Direct habitat descriptors improve the understanding of the organization of fish and macroinvertebrate communities across a large catchment.

In large-scale aquatic ecological studies, direct habitat descriptors (e.g. water temperature, hydraulics in river reaches) are often approximated by coarse-grain surrogates (e.g. air temperature, discharge respectively) since they are easier to measure or model. However, as biological variability can be very strong at the habitat scale, surrogate variables may have a limited ability to capture all of this variability, which may lead to a lesser understanding of the ecological processes or patterns of interest. In this study, we aimed to compare the capacity of direct habitat descriptors vs. surrogate environmental variables to explain the organization of fish and macroinvertebrate communities across the Loire catchment in France (105 km2). For this purpose, we relied on high-resolution environmental data, extensive biological monitoring data (>1000 sampling stations) and multivariate analyses. Fish and macroinvertebrate abundance datasets were considered both separately and combined to assess the value of a cross-taxa approach. We found that fish and macroinvertebrate communities exhibited weak concordance in their organization and responded differently to the main ecological gradients. Such variations are probably due to fundamental differences in their life-history traits and mobility. Regardless of the biological group considered, direct habitat descriptors (water temperature and local hydraulic variables) consistently explained the organization of fish and macroinvertebrate communities better than surrogate descriptors (air temperature and river discharge). Furthermore, the organization of fish and macroinvertebrate communities was slightly better explained by the combination of direct or surrogate environmental variables when the two biological groups were considered together than when considered separately. Tied together, these results emphasize the importance of using a cross-taxa approach in association with high-resolution direct habitat variables to more accurately explain the organization of aquatic communities.