The golden jackal’s Canis aureus range in Europe is expanding rapidly and populations are increasing. Historically restricted to the Mediterranean and Black sea coastal regions, jackals are now reproducing in most of Southeastern Europea and some Central European countries (1,2). In addition, dispersing animals have been detected further to the North and West (e.g. Belarus, Estonia, Finland, Germany, Switzerland). Two main causes have been suggested to explain this continental-scale range expansion: an improvement in human attitude and legal status, and a decrease and fragmentation of previously dense grey wolf Canis lupus populations (1,3,4). In particular, local evidence of golden jackals avoiding core areas occupied by wolves is accumulating in several countries e.g. Slovenia, Greece. From an applied perspective, the presence of this new carnivore could impact existing animal communities (5) and is already receiving high interest among wildlife managers. In this study, we used species distribution models to describe the golden jackal environmental niche and to identify areas of high habitat suitability, which are likely to be colonized in the future. Since jackals are highly mobile and opportunist animals, dispersers can temporarily occupy nearly all types of habitats. To prevent overestimation of the species’ environmental niche, we considered as presence only locations of established territorial jackal groups. These were contrasted with background points representing available environmental conditions. We controlled for sampling selection bias by manipulating presence weights and background spatial selection (6). We modeled the jackal environmental niche using annual duration of snow cover as well as ten land-cover variables. In addition, we included a grey wolf presence covariate derived from a categorical expert-based distribution map (7). All modeling was done at a 4km resolution, coherent with both jackal territory size and error associated with howling surveys (8). Within the core range of the species, we calibrated ten different model types and evaluated their performance considering both an internal evaluation (with a repeated split plot) and an external evaluation (with a geographically stratified cross-validation). Absence evaluation points were drawn from a combination of three data sources: hunting-statistics, expert-based distribution models and opportunistic jackal records. The final model was achieved through an ensemble model procedure and projected across the continent. Finally, we investigated the robustness of our predictions to extrapolation using a multivariate environmental surface analysis. We gathered a total of 1,517 recent locations of territorial jackal groups from 14 European countries (c. 80% from howling surveys and 20% from opportunistic records). Our model performed very well according to internal evaluation (AUC > 0.90 for GBM and MaxEnt). Snow cover duration and wolf presence were identified as the most important variables in explaining jackal distribution, followed by proportion of forest and agriculture, and distance from urban centers. Jackal relative probability of presence was highest in areas characterized with low snow cover duration and absence of permanent wolf populations. The presence of territorial jackal groups in areas of relatively long snow cover duration in Eastern Italy, where wolves are absent suggests that wolf presence is a relevant large-scale predictor of the jackal distribution. In addition, the low resolution of our wolf presence covariate certainly underestimates the importance of wolf presence in constraining jackal distribution. Four land cover covariates were also important predictors. Relative probability of presence was highest in areas of intermediary agriculture, medium-low forest, medium-low shrub and high water bodies prevalence. Hence, areas characterized by mosaic habitats seem to be most suitable, which confirms previous analyses of habitat selection at a finer scale (9). The ensemble model procedure reveals that large parts of Europe appear suitable for golden jackals (Figure 1.), so we can expect further expansion of this species in the future. These results provide managers with the opportunity to prepare for the jackal’s future colonization of areas where the expansion is most likely.

Ranc, N.G.; Cagnacci, F.; Banea, O.C.; Berce, T.; Ćirović, D.; Csànyi, S.; Giannatos, G.; Heltai, M.; Lanszki, J.; Lapini, L.; Maiorano, L.; Malešević, D.; Migli, D.; Mladenovič, J.; Pankov, I.A.; Penezić, A.; Šálek, M.; Selanec, I.; Stoyanov, S.; Szabó, L.; Trbojević, I.; Krofel, M. (2015). Where to go next? Predicting habitat suitability of an expanding mesocarnivore: the golden jackal (Canis aureus) in Europe. In: ICCB : 27th International Congress for Conservation Biology, 4th European Congress for Conservation Biology, August 2-6 2015, Montpellier, France. handle: http://hdl.handle.net/10449/27742

Where to go next? Predicting habitat suitability of an expanding mesocarnivore: the golden jackal (Canis aureus) in Europe

Ranc, Nathan Geoffrey;Cagnacci, Francesca;
2015-01-01

Abstract

The golden jackal’s Canis aureus range in Europe is expanding rapidly and populations are increasing. Historically restricted to the Mediterranean and Black sea coastal regions, jackals are now reproducing in most of Southeastern Europea and some Central European countries (1,2). In addition, dispersing animals have been detected further to the North and West (e.g. Belarus, Estonia, Finland, Germany, Switzerland). Two main causes have been suggested to explain this continental-scale range expansion: an improvement in human attitude and legal status, and a decrease and fragmentation of previously dense grey wolf Canis lupus populations (1,3,4). In particular, local evidence of golden jackals avoiding core areas occupied by wolves is accumulating in several countries e.g. Slovenia, Greece. From an applied perspective, the presence of this new carnivore could impact existing animal communities (5) and is already receiving high interest among wildlife managers. In this study, we used species distribution models to describe the golden jackal environmental niche and to identify areas of high habitat suitability, which are likely to be colonized in the future. Since jackals are highly mobile and opportunist animals, dispersers can temporarily occupy nearly all types of habitats. To prevent overestimation of the species’ environmental niche, we considered as presence only locations of established territorial jackal groups. These were contrasted with background points representing available environmental conditions. We controlled for sampling selection bias by manipulating presence weights and background spatial selection (6). We modeled the jackal environmental niche using annual duration of snow cover as well as ten land-cover variables. In addition, we included a grey wolf presence covariate derived from a categorical expert-based distribution map (7). All modeling was done at a 4km resolution, coherent with both jackal territory size and error associated with howling surveys (8). Within the core range of the species, we calibrated ten different model types and evaluated their performance considering both an internal evaluation (with a repeated split plot) and an external evaluation (with a geographically stratified cross-validation). Absence evaluation points were drawn from a combination of three data sources: hunting-statistics, expert-based distribution models and opportunistic jackal records. The final model was achieved through an ensemble model procedure and projected across the continent. Finally, we investigated the robustness of our predictions to extrapolation using a multivariate environmental surface analysis. We gathered a total of 1,517 recent locations of territorial jackal groups from 14 European countries (c. 80% from howling surveys and 20% from opportunistic records). Our model performed very well according to internal evaluation (AUC > 0.90 for GBM and MaxEnt). Snow cover duration and wolf presence were identified as the most important variables in explaining jackal distribution, followed by proportion of forest and agriculture, and distance from urban centers. Jackal relative probability of presence was highest in areas characterized with low snow cover duration and absence of permanent wolf populations. The presence of territorial jackal groups in areas of relatively long snow cover duration in Eastern Italy, where wolves are absent suggests that wolf presence is a relevant large-scale predictor of the jackal distribution. In addition, the low resolution of our wolf presence covariate certainly underestimates the importance of wolf presence in constraining jackal distribution. Four land cover covariates were also important predictors. Relative probability of presence was highest in areas of intermediary agriculture, medium-low forest, medium-low shrub and high water bodies prevalence. Hence, areas characterized by mosaic habitats seem to be most suitable, which confirms previous analyses of habitat selection at a finer scale (9). The ensemble model procedure reveals that large parts of Europe appear suitable for golden jackals (Figure 1.), so we can expect further expansion of this species in the future. These results provide managers with the opportunity to prepare for the jackal’s future colonization of areas where the expansion is most likely.
Species distribution modelling
Colonization
2015
Ranc, N.G.; Cagnacci, F.; Banea, O.C.; Berce, T.; Ćirović, D.; Csànyi, S.; Giannatos, G.; Heltai, M.; Lanszki, J.; Lapini, L.; Maiorano, L.; Malešević, D.; Migli, D.; Mladenovič, J.; Pankov, I.A.; Penezić, A.; Šálek, M.; Selanec, I.; Stoyanov, S.; Szabó, L.; Trbojević, I.; Krofel, M. (2015). Where to go next? Predicting habitat suitability of an expanding mesocarnivore: the golden jackal (Canis aureus) in Europe. In: ICCB : 27th International Congress for Conservation Biology, 4th European Congress for Conservation Biology, August 2-6 2015, Montpellier, France. handle: http://hdl.handle.net/10449/27742
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