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      The geography of metapopulation synchrony in dendritic river networks

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          Abstract

          Dendritic habitats, such as river ecosystems, promote the persistence of species by favouring spatial asynchronous dynamics among branches. Yet, our understanding of how network topology influences metapopulation synchrony in these ecosystems remains limited. Here, we introduce the concept of fluvial synchrogram to formulate and test expectations regarding the geography of metapopulation synchrony across watersheds. By combining theoretical simulations and an extensive fish population time‐series dataset across Europe, we provide evidence that fish metapopulations can be buffered against synchronous dynamics as a direct consequence of network connectivity and branching complexity. Synchrony was higher between populations connected by direct water flow and decayed faster with distance over the Euclidean than the watercourse dimension. Likewise, synchrony decayed faster with distance in headwater than mainstem populations of the same basin. As network topology and flow directionality generate fundamental spatial patterns of synchrony in fish metapopulations, empirical synchrograms can aid knowledge advancement and inform conservation strategies in complex habitats.

          Abstract

          Synchrony between spatially separated populations influences species persistence and ecosystem stability. We provide theoretical and empirical evidence that in dendritic habitats, such as river ecosystems, network topology and flow directionality generate fundamental spatial patterns in fish metapopulation synchrony. We articulate an empirical geography of synchrony within river basins that allow predicting synchrony patterns even if population time‐series data are not available.

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          Biodiversity as spatial insurance in heterogeneous landscapes.

          The potential consequences of biodiversity loss for ecosystem functioning and services at local scales have received considerable attention during the last decade, but little is known about how biodiversity affects ecosystem processes and stability at larger spatial scales. We propose that biodiversity provides spatial insurance for ecosystem functioning by virtue of spatial exchanges among local systems in heterogeneous landscapes. We explore this hypothesis by using a simple theoretical metacommunity model with explicit local consumer-resource dynamics and dispersal among systems. Our model shows that variation in dispersal rate affects the temporal mean and variability of ecosystem productivity strongly and nonmonotonically through two mechanisms: spatial averaging by the intermediate-type species that tends to dominate the landscape at high dispersal rates, and functional compensations between species that are made possible by the maintenance of species diversity. The spatial insurance effects of species diversity are highest at the intermediate dispersal rates that maximize local diversity. These results have profound implications for conservation and management. Knowledge of spatial processes across ecosystems is critical to predict the effects of landscape changes on both biodiversity and ecosystem functioning and services.
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            Spatial Synchrony in Population Dynamics*

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                Author and article information

                Contributors
                larsen.stefano@gmail.com
                Journal
                Ecol Lett
                Ecol Lett
                10.1111/(ISSN)1461-0248
                ELE
                Ecology Letters
                John Wiley and Sons Inc. (Hoboken )
                1461-023X
                1461-0248
                22 February 2021
                April 2021
                : 24
                : 4 ( doiID: 10.1111/ele.v24.4 )
                : 791-801
                Affiliations
                [ 1 ] Unit of Computational Biology Research and Innovation Centre Fondazione Edmund Mach via E. Mach 1 San Michele all'Adige 38010 Italy
                [ 2 ] Department of Civil Environmental and Mechanical Engineering University of Trento Trento Italy
                [ 3 ] School of Aquatic and Fishery Sciences University of Washington Seattle WA 98105 USA
                [ 4 ] School of Biological Sciences Illinois State University Normal IL 61790 USA
                [ 5 ] CIBIO/InBio Centro de Investigação em Biodiversidade e Recursos Genéticos Universidade do Porto Vairão Portugal
                [ 6 ] Instituto Superior de Agronomia Universidade de Lisboa Lisboa Portugal
                [ 7 ] Department of Ecology and Evolutionary Biology University of Toronto Toronto ON M5S 3B2 Canada
                [ 8 ] Department of Aquatic Ecology Swiss Federal Institute of Aquatic Science and Technology Eawag, Dübendorf Switzerland
                [ 9 ] Complex Systems Lab INRAE – Centre Clermont‐Auvergne‐Rhône‐Alpes 9 avenue Blaise Pascal Aubière, 63170 France
                [ 10 ] Department of Evolutionary Biology and Environmental Studies University of Zurich Zürich Switzerland
                [ 11 ] German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig Leipzig 04103 Germany
                [ 12 ] Institute of Biodiversity Friedrich‐Schiller‐University Jena Jena 07743 Germany
                [ 13 ] UMR EDB CNRS 5174 UPS Université Paul Sabatier IRD 253 Toulouse France
                [ 14 ] MTA Centre for Ecological Research Balaton Limnological Institute Klebelsberg K. u. 3 Tihany 8237 Hungary
                [ 15 ] Biology Department Southern California Coastal Water Research Project Costa Mesa CA 92626 USA
                [ 16 ] Department of Environmental Science, Policy, and Management University of California Berkeley, Berkeley CA 94720 USA
                [ 17 ] Department of Biology York University 4700 Keele Street Toronto ON M3J 1P3 Canada
                Author notes
                [*] [* ] Correspondence: E‐mail: larsen.stefano@ 123456gmail.com

                Author information
                https://orcid.org/0000-0002-6774-1407
                https://orcid.org/0000-0001-8030-0019
                https://orcid.org/0000-0001-7862-2676
                https://orcid.org/0000-0002-9935-1366
                https://orcid.org/0000-0002-7913-0689
                https://orcid.org/0000-0002-3771-8986
                https://orcid.org/0000-0001-5972-5928
                https://orcid.org/0000-0001-9156-583X
                https://orcid.org/0000-0002-2252-3115
                https://orcid.org/0000-0002-5239-9477
                https://orcid.org/0000-0002-6582-7979
                https://orcid.org/0000-0003-4011-6457
                https://orcid.org/0000-0003-4571-2768
                https://orcid.org/0000-0003-2143-1187
                Article
                ELE13699
                10.1111/ele.13699
                8049041
                33619868
                61e2135e-8b38-4f6b-a017-49eb3478a9c5
                © 2021 The Authors. Ecology Letters published by John Wiley & Sons Ltd.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 30 September 2020
                : 13 August 2020
                : 07 January 2021
                Page count
                Figures: 7, Tables: 1, Pages: 11, Words: 8123
                Funding
                Funded by: H2020 Environment , open-funder-registry 10.13039/100010681;
                Award ID: Grant Agreement No. 748969
                Funded by: Deutsche Forschungsgemeinschaft , open-funder-registry 10.13039/501100001659;
                Award ID: FTZ 118
                Categories
                Letter
                Letters
                Custom metadata
                2.0
                April 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:15.04.2021

                Ecology
                fish time‐series,fluvial variography,metapopulations,network topology,spatial patterns,spatial synchrony

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