An improved procedure to estimate wolf abundance using non-invasive genetic sampling and capture–recapture mixture models

Abstract

Non-invasive genetic sampling (NGS) is increasingly used to estimate the abundance of rare or elusive species such as the wolf (Canis lupus), which cannot be directly counted in forested mountain habitats. Wolf individual and familial home ranges are wide, potentially connected by long-range dispersers, and their populations are intrinsically open. Appropriate demographic estimators are needed, because the assumptions of homogeneous detection probability and demographic closeness are violated. We compiled the capture-recapture record of 418 individual wolf genotypes identified from ca. 4,900 non-invasive samples, collected in the northern Italian Apennines from January 2002 to June 2009. We analysed this dataset using novel capture-recapture multievent models for open populations that explicitly account for individual detection heterogeneity (IDH). Overall, the detection probability of the weakly detectable individuals, probably pups, juveniles and migrants (P = 0.08), was ca. six times lower than that of the highly detectable wolves (P = 0.44), probably adults and dominants. The apparent annual survival rate of weakly detectable individuals was lower (U = 0.66) than those of highly detectable wolves (U = 0.75). The population mean annual finite rate of increase was k = 1.05 ± 0.11, and the mean annual size ranged from N = 117 wolves in 2003 to N = 233 wolves in 2007. This procedure, combining large-scale NGS and multievent IDH demographic models, provides the first estimates of abundance, multi-annual trend and survival rates for an open large wolf population in the Apennines. These results contribute to deepen our understanding of wolf population ecology and dynamics, and provide new information to implement sound long-term conservation plans.

One, no one, or one hundred thousand: how many wolves are there currently in Italy?

“…Population size estimates based on non-invasive genetics sampling have been reported for many carnivores, such as bear (Ursus spp. ; Woods et al 1999), coyote (Canis latrans; Kohn et al 1999), wolf (Canis lupus; Creel et al 2003;Marucco et al 2009;Caniglia et al 2012), and European badger (Meles meles; Wilson et al 2003), sometimes incorporating multiple methods (Solberg et al 2006). However, most of these models assume expensive long-term monitoring programs and homogeneous Capture-Marking-Recapture data, which are exceedingly difficult to obtain over long periods and large sampling areas (Ebert et al 2010).…”

“…As a result, a comprehensive overview of the current population status at the national scale is still lacking, with the most recent population estimate tracing back to the 1970s (Zimen and Boitani 1975). Local population size and predictions of population expansion have been estimated only in subsets of the Italian wolf population (Marucco et al 2009; McIntire 2010 for the Alps; Caniglia et al 2012Caniglia et al , 2014 for the Northern Apennines). Expert-based reports produced by the Large Carnivore Initiative for Europe (LCIE/IUCN) indicate ca.…”

Procedures to genotype problematic non-invasive otter (Lutra lutra) samples

“…This kind of data can be difficult to obtain, especially when dealing with rare and elusive species. Advances in molecular ecology and data analysis offer accurate tools to study and monitor wild populations in a non-invasive way (Koelewijn et al 2010;Arandjelovic et al 2011;Caniglia et al 2012;Brzeski et al 2013;Pennell et al 2013;Silveira Trinca et al 2013).…”

Efficient, Noninvasive Genetic Sampling for Monitoring Reintroduced Wolves

“…In the last decade, these methods have been adopted to assist in the management of the gray wolf Canis lupus in many regions (Stenglein et al 2010, Bohling and Waits 2011, Randi 2011, Scandura et al 2011, Caniglia et al 2012, Cohen et al 2013, Ražen et al 2016, Subba et al 2017. Despite their wide application, though, both methods have limitations.…”