Evaluating Biodiversity Metrics for Detecting Climate-Driven Ecological Change

To investigate the long-term effects of climate change on biological communities, our primary aim was to identify the most reliable indicators among available biodiversity, dominance, and evenness indices. We examined three distinct response types to climate change, represented by three taxonomic groups: Aculeata (Hymenoptera), Syrphidae (Diptera), and nocturnal macrolepidoptera (Lepidoptera). Using faunistic datasets derived from our own 3–5 decades of field surveys, we calculated 12 key indices with the vegan package in R 4.2.1. The robustness of these indices was assessed through 1000-fold bootstrap simulations and pairwise correlation analyses. Our results revealed that the Gini–Simpson, Simpson diversity, McIntosh diversity, and McIntosh evenness indices consistently demonstrated high temporal stability and strong correlations across all three climate response types. Therefore, we recommend these indices as primary climate indicators. In contrast, Chao1 estimates, Margalef Index, Menhinick Index, and the Shannon–Wiener diversity index are suitable only for analyzing specific response patterns. Meanwhile, the Berger–Parker, Buzas–Gibson indices, and Hill numbers showed high variability or limited ecological responsiveness, making them unreliable for tracking climate change impacts. Our findings underscore that selecting biodiversity indices must be tailored to the research question and the characteristics of the ecosystem in order to ensure valid and informative ecological analysis.