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J.A. Gude

Publications and source records attributed to J.A. Gude.

3 recordsLinked to original sources

Evaluating cost-efficiency and accuracy of hunter harvest survey designs

Effective management of harvested wildlife often requires accurate estimates of the number of animals harvested annually by hunters. A variety of techniques exist to obtain harvest data, such as hunter surveys, check stations, mandatory reporting requirements, and voluntary reporting of harvest. Agencies responsible for managing harvested wildlife such as deer (Odocoileus spp.), elk (Cervus elaphus), and pronghorn (Antilocapra americana) are challenged with balancing the cost of data collection versus the value of the information obtained. We compared precision, bias, and relative cost of several common strategies, including hunter self-reporting and random sampling, for estimating hunter harvest using a realistic set of simulations. Self-reporting with a follow-up survey of hunters who did not report produces the best estimate of harvest in terms of precision and bias, but it is also, by far, the most expensive technique. Self-reporting with no followup survey risks very large bias in harvest estimates, and the cost increases with increased response rate. Probability-based sampling provides a substantial cost savings, though accuracy can be affected by nonresponse bias. We recommend stratified random sampling with a calibration estimator used to reweight the sample based on the proportions of hunters responding in each covariate category as the best option for balancing cost and accuracy. ?? 2011 The Wildlife Society.

Wildlife Society Bulletin

Wolf population dynamics in the U.S. Northern Rocky Mountains are affected by recruitment and human-caused mortality

Reliable analyses can help wildlife managers make good decisions, which are particularly critical for controversial decisions such as wolf (Canis lupus) harvest. Creel and Rotella (2010) recently predicted substantial population declines in Montana wolf populations due to harvest, in contrast to predictions made by Montana Fish, Wildlife and Parks (MFWP). We replicated their analyses considering only those years in which field monitoring was consistent, and we considered the effect of annual variation in recruitment on wolf population growth. Rather than assuming constant rates, we used model selection methods to evaluate and incorporate models of factors driving recruitment and human-caused mortality rates in wolf populations in the Northern Rocky Mountains. Using data from 27 area-years of intensive wolf monitoring, we show that variation in both recruitment and human-caused mortality affect annual wolf population growth rates and that human-caused mortality rates have increased with the sizes of wolf populations. We document that recruitment rates have decreased over time, and we speculate that rates have decreased with increasing population sizes and/or that the ability of current field resources to document recruitment rates has recently become less successful as the number of wolves in the region has increased. Estimates of positive wolf population growth in Montana from our top models are consistent with field observations and estimates previously made by MFWP for 2008–2010, whereas the predictions for declining wolf populations of Creel and Rotella (2010) are not. Familiarity with limitations of raw data, obtained first-hand or through consultation with scientists who collected the data, helps generate more reliable inferences and conclusions in analyses of publicly available datasets. Additionally, development of efficient monitoring methods for wolves is a pressing need, so that analyses such as ours will be possible in future years when fewer resources will be available for monitoring.

Idaho, Montana, Wyoming

Estimation of successful breeding pairs for wolves in the Northern Rocky Mountains, USA

Under the Endangered Species Act, documenting recovery and federally mandated population levels of wolves (Canis lupus) in the Northern Rocky Mountains (NRM) requires monitoring wolf packs that successfully recruit young. United States Fish and Wildlife Service regulations define successful breeding pairs as packs estimated to contain an adult male and female, accompanied by ???2 pups on 31 December of a given year. Monitoring successful breeding pairs will become more difficult following proposed delisting of NRM wolves; alternatives to historically intensive methods, appropriate to the different ecological and regulatory context following delisting, are required. Because pack size is easier to monitor than pack composition, we estimated probability a pack would contain a successful breeding pair based on its size for wolf populations inhabiting 6 areas in the NRM. We also evaluated the extent to which differences in demography of wolves and levels of human-caused mortality among the areas influenced the probability of packs of different sizes would contain successful breeding pairs. Probability curves differed among analysis areas, depending primarily on levels of human-caused mortality, secondarily on annual population growth rate, and little on annual population density. Probabilities that packs contained successful breeding pairs were more uniformly distributed across pack sizes in areas with low levels of human mortality and stable populations. Large packs in areas with high levels of human-caused mortality and high annual growth rates had relatively high probabilities of containing breeding pairs whereas those for small packs were relatively low. Our approach can be used by managers to estimate number of successful breeding pairs in a population where number of packs and their sizes are known. Following delisting of NRM wolves, human-caused mortality is likely to increase, resulting in more small packs with low probabilities of containing breeding pairs. Differing contributions of packs to wolf population growth based on their size suggests monitoring successful breeding pairs will provide more accurate insights into population dynamics of wolves than will monitoring number of packs or individuals only.

Journal of Wildlife Management