Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning
Studying how food web structure and function varies 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 analyzed 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.
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Åbo Akademi University
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Subjects: | Baltic Sea, community structure, ecological network analysis, energy fluxes, foodweb, topology, |
Online Access: | https://research.wur.nl/en/datasets/disentangling-temporal-food-web-dynamics-facilitates-understandin |
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Baltic Sea community structure ecological network analysis energy fluxes foodweb topology Baltic Sea community structure ecological network analysis energy fluxes foodweb topology |
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Baltic Sea community structure ecological network analysis energy fluxes foodweb topology Baltic Sea community structure ecological network analysis energy fluxes foodweb topology Kortsch, Susanne Frelat, Romain Pecuchet, Laurene Olivier, Pierre Putnis, Ivars Bonsdorff, Erik Ojaveer, Henn Jurgensone, Iveta Strāķe, Solvita Rubene, Gunta Krūze, Ēriks Nordström, Marie C. Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning |
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Studying how food web structure and function varies 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 analyzed 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. |
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Dataset |
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Baltic Sea community structure ecological network analysis energy fluxes foodweb topology |
author |
Kortsch, Susanne Frelat, Romain Pecuchet, Laurene Olivier, Pierre Putnis, Ivars Bonsdorff, Erik Ojaveer, Henn Jurgensone, Iveta Strāķe, Solvita Rubene, Gunta Krūze, Ēriks Nordström, Marie C. |
author_facet |
Kortsch, Susanne Frelat, Romain Pecuchet, Laurene Olivier, Pierre Putnis, Ivars Bonsdorff, Erik Ojaveer, Henn Jurgensone, Iveta Strāķe, Solvita Rubene, Gunta Krūze, Ēriks Nordström, Marie C. |
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Kortsch, Susanne |
title |
Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning |
title_short |
Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning |
title_full |
Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning |
title_fullStr |
Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning |
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Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning |
title_sort |
disentangling temporal food web dynamics facilitates understanding of ecosystem functioning |
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Åbo Akademi University |
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https://research.wur.nl/en/datasets/disentangling-temporal-food-web-dynamics-facilitates-understandin |
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dig-wur-nl-wurpubs-5971692024-12-23 Kortsch, Susanne Frelat, Romain Pecuchet, Laurene Olivier, Pierre Putnis, Ivars Bonsdorff, Erik Ojaveer, Henn Jurgensone, Iveta Strāķe, Solvita Rubene, Gunta Krūze, Ēriks Nordström, Marie C. Dataset Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning 2021 Studying how food web structure and function varies 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 analyzed 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. Studying how food web structure and function varies 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 analyzed 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. Åbo Akademi University text/html https://research.wur.nl/en/datasets/disentangling-temporal-food-web-dynamics-facilitates-understandin 10.5061/dryad.6t1g1jwwn https://edepot.wur.nl/569566 Baltic Sea community structure ecological network analysis energy fluxes foodweb topology Wageningen University & Research |