN) levels may be influenced 

by both levels of production and excretion. The BUN 

levels found in both groups of elk calves were within 

normal ranges, though calves that died had slightly 

higher levels of BUN than those that survived. 

Contrarily, surviving white-tailed deer fawns had 

higher levels of BUN than those killed by predators 

(Kunkel and Mech 1994). Levels of BUN in bovine 

calves are very dynamic during the first few weeks 

of life (Knowles et al. 2000). Protein catabolism 

from muscle may cause increased levels of BUN 

in undernourished animals and thus differences 

between groups of elk calves may reflect a decreased 

plane of nutrition in calves that did not survive.

In summary, differences we observed in serum 

chemistries between calves that survived and those 

Discussion
18 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

that died may reflect better condition and/or higher 

intake of milk of surviving calves. This inference is 

consistent with nutritional studies at the Starkey 

Experimental Forest where lower levels of serum 

alkaline phosphatase, phosphorus, and glucose and 

elevated BUN correlated with poorer nutrition of elk 

neonates (J. G. Cook, pers. commun.).

Rate of Gain—Birth weights did not differ between 

the early and late 1990s, but calf growth rates and 

mortality did. The selective pressures of predation, 

hypothermia, and seasonal food restrictions have 

uniformly acted to produce relatively high neonatal 

milk intake; growth rates in temperate and arctic 

ungulates (Robbins and Robbins 1979). For 

example, Gerhart et al. (1996) reported that caribou 

calves attain their maximum genetic potential for 

daily weight gain during the first 4 weeks of life. 

Consequently, the highest energetic costs to female 

cervids occur during early lactation (Cowan and 

Wood 1955, Clutton-Brock and Albon 1989, Robbins 

and Robbins 1979, Spalinger 2000), and growth of 

calves is closely related to the milk yield of mothers 

(Mitchell et al. 1976, Blaxter and Hamilton 1980, 

Clutton-Brock and Albon 1989). Robbins et al. (1981) 

suggested that food intake of elk increases during 

late gestation and early lactation to compensate for 

decreased energy reserves following winter. Less 

than optimum foraging conditions and nutrition in 

several species of deer and domestic mammals will 

adversely affect the dam, her milk yield, and hence 

the growth rate, postnatal survival, and weaning 

weight of offspring (Clutton-Brock et al. 1982, 

Louden et al. 1983, Cameron et al. 1993, Cook et al. 

2004).

Not only did mortality increase during the late 1990s 

(particularly among females), but calves remained 

vulnerable to mortality, particularly predation, for 

twice as long following birth (Figures 4, 6; Appendix 

B). Elk calves are hiders (Geist 1982). After they 

are big and strong enough to follow their mothers 

and join nursery groups, calves benefit from the 

protection afforded by adults from predators that 

employ search techniques similar to bears. Calves 

that grow slowly may be nutritionally compromised, 

remain dependent on the hider strategy longer, 

and be less capable of avoiding predation. Female 

calves, which had lower birth weights than males 

throughout the 1990s, may have suffered more than 

males from the reduced weight gains we measured 

during the late 1990s. 

Weather—As in red deer (Cervus elaphus; Albon et 

al. 1987), our results suggest that neonatal survival 

was affected in a density-independent fashion by 

April temperatures -- not because of the influence 

of April temperatures on cohort birth weights but 

their influence on daily rates of gain immediately 

postpartum. We cannot unequivocally demonstrate 

the causative relationships between stochastic 

conditions, calf weight gains, and neonatal survival. 

We did not directly measure annual quality of forage 

available to elk during late gestation and early 

lactation, nor did we measure milk production of elk. 

However, onset of forage green-up, as indicated by 

NDVI during April, was strongly related to April 

temperatures, and we hypothesize that post-winter 

recovery of body condition and milk production of 

mothers varied with spring green-up of vegetation. 

New vegetative growth generally first appears 

in Jackson Hole in April and is significantly more 

nutritious and digestible than cured forage and 

rations of alfalfa hay fed elk on NER (Smith et al. 

1997). Merrill et al. (1993) reported that cool spring 

temperatures that delayed snowmelt retarded 

the onset of new plant growth by as much as one 

month in Yellowstone National Park. Cooler April 

temperatures during the late 1990s (a densityindependent effect), possibly compounded by 

increased competition for high quality forage on 

winter ranges among larger numbers of elk (a 

density-dependent effect), may have been the 

ultimate factors responsible for diminished neonatal 

growth and survival in the Jackson elk herd.

Recruitment and Density Dependence 

Adult survival of the Jackson elk herd is high, 

despite harvests averaging 3,050 elk annually during 

the 1990s (Smith and Anderson 1998, Wyoming 

Game and Fish Department 2000, Lubow and Smith 

2004). Reduced survival of neonates, in combination 

with hunter harvest of antlerless elk, has produced 

a slow decline in the elk herd from 18,200 elk in 1997 

toward the State of Wyoming’s population objective 

of 11,029 elk (Lubow and Smith 2004). 

Recruitment in ungulates is the main target of 

limiting factors, both density-dependent and 

density-independent (Gaillard et al. 1998). Houston 

(1982) and Singer et al. (1997) reported that both 

climate and population density influenced neonatal 

survival when the northern Yellowstone elk herd 

was near carrying capacity. Clutton-Brock et al. 

(1982) and Sæther (1997) concluded that density had 

a more significant influence on winter survival of 

calves than on neonatal survival. As numbers of red 

deer on Rhum increased, selection against light-born 

calves rose, despite no consistent change in cohort 

birth weights (Clutton-Brock et al. 1982). During the 

1990s, we found calf:100 cow ratios during August in 

GTNP and mid-winter on the NER (where most elk 

from calving areas in which we worked spent winter, 

Smith 1994), were inversely related to population 

size, suggesting a density-dependent relationship 

in calf recruitment. Boyce (1989) reported similar 

findings prior to 1990. Rather than declining 

fecundity, which we found unchanged from the 

1980s, the effect during our study was likely reduced 

juvenile survival. The August and mid-winter 

calf:100 cow ratios corroborated the trend, but not 

the amplitude, in annual neonatal survival (Table 8).

We modeled a decline between 1990 - 1992 and 

1997 - 1999 of 486 calves (11%) from a potential 

recruitment of 4,498 elk resulting from the different 

rates of neonatal mortality we measured during 

those time periods. If we account for potentially 

unmeasured perinatal mortality by comparing 

expected and observed midsummer recruitment, 
 19

estimated decline in recruitment was 756 elk (17%, 

Table 8). Gaillard et al. (1998) found that in 14 

species of ungulates, juvenile survival varied more 

than adult survival. However, a change in adult 

survival had 3 times the effect on λ as an equivalent 

change in recruitment. Our findings suggest adult 

female survival had twice the effect on λ as a change 

in neonatal survival (Table 9).

We did not measure a functional response of either 

weight gain or mortality of neonates to increased 

herd size during our study. Increased competition for 

spring forage among adults or social stressors may 

have diminished milk yields; but retarded postnatal 

growth and increased mortality of calves may have 

resulted from other factors, such as reduced milk 

production due to delayed vegetative green-up, 

or more predators. Winter food supplementation 

of 70% of the Jackson elk herd confounds any 

influence of increased elk densities on calf survival 

(Lubow and Smith 2004). However, daily rations and 

duration of feeding of NER elk were no different 

between our two study periods, and presumably did 

not affect differentially the condition of adult female 

elk or subsequent growth rates of their offspring. 

Furthermore, Bailey (1999) compared elk that 

wintered off feedgrounds to elk fed on the NER 

during winters 1996-97 and 1997-98 and found no 

differences in pregnancy rates, fetal growth, or body 

condition of cow elk. Finally, population analyses by 

Lubow and Smith (2004) found strong support for 

weather-dependent neonatal survival but only weak 

evidence of density dependence in neonatal survival 

at the range of population sizes modeled in the 

Jackson elk herd from 1980 to 2002 (9,000­­ - 18,200).

As Sæther (1997) noted, density dependence is 

particularly difficult to detect and demonstrate in 

ungulates, which are long-lived and show a high 

degree of age dependence in fecundity and mortality. 

These age-specific effects may generate time lags 

of 3 - 10 years in density-dependent responses and 

increase the length of study required to detect 

responses. Due to the nonlinearity of density 

dependence (Fowler 1987), detection may require 

that populations approach or exceed carrying 

capacity, which the food-supplemented Jackson herd 

apparently did not during the 1990s (Lubow and 

Smith 2004). 

Predation 

In general, neonatal loses are high in ungulates and 

may result from high rates of predation (Linnell 

et al. 1995, Sæther 1997). We found 68% and 76% 

of mortality during 1990 - 1992 and 1997 - 1999, 

respectively, was due to predation. Black bears 

accounted for 11 of 15 predator kills and 50% of all 

mortality during 1990 - 1992, and at least 16 of 32 

predator kills and 38% of all mortality during 1997 

- 1999. Black bears, which can also be important 

predators of moose (Alces alces) (Ballard et al. 1981, 

Schwartz and Franzmann 1991) and white-tailed 

deer (Kunkel and Mech 1994, Ozoga and Clute 1988), 

accounted for 24 of 35 neonatal elk mortalities in 

Idaho (Schlegel 1976). 

Singer et al. (1997) reported 75% of neonatal 

elk losses in Yellowstone National Park resulted 

from predation primarily by grizzly bears and 

coyotes. The 31% mortality of 127 radioed calves in 

Yellowstone is similar to the 27.5% loss we recorded 

during 1997 - 1999 when grizzly bears and mountain 

lions, in addition to black bears and coyotes, preyed 

on elk neonates. Gray wolves did not kill radioed 

neonates, but only one pack had colonized our study 

areas and not until the final year of our study.

Visitation rates at HCCs did not reflect relative 

predation rates on elk by black and grizzly bears. 

Black bears left 9 times more hair samples than 

grizzly bears at HCCs in the East SA, but killed 7 

calves compared to 5 killed by grizzly bears (Table 

6; Appendices A, C). Singer et al. (1997) noted that 

grizzly bears killed several times more elk neonates 

than did black bears in Yellowstone National Park 

where densities of the 2 bear species were roughly 

equivalent. Likewise, Ballard et al. (1988) and 

Larsen et al. (1989) found grizzly bears were more 

predatory than black bears on moose neonates in 

Alaska. 

Bears are effective predators on neonatal ungulates 

and may either opportunistically develop this 

behavior or learn it from their mothers (Schlegel 

1976, French and French 1990). Craighead and 

Sumner (1982) and French and French (1990) felt 

that grizzly bears may travel to elk calving areas 

in May and June specifically to prey on calves, 

presumably because the nutritional rewards are 

high. Alternatively, favorable phenological stage of 

plant communities may coincidentally draw elk and 

bears to similar areas to maximize nutrient intake 

from vegetation (Schlegel 1976). 

Bear predation on elk increased during years with 

cooler April temperatures and lower April NDVI. 

Poor foraging conditions, due to delayed green-up 

may have prompted bears to find alternative food 

sources to meet nutritional requirements (Schwartz 

and Franzmann 1991). Reynolds and Garner (1987) 

hypothesized that caribou calves and carrion 

provided female bears a high protein food source 

when other foods were lower in nutrition and energy 

demands were high, especially for lactating females. 

French and French (1990) reported that sow grizzly 

bears with young preyed on elk calves more than 

their frequency in the population indicated, but 

Mattson (1997) reported male grizzly bears killed 

2.8 elk calves/bear/year compared to 0.8 for female 

grizzly bears. Black bears appear to have higher 

growth, reproductive, and survival rates when 

neonatal ungulates are available as prey (Schwartz 

and Franzmann 1991). Thus in facultative predators, 

such as bears, predatory behavior may enhance 

fitness and therefore be adaptive. If so, predatory 

behavior should increase over time, as French and 

French (1990) suggested may have occurred among 

Yellowstone Park’s grizzly bear population. However, 

Mattson’s (1997) food habits analysis of Yellowstone 

grizzly bears did not support their contention.

Discussion
20 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

In four published studies of neonatal elk mortality in 

our region, predator kills, primarily by bears, ceased 

by early July. Schlegel (1976) found 79% of predator 

losses, 94% of which were by black bears, occurred 

prior to 15 June when calves were < 21 days old. 

Singer et al. (1997) reported no calves > 28 days old 

were killed by grizzly or black bears. Of 60 grizzly 

bear predatory events on elk calves, French and 

French (1990) observed none after calves were > 

34 days old. Mattson (1997) reported 71% of elk calf 

predation by grizzly bears in Yellowstone National 

Park occurred in June. We found the oldest calf 

killed during 1990 - 1992 by a predator, a black bear, 

was 12 days old. Calves 16 - 30 days of age died from 

causes other than predation. However, during the 

late 1990s, calves as much as 56 days old were killed 

by predators, including 5 predations by black and 

grizzly bears of calves 42 - 49 days old (Appendix B). 

We believe predators were able to successfully hunt 

older calves during the late 1990s due to increased 

vulnerability of those cohorts. Predation on calves 

of below average birth weight, lower growth rates, 

and inferior physiological condition suggests that 

predators found these calves vulnerable even when 

more than a month old.

We found that grizzly bears killed five of six calves 

before 19 June in advance of cattle turn-on dates 

in the Spread Creek allotment in Bridger-Teton 

National Forest and the Elk Ranch East allotment 

in GTNP. Depredations on bovine calves began in 

late June or July (Anderson et al. 2002), confirming 

some bears traveled to these allotments in advance 

of cattle being available. We do not know, however, 

if the same bears that killed elk were responsible 

for cattle depredations, nor do we know what 

proportion of the bear population preyed on either 

species. Moving cattle to adjacent, vacant grazing 

allotments on Bridger-Teton National Forest has 

been suggested to resolve grizzly bear depredations. 

We suggest this may only shift the location of the 

problem if the new allotment is used by calving elk. 

A better solution would be to move cattle beyond the 

known distribution of grizzly bears or to areas little 

used by elk for calving.

Reliability of Mortality Evaluation

Smith and Robbins (1994) estimated fecundity of elk 

that wintered on the NER at 63 calves:100 females 

> 1 year old. Observed August calf:100 cow ratios 

of these elk, most of which calve in and adjacent to 

GTNP (Smith and Robbins 1994), averaged 45.3:100 

during 1990 - 1992 compared to 53.4:100 expected 

following 15.2% neonatal mortality, and 34.7:100 

during 1997 - 1999 compared to 45.7:100 expected 

following 27.5% mortality (Table 8).

Discrepancies between expected and observed 

recruitment are attributable to one or a combination 

of the following causes. 1) Measurement error or 

change in fecundity. Pregnancy rate of adult (>

2 years old) females was nearly identical during 

2 sampling periods (87.1%: 1978 - 1982; 86.5%: 

1998 - 2001). The combined yearling and adult 

fecundity of 63 calves:100 females, corrected for in 

utero and abortion losses, previously estimated for 

the Jackson herd (Smith and Robbins 1994) was 

statistically similar to the 60.4 calves: 100 females 

modeled by Lubow and Smith (2004) during the 

1990s. Thus, unmeasured fecundity changes are 

an unlikely source of error. 2) Some barren cows 

may occupy habitats in midsummer in which they 

are less observable than calf-cow groups, thereby 

upwardly biasing observed recruitment estimates. 

Sightability corrected surveys of the Jackson elk 

herd conducted in 1996 did not indicate such a bias 

(Anderson et al. 1998). (3) Estimates of neonatal 

mortality of free-ranging ungulates from captured 

and radioed animals are downward-biased because 

of undetected perinatal mortality, including still 

births, calves rejected and abandoned by mothers, 

nonviable births, and perinatal predation. Ozoga and 

Clute (1988) concluded they underestimated by half 

all mortality of white-tailed deer from a sample of 

radio collared fawns. More than half of mortality of 

red deer and caribou (Rangifer tarandus) neonates 

occurs within 48 hours of birth (Blaxter and 

Hamilton 1980, Whitten et al. 1992). 

Average age of our captured calves was 3.2 days 

and we surely missed the opportunity to capture 

some calves that died immediately postpartum. 

If we presume that recruitment discrepancies 

are largely due to this source, we underestimated 

mortality by an additional 13 - 17% of births (Table 

8). Nonetheless, we detected several rarely reported 

causes of perinatal mortality, including dystocia, 

hemoperitoneum, enterocolitis due to Coronavirus 

and Rotavirus, brucellosis, encephalitis, meningitis, 

and a severe congenital cardiac anomaly (right 

ventricular aplasia; Appendices B, C). Two 

additional calves (388 and 399) sustained multiple 

abrasions associated with difficult births and were 

subsequently killed by a grizzly bear and coyote, 

respectively. These 14 calves (x= 2.2 days old ± 

0.3 SE) were younger (t = 3.1, P = 0.007) when 

captured than the remaining 284 calves (x= 3.3 

days old ± 0.1 SE), suggesting such rarely reported 

predisposing conditions are less likely to be found in 

neonates that have survived to an older age.

Compensation

Lower neonatal survival during the late 1990s 

was coincident with lower April mean monthly 

temperature, lower rates of gain of neonates, 

higher elk numbers, and ostensibly higher numbers 

of predators. We could not deduce the relative 

importance or interaction of these correlates with 

calf survival. Clearly, a greater proportion of calves 

died during the late 1990s, and the proximate cause 

of much of the mortality was predation. Population 

estimates of large carnivores are hard to come by, 

even in a region as intensively studied as Jackson 

Hole. The available information indicated numbers 

of grizzly bears (Anderson et al. 2002, Schwartz et 

al. 2002) and mountain lions (D. Brimeyer, and H. 

Quigley, pers. commun.) increased during our study. 

Nevertheless, black bears were responsible for most 

neonatal predation in both study areas and both 

study periods. 

–

–
 21

A 3-day old elk with an expandable radio collar. Bruce Smith/USFWS.

Grizzly bear and mountain lion predation during 

the late 1990s (4% and 1%, respectively, of radioed 

calves) could be considered additive mortality 

because predation rates by black bears and 

coyotes did not decline. However, five of six grizzly 

predations occurred in the East SA where total 

mortality was no greater than in our relatively 

grizzly bear-free West SA (Figure 3, Table 6). 

Importantly, diseases and accidents were four times 

less prevalent in the East SA than the West SA 

during the late 1990s (Figure 3). Suitable tissues 

for disease culture were seldom recoverable at bear 

kill sites, due to extensive feeding by bears. Yet, we 

diagnosed bacterial infections in calves 333 and 338 

killed by a grizzly bear and black bear, respectively. 

Calf 388, killed by a grizzly bear, had experienced 

multiple abrasions during a difficult birth. This 

evidence suggests that some grizzly bear and other 

predation was compensatory, removing animals that 

were compromised and may have succumbed to 

other mortality. The extended temporal vulnerability 

of neonates during 1997 - 1999 supports such a 

conclusion, as does the lower birth weights among 

calves that died from predation (as well as victims 

of disease and accidents) compared to calves that 

survived the neonatal period.

If grizzly bear predation and predation in general 

is partially compensatory, the net effect on the elk 

population may be much smaller than the absolute 

numbers of neonates killed by predation. That 

is, if predators remove compromised offspring 

that otherwise would succumb by fall to disease, 

accidents, or malnutrition, then the fall harvestable 

surplus may be little affected. Small calves are 

also disadvantaged in winter and suffer increased 

winter mortality (Clutton-Brock et al. 1982, CluttonBrock and Albon 1989, Singer et al. 1997, Smith and 

Anderson 1998, Cook et al. 2004). However, exact 

compensation is rare and, further, compensation is 

influenced by population density (Sinclair and Pech 

1996). Our findings suggest changes in recruitment 

and juvenile vulnerability to predation may 

ultimately be the products of stochastic variability in 

spring weather. Consequently, we can only conclude 

that increased predation was a proximate cause of 

declining neonatal survival during the 1990s. 

Discussion
22 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

Long-term predator-prey studies are essential 

to understanding the influence and interactions 

of variation in weather and population density on 

vulnerability of neonates to predation (Gaillard et al. 

1998, Ballard et al. 2001). This is especially true in 

long-lived species, such as elk, with a high degree of 

age dependence in mortality and fecundity (Sæther 

1997).

As in many multiple species systems, our findings 

do not clearly answer the question of how predators 

affect prey populations (Boutin 1992, Orians 1997), 

but suggest mechanisms by which some neonates 

are predisposed to predation and other mortality. 

One explanation of our findings is that increased 

mortality of calves during the late 1990s occurred 

independently of their physiological condition and 

growth. More predators resulted in more mortality 

of calves. However, at high prey densities, predation 

may act in a depensatory fashion to limit but not 

regulate prey numbers (Sinclair and Pech 1996). 

Furthermore, kill rates of ungulate prey appear 

to depend on whether the predator species is an 

obligate or facultative carnivore. For obligate 

predators, such as wolves and mountain lions, per 

capita kill rates appear fairly consistent over a wide 

range of prey densities (Ballard et al. 2001). Only 2 

of 64 mortalities during our study were by obligate 

predators. Kill rates of facultative carnivores, such 

as bears and coyotes, may depend more on alternate 

food sources and prey density, particularly regarding 

predation on neonates (Schwartz and Franzmann 

1991). For example, Mattson (1997) found annual use 

of ungulates as food by Yellowstone National Park 

grizzly bears was inversely related to availability 

and consumption of whitebark pine seed. Thus, 

the degree to which predation is compensatory is a 

product of predator numbers and relative abundance 

of alternate food sources.

We conclude that postpartum conditions for neonates 

declined during the 1990s resulting in birth of 

newborns that grew more slowly and suffered higher 

mortality during the two months postpartum. Slower 

growth extended the time during which calves were 

vulnerable to mortality, particularly predation. Low 

birth weight calves, particularly females, came 

under increasing and extended pressure of predation 

during the late 1990s. In short, adverse spring 

foraging conditions, for both predators and prey, 

possibly exacerbated by increased elk densities, may 

have precipitated a cascade of events that reduced 

calf recruitment. This scenario generates a complex 

model of predator-prey dynamics. The stochasitic 

ebb and flow of prey vulnerability and availability of 

alternate food sources for predators interact with 

predator abundance to dictate the degree to which 

predation is additive or compensatory over time.

Conclusion
 23

The continuing restoration and expansion of large 

carnivore populations in Jackson Hole, Wyoming, 

provide a unique opportunity to evaluate the 

interaction of a multi-predator community on a 

common prey species formerly released for several 

decades from predation by grizzly bears and gray 

wolves (Berger et al. 2001b). While predation on elk 

by black and grizzly bears and coyotes is largely 

restricted to neonates (Schlegel 1976, Singer et 

al. 1997), wolves and mountain lions are capable 

yearlong predators of juvenile and adult elk (Kunkel 

and Mech 1994, Murphy 1998, Kunkel et al. 1999, 

Smith et al. 1999). If predator numbers increase 

or the elk population declines, competition among 

these five extant carnivores, particularly during May 

- July, and pressure on recruitment will intensify, 

altering age structure of the elk herd. Given the 

economic importance of elk in this area (Smith 

2001), a court-mandated environmental analysis 

of the elk winter feeding program (Urbina 1998), 

pending removal of grizzly bears and gray wolves 

from federal protection as threatened species, and 

keen public interest, we believe the following theses 

justify careful future evaluation.

a) Winter-spring predation by wolves and mountain 

lions could be partly compensatory with winter 

losses if predation is directed at nutritionally disadvantaged calves (Kunkel et al. 1999, Mech et al. 

2001). If that predation focuses on elk not attending winter feedgrounds, and if wildlife managers 

respond by feeding additional elk to maintain 

population size, an increasing proportion of the 

elk herd will use feedgrounds in coming years. 

This has several ecological and economic consequences (Smith 2001).

b) Elk are a preferred prey of wolves and mountain 

lions in northern Rockies ecosystems (Kunkel 

et al. 1999, Murphy 1998, Mech et al. 2001). If 

elk numbers decline, alternate prey to elk will 

become more widely exploited by these predators 

(Kunkel and Pletscher 1999, Smith et al. 2000).

c) If predation on elk by a restored predator community in Jackson Hole is largely additive mortality, a decline in calf recruitment will require managers to make downward adjustments in human 

harvest of elk to maintain a stable population size 

(Gasaway et al. 1992, Kunkel and Pletscher 1999). 

However, if grizzly bears and wolves are delisted 

as threatened species, commensurate regulated 

harvest of these and the other predators of elk 

could maintain recruitment of elk.

d) Contrarily, if predation is largely compensatory, 

we will not see significant changes in the size of 

the elk population beyond those expected from 

human exploitation and variation in annual weather conditions, as modeled by Lubow and Smith 

(2004). As Sæther (1997) argued, more long-term 

investigations are needed to understand the complex interactions among ungulate recruitment, 

predation, weather, and nutrition. The Jackson 

herd provides one case study to compare with 

others in the northern Rocky Mountains.

Public interest in viewing large carnivores and 

commensurate economic benefits derived by states 

supporting carnivore populations have escalated 

during the past decade. Wildlife management 

decisions are now made under intense scrutiny 

by a public holding strong and divergent views 

on management (i.e. restoration, reintroduction, 

control) of large carnivores (Bath 1991, Fisher 1995, 

Orians 1997, U.S. Fish and Wildlife Service 1998). 

A skeptical public demands reliable information 

about how predators interact with ungulate 

populations, and insists on well-founded 

justifications for predator management programs. 

Meeting those needs are essential steps toward 

informed decision-making that balances public 

interests and maintains functional predator-prey 

systems. 

Future Research

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Appendix A.

Appendix A.

Frequency of visitation (proportion of weeks visited during the sampling period) of black and grizzly bears at 

hair collection corrals in the East and West study areas during 1997 - 1999. We monitored all corrals weekly 

from approximately 1 June through 31 July 1998 and 1999 (8 weeks). In 1997, we monitored all hair collection 

corrals 1 June through the third week of July (7 weeks) except Granite Creek and Death Canyon, which we 

monitored only during July (4 weeks). 

 Frequency of visitationa

Corral Name Study Area Species 1997 1998 1999

Murie Ridge West Black bear 0.71 0.75 0.88

Timbered Island West Black bear 0 0.13 0.63

Timbered Island West Grizzly bear 0 0 0.13

Burned Ridge West Black bear 0.29 0.50 0

RKO Road West Black bear 0.57 0.13 0

River Road West Black bear 0.29 0.13 0.38

River Road West Grizzly bear 0 0.13 0

Death Canyon West Black bear 1.00 0 0.13

Death Canyon West Grizzly bear 0 0 0.13

Granite Creek West Black bear 0.50 0.25 0.50

Three Rivers East Black bear 0 0.25 0.25

Three Rivers East Grizzly bear 0 0 0.13

Wolf Ridge East Black bear 0 0 0.25

Lava Creek East Black bear 0.57 0.63 0.13

Wallace Draw East Black bear 0 0 0.38

Mary’s Lake East Black bear 0.14 0 0.13

Mary’s Lake East Grizzly bear 0 0.13 0

All corrals West Black bear 0.48 0.27 0.36

All corrals East Black bear 0.14 0.18 0.23

All corrals West Grizzly bear 0 0.02 0.04

All corrals East Grizzly bear 0 0.03 0.03

a

 Number of weeks when hair was collected divided by the total number of weeks that we monitored hair corrals
30 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

Cause-specific mortality of radioed neonatal elk from the Jackson elk herd, northwest Wyoming, that died 

during 1990 - 1992 (n = 22 of 145 calves) and 1997 - 1999 (n = 42 of 153 calves).

 Number (%) of elk that died

Mortality class Specific cause 1990 - 1992 1997 - 1999

Predation Black bear 11 (50) 16 (38)

Coyote 4 (18) 5 (12)

Grizzly bear 6 (14)

Lion 2 (5)

Unknown predator 2 (5)

Unknown bear 1 (2)

 Subtotal 15 (68) 32 (76)

 

Accidents Drowned 1 2

Dystocia 1

Hemoperitoneum 1

 Subtotal 1 (5) 4 (10)

 

Disease Bacterial pneumonia 1 3

Viral enterocolitis 3 

Meningitis 1

Brucellosis-encephalitis 1

Congenital heart defecta 1

Emaciation 1 

Starvation 1 

 Subtotal 6 (27) 6 (14)

Grand total 22 (100) 42 (100)

a

 Calf born without a right ventricle.

Appendix B.
 31

Causes of and age at death of 22 of 145 elk neonates (sorted by dates of death) that died during 1990 - 1992 and 

42 of 153 neonates that died during 1997 - 1999 in the East (E) and West (W) study areas. 

Year Sex Study area Calf no. Cause of death Date Days old

1990 F W 20 Black bear 5 June 12

1990 M E 42 Coyote 8 June 8

1990 M E 47 Black bear 13 June 7

1990 F E 44 Starvation 4 July 30

1990 F W 53 Bacterial pneumonia 15 July 20

1991 F W 55 Black bear 29 May 10

1991 M E 67 Black bear 31 May 4

1991 M W 71 Black bear 1 June 5

1991 M W 70 Black bear 2 June 4

1991 M W 82 Black bear 3 June 6

1991 M E 58 Black bear 5 June 12

1991 M W 69 Black bear 7 June 9

1991 F W 90 Coyote 7 June 6

1991 M W 104 Emaciation 9 June 4

1991 M E 97 Enterocolitis - coronavirus 20 June 16

1991 F W 74 Black bear 21 June 3

1991 M W 101 Enterocolitis - coronavirus 23 June 18

1992 M E 121 Coyote 30 May 3

1992 M W 131 Coyote 1 June 2

1992 M E 134 Black bear 2 June 5

1992 M W 130 Drowned 22 June 24

1992 M E 160 Enterocolitis - rotavirus 28 June 24

1997 F W 346 Brucellosis-encephalitis 31 May 1

1997 M E 320 Unknown predator 3 June 8

1997 M E 334 Dystocia 4 June 3

1997 F E 333 Grizzly bear 6 June 9

1997 M W 341 Coyote 8 June 4

1997 F W 325 Black bear 10 June 11

1997 M E 317 Black bear 15 June 16

1997 M W 339 Bacterial broncho-pneumonia 18 June 14

Appendix C.

Appendix C.
32 Biological Technical Publication: Neonatal Mortality of Elk in Wyoming

Appendix C. continued

Year Sex Study area Calf no. Cause of death Date Days old

1997 F E 301 Grizzly bear 18 June 23

1997 M W 342 Drowned 23 June 24

1997 M E 335 Black bear 24 June 24

1997 M W 324 Mountain lion 7 July 35

1997 F W 329 Meningitis 7 July 37

1997 M W 303 Black bear 9 July 45

1997 F W 338 Black bear 17 July 46

1998 F W 368 Hemoperitoneum 31 May 6

1998 F W 367 Congestive heart failurea 2 June 6

1998 F E 369 Unknown bear 2 June 6

1998 F E 374 Grizzly bear 3 June 8

1998 F E 394 Black bear 8 June 6

1998 M E 397 Black bear 10 June 8

1998 M W 379 Mountain lion 10 June 10

1998 M E 387 Black bear 11 June 9

1998 M E 347 Black bear 11 June 17

1998 F W 377 Black bear 12 June 11

1998 F E 388 Grizzly bear 19 July 49

1998 M W 383 Unknown predator 22 July 56

1999 F W 416 Black bear 28 May 3

1999 M W 400 Coyote 29 May 4

1999 M W 415 Coyote 31 May 7

1999 M E 420 Black bear 7 June 9

1999 F E 425 Grizzly bear 7 June 11

1999 M W 450 Black bear 9 June 7

1999 F W 432 Grizzly bear 14 June 17

1999 M E 452 Coyote 16 June 10

1999 M E 453 Bacterial broncho-pneumonia 24 June 17

1999 M W 399 Coyote 26 June 34

1999 F W 401 Black bear 30 June 30

1999 M W 436 Drowned 12 July 45

1999 F W 445 Bacterial broncho-pneumonia 13 July 40

1999 F W 438 Black bear 14 July 42

1999 F W 437 Black bear 16 July 46

a

 Calf born without a right ventricle.

U.S. Department of the Interior

U.S. Fish & Wildlife Service

http://www.fws.gov

September 2006