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

Abstract

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.

Past and future discharge and stream temperature at high spatial resolution in a large European basin (Loire basin, France)

“…studies of Arismendi et al, 2013;Arevalo et al, 2020), to better explain and predict the possible spatial distribution of aquatic communities (e.g. study of Picard et al, 2022, who used the current dataset), and to assess the various stresses on freshwater habitat due to climate change (e.g. Lee et al, 2020).…”

“…Stream (water) temperature (Tw) is a critical parameter affecting the eutrophication of water bodies (Minaudo et al, 2018; Le Moal et al, 2019;Zhao et al, 2022), a wide range of biogeochemical processes (Ouellet et al, 2020), the life cycle (Elliott and Elliott, 2010) and spatial distribution of aquatic organisms (Cox and Rutherford, 2000;Morales-Marín et al, 2019;Picard et al, 2022). Recent evidence suggests the worldwide rise in this critical parameter due to climate change over the past decades (e.g.…”

Shadow distributions: Deconstructing the geography of human impacts on species' natural distribution

“…Our interpretations can only be as good as the data underlying the model. For our study, we could not yet include rarely-available local variables that can more accurately recover species responses to environmental variation 75 . We also had to omit potentially important threats without available data, such as multiple forms of pollution, the alteration of natural flow regimes through hydropower generation, and the location of extreme drought events.…”

Past and future discharge and stream temperature at high spatial resolution in a large European basin (Loire basin, France)

“…Stream (water) temperature (T w ) is a critical parameter affecting the eutrophication of water bodies (Minaudo et al, 2018;Le Moal et al, 2019;Zhao et al, 2022), a wide range of biogeochemical processes (Ouellet et al, 2020), and the life cycle (Elliott and Elliott, 2010) and spatial distribution of aquatic organisms (Cox and Rutherford, 2000;Morales-Marín et al, 2019;Picard et al, 2022). Recent evidence suggests the worldwide rise in this critical parameter due to climate change over the past decades (e.g., Moatar and Gailhard, 2006;Orr et al, 2015;Arora et al, 2016;Michel et al, 2020;Seyedhashemi et al, 2022b), which is also anticipated to continue in the future (e.g., Kwak et al, 2017;Carlson et al, 2017;Seixas et al, 2018;Du et al, 2019;Lee et al, 2020;Piotrowski et al, 2021;Michel et al, 2022).…”