Patterns and process in population trends of UK herpetofauna

CASE award with Amphibian and Reptile Conservation (ISAAC_KCEH20ARIES)

Patterns and process in population trends of UK herpetofauna

CASE award with Amphibian and Reptile Conservation (ISAAC_KCEH20ARIES)

Project Description


Dr Nick Isaac, Centre for Ecology & Hydrology (CEH)

Prof Richard Griffiths, School of Anthropology and Conservation, University of Kent; Durrell Institute of Conservation and Ecology (DICE)

Dr Bjorn Beckmann, Centre for Ecology & Hydrology

Dr Angela Julian, Amphibian and Reptile Groups of the UK (ARG UK)

Dr John Wilkinson, Amphibian and Reptile Conservation Trust (ARC Trust)

Scientific background

Reliable estimates of biodiversity are constrained by an inability to produce reliable estimates of nationwide status, trends and threats for many cryptic taxa. Effective decision-making therefore requires (1) a better balanced assessment of biodiversity; and (2) collation and analysis of ‘messy’ species data that are collected using a variety of protocols.

Anecdotal evidence points to declines in many of the UK’s amphibians and reptiles (or herpetofauna), particularly in formerly widespread species such as the adder and common toad. The National Amphibian and Reptile Recording Scheme (NARRS) was designed to provide evidence on trends in UK herpetofauna, but has been unable to deliver substantive insights. Fortunately, statistical tools have now emerged that are capable of providing robust trends from unstructured data, including citizen science records.

Research methodology

This project will bring together existing datasets from a range of organisations into a common modelling framework, integrating diverse datasets using hierarchical Bayesian models. These outputs will be used to:

  1. Reveal national status and trends from disparate data (including NARRS and BTO Garden Bird Watch)
  2. Determine the drivers of trends in distribution and abundance
  3. Forecast trends under scenarios of future change
  4. Explore options for the design of an integrated monitoring portfolio


The student will receive a comprehensive training experience, covering a broad range of analytical skills including Bayesian statistical techniques for spatio-temporal modelling using citizen science data, as well as transferable skills including stakeholder engagement and knowledge exchange.

Person specification

The successful candidate will have at least a 2:1 degree in a relevant subject and be capable of demonstrating good numeracy. Experience of UK wildlife conservation, especially reptiles and amphibians, would be an advantage.


  • Isaac, NJB et al. (2014) Statistics for citizen science: extracting signals of change from noisy ecological data. Methods Ecol. Evol. 5, 1052–1060
  • Griffiths, RA et al. (2015). Science, statistics and surveys: a herpetological perspective. Journal of Applied Ecology 52: 1413-1417.
  • Miller, DAW et al. (2019) The recent past and promising future for data integration methods to estimate species’ distributions. Methods in Ecology & Evolution 10, 22–37.
  • Biggs, J et al. (2014). Using eDNA to develop a national citizen science-based monitoring programme for the great crested newt (Triturus cristatus). Biological Conservation 183:19-28.
  • Burns, F. et al. (2016) Agricultural management and climatic change are the major drivers of biodiversity change in the UK. PLoS ONE 11(3): e0151595.

Key Information

  • This project has been shortlisted for funding by the ARIES NERC Doctoral Training Partnership, and will involve attendance at mandatory training events throughout the course of the PhD.
  • Successful candidates who meet UKRI’s eligibility criteria will be awarded a NERC studentship - UK and EU nationals who have been resident in the UK for 3 years are eligible for a full award.
  • Excellent applicants from quantitative disciplines with limited experience in environmental sciences may be considered for an additional 3-month stipend to take advanced-level courses in the subject area (see
  • This studentship will start on 1st October 2020, and the closing date for applications is 23:59 on 15th January 2020.
  • Shortlisted applicants will be interviewed on 18/19 February 2020.
  • For further information, please contact the supervisor.
  • Please note that the joint NERC-ESRC ARIES-SeNSS studentship projects have different deadlines and funding arrangements. For full details please visit, or contact

Further Information

Formal internal interviews for this project will be held on 31st January 2020 at the University of Kent

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