Management decision making for fisher populations informed by occupancy modeling

Harvest data are often used by wildlife managers when setting harvest regulations for species because the data are regularly collected and do not require implementation of logistically and financially challenging studies to obtain the data. However, when harvest data are not available because an area had not previously supported a harvest season, alternative approaches are required to help inform management decision making. When distribution or density data are required across large areas, occupancy modeling is a useful approach, and under certain conditions, can be used as a surrogate for density. We collaborated with the New York State Department of Environmental Conservation (NYSDEC) to conduct a camera trapping study across a 70,096-km2 region of southern New York in areas that were currently open to fisher (Pekania [Martes] pennanti) harvest and those that had been closed to harvest for approximately 65 years. We used detection–nondetection data at 826 sites to model occupancy as a function of site-level landscape characteristics while accounting for sampling variation. Fisher occupancy was influenced positively by the proportion of conifer and mixed-wood forest within a 15-km2 grid cell and negatively associated with road density and the proportion of agriculture. Model-averaged predictions indicated high occupancy probabilities (>0.90) when road densities were low ( 0.50). Predicted occupancy ranged 0.41–0.67 in wildlife management units (WMUs) currently open to trapping, which could be used to guide a minimum occupancy threshold for opening new areas to trapping seasons. There were 5 WMUs that had been closed to trapping but had an average predicted occupancy of 0.52 (0.07 SE), and above the threshold of 0.41. These areas are currently under consideration by NYSDEC for opening a conservative harvest season. We demonstrate the use of occupancy modeling as an aid to management decision making when harvest-related data are unavailable and when budgetary constraints do not allow for capture–recapture studies to directly estimate density. © 2016 The Wildlife Society.

[1]  Samuel T. Turvey,et al.  Estimating animal density using camera traps without the need for individual recognition , 2008 .

[2]  J. Nichols,et al.  Monitoring for conservation. , 2006, Trends in ecology & evolution.

[3]  Jacob S. Ivan,et al.  Spatially Explicit Power Analyses for Occupancy‐Based Monitoring of Wolverine in the U.S. Rocky Mountains , 2014, Conservation biology : the journal of the Society for Conservation Biology.

[4]  William J. Zielinski,et al.  Carnivore Translocations and Conservation: Insights from Population Models and Field Data for Fishers (Martes pennanti) , 2012, PloS one.

[5]  Todd W. Arnold.  Uninformative Parameters and Model Selection Using Akaike's Information Criterion , 2010 .

[6]  Richard B. Chandler,et al.  Spatially explicit integrated population models , 2014 .

[7]  Scott E. Nielsen,et al.  Can models of presence‐absence be used to scale abundance? Two case studies considering extremes in life history , 2005 .

[8]  A. F. O'connell,et al.  Multi-scale occupancy estimation and modelling using multiple detection methods , 2008 .

[9]  M. J. Jordan,et al.  Camera trapping estimates of density and survival of fishers Martes pennanti , 2011 .

[10]  J. Rachlow,et al.  Both forest composition and configuration influence landscape-scale habitat selection by fishers (Pekania pennanti) in mixed coniferous forests of the Northern Rocky Mountains , 2014 .

[11]  Justin A. Gude,et al.  Estimating occupancy and predicting numbers of gray wolf packs in Montana using hunter surveys , 2013 .

[12]  Jacob S. Ivan,et al.  rSPACE: Spatially based power analysis for conservation and ecology , 2015 .

[13]  R. Weir,et al.  Factors Affecting Landscape Occupancy by Fishers in North-Central British Columbia , 2010 .

[14]  Richard B. Chandler,et al.  unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance , 2011 .

[15]  J. Nichols,et al.  Monitoring carnivore populations at the landscape scale: occupancy modelling of tigers from sign surveys , 2011 .

[16]  L. L. Bailey,et al.  Efficient Species‐Level Monitoring at the Landscape Scale , 2012, Conservation biology : the journal of the Society for Conservation Biology.

[17]  P. Lancaster,et al.  Fishers, Farms, and Forests in Eastern North America , 2008, Environmental management.

[18]  John D. J. Clare,et al.  Predicting bobcat abundance at a landscape scale and evaluating occupancy as a density index in central Wisconsin , 2015 .

[19]  J. Andrew Royle,et al.  A Framework for Inference About Carnivore Density From Unstructured Spatial Sampling of Scat Using Detector Dogs , 2012 .

[20]  William J. Zielinski,et al.  Using Presence‐Absence Data to Build and Test Spatial Habitat Models for the Fisher in the Klamath Region, U.S.A. , 1999 .

[21]  Darryl I. MacKenzie,et al.  Assessing the fit of site-occupancy models , 2004 .

[22]  Rob Slotow,et al.  Evaluating Methods for Counting Cryptic Carnivores , 2009 .

[23]  W. Krohn,et al.  Habitat Use and Diet of Fishers , 1989 .

[24]  J. Buzas,et al.  Comparing Scat Detection Dogs, Cameras, and Hair Snares for Surveying Carnivores , 2007 .

[25]  E. Revilla,et al.  Use of Camera‐Trapping to Estimate Puma Density and Influencing Factors in Central Brazil , 2010 .

[26]  J. Belant,et al.  Factors Affecting Harvests of Fishers and American Martens in Northern Michigan , 2011 .

[27]  G. Proulx.  Using forest inventory data to predict winter habitat use by fisherMartes pennanti in British Columbia, Canada , 2006, Acta Theriologica.

[28]  J. Nichols,et al.  ESTIMATING SITE OCCUPANCY, COLONIZATION, AND LOCAL EXTINCTION WHEN A SPECIES IS DETECTED IMPERFECTLY , 2003 .

[29]  J. Andrew Royle,et al.  ESTIMATING SITE OCCUPANCY RATES WHEN DETECTION PROBABILITIES ARE LESS THAN ONE , 2002, Ecology.

[30]  D. Dawson,et al.  Occupancy in continuous habitat , 2012 .

[31]  Rahel Sollmann,et al.  Improving density estimates for elusive carnivores: Accounting for sex-specific detection and movements using spatial capture–recapture models for jaguars in central Brazil , 2011 .

[32]  D. Swann,et al.  Infrared-triggered cameras for detecting wildlife: an evaluation and review , 2004 .