The Greater Snow Goose: Report of the Arctic Goose Habitat Working Group 

SUGGESTED CITATIONS 

Batt, B. D. J., editor. 1998. The Greater Snow Goose: report of the Arctic Goose Habitat 

Working Group. Arctic Goose Joint Venture Special Publication. U.S. Fish and Wildlife 

Service, Washington, D.C. and Canadian Wildlife Service, Ottawa, Ontario. 88pp. 

Reed, A., Giroux, J-F, Gauthier, G. 1998. Population size, productivity, harvest and 

distribution. Pages 5-31 in B. D. J. Batt, ed. The Greater Snow Goose: report of the 

Arctic Goose Habitat Working Group. Arctic Goose Joint Venture Special Publication. 

U.S. Fish and Wildlife Service, Washington, D.C. and Canadian Wildlife Service, 

Ottawa, Ontario. 

Library of Congress Catalog Card Number 98-76205 

Printed in the United States of America 

ISBN: 0-9617279-4-2 

Printed by Paulsen Printing, Memphis, Tennessee 
Table of Contents 

EXECUTIVE SUMMARY............................................................................................................1 

INTRODUCTION Bruce Batt ....................................................................................................3 

LITERATURE CITED.....................................................................................................4 

CHAPTER 1 POPULATION SIZE, PRODUCTIVITY, HARVEST AND 

DISTRIBUTION ...............................................................................................5 

Austin Reed, Jean-François Giroux and Gilles Gauthier 

POPULATION SIZE ........................................................................................................5 

Total Population ........................................................................................................5 

Breeding Numbers on Bylot Island..........................................................................8 

PRODUCTIVITY..............................................................................................................9 

HARVEST........................................................................................................................10 

Recreational Harvest...............................................................................................10 

Age Ratio in Recreational Harvest.........................................................................11 

Subsistence Harvest.................................................................................................13 

Harvest Rate.............................................................................................................13 

DISTRIBUTION .............................................................................................................15 

Wintering Range......................................................................................................15 

Spring Staging Areas...............................................................................................17 

Breeding Range........................................................................................................19 

Fall Staging...............................................................................................................19

Interactions with Atlantic Population Canada Geese ..........................................20 

SUMMARY......................................................................................................................23 

LITERATURE CITED...................................................................................................24 

CHAPTER 2 IMPACT OF GEESE ON NATURAL HABITATS ....................................32 

Jean-François Giroux, Gilles Gauthier, Gary Costanzo and Austin Reed 

INTRODUCTION...........................................................................................................32 

ST. LAWRENCE RIVER...............................................................................................32 

Use of Natural Habitats by Greater Snow Geese along the 

St. Lawrence River..........................................................................................32 

Distribution and Area of Bulrush Marshes along the St. Lawrence River ........33 

Feeding Behavior of Geese in Bulrush Marshes ...................................................33 

Effect of Geese on Bulrush Production..................................................................34 

Effect of Geese on Plant Species Composition ......................................................36 

Effect of Geese on Bulrush Quality........................................................................37 

Effect of Geese on Marsh Erosion..........................................................................37 

Effect of Geese on Other Species............................................................................38 

Restoration of Bulrush Marshes ............................................................................38 

Conclusions – St. Lawrence River..........................................................................38 

Summary – St. Lawrence River .............................................................................39 
U.S. ATLANTIC COAST ...............................................................................................39 

Greater Snow Goose Use of Coastal Marshes.......................................................39 

Extent of Snow Goose Eat-outs Along the Atlantic Coast ...................................40 

Ecological Significance of Snow Goose Feeding Activities...................................43 

Summary – U.S. Atlantic Coast..............................................................................44 

ARCTIC BREEDING HABITAT .................................................................................44 

Habitat Use by Geese...............................................................................................44 

Annual Impact of Grazing on Vegetation .............................................................46 

Impact on Gosling Growth .....................................................................................48 

Long-term Impact of Grazing ................................................................................49 

The Carrying Capacity of Bylot Island for Brood-rearing..................................51 

Summary – Arctic Breeding Habitats ...................................................................53 

LITERATURE CITED...................................................................................................53 

CHAPTER 3 IMPACT OF GEESE ON FARMLANDS ....................................................58 

Bernard Filion, Dennis Luszcz and Guy Allard 

SOUTHERN QUÉBEC...................................................................................................58 

Introduction .............................................................................................................58 

Studies of Goose Damage to Farmlands ................................................................58 

Evaluation of Goose Damage and Compensation to Farmers.............................59 

Summary – Southern Québec.................................................................................61 

MID-ATLANTIC STATES ............................................................................................61 

Summary – Mid-Atlantic States.............................................................................63 

LITERATURE CITED...................................................................................................63 

CHAPTER 4 POPULATION MODEL OF THE GREATER SNOW GOOSE: 

PROJECTED IMPACTS OF REDUCTION IN SURVIVAL ON 

POPULATION GROWTH RATE ................................................................65 

Gilles Gauthier and Solange Brault 

INTRODUCTION...........................................................................................................65 

THE MODELING APPROACH ...................................................................................66 

CHOICE OF MODEL PARAMETERS .......................................................................68 

THE MODEL ..................................................................................................................70 

Elasticity Analysis....................................................................................................71 

Proportion of Good, Average and Bad Years .......................................................72 

ANALYSIS OF THE EFFECT OF SPORT HUNTING ON POPULATION 

GROWTH........................................................................................................73 

Estimation of Hunting Mortality............................................................................74 

Scenarios for Increased Harvest ............................................................................75 

SUMMARY......................................................................................................................78 

ACKNOWLEDGMENTS...............................................................................................79 

LITERATURE CITED...................................................................................................80 
CHAPTER 5 CONCLUSIONS AND MANAGEMENT RECOMMENDATIONS.........81 

Jean-François Giroux, Bruce Batt, Solange Brault, Gary Costanzo, Bernard Filion, Gilles 

Gauthier, Dennis Luszcz and Austin Reed 

CONCLUSIONS..............................................................................................................81 

MANAGEMENT RECOMMENDATIONS .................................................................83 

SUGGESTED STRATEGIES ........................................................................................84 

GETTING THE JOB DONE..........................................................................................87 

EVALUATION AND THE ROLE OF ADAPTIVE MANAGEMENT .....................87 

Population Monitoring............................................................................................87 

Habitat Monitoring .................................................................................................88 

LITERATURE CITED...................................................................................................88 
1
 

EXECUTIVE SUMMARY 

The spring population of the greater snow goose has increased from less than 50,000 

birds in the late 1960s to about 700,000 in the spring of 1997. The growth rate of the population 

is approximately 9% per year, about twice the rate of the mid-continent lesser snow goose. The 

population is doubling about every eight years and there are no signs to indicate any slowing of 

this pattern. At this rate, numbers of greater snow geese should reach 1,000,000 by 2002 and 

2,000,000 by 2010. 

The geese heavily use traditional spring and fall staging areas along the St. Lawrence 

River. The numbers of birds have far exceeded the carrying capacity of the natural marshes and 

the birds have expanded their use of habitat into surrounding farmlands. The long-term integrity 

of the marshes is threatened with continuing degradation but these changes are not believed to be 

permanent or irreversible if the impact of the geese could be reduced. Wintering habitat on the 

Atlantic Coast is severely impacted at a few traditionally used sites. However, this damage is 

limited in relation to the total amount of salt marsh available and these damaged areas are likely 

to recover if management practices can be implemented to redistribute the birds to other unused 

salt marsh areas. 

On wintering areas, the increased numbers of geese is also being sustained by their use of 

agricultural habitats. Some localized crop damage occurs but it is not extensive. However, 

damage to hayfields near spring staging areas along the St. Lawrence River is severe, widespread 

and of considerable economic significance. This is a major management problem for wildlife 

agencies and will worsen as the greater snow goose population continues to grow. However, 

even if population growth is arrested, the birds have adapted so thoroughly to these agricultural 

habitats that the impacts by the geese will remain very extensive and will require innovative 

corrective measures. 

Studies on the high Arctic breeding habitats do not indicate that extensive damage to that 

ecosystem is currently occurring as a result of over-abundant goose use. The population is 

estimated to be at about one-half the carrying capacity on the areas studied on Bylot Island, the 

largest breeding colony. This is likely near an ideal and long-term sustainable level. Over the 

last 19 years, body mass, size and condition measured on fall staging areas along the St. 

Lawrence River have all declined indicating density dependent factors operating during the 

brood-rearing period to reduce gosling growth. We believe these effects are likely real at the 

level of the whole population. However, survival and growth rate measurements over the recent 

8-year period on the Bylot Island nesting colony have not discovered a similar pattern. 

A comprehensive population model was developed using recent and historical 

demographic data from breeding and staging areas. It was then used to explore the effect on 

population growth rate of changing the survival of the birds during several life history stages. 

Adult survival (approximately 83%) was determined to be the most important variable, 

accounting for 60% of population growth rate in good breeding years compared to 98% in poor 

years. Survival of young birds was the second most important variable, accounting for up to 20% 

of variability in population growth in good breeding years. 

The Working Group believes that continued growth of the population will soon threaten 

the long-term integrity of the Arctic ecosystem upon which the birds depend as has occurred 

elsewhere on habitats used by mid-continent lesser snow geese. The lesser snow goose 

population serves as a relevant and timely model for the greater snow goose and provides 

managers with an unambiguous warning as to where the current trend will likely lead. Continued 

growth of the population will also result in some expansion of salt marsh degradation on the U.S. 
2 

Atlantic Coast and along the St. Lawrence River as well as increased damage to the already 

ravaged farmlands in parts of southern Québec. 

The Working Group recommends that management intervention be implemented as soon 

as possible to arrest the growth of the greater snow goose population and stabilize it, by the year 

2002, at between 800,000 and 1,000,000 birds. Stabilization should occur if harvest rate is 

doubled to 24% from the current rate of 12%. Specific suggestions of practices that will increase 

harvest rates are offered and we point out that experience gained from programs designed to 

reduce the size of the mid-continent population of lesser snow geese will provide extremely 

relevant guidance for managers. 

Any new management practices should be implemented under an Adaptive Resource 

Management scenario, thus requiring that current data collecting programs be reviewed and then 

continued, modified, or expanded where needed. Again, experience gained with management and 

evaluation of mid-continent lesser snow geese will be very helpful in developing the Adaptive 

Management program needed for these geese. Changes in future management paradigms will 

also require effective communications programs to inform, and gain the support of, all the 

relevant stakeholders. 
3
 

INTRODUCTION 

BRUCE BATT, Ducks Unlimited, Inc. 

Waterfowl managers have become increasingly concerned about the dramatic increases 

of some populations of North American Arctic nesting geese. The basis for their concern is the 

widespread habitat degradation that is occurring on many Arctic nesting colonies and staging 

areas as reviewed by Abraham and Jefferies (1997a). This damage is threatening to the snow 

geese themselves and to the myriad other species that share the same ecosystem with them. The 

extent of the damage has been quantified especially well for Hudson and James Bay coastal 

habitats used by mid-continent lesser snow geese (Anser caerulescens caerulescens) Abraham 

and Jefferies (1997b). However, biologists at many locations across the Arctic have noticed 

increased degradation of areas used by most of the “white” geese, including other lesser snow 

goose populations, greater snow geese (A. caerulescens atlantica) and Ross’ geese (A. rossii). 

Managers have been responding to increasing white goose numbers for at least the last 

decade through liberalized bag and possession limits and longer hunting seasons. These changes 

generally have increased the kill but harvest rates have been inadequate to overcome the rate at 

which some populations are growing (Rockwell et al. 1997, Chapter 4). 

The Arctic Goose Joint Venture (AGJV) of the North American Waterfowl Management 

Plan recognized these issues as needing special attention beyond what can be done under typical 

management guidelines and protocols. Their establishment of the Arctic Goose Habitat Working 

Group in 1996 initiated a series of reports and actions that have elevated the awareness of 

problems and potential management actions for the mid-continent lesser snow goose population. 

The publication of the report Arctic Ecosystems in Peril (Batt ed. 1997) provided the scientific 

underpinning that resulted in a “call to action” for increased management attention to bring the 

population back to a level that can be sustained by its Arctic ecosystem. 

Public agencies and private conservation groups have rallied to support the management 

objective with a great variety of workshops, planning exercises, public consultations and 

communications initiatives. The media have been heavily engaged in covering the issue from a 

multitude of angles. Two pieces, which provide the general reader with a solid background of the 

main issues, were provided by Rockwell et al. (1997) and Ben-Ari (1998). A documentary video 

that describes the biological basis for the problem has been produced and can be obtained from 

Ducks Unlimited, Inc. (One Waterfowl Way, Memphis, TN 38120). 

In 1997, the AGJV charged the Working Group with conducting a similar review for the 

greater snow goose which many scientists believe are on a similar path to what was determined 

for the mid-continent lesser snow goose. This report is a product of that action. It is similar in 

approach and content to what was produced in the earlier report. Again, the Working Group took 

it as their mandate to provide the Joint Venture with a solid scientific analysis of the situation 

with the greater snow goose followed by a modeling exercise designed to clarify the likely 

population impacts of a range of possible future management actions. The report also includes 

recommendations for management consideration by the AGJV and the responsible public 

agencies. 

The report was presented to the AGJV in March of 1998 in Orlando, Florida. It was 

approved in general but the writing team still had many editorial and peer review steps to take. 

That work was accomplished and led to the preparation of this final report. 
4 

Members of the Joint Venture Management Board, other Writing Team members, other 

Working Group members, the AGJV Technical Committee, the Atlantic Flyway Snow Goose 

Committee and a selection of other peers were asked to provide critical review of the March 1998 

document. The Writing Team acknowledges the comprehensive reviews received from Dr. Jean 

Bédard (Université Laval), Paul Castelli (New Jersey Division of Fish, Game and Wildlife), Dr. 

Evan Cooch (Simon Fraser University), Mike Johnson (North Dakota Game and Fish 

Department), Dr. Mark Lindberg (Ducks Unlimited), and Dr. James Nichols (U.S. Fish and 

Wildlife Service). Other useful comments on the March draft were received from Dr. Ken 

Abraham (Ontario Ministry of Natural Resources), John Dunn (Pennsylvania Game 

Commission), and Dr. Robert Jefferies (University of Toronto). 

The Writing Team met together once, in February of 1998 in New Jersey. Since then, 

vigorous and effective communications between team members have been conducted through email. Interruptions occurred because of fieldwork and other work priorities but we thank our 

employers for allowing us the time to be engaged in this project. The Canadian Wildlife Service 

provided travel funds for the three university-based team members but each other individual’s 

expenses were provided by his employer. Brenda Carlson of Ducks Unlimited, Inc. had the 

burden of pulling all the various versions and formats together through a series of drafts and 

revisions that sometimes seemed endless. Nevertheless, she prevailed and the authors thank her 

for hanging in there. Ducks Unlimited provided office support, express mail and graphic design 

support for several drafts and for the final production. 

LITERATURE CITED 

Abraham, K.F., and R.L. Jefferies. 1997a. High goose populations: causes, impacts and 

implications. Pages 7-72 in B.D.J. Batt, ed. Arctic ecosystems in Peril: Report of the 

Arctic Goose Habitat Working Group. Arctic Goose Joint Venture Special Publication. 

U.S. Fish and Wildlife Service, Washington, D.C. and Canadian Wildlife Service, 

Ottawa, Ontario. 120pp. 

Abraham, K.F., and R.L. Jefferies. 1997b. Increases in numbers of lesser snow geese and their 

effect on vegetation in the coastal region of southern Hudson Bay. Arctic Goose Joint 

Venture Project Completion Report. 40:25pp. Mimeo. 

Batt, B.D.J. editor. 1997. Arctic ecosystems in Peril: Report of the Arctic Goose Habitat Working 

Group. Arctic Goose Joint Venture Special Publication. U.S. Fish and Wildlife Service, 

Washington, D.C. and Canadian Wildlife Service, Ottawa, Ontario. 120pp. 

Ben-Ari, E.T. 1998. A new wrinkle in wildlife management. BioScience 48(9):667-673. 

Rockwell, R., E. Cooch, and S. Brault. 1997. Dynamics of the mid-continent population of lesser 

snow geese – projected impacts of reductions in survival and fertility and population 

growth rates. Pages 73-100 in B. D. J. Batt, ed. Arctic ecosystems in Peril: Report of the 

Arctic Goose Habitat Working Group. Arctic Goose Joint Venture Special Publication. 

U.S. Fish and Wildlife Service, Washington, D.C. and Canadian Wildlife Service, 

Ottawa, Ontario. 120pp. 

Rockwell, R., K.F. Abraham, and R.L. Jefferies. 1997. Living Bird. Cornell Laboratory of 

Ornithology, Ithaca, NY. 16(1):16-23. 
5
 

CHAPTER 1 

POPULATION SIZE, PRODUCTIVITY, HARVEST, AND 

DISTRIBUTION 

AUSTIN REED, Canadian Wildlife Service 
 

JEAN-FRANÇOIS GIROUX, Université du Québec à Montréal 
 

GILLES GAUTHIER, Université Laval 
 

POPULATION SIZE 

Total Population 

Population management of most North American geese is based on trends detected from 

mid-winter aerial surveys. These surveys do not provide estimates of total waterfowl numbers. 

Rather, the wintering habitat is sampled in a consistent way each year by flying standardized 

flight lines in small fixed-wing aircraft and using experienced observers to visually estimate the 

size of flocks encountered. No attempt is made to correct for error in visual estimation, nor to 

extrapolate for areas outside the flight lines. Assuming that a more-or-less equal proportion of 

the population is counted each year, these surveys can be expected to show trends that are similar 

to those occurring in the overall population. 

Snow geese (Anser caerulescens) do not lend themselves well to such an approach. 

Firstly, they are very gregarious and range widely and unpredictably over large expanses of 

coastal marshes and agricultural fields; this clumped and unpredictable distribution makes it 

unlikely that mid-winter surveys flown along standard routes would encounter an equal 

proportion of the population each year. Secondly, individual flocks are often so large as to defy 

the capabilities of even experienced observers to estimate numbers accurately. 

On the other hand the white plumage of snow geese contrasts with most backgrounds, 

making it relatively easy to detect flocks at great distances and to conduct exhaustive aerial 

surveys over large areas. The same contrasting plumage also allows the use of aerial photography 

as a means of markedly increasing the accuracy of estimating flock size. Since the mid-1950s, 

various types of aerial surveys (some using photography) have been conducted on wintering 

flocks of greater snow geese (A.c. atlanticus) in the United States (Serie 1996), and with staging 

flocks during spring and fall migration in the St. Lawrence valley, Québec (Heyland 1972, 

Bourget 1974, Gauvin and Reed 1987). A routine survey has evolved from these earlier surveys 

and now serves as the basis for greater snow goose population monitoring in the Atlantic Flyway 

(Anon 1981). This survey undoubtedly includes some lesser snow geese (A.c. caerulescens), but 

because they compose such a small proportion of the flock (judged to be less than 3%: Anon 

1981) no attempt is made to correct for this factor. 

This routine survey is conducted in spring while the geese are staging in the St. Lawrence 

valley (Fig.1-1) and involves exhaustive aerial coverage and photography to estimate the size of 

the entire population. In the 1960s through the 1980s, all flocks were photographed and all geese 

on each photograph were counted. By the late 1980s, with increased numbers of geese ranging 

over a larger geographic area, two problems were recognized. Firstly, the conducting of total 

counts on photographs became increasingly fastidious and costly, and caused delays in producing 

estimates. Secondly, with geese occupying a much larger portion of the St. Lawrence valley and 

making daily flights to farm fields well inland from the river, it became more difficult to be sure 

that all flocks were encountered during a single survey flight. 

7 

In response to these problems, a re-designed survey was initiated in 1991, involving two 

main changes: 1) the counting of geese from photographs was conducted using sampling procedures 

rather than total counts (although full photographic coverage was maintained), and 2) replicate 

surveys were conducted each spring to examine within-year variability in population estimates and 

to assess the likelihood of flocks being missed during individual surveys. The sampling procedure 

for photographic counts is conducted in two stages. Firstly, each photographed flock is assigned to 

one of three size classes or strata (small, medium, large) based on a visual estimate of the size of that 

flock recorded during the survey (refined, if necessary, from a second visual estimate from the 

photograph). A random sample of flocks (photographs) is chosen to be counted from each size-class 

stratum. Each photograph chosen for counting is overlaid by a squared grid, and a systematic 

sample of squares containing geese are counted. Estimates and their variances are generated from 

these sample counts, and if the variance exceeds the chosen value of CV = ±7%, additional 

photographs are selected and counted. During 1991-1995, three surveys were conducted each spring 

(late April, early May, mid-May); in both 1996-1997 two surveys were conducted, all in May 

(Appendix A). For the purposes of this study, we have used for each year the highest of the three 

(1991-95, or two in 1996-97) survey estimates, assuming that it was the most complete (i.e. likely to 

have missed the least number of flocks, if any). 

The estimated population sizes for spring 1965-1997 are given in Appendix B and plotted in 

Fig. 1-2. The data show a strong increasing trend over the three decades, with rapid growth rates 

evident for the periods 1968-1974 and 1983-1997. There was, however, a period of relative stability 

with little increase between 1974 and 1982. The overall annual growth rate (1965-1997) averaged 

8.9%, and has remained high during the most recent growth phase (9.7% for 1983-1997). This 

rapidly increasing trend, since about 1965, is also evident from 5-year averages of the mid-winter 

survey indices (Appendix B, Table 6) although those surveys record only about one half (52% over 

the decade 1988-1997) of the population estimated from the St. Lawrence surveys. 

800 

700 

600 

500 

400 

300 

200 

100 

0 

1965 1970 1975 1980 1985 1990 1995 

Y ear 

Population size (x1000) 

Figure 1-2. Greater snow goose populations in spring, 1967-1997, from photographic surveys in the 

St. Lawrence estuary. 
8
 

Tracking population change through years prior to 1965 is difficult because the only 

systematically recorded data are U.S. mid-winter indices going back only to 1950. Nevertheless, 

examination of historical records from early explorers suggest that population levels were probably 

much lower than present from the 1500s through to the end of the 1800s (Bent 1962, Anon 1981). 

The few available estimates from the first half of the 1900s (Lemieux 1959, Anon 1981) suggest a 

gradual increase from about 2,000 to 20,000 by 1941. In 1950 and 1951, the first two years of midwinter aerial surveys in the U.S., slightly more than 40,000 geese were recorded; from 1952 to 1964 

these U.S. aerial surveys recorded numbers fluctuating between 34,800 and 67,100 (Anon 1981) and 

showing no apparent trend. No information has been found to suggest that excessive harvest by 

aboriginal peoples or early European settlers could have been the cause of low populations in the 

16th to 19th centuries. Perhaps a more severe climate in the Arctic during this period (the so-called 

Little Ice Age) may have kept populations low because of frequent breeding failures. 

Breeding Numbers on Bylot Island 

Because of the huge expanse of the breeding range (Figs. 1-1 and 1-9) and the high costs of 

travel in the Arctic, it is not feasible to conduct regular surveys of the entire breeding population. 

Reconnaissance surveys conducted in the late 1960s through the1980s (Heyland and Boyd 1970, 

Reed et al. 1980, A. Reed unpubl. data) showed, however, that a high proportion of the total 

population bred in an area encompassing northern Baffin Island and adjacent Bylot Island. Because 

Bylot Island has the largest and densest nesting concentration (about 15% of the total breeding 

population; Reed et al. 1992) and is centrally located in the range, events occurring there are likely 

typical of those happening elsewhere in the range. Quantitative aerial photographic surveys have 

been conducted on Bylot Island once every five years since 1983 (Reed and Chagnon 1987, Reed et 

al. 1992, A. Reed unpubl. data). The survey covers the 1600 km2 south plain of the island during the 

brood-rearing period. A stratified random sample of 2x2km quadrat plots, stratified in relation to 

habitat features reflecting potentially high, medium or low brood densities, are selected. Each of the 

selected quadrats is searched intensively from a helicopter and all geese recorded; in small groups 

the geese are counted individually whereas in larger groups an oblique 35mm photograph is taken to 

be counted later in the lab. Further details on the method are given in Reed and Chagnon 1987 and 

Reed et al. 1992. 

Table 1-1 Estimated densities of greater snow goose broods on Bylot Island, 1983-1993, in relation 

to habitat quality. 

Habitat quality* Mean number of broods/km2 

1983 SE 1988 SE 1993 SE 

Good 16.4 1.6 14.9 1.7 29.9 3.3 

Moderate 5.6 0.9 7.8 2.1 16.0 3.3 

Poor 0.8 0.3 6.1 2.8 12.1 2.2 

Total 5.2 0.5 8.2 1.6 17.0 1.6 

* Predicted capability of habitat to support broods: Good = areas with abundant ponds and abundant 

graminoid vegetation (High-density stratum); Poor = areas with very few wet areas and little 

graminoid vegetation (Low-density stratum). 
9 

The estimated numbers of greater snow geese and brood densities on Bylot Island in 1983, 

1988 and 1993 are presented in Table 1-1 and Fig. 1-3. The total number of geese (breeding adults, 

moulters, and goslings) increased threefold from 52,000 in 1983 to almost 155,900 in 1993, as did 

the number of breeding adults which passed from 16,600 to 55,000. The number of non-breeding 

(moulting) adults fluctuated from 8,900 in 1983 to 5,400 in 1988 and to 14,473 in 1993 (Fig. 1-3). 

Overall, brood densities also increased threefold from 1983 to 1993, with densities increasing in all 

strata, especially in that stratum judged to represent poorest quality habitat within the study area 

(Table 1-1). 

175 

150 

Population size (x 1000) 

G o s l i ngs 

N on- br eeder s 

B r eeder s 

125 

100 

75 

50 

25 

0 

1983 1988 1 993 

Y e a r 

Figure 1-3. Numbers of greater snow geese on Bylot Island, in 1983, 1988, and 1993. 

PRODUCTIVITY 

Productivity has been documented on a regular basis by field surveys aimed at determining 

the proportion of young-of-the-year (juveniles) in the fall flight (Lynch and Singleton 1964). The 

longest record, covering 1956 to 1997, comes from surveys (mainly in Nov.) on the wintering 

grounds (Gauvin and Reed 1987, Voelzer 1986, Walter 1987-1995, Bidwell 1996; see Appendix C). 

There is also an uninterrupted series from the St. Lawrence (in Oct.) spanning 1973-1997 (Gauvin 

and Reed 1987, Reed unpubl. data; Appendix C). In addition to these ground surveys, aerial 

photography was used on the St. Lawrence River during 1969-1984 (Appendix C). 

An inherent bias in many productivity surveys stems from the fact that they are conducted 

during or after hunting has occurred; because hunting removes juvenile birds from the population at 

a greater rate than for adults, such counts can underestimate true productivity. We have sought to 

minimize this bias by using the St. Lawrence ground data (1973 to present) which were collected 

much earlier in the hunting season (mostly prior to 15 October) than were the U.S. data (mostly in 

November); however, in the absence of consistent Canadian data for years prior to 1973, we have 

used U.S. data for the earlier years 1965 to 1972 (Fig. 1-4). The data showed considerable annual 

fluctuation, varying from 0.4 to 47.8%, averaging 24.2% but, most importantly, showing no longterm trend (1965-1997: r

2 = 0.04, P = 0.26; 1973-1997: r2

 = 0.01, P = 0.78). 
10
 

U S d a ta Q u ébe c da ta 

50 

40 

30 

20 

10 

0 

1 965 1 970 1 975 1 980 1 985 1 990 1 99 5 

Y e ar 

Figure 1-4. Greater snow goose productivity data, 1965-1997. 

Concurrently with the ground surveys to determine the percentage of young in the fall flight, 

observers also recorded average brood size for « normal » families (i.e. broods accompanied by two 

parents). These data are presented in Appendix D, using U.S. data for 1971and earlier, and St. 

Lawrence data from 1973 onward. They show annual fluctuations between extreme values of 1.65 

to 2.94 young per brood with a slight increasing trend for the period 1965-1997 (r

2

 = 0.12, P = 

0.055) but not for the period 1973-1997 (r

2

 = 0.01, P = 0.84). Annual mean brood size was highly 

correlated with the proportion of young in the fall flight (1973-1997: r = 0.89, P < 0.001). 

HARVEST 

Recreational Harvest 

The recreational harvest has been estimated in Canada since 1967, and in the U.S. since 

1975 (the year in which hunting was re-opened on this subspecies in the U.S.), from the regular 

national harvest surveys in both countries (Appendix E). The Canadian data used in this report 

include all snow and blue geese for Zone 1 in Québec (CWS National Harvest Survey files). The 

U.S. data relate to all snow and blue geese for the Atlantic Flyway States (extracted from annual 

USFWS Administrative Reports). The data for both countries includes some lesser snow geese, but 

because the proportion of lessers in Atlantic Flyway staging and wintering areas is very small (Anon 

1981), and because no consistently reliable way has been found to distinguish between the two 

subspecies using the tail fans turned in by hunters, no correction is attempted. 

Since 1975, the Canadian harvest has fluctuated between 9,700 and 92,700, averaging 

approximately 39,000, and showing an increase over time (1967-1995: r2 = 0.46, P = 0.001; 1975-

1995: r2 = 0.18, P = 0.06; Fig. 1-5). The average yearly harvest increased from about 28,240 during 

the period 1975-1979 to 49,480 in 1991-1995. Also since 1975, the U.S. harvest has fluctuated 

between 8,900 and 40,400, averaging 21,600, but showing no trend (1975-1995; r2 = 0.01, P = 0.90; 

see also Appendix E). However, more recent data not available to us at the time of this analysis, 

indicated that the opening of late (Feb - Mar) seasons in 1996 in several northern states, especially Juvenile in the fall flock (

%) 
11 

Pennsylvania, resulted in large increases in harvest in these states. The combined harvest has 

fluctuated between 18,500 and 121,800, averaging 60,500 since 1975. The large annual variations in 

the harvest largely reflect annual variation in productivity (see below). Although the combined 

harvest increased between 1967 and 1995 (r2 = 0.50, P < 0.001), the increase since the opening of 

hunting in the U.S. was not significant (1975-1995: r2 = 0.11, P = 0.15). Overall, the total harvest 

averaged 47,360 during the period 1975-1979 compared to 70,100 during 1991-1995. 

120 

Harvest (x 1000) 

100 

80 

60 

40 

20 

0 

Q u éb ec 

US A 

To ta l 

1970 1975 1980 1985 1990 1995 

Year 

Figure 1-5. Greater snow goose harvest in Québec, U.S. Atlantic Flyway (only since re-opening of 

the season in 1975) and total (Québec + U.S.), 1967-1995. 

Age Ratio in Recreational Harvest 

Age ratios (juveniles:adult) in the kill have been estimated each year from tail fans sent in by 

recreational hunters participating in national harvest surveys in both Canada and the U.S. (Table 1-

2). Although juveniles always accounted for less than a half of the goose population at risk in the fall 

(Appendix C), they outnumbered adults in the harvest in almost all years (Table 1-2), averaging 

3.4: 1 in the Canadian harvest (1968-1995) and 1.2: 1 in the U.S. harvest (1976-1996). Annual 

variation was, however, considerable. This variation partly reflects low sampling intensity in some 

years, and, especially, the large annual variation in productivity, the age ratio in the kill being much 

higher in years of high productivity. The increased vulnerability of young geese to the gun, in 

comparison with adults, is explained in large part by their lack of experience in avoiding hunters. 

Similarly, juvenile geese show less vulnerability to the gun in the U.S. in comparison to Canada 

because of experience gained by those surviving the earlier hunting season in Canada. The age ratio 

in the Canadian harvest is nonetheless strongly correlated to that in the U.S. harvest (1977-1995: r2 = 

0.79, P <0.001). 
12 

Table 1-2 Age ratios in the harvests of snow geese, juveniles: 1 adult (no. of tail fans or geese 

examined), in southern Québec and the Atlantic Flyway states, 1967-1996. 

Year Can. NHS U.S. NHS Bag check – 

(Qué.) (Atl. Flyway) Cap Tourmente NWA 

1967 no data 

1968 1.77 (25) 

1969 2.21 (77) 

1970 4.95 (101) 

1971 2.05 (116) 

1972 0.15 (61) 

1973 12.33 (255) 

1974 0.67 (80) 

1975 5.85 (130) 

1976 1.28 (82) 

1977 10.63 (58) 

1978 3.26 (98) 

1979 2.79 (106) 

1980 4.38 (345) 

1981 1.85 (74) 

1982 3.03 (121) 

1983 6.75 (225) 

1984 2.98 (435) 

1985 2.03 (97) 

1986 0.35 (46) 

1987 5.80 (238) 

1988 3.10 (373) 

1989 1.73 (328) 

1990 1.74 (318) 

1991 4.78 (249) 

1992 0.32 (187) 

1993 6.14 (616) 

1994 0.54 (196) 

1995 2.56 (267) 

1996 

season closed 

season closed 

season closed 

season closed 

season closed 

season closed 

season closed 

season closed 

0.33 (77) 

1.59 (156) 

0.66 (165) 

0.74 (209) 

1.83 (185) 

1.05 (70) 

0.78 (148) 

2.76 (348) 

1.17 (384) 

0.88 (131) 

0.17 (57) 

2.53 (338) 

2.00 (309) 

1.30 (221) 

0.70 (254) 

1.86 (287) 

0.14 (172) 

2.26 (465) 

0.73 (201) 

0.56 (233) 

0.55 (405) 

12.28 (2152) 

1.79 (681) 

10.62 (1255) 

10.96 (2645) 

6.93 (2555) 

14.22 (1613) 

1.63 (701) 

18.96 (2795) 

16.59 (2849) 

9.55 (2838) 

10.41 (3182) 

26.94 (1816) 

1.37 (521) 

25.71 (3712) 

3.10 (1077) 

6.70 (1502) 

9.66 (2581) 
13
 

Subsistence Harvest 

Greater snow geese are also harvested by native subsistence hunters in northern Québec, the 

eastern Canadian Arctic and Greenland, but the kill is not well documented. Both geese and eggs 

are harvested. The most recent harvest data available for northern Québec and the eastern Arctic 

were collected in the late 1970s and early 1980s and did not distinguish between greater and lesser 

snow geese. Presently a harvest survey is underway in Nunavut (eastern Arctic) but results are not 

yet available. It seems probable that the bulk of the native harvest in Canada comes from hunters 

from those villages closest to the heart of the breeding range, namely Pond Inlet, Arctic Bay, Clyde 

River, Resolute Bay, Grise Fiord, and possibly Spence Bay. Undoubtedly others are killed during 

migration through more southerly areas of the eastern Arctic and through northern Québec (e.g. 

Cape Dorset, Hall Beach, Igloolik, Saluit, Povungnituk, Inukjuak) but we have no way of separating 

out greaters from the assumedly more-abundant lessers in their reported kill of snow geese. 

Harvest statistics for the five main locations within the Canadian breeding range of greater 

snow geese (and where very few lessers would be present) are presented in Table 1-3. The average 

estimated harvest for these five sites for the years 1981, 1982, and 1984 was 1,185 geese. Egg 

harvest, recorded only in 1984, totaled 1,414 for the same five locations. Although we are unable to 

account for any changes in harvest since the early 1980s, or for additional harvests near other native 

settlements, it appears likely that the subsistence harvest of greater snow geese is less than 5,000 

geese which represents a relatively small proportion of the total harvest. 

Table 1-3 Estimated subsistence harvest of snow geese in five locations in the northeastern Canadian 

Arctic, 1979-1984. 

Location Geese 

19791 

Geese 

19812 

Geese 

19823 

Geese 

19844 

Eggs 

19844 

Pond Inlet 642 280±48 1470±45 658 427 

Arctic Bay/Nanisivik no data 185±33 371±45 245 340 

Clyde River 18 19±2 91±5 85 647 

Resolute Bay no data 50±29 0 6 0 

Grise Fiord 20 28±10 53±6 13 0 

Total 1981-1984 562 1985 1007 1414 

1 Finley and Miller 1980 

2 Donaldson 1983 

3 Donaldson 1984 

4

 Pattimore 1985 

Harvest Rate 

A knowledge of hunting mortality is essential in order to evaluate the effect of various 

harvest management scenarios on population growth (see Chapter 4). When the estimated total 

number of birds killed by recreational hunting is expressed as a ratio of total population size, the 

resulting statistic (harvest rate) can provide an estimate of hunting mortality. This statistic is often 

calculated from band recovery data, but incomplete banding data for the early decades of the study 

period and the absence of information on band reporting rates for greater snow geese prompted us to 

use a different approach. The total number of young and adults killed each year was estimated by 

applying age ratios estimated by the national harvest surveys in Canada and the U.S. (Table 1-2) to 
14

the estimated total harvest in each country (Appendix E). 

estimated by adjusting the population size obtained by the spring census (Appendix B) for natural 

mortality occurring between the spring and fall. To do this we used a spring-to-fall survival of 

94.6%, a value proposed by Gauvin and Reed (1987) in an earlier study. improved estimate of 

spring-to-fall survival using neckband resighting data will soon be available (Stéphane Menu, 

unpubl. data), which will allow a more refined analysis. ate the size of the juvenile 

population in fall, we multiplied the estimated fall population size for adults by the proportion of 

juveniles estimated in the fall flight along the Saint Lawrence estuary (Appendix C), divided by the 

proportion of adults in the fall flight (100 -% juvenile). 

The average harvest rate during the period 1968-1995 was 15.6% (young and adult 

combined). However, as indicated earlier by Reed (1990), the data show three distinct periods with 

markedly different harvest rates (Fig. 1-6): 1) from 1968 to 1974, harvest rate averaged 8.0%; 2) 

after re-opening of hunting in the U.S., it jumped to 25.0% during 1975-1984, 3) finally, harvest rate 

dropped abruptly after 1984 and has stabilized around 11.8% since then. harvest rate 

after 1984 affected both young (67.3% 1975-1984 vs 32.9% after 1984) and adults (11.1% 1975-

1984 vs 6.0% after 1984). some obvious inaccuracies in the 

age specific data during the 1970s, as shown by harvest rate estimates of 156% and 101% for young 

in 1972 and 1978. 

Y ear

1 9 7 0 1 9 7 5 1 9 8 0 1 9 8 5 1 9 9 0 1 9 9 5

Harvest rate (%)

0

2 0

4 0

6 0

8 0

1 0 0

1 5 0

1 6 0

Y oung 

A dult

T o ta l

Figure 1-6. ber killed/estimated fall population size) for young, adult 

and total (combined young and adult), 1968-1995. 

hunting in the U.S. (1975). 

The size of the adult population in fall was 

An 

To estim

The drop in 

It should be pointed out that there are 

Greater snow harvest rate (num

Vertical dashed line indicates re-opening of 
15 

Table 1-4 Mid-winter indices of greater snow goose numbers in the Atlantic Flyway: 5-year 

averages by state, 1955-1996 1 

Period 

State 1955-60 1961-65 1966-70 1971-75 1976-80 1981-85 1986-90 1991-96 

New York 0 0 0 15 1 1 18 285 

Pennsylvania 0 0 20 9 9 10 4 2076 

New Jersey 4230 1660 2340 21661 13136 8058 37900 77400 

Delaware 0 220 240 3798 17893 45640 72839 63809 

Maryland 1707 520 940 2578 17893 45640 56339 68192 

Virginia 6759 21960 22040 12535 32022 21055 18090 11472 

North Carolina 30652 33160 23500 31620 37730 25480 21660 18433 

South Carolina 6 60 140 400 996 485 659 427 

Flyway Total 2 43377 57580 49220 72655 119775 146419 207527 242103 

1 Data from Serie (1996). Note that the first and last columns (1955-60 and 1991-96) indicate 6-year 
 

averages.
 2 Includes total for above 8 states as well VT, NH, RI, WV, GA and FL; none of these additional 6 
 

states had any 5-year averages exceeding 70 geese.
 

DISTRIBUTION 

Wintering Range 

The wintering range extends along the Atlantic coast from New Jersey to South Carolina, 

with main concentrations in New Jersey, Delaware, Maryland, Virginia and North Carolina (Anon 

1981). The main concentration areas and a current estimate of the approximate numbers of geese at 

each site are shown in Fig 1-7. Note that there are a few small concentration areas harboring a few 

thousand lesser snow geese within this range, notably at Black Water NWR in Maryland, at 

Presquile NWR in Virginia, and at Mattamuskeet NWR in North Carolina (Fig 1-7). Mid-winter 

survey indices over 40 years since 1955 (Table 1-4) show general increases in 5-year averages in 

Delaware, Maryland, and New Jersey, a decline in North Carolina, and no clear trend in Virginia and 

South Carolina; New York, Pennsylvania and New Jersey all showed marked increases in 1991-

1996. Indeed, the build up of winter flocks in Pennsylvania since 1995 is greater than indicated by 

the mid-winter surveys because of late-winter arrivals in the interior part of the state. Thus more 

geese, both numerically and proportionately, are now wintering in the central and northern portion of 

the range. This trend is only partially reflected in the hunting kill in the main five harvest states 

(Table 1-5) with only Delaware showing a general increase since 1976, New Jersey and North 

Carolina showing decreases, and Maryland and Virginia showing fluctuations. 

17 

Table1-5: Estimated snow goose harvest in the Atlantic Flyway states: 5-year averages by state, 

1976-1995 1 

Period 

State 1976-80 1981-85 1986-90 1991-95 

Vermont 

New York 

Pennsylvania 

New Jersey 

Delaware 

Maryland 

Virginia 

North Carolina 

South Carolina 

Flyway Total 2 

80 120 1020 1340 

380 80 520 360 

160 20 80 280 

9600 9280 6840 3820 

1020 6700 7880 7880 

2260 4680 2220 4380 

940 640 320 820 

7220 3920 780 1520 

140 0 0 0 

21940 25600 19920 20420 

1

 Data from Serie (1996). Note that hunting was re-instated in the Atlantic Flyway in 1975; in that 

year (not included in table) the estimated total flyway harvest was 9,200 Snow Geese. 

In addition to the above 9 states, total includes harvests from ME, NH, MA, CT, WV, and GA; 

none of these additional 6 states had 5-year average harvests exceeding 100 geese. 

Spring Staging Areas 

The traditional staging area along the St. Lawrence estuary extended along 80 km, from 

Québec City to Saint-Roch, and coincided with the major bulrush tidal marshes (Lemieux 1959); 

until the early 1960s, this was the only area of the St. Lawrence used by the geese in both spring and 

fall, and where they fed almost exclusively on bulrush (Scirpus pungens, formerly S. americanus) 

rhizomes. By 1975-1980 the geese had extended an additional 100 km downstream to the cordgrass 

marshes near Kamouraska and Isle-Verte, and 100 km upstream to include Lac Saint-Pierre, an 

enlargement of the St. Lawrence River (Anon 1981, Reed 1992); field feeding began to build up 

throughout that spring range, especially near the newly occupied cordgrass marshes and Lac SaintPierre. The spring staging area now extends along >400 km of the St. Lawrence River and estuary, 

as well as along at least three of the main tributaries, especially the Richelieu River through to its 

source in Lake Champlain (Fig.1-8), and field feeding has become commonplace. 

Formerly greater snow geese flew non-stop from Delaware Bay to the traditional bulrush 

marshes immediately downstream from Québec City (Lemieux 1959), but now many stop off first in 

Lake Champlain, along the Richelieu River, and in Lac Saint-Pierre before moving downstream to 

the traditional tidal marshes. In 1997, several large flocks also flew north along the Hudson River 

and through the Finger Lakes region of New York (B. Swift and P. Hess, pers. comm.) before 

arriving in the St. Lawrence. The Baie-du-Febvre area along the south shore of Lac St. Pierre is 

characterized by the presence of many corn fields and has now become the most important spring 

staging area with concentrations up to 500,000 birds and 12 millions goose-days (A. Béchet et al. 

UQAM, unpubl. data); this represents almost half of the cumulative goose-days during spring 

staging. Based on a telemetry study conducted in 1996-97, all marked geese in the population staged 

at Baie-du-Febvre for periods varying between 2 and 40 days; only one bird (in 1997) did not 

subsequently move to the estuary to complete spring staging. This exception is consistent with the 

observation that in 1997, for the first time, a flock of 10,000 birds stayed at Baie-du-Febvre for the 

entire staging period before departing for the Arctic breeding grounds. Nevertheless, large numbers 

of geese continue to congregate in the traditional estuarine area during much of the spring staging 

period. 

2 

19
 

The existence of a staging area for snow geese in Ungava (Fig. 1-1) was first noted by 

Manning (1949) whose observations, based on the proportion of blue phase geese, were referred to 

the lesser subspecies. The presence of greater snow geese in Ungava was first brought to light in the 

early 1970s following reconnaissance surveys and questionnaires with local residents and bush pilots 

(J.D. Heyland, P. Dupuis unpubl. data), and from incidental sightings during caribou (Rangifer 

tarandus caribou) surveys (Le Hénaff et al. 1995). It is now known that a vast area of the tundra 

portion of the Ungava peninsula is used by both lesser and greater snow geese during both spring 

and fall migration. No large, dense concentration areas are known; rather, the geese appear to move 

through the area on a broad front. Greater snow geese appear to use mainly the central and eastern 

portion of the Ungava Peninsula, especially near its southern boundary just north of the treeline (see 

also below under fall migration). Staging during spring migration by greaters occurs early (mainly 

the last week of May) and is undoubtedly of short duration (Gauthier and Tardif 1991); as a result, 

the geese are probably unable to supplement nutrient reserves to any significant amount at this time 

(Gauthier et al. 1992). 

Breeding Range 

Reconnaissance surveys conducted from the late 1960s to the late 1970s showed the 

° breeding range to extend from about 69 N in Foxe Basin northward through northern Baffin Island, 

Bylot, Somerset, Prince of Wales, Bathurst, Devon, Ellesmere, and Axel Heiberg islands, and in the 

Thule district of northeastern Greenland, with the bulk of the population occurring on northern 

Baffin Island and Bylot Island (Heyland and Boyd 1970, Anon 1981). What little new information 

has emerged since indicates no major changes or shifts; recent data suggest only the addition of a 

few areas of sparse breeding within the known range (e.g. Boyd 1989, Forbes et al. 1992), and a few 

other areas extending the range westward to Melville Island (Maltby 1978) and eastward on northern 

and western Greenland beyond the traditional breeding area near Thule (Boertmann 1994). An 

updated map of the breeding range is provided in Fig 1-9. 

Fall Staging 

Two main staging areas are used during fall migration. The first is located on the Ungava 

Peninsula and the second along the St. Lawrence River (now including portions of the Richelieu 

River and Lake Champlain). 

Satellite tracking of greater snow geese marked on Bylot Island has recently provided 

detailed information on the fall migration route (Giroux et al. 1998). Fall migration started from 

Bylot Island in late August with an initial long migration bout (> 1000 km) which took them rapidly 

southward across Baffin Island and then along the north-east shore of Foxe Basin and across Hudson 

Strait to the central portion of the Ungava Peninsula. They staged several days in Ungava, moving 5 

to 7 times over distances of 20 to 300 km between many scattered sites with no apparent dense 

concentrations. An earlier investigation revealed that during this stopover in Ungava, the geese 

occupied both rocky heathland, where they fed on berries (Empetrum, Arctostaphylos, Vaccinium 

spp.), and small shallow wetlands, where they fed on the basal portions of sedges (A. Reed and N. 

Dignard unpubl. data). By the time of departure the radio-marked geese were close to the treeline. 

From there they undertook a second long migration flight (>1000 km) following a corridor between

° ° 72 and 74 W of longitude across the boreal forest to the St. Lawrence River. Overall, between Bylot 

Island and the St. Lawrence River, the migration pattern consisted of 8-10 (8.8±0.4) bouts lasting 1-

5 (2.1±0.1) days with intervening staging periods lasting 1-7 (2.8±0.1) 
20 

days. Fall staging in Ungava is probably of particular importance for juvenile birds to rest and refuel 

just before they depart on the long flight to the St. Lawrence. 

An important change has occurred in the way the St. Lawrence staging area is used during 

fall migration. Formerly (into the 1970s), the geese staged throughout the month of October almost 

exclusively in the Scirpus marshes in the restricted portion of the St. Lawrence between Ile 

d’Orleans and St. Roch before leaving on a direct non-stop flight to Delaware Bay (Lemieux 1959, 

Blokpoel et al. 1975). In more recent years, many geese have been dispersing from this restricted 

traditional area earlier in October and moving southwesterly to Lake Saint-Pierre or northern Lake 

Champlain where they have fed in cornfields, and where some have remained well into November or 

December. This southwestern shift in the fall distribution of geese in Québec is also demonstrated 

by tail fan receipts from the National Harvest Survey (Fig. 1-10), and by decreasing numbers of 

goose-days at Cap Tourmente since 1989 (A. Reed unpubl. data). The lower estuary (Kamouraska 

and Isle-Verte) has been used only sporadically in fall in recent decades. Increasing use of the Lake 

St. Jean area has been noted since fall 1995 but not quantified. More importantly, however, some 

geese are now overflying the St. Lawrence altogether. In the mid-1980s, Maisonneuve and Bédard 

(1992) used repeated observations of neck-collared geese to estimate that 11-20% of the geese were 

flying directly to the U.S. without stopping in southern Québec and that the average staging period 

of individuals that did stop off in the estuary was 15-19 days. Based on satellite and conventional 

telemetry conducted in 1995-96, Giroux et al. (unpubl. data) confirmed that 20-22% of the geese did 

not stop off in southern Québec and those that did remained in the estuary for an average of 11 days; 

furthermore, about 25% of the geese that staged in the estuary subsequently moved to southwestern 

Québec (the corn-growing area) to stage for an additional 14 days, on average. 

Interactions with Atlantic Population Canada Geese 

There is a growing concern that greater snow geese may be displacing Canada geese in 

southern Québec, Ontario and some coastal states. During the last 30 years, the increasing use of 

some regions of southern Québec (St-Vallier, Isle-Verte, Lake St-Pierre) by greater snow geese 

during spring migration has coincided with a concomitant decline of Canada geese in these regions 

(A. Reed, pers. obs.). Increased use of the Ottawa River region in recent years by Canada geese in 

spring has also been attributed to a displacement of birds from the Lake St-Pierre area since the 

arrival of greater snow geese in the mid 1980s but this has not been demonstrated through scientific 

studies. 

At a local scale, detailed studies have been conducted in the Lake St-Pierre area where the 

two species stage in sympatry during spring migration. Competitive exclusion of Canada geese by 

greater snow geese at roosting sites (temporary floodplains) likely occurred in 1990 when limited 

run-off reduced the total flooded area. This did not happen the following year because of extensive 

flooding and no longer occurs because of creation of temporary impoundments by Ducks Unlimited 

(J.-F. Giroux, pers. obs.). On the feeding grounds, both species consume the same plant species 

when foraging on a given type of fields (Giroux and Bergeron 1996). However, little competition 

likely occurs because greater snow geese are more mobile and move to corn fields that are up to 40-

60 km from the roost whereas Canada geese feed on hayfields within about 10 km from the roost 

(Cazelais 1992, DeKoster 1992). Canada geese have changed their habitat use from corn fields to 

hayfields in this area during the last 20-25 years (Reed et al. 1977, Cazelais 1992), probably more in 

response to changes in agricultural practices (more fall plowing of corn fields) than the arrival of 

greater snow geese. 

Recent studies using satellite telemetry suggest that Canada geese marked in southern 

Ungava Bay and George River area in Labrador may overlap the current migration route of greater 


23 

snow geese in southern Québec in fall (Malecki et al. 1998). However, these birds do not represent a 

large proportion of the total population. On the other hand, birds marked on the Hudson Bay side of 

Ungava Peninsula where the greatest concentrations of AP Canada geese nest have a more westerly 

fall migration route (west of Lake Champlain) than greater snow geese. No concentrations of Canada 

geese have been regularly reported on staging areas used by greater snow geese in fall. The potential 

for competitive exclusion of AP Canada geese by greater snow geese in fall is thus currently limited. 

In conclusion, despite anecdotal evidence, there is little scientific evidence of a direct 

interaction between the two species. However, further increase of the greater snow goose population 

and/or further expansion of its distribution especially in spring could influence the staging 

distribution of AP Canada geese. It presently appears unlikely that habitat management for snow 

geese in southern Québec could short-stop AP Canada geese, but this subject deserves further study. 

SUMMARY 

1. 	 The greater snow goose population has increased from <50,000 geese in spring 1965-1968 to 

more than 650,000 in 1996-1997. After re-opening of the hunt in the U.S. in 1975, there was a 

short period of apparent stability (1975-1982). However, the average growth rate since 1982 has 

exceeded 9%. 

2. 	 Productivity, as measured by age ratios (% juveniles) in the fall flight, has averaged 24.2% over 

the period 1965-1997, showing no long-term trend. Productivity has, however, fluctuated 

considerably, reflecting the climatic harshness of their high Arctic breeding range. 

3. 	 Total recreational harvest increased during the period 1967-1995. A large part of this increase 

resulted from re-opening of hunting in the U.S. in 1975. From 1975 to 1995, the annual harvest 

increased in Canada (Québec), but not in the U.S. 

4. 	 The harvest by native subsistence hunters is poorly documented but is believed to be relatively 

unimportant in comparison to recreational harvest. 

5. 	 Some recent expansion of wintering range has been recorded, but the main result of population 

growth has been a build up of numbers in Delaware and Maryland, and since 1991 in New 

Jersey, New York, and Pennsylvania. Numbers have declined in the southern portion of the 

winter range (e.g. North Carolina). Field feeding has become widespread on the wintering 

grounds. 

6. 	 As the population has increased over the past three decades, the main staging area along the St. 

Lawrence has expanded from a 40-km portion of the river to more than 400-km, and now 

extends along the Richelieu River to northern Lake Champlain. This has been accompanied by 

increased field feeding on adjacent farmland. 

7. 	 Recent study has revealed the presence of a staging area in Ungava which may be especially 

important in fall for geese migrating between breeding areas and the St. Lawrence staging area. 

8. 	 During the last three decades, only a few new breeding areas have been discovered and the 

overall breeding range has expanded only slightly. The most important result of the increase in 

population appears to be increasing densities at main breeding colonies. This has been 

substantiated at the largest known colony, Bylot Island, where the numbers of breeding geese 

increased threefold between 1983 and 1993. 
24 

9. A factor contributing to continued population growth since the mid-1980s is the fact that the 

hunting kill has increased more slowly than the goose population, resulting in reduced harvest 

rates. Harvest rate is now about one half of the rate that prevailed during the period of nearstable population in 1975-1983. Non-hunting mortality during the non-breeding season may 

have remained low or even decreased as the geese have gradually discovered a supplementary 

food supply on agricultural land. 

10. Productivity has not declined, despite increasing densities on breeding areas where no 

agricultural food supplements are available. Nevertheless, some density dependent effects are 

showing up (see Chapter 2), but these are not presently preventing population growth nor 

reducing age ratios in the fall flight. 

11. Changing patterns of fall migration and distribution (e.g. more stop-offs, shorter flight distances 

between the traditional staging area in the St. Lawrence and the wintering grounds) could partly 

reflect increased pressure on food resources in natural habitats (see Chapter 2) resulting in 

possible decrease in body condition of the geese while staging in the St. Lawrence (Reed and 

Plante 1997). However, geese now have access to an abundant supply of high quality food in 

agricultural fields, especially in wintering areas and during spring staging, and there is evidence 

that this has lead to improved body condition in spring (Gauthier et al. 1992). 

12. The gradual shift in fall staging from the traditional Scirpus marshes of the upper St. Lawrence 

estuary to the cornfields of southwestern Québec may result in a decrease in the harvest rate 

because: 1) the tradition of hunting this species is less well developed in this area, and 2) the 

long, unpredictable daily feeding flights from roosting sites to cornfields make the geese more 

difficult to hunt than in the marshes of the St. Lawrence estuary. 

LITERATURE CITED 

Anonymous 1981. A Greater Snow Goose Management Plan. Canadian Wildlife Service, U. S. Fish 

and Wildlife Service and Atlantic Flyway Council. Ste-Foy, Qué. 68pp. 

Bent, A.C. 1962. Life histories of North American waterfowl. Part II. Dover Publications, New 

York, New York. 314pp + plates. 

Bidwell, J. (compiler). 1996. Productivity surveys of geese, swans and brant wintering in North 

America - 1996. U.S. Fish and Wildlife Service, Laurel, Md. 79pp. 

Blokpoel, H., J.D. Heyland, J. Burton, and N. Samson. 1975. Observations of the fall migration of 

Greater Snow Geese across southern Québec. Can. Field-Nat. 89:268-277. 

Boertman, D. 1994. An annotated checklist to the birds of Greenland. Meddelelser om Gronland, 

Bioscience 38:63pp. 

Bourget, A. 1974. Migrations de la sauvagine dans la région de Québec. Pages 66-72 in H. Boyd 

(ed.) Waterfowl studies in eastern Canada, 1969-73. Canadian Wildlife Service, Report 

Series Number 29. 

Boyd, H. 1989. Geese on Rowley Island, NWT, in 1987 and 1988. Canadian Wildlife Service, 

Progress Note No. 181. 6pp. 
25 

Cazelais, S. 1992. Écologie de la bernache du Canada lors de sa halte migratoire printanière dans la 

région du lac Saint-Pierre, Québec. Mémoire de maîtrise, Université du Québec à Montréal, 

Montréal. 86pp. 

DeKoster, R. 1992. Sélection de l'habitat et bilan d'activité de la Grande Oie des neiges dans la 

région de lac Saint-Pierre au printemps. Mémoire de maîtrise, Université du Québec à 

Montréal, Montréal. 76pp. 

Donaldson, J. 1983. 1981 Wildlife harvest statistics for the Baffin Region, Northwest Territories. 

Baffin Region Inuit Association. Techn. Report No.1. 

Donaldson, J. 1984. 1982 Wildlife harvest statistics for the Baffin Region, Northwest Territories. 

Baffin Region Inuit Association. Techn. Report No.2. 

Finley, K.J. and G.W. Miller. 1980. Wildlife harvest statistics from Clyde River, Grise Fiord and 

Pond Inlet, 1979. Report by LGL Limited for Petro-Canada Explorations, Calgary. 

Forbes, G., K. Robertson, C. Ogilvie, and L. Sedon. 1992. Breeding densities, biogeography, and 

nest predation of birds on Igloolok Island, N.W.T. Arctic 45: 295-303. 

Heyland, J.D. 1972. Vertical aerial photography as an aid in wildlife population studies. Pages 121-

136 in First Canadian Symposium on Remote Sensing. 

Heyland, J.D. and H. Boyd. 1970. An aerial reconnaissance of the eastern Canadian Arctic, 20-29 

July 1969, in search of Greater Snow Geese. Unpublished report, Canadian Wildlife Service, 

Ottawa. 29pp. 

Gauthier, G., J.-F. Giroux, and J. Bédard. 1992. Dynamics of fat and protein reserves during winter 

and spring migration in greater snow geese. Can. J. Zool. 70:2077-2087. 

Gauthier, G. and J. Tardif. 1991. Female feeding and male vigilance during nesting in greater snow 

geese. Condor 93:701-711. 

Gauvin, J. and A. Reed. 1987. A simulation model for the Greater Snow Goose population. 

Canadian Wildlife Service, Occas. Paper Number 64. 26pp. 

Giroux, J.-F., and R. Bergeron. 1996. Spring diet of sympatric greater snow geese and Canada geese 

in southern Québec. Can. J. Zool. 74: 950-953. 

Giroux, J.-F., F. Blouin, J. Ferron, G. Gauthier, and J. Doucet. 1998. The fall migration of greater 

snow geese tracked by satellite. Ninth North American Arctic Goose Conference and 

Workshop. 7-11 January 1998, Victoria, B.C. 

Le Hénaff, D., R. Ouellet, M. Lepage, and C. Maisonneuve. 1995. Utilisation du territoire du 

Nouveau-Québec par l’Oie des neiges, Chen caerulescens, en période de migration. Can. 

Field-Nat. 109:408-412. 

Lemieux., L. 1959. Histoire naturelle et aménagement de la grande oie blanche Chen hyperboria 

atlantica. Naturaliste canadien 86:133-192. 

Lynch, J.L., and J.R. Singleton. 1964. Winter appraisals of annual production in geese and other 

waterbirds. Wildfowl Trust Annual Report 15:114-126. 
26

Maisonneuve, C. and J. Bédard. 1992. Chronology of autumn migration by greater snow geese. J. 

Wildl. Manage. 56:55-62. 

Malecki, R.A., S.E. Sheaffer, and B. D. J. Batt. 1998. Temporal and geographic distribution of 

Atlantic Population Canada geese from satellite telemetry. Paper presented at the Ninth North 

American Arctic Goose Conference and Workshop. 7-11 January 1998, Victoria, BC. 

Maltby, L.S. 1978. Birds of the coastal zone of Melville Island, 1973-75. Can. Field-Nat. 92:24-29. 

Manning, T.H. 1949. The birds of northwestern Ungava. Pages 153-224 in Appendix to : E.W. 

Manning. A summer on Hudson Bay. Hodder and Stoughton Ltd., London. 

Pattimore, J.D. 1985. Inuit wildlife harvest for 1984 in the Baffin Region. Unpublished report, 

Baffin Region Inuit Association. 124pp. 

Reed, A. 1990. Population dynamics in a successful species: challenges in managing the increasing 

population of greater snow geese. Trans. 19th IUGB Congress, Trondheim 1989. 

Reed, A. 1992. Management of greater snow geese in relation to crop damage: the need for a 

diversified and integrated approach. Pages 93-100 in M. van Roomen and J. Madsen, eds. 

Waterfowl and agriculture : a review and future perspective of the crop damage conflict in 

Europe. Int. Waterfowl and Wetlands Res. Bur. Spec. Publ. 21. Slimbridge, U.K. 

Reed, A., H. Boyd, P. Chagnon and J. Hawkings. 1992. The numbers and distribution of greater 

snow geese on Bylot Island and near Jungersen Bay, Baffin Island, in 1988 and 1983. Arctic 

45:115-119. 

Reed, A. and P. Chagnon. 1987. Greater snow geese on Bylot Island, Northwest Territories, 1983. J. 

Wildl. Manage. 51:128-131. 

Reed, A. , G. Chapdelaine, and P. Dupuis. 1977. Use of farmland in spring by migrating Canada 

geese in the St. Lawrence valley, Québec. J. Appl. Ecol. 14:667-680. 

Reed, A., P. Dupuis, K. Fischer, and J. Moser. 1980. An aerial survey of breeding geese and other 

wildlife in Foxe Basin and northern Baffin Island, Northwest Territories, July 1979. 

Canadian Wildlife Service, Progress Note No. 114. 21pp. 

Reed, A. and N. Plante. 1997. Decline in body mass, size and condition of greater snow geese, 1975-

94. J. Wildl. Manage. 61:413-419. 

Serie, J. (compiler) 1996. Atlantic Flyway: waterfowl harvest and population survey data. U.S. Fish 

and Wildlife Service, Laurel, Md. 80pp. 

Walter, J.S. (compiler). 1987 - 1995. Productivity surveys of geese, swans and brant wintering in 

North America - 1996. U.S. Fish and Wildlife Service, Onalaska, Wisc. (8 annual reports, 

1987 to 1995). 

Voelzer, J.F. (compiler). 1986. Productivity surveys of geese, swans and brant wintering in North 

America 1983 to 1986. U.S. Fish and Wildlife Service, Portland, Or. 247pp. 
27

Appendix A: Results of spring surveys of greater snow geese in the St. Lawrence valley, 1991-1997. 

The first value is the population estimate derived from the photo counts, followed by the coefficient 

of variation (in parentheses), followed by the number of geese not included in the photo count, 

followed by the grand total, rounded to the nearest hundred. 

Period 

Year late April early May mid-May 

1991 259900 (6.4) + 12090 = 272 342100 (4.6) + 10487 = 352 287500 (4.8) + 11910 = 2994 

1992 417600 (6.0) + 16235 = 433 428400 (4.6) + 5615 = 434 436100 (4.6) + 11980 = 448 

1993 349200 (4.5) + 7570 = 356 417400 (5.2) + 165 = 417 496000 (4.2) + 2365 = 4984 

1994 403900 (6.3) + 1748 = 405 418100 (4.3) + 1916 = 420 587900 (4.5) + 3450 = 5914 

1995 501300 (6.2) + 3210 = 504 563900 (4.3) + 4039 = 567 611800 (4.1) + 4820 = 616 

1996 no sur 579700 (4.3) + 5443 = 585 664500 (5.1) + 4586 = 669 

1997 no sur 586800 (4.8) + 8902 = 595 650800 (4.2) + 6745 = 657 
28 

Appendix B: Greater snow goose population indices from mid-winter surveys in the Atlantic Flyway 

states and population size in spring (from aerial photographic counts in the St. Lawrence valley). 

Mid-winter survey in the U.S.1 Spring survey in Québec 

Year Number of geese Year Number of geese 

1964/65 46 500 1965 25 400 

1965/66 43 400 1966 25 400 

1966/67 59 900 1967 40 900 

1967/68 50 500 1968 38 900 

1968/69 62 800 1969 68 800 

1969/70 29 500 1970 89 600 

1970/71 48 500 1971 123 300 

1971/72 81 100 1972 134 800 

1972/73 60 000 1973 143 000 

1973/74 98 300 1974 165 000 

1974/75 75 400 1975 153 800 

1975/76 117 500 1976 165 600 

1976/77 152 900 1977 160 000 

1977/78 87 000 1978 192 600 

1978/79 112 200 1979 170 100 

1979/80 129 400 1980 180 000 

1980/81 95 600 1981 170 800 

1981/82 107 100 1982 163 000 

1982/83 122 500 1983 185 000 

1983/84 133 500 1984 225 400 

1984/85 273 400 1985 260 000 

1985/86 137 700 1986 303 500 

1986/87 143 700 1987 255 000 

1987/88 241 400 1988 363 800 

1988/89 283 600 1989 363 200 

1989/90 231 200 1990 368 300 

1990/91 199 000 1991 352 600 

1991/92 276 000 1992 448 100 

1992/93 181 700 1993 498 400 

1993/94 219 600 1994 591 400 

1994/95 353 500 1995 616 600 

1995/96 222 900 1996 669 100 

1996/97 1997 657 500 

1 Data extracted from: Serie, J. (compiler) 1996. Atlantic Flyway: Waterfowl Harvest and Population 

Survey Data. U.S. Fish and Wildlife Service, Laurel, Md. Mimeo 80pp. 
29 

Appendix C: Productivity surveys of greater snow geese in Canada and the U.S., 1956-1997. 

Year U.S. visual Québec visual Québec aerial photo 

1956 33.8 

1957 34.4 

1958 3.1 

1959 42.7 

1960 34.1 

1961 1.2 

1962 28.4 

1963 33.9 (2728) 

1964 20.5 (8179) 

1965 2.8 (2524) 

1966 

1967 

37.0 (5516) 

12.4 (5236)1 

1968 12.5 (3613) 

1969 24.3 (5004) 

1970 46.8 (6930) 

1971 11.3 (8334) 

1972 0.4 (3214) 

1973 41.1 (4900) 

1974 2.0 (6148) 

1975 37.3 (11460) 

1976 9.8 (34892) 

1977 23.8 (7531) 

1978 14.7 (16159) 

1979 23.2 (8041) 

1980 36.3 (12140) 

1981 17.0 (17229) 

1982 23.8 (12773) 

1983 48.9 (19206) 

1984 27.4 (11133) 

1985 31.0 (14972) 

1986 2.3 (13109) 

1987 37.9 (17467) 

1988 31.2 (14467) 

1989 30.1 (17735) 

1990 17.2 (24439) 

1991 26.2 (27805) 

1992 4.5 (10501) 

1993 44.6 (23082) 

1994 13.4 (19726) 

1995 13.3 (13221) 

1996 30.5 (23728) 

1997 

30.0 

45.6 

29.7 

40.6 (800)1 46.6 

6.4 (7282) 

31.2 (17579) 32.7 

12.6 (20847) 9.5 (120755) 

23.9 (10297) 21.6 (132425) 

17.9 (9679) 20.1 (205419) 

28.2 (20849) 22.5 (179002) 

35.3 (12120) 40.1 (164453) 

16.3 (10683) 16.8 (86039) 

25.1 (9577) 10.5 (65436) 

47.4 (12353) 41.6 (100910) 

30.4 (39781) 37.6 (103000) 

25.8 (33700) 

2.3 (22998) 

40.2 (33278) 

33.1 (40246) 

31.1 (29191) 

23.6 (20313) 

38.3 (15102) 

5.4 (32252) 

47.8 (24163) 

9.2 (16444) 

16.6 (19519) 

25.1 (22595) 

36.8 (17586) 

1

 Percentage values in bold print were used in Fig.1- 4 (see text) 
30 

Appendix D: Annual mean brood size of greater snow geese, recorded on staging (Québec, October) 

or wintering (U.S., November), 1965-1997. 

Year Where Sample size Mean brood size SE 

recorded (no. Broods) 

1965 U.S. 

1966 U.S. 

1967 U.S. 

1968 U.S. 

1969 U.S. 

1970 U.S. 

1971 U.S. 

1972 U.S. - Québec 

1973 Québec 

1974 Québec 

1975 Québec 

1976 Québec 

1977 Québec 

1978 Québec 

1979 Québec 

1980 Québec 

1981 Québec 

1982 Québec 

1983 Québec 

1984 Québec 

1985 Québec 

1986 Québec 

1987 Québec 

1988 Québec 

1989 Québec 

1990 Québec 

1991 Québec 

1992 Québec 

1993 Québec 

1994 Québec 

1995 Québec 

1996 Québec 

1997 Québec 

1.71 

2.16 

2.37 

1.65 

2.23 

2.89 

2.21 

no data 

49 2.94 

119 2.19 

1294 2.71 

419 2.46 

396 2.28 

309 2.34 

1226 2.65 

651 2.76 0.053 

229 2.30 0.081 

661 2.48 0.047 

1246 2.86 0.043 

2434 2.63 0.029 

1682 2.49 0.033 

74 1.89 0.105 

1882 2.77 0.031 

2444 2.76 0.029 

2014 2.59 0.033 

830 2.54 0.047 

1247 2.69 0.038 

404 2.06 0.048 

2743 2.75 0.028 

242 2.44 0.091 

665 2.47 0.049 

1247 2.34 0.035 

1222 2.69 0.041 
31 

Appendix E: Recreational harvests of snow geese in southern Québec and the Atlantic Flyway states, 

1967-1997. 

Year Québec Atlantic Flyway Total 

1967 16800 

1968 2700 

1969 3300 

1970 25300 

1971 13300 

1972 6100 

1973 26200 

1974 9000 

1975 31400 

1976 25100 

1977 20100 

1978 41200 

1979 23400 

1980 54400 

1981 29500 

1982 40700 

1983 45300 

1984 42400 

1985 24500 

1986 9700 

1987 38100 

1988 42800 

1989 43000 

1990 57400 

1991 46300 

1992 26700 

1993 92700 

1994 37200 

1995 44500 

1996 62900 

1997 55200 

season closed 16800 

season closed 2700 

season closed 3300 

season closed 25300 

season closed 13300 

season closed 6100 

season closed 26200 

season closed 9000 

8500 39900 

12300 37400 

28200 48300 

21600 62800 

25000 48400 

27300 81700 

13500 43000 

21700 62400 

40400 85700 

38000 80400 

15000 39500 

8800 18500 

28500 66600 

22300 65100 

17600 60600 

21200 78600 

26900 73200 

10600 37300 

29100 121800 

18300 55500 

18200 62700 

32000 94900 

35100 90300 
32 

CHAPTER 2 

IMPACT OF GEESE ON NATURAL HABITATS 

JEAN-FRANÇOIS GIROUX, Université du Québec à Montréal 
 

GILLES GAUTHIER, Université Laval 
 

GARY COSTANZO, Virginia Dept of Game & Inland Fisheries 
 

AUSTIN REED, Canadian Wildlife Service 
 

INTRODUCTION 

Greater snow geese are strict herbivores, i.e. they only eat plants, but they use several 

foraging modes. It is important to understand the difference between these foraging modes because 

their effects on plant communities will differ greatly. Foraging behavior of greater snow geese can 

be divided into two main categories: feeding on aboveground and on belowground vegetation. 

The main foraging mode of birds feeding on aboveground vegetation is grazing, which 

involves the removal of leaves, flowers or entire shoots. This is the predominant foraging mode 

used by geese in farmlands (e.g. in hayfields) or in the tundra during the summer. Feeding on cereal 

grains is another foraging mode used by geese in farmlands. This involves gleaning waste cereal 

grains such as oats or corn after the harvest. 

Belowground feeding is also very important in Greater snow geese and they are extremely 

well adapted to this activity. They have a very strong bill, much stronger in fact than most other 

goose species including lesser snow geese, which suggests that belowground feeding has always 

been a dominant foraging behavior in this species (Bolen and Rylander 1978). Grubbing is the most 

common foraging mode of geese feeding on belowground vegetation. Grubbing involves digging in 

the ground to extract rhizomes, bulbs or roots of plants (Smith and Odum 1981, Bélanger and 

Bédard 1994a). This activity is restricted to natural habitats such as tidal marshes in southern 

Québec and the United States, or in early spring in the Arctic. Geese rarely grub in farmlands 

(except perhaps in flooded fields). Shoot pulling is another foraging mode used by geese feeding on 

belowground vegetation. This behavior involved the removal of white basal stems of sedges buried 

in the ground while discarding dead or senescing aboveground parts. This occurs mostly in early 

spring or late summer in the Arctic (Gauthier 1993) or early fall in tidal marshes of southern Québec 

(Giroux and Bédard 1988a). 

ST. LAWRENCE RIVER 

Use of Natural Habitats by Greater Snow Geese along the St. Lawrence River 

Greater snow geese have traditionally used bulrush marshes during their spring and fall 

staging periods along the St. Lawrence estuary (Lemieux 1959). With the demographic expansion of 

the population in the mid-1970s, they started to spread into cordgrass salt marshes during their 

spring migration (Gauthier et al. 1988). These marshes are located in the La Pocatière, Kamouraska 

and Isle-Verte regions where geese depend to a great extent on the adjacent agricultural fields for 

feeding. Although no studies on the effects of geese on cordgrass marshes have been conducted in 

this area, no degradation comparable to eat-outs observed along the U.S. Atlantic coast has been 

noted. If goose grazing affects salt marshes, it is probably localized and at very small scale (few 

m2

). The rest of this chapter will therefore deal with the effect of geese on bulrush marshes. 
33 

Distribution and Area of Bulrush Marshes along the St. Lawrence River 

Marshes dominated by three-square bulrush (Scirpus pungens)

1

 cover approximately 4000 

ha along the St. Lawrence river (Anon. 1980, Jacques 1986). One fourth of the acreage of these 

marshes are located in the freshwater non-tidal portion of the river (specially around Lake St. Pierre) 

and their use by geese is limited. The remaining portion is found east of Québec City and consists of 

freshwater and brackish tidal marshes characterized by an upper and lower portion separated by a 

30-70 cm high micro-bluff. The upper marsh is 20- to 100-m wide and is flooded by equinoctial 

tides. It is dominated by prairie cordgrass (Spartina pectinata) and saltmarsh sedge (Carex 

paleacea) and is mostly used by geese for resting. The lower marsh located below mean high water 

mark is characterized by a mixed semidiurnal tide with two complete oscillations per day, unequal in 

height and duration. Tidal amplitude reaches 4 to 6 m. The lower marsh which is the main feeding 

area of geese consists of a 100- to 1,000-m band of vegetation dominated by Scirpus pungens with 

sparse growth of wild rice (Zizania aquatica var. brevis), arrowhead (mostly Sagittaria latifolia), 

Torrey bulrush (Scirpus torreyi), and spikerush (Eleocharis spp.) (Giroux and Bédard 1988b). It is 

also bordered by bare mudflats extending 200 to 1,000 m from the vegetation down to the lowest 

low tide. 

This section of the estuary is characterized by high natural turbidity resulting in 

sedimentation of tidal marshes from June to mid-September (Sérodes and Troude 1984). Accretion 

of sediments along the south shore can be up to 14 cm (Giroux and Bédard 1988b) and 30 cm at Cap 

Tourmente (Sérodes and Troude 1984). Two periods of rapid erosion (October-November and 

April) bring the mud flat surface back to its approximate original level. From December to April, 

these marshes are covered by a 1.0- to1.5-m layer of ice. 

In the last 50 years, approximately 15% of the marshes of the estuary have disappeared 

through reclamation for agriculture, road construction or other developments (Anon. 1981). Several 

of the bulrush marshes used by geese are now part of the Migratory Bird Sanctuary network or 

located within the Cap Tourmente National Wildlife Area. 

Feeding Behavior of Geese in Bulrush Marshes 

Greater snow geese feed in bulrush marshes during both their spring and fall migrations 

(Giroux and Bédard 1988c, Reed 1989). In the early 1980s, Gauthier et al. (1988) estimated that, in 

spring, geese spent approximately 90% of their feeding time in those marshes and the remaining in 

adjacent agricultural fields. In 1997, preliminary observations of radio marked birds revealed that 

this is probably less than 50% (A. Béchet, Ph.D. candidate, UQAM, unpubl. data). 

In fall, the relative use of marshes varies among sites depending upon the amount of hunting 

activities in adjacent agricultural fields. At Cap Tourmente where large tracts of fields are available 

for geese, Reed (1989) estimated that only 30% of fall usage recorded between 1980 and 1985 

occurred on the tidal marsh. Part of the remaining 70% occurred in fields, and over the years this 

has probably remained stable (A. Reed unpubl. data). Along the south shore during the mid-1980s, 

geese were totally dependent upon marshes for feeding because of the presence of hunters in nearly 

all-adjacent fields (Giroux and Bédard 1988c). In recent years, however, a greater proportion of 

feeding time is spent in agricultural fields thus reducing the relative use of marshes by geese (J.-F. 

Giroux and G. Gauthier, unpubl. data). 

1

 Based on his taxonomic review, Schuyler (1974) proposed that plants usually treated as Scirpus americanus 

Pers. should be called Scirpus pungens Vahl and those identified as Scirpus Olneyi Gray be treated as Scirpus 

americanus Pers. 
34 

Despite these changes, marshes located within the migratory bird sanctuaries are still used to 

a greater extent than adjacent marshes because of their greater use in fall attributed to hunting 

pressure. Marshes outside the sanctuaries are used in spring and during nighttime in fall, a situation 

prevailing in the mid-1980s (Giroux and Bédard 1988c). 

In fall, three-square bulrush represents approximately 75% of the diet of geese feeding in 

marshes (Giroux and Bédard 1988a). Wild rice, arrowhead and spikerush account for another 20% 

while the rest of the diet is composed of several less important species. Juveniles feed to a greater 

extent on the above- and belowground stems of bulrush while adults feed more on rhizomes. The 

proportion of stems in the diet decreases during the season with depletion of this resource and 

possibly with the increased efficiency of juveniles in grubbing. 

Dead plants are either exported by tide in late fall or ultimately removed at spring break-up 

when large ice floes plowed and scoured the marsh surface (Bélanger and Bédard 1994a). 

Aboveground vegetation has therefore completely disappeared when the geese return to the marshes 

in spring. Bédard and Gauthier (1989) estimated that 97-99% of the diet of geese feeding in spring 

in marshes was constituted by bulrush rhizomes. Bélanger and Bédard (1994b) reported that geese 

also grazed on the emerging shoots of bulrush in late spring but their relative importance in the diet 

has never been established. They speculated that this grazing strategy compared to grubbing was 

best explained by a lower foraging cost since the nutritive value of emerging shoots was comparable 

to rhizomes (Bélanger and Bédard 1992). 

When the birds arrived in fall, they used the stems of bulrush as a cue to get to the rhizomes 

10-25 cm below the surface (Reed 1989, Bélanger and Bédard 1995). Stems disappear quickly 

through trampling, clipping or eating and the marsh surface is then covered by a layer of soft 

sediment. Digging is done more or less randomly at that time. When sediments eroded in late fall 

and spring, geese concentrate their activity in or at the edge of ice-scoured depressions to extract 

rhizomes (Bélanger and Bédard 1995). They avoid any undisturbed and/or hardened rocky marsh 

surface. As the ebb tide exposes the marsh, geese spread out and move continuously from one 

depression to another. Feeding activities remain high until low tide when it drops to nearly 50%, 

and remains moderate through flood tide (Gauthier et al. 1988). It is believed that foraging geese 

follow the tide to take advantage of a softer substrate. 

Effect of Geese on Bulrush Production 

Based on the number of goose-hours recorded at the Montmagny sanctuary and on the 

ingestion rate calculated by Bédard and Gauthier (1989), Giroux and Bédard (1987a) estimated that 

up to 62 g/m2 of rhizomes were eaten annually (fall + spring). This represented 23% of the 

belowground biomass available and 59% of the net belowground primary production. Using a series 

of exclosures established at Cap Tourmente, Reed (1989) estimated that geese removed 55 g/m2 

during their fall staging period which represented 32% of the belowground biomass available. By 

comparing seasonal changes in belowground biomass, Reed (1989) also measured a decrease of 112 

g/m2

 or 74% between September (before goose arrival) and early June (after goose departure). This 

last figure, however, may be slightly overestimated because losses attributed to plant die-off, reserve 

translocation to shoots, erosion and ice-scouring were not considered (Reed 1989). 

In the heavily used marshes at the Montmagny sanctuary, Giroux and Bédard (1987a) 

observed a 62% difference in plant production between grazed and ungrazed plots after 2 years of 

goose exclusion (Fig. 2-1). The higher biomass in the ungrazed plots was related to both a greater 

number of shoots and a greater shoot biomass. Belowground biomass was not assessed in this study 

because a non-destructive sampling technique in permanent plots was chosen for this short-term 

evaluation. Nevertheless, there is a strong positive relationship between aboveground biomass and 
35 

belowground biomass that can be used to estimate net belowground primary production (Giroux and 

Bédard 1988d). The difference in aboveground biomass between grazed and ungrazed plots 

therefore represented 410 g/m2

 of belowground biomass. Similar results were obtained at the Cap 

St-Ignace sanctuary, a nearby marsh less used by geese. The difference between grazed and 

ungrazed plots was 28% after 1 year of goose exclusion (Giroux and Bédard 1987a). No difference 

was found, however, between grazed and ungrazed plots outside the sanctuaries at Montmagny and 

Cap St. Ignace reflecting the limited use of these marshes by geese compared to sanctuaries (Giroux 

and Bédard 1988c). Aboveground biomass (g/m2) 350 

300 

250 

200 

150 

100 

50 

0 

GRAZED UNGRAZED
 

exclosures 

1983 1984 1985 1991
 

Figure 2-1 Aboveground biomass of three-square (mean + 1 SE) in grazed and ungrazed plots at the 

Montmagny sanctuary, 1983-1985, 1991. Note: exclosures were put up after the growing season in 

1983 just before goose arrival. Non-destructive sampling of the same 45 paired plots was conducted 

from 1983-85. In 1991, plots (excluding exclosures) were located at approximately the same place as 

in 1983-85 (Data from J.-F. Giroux, UQAM and A. Reed, CWS). 

At Montmagny, the aboveground biomass in the grazed plots was stable between 1983 and 

1985 and averaged 106 g/m2

 or 267 g/m2 of belowground biomass (Fig. 2-1). Giroux and Bédard 

(1987a) concluded that geese maintained the system at a low-level steady state while Bélanger and 

Bédard (1994b) argued that this resulted from a shift by geese of their foraging sites within the 

marsh when a minimal threshold of food was reached. Based on their study of the foraging behavior 

of geese, Bélanger and Bédard (1994b) suggested that this level was approximately 220 g/m2

 of 

belowground biomass. In 1991, the aboveground biomass was still at the same level than during the 

previous sampling period supporting the idea of a steady state (Fig. 2-1). 

A unique long-term data set is available for the Cap Tourmente marshes where bulrush stem 

density has been determined annually between 1971 and 1984 and every second year since. Annual 

variations between 1971 and 1996 were important and may be attributed to the growing conditions 

prevailing during the summer as shown by Giroux and Bédard (1987b). Nevertheless, stem density 

declined by 40% during the last 25 years (Fig. 2-2; n = 18 years, r2= 0.28, t =-2.67, P = 0.02). 

These evaluations on the effect of goose grubbing on plant production conducted at 

Montmagny and Cap Tourmente are supported by an experimental study that showed that even a low 

intensity of simulated feeding can reduce subsequent production of bulrush (Giroux and Bédard 

1987c). This is consistent with the role of nutrient reserves played by the belowground parts of 

bulrush which does not allow for compensation as has been observed for aboveground herbivory 

(Cargill and Jefferies 1984). 
36 

Unlike alkali bulrush (Scirpus robustus), three-square bulrush does not respond to removal 

of its belowground reserves by increasing its sexual reproduction (Smith and Odum 1981, Giroux 

and Bédard 1987a). Giroux and Bédard (1995) speculated that this was related to the poor seedling 

establishment due to the important sediment accretion occurring in these marshes at that time. 

700 

600 

Nb stems/m2 

500 

400 

300 

200 

100 

0 

1971 1974 1977 1980 1983 1986 1989 1992 1995 

Figure 2-2 Stem density of three-square bulrush (mean + 1 SE) at the Cap Tourmente National 

Wildlife Area, 1971-196. Sample size was 375 plots/year although in some years it varied between 

297 and 382 (Data from A. Reed, CWS). 

Effect of Geese on Plant Species Composition 

During his long-term study, Reed (1989, unpubl. data) recorded an inverse relationship 

between three-square bulrush and wild rice stem densities (r = -0.51, n= 18, P = 0.03). At the 

Montmagny sanctuary, Giroux and Bédard (1987a) found a greater production of wild rice in grazed 

than in ungrazed plots. They suggested that the small depressions created by geese when grubbing 

for rhizomes of bulrush offer a good substrate for the germination of wild rice because they are filled 

with unconsolidated nutrient-rich sediment. Moreover, the decreased biomass of bulrush in the 

grazed plots decreases the shading effect and increases light availability for the seedlings of wild 

rice. This suggestion was supported by the results of Bélanger and Bédard (1994a) who observed a 

greater production of wild rice in grazed disturbed patches (ice-made depressions) than in 

undisturbed patches. 

Giroux and Bédard (1987b) suggested that competitive interference was occurring between 

three-square and Torrey bulrush but did not observe an increase of Torrey bulrush in their grazed 

plots (Giroux and Bédard 1987a). Bélanger and Bédard (1994a), however, found a greater 

production of Torrey bulrush in grazed patches disturbed for at least 2 years and suggested that 

grubbing by geese facilitates colonization by Torrey bulrush. This species lacks the white 

belowground stem of three-square bulrush and its rhizomes are much smaller making it an 

unattractive food source for geese. During a visit of the Montmagny sanctuary in August 1997, J.-F. 

Giroux noted that the relative abundance of Torrey bulrush appears to have considerably increased in 

recent years at the expense of three-square bulrush. It is interesting to note that Torrey bulrush is 

candidate to be considered a vulnerable plant in Québec (Gratton and Dubreuil 1990). We believe 

that its abundance at Montmagny and in nearby marshes does not warrant such consideration 

anymore. 
37
 

Effect of Geese on Bulrush Quality 

In several Arctic ecosystems including Bylot Island, goose grazing improves forage quality 

(nitrogen content) by keeping plants at an early growth stage (Gauthier et al. 1995). Bélanger et al. 

(1990), however, found no difference in plant quality (fiber and nitrogen) between belowground 

parts of three-square bulrush extracted from grazed and ungrazed plots where geese had been 

excluded for 3 years. The only difference was a lower proportion of roots attached to rhizomes in 

grazed plots (12.2±2.2%) compared to ungrazed plots (34.0±6.0%). Less roots may facilitate 

extraction of rhizomes and this can be considered an improvement of the feeding sites following 

grubbing by geese. 

Deposition of secondary metabolites possibly acting as deterrents to herbivores is a common 

evolutionary response of plants in many plant-herbivore systems (Rhoades 1985). Such an 

antiherbivory mechanism does not appear to have evolved in three-square bulrush because no 

difference in total phenols was observed between rhizomes from grazed and ungrazed plots 

(Bélanger et al. 1990). 

Effect of Geese on Marsh Erosion 

Dionne (1985) predicted that grubbing by geese at the surface of bulrush marshes in the 

estuary would result in vertical erosion. Quantitative data are not available and the exact role of 

geese have not been established either. Nevertheless, casual observations by local people and J.-F. 

Giroux confirm that marsh elevation at least in the Montmagny sanctuary is now lower than in the 

mid-1980s. 

Dionne (1985) also claimed that removal of aboveground vegetation by geese in fall was 

contributing to erosion of the micro-bluff that separates the lower and upper marsh at Montmagny by 

increasing wave action. He measured annual retreats up to 1 m but the relative contribution of geese 

to this phenomenon is unknown because similar retreats were measured in other marshes where 

geese are absent (Dionne 1986). Nevertheless, snow geese may exacerbate a natural problem of 

erosion associated with a recent sea-level rise that increases ice and wave action and results in bare 

mudflats at the upper end of the lower marsh (Dionne 1986). These bare mudflats, however, are 

colonized by three-square bulrush through sexual reproduction (Giroux and Bédard 1995). 

Although published quantitative data are limited and the relative role of geese unknown, a 

marked retreat of the micro-bluff occurred between the mid-1980s and 1997 at Montmagny and 

possibly in nearby marshes (J.-C. Dionne, pers. comm., J.-F. Giroux, pers. obs.). Associated with 

the geo-morphological changes observed at Montmagny, the plant community characterized by 

three-square bulrush, spikerush, Torrey bulrush, nodding beggarticks (Bidens cernua), arrowhead, 

burreed (Sparganium spp.), and waterparsnip (Sium suave) located at the upper end of the lower 

marsh (Community 4 of Giroux and Bédard 1988a) has been replaced by a community dominated by 

three-square and Torrey bulrush (J.-F. Giroux, pers. obs.). The significance of this increase of 

potential feeding habitats for geese has not been established. 

Sérodes and Troude (1984) have established a relationship between the amount of sediments 

accreting in marshes and the number of bulrush stems that act as trap to sediments. Reduction in 

stem density following grubbing by geese (Reed, unpubl. data, Giroux and Bédard 1987a) may thus 

contribute to changes in the annual sedimentation rate of these marshes influencing the equilibrium 

between erosion and sedimentation. 
38 

Effect of Geese on Other Species 

No detailed information is available regarding the consequences of goose grubbing on other 

species. These marshes are used by ducks and the traditional concentrations of fall staging northern 

pintails (Anas acuta) at the Montmagny sanctuary, and pintails, green-winged teal (A. crecca) and 

American black ducks (A. rubripes) at Cap Tourmente, are still observed (J.-F. Giroux and A. Reed, 

unpubl. data). The greatest abundance of wild rice following goose grubbing may even enhance the 

attractiveness of these marshes for waterfowl in late summer and early fall. Large numbers of 

gastropods and invertebrate larvae have been observed on mudflats covered by algae (in the mid1980s) at Montmagny and Cap Tourmente (J.-F. Giroux and A. Reed, pers. obs.) but their abundance 

and distribution have not been monitored. The fish community of these marshes has received little 

attention and the effect of goose grazing on the sites used by fishes in the lower and upper marshes 

has not been studied. 

Restoration of Bulrush Marshes 

Restoration of bulrush marshes is very difficult. The limited contribution of sexual 

reproduction precludes seeding and therefore requires the transplantation of rhizomes or pieces of 

sods including rhizomes with or without shoots. This is very laborious and expensive. The best 

strategy that has been recommended for many years is the rotation of the sanctuaries in an attempt to 

equilibrate goose use (Giroux and Bédard 1987a, Bélanger and Bédard 1994b). This has not been 

done so far. 

Conclusions - St. Lawrence River 

Studies on the effect of geese on bulrush marshes conducted in the mid- and late 1980s 

along the estuary concluded that geese and marshes were at equilibrium but at a low-level steady 

state (Giroux and Bédard 1987a, Reed 1989). Giroux and Bédard (1987a) also claimed that threesquare bulrush had a good ability to withstand high, chronic grazing because it recovered rapidly 

once geese were removed. They based their suggestion on the fact that bulrush production in the 

Montmagny sanctuary exclosures reached levels comparable to the ungrazed portions of the marsh 

outside the sanctuary after only 2 years of goose exclusion. These studies, however, took place 

when the population was less than half of what it is now. The decreased number of goose-days 

recorded in fall at Cap Tourmente during the last 10 years (A. Reed, unpubl. data), the declining 

productivity of three-square bulrush at Cap Tourmente and possibly at Montmagny, changes in plant 

species composition in several marshes and erosion of marshes along the south shore are all 

indications that the carrying capacity of these marshes may have been reached and that they can no 

longer accommodate the increasing number of geese. 

Based on the fall use of the Montmagny marshes by geese during the mid-1980s (4,316 

goose-days/ha) when the system was believed to be at equilibrium (Giroux and Bédard 1987a, 

1988b) it is estimated that the 3,000 ha of bulrush marshes present along the estuary could 

theoretically accommodate the 1 million birds of the 1997 fall flight for only 13 days (Giroux, 

unpubl. data). This illustrates the potential value of increasing the carrying capacity of this fall 

habitat. It is therefore urgent that rotation of sanctuaries be implemented to equilibrate bird use. 

Management of agricultural habitats near sanctuaries is also essential to lessen the grazing pressure 

in the tidal marshes and to retain more birds for longer periods in order to benefit from this resource. 

Bulrush marshes play an important role in the St. Lawrence estuary ecosystem. Deschênes 

and Sérodes (1986) demonstrated that three-square bulrush can assimilate heavy metals and large 

quantity of nutrients such as phosphorous indicating an important purification role of these marshes. 

Moreover, all the plant material exported in fall to the lower estuary and the Gulf contributes to 
39
 

trophic chains of these ecosystems. The overall functions of bulrush marshes should therefore be 

considered when evaluating the impact of geese on these marshes. Costanza et al. (1997) recently 

produced an interesting analysis on the nature capital and ecosystem services that help appreciate 

some of the externalities not usually considered in assessing environmental impacts and socioeconomic benefits or losses related to man-made developments. Wildlife damage to natural 

ecosystems, especially when human induced, also have their hidden costs. 

Summary - St. Lawrence River 

1. 	 During their spring and fall migrations along the St. Lawrence estuary, greater snow geese feed 

in approximately 3,000 ha of bulrush marshes by grubbing for rhizomes. 

2. 	 Most studies on the effects of geese on marshes were conducted in the mid-1980s when the 

population was less than half of what it is now. These studies concluded that the marshes and 

the geese were at a low-level steady states and that marshes quickly recover when goose grazing 

is reduced. 

3. 	 In recent years, changes in plant species composition, declines in plant production and marsh 

erosion indicate that the carrying capacity of bulrush marshes may have been reached. It is 

concluded that bulrush marshes cannot accommodate the increasing number of geese. 

4. 	 No eat-outs comparable to those reported along the U.S. Atlantic coast have been observed 

along the St. Lawrence river but actions should be taken to prevent further deterioration of the 

St. Lawrence bulrush marshes by geese. 

U.S. ATLANTIC COAST 

Greater Snow Goose Use of Coastal Marshes 

The effects of snow goose feeding activities on coastal wintering habitats have been 

recognized for a long time (Griffith 1940, Lynch et al. 1947). Prior to the 1960s, however, overall 

impacts from snow geese on coastal marshes appeared relatively small. As the snow goose 

population began to increase in the late 1960s and early 1970s, these impacts became more apparent. 

During the 1970s and 1980s, areas of denuded marsh (referred to as marsh "eat-outs") could be 

found from New Jersey to North Carolina. As the population continues to grow, there is increasing 

concern about the ecological effects that snow goose are having on coastal marshes. 

Coastal salt marshes used by Greater snow geese in the Mid-Atlantic region are dominated 

by smooth cordgrass Spartina alterniflora and salt meadow cordgrass (Spartina patens). These 

Spartina grasses are perennial species that reproduce predominantly by vegetative means and less so 

by seed or sexual reproduction (Smith and Odum 1981). They store considerable amounts of 

energy in their roots and tubers (Gallagher 1983). Removal of large amounts of these root reserves 

will affect plant regeneration and the amount of subsequent vegetative cover on the marsh. Spartina 

alterniflora marshes grazed heavily by snow geese have been found to produce ten times less 

vegetative cover than ungrazed marshes (Widjeskog 1977). Estimates of belowground biomass in 

grazed Spartina marshes are also significantly lower than those for undisturbed Spartina marshes 

(Smith and Odum 1981, Young 1985). Other marsh types, such as freshwater and brackish-water 

bulrush (Scirpus robustus) marshes appear to recover more rapidly because they rely to some extent 

on sexual reproduction (Smith and Odum 1981). 

The degree to which Spartina marshes are affected or the length of time required for 

Spartina marshes to recover from grazing may vary. Factors including the extent of the vegetation 
40 

removed, the size of the area impacted, degree of tidal circulation, associated wind and wave action, 

and other environmental variables are important in influencing the severity of the impacts and the 

recovery of the marsh. Some marshes denuded of standing vegetation may be able to recover 

relatively quickly if sufficient belowground biomass remains (Smith and Odum 1981). Marshes 

with little below ground biomass will recover slower if they must depend on seeds to generate new 

plants. In North Carolina, exclosures placed in a heavily grazed marsh had 60% greater plant cover 

than unprotected areas after one year (Smith and Odum 1981) (Fig. 2-1). Exclosures in heavily 

grazed marshes in Delaware also produced greater aerial plant cover than unprotected areas (Young 

1985). In addition, the Spartina production in the grazed areas was stunted and seed production was 

reduced. Widjeskog (1978) noted that in New Jersey, some marshes along the Delaware Bay 

appeared able to recover in 2-3 years when grazing pressure was removed. In other areas, mostly 

seaside coastal marshes, recovery appeared slower, possibly because restricted tidal flow did not 

provide an ample seed source (Lee Widjeskog, NJ Fish, Game and Wildl., pers. commun.). In large 

eat-out areas, marsh recovery may progress through stages of colonization by Cladophora spp. 

(algae) and Salicornia spp. (glassworts) before Spartina becomes reestablished (Widjeskog 1978). 

Areas that are grazed year after year may be maintained as mud flats. Young (1985) noted 

that in Delaware, impacted sites often regenerated to some extent each year, yet large amounts of 

once densely vegetated marshes stood as patchy growths of Spartina alterniflora plus mudflats. 

Annual vegetation sampling at Bombay Hook National Wildlife Refuge (NWR) in Delaware from 

1989 through 1997 show consistently lower vegetative cover in marshes that are grazed annually as 

compared to marshes that are not grazed (USFWS 1997). In the coastal marsh at the Forsythe NWR 

in New Jersey, a large eat-out has been maintained by continued annual grazing. The lack of marsh 

vegetation at this site has resulted in a large area of open water at higher tides. Wind and wave 

action across this open water is causing further marsh erosion and may be preventing plant reestablishment. 

Extent of Snow Goose Eat-outs Along the Atlantic Coast 

Marsh eat-outs have been found around most refuges on the Atlantic Coast where greater 

snow geese stage or winter (Fig. 1-7). The amount of salt marsh habitat impacted by snow geese 

increased throughout the 1970s and into the 1980s, paralleling the increase in snow goose numbers. 

In recent years, however, the impacts on the marsh have not increased in proportion to the size of the 

snow goose population. The extent of damage appears to depend upon the number of geese feeding, 

the length of time they are present, and the availability of alternative food resources such as 

agricultural crops. Traditionally, snow geese fed almost exclusively on marsh vegetation in coastal 

marsh habitats. As the population has grown over the past 20-30 years, the birds have made greater 

use of green grain fields such as winter wheat, barley and rye, and harvested corn and soybean 

stubble fields. In areas where snow geese have taken advantage of agricultural crops, their impacts 

on coastal marshes appears to have stabilized. 

At Bombay Hook NWR in Delaware, 539 acres of Spartina alterniflora marsh were lost or 

reduced to bare mud from 1980-1984 (Young 1985). Other areas of the marsh have been impacted 

to a lesser degree (less than 50% of the vegetation removed) but this damage has not been quantified. 

Estimates of the area denuded by snow geese (eat-out area) for the past 8 years (1989-1997) have 

been relatively stable between 510-600 acres each year (USFWS 1997), and are similar to the 

estimate made in 1985. This represents about 5% of the salt marsh habitat available on the refuge 

(~12,000 acres) and a smaller percentage of the amount of salt marsh available in the state (67,000 

acres). During the same period, the number of snow geese using the Refuge vicinity has increased 

from around 65,000 in the late 1980s to over 130,000 in the last two years. In addition to feeding in 

the marsh, many of the snow geese using the Refuge now fly inland to agricultural fields in 

Delaware or Maryland, or even across Delaware Bay to fields in southern New Jersey. This has 
41
 

taken some of the feeding pressure off of the marsh. Most of the feeding activity on the Bombay 

Hook marshes had been confined to the same areas each year. Little pioneering into new areas was 

noted until the past two years when record numbers of snow geese have been using the refuge. 

During this time, snow geese have moved to a new site but have denuded only a few additional acres 

(<5) thus far. 

Snow goose numbers have also increased at the Prime Hook NWR, located 30 miles south 

of Bombay Hook NWR along the Delaware coast. Peak numbers increased from 3-4,000 in the 

early 1980s to around 120,000 birds in the mid-1990s. The Prime Hook refuge contains about 6,000 

acres of marsh, of which 1,500 acres is tidal salt marsh and 4,500 acres is freshwater impoundments. 

Some minor impacts of snow goose feeding activities to coastal salt marshes have been noted in this 

area but they have not been quantified (Annibel Larsen, USFWS, Prime Hook NWR, pers. 

commun.). Snow geese have been found feeding to a greater extent in the freshwater impoundments 

on the refuge and in cattle feedlots on private farms off the refuge. Feeding activities in the 

freshwater impoundments are not thought to be detrimental but instead may have some beneficial 

effects. Snow geese may help open up areas of dense vegetation and maintain early successional 

wetland plants (annuals) that are beneficial to other waterfowl (Annibel Larsen, USFWS, Prime 

Hook NWR, pers. commun.). 

In New Jersey, an estimated 20% (~ 1,700 acres) of the Spartina salt marsh in the vicinity 

of the Forsythe NWR (Brigantine Division) was severely impacted (>40% denuded) by snow geese 

between 1971-1978 (Widjeskog 1978). Snow goose numbers on the refuge had expanded rapidly at 

that time from around 2,000 in the late 1960s to a high of 60,000 in some years during the 1970s. 

Numbers have fluctuated over the past 20 years but have generally remained between 20-40,000 

(USFWS, Forsythe NWR, unpubl. data). Snow goose numbers on the refuge generally peak during 

November and decline when colder winter weather arrives in December. These geese remain 

closely associated with the refuge and its surrounding marshes and do not use other Atlantic coastal 

marshes to any great extent despite the fact that there are >70,000 acres of additional salt marsh 

habitat further south along the New Jersey coast. There is little agricultural food in the vicinity of 

the refuge and the geese have continued to feed predominantly on the salt marsh vegetation. It 

appears that the area of marsh impacted has increased gradually over time and this has led to further 

marsh erosion (Paul Castelli, NJ Fish, Game and Wildl., pers. commun.). Because of the loss of the 

vegetation, wind and wave action has severely impacted the dike on the north side of the refuge 

impoundments (Paul Steblein, USFWS, Forsythe NWR, pers. commun.). Work to repair the dike 

over the past two years has cost over $150,000. Forsythe NWR is among the best bird watching 

sites in eastern U.S. and there are concerns that marsh degradation by Greater snow geese could 

affect the potential of the area. 

Snow geese have also impacted marshes along the Delaware Bay coast of New Jersey. The 

number of snow geese in this area generally range from 20,000-40,000 in the fall. Similar to the 

geese at the Forsythe NWR, most birds move out with the onset of colder weather in December. 

Numbers increase again in late winter and early spring when as many as 175,000 snow geese may 

use the area during the northward migration (Perry, Obrecht and Goldsberry unpubl. rep.). Between 

1,000-3,000 acres of Spartina spp. marsh, approximately 2% of the cordgrass marshes along the 

Delaware Bay shore of New Jersey, were impacted in the 1970s and 1980s. Snow geese still use 

these marshes but the extent of damage appears to have stabilized or even decreased in recent years 

(Lee Widjeskog, NJ Fish, Game and Wildl., pers. commun.). These geese have not been as 

restrictive in their use of habitats and have dispersed inland to use agricultural fields in southwestern 

New Jersey and inland in Pennsylvania. 

Snow goose numbers have been increasing in Pennsylvania since the early 1990s. Few birds 

are present in the fall. They begin arriving in mid-December when up to 20,000 have been counted 
42 

the last several years. Their numbers increase substantially in late winter (mid-February to March) 

at the start of the northward migration. Up to 150,000 snow geese have been using the southeastern 

part of the state during this time period in the past couple years (John Dunn, PA Game Comm., pers. 

commun.). The geese have generally been using agricultural fields for feeding and little impact on 

marshes has been noted. 

In Maryland, damage to salt marshes dominated by Spartina alterniflora has occurred near 

Newport Bay at the north end of Chincoteague Bay, and on several marsh islands in Chincoteague 

Bay. Although snow geese feed in agricultural fields during the day, wetland damage results when 

birds return to the salt marsh at night. Impacts have been most severe on Big Bay Point and Robbins 

Tump, two marsh islands in lower Chincoteague Bay. Snow geese have lowered the marsh 

elevation, causing nine ponds to become incorporated into three large ponds, and increasing the size 

of the open water area by >300% (L.J. Hindman, Maryland Dept. Nat. Res., Wye Mills, pers. 

commun.). Property owners have proposed a project to use either dredge spoil or excavated material 

from existing ponds to restore the marsh level to where it will support Spartina alterniflora. 

Damage to salt marsh has also been noted on the lower end of an adjacent island, Tizzard Island, in 

Chincoteague Bay. If this foraging activity continues, it is likely that these coastal islands will be 

converted to mud flats as erosion accelerates. Overgrazing was noted for the first time in October 

1997 on the north end of Assateague Island (Dave Brinker, Maryland Dept. Nat. Res., Annapolis, 

pers. commun.). However, severe damage by snow geese has not been recorded on Assateague 

Island National Seashore. 

In Virginia, there is anecdotal information about minor impacts on coastal salt marshes in 

the early 1970s, but there is little documented information. A small area of marsh eat-out (only 1-2 

acres) was noted in the early 1980s in the salt marsh around the Chincoteague NWR. In the past 5 

years, two other areas, one about 5-7 acres and another 1-2 acres, have been created in the refuge 

vicinity. These eat-outs have occurred during late winter-early spring just prior to or during the 

northward migration (Irv Ailes, USFWS, Chincoteague NWR, pers. commun.). The number of 

snow geese using the Chincoteague area from the late 1970s through the early 1990s was generally 

between 5-15,000. In the last 5 years (1994-1998), larger numbers of geese (between 20-50,000) 

have been using the refuge area in late fall to early winter. These geese have been found feeding in 

both salt marsh habitats and inland agricultural fields in Virginia and Maryland. Snow goose 

numbers decrease to around 5,000 in mid-winter (January) as birds disperse from the refuge area and 

move further south. 

The Back Bay/Mackay Island area of Virginia/North Carolina is a fresh-to-brackish water 

system located inland of the coastal barrier dune. The area generally winters from 10-15,000 greater 

snow geese. An annual cyclic pattern of Scirpus americanus marsh denudation was observed in the 

1970s in which snow geese would rotate around the marsh over a period of years. Geese would 

denude one section of the marsh one year, then move to another area of the marsh the following 

year. This allowed impacted areas to recover over the course of several years (Atlantic Flyway 

Council 1981). It was noted that heavy grazing in some portions of Scirpus marsh could result in the 

invasion of less desirable vegetation such as Cyperus spp. or Juncus spp. Snow geese began using 

agricultural fields in the Virginia/North Carolina area in the late 1960s and early 1970s as evidence 

from the complaints by farmers at that time (Otto Florschutz, USFWS, Washington NC, unpubl. 

rep.). Currently, snow geese use both marsh and agricultural fields in the area and do not appear to 

have long-term negative impacts on either habitats. 

In coastal North Carolina, snow goose eat-outs were evident in the early 1970s in the 

vicinity of the Pea Island National Wildlife Refuge (Bob Nofsinger, USFWS, pers. commun.). 

Different habitat types including freshwater, brackish-water, and coastal salt marsh habitats were 

impacted (Smith and Odum 1981). The fresh and brackish-water marshes were able to recover 
43 

quicker than the Spartina marsh, which required several years without grazing to fully revegetate. 

The number of snow geese using the Pea Island area has declined from around 5,000 birds in the 

1970s and early 1980s to between 1-2,000 over the last 10 years. Little damage to coastal salt 

marshes have been noted during this time. Snow geese have, however, fed in a restored freshwater 

wetland mitigation site that was created in the mid-1990s. Along with Canada geese, they have 

denuded this 35 acre wetland of vegetation during the last two years (Dennis Stewart, USFWS, Pea 

Island NWR, pers. commun.). 

Mattamuskeet and Pocosin Lakes NWRs in North Carolina are predominantly freshwater 

marsh systems that winter both lesser and greater snow geese. Only small numbers of snow geese 

were found on these refuges in the 1960s and early 1970s (Bob Nofsinger, USFWS, unpublished 

data). At Mattamuskeet NWR, the number of lesser snow goose increased to between 3-6,000 

during the 1970s and 1980s. In the past two years 5,000 lesser snow geese have been using the 

Lake Mattamuskeet area joined occasionally for short periods by flocks of greater snow geese from 

adjacent refuges. At Pocosin Lakes NWR, mid-winter numbers of snow goose increased to 2-5,000 

from 1975 through 1985, peaking at 12,000 in 1990. The number of greater snow geese has 

stabilized at 6-8,000 since then. Little impact on habitats in and around these refuges had been noted 

in the past. A Ph.D. study is now underway to evaluate the impacts that snow geese and other 

waterfowl are having on the vegetation in portions of Lake Mattamuskeet. 

Ecological Significance of Snow Goose Feeding Activities 

Snow goose feeding behavior has a number of detrimental effects on coastal salt marsh 

systems. Overgrazing and grubbing activities can lead to the loss of marsh vegetation, an increase in 

erosion, and a decrease in marsh primary productivity. Species that depend on these habitats for 

nesting or foraging, such as the clapper rail, black duck, willet, sharp-tailed sparrow and northern 

harrier will be affected (Ferrigno 1976). Grazed marshes in New Jersey were unsuitable for clapper 

rail nesting and the number of rails declined in these areas (Widjeskog 1978). Invertebrates 

associated with the salt marsh vegetation including the salt marsh snail (Melampus bidentatus), 

ribbed mussel (Geukensia demissa), and fiddler crabs (Uca spp.) also declined in eat-out areas. 

Invertebrates are a major component of the black duck diet and the loss of marsh invertebrates can 

negatively affect the winter carrying capacity for black ducks (Atlantic Flyway Council 1981). 

Invertebrate populations did not fully recover until a year after the recovery of the marsh vegetation 

(Widjeskog 1979). 

Although greater snow geese can have significant negative impacts on salt marshes, they 

may also have beneficial effects. Eat-outs create openings that provide habitat diversity in 

monotypic stands of Spartina marsh. These openings can provide habitat for shorebirds and wading 

birds, and roosting and loafing sites for other waterfowl. Grazing and grubbing activities may aid in 

recycling nutrients and providing resources for other marsh consumers (Smith and Odum 1981). 

Goose grazing may also lead to a greater diversity of plant species and prevent the invasion of 

woody species in certain areas (Smith 1983). 

The ecological significance of snow goose feeding behavior depends upon the magnitude of 

their impacts in relation to available habitats, and how they affect other species using these habitats. 

Short-term effects on salt marsh habitats have been demonstrated, but long-term impacts on coastal 

ecosystems are harder to identify and interpret. In areas where snow geese have adapted to feeding 

in agricultural habitats, their winter range has expanded and their relative impacts on coastal marshes 

appear reduced. Yet, the nutritional subsidy provided by agricultural grains has likely contributed 

to the snow goose population increase (Abraham and Jefferies 1997). Increased damage to coastal 

habitats during the last 5-10 years has occurred in areas where agricultural foods are less available or 
44 

where large increases in snow goose numbers have occurred rapidly. Continued growth of this 

population will likely present additional challenges for wildlife managers. 

Summary - U.S. Atlantic Coast 

1. 	 Impacts to Mid-Atlantic coastal marshes from greater snow goose feeding activities appeared to 

increase in the 1970s and early 1980s along with the general increase in snow goose populations. 

2. 	 Damage to coastal salt marshes in the 1990s does not appear to have increased in proportion to 

population size in areas where agricultural fields are used. However, in traditional snow goose 

concentration areas along the coast, areas of salt marsh eat-outs have been maintained or 

expanded. 

3. The amount of salt marsh habitat impacted by greater snow geese is relatively small in 

comparison to the total amount of coastal salt marsh habitat available. However, extensive 

damage does exist in some areas and can have detrimental effects on the environment and other 

wildlife species. 

4. 	 Depending upon a number of variables including the degree, extent, timing, and location of 

impacts, some habitat changes resulting from snow goose feeding activities could be considered 

beneficial. 

ARCTIC BREEDING HABITATS 

Habitat Use by Geese 

The breeding range of greater snow geese extends over a vast area of the Canadian Arctic 

archipelago, and data on habitat use and impact of geese on the vegetation is available from very few 

sites. Published information on the habitat use is available only from two sites: Jungersen Bay 

which is located at the base of Admiralty Inlet on northern Baffin Island, and Bylot Island. 

Giroux et al. (1984) studied habitat use by greater snow geese during the brood-rearing period 

at Jungersen Bay in summer 1981. Habitats most heavily used by geese at this site included a tidal 

marsh dominated by Puccinellia phryganodes and Carex subspathacea, and wet sedge meadows 

around freshwater ponds dominated by a mixture of sedges (Carex spp, especially C. aquatilis, and 

Eriophorum spp.) and grasses (Dupontia fisheri, Arctagrostis latifolia). Mosses were also a 

dominant feature of wet sedge meadows. They also reported a small amount of old grubbing 

(presumably from the spring) and shoot pulling. Although they made no direct measurements of the 

impact of grazing by geese on the vegetation, they estimated that the amount of Arctic habitat 

available for greater snow geese was more than an order of magnitude greater than what was 

required by the total population at that time (170,000 geese in 1981). This conclusion was reached 

by combining information on plant production estimated at other high Arctic sites, the amount of 

tundra habitat available (estimated from the Arctic Ecology Map Series of Canadian Wildlife 

Service) the proportion of habitat suitable for geese at their study site, and known daily food 

requirement of geese. 

Since 1990, Gauthier and collaborators have conducted detailed studies on plant production, 

grazing impact, habitat use and gosling growth at the Bylot Island snow goose colony. Tidal 

marshes are very restricted on Bylot Island and, although used by geese, account for a negligible 

fraction of habitats available to them. This situation appears common in many areas used by greater 

snow geese in the summer as the rugged and steep coastline of many Arctic islands is not suitable for 

the formation of large tidal flats. Wetlands used by geese on the south plain of Bylot Island are thus 

inland, freshwater habitats. Many of these wetlands result from the action of permafrost which 
45 

creates topographic features such as patterned grounds (polygon) or thermokast pits that impede 

drainage and favor water retention. 

On Bylot Island, Hughes et al. (1994b) described 12 habitat types used by geese grouped in 

three main categories: pond/lake, wet meadow and upland. Pond/lake are small to large permanent 

water bodies with a narrow band of rich graminoid cover and mosses along the edge. Wet meadows 

(often called sedge meadows) are shallow basins (e.g. polygons) that do not retain standing water 

permanently. These wetlands are essentially fens and are covered by a thick carpet of mosses and 

graminoid plants. Upland habitats are a mixture of moist to dry habitats located mostly on sloping 

terrain and are characterized by sparse vegetation but may also contain isolated wet patches (e.g. 

along seasonal streams). Wet habitats are dominated by sedges (Carex aquatilis, Eriophorum 

scheuchzeri and E. angustifolium) and grasses (Dupontia fisheri, Pleuropogon sabinei and 

Arctagrostis latifolia). Moist upland habitat has a diverse but variable vegetative cover depending of 

the amount of soil moisture. Common plants include shrubs such as Salix spp and Vaccinium 

uliginosum, forbs such as Cassiope tetragona, Oxytropis maydelliana and Polygonum viviparum and 

graminoids such as Arctagrostis latifolia, Alopecurus alpinus, Poa glauca and Luzula confusa 

(Gauthier et al. 1996). 

Habitats used by geese on Bylot Island vary seasonally. To better characterize habitat use, the 

summer period can be divided into four periods: arrival and pre-laying, nesting, brood rearing and 

fledging. Geese generally arrive on the island in late May, when most wetland habitats located in 

lowland areas are still frozen and covered by snow. At many lesser snow goose colonies (e.g. west 

Hudson Bay), damage to the vegetation can occur at snowmelt because large number of birds nesting 

further north will stage at more southerly colonies and heavily grub before moving on. This does not 

appear to be the case on Bylot Island where we never observed large flocks of birds passing through 

in late May or early June. Use of the island at snowmelt appears to be largely restricted to birds 

breeding on the island or in the immediate vicinity. Arriving geese will initially feed in snow-free 

sloping areas. Their diet in these upland habitats is diverse and includes leaves, roots and bulbs of 

several species of grasses and forbs (Gauthier 1993). Grubbing can be locally intensive as 

belowground vegetation accounts for about 50% of their diet. As snowmelt progresses and lowland 

areas become snow-free, geese concentrate their foraging on the edge of ponds and flooded wet 

meadows. They feed mostly on basal stems and roots of Eriophorum and Carex (shoot-pulling). 

Belowground vegetation is still important, accounting for >50% of the diet. 

During the nesting period, food intake by geese is limited and their foraging activity 

concentrated in the immediate vicinity of the nest (Reed et al. 1995). Nesting habitats include 

upland habitat and polygon rims on the edge of wet meadows or ponds (Lepage et al. 1996). Diet of 

geese during this period is also diverse as they often take advantage of temporary available food 

items such as opening buds, emerging leaves and catkins of willows, horsetail shoots or flowers of 

Oxytropis (Gauthier 1993, Gauthier and Hughes 1995, Reed et al. 1995). Belowground vegetation 

still accounts for up to 30% of the diet of early incubating geese but decreases thereafter as shootpulling of Carex is gradually replaced by grazing of graminoid plants. 

After hatch, goose families settle mostly in pond/lake and wet meadow habitats, although 

upland is also used to some extent, especially late in the season (Hughes et al. 1994a, b). During this 

period, foraging mode is almost exclusively grazing on leaves. Dupontia fisheri, a grass, and 

Eriophorum scheuchzeri, a sedge, are the principal plants grazed by geese at that time (Manseau and 

Gauthier 1993, Gauthier et al. 1995). With the addition of growing goslings to the population, this is 

the period when grazing is most intensive. A small number of non-parental birds (failed or nonbreeders) are also present on the island during the summer. During molt, these flocks of birds are 

largely restricted to pond/lake habitat (especially the larger lakes) where they also graze grasses and 

sedges in these wetlands (Hughes et al. 1994b). 
46
 

Shortly before fledging in late summer, broods tend to disperse away from wet lowlands to 

upland habitats (Hughes et al. 1994a, b). Casual observations suggest that use of upland habitat 

increases further after fledging and before departure for the southward migration, which occurs in 

the last days of August. Little information is available on the diet of geese at that time although they 

appear to revert again to feeding on belowground vegetation (grubbing and shoot-pulling of Carex 

and Eriophorum) in addition to grazing. Feeding on berries in some areas is also possible. 

Annual Impact of Grazing on Vegetation 

Information on the effect of grazing by greater snow geese on plants is available only from the 

intensive work that G. Gauthier has been conducting on Bylot Island. All the measurements of 

impact on the vegetation have been made in wetlands (pond/lake and wet meadows) because these 

are clearly the preferred and most heavily used habitats, especially by brood-rearing geese, even 

though they account for only about 10% of the total area of the south plain of Bylot Island (Massé 

1998). Every year since 1990, a series of 1x1 m exclosures are erected in wetlands of the largest 

glacial valley of Bylot Island to monitor production of graminoid plants and grazing impact of geese. 

Exclosures are set up in mid June, shortly after snowmelt. The area sampled is mostly exposed to 

grazing by brood-rearing geese although a variable but small amount of early spring and/or late 

summer grubbing and shoot-pulling also takes place in some areas. 

Plant production is variable among years on Bylot Island. For instance, aboveground biomass 

of graminoid plants in annual exclosures at the end of the growing season was half of normal in 

1994, a drought year (Fig. 2-3). We detected an impact of grazing by geese on aboveground plant 

biomass in all years, but the effect was also variable among years (Fig. 2-3). The highest grazing 

impact occurred in 1993: Gauthier et al. (1995) estimated that geese consumed 78% of the annual 

production of Dupontia fisheri and 100% of the production of Eriophorum scheuchzeri in preferred 

brood-rearing habitats that year. There is no evidence of long-term increase in grazing impact 

despite the increase in population size on Bylot Island (Chapter 1). Annual variation in grazing 

impact largely represents annual variation in the intensity of use of the area by brood-rearing geese. 

In 1993, faeces counts suggested that use of the lowland areas was the largest ever recorded on Bylot 

Island (Fig. 2-4). This resulted from an unusually large reproductive effort by geese that year due to 

the early snowmelt, and a high nesting success (Lepage et al. 1996). Other factors such as nesting 

phenology, the timing of dispersal by broods from lowlands to uplands or weather conditions could 

also explain some of the annual differences in grazing impact. 

Herbivores can sometimes have a positive impact on their plant food. For instance, grazing 

often results in an increase in plant quality (higher nitrogen concentration) and in enhanced plant 

production (overcompensation). Such positive feedbacks on the vegetation have been reported at 

moderate levels of grazing by lesser snow geese at La Pérouse Bay (Cargill and Jefferies 1984, Hik 

and Jefferies 1990). On Bylot Island, nitrogen concentration of grazed plants is generally higher 

than ungrazed plants (Gauthier et al. 1995), though not always (Piedboeuf 1996). However, in 

contrast to the situation prevailing in the coastal marshes of Hudson Bay, we failed to detect any 

evidence of overcompensation in plants grazed by snow geese in wetlands of Bylot Island as 

regrowth following grazing was not higher than in ungrazed swards. On the contrary, annual 

production of Dupontia fisheri in grazed areas was slightly lower than in ungrazed areas. 

An increase in the availability of nitrogen to plants via the deposition of goose faeces was a 

key factor in explaining the positive response of graminoids to moderate grazing at La Pérouse Bay 

(Bazely and Jefferies 1985, Hik and Jefferies 1990). However, controlled experiments on Bylot 

Island showed that goose faeces did not have any fertilization effect on graminoid plants (Beaulieu 

et al. 1996), even though fertilization experiments showed that nitrogen was limiting plant growth 
47
 

40 

35 

30 

25 

20 

15 

10 

5 

0 

1990 1991 1992 1993 1994 1995 1996 1997 

16 

Ungrazed 

Grazed 

All graminoids 

14 

12 

10 

8 

6 

4 

2 

0 

1990 1991 1992 1993 1994 1995 1996 1997 

30 

Ungrazed 

Grazed 

Eriophorum

25 

20 

15 

10 

5 

0 

1990 1991 1992 1993 1994 1995 1996 1997 

Ungrazed 

Grazed 

Dupontia

Figure 2-3. Live aboveground biomass (dry mass) of graminoids on 15 August in grazed and 

ungrazed areas (n = 12) on Bylot Island (mean + SE), 1990-1997. No data from ungrazed area in 

1992 because grazing was negligible following the almost complete breeding failure of geese. Cumulative feces density (n/m2) 

Above-ground live biomass (g/m2) 

10 

8 

6 

4 

2 

0 

1990 

1991 

1993 

1994 

1995 

1996 

1997 

20 30 10 20 30 10 20 

JUNE JULY AUGUST 

Figure 2-4. Cumulative faeces density showing the use of the Base-camp Valley by greater 

snow goose families on Bylot Island (n = 12 transects of 1 x 10 m), 1990-1997. 
48 

(Pineau 1998). One important difference, however, with coastal marshes of Hudson Bay is the 

presence of a thick layer of moss in wet meadows used by snow geese on Bylot Island. It is possible 

that most nutrients leaching from goose faeces are absorbed by mosses rather than graminoids 

because mosses have a higher ion exchange capacity than vascular plants. Preliminary results from 

fertilization experiments showed that mosses absorbed nitrogen at a lower level of fertilization than 

graminoids (Pineau 1998). This suggests that mosses act like a sponge, soaking up most of the 

nutrients released from faeces. It thus appears that nitrogen cycling in this ecosystem is more 

complex and involves three levels (graminoids, mosses and herbivore) rather than only two. 

Impact on Gosling Growth 

The growth rate of greater snow geese is exceptionally high for a self-feeding precocial bird of 

that size, undoubtedly an adaptation to the short Arctic summer (Lesage and Gauthier 1997). In 

order to achieve optimal growth, goslings must have access to abundant and high quality food. 

Lepage et al. (1998) showed that the total amount of nitrogen available in plant food during the 

summer could explain a large proportion of seasonal and annual variations in gosling growth. 

Because gosling growth rate is likely to be the first parameter to be affected by a decline in food 

supply, that rate could be used as an index of habitat quality and to detect possible habitat 

deterioration related to population expansion. At La Pérouse Bay, Cooch et al. (1991) showed a 

long-term decline in gosling mass and size near fledging in response to a gradual deterioration of 

brood-rearing habitats due to overgrazing. 

In greater snow geese, Reed and Plante (1997) showed a significant decline in mass, size and 

condition of goslings measured during the fall hunt in southern Québec over a 19-year period (1975-

1994). They suggested that this could be a consequence of density dependent factors occurring 

during the brood-rearing period in the Arctic: as the population expanded, increasing numbers of 

goslings may be encountering a reduced per capita availability of food, and thereby experiencing 

lower growth rates and reduced final size. Annual monitoring of gosling mass and size near fledging 

at Bylot Island over a 7-year period (1991-1997; Fig. 2-5) failed to substantiate the findings of Reed 

and Plante (1997): based on large sample sizes obtained during our annual banding operation, we 

found no evidence of long-term decline in gosling growth. However, in accordance with the 

previous study, we found large annual variation in gosling growth. For instance, very poor growth 

was observed in 1994, a year with relatively low brood density but with very low plant production 

due to drought conditions (Fig. 2-3). In the year of highest brood density (1993), gosling mass near 

fledging tended to be low (though not size). Our inability to detect long-term decline in gosling 

growth at Bylot Island may be related to the large annual variability in growth and the relatively 

small number of years (7) compared to the data set of Reed and Plante (1997). 
49
 

Mass (g) Size (PC1) 

1 . 0 

0 . 5 

0 . 0 

-0 . 5 

-1 . 0 

91 92 93 94 95 96 97 

2000 

1800 

1600 

1400 

91 92 93 94 95 96 97 

Y ear 

Figure 2-5. Annual body size and mass (g) of goslings measured during banding at Bylot 

Island, 1991-97 (n = 11,632). Measurements are standardized at 35 d of age (Least-square 

means + SE). The first axis of a principal component analysis including culmen, head and 

tarsus length (PC1) was used as an index of body size. Regression of mass or size on year 

were not significant (P > 0.05). 

Long-term Impact of Grazing 

Annual plant production at Bylot Island (range: 20-35 g/m2

) tends to be at the lower end of the 

range for wet Arctic graminoid communities (Gauthier et al. 1996). This could partly reflect sitespecific differences in net primary production, or could be a consequence of the intense, chronic 

grazing by geese on Bylot Island. We found that accumulation of soluble carbohydrates in rhizomes 

was lower in grazed than in ungrazed plants (Beaulieu et al. 1996). As belowground reserves are 

important to sustain production of new tillers in Arctic graminoids, chronic grazing could eventually 

lead to a decrease in tiller density and thus overall production. The shoot-pulling habit of geese in 

early spring and late summer is another factor that may contribute to the decrease in tiller numbers in 

grazed areas. 

Preliminary results from the monitoring of long-term goose exclosures showed that, indeed, 

both the production and composition of the community is affected by geese. In 1994, we resampled 

13 1x1m exclosures that had been left standing after our annual sampling in 1990 or 1991. After 4 

to 5 years of goose exclusion, biomass of Eriophorum, the preferred food plant of geese, was 3 times 

higher at the end of the summer than in sites protected from goose grazing only in the current year 

(23 vs 8 g/m2

, respectively; Fig. 2-6a) and the number of tillers was twice as high (2048 vs 1081 

tillers/m2

; Fig. 2-6b). Although Eriophorum was less abundant than Dupontia in the first year of 

goose exclusion (37% of total graminoid biomass), it had become the dominant species 5 years later 

(55% of biomass). The standing litter (dead aboveground vegetation) had also increased by more 

than two fold (Fig. 2-6c). These results suggest that chronic, intense grazing by geese leads to a 

low-level production equilibrium between geese and the plants similar to the situation documented 
50 

in some Scirpus marshes along the Saint Lawrence estuary (Giroux and Bédard 1987a). However, 

they also show that when grazing is stopped, plant biomass increases rapidly within a few years. 

50 

90 / 91 - 1 y ear 

9 4 - 1 y ear 

9 4 - 4 / 5 y e ar s 

A 

NS 

A A 

AB A B

B 

2) Live biomass (g/

m2) 

40 

30 

20 

10 

0 

D upo n t i a E r i o p hor u m A l l g r am i noi d s 

5000 

4000 

3000 

2000 

1000 

0 

Number of tillers (n/

m2) 

9 4 - 1 ye ar 

9 4 - 4/ 5 yea r s 

B 

NS 

* 

* 

D upo n tia E rio p horu m A l l G ra m inoid s 

40 

30 

20 

10 

0 

94 - 1 y ear 

94 - 4 / 5 y ear s C 

* 

* 

* 

Dead biomass (g/m 

D u p ont ia E riopho r u m A l l gr am in o ids 

Figure 2-6. Live aboveground biomass (A), number of tillers (B) and dead aboveground biomass (C) 

of graminoid plants at the end of the summer (dry mass; Mean + SE) after one year and 4 or 5 years 

of goose exclusion in preferred wetlands used by brood-rearing geese on Bylot Island (n = 13 1x1 m 

exclosures). Bars with * or different letters within each categories differ significantly (P < 0.05; NS 

= not significant). 

A more complete set of larger exclosures (4x4 m) was set up in 1994 to monitor long-term 

changes to the vegetation on Bylot Island at sites where only grazing occurs, and others where both 

grazing and shoot-pulling is common. Results for the graminoid plants after 3 years of exclusion 

mirror those obtained with the smaller size exclosures. Moss production is also monitored because 

increase in biomass and litter of vascular plants could adversely affect mosses. 

Grubbing, which is much more devastating for the vegetation than grazing, is not yet 

extensive on Bylot Island although it occurs regularly at snowmelt. Even though the island is not 

used as a staging areas for geese migrating further north in spring, grubbing is likely to increase with 

the continuous increase in the population. In lesser snow geese, even colonies which are at the 

terminus of migration and receive little staging birds such as Queen Maud Gulf are suffering from 
51 

habitat degradation caused by locally breeding birds (Abraham and Jefferies 1997). This process is 

likely to occur as well in areas used by greater snow geese in the future. 

The Carrying Capacity of Bylot Island for Brood-rearing 

Extensive damage done by lesser snow geese to the salt-marshes of Hudson Bay suggests that 

geese have exceeded the carrying capacity of their habitat (Abraham and Jefferies 1997). The 

carrying capacity can be defined as the number of individuals that a given habitat can sustain at 

equilibrium. Estimating the carrying capacity of a habitat can be a useful step when attempting to 

set population goals for a species. Estimating the carrying capacity of the Arctic islands for greater 

snow geese is impossible at this stage. However, because Bylot Island is one of the most important 

breeding colonies for this species and since growth rate of the colony has been as rapid as the 

population as a whole (Chapter 1), estimating the carrying capacity of the island for geese may be 

used as an index for the whole population. 

The study of Hélène Massé (1998) recently estimated the carrying capacity of freshwater 

wetland habitats used by greater snow geese on Bylot Island during brood-rearing. The approach 

that she used was to evaluate in detail food availability and to compare it to the requirement of the 

birds. This involved: 1) mapping the different wetland types available to geese on the 1600-km2 

south plain of the island, 2) estimating plant production of these habitats at several sites on the 

island, 3) comparing total food availability with estimated total nutrient requirement of growing 

goslings and adults, and 4) validating the model by comparing the predicted amount of plant biomass 

consumed with the intensity of goose grazing measured at several sites. As a first step, she limited 

her estimate of the carrying capacity only to wetland habitats. Although additional food resources 

can be found by geese in upland habitat, this habitat is of marginal quality for them and it is unlikely 

that geese could rely exclusively on this habitat throughout the summer. As this work is still in 

progress, only preliminary results will be presented here. 

Five types of wetland habitats were retained for mapping purposes: wet polygon, polygon 

channels, lake polygons, stream banks and lake shores. Stream banks, wet polygons and polygon 

channels were the most widespread habitats, accounting for 92% of all wetland habitats on the island 

(Table 2-1). However, a large proportion of some wetland habitats (e.g. polygon channels) was 

unsuitable for goose feeding because of the presence of deep water or patches of dry upland habitat. 

The total availability of food for geese per habitat was assessed by combining data on habitat area 

covered by suitable forage plants and the associated production. The vegetation of stream banks 

represented up to 70% of the total food supply available on the island wetlands (2,004 tonnes), 

followed by the vegetation of wet polygons which accounted for 24% of all suitable forage. 

Food requirements of geese were calculated from data derived from the literature. 

Requirements of individual birds were multiplied by the population size estimated during the last 

census of Bylot Island (Chapter 1) to obtain annual food consumption of geese on the island. The 

total amount of food that would have been consumed by the 1993 population was estimated at 1,182 

tonnes of vegetation (Massé 1998) which represented 59% of the estimated carrying capacity of the 

south plain of Bylot Island (2,004 tonnes of forage). Although the total population has increased 

since 1993, the abundance of birds on the island during the years that the carrying capacity was 

estimated (1996-1997) was probably comparable since 1993 was a year of very high brood density 

for geese on Bylot Island. 
52 

Table 2-1. Area covered by wetland habitats, area covered by suitable forage plants within habitats, 

aboveground plant production and total availability of suitable forage plants for geese in wetland 

habitats on the south plain of Bylot Island (Massé 1998; do not cite this table without permission of 

the author). 

Habitat type1 Total area 

(km2) 

Area covered by 

suitable forage 

plants (km2

) 

Production 

(g/m2/yr) 

Total availability of 

suitable forage plants 

(kg x 1000) 

SB 44.6 41.5 33.6 1,394 

WP 30.2 17.4 27.8 484 

PC 30.0 1.9 54.1 103 

LP 8.4 0.6 32.0 19 

LS 0.3 0.2 20.2 4 

Total 113.5 62.7 2,004 

1 SB = Stream-bank, WP = Wet polygon, PC = Polygon channels, LP = Lake polygons, 

LS = Lake shores 

To validate the model, Massé (1998) compared the proportion of consumed biomass 

predicted by the model with actual measurements of grazing impact. In 1996-1997, grazing impact 

in the five habitats was measured at 7 sites throughout the south plain of Bylot Island (N = 154 

exclosures). These measurements yielded an average value of 35% of aboveground biomass 

removed by geese by 15 August. If we only consider the food requirement of the geese up to the 

time that exclosures were sampled (15 August), the model estimated that geese should have 

consumed about 45% of the total food available in the Bylot Island wetlands by then. These two 

values agree reasonably well considering the error associated with each of them. The higher value 

predicted by the model may be because food available in isolated wetlands in upland habitat, and in 

the marginal upland habitat itself was not measured (Hughes et al. 1994b). It is also important to 

remember that this is a crude estimate of the carrying capacity of the south plain of Bylot Island 

because several sources of error could affect these calculations. This value could also fluctuate over 

time because of weather related variation in annual plant production as shown before. These 

calculations nonetheless suggest that, although the carrying capacity of Bylot Island for snow geese 

is not yet reached, it could be in the near future with the continuous increase in the population. 

Summary – Arctic Breeding habitats 

1. 	 In contrast to other snow goose populations breeding in the low Arctic, salt marshes are rare in 

the high Arctic and are thus little used by greater snow geese. Wetlands used by geese in the 

high Arctic are thus largely inland, freshwater habitats. The most important habitats include 

small to large permanent water bodies (pond/lake) and wet meadows (often called sedge 

meadows). These wetlands are essentially fens and are covered by a thick carpet of mosses and 

graminoid plants, of which Dupontia fisheri, Eriophorum scheuchzeri and Carex aquatilis are 

the most important forage species for geese. 
53
 

2. 	 Also in contrast to the situation prevailing along the southern and western coasts of Hudson Bay, 

Bylot Island is not used by waves of migrating geese en route to nesting grounds further north. 

Use of the island in spring appears to be limited to those breeding in the area. However, spring 

grubbing by locally breeding birds already occurs on a small scale and is likely to increase with 

the continuous increase of the population. 

3. 	 Although grazing level can be very high in some years on Bylot Island, we have not yet seen 

evidence of damage to the vegetation in terms of absence of regrowth following grazing. 

Evidence from other sites in the high Arctic are virtually non existent. Several researchers have 

visited greater snow goose colonies elsewhere in the Arctic islands (e.g. Doug Heyland, Hugh 

Boyd, Austin Reed and Jean-François Giroux) since the 1970s but none reported goose-related 

damage to the vegetation at these colonies. 

4. Lepage et al. (1998) showed that variation in food availability during the summer could explain 

a large proportion of seasonal and annual variations in gosling growth. Reed and Plante (1997) 

reported a decline in mass, size and condition of goslings measured during the fall hunt in 

southern Québec over an 19-year period, and suggested that this was consequence of density 

dependent factors occurring during the brood-rearing period in the Arctic. Annual monitoring of 

gosling mass and size near fledging at Bylot Island over a 7-year period did not reveal similar 

trends although large annual variations may obscure long-term trends. 

5. 	 Monitoring of long term goose exclosures showed that the composition of the community is 

modified by geese, and annual production is reduced in heavily grazed areas. After 4-5 years of 

goose exclusion, biomass and tiller density of Eriophorum, the preferred food plant of geese, 

increased three-fold. Chronic, intense grazing by geese apparently leads to a low-level 

production equilibrium between geese and the plants in Arctic wet meadows. However, when 

grazing is stopped, plant biomass increases rapidly within a few years. 

6. 	 A recent survey estimated the total amount of forage plants available to snow geese in all 

wetlands of the south plain of Bylot Island at 2,004 tonnes. Two independent estimates of the 

total amount of food consumed by geese on the island was also obtained based on food 

requirements of individual birds and estimated population size, and the actual differences in 

biomass removed between paired grazed and unpaired plots across the island. Both methods 

suggested that almost 60% of total available forage plants in wetland habitats were consumed by 

geese at current population size. These calculations nonetheless suggest that, although the 

carrying capacity of Bylot Island for snow geese is not yet reached, it could be in the near future 

with the continuous increase in the population. 

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on Bylot Island, Northwest Territories. J. Wild. Manage. 58:536-545 

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geese Anser caerulescens. Wildfowl 45:49-64. 

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muskrats to Gulf Coast Marshes. J. Wildl. Manage., 11:50-76. 

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consequence of constraints on laying dates? Can.J. Zool.74:1866-1875. 

Lepage, D., G. Gauthier, and A. Reed. 1998. Seasonal variation in growth of greater snow goose 

goslings: the role of food supply. Oecologia 114:226-235. 

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Auk 114:229-241. 

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habitat. Ecology 74:2045-2055. 

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par la grande oie des neiges nichant à l’Île Bylot, TNO. MSc thesis, dept. phytologie, Univ. 

Laval. 

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est-il avantageux d'utiliser des sites déjà broutés? MSc thesis, dept. biologie, Univ. Laval. 

Pineau, C. 1998. Facteurs limitant la croissance des plantes graminoïdes et des mousses dans les 

polygones de tourbe utilisés par la grande oie des neiges. MSc thesis, dept. phytologie, Univ. 

Laval. 

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Pages 605-616 in R. R. Sharitz and J. W. Gibbons (eds.). Freshwater wetlands and wildlife. 

USDOE Office of Scientific and Technical Information. Tennessee. 

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snow geese. Condor 97:993-1001. 

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1975-1994. J. Wildl. Manage. 61:413-419. 
57 

Rhoades, D.F. 1985. Offensive-defensive interactions between herbivores and plants: their relevance 

in herbivore population dynamics and ecological theory. Am. Nat. 125:205-238. 

Sérodes, J.-B. and J.-P. Troude. 1984. Sedimentation cycle of a freshwater tidal flat in the St. 

Lawrence estuary. Estuaries 7:119-127. 

Smith, T.J. III. 1983. Alteration of salt marsh plant community composition by grazing snow geese. 

Holarctic Ecology 6:204-210. 

Smith, T.J. III and W.D. Odum. 1981. The effects of grazing by snow geese on coastal salt marshes. 

Ecology 62:98-106. 

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Bombay Hook NWR and related wetland changes. Progress Report No. 9. 22 pp. 

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Delaware. 63 pp. 
58 

CHAPTER 3 

IMPACT OF GEESE ON FARMLANDS 

BERNARD FILION, Ducks Unlimited Canada 
 

DENNIS LUSZCZ, North Carolina Wildlife Resources Commission 
 

GUY ALLARD, Université Laval 
 

SOUTHERN QUÉBEC 

Introduction 

Contrary to the waterfowl depredation occurring on small cereal grains in western Canada 

during the fall, crop depredation by greater snow geese in Québec occurs in the spring. Depredation 

takes place mainly in hayfields devoted to forage production (mixtures of grasses and legumes), 

particularly east of Québec City along the St. Lawrence River estuary. However, the spring staging 

distribution of geese is gradually shifting toward southwestern Québec and the north shore of the St. 

Lawrence River west of Québec City. This shift as well as a longer stay in these areas could mean 

increasing depredation problems within these areas in the near future. Reasons for these changes are 

unknown but coincide with the rapid increase in the greater snow goose population (Chapter 1). 

Until the 1960s, greater snow geese staged in their traditional bulrush marshes of the upper 

St. Lawrence River estuary. They gradually started field feeding along the south shore in the late 

1960s (Anon 1981, Reed 1992) and early 1970s at the Cap Tourmente National Wildlife Area 

(Laperle pers. comm.). This was initiated when the population reached approximately 100,000 birds. 

Concurrently, the geese invaded the cordgrass marsh in the lower St. Lawrence River estuary, and 

were well established there by the end of the 1970s (Chapter 1). During the springs of 1979 and 

1980, Gauthier et al. (1988) observed that geese staging in the cordgrass marsh spent 28% of their 

time field feeding as compared to 10% for those staging in the traditional bulrush marsh. In the 

springs of 1993 and 1994, geese staging near cordgrass marshes spent 59% of the daylight period in 

fields and 41% in marshes (UPA 1995). Bédard and Gauthier (1989) further determined that the salt 

marsh cordgrass was of low nutritional value for snow geese in the spring. This could explain the 

more important field feeding activity of geese staging in the lower estuary compared to those using 

the traditional bulrush habitat. 

The impact of geese is markedly different between spring and fall. In October and early 

November, the birds converge on a small number of areas where hunting is prohibited. These are 

located in the traditional bulrush marshes of the St. Lawrence estuary. They visit hayfields to some 

extent but cause little damage since the plants are dormant at this time. In April and May however, 

the geese are widely distributed throughout the St. Lawrence River valley where they may stage for 

up to 7 weeks in some areas. Goose displacements are not restricted by hunting activities in the 

spring and field feeding is much more intensive. This also corresponds to the onset of growth of the 

hay, a period when plants are vulnerable to grazing. 

Studies of Goose Damage to Farmlands 

Geese feeding in agricultural fields of the lower St. Lawrence estuary in the spring showed a 

strong preference for new hayfields with young grass growth and abundant grains leftover from the 

harvest of the previous year (Gauthier et al. 1988; Reed and Cloutier 1990). In the Montmagny 

agricultural area, 50 km east of Québec City along the south shore of the estuary, hay crop loss due 

to goose grazing increased from 0.47 to 0.78 metric ton/ha between 1980 and 1985 (Bédard et al. 
59 

1986, Bédard and Lapointe 1991). Goose numbers in the study area only rose by 11.5%; the spring 

population was around 200,000 birds. However, grazing pressure went up as shown by the density of 

goose droppings which increased threefold between 1980 and 1985. Bédard (1988) noted that even 

if the behavior and distribution of snow geese were continuously changing, some elements remained 

constant. The areas intensively used in 1984 remained the same in 1988. Also, while the number of 

geese using the Montmagny area did not increase markedly, the time spent feeding in farmlands 

increased considerably. Bédard and Lapointe (1991) predicted that an increase in grazing pressure 

due to a rapid goose population growth would soon lead to unacceptable damage. They surmised that 

in the spring of 1989 when the snow goose population was 363,000 birds, some 5,000 ha of 

agricultural land were affected in southern Québec at levels similar to the ones measured around 

Montmagny in 1985 (Chapter 1). 

In 1994, a large-scale on-farm research project was launched by Ducks Unlimited Canada at 

Isle-Verte, 200 km east of Québec City. The objective of the study was to determine the effect of 

goose grazing on various seeded forage mixtures, grasses and legumes, established with or without a 

cover crop. First year results in 1995 confirmed an average yield loss of 24% or 1 metric Ton/ha for 

the first cut, and a 7 to 10 day delay in plant maturity (Filion 1998). 

Crop damage occurs from the onset of vegetative growth in the spring, in early May, until 

the geese leave for the Arctic during the last week of May. However, damage intensity is not 

uniform throughout this period. Because forage growth in spring is closely linked to the 

accumulation of growing degree-days, crop damage is proportional to the accumulation of degreedays from the beginning of the growing season until the departure of the geese. This suggests that 

damage by geese occurs when geese graze during the growing season and that maximum damage 

will occur when geese graze intensively in the last few days preceding their departure (Filion and 

Allard in preparation). This also suggests that protecting fields only at the end of the spring staging 

period could be more cost effective in terms of reducing damage. This issue is currently being 

addressed by a study at Isle-Verte. 

In addition to grazing in hayfields, geese staging in southern Québec also feed on waste 

grain. Along the St. Lawrence estuary, around Montmagny and eastward, they feed on small grain 

cereals such as oats or barley (Bédard and Gauthier 1989, Reed 1974). Expansion in the distribution 

of the geese in southwestern Québec occurred mostly in corn-growing areas where they feed heavily 

on waste corn in both spring and fall (Giroux and Bergeron 1996). Feeding on these cereal grains 

does not cause any damage because it occurs after the harvest is completed. 

Evaluation of Goose Damage and Compensation to Farmers 

The Québec Farmers Union (UPA) is asking for a control of the goose population as well as 

equitable compensation for farmers who suffer a yield loss. In some agricultural areas, compensation 

is not sufficient as some farmers no longer want to see geese in their fields. The burden of hazing 

large goose flocks from large tracts of land from dawn to dusk is certainly overwhelming for many 

farmers in the spring, a period of the year when their work load peaks. 

In Québec, unpredictable and randomly occurring damage is usually covered by crop 

insurance, for farmers that have paid their premium. As goose damage is more predictable in time 

and space, farmers cannot be covered by insurance because the premium would be too high. 

Therefore, a compensation fund corresponding to 80% of the loss incurred by farmers was set up in 

1992 following a non-recurrent five-year federal-provincial government agreement. Agricultural 

departments and wildlife agencies contributed to it from 1992 to 1994. Since then, the agricultural 

departments have been the sole contributors to the compensation fund but have claimed that wildlife 

agencies should pay for the damage. 
60
 

To obtain compensation on areas larger than 1 ha, farmers must advise the Québec Crop 

Insurance Board of suspected damage as soon as the geese depart the area in May. At that time, the 

Board initiates an evaluation process based on a collective assessment rather than an individual one 

in order to reduce the cost of the evaluation. Damages are determined on a regional basis using 30 

fields in each agricultural zone exposed to goose grazing. Early in the spring, a variable number of 

1x1m goose exclosures are set up in each field, as reference plots that will not be grazed. When the 

geese leave for the Arctic, an initial visual inspection is carried out, both in fields with exclosures 

and in those of individual farmers that reported damage, in order to confirm the extent and the 

intensity (rated as high, moderate and low) of grazing, and taking into account other factors such as 

winterkill or spring flooding. Prior to the first and the second hay cuts, two paired 1x1m plots 

(inside and outside exclosures), are clipped in each field in order to evaluate the loss in forage yield 

due to goose grazing. Average yield loss is estimated separately for fields rated high and moderate 

grazing intensities within each agricultural district. The average loss is used to compensate 

individual farmers according to the initial visual assessment of damage on their property by the 

Board. 

The most severe damage was determined in 1995, with 900,000 Can$ being claimed by 369 

producers farming 6,500 ha (Table 3-1). However, only 62% of that year’s claim was paid due to a 

lack of funds, and the farmers had to assume the difference. From 1992 to 1996, only about 70% of 

the estimated loss was compensated due to lack of funds. Furthermore, according to many farmers 

these losses are only one aspect of the problem. Yield losses could mean feed shortages for dairy 

producers who will have to buy replacement feed. Goose grazing has also been blamed for 

increasing the abundance of weeds and decreasing stand vigor which leads to more frequent 

reseeding and increased production costs. Results of the long-term study carried out at Isle-Verte 

should shed more light on these issues. 

Table 3-1. Compensation paid by the Federal / provincial plan since 1992. 

Year Producers Ha 

affected 

Estimated 

losses 

Paid 

($CDN) 

% compensated 

losses 

1992 251 8,176 466,589 373,271 80 

1993 136 3,526 211,514 169,211 80 

1994 309 10,348 534,891 399,970 74 

1995 369 16,081 904,043 560,000 62 

1996 293 11,940 844,213 560,000 66 

1997 283 11,411 485,312 485,312 80 

With the recent shift of geese towards the upper estuary (Lake Saint-Pierre) and their later 

departure from these regions, damage to forage production could increase and new crops such as 

winter cereals could be affected as well. In the St. Lawrence floodplain, some wet agricultural fields 

may also be susceptible to goose grubbing in the spring. In these situations, newly established crops 

could suffer severe losses. Whether or not they occur at random and could be covered by the crop 

insurance program remains unknown. Nevertheless, recent changes in the duration and staging 

pattern of snow geese in the St. Lawrence River valley, including along major tributaries such as the 

Richelieu River, need to be closely monitored. 
61
 

Summary – Southern Québec 

The agricultural industry is subject to a growing number of constraints and a more 

competitive world market. Farmers cannot be expected to sustain alone recurrent economic losses 

for the benefit of wildlife. On the other hand, the geese have become largely dependent on 

agricultural areas during their wintering and staging periods. Therefore, wildlife agencies must work 

hand-in-hand with agricultural agencies to develop and implement sustainable management 

measures to prevent or compensate damage due to wildlife. This is essential to maintain the social, 

cultural and economic benefits offered by the greater snow geese as a natural resource. In this 

respect, it is urgent that wildlife managers and farmers jointly design and implement measures that 

have the potential to reach these objectives as well as improve the economic benefits to affected 

farmers. To this end, government agencies will need to adapt their management programs to the 

dynamics of the snow goose population. 

MID-ATLANTIC STATES 

The widespread use of agricultural lands for feeding by greater snow geese is a relatively 

recent adaptation. Small groups of greater snow geese were first observed feeding in agricultural 

fields in southeast Virginia and northeast North Carolina during the early 1960s (Anonymous, 1981). 

The first reports of agricultural depredations in the U.S. portion of the Atlantic Flyway 

occurred during the winter of 1971-72. By the winter of 1973-74 large numbers of the birds were 

invading fields of winter wheat (Triticum aestivum) in northeast North Carolina and southeast 

Virginia (Findley, J.D., Atlantic Flyway Council, unpubl. rep., 1975). This activity resulted in 

increased complaints from local farmers. In New Jersey during the winter of 1975-76, snow geese 

used in excess of 1,500 acres of wheat, rye, sod, and pasture crops (Hall, R., NJ Fish, Game, and 

Shell Fish., unpubl. rep., 1976). Hall described the New Jersey farmers as being “relatively 

unconcerned”. 

Fear of economic loss caused added interest in reopening hunting seasons on snow geese in 

the U.S. portions of the Atlantic Flyway. It also caused state and federal wildlife agencies to begin 

to quantify and deal with the damage. During the winter of 1973-74 the FWS undertook an effort to 

haze snow geese out of fields lying within a 20x40-mile section of land, near Currituck Sound and 

Back Bay (Florschutz, O., U.S. Fish and Wildl. Serv., unpubl. rep., Washington NC, 1974). The 

hazing was discontinued because it was not considered by participating biologists to be effective in 

reducing goose usage on target fields and required a large commitment of personnel and aircraft. A 

subjective follow-up survey at the time of wheat harvest concluded that yields were reduced in fields 

which received heavy goose usage, but that the decrease was not as large as anticipated. Hartke 

(U.S.D.A., APHIS, unpubl. rep., Raleigh NC, 1986) reported over $5,000,000 in cumulative damage 

resulting from snow geese and tundra swans (Cygnus columbianus columbianus), in 7 counties in 

northeast North Carolina, during 1980-86. Wildlife managers at the time believed that this estimate 

of dollar loss, was inflated because it was based on unsubstantiated reports from the farmers 

themselves. 

The effect of grazing by related waterfowl species on the vegetative parts of small grain 

crops has been studied. Conover (1988) concluded that grazing of rye by Canada geese reduced 

subsequent biomass of leaves and roots and reduced its value as a cover crop. Allen et al. (1985) 

noted that the yield and plant height at harvest, of winter wheat fields heavily grazed by Canada 

geese, was reduced, and maturity was delayed. This occurred even if the heavy grazing occurred in 

a single episode. Kahl and Sampson (1984) observed that in some cases grazing by captive Canada 

geese reduced yield and plant height, of winter wheat. Light and moderate grazing of winter wheat 
62 

by tundra swans, near Mattamuskeet NWR, had little effect on yield and in some cases of light 

grazing, served to increase yield (Crawley, 1997). Crawley observed that heavy grazing decreased 

yield slightly. 

Greater snow geese are also making increased use of corn and soybean stubble fields to feed 

on waste grain. As would be expected, this feeding activity has not resulted in damage complaints. 

The preference of grain over traditional marsh foods by greater snow geese in the Mid-Atlantic 

states is a relatively recent event. During the late 1970s, corn, wheat, and rice were not effective in 

attracting snow geese to rocket nets at Pea Island NWR (R. Brame, N.C.S.U.,pers. comm). By 1985 

however, snow geese seeking corn began to monopolize several banding sites in North Carolina, and 

interfered with the capture of Canada geese and other waterfowl. Hill and Frederick (1997) 

observed that radio-tracked greater snow geese near Bombay Hook NWR feed heavily in cornfields 

in the early (Oct.-Nov.) and mid (Dec.-Jan.) seasons. Use of cornfields declined in the late season 

(Feb.-Mar.) as waste grain became less available and new growth of green vegetation resumed. 

Conversely the leaves of winter wheat and barley were used little in the early season but became the 

most important feeding habitat in the late season. Lesser snow geese at Desoto NWR spent more of 

their time feeding in corn stubble fields in the fall than they did in wheat fields (Frederick and Klaas, 

1982). The wheat fields were used primarily for loafing and sleeping. 

The use of waste grain may also reduce the species dependence on traditional marsh habitat 

as evidenced by declining use of some areas having mostly marsh and estuarine habitats, such as the 

Outer Banks of North Carolina. It also may have resulted in movement of geese into locations, 

where marsh resources are limited but agricultural land is abundant. Such areas include Middle 

Creek, Pennsylvania, Pocosin Lakes refuge in North Carolina, and portions of the Delmarva 

peninsula. Snow geese may leave marshland habitat used for early season feeding and roosting on 

refuges and move to farm ponds or other water bodies closer to cropland feeding areas (Hill and 

Frederick, 1997, D. Luszcz, NC Wildl. Res. Comm., pers. obs.). One developing concern over the 

increasing use of corn by greater snow geese is that the birds might interfere with management 

targeting other waterfowl species. In Maryland (W. Harvey, MD DNR, pers. comm.) and in 

northeast North Carolina, flocks of snow geese are successfully competing for standing corn, 

purchased by state agencies and set aside for diminished wintering populations of Atlantic 

Population Canada geese (Branta canadensis). 

Recent literature on greater snow goose depredations on agriculture in the Mid-Atlantic 

states is lacking. Therefore, an informal questionnaire survey was sent to wildlife agencies of states 

with wintering populations of the birds. Pennsylvania, New Jersey, Maryland, Delaware, Virginia, 

and North Carolina responded. We asked state personnel to indicate the average annual number of 

damage complaints submitted from farmers for the last three years. Less than 35 complaints 

annually were indicated from all 6 states. Pennsylvania (15) and Maryland (10) received the most 

snow goose complaints, followed by Delaware (5), and New Jersey (3, 1996-97 only). Virginia and 

North Carolina indicated only occasional complaints, while New York reported none. Damage 

occurred most often to winter wheat and barley. A few reports of damage to rye (PA) and clover 

(NJ) were also mentioned. In New Jersey, farmers growing salt hay (Spartina patens) are concerned 

about damage but have apparently learned to prevent it by using propane cannons throughout the 

winter (L. Widjeskog, NJ Div. of Fish, Game, and Wildlife, pers. comm.). Damage was reported to 

be on the increase in Pennsylvania, Maryland, and Delaware, and stable in the remaining states. 

Virginia and North Carolina reported that damage complaints were relatively high in the 1970s, but 

had dwindled to nearly none in recent years. Damage mechanisms include clipping of leaves, 

uprooting and trampling of plants, and soil compaction, particularly under wet conditions. Only 

Pennsylvania and North Carolina respondents feel that hunting snow geese alleviates damage to 

agricultural crops but Delaware and Maryland indicate that persistent harassment may be helpful. 
63 

Depredation problems arising from feeding greater snow geese are currently not a serious 

problem in the U.S. portion of the Atlantic Flyway. This is evidenced by the small number of 

complaints relative to the number of farmers accommodating the birds on their land each winter. 

Initially, farmers reacted in alarm as large numbers of the birds started using wheat fields. They 

have apparently learned to live with the damage and/or are dealing with it on their own. Damage 

complaints may not be as prevalent in the Mid-Atlantic states as they are in Québec due to the 

relative size of the farmed area in each location. In Québec the farmland acreage adjacent to roost 

sites is relatively small. In the states, farmland blocks in those areas used by snow geese may cover 

tens of thousands of acres. This may result in less intense use of individual ownership than in the 

more restricted northern farms. Also, in the U.S., farmers are not traditionally reimbursed for 

wildlife damage and thus have less incentive to report damage to the government. Timing of grazing 

may also be a factor since in the spring the tender growing plants may be far more vulnerable to 

damage than are the dormant plants of winter. In Delaware, Maryland, and portions of the other 

states which have a history of leased hunting, snow geese provide economic incentives to farmers to 

tolerate the limited damage received. As the greater snow goose population continues to increase 

however, we can anticipate increased agricultural depredations in some areas of the flyway. 

Summary – Mid-Atlantic States 

1. 	 Snow geese were first seen feeding in farmlands in the Mid-Atlantic states around 1960 and the 

first depredation complaints were received in 1972. 

2. 	 Snow geese in farm lands feed primarily on the leaves of winter wheat, barley, and rye, and on 

waste grain in corn and soybean stubble fields. In recent years grain has become the preferred 

food. 

3. Feeding by snow geese on winter wheat plants seems to reduce grain yield. 

4. 	 Gauged by the low number of complaints received from farmers, snow goose have not yet 

caused serious unacceptable damage to crops in the Mid-Atlantic states. This could become a 

serious problem as snow goose numbers increase and the tolerance level of farmers is exceeded. 

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grazing on winter wheat: an experimental approach. Proc. East. Wildl. Damage Control 

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Anonymous. 1981, A Greater Snow Goose Management Plan. Can. Wildl. Serv., Atlantic Flyway 

Counc., U. S. Fish and Wildl. Serv., Washington, D.C. 69 pp. 

Bédard, J. 1988. Les oies blanches et l'agriculture dans l'estuaire du Saint-Laurent: problèmes et 

solutions. Une opinion technique soumise au ministère du Loisir, de la Chasse et de la 

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Bédard, J. and G. Gauthier. 1989. Comparative energy budgets of Greater snow geese Chen 

caerulescens atlantica staging in two habitat in spring. Ardea 77: 3-20. 

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snow geese. Journal of Applied Ecology 28: 187-193. 

Bédard, J., A. Nadeau, and G. Gauthier. 1986. Effects of spring grazing by Greater snow geese on 

hay production. Journal of Applied Ecology, 23:65-75. 
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Conover, M.R. 1988. Effect of grazing by Canada geese on the winter growth of rye. J. Wildl. 

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McIlhenny, E.A. 1932. The blue goose in its winter home. Auk 49:279-306. 

Reed, A. 1974. Studies on the effects of grazing by wild geese in agricultural fields in the St. 

Lawrence Valley, Québec, 1974. Can. Wildl. Serv., Ste-Foy, Qué. 27pp. 

Reed, A. 1992. Management of greater snow geese in relation to crop damage: the need for a 

diversified and integrated approach. Pages 93-100 in M. van Roomen and J. Madsen. 

Waterfowl and agriculture: review and future perspective of the crop damage conflict in 

Europe. Int. Waterfowl Research Bureau Special publication No. 21. 

Reed, A. and D. Cloutier. 1990. Fréquentation des terres agricoles par les Oies des neiges et 

expérience d’appatage, Kamouraska, printemps 1989. Union des Producteurs Agricoles et 

Service canadien de la faune. Ste-Foy, Qué. 27pp. 

UPA. 1995. Minimisation des dommages occasionnés par le passage printanier des oies blanches sur 

les terres agricoles. Fédération de l’Union des Producteurs Agricoles de la Côte-du-Sud. La 

Pocatière, Qué. 40pp. 
65
 

CHAPTER 4 

POPULATION MODEL OF THE GREATER SNOW GOOSE: 

PROJECTED IMPACTS OF REDUCTION IN SURVIVAL ON 

POPULATION GROWTH RATE 

GILLES GAUTHIER, Université Laval 

SOLANGE BRAULT, University of Massachusetts 

INTRODUCTION 

The rapid and continuous increase of the greater snow goose population has brought some 

concerns about possible over-abundance problems similar to those observed in the mid-continent 

population of the lesser snow goose. We therefore undertook this modelling exercise to accomplish 

two objectives. First, we built a matrix-based model of the greater snow goose population using the 

most accurate demographic information currently available. Second, we explored the effect of a 

reduction in survival rate through projected increase in harvest rate on population growth rate. 

The data on greater snow goose population size obtained from the annual spring photo count 

along the Saint Lawrence estuary since 1965 (see Chapter 1) is by far the most accurate estimates for 

this population, and probably one of the most accurate estimate of population size of any goose 

population in North America. Although there is evidence of density dependent effects on some 

population traits (e.g. body size of birds; Reed and Plante 1997, Chapter 2), so far we have failed to 

detect any such effects on survival or fecundity (Chapter 1, Menu 1998). Moreover, the graph of 

population size (Chapter 1) strongly suggests that over the 1965-97 period, the growth rate of the 

population has been exponential. We have therefore estimated the growth rate of the population 

using an exponential model (Nt = N0 e

 rt). 

Adjusting an exponential model for the whole period yielded an estimated growth rate, λ

(λ = er

), of 1.089 (95% CI: 1.078-1.102; Fig. 4-1). Although the fit of the model is rather impressive 

(R2

 = 0.893), the distribution of the residuals along the regression line tends to be non-uniform with 

all data points for the period 1965-1968 falling below the line whereas those for the period 1970-

1980 all falling above. This is a consequence of the near stabilization of the growth rate of the 

population during the mid and late seventies, as pointed out in Chapter 1. However, this had little 

effect on the estimate of the overall growth rate of the population. Indeed, if we restrict the model to 

the most recent period (1982-1997), the estimated growth rate is very similar (λ = 1.097; 95% CI: 

1.085-1.108) even though the fit is improved (R2

 = 0.964) and the distribution of the residuals is 

uniform (Fig. 4-1). 

This analysis shows that the greater snow goose population is growing at a very rapid rate 

which has been sustained over most of the last 30 years. An average annual growth rate of 9-10% is 

twice as high as the growth rate of the mid-continent population (5%; Rockwell et al. 1997). This 

means that the greater snow goose population is doubling every 8 years on average. If this growth 

rate is maintained, the spring population will have reached 1 million birds in 2002 and 2 millions 

birds in 2010. With the annual production of young, the fall population size will exceed these values 

much sooner. In this chapter, we examine the effect of changes in harvest rate on the growth rate of 

the population under various scenarios. More specifically, we ask by how much harvest rate should 

be increased to stop the population increase (λ = 1.0) or to reduce population size at an annual rate 

ranging from about 5 to 20% (i.e. λ = 0.95 to 0.80). 
14 

66 

13 

12 

1965-97: y = 0.0857x -157.733 (R2 = 0.893) 

1982-97: y = 0.0923x -170.878 (R2

 = 0.964) 

Population size (ln(N)) 11 

10 

1965 1970 1975 1980 1985 1990 1995 

Year 

Figure 4-1. Growth of the greater snow goose population, 1965-1997. The slope of the relationship 

is an estimate of r, the annual rate of increase. The regression is calculated for the whole period 

(1965-1997) and for the period of most recent increase (1982-1997). 

THE MODELLING APPROACH 

For the purpose of the model, we have chosen to reduce the life cycle of the geese to 4 stages, 

which correspond to 4 reproductive classes (Fig. 4-2). Following the approach of Brault et al. 

(1994) and Rockwell et al. (1997), we used a birth-pulse matrix projection model that corresponds to 

the synchronous breeding patterns of the birds. We used the production of fledgling at the end of the 

summer as our measure of “fecundity”. As this was the starting point of the year in our model, the 

model had a post-breeding census formulation (Caswell 1989). Stage 1 of the model (Juvenile) thus 

extended from fledging in year t (~1 month of age) until the end of summer t+1 (~1.1 years old). 

Stage 2 extended from the end of summer t+1 to the end of summer t+2 (2.1 years old). Because 

snow geese can start to breed at 2 year of age, some birds could have non-zero fecundity already in 

the 2nd stage. However, because fecundity occurred at the very end of the stage, a survival term had 

to be included in the estimation of fecundity. Stage 3 extended from the end of summer t+2 to the 

end of summer t+3. Finally, stage 4 included all subsequent reproductive classes (t+4, t+5, ...etc.). 
67

F2 

F3 

F4 

Sa S Sa 1 

Yr 3 Yr 4+ Juvenile Yr 2

Sa

Figure 4-2. Life cycle of the greater snow goose used for the model. F = fecundity, S = survival. 

Numbers refer to stage, each stage referring to an age class (or year), starting at 1 month of age (i.e. 

at banding). Thus, Stage 1 of the model (Juvenile) extends from fledging (~1 month of age) until 

~1.1 years old. See text for details. (S1 = 1st

 year survival, Sa = adult survival). 

This model can be cast into a Leslie style matrix where demographic parameters are included 

into matrix A and the population size in a vector n. In matrix A, the first row contains the fecundity 

terms (Fi) for each stage i, and subsequent rows contain the transition probabilities (Si), i.e. the 

probability of passing from one stage to the other (= survival). In vector n, each row corresponds to 

the number of individuals in stage (i.e. age-class) i. For a 4 stages model, the matrix is: 

 0 F2 F3 F4



A = 

S1 0 0 0 

 0 S2 0 0 

 0 0 S3 S4

 n1      n = 

n2   n3      n4 

The population was modelled or “projected” through time as: n t+1 = A • n t , and the projection 

interval was of one year. The population growth rate (λ) was calculated analytically as the largest 

positive eigenvalue of the transition matrix A. This growth rate is the asymptotic rate, i.e. the rate 

that will dominate the growth pattern of the population once it reaches a stable stage distribution. 

Given that the greater snow goose population has been increasing at a relatively steady rate in the 

last decade, this growth rate value should be a good estimate of the current rate. 

Parameters F (fecundity) and S (survival) were estimated as follows. For the fecundity, we 

used the fitness component model of Rockwell to estimate this parameter (see Lepage 1997 for 

details). 
68 

Fi = BPi • (TCLi / 2) • NSi • P1i • P2i • P3i • Sa

Si = S1 for i = 1 

Si = Sa for i > 1 

where i = stage, BP = breeding propensity, TCL = clutch size, NS = nesting success, P1 = egg 

survival in successful nests, P2 = hatching success, P3 = gosling survival from leaving the nest until 

banding, S1 = 1st

 year survival, Sa = annual adult survival (age > 1). A full definition of these 

variables can be found in Table 4-1. We divided clutch size by 2 because we modelled only the 

female component and assumed a 1:1 sex ratio at hatching. 

Table 4-1. Definition of reproductive and survival parameters. 

Parameter Definition 

Breeding propensity (BP) Probability that a female alive at time t will attempt to breed. 

Total clutch laid (TCL) Total number of eggs laid by a nesting female (clutch size). 

Nesting success (NS) Probability that a nest will be successful, i.e. that at least one egg will 

hatch. 

Egg survival (P1) Probability that an egg will survive to hatching in successful nests. 

Hatching success (P2) Probability that an egg that reached hatching stage in successful nests 

will produce a gosling leaving the nest. 

Gosling survival (P3) Probability that a gosling leaving the nest survives until banding, 

which occurs just prior to fledging. 

1st year survival (S1) Probability that a bird will survive from banding at ~1 month to the 

next banding period, at ~1.08 years. 

Annual adult survival (Sa) Probability that an adult bird (> 1 year old) will survive from one 

banding period to the next. 

CHOICE OF MODEL PARAMETERS 

There are no published demographic data for greater snow geese. The only available data 

comes from the ongoing population study conducted by Gilles Gauthier, Austin Reed and their 

students at the Bylot Island colony since 1990. One disadvantage of having only one data set is that 

it comes from a single colony whereas the breeding range of the species covers a vast area of the 

Canadian Arctic islands (Chapter 1). Thus, one should keep in mind that parameters estimated at 

this one site may not always apply throughout the breeding range of the species. A second potential 

problem with the data set is that the demographic parameters were estimated over a relatively short 

time frame (5 to 7 years in most cases) for a long-lived species. However, we have shown earlier 

that growth rate of the population has been fairly stable at least since 1982, which includes the 

period during which demographic data were collected. Finally, censuses conducted every 5 years at 

the Bylot Island colony since 1983 suggest that the growth rate of this colony has kept pace with that 

of the population as a whole during this period. Thus, all these considerations suggest that the Bylot 

Island data should be fairly representative of the population as a whole. 

Most of the estimates of demographic parameters coming from the Bylot Island study can be 

found only in theses. They come from the Ph.D. work of Denis Lepage (1997) and Stéphane Menu 

(1998), and from some analyses conducted by Gilles Gauthier and Austin Reed. For these reasons, 

methodological details will be provided where appropriate. Although the best available parameter 
69 

estimates were used for the model, some of these analyses are still underway, and thus these 

estimates should be viewed as preliminary. As more data continues to accumulate from the Bylot 

Island banding program, new analyses will result in revised values for some of the parameters. 

Parameter values used in the current model can be found in Table 4-2. For one parameter (breeding 

propensity), no estimate is yet available from the Bylot Island project. We therefore used the values 

estimated for the Lesser Snow Goose at LaPérouse Bay (Rockwell et al. 1997). 

Table 4-2. Estimates of reproductive and survival parameters for greater snow geese. All values are 

estimated from Bylot Island except breeding propensity which are values taken from LaPérouse Bay 

(Rockwell et al. 1997). Note that breeding propensity and adult survival were set equal in good, 

average and bad years. 

Parameter Stage Good year Average year Bad year 

(age class) 

Breeding propensity (BP) 

Total clutch laid (TCL) 

Nesting success (NS) 

Egg survival (P1) 

Hatching success (P2) 

Gosling survival (P3) 

Survival (S) 

1 0 

2 0.35 

3 0.77 

4 0.85 

2 – 4 4.44 3.81 3.39 

2 – 4 0.89 0.71 0.14 

2 – 4 0.956 0.905 0.885 

2 – 4 0.960 0.930 0.879 

2 – 4 0.759 0.705 0.529 

1 0.50 0.35 0.12 

2-4 0.83 

One characteristic of the greater snow goose population is that it nests in a high Arctic 

environment where conditions are highly variable among years. This has a considerable effect on 

annual production of young which can vary by more than one order of magnitude between a “good” 

and a “bad” year, with periodic breeding failures (see Chapter 1; also, Lepage et al. 1996, Lepage 

1997). Because of this variability, we have selected 3 sets of parameters, corresponding respectively 

to a “Good”, “Average” and “Bad” year of reproduction. Our analyses suggest that all fecundity 

parameters will be enhanced or reduced in a good or a bad year, respectively. First-year survival 

will also differ between a good, average or bad year because environmental conditions prevailing 

during breeding may have a strong influence on survival immediately after fledging, especially 

during fall migration (Menu 1998). In contrast, adult survival appears little affected by variable 

conditions in the Arctic. Data for a good year come mostly from 1991 and 1993 whereas data for a 

bad year come mostly from 1992 and 1994. 

Details on the estimates of total clutch laid, nesting success, egg survival and hatching success 

can be found in Lepage (1997). Gosling survival was estimated with SURGE at 30% using 

recaptures of web-tagged goslings by Lepage (1997). However, this estimate is unrealistically low 

and is not supported by field observations of change in brood size during the summer. We suspect 

the presence of some sources of heterogeneity in the estimation of the recapture probability, which 

would cause an underestimation of survival with this method. We preferred to use another estimate 

of gosling survival which can be obtained from direct observations of brood size and young:adult 

ratio at banding. Change in brood size between hatch and banding gives an estimate of loss of 

goslings in broods that are not totally lost. Over the period 1991-1995, the apparent probability of 
70 

survival of goslings was 0.835 ± (SE) 0.040 (annual range: 0.734 – 0.960). This estimate, however, 

has to be corrected for broods that lost all their goslings. The proportion of broods that lost all their 

goslings (TBL) can be calculated as follows: 

TBL = 1 − NG / NA

BS / 2

where NG/NA is the gosling:adult ratio in banding catches and BS is the average brood size observed 

at the time of banding. Over the period 1990-1997, total brood failure was estimated at 0.177 ± 

0.049 (annual range: 0.0 – 0.290). Combining these two estimates yielded an average estimate of 

gosling survival (P3) of 70.5%, a value considerably higher than the one estimated by recapture of 

web-tagged goslings. The former estimate assumes that 1) all young are accompanied by two 

parents, 2) non-breeders or birds that lose their clutch before hatch are not captured at banding, and 

3) birds that lose all their young after hatch have an equal chance of being captured at banding than 

those that retained some young. Assumption 1 is likely to be true most of the time. Assumption 2 is 

also largely true on Bylot Island. Indeed, telemetry data and observations of flock of non-breeders 

show that these birds leave the island or have regained flight abilities before our banding. 

Assumption 3, however, may not always be true: birds that lose all their young tend to molt together 

and may be less likely to be caught at banding. Thus, total brood failure may be slightly 

underestimated and gosling survival overestimated with this method. 

First year survival was estimated using band-recovery analyses for birds banded on Bylot 

Island between 1990-1996. Analyses using SURVIV suggested that 1st year survival was time 

dependent with large annual variations (Menu 1998; Table 4-2). During that period, average 

survival was 0.35 and did not differ between sexes except in one year. There was no evidence of 

consistent temporal trend (i.e. long-term decrease or increase). Adult survival was estimated using 

several methods. The first one used resightings of neck-banded females. Using this method, 

survival of females was estimated at 0.83 ± (SE) 0.06. Band-recovery analyses of females only 

yielded an almost identical survival estimate (0.82 ± 0.09). Finally, band-recovery analyses of male 

and females simultaneously yielded an estimate of 0.79 ± 0.03 while accepting the hypothesis of 

equality of survival rates between sexes (Menu 1998). All these analyses accepted the hypothesis of 

constant survival rate over time and none of these values differed significantly. For modelling 

purpose, we retained the value of 0.83 (females only). 

Selection of a constant survival rate for adults in the face of a declining harvest rate has been a 

contentious issue in the population model of the mid-continent lesser snow geese (Cooke and Cooch 

1998). However, contrary to lesser snow geese, harvest rate of greater snow geese has been fairly 

stable since an abrupt decline in the mid-eighties (Chapter 1). Harvest rate has remained stable in 

recent years because total harvest has increased steadily in Canada. Thus, the hypothesis of constant 

adult survival rate over the last 10-15 years appears reasonable. 

THE MODEL 

When we used the values for a year of average reproduction (Table 4-2) in the model, we 

obtain a λA = 1.009, i.e. an almost stable population. Clearly, this suggests that average values do 

not describe very well the population, which currently has a λˆ ≈ 1.09. In contrast, using values for a 

good year yielded a λG of 1.174, a value much higher than the current growth rate. Finally, 

parameter values for a bad year yielded a λB of 0.840, indicating a declining population. We 

calculated the proportion of good, average and bad years of production based on the proportion of 

young estimated in the fall flock (Chapter 1). Good years were defined as years with >30% young in 

the fall flock, average years had >10% and < 30% young, and bad years (i.e. years of breeding 

failure) had <10% young. Since 1982 (i.e. during the most recent period of sustained population 

growth; Fig. 4-1), there were 8 good, 5 average and 3 bad years, for a ratio of 5:3:2 over a 10-year 
71 

period. Combining good, average and bad years using this ratio, we obtained through simulations2 

an average λ of 1.061 (0.995-1.124 95% CI; geometric mean = 1.049), which is still below the actual 

growth rate of the population. A ratio of 6:3:1 (good:average:bad years) was required to obtain an 

average λ of 1.104 (1.043-1.156 95% CI; geometric mean = 1.085), a value close to the actual 

growth rate of the population. 

Elasticity Analyses 

The elasticity of any element in a Leslie matrix is its proportionate contribution to the growth 

rate of the population (they sum to 1). Each elasticity can also be viewed as the proportional change 

one would expect in the growth rate given a proportionate change in that element. Changing 

elements with higher elasticity will alter the growth rate more than changing those with lower 

elasticity. 

The elasticity of the 7 elements of each matrix (good, average and bad years) is shown in Fig. 

4-3a, along with each parameter value (Fig 4-3b). As usual in long-lived animals, elasticities of 

survival are much higher than the ones of fecundity. Even in a good year of reproduction, combined 

elasticities of all fecundity elements (F2 to F4) sum up to only 0.202, compared to 0.202 for 1st year 

survival (S1) and 0.597 for adult survival (S2 to S4). This means that all fecundity parameters and 1st 

year survival contribute in about the same proportion to the population growth (20% each) but adult 

survival by itself contributes for 60% of the population growth. When reproductive success is 

reduced (average and bad year), the elasticities of all fecundity elements and survival of younger age 

classes (S1 to S3) are reduced whereas the elasticity of older adults (S4) is increased. For an average 

year, fecundity and 1st

 year survival contribute for 14% of the population growth each compared to 

72% for adult survival. Differences are much more extreme in a year where reproductive success is 

very poor. Under these conditions, adult survival contributes to as much as 97% of the growth of the 

population. 

The contribution of the survival elements of the matrix to population growth is actually 

slightly underestimated because the variable adult survival (Sa) is also included in the estimation of 

fecundity (see fecundity equation above). This occurs because we used a post-breeding census 

model (Caswell 1989). It is possible to estimate the exact contribution of adult survival to the 

elasticity of λ by partial differentiation (Rockwell et al. 1997). These contributions are termed 

“lower level elasticities” and, while they do not sum to 1 (as do higher level elasticities), they 

provide a relative measure of the impact of a proportionate change of a given parameter on 

population growth. The same procedure can be used to estimate the lower level elasticity of each 

parameter entering in the calculation of fecundity (see fecundity equation and Table 4-2). 

Results from this analysis clearly show that adult survival makes by far the largest 

contribution to population growth (Fig. 4-4). For example, a 10% reduction in adult survival in a 

good year of reproduction would result in more than a 4-fold greater reduction in λ than a 10% 

reduction in any component of fecundity. The difference would even be greater in average or bad 

years of reproduction. Contribution of the various components of fecundity to population growth is 

about equal although breeding propensity of experienced breeders appears to be the most important 

2

 We ran 1000 simulations of 30 years each. At each yearly iteration, one of the three matrices was randomly 

selected based on probabilities equal to the chosen ratio of good:average:bad years. For each simulation, the 

mean growth rate (λ) was calculated as [ln(N30)-ln(N1)]/29. The λ values from the 1000 simulations were used 

to calculate mean λ and the approximate 95% confidence limits, defined as the 2.5th and 97.5th percentiles of λ

values sorted from the lowest to the highest value. We used this method to calculate the average and 

confidence intervals of λ whenever we used a ratio of good, average and bad years, unless mentioned 

otherwise in the text. 
0.9

72 0.8

0.7

Elasticities

0.6

0.5

0.4

0.3

0.2

A 

1.0

Good (λ = 1.174)

Average (λ = 1.008)

Bad (λ = 0.840)

0.1

0.0

F2 F3 F4 S1 S2 S3 S4

1.0

0.9

B 

Parameter values0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

F2 F3 F4 S1 S2 S3 S4

Parameters

factor (Fig. 4-4). In bad years of reproduction, the contribution of all components of fecundity to 

population growth is extremely small. 

Figure 4-3. Elasticities (A) and values (B) of parameters used in the model for good, average and 

bad years of reproduction. F = fertility, S= survival. Numbers refer to stages (= age classes; see Fig. 

4-2). 

Proportion of Good, Average and Bad Years 

One could argue that the proportion of good years used in the model (60%) to adequately 

describe the current growth rate is too high. This may be true and may in fact point out to some 

limitations of the data. A first problem may be that we simply don’t have enough years of data 

available from the Bylot Island study, especially considering that we have a relatively long lived bird 

which breeds in a highly variable environment. A second problem may be related to the imprecision 

of some parameter estimates, especially adult survival and breeding propensity. Because of the very 

high elasticity of Sa, a slight error in the estimation of this parameter will have a large impact on our 

estimate of λ. To illustrate this, we have increased Sa by 1 standard error (0.83+0.06). Doing this 

results in substantially higher λ (λG = 1.239, λA = 1.070 and λB = 0.900). Mean λ then becomes 

1.154 (1.092-1.207 95% CI; geometric mean = 1.148) for a ratio 6 good:3 average:1 bad, a value 

higher than the observed population growth, and 1.107 (1.046-1.166 95% CI; geometric mean = 

1.112) for a ratio 5:3:2, a value close to the observed one. This illustrates the importance of 

estimating Sa with high precision, something that can only be achieved with long-term banding 

program, and requires large samples of banded and resighted birds. 
73

1.0

0.9

0.8

0.7

0.6

0.5

0.4

0.3

0.2

0.1

0.0

Good (λ = 1.174)

Average (λ = 1.008)

Bad (λ = 0.840)

BP2 BP3 BP4 TCL NS P1 P2 P3 S1 Sa

Parameters

Figure 4-4. Relative lower level elasticities of the reproductive and survival parameters for good, 

average and bad years of reproduction. See Table 4-1 for definition of parameters. For BP, numbers 

refer to age-classes. 

The estimation of breeding propensity (BP) is also problematic because no estimate is 

available for the greater snow goose (remember that we used the values for the lesser snow goose at 

LaPérouse Bay). We suspect that in a good year, BP may be higher than the values used, and this 

could have a large effect on λG. To illustrate this point, assume that in a good year, BP for 2, 3 and 

4+ years old are 0.7, 0.85 and 0.95 (compared to values of 0.35, 0.77 and 0.85). Under this scenario, 

λG is 1.234, a substantial increase over the original value (1.174). Conversely, we can suppose that 

BP will also decrease in a bad year. However, even if BP is reduced by 50% in a bad year (values of 

0.175, 0.385 and 0.425 for 2, 3 and 4+ years respectively), λB will suffer only a slight reduction to 

0.835 (vs 0.840 previously). This, of course, is a consequence of the large difference in the elasticity 

of BP between a good and a bad year (Fig. 4-4): in a bad year, a decrease in BP has little effect on λ

because the reproductive success is already very low. In contrast, in a good year, even a slight 

increase in BP can have a large effect in λ. Good breeding years will therefore have a 

disproportionate effect on the overall growth rate of the population. If we used these adjusted BP 

values (i.e. enhanced in good years, reduced in bad ones), the ratio of good:average:bad years 

observed in the population (5:3:2) then yields an average λ of 1.129 (1.057-1.211 95% CI; geometric 

mean = 1.074), a value closer to the observed population growth. 

At this stage, we have chosen to retain in the model the three sets of parameters (good, 

average, and bad) in a proportion 6:3:1 to explore the effect of change in harvest on population 

growth. We felt that using different values of survival or breeding propensity without further 

quantitative data was too speculative at this stage, and therefore not warranted. 

ANALYSIS OF THE EFFECT OF SPORT HUNTING ON POPULATION GROWTH 

The previous analysis showed that the most important variable affecting growth rate of the 

greater snow goose population is adult survival, followed by 1st

 year survival and fecundity. 

Because of the low elasticity value of fecundity and the difficulty of directly affecting this parameter 

through management action (e.g. large scale egg harvesting), we do not believe that such action is a 

viable option. Although egg harvesting can contribute to a reduction of population growth, its 

overall effect on growth will be small even with a large-scale program (Rockwell et al. 1997). 

Furthermore, the remoteness and widespread dispersal of greater snow geese breeding areas (see Relative lower level elasticities
74 

Chapter 1) would make large scale egg harvesting even more prohibitive than in the lesser snow 

goose. Therefore, we chose not to examine the effect of reducing fecundity, and to concentrate on 

the effect of reducing survival through an increase in sport hunting in fall, winter and spring on 

population growth. 

Estimation of Hunting Mortality 

In order to examine the effect of harvest through sport hunting on population growth, we first 

have to determine what is presently the contribution of sport hunting to the annual mortality of 

young and adult greater snow geese. Hunting mortality can be estimated from two sources: the 

regular national harvest surveys in Canada and the US, and band recovery analyses. Both sources of 

information can be biased. We did not use data band recovery analyses because: 1) band recovery 

data are available for only a small number of years (since 1990) and, 2) reporting rate of banded 

birds that are shot is poorly known, especially in Québec where it could be different from the U.S. 

We chose to use data from the harvest survey to estimate hunting mortality. An estimate of 

hunting mortality is provided by the harvest rate (HR), which is the ratio between the total number of 

birds killed by recreational hunting and the total fall population size. In Chapter 1, we estimated 

annual harvest rate for young and adults for the period 1968-95. Our analysis showed that harvest 

rate has been relatively stable since 1985, following an abrupt drop in 1984-85. We therefore used 

harvest rate data since 1985 as an index of hunting mortality. Rockwell et al. (1997) did not use 

harvest rate to estimate hunting mortality in lesser snow geese because they argued that both 

population size (obtained from mid-winter counts) and harvest were merely indices, and therefore 

poor estimators of true values (see also Cooke and Cooch 1998). However, we believe that these 

limitations do not apply to greater snow geese. First, we used population size data from the annual 

census conducted every year in the St. Lawrence estuary, Québec, which is a total population count 

much more accurate than the mid-winter counts (see Chapter 1). Second, the accuracy of harvest 

estimates through the national harvest surveys has increased over the years. Third, because the 

range of the greater snow goose is restricted to the Atlantic Flyway and overlaps little with other 

snow goose populations, harvest estimate is not likely to be contaminated by other populations. 

Annual survival (S) of birds from one banding period to the next (i.e. from late summer to late 

summer) can be seen as the product of three independent events: 

S = SNA1 • SH • SNA2

where SNA1 is the probability of surviving to natural mortality (MNA1) occurring during the fall 

migration (i.e. before the hunting season), SH is the probability of surviving to hunting mortality 

(MH), and SNA2 is the probability of surviving to natural mortality after the fall migration, i.e. during 

and after the hunting season (MNA2; this assumes that hunting mortality is additive to non-hunting 

mortality). In adults, we assumed that mortality during the fall migration is negligible and we set 

this value equal to 0 (SNA1 = 1). Over the period 1985-95, the average annual harvest rate (= MH) of 

adults has been 0.06 (Chapter 1). Using our estimate of annual survival (Sa = 0.83), we estimated 

natural mortality in adults at 0.12 (Table 4-3), suggesting that hunting mortality accounts for about a 

third of annual mortality of adults. 

In contrast to adults, assuming that mortality of young is negligible during the fall migration is 

clearly inappropriate because natural mortality during this period can be very high (Menu 1998). 

We estimated hunting mortality of young separately for good, average and bad years because of 

large annual differences in fall migration survival and, to a lesser extent, in harvest rate (Table 4-3). 

Data for fall migration survival is available for 4 years (1993-96) and we used the lowest and highest 

value for our estimate of good and bad years. Harvest rate (= MH) of young was 0.28 in good years 

(about 47% of total mortality), 0.32 in an average year (37% of total mortality) and 0.37 in a bad 

year (21% of total mortality). However, values of post-migration natural mortality for young appear 
 

75 

to be too low (Table 4-3). We suspect that fall migration mortality and/or the hunting mortality are 

biased high although we have no means to correct for this potential bias. 

Table 4-3. Estimation of hunting mortality in young (1st

 year) and adult greater snow geese for years 

of good, average and bad production of young based on harvest rate data calculated from national 

harvest surveys in Canada and the U.S. 

Year Annual 

mortality 

Fall migration 

natural mortality 

Hunting mortality 

(Harvest rate) 

Post-migration 

natural mortality 

Total natural 

mortality 

Adult 

All years 0.17 0.00 0.06 0.12 0.12 

Young 

Good 0.50 0.28 0.28 0.04 0.31 

Average 0.65 0.45 0.32 0.07 0.49 

Bad 0.88 0.81 0.37 0.03 0.81 

Annual Mortality (M): from Table 4-2. 

Fall migration natural mortality (MNA1): data are from Menu (1998). To contrast mortality during the 

fall migration in a good, average and bad years we used data for the 1995 (good), 1996 (average) and 

1994 (bad) fall migration. 

Harvest rate (HR): data are from Chapter 1, for the period 1985-1995. For young, harvest rate was 

calculated separately for years of good (>30% young in fall flock), average (>10% and < 30%) and 

bad (<10%) production during the period 1985-95. 

 1− M  Post-migration natural mortality (MNA2): MNA2 = 1 −





(1− MNA1) • (1− HR)



Total natural mortality (MNA): MNA = 1 − [(1− MNA1) • (1− MNA2)]

Scenarios for Increased Harvest 

We simulated three scenarios of increased harvest through sport hunting on the greater snow 

goose population growth: 

A. Increase in hunting mortality of adults only 

B. Increase in hunting mortality of young only 

C. Increase in hunting mortality of adults and young simultaneously 

To achieve this, we increased hunting mortality by increments of 25% from 0 to 200%. This 

corresponds to multiplying hunting mortality by a factor ranging from 0 (no increase) to 3.0 (200% 

increase). This factor is referred to as the “Proportional increase in hunting mortality”. Because 

hunting mortality varies between good, average and bad years, we repeated the simulations for each 

of these matrices. We also combined the results of the good/average/bad matrices in a ratio 6:3:1, 

the ratio that best explained the current population growth (see above). 

For adults, increasing hunting mortality by a factor of 3 (i.e. from the current value of 0.06 to 

0.18) meant that Sa in the Leslie matrix model was reduced from 0.83 to 0.72 (Table 4-4; we set 

natural mortality constant at 0.12, i.e. we assumed that hunting mortality was completely additive). 

Because the fecundity terms included adult survival (i.e. post-breeding census, see equation for 

fecundity above), we had to adjust the F2, F3 and F4 values each time Sa was modified, taking the 

different fecundity values in good/average/bad years (Table 4-2). For young, we increased hunting 

mortality from 0.28 to 0.84 (3-fold increase) in a good year (1st year survival, S1 = 0.50 to 0.11, 

Table 4-4), from 0.32 to 0.96 in an average year (S1 = 0.35 to 0.02), and 0.37 to 1.00 in a bad year 

(S1 = 0.12 to 0.0). One should note that increasing the current hunting mortality by a similar factor 
76 

in young and adults results in a greater reduction in the 1st year survival than in adult survival (Table 

4-4). This is because the hunting mortality is up to 6 times higher in young than in adults. Indeed, 

we showed in Chapter 1 that the average annual kill for the last 5 years is 44,500 young and 25,500 

adults, almost a ratio 2:1 (Y:A). In essence, scenario C (similar increase in hunting mortality for 

adult and young) assumes that this age ratio is maintained in the harvest, in contrast to scenarios A 

(increase in hunting mortality of adults only) or B (increase in hunting mortality of young only) 

which assume that this ratio declines (scenario A) or increases (scenario B). Therefore, increasing 

hunting mortality by a similar factor in young and adults (scenario C) will result in a much higher 

increase in absolute number of young birds killed compared to adults. 

The effect of increasing hunting mortality on population growth rate (λ) is presented in Table 

4-4 and Fig. 4-5. We note that an increase in hunting mortality of young causes a larger reduction in 

population growth rate than a similar increase in adult mortality for good and average years (Fig. 4-

5; this does not occur in a bad year because production of young is so low that increasing their 

hunting mortality will have little impact on population growth). This surprising result appears in 

contradiction with our earlier statement that adult survival is the parameter that contributes the most 

to population growth because of its high elasticity. This difference stems from the fact that hunting 

mortality is about 4 to 6 times higher in young than in adults. Therefore, increasing hunting 

mortality by the same factor in both groups will result in a much more substantial decrease in 

survival of young compared to adults, and hence will have greater impact on λ. 

We believe that a liberalization of hunting regulations for greater snow geese will likely affect 

both adult and young and that it will be difficult to achieve a disproportionately large increase in 

hunting mortality of adults. Therefore, scenario C, which assumes that any liberalization in hunting 

regulation will affect young and adult equally (and thus maintain the current hunting bias in favor of 

young) is probably the most realistic. Under the model that best describes the current population 

growth of greater snow geese (i.e. combination of good/average/bad years in proportion 6:3:1, Fig. 

4-5), a stabilization of the population (i.e. λ = 1.0) may be achieved by increasing hunting mortality 

by about 60% (i.e. 1.6x on the x axis; see also Table 4-4). Similarly, a doubling of the current 

hunting mortality would lead to a λ = 0.938, or a population decreasing at about 6%/year. These 

values would reflect the actual situation over a long time period. However, because good, average 

and bad years of reproduction can occur in a random fashion, in the short term (i.e. over a 3 or 4-

year period), greater snow geese could experience a run of “good” reproduction years just by chance. 

If this was the case, then scenario C for the good reproduction years should also be considered. 

Under these conditions, a stabilization of the growth of the population (λ = 1.0) would require that 

harvest be increased by a factor 2.1 (i.e. at least a 100% increase). 

Until now, our discussion has focused on the increase in hunting mortality required to reduce 

current population growth. However, our estimation of hunting mortality is based on a data set 

(national harvest survey) that may be subject to biases; it also requires additional assumptions (e.g. 

that hunting mortality is additive) and the estimation of additional parameters (e.g. survival during 

the fall migration, Table 4-3). Although we believe that our estimate of hunting mortality is the best 

value that can be obtained, given the information available, its precision is probably low and it may 

be biased. However, an alternative way to look at this problem may be to directly examine the 

relationship between survival rate and λ (Table 4-4). This will tell us by how much we have to 

reduce adult and/or young survival to achieve targeted population growth rate. This approach could 

be especially useful if one wants to monitor the success of our management actions, i.e. by how 

much survival rate has actually been reduced once harvest regulation have been liberalized. 

Table 4-4. The effect of increase in hunting mortality (multiple) on total survival of adult and young 

greater snow geese, and on the population growth rate (λ) if only adult mortality (scenario A), only 

young mortality (scenario B) or both (scenario C) are increased. The analysis is repeated for good, 
77 

average and bad years of reproduction, and for the combination of these 3 years (in ratio 6 good : 3 

average : 1 bad) that best describes the current growth of the population. 

Increase in Survival λ 

hunting mortality Adult Young Scenario A Scenario B Scenario C 

Good year 

x1 0.830 0.500 1.174 1.174 1.174 

x1.25 0.817 0.451 1.160 1.151 1.137 

x1.5 0.804 0.403 1.146 1.126 1.099 

x1.75 0.790 0.354 1.131 1.100 1.058 

x2 0.777 0.305 1.117 1.072 1.017 

x2.25 0.764 0.257 1.103 1.043 0.975 

x2.5 0.751 0.208 1.088 1.011 0.931 

x2.75 0.737 0.160 1.073 0.977 0.883 

x3 0.724 0.111 1.059 0.939 0.833 

Average year 

x1 0.830 0.350 1.009 1.009 1.009 

x1.25 0.817 0.308 0.995 0.992 0.978 

x1.5 0.804 0.267 0.982 0.974 0.948 

x1.75 0.790 0.226 0.968 0.956 0.916 

x2 0.777 0.185 0.955 0.937 0.883 

x2.25 0.764 0.144 0.941 0.916 0.850 

x2.5 0.751 0.103 0.928 0.894 0.815 

x2.75 0.737 0.062 0.914 0.870 0.778 

x3 0.724 0.021 0.900 0.844 0.739 

Bad year 

x1 0.830 0.120 0.840 0.840 0.840 

x1.25 0.817 0.102 0.827 0.839 0.826 

x1.5 0.804 0.085 0.814 0.837 0.811 

x1.75 0.790 0.067 0.800 0.836 0.796 

x2 0.777 0.049 0.787 0.834 0.781 

x2.25 0.764 0.032 0.774 0.833 0.767 

x2.5 0.751 0.014 0.761 0.831 0.752 

x2.75 0.737 0.000 0.747 0.830 0.737 

x3 0.724 0.000 0.734 0.830 0.724 

6 Good : 3 Average : 1 Bad years 

x1 0.830 0.417* 1.104 1.104 1.104 

x1.25 0.817 0.373* 1.071 1.069 1.052 

x1.5 0.804 0.330* 1.053 1.046 1.015 

x1.75 0.790 0.287* 1.042 1.025 0.976 

x2 0.777 0.244* 1.019 1.000 0.938 

x2.25 0.764 0.200* 1.006 0.974 0.896 

x2.5 0.751 0.157* 0.990 0.948 0.854 

x2.75 0.737 0.114* 0.971 0.919 0.810 

x3 0.724 0.073* 0.957 0.889 0.767 

* Unlike adult survival, young survival differs among good, average and bad years. Therefore, the 

weighted average under a combination of 6 good: 3 average: 1 bad is only given as a general 

indication since survival is here time dependent. 
78

1.20 

1.15 

1.10 

1.05 

1.00 

0.95 

0.90 

0.85 

0.80 

0.75 

0.70 

1.15 

1.10 

1.05 

1.00 

0.95 

0.90 

0.85 

0.80 

0.75 

0.70 

0.65 

1.0 1.5 2.0 2.5 3.0 1.0 1.5 2.0 2.5 3.0 

Good year 

A: Adult only 

B: Young only 

C: Adult + Young 

Average year 

Bad year 0.6 G - 0.3 A - 0.1 B 

Proportional increase in hunting mortality 

Figure 4-5. The effect of increase in hunting mortality (multiple) on growth rate (λ) of the greater 

snow goose population in good, average and bad years of reproduction, and for the combination of 

these 3 years (in ratio 6 good : 3 average : 1 bad) that best describes the current growth of the 

population. Three scenarios are presented: increase in hunting mortality of adult only (A), young 

only (B) and both adult and young at the same time (C). For the combination 6:3:1, the 95% 

confidence interval of each estimate is presented. 

SUMMARY 

1. A model of exponential growth rate fitted well the greater snow goose population size data over 

the last 30 years. The average growth rate of the population over this period is estimated at about 

9-10% (1965-1997: λ = 1.089; 1982-1997: λ = 1.097). This means that the greater snow goose 

population is doubling about every 8 years. 

2. To model the population, we used a birth-pulse matrix projection model (i.e. Leslie-style matrix) 

using the production of fledglings at the end of the summer as our measure of “fecundity” (i.e. 

post-breeding census formulation). We defined 4 stages (i.e. age classes). Parameter estimates 

for the model all came from the on-going population study of greater snow geese on Bylot 

Island, except for breeding propensity for which we used values from the lesser snow goose at 

LaPérouse Bay. Some of these estimates, however, should be viewed as preliminary. 

3. To adequately describe the current population growth rate, we had to define 3 matrices, each 

corresponding to conditions prevailing in a good, average and bad years of reproduction. All Population growth rate (λ) 
79

fecundity parameters and 1st year survival differed among these 3 matrices, but not adult 

survival. A ratio of 6 good: 3 average: 1 bad years was required to obtain a λ of 1.104, a value 

close to the actual growth rate of the population. This corresponded relatively well to the 

proportion of good:average:bad years of reproduction observed in recent years in this population 

(ratio of 5:3:2), though not perfectly, probably reflecting the imprecision of some parameter 

estimates. 

4. The elasticity analyses showed that the most important variable affecting growth rate is adult 

survival, followed by 1st

 year survival and fecundity. Adult survival was estimated at 0.83 

(constant over time) and young survival at 0.5 (good year), 0.35 (average) and 0.12 (bad). 

5. We used data from the national harvest survey in Canada and the US to estimate hunting 

mortality. We estimated that hunting mortality of adults was 0.06, about a third of total annual 

mortality (0.17). For young, we estimated hunting mortality at 0.28 in a good year (about 47% of 

total mortality), 0.32 in an average year (37% of total mortality) and 0.37 in a bad year (21% of 

total mortality). 

6. Under the model that best describes the current population growth of greater snow geese (i.e. 

combination of good/average/bad years in a ratio of 6:3:1), a stabilization of the population (i.e. 

λ = 1.0) should be achieved by increasing hunting mortality by about 60% (i.e. 1.6x actual 

harvest). However, if greater snow geese were to experience a run of “good” years of 

reproduction, a stabilization of population growth would require that harvest be increased by a 

factor 2.1 (i.e. at least a 100% increase). 

7. During the period of stabilization of population growth (1975-85), harvest rate was estimated at 

25%, compared to 12% now. This “natural experiment” suggests that a 2-fold increase in 

hunting mortality is required to bring stability. Our model predicted that stabilization could in 

theory be achieved by increasing hunting mortality by a factor of 1.6. On the other hand, under 

good breeding conditions, the model also predicted that a 2-fold increase in harvest rate is 

required. However, we should be cautious in this comparison because: 1) harvest data may have 

some biases (which may have been larger in the earlier years compared to later ones), and, 2) 

demography of the population (i.e. natural mortality, fecundity, etc) may have changed. 

8. Our analysis emphasizes the importance of long-term studies to obtain reliable estimates of 

demographic parameters. At the same time, it points out the limitations of some of the current 

estimates (e.g. breeding propensity, hunting mortality), and underlines the need to improve the 

quality of these estimates. For instance, as additional banding data accumulate, it may be 

possible to obtain a better estimate of hunting mortality using recovery rates instead of harvest 

surveys. Finally, monitoring adult and young survival through a continued banding program 

may be the best way to monitor our success in increasing mortality, and thus reducing 

population growth, through a liberalization of hunting regulations. 

ACKNOWLEDGMENTS 

We thank Rocky Rockwell, Jim Nichols, Evan Cooch and Mark Lindberg for their thorough 

comments on this paper. 

LITERATURE CITED 

Brault, S., S. Boyd, F. Cooke, and J. Takekawa. 1994. Population models as tools for research 

cooperation and management: the Wrangel Island snow geese. Trans. N. Am. Wildl. Natur. 

Conf. 59:79-90. 
80 

Caswell, H. 1989. Matrix population models. Sinauer Assoc., Sunderland, MA, 328pp. 

Cooke, F., and E.G. Cooch. 1998. Impact of hunting on population growth in mid-continent lesser 

snow geese. Unpublished manuscript. 

Lepage, D. 1997. Variations saisonnières du succès reproducteur chez la Grande Oie des neiges 

(Chen caerulescens atlantica). Ph.D. thesis, Université Laval, Québec. 

Lepage, D., G. Gauthier, and A. Reed. 1996. Breeding site infidelity in greater snow goose: a 

consequence of constraints on laying dates? Can.J. Zool.74:1866-1875. 

Menu, S. 1998. Survie de la grande oie des neiges: aspects méthodologiques et implication dans la 

dynamique de population. Ph.D. thesis, Université Laval, Québec. 

Reed, A., and N. Plante. 1997. Decline in body mass, size, and condition of greater snow geese, 

1975-1994. J. Wildl. Manage. 61:413-419. 

Rockwell, R.F., S. Brault, and E.G. Cooch.1997. Dynamics of the mid-continent population of lesser 

snow geese - projected impacts of reduction in survival and fertility on population growth 

rates. Pages 73-100 in B.D.J. Batt, ed. Arctic ecosystems in peril: report of the Arctic goose 

habitat working group. Arctic Goose Joint Venture Special Publication. U.S. Fish and Wildlife 

Service, Washington D.C. and Canadian Wildlife Service, Ottawa, Ont. 
81

CHAPTER 5 

JEAN-FRANÇOIS GIROUX, Université du Québec à Montréal 

BRUCE BATT, Ducks Unlimited, Inc. 

SOLANGE BRAULT, University of Massachusetts 

GARY COSTANZO, Virginia Dept of Game & Inland Fisheries 

BERNARD FILION, Ducks Unlimited Canada 

GILLES GAUTHIER, Université Laval 

DENNIS LUSZCZ, North Carolina Wildlife Resources Commission 

AUSTIN REED, Canadian Wildlife Service 

CONCLUSIONS AND MANAGEMENT RECOMMENDATIONS 

CONCLUSIONS 

1. Under current management strategies the greater snow goose population will soon 

exceed 1 million birds and continue to double every eight years. 

The average growth rate of the greater snow goose population since 1982 has exceeded 

9% which is nearly twice the rate observed for mid-continent lesser snow geese (Rockwell et al. 

1997). The population has increased from less than 50,000 geese during the springs 1965-1968 to 

more than 650,000 in 1996-1997. At this rate, the spring population could reach 1 million birds 

by 2002 and 2 million by 2010. Productivity, as measured by age ratios (% juveniles) in the fall 

flight, has averaged 24% over the period 1965-1997, showing no long-term trend. 

Reduced harvest rates have been the main factor contributing to continued population 

growth since the mid-1980s. The current 12% harvest rate is about one half of the rate that 

prevailed when the population was near stability during the 1975-1983 period. Non-hunting 

mortality during the non-breeding season may have remained low or even decreased as the geese 

have gradually discovered a supplementary food supply on agricultural land. Another factor in 

continued population growth is that supplemental agricultural foods in spring improve body 

condition, thereby improving snow goose recruitment. 

2. Expansion of greater snow geese into new habitats has not kept pace with increases in 

the population in some portions of the range. 

During the 1960s and 1970s the adaptation to exploit agricultural lands for feeding 

significantly expanded snow goose wintering habitat. More recently, some additional expansion 

of wintering range has been recorded, but the main result of population growth has been a build 

up of numbers in Delaware and Maryland, and since 1991 in New Jersey, New York, and 

Pennsylvania. Numbers have not increased in the southern portion of the winter range in North 

Carolina. 

The main spring staging area along the St. Lawrence valley has expanded from a 40-km 

portion of the river to more than 400-km, and now extends along the Richelieu River to northern 

Lake Champlain. Similar expansion has been observed in fall but the most important change has 

been the increasing number of birds that are now flying directly to the U.S. without stopping in 

southern Québec. The fall staging period of individual birds along the St. Lawrence estuary is 

also shorter now than 15 years ago. 
82

During the last three decades, only a few new breeding areas have been discovered and 

the overall breeding range has expanded only slightly. The most important result of the increase 

in population and the failure to colonize new breeding areas has been increasing densities at main 

breeding colonies. 

3. Greater snow goose populations have reached carrying capacity in some marshes within 

staging and wintering areas and could exceed it in Arctic breeding areas in the near 

future under current management. This may be detrimental to the snow geese 

themselves and to other wildlife with which they share these habitats. 

The feeding activities of large numbers of greater snow geese have a significant influence 

on wetland communities throughout their range. Habitat change caused by snow geese may favor 

some species of wildlife but are probably harmful to others. There is a growing concern that 

greater snow geese may displace Atlantic Population Canada geese on some staging areas. Overabundant greater snow geese may interfere with management of other waterfowl species by 

monopolizing winter banding sites and feeding sanctuaries developed for other species. 

Arctic breeding habitats are likely the most limiting of any used by the geese during their 

annual cycle. Actual estimates at Bylot Island, the largest breeding colony, indicate that the 

population is already over 50 percent of the carrying capacity. Significant declines in body mass, 

structural size, and condition of goslings during the fall in southern Québec over a 19 year period 

(1975-1994) indicate that density dependent effects on growth are likely occurring during the 

brood rearing period. Extensive damage to arctic habitats, such as those resulting from lesser 

snow geese feeding along the Hudson Bay coast has not yet been observed for greater snow 

geese. However, as carrying capacity is reached and exceeded, long-term, even irreversible 

damage to these fragile habitats will likely occur. 

Greater snow geese are affecting marsh habitats in migration and wintering areas. Along 

the St. Lawrence River, recent observations of bulrush marshes used by geese during their fall 

and spring migration have shown that the carrying capacity of some of these marshes has been 

reached. The most deteriorated marshes occur within bird sanctuaries where geese concentrate 

their feeding activities in fall. Plant species composition changes, declines in plant production, 

and marsh erosion have occurred. These marshes, however, could recover within a few years if 

the distribution of geese was modified by periodically changing location of sanctuaries. Snow 

geese have not had a significant effect on cordgrass marshes along the St. Lawrence River. 

Cordgrass marshes used by wintering geese along the U.S. Atlantic coast appear to be 

more affected. Eat-outs have been reported for a long time and it may take several years before 

these marshes become fully vegetated again. The effect of eat-outs on other wildlife species is a 

major concern in some refuges, which are among the best bird-watching spots in the eastern U.S. 

The loss of some marsh invertebrates that support wintering American black ducks is also a 

concern. Nevertheless, areas of eat-outs have not increased proportionally with the demographic 

expansion of the population because geese are not utilizing additional salt marsh habitats in 

proportion to their increasing numbers. Rather they are increasing in density on their traditional 

sites, exerting even greater grazing pressure on already damaged habitats. Snow geese are 

making greater use of agricultural habitats, in most parts of the wintering range. 
83 

4. Increasing numbers of greater snow geese feeding in agricultural fields causes economic 

losses for farmers and will increasingly interfere with wildlife management programs 

for other species. 

The increasing tendency of greater snow geese to feed on agricultural crops has 

undoubtedly been the primary reason for the rapid increase in numbers since 1960. Food 

supplies, during the spring migration and wintering periods, are less likely to be limiting factors 

and breeding geese now have advantages in body condition, probably not realized by previous 

generations of the birds limited to marsh feeding during winter. One other consequence of 

increasing numbers of field feeding greater snow geese is crop depredation problems in southern 

Québec, and to a lesser extent in the U.S. 

Damage to hay fields in early spring is the most serious problem in Québec. Somewhat 

less than 1 million dollars of damage is recorded annually along the St. Lawrence estuary but 

these losses affect individual farmers who are only partially compensated. The problem seriously 

affects a non-negligible number of farmers who have been unable to recuperate losses by renting 

out hunting rights, and cannot (for climatic reasons and because of specific forage requirements) 

grow other types of crops. 

Farmers in the Mid-Atlantic states suffer losses to winter wheat, barley, rye, and salt hay. 

However, recent complaints to government have been minimal. U.S. farmers are not 

compensated for such losses, and apparently accept or have learned to cope with the losses. Fees 

for hunting leases may be a mitigating factor in some areas. 

A concern of wildlife agencies in both countries is the affect that overabundant geese 

have on relationships with the farming community. These relationships are essential for the 

proper management of waterfowl, other game, and non-game wildlife in agricultural habitats. 

Moreover, part of the solution to manage greater snow geese requires the participation of farmers. 

MANAGEMENT RECOMMENDATIONS 

The Arctic Goose Habitat Working Group recommends that the population be 

stabilized by 2002 at a population level of 1 million or less. 

With a 9% annual increase, the Arctic Goose Habitat Working Group recommends that 

the growth of the population of greater snow geese be stopped by the year 2002. In their 

population model, Gauthier and Brault (Chapter 4) calculated that increasing hunting mortality by 

75% could attain a stabilization of the population. This was based on a scenario of 6 good, 3 

average and 1 bad year of reproductive success over a 10-year period. To stabilize the population 

by 2002, we have in fact only 3 years to control the population (1999-2001). Based on the 6:3:1 

scenario, we could expect by chance to get 2 good and 1 average years during our initial attempt. 

We believe that we should be less optimistic and take the worst scenario, namely a succession of 

3 good years. According to the Gauthier and Brault model, stopping growth during good years 

requires a doubling of hunting mortality, or an increase of harvest rate from 12 to 24%. This 

means harvesting approximately 143,000 birds each year compared to the annual average of 

71,500 recorded since 1990. By the time this is achieved, hopefully in the next 3-4 years, the size 

of the spring population should be between 800,000 and one million birds. 

Following this short-term objective and based on an adaptive management process, 

reduction of the population could become a mid term objective if natural habitats continue to 

deteriorate or if measures taken to reduce crop depredation do not achieve the desired results. The 
84 

target population should be based on a scientific evaluation of habitat carrying capacity. We 

believe that breeding habitats, which are the most fragile, should get the first attention. We 

recommend that the carrying capacity of the spring staging grounds also be estimated, especially 

along the St. Lawrence estuary where crop depredation is important. Finally, the carrying 

capacity of wintering salt marshes should also be evaluated. These estimates should be 

determined during the period of population stabilization. The lowest carrying capacity estimates 

among the three habitats should then guide the establishment of the target population. 

If the spring population is permitted to become greater than 1,000,000 birds, the Working 

Group believes that adverse ecological effects will be an inevitable result and that population 

control will be increasingly difficult. It is therefore imperative to initiate the proposed measures 

as soon as possible. Recognizing that hunters alone may not be able to control greater snow goose 

numbers, other methods to increase mortality and decrease productivity of adult geese should be 

simultaneously explored. 

SUGGESTED STRATEGIES 

1. Implement a greater snow goose communication program. 

A comprehensive communication plan aimed at informing all potentially affected 

interests about the greater snow goose problem and the need for action should be developed and 

implemented immediately. The experience gained from the successful communications and 

public review efforts with the mid-continent lesser snow geese will provide excellent guidance 

for a communications effort with greater snow geese. In Canada, such information would be 

required in both official languages and special care should be taken to make the information 

available to the Nunavut Inuit. 

2. Increase the interest and effectiveness of recreational snow goose hunters. 

Snow geese have proven to be much less vulnerable to traditional waterfowl hunting 

techniques than most other species of waterfowl. As a result, harvest success has declined to the 

point where many hunters have lost interest in the sport, or if they have continued to hunt snow 

geese, harvest fewer birds. In response, both countries have greatly liberalized harvest 

regulations for greater snow geese, but the desired increase in hunter interest and success has not 

occurred. 

The U.S. harvest is low despite a much longer annual period when geese are available to 

U.S. hunters in comparison to Canadian hunters. Moreover, the increasing number of geese overflying southern Québec directly to the U.S. has not improved the U.S. harvest which has 

remained constant since 1990. Expansion of areas used by geese during migration in southern 

Québec may have contributed to a slight increase in harvest in that province. The proportion of 

the total kill in Québec compared to the U.S. has increased from 66% in 1988-92 to 70% in 1993-

97. 

Efforts should be made to encourage current and former goose hunters to be active and to 

encourage new recruits to the sport. Greater hunting success may also help to achieve these 

objectives. Some hunters and parts of the general public have expressed concern over the ethics 

of using some hunting practices, particularly those heretofore illegal, to harvest more snow geese. 

This is a serious issue that must be addressed by the communications program. We believe that 

the larger ethical question relates to our responsibility to protect the ecosystems that will almost 

definitely undergo near irreversible damage if goose population growth is not arrested. A 
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distinction should be made between regular snow goose hunting seasons under traditional basic 

regulations, and conservation hunts which would take place when no other waterfowl hunting is 

allowed. 

Some suggestions for increasing hunter interest include reciprocal licenses between states 

and provinces for snow goose hunters, programs to increase access to private and public hunting 

areas, and distribution of information on successful hunting techniques. Bag limits should remain 

liberal and information on better use of harvested geese (recipes etc.) would be an incentive. A 

promising measure might be to allow hunting of snow geese in/near fields where portions of 

crops are left after harvest. It should be only allowed during some periods at special designated 

hunting areas for snow geese. This would get general support among hunters and may help 

sustain interest in snow goose hunting. The use of live decoys should also be considered. Less 

controversial techniques, like electronic callers and extension of shooting hours should be 

immediately allowed in tightly controlled snow goose hunts on public lands or after other 

waterfowl seasons have closed. In Québec, ways should be explored to make sneaking 

(sometimes called creeping) legal and more acceptable to hunters. Hunter support of these 

programs is essential. It is crucial to clarify for hunters and the general public how important 

their participation is in solving this problem of overabundant snow geese. 

3. Promote and facilitate subsistence harvest. 

There is potential for an increased impact from egging or subsistence harvest on the 

greater snow goose population, although only a few small communities are located near breeding 

colonies. Programs should be developed to encourage and assist Inuit communities of the 

Nunavut to increase their harvest of snow geese. These programs might include subsidies for 

travel and equipment, transport of harvested geese to other communities for barter, or perhaps 

even development of programs to commercially produce and export snow goose meat products 

under strict guidelines. The harvest on the fall staging grounds in northern Québec might also be 

increased, but is hampered by the birds stopping in the central portion of the Ungava Peninsula, 

far from communities which are generally on the coast. 

4. Initiate conservation hunts that utilize hunting periods and techniques distinct from 

traditional recreational hunting. 

Conservation hunts should be implemented to allow hunters to harvest greater snow 

geese after the period when normal waterfowl hunting seasons have been closed. This is an 

important law enforcement consideration because it must be unambiguous that the hunters only 

have the right to pursue snow geese during this period and that the harvest of any other wildlife 

species is illegal. A variety of special measures, such as those mentioned in Section 3 above, 

could be allowed during these hunts. Conservation hunts could occur during the regular season 

frameworks which end on March 10th or beyond that date by special understanding between 

Canadian and American officials responsible for the Migratory Birds Treaty. The critical issue is 

that no other species could be harvested. 

5. Manage snow goose use of public and private lands to increase hunter success, minimize 

impacts of natural wintering and staging habitats and reduce agricultural depredation. 

Sanctuaries, particularly federal, provincial, and state wildlife areas and refuges, and 

adjacent private lands are heavily used by greater snow geese within the Atlantic Flyway. An 

evaluation should be made of each sanctuary complex to assess the impacts of management on 

regional snow goose harvest. Management strategies should be developed which make 
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sanctuaries useful tools for increasing harvest of snow geese rather than simply providing 

resources which boost snow goose condition and productivity. Management programs that 

provide for non-disturbed feeding or otherwise restrict movement of snow geese to hunted areas 

are undesirable and should be revised. Systems of small sanctuaries that are alternatively hunted 

may be useful to enhance movement of snow geese. Managers could provide further 

encouragement to hunters by making available decoys and other equipment or making 

improvements that facilitate access to hunting locations. 

Management should strive to maintain traditional migration patterns between regions and 

actions designed to increase local harvest should not be made at the expense of harvest in other 

areas. In southern Québec, for example, managers are especially concerned with recent increases 

in the proportion of birds that bypass the region and fly directly to the U.S. 

Active management of snow goose movements and habitat use should also be used to 

minimize the impacts of large numbers of snow geese on natural marshes and agricultural crops. 

More frequent movements of geese, whether caused by purposefully applied disturbance, or 

hunting activities, will reduce habitat and crop damage by preventing localized long-term use of 

individual areas and will limit, to some extent, the accumulation of nutrient reserves. Monitoring 

of marsh condition in areas of high snow goose numbers will indicate where management actions 

can help shift goose use from highly or over-used areas to marshes able to withstand additional 

feeding activity. 

Achievement of this strategy will require development of well-coordinated programs in 

individual provinces, states, and regions to influence snow goose movements and use of habitats. 

The actual management programs may involve rotation of hunting pressure, the use of lure crops, 

other modifications to farming practices, hazing, and similar means. There presently is some 

uncertainty on whether or not habitat management for greater snow geese in southern Québec 

could short stop Canada geese. This subject deserves further discussion. 

6. Explore the feasibility, logistics and effectiveness of non-traditional means to reduce 

numbers of snow geese. 

Since there is great uncertainty as to whether or not the previous strategies will be 

completely successful in controlling greater snow goose numbers, alternative methods should be 

simultaneously considered as the initial management actions are taken by hunters. Culling of 

molting adult snow geese from within the most populated breeding colonies may, for example, be 

an effective technique. The population model indicates that reducing adult survival will have a 

much greater influence on snow goose numbers, than alternatives which reduce recruitment. 

However, because of the extreme difficulty and cost of working in remote Arctic areas, 

opportunities to reduce the population should also be explored in more accessible staging and 

wintering areas. 

We recognize that measures such as culling of large numbers of snow geese, even in 

remote breeding areas, may be unpopular with animal rights and humane groups, many waterfowl 

hunters and maybe the Nunavut Inuit. However, the risk of serious ecological damage will 

increase in parallel with increasing numbers of greater snow geese. We believe that it is prudent 

and responsible to have such a program ready to implement in case methods, more acceptable to 

the public, fail. Planning should include, monitoring habitat condition of major breeding 

colonies, staging and wintering marshes, estimating funding and logistic needs, and selection of 

techniques for trapping, humane euthanasia, and use of the geese. Commercial hunting is another 

practice that could be considered if the initial methods are not effective. Needless to say, if 
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strategies of this type prove necessary, success will depend on excellent public education and 

relations programs. 

GETTING THE JOB DONE 

Achievement of the management objectives will absolutely require a high level of 

cooperation and coordination between federal, provincial, and state wildlife agencies, private 

conservation organizations, and the many sportsmen’s, farmer’s and other groups with a stake in 

the future of the greater snow goose. The high rate of increase in the greater snow goose 

population and associated problems demands that work on each independent strategy or related 

group of strategies begin immediately and go forward concurrently. 

We suggest that several management teams be established to plan and implement each 

group of related tasks. Leadership of these teams and international coordination should be 

managed within each country by representatives of the U.S. and Canadian Federal agencies 

responsible for migratory bird management. 

The experience being gained from the lesser snow goose management initiative will be 

crucial to the progress and success of the greater snow goose issue. Wildlife agencies and 

governments are learning a lot from that exercise which will help guide the implementation of 

programs to deal with the greater snow goose problem. 

EVALUATION AND THE ROLE OF ADAPTIVE MANAGEMENT 

The Arctic Goose Habitat Working Group believes that the management of the greater 

snow goose population should be based on an adaptive process (Lancia et al. 1996). This will be 

feasible only if proper scientific monitoring programs are also implemented along with the 

various management practices. Some components of the monitoring program already exist and 

should therefore be maintained and improved whereas other components should be established as 

population control is started. We offer the following guidance for those who will be more 

integrally involved in developing an effective adaptive management approach to this program. 

1. Population Monitoring 

a) Maintain the annual spring census of the entire population in southern Québec and design a 

method based on capture-recapture using telemetry to obtain error values on the estimate of 

the population size. The greater snow goose is probably one of the best monitored 

populations and this should be a priority of the monitoring program. 

b) Maintain the survey of the Bylot Island breeding colony and additional new sites if necessary 

every 5 years. It is essential to determine if changes in population numbers are also reflected 

on the current breeding grounds or if expansion into new areas is occurring. 

c) Maintain the mid-winter inventory for greater snow geese in the U.S. to provide as a measure 

of distribution. 

c) Maintain harvest monitoring and improve the National Harvest Survey and the Species 

Composition Survey for greater snow geese. Since harvest is expected to be the main tool, 

dependable estimates of harvest both in Canada and U.S. are needed. 
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e) Maintain the banding program on Bylot Island to monitor population demographic 

parameters. Initiate new banding programs at a few other colonies. A main objective of the 

management strategies are to reduce adult and, to a lesser extent, juvenile survival through 

harvest. We therefore need to estimate these parameters with the greatest accuracy before 

and during the implementation of the management plan. We hypothesize that harvest is 

dominantly an additive process and not compensatory for greater snow geese. Knowledge of 

the harvest rate/survival relationship is required for adaptive management. A band reward 

study may be required to get more precise estimates of reporting rates specially for French 

speaking hunters. 

f) Maintain monitoring of productivity (% of juveniles) in fall and early winter to determine 

annual variation in production (good, average and bad years). 

g) Maintain goose measurement operations in fall at the Cap Tourmente NWA to assess if the 

reported density-dependent effects on size and condition of the birds will still operate after 

population stabilization. 

2. Habitat Monitoring 

a) Maintain habitat monitoring in the Arctic especially on Bylot Island and expand it to other 

sites where deemed necessary. The core concern of the Working Group is the maintenance of 

the integrity of the natural habitats, especially the Arctic breeding grounds. 

b) Continue the monitoring of bulrush marshes at Cap Tourmente every 2 years. 

b) Initiate a monitoring program of the main St. Lawrence bulrush marshes every 5 years. 

d) Initiate an assessment of the extent of damage to salt marsh habitats along the Atlantic coast, 

especially at refuges with large snow goose concentrations. 

d) Continue and improve monitoring of crop depredation wherever it occurs. 

f) Establish the carrying capacity of the various habitats used during the wintering, spring 

staging and breeding periods in order to establish a target population. 

LITERATURE CITED 

Lancia, R. A., C. E. Braun, M. W. Collopy, R. D. Dueser, J. G. Kie, C. J. Martinka, J. D. Nichols, 

T. D. Nudds, W. R. Porath, N. G. Tighman. 1996. ARM! For the future: adaptive resource 

management in the wildlife profession. Wildl. Soc. Bull. 24: 436-442. 

Rockwell, R., E. Cooch, and S. Brault. 1997. Dynamics of the mid-continent population of lesser 

snow geese - projected impacts of reductions in survival and fertility on population growth 

rates. Pages 73-100 in B. D. J. Batt, ed. Arctic ecosystems in Peril: Report of the Arctic 

Goose Habitat Working Group. Arctic Goose Joint Venture Special Publication. U.S. Fish 

and Wildlife Service, Washington, D.C. and Canadian Wildlife Service, Ottawa, Ontario.