Climate change has been unequivocally known to be real, and its impacts are recognized as one of the most pressing global issues in the current decade. Evidences from a variety of different studies show that the impacts of climate change have become a major threat to agriculture and the food security in both the developed and developing countries across the world. With unabated increase in the anthropogenic atmospheric greenhouse gas emission that is known to interfere with `the regional and global circulation systems, global warming, and climate change in the twenty first century and beyond, would continue to be the most important agenda of debate and scientific discourses. Moreover, the negative impacts of climate change have been observed to be more pronounced in the high latitude areas, such as the mountainous countries in the Himalayas and elsewhere. Studies have also strongly postulated that the adverse impacts of climate change are most likely to be more severe in the developing countries in south Asia, Southeast Asia, Sub-Saharan Africa, and Latin America, due to their low adoption of farming technologies and lack of capacity to respond.

As many developing countries in the region report the negative impacts of climate change, Bhutan—an agrarian country located in the Eastern Himalayas, is no exception. The country has experienced increasing incidences of risks and disasters associated with climatic variabilities in the recent years. There have been pervasive issues of changing weather patterns that make farming a highly risky and vulnerable occupation. Apart from this, there are other pre-disposing factors that make Bhutan an even more sensitive and vulnerable to the climate variabilities. The highly rugged mountainous topography is one of the most important factors that make farming very challenging, as farmlands are concentrated in the river valleys with scattered land parcels in the mountain slopes. Thus the farms are highly prone to natural disasters that are triggered by weather and climatic events. The dramatic rise in elevation even over a small distance is another factor, which influence the orographic effects of mass air-flow systems, contributing to sudden changes in weather, thus negatively impacting crops and farms. Moreover, the Himalayan Mountains are considered to be geologically fragile, with inherently infertile soils for farming. This further makes farming prone to the destructive natural events, including those of weather phenomena. All of these, contribute to the challenging and subsistence nature of farming in the Bhutanese agricultural system. Therefore, this research was undertaken to study climate change and its impacts on various aspects of agriculture across different agro-ecological zones in Bhutan. The study used a combination of farmers’ perception analysis, geo-spatial techniques and modelling approaches to fill the much-needed knowledge gap on the issues of climate change faced by the Bhutanese farmers, and provides insights into the past, present and future climate change impact scenarios. Much of the climate and impact reports on Bhutan were based on hearsay, and scientific studies are few and far between.

As part of this research, a thorough review of agricultural production management system and pertinent issues of climate change impacts in Bhutan was undertaken. It was found that agriculture in Bhutan and the study region have been largely affected by the rising temperature, droughts and precipitation changes, which in turn have led to many other issues, ranging from water availability, crop and infrastructure damage to land degradation. Moving further, assessment of land cover changes in Punatsang Chhu Basin of Bhutan indicated large scale changes, especially in the high elevation areas. The findings from this study show that there is an increased rate of glacier retreat, with repercussions of Glacial Lake Outburst Floods (GLOF) and erosive activities of rivers and streams that directly and indirectly affect farming downstream in the river valleys. This indicates that mountain agriculture is highly vulnerable to the impacts of climate change and is at high risks of food insecurity. Likewise, the results from the analysis of farmers’ perceptions across the various agro-ecological zones in Bhutan indicated that farming has become more and more challenging. The extreme weather events, such as untimely rains, droughts and windstorms have become frequent occurrences, thus inflicting between 1-19% crop damages. The monsoon rains were assessed to be highly unpredictable, and untimely, which were perceived to have impacted the decisions of farmers, due to drying up of water sources, crop losses, land fallowing and cropping pattern changes. Farmers have also perceived issues of the emergence of diseases and pests, which together with aggressive incursion of invasive species (Parthenium hysterophorus, for example) would herald uncertainties and rising pressure on Bhutan’s limited arable land. Further, based on the projections of the Intergovernmental Panel on Climate Change (IPCC), MaxEnt modelling of rice distribution indicated large changes in crop suitability shift. Such a crop suitability change, especially from high to low suitability in the major rice growing areas, indicates decline in crop area and yield under the impact of climate change in the near future. Therefore, for improving the resilience and sustainability of the Bhutanese farms, a comprehensive climate change adaptation plan, backed up by in-depth research and policy instrument must be put in place.

Understanding the variability in crop yield in relation to the spatial variationsin soil properties can help to more efficiently apply agricultural inputs on a site-specific basis. This study was designed to characterize and quantify the spatialvariation in soil properties and wheat yield and to delineate prescription maps forsite- specific fertilization. A wheat field was selected at the research farm of theUniversity of Agriculture, Faisalabad, Pakistan, and a grid pattern (30 m * 30 m)was established at the experimental sites to collect soil and crop yield samples attwo sampling depths (0– 15 & 15– 30 cm). The soil samples were analysed for soilnitrogen (N), phosphorus (P), potassium (K), pH, electrical conductivity (EC),soil organic matter (SOM) and saturation (S) at both sampling depths. The loca-tions of the sampling points and field boundary were marked with a GPS receiver.Results of classical, geo-statistical and interpolated maps revealed significant spa-tial variability in soil properties and crop yield, demanding for site-specific nutri-ent management. The cluster analysis was performed to group the soil and yielddata into five productivity zones termed as 'very low', 'low', 'medium', 'high' and'very high' without prior knowledge of productivity potential with the internalhomogeneity and external heterogeneity at a similarity level of greater than 70%.Results of correlation matrix suggested significant relationships among the cropyield and the soil properties. Results of means comparison in different produc-tivity zones indicated that the crop yield and soil properties were significantlydifferent in developed management zones except 'low' and 'very low' zones. Significant variation of soil nutrients in very low-to-very high productivity zones at both sampling depths suggested that the soil nutrients in combination with soil pH and organic matter can be used to develop prescription maps for site-specific fertilization. Furthermore, the results of this study emphasize the need to predict soil and crop variables using sensors, in future studies, to delineate pre-scription maps, as soil sampling and analysis is expansive and time consuming. Site-specific fertilization based on soil and crop needs can improve economic and environmental efficiency.

The impacts of climate change on tea production systems may be very variable, at both the national and global levels. In particular, Sri Lanka is considered vulnerable to climate fluctuations due to a variety of geographic, socioeconomic, and political factors. The predicted effects of climate change could have serious and irreversible consequences for tea production, quality, and habitats. Therefore, the consequences of climate change on Sri Lanka's tea industry should be extensively researched to determine its impact on production and quality, which in turn related to export revenues and employment for rural populations. However, information is exiguous on how climate change could affect climate/land suitability and tea quality under rainfed conditions in Sri Lanka. To narrow this gap, this study aimed at evaluating the effects of climate change on climate/land suitability for tea and its quality using a case study of Sri Lanka, a well-known high-quality black tea producer, as a classic example of a susceptible region. The study used species distribution techniques, geographic information system (GIS), remote sensing (RS)–based applications, and chemical analysis of tea leaves. The systematic review suggested that the impacts of the current and future climate on tea production systems outweigh the beneficial impacts, having multidimensional and multifaceted consequences. Tea yield increases when CO₂ levels rise, but this positive effect could be hindered by rising temperatures. Further, tea yield would be negatively impacted by drought, uneven rainfall, and extreme weather events. For tea quality attributes, climate change can serve as both a boon and a bane, leaving questions and giving research priority to quantifying the thresholds of biochemicals to define tea quality, according to customer satisfaction. Climate change affects tea habitats by causing losses, gains, and shifts in climate suitability. Further review suggested the scarcity of appropriate method to model impacts of future climate changes on tea quality and for determining climate suitability for tea. It also highlighted the importance of implementation of adaptive and mitigation measures in tea production to alleviate the undesirable impacts of climate change. At regional scale climate modelling for Sri Lanka's tea sector, indicated that precipitation seasonality, annual mean temperature and annual precipitation are the three most important bioclimatic variables of tea habitat distribution in Sri Lanka. Land suitability classes for tea cultivation comprised of low suitability (42.1%), unsuitable (28.5%), moderate (12.4%), highly suitable (13.9%), and very highly suitable (2.5%). There is a chance of decrease in optimal and medium suitability areas in low-elevation regions in the future, with overall decline assessed to be between 8-17% for all suitability areas. This indicating that climate change will have a negative effect on the habitat suitability of tea in Sri Lanka by 2050 and 2070. Further, the refinement in land suitability classification through inclusion of other climatic and environmental variables (solar radiation, temperature, rainfall, topographic and soil) in climate model made two suggestions namely (1) there is a noticeable difference between tea- and non-tea-growing areas in terms of all above factors" (2) under future climate change scenario, tea-growing regions in Sri Lanka could expand to a range of locales, if some key variables are carefully managed.

For tea quality assessment, model showed a significant interaction effect of weather conditions, cultivar, and geographical location over the concentrations of major tea quality biochemicals (total polyphenol content (TPC), free sugar, protein, and theanine) in tea leaves. The bioclimatic variables present seasonality (monthly range in temperature and precipitation), monthly trends (mean monthly temperature, monthly total precipitation), and extreme environmental variables (temperature of the coldest and warmest month, and precipitation of the wettest and driest months). They particularly caused changes in the four tested biochemicals of tea. The thresholds of all tested biochemicals are likely to increase with future climate change as temperatures and rainfall intensities are likely to increase. The distribution class with "very high" concentrations of TPC and theanine is expected to increase by 10% and 14%, respectively, in the future, while protein and free sugar classes are expected to decrease by 14% and 12%, respectively. For tea quality assessment, model showed a significant interaction effect of weather conditions, cultivar, and geographical location over the concentrations of major tea quality biochemicals (total polyphenol content (TPC), free sugar, protein, and theanine) in tea leaves. The bioclimatic variables present seasonality (monthly range in temperature and precipitation), monthly trends (mean monthly temperature, monthly total precipitation), and extreme environmental variables (temperature of the coldest and warmest month, and precipitation of the wettest and driest months). They particularly caused changes in the four tested biochemicals of tea. The thresholds of all tested biochemicals are likely to increase with future climate change as temperatures and rainfall intensities are likely to increase. The distribution class with "very high" concentrations of TPC and theanine is expected to increase by 10% and 14%, respectively, in the future, while protein and free sugar classes are expected to decrease by 14% and 12%, respectively.

Village Tank Cascade System (VTCS) landscapes in the dry zone of Sri Lanka provide multiple ecosystem services (ESs) and benefits to local communities, sustaining the productivity of their land use systems (LUSs). However, there is a lack of adequate scientific research on the ESs of LUSs, despite the recent land use changes that have greatly impacted the provisioning of ESs. Collection of baseline ESs data is a pre-requisite for decision making on ESs-based ecological restoration and management of the VTCS. Thus, this study aimed at assessing ESs of the Mahakanumulla VTCS (MVTCS) located in the Anuradhapura district of Sri Lanka by using a participatory approach involving the integration of local knowledge, expert judgements and LUSs attribute data to assess the ESs. The methodology was designed to integrate the biodiversity and land degradation status of LUSs in a way that is directly linked with the supply of ESs. The study identified twenty-four ESs of the MVTCS based on community perceptions. The identified ESs were assessed as a function of LUSs to develop an ecosystem service supply (ESS) and demand (ESD) matrix model. The results reveal that the current overall ESD for regulating and supporting ESs is higher than the ESS capacity of MVTCS. The assessment also revealed that land degradation and biodiversity deterioration reduce the capacity to provide ESs. Downstream LUSs of the meso-catchment were found to be more vulnerable to degradation and insufficient to provide ESs. Further, the study established that ESs in the MVTCS are generated through direct species-based and biophysical-based providers. In addition, it emerged that social and cultural engagements also played an important role in association with both providers to generate certain types of ESs. Therefore, it can be concluded that VTCS ecological restoration depends on the extent to which integrated effort addresses the levels of ecological complexity, as well as the social engagement of communities and stakeholders. The results of this study provide a scientific basis that can inform future land use decision making and practices that are applicable to successful ESs-based ecological restoration and management of the VTCSs in the dry zone of Sri Lanka.

This study evaluates energy efficiency of pastoral (PDFs) and barn (BDFs) dairy farming systems in New Zealand through application of data envelopment analysis (DEA) approach. Two models constant return to scale (CCR) and variable return to scale (BCC) of DEA were employed for determining the technical (TE), pure technical (PTE) and scale (SE) efficiencies of New Zealand pastoral and barn dairy systems. Further, benchmarking was also performed to separate efficient and inefficient dairy farms and energy saving potential was identified for both dairy systems based upon their optimal energy consumption. For this study, the energy inputs data were taken from 50 dairy farms (including PDFs and BDFs) across Canterbury, New Zealand. The results indicated that the average technical, pure technical and scale efficiencies of pastoral (PDFs) dairy systems were 0.84, 0.90, 0.93 and for barn (BDFs) systems were 0.78, 0.84, 0.92, respectively, showing that energy efficiency is slightly better in PDFs system than the BDFs. From the total number of dairy farms 40% and 48% were efficient based on the constant return to scale and variable return to scale models, respectively. Further, the energy saving potential for PDFs and BDFs dairy systems through optimal energy consumption were identified as 23% and 35%, respectively. Thus, energy auditing, use of renewable energy and precision agricultural technology were recommended for energy efficiency improvement in both dairy systems.

In 2020, mango (Mangifera indica) exports contributed over 40 million tons, worth around US$20 billion, to the global economy. Only 10% of this contribution was made from African countries including Ghana, largely due to lower investment in the sector and general paucity of research into the mango value chain, especially production, quality and volume. Considering the global economic importance of mango coupled with the gap in the use of the remote sensing technology in the sector, this study tested the hypothesis that phenological stages of mango can be retrieved from Sentinel-2 (S2) derived time series vegetation indices (VIs) data. The study was conducted on four mango farms in the Yilo Krobo Municipal Area of Ghana. Seasonal (temporal) growth curves using four VIs (NDVI, GNDVI, EVI and SAVI) for the period from 2017 to 2020 were derived for each of the selected orchards and then aligned with five known phenology stages: Flowering/Fruitset (F/FS), Fruit Development (FRD), Maturity/Harvesting (M/H), Flushing (FLU) and Dormancy (D). The significance of the variation "within" and "between" farms obtained from the VI metrics of the S2 data were tested using single-factor and two-factor analysis of variance (ANOVA). Furthermore, to identify which specific variable pairs (phenology stages) were significantly different, a Tukey honest significant difference (HSD) post-hoc test was conducted, following the results of the ANOVA. Whilst it was possible to differentiate the phenological stages using all the four VIs, EVI was found to be the best related with p < 0.05 for most of the studied farms. A distinct annual trend was identified with a peak in June/July and troughs in December/January. The derivation of remote sensing based 'time series' growth profiles for commercial mango orchards supports the 'benchmarking' of annual and seasonal orchard performance and therefore offers a near 'real time' technology for identifying significant variations resulting from pest and disease incursions and the potential impacts of seasonal weather variations.