科学估算农业生态服务价值损失及其空间分布差异有益于客观评价城镇化的社会经济影响，理论支撑集约、绿色新型城镇化发展。参照中国陆地生态系统服务价值当量因子表，估算耕地非农化造成的农业生态服务价值损失，并结合不同时段的社会发展系数进行修正。测算结果表明：2001—2016年耕地转为建设用地造成的农业生态服务价值损失理论值达1 066.59亿元，现实值约476.25亿元，其中农业生态系统保持土壤功能价值现实损失达107.54亿元。耕地征收导致的农业生态服务价值均值现实损失地域分布从大到小依次为东部、中部、东北部和西部，从省域尺度来看，江苏、云南和浙江的累计耕地生态服务价值现实损失量最多。耕地转为建设用地的热点地区已由东部向中西部转移，应尽快完善多元化耕地保护补偿制度，重点推进中西部地区人的城镇化。

Evaluating the loss of agroecosystem service value comprehensively and analyzing the spatial distribution are beneficial to evaluate the social and economic impact of urbanization objectively and can provide certain theory support for the development of intensive and green new-type urbanization. this paper calculates theoretical loss of agriculture ecological service value applying the equivalent factor method of ecosystem service value and assesses its real loss by correcting the social development coefficient at different times. The result shows that, during 2001 and 2016, the theoretical loss of agroecosystem service value caused by cultivated land converted to construction is up to 106.66 billion yuan and its real loss is about 47.63 billion yuan including 10.75 billion yuan of the soil functional value. The real loss of agroecosystem services value caused by farmland occupation gradually reduces from the east to the west. From the provincial perspective, the areas heavily suffering the real loss are distributed in Jiangsu Province, Yunnan Province and Zhejiang Province. Based on the trend of hotspots converting arable land to construction land is shifting from the east to the Midwest, diversified farmland protection and compensation systems should be improved and urbanization of population should be promoted emphatically.

基于1980—2020年中国土地利用数据和社会经济统计面板数据，对耕地非农化与非粮化时空演变特征进行系统分析，揭示其变化规律及驱动机制，以期为耕地可持续利用和稳定粮食安全提供依据。采用标准差椭圆、趋势分析估计综合评估非农化、非粮化动态演变特征，构建非农化、非粮化综合指标体系，构建偏相关模型量化各因子相对贡献。结果表明：（1）时间上，我国非农化形势总体不断趋好，而部分地区非粮化表现出加剧趋势。（2）空间上，东北和中东部地区的非农化问题较为突出，西北、华南以及东南沿海部分地区非粮食生产的比例相对较高。非农化演变存在沿东北-东南方向“极化现象”，非粮化中心呈现出从西南向东北移动的发展态势。（3）经济因素是非农化主导驱动作用，且近10 a来影响程度有所降低。农业生产条件是非粮化的基础因素，同时粮食每亩产值、城乡收入差距等经济因素的推动作用逐渐增加。1980—2020年中国非农化、非粮化时空演变特征与影响因素研究可为科学实施耕地保护决策提供参考。

Drawing upon China’s comprehensive land use data and socioeconomic panel statistics spanning 1980-2020, this study meticulously analyzed the spatiotemporal evolution characteristics of nonagricultural and nongrain farmland. It aimed to elucidate their underlying patterns of change and driving mechanisms, establishing a solid foundation for sustainable cultivated land utilization and stable food security. Utilizing the SD ellipse and trend analysis, we comprehensively assessed the dynamic evolution traits of these nontraditional agricultural uses. Furthermore, we constructed a comprehensive index system tailored for nonagricultural and nongrain farmlands and developed a partial correlation model to quantitatively assess the relative contributions of various influencing factors. This comprehensive approach offers a nuanced understanding of the intricate dynamics governing these farmland transitions and their implications for China’s agricultural sustainability and food security. (1) Regarding time, the current situation of nonagriculture farmland in China is getting better, but the nonagriculture phenomenon is still prominent in some areas and tends to intensify further. (2) Regarding space, the degree of nonagriculture is more serious in the northeast, central, and eastern regions, while it is higher in the northwest, south, and some coastal areas of southeast China. The polarization phenomenon exists in the direction of nonagricultural chemical evolution. The nongrain center exhibited a development trend of moving from the southwest to the northeast. (3) Economic factors are the leading driving effect of nonagricultural chemistry, and their degree of influence has decreased in the past ten years. Agricultural production condition is the basic factor of nongrain production, and it is gradually increased by economic factors, such as the output value of grain per acre and the income gap between urban and rural areas. The spatiotemporal evolution characteristics and influencing factors of nonagricultural and nongrain lands in China from 1980 to 2020 can provide a reference for the scientific implementation of cultivated land protection decisions.

基于综合评价法和敏感度模型，以湖北省为例分析2010—2022年农业绿色发展水平对粮食生产能力变化的敏感度。研究发现：（1）湖北省农业绿色发展呈现“N”型变化特征，其中资源利用和产出水平得分平均值下降，环境保护得分平均值上升。（2）湖北省粮食生产经历了“递增—下降—高产—稳产”阶段，年均产量鄂中>鄂西>鄂东，粮食生产能力与农业绿色发展各维度之间存在不同的响应关系。（3）湖北省农业绿色发展对粮食生产能力变化的敏感性总体上先降后升，其中资源利用对粮食生产能力变化的敏感性持续下降，环境保护对粮食生产能力变化的敏感性持续上升，产出水平对粮食生产能力变化的敏感性先降后升，敏感区数量存在波动且具有明显的空间差异。应进一步提高农业资源利用效率，增强农业绿色发展保障粮食安全的能力，优化农业发展格局。

Based on the comprehensive evaluation method and sensitivity model, the sensitivity of green agricultural development level to the change of grain production capacity from 2010 to 2022 was analyzed with Hubei province as an example. The findings are as follows: (1) The green agricultural development in Hubei presented an "N-shaped" change pattern, that is, the average score of resource utilization and output level decreased and the average score of environmental protection increased. (2) The grain production in the province experienced the stage of "increasing-decreasing-high yield-stable yield", and the average annual output was Central Hubei>Western Hubei>Eastern Hubei. There were different response relationships between grain production capacity and various dimensions of green agricultural development. (3) On the whole, the sensitivity of green agricultural development in the province to the change of grain production capacity decreased first and then increased, the sensitivity of resource utilization to the change of grain production capacity continued to decrease, the sensitivity of environmental protection to the change of grain production capacity continued to increase, the sensitivity of output level to the change of grain production capacity decreased first and then increased, and the number of sensitive areas fluctuated with obvious spatial differences. We should further improve the utilization efficiency of agricultural resources, enhance the capacity of green agricultural development to ensure food security, and optimize the agricultural development pattern.

耕地占补平衡已由管控非农建设占用耕地的“小占补”转变为管控各类占用耕地的“大占补”。面向耕地保护的新形势，科学合理细化耕地占补平衡思路与方法，基于耕地用途管制探讨耕地保护思路，对保障国家粮食安全和耕地资源可持续利用具有重要意义。本文基于“大占补”视角下耕地用途管制的系统解析，构建了“自然-耕作-管理-生产”多维导向的耕地利用水平以及“规划-经济-生态-社会”多维限制的补充耕地潜力评估框架，明晰耕地资源利用和补充潜力水平及其空间分异特征，通过耦合数量与适宜性划定基于“大占补”视角下的耕地保护分区。结果表明：① 中国耕地利用水平整体良好，但在空间上呈现不均衡性，其中长江中下游地区和黄淮海平原区表现最优。② 中国补充耕地具备一定潜力规模，但呈现空间差异，补充耕地可在依法依规的要求下优先考虑疏林地、其他林地与中低覆盖度草地。③ 新形势下中国耕地可划分为战略储备区（1,274万hm²）、重点保护区（11,469万hm²）、休养生息区（311万 hm²）、多元发展区（963万hm²），并按照刚性管制与弹性调控的思路分类施策。研究可为科学推进耕地占补平衡制度提供支撑，并为耕地资源可持续利用与国土空间开发保护格局优化提供参考借鉴。

中国耕地非粮化现象日趋严峻，全面把握耕地非粮化演变规律及其形成机制，对于加强耕地保护和粮食安全具有重要意义。目前关于耕地非粮化的内涵和测度方法丰富多样，但测算结果却存在显著差异。论文采用荟萃分析方法对207篇有效文献进行统计分析，揭示了2000—2021年中国耕地非粮化演变特征与驱动机制。研究发现：① 非粮作物面积占比法、复种指数法和秋粮面积法的使用频次较高、范围广泛，在全国、区域及省际尺度上具有可比性，可作为耕地非粮化测度方法的优选。② 研究期内中国耕地非粮化率总体稳定在30.0%左右，并呈小幅度波动下降；九大农业区中，东北平原区、黄淮海平原区和黄土高原区耕地非粮化率低于30.0%且相对稳定，华南区耕地非粮化率高于50.0%且涨幅较大，其他地区处于30.0%~50.0%区间且基本上增长了10.0%~20.0%，北方粮食作物种植制度区的耕地非粮化率和增幅均低于南方地区；从粮食主产区、产销平衡区到主销区的耕地非粮化率和增幅均逐渐提升，省际层面的耕地非粮化呈现集聚式递增和阶段性分化的动态过程。③ 中国耕地非粮化受自然环境、经济发展、社会活动和政策技术等多重因素影响，通过共性和差异性因子的基础性、双向性、推动性和调控性等作用，形成耕地非粮化的本底、催化、增强和阻滞等驱动效应。论文支持和补充了已有研究的观点，为深入开展耕地非粮化影响效应分析提供了数据参考，也为科学推进耕地非粮化治理提出了优化对策。

The non-grain production of cultivated land in China is becoming increasingly severe. A comprehensive understanding of the patterns of change and formation mechanisms of non-grain production of cultivated land is of great significance for enhancing cultivated land protection and ensuring food security. Currently, there are diverse perspectives and methodologies for measuring non-grain production yet the results vary significantly, and comparative and integrated research on various measurement methods remains inadequate. Therefore, this study employed a meta-analysis approach to statistically examine 207 existing research articles, revealing the characteristics of change and driving mechanisms of non-grain production of cultivated land in China from 2000 to 2021. The findings are as follows: 1) The methods of non-grain crop area proportion, multiple cropping index, and autumn grain crop area are frequently used and widely applied, offering comparability at the national, regional, and provincial scales, which can be considered preferred methods for measuring non-grain production of cultivated land. 2) During the study period of this research, the rate of non-grain production of cultivated land in China remained stable at around 30.0% overall, with a slight downward fluctuation. Among the nine major agricultural regions, the Northeast China Plain, the Huang-Huai-Hai Plain, and the Loess Plateau had non-grain production rates below 30.0% that remained relatively stable, the rate of non-grain production of cultivated land in South China was higher than 50.0% and the increase was larger, while in other regions the rates were in the range of 30.0% to 50.0%, with a general increase of 10.0% to 20.0%. The rate and growth of non-grain production of cultivated land were both lower in the northern grain crop planting regions than in the southern regions, which gradually increased in the main grain-producing areas, grain balanced areas, and main grain-marketing areas. At the provincial level, non-grain production exhibited a dynamic process characterized by clustered incremental increases and phased differentiation. 3) Non-grain production of cultivated land in China is influenced by multiple factors, including natural environment, economic development, social activities, policies, and technology. Through the foundational, bidirectional, driving, and regulatory effects of common and differential factors, the driving effects of non-grain production of cultivated land such as background, catalytic, enhancement, and retardation effects are formed. This study supports the viewpoints of many scholars, provides data references for in-depth research on the socioeconomic and natural environmental effects of non-grain production, and proposes optimization strategies for the effective implementation of scientific measures to manage non-grain production of cultivated land.

土地利用方式不断发生变化，对黄河流域的生态环境、社会经济发展均产生深远的影响。明晰黄河中游流域土地利用的动态变化特征，可为实现黄河流域的可持续发展提供科学依据。本研究基于黄河流域中游1995年、2005年、2015年、2023年4期Landsat遥感数据，通过支持向量机（SVM）和最大似然法分类获得示范区土地利用空间分布，利用土地利用变化、转移矩阵等定量指标，分析研究区1995~2023年土地利用变化特征，并通过建立FLUS-Markov模型，预测研究区2025年、2030年的土地利用变化。针对6类（森林、草原、湿地、耕地、建设用地和未利用地）土地利用变化，结果显示：①在过去近30年，耕地和林地分别减少8 600 km²、6 400 km²，建设用地面积增加7 500 km²；②土地利用类型的转移方向多样，主要为耕地向建设用地、植被方向转变，各地类景观在空间分布上趋于均衡，城市协调发展；③在1995年至2023年期间，森林、草原和建设用地的数量呈上升趋势，而湿地、耕地和未利用土地的数量呈下降趋势；④未来10年间，黄河中游土地利用变化明显，因为人类需要更多的土地进行建设。

非农化和非粮化造成大量耕地不再用于农业用途和粮食生产，严重影响粮食综合生产能力，威胁国家粮食安全。识别非农化和非粮化时空演化特征及不同阶段的驱动因素是科学管控和决策的基础。本文以县域为基本研究单元，评估了非农化和非粮化动态演变特征，选择耕地资源本底、社会经济及农户主观因素构建综合指标体系，采用地理探测器模型量化了不同阶段的驱动因子。分析发现，中国耕地非农化和非粮化具有明显的空间集聚效应，“胡焕庸线”以东非农化程度较高，非粮化现象呈现由东北向西南加剧的空间格局。1980—2020年非农化程度呈现减弱且范围缩小的趋势，而非粮化经历了“增长—平稳”的变化过程。1980—2020年主产区非粮化进程减缓，而2010—2020年主销区非粮化增长速度分别为主产区和产销平衡区的1.49倍和1.33倍。与1980—2000年相比，2010—2020年主产区的非农化速度下降了77%，而产销平衡区非农化的增加速度分别是主销区和主产区的1.63倍和4.65倍。耕地资源禀赋是导致非粮化的基础原因，且土壤质量、地形因子与社会经济存在显著的交互作用，农民的逐利行为是决定耕地非粮化根本原因。农业劳动力为非农化的显著影响因子，城镇化对非农化的解释力2010—2020年有所提升。本文提出分类设定管制规则和补贴机制、分区推进管控政策、加强动态监测与风险预警、加强责任监督与考核的建议。

The land conversion processes concerning non-agricultural and non-grain production areas have prominently decreased arable land availability, which substantially impacted grain production capacity and threatened national food security. Thus, it is critical to establish a novel scientific approach to identify spatio-temporal evolution patterns of land conversion and its influencing factors in different stages. This study evaluates the evolutionary characteristics of non-agricultural and non-grain fields by constructing a comprehensive index system that considers factors like cultivated land resources, social and economic conditions, and farmers' subjective perspectives, using a county as the basic research unit. For a comprehensive analysis, a geographical detector model was utilized to quantify driving factors in different stages. The results indicated spatial clustering effects for non-agricultural and non-grain fields throughout China, particularly in the eastern region beyond the "Hu Huanyong Line". Further analysis revealed a spatial pattern for non-grain conversion phenomenon was more intense in the southwestern than the northeastern fields. Over the past four decades, non-agricultural fields recorded an area expansion, but the year-wise area increase was gradually reduced, while non-grain areas exhibited a "growth-stable" change pattern. Although progress in non-grain was less in primary producing areas over the last 40 years, an increase of 1.49 times and 1.33 times was recorded from 2010 to 2020 in PSB (production and sales balance area) and Mrt (marketing) areas, respectively. Compared to the period 1980-2000, the rate of non-agricultural conversion in primary producing areas decreased by 77% during 2010-2020, while the rate of non-agricultural conversion increased by 1.63 and 4.65 times for PSB and Mrt regions, respectively. Based on these findings, this paper puts forward suggestions, such as setting control rules and subsidy mechanisms according to area classification, promoting control policies based on regional considerations, strengthening dynamic monitoring and risk warning, as well as enhancing supervision and assessment.

研究选择地下水埋深作为评估荒漠河岸林水资源承载力风险的核心指标，以胡杨（Populus euphratica）、柽柳（Tamarix karelinii）为研究对象，采用随机森林算法建立了2020年地下水埋深与气温、降水之间的关系，并预测了未来不同气候情景下额济纳绿洲荒漠河岸林的水资源承载力风险。研究结果显示：①额济纳绿洲荒漠河岸林整体地下水埋深范围为1.12~9.18 m，平均值为2.82 m。2020年，胡杨和柽柳的分布总面积分别为326.04 km²和3567.94 km²。胡杨分布区有77.02%的区域水资源承载力处于超载状态，柽柳分布区有21.00%的区域水资源承载力处于超载状态。②在SSP1-1.9和SSP5-8.5气候情景下，2025—2050年胡杨分布区的平均地下水埋深预计将分别增加0.31 m和0.49 m，柽柳分布区的平均地下水埋深预计将分别增加0.47 m和0.63 m；而在SSP2-4.5气候情景下，胡杨分布区和柽柳分布区的平均地下水埋深将减少0.43 m。3种未来气候情景下，预计2025—2050年荒漠河岸林胡杨和柽柳分布区地下水埋深将整体上呈现增长趋势，这些空间分布变化在额济纳河上游狼心山附近和下游额济纳旗达来呼布镇附近表现较为显著。研究结论指出，未来气候变化将加剧额济纳绿洲荒漠河岸林水资源承载力风险，对其生态系统产生显著的影响。因此，为了实现荒漠河岸林生态系统的可持续发展，必须加强区域水资源的有效管理和合理配置。同时，水资源管理应平衡生态保护与经济发展，推动高效利用。这些措施有助于提升荒漠河岸林生态系统的健康稳定，保障区域环境可持续发展。

多情景模拟土地利用变化是未来土地利用规划的基本依据,对实现区域社会—经济—生态和谐稳定具有重要意义。基于南川区2000年、2010年和2020年土地利用数据,借助动态度、转移矩阵分析研究区2000—2020年近20 a土地利用时空特征,从社会经济、地理环境和交通路网3个方面选取15个驱动因子,设置经济发展、生态保护和耕地保护3种情景,利用PLUS模型模拟研究区2030年土地利用分布,对比分析各情景模拟差异。结果表明:①近20 a,研究区耕地减少明显,达63.56 km²;建设用地增幅显著,占比从0.3%增至2.8%,主要集中在研究区中部和西南部。②2020年模拟结果的Kappa系数和总体精度分别为0.938、0.957,均高于标准值,PLUS模型适用于研究区土地利用模拟。③综合比较不同情景模拟结果发现,耕地保护情景下耕地总量得以保障,同时生态用地得到保护、建设用地大幅蔓延受到一定限制,该模拟结果更符合研究区今后可持续发展,可为南川区合理规划土地资源以及打造高品质新城区提供参考。

On the basis of remotely sensed land use data in 1980,1995 and 2000, we quantitatively analyzed the characteristics of the spatio-temporal distribution of land use/cover changes (LUCC) in the Jialingjiang River Basin by using GIS technical platform and establishing index model. Furthermore, we analyzed the driving forces of the LUCC in detail. Results show that farmland, forest and grassland were major land covers in the studied area, and the conversion among the three was the major pattern of land use change. During the period from 1980 to 2000, farmland and forest decreased initially and increased afterwards; grassland increased initially and then decreased; land for construction showed an ever-increasing trend; other land use types were in small change. The analysis showed that natural factor, economy, population, macro-policy and large-scale projects were the main driving forces of LUCC in the studied area. All the factors restricted each other and then affected the land use patterns.

干旱是影响新疆地区生态环境和农业生产的重要因素，及时开展干旱监测对于新疆地区保证粮食安全具有指导意义。本文基于2001—2020年间MODIS数据的地表温度（LST）和归一化植被指数（NDVI）构建温度植被干旱指数（TVDI），探索新疆地区干旱分布特征及未来演变趋势。结果表明：（1） 新疆地区年均有78.7%的区域在遭受不同程度的干旱，近20 a TVDI均值为0.58，整体处于轻旱水平。（2） 新疆地区未来干旱情况有所缓解，TVDI下降速率为每年0.0017，81%的地区有逐渐湿润的趋势。（3） TVDI与气象因子呈现弱相关，与海拔呈现强相关关系。干旱程度较高时，未利用地对TVDI的贡献率较大；干旱程度较低时，草地对TVDI的贡献率较大。未利用地面积和干旱呈现正相关关系，林地和草地面积与干旱呈现负相关关系，减少未利用地面积、增加林地和草地覆盖对缓解干旱具有积极意义。

Drought is a significant factor affecting the ecological stability and agricultural productivity of Xinjiang. Timely drought monitoring is crucial for ensuring food security in the region. This study constructed the TVDI based on the Land Surface Temperature and the Normalized Difference Vegetation Index derived from the MODIS data between 2001 and 2020. This study explores the spatial distribution characteristics of drought in Xinjiang and its potential future evolution trends. The results indicate that: (1) On average, 78.7% of the region experiences drought of varying degrees, with a mean TVDI of 0.58 over the past two decades, suggesting a generally mild drought. (2) Future drought conditions in Xinjiang are expected to ease, with a TVDI decline rate of 0.0017 per year, and 81% of the region showing a trend toward increasing moisture levels. (3) TVDI correlates weakly with meteorological factors but strongly with elevation. When the degree of drought is relatively high, unused land contributes significantly to the TVDI, whereas grassland contributes significantly to the TVDI when the degree of drought is relatively low. Additionally, the unused land area correlates positively with drought, whereas forest and grassland areas correlate negatively with drought. These findings highlight the importance of reducing unused land and expanding forest and grassland areas to mitigate drought conditions.