Sustainable agricultural intensification or Jevons paradox? The role of public governance in tropical South America

The process of global deforestation calls for urgent attention, particularly in South America where deforestation rates have failed to decline over the past 20 years. The main direct cause of deforestation is land conversion to agriculture. We combine data from the FAO and the World Bank for six tropical Southern American countries over the period 1970–2006, estimate a panel data model accounting for various determinants of agricultural land expansion and derive elasticities to quantify the effect of the different independent variables. We investigate whether agricultural intensification, in conjunction with governance factors, has been promoting agricultural expansion, leading to a “Jevons paradox”. The paradox occurs if an increase in the productivity of one factor (here agricultural land) leads to its increased, rather than decreased, utilization. We find that for high values of our governance indicators a Jevons paradox exists even for moderate levels of agricultural productivity, leading to an overall expansion of agricultural area. Agricultural expansion is also positively related to the level of service on external debt and population growth, while its association with agricultural exports is only moderate. Finally, we find no evidence of an environmental Kuznets curve, as agricultural area is ultimately positively correlated to per-capita income levels.     

广东农业水灾的年际分布规律及重灾年份预测

水灾是广东省最严重的农业自然灾害之一,几乎年年都有发生。广东农业水灾的受灾率异常指数和成灾率异常指数的变化规律揭示:过去55年间,农业水灾具有明显的波动性与阶段性,大致以5年为尺度,轻重灾期交替出现;受灾率与成灾率具有同步性,在重灾期尤为明显;1980年以来灾情更为严重,成灾率、受灾率、重灾几率都较大。根据异常指数的变化,建立起农业水灾灰色灾变预测模型,进行重灾预测。结果表明,今后20年将出现4个重灾年份,分别在2007-2009年、2012-2014年、2017-2019年和2023-2025年。     

SEDIMENT TRANSPORT PROCESSES IN AGRICULTURAL WATERSHEDS

lINTR0DUCTI0NTheerosion,transportanddep0siti0nofsedimentinawatershedarepallofthenaturalsystemofwatershedprocesses.InanundistUrbedwatershed,s0ilsinuplandareasaregraduallyeroded,transportCdforsomedistanceandeventuallydepositedatlowereIevations.WhenwatershedsaredistUrbedbyhumanactivitiessuchasclearingofvegetation,urbaniZati0n,orotherchangesthataffectthelandscaPe,unstablechannelswithlocallyhighratesoferosion,transport,0rdepositionofsedimentoftenaretheresult.Theimpact0fer0sionisespeciallyhigh…     

Agricultural water poverty: Using Q-methodology to understand stakeholders' perceptions

The aim of this Q methodology study was to identify perceptions of farmers and agricultural specialists toward agricultural water poverty concept and its causes in Marvdasht County, Iran. Seventy five participants completed the Q sort procedure. Data analysis identified seven types of perceptions toward agricultural water poverty: Management-adherents, Adaptive-adherents, Fatalists, Support-seekers, Farmer blamer Pessimists, Technocratic Realists and Optimists. The first four types of perceptions were dominated by farmers and the last three by agricultural specialists. These different perspectives indicated that various individuals think differently about the nature, causes, effects and permanency of agricultural water poverty. Understanding the multiple meaning systems of agricultural water poverty for decision and policy makers will be critical as they may provide the basis for the development of more appropriate strategies to mitigate water poverty in agricultural sector.     

Agricultural risk management policies under climate uncertainty

Climate change is forecasted to increase the variability of weather conditions and the frequency of extreme events. Due to potential adverse impacts on crop yields it will have implications for demand of agricultural risk management instruments and farmers’ adaptation strategies. Evidence on climate change impacts on crop yield variability and estimates of production risk from farm surveys in Australia, Canada and Spain, are used to analyse the policy choice between three different types of insurance (individual, area-yield and weather index) and ex post payments. The results are found to be subject to strong uncertainties and depend on the risk profile of different farmers and locations; the paper provides several insights on how to analyse these complexities. In general, area yield performs best more often across our countries and scenarios, in particular for the baseline and marginal climate change (without increases in extreme events). However, area yield can be very expensive if farmers have limited information on how climate change affects yields (misalignment in expectations), and particularly so under extreme climate change scenarios. In these more challenging cases, ex post payments perform well to increase low incomes when the risk is systemic like in Australia; Weather index performs well to reduce the welfare costs of risks when the correlation between yields and index is increased by the extreme events. The paper also analyses the robustness of different instruments in the face of limited knowledge of the probabilities of different climate change scenarios; highlighting that this added layer of uncertainty could be overcome to provide sound policy advice under uncertainties introduced by climate change. The role of providing information to farmers on impacts of climate change emerges as a crucial result of this paper as indicated by the significantly higher budgetary expenditures occurring across all instruments when farmers’ expectations are misaligned relative to actual impacts of climate change.     

The Role of Local Knowledge in the Risk Management of Extreme Climates in Local Communities: A Case Study in a Nomadic NIAHS Site

In the context of climate change, research on extreme climates and disaster risk management has become a crucial component of climate change adaptation. Local communities, which have been facing extreme climates for a long time in their production and daily life, have developed some locally applicable traditional knowledge that has played an important role in their adaptation to extreme climate and disaster risk management. Therefore, this research aims to link Local knowledge (LK) to community extreme climate disaster risk management in order to construct a conceptual model. It then takes the extreme climate adaptation strategy of traditional nomads in a temperate grassland of China as an example to analyze the role of LK in extreme climate adaptation using the proposed theoretical framework. The main research objectives of this study are: (1) To construct a conceptual model to illustrate the relations among extreme climate events, risk management, LK, and farmers' adaptation strategies; (2) To apply the theoretical framework to a field case to reveal context-specific extreme climate adaptation mechanisms with LK as a critical component; (3) To test the framework and provide suggestions for the extreme climates adaptation, and the conservation of LK related to climate change adaptation. The results show that from the perspective of disaster risk management, local communities could manage extreme climates as a disaster risk through adaptation strategies formed from LK, because as a knowledge system, LK contains relevant knowledge covering the whole process of disaster risk management.     

人工增雨农业减灾技术研究

该项目在河南、山东、吉林3省建立了层状云人工增雨外场观测作业试验区，研制了层状云数值模式，结合分析得出了层状云人工增雨新的概念模型、相应的催化条件判据和作业指标；研制了催化条件的飞机实时识别技术和地面综合集成识别技术；建立了中尺度层状云系数值模拟预报的实时业务和省级的人工增雨综合技术系统（催化条件综合识别判据、实时监测识别技术、催化指标和作业决策系统等），提出了相应的作业流程。 在鄂西北（十堰市）对流云人工增雨作业试验区进行了大量外场观测和作业试验，用研制的三维对流云催化模式进行实时预报和催化数值试验，初步提出了催化的最佳部位、时机和剂量；开发应用了高成核率火箭；用雷达识别作业条件并建立了指挥作业的技术流程，因而大大减少了作业的盲目性，提高了对流云人工增雨作业的科学性。     

Modeling N2O Emissions from Agricultural Fields in Southeast China

DNDC, a rainfall-driven and process-oriented model of soil carbon and nitrogen biogeochemistry, is applied to simulate the nitrous oxide emissions from agricultural ecosystem in Southeast China. We simulated the soil N₂O emission during a whole rice-wheat rotation cycle (from Nov. 1, 1996 to Oct. 31, 1997) under three different conditions, which are A) no fertilizer, B) both chemical fertilizer and manure and, C) chemical fertilizer only. The processes of N₂O emission were discussed in detail by comparing the model outputs with the results from field measurement. The comparison shows that the model is good at simulating most of the N₂O emission pulses and trends. Although the simulated N₂O emission fluxes are generally less than the measured ones, the model outputs during the dryland period, especially during the wheat reviving and maturing stages in spring, are much better than those during the paddy field period. Some sensitive experiments were made by simulating the N₂O emissions in spring, when there is a smallest gap between the simulated fluxes and the measured ones. Meanwhile, the effects of some important regulating factors, such as the rainfall, N deposition by rainfall, temperature, tillage, nitrogen fertilizer and manure application on N₂O emission during this period were analyzed. From the analysis, we draw a conclusion that soil moisture and fertilization are the most important regulating factors while the N₂O emission is sensitive to some other factors, such as temperature, manure, tillage and the wet deposition of atmospheric nitrate.     

贵州省水稻实时农业气候综合评价方法研究

利用1979～1991年贵州水稻气象与物候观测等资料和数理统计分析方法，研究了水稻实时农业气候综合评价方法。应用该方法对贵州省水稻产量年景进行了验证，结果表明该方法对水稻生产具有较高的实用价值。     

从"四地"期刊载文审视中国农业与乡村地理学研究发展特征

基于中国学术期刊出版总库所提供的《地理学报》《地理科学》《地理研究》《地理科学进展》（简称“四地”期刊）创刊以来至2020年12月间的农业与乡村地理学论文数据,采用Citespace可视化科学文献计量方法,对566篇文献的主题、引文和关键词等特征进行可视化分析。系统梳理了农业与乡村地理学术论文所反映的主题脉络、知识演进、历史热点、研究机构发展和发文作者分析。这些分析充分体现出了中国农业与乡村地理学研究的发展历程、目前的主要研究议题与未来的发展趋势。研究结果显示,农业地理、聚落与古村落、土地利用及其发展模式、乡村居民点及其空间格局、城乡一体化、新农村建设、乡村重构、乡村振兴和城乡融合发展等主要研究议题是不同时期的研究聚焦点。从研究热度看大致经历了由以农业地理研究为主,转向农业地理与乡村聚落地理并驾齐驱,再到城乡融合与乡村振兴研究3个阶段。其研究发展过程呈现出3大转向：① 由单一的农业地理和乡村聚落地理转向综合的农业与乡村地理学研究;② 从单一的农业生产要素、社会经济要素格局研究转向区域城乡人地系统融合的过程、机制和影响研究;③ 由传统的调研统计、田野观测、数字模拟技术方法转向大数据、多源时空监测模拟和农业地理工程实践。乡村转型-城乡融合-乡村振兴-高质量发展将成为未来城乡发展的大逻辑、新常态,也是未来农业与乡村地理学研究的重点和方向。主要研究议题方面有乡村地域类型、乡村功能转型、乡村空间重构、乡村聚落重构、乡村人居环境质量、乡村发展的新因素及其作用机制、乡村弹性与可持续性发展、乡村产业结构调整与升级、城乡基础设施与服务统筹规划建设等。学科发展应注重综合研究,深化对农业与乡村发展新驱动力的认识,切实加强乡村地理学研究的理论与方法创新,借以更好地服务于国家乡村振兴战略。