野生动物种群动态受到非生物和生物因素的调节,典型的气候,资源可用性,密度依赖效应,和捕食者-猎物的相互作用。了解人类造成的干扰是否以及如何影响这些生态过程,有助于在日益人类主导的景观中保护和管理野生动植物及其栖息地。然而,许多司法管辖区既缺乏野生动物种群的长期纵向数据,也缺乏人类介导的干扰之间相互作用的衡量标准,气候,和捕食者密度。这里,我们使用50年的时间序列(1962-2012年)对mu鹿(Odocoileushemionus)的人口统计学,季节性天气,捕食者密度,以及北达科他州荒地的石油和天然气开发模式,美国,为了研究景观水平干扰对骡鹿幼鹿秋季招募的长期影响,在过去的几十年里急剧下降。本研究中的Mule鹿小鹿秋季招募代表了每个雌性的小鹿数量(小鹿:雌性比率),它们在夏季至10月期间存活。我们使用这个小鹿招募指数来评估年际极端天气条件的综合影响,能源开发,和捕食者密度。我们发现,依赖密度的影响和恶劣的季节性天气是北达科他州荒地小鹿秋季招募的主要驱动因素。这些影响进一步由恶劣的季节性天气和捕食者密度之间的相互作用形成(即,当恶劣天气与较高的捕食者密度相结合时,较低的小鹿秋季招募量)。此外,我们发现,小鹿秋季的招募受到季节性天气和能源开发之间相互作用的调节(即,当恶劣天气与较高密度的活跃油气井相结合时,较低的小鹿秋季募集)。有趣的是,我们发现捕食者密度和能量发展的综合作用不是相互作用的,而是累加的。我们的分析表明,能源开发如何调节m鹿小鹿秋季募集与生物同时发生的波动(密度依赖性,栖息地,捕食,木本植被侵蚀)和非生物(恶劣的季节性天气)驾驶员。依赖密度的模式出现了,大概是由于栖息地质量有限,是影响m鹿秋季小鹿招募的主要因素。其次,随机天气事件会定期导致招聘人数急剧下降。最后,人为干扰和捕食的累加效应会引起小鹿秋季募集的波动。在这里,我们利用长期数据集来设定决策者和公众可以理解和支持的长期野生动物管理目标。
Wildlife population dynamics are modulated by abiotic and biotic factors, typically climate, resource availability, density-dependent effects, and predator-prey interactions. Understanding whether and how human-caused disturbances shape these ecological processes is helpful for the conservation and management of wildlife and their habitats within increasingly human-dominated landscapes. However, many jurisdictions lack either long-term longitudinal data on wildlife populations or measures of the interplay between human-mediated disturbance, climate, and predator density. Here, we use a 50-year time series (1962-2012) on mule deer (Odocoileus hemionus) demographics, seasonal weather, predator density, and oil and gas development patterns from the North Dakota Badlands, USA, to investigate long-term effects of landscape-level disturbance on mule deer fawn fall recruitment, which has declined precipitously over the last number of decades. Mule deer fawn fall recruitment in this study represents the number of fawns per female (fawn:female ratio) that survive through the summer to October. We used this fawn recruitment index to evaluate the composite effects of interannual extreme weather conditions, energy development, and predator density. We found that density-dependent effects and harsh seasonal weather were the main drivers of fawn fall recruitment in the North Dakota Badlands. These effects were further shaped by the interaction between harsh seasonal weather and predator density (i.e., lower fawn fall recruitment when harsh weather was combined with higher predator density). Additionally, we found that fawn fall recruitment was modulated by interactions between seasonal weather and energy development (i.e., lower fawn fall recruitment when harsh weather was combined with higher density of active oil and gas wells). Interestingly, we found that the combined effect of predator density and energy development was not interactive but rather additive. Our analysis demonstrates how energy development may modulate fluctuations in mule deer fawn fall recruitment concurrent with biotic (density-dependency, habitat, predation, woody vegetation encroachment) and abiotic (harsh seasonal weather) drivers. Density-dependent patterns emerge, presumably due to limited quality habitat, being the primary factor influencing fall fawn recruitment in mule deer. Secondarily, stochastic weather events periodically cause dramatic declines in recruitment. And finally, the additive effects of human disturbance and predation can induce fluctuations in fawn fall recruitment. Here we make the case for using long-term datasets for setting long-term wildlife management goals that decision makers and the public can understand and support.