Wiens J David, Schumaker Nathan H, Inman Rich D, Esque Todd C, Longshore Kathleen M, Nussear Kenneth E
U.S. Geological Survey Forest and Rangeland Ecosystem Science Center, Corvallis, OR, 97330.
U.S. Environmental Protection Agency, Corvallis, OR 97333.
J Raptor Res. 2017 Sep;51(3):234-257. doi: 10.3356/JRR-16-77.1.
Spatial demographic models can help guide monitoring and management activities targeting at-risk species, even in cases where baseline data are lacking. Here, we provide an example of how site-specific changes in land-use and other anthropogenic stressors can be incorporated into a spatial demographic model to investigate effects on population dynamics of Golden Eagles (). Our study focused on a population of Golden Eagles exposed to risks associated with rapid increases in renewable energy development in southern California, USA. We developed a spatially-explicit, individual-based simulation model that integrated empirical data on demography of Golden Eagles with spatial data on the arrangement of nesting habitats, prey resources, and planned renewable energy development sites. Our model permitted simulated eagles of different stage-classes to disperse, establish home ranges, acquire resources, prospect for breeding sites, and reproduce. The distribution of nesting habitats, prey resources, and threats within each individual's home range influenced movement, reproduction, and survival. We used our model to explore potential effects of alternative disturbance scenarios, and proposed conservation strategies, on the future distribution and abundance of Golden Eagles in the study region. Results from our simulations suggest that probable increases in mortality associated with renewable energy infrastructure (e.g., collisions with wind-turbines and vehicles, electrocution on power poles) could have negative consequences for population trajectories, but that site-specific conservation actions could reduce the magnitude of negative impacts. Our study demonstrates the use of a flexible and expandable modeling framework to incorporate spatially dependent processes when determining relative risks of proposed management options to Golden Eagles and their habitats.
空间人口统计学模型有助于指导针对濒危物种的监测和管理活动,即使在缺乏基线数据的情况下也是如此。在此,我们提供一个示例,说明如何将特定地点的土地利用变化和其他人为压力因素纳入空间人口统计学模型,以研究其对金雕种群动态的影响。我们的研究聚焦于美国加利福尼亚州南部一群面临可再生能源开发快速增长所带来风险的金雕。我们开发了一个空间明确、基于个体的模拟模型,该模型将金雕种群统计学的实证数据与筑巢栖息地、猎物资源和规划中的可再生能源开发地点的空间数据整合在一起。我们的模型允许不同阶段等级的模拟金雕进行扩散、建立活动范围、获取资源、寻找繁殖地点并进行繁殖。每个个体活动范围内筑巢栖息地、猎物资源和威胁的分布会影响其移动、繁殖和生存。我们利用模型探索替代干扰情景和拟议的保护策略对研究区域内金雕未来分布和数量的潜在影响。模拟结果表明,与可再生能源基础设施相关的死亡率可能增加(例如与风力涡轮机和车辆碰撞、在电线杆上触电)可能会对种群轨迹产生负面影响,但特定地点的保护行动可以减少负面影响的程度。我们的研究展示了在确定拟议管理方案对金雕及其栖息地的相对风险时,使用灵活且可扩展的建模框架来纳入空间依赖过程。