Data from: Linking genetic kinship and demographic analyses to characterize dispersal: methods and application to Blanding’s turtle

Characterizing how frequently, and at what life stages and spatial scales, dispersal occurs can be difficult, especially for species with cryptic juvenile periods and long reproductive life spans. Using a combination of mark–recapture information, microsatellite genetic data, and demographic simulations, we characterize natal and breeding dispersal patterns in the long-lived, slow-maturing, and endangered Blanding’s turtle (Emydoidea blandingii), focusing on nesting females. We captured and genotyped 310 individual Blanding’s turtles (including 220 nesting females) in a central Wisconsin population from 2010 to 2013, with additional information on movements among 3 focal nesting areas within this population available from carapace-marking conducted from 2001 to 2009. Mark–recapture analyses indicated that dispersal among the 3 focal nesting areas was infrequent (<0.03 annual probability). Dyads of females with inferred first-order relationships were more likely to be found within the same nesting area than split between areas, and the proportion of related dyads declined with increasing distance among nesting areas. The observed distribution of related dyads for nesting females was consistent with a probability of natal dispersal at first breeding between nearby nesting areas of approximately 0.1 based on demographic simulations. Our simulation-based estimates of infrequent female dispersal were corroborated by significant spatial genetic autocorrelation among nesting females at scales of <500 m. Nevertheless, a lack of spatial genetic autocorrelation among non-nesting turtles (males and females) suggested extensive local connectivity, possibly mediated by male movements or long-distance movements made by females between terrestrial nesting areas and aquatic habitats. We show here that coupling genetic and demographic information with simulations of individual-based population models can be an effective approach for untangling the contributions of natal and breeding dispersal to spatial ecology.厘清扩散发生的频率、所处生命阶段以及空间尺度颇具挑战，尤其是对于存在隐蔽幼体期且生殖寿命较长的物种而言。本研究结合标记重捕法（mark–recapture）信息、微卫星遗传数据（microsatellite genetic data）与种群人口统计学模拟（demographic simulations），针对长寿、生长缓慢且处于濒危状态的布氏拟龟（Emydoidea blandingii），聚焦筑巢雌性个体，解析其出生扩散（natal dispersal）与繁殖扩散（breeding dispersal）模式。2010至2013年间，我们在威斯康星州中部的一个种群中捕获并完成基因分型的布氏拟龟共计310只（其中包含220只筑巢雌性）；此外，2001至2009年通过背甲标记（carapace-marking）获得了该种群内3个核心筑巢区域间的移动相关信息。标记重捕法分析显示，3个核心筑巢区域间的扩散频率极低，年扩散概率<0.03。被推断具有一级亲缘关系（first-order relationships）的雌性配对，更倾向于出现在同一筑巢区域内，而非分散于不同区域；且亲缘配对的比例随筑巢区域间距离的增加而下降。基于种群人口统计学模拟，筑巢雌性的亲缘配对观测分布，与首次繁殖时在邻近筑巢区域间的出生扩散概率约为0.1的情形相符。我们基于模拟得到的雌性扩散频率较低的结果，得到了以下佐证：筑巢雌性在<500米尺度上存在显著的空间遗传自相关（spatial genetic autocorrelation）。尽管如此，非筑巢个体（雄性与雌性）并未表现出空间遗传自相关，这表明种群存在广泛的局部连通性，其介导方式可能为雄性移动，或是雌性在陆地筑巢区（terrestrial nesting areas）与水生栖息地（aquatic habitats）间进行的长距离移动。本研究表明，将遗传与种群人口统计学信息同基于个体的种群模型（individual-based population models）模拟相结合，可有效厘清出生扩散与繁殖扩散对空间生态学的贡献。