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The geographical range of agricultural crops is shifting because of climate change. Reducing the potential negative impact of this shift requires efficient crop switching at farm level. Yet there are scant studies that examine how crop switching is currently taking place and what factors facilitate the process. Even these few existing studies often based their analysis on inadequately established causal link between climate change and switching decisions. This study aims to identify the specific switching decisions that are primarily motivated by climate change, and their determinants.

The study used a household survey on 190 households in Semien Shewa Zone in Ethiopia. Subjective rating of farmers was used to identify the relative importance of climate change in motivating the different types of switching decisions. A logit model is used to identify determinants of crop switching decisions primarily motivated by climate change.

Farmers in the study area are currently abandoning certain crops as a response to climate change. The adoption of new crops is, however, mainly attributed to price changes. Most farmers who abandoned at least one crop adopted mung bean mainly due to its price advantages. As expected, crop switching as an adaptation strategy is more prevalent particularly in drier and hotter agroecologies. The logit model showed that crop switching is strongly correlated with land size and agroecology.

This paper provides an in-depth examination of crop switching as an adaptation strategy to climate change. Crop switching is an adaptation strategy that is expected to substantially reduce the damage from climate change in agriculture. The findings are particularly relevant for adaptation planning in the context of smallholder agriculture.

Crop suitability analysis is vital for identifying a piece of land’s potential for sustainable crop production and aids in the formulation of an effective agricultural management plan. This study aims to conduct crop suitability analysis of prominent Kharif (rice and maize) and Rabi (potato and wheat) crops in Sirajganj district, a flood-prone area of Bangladesh, and recommend a suitable cropping pattern to mitigate the detrimental effects of flooding.

Various factors such as soil drainage, soil depth, soil moisture, soil texture, soil permeability, soil pH, erosion hazard, nutrient status and flooding risk were considered for this study. For all four crops, the weights of each factor were determined using the analytical hierarchy process approach, and the scores of each subfactor were assigned on the basis of favorable circumstances of crop cultivation. Using the weighted overlay analysis in the ArcGIS 10.3 environment, the crop suitability maps were generated and were divided into four suitable classes. Geographic information system integration of crop suitability for all the crops determined the suitable cropping pattern of the study area in Kharif and Rabi seasons.

A vast portion of the study area covering 64.80% of the total land is suitable for cultivating either rice or maize in Kharif season followed by either potato or wheat in Rabi season. Other suitable cropping pattern for Kharif and Rabi seasons found in the study area are rice-wheat, rice-wheat/potato, rice/maize-wheat and rice/maize-potato, which covers a little portion of the study area.

This research validates the suitable location of crop cultivation on the basis of flooding occurrences in the locality.

The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau has undergone great changes. This paper aims to clarify the response mechanisms of vegetation to climate change, to provide support for the restoration and environmental treatment of vegetation on the Loess Plateau.

The Savitsky–Golay (S-G) filtering algorithm was used to reconstruct time series of moderate resolution imaging spectroradiometer (MODIS) 13A2 data. Combined with trend analysis and partial correlation analysis, the influence of climate change on the phenology and enhanced vegetation index (EVI) during the growing season was described.

The S-G filtering algorithm is suitable for EVI reconstruction of the Loess Plateau. The date of start of growing season was found to gradually later along the Southeast–Northwest direction, whereas the date of the end of the growing season showed the opposite pattern and the length of the growing season gradually shortened. Vegetation EVI values decreased gradually from Southeast to Northwest. Vegetation changed significantly and showed clear differentiation according to different topographic factors. Vegetation correlated positively with precipitation from April to July and with temperature from August to November.

This study provides technical support for ecological environmental assessment, restoration of regional vegetation coverage and environmental governance of the Loess Plateau over the past two decades. It also provides theoretical support for the prediction model of vegetation phenology changes based on remote sensing data.

This paper aims to describe the indigenous and innovative practices adopted by the small-scale farmers to cope with the impacts of climate change hazards on subsistence farming.

The data were collected through focus group discussions with 72 small-scale farmers from a rural community in Limpopo Province, South Africa. The discussions were analysed through verbatim transcripts and content analysis.

The study results show the farmers’ understanding of climate change variability and its hazards in the form of rainfall scarcity and excessively increased temperature, which are responsible for a declining production of indigenous crops. It has also been found that in the face of these hazards, the farmers experience low crop yields, which cannot provide the household food requirements. However, the small-scale farmers use a combination of local and innovative knowledge and skills to improve their crop production. They have adopted the indigenous adaptation mechanisms, which include rainfall prediction, preparation of the gardens, change of crops and the planting season to ensure better crop yields. The farmers also adopted innovative adaptation practices such as the use of fertilisers, growing of exotic crops and use of extension officers’ guidance and skills to minimise the risks and maximise the chances of resilient crop production.

This paper describes the farmers’ ability to use the indigenous and innovative adaptation practices. It is only focused on the farmers’ knowledge and skills other than the extension officers’ skills.

The adaptation practices reported in the study fall within the adaptation and mitigation systems stipulated in the South African National Climate Change Strategy to assist the small-scale farmers grow and maintain the crops to improve production and minimise the risks, thus ensuring food security under observable harsh climate hazards.

Understanding farmers’ perceptions of how the climate is changing is vital to anticipating its impacts. Farmers are known to take appropriate steps to adapt only when they perceive change to be taking place. This study aims to analyse how African indigenous vegetable (AIV) farmers perceive climate change in three different agro-climatic zones (ACZs) in Kenya, identify the main differences in historical seasonal and annual rainfall and temperature trends between the zones, discuss differences in farmers’ perceptions and historical trends and analyse the impact of these perceived changes and trends on yields, weeds, pests and disease infestation of AIVs.

Data collection was undertaken in focus group discussions (FGD) (N = 211) and during interviews with individual farmers (N = 269). The Mann–Kendall test and regression were applied for trend analysis of time series data (1980-2014). Analysis of variance and least significant difference were used to test for differences in mean rainfall data, while a chi-square test examined the association between farmer perceptions and ACZs. Coefficient of variation expressed as a percentage was used to show variability in mean annual and seasonal rainfall between the zones.

Farmers perceived that higher temperatures, decreased rainfall, late onset and early retreat of rain, erratic rainfall patterns and frequent dry spells were increasing the incidences of droughts and floods. The chi-square results showed a significant relationship between some of these perceptions and ACZs. Meteorological data provided some evidence to support farmers’ perceptions of changing rainfall. No trend was detected in mean annual rainfall, but a significant increase was recorded in the semi-humid zone. A decreasing maximum temperature was noted in the semi-humid zone, but otherwise, an overall increase was detected. There were highly significant differences in mean annual rainfall between the zones. Farmers perceived reduced yields and changes in pest infestation and diseases in some AIVs to be prevalent in the dry season. This study’s findings provide a basis for local and timely institutional changes, which could certainly help in reducing the adverse effects of climate change.

This is an original research paper and the historical trends, farmers’ perceptions and effects of climate change on AIV production documented in this paper may also be representative of other ACZs in Kenya.

Fewer researchers have investigated the climatic and economic drivers of land-use change simultaneously and the interplay between drivers. This paper aims to investigate the nonlinear and interaction effects of price and climate variables on the rice acreage in high-latitude regions of China.

This study applies a multivariate adaptive regression spline to characterize the effects of price and climate expectations on rice acreage in high-latitude regions of China from 1992 to 2017. Then, yield expectation is added into the model to investigate the mechanism of climate effects on rice area allocation.

The results of importance assessment suggest that rice price, climate and total agricultural area play an important role in rice area allocation, and the importance of temperature is always higher than that of precipitation, especially for minimum temperature. Based on the estimated hinge functions and coefficients, it is found that total agricultural area has strong nonlinear and interaction effects with climate and price as forms of third-order interaction. However, the order of interaction terms reduces to second order after absorbing the expected yield. Additionally, the marginal effects of driven factors are calculated at different quantiles. The total area shows a positive and increasing marginal effect with the increase of total area. But the positive impact of price on the rice area can only be observed when price reached 50% or higher quantiles. Climate variables also show strong nonlinear marginal effects, and most climatic effects would disappear or be weakened once absorbing the expected rice yield. Expected yield is an efficient mechanism to explain the correlation between crop area and climate variables, but the impact of minimum temperature cannot be completely modeled by the yield expectation.

To the best of the authors’ knowledge, this is the first study to examine the nonlinear response of land-use change to climate and economic in high-latitude regions of China using the machine learning method.

In view of the consensus that climate change is happening, scientists have documented several findings about Uganda’s recent climate, as well as its variability and change. The purpose of this study is to review what has been documented, thus it gives an overview of what is known and seeks to explain the implications of a changing climate, hence what ought to be known to create a climate resilient environment.

Terms such as “climate”, “climate change” and “climate variability” were identified in recent peer-reviewed published literature to find recent climate-related literature on Uganda. Findings from independent researchers and consultants are incorporated. Data obtained from rainfall and temperature observations and from COSMO-CLM Regional Climate Model-Coordinated Regional Climate Downscaling Experiment (CCLM CORDEX) data, European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data and Global Precipitation Climatology Centre (GPCC) have been used to generate spatial maps, seasonal outputs and projections using GrADS 2.02 and Geographic Information System (GIS) software for visualization.

The climate of Uganda is tropical in nature and influenced by the Inter-Tropical Convergence Zone (ITCZ), varied relief, geo-location and inland lakes, among other factors. The impacts of severe weather and climate trends and variability have been documented substantially in the past 20-30 years. Most studies indicated a rainfall decline. Daily maximum and minimum temperatures are on the rise, while projections indicate a decrease in rainfall and increase in temperature both in the near and far future. The implication of these changes on society and the economy are discussed herein. Cost of inaction is expected to become huge, given factors like, the growing rate of the population and the slow expanding economy experienced in Uganda. Varied forms of adaptation to the impacts of climate change are being implemented, especially in the agricultural sector and at house hold level, though not systematically.

This review of scientific research findings aims to create a better understanding of the recent climate change and variability in Uganda and provides a baseline of summarized information for use in future research and actions.

This study aims to assess gender-based differences on farmers’ perception of impacts and vulnerability to climate change and the implementation of adaptation strategies in the Pra River Basin of Ghana, while also providing lessons for other Sub-Saharan nations and regions with similar conditions.

The study used semi-structured interviews and questionnaires to collect data from 344 farmers, 64 participants in focus group discussions and 6 agriculture extension officers (key informants) from 10 districts in the Pra River Basin of Ghana.

Results showed several differences in how climate change is perceived and tackled by male and female genders. In the perception of male farmers, for example, they were found to be more vulnerable to increased temperature, and changes in rainfall and growing season, whereas female farmers on average were considered to be less resilient to floods and droughts for different reasons. Moreover, floods posed higher risks to farming than other climate change impacts. Gender roles had a significant correlation with the type of adaptation strategies practised. Men adopted agrochemicals more often than women, as an adaptation strategy.

Gender-differentiated interventions should be incorporated in the national climate change action plan for sustainable development in a rain-fed agricultural economy such as Ghana. The study recommends several actions to promote gender equity in the assessed region.

This research assessed the gender differentials in climate trends, impact, vulnerability and adaptation based on primary data collected between April and May 2019 and compared the results with climate data in the basin for the period 1991–2014. It is an empirical study focused on primary data analysis obtained in loco by authors, involving approximately 400 participants.

This paper aims to understand the significant farm and market-level factors that incentivize the adoption and marketing of pulses influencing its supply response to changing demand.

The authors first use a modified Nerlovian supply response model using secondary data to identify the major price and non-price factors influencing the supply of pigeon pea, black and green gram in the major pulses growing states in India. Second, using primary qualitative data the authors map the pulses value chain from farm to retail to identify the how proportional and fixed transaction costs (FCTs) influence market participation of pulses growers and limit the transmission of price and quality information.

The supply response model shows some positive influence of price on area allocation for pigeon pea and black gram and some negative effects of yield and price increase of competing crops on pigeon pea acreage. However, for the most part, the area of Kharif pulses is inelastic to prices in the long run. Irrigation, rainfall and yields in the lag year are shown to have a significant influence on area allocation for pulses. The market study reveals that low yields, low landholding size and geographical disadvantages of high agro-climatic risk and poor connectivity hinder market access of pulses farmers relative to other crops. Market power in favor of buyers and poor price and quality information is a disadvantage to sellers, influencing their ability to participate in markets.

A quantitative study would be required to identify the magnitude of farm and market-level transaction costs.

This study helps to understand the supply response of pulses and gives suggestions to direct policy to rectify this.

The purpose of this paper is to provide an overview of the current state of knowledge on the economic performance of genetically modified (GM) cotton worldwide based on a wide range of data and source from available literature, and second to assess yield gain and economic performance.

A systematic review was captured to provide the evidence of potential benefits of GM cotton. A country-specific analysis was conducted in order to compare economic indicators and employed meta-analysis to find out the significance of the different of GM cotton over its counterpart.

This paper depicts positive impact of commercialized GM cotton in terms of net revenue, and the benefits, especially in terms of increased yields, are greatest for the mostly farmers in developing countries who have benefitted from the spill over of technology targeted at farmers in industrialized countries.

Due to the variability of the data which came from different methodologies, it is difficult to determine the differences of the performances each individual study.

This, it is believed that results from this study can be useful for operations of all sizes as the authors think about what needs to be focussed on for long-term producers survival.

The paper clearly indicates that China is the highest cotton yield of GM cotton, the lowest cost of GM seed and the lowest cost of chemical spray compare to any other countries. Therefore, this is the fact that the adoption of GM cotton has been widely spread among the farmers across the regions in China.