Evidence of climate change impacts on crop comparative advantage and land use

Relative agricultural productivity shocks emerging from climate change will alter regional cropland use. Land allocations are sensitive to crop profits that in turn depend on yield effects induced by changes in climate and technology. We develop and apply an integrated framework to assess the impact of climate change on agricultural productivity and land use for the U.S. Northern Great Plains. Crop-specific yield–weather models reveal crop comparative advantage due to differential yield impacts of weather across the region's major crops, that is, alfalfa, wheat, soybeans, and maize. We define crop profits as a function of the weather-driven yields, which are then used to model land use allocation decisions. This ultimately allows us to simulate the impact of climate change under the RCP4.5 emissions scenario on land allocated to the region's major crops as well as to grass/pasture. Upon removing the trends effects in yields, climate change is projected to lower yields by 33–64% over 2031–2055 relative to 1981–2005, with soybean being the least and alfalfa the most affected crops. Yield projections applied to the land use model at present-day input costs and output prices reveals that Dakotas’ grass acreage will increase by up to 23%, displacing croplands. Wheat acreage is expected to increase by up to 54% in select southeastern counties of North Dakota and South Dakota, where maize/soy acreage had increased by up to 58% during 1995–2016.     

Farm-level adaptation to climate change in Western Bangladesh: An analysis of adaptation dynamics,profitability and risks

Using long-term district-level climate data and a case study from a drought-prone village in western Bangladesh, this research explored trends in climate change, and analysed farmers’ adaptation dynamics, profitability and risks. This is the first study of its kind for drought-prone areas in Bangladesh.Farmers perceived climate changes included increases in temperature and decreases in rainfall which were as consistent with the trends of Chuadanga climate records. Farmers’ adaptation measures included changes in cropping systems, cropping calendars, crop varieties, agronomic practices, crop diversification and improved animal husbandry. Reducing environmental stress, ensuring self-sufficiency in staple crops (mainly rice) and other crop production practices, and enhancing economic viability of farm enterprises have underpinned these adaptations. Off-farm and non-farm wage employment, temporary migration, self-employment and educating children, constituted the core non-farm adaptation strategies.Emerging cropping systems like maize/cucumber and maize/stem amaranth/rice were economically more viable than the traditional rice/rice and rice/maize systems. Despite some uncertainties, farming was preferred to off-farm work, generating higher returns to labour for all cropping systems. Limited access to stress-tolerant varieties, extension services and affordable agricultural credit, combined with high production costs, variability in crop yields and output prices, are the main barriers to adaptation. Stronger agricultural research and support services, affordable credit, community-focussed farming education and training are critically important for effective adaptation to climate change.     

全球变化背景下气候变暖对中国农业生产的影响

全球变化背景下,气候变暖势必对我国农业生产要素、生产环境、农业生产活动及粮食安全产生重大影响。文章采用文献综述与比较研究的方法,系统分析气候变化对我国光资源、温度、水环境和土壤环境等农业生产要素的影响特征及变化趋势,探讨气候变化对我国作物种植区域和种植制度、农作物病虫害、农业生产能力、农业经济与管理等农业生产活动以及农田生态系统过程、农业生态环境(水环境、土壤环境、耕作环境)的实际影响。在此基础上,明确了我国农业在应对气候变化过程中所面临的主要问题:极端气候事件发生频率加大,自然灾害、气象灾害的风险提高,农业生产的波动性增强;农业病虫害的为害时间延长、危害程度加剧、为害范围增大;农业生态环境日趋恶化,农田土壤的干旱化、盐渍化程度加剧,农业生产能力下降;应对气候变化的农业发展策略及其关键技术亟需解决。     

Climate Smart Agriculture? Assessing the Adaptation Implications in Zambia

We examine a set of potentially climate smart agricultural practices, including reduced tillage, crop rotation and legume intercropping, combined with the use of improved seeds and inorganic fertiliser, for their effects on maize yields in Zambia. We use panel data from the Rural Incomes and Livelihoods Surveys merged with a novel set of climatic variables based on geo‐referenced historical rainfall and temperature data to explore the changing effects of these practices with climatic conditions. We estimate the impacts on maize yields, and also on the exhibition of very low yields and yield shortfalls from average levels, as indicators of resilience, while controlling for household characteristics. We find that minimum soil disturbance and crop rotation have no significant impact on these yield outcomes, but that legume intercropping significantly increases yields and reduces the probability of low yields even under critical weather stress during the growing season. We also find that the average positive impacts of modern input use (seeds and fertilisers) are significantly conditioned by climatic variables. Timely access to fertiliser emerges as one of the most robust determinants of yields and their resilience. These results have policy implications for targeted interventions to improve the productivity and the resilience of smallholder agriculture in Zambia in the face of climate change.     

基于大数据分析的农业气候与农作物产量变化研究

[目的]作为农业大国,我国农业产量直接影响着我国未来发展进度,而气候的变化直接牵动着农业产量的变化。[方法]文章基于农业气候对农作物产量的影响,借鉴已有研究从农业气候变化的角度入手,介绍气候变化对农作物产量等方面的影响,并以华北、华东及东北水稻产区为例,通过主成分因素分析设定降水量、气温、光照及太阳辐射度等指标因素,并建立C-D-A模型,[结果]降水量、气温及光照等气候因素对农作物产量的影响明显,其中干旱天气的影响最大。[结论]通过实证分析验证了该模型具有较高的可信度,以期为各种天气条件下保障与提高农作物产量提供理论依据。     

Economic impacts of climate change on the Australian dairy sector

We analyse the economic implications of climate‐driven pressures on the pasture‐based dairy sector in Australia. We use an integrated assessment model that includes a climate scenario generator, a climate‐biophysical response framework and an economywide analytical framework. For the climate scenario generator, we use data from the OzClim database of the Commonwealth Scientific and Industrial Research Organisation. For the climate‐biophysical response framework, we use the DairyMod model with inputs of changes in climate variables from OzClim to quantify climate change effects on pasture growth and productivity. For the economywide analytical framework, we use the National Integrated Assessment Model to quantify the economic implications of these effects on the dairy sector. The simulated pattern of regional changes in dairy output is not a simple function of the changes in dairy productivity. Our results show that the relative size of productivity changes across regions affects the relative competitive advantage of dairy‐producing regions. Several factors affect the regional distribution of simulated dairy‐output changes, including substitution among sources of dairy output and competition for inputs like supplementary feed. An increased output in regions with moderate reductions in dairy productivity may occur because the severely climate‐affected regions absorb the greatest loss in output.     

Cropland use,yields, and droughts: spatial data modeling for Burkina Faso and Niger

For countries with recurrent droughts, the design of drought impact mitigation measures could benefit from analyses of determinants of yields and prices of local crops at regional and district level. This study applies dynamic spatial panel data regression models to yields and prices of four major food crops across regions of Burkina Faso and Niger, over sample periods between 1984 and 2006. Results lend support to mainly simultaneous spatial spillovers, particularly for millet and cowpea prices and sorghum yields in Niger, and maize yields in Burkina Faso. After accounting for these effects, most crop yields are found to be weakly price‐responsive, as envisaged by a supply‐side geographical diffusion hypothesis. Seasonal rainfall elasticity estimates suggest that dominant food crops have slight advantage margins in terms of relative resilience to rainfall shortages. However, this result is to be weighed against low millet yields in Niger, and marked drops in sorghum yields during officially declared droughts in Burkina Faso.     

System of crop intensification for more productive,resource-conserving,climate-resilient,and sustainable agriculture: experience with diverse crops in varying agroecologies

With continually increasing demand for food accompanied by the constraints of climate change and the availability and quality of soil and water, the world’s farmers are challenged to produce more food per hectare with less water, and with fewer agrochemical inputs if possible. The ideas and methods of the system of rice intensification which is improving irrigated rice production are now being extended/adapted to many other crops: wheat, maize, finger millet, sugarcane, tef, mustard, legumes, vegetables, and even spices. Promoting better root growth and enhancing the soil’s fertility with organic materials are being found effective means for raising the yields of many crop plants with less water, less fertilizer, reduced seeds, fewer agrochemicals, and greater climate resilience. In this article, we review what is becoming known about various farmer-centred innovations for agroecological crop management that can contribute to agricultural sustainability. These changes represent the emerging system of crop intensification, which is being increasingly applied in Asian, African, and Latin American countries. More research will be needed to verify the efficacy and impact of these innovations and to clarify their conditions and limits. But as no negative effects for human or environmental health have been identified, making these agronomic options more widely known should prompt more investigation and, to the extent justified by results, utilization of these methodologies.     

Specialization,diversification, and productivity: a panel data analysis of rice farms in Korea

This article examines the microeconomics of productivity associated with specialization/diversification in production activities, with an application to Korean rice farms. Korean rice farms tend to be very small and highly specialized. Our analysis examines the productivity effects associated with both farm size and farm specialization/diversification in Korean agriculture. Relying on farm‐level panel data, the analysis studies farm productivity in a multi‐input multi‐output context, accounting not only for changes in inputs and technical change in rice production, but also for the role of diversification in the production of other crops in current and previous periods. We find positive but small productivity gains from farm diversification. These gains come mostly from complementarity effects across farm outputs, with minimal effect of scale economies. The positive complementarity effects work against nonconvexity effects, which provide strong productivity incentives for rice farms to specialize.     

Climate Change,Crop Selection and Agricultural Revenue in Ghana: A Structural Ricardian Analysis

We apply a Structural Ricardian Model (SRM) to farm‐level data from Ghana for seven principal food crops in order to model the factors which influence farmers' decisions about which food crops to grow and the revenue conditional on these choices. Our application of the SRM incorporates a flexible functional form to allow for the possibility that the effects of temperature and rainfall may not be linearly separable. We use this model as a basis for simulations of the effects of climate change. These simulations suggest that extreme climate change will lead to a significant reduction in the average net revenue per hectare from maize, which accounts for over half of current food production. Across a range of climate change scenarios, there is also substantial substitution of maize for heat‐tolerant millet, and a reduction in the cultivation of other crops. Under most of the climate change scenarios that we consider, these results imply a substantial reduction in the aggregate value of agricultural production, since millet is the lowest‐value crop.     

Utilising farm-level panel data to estimate climate change impacts and adaptation potentials

We combine farm accounting data with high-resolution meteorological data, and climate scenarios to estimate climate change impacts and adaptation potentials at the farm level. To do so, we adapt the seminal model of Moore and Lobell (2014) who applied panel data econometrics to data aggregated from the farm to the regional (subnational) level. We discuss and empirically investigate the advantages and challenges of applying such models to farm-level data, including issues of endogeneity of explanatory variables, heterogeneity of farm responses to weather shocks, measurement errors in meteorological variables, and aggregation bias. Empirical investigations into these issues reveal that endogeneity due to measurement errors in temperature and precipitation variables, as well as heterogeneous responses of farms toward climate change may be problematic. Moreover, depending on how data are aggregated, results differ substantially compared to farm-level analysis. Based on data from Austria and two climate scenarios (Effective Measures and High Emission) for 2040, we estimate that the profits of farms will decline, on average, by 4.4% (Effective Measures) and 10% (High Emission). Adaptation options help to considerably ameliorate the adverse situation under both scenarios. Our results reinforce the need for mitigation and adaptation to climate change.     

Effects of food consumption patterns on paddy field use in Taiwan

Societal metabolism and land use are significant and interrelated issues, and play a role in sustainable development. How a society's metabolism relates to local land use is typically affected by the particular context of the society under study, which is usually shaped by many factors, including economic, ecological, cultural, technological, and political factors. This study examines the effects of changes in food consumption patterns – decreasing per capita consumption of rice and increasing per capita consumption of wheat flour and meat – on the use of paddy fields in Taiwan. Although rice is grown domestically, wheat, which is a substitute for rice, is mainly imported. Moreover, the domestic livestock industry depends heavily on imported crops for low-cost feed. Accordingly, dietary changes have significantly decreased the demand for local paddy fields to grow crops. Additionally, the diversion of paddy fields to grow forage crops, which has been promoted by the Taiwanese government by guaranteeing prices for feed maize for 14 years, was discouraged when Taiwan joined the World Trade Organization in 2002, as Taiwan was required at that time to reduce by 20% its aggregate measure of support. The presented Taiwan case provides an empirical example of how a change in input characteristics (supply sources in a spatial dimension) of societal metabolism can, together with other factors, significantly affect local paddy fields, and discusses the underlying implications for sustainable development.     

Productivity and efficiency impact of climate change and agroecology on Bangladesh agriculture

The paper estimates the impacts of climate change, agroecological and socio-economic characteristics on agricultural productivity and efficiency changes in Bangladesh agriculture using a rich panel dataset of 17 regions covering a period of 61-years (1948–2008). Results revealed that land has the most dominant role in increasing agricultural production followed by labour and irrigation. The contribution of non-cereal crops (i.e., potatoes, pulses, oilseeds, jute and cash crops) to total production are also significant, ranging from 2 to 8% per annum. An increase in annual-rainfall and long-term-temperature (LTT) significantly enhance production. Production is significantly higher in floodplain agroecologies. However, production efficiency fluctuated sharply and declined overtime. The mean efficiency score of 0.74 implies substantial room to improve production by resource reallocation. Average farm size, crop specialization and investment in R&D significantly improve efficiency whereas increases in annual temperature-variability and LTT significantly reduce efficiency. Efficiency is significantly lower in low-lying floodplain and coastal-plain agroecologies. Policy implications include investments in diversifying cropping portfolio into other cereals (i.e., wheat and maize), research to develop crop varieties suited to changing climatic conditions and specific agroecological regions, and land/tenurial reforms to consolidate farm size to enhance productivity and efficiency of Bangladesh agriculture.     

Projecting future crop productivity for global economic modeling

Assessments of climate change impacts on agricultural markets and land‐use patterns rely on quantification of climate change impacts on the spatial patterns of land productivity. We supply a set of climate impact scenarios on agricultural land productivity derived from two climate models and two biophysical crop growth models to account for some of the uncertainty inherent in climate and impact models. Aggregation in space and time leads to information losses that can determine climate change impacts on agricultural markets and land‐use patterns because often aggregation is across steep gradients from low to high impacts or from increases to decreases. The four climate change impact scenarios supplied here were designed to represent the most significant impacts (high emission scenario only, assumed ineffectiveness of carbon dioxide fertilization on agricultural yields, no adjustments in management) but are consistent with the assumption that changes in agricultural practices are covered in the economic models. Globally, production of individual crops decrease by 10–38% under these climate change scenarios, with large uncertainties in spatial patterns that are determined by both the uncertainty in climate projections and the choice of impact model. This uncertainty in climate impact on crop productivity needs to be considered by economic assessments of climate change.     

Intertemporal and Interfirm Heterogeneity: Implications for Pesticide Productivity

This paper presents evidence concerning the existence and implications of heterogeneity effects for estimates of the marginal productivity of pesticides, The paper extends the work of Calpentier and Weaver (1996a), which considered fured effects that homothetically shift the conditional mean of output. This paper considers the implications of time-varying marginal productivity, allowing for nonhomothetic shifts in production. The extent and structure of heterogeneity found in French crop agriculture is first presented to illustrate that persistent heterogeneity exists across these firms. Next, we review the implications of such heterogeneity for econometric estimates and show that estimates of marginal productivity of pesticides will be biased when based on models that do not explicitly account for these types of heterogeneity across firms and time. An alternative estimation approach is proposed, based on Chamberlain (1982 and 1984) and implemented to produce asymptotically unbiased estimates and to statistically validate the model specification. Existence of fixed firm effects is statistically confirmed and temporal variation of marginal productivity is found to be substantial.     

Impact of off‐farm income on food expenditures in rural Bangladesh: an unconditional quantile regression approach

This study examines the effects of off‐farm income on food expenditures of rural Bangladeshi households. Our analysis yields unbiased estimates of the unconditional impact of off‐farm income on food expenditures and reveals the heterogeneous effects that occur across the distribution of total food consumption expenditures. The findings suggest that the impacts of off‐farm income are uniformly positive across the unconditional quantile regression and significantly increase food consumption expenditures for all quantiles, except for the 25th quantile. In addition, we found that schooling, experience, and location of the household increase the food expenditures of rural households. Most importantly, this article argues that female‐headed rural households in which the female works off the farm tend to have significantly lower food expenditures.     

The research cost of adapting agriculture to climate change: A global analysis to 2050

Investments in agricultural research and development (R&D) made over the next few decades will likely prove critical in offsetting adverse climate change impacts on the global food system. In this study, we offer cost estimates of public R&D-led adaptation to climate change grounded in an explicit framework relating the flow of annual R&D expenditures to building knowledge capital and thereby raising productivity in agriculture. Our research uses a comprehensive collection of historical public agricultural R&D expenditure and a literature review of elasticity estimates linking knowledge stocks to agricultural productivity growth for key world regions. Given climate-driven crop yield projections generated from extreme combinations of crop and global circulation models, we find that offsetting crop yield losses projected by climate and crop models over 2006–2050 would require increased R&D adaptation investments of between $187 billion and $1,384 billion (in 2005 $PPP) if we invest between 2020 and 2040. This is 16–118% higher than global R&D investment if present spending trends continue. Although these costs are significant, worldwide R&D-led climate adaptation could offer favorable economic returns. Moreover, R&D-led adaptation could deliver gains in food security and environmental sustainability by mitigating food price increases and slowing cropland expansion.     

基于快速设定决策阈值的大范围作物种植分布的遥感监测研究

[目的]作物分布是研究作物种植结构的基础,利用遥感进行大范围作物布局的监测识别,对推进农业种植结构研究、分析农业模式和制定农业政策都具有重要的意义。为了更好地适应作物生产的需求,解决大范围作物种植分布遥感监测方法复杂的问题,亟待构建一种快速实用的作物提取方法,实现作物种植信息的快速高效获取。[方法]以江苏省水稻、小麦和玉米为研究对象,利用作物关键生育期内的多时相中分辨率遥感影像,针对作物生长特点进行影像的特征转换,以行政区县为基础的作业单元进行区域划分及阈值设定,构建多时相阈值决策提取模型,并提出一种基于少量样本投射的阈值快速确定的方法,实现大范围作物分布的快速识别。[结果]该方法能够快速分单元确定模型的阈值,     

Determinants and implications of crop production loss: An empirical exploration using ordered probit analysis

This study investigates farmers’ perception about the severity of loss for three rice crops, identifies their determinants and explores policy implications based on findings. This research employs an ordered probit model to data collected from 1800 farm households from drought-prone and groundwater depleted areas of Bangladesh. This is the first study of its kind.Severity of rice production loss, while differing across all three rice crops, was higher for rain-fed crops. This was broadly consistent with available independent evidence. Geophysical factors, household characteristics, institutional and market accessibility, and household adaptation strategy were key determinants of crop loss. The impact of these factors was specific to the crop and severity of loss.This study has several policy implications involving market, R & D and institutional support based options. Strengthening support systems for institutional and market accessibility, and science driven climate change adaptation strategy including generation and wider dissemination of drought tolerant rice varieties, and enhancing farmers’ capacity to change rice varieties on a regular basis, constitute key areas for policy intervention.     

Climate adaptation imperatives: untapped global maize yield opportunities

Climate change represents an unavoidable and growing challenge to food security, imposing new adaptation imperatives on all farmers. Maize is arguably the world's most productive grain crop, as measured by grain yield. However, maize yields vary dramatically due to many factors, including soils, climate, pests, disease, agronomic practices, and seed quality. The difference between observed yields and those achievable by optimized crop production methods is called the yield gap. In this work we quantified the current yield gap for 44 countries through the use of a large private-sector data set recently made available to the crop modelling community. The yield gap was quantified for three groups of countries, categorized by level of intensification. Observed yield gaps for high, medium, and low levels of intensification are 23%, 46%, and 68%, respectively. If all maize production countries were able to shrink their yield gap to 16.5% (as in the USA) an additional 335?million metric tons (MMT) of maize grain would be produced. This represents a 45% increase over the 741?MMT produced by these countries in 2010. These data demonstrate that a major untapped maize yield opportunity exists, especially in those countries where intensification has not kept pace with the rest of the world.