We compared woody plant species distributions across nested spatial scales (local scale to entire Western Himalaya) and explored landscape scale patterns in detail to obtain inferences about the elevational gradient in species richness. Distribution data were compiled for 1100 species in the Western Himalaya, and primary data, comprising 123 species and 47 000 individuals, were collected for a landscape. Correlates of diversity were examined for the five spatial scales, and for different biogeographic groups at the landscape scale. The results indicate multiple mechanisms both within and across scales. At the landscape scale, though the mechanisms explaining unimodal species richness patterns were hard to separate, the underlying correlates of biogeographic groups were more distinct; temperate species richness followed mid‐domain model predictions, and showed a nonlinear relationship with temperature, whereas tropical species richness tracked temperature and area. Simulations demonstrated that models with varying assumptions, while resulting in monotonic, unimodal, or multimodal patterns at local scales, could all lead to unimodal patterns at regional scales when multiple local replicates are aggregated, with a peak in the major ecotone. The turnover or successive accumulation of marginal species in ecotones potentially explains the mid‐elevational peak in this zone. Landscape scale primary data on distribution and abundance could therefore be critical to understanding key aspects of macroecological patterns.

Zoonotic diseases affect resource-poor tropical communities disproportionately, and are linked to human use and modification of ecosystems. Disentangling the socio-ecological mechanisms by which ecosystem change precipitates impacts of pathogens is critical for predicting disease risk and designing effective intervention strategies. Despite the global "One Health" initiative, predictive models for tropical zoonotic diseases often focus on narrow ranges of risk factors and are rarely scaled to intervention programs and ecosystem use. This study uses a participatory, co-production approach to address this disconnect between science, policy and implementation, by developing more informative disease models for a fatal tick-borne viral haemorrhagic disease, Kyasanur Forest Disease (KFD), that is spreading across degraded forest ecosystems in India. We integrated knowledge across disciplines to identify key risk factors and needs with actors and beneficiaries across the relevant policy sectors, to understand disease patterns and develop decision support tools. Human case locations (2014-2018) and spatial machine learning quantified the relative role of risk factors, including forest cover and loss, host densities and public health access, in driving landscape-scale disease patterns in a long-affected district (Shivamogga, Karnataka State). Models combining forest metrics, livestock densities and elevation accurately predicted spatial patterns in human KFD cases (2014-2018). Consistent with suggestions that KFD is an "ecotonal" disease, landscapes at higher risk for human KFD contained diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high PLOS NEGLECTED TROPICAL DISEASES

Article impact statement: Wallach et al.’s framing of compassionate conservation is flawed and impractical and could be dangerous for people, wildlife, and ecosystems.

Smallholder farmer and tribal communities are often characterised as marginalised and highly vulnerable to emerging zoonotic diseases due to their relatively poor access to healthcare, worse-off health outcomes, proximity to sources of disease risks, and their social and livelihood organisation. Yet, access to relevant and timely disease information that could strengthen their adaptive capacity remain challenging and poorly characterised in the empirical literature. This paper addresses this gap by exploring the role of disease information in shaping the adaptive capacity of smallholder farmer and tribal groups to Kyasanur Forest Disease (KFD), a tick-borne viral haemorrhagic fever. We carried out household surveys (n = 229) and in-depth interviews (n = 25) in two affected districts–Shimoga and Wayanad–in the Western Ghats region. Our findings suggest that, despite the generally limited awareness about KFD, access to disease information improved households’ propensity to implement adaptation strategies relative to households that had no access to it. Of the variety of adaptation strategies implemented, vaccination, avoiding forest visits, wearing of protective clothing and footwear, application of dimethyl phthalate (DMP) oil and income diversification were identified by respondents as important adaptive measures during the outbreak seasons. Even so, we identified significant differences between individuals in exposure to disease information and its contribution to substantive adaptive action. Households reported several barriers to implement adaptation strategies including, lack of disease information, low efficacy of existing vaccine, distrust, religio-cultural sentiments, and livelihood concerns. We also found that informal information sharing presented a promising avenue from a health extension perspective albeit with trade-offs with potential distortion of the messages through misinformation and/or reporting bias. Altogether, our findings stress the importance of contextualising disease information and implementing interventions in a participatory way that sufficiently addresses the social determinants of health in order to bolster households’ adaptive capacity to KFD and other neglected endemic zoonoses.