机器学习与统计模型在石羊河流域气候降尺度研究中的适用性对比

高分辨率气候数据是研究气候变化对农业、生态、水文影响的驱动数据,动力和统计降尺度模型是两类常用的生成高分辨率气候数据的方法,近年来机器学习模型也被用到气候变化的研究中,但针对不同站点(下垫面)的多种统计降尺度模型的对比研究较少.石羊河流域土地利用类型多样,海拔变化显著,适合研究降尺度模型的适用性.本研究选择2种传统统计...     

1993—2017年气候变化对西藏谷物单产的定量影响

气候变化对农业的影响是全球关注的热点问题之一,青藏高原对气候变化尤其敏感,但气候变化对青藏高原农业产量的定量影响缺乏系统研究。为定量评估气候变化对西藏谷物单产的影响,本文使用气象数据与年鉴统计数据,选取了固定效应模型、差分模型和线性去趋势模型3类统计模型,分析了1993—2017年间气候变化（最低气温、降水量、生长度日和太阳辐射）对西藏县（区）级、市级和自治区3个尺度的谷物单产的影响。结果表明：西藏整体对于温度（最低气温和生长度日）的敏感性大于降水量和太阳辐射。各项气候因子对西藏谷物单产的整体影响为正影响,但不同区域对气候因子的敏感程度和显著性不同。除了生长度日对于拉萨为负影响以外,最低气温、降水量和太阳辐射对于所有市均为正影响。气候趋势对于西藏整体谷物单产的影响为正影响,不同模型计算结果集中在1.5%~4.8%区间内。3类模型中固定效应模型稳定性最好,线性去趋势模型好于差分模型,差分模型在引入气候因子间的交互项后模型稳定性降低。本文有助于西藏实施更加有空间针对性的农业适应气候变化措施,以应对气候造成的青藏高原农业生态系统变化。     

Impacts of climate change in Central Planins of China： on winter wheat yield Case study of Shangqiu

为探明气候变化对商丘地区冬小麦产量的影响,根据1991～2010商丘市气候资料和小麦产量资料,利用数学统计与Thornthwaite Memoriae模型,结合未来气候预测结果定量分析了气候变化对冬小麦产量的影响。结果表明,冬小麦产量整体上呈波动上升趋势;主成分分析表明,气温、降水量、蒸发量与极端温度为影响冬小麦产量的主要气候因子,蒸发量过大及极端低温对冬小麦生产不利。商丘地区“暖湿型”气候有利于冬小麦生产力的提高,“冷干型”气候对冬小麦生产最为不利;未来几十年内气候可能将向“暖湿型”变化,对商丘地区粮食作物产量的提升较为有利。     

中原腹地气候变化对冬小麦产量的影响——以商丘地区为例

为探明气候变化对商丘地区冬小麦产量的影响,根据1991～2010商丘市气候资料和小麦产量资料,利用数学统计与Thornthwaite Memoriae模型,结合未来气候预测结果定量分析了气候变化对冬小麦产量的影响。结果表明,冬小麦产量整体上呈波动上升趋势;主成分分析表明,气温、降水量、蒸发量与极端温度为影响冬小麦产量的主要气候因子,蒸发量过大及极端低温对冬小麦生产不利。商丘地区"暖湿型"气候有利于冬小麦生产力的提高,"冷干型"气候对冬小麦生产最为不利;未来几十年内气候可能将向"暖湿型"变化,对商丘地区粮食作物产量的提升较为有利。     

全球气候变化影响下中国农业产量的可持续性

气候变化的区域影响愈益成为具有挑战性的问题,尤其是气候变化对农业产量可持续性的影响已引起广泛的关注。基于全示气候变化对中国的影响和区域气候变率分析,提出了粮食气候产量形成模型,半将其应用于黄淮海地区冬小麦小分条件和产量研究,同时对全球气候变化情形下冬小麦产量的变化做出评价。     

未来气候情景下气候变化响应过程研究综述

气候变化将会对生态系统、自然资源、极端气候和人类社会产生一定的影响,科学评估未来气候变化响应是应对气候变化的前提。通过对当前研究成果的回顾,建立未来气候情景下气候变化响应研究的系统思路,并总结了研究所涉及的方法。系统论述了应用第5阶段耦合模式比较计划(CMIP5)气候模式前进行适用性评价的必要性;分析了当前降尺度方法尤其是统计降尺度的主要方法及进展;归纳了偏差校正过程中普遍使用的方法,最后,综合分析了整个研究过程中的不确定性。研究将为气候变化响应分析提供方法和思路指导。     

年代际尺度海岸演化机制与动力-统计建模方法

发展中长时间尺度的海岸演化预测方法与机理模型,是目前国际海岸演化研究领域关注的焦点和最具挑战性课题。本文系统性地回顾了近半个世纪以来不同时间尺度海岸演化模式的研究发展历程和成果,从动力机制和时间尺度两个方面对海岸演化机理模型存在的主要建模瓶颈问题进行了系统总结。通过对渤海湾西岸近一个半世纪以来海岸演化机制的初步分析,提出了以泥沙收支、环流输送、波浪掀沙以及波气候变化等要素作为年代际尺度海岸演化主要驱动因子,基于驱动力概化与统计升尺度有机衔接的年代际尺度海岸演化机理模型的动力—统计建模方法框架新思路,为推动海岸演化动力学理论体系和中长时间尺度海岸演化预测方法创新,提供了重要科学依据和借鉴。     

全球气候变化下中国农业的脆弱性与适应对策

全球气候变化问题虽然还存在某些不确定性，但已得到广泛认同，对气候条件颇为敏感的农业将受影响，主要效应可概括为：（１）农业地理限制的变动；（２）作物产量的变化；（３）对农业系统的冲击。中国农业对气候变化与波动尤其敏感，加之人口压力进一步加大和农业资源已有紧缺，粮食自给的能力将受到严重威胁，必须充分重视适应和调整对策的研究，变动性与不确定性是气候的固有特征，在评价全球气候变化对农业的影响时应该认识到这     

森林砍伐、气候变化与农业可持续性：综述（英文）

本研究通过总结相关文献探讨了森林砍伐与农业之间的关系,并评估了气候变化对其潜在影响。选择具有重要生态意义的西高止山区作为研究对象,通过整理各个研究主题下的相关结果,我们详细探讨了包括森林砍伐的根本原因,森林土地转化为农业用途,农业、森林砍伐与气候变化之间的关系,气候驱动的农业脆弱性以及如何在保护森林与发展农业之间取得平衡。研究发现,农业的转变已经成为引发森林砍伐的主要原因;气候变化对农业的主要影响体现在作物产量的下降。印度的干旱和亚热带地区对气候变化的敏感性较高,这很可能是由于印度的热带森林遭受了较严重的砍伐。西高止山区联合森林规划和管理区域的树木密度较高,这为剩余土地用于非森林用途（如农业）创造了潜在的机会。     

三江平原湿地生态风险评价的尺度依存性及区域生态风险评价方案制定

通过识别三江平原湿地主要生态风险源(气候变化、沟渠建设、农业非点源污染、湿地旅游活动的开展)与风险受体(植物群落退化演替、生物多样性下降、固碳水平降低),发现风险源主要来自于湿地系统外部,而风险受体则依存于单一的湿地生态系统。为了解决尺度矛盾问题,提出尺度上推(将风险受体扩展到区域或流域上,以匹配风险源的空间尺度)与尺度下推(将风险源尺度缩小到局地甚至点上,通过实验设置,模拟风险源发生水平,以匹配风险受体的空间尺度)两种解决方案。在此基础上,探讨了三江平原湿地区域生态风险评价方案和流程的合理构建过程,包括风险源空间化方案(气候变化情景降尺度、沟渠密度制图、农业非点源输出模拟和湿地旅游活动强度的缓冲区表达等)、表征生态系统内在属性的生态资产指数和生态脆弱性指数构建、风险值表征问题。     

A review on statistical models for identifying climate contributions to crop yields

Statistical models using historical data on crop yields and weather to calibrate relatively simple regression equations have been widely and extensively applied in previous studies, and have provided a common alternative to process-based models, which require extensive input data on cultivar, management, and soil conditions. However, very few studies had been conducted to review systematically the previous statistical models for indentifying climate contributions to crop yields. This paper introduces three main statistical methods, i.e., time-series model, cross-section model and panel model, which have been used to identify such issues in the field of agrometeorology. Generally, research spatial scale could be categorized into two types using statistical models, including site scale and regional scale (e.g. global scale, national scale, provincial scale and county scale). Four issues exist in identifying response sensitivity of crop yields to climate change by statistical models. The issues include the extent of spatial and temporal scale, non-climatic trend removal, colinearity existing in climate variables and non-consideration of adaptations. Respective resolutions for the above four issues have been put forward in the section of perspective on the future of statistical models finally.     

Progress on quantitative assessment of the impacts of climate change and human activities on cropland change

It is important to study the contributions of climate change and human activities to cropland changes in the fields of both climate change and land use change. Relationships between cropland changes and driving forces were qualitatively studied in most of the previous researches. However, the quantitative assessments of the contributions of climate change and human activities to cropland changes are needed to be explored for a better understanding of the dynamics of land use changes. We systematically reviewed the methods of identifying the contributions of climate change and human activities to cropland changes at quantitative aspects, including model analysis, mathematical statistical method, framework analysis, index assessment and difference comparison. Progress of the previous researches on quantitative evaluation of the contributions was introduced. Then we discussed four defects in the assessment of the contributions of climate change and human activities. For example, the methods were lack of comprehensiveness, and the data need to be more accurate and abundant. In addition, the scale was single and the explanations were biased. Moreover, we concluded a clue about quantitative approach to assess the contributions from synthetically aspect to specific driving forces. Finally, the solutions of the future researches on data, scale and explanation were proposed.     

气候变化和人类活动对耕地格局变化的贡献归因综述（英文）

It is important to study the contributions of climate change and human activities to cropland changes in the fields of both climate change and land use change. Relationships between cropland changes and driving forces were qualitatively studied in most of the previous researches. However, the quantitative assessments of the contributions of climate change and human activities to cropland changes are needed to be explored for a better understanding of the dynamics of land use changes. We systematically reviewed the methods of identifying the contributions of climate change and human activities to cropland changes at quantitative aspects, including model analysis, mathematical statistical method, framework analysis, index assessment and difference comparison. Progress of the previous researches on quantitative evaluation of the contributions was introduced. Then we discussed four defects in the assessment of the contributions of climate change and human activities. For example, the methods were lack of comprehensiveness, and the data need to be more accurate and abundant. In addition, the scale was single and the explanations were biased. Moreover, we concluded a clue about quantitative approach to assess the contributions from synthetically aspect to specific driving forces. Finally, the solutions of the future researches on data, scale and explanation were proposed.     

气候变化和人类活动对耕地格局变化的贡献归因综述

定量辨识气候变化和人类活动对耕地格局变化的贡献归因,是当今气候变化和土地利用变化领域的热点问题。目前研究大都结合耕地的时空变化格局和相关驱动因素进行双变量或多变量的定性分析,未进一步定量给出气候变化和人类活动的贡献程度。本文对国内外相关研究进行总结,介绍了定量评价气候变化和人类活动对耕地格局变化的贡献程度的5种主要研究方法,即模型分析法、数理统计法、框架分析法、指标评价法和差值比较法。综述了气候变化、人类活动以及两者共同作用对耕地格局变化的贡献归因的主要结论。总结了目前研究存在的方法综合性较差、数据全面性与准确性欠缺、尺度单一和解释片面等问题,针对以上问题,提出了从综合作用到具体因素的贡献程度归因评价的思路,并就数据、尺度与驱动力的解释问题提出了研究展望。     

CROP RESPONSE TO CLIMATE CHANGE IN THE SOUTHERN GREAT PLAINS: A SIMULATION STUDY*

This study utilizes global climate models and crop growth models to estimate the potential agricultural effects of climate change caused by a doubling of atmospheric carbon dioxide for the southern Great Plains. Projected climate changes cause simulated wheat and corn yields to decrease in the study area. Decreases in modeled grain yields are caused primarily by temperature increases which shorten the duration of crop life cycle and curtail the harvestable biomass production. While physiological effects of carbon dioxide and changing cultivars offer some hope of climate change mitigation, detrimental consequences to regional crop production, including need for increased irrigation, are suggested.     

1993-2017年气候变化对西藏谷物单产的定量影响

Climate change is a global environmental crisis, but there have been few studies of the effects of climate change on cereal yields on the Tibetan Plateau. We used data from meteorological stations and statistical yearbooks to assess the impacts of climate change on cereal yields in Tibet. Three types of statistical models were selected: fixed-effects model, first-difference models, and linear detrending models. We analyzed the impacts of climate change(including the minimum temperature, precipitation, growing degree days and solar radiation) on cereal yields in Tibet from 1993 to 2017 at the county, prefecture-level city, and autonomous region scales. The results showed that the sensitivity of cereal yields in Tibet to temperature(minimum temperature and growing degree days) was greater than their sensitivity to precipitation and solar radiation. The joint impacts of climate variables were positive, but the sensitivity and significance varied in different regions. The impacts of minimum temperature, precipitation, and solar radiation were positive in all cities, apart from the negative impacts of growing degree days on cereal yields in Lhasa. The impacts of climate trends on cereal yields in Tibet were positive and the results were in the range of 1.5%–4.8%. Among the three types of model, the fixed-effects model was the most robust and the linear detrending model performed better than the first-difference model. The robustness of the first-difference model decreased after adding the interaction terms between different climate variables. Our findings will help in implementing more spatially targeted agricultural adaptations to cope with the impacts of climate change on the agro-ecosystem of the Tibetan Plateau.     

Development of quantitative methods for detecting climate contributions to boundary shifts in farming-pastoral ecotone of northern China

The quantitative effect of climate change on fragile regions has been a hot topic in the field of responses to climate change. Previous studies have qualitatively documented the impacts of climate change on boundary shifts in the farming-pastoral ecotone (FPE); however, the quantitative methods for detecting climate contributions remain relatively limited. Based on long-term data of meteorological stations and interpretations of land use since 1970, climate and land use boundaries of the 1970s, 1980s, 1990s and 2000s were delineated. To detect climate contributions to the FPE boundary shifts, we developed two quantitative methods to explore the spatial-temporal pattern of climate and land use boundary at the east-west (or south-north) (FishNet method) and transect directions (Digital Shoreline Analysis System, DSAS method). The results indicated that significant differences were exhibited in climate boundaries, land use boundaries, as well as climate contributions in different regions during different periods. The northwest FPE had smaller variations, while the northeast FPE had greater shifts. In the northwest part of the southeast fringe of the Greater Hinggan Mountains and the Inner Mongolian Plateau, the shifts of climate boundaries were significantly related to the land use boundaries. The climate contributions at an east-west direction ranged from 10.7% to 44.4%, and those at a south-north direction varied from 4.7% to 55.9%. The majority of the results from the DSAS were consistent with those from the FishNet. The DSAS method is more accurate and suitable for precise detection at a small scale, whereas the FishNet method is simple to conduct statistical analysis rapidly and directly at a large scale. Our research will be helpful to adapt to climate change, to develop the productive potential, as well as to protect the environment of the FPE in northern China.     

气候变化对北方农牧交错带界线变迁影响的定量探测方法研究（英文）

The quantitative effect of climate change on fragile regions has been a hot topic in the field of responses to climate change. Previous studies have qualitatively documented the impacts of climate change on boundary shifts in the farming-pastoral ecotone(FPE); however, the quantitative methods for detecting climate contributions remain relatively limited. Based on long-term data of meteorological stations and interpretations of land use since 1970, climate and land use boundaries of the 1970 s, 1980 s, 1990 s and 2000 s were delineated. To detect climate contributions to the FPE boundary shifts, we developed two quantitative methods to explore the spatial-temporal pattern of climate and land use boundary at the east-west(or south-north)(Fish Net method) and transect directions(Digital Shoreline Analysis System, DSAS method). The results indicated that significant differences were exhibited in climate boundaries, land use boundaries, as well as climate contributions in different regions during different periods. The northwest FPE had smaller variations, while the northeast FPE had greater shifts. In the northwest part of the southeast fringe of the Greater Hinggan Mountains and the Inner Mongolian Plateau, the shifts of climate boundaries were significantly related to the land use boundaries. The climate contributions at an east-west direction ranged from 10.7% to 44.4%, and those at a south-north direction varied from 4.7% to 55.9%. The majority of the results from the DSAS were consistent with those from the Fish Net. The DSAS method is more accurate and suitable for precise detection at a small scale, whereas the Fish Net method is simple to conduct statistical analysis rapidly and directly at a large scale. Our research will be helpful to adapt to climate change, to develop the productive potential, as well as to protect the environment of the FPE in northern China.