When enough is enough: Optimising monitoring effort for large‐scale wolf population size estimation in the Italian Alps

• Published in: Ecology and evolution Vol. 14; no. 8; pp. e70204 - n/a
• Main Authors: Boiani, M. V., Dupont, P., Bischof, R., Milleret, C., Friard, O., Geary, M., Avanzinelli, E., Hardenberg, A., Marucco, F.
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.08.2024; John Wiley and Sons Inc; Wiley
• Subjects: Abundance; adaptive management; Animal populations; Canis lupus; Conservation Ecology; Cost analysis; Data collection; Datasets; Environmental protection; Estimates; Genetic testing; Laboratories; large carnivore; large scale monitoring; long‐term monitoring; Monitoring; monitoring optimisation; non‐invasive sampling; Optimization; Population density; Population number; Population studies; Probability; Sampling; Searching; Sensors; spatial capture‐recapture; Wildlife conservation; wolf population; Alps; Europe; non‐invasive sampling; monitoring optimisation; long‐term monitoring; adaptive management; large scale monitoring; spatial capture‐recapture; wolf population; large carnivore
• ISSN: 2045-7758; 2045-7758
• DOI: 10.1002/ece3.70204

The ongoing expansion of wolf (Canis lupus) populations in Europe has led to a growing demand for up‐to‐date abundance estimates. Non‐invasive genetic sampling (NGS) is now widely used to monitor wolves, as it allows individual identification and abundance estimation without physically capturing individuals. However, NGS is resource‐intensive, partly due to the elusive behaviour and wide distribution of wolves, as well as the cost of DNA analyses. Optimisation of sampling strategies is therefore a requirement for the long‐term sustainability of wolf monitoring programs. Using data from the 2020–2021 Italian Alpine wolf monitoring, we investigate how (i) reducing the number of samples genotyped, (ii) reducing the number of transects, and (iii) reducing the number of repetitions of each search transect impacted spatial capture‐recapture population size estimates. Our study revealed that a 25% reduction in the number of transects or, alternatively, a 50% reduction in the maximum number of repetitions yielded abundance estimates comparable to those obtained using the entire dataset. These modifications would result in a 2046 km reduction in total transect length and 19,628 km reduction in total distance searched. Further reducing the number of transects resulted in up to 15% lower and up to 17% less precise abundance estimates. Reducing only the number of genotyped samples led to higher (5%) and less precise (20%) abundance estimates. Randomly subsampling genotyped samples reduced the number of detections per individual, whereas subsampling search transects resulted in a less pronounced decrease in both the total number of detections and individuals detected. Our work shows how it is possible to optimise wolf monitoring by reducing search effort while maintaining the quality of abundance estimates, by adopting a modelling framework that uses a first survey dataset. We further provide general guidelines on how to optimise sampling effort when using spatial capture‐recapture in large‐scale monitoring programmes. The ongoing wolf recolonization is followed by the growing demand from administrations for increasingly up‐to‐date and accurate population estimates. Although the methods for obtaining such estimates are well known, there is now a growing interest in applying it over large spatial extents. However, the difficulty of repeating sampling surveys over time is a limitation that often makes it impossible to complete long‐term monitoring programmes. In this study, we used data from Alpine‐scale wolf monitoring conducted in 2020/2021 in northern Italy and subsampled the original dataset to assess the robustness of SCR estimates under different effort scenarios or reduced samples. Our results demonstrate the possibility of reducing monitoring effort even at large scales and for complex and elusive species such as wolves. They encourage the continuation of such studies by adapting the sampling design over the years and optimising it for a long‐term monitoring programme.