Justin Isip

Justin Isip

Profile
Profile Display Name:

Justin Isip

E-mail Address:

justin.isip.21@ucl.ac.uk

Start Year

2021 (Cohort 8)

Research interests:
Hobbies and interests:

PhD Project
PhD Title

How do anthropogenic threats reorganise insect communities?

Research Theme

Biodiversity, Ecology and Conservation

Primary Supervisor
Primary Institution

NHM

Secondary Supervisor
Secondary Institution

UCL

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.

Policy Impact
Background Reading
Collaborators

Global Insect Threat Response Synthesis (GLiTRS is a consortium of six institutions in the UK and South Africa, with partners around the world.) website: https://glitrs.ceh.ac.uk/

Publications
Datasets

Lepidosaur bite-force data These are the data required for the analyses. Full metadata are provided for the raw data, and the data used to build the sub-datasets for each analysis. All are included here for completeness. For more details see https://github.com/nhcooper123/lepidosaur-biteforce.. Contributors: JE Isip, MEH Jones, N Cooper

Activities
Conferences and Workshops

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