Literature DB >> 33608888

Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning.

Susanne Kortsch1, Romain Frelat2, Laurene Pecuchet1,3, Pierre Olivier1, Ivars Putnis4, Erik Bonsdorff1, Henn Ojaveer5,6, Iveta Jurgensone7, Solvita Strāķe7, Gunta Rubene4, Ēriks Krūze4, Marie C Nordström1.   

Abstract

Studying how food web structure and function vary through time represents an opportunity to better comprehend and anticipate ecosystem changes. Yet, temporal studies of highly resolved food web structure are scarce. With few exceptions, most temporal food web studies are either too simplified, preventing a detailed assessment of structural properties or binary, missing the temporal dynamics of energy fluxes among species. Using long-term, multi-trophic biomass data coupled with highly resolved information on species feeding relationships, we analysed food web dynamics in the Gulf of Riga (Baltic Sea) over more than three decades (1981-2014). We combined unweighted (topology-based) and weighted (biomass- and flux-based) food web approaches, first, to unravel how distinct descriptors can highlight differences (or similarities) in food web dynamics through time, and second, to compare temporal dynamics of food web structure and function. We find that food web descriptors vary substantially and distinctively through time, likely reflecting different underlying ecosystem processes. While node- and link-weighted metrics reflect changes related to alterations in species dominance and fluxes, unweighted metrics are more sensitive to changes in species and link richness. Comparing unweighted, topology-based metrics and flux-based functions further indicates that temporal changes in functions cannot be predicted using unweighted food web structure. Rather, information on species population dynamics and weighted, flux-based networks should be included to better comprehend temporal food web dynamics. By integrating unweighted, node- and link-weighted metrics, we here demonstrate how different approaches can be used to compare food web structure and function, and identify complementary patterns of change in temporal food web dynamics, which enables a more complete understanding of the ecological processes at play in ecosystems undergoing change.
© 2021 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Keywords:  Baltic Sea; community structure; ecological network analysis; energy fluxes; food web; topology

Year:  2021        PMID: 33608888     DOI: 10.1111/1365-2656.13447

Source DB:  PubMed          Journal:  J Anim Ecol        ISSN: 0021-8790            Impact factor:   5.091


  5 in total

1.  Temporal and spatial changes in benthic invertebrate trophic networks along a taxonomic richness gradient.

Authors:  Julie A Garrison; Marie C Nordström; Jan Albertsson; Francisco J A Nascimento
Journal:  Ecol Evol       Date:  2022-06-05       Impact factor: 3.167

2.  Food web rewiring drives long-term compositional differences and late-disturbance interactions at the community level.

Authors:  Francesco Polazzo; Tomás I Marina; Melina Crettaz-Minaglia; Andreu Rico
Journal:  Proc Natl Acad Sci U S A       Date:  2022-04-19       Impact factor: 12.779

Review 3.  Food web assessments in the Baltic Sea: Models bridging the gap between indicators and policy needs.

Authors:  Samuli Korpinen; Laura Uusitalo; Marie C Nordström; Jan Dierking; Maciej T Tomczak; Jannica Haldin; Silvia Opitz; Erik Bonsdorff; Stefan Neuenfeldt
Journal:  Ambio       Date:  2022-01-29       Impact factor: 6.943

4.  Network analysis suggests changes in food web stability produced by bottom trawl fishery in Patagonia.

Authors:  Manuela Funes; Leonardo A Saravia; Georgina Cordone; Oscar O Iribarne; David E Galván
Journal:  Sci Rep       Date:  2022-06-27       Impact factor: 4.996

5.  DNA metabarcoding reveals trophic niche diversity of micro and mesozooplankton species.

Authors:  Andreas Novotny; Sara Zamora-Terol; Monika Winder
Journal:  Proc Biol Sci       Date:  2021-06-16       Impact factor: 5.349

  5 in total

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