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.

中文翻译：

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灵活的基于模型的方法来描述野生动物管理单位

划定采伐野生动植物的管理单位时，应努力在每个单位内最大程度地实现同质化，但要考虑到地理因素和与人为导致的生命率变化相关的因素所造成的异质性。划定白尾鹿（Odocoileus virginianus）管理单位的先前工作）使用回归分析确定与女性收成密度相关的环境和社会因素，然后进行空间约束聚类分析以选择多县单位进行管理。我们使用了2012年至2017年美国印第安纳州的县级数据，提出了一种改进的方法：1）同时利用空间，环境和社会文化解释变量对4种类型的人类介导的鹿死亡率变化进行建模。2）使用局部连续性约束对县进行聚类，该约束明确考虑了非空间变量；3）依靠专家意见评估模型的适当性并提出改进建议。死亡率的多变量负二项式回归来自4个来源（合法的无角鹿角和鹿角收成，报告的鹿与车辆碰撞，由于纬度（标准化系数，β范围= −0.18–0.24）以及鹿栖息地的非空间变量（β范围= 0.26–1.02）和猎人的密度，产生了对所有单变量模型具有足够拟合度和可观效果的加性模型（β范围= 0.25–1.02）。加入保护区计划的农田面积与收获呈正相关（β范围= 0.10–0.13），人类的总体发展与鹿撞死（β范围= 0.25–0.28）呈正相关，并带有掠夺许可（β范围） = 0.07–0.24）。具有部分连续性的聚类县的单位内非空间同质性比具有严格邻接性的聚类增加了1.7-1.9倍。10位机构生物学家和保护人员对在线调查的答复提供了一致（平均值±SD = 85.2±3。4％的专家和模型得出的地图，以及有关合并单独的城市管理部门的有用建议。将基于死亡率的统计模型与专家评估相结合，提供了一种严格而灵活的方法来划定野生动植物管理的空间单位，可以轻松地适应多个辖区的各种采伐物种。©2020野生动物协会。