- Category: Ecological
- Subcategory: Ecosystem functioning & biodiversity
- Tool Type : Application of graph theory, conceptual model
- Input data: Species (presence/absence, or abundances/biomasses), links (presence/absence), body mass, metabolic rates, temperature etc.
- Output: Network, interaction structure, interaction strengths
- Target users: Scientists, other experts
- Location tested: Testing ongoing (Archipelago Sea, Bay of Biscay, Porsanger etc.)
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- Barnes et al. (2018) Energy flux: the link between multitrophic biodiversity and ecosystem functioning. Trends in Ecology and Evolution 33: 186-197
- Delmas et al. (2019) Analysing ecological networks of species interactions. Biological Reviews 94: 16-36
- Gauzens et al. (2019) fluxweb: an R package to easily estimate energy fluxes in food webs. Methods in Ecology and Evolution 10: 270-279
- Kortsch et al. (2021) Disentangling temporal food web dynamics facilitates understanding of ecosystem functioning. Journal of Animal Ecology 90: 1205-1216
- Kraufvelin et al. (in press) Warming simplifies marine ecological networks through losses in trophic and non-trophic interactions. Marine Ecology Progress Series (2026)
- Nordström & Bonsdorff (2017) Organic enrichment simplifies marine benthic food web structure. Limnology and Oceanography 62: 2179-2188
- Name: Marie C. Nordström
- Organization: University of Helsinki
- Email: nordstrom@helsinki.fi
Assessing Food Web Structure and Function Using Ecological Interaction Network Approaches and Bioenergetic Modelling
Ecological interaction networks consist of nodes (or vertices) and links (or edges) representing species in a community and the interactions among them. The interactions can represent feeding links, or trophic interactions, describing “who eats whom” in the food web. Trophic interactions represent a dimension of biodiversity that is central to the functioning and stability of marine ecosystems. The organisation of the network – its topological structure – can be described and quantified using different metrics. These can either be network-level metrics, describing e.g. the number of links and the connectance of the network, or species-level metrics, such as generality and vulnerability, which are properties that show some of the functional roles of different taxa. The feeding links can be binary or weighted, e.g., assigned an estimate of importance using bioenergetic modelling, taking advantage of allometric scaling laws to quantify metabolic rates. Interaction strength is here defined as energy flux, effectively a common currency of ecosystem functioning. Energy flux dynamics in networks elegantly link together biodiversity, structure, and ecosystem functioning, and many fluxes are further translatable to ecosystem services. In summary, flux-weighted interaction networks provide an approach with which one can examine shifts in biodiversity (species richness, composition, relative biomasses) and ecosystem functioning (flux of energy through the community) in changing marine ecosystems.
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