Interpretation of interannual variability in long-term aquatic ecological surveys

被引:10
|
作者
Cauvy-Fraunie, Sophie [1 ]
Trenkel, Verena M. [2 ]
Daufresne, Martin [3 ]
Maire, Anthony [4 ]
Capra, Herve [1 ]
Olivier, Jean-Michel [5 ]
Lobry, Jeremy [6 ]
Gazelles, Bernard [7 ,8 ]
Lamouroux, Nicolas [1 ]
机构
[1] Irstea, UR RIVERLY, Ctr Lyon Villeurbanne, Villeurbanne, France
[2] IFREMER, BP 21105, Nantes 44311 3, France
[3] Irstea, UR Recover, Aix En Provence 13182, France
[4] EDF R&D, LNHE Lab Natl Hydraul & Environm, Chatou, France
[5] Univ Claude Bernard Lyon 1, Univ Lyon, CNRS, ENTPE,UMR 5023,LEHNA, F-69622 Villeurbanne, France
[6] Irstea, UR EABX, Ctr Bordeaux, F-33612 Cestas, France
[7] UMMISCO, IRD UPMC UMI 209, Bondy 93143, France
[8] Ecole Normale Super, IBENS, CNRS, UMR 8197, Paris 75005, France
关键词
AGE-0; RAINBOW-TROUT; FISH COMMUNITY; TIME-SERIES; BROWN TROUT; STATISTICAL POWER; HABITAT USE; RIVER; DENSITY; POPULATIONS; SYNCHRONY;
D O I
10.1139/cjfas-2019-0146
中图分类号
S9 [水产、渔业];
学科分类号
0908 ;
摘要
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 similar to 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%, and 0% for spatial, cohort, and environmental effects, respectively), 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 indicates 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.
引用
收藏
页码:894 / 903
页数:10
相关论文
共 50 条
  • [1] Long-term trends of interannual variability in the California Current system
    Lluch-Belda, D
    Laurs, RM
    Lluch-Cota, DB
    Lluch-Cota, SE
    CALIFORNIA COOPERATIVE OCEANIC FISHERIES INVESTIGATIONS REPORTS, 2001, 42 : 129 - 144
  • [3] Interannual variability and long-term trends in upper tropospheric humidity
    Bates, JJ
    12TH SYMPOSIUM ON GLOBAL CHANGE AND CLIMATE VARIATIONS, 2001, : 148 - 151
  • [4] On the long-term interannual variability of the east Asian winter monsoon
    D'Arrigo, R
    Wilson, R
    Panagiotopoulos, F
    Wu, BY
    GEOPHYSICAL RESEARCH LETTERS, 2005, 32 (21) : 1 - 4
  • [5] Long-term variability of zooplankton populations in aquatic mesocosms
    Knauer, K
    Maise, S
    Thoma, G
    Hommen, U
    Gonzalez-Valero, J
    ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY, 2005, 24 (05) : 1182 - 1189
  • [6] Long-term warming and interannual variability contributions' to marine heatwaves in the Mediterranean
    Simon, Amelie
    Pires, Carlos
    Frolicher, Thomas L.
    Russo, Ana
    WEATHER AND CLIMATE EXTREMES, 2023, 42
  • [7] INTERANNUAL AND LONG-TERM VARIABILITY OF INDIAN-SUMMER MONSOON RAINFALL
    PARTHASARATHY, B
    PROCEEDINGS OF THE INDIAN ACADEMY OF SCIENCES-EARTH AND PLANETARY SCIENCES, 1984, 93 (04): : 371 - 385
  • [8] Long-term seasonal and interannual variability of marine aerobic anoxygenic photoheterotrophic bacteria
    Adrià Auladell
    Pablo Sánchez
    Olga Sánchez
    Josep M. Gasol
    Isabel Ferrera
    The ISME Journal, 2019, 13 : 1975 - 1987
  • [9] Long-term fluxes of carbonyl sulfide and their seasonality and interannual variability in a boreal forest
    Vesala, Timo
    Kohonen, Kukka-Maaria
    Kooijmans, Linda M. J.
    Praplan, Arnaud P.
    Foltynova, Lenka
    Kolari, Pasi
    Kulmala, Markku
    Back, Jaana
    Nelson, David
    Yakir, Dan
    Zahniser, Mark
    Mammarella, Ivan
    ATMOSPHERIC CHEMISTRY AND PHYSICS, 2022, 22 (04) : 2569 - 2584
  • [10] Interannual variability in summer climate change controls GPP long-term changes
    He, Panxing
    Ma, Xiaoliang
    Sun, Zongjiu
    ENVIRONMENTAL RESEARCH, 2022, 212