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Untangling interactions: do temperature and habitat fragmentation gradients simultaneously impact biotic
Poppy Lakeman-Fraser1, Robert M Ewers2
1Centre for Environmental Policy, Imperial College London, South Kensington, London SW7 1NA, UK p.lakeman-fraser@imperial.ac.uk.
Proceedings. Biological Sciences
|June 6, 2014
Summary
Global environmental change drivers interact non-additively across trophic levels. Climate and habitat fragmentation impact species density and ecological processes differently, affecting food chains.
Area of Science:
- Ecology
- Environmental Science
- Conservation Biology
Background:
- Anthropogenic change impacts ecosystems through multiple drivers acting simultaneously.
- Few studies assess the combined effects of global change drivers across trophic levels.
- Understanding these interactions is crucial for predicting ecological responses.
Purpose of the Study:
- To investigate the interactive effects of climate and habitat fragmentation on a New Zealand tri-trophic food chain.
- To examine differential impacts on species density and biotic processes at each trophic level.
- To determine if drivers act additively or non-additively across the food chain.
Main Methods:
- Utilized temperature gradients as a surrogate for climate variation.
- Quantified habitat fragmentation by fragment area and distance to edges.
- Assessed impacts on plant, herbivore, and natural enemy densities and interactions.
- Measured herbivory and parasitoid attack rates as key biotic processes.
Main Results:
- Drivers acted non-additively across trophic levels.
- Synergistic interactions between location and fragmentation exacerbated negative effects on consumer density.
- Antagonistic interactions ameliorated impacts on plant density and trophic interactions.
- Differential effects observed on species density versus ecological processes.
Conclusions:
- Ecological consequences of multiple global change drivers are strongly interactive.
- Interactions vary significantly by trophic level and measured response (density vs. process).
- Findings highlight the complexity of predicting ecosystem responses to global change.
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