Vegetation recovery under global change and its consequent evolution of eco-hydrological processes have modulated the water resources conservative capacity in the source region of the Yellow River (YRSR). Based on climatological data, remotely sensed vegetation index and geographical information, the integrated simulations of water and carbon cycles in the YRSR are presented, with the vegetation interface processes (VIP) distributed eco-hydrological dynamic model. Then the co-evolving mechanisms of hydrological and vegetation dynamics are investigated. Results show that warming and wetting climate in the YRSR has improved the vegetation growing condition and extended the growing period for more than 10 days in recent decades. Averaged NDVI from 2010 to 2020 increased by 4.5% relative to that from 2000 to 2009. Vegetation gross primary productivity (GPP) shows a significant uptrend with a rate of 4.57 gC m-2 a-1, 77% of which is contributed by climate change and elevated atmosphere CO2 fertilization, and the rest 23% is by vegetation greening. Evapotranspiration (ET) is increasing at a rate of 2.54 mm a-1 and vegetation water use efficiency (WUE, expressed as GPP/ET) is also improving at a relative rate of 5.1% a-1. Generally, annual ET, GPP and WUE and their trends are decreasing along the elevation below 4200 m. At basin scale, there are significant positive correlations between the vegetation greenness and the runoff coefficient with precipitation in the current and previous years, demonstrating a legacy effect of precipitation for vegetation recovery on water conservation capacity. The increased ET might be a benefit to the water recycle between land surface and atmosphere, which will alleviate the reduced potential of water yield owing to ecological restoration and establish trades-off and synergies among precipitation, vegetation and water yield. Conclusively, exploring the mechanisms of hydrological responses to climate change and vegetation recovery and its feedback will provide scientific support to the assessment of ecological engineering programs in the source regions.

全球变化下黄河源区水文过程的演变影响流域生态系统的水源涵养功能,流域植被改变也影响水循环。本文基于气候、植被信息和VIP分布式生态水文模型,开展黄河源区水碳循环要素变化的集成模拟,分析了气候—植被—水文要素的协同演变机制。结果表明,2000年以来黄河源区气候呈暖湿化趋势;植被绿度明显提高,2010—2019年比2000—2009年平均增加了4.5%;生长季延长了至少10 d;植被生产力（GPP）显著上升,倾向率为4.57 gC m^-2 a^-1;植被恢复措施对GPP变化的贡献约为23%,气候变化和大气CO₂升高的施肥效应的贡献为77%。源区植被蒸散量（ET）呈增加趋势,倾向率为2.54 mm a^-1,水分利用效率（WUE）亦提高,平均相对上升率为5.1% a^-1。GPP、ET和WUE年总量及其变化率在海拔4200 m以下随高度上升而减小,之后变化趋缓。源区植被绿度和径流系数与当年和前一年降水呈显著正相关,反映降水蓄存于植物根层土壤的遗留效应。蒸散增强在一定程度上有利于源区地表—大气之间的水分再循环,帮助缓解生态恢复引起的产水能力下降,促进降水—植被—径流之间的良性互馈关系的形成。揭示水文对气候变化和植被恢复的响应和互馈机制,可为生态恢复措施对源区水源涵养功能的影响及效应的定量评估提供科学依据。

Evapotranspiration is a key variable and key process in global water cycle, and it is crucial for understanding how anthropogenic and climate changes have impacts on terrestrial water cycle. In the last decade, global vegetation changes are dramatic, reflected by land use and land cover changes and increase in leaf area index. It remains unclear how these changes influence terrestrial evapotranspiration processes. This study uses a coupled evapotranspiration and gross primary product model (PML-V2) that is run at 500 m and 8-day resolutions across the globe to investigate the impacts of vegetation changes on spatial pattern and dynamics of evapotranspiration in the period of 2003-2017. We found that evapotranspiration across the globe has increased noticeably because of vegetation changes, which is characterized by clear regional and non-regional patterns. Transpiration has strongly increased in the central and northern parts of North America, Europe, eastern China, southern Africa, and eastern and northern Australia. Under different land cover types, shrubs and cropland have been influenced strongly, and their impact is stronger in the post-2012 period than that in the pre-2012 period. The recent total increase from these two land cover types amounts to about 0.41 ×103 km3 a-1, which is about 8 times of natural annual runoff from the Yellow River Basin. The results from this study can help improve the understanding of how vegetation changes caused by recent land use and land cover changes influence terrestrial water cycle and the potential local and regional climate change.

蒸散发是陆面水循环的关键环节和过程,是研究水循环对人类活动和气候变化响应的关键要素。过去十几年,全球下垫面的植被变化剧烈,但如何影响全球陆面蒸散发仍未得到清晰的揭示。本文采用500 m分辨率MODIS数据驱动PML-V2模型,定量解析了2003—2017年植被变化对全球陆面蒸散发的影响。结果显示：在全球尺度上,植被变绿使得全球蒸散发呈现显著的增加趋势,使陆地水循环加快;区域尺度上,植被变化对蒸散发的影响则存在明显的地带性和非地带性特征,如在北美洲中北部、欧洲、中国东部、非洲南部和澳大利亚东北部等地区,蒸散发总量的增加主要是由植被蒸腾增加而引起的。分析不同植被功能类型区的贡献显示,下垫面变化对灌木和耕地影响尤为明显,并在2012年以后呈现增强趋势;这2个植被类型区的全球年总蒸散发累积增加量为0.41×10³ km³ a^-1,约为黄河流域多年平均径流量的8倍。该研究结果有助于进一步加强关于下垫面变化对陆地水循环的影响及其可能带来的局部气候变化的认识。

Satellite data show increasing leaf area of vegetation due to direct (human land-use management) and indirect factors (climate change, CO fertilization, nitrogen deposition, recovery from natural disturbances, etc.). Among these, climate change and CO fertilization effect seem to be the dominant drivers. However, recent satellite data (2000-2017) reveal a greening pattern that is strikingly prominent in China and India, and overlapping with croplands world-wide. China alone accounts for 25% of the global net increase in leaf area with only 6.6% of global vegetated area. The greening in China is from forests (42%) and croplands (32%), but in India is mostly from croplands (82%) with minor contribution from forests (4.4%). China is engineering ambitious programs to conserve and expand forests with the goal of mitigating land degradation, air pollution and climate change. Food production in China and India has increased by over 35% since 2000 mostly due to increasing harvested area through multiple cropping facilitated by fertilizer use and surface/ground-water irrigation. Our results indicate that the direct factor is a key driver of the "Greening Earth", accounting for over a third, and likely more, of the observed net increase in green leaf area. They highlight the need for realistic representation of human land-use practices in Earth system models.

Terrestrial net primary production (NPP) quantifies the amount of atmospheric carbon fixed by plants and accumulated as biomass. Previous studies have shown that climate constraints were relaxing with increasing temperature and solar radiation, allowing an upward trend in NPP from 1982 through 1999. The past decade (2000 to 2009) has been the warmest since instrumental measurements began, which could imply continued increases in NPP; however, our estimates suggest a reduction in the global NPP of 0.55 petagrams of carbon. Large-scale droughts have reduced regional NPP, and a drying trend in the Southern Hemisphere has decreased NPP in that area, counteracting the increased NPP over the Northern Hemisphere. A continued decline in NPP would not only weaken the terrestrial carbon sink, but it would also intensify future competition between food demand and proposed biofuel production.

Drought affects more people than any other natural disaster but there is little understanding of how ecosystems react to droughts. This study jointly analyzed spatio-temporal changes of drought patterns with vegetation phenology and productivity changes between 1999 and 2010 in major European bioclimatic zones. The Standardized Precipitation and Evapotranspiration Index (SPEI) was used as drought indicator whereas changes in growing season length and vegetation productivity were assessed using remote sensing time-series of Normalized Difference Vegetation Index (NDVI). Drought spatio-temporal variability was analyzed using a Principal Component Analysis, leading to the identification of four major drought events between 1999 and 2010 in Europe. Correspondence Analysis showed that at the continental scale the productivity and phenology reacted differently to the identified drought events depending on ecosystem and land cover. Northern and Mediterranean ecosystems proved to be more resilient to droughts in terms of vegetation phenology and productivity developments. Western Atlantic regions and Eastern Europe showed strong agglomerations of decreased productivity and shorter vegetation growing season length, indicating that these ecosystems did not buffer the effects of drought well. In a climate change perspective, increase in drought frequency or intensity may result in larger impacts over these ecosystems, thus management and adaptation strategies should be strengthened in these areas of concerns.

The boreal forests, identified as a critical "tipping element" of the Earth's climate system, play a critical role in the global carbon budget. Recent findings have suggested that terrestrial carbon sinks in northern high-latitude regions are weakening, but there has been little observational evidence to support the idea of a reduction of carbon sinks in northern terrestrial ecosystems. Here, we estimated changes in the biomass carbon sink of natural stands throughout Canada's boreal forests using data from long-term forest permanent sampling plots. We found that in recent decades, the rate of biomass change decreased significantly in western Canada (Alberta, Saskatchewan, and Manitoba), but there was no significant trend for eastern Canada (Ontario and Quebec). Our results revealed that recent climate change, and especially drought-induced water stress, is the dominant cause of the observed reduction in the biomass carbon sink, suggesting that western Canada's boreal forests may become net carbon sources if the climate change-induced droughts continue to intensify.

We evaluated the response of the Earth land biomes to drought by correlating a drought index with three global indicators of vegetation activity and growth: vegetation indices from satellite imagery, tree-ring growth series, and Aboveground Net Primary Production (ANPP) records. Arid and humid biomes are both affected by drought, and we suggest that the persistence of the water deficit (i.e., the drought time-scale) could be playing a key role in determining the sensitivity of land biomes to drought. We found that arid biomes respond to drought at short time-scales; that is, there is a rapid vegetation reaction as soon as water deficits below normal conditions occur. This may be due to the fact that plant species of arid regions have mechanisms allowing them to rapidly adapt to changing water availability. Humid biomes also respond to drought at short time-scales, but in this case the physiological mechanisms likely differ from those operating in arid biomes, as plants usually have a poor adaptability to water shortage. On the contrary, semiarid and subhumid biomes respond to drought at long time-scales, probably because plants are able to withstand water deficits, but they lack the rapid response of arid biomes to drought. These results are consistent among three vegetation parameters analyzed and across different land biomes, showing that the response of vegetation to drought depends on characteristic drought time-scales for each biome. Understanding the dominant time-scales at which drought most influences vegetation might help assessing the resistance and resilience of vegetation and improving our knowledge of vegetation vulnerability to climate change.

Despite the growing interest in predicting global and regional trends in vegetation productivity in response to a changing climate, changes in water constraint on vegetation productivity (i.e., water limitations on vegetation growth) remain poorly understood. Here we conduct a comprehensive evaluation of changes in water constraint on vegetation growth in the extratropical Northern Hemisphere between 1982 and 2015. We document a significant increase in vegetation water constraint over this period. Remarkably divergent trends were found with vegetation water deficit areas significantly expanding, and water surplus areas significantly shrinking. The increase in water constraints associated with water deficit was also consistent with a decreasing response time to water scarcity, suggesting a stronger susceptibility of vegetation to drought. We also observed shortened water surplus period for water surplus areas, suggesting a shortened exposure to water surplus associated with humid conditions. These observed changes were found to be attributable to trends in temperature, solar radiation, precipitation, and atmospheric CO. Our findings highlight the need for a more explicit consideration of the influence of water constraints on regional and global vegetation under a warming climate.

Coupled climate-carbon cycle models suggest that Amazon forests are vulnerable to both long- and short-term droughts, but satellite observations showed a large-scale photosynthetic green-up in intact evergreen forests of the Amazon in response to a short, intense drought in 2005. These findings suggest that Amazon forests, although threatened by human-caused deforestation and fire and possibly by more severe long-term droughts, may be more resilient to climate changes than ecosystem models assume.

. We investigated the impact of drought on interannual variability of net primary productivity (NPP) from 1997 to 2009, using the standardized precipitation evapotranspiration index (SPEI) drought index and satellite-derived vegetation greenness converted to NPP. SPEI is positive for wet conditions and negative for dry conditions. We found that SPEI and NPP were coupled and showed in-phase behaviour on a global scale. We then used the Köppen climate classification to study the SPEI–NPP relations regionally and found that while NPP and SPEI were positively related (high SPEI, high NPP) in arid and in seasonal dry regions, the opposite occurs in most boreal regions (high SPEI, low NPP). High intensity drought events, such as the 2003 drought in Europe were picked up by our analysis. Our findings suggest that the strong positive relation between global average moisture availability and NPP consists of a composite of the positive relation across dry regions and the coherent NPP decline during and after intensive drought events in humid regions. Importantly, we also found that there are many areas on the globe that show no strong correlation between drought and NPP.\n

Global vegetation greening trend stalled after the late 1990s due to increased atmospheric water demand.

Global vegetation and associated ecosystem services critically depend on soil moisture availability which has decreased in many regions during the last three decades. While spatial patterns of vegetation sensitivity to global soil water have been recently investigated, long-term changes in vegetation sensitivity to soil water availability are still unclear. Here we assess global vegetation sensitivity to soil moisture during 1982-2017 by applying explainable machine learning with observation-based leaf area index (LAI) and hydro-climate anomaly data. We show that LAI sensitivity to soil moisture significantly increases in many semi-arid and arid regions. LAI sensitivity trends are associated with multiple hydro-climate and ecological variables, and strongest increasing trends occur in the most water-sensitive regions which additionally experience declining precipitation. State-of-the-art land surface models do not reproduce this increasing sensitivity as they misrepresent water-sensitive regions and sensitivity strength. Our sensitivity results imply an increasing ecosystem vulnerability to water availability which can lead to exacerbated reductions in vegetation carbon uptake under future intensified drought, consequently amplifying climate change.© 2022. The Author(s).

The 2009/2010 extreme drought in southwest China (SWC) was a “once-in-a-century” drought event, which caused unprecedented damage to the regional ecology and socioeconomic development. The event provided a chance to explore the resilience of vegetation growth and productivity to the extreme drought. Here, we used the self-calibrating Palmer drought severity index (scPDSI) to describe the characteristics of the extreme drought. Vegetation growth and productivity indices, including the normalized difference vegetation index (NDVI), leaf area index (LAI), and gross primary productivity (GPP), were applied to analyze the resilience of different vegetation types to the extreme drought. Our results showed that the extreme drought event occurred mainly in Yunnan Province, Guizhou Province, central and northern Guangxi Zhuang Autonomous Region, and northwestern Sichuan Province. The spatial heterogeneity of the extreme drought was related to the temperature increase and water deficit. During the extreme drought, the vegetation growth and productivity of evergreen broadleaf forest were the least suppressed, whereas cropland was greatly suppressed. The recovery of cropland was higher than that of evergreen broadleaf forest. NDVI and LAI were recovered in more than 80% of the drought-affected area within 5 months, whereas GPP required a longer time to recover. Moreover, the results of multiple linear regression showed that an increase in surface soil moisture was able to significantly improve the resistance of vegetation NDVI and LAI in evergreen broadleaf forest, evergreen needleleaf forest, evergreen broadleaf shrubland, deciduous broadleaf shrubland, and grassland. Our study highlights the differences in the resilience of different vegetation types to extreme drought and indicates that surface soil moisture is an important factor affecting vegetation resistance in SWC.

Compound extremes such as cooccurring soil drought (low soil moisture) and atmospheric aridity (high vapor pressure deficit) can be disastrous for natural and societal systems. Soil drought and atmospheric aridity are 2 main physiological stressors driving widespread vegetation mortality and reduced terrestrial carbon uptake. Here, we empirically demonstrate that strong negative coupling between soil moisture and vapor pressure deficit occurs globally, indicating high probability of cooccurring soil drought and atmospheric aridity. Using the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we further show that concurrent soil drought and atmospheric aridity are greatly exacerbated by land-atmosphere feedbacks. The feedback of soil drought on the atmosphere is largely responsible for enabling atmospheric aridity extremes. In addition, the soil moisture-precipitation feedback acts to amplify precipitation and soil moisture deficits in most regions. CMIP5 models further show that the frequency of concurrent soil drought and atmospheric aridity enhanced by land-atmosphere feedbacks is projected to increase in the 21st century. Importantly, land-atmosphere feedbacks will greatly increase the intensity of both soil drought and atmospheric aridity beyond that expected from changes in mean climate alone.

. The amount of impervious surface is an important\nindicator in the monitoring of the intensity of human activity and\nenvironmental change. The use of remote sensing techniques is the only means\nof accurately carrying out global mapping of impervious surfaces covering\nlarge areas. Optical imagery can capture surface reflectance\ncharacteristics, while synthetic-aperture radar (SAR) images can be used to\nprovide information on the structure and dielectric properties of surface\nmaterials. In addition, nighttime light (NTL) imagery can detect the\nintensity of human activity and thus provide important a priori\nprobabilities of the occurrence of impervious surfaces. In this study, we\naimed to generate an accurate global impervious surface map at a resolution\nof 30 m for 2015 by combining Landsat 8 Operational Land Image (OLI) optical images, Sentinel-1 SAR\nimages and Visible Infrared Imaging Radiometer Suite (VIIRS) NTL images based on\nthe Google Earth Engine (GEE) platform. First, the global impervious and\nnonimpervious training samples were automatically derived by combining the\nGlobeLand30 land-cover product with VIIRS NTL and MODIS enhanced vegetation\nindex (EVI) imagery. Then, the local adaptive random forest classifiers,\nallowing for a regional adjustment of the classification parameters to take into\naccount the regional characteristics, were trained and used to generate\nregional impervious surface maps for each 5∘×5∘ geographical grid using local training samples and multisource\nand multitemporal imagery. Finally, a global impervious surface map,\nproduced by mosaicking numerous 5∘×5∘\nregional maps, was validated by interpretation samples and then compared\nwith five existing impervious products (GlobeLand30, FROM-GLC, NUACI, HBASE and GHSL). The results indicated that the global\nimpervious surface map produced using the proposed multisource,\nmultitemporal random forest classification (MSMT_RF) method\nwas the most accurate of the maps, having an overall accuracy of 95.1 %\nand kappa coefficient (one of the most commonly used statistics to test\ninterrater reliability; Olofsson et al., 2014) of 0.898 as\nagainst 85.6 % and 0.695 for NUACI, 89.6 % and 0.780 for\nFROM-GLC, 90.3 % and 0.794 for GHSL, 88.4 % and 0.753 for\nGlobeLand30, and 88.0 % and 0.745 for HBASE using all 15 regional\nvalidation data. Therefore, it is concluded that a global 30 m impervious\nsurface map can accurately and efficiently be generated by the proposed\nMSMT_RF method based on the GEE platform. The global\nimpervious surface map generated in this paper is available at https://doi.org/10.5281/zenodo.3505079 (Zhang and Liu, 2019).\n

. Over past decades, a lot of global land-cover products have been released; however, these still lack a global land-cover map with a fine classification system and spatial resolution simultaneously. In this study, a novel global 30 m land-cover classification with a fine classification system for the year 2015 (GLC_FCS30-2015) was produced by combining time series of Landsat imagery and high-quality training data from the GSPECLib (Global Spatial Temporal Spectra Library) on the Google Earth Engine computing platform. First, the global training data from the GSPECLib were developed by applying a series of rigorous filters to the CCI_LC (Climate Change Initiative Global Land Cover) land-cover and MCD43A4 NBAR products (MODIS Nadir Bidirectional Reflectance Distribution Function-Adjusted Reflectance). Secondly, a local adaptive random forest model was built for each 5∘×5∘ geographical tile by using the multi-temporal Landsat spectral and texture features and the corresponding training data, and the GLC_FCS30-2015 land-cover product containing 30 land-cover types was generated for each tile. Lastly, the GLC_FCS30-2015 was validated using three different validation systems (containing different land-cover details) using 44 043 validation samples. The validation results indicated that the GLC_FCS30-2015 achieved an overall accuracy of 82.5 % and a kappa coefficient of 0.784 for the level-0 validation system (9 basic land-cover types), an overall accuracy of 71.4 % and kappa coefficient of 0.686 for the UN-LCCS (United Nations Land Cover Classification System) level-1 system (16 LCCS land-cover types), and an overall accuracy of 68.7 % and kappa coefficient of 0.662 for the UN-LCCS level-2 system (24 fine land-cover types). The comparisons against other land-cover products (CCI_LC, MCD12Q1, FROM_GLC, and GlobeLand30) indicated that GLC_FCS30-2015 provides more spatial details than CCI_LC-2015 and MCD12Q1-2015 and a greater diversity of land-cover types than FROM_GLC-2015 and GlobeLand30-2010. They also showed that GLC_FCS30-2015 achieved the best overall accuracy of 82.5 % against FROM_GLC-2015 of 59.1 % and GlobeLand30-2010 of 75.9 %. Therefore, it is concluded that the GLC_FCS30-2015 product is the first global land-cover dataset that provides a fine classification system (containing 16 global LCCS land-cover types as well as 14 detailed and regional land-cover types) with high classification accuracy at 30 m. The GLC_FCS30-2015 global land-cover products produced in this paper are free access at https://doi.org/10.5281/zenodo.3986872 (Liu et al., 2020).\n

The authors propose a new climatic drought index: the standardized precipitation evapotranspiration index (SPEI). The SPEI is based on precipitation and temperature data, and it has the advantage of combining multiscalar character with the capacity to include the effects of temperature variability on drought assessment. The procedure to calculate the index is detailed and involves a climatic water balance, the accumulation of deficit/surplus at different time scales, and adjustment to a log-logistic probability distribution. Mathematically, the SPEI is similar to the standardized precipitation index (SPI), but it includes the role of temperature. Because the SPEI is based on a water balance, it can be compared to the self-calibrated Palmer drought severity index (sc-PDSI). Time series of the three indices were compared for a set of observatories with different climate characteristics, located in different parts of the world. Under global warming conditions, only the sc-PDSI and SPEI identified an increase in drought severity associated with higher water demand as a result of evapotranspiration. Relative to the sc-PDSI, the SPEI has the advantage of being multiscalar, which is crucial for drought analysis and monitoring.

Drought is one of the most expensive but least understood natural disasters. Remote sensing based integrated drought indices have the potential to describe drought conditions comprehensively, and multi-criteria combination analysis is increasingly used to support drought assessment. However, conventional multi-criteria combination methods and most existing integrated drought indices fail to adequately represent spatial variability. An index that can be widely used for drought monitoring across all climate regions would be of great value for ecosystem management. To this end, we proposed a framework for generating a new integrated drought index applicable across diverse climate regions. In this new framework, a local ordered weighted averaging (OWA) model was used to combine the Temperature Condition Index (TCI) from the Moderate-resolution Imaging Spectroradiometer (MODIS), the Vegetation Condition Index (VCI) developed using the Vegetation Index based on Universal Pattern Decomposition method (VIUPD), the Soil Moisture Condition Index (SMCI) derived from the Advanced Microwave Scanning Radiometer-Earth Observation System (AMSR-E), and the Precipitation Condition Index (PCI) derived from the Tropical Rainfall Measuring Mission (TRMM). This new index, which we call the "Geographically Independent Integrated Drought Index (GIIDI)," was validated in diverse climate divisions across the continental United States. Results showed that GIIDI was better correlated with in-situ PDSI, Z-index, SP1-1, SPI-3 and SPEI-6 (overall r-value = 0.701, 0.794, 0.811, 0.733, 0.628; RMSE = 1.979, 0.810, 0.729, 1.049 and 1.071, respectively) when compared to the Microwave Integrated Drought Index (MIDI), Optimized Meteorological Drought Index (OMDI), Scaled Drought Condition Index (SDCI), PCI, TCI, SMCI, and VCI. GIIDI also performed well in most climate divisions for both short-term and long-term drought monitoring. Because of the superior performance of GIIDI across diverse temporal and spatial scales, GIIDI has considerable potential for improving our ability to monitor drought across a range of biomes and climates.

A monthly global dataset of a multiscalar drought index is presented and compared in terms of spatial and temporal variability with the existing continental and global drought datasets based on the Palmer drought severity index (PDSI). The presented dataset is based on the standardized precipitation evapotranspiration index (SPEI). The index was obtained using the Climatic Research Unit (CRU) TS3.0 dataset at a spatial resolution of 0.5°. The advantages of the new dataset are that (i) it improves the spatial resolution of the unique global drought dataset at a global scale; (ii) it is spatially and temporally comparable to other datasets, given the probabilistic nature of the SPEI; and, in particular, (iii) it enables the identification of various drought types, given the multiscalar character of the SPEI. The dataset is freely available on the Web page of the Spanish National Research Council (CSIC) in three different formats [network Common Data Form (netCDF), binary raster, and plain text].

Extensive studies have focused on instantaneous and time-lag impacts of climatic factors on vegetation growth; however, the chronical and accumulative indirect impacts of antecedent climatic factors carrying over for a period of time on vegetation growth, defined as cumulative effects, are less investigated. Here we aimed to disentangle the cumulative effects of climatic factors on vegetation growth by using vegetation indexes and accumulated meteorological data. First, we investigated the explanation and fit of climate changes on vegetation variations by applying stepwise multiple linear regression with Akaike information criterion. Then, we obtained the correlation coefficients and lagged time of climatic factors on vegetation growth whereby partial correlation and time-lag effect analyses. Results showed that (i) consideration of cumulative climate effects increased the explanation and fit of climate changes on vegetation dynamics for more than 77% of vegetated surface with an average global explanation of 68.33%, which was approximately 3.35% higher than the scenario when only time-lag effects were considered; (ii) big differences exhibited in the correlation coefficients and lagged times under the scenarios with cumulative climate effects considered or not; and (iii) positive accumulated temperature (accumulated solar radiation) effects with zero (three-month) time lag dominates most mid-high latitude ecosystems, and negative accumulated temperature effects with three-month delay dominates the temperate arid and semiarid regions and tropical dry ecosystems. By comparison, accumulated precipitation had relatively complex cumulative effects on vegetation growth. We concluded that climatic factors had significant cumulative effects on vegetation growth; consideration of the cumulative effects helps us better understand the climate-vegetation interactions.

The terrestrial forest ecosystems in the northern high latitude region have been experiencing significant warming rates over several decades. These forests are considered crucial to the climate system and global carbon cycle and are particularly vulnerable to climate change. To obtain an improved estimate of the response of vegetation activity, e.g., forest greenness and tree growth, to climate change, we investigated spatiotemporal variations in two independent data sets containing the dendroecological information for this region over the past 30 years. These indices are the normalized difference vegetation index (NDVI3g) and the tree-ring width index (RWI), both of which showed significant spatial variability in past trends and responses to climate changes. These trends and responses to climate change differed significantly in the ecosystems of the circumarctic (latitude higher than 67°N) and the circumboreal forests (latitude higher and lower than 50°N and 67°N, respectively), but the way in which they differed was relatively similar in the NDVI3g and the RWI. In the circumarctic ecosystem, the climate variables of the current summer were the main climatic drivers for the positive response to the increase in temperatures showed by both the NDVI3g and the RWI indices. On the other hand, in the circumboreal forest ecosystem, the climate variables of the previous year (from summer to winter) were also important climatic drivers for both the NDVI3g and the RWI. Importantly, both indices showed that the temperatures in the previous year negatively affected the ecosystem. Although such negative responses to warming did not necessarily lead to a past negative linear trend in the NDVI3g and the RWI over the past 30 years, future climate warming could potentially cause severe reduction in forest greenness and tree growth in the circumboreal forest ecosystem.© 2018 John Wiley & Sons Ltd.

Grasslands are key repositories of biodiversity and carbon storage and are heavily impacted by effects of global warming and changes in precipitation regimes. Patterns of grassland dynamics associated with variability in future climate conditions across spatiotemporal scales are yet to be adequately quantified. Here, we performed a global meta-analysis of year and growing season sensitivities of vegetation aboveground biomass (AGB), aboveground net primary productivity (ANPP), and species richness (SR) and diversity (Shannon index, H) to experimental climate warming and precipitation shifts. All four variables were sensitive to climate change. Their sensitivities to shifts in precipitation were correlated with local background water availability, such as mean annual precipitation (MAP) and aridity, and AGB and ANPP sensitivities were greater in dry habitats than in nonwater-limited habitats. There was no effect of duration of experiment (short vs long term) on sensitivities. Temporal trends in ANPP and SR sensitivity depended on local water availability; ANPP sensitivity to warming increased over time and SR sensitivity to irrigation decreased over time. Our results provide a global overview of the sensitivities of grassland function and diversity to climate change that will improve the understanding of ecological responses across spatiotemporal scales and inform policies for conservation in dry climates.© 2021 The Authors New Phytologist © 2021 New Phytologist Foundation.

Global ecosystem function is highly dependent on climate and atmospheric composition, yet ecosystem responses to environmental changes remain uncertain. Cold, high-latitude ecosystems in particular have experienced rapid warming(1), with poorly understood consequences(2-4). Here, we use a satellite-observed proxy for vegetation cover-the fraction of absorbed photosynthetically active radiation(5)-to identify a decline in the temperature limitation of vegetation in global ecosystems between 1982 and 2012. We quantify the spatial functional response of maximum annual vegetation cover to temperature and show that the observed temporal decline in temperature limitation is consistent with expectations based on observed recent warming. An ensemble of Earth system models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) mischaracterized the functional response to temperature, leading to a large overestimation of vegetation cover in cold regions. We identify a 16.4% decline in the area of vegetated land that is limited by temperature over the past three decades, and suggest an expected large decline in temperature limitation under future warming scenarios. This rapid observed and expected decline in temperature limitation highlights the need for an improved understanding of other limitations to vegetation growth in cold regions(3,4,6), such as soil characteristics, species migration, recruitment, establishment, competition and community dynamics.

Recent climatic changes have enhanced plant growth in northern mid-latitudes and high latitudes. However, a comprehensive analysis of the impact of global climatic changes on vegetation productivity has not before been expressed in the context of variable limiting factors to plant growth. We present a global investigation of vegetation responses to climatic changes by analyzing 18 years (1982 to 1999) of both climatic data and satellite observations of vegetation activity. Our results indicate that global changes in climate have eased several critical climatic constraints to plant growth, such that net primary production increased 6% (3.4 petagrams of carbon over 18 years) globally. The largest increase was in tropical ecosystems. Amazon rain forests accounted for 42% of the global increase in net primary production, owing mainly to decreased cloud cover and the resulting increase in solar radiation.

Global vegetation greening trend stalled after the late 1990s due to increased atmospheric water demand.

Increasing heatwave and drought events can potentially alter the carbon cycle. Few studies have investigated the impacts of hundred-year return heatwaves and droughts, as those events are rare. In the summer of 2013, southern China experienced its strongest drought and heatwave on record for the past 113 years. We show that the record-breaking heatwave and drought lasted two months (from July to August), significantly reduced the satellite-based vegetation index and gross primary production, substantially altered the regional carbon cycle and produced the largest negative crop yield anomaly since 1960. The event resulted in a net reduction of 101.54 Tg C in carbon sequestration in the region during these two months, which was 39–53% of the annual net carbon sink of China’s terrestrial ecosystems (190–260 Tg C yr−1). Moreover, model experiments showed that heatwaves and droughts consistently decreased ecosystem vegetation primary production but had opposite impacts on ecosystem respiration (TER), with increased TER by 6.78 ± 2.15% and decreased TER by 15.34 ± 3.57% assuming only changed temperature and precipitation, respectively. In light of increasing frequency and severity of future heatwaves and droughts, our study highlights the importance of accounting for the impacts of heatwaves and droughts in assessing the carbon sequestration in terrestrial ecosystems.

Drought is an intermittent disturbance of the water cycle that profoundly affects the terrestrial carbon cycle. However, the response of the coupled water and carbon cycles to drought and the underlying mechanisms remain unclear. Here we provide the first global synthesis of the drought effect on ecosystem water use efficiency (WUE = gross primary production (GPP)/evapotranspiration (ET)). Using two observational WUE datasets (i.e., eddy-covariance measurements at 95 sites (526 site-years) and global gridded diagnostic modelling based on existing observation and a data-adaptive machine learning approach), we find a contrasting response of WUE to drought between arid (WUE increases with drought) and semi-arid/sub-humid ecosystems (WUE decreases with drought), which is attributed to different sensitivities of ecosystem processes to changes in hydro-climatic conditions. WUE variability in arid ecosystems is primarily controlled by physical processes (i.e., evaporation), whereas WUE variability in semi-arid/sub-humid regions is mostly regulated by biological processes (i.e., assimilation). We also find that shifts in hydro-climatic conditions over years would intensify the drought effect on WUE. Our findings suggest that future drought events, when coupled with an increase in climate variability, will bring further threats to semi-arid/sub-humid ecosystems and potentially result in biome reorganization, starting with low-productivity and high water-sensitivity grassland.

The Qinling Mountains, located at the junction of warm temperate and subtropical zones, serves as the boundary between North and South China. Exploring the sensitivity of vegetation response to hydrothermal dynamics can be conducive to understanding the pattern and dynamics of main vegetation types and the mechanism of their response to changes in temperature and moisture. Importance should be attached to the laws of vegetation change in different climate zones. To reveal the sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics, the spatial and temporal variation characteristics of NDVI and SPEI on the southern and northern slopes of the Qinling Mountains from 2000 to 2018 are explored using the meteorological data from 32 meteorological stations and the MODIS NDVI datasets. The results show that: (1) The overall vegetation coverage of the Qinling Mountains improved significantly from 2000 to 2018. The NDVI rise rate and area ratio on the southern slope were higher than those on the northern slope, and the vegetation on the southern slope exhibited better improvement than that on the northern slope. The Qinling Mountains showed an insignificant humidification trend. The humidification rate and humidification area of the northern slope were greater than those on the southern slope. (2) Vegetation on the northern slope of the Qinling Mountains was more sensitive to hydrothermal dynamics than that on the southern slope. Vegetation was most sensitive to hydrothermal dynamics from March to June on the northern slope, and from March to May (spring) on the southern slope. The vegetation on the northern and southern slopes was mainly affected by hydrothermal dynamics on a scale of 3-7 months, and it responds weakly to hydrothermal dynamics on a scale of 11-12 months. (3) 90.34% of NDVI and SPEI were positively correlated in the Qinling Mountains. Spring humidification in most parts of the study area could promote the growth of vegetation all the year round. The sensitivity of vegetation responses to hydrothermal dynamics with increasing altitude increased first and then decreased. The altitude of 800 to 1200 m was the most sensitive altitude for vegetation response to hydrothermal dynamics. The sensitivity of vegetation response at the elevation of 1200-3000 m decreased with the increasing altitude. The grass was the most sensitive vegetation type to hydrothermal dynamics on the northern and southern slopes of the Qinling Mountains, but most of other vegetation types on the northern slope were more sensitive to hydrothermal dynamics than those on the southern slope.

秦岭位于暖温带与亚热带交界处,也是中国南北地理分界线,秦岭南北坡植被对干湿变化响应敏感性,可以折射出暖温带、亚热带地区主要植被类型对干湿变化的响应规律和机制特征,对深入理解不同气候带植被变化规律具有重要意义。本文利用秦岭山地32个气象站点的气象数据和MODIS NDVI时间序列数据集,探讨了2000—2018年秦岭南北坡NDVI和SPEI时空变化特征,揭示了南北坡植被对干湿变化响应敏感性及其空间差异。结果表明：① 2000—2018年秦岭植被覆盖情况整体显著改善,但秦岭南坡NDVI上升幅度和面积占比均高于北坡,南坡植被比北坡改善情况好。秦岭湿润化趋势不显著,但秦岭北坡湿润化速率和面积占比均大于南坡。② 秦岭北坡植被比南坡植被更易受干湿变化影响,秦岭北坡植被对3—6月总体干湿变化最为敏感,南坡植被对3—5月（春季）干湿变化最为敏感。秦岭南北坡植被主要受3~7个月尺度干湿变化影响,对11~12个月尺度的干湿变化响应较弱。③ 秦岭有90.34%的区域NDVI与SPEI呈正相关,大部分地区春季湿润化能促进全年植被生长;随海拔上升,植被对干湿变化响应敏感性先上升再下降,海拔800~1200 m是植被响应最敏感的海拔段,海拔1200~3000 m随海拔上升植被响应敏感性下降;南北坡草丛均是对干湿变化响应最为敏感的植被类型,但秦岭北坡多数植被类型对干湿变化响应比南坡敏感。

Compound drought and aridity events will be more extreme and frequent, exerting an increasingly negative impact on carbon uptake.

Based on the observed daily temperature and precipitation of the land surface of 603 meteorological stations in China, the Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) 3rd generation dataset, the changing patterns of NDVI in China during 1982-2015 were investigated and the corresponding contributions of the main driving forces, climatic change and human activities, to these changes were distinguished using the methods of trend analysis and multiple regression residuals analysis. The results showed that vegetation recovered in whole China in research period significantly. Shanghai was the single case with a decrease in growing season NDVI in the selected 32 provincial-level administrative regions, while the growing season NDVI in Shanxi, Shaanxi, and Chongqing increased much faster compared with other regions. The climatic change and human activities drove the NDVI change jointly as main forces in China and induced both a rapid increasing trend on the whole and a huge spatial difference. The impacts of climatic change on NDVI change in the growing-season ranged from -0.01×10 -3 a -1 to 1.05×10 -3 a -1, while the impacts of human activities changed from -0.32×10 -3 a -1 to 1.77×10 -3 a -1. The contributions of climatic change and human activities accounted for 40% and 60%, respectively, to the increase of NDVI in China in the past 34 years. The regions where the contribution rates of human activities were more than 80% were mainly distributed in the central part of the Loess Plateau, the North China Plain, and the northeast and the southwest of China. There were 22 provincial-level regions where the contributions of human activities were more than 50%, and the shares of contribution induced by human activities in Shanghai, Heilongjiang, and Yunnan were much greater than those of any other regions. The results suggest that we should focus more on the role of human activities in vegetation restoration in the whole country.

基于中国603个气象站的地表气温和降水观测资料以及GIMMS NDVI3g数据,采用变化趋势分析和多元回归残差分析等方法研究了1982—2015年中国植被NDVI变化特征及其主要驱动因素（即气候变化和人类活动）的相应贡献。结果表明：① 1982—2015年中国植被恢复明显,在选择的32个省级行政区中,山西、陕西和重庆的生长季NDVI增加最快,仅上海生长季NDVI呈减小趋势。② 气候变化和人类活动的共同作用是中国植被NDVI呈现整体快速增加和巨大空间差异的主要原因,其中气候变化对各省生长季NDVI变化的影响在-0.01×10 ^-3~1.05×10 ^-3 a ^-1之间,而人类活动的影响在-0.32×10 ^-3~1.77×10 ^-3 a ^-1之间。③ 气候变化和人类活动分别对中国近34年来植被NDVI的增加贡献了40%和60%;人类活动贡献率超过80%的区域主要集中在黄土高原中部、华北平原以及中国东北和西南等地;人类活动贡献率大于50%的省份有22个,其中贡献率最大的3个地区为上海、黑龙江和云南。研究结果建议应更加重视人类活动在植被恢复中的作用。