Long‐term warming destabilizes aquatic ecosystems through weakening biodiversity‐mediated causal networks

Autor: George Sugihara, Yin-Ru Chiang, Orlane Anneville, Michio Kumagai, Fuh-Kwo Shiah, Satoshi Ichise, Ethan R. Deyle, Sami Souissi, Hao Ye, Chun-Wei Chang, Takeshi Miki, Rita Adrian, Shin-ichiro S. Matsuzaki, Chih-hao Hsieh, Jiunn-Tzong Wu
Přispěvatelé: Academia Sinica, National Taiwan Ocean University (NTOU), Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 (LOG), Centre National de la Recherche Scientifique (CNRS)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Institut national des sciences de l'Univers (INSU - CNRS), Centre Alpin de Recherche sur les Réseaux Trophiques et Ecosystèmes Limniques (CARRTEL), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB), Ritsumeikan University, National Taiwan University National Center for Theoretical Sciences Foundation for the Advancement of Outstanding Scholarship Ministry of Science and Technology, Taiwan Marie SklodowskaCurie-Actions, H2020-MSCA-ITN_2016 French Foundation for Research on Biodiversity Bio-Asia FASCICLE project Geisha project John Wesley Powell Center for Analysis and Synthesis, Institut national des sciences de l'Univers (INSU - CNRS)-Université du Littoral Côte d'Opale (ULCO)-Université de Lille-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Nord])
Rok vydání: 2020
Předmět:
Zdroj: Global Change Biology
Global Change Biology, Wiley, 2020, 26 (11), pp.6413-6423. ⟨10.1111/gcb.15323⟩
Global Change Biology, 2020, 26 (11), pp.6413-6423. ⟨10.1111/gcb.15323⟩
ISSN: 1365-2486
1354-1013
DOI: 10.1111/gcb.15323
Popis: International audience; Understanding how ecosystems will respond to climate changes requires unravelling the network of functional responses and feedbacks among biodiversity, physicochemical environments, and productivity. These ecosystem components not only change over time but also interact with each other. Therefore, investigation of individual relationships may give limited insights into their interdependencies and limit ability to predict future ecosystem states. We address this problem by analyzing long-term (16-39 years) time series data from 10 aquatic ecosystems and using convergent cross mapping (CCM) to quantify the causal networks linking phytoplankton species richness, biomass, and physicochemical factors. We determined that individual quantities (e.g., total species richness or nutrients) were not significant predictors of ecosystem stability (quantified as long-term fluctuation of phytoplankton biomass); rather, the integrated causal pathway in the ecosystem network, composed of the interactions among species richness, nutrient cycling, and phytoplankton biomass, was the best predictor of stability. Furthermore, systems that experienced stronger warming over time had both weakened causal interactions and larger fluctuations. Thus, rather than thinking in terms of separate factors, a more holistic network view, that causally links species richness and the other ecosystem components, is required to understand and predict climate impacts on the temporal stability of aquatic ecosystems.
Databáze: OpenAIRE
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