Data from: Optimising trait and source selection for explaining occurrence and abundance changes: a case study using British Butterflies

Functional traits that define the ecological role of an organism are increasingly being used to determine and predict responses to environmental change. Functional trait analyses of butterflies remain underexplored compared with other taxa, such as plants. Previous works using butterfly functional traits have not comprehensively addressed issues about the quality of trait data sets used and the relative predictive power of different trait types.

We compare the consistency of trait descriptions between six widely used trait sources for the British butterfly fauna. We analysed consistency of trait sources using Fleiss's kappa and ICC. PCA was used to produce species ordinations, comparing outputs to examine which trait sets were better at explaining recent species range and abundance changes within the UK.

There was a large range in congruence values for specific traits between sources. No single source can be relied upon to produce accurate trait information for British butterflies. Most trait sets are poor predictors of abundance and occurrence changes but are better at predicting current occurrence. An extensive trait set, supplementing biotope-related traits with explicit resource-based information recovers more informative ecological classifications and models than those primarily based on life-history traits or biotope descriptors. Smaller trait sets do, however, recover the specialist-generalist continuum.

We conclude that analyses of distribution and abundance changes that rely on traits are highly dependent on trait source and trait type. For butterflies, traits that are based on measures of biotope occupancy should be avoided in explaining changes of abundance and distribution. Including trait information that describes their resource requirements is essential for such analyses.

决定生物体生态作用的功能性状（functional trait）正愈发广泛地被用于确定和预测生物对环境变化的响应。相较于植物等其他生物类群，针对蝴蝶的功能性状分析仍有待深入开展。既往基于蝴蝶功能性状的相关研究，尚未全面厘清所用性状数据集的质量问题，以及不同性状类型的相对预测能力。

本研究针对英国蝴蝶区系，对比了6种常用性状数据源的性状描述一致性。采用弗莱西斯Kappa系数（Fleiss's kappa）与组内相关系数（ICC）分析各性状数据源的一致性；通过主成分分析（PCA）生成物种排序结果，并对比不同输出结果，以探究哪类性状集合更能解释英国境内近期物种种群分布范围与丰度的变化。

不同数据源针对特定性状的一致性数值差异显著。目前尚无任何一种数据源可可靠提供英国蝴蝶的精准性状信息。多数性状集合对种群丰度与分布变化的预测效果欠佳，但在预测当前物种分布状况时表现更优。相较于以生活史性状或生境描述为核心的数据集，将生境相关性状与明确的资源依赖信息相结合的大规模性状集合，可生成更具信息量的生态分类与模型。不过，规模较小的性状集合仍可还原物种的特化-泛化连续谱。

本研究得出结论：基于性状的物种分布与丰度变化分析，高度依赖性状数据源与性状类型。针对蝴蝶而言，基于生境占据情况测定的性状，不适用于解释其丰度与分布变化；纳入描述物种资源需求的性状信息，对这类分析而言至关重要。