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Love (eating) thy neighbour? Understanding and predicting food-web structure and dynamics

Wootton, Kate (2020). Love (eating) thy neighbour? Understanding and predicting food-web structure and dynamics. Diss. (sammanfattning/summary) Sveriges lantbruksuniv., Acta Universitatis Agriculturae Sueciae, 1652-6880 ; 2020:43
ISBN 978-91-7760-604-8
eISBN 978-91-7760-605-5
[Doctoral thesis]

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Food webs are networks of feeding interactions that provide the backbone of ecological communities. The structure - who eats whom - and dynamics - how population abundances fluctuate as a result - of food webs depend on the traits of the species present. The exchange of individuals or material between food webs can have further consequences for the structure and dynamics of both the donor and recipient communities. Increasing our insight into how species traits constrain both structure and dynamics of food webs, and how this is affected by exchanges with other communities, will advance both the theory and predictive capacity of food-web ecology.
In this thesis, I make a multifaceted foray into the factors behind food-web structure and dynamics. To provide a general framework for selecting and applying traits to food-web interactions, I show how a trophic interaction can be broken into steps and, combined with traits, used to parameterize dynamic food-web models. The resulting framework is sufficiently general and flexible to be applied to any community and to guide comparison across diverse interaction types and ecosystems. Using this framework, I developed a dynamic model parameterized by body size and microhabitat use and applied it in a mesocosm experiment. I found that different versions of the model fit the data equally well, but generated vastly different predictions for interactions with a hypothetical new species. With data from a tritrophic Salix-galler-parasitoid network, I used a suite of statistical approaches to reveal different facets of the relationship between traits and network structure, finding that traits explained more of the galler-parasitoid than Salix-galler network, and that the relationship between traits and network structure was non-linear. Finally, I returned to dynamic models to address the question of how coupled food webs affect each other. I simulated food-web and soilnutrient dynamics in adjacent habitats differing in fertility and plant diversity. The foraging movement of consumers between habitats affected all elements of ecosystem function. This was especially evident in low fertility habitats coupled to high fertility habitats, with considerable applied and theoretical implications.
In total, I show that a trait-based approach to food webs has great promise for understanding food-web structure and dynamics and our ability to make accurate predictions, but that there are still a number of challenges to address. I lay out a framework and ground-work experiments for addressing some of these challenges, and show how the iteration between theory, empirical experiments, and analysis is ultimately required to reach the promise that trait-based approaches hold.

Authors/Creators:Wootton, Kate
Title:Love (eating) thy neighbour? Understanding and predicting food-web structure and dynamics
Series Name/Journal:Acta Universitatis Agriculturae Sueciae
Year of publishing :2020
Number of Pages:80
Publisher:Department of Ecology, Swedish University of Agricultural Sciences
ISBN for printed version:978-91-7760-604-8
ISBN for electronic version:978-91-7760-605-5
Publication Type:Doctoral thesis
Article category:Other scientific
Version:Published version
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 1 Natural sciences > 106 Biological Sciences (Medical to be 3 and Agricultural to be 4) > Ecology
Keywords:Species traits, ecological network, trophic interactions, habitat use, allometric trophic network model, foraging movement, trait-matching
Permanent URL:
ID Code:17486
Faculty:NJ - Fakulteten för naturresurser och jordbruksvetenskap
Department:(NL, NJ) > Dept. of Ecology
(S) > Dept. of Ecology
Deposited By: SLUpub Connector
Deposited On:04 Sep 2020 08:36
Metadata Last Modified:15 Jan 2021 19:48

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