厘清气候变化和人类活动对植被净初级生产力（NPP）的影响，对区域生态系统变化与可持续发展具有重要意义。基于CASA模型，利用1994—2018年5期Landsat遥感影像及气象数据，通过仿真情景实验研究了人类活动和气候变化对哈萨克斯坦首都圈植被净生产力的影响。结果表明：（1） 1994—2018年间，哈萨克斯坦首都圈植被NPP呈波动上升趋势，NPP多年均值为226.21 g C·m^-2·a^-1；（2） 首都圈人工造林面积不断增加，对NPP有显著的正增益效果（0.38 Tg C·a^-1, P-1</sup>, P=0.34）；在土地覆盖变化和气候变化共同作用下，哈萨克斯坦首都圈植被NPP总体上呈显著正增益效果（0.27 Tg C·a^-1, P-2</sup>·a^-1、201.19 g C·m^-2·a^-1降到189.00 g C·m^-2·a^-1、188.48 g C·m^-2·a^-1；2000—2006年和2012—2018年期间随着降水条件的改善，该地区NPP均值显著上升，均值分别达到201.19 g C·m^-2·a^-1、207.73 g C·m^-2·a^-1。本文研究结果有助于揭示气候变化和人类活动对植被NPP的影响机制，可为改善荒漠草原区生态环境质量，缓解全球变暖问题和实现哈萨克斯坦2060年碳中和目标提供参考。

为定量区分退耕还林还草背景下北方典型农牧交错带植被变化过程中气候变化和人类活动的相对贡献率,以宁夏盐池县2000&#x02014;2020年植被变化为研究对象,基于MODIS13Q1-NDVI数据、地表覆盖数据和气象数据,采用Thornthwaite纪念模型和CASA（Carnegie-ames-stanford approach）模型分别估算了逐年的潜在净初级生产力（Potential net primary productivity, PNPP）和实际净初级生产力（Actual net primary productivity, ANPP）。综合运用趋势分析、相关分析和差值比较法分析了2000&#x02014;2020年盐池县净初级生产力（Net primary productivity, NPP）时空变化特征及其驱动力,并定量确定了气候因子和人类活动对盐池县植被变化的相对贡献率。结果表明：（1） 在2000&#x02014;2020年盐池县NPP总体呈上升趋势,但存在着显著的空间异质性,主要表现为植被NPP改善区面积远大于NPP退化区面积,且改善或退化程度也存在显著的空间分异。植被改善区主要分布于荒漠、荒漠草原等退耕还林还草工程区域和灌溉区,而植被退化区则分布于荒漠和荒漠草原的边缘地带。（2） 植被变化归因分析表明,在植被改善区,气候变化和人类活动共同主导驱动了植被的改善,但气候变化的相对贡献率（59.77%）大于人类活动的相对贡献率（40.23%）,而在植被退化区,人类活动的相对贡献率（91.77%）则显著高于气候变化的相对贡献率（8.23%）。（3） 驱动力分析表明,研究区植被NPP变化与降水量呈显著正相关,而与气温的相关性较弱;而人类活动是驱动植被退化区NPP下降的主要原因,但负向影响力有所减弱。总体而言,气候变化是植被改善区的主要驱动力,而人类活动是植被退化区的主要驱动因素,两者共同作用则使盐池县整体生态环境得以改善。

This study aims to quantitatively differentiate the relative contribution rate of climate change and human activities during the vegetation cover change in the typical agricultural pastoral ecotone of Northern China under the background of the “grain to green project”. Taking vegetation change from 2000 to 2020 in the Yanchi County, Ningxia Province as the study object and using MODIS13Q1-NDVI, land cover data, and meteorological data from 2000 to 2020, the annual potential net primary productivity and actual net primary productivity were simulated using the models of Thornthwaite Memorial and Carnegie Ames Stanford Approach. The spatial and temporal change characteristics of the net primary productivity (NPP) in the Yanchi County and its driving force were analyzed, and the relative contribution rates of meteorological factors and human activities in the process of vegetation cover change were quantitatively calculated using trend analysis, correlation analysis, and difference comparison. The results showed the following: (1) The NPP totally presented an increasing trend, but there was an obvious spatial heterogeneity in the NPP change trend and degree, mainly manifested when the vegetation NPPs of the improved areas were far greater than the those of the degraded areas, and the extents of improvement and degradation showed significant spatial heterogeneity. The vegetation-improved areas were mainly distributed in the desert and desert steppe (where the “grain to green project” was conducted) and in irrigated areas, whereas the vegetation-degraded areas were mainly distributed in the edge zones of the desert and desert steppe. (2) The vegetation change attribution analysis results indicated that in the vegetation-improved areas, the relative contribution rate of climate change (59.77%) was higher than that of human activities (40.23%). Meanwhile, in the vegetation-degraded areas, the relative contribution rate of human activities (91.77%) was higher than that of climate change (8.23%). (3) The driving force analysis results indicated that the vegetation NPP was positively correlated with precipitation but weakly correlated with temperature. Human activities were the main driving force that drove the NPP decrease in the vegetation-degraded areas. In summary, climate change was the main driving force that drove the NPP improvement in the vegetation-improved areas, whereas human activities were the main driving factors that led to the NPP decrease in the vegetation-degraded areas. Climate and human activities jointly dominated the improvement of the total ecological environment in the Yanchi County.

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。

It is important to study the contributions of climate change and human activities to spatial-temporal changes of cropland in the fields of climate change and land use change. Relationships between spatial-temporal cropland changes and driving forces were studied at qualitative aspects in most of the previous researches. However, the quantitative assessments of the contributions of climate change and human activities to spatial-temporal changes of cropland need to be explored for a better understanding of the dynamics of land use changes. We systematically reviewed the methods of identifying contributions of climate change and human activities to temporal-spatial cropland changes at quantitative aspects, e.g. model analysis, mathematical statistical method, framework analysis, index assessment and difference comparison. The progresses of the previous researches on quantitative evaluation of the contributions were introduced. However, there were four defects in assessing the contributions of climate change and human activities to spatial-temporal cropland changes. For example, the methods were lack of comprehensiveness, and the data need to be more accurate and abundant. Moreover, the scale was single and the explanations were biased. Meanwhile, we concluded a clue about quantitative approaches to assess the contributions from the synthetical aspect to specific driving forces. Besides, the solutions of the future researches on data, scale and explanation were proposed.

Climate change and human activities are two key factors that affect grassland ecosystem. Accurately estimating the effects of these two factors on grassland dynamics and understanding the driving forces of the dynamics are important in controlling grassland degradation. In this study, the potential Net Primary productivity (NPPP) and the difference between NPPP and actual NPP (NPPA) are used as indicators of climate change and human activities on grassland ecosystem in Xinjiang. An overall grassland NPPA increase than decrease (69.7% vs 30.3%) is found over the study period of 2000 to 2014. While human activities played a dominant role for such a NPPA increase, both human activities and climate change contributed almost equally to the grassland NPPA decrease. Within the three types of grasslands in Xinjiang, the desert grassland showed the greatest NPPA increasing trend that mostly attributed to human activities; the meadow showed an overall NPPA decreasing trend that was mainly caused by human activities; the steppe showed similar NPPA decreasing and increasing trend in terms of area percentage. Based on this study, our recommendations are (1) to continue the grazing prohibition policy in desert grassland and (2) to extensively implement the rest grazing policy in steppe and meadow grasslands.

定量评估气候变化和人类活动对陆地生态系统碳循环的影响,对于深入理解植被变化驱动机制和生态建设与保护具有重要意义。基于2000&#x02014;2019年生态过程模型BIOME-BGC计算的实际净初级生产力和气候模型计算的潜在净初级生产力,定量分析气候变化和人类活动对陕西植被生态系统的影响。结果表明,2000&#x02014;2019年间,陕西省植被NPP的变化主要由气候驱动的区域占总面积的11.96%;叠加上人类活动影响,且后者作用更强的区域占比为86.93%。陕西省的植被NPP增加的区域占总面积的98.06%,其中有11.93%的区域是由气候因素驱动,主要分布在关中地区和汉中盆地的农作区;86.13%是由人类活动驱动,主要分布在陕北、陕南地区,说明了这两个地区退耕还林、天然林保护等生态建设工程取得了显著成效。减少的区域占总面积的0.83%,其中有0.03%的区域是由气候因素驱动,零星分布在全省各地;而0.8%的区域是由人类活动,尤其是城镇建设所致,分布在城镇周边区域。还有1.11%的面积NPP没有发生变化。陕西省植被NPP的变化受到气候和人类活动两种驱动力的作用,而主要驱动力是人类活动。

以人类活动为主导的城市扩张和土地覆被变化对城市生态环境产生了重要影响,并与气候变化共同影响植被净初级生产力(NPP),但目前从时空尺度上脱离气候干扰仅以人类活动为主导因素来定量分析其对植被NPP影响的研究尚不充分.本研究以广州市为研究区,利用CASA模型估算2001—2013年实际净初级生产力(NPP_act),结合CHIKUGO模型估算得到的潜在净初级生产力(NPP_p)计算因土地覆被变化导致的NPP损失(NPP_lulc),并建立相对贡献指数(RCI)定量分析和评价在城市扩张过程中人类活动对NPP的影响.结果表明:2001—2013年间,广州总体及其5片区NPP_act和NPP_lulc分别呈减少和增加趋势,并存在明显的空间差异性;RCI呈明显增加趋势,东北片区RCI值最低,为0.31,表明气候变化是其NPP变化的主要原因,其他4个片区的RCI值均高于0.5,说明4个片区人为干扰严重,人类活动是其NPP减少的主导因素;广州市及其5片区的RCI变化斜率均大于0,人类活动对植被的干扰逐年增强,北部片区RCI变化斜率值最大(0.693),人为干扰增加趋势最明显.

Urban expansion and land cover changes driven primarily by human activities have significant influences on urban eco-environment, and together with climatic change jointly affect net primary productivity (NPP). However, quantitative analysis about the impacts of human activities on NPP change isolated from climatic change in the spatiotemporal scale is poorly understood. We took Guangzhou City as study area to estimate the actual NPP (NPP_act) and the potential NPP (NPP_p) from 2001 to 2013 based on Carnegie Ames Stanford Approach (CASA) model and CHIKUGO model, and calculated the loss of NPP due to land use and land cover change (NPP_lulc) from NPP_act and NPP_p. The impact of human activities on NPP in the process of urban sprawl was quantitatively analyzed and assessed by examining a relative contribution index (RCI) based on NPP_p and NPP_lulc. Guangzhou City and its five regions showed a declined trend of NPP_act and an increased trend of NPP_lulc from 2001 to 2013, and significant spatial differences of NPP_act and NPP_lulc were found in all regions. RCI had an increasing trend over 13 years, the smallest value of average RCI occurred in northeastern region (0.31), indicating climatic change was the main cause of NPP change, while the average RCI was higher than 0.5 in the other four regions, indicating that these regions were subjected to severe anthropogenic disturbances and human activities were the dominant factors of NPP reduction. The slopes of RCI change were positive in Guangzhou and its five regions, revealing an increasing human disturbance trend. Northern region had the largest RCI slope of 0.693, suggesting the trend was most obviously in this region.

该文在综合分析已有光能利用率模型的基础上，构建了一个净初级生产力(NPP)遥感估算模型，该模型体现了3方面的特色：1)将植被覆盖分类引入模型，并考虑植被覆盖分类精度对 NPP 估算的影响，由它们共同决定不同植被覆盖类型的归一化植被指数(NDVI)最大值；2)根据误差最小的原则，利用中国的NPP实测数据，模拟出各植被类型的最大光能利用率，使之更符合中国的实际情况；3)根据区域蒸散模型来模拟水分胁迫因子，与土壤水分子模型相比，这在一定程度上对有关参数实行了简化，使其实际的可操作性得到加强。模拟结果表明，1989～1993年中国陆地植被NPP平均值为3.12 Pg C (1 Pg=10¹⁵ g)，NPP模拟值与观测值比较接近，690个实测点的平均相对误差为4.5%；进一步与其它模型模拟结果以及前人研究结果的比较表明，该文所构建的NPP遥感估算模型具有一定的可靠性，说明在区域及全球尺度上，利用地 理信息系统技术将遥感数据和各种观测数据集成在一起，并对NPP模型进行参数校正， 基本上可以实现全球范围不同生态系统NPP的动态监测。