Species distribution models (SDMs) are practical tools to assess the habitat suitability of species with numerous applications in environmental management and conservation planning. The manipulation of the input data to deal with their spatial bias is one of the advantageous methods to enhance the performance of SDMs. However, the development of a model parameterization approach covering different SDMs to achieve well‐performing models has rarely been implemented. We integrated input data manipulation and model tuning for four commonly‐used SDMs: generalized linear model (GLM), gradient boosted model (GBM), random forest (RF), and maximum entropy (MaxEnt), and compared their predictive performance to model geographically imbalanced‐biased data of a rare species complex of mountain vipers. Models were tuned up based on a range of model‐specific parameters considering two background selection methods: random and background weighting schemes. The performance of the fine‐tuned models was assessed based on recently identified localities of the species. The results indicated that although the fine‐tuned version of all models shows great performance in predicting training data (AUC > 0.9 and TSS > 0.5), they produce different results in classifying out‐of‐bag data. The GBM and RF with higher sensitivity of training data showed more different performances. The GLM, despite having high predictive performance for test data, showed lower specificity. It was only the MaxEnt model that showed high predictive performance and comparable results for identifying test data in both random and background weighting procedures. Our results highlight that while GBM and RF are prone to overfitting training data and GLM over‐predict nonsampled areas MaxEnt is capable of producing results that are both predictable (extrapolative) and complex (interpolative). We discuss the assumptions of each model and conclude that MaxEnt could be considered as a practical method to cope with imbalanced‐biased data in species distribution modeling approaches.

We determined the effects of past and future climate changes on the distribution of the Montivipera raddei species complex (MRC) that contains rare and endangered viper species limited to Iran, Turkey and Armenia. We also investigated the current distribution of MRC to locate unidentified isolated populations as well as to evaluate the effectiveness of the current network of protected areas for their conservation. Present distribution of MRC was modeled based on ecological variables and model performance was evaluated by field visits. Some individuals at the newly identified populations showed uncommon morphological characteristics. The distribution map of MRC derived through modeling was then compared with the distribution of protected areas in the region. We estimated the effectiveness of the current protected area network to be 10%, which would be sufficient for conserving this group of species, provided adequate management policies and practices are employed. We further modeled the distribution of MRC in the past (21,000 years ago) and under two scenarios in the future (to 2070). These models indicated that climatic changes probably have been responsible for an upward shift in suitable habitats of MRC since the Last Glacial Maximum, leading to isolation of allopatric populations. Distribution will probably become much more restricted in the future as a result of the current rate of global warming. We conclude that climate change most likely played a major role in determining the distribution pattern of MRC, restricting allopatric populations to mountaintops due to habitat alterations. This long-term isolation has facilitated unique local adaptations among MRC populations, which requires further investigation. The suitable habitat patches identified through modeling constitute optimized solutions for inclusion in the network of protected areas in the region.

Wildlife attacks on humans are an example of serious human–wildlife conflict. Such attacks are rarely studied in Asia and particularly not in Iran. A total of 53 wolf (Canis lupus) attacks were recorded on humans in the Hamedan province, a human-dominated landscape in west Iran, between April 2001 and April 2012. Most attacks were classified as predatory (68%) and pet-related (19%) in nature. The majority of victims were children (12 years old or younger; 62%). Most incidents (70%) took place during the wolf’s pup-rearing season. The most frequent human activities at time of attack were recreation based (57%). The locations of attacks occurred frequently in the farmlands (43%) and outskirts of villages (41%). We recommend that future wolf attacks could be reduced or prevented through modification of human behavior and public education designed to prevent the habituation of wolves.

The feeding ecology of gray wolves has been investigated extensively worldwide. Despite previous studies on food habits of wolves in Asia and Iran, none has focused on the diet of the species in a scenario of depleted of wild prey and with recent records of attacks on humans. Here, we combined telemetry methods and scat analysis to study the diet of wolves in areas of Hamadan province, Iran, where medium to large wild prey is almost absent. Between October 2015 and March 2017, we studied the feeding behavior (by identifying feeding sites through clusters of GPS locations) of three wolves fitted with GPS collars, belonging to different wolf packs. We also collected and analyzed 110 wolf scats during the same period within the same areas. Overall, we investigated 850 clusters of GPS locations in the field, and identified 312 feeding sites. Most feeding clusters were linked to dumpsites and poultry farms around villages. We found 142 and 170 events of predatory (kill sites) and scavenging behavior, respectively. Prey composition based on kill sites was comprised of 74.6% livestock, 19.7% lagomorphs, 3.5% dogs, 1.4% red fox, and 0.7% golden jackal. Similarly, prey composition based on scavenging clusters was comprised of 79.9% livestock, 10.6% red fox, and 9.4% golden jackal. Scat analysis, however, indicated that livestock (34.3%), garbage (23.7%), poultry (16.0%), and European hare (15.4%) were the most frequent food items. We discuss the role of anthropogenic food sources in a context where agonistic wolf-human encounters occur recurrently, and suggest management guidelines regarding illegal dumping of animal carcasses and garbage dumpsites, in order to minimize wolf-human negative interactions.

As human populations expand, there is increasing demand and pressure for land. Under this scenario, behavioural flexibility and adaptation become important processes leading to the persistence of large carnivores in human-dominated landscapes such as agroecosystems. A growing interest has recently emerged on the outcome of the coexistence between wolves and humans in these systems. It has been suggested that spatial heterogeneity in human activities would be a major environmental factor modulating vulnerability and persistence of this contentious species in agroecosystems. Here, we combined information from 35 den sites detected between 2011 and 2012 in agroecosystems of western Iran (Hamedan province), a set of environmental variables measured at landscape and fine spatial scales, and generalized linear models to identify patterns of den site selection by wolves in a highly-modified agroecosystem. On a landscape level, wolves selected a mixture of rangelands with scattered dry-farms on hillsides (showing a low human use) to locate their dens, avoiding areas with high densities of settlements and primary roads. On a fine spatial scale, wolves primarily excavated dens into the sides of elevated steep-slope hills with availability of water bodies in the vicinity of den sites, and wolves were relegated to dig in places with coarse-soil particles. Our results suggest that vulnerability of wolves in human-dominated landscapes could be compensated by the existence of spatial heterogeneity in human activities. Such heterogeneity would favor wolf persistence in agroecosystems favoring a land sharing model of coexistence between wolves and people.

The Iranian black bear (Ursus thibetanus gedrosianus; IBB) is a critically endangered subspecies. The IBB needs connectivity to access seasonally available foods and to provide gene flow among populations in the mountains of Kerman, Hormozgan, and Sistan and Baluchistan provinces of Iran. We identified IBB cores to be used as termini for modelled corridors. We mapped 31 habitat cores based on 200 IBB presence points from studies during 2008–2013, and 70 presence points from our own observations of IBB footprints and scats in 2014. We used MaxEnt on 101 spatially independent presence points to map areas of high-quality habitat. The largest population patch (approx. 8,700 km2) covered 4 protected areas. We used least-cost modelling to model habitat corridors among 31 habitat cores. We considered a corridor locally important if it helped join nearby cores into a cluster that would support a large demographically and genetically vigorous population. We considered a corridor regionally important if it...