Modelling butterfly abundance at varying spatial scales to inform conservation delivery

CASE award with Butterfly Conservation (MCCREA_K19ARIES)

Modelling butterfly abundance at varying spatial scales to inform conservation delivery

CASE award with Butterfly Conservation (MCCREA_K19ARIES)

Project Description

Supervisors

Dr Rachel McCrea (University of Kent)

Dr Emily Dennis (Butterfly Conservation)

Prof Tom Brereton (Butterfly Conservation)

Prof Byron Morgan (University of Kent)

Dr David Roy (Centre for Ecology and Hydrology)

Scientific background

Three-quarters of UK butterfly species have declined over the past four decades. Butterflies respond quickly to habitat and climatic change, hence their population status is a valuable biodiversity indicator. Analysis of long-term butterfly monitoring datasets has provided some of

the world’s best evidence of the biological impacts of climate change, including major phenological and distribution shifts, evolutionary responses and the impacts of extreme events.

Population trends are primarily assessed at national scales. This project will undertake more detailed analysis across spatial scales (e.g across regions, specific habitats or individual sites) to identify butterfly population responses to major drivers of change.  As well as delivering high impact scientific insight, this will underpin more effective conservation, from local land management to strategic planning across regions, including the production of new biodiversity indicators and site level alerts.

National-scale butterfly monitoring will be enhanced by refining survey guidance for threatened species, improving knowledge of butterfly lifespans and furthering methods for assessing species threatened status.

Research methodology

The project will involve new statistical model developments and incorporation of high-resolution land-cover data. The student will combine multiple complex ecological datasets and will produce new population metrics, accounting for the influence of external factors such as weather.

Training

The student will develop a strong, highly transferable skillset in statistical modelling and analysis using modern statistical and computational techniques applied to large, long-running datasets and will have the opportunity to undertake fieldwork to better understand the practical issues which arise with data collection.

The student will benefit from interactions with conservation professionals at Butterfly Conservation, researchers at the Centre for Ecology and Hydrology, and the statistical ecology group at the University of Kent (SE@K), which is a founder member of the National Centre for Statistical Ecology (NCSE).

At least three months will be spent at Butterfly Conservation, providing experience of data collection methods, field surveys and the use of data for conservation delivery.

Person specification

Applicants should have a good degree in a subject such as statistics, mathematics, or another scientific discipline with a substantial quantitative component. A keen interest in ecology is advantageous.

 

References

  • Dennis, E.B., Morgan, B.J.T., Freeman, S.N., Brereton, T.M. and Roy, D.B. (2016). A generalized abundance index for seasonal invertebrates. Biometrics, 72, 1305-1314.
  • Dennis, E.B., Morgan, B.J.T., Brereton, T., Freeman, S.N. and Roy, D.B. (2016). Dynamic models for longitudinal butterfly data. Journal of Agricultural, Biological, and Environmental Statistics, 21, 1-21.
  • Dennis, E.B., Morgan, B.J.T., Roy, D.B. and Brereton, T.M (2017). Urban indicators for UK butterflies. Ecological Indicators, 76, 184-193.
  • McCrea, R.S. and Morgan, B.J.T. (2014). Analysis of capture-recapture data. Chapman and Hall/CRC Press.
  • McCrea, R.S. Morgan, B.J.T. and Gimenez, O. (2016). A new strategy for diagnostic model assessment in capture-recapture. Journal of the Royal Statistical Society: Series C (Applied Statistics), 66, 815-831.

Open for applications

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