Expanding or shrinking? range shifts in wild ungulates under climate change in Pamir-Karakoram mountains, Pakistan

Climate change is expected to impact a large number of organisms in many ecosystems, including several threatened mammals. A better understanding of climate impacts on species can make conservation efforts more effective. The Himalayan ibex (Capra ibex sibirica) and blue sheep (Pseudois nayaur) are economically important wild ungulates in northern Pakistan because they are sought-after hunting trophies. However, both species are threatened due to several human-induced factors, and these factors are expected to aggravate under changing climate in the High Himalayas. In this study, we investigated populations of ibex and blue sheep in the Pamir-Karakoram mountains in order to (i) update and validate their geographical distributions through empirical data; (ii) understand range shifts under climate change scenarios; and (iii) predict future habitats to aid long-term conservation planning. Presence records of target species were collected through camera trapping and sightings in the field. We constructed Maximum Entropy (MaxEnt) model on presence record and six key climatic variables to predict the current and future distributions of ibex and blue sheep. Two representative concentration pathways (4.5 and 8.5) and two-time projections (2050 and 2070) were used for future range predictions. Our results indicated that ca. 37% and 9% of the total study area (Gilgit-Baltistan) was suitable under current climatic conditions for Himalayan ibex and blue sheep, respectively. Annual mean precipitation was a key determinant of suitable habitat for both ungulate species. Under changing climate scenarios, both species will lose a significant part of their habitats, particularly in the Himalayan and Hindu Kush ranges. The Pamir-Karakoram ranges will serve as climate refugia for both species. This area shall remain focus of future conservation efforts to protect Pakistan’s mountain ungulates.

Erosion of the Himalaya-Karakoram recorded by Indus Fan deposits since the Oligocene

The Cenozoic erosion history of the Himalaya-Karakoram, which is a function of tectonically driven uplift and monsoon climatic evolution in South Asia, remains elusive, especially prior to the Miocene. Here, we present a multiproxy geochemical and thermochronological analysis of the oldest samples available from the Arabian Sea, which we used to investigate the erosion history of the Himalayan and Karakoram orogenic system. The Indus Fan records rapid and sustained erosion of the Himalayan-Karakoram mountains from before 24 Ma (ca. 30) to ca. 16 Ma concurrent with changing provenance from the Indian (Himalayan) and Eurasian plates. Our data, combined with previous studies of younger Indus Fan deposits, indicate that the mid-to-late Cenozoic erosion history of the Himalayan-Karakoram mountains is overall consistent with a vigorous monsoonal climate from the late Oligocene to middle Miocene and with changes in global climate in the late Miocene, whereas erosion and deposition are relatively insensitive to changes in sources and rock erodibility. Although tectonic processes were active throughout, we suggest that the erosional signatures of the Himalayan-Karakoram mountains from the Indus Fan largely preserve a record of climate changes since the Oligocene.

Spatiotemporal Variability in the Glacier Snowline Altitude across High Mountain Asia and Potential Driving Factors

The glacier snowline altitude (SLA) at the end of the melt season is an indicator of the glacier equilibrium line altitude and can be used to estimate glacier mass balance and reconstruct past climate. This study analyzes the spatiotemporal variability in glacier SLA across High Mountain Asia, including the Altai Mountains, Karakoram Mountains, Western Himalayas, Gongga Mountains, Tian Shan, and Nyainqentanglha Mountains, over the past 30 years (1989–2019) to better elucidate the state of these mountain glaciers. Remote-sensing data are processed to delineate the glacier SLA across these mountainous regions, and nearby weather station data are incorporated to determine the potential relationships between SLA and temperature/precipitation. The mean SLAs across the Altai and Karakoram mountains ranged from 2860 ± 169 m to 3200 ± 152 m and from 5120 ± 159 m to 5320 ± 240 m, respectively, with both regions experiencing an average increase of up to 137 m over the past 30 years. Furthermore, the mean glacier SLAs across the Western Himalayas and Gongga Mountains increased by 190–282 m over the past 30 years, with both regions experiencing large fluctuations. In particular, the mean glacier SLA across the Western Himalayas varied from 4910 ± 190 m in 1989 to 5380 ± 164 m in 2000, and that across the Gongga Mountains varied from 4960 ± 70 m in 1989 to 5330 ± 100 m in 2012. Correlation analyses between glacier SLA and temperature/precipitation suggest that temperature is the primary factor influencing glacier SLA across these High Mountain Asia glaciers. There is a broad increase in glacier SLA from the Altai Mountains to the Karakoram Mountains, with a decrease in glacier SLA with decreasing latitude across the Himalayas; the maximum SLA occurs near the northern slopes of the Western Himalayas. The glacier SLA is lower on the eastern side of the Tibetan Plateau and exhibits a longitudinal distribution pattern. These results are expected to provide useful information for evaluating the state of High Mountain Asia glaciers, as well as their response and feedback to climate change.

Spatio-temporal variation analysis of snow cover in China-Pakistan Economic Corridor based on remote sensing technology

Based on the MODIS10A2 snow product data from 2001 to 2019, the characteristics of annual variation, interannual variation and spatial distribution of snow cover in China Pakistan Economic Corridor from 2001 to 2019 are analyzed by using remote sensing technology. The result shows that: the snow-cover in a year generally starts from the middle of October, and the snow cover area reaches the maximum value in January of the next year, and reaches the minimum value in July. From 2001 to 2019, the snow area of China-Pakistan Economic Corridor generally showed a decreasing trend. The distribution of snow in the China-Pakistan Economic Corridor is extremely uneven. The northern area is obviously more than that in the south. The mountainous and plateau areas are with high frequency of snow cover, and the plains are areas with low frequency of snow-cover. Permanent snow-cover is relatively low. Few, mainly concentrated in the Karakoram Mountains, in terms of distribution range, mainly distributed in 4452-8378 m.

Consolidating the Randolph Glacier Inventory and the Glacier Inventory of China over the Qinghai-Tibetan Plateau and Investigating Glacier Changes Since the mid-20^th Century

Glacier retreat in the Qinghai-Tibetan Plateau (QTP), the "third pole of the world", has attracted the attention of researchers worldwide. Glacier inventories in the 1970s and the 2000s provide valuable information to infer changes in individual glaciers. However, individual glacier volumes are either missing, incomplete or have large errors in these inventories, and thus, the use of these datasets to investigate changes in glaciers in QTP in the past few decades has become a challenge, particularly in the context of climate change. In this study, individual glacier volume data in the Randolph Glacier Inventory version 4.0 (RGI 4.0, 1970s) and the second Glacier Inventory of China (GIC-Ⅱ, 2000s) are recalculated and consolidated using a slope-dependent algorithm based on elevation datasets for the QTP. The two consolidated inventories (The data are available under https://doi.org/10.11888/Glacio.tpdc.270390 (Liu, 2020). For the time of review, the data will be accessible through the following review link https://data.tpdc.ac.cn/en/data/4b88e394-0eb4-44c4-aa38-32aeb614daff/.) are validated by comparing the observed and estimated glacier data reported in the literature. The two consolidated glacier inventories are then compared for different mountains over the QTP to detect changes in glacier areas, volumes, fragmentation status, etc. during the past 3–4 decades. Based on the results, the slope-dependent algorithm performed well in computing individual glacier volumes and other elements, compared with the widely used volume-area scaling which often leads to overestimation in the interior Plateau and underestimation in other areas of the QTP in both RGI 4.0 and GIC-Ⅱ. The comparison of the two inventories reveals a total area of glaciers in the QTP of approximately 59026.5 km2 in the RGI 4.0 and 44301.2 km2 in the GIC-Ⅱ. The total glacier volume is 4045.9 km3 in the GIC-Ⅱ compared with 4716.7 km3 in the RGI 4.0. The results suggest a significant retreat and melting of glaciers in the QTP. However, variations are observed in different glaciers. The Karakoram Mountains contain the largest number of surged glaciers, while the highest level of retreat is observed in the Gandise Mountains. An increase in the fragmentation index is observed in the northern mountains, particularly the Pamir Plateau, which displays the highest trends of glacier movement and deformation. The glacier volumes decrease mainly on south-westward aspects and increase to various extents on the other aspects of most mountains. The consolidation of the glacier inventories and the findings of the analysis performed in this study provide important databases for future glacier-related studies, particularly for investigating the effects of climate change on glaciers in the past and projecting future effects.