Centre d'Ecologie Evolutive et Fonctionnelle UMR 5175, Campus CNRS, 1919 Route de Mende 34293 Montpellier Cedex 5, France.
Ecology. 2011 Aug;92(8):1672-9. doi: 10.1890/10-2224.1.
Both evolutionary ecologists and wildlife managers make inference based on how fitness and demography vary in space. Spatial variation in survival can be difficult to assess in the wild because (1) multisite study designs are not well suited to populations that are continuously distributed across a large area and (2) available statistical models accounting for detectability less than 1.0 do not easily cope with geographical coordinates. Here we use penalized splines within a Bayesian state-space modeling framework to estimate and visualize survival probability in two dimensions. The approach is flexible in that no parametric form for the relationship between survival and coordinates need be specified a priori. To illustrate our method, we study a game species, the Eurasian Woodcock Scolopax rusticola, based on band recovery data (5000 individuals) collected over a > 50 000-km2 area in west-central France with contrasted habitats and hunting pressures. We find that spatial variation in survival probability matches an index of hunting pressure and creates a mosaic of population sources and sinks. Such analyses could provide guidance concerning the spatial management of hunting intensity or could be used to identify pathways of spatial variation in fitness, for example, to study adaptation to changing landscape and climate.
进化生态学家和野生动物管理者都基于适应性和种群动态在空间上的变化来进行推断。由于（1）多地点研究设计不适用于在大面积连续分布的种群，以及（2）现有的考虑检测率小于 1.0 的统计模型不易处理地理坐标，因此在野外评估生存的空间变化具有一定难度。在这里，我们使用贝叶斯状态空间建模框架内的惩罚样条来估计和可视化二维空间中的生存概率。该方法非常灵活，因为不需要先验指定生存与坐标之间关系的参数形式。为了说明我们的方法，我们研究了一个游戏物种，欧亚云雀 Scolopax rusticola，该物种基于在法国中西部一个超过 50000 平方公里的地区收集的带回收数据（5000 个个体），该地区具有不同的生境和狩猎压力。我们发现，生存概率的空间变化与狩猎压力指数相匹配，并形成了一个由种群源和汇组成的镶嵌体。这种分析可以为狩猎强度的空间管理提供指导，也可以用于识别适应性的空间变化途径，例如，研究适应不断变化的景观和气候。
