4.2 Conservation of connectivity networks and core habitat
distribution:
Effective conservation of large carnivores requires identifying
predicted core habitats and corridor networks between them (Cushman et
al., 2018; Khosravi et al., 2018; Shahnaseri et al., 2019). According to
our connectivity analysis the southern parts of the study area were
predicted to contain the largest extent of potentially suitable habitats
for both target species (Figure 5). We identified four and two important
core habitats for grey wolf and golden jackal in the southern part of
the landscape, respectively (Figure 3 to 5). High connectivity areas in
the southern parts of the study area are predicted to connect these core
habitats (Figure 6).
Most important linkage for both species occurred in the South from East
to West which is strong for both species .Our result showed that C1 at
larger dispersal abilities was most important core area for both
species. For this regards, considering this core area is essential as
the most important landscape conservation area for promoting network
connectivity.
Our resistant kernel analysis showed that between 32 – 41 % of
identified core habitats for grey wolf are covered by Protected Area
networks depending on dispersal ability. For the golden jackal we found
a lower contribution of the PAs as core habitats (15-21%), which was
explained by species’ association with human dominated landscapes. Our
results for golden jackal connectivity are aligned with the outcomes of
Shahnaseri et al (2019). For this canid, the highest overlap between
core habitats and protected sites was observed for C1 and C2
incorporating a considerable number of villages. In contrast, the
highest overlap between grey wolf core habitats and Protected Areas was
observed for core numbers C1, C2, C3 and C4 (Figure 4), with 40 % of
core habitats intersecting with the protected area network (Figure 4).
However, the coverage of Protected Areas is not sufficient, particularly
for those cores in the northern and western parts of the study area, due
to the small size and wide separation of protected areas in that part of
the study landscape.
The largest protected area in the southern part of the study area
supports large numbers of natural prey species including wild goat, wild
sheep and Persian gazelle and our model predicted this area is an
important habitat core area and connectivity node for both species of
canid in central Iran. These core habitats have also been documented to
have a high potential for supporting other carnivore species such as red
fox (Vulpes vulpes ) and Persian leopard (Panthera pardus
saxicolor ). However, of Protected Areas’ coverage is not sufficient to
safeguard core habitats in the northern and western portions of the
study area. Therefore, we believe that the proportion of protected area
networks should be increased and located along with strategic locations
where the new PAs protect both important unprotected core areas and lie
along the most important connectivity corridors through the system.
Similar results and recommendations were produced by Moqanaki and
Cushman (2016) and Khosravi et al (2018), who found that Protected Area
status is the most important predictor of the occurrence and dispersal
of Asiatic cheetah and sympatric carnivores (Asiatic cheetah, Persian
leopard, caracal, wild cat, sand cat and grey wolf), respectively.
Therefore, protected area network coverage should be accompanied by
protected connected land to increase functional landscape connectivity
for carnivores.
Most protected areas networks in developing countries, such as Iran, are
fragmented by roads, and road collisions present a serious threat for
carnivores. In this research, vulnerable parts of the connectivity
network were found in the southern part of the study area (C1 and C2)
where roads intersected important movement corridors (Cushman, McRae, et
al., 2013). The vulnerability of these locations is related to the high
potential for grey wolf and golden jackal vehicle collisions. Our
findings are similar to Moqanaki and Cushman (2016) (Moqanaki &
Cushman, 2017) and Khosravi et al (2018) (Khosravi et al., 2018). They
showed that primary and secondary roads cross the predicted corridor
paths between the core patches. One of our study’s most novel aspects is
the validation of our predicted connectivity maps with independent data
on road mortality and crossing locations of both species. Relatively few
studies have independently validated connectivity predictions with
movement (Cushman et al., 2014), density (Puyravaud, Cushman, Davidar,
& Madappa, 2017) mortality, or genetic data (Mateo-Sánchez et al.,
2015; Zeller et al., 2018). Our spatial randomization approach provided
strong support for our predicted connectivity value. Predicted
connectivity is highly related to the actual patterns of observed road
mortality and crossing in the study area for both species, giving
important independent validation of our predictions. This significantly
strengthens their utility for decision-making.