Modelling removal and re-introduction data for improved conservation

Lead Research Organisation: University of Kent
Department Name: Sch of Maths Statistics & Actuarial Scie

Abstract

Conservation monitoring schemes are constrained by time and cost and as such study design needs to be optimised to make the most of these available resources. Removal studies are conducted to protect target species from sites planned for development and the aim of such sampling is to capture and remove the entire population. Typically the studies are designed in an ad-hoc way with some repeated surveys on a single day, and some with simply daily visits. Sampling of sites is often avoided when weather conditions are considered not favourable. Removed species are trans-located to other habitats considered suitable for the specific species. However, measures to determine whether such translocations, and related re-introduction programmes have been successful are currently lacking. Developing robust approaches for both removal and re-introduction programmes will allow resources to be allocated optimally to ensure monitoring can be carried out for a sufficient period of time, to minimise the risk to the species under study.

This project will develop new statistical approaches to make the most of the information available from removal and re-introduction data. The types of data which can be collected on animal populations are wide-ranging - for example, simple population counts, presence/absence data, presence only data, batch-marked data, and capture-recapture data. The difficulty and survey intensity required to collect these data will also depend on the associated skill set of data collector as well as the resources available to the team or individual responsible for designing the scheme. As well as proposing optimal study design for removal count data, the project will also address how to optimise study design if multiple types of data are collected simultaneously on a population. Further, we will explore how populations could be monitored with multiple types of data collection to better determine how successfully the population has established itself following some form of intervention (such as trans-location of individuals or re-introducing a previously locally extinct species back into an area).

When fitting models to data it is possible to consider different structures to the model, for example to account for time-variation within detectability of the species, and therefore a model selection procedure needs to be implemented to select the structure of the model that best represents the observed data. Current approaches require an understanding of the statistical procedures implemented within this model selection step, however the methodological developments proposed within this project are aimed at a user-base who may have no such knowledge. Therefore within the project we will investigate the development of an automated procedure which will both select a best model(s) out of the models considered for the data set and will also assess how well the model(s) fits the observed data. A best candidate model may in fact fit the observed data very poorly and therefore this check of model fit is crucial if the results of the model will be used to make management decisions as otherwise erroneous conclusions could be drawn.

Software with a graphical-user-interface will be developed to make the statistical developments accessible to those with no programming experience. The software will be web-based which will overcome operating system compatibility issues and user-manuals and tutorials will be produced to help end-users to make the most of the software's capabilities.

Planned Impact

This grant proposal describes a number of key statistical developments which will improve the study design and analysis for data collected when removing a species from a population and also when re-introducing a species into an area. The statistical theory is motivated by a real need for a clear understanding of the success or failure of such initiatives, whether these are for protecting species prior to land development or for conservation strategies to improve the distribution of at-risk species. The key aspect for optimising the impact of this research is hence to get the methodology used by the relevant communities. In order to achieve this the project has strategically partnered with three organisations - Amphibian and Reptile Conservation Trust, Mauritian Wildlife Foundation and Durrell Wildlife Conservation Trust. Engagement with the project partners has ensured that methodological developments are driven from data collected in real-life settings. Some of these data have already been collected, some are being collected and plans are being made for new data collection, therefore we can inform their current approaches using rigorous statistical techniques. Through these collaborations, we will inform long-term policy change.

It will be necessary to publish peer-reviewed papers in both statistical and ecological journals. Attendance and presentation of work at conferences will be of prime importance; the International Biometric conference (July 2020) and Royal Statistical Society conferences (September 2019, 2021) provides the opportunity to target a general statistical audience, whilst the bi-annual International Statistical Ecology conference (July 2020) will be the perfect opportunity to communicate directly with biologists and applied statisticians. We will also apply to present a workshop at the British Ecological Society Annual Meeting in December 2021 and attend and lead events at more species-specific events such as the Herpetofauna Worker's Meeting (February 2020, 2021 and 2022).

Software will be developed with a graphical user-interface to allow end-users with no experience of R to utilise the methods in a simple and informative way. The PDRA will undertake training in the development of software with a graphical user interface to facilitate this essential component of the project.

We will engage with ecological consultants and volunteers who run monitoring schemes so that our methodology will be used by them to optimise the way they run their study and maximise the information they can obtain from their data. Workshops will be run (Herpetofauna Workers Meeting, British Ecological Society Annual Meeting and training events at the University of Kent), targeting attendees who conduct environmental impact assessments in their day-to-day jobs. Specific training workshops for teams within the project partner institutions will also be run to ensure the proposals work well in practice for them.

Overall the project will achieve four general forms of impact:
- A more rigorous understanding of the fragility of at risk species within an ecosystem and an evaluation of how changes in government-driven legislation changes could affect UK biodiversity.
- Knowledge and skill development for ecologists collecting and analysing data
- Cost-saving benefits in terms of stream-lining data collection and optimising survey strategies through the use of the new software
- Ecological consultants will be employed by developers to conduct these surveys and so the training given to them will ultimately save land developers time and money

Publications

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