Evaluating the performance of multiple remote sensing indices to predict the spatial variability of ecosystem structure and functioning in Patagonian steppes

Assessing the spatial variability of ecosystem structure and functioning is an important step towards developing monitoring systems to detect changes in ecosystem attributes that could be linked to desertification processes in drylands. Methods based on ground-collected soil and plant indicators are being increasingly used for this aim, but they have limitations regarding the extent of the area that can be measured using them. Approaches based on remote sensing data can successfully assess large areas, but it is largely unknown how the different indices that can be derived from such data relate to ground-based indicators of ecosystem health. We tested whether we can predict ecosystem structure and functioning, as measured with a field methodology based on indicators of ecosystem functioning (the landscape function analysis, LFA), over a large area using spectral vegetation indices (VIs), and evaluated which VIs are the best predictors of these ecosystem attributes. For doing this, we assessed the relationship between vegetation attributes (cover and species richness), LFA indices (stability, infiltration and nutrient cycling) and nine VIs obtained from satellite images of the MODIS sensor in 194 sites located across the Patagonian steppe. We found that NDVI was the VI best predictor of ecosystem attributes. This VI showed a significant positive linear relationship with both vegetation basal cover (R² = 0.39) and plant species richness (R² = 0.31). NDVI was also significantly and linearly related to the infiltration and nutrient cycling indices (R² = 0.36 and 0.49, respectively), but the relationship with the stability index was weak (R² = 0.13). Our results indicate that VIs obtained from MODIS, and NDVI in particular, are a suitable tool for estimate the spatial variability of functional and structural ecosystem attributes in the Patagonian steppe at the regional scale.     

Multi-scale evaluation of soil functional indicators for the assessment of water and soil retention in Mediterranean semiarid landscapes

Ecosystem monitoring and assessment are often based on functional indicators, which provide integrated and yet simple and affordable measures of key ecosystem functions. The landscape function analysis (LFA) assesses ecosystem functioning through three indices that represent basic soil functions: surface stability, infiltration, and nutrient cycling. Given the high scale-dependency of hydrological and erosion processes in semiarid ecosystems, the validation of the stability and infiltration indices requires a multi-scale approach, which has not been applied by previous works. Using records from a four-year monitoring of a semiarid landscape in SE Spain, we evaluated the LFA infiltration and stability indices against quantitative measurements of water and sediment flows at multiple scales. At the finest scale, the indices correctly reflected the higher infiltration and lower sediment production of plant patches as compared with bare-soil interpatches. The infiltration index also captured the spatial variation in the infiltration capacity of bare-soil interpatches. At the hillslope scale, total runoff was inversely related to the average infiltration index for bare-soil interpatches, but it was not related to the global infiltration index, which combines the values from both bare-soil interpatches and plant patches. These results suggest that the hydrological response of semiarid hillslopes depends mainly on the variation in the functioning of bare-soil interpatches. Total sediment yield from the hillslope plots was not related to the stability index. At the catchment scale, both the bare-soil interpatch and the global infiltration indices correctly captured the variability in total runoff produced by three micro-catchments of comparable size. The bare-soil infiltration index predicted bare-soil infiltration rate and hillslope runoff better than common simple indicators of soil functioning such as soil organic carbon, stone cover, crusted bare-soil cover, bulk-density and plant cover, and exhibited a similarly high indicatory potential that a variety of plant spatial-pattern indicators. In contrast to the multi-scale validation of the infiltration index, the indicatory potential of the stability index was only proved for the most contrasting soil conditions in the study site, pointing to a lower sensitivity of this latter index.     

Protected areas buffer the Brazilian semi‐arid biome from climate change

The Caatinga is a botanically unique semi‐arid ecosystem in northeast Brazil whose vegetation is adapted to the periodic droughts that characterize this region. However, recent extreme droughts events caused by anthropogenic climate change have challenged its ecological resilience. Here, we evaluate how deforestation and protection status affect the response of the Caatinga vegetation to drought. Specifically, we compared vegetation responses to drought in natural and deforested areas as well as inside and outside protected areas, using a time‐series of satellite‐derived Normalized Difference Vegetation Index (NDVI) and climatic data for 2008–2013. We observed a strong effect of deforestation and land protection on overall vegetation productivity and in productivity dynamics in response to precipitation. Overall, deforested areas had significantly lower NDVI and delayed greening in response to precipitation. By contrast, strictly protected areas had higher productivity and considerable resilience to low levels of precipitation, when compared to sustainable use or unprotected areas. These results highlight the importance of protected areas in protecting ecosystem processes and native vegetation in the Caatinga against the negative effects of climate change and deforestation. Given the extremely small area of the Caatinga currently under strict protection, the creation of new conservation areas must be a priority to ensure the sustainability of ecological processes and to avoid further desertification.     

喀斯特石漠化区生态保护红线划定——以贵州省威宁县为例

科学划定喀斯特石漠化区生态保护红线,对于维护区域生态安全,促进经济社会可持续发展具有重要意义。选择水源涵养、水土保持、生物多样性维护3种生态系统服务功能以及水土流失、石漠化2种生态环境敏感性指标,构建喀斯特石漠化区生态保护红线划定方法。以贵州省威宁县为例,结合第二次全国土地调查数据和相关规划等数据,划定生态保护红线,并从生态用地、植被覆盖度与人类扰动指数三个方面评价划定效果。结果表明：（1）威宁县生态系统综合服务功能以极重要为主,占研究区总面积的40.57%。生态环境综合敏感性以敏感为主,占总面积的67.86%。优化调整后生态保护红线面积1496.13 km²,占全县面积的23.75%,红线内生态用地面积占比高于非生态用地面积占比20%以上。（2）近些年贵州省退耕还林、岩溶地区石漠化综合治理和草海自然保护区生态修复等工程的实施,威宁县植被覆盖显著增加,红线内NDVI基本不变区、轻微改善区和明显改善区面积占比达到88.42%,红线范围内植被覆盖呈增加趋势。（3）红线内人类扰动指数低于红线外人类扰动指数,雪山镇、麻乍镇需控制红线范围内人类扰动,确保生态用地性质不改变,加强生态保护和监管。威宁县生态保护红线划定研究可为其他石漠化地区红线划定及划定效果评价提供参考。     

Regional scale relationships between ecosystem structure and functioning: the case of the Patagonian steppes

Aims 1. To characterize ecosystem functioning by focusing on above‐ground net primary production (ANPP), and 2. to relate the spatial heterogeneity of both functional and structural attributes of vegetation to environmental factors and landscape structure. We discuss the relationship between vegetation structure and functioning found in Patagonia in terms of the capabilities of remote sensing techniques to monitor and assess desertification. Location Western portion of the Patagonian steppes in Argentina (39°30′ S to 45°27′ S). Methods We used remotely‐sensed data from Landsat TM and AVHRR/NOAA sensors to characterize vegetation structure (physiognomic units) and ecosystem functioning (ANPP and its seasonal and interannual variation). We combined the satellite information with floristic relevés and field estimates of ANPP. We built an empirical relationship between the Landsat TM‐derived normalized difference vegetation index (NDVI) and field ANPP. Using stepwise regressions we explored the relationship between ANPP and both environmental variables (precipitation and temperature surrogates) and structural attributes of the landscape (proportion and diversity of different physiognomic classes (PCs)). Results PCs were quite heterogeneous in floristic terms, probably reflecting degradation processes. Regional estimates of ANPP showed differences of one order of magnitude among physiognomic classes. Fifty percent of the spatial variance in ANPP was accounted for by longitude, reflecting the dependency of ANPP on precipitation. The proportion of prairies and semideserts, latitude and, to a lesser extent, the number of PCs within an 8 × 8 km cell accounted for an additional 33% of the ANPP variability. ANPP spatial heterogeneity (calculated from Landsat TM data) within an 8 × 8 km cell was positively associated with the mean AVHRR/NOAA NDVI and with the diversity of physiognomic classes. Main conclusions Our results suggest that the spatial and temporal patterns of ecosystem functioning described from ANPP result not only from water availability and thermal conditions but also from landscape structure (proportion and diversity of different PCs). The structural classification performed using remotely‐sensed data captured the spatial variability in physiognomy. Such capability will allow the use of spectral classifications to monitor desertification.     

半干旱区生态恢复关键生态系统识别——以内蒙古自治区和林县为例

我国土地退化严重,且大部分发生在干旱半干旱地区.恢复为何种生态系统类型是生态学研究的重要课题.采用生态功能区划,根据各个生态功能区主体生态系统功能,推导发挥此功能的生态系统类型的方法,识别关键生态系统类型.以内蒙古自治区和林县为例,采用文献调研、实地调查、3S技术等方法,在评价该县生态敏感性、生态服务功能重要性的基础上,将该县划分为3个一级生态区,11个二级生态功能区.根据各个生态功能区的主体生态系统服务功能,分析发挥该功能的可能生态系统类型.再根据全国自然植被区划、气候变化趋势模型以及现状植被类型,识别各个生态功能区的关键生态系统类型.     

生物土壤结皮在喀斯特生态治理中的应用潜力

喀斯特地区生境条件复杂,生态系统脆弱,其中石漠化成为制约喀斯特地区发展的重要因素。该文综述了生态系统中生物土壤结皮的可抗逆性特征及其对加速母岩成土速率、提高地表抗侵蚀力、改善土壤环境状态,调控降水下渗、改变土壤中水分再分配格局、促进土壤微生物和植被演替以及提高生物多样性的关键作用。探讨了生物土壤结皮与喀斯特生态系统的反馈机制及人工培育结皮植被对石漠化防治的应用潜力。此外,生物土壤结皮与生态系统间的互作机制是研究喀斯特生态治理的关键,两者间的耦合关系是一个动态过程,需要长期的不间断多维度监测。建议加强对生物土壤结皮与喀斯特生境间耦合机制及其在喀斯特岩溶过程的互作机制,喀斯特地区生物土壤结皮耐胁迫特性以及在喀斯特生境下人工培植技术与机理等方面的研究。     

植被指数的地形效应研究进展

植被指数是定性、定量评估绿色植被的关键指标,已经广泛应用于地表植被的监测.森林多分布在地形复杂山区,利用植被指数进行森林植被信息反演时地形对其影响较大.本文从几何光学模型原理分析了冠层反射率的地形效应,分析比较完全比值型植被指数(简单比值植被指数SR、归一化植被指数NDVI和湿度调整植被指数MAVI)、非完全比值型植被指数(增强型植被指数EVI和土壤调整植被指数SAVI)、非比值型植被指数(减化比值植被指数RSR、修正归一化植被指数MNDVI和绿度植被指数GVI),以及地形调节植被指数TAVI对地形的响应,试图为复杂地形山区选取植被指数提供参考.最后分析了植被指数地形效应研究的不足并对未来发展进行展望.     

Estimation of forest-ecosystem site index using remote-sensed data

The estimation of site index and site quality forms the fundamental theory and basic tools in forest-ecosystem management and silviculture practice. The study on the spatial pattern and temporal dynamics of site index and site quality of forest ecosystem still lacks technological advancement. It is a novel approach for estimating forest productivity in large areas using satellite remote-sensed data. The site-index spatial distribution pattern of spruce (Picea asperata) forest in Songpan-Zhengjiangguan watershed, northwestern Sichuan Province, China, was described using the remote-sensing vegetation index application and the established inverse models. The application potential of the methodology in broad regions and forests using the accuracy assessment was evaluated. The results show that the site index of the spruce forest is in linear correlation with the remote-sensed vegetation indices (normalized difference vegetation index (NDVI) and soil adjust NDVI (TNDVI)), as well as with these inverse models with high accuracy. This study demonstrated that this approach can be used in similar estimation of different forest ecosystems.     

Estimation of forest-ecosystem site index using remote-sensed data

The estimation of site index and site quality forms the fundamental theory and basic tools in forest-ecosystem management and silviculture practice. The study on the spatial pattern and temporal dynamics of site index and site quality of forest ecosystem still lacks technological advancement. It is a novel approach for estimating forest productivity in large areas using satellite remote-sensed data. The site-index spatial distribution pattern of spruce (Picea asperata) forest in Songpan-Zhengjiangguan watershed, northwestern Sichuan Province, China, was described using the remote-sensing vegetation index application and the established inverse models. The application potential of the methodology in broad regions and forests using the accuracy assessment was evaluated. The results show that the site index of the spruce forest is in linear correlation with the remote-sensed vegetation indices (normalized difference vegetation index (NDVI) and soil adjust NDVI (TNDVI)), as well as with these inverse models with high accuracy. This study demonstrated that this approach can be used in similar estimation of different forest ecosystems.     

Confounding effects of snow cover on remotely sensed vegetation indices of evergreen and deciduous trees: An experimental study

Located at northern latitudes and subject to large seasonal temperature fluctuations, boreal forests are sensitive to the changing climate, with evidence for both increasing and decreasing productivity, depending upon conditions. Optical remote sensing of vegetation indices based on spectral reflectance offers a means of monitoring vegetation photosynthetic activity and provides a powerful tool for observing how boreal forests respond to changing environmental conditions. Reflectance-based remotely sensed optical signals at northern latitude or high-altitude regions are readily confounded by snow coverage, hampering applications of satellite-based vegetation indices in tracking vegetation productivity at large scales. Unraveling the effects of snow can be challenging from satellite data, particularly when validation data are lacking. In this study, we established an experimental system in Alberta, Canada including six boreal tree species, both evergreen and deciduous, to evaluate the confounding effects of snow on three vegetation indices: the normalized difference vegetation index (NDVI), the photochemical reflectance index (PRI), and the chlorophyll/carotenoid index (CCI), all used in tracking vegetation productivity for boreal forests. Our results revealed substantial impacts of snow on canopy reflectance and vegetation indices, expressed as increased albedo, decreased NDVI values and increased PRI and CCI values. These effects varied among species and functional groups (evergreen and deciduous) and different vegetation indices were affected differently, indicating contradictory, confounding effects of snow on these indices. In addition to snow effects, we evaluated the contribution of deciduous trees to vegetation indices in mixed stands of evergreen and deciduous species, which contribute to the observed relationship between greenness-based indices and ecosystem productivity of many evergreen-dominated forests that contain a deciduous component. Our results demonstrate confounding and interacting effects of snow and vegetation type on vegetation indices and illustrate the importance of explicitly considering snow effects in any global-scale photosynthesis monitoring efforts using remotely sensed vegetation indices.     

Threshold values of canopy reflectance indices and chlorophyll meter readings for optimal nitrogen nutrition of tomato

Sustainable and optimal economic N management requires correct and timely on‐farm assessment of crop N status to detect N deficiency or excess. Optical sensors are promising tools to assess crop N status throughout a crop or at critical times. The ability of optical sensor measurements of canopy reflectance (Crop Circle ACS 470) and leaf chlorophyll (SPAD 502 chlorophyll meter) to assess crop N status was evaluated weekly throughout an indeterminate tomato crop. Strong linear relationships with the optical sensor measurements were obtained, throughout most of the crop, for both (a) crop N content for ranges of 1.5–4.5%, and (b) the nitrogen nutrition index (NNI) for ranges of 0.4–1.3. The relationships of the optical sensor measurements to crop NNI were generally equal to or slightly better than with crop N content. Indices based on reflectance in the red, the normalised difference vegetation index (NDVI) and the red vegetation index (RVI), were the best predictors of crop N status in terms of goodness of fit, earliness and maintenance of relationships throughout the crop. SPAD chlorophyll readings and reflectance indices based on reflectance in the green, the normalised difference vegetation index on greenness (GNDVI) and the green vegetation index (GVI), were good indicators of crop N status for most of the crop, but with lower goodness of fit in the latter part of the crop. The linear relationships between sensor indices and readings with NNI or crop N content, each week, demonstrated the potential for using proximal canopy reflectance indices such as NDVI and RVI, and chlorophyll meter for monitoring crop N status of indeterminate tomato crops. Threshold values for optimal crop N nutrition for canopy reflectance indices and for chlorophyll meter readings were derived for each day of measurement from the relationships between optical sensor measurements and NNI by solving for NNI = 1. The threshold values obtained for each index and type of measurement varied during the crop cycle. The approach developed for determining threshold values from NNI can facilitate on‐farm use of optical sensors for monitoring crop N status, by enabling assessment of whether crop N status is excessive, deficient or adequate.     

Do landscape health indices reflect arthropod biodiversity status in the eucalypt woodlands of eastern Australia?

Ecosystem or landscape health indices are important tools for land managers. While strong predictable relationships between these indices and biotic diversity are often generalized, they are seldom validated. Here we use data from a semi‐arid eastern Australian woodland to examine the relationships between arthropod community structure and two sets of landscape health indicators: landscape function analysis (LFA), and a terrestrial index of ecological integrity based on common vegetation metrics (structure, composition and function; SCF). Hierarchical partitioning revealed that the ability of LFA or SCF to account for variation in arthropod richness was low, with the variable of importance taxon‐dependent. Similarly, multivariate analyses indicated relatively weak and inconsistent relationships between LFA and SCF indices and arthropod assemblage structure. Results obtained for additional habitat attributes commonly used in terrestrial vegetation monitoring were similar. Our study indicates that strong predictable relationships are rarely apparent, particularly for arthropods. This indicates that these indices have limited use as surrogates of arthropod biodiversity. These results are contrary to the past literature, highlighting the need for additional research and the development of a conceptual and empirical framework linking health indices and arthropod biodiversity. This is necessary to further the theoretical and practical application of these measurements in environmental management.     

基于地面调查的植被生态质量综合评估指标体系构建

植被是陆地生态系统的主体,是保障生态质量的基础,也是基于自然的生态系统增汇、实现“碳中和”的重要利器。植被是生态质量评价的核心要素,但目前的生态质量评价研究中所用到的植被指标多是通过遥感反演或者气象指数模型计算得到的,而基于典型生态系统尺度地面调查的植被观测数据更直接、更准确,数据也很丰富,却很少用于生态质量评价,也缺乏系统的评价指标体系。通过文献研究、专家研讨和问卷调查,并借鉴群落退化演替和生态系统长期监测研究的理论基础,构建基于地面调查的植被生态质量综合评估指标体系。该指标体系整体分为三级,一级综合指数由群落结构指数、物质生产指数、生物多样性指数、群落发展或者演替趋势4个二级分项指标构成,二级分项指标由12—14个三级指标组成,不同植被类型各有其特征指标。该体系将完善我国多尺度陆地生态系统的生态质量评价指标体系,为新时期国家生态质量评价提供科学建议,为我国生态文明建设提供技术支撑。     

Identification of current ecosystem functional types in the Iberian Peninsula

Aim To examine the geographical patterns of the interception of photosynthetically active radiation by vegetation and to describe its spatial heterogeneity through the definition of ecosystem functional types (EFTs) based on the annual dynamics of the Normalized Difference Vegetation Index (NDVI), a spectral index related to carbon gains. Location The Iberian Peninsula. Methods EFTs were derived from three attributes of the NDVI obtained from NOAA/AVHRR sensors: the annual integral (NDVI‐I), as a surrogate of primary production, an integrative indicator of ecosystem functioning; and the intra‐annual relative range (RREL) and month of maximum NDVI (MMAX), which represent key features of seasonality. Results NDVI‐I decreased south‐eastwards. The highest values were observed in the Eurosiberian Region and in the highest Mediterranean ranges. Low values occurred in inner plains, river basins and in the southeast. The Eurosiberian Region and Mediterranean mountains presented the lowest RREL, while Eurosiberian peaks, river basins, inner‐agricultural plains, wetlands and the southeastern part of Iberia presented the highest. Eurosiberian ecosystems showed a summer maximum of NDVI, as did high mountains, wetlands and irrigated areas in the Mediterranean Region. Mediterranean mountains had autumn–early‐winter maxima, while semi‐arid zones, river basins and continental plains had spring maxima. Based on the behaviour in the functional traits, 49 EFTs were defined. Main conclusions The classification, based on only the NDVI dynamics, represents the spatial heterogeneity in ecosystem functioning by means of the interception of radiation by vegetation in the Iberian Peninsula. The patterns of the NDVI attributes may be used as a reference in evaluating the impacts of environmental changes. Iberia had a high spatial variability: except for biophysically impossible combinations (high NDVI‐I and high seasonality), almost any pattern of seasonal dynamics of radiation interception was represented in the Peninsula. The approach used to define EFTs opens the possibility of monitoring and comparing ecosystem functioning through time.     

荒漠草原沙漠化植物群落及土壤物理变化

沙漠化是草地退化最严重的形式之一。以空间代替时间的方法,通过对宁夏中北部荒漠草原沙漠化过程中植物群落特征和土壤物理特性的研究,探讨草地植物群落与土壤物理特性对沙漠化的响应机制。结果表明:(1)潜在沙漠化阶段草地以牛枝子、猪毛蒿、中亚白草为优势种,轻度沙漠化阶段草地以中亚白草、苦豆子为优势种,中度沙漠化阶段草地以狗尾草、虫实为优势种,重度沙漠化阶段草地以沙米、赖草、狗尾草为优势种,极度沙漠化阶段草地以沙米为优势种。(2)随着沙漠化程度的加剧草地植物群落生物量、Shannon-Wiener指数、丰富度指数、盖度均呈降低趋势,但轻度沙漠化阶段草地植被生物量比潜在沙漠化增加了23%。(3)草地沙漠化导致土壤容重和土壤粗砂粒含量增加,而土壤水分,土壤细砂粒和粘粉粒含量降低。荒漠草原沙漠化导致了土壤环境和植被明显退化,草地生产力明显降低。     

绿洲生态系统生物量与植被指数分析

利用阜康绿洲野外实测的53个样方的植物生物量数据与同期陆地卫星MODIS影像的第1,2通道250 m遥感数据,分析植被指数与绿洲植物生物量的相关关系,建立植被指数与绿洲植物生物量的一元线性和非线性回归模型。结果表明,植被指数NDVI和MSAVI与绿洲生态系统植物生物量之间存在较好的相关性;所建植被指数与植物生物量的回归模型中,三次方程为所得到的回归模型中最适合用于绿洲生态系统植物生物量和生长监测。     

中国喀斯特地区微生物群落结构和功能的研究进展

频繁的人类生产活动使植被遭到破坏,造成基岩裸露的石漠化现象,严重制约了喀斯特地区自然和社会经济的发展,随着生态修复工程的大力开展,微生物群落的结构和功能在生态修复中逐渐受到重视,因为微生物作为喀斯特生态系统的重要组成部分,不仅在物质循环过程中起着重要作用,也在喀斯特生态系统修复中占有十分重要的地位。所以微生物群落结构和功能的研究可以作为衡量生态系统稳定性的重要指标。就中国喀斯特地区的典型植被恢复的不同阶段、成土过程、不同的土地利用方式、矿山修复过程以及不同水域中的微生物群落结构及功能等方面的研究状况进行系统梳理,结合实例综合论述喀斯特地区生态修复过程中微生物作用的研究进展,以期为喀斯特地区生态修复提供参考。     

利用水稻冠层光谱特征诊断土壤氮素营养状况

系统测定了不同秸秆还田和氮肥处理下水稻(Oryza sativa)关键生育期的冠层反射光谱及土壤速效氮含量,并对两者之间的关系进行了详尽的分析。结果表明: 土壤速效氮含量在整个水稻生育期内均与可见光波段反射率呈负相关,与近红外波段反射率呈正相关。归一化及比值植被指数与土壤速效氮含量有更好的相关性,分蘖期要优于其它生育时期,以870、1 220 nm波段与560和710 nm波段的组合最佳,但两者的关系易受土壤等背景的干扰。而转换型土壤调节植被指数TSAVI能较好地消除分蘖期土壤背景的影响,两生态点可用统一的方程来拟合,用该研究中所筛选出的最佳波段组合计算出的TSAVI的表现更好,尤其是870 nm波段和710 nm波段的组合,决定系数(R²)由0.46提高到0.60。抽穗期和灌浆期由1 220和760 nm计算的比值指数R(1 220, 760)和新土壤调节植被指数SAVI(1 220,760)与土壤速效氮含量的关系则不受生态点的影响,可用统一回归方程来拟合。这说明水稻冠层反射光谱可以用来评价稻田土壤肥力状况,但仍需进一步研究。     

近30年中国陆地生态系统NDVI时空变化特征

气候变化已明显影响到陆地植被的活动,但在不同生态系统间存在差异,研究不同陆地生态系统归一化植被指数(NDVI)的时空变化特征,不仅可揭示各生态系统植被活动对气候变化的响应规律,而且可为我国不同生态区制定应对气候变化的策略和生态文明建设提供科学依据。基于1982—2012年GIMMS NDVI3g和中国陆地生态系统类型数据,利用一元线性回归、集合经验模态分解和相关分析等方法,研究了近30年中国各陆地生态系统NDVI的时空变化特征,分析了其与气候事件的关系。结果表明,近30年中国植被活动显著上升,年平均归一化植被指数(ANDVI)的上升幅度为0.0029/10a(P0.05),年最大归一化植被指数(MNDVI)的上升幅度为0.0076/10a(P0.01);植被活动显著增强的区域主要是分布在东部季风区的农田和森林生态系统,显著下降的区域主要是分布于西北的荒漠生态系统和东北的森林生态系统;尽管ANDVI和MNDVI线性趋势的显著性有所差异,但农田、森林、草地和水体与湿地生态系统的NDVI总体呈非稳定的上升趋势,上升过程中伴随着较大波动,荒漠生态系统的NDVI呈下降趋势,植被退化显著;与线性趋势不同,各生态系统植被活动的残差趋势包含"上升—下降"两个阶段,并相继于20世纪90年代到21世纪初发生转折;上述5类生态系统的植被活动存在不同尺度的周期特征,年际周期波动特征(1.9—7.6a)比较显著,而年代际周期(10.7a和22.2a)的显著性相对较差;各生态系统的空间异质性在趋强过程中存在2.1—7.1a的年际周期节律;海洋与大气环流的短周期脉动与各生态系统植被活动的周期性节律有着明显关联,ENSO事件和太阳活动是推动植被活动周期性振荡的重要因素。