Agricultural Practices, Livelihood Dependence and Snow Leopard Conservation in Northern Pakistan: An Evidence-Based Synthesis

Abstract

Pakistan has one of the largest populations of snow leopards in the world, but they are listed as vulnerable by the International Union for Conservation of Nature (IUCN) and their numbers continue to decline. The most frequently cited drivers are poaching, climate change and human-snow leopard conflict (HSC). While these pressures are known from the literature, the particular role of conventional agricultural methods as a root cause of this decline, is rarely studied. This is important for a country like Pakistan where agriculture accounts for a large share of rural livelihoods. Closer inspection of conventional agricultural methods reveals habitat degradation, prey depletion and intensifying human-wildlife conflict as direct consequences. This is most apparent in Gilgit-Baltistan where large-scale agricultural and livestock activity has resulted in increased predation incidents on livestock and, in turn, led to a rise in retaliatory killings. These pressures have been acknowledged in previous research, but agricultural methods are seldom viewed as a key driver, rather than a contextual detail. This paper investigates the effects of agricultural activity on snow leopard habitat and conservation in the region. It draws on secondary literature and a small-scale exploratory Environmental Value System (EVS) survey (n = 48). The survey results are indicative, not representative. A majority of the respondents (62.5%) tend towards technocentrism, favouring technological interventions to balance agricultural productivity and conservation goals. The study contributes to a more holistic understanding of the indirect pathways through which agricultural systems shape snow leopard conservation outcomes in Pakistan and highlights the need for integrated, locally grounded conservation strategies.
JEL Classification Codes: Q13, Q15, Q18, Q54

Conflict of Interest: The authors declare no conflict of interest.
Acknowledgement/Informed Consent: Primary data for this study were collected through a voluntary, anonymous online survey distributed via social media. No personally identifiable or sensitive information was collected from respondents. Given the low-risk, non-invasive nature of the survey instrument, formal institutional ethical clearance was not sought. Participants’ informed consent was implied through their voluntary decision to respond.
AI Declaration/Use of Generative AI: No AI tools were used in this study.
Funding: No
Article History
Submitted: 13 Nov. 2026; Last Revised: 13 July 2026; Accepted: 7 Oct. 2026