How do anthropogenic threats reorganise insect communities?

Lead Research Organisation: University College London
Department Name: Genetics Evolution and Environment

Abstract

Insects play crucial roles in natural and managed ecosystems. They have been in rapid decline in some places around the world, but the extent of and reasons for this decline are not yet fully understood. This project aims to understand how selected threats reshape insect communities - structurally as well as in terms of overall diversity - thereby improving understanding of where declines would be expected and the ecological impacts they are likely to have. The PREDICTS database, which has collated site-level data on many thousands of terrestrial insect communities facing threats relating to land-use change, allows detailed modelling of how land use and related pressures affect different taxonomic and functional groups of insects. GLiTRS, a large NERC-funded collaboration to develop and validate a threat-response model for insects, is broadening the approach in developing a database that also considers other threats. However, because most of the data sources in those databases have sampled only single groups using single sampling methods, analyses cannot consider linked responses among groups, restricting the development of more mechanistic models. This is a problem because mechanistic models can provide a much richer ecological understanding than purely correlational models, which tend to be more descriptive. By collating and then synthesising datasets that have sampled multiple interacting insect (and even non-insect) functional groups in sites facing threats, this project will deliver deeper insights into how and why insect communities are changing. Correlational models such as general linear mixed-effects models (GLMMs) can test whether different taxa or functional groups respond differently to threats, and even to determine which ways of grouping species maximise explanatory power. Approaches such as Structural Equation Modelling can go further towards testing among alternative possible impact pathways, including both direct and indirect effects plus, where data permit, interactions among multiple threats. This work will be facilitated by access to the data (including functional trait data) from the GLiTRS and PREDICTS projects and the breadth and depth of entomological expertise at NHM.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/S007229/1 01/10/2019 30/09/2027
2547082 Studentship NE/S007229/1 01/10/2021 26/09/2025 Justin Isip