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.扩散估计——种群生态学与种群管理的核心参数之一——向来极具挑战性。借助基于似然的软件（likelihood-based software）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虚假分配结果。此外，个体的谱系关系如何影响分配准确性，以及软件输出的分配概率如何反映该准确性，目前仍不明确。本研究受入侵性美洲水鼬（Neovison vison）管理项目的启发，利用被灭杀个体的推断成对谱系关系，估算了个体扩散距离。此外，本研究通过模拟场景，探究了成对谱系推断的准确性。基于不同推断成对谱系关系得到的扩散距离估计值差异极大，其中母子/母女关系对应的扩散距离最短（平均为21千米）且准确性最高。被归类为母系半同胞（maternal half-siblings）的个体对的分配结果准确性极差，虚假分配比例达64%~97%，这表明基于该类谱系关系的野生种群扩散估计结果并不可靠。在高扩散速率场景下，虚假分配率与软件输出的分配概率并无关联。当推断出的亲本年龄更大、为外来迁入个体，且亚种群间扩散速率较低（1%与2%）时，谱系分配的准确性更高。相较于使用15个基因座（loci），使用30个基因座可提升成对谱系推断的可靠性，但半同胞（half-siblings）分配的准确性依然偏低（虚假分配比例超过59%）。在多配制物种中利用成对推断谱系关系开展研究时，最可靠的方案是避免使用半同胞类别的谱系关系。本研究提出的模拟方法可为部分抽样场景下的谱系推断应用提供指导，同时也适用于其他将谱系分配用于生态学推断的研究体系。