Evidencing success: Data requirements to model the impacts of long-term management of invasive squirrels

Abstract

Established widespread populations of invasive vertebrates can be challenging to eradicate and for small to medium-sized vertebrates, such as squirrels, is often not deemed feasible. However, long-term trapping campaigns are necessary to limit spread or reduce impacts. The scale of trapping programmes is often limited by budgets that are not commensurate to the scale of the problem. On-going costs and fundraising are key factors used by decision makers to assess the feasibility of complete removal or long-term management options of established populations. Predicting the time and effort required to successfully manage Invasive Alien Species (IAS) remains a challenge, particularly where different strategies need to be employed across different spatial scales and habitat types, and in response to changing population densities. Statistical methods such as removal models can be applied to quantify population abundance during management operations and could inform planning of resource requirements. However, in practice, the lack of awareness of data requirements results in unsuited or non-standardized data collection. We present data from an invasive grey squirrel (Sciurus carolinensis) management project in the United Kingdom as a case study to illustrate common issues that impact on quantifying project outcomes. We focus on human and operational aspects of implementation and suggest ways of prioritizing analytical requirements. Insights consider conservation targets, data collection and operational design and may be of relevance to stakeholders, analysts, field operators and managers.