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In this paper, a systematic literature review was conducted to synthesize understanding on farmers’ perception on climate change. Farmers’ perception of climate change is conceptualized as comprising of three dimensions—first, as farmers’ “awareness”; second, “conceptual understanding”; and third, the “experience” of climate change. The review included 162 papers published during the period January 2000 to July 2019. The highest number of studies was conducted in Africa, followed by Asia. A large majority of farmers report being aware of climate change. However, only a few studies elicit the difference between climate variability and climate change from farmers. A negligible number of studies attempt to identify the role of agricultural activities in greenhouse gas emissions and climate change. Furthermore, authors compare farmers’ perception with meteorological evidence, which is more aligned in terms of change in “temperature” rather than “precipitation.” The insights from the review provide guidance on conceptualization and operationalization of the variable “farmers’ perception of climate change” for future studies.

The cranberry, a commodity of social, cultural, and economic importance to New England, is under threat due to climatic change in this region of the United States. Yet, previous research reveals that cranberry growers have mixed attitudes about the anthropogenic roots of climate change, with many being skeptical. Building on the researchers’ analysis of the personal and ecological conditions that affect climate change attitudes among cranberry growers, this paper examines the effect that key actors in the growers’ social networks have on those attitudes. Through statistical analysis of survey data and content analysis of two important cranberry newsletters, the paper finds that cranberry growers’ perceived importance of two key cranberry growing institutions, the “sociopolitically focused” Cape Cod Cranberry Growers’ Association and the “technically focused” University of Massachusetts Cranberry Station, as well as connections to other cranberry growers, is associated in nuanced ways with growers’ climate change attitudes. Drawing on the sociological theory of “social capital,” the paper examines how these social ties to key actors/institutions may result in greater threat perception or worry about climate change. It then considers how “green ties,” if harnessed and supported by these important actors in the cranberry grower network, might significantly mitigate climate change in the future. Electronic supplementary material The online version of this article (10.1007/s10584-020-02808-0) contains supplementary material, which is available to authorized users.

Climate information and agro-advisory services are crucial in helping smallholder farmers and pastoralists in East Africa manage climate-related risks and adapt to climate change. However, significant gaps exist in provision of climate information that effectively addresses the needs of farmers and pastoralists. Most farmers and pastoralists, therefore, rely on indigenous knowledge (IK), where local indicators and experiences are used to observe and forecast weather conditions. While IK-based forecasting is inbuilt and established in many communities in East Africa, coordinated research and systematic documentation of IK for weather forecasting, including accuracy and reliability of IK is largely lacking. This paper documents and synthesizes existing IK for weather forecasting in East Africa using case studies from Ethiopia, Tanzania, and Uganda. The results show that farmers and pastoralists use a combination of meteorological, biological, and astrological indicators to forecast local weather conditions. IK weather forecasting is, therefore, crucial in supporting efforts to improve access to climate information in East Africa, especially in resource-poor and vulnerable communities. The paper draws valuable lessons on how farmers and pastoralists in East Africa use IK weather forecasts for making crop and livestock production decisions and demonstrates that the trust and willingness to apply scientific forecasts by farmers and pastoralists is likely to increase when integrated with IK. Therefore, a systematic documentation of IK, and a framework for integrating IK and scientific weather forecasting from national meteorological agencies can improve accuracy, uptake, and use of weather forecasts.

The assessment of the impacts of climate change at different levels of global warming helps inform national and international policy discussion around mitigation targets. This paper provides consistent estimates of global and regional impacts and risks at increases in global mean temperature up to 5 °C above pre-industrial levels, for over 30 indicators representing temperature extremes and heatwaves, hydrological change, floods and droughts and proxies for impacts on crop yields. At the global scale, all the impacts that could plausibly be either adverse or beneficial are adverse, and impacts and risks increase with temperature change. For example, the global average chance of a major heatwave increases from 5% in 1981–2010 to 28% at 1.5 °C and 92% at 4 °C, of an agricultural drought increases from 9 to 24% at 1.5 °C and 61% at 4 °C, and of the 50-year return period river flood increases from 2 to 2.4% at 1.5 °C and 5.4% at 4 °C. The chance of a damaging hot spell for maize increases from 5 to 50% at 4 °C, whilst the chance for rice rises from 27 to 46%. There is considerable uncertainty around these central estimates, and impacts and risks vary between regions. Some impacts—for example heatwaves—increase rapidly as temperature increases, whilst others show more linear responses. The paper presents estimates of the risk of impacts exceeding specific targets and demonstrates that these estimates are sensitive to the thresholds used.

To meet the growing demand for climate change information to guide national and local adaptation decision-making in the Philippines, the climate science and services community is producing an increasing volume of future climate data using a range of modelling approaches. However, there is a significant methodological challenge in how to best compare and combine information produced using different models and methods. In this paper, we present the landscape of climate model data available in the Philippines and show how multi-model, multi-method climate projections are being used and communicated to inform climate change policy and planning, focusing on the agriculture sector. We highlight the importance of examining and communicating methodological strengths and weaknesses as well as understanding the needs and capabilities of different user communities. We discuss the assessment of projections from different methods, including global and regional downscaled simulations, and discuss ways to summarise and communicate this information to stakeholders using co-production approaches. The paper concludes with perspectives on how to best use an “ensemble of opportunity” to construct defensible, plausible and usable climate projections.

Seasonal climate forecasts (SCF) provide information about future climate variability that has the potential to benefit organisations and their decision-making. However, the production and availability of SCF does not guarantee its use in decision-making per se as a range of factors and conditions influence its use in different decision-making contexts. The aim of this paper is to identify the barriers and enablers to the use of SCF across organisations in Europe. To achieve that, we conducted 75 in-depth interviews with organisations working across eight sectors (including energy, transport, water and agriculture) and 16 countries. The majority of the organisations interviewed do not currently use SCF. This was due to the low reliability and skill of SCF in Europe but also with other non-technical aspects such as the lack of relevance and awareness of SCF in the organisations. Conversely, the main enabler to the use of SCF was the interactions with the providers of SCF. In addition, the level of organisational resources, capacity and expertise were also significant enablers to the use of SCF in organisations. This paper provides the first empirical assessment of the use of SCF in Europe. Such insights provide not only an overview of the existing barriers and enablers to the use of SCF in Europe and how these can be overcome and negotiated to enhance the usability of SCF, but can also help inform the broader and emerging context of climate services development in Europe. Electronic supplementary material The online version of this article (doi:10.1007/s10584-016-1671-8) contains supplementary material, which is available to authorized users.

Livelihoods in drylands are already challenged by the demands of climate variability, and climate change is expected to have further implications for water resource availability in these regions. This paper characterizes the vulnerability of an irrigation-dependent agricultural community located in the Elqui River Basin of Northern Chile to water and climate-related conditions in light of climate change. The paper documents the exposures and sensitivities faced by the community in light of current water shortages, and identifies their ability to manage these exposures under a changing climate. The IPCC identifies potentially increased aridity in this region with climate change; furthermore, the Elqui River is fed by snowmelt and glaciers, and its flows will be affected by a warming climate. Community vulnerability occurs within a broader physical, economic, political and social context, and vulnerability in the community varies amongst occupations, resource uses and accessibility to water resources, making some more susceptible to changing conditions in the future. This case study highlights the need for adaptation to current land and water management practices to maintain livelihoods in the face of changes many people are not expecting.

During the last 30 years, the climate of the West African Sahel has undergone various changes, especially in terms of rainfall. This has large consequences for the poor-resource farmers depending mainly on rainfed agriculture. This paper investigates the impacts of current climate variability and future climate change on groundnut and cowpea production in Niger for three major agricultural regions, including the groundnut basin.Niger was one of the largest West African groundnut producing and exporting countries. Groundnut production – as a cash crop – dropped fromabout 312,000 tons in the mid 1960s (about 68% exported) to as low as 13,000tons in 1988 and increased again to 110,000 tons in 2000. Cowpea, a food crop, showsa different tendency, going from 4,000 tons in the mid fifties to a maximum of 775,000 tons in 1997, and its cultivated area is still increasing. It is also a cash crop in local economies (especially for women).To highlight the impact of climate change on groundnut and cowpea production (significantly determined by rainfall in July, August and September), the following components of the rainfall regime were calculated for the period 1951–1998: mean annual and monthly rainfall, beginning, end and lengthof the rainy season, number of rainy days per month, amount of rainfall per rainy day and the maximum length of dry spell per month. Three sub-periods whose duration varied per region were defined: for Dosso 1951–1968,1969–1984 and 1985–1998; for Maradi 1951–1970, 1971–1987 and1988–1998; and for Zinder 1951–1966, 1967–1984 and 1985–1998. A change in rainfallregime components was observed between the three sub-periods, which were characterized in chronological order by wet, dry and intermediate conditions. To assess the impact of climate variability and change on groundnut and cowpea production, a statistical modeling approach has been followed, based on thirteen predictors as described and discussed in the preceding paper. Climate change is mimicked in terms of reduced total amount of rainfall for the three main rainfall months and an increased temperature, while maintaining other significant predictors at a constant level. In 2025,production of groundnut is estimated to be between 11 and 25% lower, while cowpeayield will fall maximally 30%. Various strategies to compensate thispotential loss are presented for the two crops.

While all sectors of the economy can be impacted by climate variability and change, the agricultural sector is arguably the most tightly coupled to climate where changes in precipitation and temperature directly control plant growth and yield, as well as livestock production. This paper analyzes the direct and cascading effects of temperature, precipitation, and carbon dioxide (CO2) on agronomic and horticultural crops, and livestock production in Indiana through 2100. Due to increased frequency of drought and heat stress, models predict that the yield of contemporary corn and soybean varieties will decline by 8–21% relative to yield potential, without considering CO2 enhancement, which may offset soybean losses. These losses could be partially compensated by adaptation measures such as changes in cropping systems, planting date, crop genetics, soil health, and providing additional water through supplemental irrigation or drainage management. Changes in winter conditions will pose a threat to some perennial crops, including tree and fruit crops, while shifts in the USDA Hardiness Zone will expand the area suitable for some fruits. Heat stress poses a major challenge to livestock production, with decreased feed intake expected with temperatures exceeding 29 °C over 100 days per year by the end of the century. Overall, continued production of commodity crops, horticultural crops, and livestock in Indiana is expected to continue with adaptations in management practice, cultivar or species composition, or crop rotation.

Climate change is threatening food security in many tropical countries, where a large proportion of food is produced by vulnerable smallholder farmers. Interventions are available to offset many of the negative impacts of climate change on agriculture, and they can be tailored to local conditions often through relative modest investments. However, little quantitative information is available to guide investment or policy choices at a time when countries and development agencies are under pressure to implement policies that can help achieve Sustainable Development Goals while coping with climate change. Among smallholder adaptation options, developing seeds resilient to current and future climate shocks expected locally is one of the most important actions available now. In this paper, we used national and local data to estimate the costs of climate change to smallholder farmers in Malawi and Tanzania. We found that the benefits from adopting resilient seeds ranged between 984 million and 2.1 billion USD during 2020–2050. Our analysis demonstrates the benefits of establishing and maintaining a flexible national seed sector with participation by communities in the breeding, delivery, and adoption cycle.

Drought is known as a “creeping disaster” because drought impacts are usually noticed months or years after a drought begins. In the Pacific Island Countries and Territories (PICTs), there is almost no ability to tell when a drought will begin or end, especially for droughts other than meteorological droughts. Monitoring, forecasting and managing drought in the PICTs is complex due to the variety of different ways droughts occur, and the diverse direct and indirect causes and consequences of drought, across the PICT region. For example, the impacts of drought across the PICTs vary significantly depending on (i) the type of drought (e.g. meteorological drought or agricultural drought); (ii) the location (e.g. high islands versus atolls); (iii) socioeconomic conditions in the location affected by drought; and (iv) cultural attitudes towards the causes of drought (e.g. a punishment from God versus a natural process that is potentially predictable and something that can be managed). This paper summarises what is known and unknown about drought impacts in the PICTs and provides recommendations to guide future research and investment towards minimising the negative impacts of droughts when they inevitably occur in the PICTs.

Timely and accurate agricultural impact assessments for droughts are critical for designing appropriate interventions and policy. These assessments are often ad hoc, late, or spatially imprecise, with reporting at the zonal or regional level. This is problematic as we find substantial variability in losses at the village-level, which is missing when reporting at the zonal level. In this paper, we propose a new data fusion method—combining remotely sensed data with agricultural survey data—that might address these limitations. We apply the method to Ethiopia, which is regularly hit by droughts and is a substantial recipient of ad hoc imported food aid. We then utilize remotely sensed data obtained near mid-season to predict substantial crop losses of greater than or equal to 25% due to drought at the village level for five primary cereal crops. We train machine learning models to predict the likelihood of losses and explore the most influential variables. On independent samples, the models identify substantial drought loss cases with up to 81% accuracy by mid- to late-September. We believe the proposed models could be used to help monitor and predict yields for disaster response teams and policy makers, particularly with further development of the models and integration of soon-to-be available high-resolution, remotely sensed data such as the Harmonized Landsat Sentinel (HLS) data set.

The increasing frequency of climatic risks, such as flood, drought, heat and cold waves, is causing significant loss of farm productivity and income in agriculturally dependent communities. Timely availability of reliable information on weather conditions, agro-advisories, and market information can help to minimize losses in agriculture. This paper presents a scientific and integrated approach to identify areas of high agriculture vulnerability to climate change and availability of ICT services for dissemination of CSA information in the vulnerable areas. This study was illustrated for India where the majority of the population depends on agriculture for their livelihoods, and this sector is highly vulnerable to climate change. The study presents four regions: i) high agriculture vulnerability and low ICT services, ii) high agriculture vulnerability and high ICT services, iii) low agriculture vulnerability and low ICT services, and iv) low agriculture vulnerability and high ICT services. This methodology, which is simple, uses available data, and is easy to apply, can be useful to prioritize locations for climate-smart interventions, mode of CSA information dissemination using ICT services, and increase coverage of agro-ICT services through development of ICT services in the locations where climate change impact is high and ICT services are very low. This study also showed that there is a need to improve the quality of existing climate information and agro-advisory services in the climate risk-prone areas.

Climate-smart agriculture (CSA) has a significant role to play in reducing the gender gap in labor burden for women in agriculture. A targeted approach to address this gap can be useful in developing a women-responsive climatic risk management plan focused on reducing their labor burden in agriculture, especially in areas with high climate risks. The paper therefore presents a top–down approach to identify potential labor-saving CSA technologies for women farmers in areas facing high climate risks. It involves mapping women in agriculture, climate risks, and poverty hotspots and entails understanding the role of women in agricultural activities to identify the suitable CSA options for reducing the levels of labor drudgery. The study is illustrated for Nepal where feminization of agriculture is rapidly increasing, a high level of climatic risks persists, and adaptive capacity to climate change is very low, especially among women in agriculture. Results are presented for two hotspot districts, Rupandehi and Chitwan. Household socioeconomic characteristics were found to play a major role in women’s labor contribution in different crop production activities. Discussions with farmers provided a list of more than 15 CSA interventions with labor reduction as well as yield-improving potential. Accordingly, considering the local crop, agro-climate, and social conditions, and women’s participation in different agricultural activities, CSA technologies and practices such as direct seeded rice (zero tillage and low tillage using machine), green manuring (GM), laser land leveling (LLL), and system of rice intensification (SRI) were found to potentially reduce women’s drudgery in agriculture along with improvement in productivity and farm income.

Evidence from climate-smart village (CSV) approach to mainstream climate-smart agriculture (CSA) demonstrates improved productivity, income, and reduced climatic risks. However, its contribution to gender empowerment in diverse farming households is not documented. This study creates a Gender Empowerment Index for climate-smart villages (GEI-CSV) based on four major measurable indicators—political, economic, agricultural, and social. The gender gap was derived by mapping difference in empowerment levels across selected CSVs and non-CSVs. These indicators can be used as a vital tool to understand the process of gender empowerment that can trigger the entry points to achieve gender equality, which is also an important aspect in the adoption of climate-smart agriculture practices (CSAPs). The study measures empowerment at the inter-household and intra-household level across CSVs and non-CSVs from the individual household survey with both female and male members of the same household. This paper provides evidence demonstrating how gender empowerment differs in CSVs and non-CSVs from selected climate-smart villages (community-based approach) in two contrasting ecologies and socio-economic settings of India. The study documents the existing gender gap in CSVs and non-CSVs across India’s western (Haryana) and eastern (Bihar) Indo-Gangetic Plains (IGP). Irrespective of CSVs and non-CSVs, considerable differences in outlook and gender gap were observed between Bihar and Haryana. Both women and men in Bihar are less empowered than they are in Haryana. High empowerment level in CSVs than non-CSVs shows that the concept of CSVs has brought a change towards knowledge and capacity enhancement of both women and men farmers promoting gender equality in farming households with a varying scope of interventions made and required for scaling CSAPs across the diversity of farming households.

The effect of climate change on agriculture in the UK is here assessed using a comprehensive series of policy-relevant agro-climate indicators characterising changes to climate resources and hazards affecting productivity and operations. This paper presents projections of these indicators across the UK with gridded observed data and UKCP18 climate projections representing a range of greenhouse gas emissions scenarios. The projections can be used to inform climate change mitigation and adaptation policy. There will be substantial changes in the climate resource and hazard across the UK during the twenty-first century if emissions continue to follow a high trajectory, and there will still be some changes if emissions reduce to achieve international climate policy targets. Growing seasons for certain crops will lengthen, crop growth will be accelerated, and both drought and heat risks (for some types of production) will increase. Soils will become drier in autumn, although there will be less change in winter and spring. The longer growing seasons and warmer temperatures provide opportunities for new crops, subject to the effects of increasing challenges to production. Most of the changes are relatively consistent across the UK, although drought risk and heat stress risk increase most rapidly in the south and east. The climate change trend is superimposed onto considerable year to year variability. Although there is strong consensus across climate projections on the direction of change, there is considerable uncertainty in the rate and magnitude of change for a given emissions scenario. For the temperature-based indicators, this reflects uncertainty in climate sensitivity, whilst for the precipitation-based indicators largely reflects uncertainty in projected changes in the weather systems affecting the UK.

Crop breeding for resilience to changing climates is a key area of investment in African agricultural development, but proactively breeding for uncertain future climates is challenging. In this paper, we characterise efforts to breed new varieties of crops for climate resilience in southern Africa and evaluate the extent to which climate model projections currently inform crop breeding activity. Based on a survey of seed system actors, we find that the prioritisation of crops and traits is only informed to a limited extent by modelled projections. We use an ensemble of CORDEX models for mid and end of century for southern Africa to test some of the assumptions that underpin current breeding activity, particularly associated with breeding for reduced durations and drought tolerance in maize, and demonstrate some of the ways in which such projections can help to inform breeding priorities and agenda setting (e.g. through the case of assessing cassava toxicity risk). Based on these examples, we propose five potential applications of climate models in informing breeding priorities. Furthermore, after unpacking the sources of uncertainty within the presented model projections, we discuss general principles for the appropriate use of climate model information in crop breeding.

The interior southwest United States is one of the hottest, driest regions on the planet, yet irrigated cropland agriculture is successfully practiced where there is access to surface water and/or groundwater. Through climate change, the southwest is projected to become even hotter and drier, increasing the challenges faced by farmers across the region. We can assess the vulnerability of cropland agriculture, to assist in developing potential solutions to these challenges of warming temperatures and water scarcity. However, these types of biophysical vulnerability assessment usually generate technological or policy-level solutions that do not necessarily account for farmers’ ability to respond to climate change impacts. Further, there are non-climatic factors that also threaten the future of agriculture in the region, such as population increase, loss of agricultural land, and increasing competition for depleting water resources. In this paper, we assert that to fully address how southwestern farmers may respond to climate change impacts, we must consider both biophysical outcome and contextual vulnerabilities. Future research on individual localities and/or specific commodities and including cross-disciplinary analysis of socio-economic, institutional, cultural, and political factors alongside biophysical factors will help to develop more substantive understanding of system vulnerabilities and feasible adaptive solutions.

Assessing regional-scale vulnerability of agricultural systems to climate change and variability is vital in securing food and fiber systems, as well as sustaining rural livelihoods. Farmers, ranchers, and forest landowners rely on science-based, decision-relevant, and localized information to maintain production, ecological viability, and economic returns. This paper synthesizes the collection of research on the future of agricultural production in the Southwestern United States. A variety of assessment methods indicate the diverse impacts and risks across the Southwest, often related to water availability, which drives adaptive measures in this region. Sector- or species-specific adaptive measures have long been practiced in this region and will continue to be necessary to support agricultural production as a regional enterprise. Diversification of crop selection and income source imparts climate resilience. Building upon biophysical vulnerability through incorporating social and economic factors is critical to future adaptation planning efforts. The persistence and adaptive capacity of agriculture in the water-limited Southwest serves as an instructive example for producers outside the region expecting drier and warmer conditions and may offer solutions to reduce future climate impacts.

A growing body of research shows that extreme climatic events, e.g. heatwave, rainstorms and droughts, are becoming more frequent and intensified across various regions of the world. Australia is not isolated from these changes with marked increase in both rainfall and temperature extremes. Inherently, we understand that exposure to these extreme events could encourage decisions about population flow, and quantifying this linkage is challenging, especially for communities in small areas with an average of 10,000 people. Using spatio-temporal statistical techniques, this paper examines the possible environmental and socio-economic drivers associated with population flows of small communities as well as the possible predictive scenarios due to the effects introduced by climatic extremes. The analysis has been undertaken for a case-study region in the Murray-Darling Basin, Australia, where the economy is underpinned by agriculture and is sensitive to climate variability and extremes. The analysis reveals that in addition to the socio-economic factors, the environmental variables have a statistically significant association on shaping the distribution of the population flows in the study area. This statistical analysis can direct further data collection and causality analysis and be beneficial for policy makers, stakeholders and local communities to work together to adapt the Basin to climate extremes and changes.

This paper provides one of the first empirical studies that examine the impact of climate change adaptation practices on technical efficiency (TE) among smallholder farmers in Nepal. An adaptation index is used to explore the impact of farmers’ adaptation on TE using the stochastic frontier analysis framework. Data for six districts of Nepal representing all three agro-ecological regions (terai, hill, and mountain) were collected from a focus group discussion, a stakeholder workshop and a household survey. The survey shows that about 91% of the farming households have adopted at least one practice to minimize the adverse impacts of climate change. Empirical results reveal that adaptation is an important factor explaining efficiency differentials among farming households. Those adopting a greater number of adaptation practices on a larger scale are, on average, found to be 13% more technically efficient than those adopting fewer practices on smaller scale. The empirical results also show that average TE is only 0.72, indicating that there are opportunities for farming households in Nepal to further improve productive efficiency, on average by 28%. Other important factors that explain variations in the productive efficiency across farming households include farmer’s education level, irrigation facilities, market access, and social capital such as farmer’s participations in relevant agricultural organizations and clubs. This study provides empirical evidence to policy makers that small scale adjustments made by farmers in response to climate change impacts are effective in improving farmers’ efficiency in agriculture production. This indicates a need for farmers’ involvement in climate change adaptation planning.

Increasing global temperatures are likely to have major impacts on agriculture, but the effects will vary by crop and location. This paper describes the temperature sensitivity and exposure of selected specialty crops in California. We used literature synthesis to create several sensitivity indices (from 1 to 4) to changes in winter minimum and summer maximum temperature for the top 14 specialty crops. To estimate exposure, we used seasonal period change analysis of mid-century minimum and maximum temperature changes downscaled to county level from CMIP5 models. We described crop vulnerability on a county basis as (crop sensitivity index × county climate exposure × area of crop in county); individual crop vulnerabilities were combined to create an aggregate index of specialty crop vulnerability by county. We also conducted analyses scaled by crop value rather than area, and normalized to total specialty crop area in each county. Our analyses yielded a spatial assessment highlighting seasons and counties of highest vulnerability. Winter and summer vulnerability are correlated, but not highly so. High-producing counties (e.g., Fresno County in the San Joaquin Valley) are the most vulnerable in absolute terms, while northern Sacramento Valley counties are the most vulnerable in relative terms, due to their reliance on heat-sensitive perennial crops. Our results illustrate the importance of examining crop vulnerability from different angles. More physiological and economic research is needed to build a comprehensive picture of specialty crop vulnerability to climate change.

The states of Colorado, Montana, Nebraska, North Dakota, South Dakota, and Wyoming comprise the Northern Great Plains region of the USA. The soil and water resources contained in this region have historically supported highly diverse and productive agriculture enterprises that provide a significant proportion of the food, feed, and oilseed for the nation. The region also provides ecological services that influence air, water, and soil quality along with biological diversity. Combined with livestock production and a biofuel industry, crop production forms an integrated system that can offer producers flexibility in management decisions. Projected climatic changes for this region include increasing atmospheric CO2, a longer, warmer growing season, and increased precipitation, likely received in more frequent extreme events. These changes will impact soil and water resources in the region and create opportunities and challenges for land managers. The objectives of this paper are to describe anticipated impacts of projected mid-(2050) and late-(2085) climatic changes on crop production systems in the Northern Great Plains and provide adaptation strategies that should be developed to take advantage of positive and mitigate negative changes. Projected climatic changes will influence agricultural productivity directly as well as indirectly due to changes in weed pressure, insect populations, and diseases. A warmer, longer growing season will change the crops and distribution of those crops grown within the region. An increase in the number of extreme temperature events (high daytime highs or nighttime lows) will decrease crop yields due to increased plant stress during critical pollination and grain fill periods. Adaptation strategies to reduce vulnerability of soil and water resources to projected climatic changes include increasing cropping intensity, reducing tillage intensity, and use of cover crops to provide surface cover to reduce erosion potential and improve nutrient and water use efficiency. Increased use of perennial forages, crop residue, and failed crops in integrated crop-livestock systems will add biological diversity and provide options for converting vegetation biomass into animal protein. Socio-economic changes will need to be incorporated into adaptation strategies planning to insure that sustaining ecosystem services and meeting desired production and conservation goals is accomplished. Education and extension services will be needed to transfer adaptive knowledge in a timely manner to producers in the field.

There is increasing interest in transformational adaptation to climate change in agriculture, i.e. adaptation that involves large-scale, novel responses to reduce vulnerability to climate risks. Transformational adaptation is less well understood than incremental adaptation, since there are few studies of agricultural enterprises making transformative changes in response to climatic change. This paper is an in-depth study of an agricultural company’s attempt to implement transformational adaptation in response to climate change. We document the Peanut Company of Australia’s (PCA) response to predicted climatic change by expanding its operations into Katherine, Northern Territory, after decades of below-average rainfall in their traditional production region in south-east Queensland. Our research question was: what conditions and processes influenced the outcome of the company’s response? We conducted 37 semi-structured interviews with company, government and community representatives to examine diverse perspectives on PCA’s expansion into Katherine and its subsequent strategic retreat. To reveal insights into why, when and how this attempted transformational adaptation occurred we reviewed the literature and identified Park et al.’s (2012) Adaptation Action Cycles (AAC) framework and aspects from the organisational adaptation literature as useful for our analysis. Based on our findings, we revised the AAC framework to better reflect the way that incremental adaptation in situ can occur simultaneously with transformational adaptation at a new location. Our study illustrates that transformational adaptation in agriculture is difficult, complex, risky and costly and sometimes unsuccessful, revealing some of the challenges of and barriers to organisational adaptation in agriculture, especially when moving to a new location.

Downscaled climate change projections for California, when translated into changes in irrigation water delivery and then into profit from agriculture in the Central Valley, show an increase in conventional measures of variability such as the variance. However, these increases are modest and mask a more pronounced increase in downside risk, defined as the probability of unfavorable outcomes of water supply or profit. This paper describes the concept of downside risk and measures it as it applies to outcomes for Central Valley agriculture projected under four climate change scenarios. We compare the effect of downside risk aversion versus conventional risk aversion or risk neutrality when assessing the impact of climate change on the profitability of Central Valley agriculture. We find that, when downside risk is considered, the assessment of losses due to climate change increases substantially.

Deltas around the globe are facing a multitude of intensifying environmental change and development-linked pressures. One key concern is the reduction in the quantity of suspended sediment reaching and building floodplains. Sediment deposition provides multiple services to deltaic social-ecological systems, in particular, countering the subsidence of the delta-body, and providing plentiful nutrients. Experiencing particularly rapid change is the Vietnamese Mekong Delta (VMD). In An Giang Province an increasing number of high dyke rings, which exclude the flood and facilitate triple rice-cropping, simultaneously prevent much of the sediment load from reaching the floodplain. This paper explores the trade-offs implicit in the decision to shift from (i) doublecropping (higher sediment deposition) to (ii) triple cropping (lower sediment deposition) by asking: what is the impact of the shift on VMD farmers? Is it sustainable? And what is the significance of the associated sediment exclusion? A novel survey of An Giang rice farmers was conducted, investigating key agricultural practices, and uniquely, the farmers’ estimates of annual sediment deposition depth. The survey elicits some key changes under the adapted system (ii), particularly, unsustainable trajectories in the yield to fertiliser ratio which penalise land-poor farmers. Furthermore, the value (to farmers) of the sediment contribution to agricultural fertilisation which is lost due to triple-cropping is estimated at USD 15 (±5) million annually. We argue that our growing understanding of the importance of sediment in the deltaic social-ecological system may be revealing an emergent risk; arising from conflicting long and short-term adaptation and agricultural development objectives. Electronic supplementary material The online version of this article (doi:10.1007/s10584-016-1684-3) contains supplementary material, which is available to authorized users.

The overall global-scale consequences of climate change are dependent on the distribution of impacts across regions, and there are multiple dimensions to these impacts. This paper presents a global assessment of the potential impacts of climate change across several sectors, using a harmonised set of impacts models forced by the same climate and socio-economic scenarios. Indicators of impact cover the water resources, river and coastal flooding, agriculture, natural environment and built environment sectors. Impacts are assessed under four SRES socio-economic and emissions scenarios, and the effects of uncertainty in the projected pattern of climate change are incorporated by constructing climate scenarios from 21 global climate models. There is considerable uncertainty in projected regional impacts across the climate model scenarios, and coherent assessments of impacts across sectors and regions therefore must be based on each model pattern separately; using ensemble means, for example, reduces variability between sectors and indicators. An example narrative assessment is presented in the paper. Under this narrative approximately 1 billion people would be exposed to increased water resources stress, around 450 million people exposed to increased river flooding, and 1.3 million extra people would be flooded in coastal floods each year. Crop productivity would fall in most regions, and residential energy demands would be reduced in most regions because reduced heating demands would offset higher cooling demands. Most of the global impacts on water stress and flooding would be in Asia, but the proportional impacts in the Middle East North Africa region would be larger. By 2050 there are emerging differences in impact between different emissions and socio-economic scenarios even though the changes in temperature and sea level are similar, and these differences are greater in 2080. However, for all the indicators, the range in projected impacts between different climate models is considerably greater than the range between emissions and socio-economic scenarios.

This paper analyzes the meteorological drought events in Paraguay in the period of 1964 to 2011, using the Standardized Precipitation Index (SPI). The objective is to determine if the frequency and/or severity of droughts has increased or decreased in the last years, in response of climate change. They The southernmost parts of the country are affected by severe droughts producing damage to soybean and corn crop during the rainy season (October–March) especially during the summer of 2008–2009. The years of 1967, 1968, 1978, 1979, 2000 and 2008 was identified as severe to extreme drought events and coincides with La Nina event. However, the relationship between all drought events, especially those agricultural droughts and La Nina is not clear, suggesting the necessity of new research, focusing on new drivers to explain the cause of the droughts. The economy of Paraguay, based for good part on agriculture, is clearly vulnerable to droughts. Even though no undeniable increasing trend in drought frequency/severity was detected, contingency plans to diminish drought impacts ought to be elaborated.

Climate models agree that semi-arid regions around the world are likely to experience increased rainfall variability and longer droughts in the coming decades. In regions dependent on agriculture, such changes threaten to aggravate existing food insecurity and economic underdevelopment, and to push migration to urban areas. In the Brazilian semi-arid region, the Sertao, farmers’ vulnerability to climate—past, present, and future—stems from several factors, including low yielding production practices and reliance on scarce and seasonally variable water resources. Using interpolated local climate data, we show that, since 1962, in the Bacia do Jacuipe—one of the poorest regions in the Sertao of Bahia state—average temperatures have increased ~ 2 °C and rainfall has decreased ~ 350 mm. Over the same time period, average milk productivity—the main rural economic activity in the county—has fallen while in Brazil and in Bahia as a whole milk productivity has increased dramatically. This paper teases apart the drivers of climate vulnerability of the Bacia do Jacuipe in relation to the rest of Bahia. We then present the results of a suite of pilot projects by Adapta Sertao, a coalition of organizations working to improve the adaptive capacity of farmers living in the semi-arid region. By testing a number of different technologies and arrangements at the farm level, Adapta Sertao has shown that interventions focused on balanced animal diets and efficient irrigation systems can help reduce (but not eliminate) the dependence of production systems from climate. They are thus viable adaptation strategies that should be tested at a larger scale, with implications for semi-arid regions worldwide.

For agriculture, there are three major options for mitigating greenhouse gas (GHG) emissions: 1) productivity improvements, particularly in the livestock sector; 2) dedicated technical mitigation measures; and 3) human dietary changes. The aim of the paper is to estimate long-term agricultural GHG emissions, under different mitigation scenarios, and to relate them to the emissions space compatible with the 2 °C temperature target. Our estimates include emissions up to 2070 from agricultural soils, manure management, enteric fermentation and paddy rice fields, and are based on IPCC Tier 2 methodology. We find that baseline agricultural CO2-equivalent emissions (using Global Warming Potentials with a 100 year time horizon) will be approximately 13 Gton CO2eq/year in 2070, compared to 7.1 Gton CO2eq/year 2000. However, if faster growth in livestock productivity is combined with dedicated technical mitigation measures, emissions may be kept to 7.7 Gton CO2eq/year in 2070. If structural changes in human diets are included, emissions may be reduced further, to 3–5 Gton CO2eq/year in 2070. The total annual emissions for meeting the 2 °C target with a chance above 50 % is in the order of 13 Gton CO2eq/year or less in 2070, for all sectors combined. We conclude that reduced ruminant meat and dairy consumption will be indispensable for reaching the 2 °C target with a high probability, unless unprecedented advances in technology take place.

In the past 5 years there has been a proliferation of efforts to map climate change “hotspots” — regions that are particularly vulnerable to current or future climate impacts, and where human security may be at risk. While some are academic exercises, many are produced with the goal of drawing policy maker attention to regions that are particularly susceptible to climate impacts, either to mitigate the risk of humanitarian crises or conflicts or to target adaptation assistance. Hotspots mapping efforts address a range of issues and sectors such as vulnerable populations, humanitarian crises, conflict, agriculture and food security, and water resources. This paper offers a timely assessment of the strengths and weaknesses of current hotspots mapping approaches with the goal of improving future efforts. It also highlights regions that are anticipated, based on combinations of high exposure, high sensitivity and low adaptive capacity, to suffer significant impacts from climate change.

Ghana and Cote d’Ivoire are the world’s leading cocoa (Thebroma cacao) producing countries; together they produce 53 % of the world’s cocoa. Cocoa contributes 7.5 % of the Gross Domestic Product (GDP) of Cote d’Ivoire and 3.4 % of that of Ghana and is an important cash crop for the rural population in the forest zones of these countries. If progressive climate change affected the climatic suitability for cocoa in West Africa, this would have implications for global cocoa output as well as the national economies and farmer livelihoods, with potential repercussions for forests and natural habitat as cocoa growing regions expand, shrink or shift. The objective of this paper is to present future climate scenarios for the main cocoa growing regions of Ghana and Cote d’Ivoire and to predict their impact on the relative suitability of these regions for growing cocoa. These analyses are intended to support the respective countries and supply chain actors in developing strategies for reducing the vulnerability of the cocoa sector to climate change. Based on the current distribution of cocoa growing areas and climate change predictions from 19 Global Circulation Models, we predict changes in relative climatic suitability for cocoa for 2050 using an adapted MAXENT model. According to the model, some current cocoa producing areas will become unsuitable (Lagunes and Sud-Comoe in Cote d’Ivoire) requiring crop change, while other areas will require adaptations in agronomic management, and in yet others the climatic suitability for growing cocoa will increase (Kwahu Plateu in Ghana and southwestern Cote d’Ivoire). We recommend the development of site-specific strategies to reduce the vulnerability of cocoa farmers and the sector to future climate change.

This paper investigates the impacts of climate change on US returns to research investments on agricultural productivity. We examine this using a historical data set in a panel time-series econometric model of state agricultural productivity. The fitted model allows derivation of the rate of return to research investments and the effects of climate change thereon. We find climate change is altering the rate of return to public agricultural research in a spatially heterogeneous manner. Increases in precipitation raise returns to research, while the impact of higher temperatures varies by region, are negative in Southern areas, particularly the Southern Plains, and positive in northern areas. We simulate the impact of projected climate change and find cases where agricultural productivity is reduced, for example in the Southern Plains. Finally, we consider the amount of research investment that is needed to adapt to overcome the impacts of climate change on agricultural productivity. Under the 2100 scenario, a 7–17 % increase in total US research investment is needed to adapt, but effects by region differ greatly—some requiring little changes and the Southern Plain requiring an increase as high as 57 %.

Most research on future climate change discusses mitigation and impacts/adaptation separately. However, mitigation will have implications for impacts and adaptation. Similarly, impacts and adaptation will affect mitigation. This paper begins to explore these two veins of research simultaneously using an integrated assessment model. We begin by discussing the types of interactions one might expect by impact sector. Then, we develop a numerical experiment in the agriculture sector to illustrate the importance of considering mitigation, impacts, and adaptation at the same time. In our experiment, we find that climate change can reduce crop yields, resulting in an expansion of cropland to feed a growing population and a reduction in bioenergy production. These two effects, in combination, result in an increase in the cost of mitigation.

Ethiopia’s agriculture is predominantly rainfed and hence any irregularity in weather conditions has adverse welfare implications. Using panel data, this paper analyzes the effect of rainfall shocks on Ethiopian rural households’ food security and vulnerability over time while controlling for a range of other factors. To this end, we generate a time-variant household food security index which is developed by principal components analysis. Based on this index, households are classified into relative food security groups and their socioeconomic differences are assessed. The exploratory results show that compared to the less secured households, the more secured ones have male and literate household heads, tend to have a greater number of economically active household members, own more livestock, experience better rainfall outcome, and participate in local savings groups. Using the food security index as the dependent variable, we use a fixed effects instrumental variable regression model to identify determinants of households’ food security over time and find that rainfall variability is an important factor. Moreover, household size, participation in local savings groups, and livestock ownership positively affect food security. Results from multinomial logistic regression model complement the fixed effects instrumental variable regression results by showing that the level and variability of rainfall are important determinants of persistent food insecurity and vulnerability. The results highlight the need for efficient risk reduction and mitigation programs to improve risk exposure and coping ability of rural households. Careful promotion of investment in infrastructure to support irrigation and water resources development is one aspect worth considering.

There is growing evidence that, as a result of global climate change, some of the most severe weather events could become more frequent in Europe over the next 50 to 100 years. The paper aims to (i) describe observed trends and scenarios for summer heat waves, windstorms and heavy precipitation, based on results from simulations with global circulation models, regional climate models, and other downscaling procedures, and (ii) discuss potential impacts on agricultural systems and forests in Switzerland. Trends and scenarios project more frequent heavy precipitation during winter corresponding, for example, to a three-fold increase in the exceedance of today's 15-year extreme values by the end of the 21st century. This increases the risk of large-scale flooding and loss of topsoil due to erosion. In contrast, constraints in agricultural practice due to waterlogged soils may become less in a warmer climate. In summer, the most remarkable trend is a decrease in the frequency of wet days, and shorter return times of heat waves and droughts. This increases the risk of losses of crop yield and forage quality. In forests, the more frequent occurrence of dry years may accelerate the replacement of sensitive tree species and reduce carbon stocks, and the projected slight increase in the frequency of extreme storms by the end of the century could increase the risk of windthrow. Some possible measures to maintain goods and services of agricultural and forest ecosystems are mentioned, but it is suggested that more frequent extremes may have more severe consequences than progressive changes in means. In order to effectively decrease the risk for social and economic impacts, long-term adaptive strategies in agriculture and silviculture, investments for prevention, and new insurance concepts seem necessary.

This paper describes two case studies of demand-side water management in the Okanagan region of southern British Columbia, Canada. The case studies reveal important lessons about how local context shapes the process of adaptation; in these cases, adaptation to rising and changing water demand under a regime of increasingly limited supply in a semi-arid region. Both case studies represent examples of water meter implementation, specifically volume-based pricing in a residential area and as a compliance tool in a mainly farming district. While the initiative was successful in the residential setting, agricultural metering met with stiff resistance. These cases suggest many factors shape the character of the adaptation process, including: interpretation of the signal relative to context, newness of the approach, consumer values, and local and provincial political agendas. Although context has been explored in resource management circles, thus far climate change adaptation research has not adequately discussed the embeddedness of adaptation. In other words, how context matters and what aspects of context, unrelated to climate change, could encourage or thwart the act of adapting. This study is a simple illustration of the potential drivers, barriers and enabling factors that have influenced the adaptation process of water management decisions in the Okanagan.

During the recent decade, with the growing recognition of the possibility of climate change and clear evidence of observed changes in climate during 20th century, an increasing emphasis on food security and its regional impacts has come to forefront of the scientific community. In recent times, the crop simulation models have been used extensively to study the impact of climate change on agricultural production and food security. The output provided by the simulation models can be used to make appropriate crop management decisions and to provide farmers and others with alternative options for their farming system. It is expected that in the coming decades with the increased use of computers, the use of simulation models by farmers and professionals as well as policy and decision makers will increase. In India, substantial work has been done in last decade aimed at understanding the nature and magnitude of change in yield of different crops due to projected climate change. This paper presents an overview of the state of the knowledge of possible effect of the climate variability and change on food grain production in India.

The thesis of this paper is that impacts from climatic change can be evaluated effectively as changes in the frequency of short-term, anomalous climatic events. These can then be expressed as changes in the level of risk of impact from climatic extremes. To evaluate this approach, the risk of crop failure resulting from low levels of accumulated temperature is assessed for oats farming in southern Scotland. Annual accumulated temperatures are calculated for the 323-year-long temperature record compiled by Manley for Central England. These are bridged across to southern Scotland and, by calculating mean levels of risk for different elevations, an average ‘risk surface’ is constructed. One-in-10 and 1-in-50 frequencies of crop failure are assumed to delineate a high-risk zone, which is mapped for the 323-year period by constructing isopleths of these risk levels. By redrawing the risk isopleths for warm and cool 50-year periods, the geographical shift of the high-risk zone is delineated. The conclusion is that relatively recent and apparently minor climatic variations in the United Kingdom have in fact induced substantial spatial changes in levels of agricultural risk. An advantage of expressing climatic change as a change in agricultural risk is that support programs for agriculture can be retuned to accommodate acceptable frequencies of impact by adjusting support levels to match new risk levels.

Changes in the agriculture sector are essential to mitigate and adapt to climate change, meet growing food demands, and improve the livelihoods of poor smallholder producers. What agricultural strategies are needed to meet these challenges? To what extent are there synergies among these strategies? This paper examines these issues for smallholder producers in Kenya across several agroecological zones. Several practices emerge as triple wins, supporting climate adaptation, greenhouse gas mitigation, and profitability goals. In particular, integrated soil fertility management and improved livestock feeding are shown to provide multiple benefits across all agroecological zones examined. Triple wins of other agricultural practices are limited to specific agroecological zones. Irrigation and soil and water conservation, for example, are essential for adaptation, mitigation, and profitability in arid areas. The results suggest that agricultural investments targeted toward these triple-win strategies will have the greatest payoff in terms of increased resilience of farm and pastoralist households and global climate change mitigation. To reap the benefits of triple-win strategies will require that policymakers, researchers, and practitioners move away from isolated approaches focused on either adaptation or mitigation or rural income generation toward a more holistic assessment of joint strategies as well as their tradeoffs and synergies.

A recent Climatic Change paper suggests a relationship between climatic change in the 7th century BCE and the fall of the Assyrian Empire. However, available archaeological and textual evidence does not support the hypothesis that Assyria was overpopulated during this time and for that reason susceptible to outbreaks of drought. Besides long-term climatic variation, inter-annual variability in crops has always been very high in the dry farming areas of Upper Mesopotamia. To cope with this uncertainty, the local population developed several strategies (e.g. storage of agricultural surpluses in granaries and artificial irrigation in river valleys). Finally, slave prices, known to have declined during times of famine, were relatively stable during the entire century suggesting absence of prolonged periods of food shortage.