Reconstructing past environmental change in the Caribbean to inform ecosystem restoration and rewilding

Theme: Biodiversity, Ecology & Conservation

Primary Supervisor:

Helen Bennion

Geography, UCL

Helen Bennion's Profile Picture

Secondary Supervisor:

Samuel Turvey

Biodiversity and Macroecology Theme, IOZ

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Project Description:

The Caribbean island region has experienced dramatic environmental change over the Anthropocene, with different waves of human colonisation and changing anthropogenic land-use driving widespread ecosystem state shifts. Island-wide extirpation of Caribbean mammal faunas may reflect complex interactions between overexploitation and habitat loss. However, we currently lack quantitative spatial understanding of historical distributions of Caribbean ecosystems and biodiversity, and their change and loss through time, to identify key drivers of change and guide spatial conservation decision-making. Unpicking these long-term drivers of local extinction through reconstructing former ecosystem distributions and functions is needed to inform future targeted landscape planning, and the potential for rewilding and restoration of these global-priority tropical island systems.

This PhD will collate different lines of long-term environmental data to develop hindcast models of past ecosystem structure and spatiotemporal anthropogenic land-use across Caribbean island landscapes that represent candidates for rewilding, such as the Cayman Islands and Bahamas. It will use current and past climatic data with remote sensing, ecological niche modelling and palaeoecological studies to generate terrestrial ecosystem and species distribution models, and identify anthropogenic and climatic drivers of local environmental and biodiversity change. This will provide a new understanding of where rewilding and rehabilitation efforts are feasible and should be prioritised, to build ecosystem resilience and reduce future pressures.

Policy Impact of Research:

The research will provide a nuanced understanding of ecological responses to environmental change, and assess the usefulness of multi-disciplinary data sources for conservation planning. This approach will provide new data and techniques to spatially assess wider terrestrial rewilding and restoration opportunities.


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