Montana Cooperative Wildlife Research Unit, Wildlife Biology Program, University of Montana, Missoula, MT, USA.
US Geological Survey, Montana Cooperative Wildlife Research Unit, Wildlife Biology Program, University of Montana, Missoula, MT, USA.
Proc Biol Sci. 2022 Jan 12;289(1966):20212512. doi: 10.1098/rspb.2021.2512.
Ecologists have long sought to understand space use and mechanisms underlying patterns observed in nature. We developed an optimality landscape and mechanistic territory model to understand mechanisms driving space use and compared model predictions to empirical reality. We demonstrate our approach using grey wolves (). In the model, simulated animals selected territories to economically acquire resources by selecting patches with greatest value, accounting for benefits, costs and trade-offs of defending and using space on the optimality landscape. Our approach successfully predicted and explained first- and second-order space use of wolves, including the population's distribution, territories of individual packs, and influences of prey density, competitor density, human-caused mortality risk and seasonality. It accomplished this using simple behavioural rules and limited data to inform the optimality landscape. Results contribute evidence that economical territory selection is a mechanistic bridge between space use and animal distribution on the landscape. This approach and resulting gains in knowledge enable predicting effects of a wide range of environmental conditions, contributing to both basic ecological understanding of natural systems and conservation. We expect this approach will demonstrate applicability across diverse habitats and species, and that its foundation can help continue to advance understanding of spatial behaviour.
生态学家长期以来一直试图了解自然界中观察到的空间利用模式和潜在机制。我们开发了一个最优景观和机械领域模型来理解驱动空间利用的机制，并将模型预测与经验现实进行比较。我们使用灰狼（）来演示我们的方法。在模型中，模拟动物通过选择具有最大价值的斑块来经济地获取资源，从而在最优景观上考虑防御和利用空间的收益、成本和权衡。我们的方法成功地预测和解释了狼的第一和第二级空间利用，包括种群的分布、单个狼群的领地以及猎物密度、竞争密度、人为死亡率风险和季节性的影响。它使用简单的行为规则和有限的数据来为最优景观提供信息，从而实现了这一点。结果为经济的领地选择是空间利用和景观上动物分布之间的机械桥梁提供了证据。这种方法和由此产生的知识增益使我们能够预测广泛的环境条件的影响，为自然系统的基础生态理解和保护做出贡献。我们预计这种方法将适用于各种不同的栖息地和物种，并且其基础可以帮助继续推进对空间行为的理解。
