Impact of climate change on maize yield in China from 1979 to 2016

Climate change severely impacts agricultural production, which jeopardizes food security. China is the second largest maize producer in the world and also the largest consumer of maize. Analyzing the impact of climate change on maize yields can provide effective guidance to national and international economics and politics. Panel models are unable to determine the group-wise heteroscedasticity, cross-sectional correlation and autocorrelation of datasets, therefore we adopted the feasible generalized least square(FGLS) model to evaluate the impact of climate change on maize yields in China from 1979–2016 and got the following results:(1) During the 1979–2016 period, increases in temperature negatively impacted the maize yield of China. For every 1°C increase in temperature, the maize yield was reduced by 5.19 kg 667 m–2(1.7%). Precipitation increased only marginally during this time, and therefore its impact on the maize yield was negligible. For every 1 mm increase in precipitation, the maize yield increased by an insignificant amount of 0.043 kg 667 m–2(0.014%).(2) The impacts of climate change on maize yield differ spatially, with more significant impacts experienced in southern China. In this region, a 1°C increase in temperature resulted in a 7.49 kg 667 m–2 decrease in the maize yield, while the impact of temperature on the maize yield in northern China was insignificant. For every 1 mm increase in precipitation, the maize yield increased by 0.013 kg 667 m–2 in southern China and 0.066 kg 667 m–2 in northern China.(3) The resilience of the maize crop to climate change is strong. The marginal effect of temperature in both southern and northern China during the 1990–2016 period was smaller than that for the 1979–2016 period.     

基于格网的GCM数据修订分析未来海南岛农业水热资源的变化特征

以海南岛为研究区域，选用5个大气环流模式（GCMs）1970−1999年的逐日输出数据和同期地面气象观测数据，使用空间插值降尺度到0.5°×0.5°格网。以格网单元为基础，应用系统误差修订（修正值法或比值法）和多模式集合平均方法（贝叶斯模型平均法BMA或等权重平均法EW），训练与验证GCMs输出值并进行综合修订。在此基础上，分析RCP2.6、RCP4.5和RCP8.5情景下，未来海南岛近期（2020−2059年）和远期（2060−2099年）农业水热资源，包括年平均气温、1月平均气温、≥10℃积温、≥20℃积温、年降水量、1月降水量和≥20℃界限温度生长期间降水量的变化特征。结果表明：GCMs输出值的系统误差和BMA权重系数在格网间存在较大的空间差异，且GCMs输出值低估逐日最高气温约3.55℃，高估逐日最低气温约1.19℃，逐日降水量仅为观测值的54.35%。基于格网的综合修订，可有效降低GCMs输出值在空间上的不确定性，BMA与EW的修订结果相似，均优于单一GCM模式。通过格网BMA综合修订后，最高气温、最低气温和降水量在验证期的相关系数r分别约提升0.10、0.07和0.06；均方根误差RMSE分别约降低2.38℃、1.01℃和1.01mm；较单一GCM相对观测值的偏差平均约减少3.25℃、1.13℃和25.67mm。未来海南岛农业热量资源在空间上主要表现为从中部向外围逐渐升高，高温主要分布在南部至西部沿海地区，年平均气温的增幅全岛较为接近，1月平均气温、≥10℃积温和≥20℃积温的增幅分别表现为由东向西、由北向南和由中部向外围递减。在时间上，RCP8.5情景下所有农业热量资源均为极显著增加且增温最快，RCP4.5情景为先增加后平缓，RCP2.6情景较为平缓，远期无显著增温。未来海南岛降水资源在空间上转为由东向西逐步递减的格局，南部和北部沿海地区降水变率增加，西部和中部降水变率减少，在时间上无显著变化趋势。随着未来海南岛气候变暖和降水格局的改变，农作物适宜种植面积扩大，会对农业生产带来巨大挑战，应提前布局，做好趋利避害。     

云南不同气候带农业气候资源变化特征研究

为分析全省平均以及各气候带光能、热量、水分资源的时空变化特征,使用云南115站及6个气候带代表站1961—2018年的气候要素计算各地农业气候资源统计量。结果表明,光能资源变化以减少趋势为主,出现显著突变,各气候带太阳辐射变化可能会引起云南太阳辐射高低值中心发生变化,2009年以来辐射明显增加可能会导致太阳辐射出现新的变化趋势和突变点;热量资源一致显著增加,喜凉及喜温作物的活动积温、积温持续时间及无霜期长度均显著增加,并且呈现初日提前、终日推后的趋势,对作物生长有利;水分资源总体呈现减少趋势,尤其21世纪以来下降趋势明显,亚热带地区暖干化现象突出,干旱风险等级较高。     

共享经济模式下重庆食用菌旅游资源发展趋势及创新路径

从共享旅游文化、共享食用菌历史文化的角度,讨论了发展食用菌个性化旅游和体验式旅游的思路;结合食用菌绿色、健康和生态的核心体验元素,给出了依托食用菌绿色、生态的品牌优势,打造食用菌旅游产业的具体方法。在此基础上,探讨了重庆食用菌旅游资源的共享经济模式,提出以重庆食用菌美食为龙头,利用多种共享经济新业态来带动重庆食用菌旅游产业的发展。     

护林防火技术在森林资源保护中的应用

合理运用护林防火技术可以提升森林资源保护工作的整体质量,推动林业不断发展。本文分析了森林火灾发生的原因,总结了护林防火技术,提出了相关应用对策,以期为减少森林火灾的发生和保护森林资源提供参考。     

Studies on Tomato Seedling Quality Indices Under Simulated Shipping and Storage Conditions

Indices of the tomato seedling quality maintenance level after production before field planting were studied through simulated experiments, small--scale operation, indoor analyses and measurements, and field observation. The results showed that under simulated shipping and storage conditions, seedling quality change following different durations (days) of shipping and storage was correlated significantly or even very significantly with certain physiological and morphological indices. With various measured indices following different periods of shipping and storage treatment subjected to multinomial successive regressive correlation analysis, the principal factors influencing seedling quality maintenance level are identified to be chlorophyll content→dry short weight→ leaf freshness index in order of their importance. Significance analysis with multinomial fitted equation indicated that correlations between any one of above three factors and the growth index after field planting reached very significant difference level.     

电子政务环境下政府信息资源共享模式探索

电子政务环境下政府信息资源共享是多种社会动力共同作用的结果.构建信息公开发布、增值开发、公共数据中心和政务信息交换平台四种政府信息资源共享模式,破除阻碍我国电子政务环境下政府信息资源共享的各种因素,是贯彻落实党的十七大提出的构建和谐社会、以人为本,使全社会成员享受改革开放成果的执政理念的必然要求.     

利用高等数学推导边际分析在经济学中的应用

本文从高等数学的基本理论导数的概念出发，引出了经济管理学中重要的概念边际函数，通过介绍经济科学中常用的函数及大量的实例，探讨了高等数学在经济管理学中的应用，给出了解决这些问题的一般方法。     

A novel approach to studying the effects of temperature on soil biogeochemistry using a thermal gradient bar

The temperature dependence of chemical reaction rates and microbial metabolism mean that temperature is a key factor regulating soil trace gas emissions and hydrochemistry. Here we evaluated a novel approach for studying the thermal response of soils, by examining the effects of temperature on gas emissions and hydrochemistry in (a) peat and (b) soil from a Sitka spruce plantation. A thermal gradient was applied along an aluminium bar, allowing soil to be incubated contemporaneously from 2 to 18 °C. The approach demonstrated clear differences in the biogeochemical responses of the two soil types to warming. The peat showed no significant emission of CH₄ at temperatures below 6 °C, while above 6 °C, a marked increase in the rate of release was apparent up to 15 °C (Q₁₀ = 2.5) with emissions being similar between 15 and 18 °C. Conversely, CH₄ emissions from the forest soil did not respond to warming. Nitrate availability in the peat decreased by 90% between 2 and 18 °C (P < 0.01), whereas concentrations in the forest soil did not respond. Sulphate availability in the peat decreased significantly with warming (60%, P < 0.01), while the forest soil showed the opposite response (a 30% increase, P < 0.01). Conventionally, thermal responses are studied by incubating individual soil samples at different temperatures, involving lengthy preparation and facilities to incubate samples at different temperatures simultaneously. Data collected on a given thermal response is usually limited and thus interpolated or extrapolated. The thermal gradient method overcomes these problems, is simple and flexible, and can be adapted for a wide range of sample types (not confined to soil). Such apparatus may prove useful in the optimization of management practices to mitigate the effects of climate change, as thermal responses will differ depending on land use and soil type.