A Flexible Model‐based Approach to Delineate Wildlife Management Units

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.

Density from pellet groups: Comparing methods for estimating dung persistence time

“…We conducted all pellet-group monitoring in west-central Indiana, USA, centrally located in deer management unit 3 (10,233.3 km 2 ; Swihart et al 2020; Figure 1).…”

“…We conducted all pellet‐group monitoring in west‐central Indiana, USA, centrally located in deer management unit 3 (10,233.3 km 2 ; Swihart et al 2020; Figure 1). The management unit was located within the Central and Eastern Corn Belt Plains ecoregions (U.S. Environmental Protection Agency 1997).…”

Integrated species distribution models reveal spatiotemporal patterns of human–wildlife conflict

“…Finally, because this model must be evaluated across the entire study area, all of the data are already in place to develop spatial predictions of a species distribution and likelihood of conflict (Figure 2). While this latter point may seem minor, maps are a key decision‐support tool for wildlife management (Swihart et al, 2020), though their predictive accuracy should be assessed. Thus, we strongly encourage the use of this modeling framework to develop stronger collaborations with wildlife management agencies and conduct research that could mitigate human–wildlife conflict.…”

Spatially biased reduction of browsing damage by sika deer through culling

“…Effective management strategies rely on an appropriate spatial scale and size of management units (Fattorini et al 2020, Swihart et al 2020). Previous researchers primarily used an individual‐based approach, tracking parameters such as movement or home range (Webb et al 2007, Jarnemo 2008, Meisingset et al 2018); research using a culling‐based approach has been limited.…”