Temporal changes in unweighted and weighted food webs in the Gulf of Riga (1981-2014)
Ståhl, Patrik (2022)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2022060242311
https://urn.fi/URN:NBN:fi-fe2022060242311
Tiivistelmä
Network research offers a framework to investigate how ecological food web structure and function varies over time, which allows addressing and anticipating changes in ecosystems. This understanding is of vital importance for shaping conservation efforts and ecosystem management in light of anthropogenic change. Our current understanding of how resolved food webs vary through time comes primarily from binary (presence/absence) networks. These networks ignore the strength of the trophic interactions. In contrast, weighted networks account for interaction strength (energy fluxes), and hence can reveal more subtle fluctuations in community structure through changes in the biomasses of species, and their fluxes, rather than just through fluctuations in species number and identity.
Using a time series of food webs constructed with long-term biomass data and highly resolved information on species trophic relationships, combined with a bioenergetic modeling approach, allowed the comparison how unweighted (topology-based) and weighted (flux-based) food web approaches differ with regard to modularity through time. The stability of food webs is thought to be enhanced by greater modularity, with respect to the spread of disturbances in a network, as said perturbations may be contained within the modules. Looking at modularity also facilitates the assessment of species functional roles through time by quantifying their position in the network related to modularity.
The analyses revealed that the link-weighted approach resulted in a more refined partitioning of network community structure (modularity) and how it changed over time. The weighted networks also showed more subtle changes in species roles, for example changes in how some species connect modules, giving a better understanding of how the functioning of the network changed over time. For example, the weighted food webs clearly captured a collapse of benthos in the mid-90s through its impact on modularity, which was hardly reflected in the unweighted version.
The results outlined in this thesis further support previous findings that the inclusion of flux-based information and link-weighted food web network analyses is vital to gain a more complete understanding of how ecological networks change through time with regard to their structure and functioning.
Using a time series of food webs constructed with long-term biomass data and highly resolved information on species trophic relationships, combined with a bioenergetic modeling approach, allowed the comparison how unweighted (topology-based) and weighted (flux-based) food web approaches differ with regard to modularity through time. The stability of food webs is thought to be enhanced by greater modularity, with respect to the spread of disturbances in a network, as said perturbations may be contained within the modules. Looking at modularity also facilitates the assessment of species functional roles through time by quantifying their position in the network related to modularity.
The analyses revealed that the link-weighted approach resulted in a more refined partitioning of network community structure (modularity) and how it changed over time. The weighted networks also showed more subtle changes in species roles, for example changes in how some species connect modules, giving a better understanding of how the functioning of the network changed over time. For example, the weighted food webs clearly captured a collapse of benthos in the mid-90s through its impact on modularity, which was hardly reflected in the unweighted version.
The results outlined in this thesis further support previous findings that the inclusion of flux-based information and link-weighted food web network analyses is vital to gain a more complete understanding of how ecological networks change through time with regard to their structure and functioning.