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The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher's alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between ∼ 40,000 and ∼ 53,000, i.e., at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of ∼ 19,000-25,000 tree species. Continental Africa is relatively depauperate with a minimum of ∼ 4,500-6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa.

Smallholder farmers are among the most vulnerable to climate shocks in Sri Lanka. Lack of education and technical skills, poverty, risks inherent to agricultural investments, limited assets, and financial capital are major reasons for low investments in enhancing adaptive capacity. The study explores the use of agricultural technologies in improving smallholder resilience to water-related disasters and their opportunities for recovery. We tested four bundled services to promote climate-smart agriculture practices namely weather index insurance (WII), agronomic advisories dissemination via SMS, weather services, and climate- resilient seeds of maize and rice. The integrated solutions are referred to as Bundled Solutions of Index Insurance with Climate Information and Seed Systems (BICSA) to manage agricultural risks in Sri Lanka. The study conducted the bundled solutions in three agroecological regions spread over five districts and covering more than 2,500 farmers in three cropping periods of Maha and Yala seasons. The results demonstrate that providing bundled solutions significantly protects smallholders against moderate drought events. The satellite-based weather index insurance can offset the long-term consequences of severe yield losses and mitigate the long-term drop in farm productivity. Our findings demonstrate the importance of bundled insurance to mitigate financial risks associated with extreme weather events and enhance resilience to climate change among vulnerable smallholders. It is evident from the study promoting a viable business model among seed companies, insurance companies, and technological partners, along with public institutions such as agricultural extension services can help production-level improvements and develop strategies at both the farm and policy levels that will support a transition to a more resilient farming system. [ABSTRACT FROM AUTHOR]

Forest fires pose a threat more serious than illegal felling in developing countries and are a cause of major concern for environmental security. Fires in tropical forests, though not devastating on a large scale as compared to large and infrequent fires in boreal or Mediterranean systems, still cause loss to biodiversity and economic and monetary value. In India, human-induced forest fires increasingly affect legally protected nature conservation areas. An array of satellite sensors that are now available can be deployed to monitor such events on a global and local scale. The present study uses night-time Advanced Along Track Scanning Radiometer (A)ATSR satellite data from the last nine years to identify high fire-prone zones, fire affected areas in protected zones and the distribution of these incidents in relation to bio-geographic zones. Central India, with its vegetation type that is just right for fire ignition and spread, was observed to be the most severely affected area with maximum fire incidences. The bio-geographic zone comprising this area–such as the Deccan peninsula, which includes provinces like Central Highlands, Eastern Highlands, Central Plateau and Chhota Nagpur–was observed to be the most affected, accounting for approximately 36% of the total fire occurrences during the period 1997–2005. In protected areas, 778 fire incidents were observed within the last eight years. Comparison of (A)ATSR fire locations with MODIS active fire data for the Western Ghats (mainly of tropical evergreen forests and savannahs) and the Eastern Ghats (tropical deciduous) showed a spatial agreement of 72% with a minimum distance between the two products of 100 m. This study focuses on regions in India that are vulnerable to forest fires during specific time-frames and appraises the situation with an aim to minimize such incidents, if not completely stop the fire spread and its consequent destruction and loss. Our main objective is to understand seasonal and spatial variation in fire pattern and to identify zones of frequent burning.

This study used time series remote sensing data from 1973, 1990 and 2004 to assess spatial forest cover change patterns in the Kalakad-Mundanthurai Tiger Reserve (KMTR), South Western Ghats (India). Analysis of forest cover changes and its causes are the most challenging areas of landscape ecology, especially due to the absence of temporal ground data and comparable space platform based data. Comparing remotely sensed data from three different sources with sensors having different spatial and spectral resolution presented a technical challenge. Quantitative change analysis over a long period provided a valuable insight into forest cover dynamics in this area. Time-series maps were combined within a geographical information system (GIS) with biotic and abiotic factors for modelling its future change. The land-cover change has been modelled using GEOMOD and predicted for year 2020 using the current disturbance scenario. Comparison of the forest change maps over the 31-year period shows that evergreen forest being degraded (16%) primarily in the form of selective logging and clear felling to raise plantations of coffee, tea and cardamom. The natural disturbances such as forest fire, wildlife grazing, invasions after clearance and soil erosion induced by anthropogenic pressure over the decades are the reasons of forest cover change in KMTR. The study demonstrates the role of remote sensing and GIS in monitoring of large-coverage of forest area continuously for a given region over time more precisely and in cost-effective manner which will be ideal for conservation planning and prioritization.

Landslides are among the most dangerous natural hazards, particularly in developing countries where ground observations for operative early warning systems are lacking. In these areas, remote sensing can represent an important tool to forecast landslide occurrence in space and time, particularly satellite rainfall products that have improved in terms of accuracy and resolution in recent times. Surprisingly, only a few studies have investigated the capability and effectiveness of these products in landslide forecasting, to reduce the impact of this hazard on the population. We have performed a comparative study of ground- and satellite-based rainfall products for landslide forecasting in India by using empirical rainfall thresholds derived from the analysis of historical landslide events. Specifically, we have tested Global Precipitation Measurement (GPM) and SM2RAIN-ASCAT satellite rainfall products, and their merging, at daily and hourly temporal resolution, and Indian Meteorological Department (IMD) daily rain gauge observations. A catalogue of 197 rainfall-induced landslides occurred throughout India in the 13-year period between April 2007 and October 2019 has been used. Results indicate that satellite rainfall products outperform ground observations thanks to their better spatial (10 km vs 25 km) and temporal (hourly vs daily) resolution. The better performance is obtained through the merged GPM and SM2RAIN-ASCAT products, even though improvements in reproducing the daily rainfall (e.g., overestimation of the number of rainy days) are likely needed. These findings open a new avenue for using such satellite products in landslide early warning systems, particularly in poorly gauged areas. [ABSTRACT FROM AUTHOR]

Floods cause catastrophic destruction to life and livelihood in South Asia than any other parts of the world. This research assessed long term (2001 to 2015) flood risk at South Asia level using eight-day Moderate Resolution Imaging Spectroradiometer data and subsequently expanded this methodology to identify potential zones for piloting flood index insurance scheme in Bihar, India. Bihar was further assessed for sub-regional segmentation of its 37 districts into four flood risk zones based on k-means clustering and Getis-Ord Gi* analysis of multi-modal dataset consisting of demographics, meteorological, agricultural, flood characteristics and economic loss from floods. Satellite based risk assessment identified parts of Indus basin in Pakistan, Ganges basin in North India and majority of Bangladesh as flood hotspots. Site prioritization for flood index insurance in Bihar identified Madhubani, Darbhanga, Muzaffarpur and Sitamarhi districts as very high flood risk districts by both methods signifying large impact of any potential interventions implemented in these districts. [ABSTRACT FROM AUTHOR]