关键词： 气候变化   农业   气象灾害   病虫害  

摘要： 我国是农业大国,农业受气候变化的影响较大,使农业病虫害的危害程度不断加剧,严重阻碍了农业的稳定、健康发展。本文主要研究气候变化对农业气象灾害与病虫害的影响,以期确保农作物稳产丰收。

关键词： 气候变化   粮食   影响   一般均衡模型  

摘要： 采用静态多区域农业一般均衡模型,把A2气候变化情景和B2气候变化情景导致粮食产量变化作为政策模拟条件,笔者研究了气候变化对中国粮食生产、消费及其经济增长的影响。模拟结果显示,无论是A2还是B2气候变化情景,中国玉米、小麦和水稻总体产出增加态势较为明显,中间投入需求和家庭消费需求明显增加,同时模拟结果还显示中国各地区玉米、小麦和水稻的出口将会随着产出的增长而大幅增加、进口随着产出的增加而大幅下降。在经济增长方面,绝大多数地区宏观经济呈增长态势,表现在实际GDP、实际投资、总进出口额的增加。基于研究结果本研究得出如下结论:气候变化会导致中国粮食总产量增加,中国经济增长得以保障。气候变化所引起的粮食产量变化地区间有所差异,总的来说,粮食主产区增长幅度要高于非主产区增长幅度,其中东北三省粮食增幅最为明显;不同作物产量因时(时间)因景(气候变化情景)有较大差异;虽然气候变化导致中国各地区粮食产量总体呈增加态势,但未来不确定因素较多,中国粮食安全问题仍不可忽视。

关键词： 华北平原   气候变化   水资源量  

摘要： 水资源是制约华北平原农业稳定和可持续发展的主要因素。气候变化对华北平原水资源和农业需水影响显著。1950年以来,华北平原气候总体趋向于暖干化,潜在蒸散呈下降趋势。近30年实际蒸散量呈现弱的上升趋势,与潜在蒸散有互补关系。未来气候变化情景下,区域水分盈余量下降,华北地区干旱化趋势加重。作物生育期耗水量和灌溉需水量增加,其中北部地区水量亏缺更为严重,南部地区水量盈余则减少。调整春季高耗水作物种植面积和空间布局,减少农业用水量,是适应气候变化的必要途径。

关键词： 气候变化   气象灾害   病虫害  

摘要： 在我国的农业生产中,气候对农业的影响非常的大,并且使多方面的、多尺度的影响,好的气候不仅仅会使粮食丰收,也会造成气象灾害与病虫害。气候为农业带来的气象灾害因地区的不同也有不同的表现,在北方则比较容易受到干旱困扰,在南方则会有洪涝灾害。病虫害的发生与气候有着非常深切的关系,不同的气温条件带来的病虫害的种类也有所不同,病虫害为农业带来的危害非常的严重。所以对于影响农业生产的气象灾害与病虫害进行深入的研究,有着非常重要的意义。

关键词： 气候变化   农业生产   模型   研究方法  

摘要： 农业是对气候变化反应敏感的特殊部门,农业的稳定对中国的稳定发展至关重要。气候变化使长期形成的农业生产格局和种植模式受到冲击,影响粮食安全和农业生态环境。研究气候变化对农业影响的模型包括农业经济模拟模型、农业生态地带模型、基于经济分析的李嘉图模型和可计算的一般均衡模型等。总结各类经济学模型的设定和研究结论,可以发现,是否考虑农民的适应行为以及适应期的时间长短是争议的焦点。因此,本文研究了目前气候变化对农业生产影响的研究方法,发现研究气候变化对农业影响的计量工具从单一模型通过纳入新因素实现拓展以及多模型框架的嵌套综合成为研究方法的发展趋势。

关键词： Seed corn   Fertilizer   Ethics   Environment   Consolidation  

摘要： This paper examines structural barriers to the adoption of climate change mitigation practices and the evolution of a climate change ethic among American farmers. It examines how seed corn contracts in Michigan constrain the choices of farmers and allow farmers to rationalize the over-application of fertilizer and associated water pollution and greenhouse gas emissions. Seed corn contracts use a competitive "tournament" system where farmers are rewarded for maximizing yields. Interviews and a focus group were used to understand fertilizer over-application and barriers to participating in a climate change mitigation program. Results indicate that farmers agree that they over-apply fertilizer but would be unlikely to participate in a mitigation program due to their contracts and lack of support from seed corn companies. Because only a few companies control access to the seed corn market, farmers feel they have few choices. Farmers rationalized their practices as their only option given the competitive nature of their contracts and blamed other sources of pollution. Despite increasing efforts to educate farmers about climate change, structural barriers will continue to constrain participation in mitigation efforts and the development of a climate change ethic.

关键词： strategic planning   agriculture   climate change   predictive model   Ukraine  

摘要： The essence of the "strategic planning" is explored and the peculiarities of strategic planning in the agricultural sector are defined. Global climate change as a factor stimulating the formation of new approaches to strategic planning of agricultural development is considered, and the impact of climate change on the agricultural sector of Ukraine is evaluated. A predictive model of changes in the parameters of agricultural production under expected climate change conditions is constructed, and organizational, socio-economical and environmental components of the strategy of agricultural development are outlined and the conceptual bases for improvement of strategic planning for the development of the agricultural sector in the face of climate change are substantiated.

关键词： agriculture   Flowcharts   Climate   System analyses   climate change   Systems approach   agricultural production  

摘要： Estimating the exposure of agriculture to climate variability and change can help us understand key vulnerabilities and improve adaptive capacity, which is vital to secure and increase world food production to feed its growing population. A number of indices to estimate exposure are available in literature. However, testing or validating them is difficult and reveals a considerable variability, and no systematic methodology has been developed to guide users in selecting indices for particular applications. This need is addressed in this paper by developing a flowchart from a conceptual model that uses a system's approach. Also, we compare five approaches to estimate exposure indices (EIs) to study the exposure of agriculture to climate variability and change: single stressor-mean climate, single stressor-extreme climate, multiple stressor-mean climate, multiple stressor-extreme climate;and combinations of the above approaches. The developed flowchart requires gathering information on the region of study, including its agriculture, stressor(s), climate factor(s) (CF), period of interest and the method of aggregation. The flowchart was applied to a case study in Kansas to better understand the five approaches to estimate EIs and the implications of the choices made in each step on the estimated the exposure. The flowchart provides options that guide EI estimation by selecting the most appropriate stressor(s), associated CF(s), and aggregation methods when a detailed methodological analysis is possible, or proposes a default method when data or resources do not allow a detailed analysis. Climate adaptation involves integration of a multitude of factors across complex systems. A more standardized approach to assessing exposure can promote information sharing across different locations and systems as this rapidly evolving area of study moves forward.

关键词： land suitability   Analytical Hierarchy Process   Fuzzy Analysis   Fuzzy AHP   agriculture   climate  

摘要： Land suitability analysis is employed to evaluate the appropriateness of land for a particular purpose whilst integrating both qualitative and quantitative inputs, which can be continuous in nature. However, in agricultural modelling there is often a disregard of this contiguous aspect. Therefore, some parametric procedures for suitability analysis compartmentalise units into defined membership classes. This imposition of crisp boundaries neglects the continuous formations found throughout nature and overlooks differences and inherent uncertainties found in the modelling. This research will compare two approaches to suitability analysis over three differing methods. The primary approach will use an Analytical Hierarchy Process (AHP), while the other approach will use a Fuzzy AHP over two methods;Fitted Fuzzy AHP and Nested Fuzzy AHP. Secondary to this, each method will be assessed into how it behaves in a climate change scenario to understand and highlight the role of uncertainties in model conceptualisation and structure. Outputs and comparisons between each method, in relation to area, proportion of membership classes and spatial representation, showed that fuzzy modelling techniques detailed a more robust and continuous output. In particular the Nested Fuzzy AHP was concluded to be more pertinent, as it incorporated complex modelling techniques, as well as the initial AHP framework. Through this comparison and assessment of model behaviour, an evaluation of each methods predictive capacity and relevance for decision-making purposes in agricultural applications is gained.

关键词： Agriculture   adaptive capacity and exposure   climate change   sensitivity   vulnerability  

摘要： Assessing vulnerability to climate change and variability is an important first step in evolving appropriate adaptation strategies to changing climate. Such an analysis also helps in targeting adaptation investments, specific to more vulnerable regions. Adopting the definition of vulnerability given by IPCC, vulnerability was assessed for 572 rural districts of India. Thirty eight indicators reflecting sensitivity, adaptive capacity and exposure were chosen to construct the composite vulnerability index. Climate projections of the PRECIS model for A1B scenario for the period 2021-2050 were considered to capture the future climate. The data on these indicators were normalized based on the nature of relationship. They were then combined into three indices for sensitivity, exposure and adaptive capacity, which were then averaged with weights given by experts, to obtain the relative vulnerability index. Based on the index, all the districts were divided into five categories with equal number of districts. One more district was added to 'very high' and 'high' categories. The analysis showed that districts with higher levels of vulnerability are located in the western and peninsular India. It is also observed that the highly fertile Indo-Gangetic Plains are relatively more sensitive, but less vulnerable because of higher adaptive capacity and lower exposure.