Detection and attribution of vegetation greening trend in China over the last 30 years

Effects of Climate and Land Use changes on Vegetation Dynamics in the Yangtze River Delta, China Based on Abrupt Change Analysis

Vegetation dynamics is thought to be affected by climate and land use changes. However, how the effects vary after abrupt vegetation changes remains unclear. Based on the Mann-Kendall trend and abrupt change analysis, we monitored vegetation dynamics and its abrupt change in the Yangtze River delta during 1982–2016. With the correlation analysis, we revealed the relationship of vegetation dynamics with climate changes (temperature and precipitation) pixel-by-pixel and then with land use changes analysis we studied the effects of land use changes (unchanged or changed land use) on their relationship. Results showed that: (1) the Normalized Vegetation Index (NDVI) during growing season that is represented as GSN (growing season NDVI) showed an overall increasing trend and had an abrupt change in 2000. After then, the area percentages with decreasing GSN trend increased in cropland and built-up land, mainly located in the eastern, while those with increasing GSN trend increased in woodland and grassland, mainly located in the southern. Changed land use, except the land conversions from/to built-up land, is more favor for vegetation greening than unchanged land use (2) after abrupt change, the significant positive correlation between precipitation and GSN increased in all unchanged land use types, especially for woodland and grassland (natural land use) and changed land use except built-up land conversion. Meanwhile, the insignificant positive correlation between temperature and GSN increased in woodland, while decreased in the cropland and built-up land in the northwest (3) after abrupt change, precipitation became more important and favor, especially for natural land use. However, temperature became less important and favor for all land use types, especially for built-up land. This research indicates that abrupt change analysis will help to effectively monitor vegetation trend and to accurately assess the relationship of vegetation dynamics with climate and land use changes.

Evidence of Carbon Uptake Associated with Vegetation Greening Trends in Eastern China

Persistent and widespread increase of vegetation cover, identified as greening, has been observed in areas of the planet over late 20th century and early 21st century by satellite-derived vegetation indices. It is difficult to verify whether these regions are net carbon sinks or sources by studying vegetation indices alone. In this study, we investigate greening trends in Eastern China (EC) and corresponding trends in atmospheric CO2 concentrations. We used multiple vegetation indices including NDVI and EVI to characterize changes in vegetation activity over EC from 2003 to 2016. Gap-filled time series of column-averaged CO2 dry air mole fraction (XCO2) from January 2003 to May 2016, based on observations from SCIAMACHY, GOSAT, and OCO-2 satellites, were used to calculate XCO2 changes during growing season for 13 years. We derived a relationship between XCO2 and surface net CO2 fluxes from two inversion model simulations, CarbonTracker and Monitoring Atmospheric Composition and Climate (MACC), and used those relationships to estimate the biospheric CO2 flux enhancement based on satellite observed XCO2 changes. We observed significant growing period (GP) greening trends in NDVI and EVI related to cropland intensification and forest growth in the region. After removing the influence of large urban center CO2 emissions, we estimated an enhanced XCO2 drawdown during the GP of −0.070 to −0.084 ppm yr−1. Increased carbon uptake during the GP was estimated to be 28.41 to 46.04 Tg C, mainly from land management, which could offset about 2–3% of EC’s annual fossil fuel emissions. These results show the potential of using multi-satellite observed XCO2 to estimate carbon fluxes from the regional biosphere, which could be used to verify natural sinks included as national contributions of greenhouse gas emissions reduction in international climate change agreements like the UNFCC Paris Accord.

Quantitatively Assessing and Attributing Land Use and Land Cover Changes on China’s Loess Plateau

The global land surface cover is undergoing extensive changes in the context of global change, especially in the Loess Plateau, where ecological restoration policies have been vigorously implemented since 2000. Evaluating the impact of these policies on land cover is of great significance for regional sustainable development. Nonetheless, there are few quantitative assessment studies of the impact of ecological restoration policies on land use and land cover change (LULCC). In this study, a relative contribution conceptual model (RCCM) was used to explore the contribution of the policies to LULCC under the influence of natural background change, which was based on the Markov chain and the future land use simulation (FLUS) model. The results show that LULCC is influenced by ecological restoration policies and the natural environment, of which the policies contribute about 72.37% and natural change contribute about 27.63%. Ecological restoration policies have a profound impact on LULCC, changing the original direction of LULCC greatly. Additionally, these policies regulate the pattern of LULCC by controlling the amount of cropland as a rebalanced leverage. These findings provide useful information for facilitating sustainable ecological development in the Loess Plateau and theoretically supporting environmental decision-making.

Forest management in southern China generates short term extensive carbon sequestration

Land use policies have turned southern China into one of the most intensively managed forest regions in the world, with actions maximizing forest cover on soils with marginal agricultural potential while concurrently increasing livelihoods and mitigating climate change. Based on satellite observations, here we show that diverse land use changes in southern China have increased standing aboveground carbon stocks by 0.11 ± 0.05 Pg C y^-1 during 2002-2017. Most of this regional carbon sink was contributed by newly established forests (32%), while forests already existing contributed 24%. Forest growth in harvested forest areas contributed 16% and non-forest areas contributed 28% to the carbon sink, while timber harvest was tripled. Soil moisture declined significantly in 8% of the area. We demonstrate that land management in southern China has been removing an amount of carbon equivalent to 33% of regional fossil CO₂ emissions during the last 6 years, but forest growth saturation, land competition for food production and soil-water depletion challenge the longevity of this carbon sink service.

Effects of Climate Factors and Human Activities on the Ecosystem Water Use Efficiency throughout Northern China

Global climate changes have increased the imbalance of water resources, especially in northern China, which comprises typical arid and semiarid regions. Large-scale afforestation has been implemented over the past three decades in northern China. The ecosystem water use efficiency (WUE) connects the carbon cycle and water cycle of the terrestrial ecosystems and is defined as the ratio of the gross primary productivity (GPP) to the evapotranspiration. However, there are still an insufficient number of studies on the impact of the afforestation on the WUE. In this study, we applied the random forest (RF) model to explore the impacts of climate and nonclimate factors on the WUE in northern China. The results showed that in areas with high precipitation, the forests had the highest WUE, while in the arid areas, the croplands had the highest WUE. Of the total area, 44.34% showed a significant increase, and 5.89% showed a significant decrease in the WUE from 1982–2015 in northern China. The main driving factors for the changes in the WUE were climate factors, including the precipitation, temperature and solar radiation, which contributed to approximately 84% of the WUE trends, while human activities, such as afforestation, contributed to approximately 16% of the WUE trends. Overall, although the climate had a larger impact on the WUE dynamics than the human activities, our results suggested that the impacts of the afforestation programs on forest carbon and water cycles should be considered in the context of climate change.

Spatiotemporal variation of vegetation coverage and its associated influence factor analysis in the Yangtze River Delta, eastern China

Vegetation is a natural tie that connects the atmosphere, hydrosphere, biosphere, and pedosphere. Quantitatively evaluating the variability of vegetation coverage and exploring its associated influence factors are essential for ecological security and sustainable economic development. In this paper, the spatiotemporal variation of vegetation coverage and its response to climatic factors and land use change were investigated in the Yangtze River Delta (YRD) from 2001 to 2015, based on normalized difference vegetation index (NDVI) data, vegetation type data, climate data, and land use/cover change (LUCC) data. The results indicated that the annual mean vegetation coverage revealed a nonsignificant decreasing trend over the whole YRD. Areas characterized by significant decreasing (P < 0.05) trends were mainly concentrated on the central and northern part of the YRD, and significant increasing (P < 0.05) trends were mainly located in the southern part of the study area. Except for grassland and cultivated crops, vegetation coverage of the other types of vegetation was all exhibiting increasing trends. Temperature has a more pronounced impact on vegetation growth than precipitation at both the annual and monthly scales. Furthermore, vegetation growth exhibited a time lag effect for 1~2 months in response to precipitation, while there was no such phenomenon with temperature. Land use change caused by urbanization is an important driving factor for the decrease of vegetation coverage in the YRD, and the effect of land use change on the vegetation dynamic should not be overlook.

Remote Sensing Greenness and Urbanization in Ecohydrological Model Analysis: Asia and Australasia (1982-2015)

Linking remote sensing information and ecohydrological models to improve understanding of terrestrial biosphere responses to climate and land use change has become the subject of increased interest due to the impacts of current global changes and the effect on the sustainability of human lifestyles. An application to Asia and Australasia (1982–2015) is presented, revealing the following results: (i) The broad distribution of regions with the enhanced vegetation greenness only follows the general pattern as for the whole, without obvious dependence on regional or climate fluxes ratios. That indicates a prevailing increasing greenness over land due to both the impacts of current global changes and the sustainability of human lifestyles; (ii) regions with vegetation greenness reduction reveal a unique distribution, concentrating in the water-limited domain due to the impacts of external (climatically “dry gets drier and wet gets wetter”) and internal (anthropogenically increased evaporation) changes; (iii) the external changes of dryness diverge at the boundary separating energy from water-limited regimes, and the internal changes indicate large-scale afforestation and deforestation) that occur mainly in China and Russia due to a conservation program and illegal logging, respectively, and a massive conversion of tropical forest to industrial tree plantations in Southeast Asia, leading to an increased evaporation.

Greening Implication Inferred from Vegetation Dynamics Interacted with Climate Change and Human Activities over the Southeast Qinghai–Tibet Plateau

Vegetation dynamics are sensitive to climate change and human activities, as vegetation interacts with the hydrosphere, atmosphere, and biosphere. The Yarlung Zangbo River (YZR) basin, with the vulnerable ecological environment, has experienced a series of natural disasters since the new millennium. Therefore, in this study, the vegetation dynamic variations and their associated responses to environmental changes in the YZR basin were investigated based on Normalized Difference Vegetation Index (NDVI) and Global Land Data Assimilation System (GLDAS) data from 2000 to 2016. Results showed that (1) the YZR basin showed an obvious vegetation greening process with a significant increase of the growing season NDVI (Zc = 2.31, p < 0.05), which was mainly attributed to the wide greening tendency of the downstream region that accounted for over 50% area of the YZR basin. (2) Regions with significant greening accounted for 25.4% of the basin and were mainly concentrated in the Nyang River and Parlung Tsangpo River sub-basins. On the contrary, the browning regions accounted for <25% of the basin and were mostly distributed in the urbanized cities of the midstream, implying a significant influence of human activities on vegetation greening. (3) The elevation dependency of the vegetation in the YZR basin was significant, showing that the vegetation of the low-altitude regions was better than that of the high-altitude regions. The greening rate exhibited a significantly more complicated relationship with the elevation, which increased with elevated altitude (above 3500 m) and decreased with elevated altitude (below 3500 m). (4) Significantly positive correlations between the growing season NDVI and surface air temperature were detected, which were mainly distributed in the snow-dominated sub-basins, indicating that glaciers and snow melting processes induced by global warming play an important role in vegetation growth. Although basin-wide non-significant negative correlations were found between precipitation and growing season NDVI, positive influences of precipitation on vegetation greening occurred in the arid and semi-arid upstream region. These findings could provide important information for ecological environment protection in the YZR basin and other high mountain regions.

Vegetation change in response to climate factors and human activities on the Mongolian Plateau

Background

Vegetation in the Mongolian Plateau is very sensitive to climate change, which has a significant impact on the regulation of terrestrial carbon cycle.

Methods

We analyzed spatio-temporal changes of both growing season and the seasonal Normalized Difference Vegetation Index (NDVI) using simple linear trend analysis. Besides, correlation analysis was applied to explore the climate factors’ effects on vegetation growth at temporal and spatial scale. Potential effects of human factors on vegetation growth were also explored by residual trend analysis.

Results

The results indicated that vegetation growth showed a greening trend in the Mongolian Plateau over the past 30 years. At the temporal scale, the growing season NDVI showed an insignificant increasing trend (at a rate of 0.0003 yr⁻¹). At the spatial scale, a large region (53.8% of the whole Mongolian Plateau) with an increasing growing season NDVI, was primarily located in the southern and northern parts of the plateau. The correlation analysis suggested that temperature and precipitation were the main limiting factors that affected vegetation growth in spring and the growing season, respectively. The residual trend analysis showed that human activities primarily stimulated the growth of grasslands and shrublands, while croplands displayed a decreasing trend due to human disturbances, implying that anthropogenic factors may lead to croplands abandonment in favor of grasslands restoration. Our results provided detailed spatial and temporal changes of vegetation growth, and explored how climate and human factors affected vegetation growth, which may offer baseline data and scientific suggestions for local land and resources management, and facilitate the sustainable development of the terrestrial ecosystems.

Time Series of Landsat Imagery Shows Vegetation Recovery in Two Fragile Karst Watersheds in Southwest China from 1988 to 2016

Since the implementation of China’s afforestation and conservation projects during recent decades, an increasing number of studies have reported greening trends in the karst regions of southwest China using coarse-resolution satellite imagery, but small-scale changes in the heterogenous landscapes remain largely unknown. Focusing on two typical karst regions in the Nandong and Xiaojiang watersheds in Yunnan province, we processed 2,497 Landsat scenes from 1988 to 2016 using the Google Earth Engine cloud platform and analyzed vegetation trends and associated drivers. We found that both watersheds experienced significant increasing trends in annual fractional vegetation cover, at a rate of 0.0027 year−1 and 0.0020 year−1, respectively. Notably, the greening trends have been intensifying during the conservation period (2001–2016) even under unfavorable climate conditions. Human-induced ecological engineering was the primary factor for the increased greenness. Moreover, vegetation change responded differently to variations in topographic gradients and lithological types. Relatively more vegetation recovery was found in regions with moderate slopes and elevation, and pure limestone, limestone and dolomite interbedded layer as well as impure carbonate rocks than non-karst rocks. Partial correlation analysis of vegetation trends and temperature and precipitation trends suggested that climate change played a minor role in vegetation recovery. Our findings contribute to an improved understanding of the mechanisms behind vegetation changes in karst areas and may provide scientific supports for local afforestation and conservation policies.

Tracking the Spatial–Temporal Evolution of Carbon Emissions in China from 1999 to 2015: A Land Use Perspective

China has been a leader in global carbon emissions since 2006. The question of how to reduce emissions while maintaining stable economic growth is a serious challenge for the country. To achieve this, it is of great significance to track the spatial and temporal evolution of carbon emissions in China during recent decades, which can provide evidence-based scientific guidance for developing mitigation policies. In this study, we calculated the carbon emissions of land use in 1999–2015 using the carbon emissions factor method proposed by the Intergovernmental Panel on Climate Change (IPCC). The Kuznets curve model was used to explore the influence of economic growth and urbanization on carbon emissions at the national and provincial levels. The results indicated that (1) China’s emissions increased from 927.88 million tons (Mt) in 1999 to 2833.91 Mt in 2015 at an average annual growth rate of 12.94%, while carbon sinks grew slightly, from 187.58 Mt to 207.19 Mt. Both emissions and sinks presented significant regional differences, with the Central and Southwest regions acting as the biggest emissions and sink contributors, respectively. (2) Built-up land was the largest land carrier for carbon emissions in China, contributing over 85% to total emissions each year; and (3) at the national level, the relationships between economic growth, urbanization, and carbon emissions presented as inverted U-shaped Kuznets curves, which were also found in the majority of the 30 studied provinces. While carbon emissions may be reaching a peak in China, given the disproportionate role of built-up land in carbon emissions, efforts should be devoted to limiting urbanization and the production of associated carbon emissions.

Influence of Landscape Heterogeneity and Spatial Resolution in Multi-Temporal In Situ and MODIS NDVI Data Proxies for Seasonal GPP Dynamics

The objective of this paper was to evaluate the use of in situ normalized difference vegetation index (NDVIis) and Moderate Resolution Imaging Spectroradiometer NDVI (NDVIMD) time series data as proxies for ecosystem gross primary productivity (GPP) to improve GPP upscaling. We used GPP flux data from 21 global FLUXNET sites across main global biomes (forest, grassland, and cropland) and derived MODIS NDVI at contrasting spatial resolutions (between 0.5 × 0.5 km and 3.5 × 3.5 km) centered at flux tower location. The goodness of the relationship between NDVIis and NDVIMD varied across biomes, sites, and MODIS spatial resolutions. We found a strong relationship with a low variability across sites and within year variability in deciduous broadleaf forests and a poor correlation in evergreen forests. Best performances were obtained for the highest spatial resolution at 0.5 × 0.5 km). Both NDVIis and NDVIMD elicited roughly three weeks later the starting of the growing season compared to GPP data. Our results confirm that to improve the accuracy of upscaling in situ data of site GPP seasonal responses, in situ radiation measurement biomes should use larger field of view to sense an area, or more sensors should be placed in the flux footprint area to allow optimal match with satellite sensor pixel size.

Divergent changes in the elevational gradient of vegetation activities over the last 30 years

The reported progressive change of vegetation activity along elevational gradients has important aesthetic and conservation values. With climate change, cooler locations are suggested to warm faster than warmer ones, raising concerns of a more homogenized landscape along the elevation. Here, we use global satellite data to investigate the spatio-temporal dynamics of the elevational gradient (EG) in vegetation greenness (NDVI_max3), spring (SOS) and autumn phenology (EOS) during 1982-2015. Although we find clear geographical patterns of the EG in NDVI_max3 and SOS, there are no prevalent trends of vegetation homogenization or phenology synchronization along elevational gradients. Possible mechanisms, including spatially heterogeneous temperature lapse rate changes, different vegetation sensitivities to climate change, and human disturbances, may play diverse roles across different regions. Our finding of mixed EG trends and no general rules controlling EG dynamics poses challenges for mitigating possible adverse impacts of climate change on mountainous biological diversity and ecosystem services.

Identification of Natural and Anthropogenic Drivers of Vegetation Change in the Beijing-Tianjin-Hebei Megacity Region

Identifying the natural and anthropogenic mechanisms of vegetation changes is the basis for adapting to climate change and optimizing human activities. The Beijing-Tianjin-Hebei megacity region, which is characterized by significant geomorphic gradients, was chosen as the case study area. The ordinary least squares (OLS) method was used to calculate the NDVI trends and related factors from 2000 to 2015. A geographic weighted regression (GWR) model of NDVI trends was constructed using 14 elements of seven categories. Combined with the GWR calculation results, the mechanisms of the effects of explanatory variables on NDVI changes were analyzed. The findings suggest that the overall vegetation displayed an increasing trend from 2000 to 2015, with an NDVI increase of ca. 0.005/year. Additionally, the NDVI fluctuations in individual years were closely related to precipitation and temperature anomalies. The spatial pattern of the NDVI change was highly consistent with the gradients of geomorphology, climate, and human activities, which have a tendency to gradually change from northwest to southeast. The dominant climate-driven area accounted for only 5.98% of the total study area. The vegetation improvement areas were regionally concentrated and had various driving factors, and vegetation degradation exhibited strong spatial heterogeneity. The vegetation degradation was mainly caused by human activities. Natural vegetation was improved because of natural factors and reductions in human activities. Moreover, cropland vegetation as well as urban and built-up area improvements were related to increased human actions and decreased natural effects. This study can assist in ecological restoration planning and ecological engineering implementation in the study area.

Altered trends in carbon uptake in China's terrestrial ecosystems under the enhanced summer monsoon and warming hiatus

The carbon budgets in terrestrial ecosystems in China are strongly coupled with climate changes. Over the past decade, China has experienced dramatic climate changes characterized by enhanced summer monsoon and decelerated warming. However, the changes in the trends of terrestrial net ecosystem production (NEP) in China under climate changes are not well documented. Here, we used three ecosystem models to simulate the spatiotemporal variations in China's NEP during 1982-2010 and quantify the contribution of the strengthened summer monsoon and warming hiatus to the NEP variations in four distinct climatic regions of the country. Our results revealed a decadal-scale shift in NEP from a downtrend of -5.95 Tg C/yr² (reduced sink) during 1982-2000 to an uptrend of 14.22 Tg C/yr² (enhanced sink) during 2000-10. This shift was essentially induced by the strengthened summer monsoon, which stimulated carbon uptake, and the warming hiatus, which lessened the decrease in the NEP trend. Compared to the contribution of 56.3% by the climate effect, atmospheric CO₂ concentration and nitrogen deposition had relatively small contributions (8.6 and 11.3%, respectively) to the shift. In conclusion, within the context of the global-warming hiatus, the strengthening of the summer monsoon is a critical climate factor that enhances carbon uptake in China due to the asymmetric response of photosynthesis and respiration. Our study not only revealed the shift in ecosystem carbon sequestration in China in recent decades, but also provides some insight for understanding ecosystem carbon dynamics in other monsoonal areas.

Factors Affecting Long-Term Trends in Global NDVI

Diagnosing the evolution trends of vegetation and its drivers is necessary for ecological conservation and restoration. However, it remains unclear what the underlying distribution pattern of these trends and its correlation with some drivers at large spatial-temporal scales. Here we use the normalized difference vegetation index (NDVI) to quantify the activity of vegetation by Theil–Sen median trend analysis and the Mann–Kendall test, Pearson correlation analysis and Boosted regression trees (BRT) model. Results show that about 34% of the global continent area has experienced greening in the grid annual NDVI from 1982 to 2015. The major greening areas were observed in the Sahel, European, India and south China. Only 10% of the global continent land areas were browning, and these were observed in Canada, South America, central Africa and Central Asia. BRT model shows that rainfall is the most important factor affecting vegetation evolution (63.1%), followed by temperature (15%), land cover change (8.6%), population (6.5%), elevation (6.4%) and nightlight (0.4%). It’s about 21% of the world’s continent were affected by rainfall, mainly in arid regions such as central Asia and Australia. The main temperature-affected areas accounted for 36%, located near the equator or in high latitudes.

Spatiotemporal Variability of Asymmetric Daytime and Night-Time Warming and Its Effects on Vegetation in the Yellow River Basin from 1982 to 2015

Temperatures from 1982 to 2015 have exhibited an asymmetric warming pattern between day and night throughout the Yellow River Basin. The response to this asymmetric warming can be linked to vegetation growth as quantified by the NDVI (Normalized Difference Vegetation Index). In this study, the time series trends of the maximum temperature (T_max) and the minimum temperature (T_min) and their spatial patterns in the growing season (April-October) of the Yellow River Basin from 1982 to 2015 were analyzed. We evaluated how vegetation NDVI had responded to daytime and night-time warming, based on NDVI and meteorological parameters (precipitation and temperature) over the period 1982-2015. We found: (1) a persistent increase in the growing season T_max and T_min in 1982-2015 as confirmed by using the Mann-Kendall (M-K) non-parametric test method (p < 0.01), where the rate of increase of T_min was 1.25 times that of T_max, and thus the diurnal warming was asymmetric during 1982-2015; (2) the partial correlation between T_max and NDVI was significantly positive only for cultivated plants, shrubs, and desert, which means daytime warming may increase arid and semi-arid vegetation's growth and coverage, and cultivated plants' growth and yield. The partial correlation between T_min and NDVI of all vegetation types except broadleaf forest is very significant (p < 0.01) and, therefore, it has more impacts vegetation across the whole basin. This study demonstrates a methodogy for studying regional responses of vegetation to climate extremes under global climate change.

China and India lead in greening of the world through land-use management

Satellite data show increasing leaf area of vegetation due to direct (human land-use management) and indirect factors (climate change, CO2 fertilization, nitrogen deposition, recovery from natural disturbances, etc.). Among these, climate change and CO2 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.

A 110-year pollen record of land use and land cover changes in an anthropogenic watershed landscape, eastern China: Understanding past human-environment interactions

Land use and land cover changes (LUCCs) have largely altered terrestrial ecosystems and landscapes during the Anthropocene. Reconstructing past LUCCs is necessary to better understand terrestrial ecosystem succession and human-environment interactions so that ecosystem services can be used conservatively and developed sustainably. In this paper, we reconstructed the LUCCs over the past century in a typical anthropogenic watershed based on a high-resolution pollen record from Changdang Lake, eastern China. The sediment core was ²¹⁰Pb dated and constrained cluster analysis identified different periods of LUCCs associated with the 110-year pollen record. Multi-sedimentary proxies, historical records, and remote sensing LUCC maps were analyzed to complement the palynological results. Our results demonstrate that pollen records can accurately capture LUCCs during different historical periods. Extra-regional arboreal pollen, fern spores, and pollen concentration can record the hydrological variations of waterbodies under both climatic and anthropogenic impacts. Multiple agriculture-related pollen indicators, such as cereal, Cruciferae, and wetland taxa are significantly related to the corresponding vegetation cover and landscape variations. Specifically, the anthropochore taxa to wetland taxa ratio is a good indicator of agricultural intensity. Dominant arboreal pollen (Pinus and Quercus) and the arboreal taxa to non-arboreal taxa ratio reflects the forestry landscape changes. Urban greening arboreal pollen (including Platanus, Salix, and Ulmus) is found to be an indirect indicator of urbanization. In addition, agriculture and urbanization in the region are causing the pollen diversity to increase in lake sediments. This study from a shallow lake in eastern China contributes to our understanding of pollen-based LUCC studies in similar climatic and anthropogenic regions around the world.

Have Synergies Between Nitrogen Deposition and Atmospheric CO2 Driven the Recent Enhancement of the Terrestrial Carbon Sink?

The terrestrial carbon sink has increased since the turn of this century at a time of increased fossil fuel burning, yet the mechanisms enhancing this sink are not fully understood. Here we assess the hypothesis that regional increases in nitrogen deposition since the early 2000s has alleviated nitrogen limitation and worked in tandem with enhanced CO2 fertilization to increase ecosystem productivity and carbon sequestration, providing a causal link between the parallel increases in emissions and the global land carbon sink. We use the Community Land Model (CLM4.5-BGC) to estimate the influence of changes in atmospheric CO2, nitrogen deposition, climate, and their interactions to changes in net primary production and net biome production. We focus on two periods, 1901-2016 and 1990-2016, to estimate changes in land carbon fluxes relative to historical and contemporary baselines, respectively. We find that over the historical period, nitrogen deposition (14%) and carbon-nitrogen synergy (14%) were significant contributors to the current terrestrial carbon sink, suggesting that long-term increases in nitrogen deposition led to a substantial increase in CO2 fertilization. However, relative to the contemporary baseline, changes in nitrogen deposition and carbon-nitrogen synergy had no substantial contribution to the 21st century increase in global carbon uptake. Nonetheless, we find that increased nitrogen deposition in East Asia since the early 1990s contributed 50% to the overall increase in net biome production over this region, highlighting the importance of carbon-nitrogen interactions. Therefore, potential large-scale changes in nitrogen deposition could have a significant impact on terrestrial carbon cycling and future climate.

Spatial and Temporal Variation of Drought Based on Satellite Derived Vegetation Condition Index in Nepal from 1982⁻2015

Identification of drought is essential for many environmental and agricultural applications. To further understand drought, this study presented spatial and temporal variations of drought based on satellite derived Vegetation Condition Index (VCI) on annual (Jan⁻Dec), seasonal monsoon (Jun⁻Nov) and pre-monsoon (Mar⁻May) scales from 1982⁻2015 in Nepal. The Vegetation Condition Index (VCI) obtained from NOAA, AVHRR (National Oceanic and Atmospheric Administration, Advanced Very High Resolution Radiometer) and climate data from meteorological stations were used. VCI was used to grade the drought, and the Mann⁻Kendall test and linear trend analysis were conducted to examine drought trends and the Pearson correlation between VCI and climatic factors (i.e., temperature and precipitation) was also acquired. The results identified that severe drought was identified in 1982, 1984, 1985 and 2000 on all time scales. However, VCI has increased at the rate of 1.14 yr^-1 (p = 0.04), 1.31 yr^-1 (p = 0.03) and 0.77 yr^-1 (p = 0.77) on the annual, seasonal monsoon and pre-monsoon scales, respectively. These increased VCIs indicated decreases in drought. However, spatially, increased trends of drought were also found in some regions in Nepal. For instance, northern areas mainly in the Trans-Himalayan regions identified severe drought. The foothills and the lowlands of Terai (southern Nepal) experienced normal VCI, i.e., no drought. Similarly, the Anomaly Vegetation Condition Index (AVCI) was mostly negative before 2000 which indicated deficient soil moisture. The exceedance probability analysis results on the annual time scale showed that there was a 20% chance of occurring severe drought (VCI ≤ 35%) and a 35% chance of occurring normal drought (35% ≤ VCI ≤ 50%) in Nepal. Drought was also linked with climates in which temperature on the annual and seasonal monsoon scales was significant and positively correlated with VCI. Drought occurrence and trends in Nepal need to be further studied for comprehensive information and understanding.

Seasonal Divergent Tree Growth Trends and Growth Variability along Drought Gradient over Northeastern China

With the increasing temperature and intensified drought, global climate change has profound impacts on tree growth in temperate regions, which consequently regulates terrestrial-atmosphere biogeochemical processes and biophysical feedbacks. Thus, increasing numbers of studies have addressed the long-term annual trends in tree growth and their response to climate change at diverse spatial scales. However, the potential divergence in tree growth trends and growth variability (represented by coefficient of variance) in different seasons across large-scale climate gradients remains poorly understood. Here, we investigated the tree growth trends and growth variability in different seasons across diverse drought conditions in forested regions over northeastern China during the period 1982–2015, using both remote sensing observations and in situ tree-ring measurements. We found clear seasonal divergence in tree growth trends during 1982–2015, and the apparent increase was mainly observed in spring and autumn, attributed mainly to the increase in spring temperature and autumn solar radiation, respectively, but not in summer. The magnitudes of increasing trends in tree growth decrease with the increase of the multi-year average dryness index (MAI) in semi-arid areas (1.5 < MAI < 4.0) in all seasons. We further revealed that the interannual variability in tree growth was much larger in the semi-arid regions than in the humid and semi-humid regions in all seasons, and tree growth variability was significantly and negatively correlated with the variations in temperature and water deficit. Our findings improve our understanding of seasonal divergence in tree growth trends and provide new insights into spatial patterns in forest vulnerability in a warmer and drier climate.

Influences of vertical differences in population emigration on mountainous vegetation greenness: A case study in the Taihang Mountains

With the rapid advance of urbanization, rural population emigration has become a key factor that affects the man-land relationship in China's mountainous areas and may have a huge impact on ecological restoration. This study used the NDVI in the growing seasons to analyze the variation trend of vegetation greenness at different elevations in the Taihang Mountains during 2000-2010, employing trend analysis method. Then, we selected 990 samples, each of which was a circular area with a radius of 3 km. On this basis, we quantitatively analyzed the contribution degree of population emigration to this variation trend after eliminating the influences of precipitation, temperature, and other factors. The results showed that rural population emigration was significant in the Taihang Mountains in the past 10 years, with a rural population emigration rate of up to 16.3%; The vegetation in the Taihang Mountains presented a trend of overall improvement, but local deterioration; The results of the regression analysis showed that population emigration had significantly impacts on vegetation greenness at 1% significance level and 1% of population emigration can increase the NDVI variation trend by 0.06%. Furthermore, the impact gradually weakened with increasing elevation.

Acceleration of global vegetation greenup from combined effects of climate change and human land management

Global warming and human land management have greatly influenced vegetation growth through both changes in spring phenology and photosynthetic primary production. This will presumably impact the velocity of vegetation greenup (Vgreenup, the daily rate of changes in vegetation productivity during greenup period), yet little is currently known about the spatio-temporal patterns of Vgreenup of global vegetation. Here, we define Vgreenup as the ratio of the amplitude of greenup (Agreenup) to the duration of greenup (Dgreenup) and derive global Vgreenup from 34-year satellite leaf area index (LAI) observations to study spatio-temporal dynamics of Vgreenup at the global, hemispheric, and ecosystem scales. We find that 19.9% of the pixels analyzed (n = 1,175,453) experienced significant trends toward higher greenup rates by an average of 0.018 m²  m^-2  day^-1 for 1982-2015 as compared to 8.6% of pixels with significant negative trends (p < 0.05). Global distribution and dynamics of Vgreenup show high spatial heterogeneity and ecosystem-specific patterns, which is primarily determined by the high spatial variation in Agreenup, while the temporal dynamics of Vgreenup are directly controlled by both changes in Dgreenup and Agreenup. Areas with the largest Vgreenup and largest positive trends are both observed in deciduous and mixed forests as compared to nonforest ecosystems showing both lower Vgreenup and trends. For nonforest ecosystems, human-managed ecosystems (e.g., rangelands and rainfed croplands) exhibited higher Vgreenup and positive trends than those of natural counterparts, suggesting strong imprints of human land management on terrestrial ecosystem functioning. Globally, warming has accelerated Vgreenup in temperature-constrained high latitude forest ecosystems and arctic regions, but decelerated Vgreenup in temperate and arid/semiarid areas. These results suggest that the combined effects of climate change and human land management have greatly accelerated global vegetation greenup, with important implications for changes in terrestrial ecosystem functioning and global carbon cycling.

Spatiotemporal Patterns of Vegetation Greenness Change and Associated Climatic and Anthropogenic Drivers on the Tibetan Plateau during 2000–2015

Alpine vegetation on the Tibetan Plateau (TP) is known to be sensitive to both climate change and anthropogenic disturbance. However, the magnitude and patterns of alpine vegetation dynamics and the driving mechanisms behind their variation on the TP remains under debate. In this study, we used updated MODIS Collection 6 Normalized Difference Vegetation Index (NDVI) from the Terra satellite combined with linear regression and the Break for Additive Season and Trend model to reanalyze the spatiotemporal patterns of vegetation change on the TP during 2000–2015. We then quantified the responses of vegetation variation to climatic and anthropogenic factors by coupling climatic and human footprint datasets. Results show that growing season NDVI (GNDVI) values increased significantly overall (0.0011 year−1, p < 0.01) during 2000–2015 and that 70.37% of vegetated area on the TP (23.47% significantly with p < 0.05) exhibited greening trends with the exception of the southwest TP. However, vegetation greenness experienced trend shifts from greening to browning in half of the ecosystem zones occurred around 2010, likely induced by spatially heterogeneous temporal trends of climate variables. The vegetation changes in the northeastern and southwestern TP were water limited, the mid-eastern TP exhibited strong temperature responses, and the south of TP was driven by a combination of temperature and solar radiation. Furthermore, we found that, to some extent, anthropogenic disturbances offset climate-driven vegetation greening and aggravated vegetation browning induced by water deficit. These findings suggest that the impact of anthropogenic activities on vegetation change might not overwhelm that of climate change at the region scale.

Future biomass carbon sequestration capacity of Chinese forests

Chinese forests, characterized by relatively young stand age, represent a significant biomass carbon (C) sink over the past several decades. Nevertheless, it is unclear how forest biomass C sequestration capacity in China will evolve as forest age, climate and atmospheric CO₂ concentration change continuously. Here, we present a semi-empirical model that incorporates forest age and climatic factors for each forest type to estimate the effects of forest age and climate change on total forest biomass, under three different scenarios based on the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We estimate that age-related forest biomass C sequestration to be 6.69 Pg C (∼0.17 Pg C a^-1) from the 2000s to the 2040s. Climate change induces a rather weak increase in total forest biomass C sequestration (0.52-0.60 Pg C by the 2040s). We show that rising CO₂ concentrations could further increase the total forest biomass C sequestration by 1.68-3.12 Pg C in the 2040s across all three scenarios. Overall, the total forest biomass in China would increase by 8.89-10.37 Pg C by the end of 2040s. Our findings highlight the benefits of Chinese afforestation programs, continued climate change and increasing CO₂ concentration in sustaining the forest biomass C sink in the near future, and could therefore be useful for designing more realistic climate change mitigation policies such as continuous forestation programs and careful choice of tree species.

The impact of drought on vegetation conditions within the Damqu River Basin, Yangtze River Source Region, China

Drought and vegetation conditions within the Damqu River Basin, part of the Yangtze River Source Region (YRSR), are assessed here using the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the normalized difference vegetation index (NDVI), and the leaf area index (LAI). We utilized Sen’s method, least squares regression method, linear regression and Pearson’s correlation analysis to study variations in drought and vegetation indices and the drought effect on vegetation between 1988 and 2015. Results reveal that droughts occurred at a 25% frequency over this period; SPI and SPEI analyses show that 1994, 1999, 2005, and 2010 were change points and that the basin was characterized by varying drought and humidity trends. Subsequent to 2010, both SPI and SPEI decreased within the basin, while 1995, 2000, 2004, and 2010 were change points for NDVI and LAI while the watershed exhibited variable trends in vegetation reduction and increase. The NDVI-annual values of 63.36% regions and the LAI-summer values of 68.39% areas within the basin were decreased during 1988–2015 and 2000–2015, respectively. Subsequent to 2010, both NDVI and LAI decreased within the basin and significant positive correlations at inter-annual and inter-summer time scales were seen in both drought and vegetation indices; drought has exerted a lag effect on vegetation as shown by significant positive correlations between annual SPI/SPEI values and following year NDVI/LAI values.

Greening and Browning of the Hexi Corridor in Northwest China: Spatial Patterns and Responses to Climatic Variability and Anthropogenic Drivers

The arid region of northwest China provides a unique terrestrial ecosystem to identify the response of vegetation activities to natural and anthropogenic changes. To reveal the influences of climate and anthropogenic factors on vegetation, the Normalized Difference Vegetation Index (NDVI), climate data, and land use and land cover change (LUCC) maps were used for this study. We analyzed the spatiotemporal change of NDVI during 2000–2015. A partial correlation analysis suggested that the contribution of precipitation (PRE) and temperature (TEM) on 95.43% of observed greening trends was 47% and 20%, respectively. The response of NDVI in the eastern section of the Qilian Mountains (ESQM) and the western section of the Qilian Mountains (WSQM) to PRE and TEM showed opposite trends. The multiple linear regressions used to quantify the contribution of anthropogenic activity on the NDVI trend indicated that the ESQM and oasis areas were mainly affected by anthropogenic activities (26%). The observed browning trend in the ESQM was attributed to excessive consumption of natural resources. A buffer analysis and piecewise regression methods were further applied to explore the influence of urbanization on NDVI and its change rate. The study demonstrated that urbanization destroys the vegetation cover within the developed city areas and extends about 4 km beyond the perimeter of urban areas and the NDVI of buffer cities (counties) in the range of 0–4 km (0–3 km) increased significantly. In the range of 5–15 (4–10) km (except for Jiayuguan), climate factors were the major drivers of a slight downtrend in the NDVI. The relationship of land use change and NDVI trends showed that construction land, urban settlement, and farmland expanded sharply by 171.43%, 60%, and 10.41%, respectively. It indicated that the rapid process of urbanization and coordinated urban-rural development shrunk ecosystem services.

Global land change from 1982 to 2016

Land change is a cause and consequence of global environmental change1,2. Changes in land use and land cover considerably alter the Earth's energy balance and biogeochemical cycles, which contributes to climate change and-in turn-affects land surface properties and the provision of ecosystem services1-4. However, quantification of global land change is lacking. Here we analyse 35 years' worth of satellite data and provide a comprehensive record of global land-change dynamics during the period 1982-2016. We show that-contrary to the prevailing view that forest area has declined globally5-tree cover has increased by 2.24 million km2 (+7.1% relative to the 1982 level). This overall net gain is the result of a net loss in the tropics being outweighed by a net gain in the extratropics. Global bare ground cover has decreased by 1.16 million km2 (-3.1%), most notably in agricultural regions in Asia. Of all land changes, 60% are associated with direct human activities and 40% with indirect drivers such as climate change. Land-use change exhibits regional dominance, including tropical deforestation and agricultural expansion, temperate reforestation or afforestation, cropland intensification and urbanization. Consistently across all climate domains, montane systems have gained tree cover and many arid and semi-arid ecosystems have lost vegetation cover. The mapped land changes and the driver attributions reflect a human-dominated Earth system. The dataset we developed may be used to improve the modelling of land-use changes, biogeochemical cycles and vegetation-climate interactions to advance our understanding of global environmental change1-4,6.

Association analysis between spatiotemporal variation of vegetation greenness and precipitation/temperature in the Yangtze River Basin (China)

The variation in vegetation greenness provides good understanding of the sustainable management and monitoring of land surface ecosystems. The present paper discusses the spatial-temporal changes in vegetation and controlling factors in the Yangtze River Basin (YRB) using Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI) for the period 2001-2013. Theil-Sen Median trend analysis, Pearson correlation coefficients, and residual analysis have been used, which shows decreasing trend of the annual mean NDVI over the whole YRB. Spatially, the regions with significant decreasing trends were mainly located in parts of central YRB, and pronounced increasing trends were observed in parts of the eastern and western YRB. The mean NDVI during spring and summer seasons increased, while it decreased during autumn and winter seasons. The seasonal mean NDVI shows spatial heterogeneity due to the vegetation types. The correlation analysis shows a positive relation between NDVI and temperature over most of the YRB, whereas NDVI and precipitation show a negative correlation. The residual analysis shows an increase in NDVI in parts of eastern and western YRB and the decrease in NDVI in the small part of Yangtze River Delta (YRD) and the mid-western YRB due to human activities. In general, climate factors were the principal drivers of NDVI variation in YRB in recent years.

Divergent hydrological response to large-scale afforestation and vegetation greening in China

China has experienced substantial changes in vegetation cover, with a 10% increase in the leaf area index and an ~41.5 million-hectare increase in forest area since the 1980s. Earlier studies have suggested that increases in leaf area and tree cover have led to a decline in soil moisture and runoff due to increased evapotranspiration (ET), especially in dry regions of China. However, those studies often ignored precipitation responses to vegetation increases, which could offset some of the negative impact on soil moisture by increased ET. We investigated 30-year vegetation impacts on regional hydrology by allowing for vegetation-induced changes in precipitation using a coupled land-atmosphere global climate model, with a higher spatial resolution zoomed grid over China. We found high spatial heterogeneity in the vegetation impacts on key hydrological variables across China. In North and Southeast China, the increased precipitation from vegetation greening and the increased forest area, although statistically insignificant, supplied enough water to cancel out enhanced ET, resulting in weak impact on soil moisture. In Southwest China, however, the increase in vegetation cover significantly reduced soil moisture while precipitation was suppressed by the weakened summer monsoon. In Northeast China, the only area where forest cover declined, soil moisture was significantly reduced, by -8.1 mm decade^-1, likely because of an intensified anticyclonic circulation anomaly during summer. These results suggest that offline model simulations can overestimate the increase of soil dryness in response to afforestation in North China, if vegetation feedbacks lead to increased precipitation like in our study.

Detection and attribution of nitrogen runoff trend in China's croplands

Reliable detection and attribution of changes in nitrogen (N) runoff from croplands are essential for designing efficient, sustainable N management strategies for future. Despite the recognition that excess N runoff poses a risk of aquatic eutrophication, large-scale, spatially detailed N runoff trends and their drivers remain poorly understood in China. Based on data comprising 535 site-years from 100 sites across China's croplands, we developed a data-driven upscaling model and a new simplified attribution approach to detect and attribute N runoff trends during the period of 1990-2012. Our results show that N runoff has increased by 46% for rice paddy fields and 31% for upland areas since 1990. However, we acknowledge that the upscaling model is subject to large uncertainties (20% and 40% as coefficient of variation of N runoff, respectively). At national scale, increased fertilizer application was identified as the most likely driver of the N runoff trend, while decreased irrigation levels offset to some extent the impact of fertilization increases. In southern China, the increasing trend of upland N runoff can be attributed to the growth in N runoff rates. Our results suggested that increased SOM led to the N runoff rate growth for uplands, but led to a decline for rice paddy fields. In combination, these results imply that improving management approaches for both N fertilizer use and irrigation is urgently required for mitigating agricultural N runoff in China.

Response of ecosystem functions to climate change and implications for sustainable development on the Inner Mongolian Plateau

The responses of ecosystem functions in Inner Mongolian grasslands to climate change have implications for ecosystem services and sustainable development. Research published in two previous Special Issues of The Rangeland Journal shows that recent climate change added to overgrazing and other factors caused increased degradation of Inner Mongolian rangelands whereas on the Qinghai-Tibetan Plateau, climate change tended to ameliorate the impacts of overgrazing. Recent climate change on the Mongolian Plateau involved warming with increasingly variable annual precipitation and decreased summer rainfall. Future climate projections are different, involving modest increases in precipitation and further climate warming. Research published in the current Special Issue shows that precipitation is the climate factor that has the most substantial impact on ecosystem functions in this region and is positively correlated with plant species diversity, ecosystem carbon exchange and Normalised Difference Vegetation Index. Increased flows of provisioning and regulating ecosystem services are expected with future climate change indicating that its impacts will be positive in this region. However, spatial heterogeneity in the environments and climates of Inner Mongolia highlights the risk of over-generalising from local-scale studies and indicates the value of increased attention to meta-analysis and regional scale models. The enhanced flows of ecosystem services from climate change may support sustainable development by promoting recovery of degraded grasslands with flow-on benefits for livelihoods and the regional economy. However, realising these potential benefits will depend on sound landscape management and addressing the risk of herders increasing livestock numbers to take advantage of the extra forage available. Investment in education is important to improve local capacity to adapt rangeland management to climate change, as are policies and strategies that integrate social, economic and ecological considerations and are tailored to specific regions. Gaps in understanding that could be addressed through further research on ecosystem functions include; belowground carbon exchange processes; the impact of increased variability in precipitation; and the impact of different management practices under changed climates.

Moisture-induced greening of the South Asia over the past three decades

South Asia experienced a weakening of summer monsoon circulation in the past several decades, resulting in rainfall decline in wet regions. In comparison with other tropical ecosystems, quantitative assessments of the extent and triggers of vegetation change are lacking in assessing climate-change impacts over South Asia dominated by crops. Here, we use satellite-based Normalized Difference Vegetation Index (NDVI) to quantify spatial-temporal changes in vegetation greenness, and find a widespread annual greening trend that stands in contrast to the weakening of summer monsoon circulation particularly over the last decade. We further show that moisture supply is the primary factor limiting vegetation activity during dry season or in dry region, and cloud cover or temperature would become increasingly important in wet region. Enhanced moisture conditions over dry region, coinciding with the decline in monsoon, are mainly responsible for the widespread greening trend. This result thereby cautions the use of a unified monsoon index to predict South Asia's vegetation dynamics. Current climate-carbon models in general correctly reproduce the dominant control of moisture in the temporal characteristics of vegetation productivity. But the model ensemble cannot exactly reproduce the spatial pattern of satellite-based vegetation change mainly because of biases in climate simulations. The moisture-induced greening over South Asia, which is likely to persist into the wetter future, has significant implications for regional carbon cycling and maintaining food security.

Attribution of seasonal leaf area index trends in the northern latitudes with "optimally" integrated ecosystem models

Significant increases in remotely sensed vegetation indices in the northern latitudes since the 1980s have been detected and attributed at annual and growing season scales. However, we presently lack a systematic understanding of how vegetation responds to asymmetric seasonal environmental changes. In this study, we first investigated trends in the seasonal mean leaf area index (LAI) at northern latitudes (north of 30°N) between 1982 and 2009 using three remotely sensed long-term LAI data sets. The most significant LAI increases occurred in summer (0.009 m²  m^-2  year^-1 , p < .01), followed by autumn (0.005 m²  m^-2  year^-1 , p < .01) and spring (0.003 m² m^-2  year^-1 , p < .01). We then quantified the contribution of elevating atmospheric CO₂ concentration (eCO₂ ), climate change, nitrogen deposition, and land cover change to seasonal LAI increases based on factorial simulations from 10 state-of-the-art ecosystem models. Unlike previous studies that used multimodel ensemble mean (MME), we used the Bayesian model averaging (BMA) to optimize the integration of model ensemble. The optimally integrated ensemble LAI changes are significantly closer to the observed seasonal LAI changes than the traditional MME results. The BMA factorial simulations suggest that eCO₂ provides the greatest contribution to increasing LAI trends in all seasons (0.003-0.007 m²  m^-2  year^-1 ), and is the main factor driving asymmetric seasonal LAI trends. Climate change controls the spatial pattern of seasonal LAI trends and dominates the increase in seasonal LAI in the northern high latitudes. The effects of nitrogen deposition and land use change are relatively small in all seasons (around 0.0002 m²  m^-2  year^-1 and 0.0001-0.001 m²  m^-2  year^-1 , respectively). Our analysis of the seasonal LAI responses to the interactions between seasonal changes in environmental factors offers a new perspective on the response of global vegetation to environmental changes.

Inconsistencies of interannual variability and trends in long-term satellite leaf area index products

Understanding the long-term performance of global satellite leaf area index (LAI) products is important for global change research. However, few effort has been devoted to evaluating the long-term time-series consistencies of LAI products. This study compared four long-term LAI products (GLASS, GLOBMAP, LAI3g, and TCDR) in terms of trends, interannual variabilities, and uncertainty variations from 1982 through 2011. This study also used four ancillary LAI products (GEOV1, MERIS, MODIS C5, and MODIS C6) from 2003 through 2011 to help clarify the performances of the four long-term LAI products. In general, there were marked discrepancies between the four long-term LAI products. During the pre-MODIS period (1982-1999), both linear trends and interannual variabilities of global mean LAI followed the order GLASS>LAI3g>TCDR>GLOBMAP. The GLASS linear trend and interannual variability were almost 4.5 times those of GLOBMAP. During the overlap period (2003-2011), GLASS and GLOBMAP exhibited a decreasing trend, TCDR no trend, and LAI3g an increasing trend. GEOV1, MERIS, and MODIS C6 also exhibited an increasing trend, but to a much smaller extent than that from LAI3g. During both periods, the R² of detrended anomalies between the four long-term LAI products was smaller than 0.4 for most regions. Interannual variabilities of the four long-term LAI products were considerably different over the two periods, and the differences followed the order GLASS>LAI3g>TCDR>GLOBMAP. Uncertainty variations quantified by a collocation error model followed the same order. Our results indicate that the four long-term LAI products were neither intraconsistent over time nor interconsistent with each other. These inconsistencies may be due to NOAA satellite orbit changes and MODIS sensor degradation. Caution should be used in the interpretation of global changes derived from the four long-term LAI products.

Inconsistent estimates of forest cover change in China between 2000 and 2013 from multiple datasets: differences in parameters, spatial resolution, and definitions

The Chinese National Forest Inventory (NFI) has reported increased forest coverage in China since 2000, however, the new satellite-based dataset Global Forest Change (GFC) finds decreased forest coverage. In this study, four satellite datasets are used to investigate this discrepancy in forest cover change estimates in China between 2000 and 2013: forest cover change estimated from MODIS Normalized Burn Ratio (NBR), existing MODIS Land Cover (LC) and Vegetation Continuous Fields (VCF) products, and the Landsat-based GFC. Among these satellite datasets, forest loss shows much better agreement in terms of total change area and spatial pattern than do forest gain. The net changes in forest cover as a proportion of China's land area varied widely from increases of 1.56% in NBR, 1.93% in VCF, and 3.40% in LC to a decline of -0.40% in GFC. The magnitude of net forest increase derived from MODIS datasets (1.56-3.40%) is lower than that reported in NFI (3.41%). Algorithm parameters, different spatial resolutions, and inconsistent forest definitions could be important sources of the discrepancies. Although several MODIS datasets support an overall forest increase in China, the direction and magnitude of net forest change is still unknown due to the large uncertainties in satellite-derived estimates.

Separating Vegetation Greening and Climate Change Controls on Evapotranspiration trend over the Loess Plateau

Evapotranspiration (ET) is a key ecological process connecting the soil-vegetation-atmosphere system, and its changes seriously affects the regional distribution of available water resources, especially in the arid and semiarid regions. With the Grain-for-Green project implemented in the Loess Plateau (LP) since 1999, water and heat distribution across the region have experienced great changes. Here, we investigate the changes and associated driving forces of ET in the LP from 2000 to 2012 using a remote sensing-based evapotranspiration model. Results show that annual ET significantly increased by 3.4 mm per year (p = 0.05) with large interannual fluctuations during the study period. This trend is higher than coincident increases in precipitation (2.0 mm yr⁻²), implying a possible pressure of water availability. The correlation analysis showed that vegetation change is the major controlling factor on interannual variability of annual ET with ~52.8% of pixels scattered in the strip region from the northeastern to southwestern parts of the LP. Further factorial analysis suggested that vegetation greening is the primary driver of the rises of ET over the study period relative to climate change. Our study can provide an improved understanding of the effects of vegetation and climate change on terrestrial ecosystem ET in the LP.