3.1 Distribution of grey wolf and golden jackal
Among all the model’s RF and GLM represented the highest and lowest
performance in predicting habitat suitability for both species,
respectively (Table 1). All five employed models produced good
discriminating power; however, the models’ accuracy was better for
golden jackal compared with grey wolf. For grey wolf, elevation,
topographic roughness and distance from agriculture lands were the
strongest predictors; however, for golden jackal, distance from
agriculture lands, human settlements and topographic roughness were the
most important variables predicting occurrence in the study area (Table
S1).
Golden jackal showed a positive association with increasing distance
from agriculture lands, roads, human settlements and elevation (Figure
S1). Besides, it showed a decrease in occurrence rate with increasing
NDVI, roughness and distance from dumpsites (Figure S1). Grey wolf had a
positive association with increasing distance from agriculture lands,
roads, human settlements, NDVI (Figure S2). Also, grey wolf showed a
decrease in occurrence rate with increasing roughness (Figure S2).
Prediction of the ensemble models for grey wolf and golden jackal
revealed that large parts of the landscape had the potential to support
the occurrence of both species (Figure 2). However, the predicted
suitable areas for gray wolf were more concentrated and spatially
demarcated. 75 percent of the area was suitable for grey wolf and
slightly less (74%) for golden jackal (Figure S3).
Fig 2. Predicted suitability of the study area for grey wolf and golden
jackal based on the combined result of five SDMs.
Table1: Accuracy evaluation of the different models’ models (TSS, AUC)
used to predict distribution of grey wolf and golden jackal in central
Iran.
3.2 Core habitat:
Our connectivity simulation modeling for grey wolf revealed that core
habitats are extensive, concentrating in the study area’s southern
parts. Among the identified core habitat, eight are more extensive than
2000 km2. The largest and most important core area (C1
in Figure 3) is of 49800 km2 and is located in the
south part of the landscape (Figure 3). The second largest and most
important core area, based on size (6200 km2) and
strength (sum of kernel value), occurred in the southwestern part of the
landscape (Haftadgholleh and Alvand protected areas and Rasvand Wildlife
Refuge). Also, an average of 37.84 % of the identified core habitats
for the grey wolf is covered by Protected Areas Networks (Table 2). The
highest overlap between core habitats and Protected Areas networks was
observed in the southern part of the landscape which three CAs
(Haftadgholleh and Alvand protected areas and Rasvand Wildlife Refuge)
were covered by the most important identified core areas. The largest
and most important core area (C1 in Fig 4) for golden jackal, according
to size (38800.20 km2) and strength, is in the south
parts of the study area (Figure 4 and Table 2). Among the predicted core
habitats of this species, 18.6 % are covered by IUCN Protected Areas
Networks.
Fig 3: Grey wolf core areas at dispersal ability 50, 100, 150 and 200 km
respectively and network of protected areas and roads.
Fig 4: Golden Jackal core areas at dispersal ability 50, 100, 150 and
200 km respectively and network of protected areas and roads.
Table 2. The extent and percent of core habitats covered by current
conservation networks for grey wolf and golden jackal in Central Iran.
The median value of habitat suitability for presence points was used as
the threshold to define the highly suitable habitats.