Fisher Jason T, Wheatley Matthew, Mackenzie Darryl
Alberta Innovates - Technology Futures, Ecosystem Management Unit, 3-4476 Markham St, Victoria, BC V8Z 7X8, Canada.
Conserv Biol. 2014 Oct;28(5):1249-59. doi: 10.1111/cobi.12302. Epub 2014 Apr 24.
Conservation programs often manage populations indirectly through the landscapes in which they live. Empirically, linking reproductive success with landscape structure and anthropogenic change is a first step in understanding and managing the spatial mechanisms that affect reproduction, but this link is not sufficiently informed by data. Hierarchical multistate occupancy models can forge these links by estimating spatial patterns of reproductive success across landscapes. To illustrate, we surveyed the occurrence of grizzly bears (Ursus arctos) in the Canadian Rocky Mountains Alberta, Canada. We deployed camera traps for 6 weeks at 54 surveys sites in different types of land cover. We used hierarchical multistate occupancy models to estimate probability of detection, grizzly bear occupancy, and probability of reproductive success at each site. Grizzly bear occupancy varied among cover types and was greater in herbaceous alpine ecotones than in low-elevation wetlands or mid-elevation conifer forests. The conditional probability of reproductive success given grizzly bear occupancy was 30% (SE = 0.14). Grizzly bears with cubs had a higher probability of detection than grizzly bears without cubs, but sites were correctly classified as being occupied by breeding females 49% of the time based on raw data and thus would have been underestimated by half. Repeated surveys and multistate modeling reduced the probability of misclassifying sites occupied by breeders as unoccupied to <2%. The probability of breeding grizzly bear occupancy varied across the landscape. Those patches with highest probabilities of breeding occupancy-herbaceous alpine ecotones-were small and highly dispersed and are projected to shrink as treelines advance due to climate warming. Understanding spatial correlates in breeding distribution is a key requirement for species conservation in the face of climate change and can help identify priorities for landscape management and protection.
保护计划通常通过物种生存的景观来间接管理种群数量。从经验来看,将繁殖成功率与景观结构和人为变化联系起来是理解和管理影响繁殖的空间机制的第一步,但这一联系尚未得到充分的数据支持。分层多状态占用模型可以通过估计景观中繁殖成功率的空间模式来建立这些联系。为了说明这一点,我们调查了加拿大艾伯塔省落基山脉中灰熊(棕熊)的出现情况。我们在不同土地覆盖类型的54个调查地点部署了6周的相机陷阱。我们使用分层多状态占用模型来估计每个地点的检测概率、灰熊占用率和繁殖成功率。灰熊的占用率在不同覆盖类型之间有所不同,在草本高山交错带比在低海拔湿地或中海拔针叶林中更高。在灰熊占用的情况下,繁殖成功的条件概率为30%(标准误差=0.14)。有幼崽的灰熊比没有幼崽的灰熊被检测到的概率更高,但根据原始数据,只有49%的地点被正确分类为有繁殖雌性占据,因此会被低估一半。重复调查和多状态建模将将繁殖者占据的地点误分类为未被占据的概率降低到<2%。繁殖灰熊的占用概率在整个景观中各不相同。那些繁殖占用概率最高的斑块——草本高山交错带——面积小且高度分散,预计随着气候变暖树木线推进,它们会缩小。了解繁殖分布中的空间相关性是面对气候变化时物种保护的关键要求,并且有助于确定景观管理和保护的优先事项。