Data from: Shared spatial effects on quantitative genetic parameters: accounting for spatial autocorrelation and home range overlap reduces estimates of heritability in wild red deer

Social structure, limited dispersal and spatial heterogeneity in resources are ubiquitous in wild vertebrate populations. As a result, relatives share environments as well as genes, and environmental and genetic sources of similarity between individuals are potentially confounded. Quantitative genetic studies in the wild therefore typically account for easily captured shared environmental effects (e.g. parent, nest or region). Fine-scale spatial effects are likely to be just as important in wild vertebrates, but have been largely ignored. We used data from wild red deer to build ‘animal models’ to estimate additive genetic variance and heritability in four female traits (spring and rut home range size, offspring birth weight and lifetime breeding success). We then, separately, incorporated spatial autocorrelation and a matrix of home range overlap into these models to estimate the effect of location or shared habitat on phenotypic variation. These terms explained a substantial amount of variation in all traits and their inclusion resulted in reductions in heritability estimates, up to an order of magnitude up for home range size. Our results highlight the potential of multiple covariance matrices to dissect environmental, social and genetic contributions to phenotypic variation, and the importance of considering fine-scale spatial processes in quantitative genetic studies.

社会结构、有限扩散行为与资源空间异质性广泛存在于野生脊椎动物种群之中。受此影响，亲缘个体不仅共享基因，亦共享所处环境，而个体间相似性的环境来源与遗传来源往往存在混淆。故而野外定量遗传学研究通常会纳入易于量化的共享环境效应（例如亲本、巢穴或区域效应）。在野生脊椎动物类群中，精细尺度空间效应的重要性亦相当关键，但长期以来却遭到了广泛忽视。本研究借助野生马鹿的观测数据构建动物模型（animal model），对4项雌性性状的加性遗传方差与遗传力展开估算：春季家域面积、发情期家域面积、后代出生体重以及终身繁殖成功率。随后，我们分别在上述模型中纳入空间自相关项与家域重叠矩阵，以量化地理位置或共享生境对表型变异的影响。上述纳入的效应项能够解释所有性状的大量变异，且纳入这些项后，遗传力估算值出现了显著下降，其中家域面积的遗传力估算值降幅最高可达一个数量级。本研究结果证实，利用多重协方差矩阵可有效拆解环境、社会与遗传因素对表型变异的相对贡献，同时也凸显了在定量遗传学研究中纳入精细尺度空间过程的必要性与重要性。