Data from: Relationship type affects the reliability of dispersal distance estimated using pedigree inferences in partially sampled populations: a case study involving invasive American mink in Scotland

Estimating dispersal—a key parameter for population ecology and management—is notoriously difficult. The use of pedigree assignments, aided by likelihood-based software, has become popular to estimate dispersal rate and distance. However, the partial sampling of populations may produce false assignments. Further, it is unknown how the accuracy of assignment is affected by the genealogical relationships of individuals and is reflected by software-derived assignment probabilities. Inspired by a project managing invasive American mink (Neovison vison), we estimated individual dispersal distances using inferred pairwise relationships of culled individuals. Additionally, we simulated scenarios to investigate the accuracy of pairwise inferences. Estimates of dispersal distance varied greatly when derived from different inferred pairwise relationships, with mother–offspring relationship being the shortest (average = 21 km) and the most accurate. Pairs assigned as maternal half-siblings were inaccurate, with 64%–97% falsely assigned, implying that estimates for these relationships in the wild population were unreliable. The false assignment rate was unrelated to the software-derived assignment probabilities at high dispersal rates. Assignments were more accurate when the inferred parents were older and immigrants and when dispersal rates between subpopulations were low (1% and 2%). Using 30 instead of 15 loci increased pairwise reliability, but half-sibling assignments were still inaccurate (>59% falsely assigned). The most reliable approach when using inferred pairwise relationships in polygamous species would be not to use half-sibling relationship types. Our simulation approach provides guidance for the application of pedigree inferences under partial sampling and is applicable to other systems where pedigree assignments are used for ecological inference.

扩散是种群生态学与种群管理的关键参数，对其进行估算向来极具挑战性。借助基于似然的软件开展谱系分配（pedigree assignments），已成为估算扩散速率与扩散距离的主流方法。然而，种群的部分抽样可能会导致错误分配。此外，个体的谱系关系如何影响分配准确率，以及软件输出的分配概率能否反映该准确率，目前仍不明确。本研究受入侵性美洲水鼬（Neovison vison）治理项目的启发，利用被捕杀个体的推断成对谱系关系，估算了个体的扩散距离。此外，我们通过模拟场景，探究了成对谱系推断的准确率。基于不同推断成对谱系关系得到的扩散距离估算值差异显著，其中母子（女）关系对应的扩散距离最短（平均为21千米）且准确率最高。被归类为母系半同胞的个体对准确率极低，错误分配率达64%~97%，这表明野生种群中基于此类关系的扩散距离估算并不可靠。在高扩散速率下，错误分配率与软件输出的分配概率并无关联。当推断的亲本年龄更大且为外来个体，以及亚种群间的扩散速率较低（1%和2%）时，谱系分配的准确率更高。使用30个基因座（loci）而非15个基因座可提升成对谱系推断的可靠性，但半同胞分配的准确率依然偏低（错误分配率超过59%）。在多配制物种中利用推断成对谱系关系开展研究时，最稳妥的方案是避免使用半同胞关系类型。本研究提出的模拟方法可为部分抽样条件下的谱系推断应用提供指导，同时也适用于其他通过谱系分配开展生态学推断的研究体系。