One century of eel growth: changes and implications

• Published in: Ecology of Freshwater Fish
• Main Authors: Daverat, Françoise, Beaulaton, Laurent, Poole, R., Lambert, Patrick, Wickström, H., Andersson, J., Aprahamian, Miran, Hizem, B., Elie, Pierre, Gumus, A.
• Other Authors: Ecosystèmes estuariens et poissons migrateurs amphihalins (UR EPBX), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Agence Française pour la Biodiversité (AFB), MARINE INSTITUTE MAYO IRL, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), SWEDISH BOARD OF FISHERIES DROTTNINGHOLM SWE, SWEDISH BOARD OF FISHERIES FIGEHOLM SWE, ENVIRONMENT AGENCY NORTH WEST REGION WARRINGTON GBR, INSTM SALAMMBO TUN, ONDOKUZMAYIS UNIVERSITY SAMSUN TUR
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2012
• Subjects: [SDE]Environmental Sciences; Anguilla anguilla
• Online Access: https://hal.inrae.fr/hal-02597028; https://doi.org/10.1111/j.1600-0633.2011.00541.x

International audience A cooperative effort gathered a large European length-at-age data set (N = 45,759, Lat. 36S–61N Long.10W–27E) for Anguilla anguilla, covering one century. To assess the effect of global warming during the last century and habitat effects on growth, a model was fitted on the data representing the conditions met at the distribution area scale. Two GLMs were designed to predict eel log(GR): one model was fitted to the whole data and the other was fitted to the female data subset. A model selection procedure was applied to select the best predictors among sex, age class, five temperature parameters and six habitat parameters (depth, salinity and four variables related to the position in the catchment). The yearly sum of temperatures above 13 °C (TempSUP13), the relative distance within the catchment, sex, age class, salinity class and depth class were finally selected. The best model predicted eel log(GR) with a 64.46% accuracy for the whole data and 66.91% for the female eel data. Growth rate (GR) was greater in habitats close to the sea and in deep habitats. TempSUP13 variable had one of the greatest predictive powers in the model, showing that global warming had affected eel growth during the last century.