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Souchay, G., O. Gimenez, G. Gauthier, and R. Pradel. 2014. Variations in band reporting rate and implications for kill rate in Greater Snow Geese.*Avian Conservation and Ecology* **9**(1): 1.

http://dx.doi.org/10.5751/ACE-00628-090101

Research PaperSouchay, G., O. Gimenez, G. Gauthier, and R. Pradel. 2014. Variations in band reporting rate and implications for kill rate in Greater Snow Geese.

http://dx.doi.org/10.5751/ACE-00628-090101

Variations du taux de retour de bagues et répercussions sur le taux de récolte chez la Grande Oie des neiges.

- Abstract
- Introduction
- Methods
- Results
- Discussion
- Responses to This Article
- Acknowledgments
- Literature Cited

Nous avons déterminé la variabilité spatiale et temporelle de la probabilité de retourner des bagues de Grandes Oies des neiges (*Chen caerulescens atlantica*) récoltées par les chasseurs dans l'Est de l’Amérique du Nord, et évalué les biais inhérents potentiels dans l’estimation du taux de récolte. Les oies adultes ont été marquées à l’aide de bagues récompense (d’une valeur de 10, 20, 30, 50 ou 100 $ US) et standards (0 $ US, témoin) dans l’Arctique canadien de 2003 à 2005. Afin d’estimer le taux de retour de bagues par les chasseurs et le taux de récolte, nous avons utilisé un modèle multinomial spatialement explicite fondé sur 200 récupérations directes de bagues provenant d’un ensemble de 4256 oies baguées. Nos résultats indiquent que le taux de retour par les chasseurs pour les bagues standards a varié au cours du temps, tandis que le taux de récolte était plus élevé au Canada qu’aux États-Unis. La probabilité de retour de bagues par les chasseurs a augmenté de 0,40 ± 0,11 la première année de l’étude à 0,82 ± 0,14 et 0,84 ± 0,13 les deuxième et troisième années, respectivement. Ces taux de retour de bagues sont supérieurs à ceux estimés précédemment pour cette population, entrainant des estimations du taux de récolte plus faibles. Toutefois, la forte variation interannuelle dans les taux de retour de bagues par les chasseurs observée dans la présente étude engendre une grande incertitude pour l’estimation du taux de récolte. Nous suggérons que l’augmentation du taux de retour de bagues observée au cours des deux dernières années de notre étude pourrait être attribuable à la dissémination de l’information au sein des chasseurs quant à l’existence de bagues récompense sur les oiseaux, conduisant ainsi à une augmentation du taux de retour pour tout type de bagues. Cette étude souligne l’importance des informations à transmettre au public lors d’études à grande échelle afin d’éviter des tendances temporelles indésirables au cours de celles-ci.

Key words: Atlantic Flyway; band recovery; Greater Snow Goose; kill rate; reporting rate; reward band; spatial variation; temporal variation; waterfowl

An alternative method to estimate harvest rate relies on direct recoveries of banded birds (Baldassarre and Bolen 2006). Newly banded birds can be re-encountered when shot and retrieved during the following hunting season, i.e., direct recoveries. In hunted species, most reported bands are reported by hunters, e.g., > 97% in the Greater Snow Goose (

Reward band studies are typically used to estimate reporting rate (Nichols et al. 1991, 1995, Royle and Garrettson 2005, Zimmerman et al. 2009

Previous studies have examined reporting probabilities in duck and goose populations across North America (Nichols et al. 1991, 1995, Royle and Garrettson 2005, Zimmerman et al. 2009

Our objectives were to study geographical and temporal variation in reporting probability by Greater Snow Goose hunters in eastern North America. This goose population is unique in two ways, namely that harvest is equal or higher in Canada than in the U.S. (Calvert and Gauthier 2005), unlike most other waterfowl populations, and Canadian hunting occurs almost exclusively in Québec, the predominantly French-speaking province of Canada. Anecdotal observations (G. Gauthier,

Methods used to estimate reporting-rates of standard bands require the major assumption that 100% of the reward bands found with the highest dollar value are reported, otherwise estimates of reporting rates will be biased (Conroy and Williams 1981). Thus, our first objective was to assess the validity of the assumption that the reporting rate (

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In a second step, we tested temporal and regional effects on reporting rate. We started by estimating annual reporting (λ) and harvest (

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We adopted a Bayesian approach using Markov Chain Monte Carlo (MCMC) simulations to implement all models. We specified the model to run in the form of the likelihood and noninformative prior distributions for all parameters to be estimated. We used empirical means and standard deviations to summarize these posterior parameter distributions (Gimenez et al. 2009, 2012). For priors, we used a Normal distribution (0, 10) for α, a Normal distribution (0, 100) for β, and a Uniform distribution (0, 1) for

In a final step, we applied the estimation of reporting rate λ obtained in the Bayesian analysis to

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In our evaluation of temporal and spatial effects on reporting rate, the top-ranked model retained both of these effects in interaction (Table 2). Whereas adding the year effect on reporting rate greatly improved the fit compared to the constant model, region improved the fit only when added in combination with year. Moreover, because a model without a region effect on reporting rate fitted the data almost as well as one with such an effect (M3 vs. M4, Table 2) and was more parsimonious, we based our interpretation on the model with only a year effect. Reporting rate of birds with standard USGS bands only was very similar in 2004 and 2005 but was only half of those values in the first year of the study (2003; Model M3, Table 3). We further note that the interaction with region in the more complex model (M4) was mostly due to the very low reporting rate in the USA compared to Québec in the first year of the study (0.24 ± 0.13 [SE] and 0.56 ± 0.18, respectively). However, we recognize that point estimates were based on relatively small sample size when broken down by region and years (Appendix 1). Finally, our two top-ranked models included only spatial effect on the harvest rate with no time-dependent effects (models with a year effect on harvest rate had a ΔDIC > 3; Table 2). Harvest rates estimates were higher for Québec (0.034 ± 0.004) than for the USA (0.023 ± 0.003), as expected.

We estimated kill rate for the period of the reward-band study (2003-2005) using the various point estimates of λ obtained in models M1 to M4 (Table 3) to examine the sensitivity of this parameter to reporting rate. We added estimation of kill rate from other studies using reporting rate values calculated by Calvert and Gauthier (2005) and Zimmerman et al. (2009

Finally, we examined how using various estimates of reporting rate could have affected our evaluation of temporal trends in kill rates of Greater Snow Geese over the period 2002-2010 (Fig. 3). For both juvenile and adult, kill rates estimated using our constant reporting rate value were the lowest. Kill rates based on Zimmerman et al. (2009

In an analysis combining both Canada Geese and Snow Geese, Zimmerman et al. (2009

Our most surprising finding is the strong evidence for temporal variation in reporting rate over the three-year reward-band study, which was not documented by Zimmerman et al. (2009

The presence of temporal variation in the estimation of reporting rate creates problems for the estimation of kill rate. If hunters indeed changed their attitude after the first year of this reward-band study and reported bands at a higher rate as we suggested, then the more realistic and least biased reporting rate should be the one associated with the first year of the study, 0.40 ± 0.11 in our case. We note that this estimation of reporting rate is similar to the one (0.36 to 0.40) of Calvert and Gauthier (2005) based on the relationship between band-recovery rate and harvest rate, independent of any reward-band study. However, because reward bands persist in the marked population for a few years and hunters remain aware of them, then a reporting rate close to 0.84 ± 0.13 may be more appropriate in the short term. We note that these differences are not trivial because they would result in a twofold difference in the estimation of kill rate. Kill rate estimates derived from the hunter survey were in the range of those estimated from band recovery analysis. However, because these estimates are also subject to potential biases (Calvert and Gauthier 2005, Padding and Royle 2012), they are not accurate enough to determine which band reporting rate estimate is most appropriate. Therefore, in the face of all those uncertainties, using the intermediate band reporting rate value provided by our constant model (λ = 0.65 ± 0.10) may be the best alternative at the moment. This estimate is higher than the one from Zimmerman et al (2009

The increase in reporting rates after the first year of the reward-band study that we observed raises questions about what is the best public policy strategy to adopt when implementing such large scale programs. When no public information is released at the onset of the program, as was the case here, the spread of information or misinformation during the study could result in undesirable temporal changes in reporting rates over the period of the study, including for standard, nonreward bands. In contrast, a public information campaign at the start of such a program could make clear the distinction between a reward and a nonreward band. We recognize that publicizing a reward-band program could lead to increased harvest rate if hunters increased their activity in the hope of shooting a bird with a reward band. Nonetheless, we believe that a carefully designed public information campaign at the start of such a program may be desirable, especially if hunters are made aware of the low probability of shooting a bird with a reward-band.

This study was funded by the Natural Sciences and Engineering Research Council of Canada, the Arctic Goose Joint Venture (Canadian Wildlife Service), the Centre d’Études Nordiques, the Department of Indian and Northern Affairs Canada, and the International Research Group Dynamics of Biodiversity and Life-History traits. Funding for the reward program (bands and rewards) was provided by the United States Geological Survey Bird Banding Laboratory. We especially thank T. J. Moser for managing the reward-band program and for valuable information about the program. P. Garrettson and A. Royle provided precious help to carry out the statistical analyses. We are grateful to the numerous field assistants that helped with goose banding and especially G. Picard, and to all the hunters who reported the banded birds that they shot. We thank M.-C. Cadieux for managing the database and for assistance in the field. We are grateful to two anonymous reviewers for their valuable comments to improve our earlier version of our manuscript.

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