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Frontiers in Ethology ·

Volume 5 - 2026 | https://doi.org/10.3389/fetho.2026.1950752

Comparing wolf feeding ecology between historical ranges and recently colonized human-dominated lowlands

  • Elisa Torretta1*corresponding author
  • Laura Giussani1
  • Giulia Rampazi1
  • Olivia Dondina2
  • Monica Di Francesco3
  • Luca Canova4
  • Achaz von Hardenberg1
  1. 1Department of Earth and Environmental Sciences, University of Pavia, Pavia, Italy
  2. 2Department of Earth and Environmental Sciences, University of Milano-Bicocca, Milan, Italy
  3. 3Parco Lombardo della Valle del Ticino, Pontevecchio di Magenta, MI, Italy
  4. 4Department of Chemistry, University of Pavia, Pavia, Italy
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Abstract

The recent spread of wolves into highly human-modified landscapes in Europe is an important example of large carnivore recovery and illustrates their ability to live in environments very different from those usually considered suitable for the species. This study aimed to evaluate how wolf feeding habits vary over time and across space by comparing diet composition, trophic niche breadth, and key prey consumption between the historical Apennine range and the recently colonized Po Plain in north-western Italy, based on scat samples collected between 2021 and 2025. Results show that wolf diet remained overwhelmingly based on wild prey, with negligible use of anthropogenic resources such as livestock or pets across both sectors. However, marked spatial and temporal differences in wild prey composition were detected, with wild ungulates dominating in the Apennines and medium-sized mammals, particularly coypu, prevailing in the Po Plain. Coypu emerged as a key ecological resource in the newly colonized area, while roe deer remained the main prey in the Apennines, with both species explaining most dietary divergence and showing converging temporal trends. Trophic niche breadth remained relatively narrow in both sectors, although increasing in the Plain over time, indicating progressive dietary adjustment as colonization proceeded. Overall, wolves expanded into a human-dominated landscape without increasing their use of human food sources. Instead, they changed the main prey they rely on, with coypu acting as an important early food resource and this trophic shift reflecting a dynamic process during population establishment.

Keywords

1 Introduction

The wolf (Canis lupus) is among the terrestrial carnivores that best exemplifies ecological adaptability.

Its recovery across Europe demonstrates its remarkable capacity to respond to changing ecological conditions: after experiencing dramatic declines in the twentieth century, wolves rapidly recolonized large suitable areas as reforestation, agricultural land abandonment, and legal protection created new opportunities for expansion (e.g., Boitani et al., 2022; Chapron et al., 2014; Cimatti et al., 2021). According to Boitani et al. (2022), in the last decade only, the European range of the species has increased by more than 25%, with populations now established across landscapes heavily modified by human activities (Di Bernardi et al., 2025). Indeed, the species thrives across a wide diversity of environments, provided that adequate food resources and suitable, safe habitats for critical life stages are available (Ciucci et al., 2026).

Although wolves generally achieve higher survival rates in less disturbed environments (Barber-Meyer et al., 2021), they have proven to be particularly successful at persisting in heavily human-modified landscapes (Nakamura et al., 2026). This success relies on a high degree of behavioral plasticity. Wolves typically reduce the risk of human encounters through marked spatial and temporal avoidance (e.g., Ferreiro‐Arias et al., 2024; Llaneza et al., 2012, 2016; Reinhardt et al., 2026; Theuerkauf et al., 2003; Torretta et al., 2023), yet they can also exploit anthropogenic food subsidies, including livestock, animal by-products, garbage, and pet food, not only as an alternative to scarce wild prey (Llaneza and López-Bao, 2015; Meriggi and Lovari, 1996; Mohammadi et al., 2019; Tourani et al., 2014; Zlatanova et al., 2014), but also when such resources are highly accessible, even in ecosystems supporting abundant and diverse wild prey communities (Ciucci et al., 2020). Such behavioral flexibility is widely recognized as a key mechanism enabling the species to persist across anthropogenic environments.

The rapid expansion of wolves across much of Europe has provided a unique opportunity to investigate ecological and behavioral adaptations in what is arguably the most human-modified continent in the world. During this ongoing recolonization process, wolves are increasingly establishing territories in novel environments, where not only demographic processes (e.g., survival and reproduction) but also ecological interactions (e.g., prey use) may differ from those in historical ranges (Nakamura et al., 2021; Sunde et al., 2021; Torretta et al., 2024).

Wolves are opportunistic carnivores capable of exploiting a broad prey spectrum, ranging from small mammals such as hares (Lepus spp., ~1 kg) to large ungulates such as bison (Bison spp., up to 1000 kg) (Newsome et al., 2016; Peterson and Ciucci, 2003). In Europe, their diet is predominantly based on medium- and large-sized wild ungulates, although it varies considerably among populations and across regions (Zlatanova et al., 2014). Generally, one or two main prey species characterize the diet (Peterson and Ciucci, 2003), with wild boar (Sus scrofa) and roe deer (Capreolus capreolus) being the most frequently consumed (e.g., Barja et al., 2023; Lippitsch et al., 2024; Mori et al., 2017). The predominance of these species is largely explained by their availability and ecological characteristics. Wild boars are abundant, widely distributed, live in large and easily detectable groups, and dispersing sub-adults are especially vulnerable to predation. Roe deer, despite their solitary and elusive behavior, can represent profitable prey because they require relatively little handling time and may occur at high local densities, increasing encounter rates (Meriggi et al., 2020). Depending on local prey availability, wolves also frequently prey on other cervids, particularly red deer (Cervus elaphus) (Guimarães et al., 2022) and fallow deer (Dama dama) (Ferretti et al., 2019; Lazzeri et al., 2024) as well as other wild ungulates such as European bison (Bison bonasus), chamois (Rupicapra spp.), ibex (Capra spp.), and mouflon (Ovis orientalis musimon) (Zlatanova et al., 2014). Smaller species (e.g., small mammals, lagomorphs, and mesocarnivores) are generally consumed only occasionally. However, locally abundant non-native species may also become relevant prey resources for wolves, as documented for coypu (Myocastor coypus) in Italy (Ferretti et al., 2019; Lazzeri et al., 2024).

The marked variation in prey use across the wolf range reflects the adaptive nature of its foraging strategies. Diet represents one of the most flexible components of species ecological niche and trophic cascades are highly context-dependent. Therefore, understanding spatial and temporal variation in wolf diet is essential to interpret responses to changes in prey communities and environmental heterogeneity, and to assess how these factors shape wolf trophic ecology.

A long-term research project conducted in Italy provides an opportunity to closely monitor these dynamics (Torretta et al., 2024 and references therein). Previous results from this study, carried out in the Northern Apennines, documented a dietary shift characterized by increasing consumption of wild ungulates and a concurrent decrease in livestock, consistent with broader European trends (Meriggi and Lovari, 1996; Newsome et al., 2016). Up to 2021, roe deer and wild boar were the main prey species, showing contrasting temporal trends: the diet shifted from a predominance of wild boar (2007–2008 and 2011-2012) to an increasing dominance of roe deer from 2015 onwards (Torretta et al., 2024).

The present study updates previous knowledge of wolf trophic ecology; indeed, following the species expansion into lowland areas, the study area was extended to include the Po Plain, focusing on areas of stable wolf presence where pack reproduction has been confirmed. In this context, the Po Plain represents the recently colonized sector (Canova and Meriggi, 2026; De Feudis et al., 2025), whereas the Apennines represent the historical source area from which wolves expanded (Torretta et al., 2024). These sectors differ markedly in landscape structure and composition, prey communities, and the intensity of human activities, potentially influencing prey availability and, consequently, wolf feeding habits. Comparing these two sectors therefore provides an opportunity to evaluate how wolf diet varies between historical source areas and recently colonized ones.

Accordingly, the study aims to:

  • evaluate temporal and spatial variation in diet composition, with particular emphasis on differences between the Apennine and Plain sectors of the study area;
  • assess temporal and spatial variation in trophic niche breadth;
  • identify the prey species driving the observed differences in diet composition;
  • describe temporal and spatial trends in the consumption of key prey species.

2 Materials and methods

2.1 Study area

The study area is located in north-western Italy, within the Lombardy region (Figure 1A) and comprises two distinct sectors: the Lombard Apennines, representing the historical wolf range, and the Po Plain, where wolves have only recently established resident packs.

**(A)** Location of the study area in north-western Italy. Sampling grid (5 x 5 km) and routes (n = 61) used for wolf (*Canis lupus*) monitoring in the Lombardy region (Province of Pavia, “Ticino Valley” Natural Park, and “Monticchie” Natural Reserve) during 2022-2025; **(B)** Land use classes of the study area derived from DUSAF 2023 ([https://www.geoportale.regione.lombardia.it/](https://www.geoportale.regione.lombardia.it/)).
Figure 1. (A) Location of the study area in north-western Italy. Sampling grid (5 x 5 km) and routes (n = 61) used for wolf (Canis lupus) monitoring in the Lombardy region (Province of Pavia, “Ticino Valley” Natural Park, and “Monticchie” Natural Reserve) during 2022-2025; (B) Land use classes of the study area derived from DUSAF 2023 (https://www.geoportale.regione.lombardia.it/).

The Lombard Apennine sector is located in the southern portion of the study area, within the Province of Pavia (Figure 1A). The landscape forms a gradient from low hills dominated by permanent crops, mainly vineyards, to higher hills where agricultural areas, particularly permanent grasslands, alternate with deciduous forests, and finally to montane areas largely covered by woodlands (Torretta et al., 2024) (Figure 1B). Livestock farming is a secondary activity and is mainly based on extensive grazing, with cattle representing the main livestock (Torretta et al., 2018). The transition between upland and lowland areas occurs at approximately 200 m a.s.l. (Figure 1A). The Po Plain sector comprises the northern and central portions of the study area. It includes the lowland portion of the Province of Pavia, as well as the “Ticino Valley” Natural Park (20,500 ha), which forms a continuous woodland corridor connecting the Po River in the south to Lake Maggiore in the north and extends across the Provinces of Pavia, Milan, and Varese. The sector also includes the small “Monticchie” Natural Reserve (250 ha) in the Province of Lodi (Figure 1A). The landscape is intensively cultivated and can be divided into two main sub-areas: rice fields dominate north of the Po River, whereas non-irrigated arable land prevails south of the river. Within this highly anthropized landscape, the Ticino River represents an important ecological corridor preserving relict wooded habitats of high conservation value (Dondina et al., 2020) (Figure 1B). Livestock farming is predominantly based on intensive, stall-fed systems, although seasonal extensive grazing by transhumant sheep and goat herds also occurs during the spring-summer period.

Considering the whole study area, the ungulate community includes wild boar and roe deer, both widespread and abundant throughout the area; fallow deer, which is present across the entire area but occurs with scattered distribution; and red deer, which is only occasionally found in the Plain but is more abundant in the Apennine. Population density estimates are not available for the entire study area. However, density estimates are available for roe deer in specific sampling areas: 12.5 ± 3.0 (SE) individuals/km² in the Apennine (study area: “Val Tidone”) and 11.5 ± 1.2 (SE) individuals/km² in the Plain (study area: “Boschi Negri and Moriano”, “Ticino Valley” Natural Park) (Torretta, 2024). Medium-sized herbivores include the brown hare (Lepus europaeus) and crested porcupine (Hystrix cristata), which are widespread, as well as the eastern cottontail (Sylvilagus floridanus) and coypu, particularly abundant in low hills and the lowland. Mesocarnivores include red fox (Vulpes vulpes), European badger (Meles meles), stone marten (Martes foina), pine marten (Martes martes), European polecat (Mustela putorius), and least weasel (Mustela nivalis), with the latter two species scarcely detected within the area.

The wolf is the only large carnivore present in the study area since the late 1980s. In the Apennine sector, early monitoring (1987-1992) documented two breeding pairs in the higher-elevation mountain belt (Meriggi et al., 1991). More recent estimates (2015-2018) suggested the presence of 4–6 packs, corresponding to approximately 22–34 individuals, distributed across the entire Apennine sector (Torretta and Meriggi, 2018). The first evidence of resident wolf packs in the Plain sector was recorded in 2021-2022. By 2025, reproduction was confirmed for 13 packs across the province of Pavia (Apennine: n = 8; Plain: n = 5), with a mean pack size of 6.6 ± 0.6 (SE) individuals (Torretta et al., 2026), and for 4 packs across the province of Lodi (Canova, personal communication).

2.2 Scat sampling and diet analysis

Wolves were monitored using a non-invasive sampling approach based on the detection of field signs, mostly scats, along predefined routes or at marking sites. The study area was subdivided into 25 km² grid cells (5 × 5 km). Within each cell, at least one sampling route was randomly selected from existing footpaths and dirt roads (Figure 1A), thus, the routes were uniformly distributed across the study area. In total, 61 routes were surveyed (Apennines: n = 28; Plain: n = 33), with a mean length ± SD of 5.6 ± 2.6 km (range: 1.5-12.5 km). Each route was walked by trained personnel four times per year, corresponding to seasonal sampling sessions (spring: March-May; summer: June-August; autumn: September-November; winter: December-February).

In the Apennine sector, standardized route-based monitoring was conducted in 2021, 2023, and 2024. In 2022 and 2025, as systematic sampling was not feasible, opportunistic surveys were conducted by inspecting known wolf marking sites (e.g., trail junctions, prominent landmarks, and frequently used paths; 2022: n = 18; 2025: n = 29) at least once per season. In the Plain sector, standardized route-based monitoring began in 2023, initially limited to a single winter session. Before this, data were collected on an occasional basis without a standardized sampling design (Table 1), with the exception of the area covered by the “Ticino Valley” Natural Park, where systematic sampling was conducted from 2017 onwards (De Feudis et al., 2025).

Table 1. Sampling strategy for wolf (Canis lupus) scat collection adopted across years (2021-2025) and sectors (plain and apennine) within the study area in north-western Italy.

YearApenninePlain
2021StandardizedOccasional
2022OpportunisticOccasional
2023StandardizedOccasional / Standardized
2024StandardizedStandardized
2025OpportunisticStandardized

Sampling approaches are classified as occasional (non-systematic data collection), standardized (seasonal route-based surveys), opportunistic (sampling at known wolf marking sites).

During sampling, wolf scats, identified by size, shape, and location (Černe et al., 2019), were collected and stored for subsequent laboratory analyses. Field identification was based on these characteristics, which allowed wolf scats to be distinguished from those of other medium-sized wild carnivores occurring in the study area (e.g. red fox and badger), while scat contents were also considered to help exclude scats from domestic dogs. Stray dogs are absent from the study area. As a countercheck, 38 samples collected between 2022 and 2025 were subjected to molecular species identification, and all were confirmed as wolf scats, with no samples identified as dogs or red foxes.

In line with previous studies carried out in the same study area (i.e., within the Apennine sector: Meriggi et al., 1991, 1996, 2015; Milanesi et al., 2012; Torretta et al., 2024), wolf diet was assessed through scat analysis, with prey items identified from undigested remains. Scats were processed to identify food items based on diagnostic remains, including hairs, bones, hooves, and claws for medium- and large-sized mammals, hairs and mandibles for small mammals, and seeds for fruits. Remains were identified by comparison with a private reference collection (including hairs and mandibles collected from carcasses and seeds gathered from plants) and published identification keys and atlases (Brunner and Coman, 1974; De Marinis and Asprea, 2006; Teerink, 1991). Hair samples were examined under an optical microscope (Leica DM750; Leica Microsystems, Wetzlar, Germany) to determine prey species based on cuticle scale patterns, medullary structure, and root morphology.

2.3 Data analysis

Identified prey items were grouped into food categories, following previous studies (Meriggi et al., 1991, 1996, 2015; Milanesi et al., 2012; Torretta et al., 2024), to facilitate comparison of results. Diet composition was quantified using both Frequency of Occurrence (FO%) and Mean Volume (MV%) for each food category and prey species. FO% was calculated as the percentage of scats containing a given food category or prey species relative to the total number of analyzed scats. For MV%, the relative proportion of each prey species within each scat was visually estimated from undigested remains, taking into account the estimated proportion of each prey as consumed. Each prey species was then assigned to one of seven volumetric classes (<1%, 1-5%, 6-25%, 26-50%, 51-75%, 76-95%, and >95%), which were converted to the corresponding midpoint values. MV% was calculated as the mean of these values across all analyzed scats for each food category and prey species (Belardi et al., 2024; Imbert et al., 2016; Kruuk and Parish, 1981; Meriggi et al., 2015; Torretta et al., 2024). Remains that could not be assigned to any food category were excluded from the calculation of MV%.

We evaluated sampling adequacy using the Brillouin diversity index (Hb; Brillouin, 1956). Diversity curves were generated through bootstrap resampling (1,000 iterations), and sampling effort was considered sufficient when the curve reached an asymptote and the incremental increase in Hb dropped below 1%.

Spatial and temporal variation in diet composition was assessed using MV% values. Overall differences were tested by permutational multivariate analysis of variance (PERMANOVA; Anderson, 2001), with separate analyses used to evaluate differences among years within each sector and between sectors. A two-way PERMANOVA including sector, year, and their interaction was additionally performed to test whether temporal changes in diet composition differed between sectors. Pairwise comparisons were adjusted using the Bonferroni correction.

To further assess variation in the contribution of individual food categories and prey species, temporal differences within each sector were evaluated using Kruskal-Wallis tests followed by Dunn’s post hoc tests, whereas spatial differences between sectors were assessed using Mann-Whitney U tests.

We also quantified trophic niche breadth for each sector and year using the standardized Levins index (B; Feinsinger et al., 1981), with 95% confidence intervals obtained by nonparametric bootstrap resampling (1,000 iterations) to quantify the uncertainty of estimates.

To identify the prey species that contribute most to dietary dissimilarity between the two sectors, we performed a Similarity Percentage (SIMPER; Clarke, 1993) analysis based on Bray-Curtis dissimilarities. Species were ranked by their contribution, and those cumulatively accounting for up to 70% of the total dissimilarity were considered the main drivers of dietary differences.

Finally, to investigate whether the occurrence of the prey species identified as the main drivers of dietary differences varied across space and time, we fitted generalized linear models (GLMs) with a binomial error distribution, including sector, year, and their interaction as explanatory variables to assess spatio-temporal variation in occurrence.

All analyses were performed in R version 4.5 (R Core Team, 2026), using the packages stats, vegan (Oksanen et al., 2026), ggeffects for model predictions (Lüdecke, 2018), ggplot2 for data visualization (Wickham, 2016), and dplyr and tidyr for data manipulation (Wickham et al., 2025, 2026).

3 Results

During the study period, a total of 1078 wolf scats were collected and analyzed to study wolf feeding habits (Apennine: n = 792; Plain: n = 286; Figure 2).

Spatial distribution of wolf (*Canis lupus*) scats collected in the study area in north-western Italy (Apennine: n = 792; Plain: n = 286) across different sampling years (2021-2025).
Figure 2. Spatial distribution of wolf (Canis lupus) scats collected in the study area in north-western Italy (Apennine: n = 792; Plain: n = 286) across different sampling years (2021-2025).

3.1 Sampling adequacy

The number of analyzed samples was generally adequate to describe wolf diet across sectors and years, except for the Plain sector in 2022, where the sample size was small (n = 11). In all other sector-year combinations, the diversity curves reached an asymptote and the threshold of <1% incremental change in Hb was reached before the total number of analyzed samples (Supplementary Material 1).

3.2 Overall patterns of diet composition

We identified seven food categories in the wolf diet: livestock, wild ungulates, small mammals, medium-sized mammals, birds, fruit, and grass (Table 2; Supplementary Material 2). Overall, the two sectors showed distinct dietary patterns (PERMANOVA: F = 1001.6, p < 0.001) and significant interannual variation was detected in both. In both sectors, diet composition differed significantly between the first and last years of the study period. In the Apennine (F = 21.57, p < 0.001), pairwise comparisons highlighted differences between 2021 and both 2024 and 2025, as well as between 2022 and both 2024 and 2025 (Bonferroni-adjusted p = 0.01 for all comparisons). In the Plain sector (F = 15.25, p < 0.001), pairwise comparisons indicated differences between 2025 and both 2021 and 2024 (Bonferroni-adjusted p ≤ 0.02).

Table 2. Diet composition of wolf (Canis lupus) across years (2021-2025) and sectors (plain and apennine) in north-western Italy, expressed as mean percent volume (MV % ± SE).

ApenninePlain
Year2021202220232024202520212022202320242025
N° of samples262189188777620113812493
Species and categories
Sheep (Ovis aries)0.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.5 ± 0.50.0 ± 0.0
Goat (Capra hircus)0.0 ± 0.00.0 ± 0.00.5 ± 0.50.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.3 ± 0.30.0 ± 0.0
Cattle (Bos taurus)0.7 ± 0.50.5 ± 0.51.0 ± 0.70.0 ± 0.02.4 ± 1.70.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.01.1 ± 1.1
Livestock0.7 ± 0.50.5 ± 0.51.5 ± 0.90.0 ± 0.02.4 ± 1.70.0 ± 0.00.0 ± 0.00.0 ± 0.00.8 ± 0.81.1 ± 1.1
Wild boar (Sus scrofa)14.3 ± 2.024.9 ± 2.947.5 ± 3.335.1 ± 5.35.7 ± 2.69.8 ± 6.78.9 ± 8.913.9 ± 5.51.3 ± 0.912.7 ± 3.4
Roe deer (Capreolus capreolus)72.9 ± 2.563.6 ± 3.238.3 ± 3.339.2 ± 5.469.3 ± 5.00.0 ± 0.08.9 ± 8.94.8 ± 3.416.6 ± 3.227.8 ± 4.6
Fallow deer (Dama dama)6.0 ± 1.54.0 ± 1.43.8 ± 1.34.9 ± 2.45.2 ± 2.50.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.02.1 ± 1.5
Red deer (Cervus elaphus)1.5 ± 0.72.3 ± 1.00.5 ± 0.52.4 ± 1.71.3 ± 1.30.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.0
Cervids (not determined)0.0 ± 0.00.0 ± 0.00.0 ± 0.01.3 ± 1.31.3 ± 1.30.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.0
Wild ungulates94.7 ± 1.094.8 ± 1.190.1 ± 1.982.8 ± 3.982.7 ± 4.09.8 ± 6.717.8 ± 12.018.7 ± 6.117.9 ± 3.342.6 ± 5.0
Rat (Rattus sp.)0.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.8 ± 0.81.1 ± 1.1
Hedgehog (Erinaceus europaeus)0.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.7 ± 0.70.0 ± 0.0
Vole (Microtus sp.)0.0 ± 0.00.0 ± 0.00.3 ± 0.30.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.0
Dormouse (Glis glis)0.2 ± 0.20.0 ± 0.03.1 ± 1.30.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.0
Species not determined0.0 ± 0.00.1 ± 0.10.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.0
Small mammals0.2 ± 0.20.1 ± 0.13.5 ± 1.30.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.01.5 ± 1.01.1 ± 1.1
Coypu (Myocastor coypus)0.0 ± 0.00.0 ± 0.00.0 ± 0.04.9 ± 2.43.9 ± 2.283.3 ± 8.068.1 ± 13.671.7 ± 7.076.0 ± 3.543.1 ± 5.0
Brown hare (Lepus europaeus)1.1 ± 0.60.0 ± 0.00.3 ± 0.35.1 ± 2.52.6 ± 1.80.0 ± 0.00.0 ± 0.02.6 ± 2.60.0 ± 0.01.1 ± 0.9
Eastern cottontail (Sylvilagus floridanus)0.0 ± 0.00.0 ± 0.00.6 ± 0.50.0 ± 0.00.0 ± 0.04.9 ± 4.98.9 ± 8.93.6 ± 2.70.9 ± 0.83.2 ± 1.8
Martens (Martes sp.)0.0 ± 0.01.2 ± 0.60.9 ± 0.60.0 ± 0.01.3 ± 1.30.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.0
European badger (Meles meles)0.1 ± 0.10.0 ± 0.00.0 ± 0.02.5 ± 1.82.6 ± 1.80.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.01.1 ± 1.1
Red fox (Vulpes vulpes)0.0 ± 0.00.5 ± 0.50.2 ± 0.10.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.0
Dog (Canis lupus familiaris)0.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.02.9 ± 1.7
Domestic cat (Felis catus)0.0 ± 0.00.5 ± 0.50.5 ± 0.50.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.0
Medium-sized mammals1.3 ± 0.72.3 ± 0.92.6 ± 1.112.6 ± 3.710.3 ± 3.588.2 ± 6.777.0 ± 11.977.9 ± 6.576.9 ± 3.551.3 ± 5.0
Birds0.4 ± 0.40.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.0 ± 0.00.4 ± 0.4
Fruit0.4 ± 0.20.2 ± 0.20.2 ± 0.11.1 ± 1.10.8 ± 0.50.0 ± 0.00.0 ± 0.00.0 ± 0.00.2 ± 0.10.2 ± 0.2
Grass0.1 ± 0.10.4 ± 0.10.4 ± 0.10.7 ± 0.20.7 ± 0.20.1 ± 0.13.9 ± 3.41.3 ± 1.00.2 ± 0.10.3 ± 0.1

Sample size (N) is reported for each year and sector. Food items are grouped into categories (livestock, wild ungulates, small mammals, medium-sized mammals, birds, fruit, and grass; shown in bold), with prey species listed within each category.

The two-way PERMANOVA showed a significant interaction between sector and year, indicating that the magnitude of differences in diet between sectors varied over time. Sector explained 48% of the variation in diet composition, whereas the sector × year interaction explained 2% (Table 3). Year-specific comparisons showed a very strong spatial differentiation in 2021 (F = 455.23, p < 0.001), a weaker but still significant difference in 2023 (F = 3.81, p = 0.034) and 2024 (F = 3.88, p = 0.037), whereas differences were not significant in 2022 (F = 0.56, p = 0.639) or 2025 (F = 1.17, p = 0.289).

Table 3. Effects of sector (apennine and plain) and year (from 2021 to 2025) on diet composition of wolf (Canis lupus) in north-western Italy tested by two-way PERMANOVA.

TermR2Fp
Sector0.481041.67< 0.001
Year0.00040.840.382
Sector x Year0.0244.17< 0.001

Coefficient of determination (R2), test statistics (F) and p-values are reported.

3.3 Variation in individual food categories

In the Apennine sector, wild ungulates represented the dominant food category, but their contribution varied significantly across years (Kruskal-Wallis test: H = 30.74, p < 0.001), being higher during the first three years compared to the last two. Pairwise comparisons confirmed lower use in 2024 compared to 2021 (p = 0.04), 2022 (p = 0.004), and 2023 (p < 0.001), and, similarly, in 2025 compared to 2021 (p = 0.03), 2022 (p = 0.003), and 2023 (p < 0.001). In contrast, medium-sized mammals, representing a secondary prey category, showed the opposite and significant trend (H = 21.54, p < 0.001), with consumption increasing in 2024 and 2025. Pairwise comparisons confirmed higher use in 2024 compared to 2021 (p = 0.003) and 2023 (p = 0.028), and in 2025 compared to 2021 (p = 0.015). Although most of the remaining food categories also showed significant interannual variation, their contribution to the overall diet was negligible (Table 2, Figure 3; Supplementary Material 3).

Food categories consumed by wolves (*Canis lupus*) across years (2021-2025) in the two sectors (apennine and plain) of the study area in north-western Italy expressed as mean percent volume (MV % ± SE).
Figure 3. Food categories consumed by wolves (Canis lupus) across years (2021-2025) in the two sectors (apennine and plain) of the study area in north-western Italy expressed as mean percent volume (MV % ± SE).

In the Plain sector, medium-sized mammals represented the main food category and their contribution varied significantly across years (H = 28.94, p < 0.001), showing a decrease from the first to the last year. Pairwise comparisons confirmed lower use in 2025 compared to 2021 (p = 0.003), 2023 (p = 0.003), and 2024 (p < 0.001). In contrast, wild ungulates also showed significant temporal variation (H = 22.72; p = 0.001), with higher values in 2025 compared to 2021 (p = 0.015), 2023 (p = 0.037), and 2024 (p < 0.001). Other dietary categories were consumed at low levels and showed no consistent temporal patterns (Table 2, Figure 3).

Both wild ungulates and medium-sized mammals showed significant differences between the Apennine and the Plain across all years (all p < 0.001), indicating persistent spatial differences in the contribution of these key prey categories to the wolf diet.

3.4 Variation within food categories

Among wild ungulates, wild boar and roe deer were the most consumed species. In the Apennine sector, the two species exhibited significant but contrasting temporal patterns, with wild boar consumption increasing from 2021 to a peak in 2023 and then declining markedly through 2025 (H = 116.07, p < 0.001), with post hoc tests indicating significant differences among most year pairs, particularly between 2023 and other years. In contrast, roe deer consumption decreased until 2023 and increased thereafter (H = 93.02, p < 0.001), with significant differences primarily separating 2023–2024 from other years (Table 4). Fallow deer and red deer contributions remained comparatively low and did not show significant variation among years (Figure 4). In the Plain sector, roe deer showed an overall increase from the first to the last year (H = 16.88, p = 0.002) with significant differences involving 2021-2025 (p = 0.023) and 2023-2025 (p = 0.012). In contrast, wild boar remained relatively stable over time, except for a marked decrease in 2024 (H = 14.02, p = 0.007). Fallow deer was rarely consumed and contributed marginally to the overall diet (Figure 4).

Table 4. Pairwise comparisons (Dunn’s post hoc tests) among years for wild ungulate species in the wolf (Canis lupus) diet (Apennine sector; north-western Italy) based on their mean percent volume (MV%) in analyzed samples.

Wild boarRoe deer
2021202220232024202520212022202320242025
2021–0.006< 0.0010.003n.s.2021–0.016< 0.001< 0.001n.s.
2022–< 0.001n.s.< 0.0012022–< 0.0010.012n.s.
2023–0.013< 0.0012023–n.s.< 0.001
2024–< 0.0012024–< 0.001
2025–2025–
Species of wild ungulates consumed by wolves (*Canis lupus*) across years (2021-2025) in the two sectors (Apennine and Plain) of the study area in north-western Italy expressed as mean percent volume (MV % ± SE).
Figure 4. Species of wild ungulates consumed by wolves (Canis lupus) across years (2021-2025) in the two sectors (Apennine and Plain) of the study area in north-western Italy expressed as mean percent volume (MV % ± SE).

In the Apennine sector, the consumption of medium-sized mammals increased during the last two years, still representing a secondary category. Coypu, in particular, showed the most pronounced change, being absent from 2021 to 2023 and increasing in 2024 and 2025 (H = 30.13, p < 0.001). Other species were occasionally consumed and did not show clear trends, though the consumption of brown hare (H = 11.22, p = 0.024), martens (H = 16.68, p = 0.002) and badger (H = 12.27, p = 0.015) also varied significantly (Figure 5). In the Plain sector, the coypu was the most important prey, but showed a decrease during the period (H = 33.28, p < 0.001); in particular, species consumption in 2025 was significantly lower compared to 2021 (p = 0.002), 2023 (p = 0.008), and 2024 (p < 0.001). Other species were consumed only sporadically and did not show clear temporal trends (Figure 5).

Species of medium-sized mammals consumed by wolves (*Canis lupus*) across years (2021-2025) in the two sectors (apennine and plain) of the study area in north-western Italy expressed as mean percent volume (MV % ± SE).
Figure 5. Species of medium-sized mammals consumed by wolves (Canis lupus) across years (2021-2025) in the two sectors (apennine and plain) of the study area in north-western Italy expressed as mean percent volume (MV % ± SE).

3.5 Trophic niche breadth

Wolf diet was generally narrow in our study area. In the Apennine sector, niche breadth remained lower and relatively stable across years, ranging from 0.01 (0.004 - 0.02) in 2021 to 0.06 (0.03 - 0.1) in 2025, with extensive overlap in confidence intervals across all years. In the Plain, niche breadth increased from 0.04 (0.00 - 0.1) in 2021 to 0.18 (0.15 - 0.21) in 2025, although intermediate years showed substantial overlap in confidence intervals, indicating no clear separation among these estimates. Overall, meaningful separation between sectors is evident mainly in 2025, when the Plain exhibited higher niche-breadth values than the Apennine sector; in contrast, in previous years, the overlap in confidence intervals suggests no significant differences (Figure 6).

Trophic niche breadth of wolves (*Canis lupus*) across years (2021-2025) and sectors (Plain and Apennine) in north-western Italy measured by the standardized Levins index (B). Error bars depict lower and upper 95% CIs.
Figure 6. Trophic niche breadth of wolves (Canis lupus) across years (2021-2025) and sectors (Plain and Apennine) in north-western Italy measured by the standardized Levins index (B). Error bars depict lower and upper 95% CIs.

3.6 Key prey species and consumption trends

Differences in the wolf diet between the Apennine and Plain sectors were driven primarily by coypu and roe deer. Coypu alone accounted for 38.5% of the dissimilarity, while the combined contribution of coypu and roe deer explained 71.6% of the total dissimilarity between sectors (Supplementary Material 4).

These two species exhibited opposite spatial and temporal occurrence trends, with the coypu showing increasing occurrence probabilities in the Apennines and decreasing in the Plain, and the roe deer showing decreasing occurrence probabilities in the Apennines and increasing in the Plain (Table 5, Figure 7).

Table 5. Parameter estimates from the GLM evaluating the occurrence of coypu (Myocastor coypus) and roe deer (Capreolus capreolus) in the wolf (Canis lupus) diet in north-western Italy.

TermβSE95% CIpOR
Coypu
Intercept-5.6740.781-7.203; -4.144< 0.0010.003
Sector (Plain)7.2400.8205.632; 8.847< 0.0011393.546
Year1.3230.4200.500; 2.1450.0023.753
Sector x Year-1.9200.447-2.796; -1.044< 0.0010.147
Roe deer
Intercept0.5210.0780.369; 0.673< 0.0011.684
Sector (Plain)-2.9710.362-3.681; -2.261< 0.0010.051
Year-0.2950.058-0.409; -0.181< 0.0010.744
Sector x Year1.0410.2130.625; 1.459< 0.0012.834

Regression coefficients (β), standard errors (SE), 95% confidence intervals (CI), p-values, and odds ratios (OR = exp(β)) are reported.

Predicted response curves from the GLMs describing the probability of **(A)** coypu (*Myocastor coypus*) and **(B)** roe deer (*Capreolus capreolus*) occurrence in the wolf (*Canis lupus*) diet across years (2021-2025) and sectors (Plain and Apennine) in north-western Italy.
Figure 7. Predicted response curves from the GLMs describing the probability of (A) coypu (Myocastor coypus) and (B) roe deer (Capreolus capreolus) occurrence in the wolf (Canis lupus) diet across years (2021-2025) and sectors (Plain and Apennine) in north-western Italy.

4 Discussion

The rapid expansion of wolves into highly anthropized landscapes raises important questions about how their trophic ecology responds to novel prey assemblages and whether they maintain their reliance on wild prey or exploit anthropogenic and alternative food resources (Cerri et al., 2026). Our results show that wolf diet remained overwhelmingly based on wild prey despite the expansion into one of the most human-modified landscapes in Europe. However, the relative contribution of different prey species varied markedly between sectors and changed over time, highlighting a high degree of trophic flexibility while maintaining a predominantly wild prey-based diet.

Interestingly, we observed a negligible use of anthropogenic food resources. Livestock consistently represented only a very small proportion of the diet, while domestic pets were almost completely absent, indicating that wolves remained almost entirely dependent on wild prey despite colonizing an area potentially rich not only in livestock and pets but also in other anthropogenic food sources, such as livestock carcass remains or waste associated with intensive farming. Regarding livestock, sheep, goats, and cattle were only occasionally consumed both in the Apennine and in the Plain. This pattern is consistent with numerous studies showing that, where wild prey are abundant, livestock constitutes a secondary or a minor component of wolf diet (e.g., Barja et al., 2023; Gazzola et al., 2005; Jędrzejewski et al., 2012; Mysłajek et al., 2022; Nowak et al., 2011, 2024; Reinhardt et al., 2026; Sin et al., 2019; Torretta et al., 2017; Trbojević et al., 2020; Wagner et al., 2012). Moreover, long-term studies have shown that wolf reliance on livestock may decline over time and eventually become negligible, as wild prey populations provide increasingly abundant food resources available year-round (Figueiredo et al., 2020; Imbert et al., 2016; Torretta et al., 2024).

Overall, these findings indicate that wolves successfully expanded into highly anthropogenic landscapes without increasing their reliance on anthropogenic food resources. This contrasts with the expectation that human-dominated landscapes may expose wolves to novel food subsidies, a topic that remains insufficiently investigated in expanding wolf populations (Cerri et al., 2026).

Despite this overall similarity in trophic strategy, prey composition differed markedly between the historically occupied Apennine and the recently colonized Plain. In the Apennine, wild ungulates represented the bulk of wolf diet, whereas in the Plain, medium-sized mammals were the most consumed category, followed by wild ungulates.

Predictions derived from a wolf colonization model suggested that lowland areas characterized by higher wild ungulate abundance, particularly roe deer abundance, would represent the most likely sites for future wolf establishment (Torretta et al., 2024). These predictions were confirmed, as the first packs settled along the main rivers crossing the Plain, where riverine habitats characterized by continuous tree cover at the interface with agricultural landscapes provide optimal conditions for the species. A notable example is the Ticino River, where roe deer occur at high densities (De Pasquale et al., 2019; Torretta, 2024) and which currently supports at least two wolf packs (De Feudis et al., 2025; Torretta et al., 2026). Unexpectedly, however, wild ungulates represented only a secondary component of the diet in the Plain sector. This pattern may suggest that factors in addition to prey availability contribute to prey use, such as prey accessibility, profitability and capture effort, which may play a major role in determining diet during the early stages of colonization.

Despite marked differences in prey composition, trophic niche breadth remained relatively narrow in both sectors. However, while niche breadth remained stable in the Apennine sector, it increased substantially in the Plain sector over the years. This suggests that the colonization process involved not only a shift in prey use, driven by differences in prey availability and accessibility, but also a progressive broadening of the trophic niche.

Regarding the Apennine, we observed an interesting temporal prey switching between two ungulate species, roe deer and wild boar, which departed from the long-term pattern described in Torretta et al. (2024). A plausible explanation is the spread of African Swine Fever (ASF; European Food Safety Authority (EFSA) et al., 2023) across northern Italy. ASF-infected wild boar can exhibit severe clinical signs, including disorientation, abnormal movements, reduced wariness, and weakened condition, which may increase their vulnerability to wolf predation (Morelle et al., 2023; Sauter-Louis et al., 2021). Consequently, wolves may have temporarily increased their consumption of wild boar by exploiting this increase in prey susceptibility. As ASF progressed and the pool of vulnerable individuals declined, wolves apparently shifted back toward their previous reliance on roe deer.

Regarding the Plain, coypu emerged as a key prey resource supporting wolves. Previous studies conducted in a very different context, i.e. the “Maremma” Regional Park (Central Italy), have generally described coypu as a secondary prey item in wolf diet (Ferretti et al., 2019; Lazzeri et al., 2024). In contrast, in the Po Plain the coypu may represent a more important resource for wolves. The species can be considered a particularly profitable prey, as it is extremely abundant and widespread (Balestrieri et al., 2016), relatively easy to capture, and its body mass (typically 4–8 kg) provides a substantial energetic reward (Cerri et al., 2026) while remaining much easier to subdue than an ungulate. Moreover, as an invasive species introduced to Italy through escapes and releases from fur farms (Bertolino and Viterbi, 2010), coypu probably retains relatively weak antipredator responses towards wolves. Consequently, the coypu may represent an important ecological subsidy, providing a highly profitable energetic resource that facilitates wolf persistence and establishment during the early stages of colonization. Future studies should investigate whether wolf predation affects coypu population dynamics and whether wolves may contribute to reducing the impacts of this invasive species on human activities and ecosystems.

The dietary differences between sectors were largely explained by only two prey species, coypu and roe deer, whose temporal trajectories appeared to converge. As colonization progressed, the contribution of coypu declined while roe deer became increasingly important in the Plain. This pattern suggests that wolf diet may undergo a progressive adjustment following population establishment, reflecting changes in pack structure, hunting efficiency and prey exploitation. One possible explanation is that, as newly established packs increase in size and reproductive output, the energetic requirements of the group also increase. Under these conditions, larger prey such as roe deer may become progressively more profitable than medium-sized prey because each successful hunting event provides substantially greater biomass. This interpretation is also consistent with the observed increase in trophic niche breadth in the Plain during the last year of the study, suggesting that newly established packs initially exploit the most accessible prey before progressively incorporating larger ungulates into their diet as they become established.

Understanding how wolf trophic ecology changes as populations establish in newly colonized landscapes is challenging, particularly when wolf presence is still unstable, thus scat detection can be difficult. This may affect the number and reliability of samples collected and should therefore be considered when interpreting the results. In our study, field identification of wolf scats was performed by experienced and trained operators. Moreover, the study area is characterized by the absence of stray dogs, while the wolf is the only large carnivore occurring in the area, making misidentification with other carnivores unlikely (but see Echegaray and Vilà, 2010). This is also supported by the molecular identification performed on a subset of samples, for which all analyzed scats were confirmed as wolf scats, with no samples assigned to dogs or foxes. Although a small proportion of scats may have been misidentified in the field, we expect this potential error to have had little influence on the overall results given the large number of samples analyzed. This is particularly true for the Apennine sector, where a large number of samples was collected in each year. In the Plain sector, however, the potential effect of a few misidentified samples may have been greater in some years because of the smaller number of samples available. Finally, differences in sampling protocols among years and sectors should be taken into account when assessing temporal and spatial patterns in diet composition.

Apart from the considered limitations, the results suggest that feeding habits are highly dynamic during wolf range expansion: as packs become established, their diet progressively shifts from readily accessible prey resources exploited during the initial colonization phase toward prey supporting long-term persistence, emphasizing the need to understand how wolf trophic ecology evolves in newly occupied ecosystems (Cerri et al., 2026).

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fetho.2026.1950752/full#supplementary-material

Supplementary material Supplementary material at the source

Footnotes

Edited by: Stephanie Ann Poindexter, University at Buffalo, United States

Reviewed by: Ron Moen, University of Minnesota Duluth, United States

Emma Reasoner, Cheetah Conservation Fund, Namibia

Sofia Lino, Universidade de Lisboa, Portugal

Statements

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The authors ET, AH declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Data availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

ET: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing. LG: Data curation, Investigation, Writing – review & editing. GR: Data curation, Investigation, Writing – review & editing. OD: Project administration, Writing – review & editing. MF: Project administration, Writing – review & editing. LC: Investigation, Writing – review & editing. AH: Resources, Supervision, Writing – review & editing.

Acknowledgements

We are grateful to all the students who contributed to this research, particularly C. Albera and M. T. Zarroli. We also thank the park rangers of the “Ticino Valley” Natural Park and the volunteer ecological guards (GEV) of the Province of Pavia, whose valuable support was essential for the field collection of samples.

References

  1. Anderson M. J. (2001). A new method for non-parametric multivariate analysis of variance. Austral Ecol. 26, 32 – 46. doi: doi:10.1111/j.1442-9993.2001.01070.pp.x
  2. Balestrieri A., Zenato M., Fontana E., Vezza P., Remonti L., Caronni F. E.. (2016). An indirect method for assessing the abundance of introduced pest Myocastor coypus (Rodentia) in agricultural landscapes. J. Zool. 298, 37 – 45. doi: doi:10.1111/jzo.12284
  3. Barber-Meyer S. M., Wheeldon T. J., Mech L. D. (2021). The importance of wilderness to wolf (Canis lupus) survival and cause-specific mortality over 50 years. Biol. Conserv. 258, 109145. doi: doi:10.1016/j.biocon.2021.109145
  4. Barja I., Navarro-Castilla Á., Ortiz-Jiménez L., España Á., Hinojosa R., Sánchez-Sotomayor D.. (2023). Wild ungulates constitute the basis of the diet of the Iberian wolf in a recently recolonized area: Wild boar and roe deer as key species for its conservation. Animals 13, 3364. doi: doi:10.3390/ani13213364
  5. Černe R., Krofel M., Jonozovič M., Sila A., Potočnik H., Marenče M.. (2019). A Fieldguide for Investigating Damages Caused by Carnivores: Brown Bear, Grey Wolf, Golden Jackal, Red Fox, Eurasian Lynx. (Ljubljana: Slovenia Forest Service - LIFE DINALP BEAR project), 88 p.
  6. Belardi I., Borkowski J., Lazzeri L., Banul R., Pacini G., Poerling A.. (2024). Spatiotemporal plasticity of prey selection in the wolf. J. Zool. 324, 118 – 127. doi: doi:10.1111/jzo.13205
  7. Bertolino S., Viterbi R. (2010). Long-term cost-effectiveness of coypu (Myocastor coypus) control in Piedmont (Italy). Biol. Invasions 12, 2549 – 2558. doi: doi:10.1007/s10530-009-9664-4
  8. Boitani L., Kaczensky P., Alvares F., Andrén H., Balys V., Blanco J. C.. (2022). Assessment of the Conservation Status of the Wolf (Canis Lupus) in Europe. Convention on the Conservation of European Wildlife and Natural Habitats …. (Strasbourg: Convention on the conservation of European wildlife and natural habitats, Standing Committee).
  9. Brillouin L. (1956). Science and Information Theory (New York: Academic Press).
  10. Brunner H., Coman B. J. (1974). The Identification of Mammalian Hair (Melbourne: Inkata Press).
  11. Canova L., Meriggi A. (2026). Reclaiming the man-made plain: Ecological factors influencing the colonization of the wolf Canis lupus in the western Po Plain (NW Italy). Hystrix Ital. J. Mammalogy 36, 16 – 22. doi: doi:10.4404/hystrix-00776-2025
  12. Cerri J., Brogi R., Musto C., Bassi E., Ventura G., Bianchi A.. (2026). Identifying and overcoming knowledge gaps in the feeding ecology of gray wolves inhabiting anthropized landscapes. Curr. Zool., zoag010. doi: doi:10.1093/cz/zoag010
  13. Chapron G., Kaczensky P., Linnell J. D. C., von Arx M., Huber D., Andren H.. (2014). Recovery of large carnivores in Europe’s modern human-dominated landscapes. Science 346, 1517 – 1519. doi: doi:10.1126/science.1257553
  14. Cimatti M., Ranc N., Benítez‐López A., Maiorano L., Boitani L., Cagnacci F.. (2021). Large carnivore expansion in Europe is associated with human population density and land cover changes. Divers. Distrib. 27, 602 – 617. doi: doi:10.1111/ddi.13219
  15. Ciucci P., Mancinelli S., Boitani L., Gallo O., Grottoli L. (2020). Anthropogenic food subsidies hinder the ecological role of wolves: Insights for conservation of apex predators in human-modified landscapes. Global Ecol. Conserv. 21, e00841. doi: doi:10.1016/j.gecco.2019.e00841
  16. Ciucci P., Sand H., Åkesson M., Kusak J. (2026). “ Wolf Canis lupus Linnaeus 1758,” in Carnivora. Eds. Loy A., Ciucci P. (Cham: Springer Nature Switzerland), 279 – 341. doi: doi:10.1007/978-3-030-44035-0_118
  17. Clarke K. R. (1993). Non‐parametric multivariate analyses of changes in community structure. Aust. J. Ecol. 18, 117 – 143. doi: doi:10.1111/j.1442-9993.1993.tb00438.x
  18. De Feudis C., Torretta E., Orioli V., Tirozzi P., Bani L., Meriggi A.. (2025). Dispersal and settlement dynamics of wolves in a lowland ecological corridor in northern Italy: Effects of resource availability and human disturbance. Biol. Conserv. 302, 110936. doi: doi:10.1016/j.biocon.2024.110936
  19. De Marinis A. M., Asprea A. (2006). Hair identification key of wild and domestic ungulates from southern Europe. Wildl. Biol. 12, 305 – 320. doi: doi:10.2981/0909-6396(2006)12[305:HIKOWA]2.0.CO;2
  20. De Pasquale D., Dondina O., Scancarello E., Meriggi A. (2019). Long-term viability of a reintroduced population of roe deer Capreolus capreolus, in a lowland area of northern Italy. Folia Zool. 68, 9. doi: doi:10.25225/fozo.045.2019
  21. Di Bernardi C., Chapron G., Kaczensky P., Álvares F., Andrén H., Balys V.. (2025). Continuing recovery of wolves in Europe. PloS Sustainability Transform. 4, e0000158. doi: doi:10.1371/journal.pstr.0000158
  22. Dondina O., Orioli V., Torretta E., Merli F., Bani L., Meriggi A. (2020). Combining ensemble models and connectivity analyses to predict wolf expected dispersal routes through a lowland corridor. PloS One 15, e0229261. doi: doi:10.1371/journal.pone.0229261
  23. Echegaray J., Vilà C. (2010). Noninvasive monitoring of wolves at the edge of their distribution and the cost of their conservation. Anim. Conserv. 13, 157 – 161. doi: doi:10.1111/j.1469-1795.2009.00315.x
  24. European Food Safety Authority (EFSA), Ståhl, K., Boklund, A., Podgórski, T., Vergne, T., Abrahantes, J. C., Papanikolaou, A., Zancanaro, G., and Mur, L. (2023). Epidemiological analysis of African swine fever in the European Union during 2022. EFSA Journal. 21 (5), e08016. doi: doi:10.2903/j.efsa.2023.8016x
  25. Feinsinger P., Spears E. E., Poole R. W. (1981). A simple measure of niche breadth. Ecology 62, 27 – 32. doi: doi:10.2307/1936664
  26. Ferreiro‐Arias I., García E. J., Palacios V., Sazatornil V., Rodríguez A., López‐Bao J. V.. (2024). Drivers of wolf activity in a human‐dominated landscape and its individual variability toward anthropogenic disturbance. Ecol. Evol. 14, e70397. doi: doi:10.1002/ece3.70397
  27. Ferretti F., Lovari S., Mancino V., Burrini L., Rossa M. (2019). Food habits of wolves and selection of wild ungulates in a prey-rich Mediterranean coastal area. Mamm. Biol. 99, 119 – 127. doi: doi:10.1016/j.mambio.2019.10.008
  28. Figueiredo A. M., Valente A. M., Barros T., Carvalho J., Silva D. A. M., Fonseca C.. (2020). What does the wolf eat? Assessing the diet of the endangered Iberian wolf (Canis lupus signatus) in northeast Portugal. PloS One 15, e0230433. doi: doi:10.1371/journal.pone.0230433
  29. Gazzola A., Bertelli I., Avanzinelli E., Tolosano A., Bertotto P., Apollonio M. (2005). Predation by wolves (Canis lupus) on wild and domestic ungulates of the western Alps, Italy. J. Zool. 266, 205 – 213. doi: doi:10.1017/S0952836905006801
  30. Guimarães N. F., Álvares F., Ďurová J., Urban P., Bučko J., Iľko T.. (2022). What drives wolf preference towards wild ungulates? Insights from a multi-prey system in the Slovak Carpathians. PloS One 17, e0265386. doi: doi:10.1371/journal.pone.0265386
  31. Imbert C., Caniglia R., Fabbri E., Milanesi P., Randi E., Serafini M.. (2016). Why do wolves eat livestock? Factors influencing wolf diet in northern Italy. Biol. Conserv. 195, 156 – 168. doi: doi:10.1016/j.biocon.2016.01.003
  32. Jędrzejewski W., Niedziałkowska M., Hayward M. W., Goszczyński J., Jędrzejewska B., Borowik T.. (2012). Prey choice and diet of wolves related to ungulate communities and wolf subpopulations in Poland. J. Mammal. 93, 1480 – 1492. doi: doi:10.1644/10-MAMM-A-132.1
  33. Kruuk H., Parish T. (1981). Feeding specialization of the European badger Meles meles in Scotland. J. Anim. Ecol. 50, 773. doi: doi:10.2307/4136
  34. Lazzeri L., Belardi I., Pacini G., Fattorini N., Ferretti F. (2024). Beyond ungulate density: Prey switching and selection by the wolf in a recolonised area. Global Ecol. Conserv. 54, e03069. doi: doi:10.1016/j.gecco.2024.e03069
  35. Lippitsch P., Kühl H., Reinhardt I., Kluth G., Böcker F., Kruk M.. (2024). Feeding dynamics of the wolf (Canis lupus) in the anthropogenic landscape of Germany: A 20-year survey. Mamm. Biol. 104, 151 – 163. doi: doi:10.1007/s42991-024-00399-2
  36. Llaneza L., García E. J., Palacios V., Sazatornil V., López-Bao J. V. (2016). Resting in risky environments: The importance of cover for wolves to cope with exposure risk in human-dominated landscapes. Biodivers. Conserv. 25, 1515 – 1528. doi: doi:10.1007/s10531-016-1134-6
  37. Llaneza L., López-Bao J. V. (2015). Indirect effects of changes in environmental and agricultural policies on the diet of wolves. Eur. J. Wildl. Res. 61, 895 – 902. doi: doi:10.1007/s10344-015-0966-9
  38. Llaneza L., López‐Bao J. V., Sazatornil V. (2012). Insights into wolf presence in human‐dominated landscapes: The relative role of food availability, humans and landscape attributes. Divers. Distrib. 18, 459 – 469. doi: doi:10.1111/j.1472-4642.2011.00869.x
  39. Lüdecke D. (2018). ggeffects: Tidy Data Frames of Marginal Effects from Regression Models. J. Open Source Softw. 3 (26), 772. doi: doi:10.21105/joss.00772
  40. Meriggi A., Brangi A., Matteucci C., Sacchi O. (1996). The feeding habits of wolves in relation to large prey availability in northern Italy. Ecography 19, 287 – 295. doi: doi:10.1111/j.1600-0587.1996.tb01256.x
  41. Meriggi A., Dagradi V., Dondina O., Perversi M., Milanesi P., Lombardini M.. (2015). Short-term responses of wolf feeding habits to changes of wild and domestic ungulate abundance in Northern Italy. Ethology Ecol. Evol. 27, 389 – 411. doi: doi:10.1080/03949370.2014.986768
  42. Meriggi A., Lovari S. (1996). A review of wolf predation in southern Europe: does the wolf prefer wild prey to livestock ? J. Appl. Ecol. 33, 1561. doi: doi:10.2307/2404794
  43. Meriggi A., Rosa P., Brangi A., Matteucci C. (1991). Habitat use and diet of the wolf in northern Italy. Acta Theriol. 36, 141 – 151. doi: doi:10.4098/at.arch.91-11
  44. Meriggi A., Torretta E., Dondina O. (2020). “ Recent changes in wolf habitat occupancy and feeding habits in Italy: Implications for conservation and reducing conflict with humans,” in Problematic Wildlife Ii: New Conservation and Management Challenges in the Human-Wildlife Interactions. Eds. Angelici F. M., Rossi L. (Cham: Springer International Publishing), 111 – 138. doi: doi:10.1007/978-3-030-42335-3_4
  45. Milanesi P., Meriggi A., Merli E. (2012). Selection of wild ungulates by wolves Canis lupus (L. 1758) in an area of the Northern Apennines (North Italy). Ethology Ecol. Evol. 24, 81 – 96. doi: doi:10.1080/03949370.2011.592220
  46. Mohammadi A., Kaboli M., Sazatornil V., López-Bao J. V. (2019). Anthropogenic food resources sustain wolves in conflict scenarios of Western Iran. PloS One 14, e0218345. doi: doi:10.1371/journal.pone.0218345
  47. Morelle K., Barasona J. A., Bosch J., Heine G., Daim A., Arnold J.. (2023). Accelerometer-based detection of African swine fever infection in wild boar. Proc. R. Soc. B. Biol. Sci. 290, 20231396. doi: doi:10.1098/rspb.2023.1396
  48. Mori E., Benatti L., Lovari S., Ferretti F. (2017). What does the wild boar mean to the wolf ? Eur. J. Wildl. Res. 63. doi: doi:10.1007/s10344-016-1060-7
  49. Mysłajek R. W., Stachyra P., Figura M., Nędzyńska-Stygar M., Stefański R., Korga M.. (2022). Diet of the grey wolf Canis lupus in Roztocze and Solska Forest, south-east Poland. J. Vertebr. Biol. 71, 22040. doi: doi:10.25225/jvb.22040
  50. Nakamura M., Monterroso P., Rio-Maior H., Godinho R., Álvares F., López-Bao J. V.. (2026). Assessing key demographic parameters and viability of a wolf population in a highly human-dominated landscape. Biol. Conserv. 316, 111784. doi: doi:10.1016/j.biocon.2026.111784
  51. Nakamura M., Rio-Maior H., Godinho R., Petrucci-Fonseca F., Álvares F. (2021). Source-sink dynamics promote wolf persistence in human-modified landscapes: Insights from long-term monitoring. Biol. Conserv. 256, 109075. doi: doi:10.1016/j.biocon.2021.109075
  52. Newsome T. M., Boitani L., Chapron G., Ciucci P., Dickman C. R., Dellinger J. A.. (2016). Food habits of the world’s grey wolves. Mammal Rev. 46, 255 – 269. doi: doi:10.1111/mam.12067
  53. Nowak S., Mysłajek R. W., Kłosińska A., Gabryś G. (2011). Diet and prey selection of wolves (Canis lupus) recolonising Western and Central Poland. Mamm. Biol. - Z. Fr. Säugetierkunde 76, 709 – 715. doi: doi:10.1016/j.mambio.2011.06.007
  54. Nowak S., Tomczak P., Kraśkiewicz A., Więckowski J., Tołkacz K., Baranowska W.. (2024). Wolf diet in the Notecka Forest, western Poland. Wildl. Biol. 2024, e01224. doi: doi:10.1002/wlb3.01224
  55. Oksanen J., Simpson G. L., Blanchet F. G., Kindt R., Legendre P., Minchin P. R.. (2026). Vegan: Community Ecology Package. Available online at: https://CRAN.R-project.org/package=vegan (Accessed May 1, 2026).
  56. Peterson R. O., Ciucci P. (2003). “ The wolf as a carnivore,” in Wolves: Behavior, Ecology and Conservation (Chicago: University of Chicago Press), 104 – 130.
  57. R Core Team (2026). R: A Language and Environment for Statistical Computing (Vienna: R Foundation for Statistical Computing). Available online at: http://www.R-project.org/ (Accessed May 1, 2026).
  58. Reinhardt I., Arbieu U., Mendgen P., Zimmermann B., Berger A., Kluth G.. (2026). How to stay wild in a highly domesticated landscape? Spatiotemporal behaviour of wolves in Germany. Wildl. Biol., e01590. doi: doi:10.1002/wlb3.01590
  59. Sauter-Louis C., Conraths F. J., Probst C., Blohm U., Schulz K., Sehl J.. (2021). African swine fever in wild boar in Europe—A review. Viruses 13, 1717. doi: doi:10.3390/v13091717
  60. Sin T., Gazzola A., Chiriac S., Rîșnoveanu G. (2019). Wolf diet and prey selection in the South-Eastern Carpathian Mountains, Romania. PloS One 14, e0225424. doi: doi:10.1371/journal.pone.0225424
  61. Sunde P., Collet S., Nowak C., Thomsen P. F., Hansen M. M., Schulz B.. (2021). Where have all the young wolves gone? Traffic and cryptic mortality create a wolf population sink in Denmark and northernmost Germany. Conserv. Lett. 14, e12812. doi: doi:10.1111/conl.12812
  62. Teerink B. J. (1991). Hair of West-European Mammals: Atlas and Identification Key (Cambridge: Cambridge Univ. Press).
  63. Theuerkauf J., Jedrzejewski W., Schmidt K., Gula R. (2003). Spatiotemporal segregation of wolves from humans in the Białowieża Forest (Poland). J. Wildl. Manage. 67, 706. doi: doi:10.2307/3802677
  64. Torretta E. (2024). Demographic and behavioural responses of the roe deer (Capreolus capreolus) to landscape modifications and landscape of fear. (Pavia: Doctoral thesis, University of Pavia). Available online at: https://iris.unipv.it/bitstream/11571/1499875/2/Thesis%20Elisa%20Toretta.pdf (Accessed May 1, 2026).
  65. Torretta E., Binetti C., Meriggi A. (2018). Distribuzione, Dieta E Impatto Del Lupo Sulla Zootecnia E Previsione Del Rischio Di Predazione Nell’appennino Pavese. Relazione Tecnica Realizzata Nell’ambito Del Progetto LIFE GESTIRE 2020, Azione A16 – Strategia Regionale Sui Grandi Carnivori. (Pavia: University of Pavia), 72.
  66. Torretta E., Brangi A., Meriggi A. (2024). Changes in wolf occupancy and feeding habits in the Northern Apennines: Results of long-term predator–prey monitoring. Animals 14, 735. doi: doi:10.3390/ani14050735
  67. Torretta E., Corradini A., Pedrotti L., Bani L., Bisi F., Dondina O. (2023). Hide-and-Seek in a highly human-dominated landscape: Insights into movement patterns and selection of resting sites of rehabilitated wolves (Canis lupus) in Northern Italy. Animals 13, 46. doi: doi:10.3390/ani13010046
  68. Torretta E., Frigerio E., Giussani L., Rampazi G., Di Francesco M., Dondina O.. (2026). Estimating pack size and reproductive success in expanding wolf populations using camera trapping. XIV Congresso Italiano di Teriologia, (Bolzano).
  69. Torretta E., Meriggi A. (2018). Monitoraggio Della Presenza Del Lupo Nell’appennino Pavese: Espansione Dell’areale, Idoneità Ambientale E Stima Della Popolazione. Relazione Tecnica Realizzata Nell’ambito Del Progetto LIFE GESTIRE 2020, Azione A16 – Strategia Regionale Sui Grandi Carnivori. (Pavia: University of Pavia), 41.
  70. Torretta E., Serafini M., Imbert C., Milanesi P., Meriggi A. (2017). Wolves and wild ungulates in the Ligurian Alps (Western Italy): Prey selection and spatial-temporal interactions. Mammalia 81, 537 – 551. doi: doi:10.1515/mammalia-2016-0066
  71. Tourani M., Moqanaki E. M., Boitani L., Ciucci P. (2014). Anthropogenic effects on the feeding habits of wolves in an altered arid landscape of central Iran. Mammalia 78, 117 – 121. doi: doi:10.1515/mammalia-2012-0119
  72. Trbojević I., Penezić A., Kusak J., Stevanović O., Ćirović D. (2020). Wolf diet and livestock depredation in North Bosnia and Herzegovina. Mamm. Biol. 100, 499 – 504. doi: doi:10.1007/s42991-020-00053-7
  73. Wagner C., Holzapfel M., Kluth G., Reinhardt I., Ansorge H. (2012). Wolf (Canis lupus) feeding habits during the first eight years of its occurrence in Germany. Mamm. Biol. - Z. Fr. Säugetierkunde 77, 196 – 203. doi: doi:10.1016/j.mambio.2011.12.004
  74. Wickham H., François R., Henry L., Müller K., Vaughan D. (2026). Dplyr: A Grammar of Data Manipulation. Available online at: https://CRAN.R-project.org/package=dplyr (Accessed May 1, 2026).
  75. Wickham H., Vaughan D., Girlich M. (2025). Tidyr: Tidy Messy Data. Available online at: https://CRAN.R-project.org/package=tidyr (Accessed May 1, 2026).
  76. Wickham H. with Sievert, C (2016). Ggplot2: Elegant Graphics for Data Analysis. 2nd ed. (Cham: Springer international publishing).
  77. Zlatanova D., Ahmed A., Valasseva A., Genov P. (2014). Adaptive diet strategy of the wolf (Canis lupus L.) in Europe: A review. Acta Zoologica Bulgarica 66, 439 – 452.

Citation

Torretta, E., et al. (2026). Comparing wolf feeding ecology between historical ranges and recently colonized human-dominated lowlands. Frontiers in Ethology, Volume 5. https://doi.org/
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5 - 2026

Copyright

Copyright © 2026 Torretta, Giussani, Rampazi, Dondina, Di Francesco, Canova and von Hardenberg.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Elisa Torretta

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