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Abstract Fire events in South America are becoming more extensive and frequent as climate extremes and human pressures increase, and even repeatedly occurring in some areas within decades. However, the relationship between recurring fires and vegetation dynamics remains unclear. Here, we extracted the number of fire occurrences using burned area satellite product and analysed the relationship between recurring fires and vegetation dynamics with remote sensing land use and vegetation index datasets in South America. We show that approximately 1.39 × 106 km2 of burnt area has experienced recurring fires during 2001–2020. More than half of burnt area of recurring fires occurred in savannahs with remaining burnt area in grasslands, forests and croplands. Although forests tended to be less susceptible to recurring fires among all vegetation types, their coverage loss with recurring fires was the greatest. The greater proportion of forest conversion to croplands concurred with more recurring fires. Conversely, the coverage of croplands and grasslands gained the most with recurring fires. In the areas without vegetation conversion, more frequent recurring fires further suppressed canopy greenness and density, even in fire‐adapted savannahs and grasslands. Our results suggest that recurring fires and land use change are generally coincident, reflecting the intense pressure of human activities on natural vegetation in South America. Thus, coordinated efforts on vegetation conservation and sustainable management of human‐induced burning in the region are urgently needed.

Abstract Permafrost ecosystems in high‐latitudes stock a large amount of carbon and are vulnerable to wildfires under climate warming. However, major knowledge gap remains in the effects of direct carbon loss from increasing wildfire biomass burning on permafrost ecosystem carbon sink. In this study, we used observation‐derived data sets and Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations to investigate how carbon emissions from wildfire biomass burning offset permafrost ecosystem carbon sink under climate warming in the 21st century. We show that the fraction of permafrost ecosystem carbon sink offset by wildfire emissions was 14%–25% during the past two decades. The fraction is projected to be 28%–45% at the end of this century under different warming scenarios. The weakening carbon sink is caused by greater increase in wildfire emissions than net ecosystem production in permafrost regions under climate warming. The increased fraction of ecosystem carbon sink offset by wildfire carbon loss is especially pronounced in continuous permafrost region during the past two decades. Although uncertainties exist in simulations of wildfire emissions and ecosystem carbon budget, results from different models still show that wildfire emissions offset more permafrost ecosystem carbon sink in the 21st century. These findings highlight that carbon sink capacity of permafrost ecosystems is increasingly threatened by wildfires under the warming climate.

A thermal infrared spectrometer is an important sensor onboard the SDGSAT-1 dedicated to serving the 2030 Agenda for Sustainable Development of the United Nations. Field campaigns were conducted from January to December 2022 to evaluate its radiometric calibrations. A radiance-based calibration method was used to derive the spectral radiance of the lake surface around the satellite overpass using a boat-deployed TIR spectrometer or radiometer. The radiometric calibration conditions were quantified by examining the temperature bias between the satellite-based brightness temperature and the predicted at-sensor brightness temperature. Our results indicated that the average brightness temperature bias reached 0.772 K, −1.032 K, and −0.300 K, with RMSEs of 1.00, 1.10, and 0.43 K in bands 1, 2 and 3, respectively. Eighty percent of the field experiments achieved a high calibration accuracy with temperature biases of less than 1 K, and the calibration accuracy of band 3 was better than that of other bands. Atmospheric conditions and surface characterization play important roles in determining the calibration accuracy through surface observations and atmospheric transfer simulations. With the increasing need for SDGSAT-1 products, periodic field experiments are needed to monitor and improve the operational radiometric calibration of satellite instruments to create high-resolution and reasonable scientific datasets.

The warming world greatly suffers the increase of frequency, severity and duration of heat wave events, which would cause the significant societal and environmental damages and implications from local to global scales. In order to eliminate the limitations of site observations in accurate spatial extent identification and large scale monitoring, this study tried to investigate global heat waves in 2018 using spatial datasets of land surface temperature (LST) derived from AQUA TIR sensors. A 15-year daily maximum LST dataset was used to identify the hot days and heat wave events using the relative threshold method based on the probability density function analysis of LST sequences, then they were adopted in analyzing spatial patterns of duration, frequency and intensity of heat wave events using heat wave numbers (HWN), the frequency of the appeared heat wave days (HWF) and the amplitude of heat wave impacts (HWA) indices, respectively. Our results indicated that more heat wave events and longer heat wave duration happened in low and middle latitudes under the warmer land surface in 2018 than last decade, especially many heat wave events occurred in the environmentally fragile regions and the dense population area. Urban regions achieved the largest HWA by 45.5 ± 6.9℃. Both annual HWF and HWN highlighted seven hot spot regions influenced by heat waves, and most of them distributed around the latitude 30°N and the latitude 30°S. Extreme heat wave of hot spot regions in the Southern Hemisphere mainly happened in winter and spring in contrast to that in North Hemisphere appeared in summer and autumn. Dry climate could contribute to the occurrence of heat waves, and heat wave indices variations also implied the compound consequences between heat waves and drought. Our findings demonstrate that remote sensing datasets are capable of providing the continuous whole-Earth coverage of heat wave changes, and they would play more important roles in preventing or mitigating the impacts of extreme heat events on people and natural environment.

The temperate deciduous broadleaf forests (DBFs) are widely distributed in middle and high latitudes and play vital role in providing ecosystem services and mitigating human induced climate change, however, the responses of the carbon sink of DBFs to recent warming slowdown were not well known at regional scale. Here, we investigated the temporal pattern of carbon sink in DBFs and its drivers based on the eddy covariance carbon flux observations at 15 FLUXNET sites from 1997 to 2014. The annual mean net ecosystem production (NEP) was 272 ± 43 g C m−2 yr−1 during 1997–2005 and it increased to 445 ± 13 g C m−2 yr−1 during 2006–2014, as a result of boosted gross primary production (GPP) and weakened ecosystem respiration, respectively. We found slowdown in trends of temperature and carbon sink enhancement during 2006–2014. The NEP decreased at the rate of −11.9 g C m−2 yr−1 during the warming slowdown period (2006–2014, p

With rising occurrence of heatwaves and ongoing urban expansion, urban residents are facing severer heat-related stress under the combined effects of urban heat island (UHI) and heatwaves. Controversial results, however, have been reported regarding whether the UHI is exacerbated during heatwaves. In this study, we used fused ground and satellite daily maximum air temperature data to evaluate the variation of UHI intensities under heatwaves across 225 major cities in mainland China during 2003–2020. Overall, urban areas showed an enhanced UHI intensity of up to 0.94 °C during heatwaves, nearly double compared to normal periods. The interaction between UHIs and heatwaves was sensitive to local background precipitation. Under the similar urbanization and vegetation greenness, the amplified warming in urban areas during heatwaves was more pronounced in wet climates. In megapolitan regions characterized by continuous urban development, the UHI intensified much stronger during heatwaves due to the heat accumulation within urbanized areas and the advection of heat from neighboring cities. Our results contribute to understanding the interactions between UHIs and heatwaves which may strongly increase heat risk in cities. Further work on the variations of this interaction under future warming and consequent impacts on human health and energy use is needed.

Abstract Global monsoon system is a major component of the Earth's climate system and carries about two‐thirds of the world's population. How large‐scale deforestation induced changes in water cycle and energy balance may modify global monsoon system and its underlying mechanisms are not well understood. Here, we use simulations of 11 models participating in the Land Use Model Intercomparison Project in the framework of the Coupled Model Intercomparison Project, phase 6 to study the response of global monsoon precipitation and atmospheric circulation to large‐scale deforestation. Global deforestation of about 38% induces annual precipitation reduction of about −15.01 mm yr−1 (Multi‐Model Ensemble) in global monsoon regions and −26.15 mm yr−1 in land monsoon regions. The precipitation reduction is particularly pronounced in the Northern Hemisphere Summer Monsoon (NHSM) regions with decreased precipitation by 16.83 mm in the summer monsoon season from May to September along with weakened circulation intensity. Deforestation causes asymmetrical temperature response in the northern high latitudes and Southern Hemisphere Tropics, leading to decreased hemispheric thermal contrast, which reduces the meridional pressure gradient and weakens the convergence of cross‐equatorial flows into the NHSM trough regions, thereby decreasing the NHSM circulation and precipitation intensity. The deforestation‐induced hemispheric temperature asymmetry also increases the northward cross‐equatorial atmosphere heat transport (c‐eq AHT) that drives southward shift of Intertropical Convergence Zone, which suppresses the NHSM precipitation. Our results show that the drying monsoon region in response to deforestation is fairly consistent among the models implying the adverse effects of large‐scale deforestation beyond the region of land use change.

This paper describes how a validated semi-empirical, but physiologically based, remote sensing model – Ensemble_all – was up-scaled using MODIS land surface temperature data (MOD11C2), enhanced vegetation indices (MOD13C1) and land-cover data (MCD12C1) to produce a global terrestrial ecosystem respiration data set (Reco) for January 2001–December 2010. The temporal resolution of this data set is 1 month, the spatial resolution is 0.05°, and the range is from 55°S to 65°N and 180°W to 180°E (crop and natural vegetation mosaic is not included). After cross-validating our data set using in-situ observations as well as Reco outputs from an empirical variable_Q10 model, a LPJ_S1 process model and a machine learning method model, we found that our data set performed well in detecting both temporal and spatial patterns in Reco’s simulation in most ecosystems across the world. This data set can be found at http://www.dx.doi.org/10.11922/sciencedb.934.

The Serengeti–Masai Mara Ecosystem (SMME) is an iconic ecological and biodiversity resource in East Africa with a spectacular great animal migration feature. Environmental shocks like droughts, floods, and land degradation threaten the SMME’s ecological functioning. However, the spatiotemporal ecosystem dynamics during climate extremes are inadequately examined. Here we quantified water availability and vegetation changes during extreme wet (EWE) and dry (EDE) events over the SMME for wet and dry seasons in 1982–2020. We derived extreme events from seasonal mean precipitation anomaly exceeding standard deviation and applied composite and correlation techniques to assess their dynamics with animal populations and migration prospects. Wet season EWE increases vegetative and moist conditions over southern SMME, suggesting elongating migrants’ occupancy compared to normal periods and delayed northward migration. Wet season EDE significantly suppresses these features, heightening ecosystem competition and survival threats, proposing an earlier northward migration. Dry season EWE increases vegetation and water availability over northern SMME, prompting the late southward migration. Dry season EDE significantly reduces vegetation and water availability over northern SMME, suggesting an early southward migration towards regions with more vegetation and increased water availability. The SMME also experiences multiple EDE occurring in consecutive seasons, prolonging dry conditions that aggregate wildlife survival threats. Notably, two EDE prevailed consecutively from the 1993 dry season to the 1994 wet season, coupled with a population decline of wildebeest (1.2–0.9 million), buffalo (40–20 thousand), and lion (1.3–0.9 thousand). We also note a reversal from more EDE to EWE during the study period. Prevalent EWE can lessen wet and vegetative conditions distribution gradient, which is imperative for the functioning of the SMME migratory ecosystem. Our study unveiled hotspot areas of extremes-driven ecosystem changes for the sustainable SMME migratory functioning essential for framing meaningful conservation management policies under climate change.

Wildfire is recognized as an increasing threat to the southern boreal forests and the permafrost beneath them, with less occurring over the cold continuous permafrost than before. However, we show that continuous permafrost was a major contribution to wildfire expansion in the pan-Arctic over the last two decades. The expansion rate of burned area over continuous permafrost was 0.9 Mha decade ^−1 , in contrast to a decreasing trend (−0.5 Mha decade ^−1 ) over the entire permafrost areas. Burned area has been rapidly growing in the north of the Arctic Circle in particular, where the total burned area in the major fire seasons during 2011–2020 nearly doubled that during 2001–2010. Wildfire expansion is closely linked to an increased soil moisture deficit, considering wildfires there combust more than 90% of belowground fuel. Continuous permafrost experiences more severe fire-induced degradation. Active layer thickening following wildfires over continuous permafrost lasts more than three decades to reach a maximum of more than triple the pre-fire thickness. These new findings highlight the massive expansion of wildfires over continuous permafrost, which can dramatically modify ecological processes, disturb organic carbon stock, and thus accelerate the positive feedback between permafrost degradation and climate warming.

Understanding the spatially and temporally non-uniform water availability trends is key to assess changes of tropical and subtropical ecosystem productivity. However, their detailed spatial-temporal patterns and the relative role of local to the overall trend are not well known. This study provides a comprehensive investigation in characteristics of the time-varying water availability trend using the ensemble empirical mode decomposition (EEMD) method based on state-of-the-art satellite microwave observation derived microwave integrated drought index (MIDI) from 1998 to 2016. The results indicated an increased area with wetting trend since 1998, and the overall water availability reversed a drying tendency to a wetting trend around 2005. Also, the Northern Hemisphere became wetter and the Southern Hemisphere became dryer in 2016, demonstrating a transformation of favorable climate from the Southern Hemisphere to the Northern Hemisphere. Spatial patterns of the trend shape determined spatial distributions of the trend contributions, showing an opposite contribution between subtropics and tropics. Additionally, tropical rainforests and shrublands governed the overall trend reversely. This analysis helps to understand the non-uniform patterns of water availability trend and related ecosystem productivity over tropics and subtropics.

Deforestation-induced landscape fragmentation causes habitat loss and isolation, modifies local climate, and therefore threatens biodiversity. While, on the contrary, how large-scale reforestation may improve the connectivity and thermal buffers of habitats is not well understood. We show that decades long large-scale reforestation in China has effectively increased the size and connectivity of forest patches by gradually filling gaps among isolated patches and creating more core forests. The core forests have a stronger capacity to cool the land surface, leading to a daily mean cooling effect of −0.42 ± 0.23 °C relative to nearby marginal forests. Moreover, the core forests reduce diurnal range and seasonal variation of land surface temperature by 1.41 ± 0.23 °C and 0.42 ± 0.55 °C, respectively, relative to nearby marginal forests. The thermal buffering capacity of large size core forest (>100 km ^2 ) is more than twice that of small size (⩽10 km ^2 ). Despite their relatively low thermal buffering capacity, the marginal forests contribute about 73% to the increase of forest area in China during the last two decades and create buffer zones for the core forests to resist external disturbances, maintaining the internal stability of the forest ecosystem. We highlight that improving the integrity and connectivity of the forests with ecological restoration and succession can further enhance potential of forests to buffer local thermal environment under the current reforestation efforts, and thereby providing better connected thermal habitats for species to survive under climate change.

The Amazon is hypothesized to reach an irreversible ‘tipping point’ when deforestation slows the hydrological cycle sufficiently that tropical forest ecosystems cannot be sustained. However, inception of such a tipping point has not been supported by observations and the relevant links between deforestation and atmospheric moisture recycling are poorly understood. Here we show that reduction in evapotranspiration from 20 years of deforestation dried the atmosphere persistently and caused moisture decoupling, i.e. an opposite sign of moisture change between the lower and middle troposphere. Increased deforestation exacerbated the lower troposphere drying and caused it to penetrate deeper into the middle troposphere in the dry and transition seasons over monsoon forests and savannas. Deforestation induced warming-enhanced buoyant updrafts, elevated hot and dry air and thereby reduced downward mixing of water supplies from the tropical Atlantic that normally moisten the Amazon forests. The severe atmospheric desiccation in the southern and eastern Amazon cannot be compensated by enhanced water supplies from the Atlantic Ocean, demonstrating an irreversible transition in Amazon hydrological cycle exacerbated by rapid deforestation. The more recent drying through the seasons over rainforests and during the wet season over the transition zones from rainforests to monsoon forests and savannas, however, suggests a window of opportunity for preventing ecosystem collapse with forest conservation.

Amazonian protected areas (PAs) play an important role in maintaining the regional and global ecosystem services, biodiversity and climate change mitigation. The effects of Amazonian PAs on climate change mitigation mainly focus on the carbon sequestration benefits. The biophysical effects of PAs on regulating the local energy budgets, and hence changing local climate, however, are often ignored. Using multiple satellite observation datasets, we evaluated the effects of Amazonian PAs on land surface temperature (LST) and the biophysical mechanisms of PAs on surface albedo and evapotranspiration (ET). We showed that Amazonian PAs have a cooling effect on local LST in relative to nearby croplands and non-protected areas (non-PAs) with the same land cover as PAs. The asymmetrical cooling effects of Amazonian PAs between daytime and nighttime, and between the dry and wet seasons sustain lower diurnal and seasonal temperature ranges, respectively, than non-PAs and croplands. The protected forests have stronger cooling effects, and more effectively moderate the diurnal and seasonal temperature ranges than the protected savannas due to the higher effects on surface albedo and ET. The non-PAs show weaker cooling effect than PAs, indicating reduced thermal buffering effect in non-PAs. Our results highlighted the great potential of natural vegetation in PAs versus non-PAs and croplands in buffering local thermal environment and the necessity of natural vegetation conservation in Amazon region.

Despite the threat that nighttime heatwave poses to public health and the environment in the developing world, it remains relatively understudied in Africa, especially in its rapidly expanding urban areas with large populations. Using meteorological observations, climate reanalysis, remote sensing datasets, and integrated methodology, we found that during 1981–2020, nighttime heatwaves dramatically increased with early onset dates over Africa. Large scale circulation induced dry conditions over land which explains the major heatwaves across all climate zones. Meanwhile, the increasing trend of nighttime heatwaves in urban areas than rural areas in both tropical and temperate climates is largely due to urbanization, which amplifies heatwaves with urban heat island (UHI) effects. The strongest contribution of urbanization to nighttime heatwaves was observed in temperate climate, leading to a 46% increase in the heatwave duration. In arid climate, urban expansion has a negative impact on nighttime heatwaves, due to the cool island effect of urban greens and weak urbanization. The major contribution of urbanization to the urban-rural contrast of nighttime heatwave trends in temperate climate can be attributed to stronger UHI intensity resulting from lower windspeed and less evapotranspiration. Without appropriate adaptation efforts to reduce heatwave exposure, the risks posed in Africa’s urban areas will continue to increase under future warming.

Future stress on water resources, and on temperate drylands in particular, remains uncertain. Here, the authors show that climate in the late twenty first century may reduce the extent of temperate drylands, dry deep soils, and create intra-regional and intercontinental differences in ecological drought.

Wetlands are complex and diverse ecosystems, substantially contributing to natural capital. Projected variations in natural and anthropogenic scenarios are likely to alter wetland dynamics by substantially impacting the hydrological and ecosystem functions. This study focuses on monitoring the probable impacts of land use change and El Niño Southern Oscillation (ENSO) variations on wetlands dynamics by analyzing the magnitude and extent of global wetland inundation trends during the study period. A microwave dataset was used to study the trends and interannual variability of surface inundation extent of global lakes, rivers, reservoirs, and wetland classes. Between 1995 and 2015, the average rate of increase in surface inundation extent of global waterbodies and wetlands of 7029.6 km2 per year occurred with the average inundation of 2.9 million km2. Whereas, 1998–2004, 2005–2009, and 2010–2015 have shown significant inter-annual variabilityduring 21 years of study period. The maximum contribution of 3.06 million km2 inundation has been recorded during the strong El Niño year of 2010. Swamps flooded forests and coastal wetlands has shown the most significant increase in surface inundation extent. Our results showed a positive lag correlation between Niño 3.4 sea surface temperature (SST) anomalies and surface inundation of different Global Lakes and Wetland classes. Moreover, lakes, rivers, reservoirs, and wetlands have revealed varying responses to different anthropogenic drivers like cropland (CL), natural vegetation (NV), and urban land (UL). CL, NV and barren land (BL) buffered region has presented strong negative connection with coastal inundation extent. Swamps demonstrated strong positive correlation with urban-land and coastal with shrub/grass land cover type. Through this study the extent of impact projected by climatic oscillations and anthropogenic drivers to water bodies and wetlands can be analyzed for well-informed conflict management and decision-making practices for minimizing the human driven impact on natural water systems.

A better understanding of the dominant climatic drivers that control vegetation trends across regions and biomes is essential for assessing ecosystem dynamics and land-climate interactions in a warming world. Temperature (TMP) has long been considered as dominant control in global vegetation trends, and growing evidence suggests that water availability plays an increasingly important role in determining trends in vegetation growth over many biomes. However, a detailed spatial-temporal evolution of the vegetation trends and the climatic drivers that effect vegetation trends are not well known. In this study, using a time-varying trend (extracted by the ensemble empirical mode decomposition) of climate and satellite-derived normalized difference vegetation index (as a proxy for vegetation productivity) from 1981 to 2015, we find that the trends in vegetation greening and terrestrial carbon uptake reversed, beginning in the early 2000s, largely driven by the recent drying trend. The relative importance of climatic controls on vegetation productivity trend is estimated using a principal component analysis procedure, and the results demonstrate a global shift in the dominant driver of vegetation trends from TMP to precipitation, and point to intensified water limitation to vegetation growth as warming continues. The findings provide empirical evidence of the spatial-temporal evolution of different climatic drivers behind trends in vegetation productivity.

The large interannual variability of global atmospheric CO _2 growth rate originates primarily from variation in carbon dioxide (CO _2 ) uptake of pantropical terrestrial ecosystems, which covaries with the El Niño–Southern Oscillation (ENSO) modulated climate fluctuations of water availability and temperature change. However, the role of ENSO in modulating the contributions of regional to overall water availability interannual variability, and the phase and strength of water availability-CO _2 coupling remain poorly constrained across functionally diverse pantropical terrestrial ecosystems. Using satellite microwave and ground water availability and well-mixed global atmospheric CO _2 concentration observations, the coupling in interannual variability of water availability-CO _2 and their relationship with ENSO was investigated from 1998 to 2016. The results demonstrated causal sequence of ENSO, water availability, and global atmospheric CO _2 growth rate, the phase and magnitude of water availability-CO _2 coupling was primarily determined by phase and strength of correlation between ENSO and water availability, revealing ENSO-driven robust and reverse coupling of water availability-CO _2 . Moreover, tropical rainforests, savannas, and shrublands dominated the pantropical water availability variations and showed stronger coupling strength. Therefore, the strong interannual variability of atmospheric CO _2 growth rate originates from ENSO-driven frequent variations of water availability and the subsequently concurrent carbon uptake over pantropical rainforests, savannas, and shrublands. The findings provided new insights to understand and predict interannual variability of water availability and CO _2 growth rate based on ENSO and its predictability.

The monitoring of meteorological drought is critically important for tropical and subtropical water-limited ecosystems, which play key roles in the global carbon cycle and ecosystem services. Satellite remote sensing is the only practical approach for tracking drought changes with high resolution and an instantaneous response. However, the application of remote sensing drought indices derived from optical and infrared bands has been constrained due to cloud contamination. Here the Microwave Integrated Drought Index (MIDI), a multi-sensor microwave remote sensing drought index integrating state-of-the-art multiple satellite microwave-derived precipitation, soil moisture and land surface temperature information, was processed to improve the meteorological drought monitoring capability of satellite remote sensing. The index was evaluated against the 1 to 12 month field-based drought indicators Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) and anomalies in the satellite-derived Enhanced Vegetation Index (EVI) from 1998 to 2014. MIDI with an optimal ensemble of multiple satellite precipitation products showed a better improvement in meteorological drought monitoring capability than MIDI based on an individual satellite precipitation dataset, and had statistically strong correlation in particular with 1 month SPI/SPEI over a wide range of bio-climatic zones spanning from arid to humid. Moreover it showed significantly higher correlations with EVI anomalies than SPI/SPEI. The results demonstrated the reliability and superiority of MIDI in monitoring meteorological drought with the ability to work in all weather conditions. Therefore, MIDI provides a gateway to employing satellite microwave remote sensing for reliable meteorological drought monitoring, with the potential for long-term drought assessments as well as near-real-time drought monitoring using operational satellites.

South Asia (SA) has been considered one of the most remarkable regions for changing vegetation greenness, accompanying its major expansion of agricultural activities, especially irrigated farming. The influence of the monsoon climate on the seasonal trends and anomalies of vegetation greenness is poorly understood in this area. Herein, we used the satellite-based Normalized Difference Vegetation Index (NDVI) to investigate various spatiotemporal patterns in vegetation activity during summer and winter monsoon (SM and WM) seasons and among irrigated croplands (IC), rainfed croplands (RC), and natural vegetation (NV) areas during 1982–2013. Seasonal NDVI variations with climatic factors (precipitation and temperature) and land use and cover changes (LUCC) have also been investigated. This study demonstrates that the seasonal dynamics of vegetation could improve the detailed understanding of vegetation productivity over the region. We found distinct greenness trends between two monsoon seasons and among the major land use/cover classes. Winter monsoons contributed greater variability to the overall vegetation dynamics of SA. Major greening occurred due to the increased productivity over irrigated croplands during the winter monsoon season; meanwhile, browning trends were prominent over NV areas during the same season. Maximum temperatures had been increasing tremendously during the WM season; however, the precipitation trend was not significant over SA. Both the climate variability and LUCC revealed coupled effects on the long term NDVI trends in NV areas, especially in the hilly regions, whereas anthropogenic activities (agricultural advancements) played a pivotal role in the rest of the area. Until now, advanced cultivation techniques have proven to be beneficial for the region in terms of the productivity of croplands. However, the crop productivity is at risk under climate change.

Combining flux tower measurements with remote sensing or land surface models is generally regarded as an efficient method to scale up flux data from site to region. However, due to the heterogeneous nature of the vegetated land surface, the changing flux source areas and the mismatching between ground source areas and remote sensing grids, direct use of in-situ flux measurements can lead to major scaling bias if their spatial representativeness is unknown. Here, we calculate and assess the spatial representativeness of 15 flux sites across northern China in two aspects: first, examine how well a tower represents fluxes from the specific targeted vegetation type, which is called vegetation-type level; and, second, examine how representative is the flux tower footprint of the broader landscape or regional extents, which is called spatial-scale level. We select fraction of target vegetation type (FTVT) and Normalized Difference Vegetation Index (NDVI) as key indicators to calculate the spatial representativeness of 15 EC sites. Then, these sites were ranked into four grades based on FTVT or cluster analysis from high to low in order: (1) homogeneous; (2) representative; (3) acceptable; and (4) disturbed measurements. The results indicate that: (1) Footprint climatology for each site was mainly distributed in an irregular shape, had similar spatial pattern as spatial distribution of prevailing wind direction; (2) At vegetation-type level, the number of homogeneous, representative, acceptable and disturbed measurements is 8, 4, 1 and 2, respectively. The average FTVT was 0.83, grass and crop sites had greater representativeness than forest sites; (3) At spatial-scale level, flux sites with zonal vegetation had greater representativeness than non-zonal vegetation sites, and the scales were further divided into three sub-scales: (a) in flux site scale, the average of absolute NDVI bias was 4.34%, the number of the above four grades is 9, 4, 1 and 1, respectively; (b) in remote sensing pixel scale, the average of absolute NDVI bias was 8.27%, the number is 7, 2, 2 and 4, respectively; (c) in land model grid scale, the average of absolute NDVI bias was 12.13%, the number is 5, 4, 3 and 3. These results demonstrate the variation of spatial representativeness of flux measurements among different application levels and scales and highlighted the importance of proper interpretation of EC flux measurements. These results also suggest that source area of EC flux should be involved in model validation and/or calibration with EC flux measurements.

An improved individual-based forest ecosystem carbon budget model for China (FORCCHN) was applied to investigate the spatial-temporal dynamics of net primary productivity of different forest types in northeastern China. In this study, the forests of northeastern China were categorized into four ecological types according to their habitats and generic characteristics (evergreen broadleaf forest, deciduous broadleaf forest, evergreen needleleaf forest and deciduous needleleaf forest). The results showed that distribution and change of forest NPP in northeastern China were related to the different forest types. From 1981 to 2002, among the forest types in northeastern China, per unit area NPP and total NPP of deciduous broadleaf forest were the highest, with the values of 729.4 gC/(m(2)•yr) and 106.0 TgC/yr, respectively, followed by mixed broadleaf- needleleaf forest, deciduous needleleaf forest and evergreen needleleaf forest. From 1981 to 2002, per unit area NPP and total NPP of different forest types in northeastern China exhibited significant trends of interannual increase, and rapid increase was found between the 1980s and 1990s. The contribution of the different forest type's NPP to total NPP in northeastern China was clearly different. The greatest was deciduous broadleaf forest, followed by mixed broadleaf- needleleaf forest and deciduous needleleaf forest. The smallest was evergreen needleleaf forest. Spatial difference in NPP between different forest types was remarkable. High NPP values of deciduous needleleaf forest, mixed broadleaf- needleleaf forest and deciduous broadleaf forest were found in the Daxing'anling region, the southeastern of Xiaoxing'anling and Jilin province, and the Changbai Mountain, respectively. However, no regional differences were found for evergreen needleleaf NPP. This study provided not only an estimation NPP of different forest types in northeastern China but also a useful methodology for estimating forest carbon storage at regional and global levels.

There is an urgent need to reduce the uncertainties in remotely sensed detection of phenological shifts of high latitude ecosystems in response to climate changes in past decades. In this study, vegetation phenology in western Arctic Russia (the Yamal Peninsula) was investigated by analyzing and comparing Normalized Difference Vegetation Index (NDVI) time series derived from the Advanced Very High Resolution Radiometer (AVHRR), the Moderate Resolution Imaging Spectroradiometer (MODIS), and SPOT-Vegetation (VGT) during the decade 2000–2010. The spatial patterns of key phenological parameters were highly heterogeneous along the latitudinal gradients based on multi-satellite data. There was earlier SOS (start of the growing season), later EOS (end of the growing season), longer LOS (length of the growing season), and greater MaxNDVI from north to south in the region. The results based on MODIS and VGT data showed similar trends in phenological changes from 2000 to 2010, while quite a different trend was found based on AVHRR data from 2000 to 2008. A significantly delayed EOS ( p