The research, led by Kat Douglas of Georg-August-Universität Göttingen together with Zahra Ebrahimi Monfared, Seyedhamed Mirkarimi, Adrian Paterson, and Mahmood Soofi, drew on face-to-face interviews with 292 residents across 30 villages lying within five kilometers of the park boundary. Interviews were conducted between April and November 2022 by two local field researchers, one male and one female, with 71 percent conducted in Turkmen and the remainder in Farsi. Respondents included livestock herders, crop farmers, beekeepers, teachers, and freelancers, reflecting the mixed livelihoods of a landscape where Turks, Kurds, Fars, Baluch, and Sistani communities live alongside some of Iran’s most threatened mammals.

Golestan National Park is a fitting laboratory for such questions. Established in 1957 as Iran’s first biosphere reserve, it covers roughly 91,895 hectares and rises from 450 to 2,411 meters, encompassing Hyrcanian temperate forest, steppe, and semi-arid habitats. The park shelters urial, bezoar goats, red deer, and roe deer, and with them the leopards, wolves, and bears that prey on them or, in the bear’s case, raid the crops and hives of surrounding farms. As human populations and agriculture have expanded through the Hyrcanian forests, negative interactions have intensified, and retaliatory or precautionary killing of carnivores remains a common response to livestock loss.

What sets this study apart is its analytical framework. Rather than treating attitudes as a simple product of economic damage, the team used Bayesian structural equation modelling, a statistical technique capable of estimating multiple direct and indirect pathways simultaneously among latent constructs such as beliefs, norms, and attitudes that cannot be measured directly. The workflow proceeded in two steps: first a confirmatory factor analysis verified that survey items reliably measured their intended constructs, with all retained items loading above 0.40 and reliability coefficients such as McDonald’s omega ranging from 0.78 to 0.83; then a structural model tested how cognitive beliefs, social beliefs, perceived management responsibility, and livestock loss shaped attitudes toward each species separately.

The headline finding is strikingly consistent. Across all three species, cognitive beliefs, the individual’s evaluations, knowledge, and perceptions of carnivores, emerged as the strongest and most reliable predictor of attitudes. For bears the standardized path coefficient reached negative 0.72, for wolves negative 0.63, and for leopards negative 0.48, with 95 percent Bayesian credible intervals that excluded zero in every case. Respondents who felt carnivore conservation was unimportant, or who believed that any carnivore attacking livestock should be killed, held markedly more negative attitudes overall. In other words, the mind, not the wallet, appears to be the primary battleground of coexistence.

Social beliefs, the expectations of family and fellow villagers about retaliatory killing, also pushed attitudes in a negative direction, though their direct effect was weaker and, in the leopard model, the credible interval overlapped zero. More intriguingly, social beliefs were positively associated with cognitive beliefs in all three models, suggesting that when peers endorse killing carnivores, individuals’ own perceptions of carnivores as dangerous are amplified. The authors caution that social desirability bias, in which respondents answer as they believe their community expects, may partly shape such patterns, a well-known hazard of attitudinal surveys. Even so, the indirect pathway points to a clear lever: shifting community-level norms could ripple through individual belief systems and soften attitudes toward predators.

Perhaps the most counterintuitive result concerns livestock loss itself. Included as an observed variable in the leopard and wolf models, it showed only a weak, statistically uncertain relationship with attitudes, with coefficients near zero and credible intervals spanning zero. Reducing the material costs of coexistence, while still vital for household welfare, appears insufficient on its own to change how people feel about carnivores. The bear model dropped livestock loss entirely, a logical choice given that brown bears in northern Iran mainly raid orchards and beehives; one study found 44 percent of negative interactions involved orchards and 32 percent beehives, against just 13 percent livestock attacks. Notably, human-caused mortality records from Iran between 1980 and 2021 show bears were killed more often than wolves or leopards, but chiefly over threats to human life and crops rather than depredation of herds.

Perceived management responsibility added another layer of nuance. The belief that government should capture and relocate carnivores after an attack was associated with more positive attitudes, an effect that was statistically credible for leopards and wolves, though modest in magnitude. Yet in the wolf and bear models this same variable correlated with more negative cognitive beliefs, hinting that institutional expectations and personal belief systems operate somewhat independently. The context matters: in Iran, compensation schemes for wildlife damage are widely described as bureaucratic and rare, and the survey confirmed this, with only 1.7 percent of respondents, five people, reporting ever receiving compensation. Post-attack support limited by funding and paperwork is known to contribute to illegal retaliation.

Several hypothesized drivers refused to stay in the models. Emotions such as fear, pride, and happiness were removed after destabilizing the analysis, though exploratory estimates hinted that positive emotions favored positive attitudes. The authors suspect social desirability bias may be at play, since roughly half of respondents reported minimal fear of leopards, wolves, or bears, a pattern that could reflect genuine tolerance or reluctance to appear afraid. Demographics including age, gender, ethnicity, literacy, and occupation were also excluded, as were legal and participatory variables, the latter perhaps reflecting the fragmented legal framework surrounding conservation in Iran. Women were underrepresented at 16 percent of the sample, a limitation rooted in cultural barriers rather than sampling design, and the authors acknowledge that the final models were deliberately simple, with two items per construct.

The practical implications reach well beyond Golestan. Because cognitive beliefs dominate attitude formation, education programs that explain the ecological role of carnivores, recalibrate perceived danger toward realistic risk, and teach practical protection, from electric fencing and guardian dogs to fox lights and other non-lethal deterrents, may do more for coexistence than compensation checks alone. Because social norms feed individual beliefs, community-wide engagement rather than one-on-one persuasion is likely to be decisive. And because trust in management shapes attitudes, transparent, participatory governance deserves a place alongside any mitigation toolkit. The authors emphasize that their findings are local in origin but plausibly generalizable in mechanism, since belief systems, social norms, and institutional perceptions recur across human-carnivore contexts worldwide. Coexistence, this study suggests, is negotiated less in pastures and orchards than in the shared beliefs of the people who live there.

Subject of Research: Local community attitudes toward large carnivores around Golestan National Park, Iran

Article Title: Claws, consequences and coexistence: Local community attitudes toward large carnivores in mountain landscapes

Article References: Douglas, K., Monfared, Z. E., Mirkarimi, S., Paterson, A., & Soofi, M. (2026). Claws, consequences and coexistence: Local community attitudes toward large carnivores in mountain landscapes. Ambio. https://doi.org/10.1007/s13280-026-02486-9

Image Credits: AI Generated

DOI: 10.1007/s13280-026-02486-9

Keywords: large carnivores, human-wildlife coexistence, Persian leopard, grey wolf, brown bear, Golestan National Park, conservation psychology, Bayesian structural equation modelling, social norms, cognitive beliefs, livestock depredation, Iran

The scale of the underlying crisis is sobering. The 2019 global assessment by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services estimated that roughly one million animal and plant species face extinction. The 2023 IUCN Red List catalogued 150,388 assessed species, of which 42,108 are threatened. Recent global threat assessments indicate that human-wildlife conflict contributes to population declines in approximately 26 percent of all threatened and near-threatened mammal species, primarily through persecution, retaliatory killing, and depredation of crops and livestock. For large carnivores such as tigers, lions, leopards, and wolves, conflict-related mortality is a dominant threat, and it ranks among the top three immediate pressures on elephants, primates, and large herbivores.

Global policy has begun to respond. The Kunming-Montreal Global Biodiversity Framework explicitly calls, under Target 4, for halting human-induced extinctions, supporting species recovery, and managing human-wildlife interactions sustainably to promote coexistence. Yet Batar contends that most conservation practice remains trapped in a binary mindset that separates conflict from coexistence as if they were fixed, opposing categories. That reductionist view, he argues, fails to capture how relationships between people and animals shift over time and space in response to historical legacies, governance decisions, livelihood pressures, cultural values, and the behaviour of wildlife itself.

To replace this binary, the paper introduces a feedback-based dynamic model built around five recurring configurations: conflict, coadaptation, coexistence, coexistence conflict, and harmonious coexistence. Crucially, these states are not stages on a one-way road. Systems can move forward, slip backward, or loop between configurations depending on ecological change, policy shifts, economic incentives, or climate shocks. Four mechanisms—interactions, relationships, impacts, and broader structural drivers—generate reversible feedback loops that determine whether an encounter escalates into violence, settles into tolerance, or matures into something deeper. Stability in any configuration, the model insists, depends on continuous negotiation, adaptive responses, and flexible governance rather than any fixed endpoint.

Each configuration is illustrated with concrete cases. Conflict, the most familiar state, arises when interactions produce negative consequences for either side, as seen in India and Sri Lanka, where agricultural expansion into elephant habitat has intensified crop raiding and retaliatory killing. Coadaptation describes mutual behavioural adjustment: around Gir National Park, pastoralist communities show high tolerance toward Asiatic lions while the cats adjust their movements around villages, and in Kenya the Lion Guardians programme helped shift Maasai norms from retaliatory killing to active stewardship as lions learned to avoid settlements. In northern Botswana, reinforced livestock kraals and consistent night herding reduced losses so effectively that lions began avoiding the protected enclosures altogether.

Coexistence, in this framework, is not the absence of conflict but a managed adaptive balance in which tolerable levels of risk are sustained through evolving interactions, social attitudes, and governance. Community-based livestock insurance and changing media portrayals have helped communities in Nepal and India adjust to snow leopards, while rural Europe has moved from wolf eradication toward compensation schemes and conservation education. But coexistence remains fragile. Climate change, policy reversals, or economic instability can destabilise it, and unresolved grievances can harden into what Batar calls coexistence conflict—a configuration of latent tension beneath apparently calm arrangements. The Nilgiri Biosphere Reserve exemplifies this: elephant conflict has been mitigated, yet communities continue to resent restrictions on land rights, resource access, and exclusion from decision-making, generating passive resistance and legal disputes rather than open confrontation.

At the aspirational summit of the model sits harmonious coexistence, in which wildlife is regarded not as a competing or threatening entity but as an intrinsic part of human cultural and ecological systems. The Satoyama landscapes of Japan, where traditional agriculture and forestry integrate biodiversity into everyday life, and India’s sacred groves, protected through spiritual governance, cultural taboos, and traditional ecological knowledge, demonstrate that such deep integration is possible without heavy-handed state enforcement. Even this state, however, is not permanent; demographic shifts, policy transitions, or weakening institutional support could push systems back toward coexistence conflict or renewed conflict.

Building on these five configurations, the paper proposes the CEAA Framework—Core Principles, Evaluation Criteria, Actions, Achievements—as a heuristic decision-support tool for guiding human-wildlife dynamics toward harmonious coexistence. Its five core principles are deliberately action-oriented. Recognize means identifying the ecological, social, cultural, and institutional drivers shaping local dynamics while acknowledging community knowledge systems. Retain focuses on protecting functional habitats and sustaining traditional livelihoods and governance. Resource demands equitable, sustainable management of shared natural resources. Restore calls for rehabilitating degraded ecosystems and reconnecting fragmented corridors. Reconnect aims to rebuild socio-ecological and cultural linkages between people, wildlife, and landscapes, restoring trust and revitalising traditional relationships with nature.

These principles are paired with evaluation criteria borrowed from programme assessment—relevance, coherence, importance, effectiveness, efficiency, impact, and sustainability—each of which can be operationalised through measurable indicators such as conflict frequency, wildlife movement patterns, cost-benefit analyses, and multi-year monitoring of ecological and social trends. The framework then organises actions at two levels. Institutional and policy actions include empowerment, collaboration, capacity building, and engagement, while societal actions span reconciliation, resilience-building, and a progression from cohabitation through coadaptation and coexistence toward harmonious coexistence. Batar notes that these actions inevitably involve negotiated trade-offs—balancing strict protection with livelihood needs, or prioritising certain species and places when resources are limited—and that the framework prescribes no single optimal solution, instead structuring the identification of options and the monitoring of outcomes over time. He points to India’s Lifestyle for Environment initiative, launched at COP26, as an example of behavioural transformation aligned with this vision.

The framework’s achievements are framed against global milestones: conflict mitigation toward a Nature Positive world by 2030, the UN Decade on Ecosystem Restoration, the Sustainable Development Goals, the Kunming-Montreal Global Biodiversity Framework, and ultimately the UN 2050 Vision of Living in Harmony with Nature. The paper is explicit that detailed, case-specific applications remain future work, and that the framework is conceptual rather than a fixed statistical model—each component can be linked to existing social-ecological datasets, conflict records, participatory assessments, and policy processes. What it offers, in the end, is a shift in perspective: away from treating wildlife as a problem to be managed and toward understanding human-wildlife dynamics as a living, adaptive system that India, and countries facing similar pressures, can deliberately steer toward mutual flourishing.

Subject of Research: A transformative conservation framework for human-wildlife dynamics and coexistence in India

Article Title: A transformative conservation framework for advancing human-wildlife dynamics in India

Article References: A transformative conservation framework for advancing human-wildlife dynamics in India. (n.d.). https://doi.org/10.1007/s44353-026-00075-1

Image Credits: AI Generated

DOI: 10.1007/s44353-026-00075-1

Keywords: human-wildlife conflict, coexistence, transformative conservation, CEAA framework, biodiversity conservation, India, coadaptation, harmonious coexistence, Kunming-Montreal Global Biodiversity Framework, governance, large carnivores, sacred groves

The research, led by Mehnaz Nazir and Tawqir Bashir of Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, together with colleagues at Lovely Professional University and the Zoological Survey of India, combined two years of painstaking fieldwork with sophisticated machine-learning models and landscape connectivity analysis. Between April 2021 and March 2023, the team walked hundreds of kilometres of mountain trails across ten protected areas, recording direct sightings and collecting scats, the latter verified to species level using DNA extraction with a Qiagen Stool Kit. The effort yielded 90 presence records for brown bears, 430 for black bears, and 876 for leopards, a dataset that formed the foundation for one of the most detailed carnivore habitat assessments ever conducted in the region.

What makes the study technically remarkable is its treatment of scale. Habitat selection, the authors emphasise, is not a one-size-fits-all phenomenon; animals respond to environmental features at multiple spatial and temporal scales, from the canopy cover of a single forest stand to the climate of an entire mountain range. To capture this complexity, the researchers calculated the focal mean of 48 ecologically relevant predictor variables, spanning 30 climatic, 9 topographic, 4 land-use, and 5 human-disturbance factors, at eight different spatial scales for brown bears, ranging from 1 to 128 kilometres, a maximum chosen to approximate the species’ average dispersal distance of 108.3 kilometres. For black bears and leopards, they used 17 and 11 radii respectively, reflecting the known dispersal biology of each species.

The modelling framework itself was equally rigorous. The team employed Random Forest, a non-parametric ensemble learning method that builds thousands of decision trees through bootstrap aggregation, an approach particularly well suited to ecological datasets with many predictors and modest sample sizes. Because true absence data are nearly impossible to obtain for cryptic, wide-ranging animals, the researchers generated pseudo-absences, spatially rarefied to a minimum separation of 2 kilometres and excluded from within 2 kilometres of any known presence record, to avoid contaminating the absence class with potentially occupied habitat. Through a two-step optimisation involving t-tests across scales, correlation filtering, and a Model Improvement Ratio based on permuted variable importance, the final models retained 8 variables for leopards, 24 for black bears, and 19 for brown bears. The resulting models performed exceptionally well, with an out-of-bag error rate of just 0.03 and an area under the curve of 0.97.

The ecological findings are as striking as the methodology. For leopards, canopy height emerged as the single most influential variable, with the cats favouring semi-open forests with canopy heights of 10 to 12 metres, south-facing slopes, and moderate precipitation of around 1,000 millimetres annually. Notably, leopards showed a marked tolerance for human presence, remaining suitable even at human population densities of 2,000 to 2,500 people, a finding consistent with the species’ reputation as one of the world’s most adaptable large predators. Black bears, by contrast, keyed in on terrain roughness, selecting rugged mid-elevation slopes above 30 degrees at elevations of 2,000 to 3,000 metres, while avoiding areas with road densities exceeding 0.1 kilometres per square kilometre.

The brown bear told a different story altogether. For this high-altitude specialist, precipitation of the driest month proved to be the dominant driver of habitat selection, a reflection of the critical role moisture plays in sustaining the plant growth and biomass that underpin the bear’s omnivorous alpine diet. Brown bears preferred open meadows with sparse forest cover below 0.2 and low canopy heights of 5 to 8 metres, and they proved acutely sensitive to human disturbance: habitat suitability declined sharply once the human footprint index exceeded 25, and the species tolerated only very low human population densities below 500. In a warming, increasingly crowded Himalaya, that sensitivity is a warning sign, because behavioural or evolutionary adaptations to climate stress tend to unfold over long timescales and may not keep pace with rapid environmental change.

Translating habitat suitability into movement, the researchers converted their models into resistance surfaces using a negative exponential transformation, producing continuous values from 1, representing minimal resistance to movement, to 100, representing near-impermeable terrain. They then deployed the UNICOR connectivity simulator, generating 500 spatially weighted nodes per species and running both cumulative resistance kernel and factorial least-cost path analyses to identify core habitats and dispersal corridors. The results paint a sobering picture of how little of the carnivores’ functional landscape actually falls within formal protection.

For leopards, the total predicted connectivity area spans roughly 12,881 square kilometres, yet only 11.19 percent of it lies inside protected areas. Black bears fare worse: of their 25,678 square kilometres of core connectivity area, just 5.31 percent is formally protected. The brown bear, the most range-restricted and vulnerable of the three, has approximately 25,813 square kilometres of core connectivity area, of which a mere 6.28 percent enjoys protection. Across all species, high-connectivity zones cluster in the Greater Himalayan ranges around Ganderbal, Kupwara, and Bandipora, and in the Pir Panjal range around Shopian, Kulgam, and Baramulla, with the Zabarwan range emerging as a crucial shared corridor linking the two mountain systems through the outskirts of Srinagar.

Perhaps the most consequential finding concerns transboundary connectivity. Least-cost path modelling repeatedly identified corridors extending from Kashmir’s protected areas, including Dachigam National Park, Tral Wildlife Sanctuary, and Kazinag National Park, through largely unprotected landscapes toward Gilgit-Baltistan and northern Pakistan. These routes suggest that the survival of Himalayan carnivore populations may depend on linkages that cross one of the world’s most heavily militarised borders, a reality that demands international cooperation rather than unilateral action. The authors argue that many of the most ecologically significant core areas and corridors lie entirely outside the existing protected area network, in districts such as Kulgam, Budgam, Kupwara, Ganderbal, and Bandipora, and that these spaces warrant urgent inclusion in conservation planning.

The study’s implications extend well beyond Kashmir. The researchers advocate a shift from fortress-style protection toward community-based conservation that aligns corridor protection with local livelihoods, engaging villages, government agencies, and non-governmental organisations in shared stewardship of the landscapes carnivores must traverse. Their integrated habitat-and-connectivity framework, combining multi-scale Random Forest modelling with resistance kernel and least-cost path analysis, offers a scalable template for conserving wide-ranging species in other fragmented mountain systems worldwide. The authors also acknowledge limitations, notably the seasonally restricted brown bear dataset, which reflects only summer habitat use because the species’ high-altitude haunts remain snowbound and inaccessible for much of the year. Even so, the message is unambiguous: protected areas remain vital refugia, but on their own they are not enough. The future of the Himalaya’s great carnivores will be decided in the corridors between them, in the unprotected valleys and ridgelines where bears and leopards still move, and in the political will to keep those pathways open.

Subject of Research: Habitat selection and landscape connectivity of large carnivores in the Kashmir Himalaya and the effectiveness of protected areas

Article Title: Are protected areas enough? Habitat selection and connectivity for large carnivore conservation in the Himalaya

Article References: Are protected areas enough? Habitat selection and connectivity for large carnivore conservation in the Himalaya. (n.d.). https://doi.org/10.1007/s10113-026-02662-3

Image Credits: AI Generated

DOI: 10.1007/s10113-026-02662-3

Keywords: Himalaya, large carnivores, protected areas, habitat connectivity, Himalayan brown bear, Himalayan black bear, leopard, Random Forest, least-cost paths, wildlife corridors, Kashmir, conservation planning