A Flexible Model‐based Approach to Delineate Wildlife Management Units. (3rd January 2020)

• Record Type: Journal Article
• Authors: Swihart, Robert K.; Caudell, Joe N.; Brooke, Jarred M.; Ma, Zhao
• Is Part Of: Wildlife Society bulletin. Volume 44:Number 1(2020)
• Page Start: 77
• Page End: 85
• Publication Date: 2020-01-03
• Subjects: cluster analysis -- deer -- expert opinion -- harvest -- Indiana -- mortality -- multivariate regression -- Odocoileus virginianus -- partial contiguity constraint; Wildlife management -- Periodicals; Wildlife conservation -- Periodicals; 333.9540973
• DOI: 10.1002/wsb.1037
• Languages: English
• ISSNs: 0091-7648

Abstract

: A method is presented to delineate wildlife management units that models variation in multiple sources of human‐mediated mortality with spatial, habitat, hunter, and human development variables, clusters counties using important nonspatial variables as well as geography, and uses expert opinion to assess model adequacy and suggest improvements. We apply our method to county‐level data on white‐tailed deer in Indiana, USA, and believe the method can be adapted easily to other species and jurisdictions. ABSTRACT: Delineation of management units for harvested wildlife should strive to maximize homogeneity within each unit subject to constraints imposed by geography and heterogeneity in factors related to human‐caused changes in vital rates. Prior efforts to delineate management units for white‐tailed deer ( Odocoileus virginianus ) used regression to identify environmental and sociological factors related to female harvest density, followed by spatially constrained cluster analysis to select multicounty units for management purposes. We used county‐level data in Indiana, USA, from 2012 to 2017 to present a modified approach that 1) simultaneously models variation in 4 types of human‐mediated deer mortality with spatial, environmental, and socio‐cultural explanatory variables; 2) clusters counties using a partial contiguity constraint that explicitly considers nonspatial variables; and 3) relies on expert opinion to assess model adequacy and suggest improvements. Multivariate negative binomial regression of mortality from 4 sources (legal antlerless and antlered harvest, reported deer–vehicle collisions, crop depredation permits) yielded additive models with adequate fit and sizable effects for all univariate models due to latitude (standardized coefficient, β range = −0.18–0.24), and the nonspatial variables deer habitat (β range = 0.26–1.02) and hunter density (β range = 0.25–1.02). Fraction of cropland enrolled in the Conservation Reserve Program was positively related to harvest (β range = 0.10–0.13), and general human development was positively related to deer collision deaths (β range = 0.25–0.28) and take with depredation permits (β range = 0.07–0.24). Clustering counties with partial contiguity increased within‐unit nonspatial homogeneity 1.7–1.9 times more than clustering with strict contiguity. Responses to online surveys by 10 agency biologists and conservation officers provided congruence (mean ± SD = 85.2 ± 3.4%) of expert and model‐derived maps and useful suggestions for incorporating a separate urban management unit. Combining mortality‐based statistical models and expert assessment offers a rigorous yet flexible approach to delineating spatial units for wildlife management that is easily adaptable for various harvested species in multiple jurisdictions. © 2020 The Wildlife Society.