A non-Euclidean movement model to quantify landscape connectivity with open spatial capture-recapture models

Open Population Spatial Capture-Recapture (OPSCR) models provide a unifying framework to simultaneously model demography and movement while accounting for imperfect detection of individuals. In OPSCR models, movements of individuals between primary occasions usually follow a random walk process that neglects the role of the landscape. Here, we developed a non-Euclidean OPSCR model to explicitly estimate the extent to which individual movements are impeded or facilitated by spatial descriptors of the landscape, also referred to as landscape connectivity. We used simulations to validate the robustness of the model and then applied it to a 5-year, non-invasive genetic monitoring dataset of brown bears (Ursus arctos) in the Pyrenees mountain range (France, Spain and Andorra). We found smaller interannual movement of bears that were close to roads. The estimated resistance of the distance to roads was negative (-1.86 [-2.91, -0.37] and -1.77 [-2.85, -0.60] for females and males, respectively), meaning that the cost of moving increased close to roads. Our new OPSCR model provides a data-driven tool to assess the impact of landscape fragmentation on population connectivity using non-invasive spatial capture-recapture data.开放种群空间捕获-再捕获（Open Population Spatial Capture-Recapture, OPSCR）模型提供了统一的建模框架，可在同时对种群动态与个体移动进行建模的过程中，兼顾个体检测不完全的问题。在OPSCR模型中，个体在主要调查时段间的移动通常遵循随机游走过程，但该过程未考虑景观的影响作用。 在此研究中，我们开发了一种非欧几里得OPSCR模型，以明确估算景观空间特征（亦称为景观连通性）对个体移动的阻碍或促进程度。 我们通过模拟实验验证了该模型的稳健性，随后将其应用于一项为期5年的棕熊（Ursus arctos）非侵入式遗传监测数据集，该数据集采自法国、西班牙及安道尔境内的比利牛斯山脉。研究发现，靠近道路的棕熊年际移动幅度更小。本次估算得到的距道路距离对应的景观阻力值为负值（雌性为-1.86 [-2.91, -0.37]，雄性为-1.77 [-2.85, -0.60]），这意味着靠近道路时的移动成本更高。 我们提出的新型OPSCR模型提供了一种数据驱动的工具，可利用非侵入式空间捕获-再捕获数据评估景观破碎化对种群连通性的影响。