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. 2017 Nov 9;12(11):e0187027.
doi: 10.1371/journal.pone.0187027. eCollection 2017.

Habitat suitability and movement corridors of grey wolf (Canis lupus) in Northern Pakistan

Muhammad Kabir  1 , Shoaib Hameed  1 , Hussain Ali  1 , Luciano Bosso  2 , Jaffar Ud Din  3   4 , Richard Bischof  5 , Steve Redpath  6 , Muhammad Ali Nawaz  1   4
Affiliations

Habitat suitability and movement corridors of grey wolf (Canis lupus) in Northern Pakistan

Muhammad Kabir et al. PLoS One. .

Abstract

Habitat suitability models are useful to understand species distribution and to guide management and conservation strategies. The grey wolf (Canis lupus) has been extirpated from most of its historic range in Pakistan primarily due to its impact on livestock and livelihoods. We used non-invasive survey data from camera traps and genetic sampling to develop a habitat suitability model for C. lupus in northern Pakistan and to explore the extent of connectivity among populations. We detected suitable habitat of grey wolf using a maximum entropy approach (Maxent ver. 3.4.0) and identified suitable movement corridors using the Circuitscape 4.0 tool. Our model showed high levels of predictive performances, as seen from the values of area under curve (0.971±0.002) and true skill statistics (0.886±0.021). The main predictors for habitat suitability for C. lupus were distances to road, mean temperature of the wettest quarter and distance to river. The model predicted ca. 23,129 km2 of suitable areas for wolf in Pakistan, with much of suitable habitat in remote and inaccessible areas that appeared to be well connected through vulnerable movement corridors. These movement corridors suggest that potentially the wolf range can expand in Pakistan's Northern Areas. However, managing protected areas with stringent restrictions is challenging in northern Pakistan, in part due to heavy dependence of people on natural resources. The habitat suitability map provided by this study can inform future management strategies by helping authorities to identify key conservation areas.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Study area (Northern Pakistan).
Scales show the altitude ranging from low (dark grey) to high (red).
Fig 2
Fig 2. Genetic or photographic detections of wolves in the study area.
The presence points were obtained from camera trap results and DNA analysis of scat samples collected from the Northern Areas of Pakistan (2009–2015). Altitude map in grey.
Fig 3
Fig 3. Wolf habitat suitability in Northern Pakistan, generated through Maxent.
Scales show the probability of presence ranging from 0 to 1.
Fig 4
Fig 4. Binary map of C. lupus in Pakistan.
White = Absence; Red = Presence.
Fig 5
Fig 5. Jackknife analysis of variables.
It shows how important each variable is in explaining wolf presence when used separately (cobalt blue), and how the model is affected when each variable is left out (aqua). Dark blue bars = Importance of single variable, light blue bars = loss in model gain, when variable is omitted. Red bar = total model gain. Alt = Altitude; bio_12 = Annual Precipitation; bio_2 = Mean Diurnal Range (Mean of monthly); bio_8 = Mean Temperature of Wettest Quarter; glc2000 = Global land cover 2000; road_dist = Distance to roads; river_dist = Distance to rivers; Soil = Soil.
Fig 6
Fig 6. Potential movement corridors of wolf in northern Pakistan.
Red areas are strong links while yellowish areas are weakest. Map also illustrating population connection found in National Park.
See this image and copyright information in PMC

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