How do environmental filtering and competition vary with spatial scale in ecological communities?

Theme: Biodiversity, Ecology & Conservation

Primary Supervisor:

Tom Fayle

School of Biological and Chemical Sciences, QMUL

Tom Fayle's Profile Picture

Secondary Supervisor:

Paul Eggleton

Life Sciences Department, NHM

Paul Eggleton's Profile Picture

Additional Supervisor(s):
Pavel Kratina (QMUL)

Project Description:

Competition causes species with similar ecological traits to segregate in space. Conversely, environmental filtering causes aggregation of species with traits that are adaptive to the local environment. Despite these clear predictions, the relative importance of competition and environmental filtering in structuring ecological communities remains poorly known. The balance between these two opposing drivers should vary with spatial scale, with competition driving community structure at small spatial scales, but environmental filtering driving structure at the larger scales over which the abiotic environment varies. This PhD project will test these predictions using ant communities as a model system. The project will leverage large open access databases both on global ant distributions (Global Ant Biodiversity Informatics project and on local ant communities (Gibb et al. 2017), many of which have associated functional trait data (Parr et al. 2017). These data will be supplemented by measurements made on ant specimens from the collections at the Natural History Museum, and online image databases (; Trait-related co-occurrence patterns will be investigated using null models of co-occurrence previously developed by the primary supervisor (Fayle et al. 2015), applied at a range of spatial scales. There will also be the opportunity to design and implement field experiments to test drivers of these patterns in tropical rain forest in Malaysian Borneo. This will be the first time that the relative importance of environmental filtering and competition have been assessed across a wide range of spatial scales, and will reveal major underlying mechanisms structuring global biodiversity.

Policy Impact of Research:

Understanding generalizable species assembly rules will allow for better management of biodiversity. For example, the spatial scale at which environmental filtering allows species co-existence can inform reserve design, while better models of trait-based competition could give early warning of potential invasive species, based on their functional traits.

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