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The Himalayan region is the most sensitive due to its fragility, especially in soil erosion; therefore, it is a growing concern for environmentalists and natural resource planners. The study river basin Mandakini is situated in the central part of the Garhwal Himalayan region (Uttarakhand, India), which is highly prone to soil erosion due to various hydro-geomorphological factors. The factors include precipitous slope, geology, rugged terrain, land use and drainage pattern. Therefore, to identify the erosion-prone areas of the study basin, employed watershed prioritization technique using geographical information system and remote sensing integrated with weighted sum analysis (WSA), sediment production rate (SPR) and Technique of Order Preference Similarity to the Ideal Solution with Analytical Hierarchical Process (AHP-TOPSIS) models. It is calculated by taking different parameters indicating linear, landscape, and shape parameters. All the sub-watersheds (SW) of the basin were prioritized in different categories for all models with model performance for the Mandakini river basin in the central Himalaya. The results are showing almost similar results except for high erosion-prone regions. The results of the SPR model indicate that vary large areas (43.47%) of the basin suffering from severe erosion limited in the north-central (WS11, WS12, WS21), eastern (WS2), and southern (WS22 and WS23) parts of the basin among 23 sub-watersheds. The result of model evaluation indicates AHP-TOPSIS is the efficient model in assessing soil erodibility. The study can help to undertake the precise decisions to propose an effective framework for soil erosion control measures and encourage soil conservation priorities of the region. The findings have implications for defining sustainable land resource management and conservation, which are critical to attaining the United Nations' 2030 Agenda for Sustainable Development's societal goals. [ABSTRACT FROM AUTHOR]

In recent decades, dengue has been expanding rapidly in the tropical cities. Even though environmental factors and landscape features profoundly impact dengue vector abundance and disease epidemiology, significant gaps exist in understanding the role of local environmental heterogeneity on dengue epidemiology in India. In this study, we assessed the role of remotely sensed climatic factors (rainfall, temperature and humidity) and landscape variables (land use pattern, vegetation and built up density) on dengue incidence (2012–2019) in Bhopal city, Central India. Dengue hotspots in the city were assessed through geographical information system based spatial statistics. Dengue incidence increased from 0.59 cases in 2012 to 9.11 cases in 2019 per 10,000 inhabitants, and wards located in Southern Bhopal were found to be dengue hotspots. Distributed lag non-linear model combined with quasi Poisson regression was used to assess the exposure-response association, relative risk (RR), and delayed effects of environmental factors on dengue incidence. The analysis revealed a non-linear relationship between meteorological variables and dengue cases. The model shows that the risk of dengue cases increases with increasing mean temperature, rainfall and absolute humidity. The highest RR of dengue cases (~2.0) was observed for absolute humidity ≥60 g/m3 with a 5–15 week lag. Rapid urbanization assessed by an increase in the built-up area (a 9.1% increase in 2020 compared to 2014) could also be a key factor driving dengue incidence in Bhopal city. The study sheds important insight into the synergistic effects of both the landscape and climatic factors on the transmission dynamics of dengue. Furthermore, the study provides key baseline information on the climatic variables that can be used in the micro-level dengue prediction models in Bhopal and other cities with similar climatic conditions. Author summary: Dengue, a viral disease transmitted by infected Aedes mosquitoes, is a major public health concern globally. In addition to its increased incidence in recent years, dengue is also spreading to new geographical regions. Local environmental factors are known to modify the mosquito vector density that directly impacts dengue virus transmission. Understanding the influence of environmental factors (meteorological conditions and landscape features) on dengue epidemiology in local settings is important for focused dengue intervention. Here, by utilizing dengue incidence and remotely sensed environmental data from 2012–2019, we have assessed the role of environmental factors in driving dengue virus transmission in the city of Bhopal in Central India. During the study period, a 14.5 fold increase in dengue incidence was observed in Bhopal city, which is way higher than the 2.3 fold increase reported at the national level. The risk of dengue virus transmission was higher with higher temperature and absolute humidity. An increase in built-up area, a proxy for urbanization, was found to be another predictor of increased dengue incidence in Bhopal. These findings can provide a stepping-stone for the development of dengue prediction models and the identification of dengue hotspots in order to improve vector control of this disease in cities with similar environmental conditions. [ABSTRACT FROM AUTHOR]

Objective: To examine the association between remittances and food security in Bangladesh, controlling for other key factors. Design: The secondary data analysis was performed on the most recent (2016) nationally representative Household Income and Expenditure Survey. We used logistic regression models to measure the association between food security of the household and remittances received. The household food security was measured based on expenditure on food items and the energy intake of the household members. The key explanatory variables included the receipt of remittances by the household and household-level socio-economic characteristics. Setting: Bangladesh. Participants: Totally, 45 977 households across seven divisions of Bangladesh. Results: Findings suggested that remittances have a significant positive effect on food security. Further, the households with female heads were significantly more likely to be food insecure. The wealth status and geographical locations were significantly associated with food security status in Bangladesh. Conclusions: The findings highlight the importance of considering remittance as one of the key factors, while stakeholders implement nutritional interventions in Bangladesh and other low-income settings. Future research should consider this as an important determinant while further examining food security in such settings. [ABSTRACT FROM AUTHOR]

Located on the south-facing slope of the Himalayas, Nepal receives intense, long-lasting precipitation during the Asian summer monsoon, making Nepal one of the most susceptible countries to flood and landslide hazards in the region. However, sparse gauging and irregular measurement constrain the vulnerability assessments of floods and landslides, which rely highly on the accuracy of precipitation. Therefore, this study evaluates the performance of Satellite-based Precipitation Products (SPPs) in the Himalayas region by comparing different datasets and identifying the best alternative of gauge-based precipitation for hydro-meteorological applications. We compared eight SPPs using statistical metrics and then used the Multi-Criteria Decision-Making (MCDM) technique to rank them. Secondly, we assessed the hydrological utility of SPPs by simulating them through the GR4J hydrological model. We found a high POD (0.60–0.80) for all SPPs except CHIRPS and PERSIANN; however, a high CC (0.20–0.40) only for CHIRPS, IMERG_Final, and CMORPH. Based on MCDM, CMORPH and IMERG_Final rank first and second. While SPPs could not simulate daily discharge (NSE < 0.28), they performed better for monthly streamflow (NSE > 0.54). Overall, this study recommends CMORPH and IMERG_Final and improves the understanding of data quality to better manage hydrological disasters in the data-sparse Himalayas. This study framework can also be used in other Himalayan regions to systematically rank and identify the most suitable datasets for hydro-meteorological applications. [ABSTRACT FROM AUTHOR]

Climate change impacts agricultural productivity and farmers' income, integrated farming systems (IFS) provide a mechanism to cope with such impacts. The nature and extent of climatic aberrations, perceived impact, and adaptation strategies by the farmers reduce the adverse effects of climate change on agriculture. Therefore, a study was conducted to investigate 2160 IFS farmers about their perceptions of climate change, barriers, and the likelihood of adapting to the negative impacts of climate change. The study observed an increasing rainfall trend for humid (4.18 mm/year) and semi-arid (0.35 mm/year) regions, while a decreasing trend was observed in sub-humid (−2.02 mm/year) and arid (−0.20 mm/year) regions over the last 38 years. The annual rise in temperature trends observed in different ACZs varied between 0.011–0.014 °C. Nearly 79% of IFS farmers perceived an increase in temperature, decreasing rainfall, variability in the onset of monsoon, heavy terminal rains, mid-season dry spells, and frequent floods due to climate change. The arid, semi-arid, sub-humid, and humid farmers' adapted several measures in different components with an adaption index of 50.2%, 66.6%, 83.3%, and 91.6%, respectively. The majority of the IFS farmers perceived constraints in adopting measures to climate change, such as meta barriers, capacity barriers, and water barriers. Therefore, we infer that educated farmers involved in diversified and profitable farms with small to medium landholdings are concerned more about climate change in undertaking adaptive strategies to reduce the environmental impact of climate change. [ABSTRACT FROM AUTHOR]

We investigate the climatic influence on COVID-19 transmission risks in 228 cities globally across three climatic zones. The results, based on the application of a Boosted Regression Tree algorithm method, show that average temperature and average relative humidity explain significant variations in COVID-19 transmission across temperate and subtropical regions, whereas in the tropical region, the average diurnal temperature range and temperature seasonality significantly predict the infection outbreak. The number of positive cases showed a decrease sharply above an average temperature of 10°C in the cities of France, Turkey, the US, the UK, and Germany. Among the tropical countries, COVID-19 in Indian cities is most affected by mean diurnal temperature, and those in Brazil by temperature seasonality. The findings have implications on public health interventions, and contribute to the ongoing scientific and policy discourse on the complex interplay of climatic factors determining the risks of COVID-19 transmission. [ABSTRACT FROM AUTHOR]

Climate change is viewed as the main obstacle to agricultural development in developing countries. The high dependence on agriculture and allied sectors makes many countries vulnerable to the climate change phenomenon. There is a gap in macro and micro-level understanding of climate change. Thoughtful farmers' perceptions and impacts of climate change on farming are fundamental for developing various mitigation and adaptation strategies. Therefore, the main aim of the present study was to understand the pattern of climate variability, farmers' perceptions about climate change, and farmers' adaptation strategies based on their socio-cultural background in the villages of Goa, on the west coast of India. The results reveal that about 62% of the sampled farmers have experienced climate change in terms of meteorological indicators such as increased average temperature, decreased total rainfall, delayed onset of monsoon, and an increase in the length of the summer season. The temperature trend analysis (0.009 °C/year) validated farmers' perceptions, while the perception of rainfall differed (−1.49 mm/year). Farmers are convinced that climate change has affected their farming (declining crop and livestock productivity, water depletion, and other related farm operations). They strive to adapt to climate change through crop diversification, an integrated crop-livestock system, contingency crop planning, and the adaptation of new crops and varieties. This study could be helpful for policymakers to establish a climate-resilient agriculture system by ensuring timely availability of farm inputs, accurate weather forecasting, and encouraging insurance products for crop and livestock enterprises, which will help farmers cope with the changing climate to enhance their income and economic wellbeing. Further, adaption of integrated farming, agroforestry, and indigenous technical knowledge is imperative to combat the ill effects of climate change. [ABSTRACT FROM AUTHOR]

The study is the first attempt to assess the role of climatic predictors in the rise of COVID-19 intensity in the Russian climatic region. The study used the Random Forest algorithm to understand the underlying associations and monthly scenarios. The results show that temperature seasonality (29.2 ± 0.9%) has the highest contribution for COVID-19 transmission in the humid continental region. In comparison, the diurnal temperature range (26.8 ± 0.4%) and temperature seasonality (14.6 ± 0.8%) had the highest impacts in the sub-arctic region. Our results also show that September and October have favorable climatic conditions for the COVID-19 spread in the sub-arctic and humid continental regions, respectively. From June to August, the high favorable zone for the spread of the disease will shift towards the sub-arctic region from the humid continental region. The study suggests that the government should implement strict measures for these months to prevent the second wave of COVID-19 outbreak in Russia. [ABSTRACT FROM AUTHOR]

The local population of Sundarbans, an environmentally vulnerable delta region in south-eastern India, is currently affected by combined negative impacts of cyclone Amphan and the COVID-19 pandemic. The lockdown measures have created an additional burden on the health care system, while flooding during Amphan increased the risk of spreading water-borne diseases. In this viewpoint, we provide a conceptual model of the complex interlinkages among the combined multi-hazard effects, human health and water availability, with possible mitigation measures. We then discuss the specific pathways through which these immediate and long-term impacts occur and highlight the risk of together slowing progress on SDG3 and SDG6 in the Sundarbans. Finally, we call for coordinated assessment, support and appropriate intervention measures to secure clean water availability and minimize the health impacts of the recent multiple disasters in this tropical delta region. [ABSTRACT FROM AUTHOR]

Thailand's agriculture is facing an ageing workforce, which could negatively influence agricultural production. Yet, there is still limited evidence regarding the perception of the ageing agricultural labour force in the country and a lack of insights into farmers' strategies to improve agricultural output. To fill this gap, we analysed primary data from questionnaire-based surveys of 365 households in Prachinburi Province, Thailand. The results show that household poverty, farm experience, retirement, health concerns, and farm accidents are positively associated with the farmers' perception on the ageing workforce, whereas education level, having an ageing farmer in the family, farm size, mentoring and access to new technology have a negative influence on the perception of the ageing workforce. Given the anticipated implications of the population ageing in Thailand, the government should consider establishing policy options to encourage younger entrants into the agricultural sector and prioritising policies related to intergenerational support. [ABSTRACT FROM AUTHOR]

This provides a critical setting to forecast the multiple effects of the Amphan-COVID-19 events in both the short- and long-term futures of the Sundarbans. Pramanik et al, "Population Health Risks in Multi-Hazard Environments: Action Needed in the Cyclone Amphan and COVID-19-Hit Sundarbans Region, India", I Climate and Development i (2020), doi:10.1080/17565529.2021.1889948. Combined COVID-19 and Cyclone Amphan Impacts Impact on Agriculture In the Sundarbans, 4.4 million people are classified as marginal workers (who have guaranteed work for less than 6 months), like agricultural labor, cultivators, and household and daily wage workers.[17] The major non-agricultural occupations in the region are in construction, driving, woodworking, and casual multipurpose labor. [Extracted from the article]

Agriculture, global biodiversity and distribution of species are increasingly influenced by changing climate. Assessing the future distribution of biodiversity under different climate change scenarios is an essential step towards conservation planning and policy implementations. To understand the climate change impacts, the present study used Garcinia gummi-gutta cash crop species as a case study that is even exported, adding the nation's foreign reserve. Given the importance of this crop for local and national economy, the main objectives of the study were to analyse the impact of present and future climates on ecologically susceptible G. gummi-gutta species in the Western Ghats based on maximum entropy model (MaxEnt). Future projections with RCP scenarios for 2050 and 2070 were made using the data of 84 species occurrence and climatic variables of three climate models from IPCC 5th assessment. The contribution of climatic variables was analysed by jackknife test, and 0.888 of AOC indicates high accuracy of the model results. It was found that annual precipitation, coldest quarter precipitation, and precipitation seasonality were the key determining factors for the suitability of this species. In addition, the results of all scenarios showed that the current suitability of the species would be dramatically decreased by 2050 and 2070. The study suggests how the MaxEnt approach can be an important tool for agricultural development, management of species habitats, conservation of biodiversity, and climate change rehabitation planning. [ABSTRACT FROM AUTHOR]

• MCDM using AHP and FR are useful methods for agricultural potential mapping. • Geological and pedagogical variables have a significant contribution in Himalayan agriculture. • Lands in the River valleys with < 15° slope, <1000 m elevation and loamy-very fine soil texture are most prospective. • Land evaluation mapping for agriculture may help to develop self-reliant village economies. • It provides a better planning and management for sustainable development of mountain agriculture. The mountainous region of the Rudraprayag district is covered with a variety of floral and faunal diversity, provide very rich biodiversity. A very limited area of the district is available for agriculture for supplying the growing demand for food and running the rural economies. Therefore, it became imperative to use this limited resource very cautiously, so that it can provide sustainable production to the farming communities. Nevertheless, due to lack of inadequate infrastructural facilities more specifically accessibility and other socio-economic barriers in the agriculture production lagging. Therefore, in the present study, we used frequency ratio (FR) and analytical hierarchy process (AHP) integrating with remote sensing (RS) and geographic information system (GIS) to identify the potential land for agriculture. The study used ten most significant topographic, geological, pedagogical, climatic, and socioeconomic variables using weighted overlay method in GIS platform. We also used expert knowledge to assign weights, then normalized by AHP eigenvector. For validation, we used receiver operating characteristic (ROC) curve, indicates both methods are very useful in agricultural potentiality mapping. The results also show that the geological and pedagogical conditions have prominent control and directly affects the agricultural practices in the area. The large areas are currently not suitable (1148.89 km2, 57.94%) and permanently unsuitable (390.43 km2, 19.69%), but very few areas (56.22 km2, 2.84%) are highly suitable in the district, which is mostly confined in the lower valley region of Alaknanda and Mandakini Rivers. The main characteristics of the region is nearly plain (<15°), elevation < 1000 m, and loamy to very fine sand soil texture. The agriculture sites proposed in the study can help farmers, regional planners and government to take precise decisions for the region to determine the potential agricultural lands and their practices. The results of the study have implications for developing sustainable agriculture management plan to ensure sustainable food production system and implement resilient agricultural practices and increase agriculture productivity and income. It can help to maintain ecosystem to strengthen capacity for agriculture adaptation, agricultural development, and self-reliant village economies in the district as well as across the Himalayan region. [ABSTRACT FROM AUTHOR]

The study aims to get insights into virtual land, water flows from producers' perspectives for cereal crops and trade in Bangladesh and provides insights into the carbon emissions from agriculture. For this purpose, FAO's cereals area, production and yield, food balance sheets, detailed trade matrix, GHG emissions, and population data for the year 2014-17 were used. Cereal water footprints data were obtained from the secondary literature. The study finds that 8% of domestic cereal supply (70% wheat, 17% maize, and 2% rice and related products) was imported through international trade. The annual average virtual cropland area and water imported through trade of 6.9 million tonnes of the three cereal crops (excluding products) were 2.1 million ha and 14 billion m3, respectively, during 2014-17. Bangladesh would need additional 2.81 million ha land and 12 billion m3 water to be cereal selfsufficient. Energy used in agriculture, including mechanization and irrigation, adds to GHG emissions, and there is potential to use renewable energy sources to reduce the GHG emissions from agriculture. An integrated management of water, energy, and carbon should be considered as one of the strategies to reduce GHG emissions from agriculture. [ABSTRACT FROM AUTHOR]