Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada.
Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada; Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, Alberta, T6G 2G1, Canada.
J Environ Manage. 2019 Oct 15;248:109299. doi: 10.1016/j.jenvman.2019.109299. Epub 2019 Jul 31.
Understanding the underlying mechanisms driving population demographics such as species-habitat relationships and the spatial scale in which these relationships occur is essential for developing optimal management strategies. Here we evaluated how landscape characteristics and winter severity measured at three spatial scales (1 km, 9 km, and hunting unit) influenced white-tailed deer occurrence and abundance across North Dakota by using 10 years of winter aerial survey data and generalized linear mixed effects models. In general, forest, wetland, and Conservation Reserve Program (CRP) lands were the main drivers of deer occurrence and abundance in most of the spatial scales analyzed. However, the effects of habitat features vary between the home-range scale (9 km) and the finer spatial scale (1 km; i.e., within home ranges). While escape cover was the main factor driving white-tailed deer occurrence and abundance at broad spatial scales, at a fine spatial scale deer also selected for food (mainly residual winter cropland). With CRP appearing in nearly all top models, here we had strong evidence that this type of program will be fundamental to sustaining populations of white-tailed deer that can meet recreational demands. In addition, land managers should focus on ways to protect other escape covers (e.g., forest and wetland) on a broad spatial scale while encouraging landowners to supply winter resources at finer spatial scales. We therefore suggest a spatial multi-scale approach that involves partnerships among landowners and government agencies for effectively managing white-tailed deer.
了解驱动人口统计数据的潜在机制,如物种-栖息地关系以及这些关系发生的空间尺度,对于制定最佳管理策略至关重要。在这里,我们使用了 10 年的冬季航空调查数据和广义线性混合效应模型,评估了景观特征和冬季严重程度在三个空间尺度(1km、9km 和狩猎单元)上如何影响北达科他州白尾鹿的出现和丰度。总的来说,森林、湿地和保护储备计划(CRP)土地是大多数分析的空间尺度中鹿出现和丰度的主要驱动因素。然而,栖息地特征的影响在栖息地范围尺度(9km)和更精细的空间尺度(1km;即在栖息地范围内)之间存在差异。虽然避难所覆盖是驱动白尾鹿在广泛空间尺度上出现和丰度的主要因素,但在精细的空间尺度上,鹿也选择食物(主要是冬季剩余耕地)。由于 CRP 几乎出现在所有顶级模型中,我们有强有力的证据表明,这种类型的计划对于维持能够满足娱乐需求的白尾鹿种群至关重要。此外,土地管理者应着眼于在广泛的空间尺度上保护其他避难所(如森林和湿地)的方法,同时鼓励土地所有者在更精细的空间尺度上提供冬季资源。因此,我们建议采用空间多尺度方法,即土地所有者和政府机构之间的伙伴关系,以有效管理白尾鹿。