气候变化对农业的影响研究进展

本文着重介绍了近几年气候变化对农业影响的最新研究进展，其中包括气象因子对农业生态环境的影响、二氧化碳浓度增加、气候变化对农作物光合作用、生长发育、产量、品质、种类、地理分布、种植制度、农业灾害以及农业成本等领域最新研究进展，最后指出了存在的问题以及研究展望。     

气候变化对中国农业生产的影响研究进展

气候变化已成为当今科学界、各国政府和社会公众普遍关注的环境问题之一,气候变化可能对生态系统和社会经济产生灾难性影响,农业是受气候变化影响最直接的脆弱行业。因此,气候变化对农业生产的影响研究一直是气候变化研究领域中的热点问题之一。该文系统介绍了有关全球气候变化对中国农业生产影响研究的现状与进展,包括气候变化对农业影响的研究方法、大气中温室气体浓度增加对农作物的影响试验、气候变化对农业气候资源的影响、气候变化对农作物生长发育和产量的影响、气候变化对农业种植制度和品种布局的影响、气候变化对农作物气候生产潜力和气候资源利用率的影响等,指出当前在研究气候变化对农业影响评估中存在的问题,提出了今后应加强对气候变化情景和预测模式不确定性的研究、气候变化对农业影响的方法研究。此外,气候变化背景下极端天气气候事件对农业生产的影响以及气候变化对农业病虫害的影响研究等仍较薄弱,有待进一步加强和深入。     

海东地区气候及气候变化对农业生态环境的影响

本文从海东地区的气候及特点和农业生态环境的关系出发，通过对代表海东地区东、南、北三个地区的民和、化隆、互助三县近40a气温、降水等资料的统计，分析海东地区气候变化对该地区农业生态环境的影响，并提出相应的治理对策。     

聊城气候变化特征及其对农业生产的影响

对聊城市４２年来的气候资料进行分析,找出主要家业气候学因子的变化规律和特征,论证了气候变化对聊城市农业生产的影响。     

大兴安岭地区近3O年气候变化及其对农业的影响

利用统计学方法对近30年来大兴安岭地区的气候变化特点进行了研究，在全球气候变暖的大背景下，从温度、降水、蒸发、冻土等气象要素分析得出：该地区气候有明显的变暖趋势，但存在区域差异，同时分析了气候变化对农业生产所产生的影响，为合理利用大兴安岭地区气候资源提供了依据。     

化州气候变化特征及其对农业生产的影响

利用1959-2008年化州市地面站气象资料,从气温、降水量和日照时数等方面分析了化州市气候变化特征,探讨了气候变化对化州市农业生产的影响.近20年来化州气温上升明显,高温天气明显增加,低温天气明显减少;降水以年际波动为主,线性变化趋势不明显,不同季节的降水量变化有升有降;日照时数年际波动明显,线性拟合呈减少趋势.气候变化导致台风、高温等极端天气事件频繁出现;气候变暖造成农作物生育期缩短、农田地力下降和农作物病虫害灾害频繁;降水变化波动大,导致旱涝交替出,这些都是气候变化对化州农业生产影响的具体体现.     

气候变化对中国农业生产影响研究展望

综述了气候变化背景下中国农业气候资源、农业气象灾害(干旱、洪涝、高温热浪、低温灾害)和农业病虫害的变化趋势与规律,从农业生产潜力变化、作物种植制度变化和作物品质变化等方面阐明了气候变化对中国农业生产的影响事实,分析了气候变化对中国农业生产的可能影响和中国农业生产适应气候变化的对策措施。在此基础上,针对气候变化背景下中国气候资源的时空分布特点及农业生产出现的新情况、新问题,指出了当前中国关于气候变化对农业影响研究存在的不足,提出了未来气候变化对中国农业生产影响研究需要重视的方面,为确保气候变化背景下中国的农业生产安全及粮食安全提供决策支持。     

气候变化对重庆农业的影响及对策研究

本文分析了重庆市气候特点及其对重庆农业的影响;并在全球气候变暖的大气候背景下,分析了重庆气候的变化趋势,并就气候变化对重庆农业可能造成的影响进行了初步的探讨;提出了重庆农业应对气候变化的适应性战略和技术措施。     

气候变化对重庆农业的影响及对策研究

本文分析了重庆市气候特点及其对重庆农业的影响;并在全球气候变暖的大气候背景下,分析了重庆气候的变化趋势,并就气候变化对重庆农业可能造成的影响进行了初步的探讨;提出了重庆农业应对气候变化的适应性战略和技术措施。     

大兴安岭地区近30年气候变化及其对农业的影响

利用统计学方法对近30年来大兴安岭地区的气候变化特点进行了研究,在全球气候变暖的大背景下,从温度、降水、蒸发、冻土等气象要素分析得出:该地区气候有明显的变暖趋势,但存在区域差异,同时分析了气候变化对农业生产所产生的影响,为合理利用大兴安岭地区气候资源提供了依据.     

Assessment of climate change impact on Eastern Washington agriculture

An assessment of the potential impact of climate change and the concurrent increase of atmospheric CO₂ concentration on eastern Washington State agriculture was conducted. Climate projections from four selected general circulation models (GCM) were chosen, and the assessment included the crops with larger economic value for the state (apples, potatoes, and wheat). To evaluate crop performance, a cropping system simulation model (CropSyst) was utilized using historical and future climate sequences. Crops were assumed to receive adequate water (irrigated crops), nutrients, and control of weeds, pests and diseases. Results project that the impact of climate change on eastern Washington agriculture will be generally mild in the short term (i.e., next two decades), but increasingly detrimental with time (potential yield losses reaching 25% for some crops by the end of the century). However, CO₂ elevation is expected to provide significant mitigation, and in fact result in yield gains for some crops. The combination of increased CO₂ and adaptive management may result in yield benefits for all crops. One limitation of the study is that water supply was assumed sufficient for irrigated crops, but other studies suggest that it may decrease in many locations due to climate change.     

A Ricardian analysis of the impact of climate change on agriculture in Germany

Based on a Ricardian analysis accounting for spatial autocorrelation and relying on recent climate change forecasts at a low spatial scale, this study assesses the impact of climate change on German agriculture. Given the limited availability of data (e.g., the unknown average soil quality at the district level), a spatial error model is used in order to obtain unbiased marginal effects. The Ricardian analysis is performed using data from the 1999 agricultural census along with data from the network of German weather observation stations. The cross-sectional analysis yields an increase of land rent along with both a rising mean temperature and a declining spring precipitation, except for in the Eastern part of the country. The subsequent simulation of local land rent changes under three different IPCC scenarios is done by entering into the estimated regression equations spatially processed data averages for the period between 2011 and 2040 from the regional climate model REMO. The resulting expected benefits arising from climate change are represented in maps containing the 439 German districts; the calculated overall rent increase corresponds to approximately 5–6% of net German agricultural income. However, in the long run, when temperature and precipitation changes will be more severe than those simulated for 2011–2040, income losses for German agriculture cannot be excluded.     

Climatic trends and impact of climate change on agriculture in an arid Andean valley

Little is known about climate change and its impacts for the arid coastal and mountainous regions in northern Chile. The Elqui river basin, part of the Norte Chico of Chile between 27oS and 33oS latitude, is located south of the hyper-arid Atacama desert. Despite water scarcity, agricultural development in this region has been enhanced by agronomic practices and the marketing of valuable products. This paper characterizes the actual climate conditions and presents an overview and analyses of past climate variability, and future possible climate trends, emphasizing those relevant to agriculture. Precipitation shows an important decrease during the first decades of the past century. Runoff shows decreasing trends for the first half of the past century and increases for 1960 to 1985. Drought appears to be increasing. Statistical downscaling was accomplished using the Long Ashton Research Station Weather Generator. Both future periods of 2011 to 2030 and 2046–65 showed trends to higher minimum and maximum temperature. The number of hot days (maximum temperature greater than or equal to 30°C) has a strong increasing trend during October to April. Even though the downscaled results for precipitation do not show trends, the continuation of the present trend of low amounts is a concern. We discuss some implications of climatic changes for agriculture and we emphasize the importance of adaptation, especially to deal with water scarcity.     

Adaptation of agriculture to climate change

Preparing agriculture for adaptation to climate change requires advance knowledge of how climate will change and when. The direct physical and biological impacts on plants and animals must be understood. The indirect impacts on agriculture's resource base of soils, water and genetic resources must also be known. We lack such information now and will, likely, for some time to come. Thus impact assessments for agriculture can only be conjectural at this time. How-ever, guidance can be gotten from an improved understanding of current climatic vulnerabilities of agriculture and its resource base, from application of a realistic range of climate change scenarios to impact assessment, and from consideration of the complexity of current agricultural systems and the range of adaptation techniques and policies now available and likely to be available in the future.     

An exploratory study on occurrence and impact of climate change on agriculture in Tamil Nadu,India

This study has been undertaken to examine the occurrence of climate change in Tamil Nadu, the southernmost state of India and its impact on rainfall pattern which is a primary constraint for agricultural production. Among the five sample stations examined across the state, the minimum temperature has increased significantly in Coimbatore while the same has decreased significantly in Vellore whereas both minimum and maximum temperatures have increased significantly in Madurai since 1969 with climate change occurring between late 1980s and early 1990s. As a result, the south-west monsoon has been disturbed with August rainfall increasing with more dispersion while September rainfall decreasing with less dispersion. Thus, September, the peak rainfall month of south-west monsoon before climate change, has become the monsoon receding month after climate change. Though there has been no change in the trend of the north-east monsoon, the quantity of October and November rainfall has considerably increased with increased dispersion after climate change. On the whole, south-west monsoon has decreased with decreased dispersion while north-east monsoon has increased with increased dispersion. Consequently, the season window for south-west monsoon crops has shortened while the north-east monsoon crops are left to fend against flood risk during their initial stages. Further, the incoherence in warming, climate change and rainfall impact seen across the state necessitates devising different indigenous and institutional adaptation strategies for different regions to overcome the adverse impacts of climate change on agriculture.

     

Adapting agriculture to climate change: a review

The agricultural sector is highly vulnerable to future climate changes and climate variability, including increases in the incidence of extreme climate events. Changes in temperature and precipitation will result in changes in land and water regimes that will subsequently affect agricultural productivity. Given the gradual change of climate in the past, historically, farmers have adapted in an autonomous manner. However, with large and discrete climate change anticipated by the end of this century, planned and transformational changes will be needed. In light of these, the focus of this review is on farm-level and farmers responses to the challenges of climate change both spatially and over time. In this review of adapting agriculture to climate change, the nature, extent, and causes of climate change are analyzed and assessed. These provide the context for adapting agriculture to climate change. The review identifies the binding constraints to adaptation at the farm level. Four major priority areas are identified to relax these constraints, where new initiatives would be required, i.e., information generation and dissemination to enhance farm-level awareness, research and development (R&D) in agricultural technology, policy formulation that facilitates appropriate adaptation at the farm level, and strengthening partnerships among the relevant stakeholders. Forging partnerships among R&D providers, policy makers, extension agencies, and farmers would be at the heart of transformational adaptation to climate change at the farm level. In effecting this transformational change, sustained efforts would be needed for the attendant requirements of climate and weather forecasting and innovation, farmer’s training, and further research to improve the quality of information, invention, and application in agriculture. The investment required for these would be highly significant. The review suggests a sequenced approach through grouping research initiatives into short-term, medium-term, and long-term initiatives, with each initiative in one stage contributing to initiatives in a subsequent stage. The learning by doing inherent in such a process-oriented approach is a requirement owing to the many uncertainties associated with climate change.     

Assessing the impact of climate change on representative field crops in Israeli agriculture: a case study of wheat and cotton

Climate changes, associated with accumulation of greenhouse gases, are expected to have a profound influence on agricultural sustainability in Israel, a semi-arid area characterized by a cold wet winter and a dry warm summer. Accordingly this study explored economic aspects of agricultural production under projected climate-change scenarios by the “production function” approach, as applied to two representative crops: wheat, as the major crop grown in Israel’s dry southern region, and cotton, representing the more humid climate in the north. Adjusting outputs of the global climate model HadCM3 to the specific research locations, we generated projections for 2070–2100 temperatures and precipitations for two climate change scenarios. Results for wheat vary among climate scenarios; net revenues become negative under the severe scenario (change from −145 to −273%), but may increase under the moderate one (−43 to +35%), depending on nitrogen applied to the crop. Distribution of rain events was found to play a major role in determining yields. By contrast, under both scenarios cotton experiences a considerable decrease in yield with significant economic losses (−240 and −173% in A2 and B2 scenarios, respectively). Additional irrigation and nitrogen may reduce farming losses, unlike changes in seeding dates.     

Assessing the influence of climate model uncertainty on EU-wide climate change impact indicators

Despite an increasing understanding of potential climate change impacts in Europe, the associated uncertainties remain a key challenge. In many impact studies, the assessment of uncertainties is underemphasised, or is not performed quantitatively. A key source of uncertainty is the variability of climate change projections across different regional climate models (RCMs) forced by different global circulation models (GCMs). This study builds upon an indicator-based NUTS-2 level assessment that quantified potential changes for three climate-related hazards: heat stress, river flood risk, and forest fire risk, based on five GCM/RCM combinations, and non-climatic factors. First, a sensitivity analysis is performed to determine the fractional contribution of each single input factor to the spatial variance of the hazard indicators, followed by an evaluation of uncertainties in terms of spread in hazard indicator values due to inter-model climate variability, with respect to (changes in) impacts for the period 2041–70. The results show that different GCM/RCM combinations lead to substantially varying impact indicators across all three hazards. Furthermore, a strong influence of inter-model variability on the spatial patterns of uncertainties is revealed. For instance, for river flood risk, uncertainties appear to be particularly high in the Mediterranean, whereas model agreement is higher for central Europe. The findings allow for a hazard-specific identification of areas with low vs. high model agreement (and thus confidence of projected impacts) within Europe, which is of key importance for decision makers when prioritising adaptation options.