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Biotic interaction models aid climate change predictions

Stemming the rapid loss of our planet’s biodiversity is one of the greatest challenges facing scientists and policymakers in the 21st century. The Earth’s ecosystems have been adversely affected by pollution and changes in land use, while the impact of climate change is expected to increase dramatically in the next decades.
Biotic interaction models aid climate change predictions
Scientists increasingly rely on computer-based models to make quantitative predictions of future biodiversity distribution under specific scenarios of climate change. Many factors complicate the assessment of climate change impact on biodiversity that are not well understood, such as uncertainties about complex biotic interactions within and across trophic levels.

The aim of the EU-funded project MATES (Understanding and predicting multispecies assemblages and interactions in space and time) was to improve the prediction of species assemblages in changing environments. Researchers used a diverse set of modelling tools including statistical analysis of spatial distribution data using Bayesian computation to elucidate important multispecies assemblages over time and space.

An individual-based community model was used to produce a set of consistent benchmarking data in multi-scale design with an array of important community and demographic processes. The benchmarking data was used as a new standard to test novel single and multi-species approaches. Results showed the predictive performance of a single species is strongly influenced by interactive effects of the species dispersal ability and by complex community interactions.

Project partners also used data about Swiss breeding bird communities to show that prediction accuracy is strongly influenced by a species habitat and resource requirements. In addition, plant communities were plotted along a steep temperature-moisture gradient in Switzerland to show unexpectedly high complexity of facilitation interactions. Facilitation intensity was strongest under cold stress, but facilitation frequency was higher under drought stress.

Finally, MATES designed a new functional-trait based approach for complexity reductions. This enabled researchers to simultaneously estimate biotic interactions between species within functional groups and between functional groups. These functional group-based joint-species distribution models (JSDMs) are being estimated and evaluated for the Swiss Breeding Bird data.

These advancements, comprehensive analyses and benchmark tests will provide the basis for more targeted research on multispecies interactions and community dynamics in the future. Understanding these complexities will be crucial for predicting the effects of climate change and the emergence of novel communities of species.

Related information

Keywords

Biodiversity, MATES, multi species assemblages, community model, joint-species distribution models
Record Number: 190979 / Last updated on: 2017-02-01
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