Data from: Spatially explicit abundance estimation of a rare habitat specialist: implications for SECR study design

Estimating abundance is an essential component of monitoring and recovery of rare species and spatially explicit capture-recapture (SECR) models provide the means for robust density estimation. Previous work has elucidated principles of SECR study design for large, generalist carnivores, but less attention has been paid to study design considerations for smaller species, with less extensive home ranges. Here we integrated data from an intensive pilot study with simulation modeling to evaluate the influence of survey sampling intensity on precision and accuracy in SECR abundance estimation for a rare lagomorph that specializes on patchily distributed early successional habitats. Doing so, we obtained the first mark-recapture density estimates for the New England cottontail (Sylvilagus transitionalis). Capture probability and density on the landscape both impacted the required intensity of the sampling design. The optimal study design for robust estimation also required a greater number of traps relative to home range size or spatial extent than those recommended in prior SECR studies. This divergence emphasizes that SECR study design considerations will differ among organisms with varying spatial extent and habitat use. Demonstrating the appropriate sampling design for a study system is important prior to embarking in a SECR study. Integrating pilot empirical data with simulations provides a powerful means for optimizing SECR study design and for facilitating applicability of SECR approaches to a wider array of organisms with varying habitat and space use. This methodology may be employed in planning a monitoring program that maximizes effectiveness while minimizing cost and effort, as part of the adaptive management approach to monitor and recover rare or endangered species.种群丰度估算是珍稀物种监测与恢复工作的核心组成部分，空间显式捕获再捕获（spatially explicit capture-recapture, SECR）模型为开展稳健的密度估算提供了可行方法。此前的研究已阐明针对大型广食性食肉动物的SECR研究设计原则，但针对家域范围更小的小型物种的研究设计相关考量，却尚未得到足够关注。本研究将集约化预研究数据与模拟建模相结合，评估了调查采样强度对一种特化依赖斑块分布早期演替生境的珍稀兔形目物种的SECR丰度估算精度与准确度的影响。借此，我们首次获得了新英格兰棉尾兔（Sylvilagus transitionalis）的标记重捕密度估算结果。景观尺度上的个体捕获概率与种群密度，均会影响采样设计所需的强度。相较于此前SECR研究中推荐的方案，用于实现稳健估算的最优研究设计，所需布设的诱捕器数量相对于家域规模或空间范围而言更多。这一差异表明，SECR研究设计的考量因素会因物种的空间分布范围与生境利用模式的不同而存在差异。在开展SECR研究前，针对特定研究系统确定合适的采样设计至关重要。将预研究实测数据与模拟建模相结合，可为优化SECR研究设计、推动SECR方法在更多具有不同生境与空间利用模式的物种中应用提供强有力的有效途径。该方法可用于规划监测方案，在提升监测效能的同时压缩成本与工作量，可作为珍稀或濒危物种监测与恢复的适应性管理框架的组成部分。