Developing models to estimate the occurrence in the English countryside of Great Crested Newts, a protected species under the Habitats Directive

The great crested newt is a European Protected Species (EPS) with a widespread distribution within Great Britain. This results in the species frequently coming into conflict with development. Consequently, decision-makers in local government and licensing authorities face complex issues when it comes to reconciling development and conservation. New approaches are therefore needed to ensure that conservation decisions are based upon the best available science. The project set out to evaluate new potential approaches to these issues using three work packages: (1) Develop, test and compare species distribution models (SDMs) for great crested newts; (2) Building on these models, develop a methodology for assessing the impact of a plan or project on the local conservation status of great crested newts; and (3) End-user testing to assess model applications and fitness for purpose. Defra commissioned the project with additional funding from Natural Resources Wales, and together with Natural England and JNCC, also provided guidance.

GLM models developed using eDNA presence-absence data for a small area of Kent provided a good prediction of the county-wide distribution of the species. GLM models developed for Cheshire and Lincolnshire using eDNA data yielded weaker models. Equally, the Kent model did not reliably fit Cheshire and Lancashire, suggesting that the predictor variables vary geographically.

Maxent and ensemble models yielded good fits to county-wide distributions but poor fits to the localised eDNA data in all three counties. These models may have utility at a broad scale, but cannot account for absences at a local scale. Equally, some important variables at a local scale cannot be obtained through GIS layers and need to be obtained through field surveys. Constructing models for different scales therefore requires different modelling tools and different types of predictor variables.

Maxent models of the national distribution of great crested newts in England gave predictions that were broadly consistent with current knowledge and can be used to calculate potential areas of occupancy.

A framework for assigning and measuring Favourable Reference Values (FRVs) for great crested newts at different scales was developed using both an ‘equilibrium’ (=’no net change’) approach and FRVs set using baseline data according to other criteria. These principles were combined with SDMs and connectivity analysis of five case studies. The case studies combine both real and hypothetical data, and illustrate how a modelling approach can be used to identify important areas of newt habitat, identify connectivity between ponds, predict potential impacts of development, and design and evaluate mitigation measures.

Three end-user consultation exercises showed that there was considerable interest and enthusiasm for the development and application of SDMs across a range of applications and stakeholders. Concerns were expressed over the quality and quantity of data available for modelling using current data-flow systems; the predictive power of models; and the potential for model outputs to be misused. Challenges that need to be addressed include training, expertise and building capacity, enhancing the regulatory framework for protected species, and the improvement and centralisation of data management systems.

Species Distribution Models (SDMs) provide an objective and evidence-based tool for use within decision-making processes involving great crested newts. They have the potential to identify priority areas for conservation, target survey effort, assess the impacts of development, and assign Favourable Reference Values for the species. However, great crested newt records and habitat data are currently dispersed across multiple recording systems and vary in quality and quantity. A well-integrated data management system is required if SDMs are to make the best use of available information.