中亚地区气候生产潜力时空变化特征

根据中亚5 国100 个气象站1901-2000 年月平均温度和降水资料,运用Miami、Thornthwaite Memorial 模型对中亚地区气候生产潜力进行了计算,用气候倾向率、Mann-Kendall 法、并结合ArcGIS 和SPSS 对其时空变化特征及驱动力进行了分析。结果表明：①中亚地区100 a 降水气候生产潜力（Yr）和蒸散气候生产潜力（Ye）均呈逐渐增加的趋势,温度气候生产潜力（Yt）趋势相反,Yr 和Ye 均发生了4 次突变,Yt 没有发生突变;②气候生产潜力区域差异明显,其中,Yt 呈从西南向东北减少的趋势,Yr 和Ye 变化比较复杂,大致具有东部大于西部的规律;③增温增湿的气候变化趋势有利于中亚气候生产潜力的提高,中亚气候生产潜力对增湿的响应更敏感。     

1901—2017年藏西南高原气候及其生产潜力时空变化

研究全球变暖背景下藏西南高原气候及气候生产潜力时空分布,对该区农牧业发展、生态保护和可持续发展等具有重要意义。基于1901—2017年的中国气象再分析数据,利用Miami和Thornthwaite Memorial模型对近117年藏西南高原气候变化、气候生产潜力的时空分布及影响因素进行了分析。结果表明：近117年来藏西南高原年均温呈上升趋势,年均降水量呈下降趋势,并存在明显周期和突变点;温度生产潜力呈增加趋势,空间上自东南向西北递减;降水、蒸散和标准生产潜力呈减小趋势,呈现自南向北递减的空间分布特征;标准生产潜力由降水和温度共同决定,降水是主要限制因子。未来气候若持续“暖干化”变化,将导致藏西南高原气候生产潜力下降。为促进畜牧业发展和生态环境的改善,未来应进一步推进退牧还草、人工种草、舍饲养殖等工程,并选用耐寒耐旱高产草种,提高牧草产量,实现草畜平衡,以推动传统畜牧业向现代牧业转变,实现草原生态保护和可持续发展。     

从栅格到县域:中国粮食生产的资源潜力区域差异分析

粮食安全是国家安全的重要组成部分。论文通过构建生产潜力模型,利用GIS技术,定量计算了1km×1km栅格和县域尺度中国粮食生产潜力;通过对粮食生产的资源禀赋状况逐级评判,揭示了中国不同地区粮食生产的资源潜力。结果表明:中国平均光温、水资源和土地资源分别具备1倍多、1倍以及近1/3的增长空间。中国县域粮食资源潜力差异显著,内蒙古及长城沿线以及黄土高原地区为县域粮食资源可开发空间较大的区域,西北、黄淮海、四川盆地区为可开发程度较低的地区。     

北方旱农区玉米自然降水生产潜力研究

针对我国北方水资源匮乏日益严重的状况,利用CERES-Maize作物模型模拟分析了北方旱区玉米自然降水生产潜力及其时空分布规律。研究表明,我国北方旱区玉米的水分生产潜力大小排序依次是半湿润区>半干旱区>干旱区,半湿润区的玉米自然降水生产潜力大约为11000kg/hm₂,干旱区大约在5000kg/hm₂,但同时半湿润区潜力的年际间波动性也最显著,干旱区则相对较为稳定。我国北方旱区东部的玉米生产潜力高于西部,但南北方向潜力差异不明显。     

洱源县农作物产量对气候变化响应的敏感性分析

以洱源县为试点,采用农作物产量分解方法和气候生产潜力计算方法,定量分析农作物产量受历史气候变化影响的程度。分析结果显示:1952—2012年,洱源县温度生产潜力呈上升趋势,降水生产潜力呈下降趋势;气候生产潜力与研究时段年均温度相关系数为-0.11,与年均降水量相关系数为0.96,表明降水量是决定洱源县气候生产潜力的主导因子。研究表明,近60a来洱源县农作物产量受气候变化影响的程度正不断上升,以负面影响为主。     

山区农业气候资源空间分布的推算方法及小地形的气候效应

本文提出了山区农业气候资源(温度、湿度、降水、风速等)空间分布的推算方法。为适应计算机技术在山地气候研究中的开发应用,作者使推算模式函数化,便于用计算机绘制山区小网格农业气候资源空间分布图。文中也提供了上述多项农业气候资源的小地形效应值。本文提出的推算方法在福建省沙溪流域实际应用的结果表明,能有效地揭示山区农业气候资源空间分布的宏观与微观变化,效果是令人满意的,精度也是高的。     

近50a气候变化背景下我国玉米生产潜力时空演变特征

以2010年我国耕地空间分布遥感监测数据为基础,在1960—2010年的长时间序列气象数据、土壤数据等数据基础上,采用GAEZ(Global Agro-Ecological Zones)模型综合考虑光、温、水、CO2浓度、农业气候限制、土壤、地形等多方面因素,估算了中国玉米生产潜力,进而分析了近50 a来气候变化背景下我国玉米生产潜力的时空格局特征。研究表明:12010年中国玉米生产潜力总量是8.34×108t,玉米生产潜力空间差异显著,总体呈现东高西低的趋势,东北平原区的玉米生产潜力总量最高,达到1.97×108t,青藏高原区玉米生产潜力总量最小;2近50 a来中国玉米单产潜力和生产潜力总量整体呈现减少的趋势;3中国玉米单产潜力和生产潜力总量变化的区域差异较大,东北平原区的平均玉米单产潜力和生产潜力总量的增长趋势都最为明显,其他各区的变化趋势都相对较小。研究揭示了近50 a来气候变化背景下我国玉米生产潜力的时空演变特征,这为探究如何适应气候变化、提高中国玉米产量水平、科学指导玉米生产经营提供了科学依据。     

1961—2015年西南区域单季稻生长季气候年型及其生产潜力分析

了解气候变化背景下农作物气候年型以及不同气候年型下作物的生产潜力,对实现农业的可持续发展具有重要意义。基于1961—2015年西南区域单季稻种植区316个气象台站的逐日气象资料和单季稻生产资料,利用异常度概念分析了单季稻生长季的10种气候年型,解析了不同气候年型下单季稻的气候生产潜力,并分析气候变化对单季稻生长季气候年型及生产潜力的影响。结果表明：（1）近55年来西南区域单季稻生长季正常年型发生频次最高,平均21.5次,其次是少雨年型和多雨年型。从空间分布来看,正常年型多出现在云南南部和西北部、四川攀西和四川盆地南部的部分地区,少雨和多雨年型多出现在四川盆地大部和其他省市的部分地区,高温年型多出现在四川攀西地区、云南和贵州的个别地区,低温和寡照年型的空间差异不明显。（2）1961—2015年,西南区域单季稻气候生产潜力平均为7065.6 kg/hm²。与正常年相比,多雨年型气候生产潜力偏高超过10%,少雨年型偏低超过14%,降水是影响单季稻气候生产潜力的最主要因子。（3）气候变暖对西南区域单季稻生长季气候年型变化的影响最为显著。与1961—1990年相比,1991—2015年暖年增加,冷年减少。近55年来西南各省市单季稻气候生产潜力均呈下降趋势,1990年代以来暖年的增加有利于气候生产潜力的提高,而少雨和寡照年的增加是气候生产潜力总体下降的主要原因。     

中国北方牧区牧草气候资源评价模型

分析确定能够反映中国北方牧区牧草与气候资源条件的7个气候因子,应用模糊数学方法,建立牧草气候资源评价模型,选取中国北方5省(区)168个气象站点资料进行计算,分别从资源总体状况、资源效能、资源利用角度对中国北方5省(区)牧草生态气候资源分布状况进行评价,在此基础上,进一步分析了代表我国北方牧区最主要气候资源分布类型的三种典型区域的气候资源特点,为畜牧业发展及草地生态保护提供决策依据。     

吉林省限制开发区域资源环境承载力综合评价

综合运用P-S-R模型、熵权TOPSIS模型与障碍度模型等方法,以吉林省限制开发区域为研究对象,分析了2008—2016年吉林省限制开发区域资源环境承载力时空格局特征及其影响因素。结果表明：（1）研究期内吉林省限制开发区域资源环境承载力呈不断下降态势,资源环境承载力状况不尽理想;相反,吉林省限制开发区域资源环境承载力变异系数却逐步提升,区域差异逐渐扩大。（2）吉林省限制开发区域资源环境承载力空间上总体呈现出自西向东不断升高的特点。其中,压力指数空间上呈现中部高、东西两翼低的格局;状态指数则呈现中部低、东西两端高的空间格局;而响应指数东西空间分异特征显著,东部明显高于中、西部地区。（3）农村居民人均纯收入、人均粮食产量、人口密度、工业废水中COD去除率、森林覆盖率、城镇化率是阻碍吉林省限制开发区域资源环境承载力水平提升的关键因素。     

东北红松林生境区划方法研究

本文通过红松年轮生长分析,用红松年生长量与23个气候因子逐步回归。结果表明:红松生长与7月平均温度,≥5℃积温,年降水量密切相关。根据这3个气候因子综合进行红松生长量适宜性区划,划分出:红松生长不适宜区,适宜较差区,适宜区3个区域。这与实际红松分布区域是吻合的。充分证明了红松的分布与其气候相适应,更进一步的说明了红松阔叶林是该地区的一种稳定的地带性植物群落。红松生长适宜区的区划,对人造红松林也会提供一定的科学依据。     

闽江口不同沼泽植被带土壤甲烷产生潜力的温度敏感性

2012年2月采集闽江河口鳝鱼滩短叶茳芏(Cyperus malaccensis),芦苇(Phragmites australis)和互花米草(Scirpus alterniflora) 3个典型潮汐沼泽植被带0~30cm(间隔5cm)土壤样品,在不同温度(10,20和30℃)进行15d室内厌氧培养实验,探讨河口区不同沼泽植被带土壤甲烷产生潜力及其温度敏感性(Q10值)的特征.结果表明,指数模型较好地拟合不同沼泽植被带土壤甲烷产生与温度的相关关系;温度由10℃升至20℃时,3个沼泽植被带土壤甲烷产生潜力Q10值的均值分别为5.04,14.92和14.81,最大值均在培养期间的第13~15d分别出现于10~15cm,15~20cm和20~25cm三个土层;温度由20℃升至30℃时,3个沼泽植被带土壤甲烷产生潜力Q10值的均值分别为3.56,4.99和3.43,最大值分别在培养期间的第4~6d,第4~6d和第7~9d出现于0~5cm,0~5cm和15~20cm三个土层;植被类型和土壤深度对甲烷产生潜力及Q10值均具有显著的影响(P<0.05).     

From site-level to regional adaptation planning for tropical commodities: cocoa in West Africa

The production of tropical agricultural commodities, such as cocoa (Theobroma cacao) and coffee (Coffea spp.), the countries and communities engaged in it, and the industries dependent on these commodities, are vulnerable to climate change. This is especially so where a large percentage of the global supply is grown in a single geographical region. Fortunately, there is often considerable spatial heterogeneity in the vulnerability to climate change within affected regions, implying that local production losses could be compensated through intensification and expansion of production elsewhere. However, this requires that site-level actions are integrated into a regional approach to climate change adaptation. We discuss here such a regional approach for cocoa in West Africa, where 70 % of global cocoa supply originates. On the basis of a statistical model of relative climatic suitability calibrated on West African cocoa farming areas and average climate projections for the 2030s and 2050s of, respectively, 15 and 19 Global Circulation Models, we divide the region into three adaptation zones: (i) a little affected zone permitting intensification and/or expansion of cocoa farming; (ii) a moderately affected zone requiring diversification and agronomic adjustments of farming practices; and (iii) a severely affected zone with need for progressive crop change. We argue that for tropical agricultural commodities, larger-scale adaptation planning that attempts to balance production trends across countries and regions could help reduce negative impacts of climate change on regional economies and global commodity supplies, despite the institutional challenges that this integration may pose.     

Implications of climate change on mitigation potential estimates for forest sector in India

Climate change is projected to impact forest ecosystems, including biodiversity and Net Primary Productivity (NPP). National level carbon forest sector mitigation potential estimates are available for India; however impacts of projected climate change are not included in the mitigation potential estimates. Change in NPP (in gC/m²/yr) is taken to represent the impacts of climate change. Long term impacts of climate change (2085) on the NPP of Indian forests are available; however no such regional estimates are available for short and medium terms. The present study based on GCM climatology scenarios projects the short, medium and long term impacts of climate change on forest ecosystems especially on NPP using BIOME4 vegetation model. We estimate that under A2 scenario by the year 2030 the NPP changes by (−5) to 40% across different agro-ecological zones (AEZ). By 2050 it increases by 15% to 59% and by 2070 it increases by 34 to 84%. However, under B2 scenario it increases only by 3 to 25%, 3.5 to 34% and (−2.5) to 38% respectively, in the same time periods. The cumulative mitigation potential is estimated to increase by up to 21% (by nearly 1 GtC) under A2 scenario between the years 2008 and 2108, whereas, under B2 the mitigation potential increases only by 14% (646 MtC). However, cumulative mitigation potential estimates obtained from IBIS—a dynamic global vegetation model suggest much smaller gains, where mitigation potential increases by only 6% and 5% during the period 2008 to 2108.     

Future production of rainfed wheat in Iran (Khorasan province): climate change scenario analysis

Projecting staple crop production including wheat under future climate plays a fundamental role in planning the required adaptation and mitigation strategies for climate change effects especially in developing countries. The main aim of this study was to investigate the direction and magnitude of climate change impacts on grain yield of rainfed wheat (Triticum aestivum L.) production and precipitation within growing season. This study was performed for various regions in Khorasan province which is located in northeast of Iran. Climate projections of two General Circulation Models (GCM) for four locations under three climate change scenarios were employed in this study for different future time periods. A stochastic weather generator (LARS-WG5) was used for downscaling to generate daily climate parameters from GCMs output. The Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5 was employed to evaluate rainfed wheat performance under future climate. Grain yield of rainfed wheat and precipitation during growth period considerably decreased under different scenarios in various time periods in contrast to baseline. Highest grain yield and precipitation during growth period was obtained under B1 scenario but A1B and A2 scenarios resulted in sharp decrease (by ?57 %) of grain yield. Climate change did not have marked effects on evapotranspiration during the rainfed wheat growth. A significant correlation was detected between grain yield, precipitation and evapotranspiration under climate change for both GCMs and under all study scenarios. It was concluded, that rainfed wheat production may decline during the next 80 years especially under A2 scenario. Therefore, planning the comprehensive adaptation and mitigation program is necessary for avoiding climate change negative impact on rainfed wheat production.     

养殖户气候适应性行为对提高养殖业生产效率的影响

气候变化给当前中国农业生产转型带来严峻挑战,从效率视角分析农户适应气候变化行为具有重要意义。本文探讨养殖户气候适应性行为与养殖业生产效率之间的逻辑关系,并基于中国五省的微观调查数据,采用倾向得分匹配方法与选择纠偏随机前沿生产函数模型（Selectivity-corrected Stochastic Production Frontier model）相结合的实证思路,分析养殖户气候适应性行为对养殖业生产效率的影响。研究表明：（1）养殖户气候适应性行为能够提高养殖业生产效率,纠正可观测因素与不可观测因素造成的选择性偏差后,适应组养殖户平均养殖业生产效率为0.618,未适应组养殖户的平均养殖业生产效率为0.551。（2）若未考虑选择性偏差,养殖户适应性行为对养殖业生产效率的影响将会错估。研究成果可为推进政府制定农户适应气候变化政策与推动农业生产转型提供有力支持。     

Reliability and input-data induced uncertainty of the EPIC model to estimate climate change impact on sorghum yields in the U.S. Great Plains

Crop simulation models are frequently used to estimate the impact of climate change on crop production. However, few studies have evaluated the model performance in ways that most researchers practiced in climate impact studies. In this article, we examined the reliability of the EPIC model in simulating grain sorghum (Sorghum bicolor (L.) Moench) yields in the U.S. Great Plains under different climate scenarios, namely in years with normal or extreme temperature and precipitation. We also investigated model uncertainties introduced by input data that are not site-specific but commonly used or available for climate change studies. Historical field trial data of sorghum at the Mead Experimental Center, NE, were used for model evaluations. The results showed that overall model reliability was about 56%. The mean absolute relative error (absRE) was about 29%. The degree of accuracy and reliability varied with climate-classes and nitrogen (N)-treatments. The largest bias occurred in drought years (RE = ?25%) and the most unreliable results were found in N-0 treatment (reliability = 32%). There was more than 69% probability that input-data-induced uncertainties were limited to less than 20% of absRE. Our results support the application of the EPIC model to climate change impact studies in the U.S. Great Plains. However, efforts are needed to improve the accuracy in simulating crop responses to extreme water- and nitrogen-stressed conditions.     

Climate change scenarios to facilitate stakeholder engagement in agricultural adaptation

To prepare agricultural systems for climate change, scientists need to be able to effectively engage with land managers and policy makers to explore potential solutions. An ongoing challenge in engagement is to distil the complexity of climate-change-management-change interactions in agro-ecological systems to identify responses that are most important for adaptation planning. This paper presents an approach for selecting climate change scenarios to provide a focal point for engaging with stakeholders to evaluate adaptation options and communicate assessment outcomes. We illustrate how scenarios selected with the approach can be used by evaluating climate change impacts and an adaptation option for livestock industries in the north-east Australian rangelands. Climate change impacts on forage production, animal liveweight gain and soil loss are found to track projected climate changes in four pasture communities; increasing by up to 50% and declining by up to 110% in response to doubled atmospheric carbon-dioxide (CO₂), 4°C warming, and +20% to ?40% changes in mean annual rainfall. The effectiveness of reducing grazing pressure as an adaptation option shows a similar response; resulting in higher forage production (up to 40%), animal liveweight gains (up to 59%) and gross margins (up to 40%), and reduced soil erosion (down by 91%) per hectare relative to the baseline management. The results show that a few key scenarios may be selected to represent the range of global climate model (GCM) projections for use in assessing and communicating impacts and adaptation; simplifying the assessments and allowing limits to the effectiveness of adaptation options to be explored. The approach provides a framework for capturing and communicating trends in climate change impacts and the utility of options, which are required for successful engagement of stakeholders in finding viable adaption responses.