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Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning

Authors: Romain Frelat; Gunta Rubene; Susanne Kortsch; Solvita Strāķe; Pierre Olivier; Ēriks Krūze; Ivars Putnis; +7 Authors

Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning

Abstract

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.

Countries
Finland, Denmark, Norway, Netherlands
Keywords

ecological network analysis, topology, Food Chain, Baltic Sea, Ecological network analysis, Population Dynamics, Topology, Foodweb, Animals, Biomass, Ecosystem, food web, Baltic sea, Energy fluxes, energy fluxes, Community structure, community structure

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    37
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
37
Top 10%
Top 10%
Top 1%
Green
hybrid