No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Predicting spatio-temporal recolonization of large carnivore populations and livestock depredation risk: Wolves in the Italian Alps
Journal of Applied Ecology
Abstract
1. Wolves Canis lupus recently recolonized the Western Alps through dispersal from the Italian Apennines, representing one of several worldwide examples of large carnivores increasing in highly human-dominated landscapes. Understanding and predicting expansion of this population is important for conservation because of its direct impact on livestock and its high level of societal opposition.
2. We built a predictive, spatially explicit, individual-based model to examine wolf population expansion in this fragmented landscape, and livestock depredation risk. We developed the model based on known demographic processes, social structure, behaviour and habitat selection of wolves collected during a 10-year intensive field study of this wolf population.
3. During model validation, our model accurately described the recolonization process within the Italian Alps, correctly predicting wolf pack locations, pack numbers and wolf population size, between 1999 and 2008.
4. We then projected packs and dispersers over the entire Italian Alps for 2013, 2018 and 2023. We predicted 25 packs (95% CI: 19–32) in 2013, 36 (23–47) in 2018 and 49 (29–68) in 2023. The South-Western Alps were the main source for wolves repopulating the Alps from 1999 to 2008. The source area for further successful dispersers will probably shift to the North-Western Alps after 2008, but the large lakes in the Central Alps will probably act as a spatial barrier slowing the wolf expansion.
5. Using the pack presence forecasts, we estimated spatially explicit wolf depredation risk on livestock, allowing tailored local and regional management actions.
6. Synthesis and applications. Our predictive model is novel because we follow the spatio-temporal dynamics of packs, not just population size, which have substantially different requirements and impacts on wolf–human conflicts than wandering dispersers. Our approach enables prioritization of management efforts, including minimizing livestock depredations, identifying important corridors and barriers, and locating future source populations for successful wolf recolonization of the Alps.
... Europe, different attempts have been made to assess potential wolf habitat during the expansion of the populations (Fechter & Storch, 2014;Jedrzejewski et al., 2008;Louvrier, Chambert, et al., 2018;Marucco & McIntire, 2010;Nowak et al., 2017), but there is a huge variability in habitat selection factors found across these studies, from road avoidance and forest selection to altitude or farmland areas. It remains unclear whether this variation reflects wolf preferences, differences in environmental conditions or food availability, or whether it is an artefact of the modelling process, especially due to data obtained at different phases of the expansion process. ...
... Germany (Massei et al., 2015;Reinhardt et al., 2021). In a regional analysis of prey abundance versus wolf abundance (Appendix S3), we did not find any effect of wolf pack numbers on the population trends of any prey species. ...
... -, suggests that past assessments of wolf habitat suitability for Europe (e.g.Fechter & Storch, 2014;Louvrier, Chambert, et al., 2018;Marucco & McIntire, 2010) were rather conservative. By colonizing the new areas in Germany, the wolf population could expand to serve as a natural connection between eastern and western wolf populations in Europe. ...
Aim
The non‐stationarity in habitat selection of expanding populations poses a significant challenge for spatial forecasting. Focusing on the grey wolf (Canis lupus) natural recolonization of Germany, we compared the performance of different distribution modelling approaches for predicting habitat suitability in unoccupied areas. Furthermore, we analysed whether grey wolf showed non‐stationarity in habitat selection in newly colonized areas, which will impact the predictions for potential habitat.
Location
Germany.
Methods
Using telemetry data as presence points, we compared the predictive performance of five modelling approaches based on combinations of distribution modelling algorithms—GLMM, MaxEnt and ensemble modelling—and two background point selection strategies. We used a homogeneous Poisson point process to draw background points from either the minimum convex polygons derived from telemetry or the whole area known to be occupied by wolves. Models were fit to the data of the first years and validated against independent data representing the expansion of the species. The best‐performing approach was then used to further investigate non‐stationarity in the species' response in spatiotemporal restricted datasets that represented different colonization steps.
Results
While all approaches performed similarly when evaluated against a subset of the data used to fit the models, the ensemble model based on integrated data performed best when predicting range expansion. Models for subsequent colonization steps differed substantially from the global model, highlighting the non‐stationarity of wolf habitat selection towards human disturbance during the colonization process.
Main Conclusions
While telemetry‐only data overfitted the models, using all available datasets increased the reliability of the range expansion forecasts. The non‐stationarity in habitat selection pointed to wolves settling in the best areas first, and filling in nearby lower‐quality habitat as the population increases. Our results caution against spatial extrapolation and space‐for‐time substitutions in habitat models, at least with expanding species.
... Wolf samples were collected yearly between 2001 to 2021 across the Italian Alps over the wolf-occupied range as part of the Piemonte Region monitoring Program [23,24]. Genetic analysis on biological samples, mainly scats, but occasional dead wolf carcasses, or saliva swabs from wounds associated with predation events have been regularly conducted. ...
... Direction. The directions of dispersal indicate that wolves in the Western Alps are moving in any direction, but primarily along the north-south axis for long distance movements, where the mountain chain is present, slightly towards less density areas present in the north compared to the south, where the recolonization process started [24]. However, we documented more wolves than expected that moved towards higher wolf density areas in the south, or to the east. ...
... It remains that the majority of studies indicate that dispersal direction is strongly influenced by the risk of interaction with humans [20], which is also showed in the present study by wolves avoiding the highly urbanized planes and dispersing towards territories in forested and mountainous areas with less human population density [16,47,48]. Mountains constitute the majority of the wolf-occupied area in the Western Alps [24], and likely constitute the habitat corridor facilitating similar dispersal routes among individuals, as seen for other species [49]. ...
Wildlife dispersal directly influences population expansion patterns, and may have indirect effects on the spread of wildlife diseases. Despite its importance to conservation, little is known about dispersal for several species. Dispersal processes in expanding wolf (Canis lupus) populations in Europe is not well documented. Documenting the natural dispersal pattern of the expanding wolf population in the Alps might help understanding the overall population dynamics and identifying diseases that might be connected with the process. We documented 55 natural dispersal events of the expanding Italian wolf alpine population over a 20-year period through the use of non-invasive genetic sampling. We examined a 16-locus microsatellite DNA dataset of 2857 wolf samples mainly collected in the Western Alps. From this, we identified 915 individuals, recaptured 387 (42.3%) of individuals, documenting 55 dispersal events. On average, the minimum straight dispersal distance was 65.8 km (±67.7 km), from 7.7 km to 517.2 km. We discussed the potential implications for maintaining genetic diversity of the population and for wildlife diseases spreading.
... Stage-structured models including age-, breeding-or dispersing-specific individual categories have been developed to project population growth rate, and hence are relevant to make projections at the population level (Haight and Mech, 1997;Marescot et al., 2012). Individual-based models (IBMs) have also been used to model population dynamics and have proven to be more flexible to represent species with complex social structure like wolves or coyotes (Chapron et al., 2016;Marucco and McIntire, 2010;Pitt et al., 2003). IBMs are bottom-up models that simulate the fate of individuals interacting with each other and/or their environment. ...
... IBMs are bottom-up models that simulate the fate of individuals interacting with each other and/or their environment. IBMs can include many individual-level mechanisms (i.e., behavioral rules) and therefore can represent complex individual interactions as exhibited by these social species (Chapron et al., 2016;Haight et al., 2002;Marucco and McIntire, 2010;Pitt et al., 2003). Population-level results emerge from the individual-level simulations (Railsback and Grimm, 2012). ...
... Researchers have used IBMs to simulate the impact of wolf-removal strategies on depredation and population viability (Haight et al., 2002), to test the robustness of abundance indices (Chapron et al., 2016) or to project the recolonization of the species and the associated risk of depredation (Marucco and McIntire, 2010). The models were all based on the fundamental processes of mortality, reproduction and dispersal. ...
The occurrence of wolf populations in human-dominated landscapes is challenging worldwide because of conflicts with human activities. Modeling is an important tool to project wolf dynamics and expansion, and help in decision making concerning management and conservation. However, some individual behaviors and pack dynamics of the wolf life cycle are still unclear to ecologists. Here we present an individual-based model (IBM) to project wolf populations while exploring the lesser-known processes of the wolf life cycle. IBMs are bottom-up models that simulate the fate of individuals interacting with each other, with population-level properties emerging from the individual-level simulations. IBMs are particularly adapted to represent social species such as the wolf that exhibits complex individual interactions. Our IBM projects wolf demography including fine-scale individual behavior and pack dynamics based on up-to-date scientific literature. We explore four processes of the wolf life cycle whose consequences on population dynamics are still poorly understood: the pack dissolution following the loss of a breeder, the adoption of young dispersers by packs, the establishment of new packs through budding, and the different breeder replacement strategies. While running different versions of the IBM to explore these processes, we also illustrate the modularity and flexibility of our model, an asset to model wolf populations experiencing different ecological and demographic conditions. The different parameterization of pack dissolution, territory establishment by budding, and breeder replacement processes influence the projections of wolf populations. As such, these processes require further field investigation to be better understood. The adoption process has a lesser impact on model projections. Being coded in R to facilitate its understanding, we expect that our model will be used and further adapted by ecologists for their own specific applications.
... Reducing LD is arguably-one of the most important tasks for facilitating a more sustainable coexistence of people, livestock and wolves (Van Eeden et al., 2018). To achieve this overarching goal, identifying the effect of land use characteristics on LD could yield valuable information for livestock herders, politics and administration (Marucco and McIntire, 2010). Identifying such spatial associations could support a more focussed planning and implementation of prevention, support and compensatory measures, and thus ensure a more cost-effective use of public funds. ...
... However, their use is constrained by the scarcity of relevant data at the appropriate scale. On the one hand, such models require information on the spatial distribution of wolves (Marucco and McIntire, 2010), which could itself be influenced by the distribution and density of wild prey (Janeiro-Otero et al., 2020). Wolves typically occupy large home range sizes (200 km 2 territory size on average in Germany, https://www.dbbw. ...
Extensive pastoral livestock systems in Central Europe provide multiple ecosystem services and support biodiversity in agricultural landscapes but their viability is challenged by livestock depredation (LD) associated with the recovery of wolf populations. Variation in the spatial distribution of LD depends on a suite of factors, most of which are unavailable at the appropriate scales. To assess if LD patterns can be predicted sufficiently with land use data alone at the scale of one federal state in Germany, we employed a machine learning supported resource selection approach. The model used LD monitoring data, and publicly available land use data to describe the landscape configuration at LD and control sites (resolution 4km*4km). We used SHapley Additive exPlanations to assess the importance and effects of landscape configuration; and cross-validation to evaluate the model performance. Our model predicted the spatial distribution of LD events with a mean accuracy of 74%. The most influential land use features included: grassland, farmland and forest. The risk of livestock depredation was high if these three landscape features co-occurred with a specific proportion. A high share of grassland, combined with a moderate proportion of forest and farmland, increased LD risk. We then used the model to predict the LD risk in five regions; the resulting risk maps showed high congruence with observed LD events. While of correlative nature and lacking specific information on wolf and livestock distribution and husbandry practices, our pragmatic modelling approach can guide spatial prioritization of damage prevention or mitigation practices to improve livestock-wolf coexistence in agricultural landscapes.
... We investigated wolf predation risk on livestock in Italy where, after a human-driven decline in the last two centuries, this large carnivore experienced a recovery following conservation efforts, recolonizing the entire Apennine chain and the Alps, thanks to the protection by laws, its adaptability to habitat changes and the marked recovery of wild prey populations (Boitani, 2000;Valiere et al., 2003;Fabbri et al., 2007;Galaverni et al., 2016). This positive trend also raised public negative attitudes due to the perceived high impact on human activities and caused concern of livestock breeders because of its predatory behaviour (Fritts et al., 2003;Marucco and McIntire, 2010;Dondina et al., 2015). ...
... Recent studies showed the usefulness of PRMs in supporting effective conservation and management actions at multiple stages of decisionmaking (i.e. from farm management to region-level policies; Miller, 2015). Thus, validation of PRMs is particularly relevant as they potentially represent a basis for management actions (Grimm and Railsback, 2005;Marucco and McIntire, 2010) and, given the high values of the validation statistics, we have confidence in our PRMs as decision support tools for implementing efforts to prevent livestock depredations. ...
Globally, large carnivore livestock predations are major causes of conflicts with humans, thus identifying hotspots of carnivore attacks is fundamental to reduce the impact of these, and hence promote coexistence with humans. Species distribution models combining predictor variables with locations of predation events instead of species occurrences (also known as predation risk models)
are increasingly used to predict livestock depredation by carnivores, but they are often developed pooling attacks on different livestock species.
We identified the main factors related to predation risk on livestock using an extensive dataset of 4604 locations of verified wolf predation events on livestock collected in northern and central Italy during 2008–2015 and assessed the importance of pooling versus splitting predation events by prey species.
We found the best predictors of predation events varied by prey species. Specifically, predation risk increased with altitude especially for cattle, with grasslands especially for cattle and sheep and with distance to human settlements, especially for goats and livestock but only slightly for cattle and sheep. However, predation risk decreased as human population density, human settlements and artificial night-time light brightness increased, especially for cattle. Finally, livestock density was positively related to predation risk when herd exceeds 500 heads for km2. Moreover, prey-specific risk models are better tools to predict wolf predation risk on domestic ungulates.
We believe that our approach can be applied worldwide on different predator-prey systems and landscapes to promote human-carnivore coexistence. Actually, while pooling predation events could be primarily used by managers and personnel of wildlife agencies/offices in developing general policies, splitting predation events by prey species could be used at farm-level to better identify livestock owners at risk in high-priority areas and which prevention tools and deterrents (e.g. electric fences, guarding dogs, predator-proof enclosures) should be applied, as the most effective measures differ by species.
... Human density was found in previous studies to influence habitat choice and dispersal of wolves in Italy (Corsi et al. 1999;Marucco & Mcintire 2010). We therefore considered human density as a candidate covariate possibly explaining spatial variation in the diffusion parameter Di. ...
... We estimated the distribution of wolves using a model explicitly incorporating biological mechanisms and making best use of the information contained in species detections and nondetections. Besides, we explored the possibility of forecasting the potential future distribution of a large carnivore, which could be used to target management areas or focus on potential conflictual areas (Marucco & Mcintire 2010;Eriksson & Dalerum 2018). ...
Species distribution models (SDMs) are important statistical tools for ecologists to understand and predict species range. However, standard SDMs do not explicitly incorporate dynamic processes like dispersal. This limitation may lead to bias in inference about species distribution. Here, we adopt the theory of ecological diffusion that has recently been introduced in statistical ecology to incorporate spatio-temporal processes in ecological models. As a case study, we considered the wolf (Canis lupus) that has been recolonizing Eastern France naturally through dispersal from the Apennines since the early 90's. Using partial differential equations for modelling species diffusion and growth in a fragmented landscape, we develop a mechanistic-statistical spatio-temporal model accounting for ecological diffusion, logistic growth and imperfect species detection. We conduct a simulation study and show the ability of our model to i) estimate ecological parameters in various situations with contrasted species detection probability and number of surveyed sites and ii) forecast the distribution into the future. We found that the growth rate of the wolf population in France was explained by the proportion of forest cover, that diffusion was influenced by human density and that species detectability increased with increasing survey effort. Using the parameters estimated from the 2007-2015 period, we then forecasted wolf distribution in 2016 and found good agreement with the actual detections made that year. Our approach may be useful for managing species that interact with human activities to anticipate potential conflicts.
... A prime example is the grey wolf (Canis lupus; hereafter: wolf ). After 20 years of wolf recolonization in Central Europe (Marucco and McIntire 2010, Nowak et al. 2017, Louvrier et al. 2018, analysing the demographic parameters including environmental information to fully comprehend the species expansion and future perspective is timely, especially regarding increasing numbers of livestock kills, a decreasing tolerance of certain stakeholder groups and loud voices for active population management (Arbieu et al. 2019, König et al. 2020, Khorozyan and Heurich 2022. ...
Demographic parameters are key to understanding population dynamics. Here, we analyse the survival and reproduction of the German wolf population in the 20 years following recolonization. Specifically, we analysed the effects of environmental, ecological and individual characteristics on 1) survival probability of the population; 2) annual survival rates of age classes; 3) reproduction probability; and 4) reproductive output, measured as the number of detected pups/juveniles. Using Cox proportional hazards model, we estimated a median survival time of circa three years for wolves. Annual survival probabilities were found to be 0.75 for juveniles, 0.75 for subadults and 0.88 for adults. Survival was lower for juveniles in winter and for subadult males in summer, probably associated with dispersal events. Low habitat suitability was clearly associated with lower survival in juveniles and subadults, but not in adults. Local territory density was related to increased survival. Reproduction probability within a territory was 0.88, but explanatory variables had no effect. Reproductive output was four pups/juveniles on average, positively related to habitat suitability and female experience, but negatively related to territory density. Survival values were very high for the species when compared to other regions. We hypothesize that carrying capacity has not been reached in the study area, thus the survival may decrease in the future if the landscape becomes saturated. Furthermore, our results highlight a spatial pattern in survival and reproduction, with area of better habitat suitability favouring faster population growth. Thus, targeting conservation measures to low habitat suitability areas will have a strong population effect on the short term by boosting survival and reproduction of the individuals, while long‐term viability should be carefully planned with high suitability areas in mind, as those contain the territories with higher survival and reproduction potential.
... With an IBM, Fredrickson and Hedrick (2006) suggested that sterilization is an effective short-term strategy to mitigate introgression between red wolves and coyotes in expanding red wolf populations, and their predictions were successively validated by empirical data (Gese & Terletzky, 2015). IBMs mimicking aspects of gray wolves' social behavior and ecology have also been developed (e.g., Chapron et al., 2016;Marucco & McIntire, 2010). More recently, a multifaceted model meant to account for the inherent complexity of wolf social behavior and dynamics has been produced (Bauduin et al., 2020) that included processes such as inbreeding avoidance, pack dissolution following the loss of a breeder, adoption of dispersers by existing packs, establishment of new packs through budding, and different modalities of breeder replacement (Bauduin et al., 2020). ...
Introgressive hybridization between wolves and dogs is a conservation concern due to its potentially deleterious long‐term evolutionary consequences. European legislation requires that wolf–dog hybridization be mitigated through effective management. We developed an individual‐based model (IBM) to simulate the life cycle of gray wolves that incorporates aspects of wolf sociality that affect hybridization rates (e.g., the dissolution of packs after the death of one/both breeders) with the goal of informing decision‐making on management of wolf–dog hybridization. We applied our model by projecting hybridization dynamics in a local wolf population under different mate choice and immigration scenarios and contrasted results of removal of admixed individuals with their sterilization and release. In several scenarios, lack of management led to complete admixture, whereas reactive management interventions effectively reduced admixture in wolf populations. Management effectiveness, however, strongly depended on mate choice and number and admixture level of individuals immigrating into the wolf population. The inclusion of anthropogenic mortality affecting parental and admixed individuals (e.g., poaching) increased the probability of pack dissolution and thus increased the probability of interbreeding with dogs or admixed individuals and boosted hybridization and introgression rates in all simulation scenarios. Recognizing the necessity of additional model refinements (appropriate parameterization, thorough sensitivity analyses, and robust model validation) to generate management recommendations applicable in real‐world scenarios, we maintain confidence in our model's potential as a valuable conservation tool that can be applied to diverse situations and species facing similar threats.
... Though, most studies have short sampling periods and do not account for the dynamic effects of temporal variation of habitat or anthropogenic covariates on wolf distribution and spatial use, such as burned areas and human population density. Since species distribution is not static and can vary through time and space, particularly in expanding populations (Marucco and McIntire, 2010), dynamic occupancy models can be a powerful tool to address wolf spatial dynamics. ...
Among large carnivores, wolves show a remarkable capability to persist in human-dominated landscapes.
However, the temporal dynamics of variation in spatial use of these landscapes remains poorly understood.
Considering the relevance of spatio-temporal variations of territorial marking on wolf behaviour, either to defend
territory boundaries and core areas or to expand into new areas, the location of wolf signs should reflect the
dynamics of spatial use. Taking advantage of a long-term non-invasive wolf monitoring dataset spanning from
2005 to 2022 we fit a dynamic occupancy model to investigate the effects of environmental and anthropogenic
factors on the dynamics of wolf spatial use in human-dominated landscapes. We focused on two dynamic parameters
– colonization and extinction – and developed a wolf habitat suitability map for Iberia. Colonization
probability increased with higher altitude, livestock density, and unpaved road density, and with the decrease of
burned areas, national-regional, and local road densities. Extinction probability decreased with higher unpaved
road density.
In addition, we evaluated the wolf range dynamics in Iberia to understand if the ecological traits explained the
expansion, stagnation or extinction sites observed since the beginning of the 2000s. Our results contribute to a
sound understanding of wolf spatial use in human-dominated landscapes and its ability to adapt to these heterogeneous
environments, allowing us to support adequate mitigation measures and conservation actions. The
strong influence of livestock on the dynamics of wolf occupancy highlights the need to assess social factors,
human dimensions, and direct wolf mortality causes for conflict management associated with livestock
depredation.
... To model the spatial variation in wolf density across S, we considered the additive and linear effect of the following 5 spatial covariates: 1, historical wolf presence (considering that current wolf density is likely the result of the recolonization history of the species [ Figure 1a]); 2, percent forest cover; 3, percent low natural vegetation; 4, percent bare rock; and 5, human population density (considering that wolves often select for forested habitat and bushlands and avoid bare rocks and human disturbance) (Falcucci et al., 2013;Marucco & McIntire, 2010). A detailed description of each covariate is in Appendix S1. ...
The wolf (Canis lupus) is among the most controversial of wildlife species. Abundance estimates are required to inform public debate and policy decisions, but obtaining them at biologically relevant scales is challenging. We developed a system for comprehensive population estimation across the Italian alpine region (100,000 km²), involving 1513 trained operators representing 160 institutions. This extensive network allowed for coordinated genetic sample collection and landscape‐level spatial capture–recapture analyses that transcended administrative boundaries to produce the first estimates of key parameters for wolf population status assessment. Wolf abundance was estimated at 952 individuals (95% credible interval 816–1120) and 135 reproductive units (i.e., packs) (95% credible interval 112–165). We also estimated that mature individuals accounted for 33–45% of the entire population. The monitoring effort was spatially estimated thereby overcoming an important limitation of citizen science data. This is an important approach for promoting wolf–human coexistence based on wolf abundance monitoring and an endorsement of large‐scale harmonized conservation practices.
... This area (600 km 2 ; altitude: 600-3500 m a.s.l.) is characterized by a typical xeric inner-alpine climate. After the eradication of the local wolf population in the 1920s (Zimen & Boitani, 1975), wolves spontaneously recolonized the area in the 1990s (Bertotto et al., 2020;Marucco & McIntire, 2010), having re-established a viable reproductive wolf population (Marucco & Avanzinelli, 2018). In the last years, several tens of wolves are annually roadkilled in this area and the surrounding valleys. ...
Predation risk largely constrains prey behavior. However, whether predators may be scary also after death remains unexplored. Here, we describe the "fight-and-flight" responses of a prey, the wild boar (Sus scrofa), to carcasses of (a) its main predator, the gray wolf (Canis lupus) and (b) a carnivore that very rarely kills wild boars, the red fox (Vulpes vulpes), in the western Alps (Italy). We recorded the behavior of wild boars at 10 wolf and 9 fox carcass sites. We found eight "fight-and-flight" responses toward wolf carcasses, and none toward fox carcasses. Our results suggest that carnivore carcasses may indeed be scary; fear responses toward them are dependent on the species to which the carcass belongs; and animals approaching the carcasses are feared mainly when the latter are relatively fresh. This emphasizes the multiple and complex roles that carrion plays in the landscape of fear and opens exciting ecological, epidemiological, and evolutionary research avenues.
... Italian wolves were nearly extinct in the late 1940s, surviving at their historical minimum population size as two isolated populations in the Southern Apennines (Boitani, 1992). However, since the late eighties, conservation policies, and the increase in the number of wild ungulates, the main wolf prey, have ensured their natural re-expansion from the Southern Apennines toward the Northwestern Apennines and French Alps (Marucco and McIntire, 2010). ...
Tapeworms are trophically-transmitted and multi-host parasites with a complex indirect life cycle, strictly depending on predator-prey interactions. Their presence in a free-living population, mainly definitive hosts, is arduous to study due to the complexity of collecting fecal samples. However, epidemiological studies on their frequency are crucial from a public health perspective, providing information on food habits and prey selection of predators. The present study aims to update the frequency of tapeworms detected in stool samples by molecular analysis in Italian wolf populations of Umbria and Marche regions collected from 2014 to 2022. Tapeworm's total frequency was 43.2%. In detail, Taenia serialis was detected in 27 samples (21.6%), T. hydatigena in 22 (17.6%), and Mesocestoides corti (syn. M. vogae) in 2 (1.6%). Three samples were identified as M. litteratus and E. granulosus s.s. (G3) and T. pisiformis, with a proportion of 0.8%, respectively. The low frequency of E. granulosus in a hyperendemic area is discussed. The results show for the first time a high frequency of Taenia serialis not comparable to other Italian studies conducted on wild Carnivora; thus, a new ecological niche is conceivable. These findings suggest a plausible wolf-roe deer cycle for T. serialisin the investigated area.
... Italian wolves were nearly extinct in the late 1940s, surviving at their historical minimum population size as two isolated populations in the Southern Apennines (Boitani, 1992). However, since the late eighties, conservation policies, and the increase in the number of wild ungulates, the main wolf prey, have ensured their natural re-expansion from the Southern Apennines toward the Northwestern Apennines and French Alps (Marucco and McIntire, 2010). ...
Tapeworms are trophically-transmitted and multi-host parasites with a complex indirect life cycle, strictly depending on predator-prey interactions. Their presence in a free-living population, mainly definitive hosts, is arduous to study due to the complexity of collecting fecal samples. However, epidemiological studies on their frequency are crucial from a public health perspective, providing information on food habits and prey selection of predators. The present study aims to update the frequency of tapeworms detected in stool samples by molecular analysis in Italian wolf populations of Umbria and Marche regions collected from 2014 to 2022. Tapeworm's total frequency was 43.2%. In detail, Taenia serialis was detected in 27 samples (21.6%), T. hydatigena in 22 (17.6%), and Mesocestoides corti (syn. M. vogae) in 2 (1.6%). Three samples were identified as M. litteratus and E. granulosus s.s. (G3) and T. pisiformis, with a proportion of 0.8%, respectively. The low frequency of E. granulosus in a hyperendemic area is discussed. The results show for the first time a high frequency of Taenia serialis not comparable to other Italian studies conducted on wild Carnivora; thus, a new ecological niche is conceivable. These findings suggest a plausible wolf-roe deer cycle for T. serialis in the investigated area.
... Growth in human populations and development over the last half century, as well as increases in some generalist wildlife populations, have increased interactions between humans and wildlife [1][2][3][4]. Certain wildlife species have been able to adapt to newly human-dominated landscapes where they use anthropogenic food sources (e.g., garbage, pet food, crops, livestock, wildlife feeders [5]) and share space with humans [6][7][8]. For example, bears (Ursus spp.) often traverse human-dominated landscapes and can exploit human resources [9][10][11][12], but they typically avoid areas with more human development [13] that they likely perceive as risky [14]. ...
Increasing human–bear conflicts are a growing concern, and managers often assume bears in developed areas are food-conditioned. We examined the relationship between human–bear conflicts and food conditioning by analyzing isotopic values of hair from black bears (Ursus americanus floridanus) involved in research (n = 34) and conflicts (n = 45). We separated research bears into wild and developed subgroups based on the impervious surface within their home ranges and separated conflict bears based on observations of human food consumption (anthropogenic = observations; management = no observations). We initially assumed wild bears were not food conditioned and anthropogenic bears were. However, using isotopic values, we classified 79% of anthropogenic bears and 8% of wild bears as food conditioned. Next, we assigned these bears to the appropriate food conditioned category and used the categorizations as a training set to classify developed and management bears. We estimated that 53% of management bears and 20% of developed bears were food conditioned. Only 60% of bears captured within or using developed areas showed evidence of food conditioning. We also found that δ13C values were a better predictor of anthropogenic foods in a bear’s diet than δ15N values. Our results indicate that bears in developed areas are not necessarily food conditioned and caution against management actions based on limited observations of bear behavior.
... Predation-risk models have long been useful statistical tools for examining predator-prey interactions (e.g., Brown, 1988;Hebblewhite & Merrill, 2007;Werner et al., 1983). Subsequent applications of these models have broadened their scope to include predicting risks of livestock-carnivore encounters (Marucco & McIntire, 2010;Miller et al., 2015;Treves et al., 2004). Predationrisk models can identify locations of high conflict risk, thus informing effective management of potentially dangerous wildlife (Almuna et al., 2020). ...
Human–wildlife interactions can have negative consequences when they involve large carnivores. Spatial risk modelling could serve as a useful management approach for predicting and pre‐emptively mitigating negative interactions. We present a mechanistic modelling framework and examine interactions between humans and sloth bears ( Melursus ursinus ) in a multi‐use forest landscape of central India. We first assessed patterns and determinants of bear distribution across the landscape using indirect sign surveys. At the same spatial scale, we then estimated spatial probabilities of bear attacks on people using information from 675 interviews with local residents, incorporating estimates of distribution probabilities from the previous step. We found the average occupancy probability across 128 grid‐cells to be 0.77 (SE = 0.03). Bear occupancy was influenced by terrain ruggedness, forest composition and configuration, vegetation productivity and size of human settlements. The average probability of a bear attack in any given grid‐cell was 0.61 (SE = 0.03), mostly determined by bear occurrence patterns, forest cover, terrain ruggedness, and size of human settlements. Using spatial information on people's dependence on forest resources, we identified locations with the highest risk of bear attacks. Our study demonstrates that human attacks by bears—generally believed to be random or incidental—in fact showed deterministic patterns. Our framework can be applied to other scenarios involving human–wildlife conflicts. Based on our findings, we propose that a proactive co‐management approach which involves collaboration between wildlife managers and local residents could help better manage human–bear conflicts in central India and elsewhere across the species' range.
... In contrast, both W2358F and W2606 dispersed shortly after the release and then settled in an area located further away (>50 km) from the release site. The net dispersal distance observed for the three wolves, which essentially resulted in the observed cumulative net displacement, was comparable to the dispersal distances observed for wolves in Southern Europe ( [30,32,33,43,[73][74][75]; but see [31]), while it was noticeably lower than dispersal distances observed in Northern Europe [15], Asia [76,77], and North America [15]. We can hypothesize that the lower values of dispersal distances observed for the monitored wolves could be attributed to the high degree of habitat fragmentation and urbanisation of the areas they crossed; highly modified landscapes are known to shorten dispersal distances due to their low permeability to wolves' movements [33]. ...
Assessing the behavioural responses of floating wolves to human presence is crucial for investigating the chance of wolf populations expanding into urbanised landscapes. We studied the movement ecology of three rehabilitated wolves in a highly human-dominated landscape (Po Plain, Italy) to explore wolf’s plasticity amid widespread human pressure. To reach this aim, we estimated individual 95% utilisation distributions (UD) after the release and inspected both 95% UDs and net squared displacements to identify individual movement patterns; tested for differences in movement patterns during day and night; and analysed the selection of resting sites during dispersal movement in a highly human-altered environment. Both the 95% UDs and step lengths were smaller for wolves settling in suitable areas than for those settling in more urbanised areas. All wolves exhibited strong temporal segregation with humans during all movement phases, particularly while dispersing across highly urbanised areas. Main roads and proximity to built-up areas were shown to limit wolves’ dispersal, whereas small-wooded patches that provide shelter during rest facilitated long-distance movements. This study provides important insights into wolf movement and settling in urban and peri-urban areas, providing critical knowledge to promote human–carnivore coexistence.
... However, populations of some mammal species have recovered from the brink of extinction and recolonized parts of their former range, such as the giant panda (Ailuropoda melanoleuca) in China , bison (Bison bison) in the United States (Meagher, 1989) and European bison (Bison bonasus) in Poland (Kowalczyk et al., 2013). The recolonization of these endangered species often brings new challenges to society, such as increased human-wildlife conflicts (Marucco and McIntire, 2010). Therefore, understanding the causes and mechanisms of population expansion of endangered species is crucial for making a better conservation strategy. ...
Recently, the northward movement of Asian elephants (Elephas maximus) in Yunnan, China, has attracted international attention. Climate change or human disturbances have been proposed to be the key drivers, but these hypotheses have not been rigorously tested. In this study, we quantified the relationship between climate change and human impacts on the recent range expansion of Asian elephants in southwest China. We found that the first observation probability of this species in a new place during 1959–2021 had a significant and positive association with change in air temperature and human density, resulting in a movement toward a high-latitude region with a warmer climate and higher human density; however, its association with precipitation was scale-dependent in time: positive or negative during the past 10 or 5 years, respectively. Under the enforced protection policy, human-dominated areas became preferred habitats for elephants. Our results indicate that climate change and enforced protection efforts in human-dominated landscapes in the last few decades are significant drivers of the recent range expansion of Asian elephants in Yunnan, China. It is necessary to expand the current protected areas or habitat corridors toward the north or set up new reserves in the north and set up barriers between human settlements and elephant habitats to facilitate elephant movements and minimize human-elephant conflicts under accelerated global change.
... Page 2 of 10 increased when wolf populations have started to expand (Treves et al. 2002, Marucco and McIntire 2010, Marucco and Boitani 2012. ...
Gray wolf Canis lupus predation on domestic dogs Canis familiaris is a considerable wolf–human conflict issue in several regions of Europe and North America but it has not been well documented in the scientific literature. Livestock depredations by wolves may be related to the abundance of wild prey. Regardless of the presumed motivations of wolves for attacking dogs (likely due to interference competition and predation), the abundance of wild prey populations may also influence the risk of wolf attacks on dogs. We examined whether the annual number of fatal attacks by wolves on dogs was related to the abundance of primary prey, including wild boar Sus scrofa and roe deer Capreolus capreolus in Estonia, as well as the abundance of moose Alces alces in Finland. Statistical models resulted in significant negative relationships, thus providing evidence that the risk of attacks in both house yards (Estonia) and hunting situations (Finland) was highest when the density of wild prey was low. Wild ungulates cause damage to agriculture and forestry, but they seem to mitigate conflicts between wolves and humans; therefore, it is necessary to develop a holistic, multispecies management approach in which the importance of wild ungulates for large carnivore conservation is addressed.
... For instance, during the 1970s, the Apennine wolf (Canis lupus italicus) experienced its historical minimum population size, fragmented in two areas in the Southern Apennines [167,178]. Since the late 1980s, thanks to increased efforts to protect large carnivores undertaken on most continents, including Italy [179][180][181][182][183], the wolf is gradually recolonising some territories of the Apennines [184][185][186][187]. In particular, in the Cilento, Vallo di Diano e Alburni National Park (Southern Italy), the widest protected area in Italy, the wolf population, estimated at four individuals in 1975 [178], is naturally expanding at a fast pace with a population currently estimated at many dozens of specimens [53]. ...
The recent and ever-growing problem of boar (Sus scrofa forms including wild boar, hybrid and feral pig) expansion is a very complex issue in wildlife management. The damages caused to biodiversity and the economies are addressed in different ways by the various countries, but research is needed to shed light on the causal factors of this emergency before defining a useful collaborative management policy. In this review, we screened more than 280 references published between 1975-2022, identifying and dealing with five hot factors (climate change, human induced habitat modifications, predator regulation on the prey, hybridization with domestic forms, and transfaunation) that could account for the boar expansion and its niche invasion. We also discuss some issues arising from this boar emergency, such as epizootic and zoonotic diseases or the depression of biodiversity. Finally, we provide new insights for the research and the development of management policies.
... We investigated resource selection of wolf reproductive sites at Johnson (1980) 3rd order of selection using Conditional Matched Case Control 1:1 Logistic Regression (Duchesne et al., 2010). We compared RS used by each wolf pack to random sites available within each pack territory with a 3000 m buffer (mean areas of 278.3 ± 107.6 km2), considering average territory sizes in the Alps (Marucco & McIntire, 2010). We applied a first level neighborhood (3x3) to RS used respect to sampling unit (grid cell of 100 m) considering that pups movements in early summer are usually<500 m from RS (Packard, 2003). ...
Ecological knowledge is considered an important factor in environmental policy-making. However, the opportunity for ecologists to influence policy can often occur within discrete time policy windows, and seizing these opportunities has been heavily emphasized as a recent global conservation need. In 2017 the Natura 2000 Conservation Measures have been finalized in Italy, and delineated the management policy and institutional responsibilities of Natura 2000 Sites, after obligations of the EU Habitat Directive. In this timeframe, we developed a multi-scalar hierarchical habitat selection model for wolf reproductive-sites to identify potentially favorable habitat for wolf reproduction in the western Italian Alps, based on 19 years of data. This habitat suitability model was useful for the definition of species conservation requirements within the Natura 2000 Sites, and has been adopted in legislation processes, representing a successful example of ecological modelling fitting into a relevant policy window and informing legal instruments to achieve nature conservation goals.
... Therefore, it is theoretically possible to design and parameterize spatially explicit models to identify and predict conflict hotspots where carnivores kill livestock. Such risk maps could be instrumental for spatial prioritization of interventions to reduce livestock depredation by large carnivores and human retaliation on large carnivores (Stahl et al. 2002;Treves et al. 2004Treves et al. , 2011Marucco and McIntire 2010). ...
How can humans and wildlife coexist? In the new book "Tarangire: Human-Wildlife Coexistence in a Fragmented Ecosystem", published @SpringerNature, we synthesize interdisciplinary research, highlight challenges & propose solutions that work for humans and wildlife.
... Therefore, it is theoretically possible to design and parameterize spatially explicit models to identify and predict conflict hotspots where carnivores kill livestock. Such risk maps could be instrumental for spatial prioritization of interventions to reduce livestock depredation by large carnivores and human retaliation on large carnivores (Stahl et al. 2002;Treves et al. 2004Treves et al. , 2011Marucco and McIntire 2010). ...
We synthesize data on the ecology of large carnivores in the Tarangire Ecosystem (TE). Despite anthropogenic pressures, all large carnivore species (lions Panthera leo, spotted hyena Crocuta crocuta, striped hyena Hyena hyena, leopard Panthera pardus, cheetah Acinonyx jubatus, and wild dog Lycaon pictus) have persisted in this fragmented ecosystem consisting of multiple protected areas among a matrix of village lands. The focal species were widely distributed across land-use gradients. While the comparatively abundant spotted hyena permanently occupied village lands, other species only sporadically used these human-dominated areas. Across species, carnivores used village lands more frequently during the rainy season, possibly following seasonal shifts in the movement of prey species. These processes can increase human-carnivore interactions, expanding the potential for conflict. In some areas, leopards, lions, and striped hyenas reached high densities, whereas cheetahs and wild dogs occurred patchily and at low densities. Our review suggests that the existence of diverse protected areas contribute to the persistence of the large carnivore community. The persistence of lions, cheetahs, and wild dogs appears dependent on human-induced mortality and prey depletion. Conserving large carnivores in TE requires the application of interventions that reduce human-induced mortality while simultaneously conserving the spatio-temporal distributions of prey species.
... Therefore, it is theoretically possible to design and parameterize spatially explicit models to identify and predict conflict hotspots where carnivores kill livestock. Such risk maps could be instrumental for spatial prioritization of interventions to reduce livestock depredation by large carnivores and human retaliation on large carnivores (Stahl et al. 2002;Treves et al. 2004Treves et al. , 2011Marucco and McIntire 2010). ...
Facilitating coexistence between humans and large carnivores is one of the most complex and pressing conservation issues globally. Large carnivores pose threats to human security and private property, and people may respond to those risks with retaliation which can jeopardize the persistence of carnivore populations. The nature of these interactions can be influenced by several variables including ecological, anthropogenic as well as political dimensions. The Tarangire Ecosystem (TE) of northern Tanzania is a stronghold for multiple large carnivore species. Despite multi-faceted and long-term carnivore conservation efforts being implemented in the ecosystem, the anthropogenic impacts on carnivore populations are pervasive. As only a portion of the TE is fully protected, the wide-ranging nature of carnivores brings them into close contact with people living among a matrix of village lands. Consequently, this ecosystem experiences high levels of human-carnivore conflicts. In this chapter, we synthesize the existing information to characterize the extent, impacts, and spatiotemporal patterns of human-carnivore interactions (which often result in severe conflicts, causing harm to people, livestock, and carnivores), examine the efficacy and challenges of implementing interventions designed to reduce human-carnivore conflict, and explore the socio-economic dimensions of these mitigation efforts.
... Therefore, it is theoretically possible to design and parameterize spatially explicit models to identify and predict conflict hotspots where carnivores kill livestock. Such risk maps could be instrumental for spatial prioritization of interventions to reduce livestock depredation by large carnivores and human retaliation on large carnivores (Stahl et al. 2002;Treves et al. 2004Treves et al. , 2011Marucco and McIntire 2010). ...
In the Tarangire Ecosystem, elephants frequently use pastoral areas, where they interact with people and livestock. To characterize the elephant-livestock interface in Manyara Ranch, we used a social-ecological approach to capture the herders’ and the elephants’ perspectives of these interactions. We interviewed cattle herders to assess their perceptions of elephants relative to other wildlife species (n = 117 interviews) and observed how elephants responded to sound playbacks associated with humans and cattle relative to sounds of wildlife species (n = 300 playbacks). Most herders (86%) supported elephant conservation, and reported spatial avoidance of elephants as the main strategy to avoid negative interactions. Among eleven large mammal wildlife species, herders ranked elephants as the fifth most problematic species to cattle. Elephants frequently reacted (e.g., bunching, fleeing, shaking the head and moving the trunk, or approaching) to human-related sound playbacks (79% of playbacks), and reacted less frequently when exposed to sounds of cattle (62%) or wildlife (34%). Playback experiments suggested that while elephants primarily reacted non-aggressively when faced with livestock, aggressive elephant behavior may be triggered by human behavior. Evidence from both the interview data and the behavioral experiments suggest that coexistence between elephants and pastoralists is mostly facilitated by mutual spatial avoidance.
... Twelve publications studied Italian and Tanzanian cases(Figure 2.4). In Italy, six studies concerned wolf depredation on livestock(Ciucci et al., 2018;Dondina et al., 2015;Marucco & McIntire, 2010; Milanesi et al., 2019Milanesi et al., , 2015Zingaro and Boitani, 2017), while the other six were on wild pig (Sus scrofa) depredation on crop(Amici et al., 2012;Cappa et al., 2019;Cerri et al., 2017;Ficetola et al., 2014;Greco et al., 2021;Lombardini et al., 2016). In Tanzania, the emblematic case of elephant (Loxodonta africana) depredation on crops was investigated in three publications(Denninger Snyder et al., 2021;Kiffner et al., 2021;Scheijen et al., 2019), while big cat depredation on livestock was investigated in four publications ...
Les espèces qui se nourrissent de plantes ou d’animaux élevés ou capturés par l’homme, un comportement appelé « déprédation », entraînent souvent de graves Conflits Homme-Faune sauvage (CHF). La déprédation a été signalée dans le monde entier et, dans les écosystèmes marins, elle a été développée par de nombreux grands prédateurs se nourrissant des prises de pêche, ce qui a un impact à la fois sur les activités de pêche et les interactions écologiques. Cependant, bien que les approches écosystémiques soient de plus en plus utilisées dans la gestion des pêches, les effets de la déprédation sur l’ensemble de l’écosystème sont encore rarement considérés de manière holistique. Par conséquent, cette thèse a (i) identifié les limites, manques et priorités pour le développement d’approches de modélisation intégrant la déprédation et (ii) évalué la capacité de deux approches de modélisation existantes pour caractériser les conséquences de la déprédation marine et, plus spécifiquement, comprendre les enjeux et conditions requises pour que les activités d’exploitation halieutique et les déprédateurs marins puissent co-exister. Cette thèse est composée de cinq chapitres. Le chapitre 1 présente le contexte dans lequel s’inscrit ces travaux. Le chapitre 2 identifie les principales lacunes dans les connaissances et met en évidence les principales orientations futures pour parvenir à une inclusion efficace de la déprédation dans les études de modélisation en réalisant une revue systématique. Le chapitre 3 utilise le cadre Ecopath pour évaluer les effets de la déprédation sur l'écosystème dans une étude de cas bien documentée impliquant des mammifères marins et une pêcherie commerciale. Le chapitre 4 s'appuie sur une modélisation qualitative pour évaluer les conditions de persistance d'une ressource exploitée, d'une pêcherie et d'une espèce déprédatrice dans les systèmes marins touchés par la déprédation, et la façon dont la déprédation marine affecte les réponses à long terme à des scénarios alternatifs. Enfin, la discussion générale présentée dans le chapitre 5, fournit des recommandations qui vise à mieux comprendre et prévoir les effets de la déprédation au niveau du socio-écosystème.
... Nevertheless, there is paucity of studies integrating the available information to show where it converges and to provide a better understanding of the mechanisms behind the dispersal process. The applicability of a more integrated understanding ranges from projecting the dynamics of wolf populations under different natural and human conditions, including shifts in distribution ranges and connectivity between subpopulations, to locating areas with high livestock depredation risk (Marucco & McIntire, 2010). ...
Dispersal is a key demographic process involving three stages: emigration, transience and settlement; each of which is influenced by individual, social and environmental determinants. An integrated understanding of species dispersal is essential for demographic modelling and conservation planning. Here, we review the dispersal patterns and determinants documented in the scientific literature for the grey wolf (Canis lupus) across its distribution range. We showed a surprisingly high variability within and among study areas on all dispersal parameters – dispersal rate, direction, distance, duration and success. We found that such large variability is due to multiple individual, social and environmental determinants, but also due to previously overlooked methodological research issues. We revealed a potential non-linear relationship between dispersal rate and population density, with dispersal rate higher at both ends of the gradient of population density. We found that human-caused mortality reduces distance, duration and success of dispersal events. Furthermore, dispersers avoid interaction with humans, and highly exposed areas like agricultural lands hamper population connectivity in many cases. We identified numerous methodological research problems that make it difficult to obtain robust estimates of dispersal parameters and robust inferences on dispersal patterns and their determinants. In particular, analyses where confounding factors were not accounted for led to substantial knowledge gaps on all aspects of dispersal in an otherwise much-studied species. Our understanding of wolf biology and management would significantly benefit if wolf dispersal studies reported the results and possible factors affecting wolf dispersal more transparently.
... The high mortality rate during roads crossing indirectly affect the success of dispersion (F. Marucco & McIntire, 2010) even though at the local level these dynamics are not representing an important threat to wolf expansion, as confirmed by the constant increase and expansion of wolf packs reported in the latest provincial report on large carnivores for 2020. In Trentino-Alto Adige (hereafter TAA), possible threats of this kind for wolf conservation may be represented by the ecological barrier of the Val d'Adige, where two busy motorways and Brennero railway run in parallel with the Adige River. ...
The Eastern Alps, and in particular Trentino-Alto Adige and Veneto regions, have undergone a rapid recolonization by wolves. In less than a decade the area saw an increase in the number of packs, from one pack in 2013 to 20-25 packs in 2019. Such comeback has implied relevant consequences especially on livestock breeders’ activities, which have experienced an increase in predations by wolves. The combination of this fast recolonization process, the unreadiness of the local people and management authorities to this new and impacting presence, and the general lack of knowledge on this species has led to a significant intensification of the attention given to the wolf by the local media. In addition, the well-known political impact of the species has further contributed to exacerbating social conflicts and polarizing the debate regarding wolves. As previous studies have demonstrated, public opinion on a given issue is highly influenced by how the media decide to frame and present it, and media framing of a given issue is in turn highly influenced by the main political forces acting at the local scale. Based on these assumption, it has been conducted a content analysis of printed and online newspaper articles published between 2019 and 2020 in these two Italian regions. Specifically, it has been assessed how the wolf is framed by the local media and what the main themes and topics presented are. In particular, were analyzed the main news elements, which are the ones that have the highest impact on the reader, that is the title, subtitle and images. Successively, it has been given a score to each element based on the attitude towards wolves, with three possible scores: positive, neutral and negative. Further detailed information from each news, such as the main topic of the news and other mentioned topics, have been collected within a database. Moreover, it has been assessed the presence and prevalence of beliefs, judgements and misconceptions about wolves. The information extracted allowed to make comparisons about the type of media framing between the two regions (Veneto and Trentino-Alto Adige) and also between the Provinces of Trento and Bolzano, as well as between Italian and German language newspapers in Alto Adige. This study provides a further comparison based on media framing among different newspapers. Results eventually offered an overview of the current media framing situation on the wolf in the area, and highlighted possible opportunities to improve connections and information sharing between wolf experts and journalists to promote a more objective and correct information on the Large Carnivore.
... oystercatchers Haematopus ostralegus, UK [54], skylarks Alauda arvensis in Denmark [55] and river salmonids in California, USA [56], sometimes across thousands of kilometres squared, e.g. grey wolves Canis lupus in the Italian alps [57], African elephants Loxodonta africana in the Kenya-Tanzania border [58] and tigers Panthera tigris in Nepal's Chitwan National Park [59]. ...
Harmonious coexistence between humans, other animals and ecosystem services they support is a complex issue, typically impacted by landscape change, which affects animal distribution and abundance. In the last 30 years, afforestation on grasslands across Great Britain has been increasing, motivated by socio-economic reasons and climate change mitigation. Beyond expected benefits, an obvious question is what are the consequences for wider biodiversity of this scale of landscape change. Here, we explore the impact of such change on the expanding population of common buzzards Buteo buteo , a raptor with a history of human-induced setbacks. Using Resource-Area-Dependence Analysis (RADA), with which we estimated individuals' resource needs using 10-day radio-tracking sessions and the 1990s Land Cover Map of GB, and agent-based modelling, we predict that buzzards in our study area in lowland UK had fully recovered (to 2.2 ind km ⁻² ) by 1995. We also anticipate that the conversion of 30%, 60% and 90% of economically viable meadow into woodland would reduce buzzard abundance nonlinearly by 15%, 38% and 74%, respectively. The same approach used here could allow for cost-effective anticipation of other animals' population patterns in changing landscapes, thus helping to harmonize economy, landscape change and biodiversity.
... (Marucco et al., 2009;Marucco and McIntire, 2010 in which hybridization has not been detected yet(Fabbri et al., 2007). The details about model parametrization are shown in Appendix B.We modeled hybridization at the level of the formation of the reproductive pairs. ...
Hybridization is the interbreeding of individuals from distinct populations. Anthropogenic hybridization is a significant threat that can cause species’ extinction. It is therefore fundamental to assess this threat and evaluate the effectiveness of management actions in an adaptive management loop. We developed demographic estimation and projection models to answer to these questions and showed their application.In the first chapter we: 1) developed a model to estimate prevalence in free‐ranging populations 2) carried out a simulation study to i) evaluate model performance, ii) compare it to naive quantifications of prevalence and iii) assess the accuracy of model-based estimates of prevalence under different sampling scenarios. The main results from this chapter were that i) the prevalence of hybrids could be estimated ii) model‐based prevalence consistently had better performance than naive prevalence in the presence of differential detectability and assignment probability and was unbiased for sampling scenarios with high detectability. Our results underline the importance of a model‐based approach to obtain unbiased estimates of prevalence of different population segments.In the second chapter we adopted targeted non-invasive genetic sampling and the capture-recapture estimation model developed in Chapter 1 to estimate the prevalence of wolf-dog hybrids in a local, protected wolf population in the northern Apennines, Italy. We discuss the results in the light of previous assessment of prevalence of wolf x dog admixed individuals in Western Europe and we illustrate the implications of the results for wolf conservation and for the management of wolf x dog hybridization in human-dominated landscapes. In particular, we estimated 64-78% recent hybrids occurring in 6 out of the 7 surveyed packs. Our findings underline that in human-modified landscapes wolf-dog hybridization may raise to unexpected levels if left unmanaged, and that reproductive barriers or dilution of dog genes through backcrossing should not be expected, per se, to prevent occurrence and the spread of introgression.In the third chapter we present a new matrix population model to project population dynamics of animal populations in presence of hybridization. We apply the model to two real-world case studies of terrestrial (wolf x dog) and marine mammal species (common dolphin Delphinus delphis x striped dolphin Stenella coeruleoalba). Our projections highlighted that i) hybridization leads to genomic extinction in the absence of reproductive isolation, ii) rare or depleted species are particularly vulnerable to genomic extinction, iii) genomic extinction depends mainly on demographic parameters of parental species, iiii) maintaining healthy and abundant populations prevents genomic extinction.In the fourth chapter we built an individual based model describing the life cycle of the gray wolf by contemplating social dynamics traits linked to hybridization rates. We applied this model to investigate the hybridization dynamics of wolves in a study population the Northern Apennines, Italy, in order to evaluate the effectiveness of different management scenarios aimed to reduce the abundance of admixed individuals during a ten-generation time. We showed that in presence of continuative immigration of admixed individuals any management action proved ineffective. In presence of immigration by pure wolves all management actions produced a decrease in prevalence, although their relative effectiveness changed depending on the mating choice scenario. In all the simulated scenarios, the impact of hybridization is predicted to extend at broad scales as large numbers of admixed dispersers are produced. Moreover, we identified demographic and social processes that need to be further investigated to more accurately project the outcomes of management alternatives.
... The number of packs in Lithuania, which is estimated to be 100, suggests a likelihood of territorial overlap, similar to that observed in Poland (Jędrzejewski et al. 2007). Such a situation may affect efforts to control wolf livestock depredation (Marucco and McIntire 2010). Lithuania has a unique opportunity for evaluating the consequences of increasing wolf-bag limits (nearly doubled in the hunting season 2018-2019) with establishment of a national program for continuous registration of wolf observations. ...
Context. In many countries, annual wolf surveys based on snow-track counts have become unreliable because of inconsistent snow coverage. We considered incidental observations by volunteers throughout the year as an alternative monitoring protocol. Aims. We recruited interested citizens throughout Lithuania, including hunters, foresters and farmers, to estimate wolf distribution, abundance, pack numbers and group size from 2015 to 2018. Methods. Observation-based records of wolves were collected using simple questionnaires that included time, location and method of observation (e.g. track, scat, vocalisation or prey-kill remains). We summarised 979 reports of 1938 observed wolves. Key results. Volunteer reports suggested an increase in wolf distribution and abundance from 2015 to 2018. The observed number of wolf packs was estimated to be at least 100 by 2018, pack size increased to 3.6, and the share of single wolves decreased from 56% in 2015 to 40% in 2018. Conclusions. We found that volunteer observations can provide useful information on wolf distribution, pack size and pack numbers. Our results support previous reports of expanding wolf populations in the Baltic region. Implications. Results of our citizen-science effort by Nature Research Centre and Lithuanian Hunters and Fishers Association have been accepted by the Ministry of Environment as a complement to other surveys in Lithuania and should aid in developing an informed wolf-management policy.
... The number of packs in Lithuania, which is estimated to be 100, suggests a likelihood of territorial overlap, similar to that observed in Poland (Jędrzejewski et al. 2007). Such a situation may affect efforts to control wolf livestock depredation (Marucco and McIntire 2010). Lithuania has a unique opportunity for evaluating the consequences of increasing wolf-bag limits (nearly doubled in the hunting season 2018-2019) with establishment of a national program for continuous registration of wolf observations. ...
Context. In many countries, annual wolf surveys based on snow-track counts have become unreliable because of inconsistent snow coverage. We considered incidental observations by volunteers throughout the year as an alternative monitoring protocol.
Aims. We recruited interested citizens throughout Lithuania, including hunters, foresters and farmers, to estimate wolf distribution, abundance, pack numbers and group size from 2015 to 2018.
Methods. Observation-based records of wolves were collected using simple questionnaires that included time, location and method of observation (e.g. track, scat, vocalisation or prey-kill remains). We summarised 979 reports of 1938 observed wolves.
Key results. Volunteer reports suggested an increase in wolf distribution and abundance from 2015 to 2018. The observed number of wolf packs was estimated to be at least 100 by 2018, pack size increased to 3.6, and the share of single wolves decreased from 56% in 2015 to 40% in 2018.
Conclusions. We found that volunteer observations can provide useful information on wolf distribution, pack size and pack numbers. Our results support previous reports of expanding wolf populations in the Baltic region.
Implications. Results of our citizen-science effort by Nature Research Centre and Lithuanian Hunters and Fishers Association have been accepted by the Ministry of Environment as a complement to other surveys in Lithuania and should aid in developing an informed wolf-management policy.
... The model makes the following assumptions (Marescot et al., 2012): 1) if subordinates survive (with survival rate Ss) one year in the natal pack they will then leave and become individuals in dispersal by their third year of age; 2) the subordinates never directly transition to being breeders; 3) individuals in dispersal can either die or survive (with survival rate Sd), and gain access to reproduction by establishing a new pack (with transition rate to the breeder stage Pes) or remain dispersers (1-Pes); 4) breeders never lose their status remaining in the breeder stage and surviving with survival rate Sa. To run the projections we used the demographic parameters that were estimated for the expanding wolf population in the Italian Alps (Marucco et al., 2009;Marucco and McIntire, 2010 in which hybridization has not been detected yet (Fabbri et al., 2007). The details about model parametrization are shown in Appendix B. ...
Hybridization affects the evolution and conservation status of species and populations. Because the dynamics of hybridization is driven by reproduction and survival of parental and admixed individuals, demographic modelling is a valuable tool to assess the effects of hybridization on population viability, e.g., under different management scenarios. While matrix models have been used to assess the long-term consequences of hybridization between crops and wild plants, to our knowledge they have not been developed for animal species. Here, we present a new matrix population model to project population dynamics in a system with two parental species or populations that interbreed. We consider the dynamics of males and females of the two parental groups as separate components, each described by species-specific vectors of initial abundance and projection matrices. Then we model hybridization as the production of hybrid fertile offspring due to the interaction of reproductive individuals of different parental species. Finally, we apply the model to two real-world case studies regarding a terrestrial and a marine mammal species in the presence of hybridization. Specifically, we investigate 1) the genomic extinction probability of two interbreeding dolphin species within a semi-enclosed gulf in Greece, under different hybrids’ fitness scenarios, 2) the possible outcomes of wolf x dog hybridization events for an expanding wolf population in Italy, under different reproductive isolation scenarios, 3) the sensitivity of the probability of genomic extinction to the main demographic parameters in the two case studies.
... These decrees and protection laws, joined with the human abandonment of high-altitude territories after the second World War (Cerea and Marcantoni 2016;Fondazione Montagne Italia 2017), contributed to the wolf's natural recolonization starting from the Apennines in central Italy and moving toward the south-western part of the Alps (Liguria and Piedmont regions at the border with France). Currently the wolf alpine population is moving to the eastern part of the Alps (year of first documented presence: 2003 in Lombardy, 2010 in Trentino-Alto Adige, and 2012 in Veneto) (Marucco et al. 2018), where they are coming in contact with the wolf population coming from the Dinaric mountains and the Carpathians (Ciucci et al. 2009;Marucco and Mcintire 2010). Wolves reappeared in South Tyrol (hereinafter ST) in 2010 after more than 100 years of absence (Stauder et al. 2019; Autonomous Province of Bolzano 2020). ...
This article provides a first investigation on the attitude of South Tyrolean residents (northern Italy) toward the return of the wolf in their province. Data were collected through an online questionnaire, which was available for 54,527 residents (≥ 18 years old) of South Tyrol with internet access and a Facebook® account and was shared on the institute’s homepage. In total, 1818 valid responses were collected in 2 months in 2018. Cluster analysis evidenced four homogenous groups of respondents characterized by the components of attitude, their district community, the wolf distribution in their area, belief factors, and the personal fear of wolves. The data analysis revealed differences and relations between the four clusters in the level of knowledge, experience with wolves, education level, and the expected impact on the tourist sector. The obtained results (1) evidence some key factors influencing the attitude of residents, (2) underline the importance of considering small spatial scale attitudinal differences, and (3) urge for an extended human dimension of wolf coexistence research to support local management strategies.
... This is mostly aggravated in areas where wild prey diversity and density is low a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 [6]. However, in the last decades, due to legal protection policies [4], natural recolonization [8] and wild ungulate increase [9], [10], wolf populations have recovered and are now expanding their ranges across some countries in Europe [1], [4], [5], [11]. ...
The Iberian wolf (Canis lupus signatus) is a top predator that inhabits the Iberian Peninsula. In Portugal, its numbers and distribution declined throughout the 20th century, due to human persecution, habitat degradation and prey decline, which have led to higher predation rates of livestock in the remaining packs. In Montesinho Natural Park (northeast Portugal), wild ungulate populations have been increasing in the last years, which may have led wolf to predate upon them. In order to assess Iberian wolf diet in this area, 85 wolf scats were collected from transects distributed throughout the study area in two periods between November 2017 and August 2019. Scat analysis indicated a high predation on wild ungulates, where the frequency of occurrence showed that roe deer was the most consumed prey (44%), followed by red deer (26%) and wild boar (24%). Domestic/wild cat (6%), domestic goat and stone marten (5%) were consumed in lower quantities. It was found a higher selection towards roe deer (D = 0.71) and this was the only prey item which was significantly dependent of the season of the year (χ² = 16.95, df = 3, p < 0.001). This is the first study in Portugal where was recorded that wolves feed mainly on wild ungulates. We conclude that lower livestock predation may be correlated with higher wild ungulates densities in our study area, as well as suitable husbandry practices, leading to a shift on Iberian wolf diet from mainly livestock on previous studies to wild ungulates.
... The outputs of these risk models are used to identify highpriority locations in which to apply conflict intervention or mitigation efforts around the world, thus informing preventative action to maximize impact and minimize cost (Marucco and Mcintire, 2010;Treves et al., 2011;Miller, 2015). Notably, the exact processes at play may differ depending on the ecological community, human culture, and environmental characteristics of the study location. ...
Carnivore depredation of livestock is a global problem which negatively impacts both agropastoral livelihoods and carnivore population viability. Given the gravity of this issue, research has increasingly focused on applied techniques capable of quantifying the factors that increase the risk of livestock depredation. One such technique is risk modeling. This multivariate approach is designed to produce predictions of the spatial configuration of depredation so as to prioritize interventionist activities. Thus, the efficacy of subsequent interventions is, in part, dependent upon the accuracy of the predictions deriving from the risk models. The predictability of spatial patterns in carnivore depredation of livestock is influenced by the degree of spatial autocorrelation evident in the data distributions. We conducted a multi-year assessment to quantify the degree of spatial autocorrelation within livestock depredation data. We centered our study in the Maasai steppe of Tanzania, which experiences some of the highest rates of human-carnivore conflict in the world. We applied three geostatistical measures to assess spatial clustering in data describing livestock depredation by lions (Panthera leo), leopards (Panthera pardus), spotted hyenas (Crocuta crocuta), black-backed jackals (Canis mesomelas), and cheetahs (Acinonyx jubatus) at the household (i.e., livestock enclosure) scale. Using an ordinal spatial scan statistic, a Bernoulli spatial scan statistic, and the Getis-Ord local spatial statistic, we found that the spatial patterns in carnivore depredation of livestock tended not to significantly differ from random. As the predictive ability of spatial risk models may be limited where spatial patterns of carnivore depredation of livestock do not statistically differ from random, explicitly assessing such patterns is an important component of conflict mitigation efforts. We discuss the inferences of this analysis for the optimization of interventionist activities intending to develop sustainable solutions for human-carnivore conflict.
... We suggest that the notion of problem carnivores in agropastoral landscapes in Africa requires additional investigation. We argue, for instance, that it is also possible that other fine-scale landscape and habitat variables may exist that would explain the spatial pattern of spotted hyena raids in bomas better than the variable tested in the current study (Porten et al., 2014), which thus invokes the possibility of considering further research on carnivore raids in bomas at a finer scale than the one we have completed (Marucco & McIntire, 2010;Montgomery et al., 2018;Treves, Martin, Wydeven, & Wieden-hoeft, 2011). ...
Human-carnivore conflicts and retaliatory killings contribute to carnivore popula-tions' declines around the world. Strategies to mitigate conflicts have been developed, but their efficacy is rarely assessed in a randomized case-control design. Further, the economic costs prevent the adoption and wide use of conflict mitigation strategies by pastoralists in rural Africa. We examined carnivore (African lion [Panthera leo], leopard [Panthera pardus], spotted hyena [Crocuta crocuta], jackal [Canis mesomelas], and cheetah [Acinonyx jubatus]) raids on fortified (n = 45, total 631 monthly visits) and unfortified (traditional, n = 45, total 521 monthly visits) livestock enclosures ("bomas") in northern Tanzania. The study aimed to (a) assess the extent of retaliatory killings of major carnivore species due to livestock depredation, (b) describe the spatiotem-poral characteristics of carnivore raids on livestock enclosures, (c) analyze whether spatial covariates influenced livestock depredation risk in livestock enclosures, and (d) examine the cost-effectiveness of livestock enclosure fortification. Results suggest that (a) majority of boma raids by carnivores were caused by spotted hyenas (nearly 90% of all raids), but retaliatory killings mainly targeted lions, (b) carnivore raid attempts were rare at individual households (0.081 raid attempts/month in fortified enclosures and 0.102 raid attempts/month in unfortified enclosures), and (c) spotted hyena raid attempts increased in the wet season compared with the dry season, and owners of fortified bomas reported less hyena raid attempts than owners of unforti-fied bomas. Landscape and habitat variables tested, did not strongly drive the spatial patterns of spotted hyena raids in livestock bomas. Carnivore raids varied randomly both spatially (village to village) and temporally (year to year). The cost-benefit analysis suggest that investing in boma fortification yielded positive net present values after two to three years. Thus, enclosure fortification is a cost-effective strategy to promote coexistence of carnivores and humans.
... Conflicts are dynamic -the landscape of risk can change over time (Olson et al., 2014) and that change can be instantaneous (e.g., decision to let a pet dog run loose in the core of a wolf pack territory). Thus, more meaningful evaluations of risk can be developed by 1) restricting analysis to areas of known co-occurrence (e.g., Olson et al., 2014), 2) incorporating spatial and non-spatial variables (e.g., Pimenta et al., 2018), 3) incorporating spatiotemporal data into risk models to account for dynamic patterns of human activities and predator populations in risk analysis (e.g., Marucco and McIntire, 2010;Olson et al., 2014), or 4) examining the landscape of risk as a surface of multiple, competing risks (this work). ...
Managing risks requires an adequate understanding of risk-factors that influence the likelihood of a particular event occurring in time and space. Risk maps can be valuable tools for natural resource managers, allowing them to better understand spatial characteristics of risk. Risk maps can also support risk-avoidance efforts by identifying which areas are relatively riskier than others. However, risks, such as human-carnivore conflict, can be diverse, multi-faceted, and overlapping in space. Yet, efforts to describe risk typically focus on only one aspect of risk. We examined wolf complaints investigated in Wisconsin, USA for the period of 1999 to 2011. We described the spatial patterns of four types of wolf-human conflict: livestock depredation, depredation on hunting hounds, depredation on non-hound dogs, and human health and safety concerns (HHSC). Using predictive landscape models and discriminant functions analysis, we visualized the landscape of risk as a continuous surface of overlapping risks. Each type of conflict had its own unique landscape signature; however, the probability of any type of conflict increased closer to the center of wolf pack territories and with increased forest cover. Hunting hound depredations tended to occur in areas considered to be highly suitable wolf habitat, while livestock depredations occurred more regularly in marginal wolf habitat. HHSC and non-hound dog depredations were less predictable spatially but tended to occur in areas with low housing density adjacent to large wildland areas. Similar to other research evaluating the risk of human-carnivore conflict, our data suggests that human-carnivore conflict is most likely to occur where humans or human property and large carnivores co-occur. However, identifying areas of co-occurrence is only marginally valuable from a conservation standpoint and could be described using spatially-explicit human and carnivore data without complex analytical approaches. These results challenge our traditional understanding of risk and the standard approach used in describing risk. We suggest that a more comprehensive understanding of the risk of human-carnivore conflict can be achieved by examining the spatial and non-spatial factors influencing risk within areas of co-occurrence and by describing the landscape of risk as a continuous surface of multiple overlapping risks.
The efficiency of the management of predations on livestock by gray wolves (Canis lupus) through culling is under debate. Evaluating wolf culling efficiency requires to simultaneously analyze the effects of culling on the wolf population and the repercussions of these population changes on livestock predation. This protocol is technically difficult to implement in the field. To properly assess culling efficiency, we provided an integrated and flexible individual‐based model that simulated interactions between wolf population dynamics, predation behavior and culling management. We considered many social processes in wolves. We calibrated the model to match the Western Alps as a case study. By considering the prey community in this area and the opportunistic nature of wolf predation, we assumed that predation on livestock at the wolf territory level increased with pack's food needs. Under this assumption and considering livestock availability as high and livestock vulnerability as uniform in space and time, culling maintained wolf population size and predation risks at low levels. Contrary to what was expected, culling decreased the mean annual proportions of dispersing wolves in our simulations, by speeding settlement. This population‐level mechanism compensated for the high mortality and the pack instability caused by culling. Compensation was however dependent on the selectivity and the timing of culling. When executed before the natural mortality module in our model, the selective culling could undermine replacement of lost breeders and therefore decrease wolf population resilience to culling. Our model gives insights about culling effects in one specific simulated context, but we do not expect that our assumption about predation behavior necessarily holds in other ecological contexts and we therefore encourage further explorations of the model.
Over the few past decades, many bird species have expanded their nesting ranges by adapting to degraded habitat. Conservation efforts have promoted the growth of populations of endangered species, and the ranges of several such species have expanded continuously. Understanding and predicting the effects of climate change on the nesting habitat ranges of endangered species can aid species recovery and habitat management. In this study, we used multi-scale data and geographic variables with a field survey of sites occurrence of Oriental Storks (Ciconia boyciana) to determine their nest selection patterns. We then simulated currently potential habitats and predicted spatio-temporal dynamics changes in their suitable nesting areas under future carbon emission scenarios in China. Our results show that Oriental Storks prefer nesting at low altitudes in flat areas near rivers. The Sanjiang Plain, the western part of Northeast China, Bohai Bay, and the middle and lower Yangtze River floodplain were the areas with potentially suitable nesting areas for Oriental Storks. We predicted that the nesting ranges of Oriental Storks will expand under two Representative Concentration Pathway scenarios (RCPs) in the future. However, under the most conservative (RCP2.6) and worst-case scenarios (RCP8.5), the rate of gain in suitable habitat will decrease, and the loss rate will increase. Change in the area of suitable nesting habitat varied among regions. The loss rate of suitable habitat in the middle and lower Yangtze River floodplain was predicted to decrease in the future, and the gain rate in the area of suitable habitat was predicted to be relatively stable and showed an increase. Some measures that could be taken to enhance the breeding habitat of Oriental Storks include identifying conservation gap areas and minimizing the loss rate of suitable habitat. Finally, scientific planning and management of potentially suitable habitats in protected areas and protected networks are needed to ensure the persistence of breeding Oriental Storks.
Understanding the causal factors associated with human/livestock-large carnivore conflict and distribution of conflict risk is key to designing effective preventative and mitigation strategies. Spatial modelling of human-carnivore conflict has recently gained traction, and predictive maps have become a great tool to understand the distribution of present and future conflict risk. However, very few such studies consider scale and use appropriate spatial modelling tools. We aimed to understand the ecological correlates of human-tiger (Panthera tigris) conflict, predict livestock predation risk by reintroduced tigers in Panna Tiger Reserve, Central India and understand the prey-predator dynamics behind the conflict. We modelled livestock kill as a function of various tiger relevant ecological variables at multiple scales employing spatially explicit statistical tools. As a first step, we used geostatistical modelling to create raster layers of covariates (prey, cover, human activities), following which we did univariate scaling. We then modelled livestock loss by tiger using a geoadditive model. Employing this model, we predicted and mapped conflict risk probabilities within our study site. It was found that prey and shrub cover both selected at a fine scale, were key ecological determinants of human-tiger conflict. Prey showed an inverse relationship while shrub showed non-linear relationship with livestock predation. Which lead us to conclude that in habitats where optimum ambush cover is available but prey presence is low at fine-scale, carnivores are more likely to depredate domestic livestock since livestock have lost most of their anti-predator behaviours. Livestock kill by tiger is thus a culmination of predator choice and foraging tactics, and prey vulnerability and defence mechanism. The spatially explicit predation risk map produced in this study can guide adequate human-tiger conflict prevention measures.
Conservation actions for endangered species often require detailed data over large temporal and spatial scales, which are usually hard to obtain from traditional scientific surveys that operate at localized scales. In contrast to the terrestrial conservation world where citizen science has become nowadays a highly relevant and useful tool to overcome such difficulties, Marine Citizen Science is still highly underrepresented. Using a dataset of 20 years of citizen science data and appropriate statistical modelling, we developed a methodological approach to monitor the presence of the endangered, notoriously elusive Mediterranean monk seal Monachus monachus . We used sighting data collected in Greece from 2000 to 2020 and fitted dynamic occupancy models that allow inferring range dynamics whilst accounting for species imperfect detectability to estimate species occupancy. The occurrence of Mediterranean monk seals of all age categories combined, and pups separately, increased during the study period. Mediterranean monk seal occurrence increased also spatially: the distribution of the species in Greece increased by approximately 12.5% for seals of all age categories and by approximately 185% for monk seal pups. Most of this distribution (i.e. 67 and 72% of the distribution of seals of all age categories and of pups, respectively) was located within the boundaries of the network of protected areas in the country. These results indicate a significant range recovery of the Mediterranean monk seal in Greece over the last two decades and facilitate the prioritization of conservation actions for the species in the country. We demonstrate how occupancy modelling and citizen science can be used to evaluate the distribution of an endangered species and become a highly relevant and reliable tool in marine mammal conservation. We advocate the increased use of citizen science in the conservation of the Mediterranean monk seal in the eastern Mediterranean Sea.
Context: Spatial modelling of human-carnivore conflict has recently gained traction, and predictive maps have become a great tool to understand the distribution of present and future conflict risk. However, very few such studies consider scale and use appropriate spatial modelling tools.
Objectives: We aimed to understand the ecological predictors of human-tiger (Panthera tigris) conflict and predict livestock predation risk by reintroduced tigers in Panna Tiger Reserve, Central India. By modelling livestock kill as a function of various tiger relevant ecological variables at multiple scales employing spatially explicit statistical tools.
Methods: We used geostatistical modelling to create raster layers of covariates (prey, cover, human activities), following which we did univariate scaling. We then modelled livestock loss by tiger using spatial Generalized Additive Model (geoGAM), predicted and mapped conflict risk probability.
Results: We found that prey and shrub cover, both selected at a fine scale, were key ecological determinants of human-tiger conflict. Prey showed an inverse relationship with livestock predation and shrub nonlinear; livestock predation increasing with an increase in shrub cover but decreasing beyond a certain point. Thus, in habitats where optimum ambush cover is available but prey presence is low at fine-scale, carnivores are more likely to depredate domestic livestock since livestock have lost most of their anti-predator behaviours.
Conclusions: Livestock kill by tiger is a culmination of predator choice and foraging tactics, and prey vulnerability and defence mechanism. The spatially explicit predation risk map produced in this study can guide adequate human-tiger conflict prevention measures.
Context
Spatial modeling of human-carnivore conflict has recently gained traction and predictive maps have become a great tool to understand the distribution of present and future conflict risk. However, very few such studies consider scale and use appropriate spatial modeling tools.
Objectives
This study aimed at understanding the ecological predictors of human-tiger conflict and predicting livestock predation risk by reintroduced tigers in Panna Tiger Reserve, Central India, by modelling livestock kill as a function of various tiger relevant ecological variables, at multiple scales employing spatially explicit statistical tools.
Methods
Geostatistical modeling was used to create raster layers of covariates (prey, cover, human activities) following which univariate scaling was done. Livestock loss by tiger was then modelled using geoGAM and spatially explicit conflict risk predicted.
Results
It was found that prey and shrub cover both selected at fine scale, were key ecological determinants of human-tiger conflict. Prey showed an inverse relationship with livestock predation and shrub non-linear, livestock predation increasing with increase in shrub cover, but decreasing beyond a certain point. Thus, in habitats where optimum ambush cover is available but prey presence is low at fine-scale, carnivores are more likely to depredate domestic livestock since livestock have lost most of their anti-predator behaviours.
Conclusions
Livestock kill by tiger is a culmination of predator choice and foraging tactics, and, prey vulnerability and defence mechanism. Thus, the spatially explicit predation risk map can provide a basis to guide adequate mitigation measures, as per the risk probability.
The Apennine wolf (Canis lupus italicus, Altobello, 1921) is currently experiencing a period of great population change. Any information that helps to understand this transformation will be valuable for managing it. Here we provide, for the first time, quantitative data (habitat suitability, segregation, seasonal activity, daily time budget, social structure and sex-ratio) on the population of Italian wolf from the Cilento, Vallo di Diano and Alburni National Park, the largest protected area in Italy, that houses a rising population. Using transects to locate signs and traces, we have identified 224 presence points, useful for elaborating the ecological suitability map for the wolf, in and around the Park. The suitable area expands up to 1042.65 km 2 , with elevation being the strongest predictive variable affecting the species. The model predicts two main suitable patches (Alburni Mountains and Cervati/Motola Mountains), and at least seven remote areas, differently linked to each other by ecological corridors. Camera-trapping information was collected in the two suitable patches (Alburni and Cervati/Motola) for the wolf and revealed some characteristics of this population. The highest number of wolves was recorded in May and December, and during the night, depending on the reproductive behavior and dynamic of dispersion. Single individuals and couples (at least 3 recorded) are observed more frequently than groups (maximum of 3 groups that varied from three to eight individuals). The sex-ratio in the population, inferred by camera-trapping, showed a balanced population, with males found to be group leader in 91% of the cases. Furthermore, genetic analysis revealed that the males were in charge of marking the territory in 86% of cases. Our data increases the knowledge of the wolf population from Cilento, which seemed to have stopped at the 1990s, until now. Our contribution could be helpful in defining a wolf management strategy in the National Park, as well as in the other regions of the Apennine mountains and Alps, where the wolf is expanding, aiming also at coexistence with local human communities.
While large carnivores are recovering in Europe, assessing their distributions can help to predict and mitigate conflicts with human activities. Because they are highly mobile, elusive and live at very low density, modeling their distributions presents several challenges due to i) their imperfect detectability, ii) their dynamic ranges over time and iii) their monitoring at large scales consisting mainly of opportunistic data without a formal measure of the sampling effort. Not accounting for these issues can lead to flawed inference about the distribution.
Here, we focused on the wolf ( Canis lupus ) that has been recolonizing France since the early 90’s. We evaluated the sampling effort a posteriori as the number of observers present per year in a cell based on their location and professional activities. We then assessed wolf range dynamics from 1993 to 2014, while accounting for species imperfect detection and time- and space-varying sampling effort using dynamic site-occupancy models.
Ignoring the effect of sampling effort on species detectability led to underestimating the number of occupied sites by 50% on average. Colonization increased with increasing number of occupied sites at short and long-distances, as well as with increasing forest cover, farmland cover and mean altitude. Colonization decreased when high-altitude increased. The growth rate, defined as the number of sites newly occupied in a given year divided by the number of occupied sites in the previous year, decreased over time, from over 100% in 1994 to 5% in 2014. This suggests that wolves are expanding in France but at a rate that is slowing down. Our work shows that opportunistic data can be analyzed with species distribution models that control for imperfect detection, pending a quantification of sampling effort. Our approach has the potential for being used by decision-makers to target sites where large carnivores are likely to occur and mitigate conflicts.
Species distribution models (SDMs) are important statistical tools for ecologists to understand and predict species range. However, standard SDMs do not explicitly incorporate dynamic processes like dispersal. This limitation may lead to bias in inference about species distribution. Here, we adopt the theory of ecological diffusion that has recently been introduced in statistical ecology to incorporate spatio-temporal processes in ecological models. As a case study, we considered the wolf (Canis lupus) that has been recolonizing Eastern France naturally through dispersal from the Apennines since the early 90’s. Using partial differential equations for modelling species diffusion and growth in a fragmented landscape, we develop a mechanistic-statistical spatio-temporal model accounting for ecological diffusion, logistic growth and imperfect species detection. We conduct a simulation study and show the ability of our model to i) estimate ecological parameters in various situations with contrasted species detection probability and number of surveyed sites and ii) forecast the distribution into the future. We found that the growth rate of the wolf population in France was explained by the proportion of forest cover, that diffusion was influenced by human density and that species detectability increased with increasing survey effort. Using the parameters estimated from the 2007-2015 period, we then forecasted wolf distribution in 2016 and found good agreement with the actual detections made that year. Our approach may be useful for managing species that interact with human activities to anticipate potential conflicts.
Wolves (Canis lupus) in Croatia are estimated at nearly 200 individuals and form part of the Dinaric-Balkan population. As in most of Europe, they are currently expanding in size and distribution. However, the wolf still faces threats that could hamper its viability. In Croatia, these threats include the worsening of public attitudes and the construction of wind power plants in their distribution range. In order to meet the 2020 European targets for renewable energy production, the Republic of Croatia is planning to build 33 wind farms, with a total installed capacity of 1,555 MW. However, in order to meet such targets, only 747.25 MW are necessary. In this study a suitability model for wolf breeding habitat was carried out using Maxent based on 6 environmental variables and 31 homesite locations collected between 1997 and 2015. The prediction of habitat suitability was then used to determine the potential impact of proposed wind farms on wolves. Lastly, a wind farm prioritisation process was carried out using the software Marxan. This allowed selecting the wind farms that contributed to the meeting of the energy targets at the minimum ecological impact on wolf breeding habitat. The model showed good performance (AUC=0.805) and its prediction was consistent with the current knowledge and distribution of wolves in Croatia. The main predictors for suitability were distance to settlements, distance to farmland, distance to roads and distance to forest edge. Moreover, Marxan allowed the selection of highly cost-efficient wind farms. In fact, in
the best scenario, selected wind farms were 44.5% of the total proposed wind farms and held only 23.3% of the total initial cost. In conclusion, this study provides valuable information and useful tools for the conservation of wolves in Croatia. In particular, the habitat suitability map can be used for the implementation of the wolf management plan, for the prevention of human-wildlife conflicts and for future conservation planning. Moreover, the result of the prioritisation will be used to inform the strategic planning of wind farms in Croatia. Lastly, the framework adopted in this study can be expanded to multiple infrastructure and multiple large carnivores’ species such as the Eurasian brown bear and the Eurasian lynx.
Managers trying to preserve populations of endangered carnivores are often forced to choose between
restoring habitat to allow larger breeding populations or reduce risks of mortality to increase survival
rates. We modelled the viability of a metapopulation of the Iberian lynx (Lynx pardinus) under several
scenarios (habitat restoration, anti-poaching, reduction in road kills) in a real landscape to evaluate
their relative effects. Increasing carrying capacity was highly effective when performed on the local
populations that acted as sources but had no effect when carried out in the sinks. Realistic scenarios
consisting of partial removal of the human-related mortality (assuming additive effects of causes) predicted
high risk of extinction. When combined, the effects of both management options are highly
dependent on where they are carried out. If the sinks are the only targets of carrying capacity enlargement,
a complete removal of human-caused mortality is required, whereas increases in the carrying
capacity of sources are always effective. The metapopulation risk of extinction decreases dramatically
(from 45.5% to 2.1% in 100) if connectivity among source populations can be improved. According
to our work, only a detailed knowledge of the spatial and demographic structure of the populations,
combined with simulations of realistic situations, can help managers to select the a priori optimal
strategy, which probably combines different management options.
In a recent analysis Woodroffe (2000) found a positive relationship between historical patterns of large carnivore extinction probability and human population density. However, much of the data in this analysis came from a period when carnivore extermination was a management objective. In order to explore the hypothesis that large carnivores can persist at high human densities when the management regime is more favourable we have repeated the analysis using up-to-date data from North America and Europe. In North America we found that large carnivore populations have increased after favourable legislation was introduced, despite further increases in human population density. In Europe we found no clear relationship between present carnivore distribution and human population density. We therefore believe that the existence of effective wildlife management structures is more important than human density per se.
We present a spatially explicit population model for analysing the expansion of brown bears (Ursus arctos) after the reintroduction program in central Austria. The model is based on field investigations into brown bears in Austria and Slovenia and on current knowledge of brown bears. The landscape of the eastern Alps is represented by a GIS-derived raster map defining local habitat suitability and five major spatial barriers to dispersal. The population model follows the fate of individual bears and simulates reproduction, dispersal, home range establishment, and mortality in annual time steps. We indirectly adjust unknown or uncertain model parameters with 10-year data on the number of females with cubs in central Austria and determine key variables of population dynamics, such as population sizes and growth rates within different population nuclei, dispersal distances, or mortality rates, for model parameterisations that reproduce the data on females with cubs. We estimated a current (1996–2000) growth rate of the population in Austria and adjacent parts of Italy of some 14%; a high proportion of this growth was due toimmigration from Slovenia. Consequently, the growth rate of the subpopulation in central Austria, which probably is isolated functionally (i.e., no exchange of females) from the nuclei along the Austrian–Slovenian border, yielded some 7%. This subpopulation may comprise seven residents, and we estimated for females a 33% risk of extinction during the 1992–2000 period. Validation and confirmation of our model results with data on bear densities that were not used for model construction and parameterisation supported our findings. The high female mortality rates, together with the vulnerability of the small population to chance events (i.e., demographic stochasticity), are the most pressing threat for the population in the eastern Alps. Our approach could be widely applied for analysing dynamics of rare and endangered species in which the paucity of data precludes an appraisal of the state of the population using standard methods.
Wolves (Canis lupus) have recently expanded their distribution range into western and southern Finland, which has not hosted breeding wolves
for over 100years. This has raised concerns and public debate over wolf-livestock conflicts. Between 1998 and 2004 there
were 45 wolf attacks on sheep on 34 farms. To assess the risk wolves may pose to sheep husbandry, we used data on depredation,
sheep management, landscape structure and moose and wolf populations from continental Finland outside the area of reindeer
husbandry to build models of the factors that may predispose sheep farms to wolf depredation. Our results provided evidence
that sheep farms with the highest risk of wolf depredation were those located in regions where wolves were abundant. These
farms were usually located close to the Russian border where the landscape is a mosaic of forest, wetlands and clear cut areas.
These regions are sparsely populated by humans and farms are located far from each other. Finally, we generated probability
maps based on generalised additive modelling to predict the risk of wolf predation on livestock in farms of southern Finland.
The growing awareness of the adverse effects of habitat fragmentation on natural systems has resulted in a rapidly increasing number of actions to reduce current fragmentation of natural systems as well as a growing demand for tools to predict and evaluate the effect of changes in the landscape on connectivity in the natural world. Recent studies used ‘least-cost’ modelling (available as a toolbox in GIS-systems) to calculate ‘effective distance’, a measure for distance modified with the cost to move between habitat patches based on detailed geographical information on the landscape as well as behavioural aspects of the organisms studied. We applied the method to a virtual landscape and a small scaled agricultural system subject to different scenarios in a land re-allotment project. We discuss the importance of technical aspects and ecological assumption underlying this modelling method. The model is shown to be a flexible tool to model functional connectivity in the study of the relation between landscape and mobility of organisms as well as in scenario building and evaluation in wild life protection projects and applied land management projects. Since ‘effective distance’ has the same units as Euclidean distance (m), this effective distance may be a straightforward way to include landscape and behavioural aspects in other models which include distance as a measure for isolation. We show the importance of the ‘ecological’ quality of the input maps and the choice of relevant landscape features and resistance values.
Over the past 15 years the endangered eastern timber wolf (Canis lupus lycaon) has been slowly recolonizing northern Wisconsin and, more recently, upper Michigan, largely by dispersing from Minnesota (where it is listed as threatened). We have used geographic information systems (GISs) and spatial radiocollar data on recolonizing wolves in northern Wisconsin to assess the importance of landscape-scale factors in defining favorable wolf habitat. We built a multiple logistic regression model applied to the northern Great Lakes states to estimate the amount and spatial distribution of favorable wolf habitat at the regional landscape scale. Our results suggest that areas with high probability of favorable habitat are more extensive than previously estimated in the northern Great Lake States. Several variables were significant in comparing new pack areas in Wisconsin to nonpack areas, including land ownership class, land cover type, road density, human population, and spatial landscape indices such as f
Wolves in Italy strongly declined in the past and were confined south of the Alps since the turn of the last century, reduced in the 1970s to approximately 100 individuals surviving in two fragmented subpopulations in the central-southern Apennines. The Italian wolves are presently expanding in the Apennines, and started to recolonize the western Alps in Italy, France and Switzerland about 16 years ago. In this study, we used a population genetic approach to elucidate some aspects of the wolf recolonization process. DNA extracted from 3068 tissue and scat samples collected in the Apennines (the source populations) and in the Alps (the colony), were genotyped at 12 microsatellite loci aiming to assess (i) the strength of the bottleneck and founder effects during the onset of colonization; (ii) the rates of gene flow between source and colony; and (iii) the minimum number of colonizers that are needed to explain the genetic variability observed in the colony. We identified a total of 435 distinct wolf genotypes, which showed that wolves in the Alps: (i) have significantly lower genetic diversity (heterozygosity, allelic richness, number of private alleles) than wolves in the Apennines; (ii) are genetically distinct using pairwise F(ST) values, population assignment test and Bayesian clustering; (iii) are not in genetic equilibrium (significant bottleneck test). Spatial autocorrelations are significant among samples separated up to c. 230 km, roughly correspondent to the apparent gap in permanent wolf presence between the Alps and north Apennines. The estimated number of first-generation migrants indicates that migration has been unidirectional and male-biased, from the Apennines to the Alps, and that wolves in southern Italy did not contribute to the Alpine population. These results suggest that: (i) the Alps were colonized by a few long-range migrating wolves originating in the north Apennine subpopulation; (ii) during the colonization process there has been a moderate bottleneck; and (iii) gene flow between sources and colonies was moderate (corresponding to 1.25-2.50 wolves per generation), despite high potential for dispersal. Bottleneck simulations showed that a total of c. 8-16 effective founders are needed to explain the genetic diversity observed in the Alps. Levels of genetic diversity in the expanding Alpine wolf population, and the permanence of genetic structuring, will depend on the future rates of gene flow among distinct wolf subpopulation fragments.
Spatial population dynamics of recolonizing wolves in the Western Alps
The fragmentation of populations is an increasingly important problem in the conservation of endangered species. Under these conditions, rare migration events may have important effects for the rescue of small and inbred populations. However, the relevance of such migration events to genetically depauperate natural populations is not supported by empirical data. We show here that the genetic diversity of the severely bottlenecked and geographically isolated Scandinavian population of grey wolves (Canis lupus), founded by only two individuals, was recovered by the arrival of a single immigrant. Before the arrival of this immigrant, for several generations the population comprised only a single breeding pack, necessarily involving matings between close relatives and resulting in a subsequent decline in individual heterozygosity. With the arrival of just a single immigrant, there is evidence of increased heterozygosity, significant outbreeding (inbreeding avoidance), a rapid spread of new alleles and exponential population growth. Our results imply that even rare interpopulation migration can lead to the rescue and recovery of isolated and endangered natural populations.
Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.
In the last two decades it has become increasingly clear that the spatial dimension is a critically important aspect of ecological dynamics. Ecologists are currently investing an enormous amount of effort in quantifying movement patterns of organisms. Connecting these data to general issues in metapopulation biology and landscape ecology, as well as to applied questions in conservation and natural resource management, however, has proved to be a non-trivial task. This book presents a systematic exposition of quantitative methods for analyzing and modeling movements of organisms in the field. Quantitative Analysis of Movement is intended for graduate students and researchers interested in spatial ecology, including applications to conservation, pest control, and fisheries. Models are a key ingredient in the analytical approaches developed in the book; however, the primary focus is not on mathematical methods, but on connections between models and data. The methodological approaches discussed in the book will be useful to ecologists working with all taxonomic groups. Case studies have been selected from a wide variety of organisms, including plants (seed dispersal, spatial spread of clonal plants), insects, and vertebrates (primarily, fish, birds, and mammals).
Gray wolves (Canis lupus) were eradicated from Montana in the 1930s and the adjacent Canadian Rockies by the 1950s, but recolonized these areas in the 1980s. We studied wolf recovery in and neat Glacier National Park (GNP), Montana, from 1979 to 1997. During this period, 31 of 58 tagged wolves dispersed. Most wolves (57%) did not make exploratory forays 3 months before permanent separation from their natal pack. Wolves usually left their natal home range quickly: (median = 4 days; mode = 1 day) after separating from the pack. Mean dispersal distance was not different (P > 0.05) between males (113 km) and females (78 lan), excluding an unusually long dispersal of 840 km by a yearling female. Wolves tended to disperse in a northerly direction to areas of higher wolf density. January-February and May-June were peak months for dispersal. Mean dispersal age (M = 28.7 months; F = 38.4 months) was not correlated with maximum pack size. Twenty percent of dispersers were greater than or equal to 57 months old at dispersal. Sex ratios of dispersers and captured wolves (both 71% F) differed from parity (P = 0.002). Annual survival rate ((x) over bar +/- SE) for dispersers and biders (philopatric wolves) did not differ (dispersers = 0.76 +/- 0.10; biders = 0.77 +/- 0.14). Wolves killed by humans died closer to roads ((x) over bar = 0.13 km) than wolves that died from other causes ((x) over bar = 0.85 km). Eighty percent (n = 30) of wolf mortalities were caused by humans, with proportionately mere dispersers (90%) than biders (60%) dying from human causes. Dispersers produced more litters than biders. Effects of mountainous terrain and management on wolf recovery are discussed.
The 400–500 wolves currently living in the Apennine range of peninsular Italy are slowly recolonizing the Alps and are expected to move northward. A nationwide management plan for the Italian wolf population is being prepared, and a zoning system with connecting corridors has been suggested. We developed a large-scale probabilistic model of wolf distribution as a contribution to the planning process. Thirteen environmental variables related to wolf needs and human presence were analyzed in 12 well-studied wolf territories and in 100 areas where the species has been absent for the past 25 years. These two areas were used as a training set in a discriminant analysis to evaluate potential wolf presence throughout the entire country. We used the Mahalanobis distance statistic as an index of environmental quality, calculated as the distance from the average environmental conditions of the wolf territories. Based on the Mahalanobis distance statistics, we constructed an actual and potential spatial distribution of the wolf for all of peninsular Italy. The jackknife procedure was used to assess the stability of the distance model and showed good confidence in our model (coefficient of variation ≤ 13%). Distance from the wolf territories’ centroid as an index of environmental quality for the wolf was tested using 287 locations where wolves have been found dead in the past 25 years as a consequence of human action (poison, shotgun, car accidents). A useful contribution to conservation planning resulted from comparing the frequency distribution of the Mahalanobis distance of the dead wolf locations with the percentage of study area within each distance class. This showed how the number of wolf casualties would greatly decrease with protection of only a minor part of the study area and indicated the usefulness of our approach for evaluation of other conservation options, such as core areas and corridor identification.
1. Reliable estimates of population parameters are often necessary for conservation management but these are hard to obtain for elusive, rare and wide-ranging species such as wolves Canis lupus. This species has naturally recolonized parts of its former habitat in Western Europe; however, an accurate and cost-effective method to assess population trend and survival has not been implemented yet.
2. We used open-model capture–recapture (CR) sampling with non-invasive individual identifications derived from faecal genotyping to estimate survival and trend in abundance for wolves in the Western Alps between 1999 and 2006. Our sampling strategy reduced individual heterogeneity in recaptures, thus minimizing bias and increasing the precision of the estimates.
3. Young wolves had lower apparent annual survival rates (0·24 ± 0·06) than adult wolves (0·82 ± 0·04); survival rates were lower in the summer than in the winter for both young and adults. The wolf population in the study area increased from 21 ± 9·6 wolves in 1999 to 47 ± 11·2 wolves in late winter 2005; the population growth rate (λ = 1·04 ± 0·27) was lower than that recorded for other recolonizing wolf populations.
4. We found a positive trend in wolf abundance, regardless of the method used. However, the abundance estimate based on snow-tracking was on average 36·2% (SD = 13·6%) lower than that from CR modelling, because young dispersing wolves are likely to have lower sign detection rates in snow-track surveys, a problem adequately addressed by CR sampling.
5. Synthesis and applications. We successfully implemented a new method to assess large carnivore population trend and survival at large spatial scales. These are the first such estimates for wolves in Italy and in the Alps and have important management implications. Our approach can be widely applied to broader spatial and temporal scales for other elusive and wide-ranging species in Europe and elsewhere.
Habitat suitability models are usually produced using species presence or habitat selection, without taking into account the demographic performance of the population considered. These models cannot distinguish between sink and source habitats, causing problems especially for species with low reproductive rates and high susceptibility to low levels of mortality as in the case of the critically endangered Apennine brown bear Ursus arctos marsicanus .
We developed a spatial model based on bear presence (2544 locations) and mortality data (37 locations) used as proxies for demographic performance. We integrated an occurrence and a mortality‐risk Ecological Niche Factor Analysis model into a final two‐dimensional model that can be used to distinguish between attractive sink‐like and source‐like habitat.
Our integrated model indicates that a traditional habitat suitability model can provide misleading management and conservation indications, as 43% of the area suitable for the occurrence model is associated with high mortality risk. Areas of source‐like habitat for the Apennine bears (highly elevated areas rich in beech forests, far from roads, and with low human density and cultivated fields) are still present, including outside the currently occupied range. However, attractive sink‐like habitat (associated with high levels of pasture, low extent of mountain meadows, low steepness, low elevation, and closeness to secondary and urban roads) are present even inside protected areas.
Synthesis and applications . Identifying attractive sink‐like habitat is crucial to prevent inappropriate management and to effectively address conservation issues: whereas existing source‐like habitats should be preserved to halt habitat loss and degradation, attractive sink‐like habitat should be managed to mitigate mortality risks or to decrease their attractiveness. In particular, area‐specific management interventions and proactive actions (increased patrolling, road closure, human activity management, threat monitoring, etc.) aimed at reducing human‐caused mortality are critical for the Apennine brown bear.
Mammalian carnivores are increasingly the focus of reintroduction attempts in areas from which they have been extirpated by historic persecution. We used static and dynamic spatial models to evaluate whether a proposed wolf reintroduction to the southern Rocky Mountain region ( U.S.A ) would advance recovery by increasing species distribution beyond what might be expected through natural range expansion. We used multiple logistic regression to develop a resource-selection function relating wolf distribution in the Greater Yellowstone region with regional-scale habitat variables. We also used a spatially explicit population model to predict wolf distribution and viability at several potential reintroduction sites within the region under current conditions and under two contrasting predictions of future landscape change. Areas of the southern Rocky Mountains with resource-selection-function values similar to those of currently inhabited areas in Yellowstone could potentially support>1000 wolves, 40% within protected areas and 47% on unprotected public lands. The dynamic model predicted similar distribution under current conditions but suggested that development trends over 25 years may result in the loss of one of four potential regional subpopulations and increased isolation of the remaining areas. The reduction in carrying capacity due to landscape change ranged from 49% to 66%, depending on assumptions about road development on public lands. Although much of the wolf population occurs outside core protected areas, these areas remain the key to the persistence of subpopulations. Although the dynamic model's sensitivity to dispersal parameters made it difficult to predict the probability of natural recolonization from distant sources, it suggested that an active reintroduction to two sites within the region may be necessary to ensure low extinction probability. Social carnivores such as the wolf, which often require larger territories than solitary species of similar size, may be more vulnerable to environmental stochasticity and landscape fragmentation than their vagility and fecundity would suggest.
Resumen: Con mayor frecuencia, los mamíferos carnívoros son el foco de intentos de reintroducción en áreas de las que han sido extirpados por persecución histórica. Utilizamos modelos espaciales estáticos y dinámicos para evaluar si la propuesta de reintroducción de lobos a la región sur de las Montañas Rocallosas ( E.U.A. ) haría progresar la recuperación al incrementar la distribución de la especie más allá de lo que pudiera esperarse por su expansión natural. Usamos regresión logística múltiple para desarrollar una función recurso-selección que relacionó la distribución de lobos en la región de Greater Yellowstone con variables de hábitat a escala regional. También utilizamos un modelo poblacional espacialmente explícito para predecir la distribución y viabilidad de lobos en varios sitios potenciales de reintroducción dentro de la región bajo condiciones actuales y bajo dos predicciones contrastantes de cambios futuros en el paisaje. Las áreas del sur de las Montañas Rocallosas con valores recurso-selección similares a los de áreas actualmente habitadas en Yellowstone potencialmente podrían albergar>1000 lobos, con 40% en áreas protegidas y 47% en tierras públicas no protegidas. El modelo dinámico predijo una distribución similar bajo condiciones actuales pero sugirió que las tendencias de desarrollo a 25 años pudieran resultar en la pérdida de una de cuatro potenciales subpoblaciones regionales y en el incremento en el aislamiento de las áreas remanentes. La reducción en la capacidad de carga debido a cambios en el paisaje varió de 49 a 66% dependiendo de la construcción proyectada de caminos en tierras públicas. Aunque buena parte de la población de lobos ocurre fuera de las áreas protegidas núcleo, estas áreas siguen siendo la clave para la persistencia de las subpoblaciones. Aunque la sensibilidad a los parámetros de dispersión del modelo dinámico dificultó la predicción de la probabilidad de recolonización a partir de fuentes lejanas, sugirió que puede ser necesaria una reintroducción activa en dos sitios dentro de la región para asegurar una baja probabilidad de extinción. Carnívoros sociales, tales como los lobos, que a menudo requieren territorios mayores que especies solitarias de similar tamaño, pueden ser más vulnerables a la estocacidad ambiental y a la fragmentación del paisaje de lo que pudieran sugerir su vagilidad y fecundidad.
Resource-selection probability functions and occupancy models are powerful methods of identifying areas within a landscape that are highly used by a species. One common design/analysis method for estimation of a resource-selection probability function is to classify a sample of units as used or unused and estimate the probability of use as a function of independent variables using, for example, logistic regression. This method requires that resource units are correctly classified as unused (i.e., the species is never undetected in a used unit), or that the probability of misclassification is the same for all units. In this paper, I explore these issues, illustrating how misclassifying units as unused may lead to incorrect conclusions about resource use. I also show how recently developed occupancy models can be utilized within the resource-selection context to improve conclusions by explicitly accounting for detection probability. These models require that multiple surveys be conducted at each of a sample of resource units within a relatively short timeframe, but given the growing evidence from simulation studies and field data, I recommend that such procedures should be incorporated into studies of resource use.
Restoring biologically appropriate habitat networks is fundamental to the persistence and connectivity of at‐risk species surviving in highly fragmented environments. For many at‐risk species, this landscape planning problem requires combining detailed biological information about the species with the landscape, economic and social realities of the restoration effort.
Here, we assess the ability of potential restored landscapes to create persistent and connected populations of the federally endangered Fender's blue butterfly ( Icaricia icarioides fenderi ) in Oregon's Willamette Valley. Like many other at‐risk species, a very small amount (0·5%) of historic habitat remains and much of this habitat is highly degraded.
To do this, we combine extensive demography and behaviour data from prior studies of Fender's blue with landscape maps of potential restoration sites by building and running a spatially explicit landscape model. We chose a simulation approach because previous attempts using more traditional population modelling did not provide sufficiently informative answers for this restoration problem.
From our simulations, we: (a) provide a solution to the general landscape restoration problem of determining whether patches that are available according to social, economic and ecological realities are sufficient to restore persistence and connectivity; (b) supported our predictions from our previous models about persistence of our large patches and expanded our inference to include connectivity and persistence of small patches; and (c) found several emergent properties of our system, including identifying stepping‐stone patches, observing asymmetric connectivity and uncovering reciprocal effects of connectivity and population dynamics.
Synthesis and applications. Assuming no large disturbances, and relying on our 14 years of data collection and models, restoring all currently degraded and potentially available habitat patches to high quality native prairie would be sufficient for long‐term persistence of Fender's blue butterfly in the West Eugene area, Oregon. This conclusion resolves many of the shortcomings of our previous population and metapopulation models that were not able to combine the necessary landscape complexity with species behaviour to address this restoration problem.
Although many reintroduction schemes for the Eurasian lynx Lynx lynx in Germany have been discussed, the implications of connectivity between suitable patches have not been assessed.
We introduce an individual‐based, spatially explicit dispersal model to assess the probability of a dispersing animal reaching another suitable patch in the complex heterogeneous German landscape, with its dense transport system. The dispersal model was calibrated using telemetric data from the Swiss Jura and based on a map of potential lynx dispersal habitat.
Most suitable patches could be interconnected by movements of dispersing lynx within 10 years of reintroduction. However, when realistic levels of mortality risks on roads were applied, most patches become isolated except along the German–Czech border. Consequently, patch connectivity is limited not so much by the distribution of dispersal habitat but by the high mortality of dispersing lynx. Accordingly, rather than solely investing in habitat restoration, management efforts should try to reduce road mortality.
Synthesis and applications . Our approach illustrates how spatially explicit dispersal models can guide conservation efforts and reintroduction programmes even where data are scarce. Clear limits imposed by substantial road mortality will affect dispersing lynx as well as other large carnivores, unless offset by careful road‐crossing management or by the careful selection of release points in reintroduction programmes.
ABSTRACT The isolated gray wolf (Canis lupus) population of the Scandinavian Peninsular is suffering from inbreeding depression. We studied dispersal of 35 wolves fitted with very high frequency (20) or Global Positioning System—global system for mobile (15) radiocollars in the neighboring Finnish wolf population. The growing wolf population in Finland has high numbers of dispersing individuals that could potentially disperse into the Scandinavian population. About half (53%) of the dispersing wolves moved total distances that could have reached the Scandinavian population if they had been straight-line moves, but because of the irregular pattern of movements, we detected no wolves successfully dispersing to the Scandinavian population. Dispersal to the Scandinavian population was also limited by high mortality of wolves in reindeer (Rangifer tarandus) management areas and by dispersal to Bothnian Bay at times of the year when ice was not present. We suggest that when a small wolf population is separated from source populations by distance, barriers, and human exploitation, wildlife managers could promote the population's viability by limiting harvest in the peripheral areas or by introducing wolves from the source population.
Aim To explore the usefulness of Spatially Explicit Population Models (SEPMs), incorporating dispersal, as tools for animal conservation, as illustrated by the contrasting cases of four British mammals.
Methods For each of the four species (American mink, Mustela vison, pine marten, Martes martes, dormouse, Muscardinus avellanarius and water vole, Arvicola terrestris ) a spatial dynamics model was developed based on an integrated geographical information system (GIS) population model that linked space use to the incidence of the species. Each model had, first, a GIS, which stored environmental, habitat and animal population information, and secondly, an individual‐based population dynamics module, which simulated home range formation, individual life histories and dispersal within the GIS‐held landscape.
Results The four models illustrated different interactions between species life‐history variables and the landscape, particularly with respect to dispersal. As water voles and dormice occupy home ranges that are small relative to blocks of their habitat, they were most effectively modelled in terms of the dynamics of local populations within habitat blocks but linked by dispersal. In contrast, because the home ranges of American mink and pine marten are large relative to blocks of habitat, they were best modelled as individuals moving through a landscape of more or less useful patches of habitat. For the water vole, the most significant predictors of population size were the carrying capacity of each habitat and the annual number of litters. For the dormouse, the likelihood of catastrophe and the upper limit to dispersal movement were the key variables determining persistence. Adult mortality and home‐range size were the only significant partial correlates of total population size for the American mink. Adult mortality was also a significant correlate of total population size in the pine marten, as were litter size and juvenile mortality. In neither the marten nor the mink was dispersal distance a significant factor in determining their persistence in the landscape.
Main conclusions At a landscape scale it is difficult to measure animal distributions directly and yet conservation planning often necessitates knowledge of where, and in what numbers, animals are found, and how their distributions will be affected by interventions. SEPMs offer a useful tool for predicting this, and for refining conservation plans before irreversible decisions are taken in practice.
Extinction models based on diffusion theory generally fail to incorporate two important aspects of population biology—social structure and prey dynamics. We include these aspects in an individual-based extinction model for small, isolated populations of the gray wolf (Canis lupus). Our model predicts mean times to extinction significantly longer than those predicted by more general (diffusion) models. According to our model, an isolated population of 50 wolves has a 95% chance of surviving just 9 years and only a 30% chance of surviving beyond 100 years. Reflecting the influence of social structure, a wolf population initially comprising 50 individuals is expected to persist only a few years longer, on average (71 years), than is a population initially comprising just a single reproductive pair (62 years). In contrast, substantially greater average prey abundance leads to dramatically longer expected persistence times. Autocorrelated prey dynamics result in a more complex distribution of extinction times than predicted by many extinction models. We contend that demographic stochasticity may pose the greatest threat to small, isolated wolf populations, although environmental stochasticity and genetic effects may compound this threat. Our work highlights the importance of considering social structure and resource dynamics in the development of population viability analyses.