New frameworks for species surrogacy in monitoring highly variable coastal ecosystems: Applying the BestAgg approach to Mediterranean coastal lagoons

Benthic invertebrates are good indicators of aquatic ecosystem health. Yet, environmental monitoring and assessment of community changes in relation to both natural and human sources of disturbance involves considerable efforts for sample processing and time-consuming identifications of organisms, which make challenging large-scale and continuous monitoring programs required under the current regulatory frameworks at European scale. The use of higher taxa (e.g. families) as surrogates for species is a mainstream approach to reduce cost and time associated to fine taxonomic resolution in environmental studies, especially concerning macro-invertebrate communities. However, this approach of 'taxonomic sufficiency' simply relies on the static grouping of organisms in taxa belonging to a single higher taxonomic level irrespective of their ecological relevance or difficulties in their taxonomic identification, leading to unnecessary losses of taxonomic detail or ecological information. A new approach, namely the Best Practicable Aggregation of Species (BestAgg), has been recently developed as an alternative procedure for species surrogacy. BestAgg is based on aggregating species in the minimum number of surrogates sufficient to depict species-level community patterns consistently, while capitalizing on ecological information. Although the approach has been successfully applied to marine and freshwater invertebrate assemblages, its effectiveness in transitional water systems, where the complex and highly variable environmental conditions may affect the performance of surrogacy methods, still remain untested. Here, we applied the BestAgg approach to quantifying spatio-temporal patterns of variability of macro-invertebrate assemblages from Mediterranean coastal lagoons (Northern Adriatic Sea). Surrogates were defined using species-level data from a representative lagoon system, which served as pilot study. Then, they were used to analyze macro-invertebrate assemblages in two independent lagoons in the same geographic area. Results showed that BestAgg surrogates were effective in depicting multivariate patterns of macro-invertebrate assemblages as at species level over and beyond potential variations among the investigated lagoons. The use of families, following a more classic approach based on taxonomic sufficiency, also provided results comparable to those obtained using species. However, with respect to families, BestAgg surrogates allowed an estimated timesaving of 40% higher while still retaining an equivalent amount of information on species-level patterns. More importantly, BestAgg allowed exploiting different criteria of species aggregation, leading to a set of surrogates more aligned with ecological/functional characteristics of organisms, suggesting that BestAgg approach may provide a fresh perspective for optimizing trade-offs between pragmatism and the need for relevant ecological information in environmental assessment and monitoring.