FN Archimer Export Format
PT J
TI Interpretation of interannual variability in long-term aquatic ecological surveys
BT 
AF Cauvy-Fraunié, Sophie
   Trenkel, Verena
   Daufresne, Martin
   Maire, Anthony
   Capra, Hervé
   Olivier, Jean-Michel
   Lobry, Jérémy
   Cazelles, Bernard
   Lamouroux, Nicolas
AS 1:1;2:2;3:3;4:4;5:5;6:6;7:7;8:8;9:5;
FF 1:;2:PDG-RBE-EMH;3:;4:;5:;6:;7:;8:;9:;
C1 Irstea Centre de Lyon-Villeurbanne, 89723, 5 rue la doua, Villeurbanne, France
   IFREMER - Centre de Nantes, 70611, Nantes, Pays de la Loire, France
   Irstea Centre d'Aix-en-Provence, 84233, Aix-en-Provence, Provence-Alpes-Côte d'Azur, France
   EDF R and D Site de Chatou, 151443, Chatou, Île-de-France, France
   Irstea Centre de Lyon-Villeurbanne, 89723, Villeurbanne, Rhône-Alpes , France
   Université Claude Bernard Lyon 1 Faculté des Sciences et Technologies, 200932, LEHNA, Villeurbanne, France
   Irstea Centre de Bordeaux, 84269, Cestas, Aquitaine, France
   ENS, 26909, Paris, Île-de-France, France
C2 IRSTEA, FRANCE
   IFREMER, FRANCE
   IRSTEA, FRANCE
   EDF, FRANCE
   IRSTEA, FRANCE
   UNIV LYON, FRANCE
   IRSTEA, FRANCE
   ENS, FRANCE
SI NANTES
SE PDG-RBE-EMH
IN WOS Ifremer UPR
   copubli-france
   copubli-p187
   copubli-univ-france
IF 1.685
TC 9
UR https://archimer.ifremer.fr/doc/00606/71805/70293.pdf
LA English
DT Article
CR EVHOE EVALUATION HALIEUTIQUE OUEST DE L'EUROPE
AB Long-term ecological surveys (LTES) often exhibit strong variability among sampling dates. The use and interpretation of such interannual variability is challenging due to the combination of multiple processes involved and sampling uncertainty. Here, we analysed the interannual variability in ~30 years of 150 species-density (fish and invertebrate) and environmental-observation time series in four aquatic-systems (stream, river, estuary, and marine continental shelf) with different sampling efforts to identify the information provided by this variability. We tested, using two empirical methods, whether we could observe simultaneous fluctuation between detrended time series corresponding to widely acknowledged assumptions about aquatic population dynamics: spatial effects, cohort effects, and environmental effects. We found a low number of significant results (36, 9, 0% for spatial, cohort, and environmental effects), suggesting that sampling uncertainty overrode the effects of biological processes. Our study does not question the relevance of LTES for detecting important trends, but clearly indicated that the statistical power to interpret interannual variations in aquatic-species densities is low, especially in large systems where the degree of sampling effort is always limited. 
PY 2020
PD MAY
SO Canadian Journal Of Fisheries And Aquatic Sciences
SN 0706-652X
PU Canadian Science Publishing
VL 77
IS 5
UT 000529378700010
BP 894
EP 903
DI 10.1139/cjfas-2019-0146
ID 71805
ER

EF