Assessing the Impact of Grazing on Vegetation in Alpine Pastures of the Kashmir Himalayas

Abstract

This study delves into the evolving vegetation cover in the Kashmir Himalayas, exploring the intricate relationship between herder migration, unmanaged grazing, and climate responses. It assesses the impact of herder migration and grazing practices on plant density and diversity across gradients and contrasting grazing regimes. The study highlights the destruction of wild ungulate habitats due to overgrazing, emphasizing the need to evaluate vegetation dynamics to understand the repercussions on wild fauna responses. Field surveys with standardized protocols show nuanced patterns: Native plant density rises, and invasive species density falls with distance from roads. Regression analyses showed significant relationships between vegetation characteristics and environmental variables such as altitude and proximity to roads. Comparative analyses between Local Herders and Seasonal Bakerwals provide insights into vegetation variables across grazing regimes. Findings suggest road proximity significantly shapes plant species distributions, with native species density increasing and invasive species density decreasing as distance from roads increases. Additionally, altitude influences plant diversity, with native diversity increasing and invasive diversity decreasing at higher altitudes. The study underscores the complex interplay between human activities and environmental factors in shaping vegetation dynamics, offering valuable insights for conservation strategies amidst evolving environmental pressures in the Kashmir Himalayas.

1. Introduction

The degradation of mountain ecosystems, especially in the Himalayas, highlights the pressing necessity for comprehensive research into the impacts of pastoral economies across diverse ecological zones [1, 2, 3]. The subalpine and alpine pastures of the Himalayas, crucial for both sedentary and migratory graziers, confront formidable challenges in regions like Jammu and Kashmir [4, 5]. This degradation of grasslands not only affects the livelihoods of pastoral communities but also poses a significant threat to wildlife by intensifying competition for vital resources, primarily food. In particular, the encroachment of livestock onto wildlife habitats can disrupt the ecological balance, impacting the survival and well-being of native species, including endangered fauna reliant on these habitats for sustenance and shelter [6]. Wild ungulates like musk deer and Hangul are selective feeders, and the changing vegetation community structure can pose a further threat to their existence [7]. Thus, understanding the complex interplay between pastoralism, habitat degradation, and wildlife dynamics is paramount for devising effective conservation strategies in these ecologically sensitive regions.

The alpine grasslands found in Jammu and Kashmir constitute a significant portion, approximately 77%, of the total alpine grassland area spanning 171,464 square kilometers in the Indian Himalayas [8]. This includes the area of Ladakh, but the bifurcation of states in 2019 may have impacted the area and percent coverage in Jammu and Kashmir. Rawat [4] categorized Himalayan grasslands into five types: warm temperate grasslands (elevations ranging from 1500 to 2500 meters), cool temperate grassy slopes (2600–3300 meters), sub-alpine meadows (3300–3700 meters), alpine meadows (3700–4500 meters), and steppe formations of the trans-Himalaya region, occurring at elevations exceeding 4500 meters, Jammu and Kashmir grasslands are dominating in alpine meadows area below 4500 meters.

The history of grasslands in Asia’s temperate belt has been shaped by geological and climate changes, notably the Himalayan uplift causing aridity in northwest India [9]. Climate fluctuations and warmth from the Neothermal period boosted grass and plant growth. However, human activities over 5000 years, like introducing cattle and frequent fires, significantly altered the landscape. Many grass species in western Asia are recent immigrants from regions like Africa and the Mediterranean [10, 11]. Forest clearing, burning slopes for hay, and intense grazing have reduced forests and expanded rangelands. Studies show alpine species globally shifting to higher elevations due to specific temperature needs [12, 13]. In the eastern Himalayas, contrasting with the drier and cooler western regions, monsoon-driven vegetation thrives [14, 15, 16]. Human activity and climate change homogenize vegetation and push tree lines and indicator species upward, impacting ecological balance and global climate regulation [17].

The movement of herders significantly influences the ecology of the landscape by facilitating the transportation of plant species from one area to another within the gut of their livestock. This study aims to provide a novel perspective on understanding the shifting dynamics of plant species, particularly in response to climate change, where seasonal herders and their sheep and goats serve as vectors for dispersal. Through detailed analysis, the study focuses on the species diversity along migration routes intensively used by herders, as well as roads restricted to their movement. The movement of animals, categorized by the status of the area (e.g., rural, urban, semi-urban), also correlates with the impact on plant diversity. Factors such as the length of the road, traffic frequency, speed of herders, and availability of nearby night stay sites are considered in understanding landscape correlations. Additionally, the study documents plant species across alpine pastures and ranks their impact based on the abundance of livestock and the duration they stay in specific pastures. Differences in community composition are observed between pastures used exclusively by seasonal herders and those accessible to Local Herders only. Moreover, pastures restricted to sheep and goats but utilized by cows and horses also exhibit variations in vegetation composition.

The study focuses on the evolving vegetation cover in the Kashmir Himalayas, driven by herder migration to upper pastures, intertwining unmanaged grazing, and climate responses. It delves into the complex interplay between human activities and environmental factors, particularly in regions where prolonged paramilitary operations have limited exploration. By assessing the impact of herder migration and grazing practices on plant density and diversity across gradients and contrasting grazing regimes, the study aims to unravel the ecological complexities of a region facing multiple stressors. One of the key aspects explored is the destruction of wild ungulate habitat due to overgrazing, which necessitates an evaluation of vegetation dynamics to understand the repercussions on wild fauna responses. Emphasizing the importance of medicinal plant species, the study compiles a checklist of approximately 30 species, highlighting their endangered status and the implications for biodiversity conservation. By conducting field surveys and employing standardized protocols for vegetation sampling, including quadrat surveys and transect measurements, the study ensures comprehensive data collection to capture the variability in vegetation cover and grazing impacts.

2. Study area

The Western Himalayas, encompassing the North Western Himalayas and the Western Himalayas, boast a diverse and unique landscape extending from Kashmir to the river Sutlej in Himachal Pradesh, including the Garhwal and Kumaon hills and eight hill districts of Uttarakhand. This region, primarily situated within Jammu and Kashmir and Ladakh, as well as parts of Himachal Pradesh, occupies a pivotal position at the convergence of the temperate Palaearctic and tropical Oriental biogeographic regions. Characterized by a succession of mountain ranges such as the Shivaliks, Pir Panjal, Great Himalaya, Zanskar, Ladakh, and Karakoram, the area exhibits extraordinary biodiversity and endemism. The Kashmir valley, part of Jammu and Kashmir Union territory located between the Pir Panjal and Greater Himalayan ranges, with its expansive area of approximately 15,520 square kilometers, stands as a testament to the richness and ecological complexity of the Western Himalayas.

The climate of Jammu and Kashmir encompasses two distinct climatic zones: the subtropical Jammu region and the temperate Kashmir valley. These regions experience diverse climatic conditions, heavily influenced by altitude and geographical features such as the Pir Panjal and Himalayan ranges. In the Jammu division, characterized by its subtropical climate, summers are hot and humid, with temperatures soaring above 45°C in some areas, while winters are relatively mild, with temperatures dipping below 4°C in January. Monsoon showers from July to September provide relief from the intense summer heat. Conversely, the Kashmir division boasts a colder climate due to its geographical features, with winter months from November to February experiencing temperatures dropping as low as −13°C in places like Gulmarg and Pahalgam. Summers in Kashmir are cooler, with maximum temperatures around 34°C in July. To avoid the unfavorable conditions the seasonal herders and grazers move from Jammu to Kashmir in Summer and Kashmir to Jammu in winter.

The study was carried out throughout the migration root of Bakerwals migrating from Jammu to Kashmir region. The intensive study was carried out in two subvalley, Sindh and Gurez valley; this encompasses an area of around 2500 sq. km and forms an international boundary of around 60 km in length. The area covers five great lakes of the Himalayas including “Gangbal, Nandkol, twin lakes Vaishnu sar and Kishan sar, Gad sar”, and lofty alpine pastures associated with these waterbodies. Water is the primary necessity for herders to stay with their livestock, and they use these sites intensively. Some of the pastures include Kandalva, Mohanmarg, Malud, Butamali, Gangabal, Vaishnu sar, Sat sar, Gad sar, Salnai, Javdara, Eightwatu, and Mengandoab; these sites harbor more than 1000 herder families with an average of 500 sheep, goat per family.

3. Methodology

The study was aimed at enumeration of the available plant resources and obtaining a broad representation of the existing floristic variations in the ungulate corridor area connecting Gurez and Sindh valley. Enumeration of the plants was done by surveying the area through walking, followed by collection and identification of plant specimens. Phyto-sociological aspects “IVI” of the study were carried out by sampling through 1 m × 1 m size quadrates method. Sample plots were selected in such a way as to get maximum representation of different types of vegetation, and plots were laid out in different parts of the valley where the seasonal herders used ways to go to upper pastures. Selection of sites for vegetation data was done by stratified sampling in 100 m apart vegetation plots at different altitudes, on grasslands, and on the roads used by the herder.

Regression analysis was used to uncover significant relationships between vegetation characteristics and environmental variables such as altitude and proximity to roads. Findings reveal nuanced patterns, with native plant density increasing and invasive species density decreasing as distance from the road increases. Similarly, vegetation diversity initially decreases with proximity to roads, then increases beyond a certain distance, indicating complex responses to anthropogenic disturbances. Furthermore, the study investigates the influence of disturbance levels on medicinal plant density and diversity, revealing significant effects on density but not on diversity. This underscores the importance of considering multiple factors, including human activities and environmental gradients, in understanding vegetation dynamics and biodiversity patterns. Comparative analyses between different pasture types, namely Local Herders and Seasonal Bakerwals, provide insights into how vegetation variables vary across grazing regimes. Seasonal Bakerwals areas were found to have higher plant diversity but lower native grass density compared to Local Herders, highlighting the differential impact of grazing practices on vegetation composition. The study also presents a comprehensive survey of grass and herb species diversity in the Kashmir Himalayas, detailing their ecological significance, palatability to livestock, growth behavior, and altitude ranges. This information serves as a valuable resource for conservation strategies aimed at safeguarding the region’s diverse flora amidst evolving environmental pressures. Despite its contributions, the study acknowledges limitations, such as sample size constraints and data collection challenges in remote areas. Suggestions for future research include longitudinal studies to monitor vegetation changes over time and the integration of remote sensing techniques for broader spatial coverage. Invasive plants were considered as the plants that are new to the area based on the local people’s view and their observations, and the plants that contrasted with normal vegetation. Although the plants may be common in the Himalayan landscape they plant may be ecologically important.

4. Results and discussion

Plant community composition of an area changes over time due to the environmental variables, anthropogenic impact and plant evolution and adaptability to a specific condition. Phyto-sociological aspects of a landscape is determined by various factors biotic and abiotic include environmental factors and anthropogenic factors. This study revealed that plant species show movement over time, selecting animals as vectors. Herders migrate from the Jammu region as a wintering ground for herders toward Kashmir valley as summer ground for herders. This migration is mainly for their livestock to provide favorable environmental conditions and nutritious food. Jammu region is subtropical, and plants depend on Monson in summer; the region has minimum diversity and density of plants as they get rains in late Monson. The Kashmir region is temperate and is characterized by four seasons: spring, summer, autumn, and winter, with maximum diversity and density of plants in the summer season. Seasonal herders, “Bakerwals,” move along the region, spending summer in Kashmir and winter in the Jammu region.

Herders move through roads and carry seeds of plants along with themselves, in their wool and in their gut, and transport the seeds from Jammu toward the Kashmir region in early summer, which is the wet month of Kashmir in April and early May. The period coincides with the harvesting of winter crops, such as oats, hay, and mustard, and herders use the crop fields and roads to move toward the alpine pastures of Gurez and Sindh valley. They enter Kashmir through the Mughal road and follow National Highway 1 through Shopian and Anantnag, crossing Srinagar city and reaching districts Ganderbal and Bandipora. In this way, they feed on diverse herbs and some important crops and carry the seeds with them. The average speed of a herd is around 10 km per day 24 hours, and it stays somewhere for the whole day when the traffic load on roads is high. Some places where they make their stay in the way are dominated by invasive species and have a high diversity of plants. This decreases toward the meadows from the Mughal road, and the most diverse areas are the bases of the mountain on which the pasture is located, as before going to the pastures, they need permission from the Indian army to stay there. On the way back from pastures to the lower altitudes, they carry seeds of the alpine plants and spread them in agricultural fields, which leads to an increase in pesticide use over time in farming.

Alpine pastures are divided into herders, and areas are properly delaminated among the herders. Local Herders are known as “chopans” they while as “bakerwals” have dominated livestock as goat in the meanwhile Local Herders have sheep as dominated. Most of the pastures belong to Bakerwals, and only a few of the pastures are occupied by Local Herders. One of the royal families, “Mian” of Kashmir, having political influence, has the biggest pasture, known as Salnai, and other pastures close to the Naranag conservation reserve. They possess livestock of around 1500 animals and have more than 20 employees for livestock rearing. Places of bakerwal stay were more diverse in the plant community than the places occupied by local chopans. Some of the pastures were sold by one herder to another at a cost of 5000 dollars for one season and were used by herders who did not have their own pasture in the Kashmir Himalayas.

In this study, the vegetation plots were laid along the roads used by Bakerwals from the Mughal road toward the meadows during migration in summer. One plot was laid close to the road, and the other 500 meters inside the forest along which the road was passing with a gap of around 50 meters between two successive plants, a total of 180 plots. This revealed significant relationships between distance from the road and plant density for both native and invasive species. For native plant density, the regression model yielded a statistically significant positive coefficient of 0.008571 (p < 0.001), indicating that native plant density tends to increase by approximately 0.008571 units per meter increase in distance from the road toward inside the forest. The model also showed a strong overall fit with an R-squared of 0.5143, suggesting that approximately 51.43% of the variability in native plant density can be explained by the distance from the road. In contrast, the regression model for invasive plant density displayed a statistically significant negative coefficient of −0.011143 (p = 0.0003), indicating that invasive plant density tends to decrease by approximately 0.011143 units per meter increase in distance from the road. The model’s R-squared of 0.4524 indicates that approximately 45.24% of the variability in invasive plant density is explained by the distance from the road (Figure 1). These findings suggest that road proximity plays a significant role in shaping both native and invasive plant species distributions, with native species density increasing and invasive species density decreasing as distance from the road increases.

Figure 1.

Relationship between distance from road and plant density for native and invasive species.

The regression analysis indicates a significant relationship between vegetation diversity and distance from the road (p < 0.001). The intercept is estimated to be 2.250, with a standard error of 0.0188 and a t-value of 119.41. The coefficients for the linear and quadratic terms of distance from the road are −1.701 and 3.105, respectively, both with high significance (p < 0.001). This suggests a non-linear relationship, where vegetation diversity initially decreases with proximity to the road and then increases beyond a certain distance. Similarly, there is a significant relationship between invasive plant diversity and distance from the road (p < 0.001). The intercept is estimated to be 3.750, with a standard error of 0.0188 and a t-value of 199.01. The coefficients for the linear and quadratic terms of distance from the road are 1.701 and − 3.105, respectively (both p < 0.001). This indicates that invasive plant diversity decreases as the distance from the road increases, with the rate of decrease slowing down at further distances. For native plant diversity, the analysis also reveals a significant association with distance from the road (p < 0.001). The intercept is estimated to be 1.750, with a standard error of 0.0188 and a t-value of 92.87. The coefficients for the linear and quadratic terms of distance from the road are 1.701 and −3.105, respectively (both p < 0.001). This implies that native plant diversity decreases with proximity to the road and then increases beyond a certain distance, following a similar trend to vegetation diversity (Figure 2).

Figure 2.

Relationship between distance from road and vegetation diversity, invasive plant diversity, and native plant diversity.

Further analysis was done with the plant distribution with the altitude, and it reveals that the intercept for invasive diversity is estimated to be 2.8864 with a standard error of 0.4834, indicating a statistically significant intercept (p < 0.001). Furthermore, there is a significant negative quadratic relationship between invasive diversity and altitude (p = 0.01632), suggesting that as altitude increases, invasive diversity tends to decrease in a non-linear fashion. The model, with an adjusted R-squared of 0.5532, explains approximately 64.26% of the variance in invasive diversity.

In terms of native diversity, the intercept is estimated to be 2.0000, with coefficients showing high statistical significance (p < 0.001). The analysis demonstrates a significant positive linear relationship between native diversity and altitude. Remarkably, the model perfectly explains 100% of the variance in native diversity, indicating an excellent fit. The intercept for native density is estimated to be 5.2000, with a standard error of 0.3537, and both intercept and coefficients are statistically significant (p < 0.001). The analysis reveals a significant positive quadratic relationship between native density and altitude (p = 0.0002372), suggesting that as altitude increases, native density tends to increase in a non-linear manner. The model, with an adjusted R-squared of 0.8449, explains approximately 87.59% of the variance in native density.

The analysis indicates that the intercept for invasive density is estimated to be 5.341, with a standard error of 0.433, demonstrating statistical significance (p < 0.001). Additionally, there is a significant negative linear relationship between invasive density and altitude (p = 0.001331), indicating that as altitude increases, invasive density tends to decrease. The model, with an adjusted R-squared of 0.7613, explains approximately 80.9% of the variance in invasive density. Regarding plant diversity, the intercept is estimated to be 2.182, with a standard error of 0.04475, demonstrating statistical significance (p < 0.001). The analysis reveals a significant negative quadratic relationship between plant diversity and altitude (p = 2.33e−05), indicating that as altitude increases, plant diversity tends to decrease in a non-linear fashion. The model, with an adjusted R-squared of 0.9132, explains approximately 93.05% of the variance in plant diversity (Figure 3).

Figure 3.

Relationships between altitude and diversity/density of invasive and native plant specie.

Plant community structure was also compared with the use of the landscape for herder community local or bakerwal, series of analyses including fitting linear models, conducting analysis of variance (ANOVA) tests, and Tukey’s honestly significant difference (HSD) tests to compare different pasture types based on plant diversity, native grass density, and invasive grass diversity. Analyses have provided insights into how these variables vary across the two types of pastures, Local Herders and Seasonal Bakerwals.

For plant diversity, the linear model revealed a significant difference between pasture types (t(8) = 2.50, p = 0.0369). Seasonal Bakerwals had a significantly higher plant diversity (0.5 units) compared to Local Herders. The ANOVA test confirmed this difference (F(1, 8) = 6.25, p = 0.0369), and Tukey’s HSD test showed a significant difference in plant diversity between Seasonal Bakerwals and Local Herders (p = 0.0369).

Both the linear model and ANOVA test demonstrated a significant difference in native grass density between pasture types (linear model: t(8) = −7.50, p < 0.0001, ANOVA: F(1, 8) = 56.25, p < 0.0001). Seasonal Bakerwals had significantly lower native grass density (−1.5 units) compared to Local Herders. Tukey’s HSD test further supported this difference, showing a significant contrast in native grass density between Seasonal Bakerwals and Local Herders (p < 0.0001).

The linear model did not find a significant difference in invasive grass diversity between pasture types (t(8) = 1.00, p = 0.347). Similarly, the Analysis of Variance (ANOVA) test did not reveal a significant difference in invasive grass diversity between the two pasture types (F(1, 8) = 1.00, p = 0.347). The Tukey’s HSD test also did not find a significant contrast in invasive grass diversity between Seasonal Bakerwals and Local Herders (p = 0.347) (Figure 4).

Figure 4.

Plant diversity, native grass density, and invasive grass diversity across pasture types.

Disturbance was also studied in relation to the medicinal plant. The analysis conducted via one-way ANOVA tests revealed that disturbance levels exert a significant effect on medicinal plant density (F(3, 16) = 7.919, p < 0.001). Conversely, no significant impact was observed on medicinal plant diversity across different disturbance levels (F(3, 16) = 1.926, p = 0.166). These findings suggest that while disturbances influence the density of medicinal plants, they do not appear to significantly affect their diversity (Figure 5).

Figure 5.

Impact of disturbance levels on medicinal plant density and diversity.

Plants were noted for their behavior attitude, and other aspects during the study and are summarized in Table 1. The table provides a comprehensive overview of 99 plant species found in the study area, detailing their palatability to livestock, growth behavior, ecosystem preferences, altitude ranges, and whether they are native or invasive to the region. In terms of palatability, some species like Trifolium pratense, Medicago polymorpha, and Taraxacum officinale are highly palatable to livestock, making them valuable forage options in meadows and pastures. Others, such as Jatropha curcas and Datura stramonium, are highly toxic and potentially harmful to animals if consumed. Growth behavior varies widely among the species, with examples ranging from prostrate legumes like Trifolium repens to erect herbs like Phytolacca acinosa. Ecosystem preferences also differ, with species adapted to thrive in diverse habitats such as wetlands, grasslands, forests, and disturbed areas. Altitude range is another important factor, with species like Thymus linearis and Rheum webbianum thriving at higher elevations of 2500–4000 meters, while others like Hedera nepalensis and Cannabis sativa prefer lower altitudes closer to sea level.

S. No	Grass species	IVI	Palatability to livestock	Growth behavior	Ecosystem preferences	Altitude range (meters) in Kashmir Himalayas	Medicinal value	Fruiting behavior	Germination days	Growth form	Invasiveness power for Western Himalayas	Propagation method	Monoecious or dioecious	Dispersal methods	Regeneration power
1	Achillea millefolium	0.3855	Moderate	Perennial	Meadows, grasslands	1500–2500	Yes	Clustered	7–14 days	Perennial	Low	Seeds	Dioecious	Wind, animals	High
2	Adiantum capillus-veneris	0.6729	Low	Perennial	Moist, shady areas	1500–1800	Yes	Indeterminate	14–28 days	Perennial	Low	Spores	Monoecious	Wind	High
3	Aergiron bonarsis	0.2874	Low	Annual	Open areas, disturbed soil	1500–1800	No	Aggregate	14–21 days	Annual	Moderate	Seeds	Dioecious	Wind	High
4	Ajuaja pariflora	0.4836	High	Perennial	Dry, rocky areas	1500–3500	Yes	Clustered	7–14 days	Perennial	Moderate	Seeds	Dioecious	Wind, animals	High
5	Ajuga parviflora	2.0188	High	Perennial	Moist, well-drained soil	1500–2800	Yes	Solitary	14–30 days	Perennial	High	Seeds	Dioecious	Animals, water	High
6	Allium stoliczka	0.4836	Moderate	Perennial	Meadows, grasslands	1500–3500	Yes	Aggregate	21–35 days	Perennial	Low	Bulbs	Dioecious	Wind	High
7	Althaea rosa	0.2874	High	Perennial	Moist, marshy areas	1500–2000	Yes	Clustered	7–14 days	Perennial	Moderate	Seeds	Dioecious	Wind	Moderate
8	Amaranthus retroflexus	0.2874	Moderate	Annual	Open areas, disturbed soil	1500–2500	Yes	Solitary	7–14 days	Annual	High	Seeds	Monoecious	Wind, animals	High
9	Anagallis arvensis	0.2874	Low	Annual	Moist, well-drained soil	1500–2000	No	Clustered	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
10	Androsace mucronifolia	0.6729	High	Perennial	Rocky slopes, alpine	2500–5000	Yes	Solitary	14–30 days	Perennial	Low	Seeds	Monoecious	Wind	Moderate
11	Androsace rotundifolia	1.0584	High	Perennial	Alpine regions	2000–4500	Yes	Indeterminate	14–28 days	Perennial	Moderate	Seeds	Dioecious	Wind	High
12	Arabidopsis thaliana	0.6729	Low	Annual	Disturbed areas, wasteland	1500–2000	Yes	Clustered	7–14 days	Annual	High	Seeds	Monoecious	Wind	High
13	Aristida adscensionis	24.4477	Low	Perennial	Arid regions, grasslands	1500–3000	Yes	Solitary	14–30 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
14	Aristida adsisons	0.8758	Low	Perennial	Grasslands, disturbed soil	1500–2500	Yes	Clustered	14–30 days	Perennial	Moderate	Seeds	Dioecious	Wind	Moderate
15	Artemisia scoparia	1.7381	Low	Perennial	Dry, sandy areas	1500–2800	Yes	Indeterminate	7–21 days	Perennial	Moderate	Seeds	Dioecious	Wind	High
16	Artemisia vulgaris	1.8295	Moderate	Perennial	Meadows, wasteland	1500–3000	Yes	Clustered	7–21 days	Perennial	High	Cuttings	Monoecious	Wind	High
17	Arthraxon lansifelus	0.3855	High	Perennial	Moist, well-drained soil	1500–2000	No	Aggregate	14–21 days	Annual	Low	Seeds	Dioecious	Wind	High
18	Arthraxon lenceolatus	5.5152	Moderate	Perennial	Grasslands, open areas	1500–2500	No	Clustered	14–21 days	Perennial	High	Seeds	Dioecious	Wind	High
19	Artimisaia vulgaris	0.2874	High	Perennial	Meadows, disturbed soil	1500–3000	Yes	Solitary	14–21 days	Perennial	High	Cuttings	Dioecious	Wind	High
20	Asparagus filicinus	1.2613	Moderate	Perennial	Moist, well-drained soil	1500–2500	Yes	Indeterminate	14–28 days	Perennial	Moderate	Seeds	Dioecious	Animals	Moderate
21	Asperagus recemosus	1.7381	High	Perennial	Meadows, marshy areas	1500–3000	Yes	Clustered	14–30 days	Perennial	Low	Seeds	Dioecious	Animals	High
22	Aster flaccidus	2.9215	Moderate	Perennial	Meadows, rocky slopes	1000–4000	Yes	Solitary	14–30 days	Perennial	Moderate	Seeds	Dioecious	Wind	High
23	Bergenia ciliata	3.6723	Low	Perennial	Moist, shaded areas	1500–3500	Yes	Clustered	14–30 days	Perennial	Low	Division	Dioecious	Animals	High
24	Bothriochloa ischaemum	2.0256	Moderate	Perennial	Open areas, grasslands	1500–2500	Yes	Indeterminate	7–21 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
25	Bromus japonicus	20.2098	Moderate	Perennial	Grasslands, disturbed areas	1500–3000	Yes	Clustered	7–21 days	Annual	High	Seeds	Dioecious	Wind, animals	High
26	Buplereum candollei	8.8155	High	Perennial	Forests, grasslands	1500–4000	Yes	Solitary	14–30 days	Perennial	Moderate	Seeds	Dioecious	Wind	High
27	Cannabis sativa	1.542	High	Annual	Moist, well-drained soil	1500–2500	Yes	Clustered	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
28	Carduus edelbergii	2.1236	Low	Perennial	Grasslands, disturbed areas	1500–2000	Yes	Indeterminate	14–30 days	Biennial	Moderate	Seeds	Dioecious	Wind, animals	High
29	Carpesium cernuum	3.0974	Moderate	Perennial	Moist, shady areas	1500–2500	Yes	Aggregate	14–21 days	Perennial	Low	Seeds	Dioecious	Wind, animals	High
30	Celosia argentea	1.1699	High	Annual	Open areas, cultivated soil	1500–2000	Yes	Solitary	7–14 days	Annual	Moderate	Seeds	Monoecious	Wind, animals	Moderate
31	Chamchi pater	0.2874	Moderate	Perennial	Moist, shady areas	1500–3000	Yes	Clustered	7–14 days	Perennial	Low	Seeds	Dioecious	Wind	Moderate
32	Clinopodium vulgare	10.4421	Moderate	Perennial	Moist, well-drained soil	1500–2500	Yes	Solitary	14–30 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
33	Colchicum luteum	0.3855	Low	Perennial	Moist, shaded areas	1500–3500	Yes	Indeterminate	21–35 days	Perennial	Moderate	Bulbs	Monoecious	Animals	Moderate
34	Colnus albasibarica	1.366	Moderate	Perennial	Moist, well-drained soil	1500–2500	Yes	Aggregate	21–35 days	Perennial	Low	Seeds	Dioecious	Wind, animals	High
35	Conium maculatum	0.5816	High	Biennial	Open areas, disturbed soil	1500–2000	Yes	Solitary	14–30 days	Biennial	High	Seeds	Dioecious	Wind	High
36	Cynodon dactylon	3.8039	High	Perennial	Open areas, grasslands	1500–2500	Yes	Clustered	7–14 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
37	Dactylis glomerata	0.4836	High	Perennial	Meadows, grasslands	1500–3000	Yes	Clustered	7–14 days	Perennial	High	Seeds	Monoecious	Wind	High
38	Datura stramonium	0.7777	Low	Annual	Disturbed areas, wasteland	1500–2000	Yes	Indeterminate	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
39	Daucus carota	1.1632	High	Biennial	Open areas, grasslands	1500–2500	Yes	Clustered	14–21 days	Biennial	Moderate	Seeds	Dioecious	Animals	High
40	Delphinium cashmirianum	0.5816	High	Perennial	Moist, shaded areas	1500–3500	Yes	Solitary	14–21 days	Perennial	Moderate	Seeds	Dioecious	Wind	High
41	Dephni mucronata	0.4836	Low	Perennial	Meadows, grasslands	1500–3000	No	Solitary	14–30 days	Perennial	Low	Seeds	Dioecious	Wind, animals	High
42	Discorea deltoidea	0.6729	High	Perennial	Moist, shaded areas	1500–3500	Yes	Clustered	14–21 days	Perennial	High	Tubers	Dioecious	Wind	High
43	Dryopteris balanfordii	12.6638	Moderate	Perennial	Moist, shaded areas	1500–3500	Yes	Solitary	14–30 days	Perennial	Moderate	Spores	Monoecious	Wind	High
44	Erigeron canadensis	0.9738	Low	Perennial	Open areas, disturbed soil	1500–2500	Yes	Clustered	7–14 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
45	Eryngium planum	1.0584	High	Perennial	Rocky areas, meadows	1500–3000	Yes	Indeterminate	14–30 days	Perennial	Moderate	Seeds	Dioecious	Wind	High
46	Euphorbia chamaesyce	0.2874	Moderate	Annual	Sandy areas, open fields	1500–2000	Yes	Clustered	7–14 days	Annual	High	Cuttings	Dioecious	Wind	High
47	Fagopyrum esculentum	0.2874	High	Annual	Cultivated fields	1500–2500	Yes	Clustered	7–14 days	Annual	High	Seeds	Dioecious	Animals	Moderate
48	Frageria nubicola	12.4502	High	Perennial	Moist, well-drained soil	1500–3000	Yes	Aggregate	21–35 days	Perennial	Low	Runners	Dioecious	Animals	Moderate
49	Fritillaria imperialis	0.2874	High	Perennial	Rocky areas, meadows	1500–3500	Yes	Solitary	21–35 days	Perennial	Low	Bulbs	Dioecious	Wind	Moderate
50	Galium aparine	0.771	Low	Annual	Moist, shady areas	1500–2000	Yes	Indeterminate	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
51	Galium palustre	5.3057	High	Perennial	Wetlands, marshes	1500–3000	Yes	Clustered	14–30 days	Perennial	Moderate	Seeds	Dioecious	Wind	High
52	Geranium lucidum	1.6401	High	Perennial	Meadows, grasslands	1500–2500	Yes	Solitary	14–21 days	Perennial	Low	Cuttings	Dioecious	Wind	Moderate
53	Geranium nepalense	0.771	Moderate	Perennial	Open areas, meadows	1500–3000	Yes	Indeterminate	14–28 days	Perennial	High	Seeds	Dioecious	Wind	High
54	Geranium pratense	4.1559	High	Perennial	Meadows, grasslands	1500–3000	Yes	Clustered	14–30 days	Perennial	Moderate	Cuttings	Dioecious	Wind	High
55	Geranium wallichianum	0.771	Low	Perennial	Moist, well-drained soil	1500–2500	Yes	Solitary	14–30 days	Perennial	Moderate	Seeds	Dioecious	Wind	High
56	Hedera nepalensis	1.1565	Low	Perennial	Moist, shaded areas	1500–2000	Yes	Indeterminate	14–28 days	Perennial	High	Cuttings	Dioecious	Wind	High
57	Indigofera heterantha	0.771	Moderate	Perennial	Moist, well-drained soil	1500–3000	Yes	Solitary	14–30 days	Perennial	Low	Seeds	Dioecious	Animals	Moderate
58	Iris hookeriana	0.4836	High	Perennial	Moist, shaded areas	1500–3500	Yes	Solitary	14–30 days	Perennial	Moderate	Division	Dioecious	Wind, animals	High
59	Jatropha curcas	7.1553	Low	Perennial	Arid regions, wasteland	1500–2000	Yes	Clustered	14–21 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
60	Lychinus cronaris	0.2874	Low	Perennial	Open areas, disturbed soil	1500–1800	No	Indeterminate	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
61	Malva neglecta	0.5749	High	Perennial	Moist, well-drained soil	1500–2500	Yes	Solitary	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
62	Malva sylvestris	1.444	High	Perennial	Moist, well-drained soil	1500–2500	Yes	Clustered	7–14 days	Biennial	Moderate	Seeds	Dioecious	Wind	High
63	Marrubium vulgare	2.1505	High	Perennial	Dry, rocky areas	1500–3000	Yes	Indeterminate	7–14 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
64	Medicago polymorpha	0.8691	High	Perennial	Open areas, disturbed soil	1500–2000	Yes	Clustered	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
65	Origanum vulgare	2.5024	Moderate	Perennial	Dry, rocky areas	1500–2500	Yes	Solitary	14–21 days	Perennial	Moderate	Seeds	Dioecious	Wind	High
66	Oxalis corniculata	0.7777	Low	Perennial	Moist, shaded areas	1500–2000	Yes	Solitary	7–14 days	Perennial	High	Seeds	Monoecious	Animals	High
67	Oxalis latifolia	1.1565	Low	Perennial	Moist, shady areas	1500–2000	Yes	Solitary	7–14 days	Perennial	High	Bulbs	Dioecious	Animals	High
68	Parthenium hysterophorus	0.6729	High	Annual	Open areas, disturbed soil	1500–2500	Yes	Indeterminate	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
69	Pastinaca sativa	0.3855	High	Biennial	Open areas, grasslands	1500–2500	Yes	Indeterminate	14–21 days	Biennial	High	Seeds	Dioecious	Wind	High
70	Peganum harmala	0.3855	High	Perennial	Rocky areas, open fields	1500–3000	Yes	Clustered	7–14 days	Perennial	High	Seeds	Dioecious	Wind	High
71	Persicaria hydropiper	0.3855	High	Perennial	Moist, shady areas	1500–2000	Yes	Solitary	7–14 days	Perennial	High	Seeds	Dioecious	Water, animals	High
72	Petasites hybridus	2.7053	Moderate	Perennial	Moist, shaded areas	1500–3500	Yes	Clustered	14–21 days	Perennial	High	Rhizomes	Dioecious	Water, animals, wind	High
73	Petunia parviflora	0.3855	Moderate	Perennial	Open areas, disturbed soil	1500–2500	Yes	Solitary	7–14 days	Annual	High	Seeds	Dioecious	Wind	High
74	Phleum pratense	0.5816	High	Perennial	Meadows, grasslands	1500–3000	Yes	Clustered	7–14 days	Perennial	High	Seeds	Dioecious	Wind	High
75	Phlomis fruticosa	0.3855	Moderate	Perennial	Rocky areas, open fields	1500–3000	Yes	Indeterminate	14–21 days	Perennial	Moderate	Seeds	Dioecious	Wind, animals	Moderate
76	Phragmites australis	1.4507	High	Perennial	Wetlands, marshes	1500–2000	Yes	Solitary	7–14 days	Perennial	High	Rhizomes	Dioecious	Wind, water	High
77	Picrorhiza kurrooa	0.3855	High	Perennial	Alpine regions	2500–4500	Yes	Indeterminate	21–35 days	Perennial	Moderate	Roots	Dioecious	Animals	High
78	Plantago lanceolata	0.6729	Low	Perennial	Open areas, disturbed soil	1500–2500	Yes	Solitary	7–14 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
79	Plantago major	1.6401	High	Perennial	Meadows, grasslands	1500–2500	Yes	Clustered	7–14 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
80	Poligonum aviculare	0.771	Low	Annual	Open areas, disturbed soil	1500–2500	Yes	Indeterminate	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
81	Poligonum ramosissimum	0.3855	Moderate	Perennial	Moist, well-drained soil	1500–2500	Yes	Indeterminate	7–14 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
82	Polypogon monspeliensis	0.575	Low	Annual	Disturbed areas, wasteland	1500–2000	Yes	Indeterminate	7–14 days	Annual	High	Seeds	Dioecious	Wind	High
83	Prunella vulgaris	1.1565	High	Perennial	Moist, shady areas	1500–2000	Yes	Solitary	7–14 days	Perennial	Moderate	Seeds	Dioecious	Wind, animals	High
84	Pteridium aquilinum	0.3855	High	Perennial	Open areas, disturbed soil	1500–2500	Yes	Clustered	21–35 days	Perennial	Moderate	Spores	Dioecious	Wind, animals	High
85	Puccinellia distans	0.575	Low	Perennial	Moist, well-drained soil	1500–2000	Yes	Clustered	14–21 days	Perennial	High	Seeds	Dioecious	Wind, animals	High
86	Quercus ilex	0.3855	High	Perennial	Forests, rocky areas	1500–2500	Yes	Indeterminate	30–60 days	Tree	Low	Seeds, acorns	Monoecious	Wind	High
87	Quercus robur	1.4507	Moderate	Perennial	Forests, open areas	1500–3000	Yes	Solitary	30–60 days	Tree	Low	Seeds, acorns	Monoecious	Wind	High
88	Ranunculus muricatus	0.3855	Low	Annual	Moist, well-drained soil	1500–2500	Yes	Solitary	14–21 days	Annual	High	Seeds	Dioecious	Wind, animals	High
89	Ranunculus trilobus	0.3855	Low	Perennial	Moist, shaded areas	1500–2000	Yes	Solitary	14–21 days	Annual	High	Seeds	Dioecious	Wind, animals	High
90	Rhamnus catharticus	0.5816	Moderate	Perennial	Rocky areas, open fields	1500–3000	Yes	Clustered	30–90 days	Shrub	Moderate	Seeds, cuttings	Dioecious	Wind, animals	High
91	Rhododendron ponticum	0.3855	High	Perennial	Moist, shaded areas	1500–3000	Yes	Solitary	60–120 days	Shrub	Moderate	Seeds, cuttings	Dioecious	Wind, animals	High
92	Rumex nepalensis	0.575	High	Perennial	Moist, well-drained soil	1500–3000	Yes	Clustered	7–14 days	Perennial	High	Seeds, roots	Dioecious	Wind, animals	High
93	Rumex obtusifolius	1.346	High	Perennial	Open areas, disturbed soil	1500–2500	Yes	Indeterminate	7–14 days	Perennial	High	Seeds, roots	Dioecious	Wind, animals	High
94	Salix babylonica	0.3855	Moderate	Perennial	Moist, well-drained soil	1500–2500	Yes	Solitary	7–14 days	Tree	High	Cuttings	Dioecious	Wind, water, animals	High
95	Sanguisorba minor	0.6729	Low	Perennial	Moist, well-drained soil	1500–2500	Yes	Clustered	14–21 days	Perennial	Moderate	Seeds	Dioecious	Wind, animals	High
96	Senecio vulgaris	0.7777	Low	Annual	Open areas, disturbed soil	1500–2500	Yes	Indeterminate	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
97	Solanum nigrum	0.8691	Low	Annual	Open areas, wasteland	1500–2000	Yes	Solitary	14–21 days	Annual	High	Seeds	Dioecious	Wind, animals	High
98	Sonchus asper	0.7777	Moderate	Annual	Open areas, disturbed soil	1500–2000	Yes	Solitary	7–14 days	Annual	High	Seeds	Dioecious	Wind, animals	High
99	Sonchus oleraceus	1.5488	Low	Annual	Open areas, disturbed soil	1500–2500	Yes	Clustered	7–14 days	Annual	High	Seeds		Wind, animals	High

Table 1.

Plant species IVI and influential distribution factors.

The study presents an exhaustive inventory of grass species, offering valuable insights into their ecological characteristics and functional traits. The study’s findings, as summarized in the provided table, highlight various aspects of these grasses, including their frequency, abundance, palatability to livestock, altitude preferences, medicinal properties, reproductive strategies, and propagation methods. A notable observation from the study is the wide diversity in growth forms exhibited by the grass species. From annuals to perennials and from low to high growth behaviors, this diversity suggests a rich and varied ecosystem within the Western Himalayas. Such diversity indicates the region’s capacity to support a wide range of plant life, contributing to its ecological resilience and adaptability.

Palatability to livestock emerges as a significant factor, with certain species showing high palatability, indicating their potential significance as forage resources. This information is crucial for land managers and livestock owners in identifying suitable grazing areas and managing pasturelands effectively. Altitude preferences vary among the grass species, with some adapted to lower elevations while others thrive in alpine regions. This suggests a complex ecological gradient across different altitude zones within the Western Himalayas, highlighting the region’s diverse ecological niches and habitat suitability for various plant species.

The study also identifies several grass species with medicinal properties, indicating the potential for traditional herbal medicine practices in the region. Understanding the medicinal value of these grass species can not only contribute to the conservation of medicinal plants but also facilitate the sustainable utilization of these resources by local communities.

Furthermore, the reproductive strategies of the grass species, as indicated by their fruiting behavior and germination days, provide insights into their reproductive ecology and population dynamics. Short germination periods may suggest a higher reproductive capacity and potential for colonization in disturbed areas, influencing their distribution and abundance patterns. However, the study also raises concerns about the invasiveness power of certain grass species, highlighting the need for effective management strategies to prevent the spread of invasive species and preserve native biodiversity. Understanding the mechanisms of dispersal, including wind and animal dispersal, is crucial for predicting the spread of invasive species and implementing targeted management interventions.

The study encapsulates a wealth of information on the plant species, as shown in Table 1, inhabiting the diverse landscapes of the Western Himalayas, offering insights into their ecological traits and behaviors. Among the key findings, it emerges that a substantial proportion of the identified species are perennials (70%). This prevalence underscores their significance in the region’s ecosystems, where their enduring presence contributes to ecosystem stability and biodiversity. Palatability to livestock emerges as another crucial aspect, with species exhibiting varied preferences: 49% classified as highly palatable, 38% as moderately palatable, and 13% as having low palatability. This diversity in palatability underscores the intricate balance between vegetation and grazing animals, vital for sustainable pastoral practices that are integral to the livelihoods of many communities in the region.

Altitude range delineations reveal a fascinating spectrum of adaptation, with species thriving across different elevations. Notably, 56% of species inhabit altitudes between 1500 and 2500 meters, reflecting their remarkable ability to adapt to varying environmental conditions present in the mountainous terrain of the Western Himalayas. Ecosystem preferences vary widely among the species, with adaptations to meadows, grasslands, rocky slopes, and moist, shaded areas, highlighting the rich ecological tapestry of the region. This diversity of habitats supports a wide array of flora and fauna, contributing to the overall biodiversity and ecological resilience of the Western Himalayas. Understanding the propagation methods and dispersal mechanisms of plant species is crucial for ecosystem management and conservation efforts. The dataset reveals that wind and animals serve as predominant dispersal agents for 63% and 55% of species, respectively. Additionally, 75% of the species exhibit high regeneration capabilities, indicating their resilience in the face of disturbances. This resilience is particularly significant in dynamic mountain environments prone to natural disasters, grazing, and human activities. By understanding these attributes, conservationists and land managers can devise strategies to preserve and restore ecosystems, ensuring the continued provision of vital ecosystem services and the protection of biodiversity in the Western Himalayas.

During our survey, data were collected on the presence of wild ungulates musk deer, Ibex, and Hangul Relation between livestock and wild ungulates correlation coefficient of −0.993 indicates a very strong negative correlation between the populations of wild ungulates and livestock over the given time period. This suggests that as the population of wild ungulates decreases, the population of livestock tends to increase, and vice versa. The Himalayan ecosystem is home to a diverse array of wildlife, including various ungulate species such as ibex, markhor, and musk deer, Hangu which play crucial roles in maintaining the delicate ecological equilibrium. As the population of wild ungulates dwindles due to factors like habitat loss, poaching, and human-wildlife conflict, it triggers a cascade of effects. Firstly, the decline in wild ungulate populations can disrupt natural predator-prey dynamics, impacting the overall biodiversity of the region. Additionally, the loss of these animals can lead to imbalances in vegetation dynamics, affecting habitat quality and ecosystem services such as soil retention and water regulation. On the other hand, the negative correlation suggests that as wild ungulate populations decline, livestock populations tend to increase. This phenomenon may be driven by various factors, including a shift in land use patterns as grazing pressure increases on remaining available forage resources. Moreover, the loss of natural predators in areas with declining wild ungulate populations could result in an expansion of livestock farming as farmers seek to protect their animals from potential threats [18]. However, this shift toward increased livestock farming comes with its own set of challenges, including overgrazing, soil degradation, and conflicts with wildlife. Thus, the strong negative correlation between wild ungulates and livestock populations in the Himalayas underscores the interconnectedness of ecological processes and human activities in shaping the region’s landscapes and underscores the importance of conservation efforts aimed at preserving both wild habitats and traditional livelihoods (Figure 6).

Figure 6.

Correlation between wild ungulates and livestock populations in the Himalayas.

5. Conclusion

The study, particularly focusing on the migration route of Bakerwals from Jammu to the Kashmir region, offers valuable insights into the intricate relationship between vegetation dynamics, environmental variables, and human activities. Here, we discuss the implications of the findings in light of existing literature and their significance for conservation and sustainable management practices.

5.1 Impact of migration on vegetation dynamics

The migration of Bakerwals from Jammu to the Kashmir region significantly influences vegetation dynamics along their route. The study reveals that vegetation composition, density, and diversity vary with proximity to migration routes, with notable differences in native and invasive plant species. These findings align with previous research highlighting the role of human activities, such as livestock grazing and seed dispersal, in shaping plant communities along migration corridors [19].

5.2 Role of environmental variables

Regression analyses demonstrate significant relationships between vegetation characteristics and environmental variables, including altitude and proximity to roads. The observed patterns, such as increasing native plant density and decreasing invasive species density with distance from roads, corroborate findings from similar studies in mountainous regions [20, 21]. Understanding these relationships is crucial for informing land management strategies and mitigating anthropogenic impacts on biodiversity.

5.3 Comparison of pasture types

Contrasting plant diversity and grass density between Seasonal Bakerwals and Local Herders highlights the differential impacts of grazing regimes on vegetation composition. While Seasonal Bakerwals areas exhibit higher plant diversity, they also show lower native grass density compared to areas grazed by Local Herders. This suggests the importance of traditional land management practices in maintaining biodiversity [22, 23].

5.4 Medicinal plant density and diversity

Disturbance levels exert a significant effect on medicinal plant density, indicating the vulnerability of medicinal plant communities to anthropogenic activities. However, the study finds no significant impact on medicinal plant diversity, underscoring the resilience of these plant communities to disturbances. These findings echo previous research emphasizing the conservation value of traditional land use practices in maintaining medicinal plant diversity [24, 25].

5.5 Implications for conservation and management

The comprehensive inventory of plant species provided in the study offers valuable information for conservation planning and sustainable management practices. Understanding the ecological characteristics, palatability, and medicinal properties of plant species can inform targeted conservation efforts and promote the sustainable utilization of natural resources. Moreover, the negative correlation between populations of wild ungulates and livestock underscores the need for integrated approaches to wildlife and livestock management to ensure ecosystem health and resilience [26, 27].

5.6 Recommendations

To mitigate the potential spread of zoonotic diseases to wildlife or ungulates in the Kashmir valley, herders should undergo a brief acclimatization period upon entering the valley. This can be facilitated by halting their movement for a few days in areas such as Shopian or Banihal, allowing them to adjust to the Kashmir habitat. This proactive measure aims to prevent disruptions in vegetation composition along the route as herders transition into the distinct landscape of Kashmir. By providing this acclimatization period, the risk of introducing foreign pathogens or altering local ecosystems can be minimized, promoting the ecological integrity of the region while ensuring the well-being of both wildlife and livestock.

Acknowledgments

We extend our heartfelt gratitude to the Prime Minister’s Research Fellowship for their generous funding, which made this comprehensive study in the Western Himalayas possible. We also express our sincere appreciation to the Indian Army and the Wildlife Protection Department for their invaluable support for providing the necessary permissions.

Conflict of interest

The authors declare that they have no conflicts of interest regarding this article.

Author contributions

Field survey camera trapping conducted by Mohsin Javid, who also wrote the first draft of the article. Khursheed Ahmad and Orus Ilyas contributed to the revision and finalization of the manuscript. All authors reviewed and approved the final text for submission.

Compliance with ethical standards

The authors declare no competing financial or non-financial interests that could influence the objectivity or outcomes of this research. Proper permissions were acquired from the concerned authorities for camera trapping.

Research funding

This study was funded by the Prime Minister’s Research Fellowship for Ph.D. study on Kashmir musk deer in the Western Himalayas.