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Harvest data (e.g., number of animals harvested, trapper effort) are an important source of information for state wildlife agencies to manage harvested furbearers. These data provide evidence to support adapting harvest regulations when necessary. Setting appropriate harvest regulations for fishers (Martes pennanti) and American martens (Martes americana) is critical, as these species often exist at low densities, are sensitive to timber-management practices and trapper-harvest, and experience some level of interspecific predation and competition in sympatric populations.We estimated effects of management (e.g., number of fishers or martens harvested per trapper per season [harvest limit], season length) and extrinsic (e.g., weather, pelt prices) factors on regulated harvests of fishers and martens in the Upper Peninsula of Michigan during 1996-2007. We used generalized linear mixed models in an information-theoretic approach (quasi-likelihood adjusted Akaike Information Criterion [QAIC]) to discern which factors most strongly influenced fisher and marten harvests. For harvest of fishers, the 3 QAIC-best models included harvest limit, season length, and number of trappers, suggesting that regulatory changes within the ranges tested may be implemented to influence harvest. The QAIC-best model (harvest limit) contained 26% of the weight of evidence, and using an independent subset of data, showed no difference betweenmodel predictions and harvest data. In contrast, harvest of martens was not strongly influenced by any factors we tested. Possible reasons for a lack of measurable effects while modeling harvest of martens include a low harvest limit (i.e., 1 marten) or incidental harvest of martens by fisher or bobcat (Lynx rufus) trappers. Knowledge of influences on harvest will lead to informed decision-making whenmanagers are setting harvest regulations, particularly for low-density furbearers. [ABSTRACT FROM AUTHOR]

Despite the common use of Clover traps to capture white-tailed deer (Odocoileus virginianus), little published information exists quantifying trap success, trap selectivity (sex-age selection), or weather correlates of trap success. We quantified these relationships using white-tailed deer data from 3 study sites in the Lower Peninsula of Michigan, USA, during winters 2001-2007. We captured 610 deer in 8,569 trap-nights; pooled capture success was 0.07 deer/trap-night, although site-year success varied from 0.021 to 0.086. We compared sex-age classes (fawn [pooled by sex], ad M, ad F) captured with sex-age classes estimated to be available on each study site during each capture season. We used generalized linear mixed modeling to construct 19 a priori models to describe probability of capture success as a function of weather covariates (daily min. temp [° C], daily snowfall [cm], daily snow depth [cm]), Julian day, site, and year. General selection patterns included fawns captured more than expected and adult males captured less than expected; adult females were generally neutrally selected. The quasi- Akaike's Information Criterion best model within our set was described by the global model without Julian day and contained all 3 weather covariates and site-year effects. Our model provided some evidence that as daily snow depth increased, probability of capture increased; the positive effect of daily snowfall on capture probability was dependent on decreasing daily minimum temperature. Our results may be used to increase efficacy of deer capture programs by researchers and managers through informed decision-making about when to allocate effort (e.g., if extreme winter weather conditions are predicted) and when to consider alternative methods (e.g., if capture of ad M is an objective). [ABSTRACT FROM AUTHOR]

Resource selection studies are commonly conducted at a single spatial scale, but this likely does not fully or accurately assess the hierarchical selection process used by animals. We used a multi-spatial scale approach to quantify White-tailed Deer (Odocoileus virginianus) cover selection in south-central Michigan during 2004-2006 by varying definitions of use and availability and ranking the relative importance of cover types under each study design. The number of cover types assigned as selected (proportional use > proportional availability) decreased from coarse (landscape level) to fine (within home range) scales, although at finer scales, selection seemed to be more consistent. Although the relative importance changed substantially across spatial scales, two cover types (conifers, upland deciduous forests) were consistently ranked as the two most important, providing strong evidence of their value to deer in the study area. Testing for resource selection patterns using a multi-spatial scale approach would provide additional insight into the ecology and behavior of a particular species. [ABSTRACT FROM AUTHOR]