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Content archived on 2024-05-29

Feedback mechanisms in models for ecological forecasts

Final Activity Report Summary - FEMMES (Feedback mechanisms in models for ecological forecasts)

We studied if hierarchical feedbacks buffer or amplify the effects of environmental change on ecological systems, how this alters their resistance and improves our ability to forecast the dynamics. We studied aquatic and terrestrial communities, focusing on: metabolism, dispersal in terrestrial plants and relationships between ecological and evolutionary dynamics in a spatial context.

Dr Dytham reviewed the literature on evolution of plant dispersal, vital for our modelling approach. He focused on continuous space in modelling and on highlight problems of discrete space in models, as well as on modelling variable habitat qualities in a spatially-explicit landscape with individual-based approaches. With Dr Schurr he tested range expansion using many dispersal parameters and repeated simulations with individual-based models. Dr Schurr worked on the evolutionary ecology of seed dispersal and the role of eco-evolutionary dynamics for the large-scale dynamics of invasive plants and species exposed to climate and land use change. While at Montpellier, he completed manuscripts on long-distance seed dispersal and the importance of mating decisions for bird demography. He also initiated several international collaborations on topics relevant to FEMMES.

Dr Walters developed an agent-based genetic model to explore extinction risk, adaptation and the role of local adaptations in spatially-structured populations. This complex model extends quantitative genetic models incorporating greater ecological complexity and space to address genotype-population feedbacks on maintaining genetic variance and the potential for adaptation. The results are the basis of further collaboration with colleagues at Zürich University where he now resides, to incorporate empirical data.

Dr Walters and Dr Schurr will use this model to assess the efficacy of different approaches to make forecasts. He also collaborated with Dr Weithoff on the adaptive significance of lifespan variance under temporally auto-correlated environments.

Dr de Castro worked on the role of body size in predator-prey relationships and community dynamics through its effects on metabolic rate. This was applied to several questions: a test of the Metabolic Theory of Ecology for plankton; a meta-analysis of field and basal metabolic rates of animals; a general model of community dynamics based on individual size and metabolic rate, and how size affects the evolution from mixotrophy to heterotrophy in algae, related to the high diversity of protists.

Dr Martínez helped to develop models combining ecology and economics (exploitation). He also collaborated with Alice Boit (host) with metabolic-based dynamic models of food webs. Both collaborations are on-going.

Dr Vos worked on individual-based cellular automaton models of a benthic community along a gradient of disturbance, with an extensive data set. The combined empirical-theoretical approach allowed to evaluate feedback between environmental change, community composition and ecosystem processes by the individuals along the gradient. He studied the responses of primary and secondary producers to temperature, the prevalence of algae toxin production and increased omnivory by consumers higher trophic levels. The community level consequences were explored using several methods: individual based models and differential equations.

Dr Moloney explored the eco-evolutionary dynamics of invasive species, analysing a large common garden experiment and a literature review. He keeps working on 3 manuscripts based on that work. Dr Fussmann worked on eco-evolutionary dynamics and how communities are impacted by environmental change. Together with T. Massie (Ph.D.) and Drs Gaedke, Weithoff (host), Blasius, he studied the dynamic links between cells and population cycles in experimental phytoplankton populations. He finished an experiment on the role of rising CO2 for phytoplankton community composition.