Chun-Wei Chang, Takeshi Miki, Hao Ye, Sami Souissi, Rita Adrian, Orlane Anneville, Helen Agasild, Syuhei Ban, Yaron Be’eri-Shlevin, Yin-Ru Chiang, Heidrun Feuchtmayr, Gideon Gal, Satoshi Ichise, Maiko Kagami, Michio Kumagai, Xin Liu, Shin-Ichiro S. Matsuzaki, Marina M. Manca, Peeter Nõges, Roberta Piscia, Michela Rogora, Fuh-Kwo Shiah, Stephen J. Thackeray, Claire E. Widdicombe, Jiunn-Tzong Wu, Tamar Zohary, Chih-hao Hsieh, Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187 (LOG), 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]), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Centre Alpin de Recherche sur les Réseaux Trophiques et Ecosystèmes Limniques (CARRTEL), and Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Untangling causal links and feedbacks among biodiversity, ecosystem functioning, and environmental factors is challenging due to their complex and context-dependent interactions (e.g., a nutrient-dependent relationship between diversity and biomass). Consequently, studies that only consider separable, unidirectional effects can produce divergent conclusions and equivocal ecological implications. To address this complexity, we use empirical dynamic modeling to assemble causal networks for 19 natural aquatic ecosystems (N24°~N58°) and quantified strengths of feedbacks among phytoplankton diversity, phytoplankton biomass, and environmental factors. Through a cross-system comparison, we identify macroecological patterns; in more diverse, oligotrophic ecosystems, biodiversity effects are more important than environmental effects (nutrients and temperature) as drivers of biomass. Furthermore, feedback strengths vary with productivity. In warm, productive systems, strong nitratemediated feedbacks usually prevail, whereas there are strong, phosphate-mediated feedbacks in cold, less productive systems. Our findings, based on recovered feedbacks, highlight the importance of a network view in future ecosystem management. This work was supported by the National Center for Theoretical Sciences, National Taiwan University, Academia Sinica, Foundation for the Advancement of Outstanding Scholarship, and the Ministry of Science and Technology, Taiwan (to C.H.H.). Data for Oneida Lake were collected with support from Cornell University’s Brown Endowment, New York State Department of Environmental Conservation, and United States Department of Agriculture, National Institute of Food and Agriculture, Hatch Project 0226747. Research on Lake Maggiore is within the framework of the LTER Italian and European networks, site ‘IT-08 Southern Alpine lakes’’ and funded by the International Commission for the Protection of Swiss-Italian Waters (CIPAIS). Data for Lake Geneva were contributed by the Observatory of alpine LAkes (OLA), © SOERE OLA-IS, AnaEEFrance, INRAE of Thonon-les-Bains, CIPEL. Data for Lake Võrtsjärv were provided by Estonian Environment Agency and by the Centre for Limnology at Estonian University of Life Sciences funded by the Estonian Research Council grants PRG 1167 and PRG709. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951963. Data for Lake Kinneret were collected by the Kinneret Limnological Laboratory, Israel Oceanographic & Limnological Research, and funded by the Israel Water Authority, with phytoplankton counts made by T. Fishbein, chlorophyll determined by Y. Yacobi, physical data collected by Y. Lechinsky, chemical analyses conducted by Mekorot Water Company, Watershed Unit, under oversight by A. Nishri, and database management services provided by M. Shlichter. Data from Lake Inba were provided by Chiba Prefecture. Data from Lake Kasumigaura were provided by the National Institute for Environmental Studies (NIES). Data from Lake Biwa were provided by Shiga Prefecture. Data for Müggelsee were provided by the Leibniz-Institute of Freshwater Ecology and Inland Fisheries within their long-term research programme. Data collection at Windermere was supported by Natural Environment Research Council award number NE/R016429/1 as part of the UKSCaPE program delivering National Capability. Data for Station L4, Western Channel Observatory were collected by Plymouth Marine Laboratory as part of the UK’s Natural Environment Research Council’s National Capability CLASS Programme grant number NE/R015953/1, and is a contribution to Theme1.3 - Biological Dynamics. This is a contribution of GEISHA project, which was jointly supported by the French Foundation for Research on Biodiversity (FRB) through its synthesis center CESAB (http:// www.cesab.org/) and the John Wesley Powell Center for Analysis and Synthesis (https:// powellcenter.usgs.gov/). Comments from B. Kraemer, M. Kondoh, M. Ushio, and P. J. Ke on an earlier draft and English editing by J. Kastelic improved the manuscript. This work was supported by the National Center for Theoretical Sciences, National Taiwan University, Academia Sinica, Foundation for the Advancement of Outstanding Scholarship, and the Ministry of Science and Technology, Taiwan (to C.H.H.). Data for Oneida Lake were collected with support from Cornell University’s Brown Endowment, New York State Department of Environmental Conservation, and United States Department of Agriculture, National Institute of Food and Agriculture, Hatch Project 0226747. Research on Lake Maggiore is within the framework of the LTER Italian and European networks, site ‘IT-08 Southern Alpine lakes’’ and funded by the International Commission for the Protection of Swiss-Italian Waters (CIPAIS). Data for Lake Geneva were contributed by the Observatory of alpine LAkes (OLA), © SOERE OLA-IS, AnaEEFrance, INRAE of Thonon-les-Bains, CIPEL. Data for Lake Võrtsjärv were provided by Estonian Environment Agency and by the Centre for Limnology at Estonian University of Life Sciences funded by the Estonian Research Council grants PRG 1167 and PRG709. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 951963. Data for Lake Kinneret were collected by the Kinneret Limnological Laboratory, Israel Oceanographic & Limnological Research, and funded by the Israel Water Authority, with phytoplankton counts made by T. Fishbein, chlorophyll determined by Y. Yacobi, physical data collected by Y. Lechinsky, chemical analyses conducted by Mekorot Water Company, Watershed Unit, under oversight by A. Nishri, and database management services provided by M. Shlichter. Data from Lake Inba were provided by Chiba Prefecture. Data from Lake Kasumigaura were provided by the National Institute for Environmental Studies (NIES). Data from Lake Biwa were provided by Shiga Prefecture. Data for Müggelsee were provided by the Leibniz-Institute of Freshwater Ecology and Inland Fisheries within their long-term research programme. Data collection at Windermere was supported by Natural Environment Research Council award number NE/R016429/1 as part of the UKSCaPE program delivering National Capability. Data for Station L4, Western Channel Observatory were collected by Plymouth Marine Laboratory as part of the UK’s Natural Environment Research Council’s National Capability CLASS Programme grant number NE/R015953/1, and is a contribution to Theme1.3 - Biological Dynamics. This is a contribution of GEISHA project, which was jointly supported by the French Foundation for Research on Biodiversity (FRB) through its synthesis center CESAB (http:// www.cesab.org/) and the John Wesley Powell Center for Analysis and Synthesis (https:// powellcenter.usgs.gov/). Comments from B. Kraemer, M. Kondoh, M. Ushio, and P. J. Ke on an earlier draft and English editing by J. Kastelic improved the manuscript.