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.
This article is an attempt to assess the invasion risk from the most noxious alien plant species using the GPS recorded locations and environmental variables. The invasion risk was modelled by combining the three ecological niche modelling algorithms- DesktopGARP, Openmodeller DesktopGARP and Maxent after validating their accuracies. The accuracies ranged from moderate to good in all the algorithms, for all six species. The result showed Ageratina adenophora and Ageratum conyzoides as highly invasive species both in terms of area coverage and the ecological tolerance range of the study site. It was also indicative that, irrespective of the species, agricultural lands are most susceptible to invasion among all other types of land uses in the study area.
Mass flowering of Borinda grossa occurred in 2015 in the central region of Bhutan. To assess its growth after natural regeneration, a field study was carried out in the Busa community forest (CF) located in Sephu gewog, Wangduephodrang district. A total of 39 sample plots of quadrat size 10 × 10 m were laid out in a study site of 80 hectares using systematic sampling to carry out bamboo inventory. The soil samples were collected using composite soil sampling from all the plots. Sample plots were categorized into bamboo presence and absence plots. Growth of bamboo was assessed in association with environmental factors. Wilcoxon signed rank test was used to compare environmental parameters between bamboo presence and absence plots. The result indicated significant differences in elevation, canopy cover and soil electrical conductivity. The growth of bamboo by diameter, height and count was highest in the elevation range between 2700 to 2800 m under medium canopy cover of 20 to 40% in loamy-sandy soil. Maximum number of bamboos was found in north and west facing slopes
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