Guidance on estimation of abundance and density of wild carnivore population:methods, challenges, possibilities

Abstract

This guidance reviews the methods for estimating relative abundance and density in nine large European wild carnivore species, somerepresenting relevant health concerns andprovides insights on how to obtain reliable estimations by using those methods. On a local scale, the appropriate method should take into accountthe characteristics of the study area, the estimated survey efforts, the expected results (i.e. a measure of true density or just an index of abundance to monitor the trend in space and time) the level of accuracy and precision, and a proper design so to obtain a correct interpretation of the data. Among all methods, the camera trapping (CT) methods, especially those recently developed, are the most promising for the collection of robust data and can be conducted in a wide range of species, habitats, seasons and densities with minimal adjustments. Some recently developed CT methods do not require individual recognition of the animals and are a good compromise of cost, effort and accuracy. Linear transects,particularly Kilometric Abundance Index (KAI) is applicable for monitoring large regions.A large challenge is compiling and validating abundance data at different spatial scales. Based on ENETWILD initiative, we recommend developing a permanent network and a data platform to collect and share local density estimates, so as abundance in the EU, which would enable to validate predictions for larger areas by modelling. It would allow to identify gaps in the data on wild carnivores (including the species not assessed in the present report) and to focus on these areas for improving predictions. This platform must facilitate the reporting by wildlife policy makers and relevant stakeholders, but also citizen science initiatives.Also, there is need to improve the reliability of local density estimations by developing practical research on methods able to derive densities in untested species and situations, making the application of methods easier for local teams.

Development of an app for processing data on wildlife density in the field

“…In this first phase, we identified the most relevant type of data required to be recorded in the field. These data relates to the main recommended density estimation protocols for medium and big sized mammals (lagomorphs, carnivores, ungulates;ENETWILD consortium et al 2018ENETWILD consortium et al , 2020aENETWILD consortium et al , 2020bENETWILD consortium et al , 2021:…”

“…This is crucial to improve current schemes of wildlife monitoring field data collection, and subsequent data flow in a standardised and harmonised way. This is foreseen as a cost effective "from field to screen" strategy which facilitates field technicians/researchers/managers collecting information to estimate wildlife abundance following validated protocols and methods previously recommended (ENETWILD consortium et al 2018(ENETWILD consortium et al , 2020a(ENETWILD consortium et al , 2020b(ENETWILD consortium et al , 2021.…”

The genetics of the European polecat in the Iberian Peninsula

“…Wildlife monitoring is essential for conservation, research, and management of biodiversity, including prompt detection of population declines (ENETWILD Consortium et al 2020). Most recommended approaches to estimate current abundance such as camera arrays or abundance indices from surveys are based on linear transects (ENETWILD Consortium et al 2020), which cannot track past oscillations in population numbers or connectivity among population units. To identify such population trends and structure at large scales, genetic‐based approaches are more suitable (Aylward et al 2022, Willi et al 2022, Horreo et al 2023).…”