Forest fire is an environmental disaster that poses immense threat to public safety, infrastructure, and biodiversity. Therefore, it is essential to have a rapid and robust method to produce reliable forest fire maps, especially in a data-poor country or region. In this study, the knowledge-based qualitative Analytic Hierarchy Process (AHP) and the statistical-based quantitative Frequency Ratio (FR) techniques were utilized to model forest fire-prone areas in the Himalayan Kingdom of Bhutan. Seven forest fire conditioning factors were used: land-use land cover, distance from human settlement, distance from road, distance from international border, aspect, elevation, and slope. The fire-prone maps generated by both models were validated using the Area Under Curve assessment method. The FR-based model yielded a fire-prone map with higher accuracy (87% success rate; 82% prediction rate) than the AHP-based model (71% success rate; 63% prediction rate). However, both the models showed almost similar extent of ‘very high’ prone areas in Bhutan, which corresponded to coniferous-dominated areas, lower elevations, steeper slopes, and areas close to human settlements, roads, and the southern international border. Moderate Resolution Imaging Spectroradiometer (MODIS) fire points were overlaid on the model generated maps to assess their reliability in predicting forest fires. They were found to be not reliable in Bhutan, as most of them overlapped with fire-prone classes, such as ‘moderate’, ‘low’, and ‘very low’. The fire-prone map derived from the FR model will assist Bhutan’s Department of Forests and Park Services to update its current National Forest Fire Management Strategy.

Polymer-coated rock mineral fertiliser (RMF) has the potential to increase wheat growth and yield; however, its effect on grain protein concentration (GPC) and nitrogen-use efficiency (NUE) remains unclear. Therefore, we examined the efficacy of slow-release RMF combined with microbial consortium inoculant (MI) compared with inorganic fertiliser (IF) with or without the MI to explore their effects on wheat growth, NUE, GPC, grain protein yield and grain yield. The glasshouse experiment was conducted with three factors (fertiliser type (control, RMF and IF), fertiliser rate (0, 23 and 46 mg N kg−1 soil), and MI (with or without)) replicated four times and harvested twice (anthesis and maturity). The treatments were arranged in a randomised complete block design. NUE was higher in plants treated with RMF plus MI compared to IF (with or without MI), likely due to extensive root system, higher shoot N content (at anthesis and maturity) and grain N content in plants treated with RMF plus MI than IF. The application of RMF enhanced grain yield and GPC compared with IF. The grain yield increased due to more grains in RMF-treated than IF-treated plants. The RMF application increased N content in shoots at anthesis and maturity and grain N content, which increased GPC compared to IF-treated plants. RMF in combination with MI can be viewed as a practical approach to assist RMF in supplying nutrients to improve NUE, grain yield and GPC in wheat.

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