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

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.

Gastrointestinal helminths of wolves (Canis lupus Linnaeus, 1758) in Piedmont, north-western Italy.

Free-ranging grey wolves (Canis lupus), which are presently recolonizing Italy, can be parasitized by a diversity of helminths, but have rarely been subject to studies of their parasites. Therefore, this study aims to determine the prevalence of gastrointestinal helminths of road-killed grey wolves from the Piedmont region of Italy. Forty-two wolves were collected and examined for the presence of helminths. We recorded 12 helminth species: nine Nematoda and three Cestoda. The nematodes were: Ancylostoma caninum (7.1%), Capillaria sp. (2.4%), Molineus sp. (2.4%), Pterygodermatites affinis (11.9%), Physaloptera sibirica (9.5%), Toxocara canis (9.5%), Toxascaris leonina (2.4%) and Uncinaria stenocephala (26.2%); the cestodes were: Dipylidium caninum (4.8%), Mesocestoides sp. (4.8%) and Taenia multiceps (76.2%). Physaloptera sibirica had the highest mean intensity and T. multiceps had the highest prevalence. Based on age and sex, no differences in the intensity or prevalence of helminth species were found among the hosts. Molineus sp. was recorded for the first time in wolves from the Palearctic region; P. affinis and P. sibirica are respectively reported for the first time in wolves from Europe and Italy.

Noninvasive molecular tracking of colonizing wolf (Canis lupus) packs in the western Italian Alps.

We used noninvasive methods to obtain genetic and demographic data on the wolf packs (Canis lupus), which are now recolonizing the Alps, a century after their eradication. DNA samples, extracted from presumed wolf scats collected in the western Italian Alps (Piemonte), were genotyped to determine species and sex by sequencing parts of the mitochondrial DNA (mtDNA) control-region and ZFX/ZFY genes. Individual genotypes were identified by multilocus microsatellite analyses using a multiple tubes polymerase chain reaction (PCR). The performance of the laboratory protocols was affected by the age of samples. The quality of excremental DNA extracts was higher in samples freshly collected on snow in winter than in samples that were older or collected during summer. Preliminary mtDNA screening of all samples allowed species identification and was a good predictor of further PCR performances. Wolf, and not prey, DNA targets were preferentially amplified. Allelic dropout occurred more frequently than false alleles, but the probability of false homozygote determinations was always < 0.001. A panel of six to nine microsatellites would allow identification of individual wolf genotypes, also whether related, with a probability of identity of < 0.015. Genealogical relationships among individuals could be determined reliably if the number of candidate parents was 6-8, and most of them had been sampled and correctly genotyped. Genetic data indicate that colonizing Alpine wolves originate exclusively from the Italian source population and retain a high proportion of its genetic diversity. Spatial and temporal locations of individual genotypes, and kinship analyses, suggest that two distinct packs of closely related wolves, plus some unrelated individuals, ranged in the study areas. This is in agreement with field observations.