We generated a dataset to describe the essential geographic layers that would be used as landscape drivers for the Marco Polo argali habitat in the southeastern Tajikistan Pamirs, and to aid a paper [1
] that was recently published. The dataset, consisting of layers in Geographic Information System (GIS) format, is available online for easy download through the New Mexico State University’s Center for Applied Spatial Ecology (CASE) website [2
] and for use by other researchers interested in studying the southeastern Tajik Pamirs. While every layer is deemed important, we put more attention and time in developing the mapping methodology of the summer pastures.
Mountain pastures are by far the greatest source of livestock forage in the eastern Pamirs. In the Food and Agriculture Organization Statistics (FAOStat) report [3
], about 87% of the total pasture land is classified as mountain pasture. With a vertical transhumance herding system, the use of elevated pasture areas depends on the season. Summer pastures, located in the productive rangelands of the southeastern Pamirs, occur between 3500 to 4700 m above mean sea level (AMSL) and typically utilized between months July to September. Pastures in much lower elevations are used for winter, spring, and fall seasons. Hay fields, which are located near rivers, are used as a source of winter livestock fodder.
After the collapse of the USSR and the support mechanism for agricultural sectors beginning in 1991, the best summer pastures that are hard to access without heavy-duty trucks, are no longer used. Distance and the consequent financial constraints have limited herder’s accessibility to summer rangelands. Also, there are difficulties in sustaining the existing remote watering points. The change of the herding patterns has negative consequences for the livelihoods of the herders on the area. Breu and Hurni [4
] elucidated the degradation of pastures at lower elevations close to the villages. As herders consider expenses too high to make a profit from high pastures, herds are concentrated near large settlement areas resulting in overgrazing and degradation of vegetation cover [5
Recent studies in the eastern Pamirs concern the extensive removal and degradation risk for teresken, a dwarf shrubby vegetation that is used as a fuel substitute [8
]. While the dwarf shrub has been documented quite extensively, less attention is paid to the quantification of the green vegetation. An unpublished thesis [12
] investigated the landcover of the Tajik Pamirs using one image of Landsat 7 acquired in 2000. Another more recent paper [6
] discussed the relationships between grazing practices and pasture potentials in the eastern Pamirs. The study concluded that there is less grazing pressure on summer pastures; however, a number of distant summer pastures showed high livestock numbers during summer. A research gap remains concerning the quantitative estimate of the summer pasture cover in the eastern Pamirs.
Satellite imagery is an essential means for capturing disturbance processes and for the estimation of land cover spatial distribution [13
]. In our efforts modeling the sheep habitat, we investigated the potential of remote sensing data to generate a summer vegetation map in an arid community that will enable us to analyze pasture dynamics and spatial changes.
The geographic layers presented in this paper are the result of our mapping efforts. The dataset could give information on the extent and the vegetation status for improving pasture management and enhancing the current knowledge of vegetation communities on the Pamirs. More importantly, the geographic layers could provide critical information needed for understanding food resources and habitat for the Marco Polo argali.
2. Data Description
The dataset is comprised of seven GIS layers: contours, possible sheep habitat, rivers and streams, slope, vegetation cover, vegetation within 1 km from stream, and water bodies. We generated the individual layers to collect essential information on argali patterns and habitat suitability in the southeastern Tajik Pamirs. Table 1
shows the type and short description of the layers.
We have shown the habitat environment of argali in terms of the seven geographic layers: slope, distance to escape terrains and water sources, elevation, and vegetation cover. The seven layers are futher described below.
The mean elevation is 4430 m AMSL. The minimum and maximum elevations observed are 4133 m and 5232 m, respectively.
The maximum degree of slope inclination is 89.26°, indicating the presence of essentially vertical inclinations in the area. About 9% of the area is considered very steep, with slopes greater than 80°. The minimum degree of slope inclination is 0.27° located on valleys and foothills. Nearly half of the study area (48.9%) is within 1° to 10° slope.
2.1.3. Rivers and Streams
The total length of rivers and streams combined is about 92.32 km. Of this length, 38.83 km is from the two major rivers inside the study area.
2.1.4. Water Bodies
The largest body of water is the lake located in the northeast region, which is about 3.24 km2 in area. The rest of the inland water sources have areas that range from 0.08 km2 to 1.04 km2.
2.1.5. Vegetation Cover
The total summer pasture cover is about 146 km2, which is approximately 23% of the total study area. About 8.48% of vegetation cover is located in the lower elevation of 4200 m AMSL, while 40% of the vegetation is at 4400 m AMSL. Less than 1% of the cover is at 5200 m AMSL. Overall, 97% of the areas covered with vegetation are at elevations 4600 m AMSL and below.
2.1.6. Vegetation within 1 km from Rivers and Streams
This layer shows how much percentage of vegetation cover is located near streams and rivers. Close to 50% of the vegetation cover within 1 km from the river is located at 4400 m AMSL. Nearly 90% is between elevations 4200 m and 4400 m AMSL.
2.1.7. Possible Sheep Habitat
This layer shows possible locations of sheep habitat for a specific area. The habitat layer is a result of the integration of the other layers plus the data from occupancy locations of wild sheep and the detailed field transect surveys. The total estimated area found to be possible sheep habitat is about 2.49 km2. This potential habitat is within 1 km from the river, within the 4200 m to 4400 m elevations, and near escape terrains (about 160 m to the next 100 m elevation).
shows the metadata variables used for the generation of the dataset. The boundary extent of the geographic layers is also highlighted in the table. All layers carry the same metadata.
To meet the U.S. Environmental Protection Agency (EPA) and Federal Geographic Data Committee (FGDC) open data metadata requirements, we used EPA Metadata Editor (EME) [15
] to generate a metadata file for each layer. The metadata files can be downloaded together with the layers.
details the metadata of the seven geographic layers, showing the type of the data, the name used in the data, and the description of each data.
In this dataset, contours were derived from NASA’s Shuttle Radar Topography Mission (SRTM) 90 m digital elevation (DEM) dataset that is available to download through the U.S. Geological Survey (USGS) website [16
]. A rescaling of the DEM was performed to the spatial resolution of the other GIS layers (30 m). The slope layer was also a byproduct of the DEM. Rivers and streams were digitized onscreen with the aid of the Landsat image, the high-resolution images from the Google Earth engine, the reconnaissance and field survey, and the expert knowledge of the area.
For the water bodies and the vegetation cover, we utilized the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) image from July 2012 to map out these features. The level-1 terrain-corrected product (L1T) Landsat data was obtained from the USGS Earth Resources Observation and Science (USGS EROS) resource archive [17
We utilized the object-based image analysis (OBIA) for our image classification, guaranteeing a much higher classification accuracy for the vegetation cover [18
]. We integrated variables such as digital elevation model (DEM), Normalized Difference Vegetation Index (NDVI) [19
], Principal Component Analysis (PCA) [20
] utilizing the first two principal components, Modified Soil-adjusted Vegetation Index (MSAVI) [21
], and texture features [22
] into the OBIA. We limit the land use classes to only three: vegetation, water, and barren land as our objective was to specifically delineate the summer vegetation cover only. The image classification showed an overall accuracy of 91.8%, and a kappa statistic of 0.85. For vegetation class alone, the producer’s accuracy (PA) was 90.8% and the user’s accuracy (UA) was 91.6%. As for the texture features, we took advantage of ENVI software’s textural filters that were based on the co-occurrence measures [23
]. We integrated homogeneity (HOM), second moment (M2), dissimilarity (DIS), entropy (ENT), and contrast (CON) in the OBIA. More detailed steps of the image analysis can be read from a complementary paper by Salas et al.
For the generation of the sheep habitat layer, we focused more on the landscape characteristics of the wet and dry meadows from our field surveys, which we believe are the good habitats for sheep. The wet meadow is popular for sheep during the winter season, while the dry upland is used in the spring. The dry upland is characterized by steep terrain, which ewes and lambs use as escape terrain. The wet meadow comprised a flatter slope compared to the dry meadow and the dry upland locations. The dry upland was located at about 4380 m AMSL; 55 m higher than the dry meadow and 76 m higher than the wet meadow. In terms of escape terrains for the sheep, the dry upland was bounded by steeper terrains in the northeast and southwest directions. The location of the dry upland community was less than 160 m to the next 100 m (higher) elevation. Using the spectral information of the pixels where the field datasets were collected, the possible sheep habitat layer was created.
The dataset resulting from this study is critical for future research of the movement of argali in the southeastern Tajik Pamirs, including their dispersal patterns and population dynamics. Additionally, the GIS layers would serve as reference information in developing a management plan for future argali habitats and how these ungulates change their preferred habitat in response to the presence of livestock competition in the area.