Biodiversity surrogates in freshwater environments: What determines their effectiveness?

Biodiversity surrogates, such as the Indicator Species Approach (ISA) and Higher-Taxon Approach (HTA), offer cost-effective alternatives to species-level identification. However, their reliability varies across studies. This article presents a large-scale evaluation of ISA and HTA using nearly 10,000 freshwater macroinvertebrate assemblages. We focused on two common surrogates: the EPT group (Ephemeroptera, Plecoptera, Trichoptera) as a proxy for the entire macroinvertebrate community (ISA), and family-level data as a proxy for species-level data (HTA). We tested whether sampling effort, the species:higher-taxon ratio, the proportional abundance of the most common species (i.e., community evenness), or environmental factors (human pressures, climate) influence surrogate performance. Overall, both ISA and HTA reliably represented alpha diversity and community structure, but performance was strongly context-dependent. Generalized Additive Mixed-effects Models (GAMMs) showed that assemblage characteristics were the main drivers of surrogate efficacy. A high species:higher-taxon ratio negatively affected family-based surrogates, indicating better performance in regions with fewer species per family. Community evenness had a positive effect, improving the reliability of family-based surrogates in communities dominated by a few species. Sampling effort also influenced the performance of EPT-based surrogates, improving congruence with species-level data under greater effort. Importantly, environmental variables had no significant effect, suggesting these surrogates are robust across broad environmental gradients; however, finer-scale studies that incorporate local, site-specific environmental variables - such as water quality parameters - remain necessary to fully assess the general applicability of these approaches. Our findings highlight that surrogate performance depends not on the method alone, but on taxonomic resolution, community structure, and sampling intensity. By identifying these mechanisms, we offer practical guidance for improving surrogate-based biomonitoring. Careful, site-specific selection of surrogate methods is essential to ensure accurate biodiversity assessments.