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Forests in developing countries are under tremendous pressure because of increasing dependence of human communities on timber, fodder, non-timber forest products, and fuelwood. Nepal’s forests approximately cover 40% of its total geographical area, which experiences very high human dependence. In the present study, we propose an innovative approach of coupling socio-ecological attributes in Kayarkhola watershed in Churia hills of Nepal using remote sensing datasets and field observations to understand the patterns of fuelwood dynamics. Using multi-temporal moderate resolution satellite datasets, we have analyzed the patterns of land use and land cover change from 1990 to 2010 and assessed the effectiveness of community forestry management. The socio-ecological coupling provided quantification of most significant drivers of fuelwood dynamics. We observed low forest loss in community forests in comparison with those falling outside community forests. We conclude that family size, income levels, and percentage of illiterate persons are the most significant individual factors, whereas these factors along with the availability of agricultural land, supply of alternative energy sources are significantly inversely related drivers controlling the fuelwood dynamics. The scenarios developed in this study can be extrapolated in different landscapes to quantify the fuelwood dynamics, which will help in better forest cover management and conservation.

The ‘spectral variation hypothesis (SVH)’ assumes spectral variability as a result of variation in species richness. In the present study, we explore the potential of satellite datasets in identifying the patterns in species richness in part of three global biodiversity hotspots falling in India viz., Himalaya, Indo-Burma, and Western Ghats. We used generalized linear models to correlate remote sensing based vegetation indices (VIs) and physiographic indices (PIs) with plant richness calculated using 1264, 1114, and 1004 field plots across 21 different forest vegetation classes in Himalaya, Indo-Burma, and Western Ghats respectively. Three different vegetation indices ranked highest in explaining the variance in plant richness in the three hotspots. The variance in species richness explained by models based on only VIs was highest (69%, P

Global warming is causing shifts in distribution of plants, leading to alterations in the native flora. In addition, increased intensity and frequency of wildfires is posing threats to Himalayan ecosystems. Modeling a species’ ecological niche and its potential distribution under projected impacts of climate change and distribution of wildfires provides an understanding of the behavior of native flora in altered climatic conditions. In this study, we predicted future distribution of four endemic tree species Pinus roxburghii, Quercus semecarpifolia, Rhododendron arboretum, and Cedrus deodara in western Himalaya under A1B scenario of Special Report on Emission Scenarios for 2030, 2050, and 2080, under two conditions: (i) without wildfire and (ii) with wildfire. We included wildfire occurrence as a predictor variable in the Maxent model along with 35 climate variables, to predict the future distribution of four indicator species. As per the predictions, there will be a significant reduction in the geographic distribution of the indicator species under the ‘with wildfire’ scenario as compared to the ‘without wildfire’ scenario. The future distribution range was shifted towards the northern and north-eastern regions of our study area owing to higher moisture availability. We predicted reduction in the range of C. deodara during 2030, R. arboreum during 2050, and P. roxburghii during 2080, while the distribution of Q. semecarpifolia remained unchanged. Our modeling predicted that climate change could induce reduction, expansion, and shift in the distributions of endemic plant species, which could lead to alteration in the endemic flora of the Himalayas.

Forest fire is one of the major global environmental issues, causing havoc in places as disparate as cold Siberia, tropical Amazon, and the temperate HKH region (Fig. 8.1).

Forests play a vital role in combating climate change and mitigating its effects. In the Hindu Kush Himalaya (HKH), they are an important source of livelihood for the region’s growing population. With forest degradation and deforestation increasing, it has become all the more necessary to have a reliable climate resilient forest management system. At present, lack of precise information on forest degradation and the impacts of climate change on forest ecosystems hinder the conservation, planning and management of forest ecosystems in Nepal. We attempt to tackle this issue in collaboration with Department of Forests and Soil Conservation (DoFSC), Nepal, by providing scientific and reliable data on vulnerability of forests to anthropogenic factors and climate change using geospatial tools and techniques. We introduced a two-way multitier approach in Nepal to support the identification and implementation of adaptation and management strategies with special focus on forest ecosystems. It aims to reduce the vulnerability of forests to climate change and the degradation of forest ecosystems due to anthropogenic drivers. We used multispectral satellite datasets, data on climate trends and projections, and published data on extraction of forest resources in the study area. We then used data mining to quantify the influence of temperature and precipitation on functioning of forests by using MODIS data of net primary productivity, leaf area index, evapotranspiration and climatic trends and projections data. Finally, we overlayed the forest degradation map on forest climate sensitivity map to identify the hotspots of degradation and sensitivity needing immediate attention. These hotspots are defined as “adaptation footprints”, which help decision makers to prioritize their activities within their district. Most of the forest ecosystems in mid-western and far-western Nepal are highly sensitive to observed and predicted impacts of climate change, which need immediate prioritization and management. The products of this study are accessible through a web-based decision support tool, which will help decision makers at district and province level to prioritize the activities of forest management.

Mountain social-ecological systems (MtSES) provide crucial ecosystem services to over half of humanity. However, populations living in these highly varied regions are now confronted by global change. It is critical that they are able to anticipate change to strategically manage resources and avoid potential conflict. Yet, planning for sustainable, equitable transitions for the future is a daunting task, considering the range of uncertainties and the unique character of MtSES. Participatory scenario planning (PSP) can help MtSES communities by critically reflecting on a wider array of innovative pathways for adaptive transformation. Although the design of effective approaches has been widely discussed, how PSP has been employed in MtSES has yet to be examined. Here, we present the first systematic global review of single- and multiscalar, multisectoral PSP undertaken in MtSES, in which we characterize the process, identify strengths and gaps, and suggest effective ways to apply PSP in MtSES. We used a nine-step process to help guide the analysis of 42 studies from 1989 screened articles. Our results indicate a steady increase in relevant studies since 2006, with 43% published between 2015 and 2017. These studies encompass 39 countries, with over 50% in Europe. PSP in MtSES is used predominantly to build cooperation, social learning, collaboration, and decision support, yet meeting these objectives is hindered by insufficient engagement with intended end users. MtSES PSP has focused largely on envisioning themes of governance, economy, land use change, and biodiversity, but has overlooked themes such as gender equality, public health, and sanitation. There are many avenues to expand and improve PSP in MtSES: to other regions, sectors, across a greater diversity of stakeholders, and with a specific focus on MtSES paradoxes. Communicating uncertainty, monitoring and evaluating impacts, and engendering more comparative approaches can further increase the utility of PSP for addressing MtSES challenges, with lessons for other complex social-ecological systems. © 2020 by the author(s).

The changes in natural ecosystems provide opportunity to increase vegetation carbon sink capacity and thereby contribute to mitigation of climate change impacts. The Indian tropics and the large ecological variation within the country afford the advantage of diverse niches and offer opportunities to reveal the role of biotic factors at different levels of organization from populations to ecosystems. The last 4 decades of research and development in the Indian space science community has been primarily application driven in response to the government space programme for national development. The expenditure in R&D over next 5 year suggest that scientific research is higher on the country's agenda. The Indo-UK Terrestrial Carbon Group (IUTCG) comprising both Indian and UK scientists, funded jointly by the Department of Science and Technology, India and the Department of Business, Innovation and Skills organised a workshop to explore ways in which Earth observation data can be effectively utilised in mitigating the impacts of climate change through vegetation management. Effective integration of field observations, collected through various monitoring networks, and satellite sensor data has been proposed to provide country-wide monitoring.

The Kangchenjunga Landscape, an important repository of biodiversity, faces several challenges owing to various drivers of change. Human‒wildlife conflict (HWC) is one of such issue that transcends social, economic, environmental, as well as national and international borders among the three participating countries – Bhutan, India, and Nepal – making it a complex, transboundary issue. Based on the existing literature, earth observation data, and geographic information system, we used maximum entropy along with relevant environmental predictor variables to model and map HWC hotspots. The results suggested that about 19 per cent of the area within the landscape is at high risk of human‒wildlife conflict, with an anthropogenic factor ‒ distance to roads ‒ as the top predictor. Some protected areas are at higher risk than others. The Himalayan subtropical pine forest ecoregion is a high HWC zone (~63 per cent), followed by the Terai‒Duars savannah and grasslands ecoregion (~43 per cent). They also revealed that the low- and mid-elevation zones are prone to conflict due to greater forest fragmentation; patchy protected areas are disconnected from each other, and not big enough for large mammals like elephants and tigers. Human-wildlife conflict is observed to vary across different elevation and climate region of the landscape and highly correlated with forest fragmentation of the midhills. Hence, a holistic approach at the landscape level is needed for tackling human‒wildlife conflict. Connecting good habitats by restoring fragmented inter and intra-country areas would be an effective measure to mitigate human‒wildlife conflict.

This study investigates agricultural land use change in Chitwan, Nuwakot and Lamjung districts of Nepal during 1990 –2017 in relation to rural outmigration. Agriculture in Nepal is characterized by subsistence farming, low productivity, limited access to markets, constraints of terrain, poor economic returns, and vulnerability to natural hazards now exacerbated by climate change. These challenging circumstances are further compounded by several physical, environmental and socioeconomic challenges, including from labour outmigration. Outmigration has steadily increased over the past two decades, and a remittance economy has fuelled urbanization processes as well as transformations in the rural economy. Data was collected from three selected districts, representing two different agro-ecological zones - the mountains and plains (Terai). We use an interdisciplinary approach integrating macro scale and longitudinal geospatial analysis with quantitative econometric causal analysis and participatory qualitative methods. Results show that agricultural land abandonment is higher in mountain areas than in the Terai. The effect of outmigration on agricultural land abandonment also has an important gender dimension: internal outmigration of women has a significant positive effect on agricultural land abandonment. This shows that when men outmigrate, women continue farming leading to feminization of agriculture, but when women migrate in significant numbers, there are only older parents left who are often unable to continue farming. Similarly, and contrary to the general narrative and previous studies, international migration (of both men and women) did not show any significant impact on agricultural land abandonment.

To illuminate future uncertainties and inform strategic plans, this chapter presents three qualitative scenarios for the status of the HKH through 2080. The scenarios (Box 4.1) emerged from a participatory visioning exercise for scenario development (also see Sect. 4.1.2) conducted by the chapter team and HIMAP secretariat between January and September 2016. Over six successive workshops, decision makers and scientists representing HKH countries determined what would constitute a “prosperous” HKH scenario for 2080—along with its less desirable alternatives, business as usual and downhill (Fig. 4.1).

For many decades, non-timber forest products (NTFPs) have been an important livelihood commodity in Nepal as a traditional source of food, fiber, and medicines. However, the importance of NTFPs have been recognized only recently. NTFPs form more than 5% of Nepal’s national gross domestic product and are facing threat due to anthropogenic drivers and changing climate. Understanding of the current distribution and future dynamics of NTFPs is essential for effective conservation planning and management. In the maiden attempt, we used the Maxent model to understand the current and predict the future distribution by 2050 of 10 major NTFPs in Chitwan Annapurna Landscape, Nepal. The prediction accuracy of the models calculated based on the area under curve was high (&gt, 90%) and the prediction by 2050 highlights potential increase in distribution range of seven NTFPs and potential decrease in that of three NTFPs in the study area. The results from our study could play an important role in planning and management of these NTFPs considering their high economic and ecological significance and sensitivity to predicted climate change.

Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively.

Mechanisms to mitigate climate change in tropical countries such as India require information on forest structural components i.e., biomass and carbon for conservation steps to be implemented successfully. The present study focuses on investigating the potential use of a one time, QuadPOL ALOS PALSAR L-band 25 m data to estimate above-ground biomass (AGB) using a water cloud model (WCM) in a wildlife sanctuary in India. A significant correlation was obtained between the SAR-derived backscatter coefficient ( σ °) and the field measured AGB, with the maximum coefficient of determination for cross-polarized (HV) σ ° for Shorea robusta , and the weakest correlation was observed with co-polarized (HH) σ ° for Tectona grandis forests. The biomass of S. robusta and that of T. grandis were estimated on the basis of field-measured data at 444.7 ± 170.4 Mg/ha and 451 ± 179.4 Mg/ha respectively. The mean biomass values estimated using the WCM varied between 562 and 660 Mg/ha for S. robusta ; between 590 and 710 Mg/ha for T. grandis using various polarized data. Our results highlighted the efficacy of one time, fully polarized PALSAR data for biomass and carbon estimate in a dense forest.

Forests offer an important basis for creating and safeguarding more climate-resilient communities over Hindu Kush Himalayan region. The forest ecosystem vulnerability assessment to climate change and developing knowledge base to identify and support relevant adaptation strategies is realized as an urgent need. The multi scale adaptation strategies portray increasing complexity with the increasing levels in terms of data requirements, vulnerability understanding and decision making to choose a particular adaptation strategy. We present here how such complexities could be addressed and adaptation decisions could be either directly supported by open source remote sensing based forestry products or geospatial analysis and modelled products. The forest vulnerability assessment under climate change scenario coupled with increasing forest social dependence was studied using IPCC Landscape scale Vulnerability framework in Chitwan-Annapurna Landscape (CHAL) situated in Nepal. Around twenty layers of geospatial information on climate, forest biophysical and forest social dependence data was used to assess forest vulnerability and associated adaptation needs using self-learning decision tree based approaches. The increase in forest fires, evapotranspiration and reduction in productivity over changing climate scenario was observed. The adaptation measures on enhancing productivity, improving resilience, reducing or avoiding pressure with spatial specificity are identified to support suitable decision making. The study provides spatial analytical framework to evaluate multitude of parameters to understand vulnerabilities and assess scope for alternative adaptation strategies with spatial explicitness.

The change in the tropical forests could be clearly linked to the expansion of the human population and economies. An understanding of the anthropogenic forcing plays an important role in analyzing the impacts of climate change and the fate of tropical forests in the present and future scenario. In the present study, we analyze the impact of natural and anthropogenic factors in forest dynamics in Katerniaghat wildlife sanctuary situated along the Indo-Nepal border in Uttar Pradesh state, India. The study site is under tremendous pressure due to anthropogenic factors from surrounding areas since last three decades. The vegetation cover of the sanctuary primarily comprised of Shorea robusta forests, Tectona grandis plantation, and mixed deciduous forest; while the land cover comprised of agriculture, barren land, and water bodies. The classification accuracy was 83.5%, 91.5%, and 95.2% with MSS, IKONOS, and Quickbird datasets, respectively. Shorea robusta forests showed an increase of 16 km2; while Tectona grandis increased by 63.01 km2 during 1975–2010. The spatial heterogeneity in these tropical vegetation classes surrounded by the human dominated agricultural lands could not be addressed using Landsat MSS data due to coarse spatial resolution; whereas the IKONOS and Quickbird satellite datasets proved to advantageous, thus being able to precisely address the variations within the vegetation classes as well as in the land cover classes and along the edge areas. Massive deforestation during 1970s along the adjoining international boundary with Nepal has led to destruction of the wildlife corridor and has exposed the wildlife sanctuary to human interference like grazing and poaching. Higher rates of forest dynamics during the 25-year period indicate the vulnerability of the ecosystem to the natural and anthropogenic disturbances in the proximity of the sanctuary.

Shorea robusta Gaertn. f. (Sal) is one of the important timber-yielding plants in India, which dominates the vegetation of Terai landscape of Uttar Pradesh state in India forming various communities based on its associations. The present study deals with delineation, mapping and characterization of various communities of Sal (Shorea robusta) forests in Terai landscape of Uttar Pradesh, India ranging across over 16 districts. Field survey and visual interpretation based forest vegetation type classification and mapping was carried out as part of the project entitled ‘Biodiversity characterization at landscape level using remote sensing and GIS’. Indian Remote Sensing-P6 (Resourcesat-1) Linear Imaging Self Scanner-III satellite data was used during the study. The total area covered by different Sal forests was found to be approximately 2256.77 km2. Sal communities were identified and characterized based on their spectral properties, physiognomy and phytosociological characteristics. Following nine Sal communities were identified, delineated and mapped with reasonable accuracy viz., Chandar, Damar, dry plains, moist plains, western alluvium, western alluvium plains, mixed moist deciduous, mixed dry deciduous and Siwalik. It is evident from the area estimates that mixed moist deciduous Sal is the most dominant community in the region covering around (1613.90 km2), other major communities were found as western alluvium plains Sal (362.44 km2), mixed dry deciduous Sal (362.44 km2) and dry plains Sal (107.71 km2). The Terai landscape of Uttar Pradesh faces tremendous anthropogenic pressure leading to deterioration of the forests. Community level information could be used monitoring the status as well as for micro level conservation and planning of the Sal forests in Terai Landscape of Uttar Pradesh.

The development and growth of geospatial techniques offer many advantages and challenges to the study of biodiversity, especially in the present era of climate change. We are now at the beginning of the international decade for biodiversity and by the time we travel through the decade, there would be sea-changes in the measurement and monitoring approaches, database management options, and inter-linked studies on biodiversity. With the onset of geoinformatics techniques comprising remote sensing, global positioning system (GPS), integrative tools, such as GIS, is realized as a complimentary system to ground-based biodiversity studies. Recently, a nationwide biodiversity study at landscape level using geoinformatics modeling techniques for India has been completed. The study has assessed plant diversity using a three-tier approach, wherein six biodiversity attributes (i.e., spatial, phytosociological, social, physical, economical, and ecological) were linked together based on their relative importance to stratify biological richness of forest vegetation (non-agricultural) of India. It has enumerated 7,964 plant species from 20,000 nested quadrate sampling plots of 0.04 ha each, delineated and mapped 120 vegetation classes; and organized the geo-spatial database on bisindia web portal. Here, we have (i) proposed a method to incorporate the fauna component in-line up with the existing methodology and (ii) utilized the GPS-gathered positional information on the distribution of two species (i.e., Medicago sativa and Poa annua to simulate their distribution for the year 2020 (SRES A1-B scenario, IPCC) using Maxent model. The study conducted in a test site of western Himalayas estimated (i) 24% increase in the overall biologically rich areas on supplement of fauna data and (ii) distribution of both the species would tend to increase in favor of shorter cold season. The study highlights the importance of geoinformatics technique-based biodiversity study for its amenability to incorporate any further change or modification, and utility of the geo-spatial biodiversity database for simulating various species distribution scenarios to understand their ecology in today’s fast changing climate for effective conservation prescriptions.

The relationships among diversity, productivity and climate are complex, especially in tropical ecosystems; and are less studied. We studied here the bi- and tri-partite relationships between and among the plant diversity, productivity and climate variables (i.e., temperature, precipitation and moisture) in a tropical ecosystem in India by analyzing three forest types for the year 2010. Comparison of productivity (Carnegie–Ames–Stanford Approach model derived-net primary productivity, NPP) and climate condition with respect to 2001 showed significant increase in NPP and temperature and overall decrease in precipitation and moisture condition in last decade. The NPP for sal forest ranged from 579.4 to 1,142 for the year 2001 and 557.2 to 1231.6 g Cm−2 year−1 for the year 2010. The mean monthly temperature varied from 18 to 21.8°C and 26 to 27°C; and the annual precipitation varied from 15 to 45 and 32 to 76 cm/year for the year 2001 and 2010 respectively. Strong correlation was observed between monthly mean temperature and productivity during 2001, while a decrease was observed during the year 2010. The ecosystem has shown a trend of rapid drying in last decade, triggering more detail studies for understanding of the eco-climatology. In general, sal forest, a natural forest sowed higher diversity and productivity followed by mixed deciduous (MD) forest and teak plantation. Though, areas with higher NPP are well correlated with higher temperature, precipitation and moisture; they seem to be related to species density rather than diversity. However, there is a need to have year-on-year assessments in order to ascertain if this difference represents a real phenomenon rather than an artefact of sampling. The pilot study helps in understanding the complex relationships and is very useful in the fast changing climate.

Wetlands are among the most productive ecosystems in the world and any alterations might lead to changes in their bio-physical, socio-economic and climatic conditions. Wetland dynamics as an index of land use change were studied. Satellite remote sensing was utilized to understand the periodic and seasonal dynamics of Samaspur wetlands using Landsat and RESOURCESAT-1 temporal data. Index-based (i.e., Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDVI)) classification resulted in meaningful discrimination of wetland classes. Results indicate (i) effective water spread areas have increased to optimum capacity at 1990 due to the influence of Sharda canal, (ii) expansion of the agricultural area has led to reduction of the wetland buffer area, and (iii) increase in vegetation biomass due to pesticide-fertilizer runoff and sedimentation load. We also reiterate (i) free availability of the Landsat satellite data in public domain facilitating such monitoring studies and (ii) availability and utility of SWIR band information in wetland classification exercise. The study concludes that policy-driven measures have both long and short term impacts on land use and its natural wetland ecosystems; and the characterizing the later serves as indictor of the former and perhaps vice versa.

International audience; A seamless vegetation type map of India (scale 1: 50,000) prepared using medium-resolution IRS LISS-III images is presented. The map was created using an on-screen visual interpretation technique and has an accuracy of 90%, as assessed using 15,565 ground control points. India has hitherto been using potential vegetation/forest type map prepared by Champion and Seth in 1968. We characterized and mapped further the vegetation type distribution in the country in terms of occurrence and distribution, area occupancy, percentage of protected area (PA) covered by each vegetation type, range of elevation, mean annual temperature and precipitation over the past 100 years. A remote sensing-amenable hierarchical classification scheme that accommodates natural and semi-natural systems was conceptualized, and the natural vegetation was classified into forests, scrub/shrub lands and grasslands on the basis of extent of vegetation cover. We discuss the distribution and potential utility of the vegetation type map in a broad range of ecological, climatic and conservation applications from global, national and local perspectives. We used 15,565 ground control points to assess the accuracy of products available globally (i.e., GlobCover, Holdridge’s life zone map and potential natural vegetation (PNV) maps). Hence we recommend that the map prepared herein be used widely. This vegetation type map is the most comprehensive one developed for India so far. It was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil. The digital map is now available through a web portal (http://bis.iirs.gov.in).

India is one of the 12 mega biodiversity countries of the world, which represents 11% of world's flora in about 2.4% of global land mass. Approximately 28% of the total Indian flora and 33% of angiosperms occurring in India are endemic. Higher human population density in biodiversity hotspots in India puts undue pressure on these sensitive eco-regions. In the present study, we predict the future distribution of 637 endemic plant species from three biodiversity hotspots in India; Himalaya, Western Ghats, Indo-Burma, based on A1B scenario for year 2050 and 2080. We develop individual variable based models as well as mixed models in MaxEnt by combining ten least co-related bioclimatic variables, two disturbance variables and one physiography variable as predictor variables. The projected changes suggest that the endemic flora will be adversely impacted, even under such a moderate climate scenario. The future distribution is predicted to shift in northern and north-eastern direction in Himalaya and Indo-Burma, while in southern and south-western direction in Western Ghats, due to cooler climatic conditions in these regions. In the future distribution of endemic plants, we observe a significant shift and reduction in the distribution range compared to the present distribution. The model predicts a 23.99% range reduction and a 7.70% range expansion in future distribution by 2050, while a 41.34% range reduction and a 24.10% range expansion by 2080. Integration of disturbance and physiography variables along with bioclimatic variables in the models improved the prediction accuracy. Mixed models provide most accurate results for most of the combinations of climatic and non-climatic variables as compared to individual variable based models. We conclude that a) regions with cooler climates and higher moisture availability could serve as refugia for endemic plants in future climatic conditions; b) mixed models provide more accurate results, compared to single variable based models.

Forest fire is one of the key drivers of forest degradation in Nepal. Most of the forest fires are human-induced and occur during the dry season, with ~89% occurring in March, April and May. The inaccessible mountainous terrain and narrow time window of occurrence complicate suppression efforts. In this paper, forest fire patterns are analysed based on historical fire incidence data to explore the spatial and temporal patterns of forest fires in Nepal. Three main factors are involved in the ignition and spread of forest fires, namely fuel availability, temperature and ignition potential. Using these factors a spatially distributed fire risk index was calculated for Nepal based on a linear model using weights and ratings. The input parameters for the risk assessment model were generated using remote sensing based land cover, temperature and active fire data, and topographic data. A relative risk ranking was also calculated for districts and village development committees (VDCs). In total, 18 out of 75 districts were found with high risk of forest fires. The district and VDC level fire risk ranking could be utilised by the Department of Forest for prioritisation, preparedness and resource allocation for fire control and mitigation.

An 18-year-old male presented with a right temporal bone tumour; histology revealed malignant fibrous histiocytoma. Following surgical excision and radiation the tumour recurred. The patient was treated with Vindesine (desacetyl vinblastine amide sulphate) with marked response. Malignant fibrous histiocytomas of the temporal bone are extremely rare; this report suggests that the occasional dramatic response may be obtained by combined modality treatment.