Diadromous fish modified timing of upstream migration over the last 30 years in France. (15th November 2020) - Legrand, Marion; Briand, Cédric; Buisson, Laëtitia; Besse, Timothée; Artur, Gwenaël; Azam, Didier; Baisez, Aurore; Barracou, David; Bourré, Nicolas; Carry, Laurent; Caudal, Anne‐Laure; Corre, Jérémie; et al.
Abstract: Numerous studies have documented a change in the phenology of migration of diadromous fish in response to climate change. Only few studies have, however, been conducted simultaneously for multiple species and at a large spatial scale. We investigated the change in the timing of upstream migration of diadromous fish species in France. We used an original dataset collected from 40 fish‐counting devices in 28 French rivers over 10–30 years for five diadromous taxa: Alosa spp., Anguilla anguilla (with a distinction between glass eel and yellow eel), Petromyzon marinus, Salmo salar, and Salmo trutta . Except for glass eel, we found that taxa shifted their migration for earlier arrival dates. This result is consistent with numerous studies reporting advancement of the phenology of species life‐events. On average, we highlighted a phenological change of −2.3 days per decade (min = −0.2, max = −3.7). Moreover, the North Atlantic Oscillation Index, sea surface temperature, air temperature, and river discharge were found to explain the timing of upstream migration of diadromous fish taxa, highlighting the importance of factors acting at different spatial scales. Given the important phenological changes observed in our study and more widely in the scientific literature, we recommend that managers incorporate these changes into the management rules; in particular, in the case of dams whose migratory transparency (i.e. the possibility for the fishes to cross the dam) is ensured by adaptive water management and gate operations. This study benefited from large‐scale monitoring of migratory phenology of multiple species and environmental variables. These monitoring data are valuable and could allow better predictive modelling of the response of species to climate change.