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Climate warming causes profound effects on structure and function of wetland ecosystem, thus affecting regional and global hydrological cycles and carbon budgets. However, how wetland plants respond to warming is still poorly understood. Here, we synthesized observations from 273 independent sites to explore responses of northern wetland plants to warming. Our results show that warming enhances biomass accumulation for vascular plants including shrubs and graminoids, whereas it reduces biomass accumulation for cryptogams including moss and lichen. This divergent response of vascular plants and cryptogams is particularly pronounced in the high latitudes where permafrost prevails. As warming continues, this divergent response is amplified, however, the reduction in cryptogams is more drastic. Warming leads to declined surface soil moisture and lowered water table, thereby shifting wetlands from a wet system dominated by cryptogams to a drier system with increased cover of vascular plants. Under a high-emission scenario of Shared Socioeconomic Pathways (SSP5), a 4.7-5.1°C mean global temperature rise will cause more than fivefold loss of cryptogams compared with current climate. As cryptogams are largely concentrated at northern high latitudes, where warming will likely be greater than the projected global mean, modification in wetland plant composition and major reduction in cryptogams are expected to occur even much earlier than 2100.

Earlier leaf-out in response to climate warming has been recorded in northern temperate and boreal regions. In turn, this shift modifies climate by altering seasonal cycles of surface energy, water and carbon budgets. Here, we use the Community Earth System Model 1.2 to investigate climate feedbacks from advanced leaf-out in northern temperate and boreal vegetation. An imposed 12-day earlier leaf-out in this region, consistent with recent observations, enhances annual surface warming in the Northern Hemisphere. We identify warming hotspots in the Canadian Arctic Archipelago (~0.7 °C), east and west edges of Siberia (~0.4 °C) and southeastern Tibetan Plateau (~0.3 °C). We attribute this enhanced warming to combined effects of indirect water vapour, cloud and snow-albedo radiative feedbacks through intensified poleward water vapour transport rather than direct vegetation albedo and latent heat biophysical feedbacks. With continued warming, positive feedbacks between climate and leaf phenology are likely to amplify warming in the northern high latitudes. Climate change has led to earlier spring leaf-out in northern temperate and boreal regions. This advanced leaf-out causes warming in the Northern Hemisphere due to the combined effects of water vapour, cloud and snow-albedo feedbacks on the surface energy budget.

Climate-related changes have already been observed at various spatial and temporal scales, along with frequent extreme climate events and emerging issues in great complexity. Meanwhile, the impacts...

Historical temperature records are often partially biased by the urban heat island (UHI) effect. However, the exact magnitude of these biases is an ongoing, controversial scientific question, especially in regions like China where urbanization has greatly increased in recent decades. Previous studies have mainly used statistical information and selected static population targets, or urban areas in a particular year, to classify urban-rural stations and estimate the influence of urbanization on observed warming trends. However, there is a lack of consideration for the dynamic processes of urbanization. The Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD), and Pearl River Delta (PRD) are three major urban agglomerations in China which were selected to investigate the spatiotemporal heterogeneity of urban expansion effects on observed warming trends in this study. Based on remote sensing (RS) data, urban area expansion processes were taken into consideration and the relationship between urban expansion rates and warming trends was investigated using data from 975 meteorological stations throughout China. Although urban areas constitute less than 1% of land in China, more than 90% of the meteorological stations experienced urban land use change and the average urban expansion rate was 0.33%/a. There was also a significant positive relationship between observed warming trends and urban expansion rates. Background warming, without the influence of urbanization and extra warming induced by urbanization processes, was estimated using a linear regression model based on observed warming trends and urban expansion rates. On average, urbanization led to an additional annual warming of 0.034 ± 0.005 °C/10a. This urbanization warming effect was 0.050 ± 0.007 °C/10a for minimum temperatures and 0.008 ± 0.004 °C/10a for maximum temperatures. Moreover, it appeared that urbanization induced greater warming on the minimum temperature during the cold season and maximum temperature during the warm season.

The Amazon Basin is experiencing climate change, altered hydrological cycles, and forest loss. The processes causing increased fires are complex, and therefore cannot be attributed to climate change or human-induced deforestation alone. Here, we show why the Amazon fires must be understood across spatial scales within the regional coupled system.

Frequent Amazonian fires over the last decade have raised the alarm about the fate of the Earth's most biodiverse forest. The increased fire frequency has been attributed to altered hydrological cycles. However, observations over the past few decades have demonstrated hydrological changes that may have opposing impacts on fire, including higher basin-wide precipitation and increased drought frequency and severity. Here, we use multiple satellite observations and climate reanalysis datasets to demonstrate compelling evidence of increased fire susceptibility in response to climate regime shifts across Amazonia. We show that accumulated forest loss since 2000 warmed and dried the lower atmosphere, which reduced moisture recycling and resulted in increased drought extent and severity, and subsequent fire. Extremely dry and wet events accompanied with hot days have been more frequent in Amazonia due to climate shift and forest loss. Simultaneously, intensified water vapor transport from the tropical Pacific and Atlantic increased high-altitude atmospheric humidity and heavy rainfall events, but those events did not alleviate severe and long-lasting droughts. Amazonia fire risk is most significant in the southeastern region where tropical savannas undergo long seasonally dry periods. We also find that fires have been expanding through the wet-dry transition season and northward to savanna-forest transition and tropical seasonal forest regions in response to increased forest loss at the "Arc of Deforestation." Tropical forests, which have adapted to historically moist conditions, are less resilient and easily tip into an alternative state. Our results imply forest conservation and fire protection options to reduce the stress from positive feedback between forest loss, climate change, and fire.

Urbanization has caused environmental changes, such as urban heat islands (UHIs), that affect terrestrial ecosystems. However, how and to what extent urbanization affects plant phenology remains relatively unexplored. Here, we investigated the changes in the satellite-derived start of season (SOS) and the covariation between SOS and temperature (R(T)) in 85 large cities across the conterminous United States for the period 2001–2014. We found that 1) the SOS came significantly earlier (6.1 ± 6.3 d) in 74 cities and R(T) was significantly weaker (0.03 ± 0.07) in 43 cities when compared with their surrounding rural areas (P < 0.05); 2) the decreased magnitude in R(T) mainly occurred in cities in relatively cold regions with an annual mean temperature

Urban heat island (UHI) plays an important role in urban sustainability under climate change. Urbanization is the driving force of UHI. However, the quantification of UHI's response to urbanization is still challenging due to the lack of robust and continuous temperature and urbanization datasets and reliable quantification methods. This study developed a framework to quantify the response of surface UHI (SUHI) to urban expansion using the annual temperate cycle model. We developed a continuous annual SUHI series at the buffer level from 2003 to 2018 in the Jing-Jin-Ji region of China using MODIS land surface temperature and imperviousness derived from a high-resolution urban map. We then investigated the spatiotemporal dynamic of SUHI under urban expansion and examined the underlying mechanism. Spatially, the largest SUHI interannual variations occurred in suburban areas compared to the urban center and rural areas. Temporally, the increase in SUHI under urban expansion was more significant in daytime compare to nighttime. We found that the seasonal variation of SUHI was largely affected by the seasonal variations of vegetation in rural areas and the interannual variation was mainly attributed to urban expansion in urban areas. Additionally, urban greening led to the decrease in summer daytime SHUI in central urban areas. These findings deepen the understanding of the long-term spatiotemporal dynamic of UHI and the quantitative relationship between UHI and urban expansion, providing a scientific basis for prediction and mitigation of future UHI.

Shifts in precipitation regimes have been given increased attention along with climate trends in the arid and semiarid Mongolian Plateau (MP), because precipitation is the dominant factor that controls vegetation growth and land-use practices in the region. However, the temporal variability and spatial heterogeneity of decadal trends in summer precipitation fraction have not been well understood. In this study, the temporal variability and spatial heterogeneity of annual and summer precipitation change were investigated with the major focus on the summer precipitation fraction across the entire MP, using monthly precipitation data from 141 meteorological stations and the Tropical Rainfall Measuring Mission (TRMM) precipitation data. The Mann–Kendall trend test, Sen’s regression, and Spatial Analyst methods were used for time series analysis. Results show that the regional summer precipitation fraction declined significantly at a rate of − 1.0%/decade (p

Water relations in plant communities are influenced both by contrasting functional groups (grasses and shrubs) and by climate change via complex effects on interception, uptake, and transpiration. ...

Accurate assessment of the strength of China's terrestrial ecosystem carbon sink is key to understanding its regional carbon budget. However, large uncertainties in current carbon sink estimations still exist, which hinder the prediction of future climate change trajectories. In this study, we generated a high-resolution (1 km x 1 km) dataset of China's net ecosystem productivity (NEP) in the last decade via a model tree ensemble approach combined with data from 46 flux sites in China and neighboring regions. The upscaling also included detailed information on nitrogen (N) deposition and forest age that have often been neglected in previous studies. The performance of MTE algorithm in simulating NEP at the site level is relatively high for both training (R-2 = 0.81, RMSE = 0.73 gC m(-2) day(-1)) and validation datasets (R-2 = 0.76, RMSE = 0.81 gC m(-2)day(-1)). Our data-driven estimation showed that roughly 70% of the area is a carbon sink, and the largest carbon sinks are found in the southeast and southwest monsoon regions. The total annual NEP in China in the last decade was 1.18 +/- 0.05 Pg C yr(-1), which is similar to the results found by another foundational global-scale study. Yet, the two studies significantly differ in the spatial distribution of carbon sink density. The seasonality of China's NEP is characterized by region-specific kurtosis and skewness in most areas. Furthermore, ecosystem carbon use efficiency (CUE), defined as the annual NEP/GPP ratio, also showed high spatial variation. For example, the Xiaoxing'anling and Changbai Mountains in northeastern China, the eastern edge of the Tibetan Plateau, and bordering areas of the southeast and southwest monsoon regions have a larger CUE than the rest of China. On average, China's terrestrial ecosystem CUE is approximately 0.17. Our data-driven NEP and CUE estimates provide a new tool for assessing China's carbon dioxide flux. Our study also highlights the necessity to incorporate more environmental variables related to vegetation growth and more data derived from flux sites into NEP upscaling to reduce uncertainties in carbon budget estimations.

Author(s): Xu, X; Riley, WJ; Koven, CD; Jia, G | Abstract: Vegetation phenology plays an important role in regulating land-atmosphere energy, water, and trace-gas exchanges. Changes in spring greenup (SG) have been documented in the past half-century in response to ongoing climate change. We use normalized difference vegetation index generated from NOAA's advanced very high resolution radiometer data in the Global Inventory Modeling and Monitoring Study project over the 1982–2005 period, coupled with climate reanalysis (Climate Research Unit-National Centers for Environmental Prediction) to investigate the SG responses to preseason climate change in northern temperate and boreal regions. We compared these observed responses to the simulated SG responses to preseason climate inferred from the Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) over 1982–2005. The observationally inferred SG suggests that there has been an advance of about 1ndays per decade between 1982 and 2005 in the northern midlatitude to high latitude, with significant spatial heterogeneity. The spatial heterogeneity of the SG advance results from heterogeneity in the change of the preseason climate as well as varied vegetation responses to the preseason climate across biomes. The SG to preseason temperature sensitivity is highest in forests other than deciduous needleleaf forests, followed by temperate grasslands and woody savannas. The SG in deciduous needleleaf forests, open shrublands, and tundra is relatively insensitive to preseason temperature. Although the extent of regions where the SG is sensitive to preseason precipitation is smaller than the extent of regions where the SG is sensitive to preseason temperature, the biomes that are more sensitive to temperature are also more sensitive to precipitation, suggesting the interactive control of temperature and precipitation. In the mean, the CMIP5 ESMs reproduced the dominant latitudinal preseason climate trends and SG advances. However, large biases in individual ESMs for the preseason period, climate, and SG sensitivity imply needed model improvements to climate prediction and phenological process parameterizations.

Many cities have been suffering from severe water deficiency in recent years due to rapid urban expansion, socioeconomic development, population growth, and climate change. Domestic water use plays an important role in the total urban water use. A framework for estimating domestic water use is highly needed to develop adaptive measures for efficient water use under climate change and urbanization. In this study, we developed an agent-based model (ABM) with two groups of agents to estimate the domestic water use. These two groups include the government agent that determines the income growth rate, adjusts water prices, and promotes water-efficient appliances, and the residential agents who consume water. To better capture the impact of urbanization and climate change on water use, the utility function of residential agents was further divided into base water use related to economic condition and seasonal water use that is sensitive to climate conditions. Moreover, a bass diffusion model was proposed and integrated into the ABM to consider the diffusion of water-efficient appliances. Results show that our ABM can capture the spatiotemporal pattern of domestic water use in different regions. Residents in the central urban area consume more water compared to residents in the suburbs in the study cities in China, but it is opposite in the study counties in the US. The growth of income and water-efficient appliances are two factors affecting domestic water use. The proposed modeling framework is transferrable to other regions to develop strategies for mitigating domestic water use.

Our planet is undergoing one of the most rapid climate changes in Earth’s history. The current change is particularly significant because it is most likely a consequence of human activities since the 19th century. The Digital Earth platform, which includes Earth-orbiting satellites, ground-based observations, and other technologies for collecting, analyzing and visualizing data, has enabled scientists to see our climate and its impacts at regional and global scales. The Digital Earth platform offers valuable information on the atmosphere, biosphere, hydrosphere and cryosphere to understand Earth’s past and present, and it supports Earth system models for climate prediction and projection. This chapter gives an overview of the advances in climate change studies based on Digital Earth and provides case studies that utilize Digital Earth in climate change research, such as in the observation of sensitive factors for climate change, global environmental change information and simulation systems, and synchronous satellite-aerial-ground observation experiments, which provide extremely large and abundant datasets. The mapping of climate extremes and impacts improves preparedness for climate change-related risks and provides robust evidence to support climate risk management and climate change adaptation for the public, decision makers, investors, and vulnerable communities. However, Digital Earth faces the challenges of multisource data coordination and integration, requiring international partnerships between governments and other organizations to advance open data policies and practices.

Evapotranspiration (ET) is one of the most important fluxes in terrestrial ecosystems that regulate atmosphere–hydrosphere–biosphere interactions. Several studies have suggested that global ET has significantly increased in the past several decades, and that such increase has exhibited big spatial variability, but there are few detailed studies on the spatio-temporal change in ET over China. Here, we developed a high-resolution data-oriented monthly ET product in China between 1982 and 2015 by integrating remote-sensing and the eddy covariance technique observed ET data in a machine learning approach (model tree ensemble, MTE). We showed that the mean annual ET over China is 552 ± 14 mm yr−1, which is comparable to the estimate from a MTE-derived product based on water balance, but is larger than that from both previous MTE-derived global product and process-based land surface models. ET in China significantly increased with a rate of 10.7 mm yr−1 per decade over the past 30 years (p 60 mm yr−1 per decade) occurred in the eastern periphery of Sichuan, southern Taiwan, and central China, which was attributed to the increases in temperature and solar radiation, as well as the enhanced vegetation productivity. About 22% of the area showed a decreasing trend in ET, mainly in parts of southeastern, southwestern, and northeastern China. The regional decrease in ET was likely due to decreasing precipitation and/or vegetation browning. Although our finding of the significant increase in China’s ET at the country scale is supported by five different ET products, there are still less agreement on the change in ET at the regional scale among different ET products.

Radiative forcing (RF) induced by land use (mainly surface albedo) change is still not well understood in climate change science, especially the effects of changes in urban albedo due to rapid urbanization on the urban radiation budget. In this study, a modified RF derivation approach based on Landsat images was used to quantify changes in the solar radiation budget induced by variations in surface albedo in Beijing from 2001 to 2009. Field radiation records from a Beijing meteorological station were used to identify changes in RF at the local level. There has been rapid urban expansion over the last decade, with the urban land area increasing at about 3.3 % annually from 2001 to 2009. This has modified three-dimensional urban surface properties, resulting in lower albedo due to complex building configurations of urban centers and higher albedo on flat surfaces of suburban areas and cropland. There was greater solar radiation (6.93 × 108 W) in the urban center in 2009 than in 2001. However, large cropland and urban fringe areas caused less solar radiation absorption. RF increased with distance from the urban center (less than 14 km) and with greater urbanization, with the greatest value being 0.41 W/m2. The solar radiation budget in urban areas was believed to be mainly influenced by urban structural changes in the horizontal and vertical directions. Overall, the results presented herein indicate that cumulative urbanization impacts on the natural radiation budget could evolve into an important driver of local climate change.

Regional climate is influenced by land surface processes through energy exchange between land and atmosphere at various scales. The performance of climate model simulation is largely influenced by land cover parameterization, especially over areas that experience rapid change of land surface characterization. Accurate land cover datasets suited for climate modeling are urgently needed to improve model parameterization for better simulation. In this study, fused urban land cover datasets have been developed by combining multi-source urban land cover products based on cross-comparison and detailed validation from medium resolution images during recent decades. Fractional cover values at different spatial scales were aggregated from integrated land cover datasets to derive improved estimates of the urban extent of big cities in China. Urbanization in China as captured by the new dataset can be divided into steadily and rapidly increasing periods with the urban area increasing by 2.5 and 6.7 % per year, respectively. Rapid urbanization mostly happens in the urban fringe, especially in eastern China, with mass conversion of cropland and woodland to urban land. An improvement in climate model simulation could be achieved using the fused data applied in climate modeling for examining the impact of rapid urbanization on the regional climate.

The distribution of rainfed agriculture, which accounts for approximately ¾ of global croplands, is expected to respond to climate change and human population growth and these responses may be especially pronounced in water limited areas. Because the environmental conditions that support rainfed agriculture are determined by climate, weather, and soil conditions that affect overall and transient water availability, predicting this response has proven difficult, especially in temperate regions that support much of the world’s agriculture. Here, we show that suitability to support rainfed agriculture in temperate dryland climates can be effectively represented by just two daily environmental variables: moist soils with warm conditions increase suitability while extreme high temperatures decrease suitability. 21st century projections based on daily ecohydrological modeling of downscaled climate forecasts indicate overall increases in the area suitable for rainfed agriculture in temperate dryland regions, especially at high latitudes. The regional exception to this trend was Europe, where suitability in temperate dryland portions will decline substantially. These results clarify how rising temperatures interact with other key drivers of moisture availability to determine the sustainability of rainfed agriculture and help policymakers, resource managers, and the agriculture industry anticipate shifts in areas suitable for rainfed cultivation.

Drylands cover 40% of the global terrestrial surface and provide important ecosystem services. While drylands as a whole are expected to increase in extent and aridity in coming decades, temperature and precipitation forecasts vary by latitude and geographic region suggesting different trajectories for tropical, subtropical, and temperate drylands. Uncertainty in the future of tropical and subtropical drylands is well constrained, whereas soil moisture and ecological droughts, which drive vegetation productivity and composition, remain poorly understood in temperate drylands. Here we show that, over the twenty first century, temperate drylands may contract by a third, primarily converting to subtropical drylands, and that deep soil layers could be increasingly dry during the growing season. These changes imply major shifts in vegetation and ecosystem service delivery. Our results illustrate the importance of appropriate drought measures and, as a global study that focuses on temperate drylands, highlight a distinct fate for these highly populated areas., 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.

Landuse in East Asia has changed substantially during the last three decades, featured with expansion of urban built-up at unprecedented scale and speed. The fast expansion of urban areas could contribute to local and even regional climate change. However, current spatial datasets of urban fractions do not well represent the extent and expansion of urban areas in the regions, and that best available satellite data and remote sensing techniques have not been well applied to serve regional modeling of urbanization impacts on near surface temperature and other climate variables. Better estimates of localized urban fractions are badly needed. Here we use high and mid resolution satellite data to estimate urban fractions and road width at local and regional scales. With our fractional cover, data fusion, and differentiated threshold approaches, more spatial details of urban cover are demonstrated than previously reported in many global datasets. Many city clusters were merging into each other, with gradual blurring of boundaries and disappearance of gaps among member cities. Cities and towns were more connected with roads and commercial corridors, while wildland and urban green areas have become more isolated as patches among built-up areas. Average road width in commercial areas was 37.2 m in Beijing (north, temperate) and 24.2 m in Guangzhou (south, tropical), which are greater than these listed in model default values. Those new estimates could effectively improve climate simulation at local and regional scales in East Asia.

Drylands occur worldwide and are particularly vulnerable to climate change because dryland ecosystems depend directly on soil water availability that may become increasingly limited as temperatures rise. Climate change will both directly impact soil water availability and change plant biomass, with resulting indirect feedbacks on soil moisture. Thus, the net impact of direct and indirect climate change effects on soil moisture requires better understanding. We used the ecohydrological simulation model SOILWAT at sites from temperate dryland ecosystems around the globe to disentangle the contributions of direct climate change effects and of additional indirect, climate change-induced changes in vegetation on soil water availability. We simulated current and future climate conditions projected by 16 GCMs under RCP 4.5 and RCP 8.5 for the end of the century. We determined shifts in water availability due to climate change alone and due to combined changes of climate and the growth form and biomass of vegetation. Vegetation change will mostly exacerbate low soil water availability in regions already expected to suffer from negative direct impacts of climate change (with the two RCP scenarios giving us qualitatively similar effects). By contrast, in regions that will likely experience increased water availability due to climate change alone, vegetation changes will counteract these increases due to increased water losses by interception. In only a small minority of locations, climate change-induced vegetation changes may lead to a net increase in water availability. These results suggest that changes in vegetation in response to climate change may exacerbate drought conditions and may dampen the effects of increased precipitation, that is, leading to more ecological droughts despite higher precipitation in some regions. Our results underscore the value of considering indirect effects of climate change on vegetation when assessing future soil moisture conditions in water-limited ecosystems.

As dominant biomes, forests play an important and indispensable role in adjusting the global carbon balance under climate change. Therefore, there are scientific and political implications in investigating the carbon budget of forest ecosystems and its response to climate change. Here we synthesized the most recent research progresses on the carbon cycle in terrestrial ecosystems, and applied an individual-based forest ecosystem carbon budget model for China (FORCCHN) to simulate the dynamics of the carbon fluxes of forest ecosystems in the northeastern China. The FORCCHN model was further improved and applied through adding variables and modules of precipitation (rainfall and snowfall) interception by tree crown, understory plants and litter. The results showed that the optimized FORCCHN model had a good performance in simulating the carbon budget of forest ecosystems in the northeastern China. From 1981 to 2002, the forests played a positive role in absorbing carbon dioxide. However, the capability of forest carbon sequestration had been gradually declining during the the same period. As for the average spatial distribution of net carbon budget, a majority of the regions were carbon sinks. Several scattered areas in the Heilongjiang Province and the Liaoning Province were identified as carbon sources. The net carbon budget was apparently more sensitive to an increase of air temperature than change of precipitation.

We introduce a new pragmatic procedure called the ‘climate learning ladder’ to structure policy analysis, support refl ection and identify critical decisions to support climate adaptation. This tool is the result of the refl exive learning process that occurred while developing innovative appraisal methods in the Alxa League of Inner Mongolia, China, and in the Guadiana river basin in the European Union. Building capacities to cope with climate change requires going beyond simply providing ‘more knowledge’ on climate impacts to policy makers. Instead, climate adaptation can be understood as a multi-step social process in which individuals and organizations need to learn how to (1) manage different framings of the issues at stake while raising awareness of climate risks and opportunities, (2) understand different motives for, and generate adequate incentives or sanctions to ensure, action, (3) develop feasible options and resources for individual and collective transformation and collaboration and (4) institutionalize new rights, responsibilities and feedback learning processes for climate adaptation in the long term. Copyright © 2010 John Wiley & Sons, Ltd and ERP Environment.

Aim Use a regression model that relates climatic variables to the relative abundances of shrubs, C4 and C3 grasses to project the plant functional type composition of temperate grasslands and shrublands within North and South America in response to climate change. Location The temperate zone grassland and shrubland regions of North and South America. Methods We used a regression model to project changes in the relative abundances of shrubs, C4 and C3 grasses under three general circulation model (GFDL, GISS, UKMO) climate change scenarios. The three climate change scenarios were applied to a global data set of mean monthly temperatures and precipitation. The regression model, which incorporates mean annual temperature, mean annual precipitation and seasonality of precipitation as input variables, was used to project plant functional type changes. Spatial patterns of change were analysed using a geographical information system. Results Relative abundance of C4 grasses were projected to increase >10% throughout most of the study region at the expense of C3 grasses. There were essentially no areas where C4 grasses decreased in abundance, and the areas with no change were largely the southern Great Plains and the Intermountain Basin and Range of North America. C3 grasses declined throughout with the exception of the north-western Great Plains of the US and Canada, and north central Argentina. Changes in shrub abundance were mixed with some increases in Patagonia and the desert regions of the south-western US; there were also some projected decreases, however, the locations varied across models. Main conclusions The projections made by our regression model were consistent with those of other more complex vegetation dynamics models. Changes in plant community composition in response to climate change may be substantial in certain areas and will probably lead to changes in water and nutrient cycling.

The responses of high latitude ecosystems to global change involve complex interactions among environmental variables, vegetation distribution, carbon dynamics, and water and energy exchange. These responses may have important consequences for the earth system. In this study, we evaluated how vegetation distribution, carbon stocks and turnover, and water and energy exchange are related to environmental variation spanned by the network of the IGBP high latitude transects. While the most notable feature of the high latitude transects is that they generally span temperature gradients from southern to northern latitudes, there are substantial differences in temperature among the transects. Also, along each transect temperature co-varies with precipitation and photosynthetically active radiation, which are also variable among the transects. Both climate and disturbance interact to influence latitudinal patterns of vegetation and soil carbon storage among the transects, and vegetation distribution appears to interact with climate to determine exchanges of heat and moisture in high latitudes. Despite limitations imposed by the data we assembled, the analyses in this study have taken an important step toward clarifying the complexity of interactions among environmental variables, vegetation distribution, carbon stocks and turnover, and water and energy exchange in high latitude regions. This study reveals the need to conduct coordinated global change studies in high latitudes to further elucidate how interactions among climate, disturbance, and vegetation distribution influence carbon dynamics and water and energy exchange in high latitudes.

The Yamal Peninsula in northwest Siberia is undergoing some of the most rapid land-cover and land-use changes in the Arctic due to a combination of gas development, reindeer herding, and climate change. Unusual geological condi- tions (nutrient-poor sands, massive ground ice and extensive landslides) exacerbate the impacts. These changes will likely increase markedly as transportation corridors are built to transport the gas to market. Understanding the nature, extent, causes and consequences (i.e., the cumulative effects) of the past and ongoing rapid changes on the Yamal is important for effective, long-term decision-making and planning. The cumulative effects to vegetation are the focus of this chapter because the plants are a critical component of the Yamal landscape that support the indigenous Nenets people and their reindeer and also protect the underlying ice-rich permafrost from melting. We are using a combination of ground-based studies (a transect of five loca- tions across the Yamal), remote-sensing studies, and analyses of Nenets land-use activities to develop vegetation-change models that can be used to help anticipate future states of the tundra and how those changes might affect traditional reindeer herding practices and the thermal state of the permafrost. This chapter provides an overview of the approach, some early results, and recommendations for expanding the concept of cumulative-effects analysis to include examining the simultaneous and interactive effects of multiple drivers of change.

This chapter provides an overview of observed changes in vegetation productivity in Arctic tundra and boreal forest ecosystems over the past 3 decades, based on satellite remote sensing and other observational records, and relates these to climate variables and sea ice conditions. The emerging patterns and relationships are often complex but clearly reveal a contrast in the response of the tundra and boreal biomes to recent climate change, with the tundra showing increases and undisturbed boreal forests mostly reductions in productivity. The possible reasons for this divergence are discussed and the consequences of continued climate warming for the vegetation in the Arctic region assessed using ecosystem models, both at the biome-scale and at high spatial resolution focussing on plant functional types in the tundra and the tundra-forest ecotones.

The causes of a greening trend detected in the Arctic using the normalized difference vegetation index (NDVI) are still poorly understood. Changes in NDVI are a result of multiple ecological and social factors that affect tundra net primary productivity. Here we use a 25 year time series of AVHRR-derived NDVI data (AVHRR: advanced very high resolution radiometer), climate analysis, a global geographic information database and ground-based studies to examine the spatial and temporal patterns of vegetation greenness on the Yamal Peninsula, Russia. We assess the effects of climate change, gas-field development, reindeer grazing and permafrost degradation. In contrast to the case for Arctic North America, there has not been a significant trend in summer temperature or NDVI, and much of the pattern of NDVI in this region is due to disturbances. There has been a 37% change in early-summer coastal sea-ice concentration, a 4% increase in summer land temperatures and a 7% change in the average time-integrated NDVI over the length of the satellite observations. Gas-field infrastructure is not currently extensive enough to affect regional NDVI patterns. The effect of reindeer is difficult to quantitatively assess because of the lack of control areas where reindeer are excluded. Many of the greenest landscapes on the Yamal are associated with landslides and drainage networks that have resulted from ongoing rapid permafrost degradation. A warming climate and enhanced winter snow are likely to exacerbate positive feedbacks between climate and permafrost thawing. We present a diagram that summarizes the social and ecological factors that influence Arctic NDVI. The NDVI should be viewed as a powerful monitoring tool that integrates the cumulative effect of a multitude of factors affecting Arctic land-cover change.

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

Phenology of vegetation is a sensitive and valuable indicator of the dynamic responses of terrestrial ecosystems to climate change. Therefore, to better understand and predict ecosystems dynamics, it is important to reduce uncertainties in detecting phenological changes. Here, changes in phenology over the past several decades across the northern high-latitude region (≥60°N) were examined by calibrating and analyzing time series of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Very High Resolution Radiometer (AVHRR). Over the past decade (2000–10), an expanded length of the growing season (LOS) was detected by MODIS, largely due to an earlier start of the growing season (SOS) by 4.7 days per decade and a delayed end of the growing season (EOS) by 1.6 days per decade over the northern high latitudes. There were significant differences between North America and Eurasia in phenology from 2000 to 2010 based on MODIS data (SOS: d f = 21, F = 49.02, p d f = 21, F = 49.25, p d f = 21, F = 79.40, p d f = 17, F = 14.63, p = 0.0015; EOS: d f = 17, F = 38.69, p d f = 17, F = 16.47, p = 0.0009) from 2000 to 2008 over the northern high latitudes. Thus, further inter-calibration between the sensors is needed to resolve the inconsistency and to better understand long-term trends of vegetation growth in the Arctic.

Variation of green vegetation cover influences local climate dynamics, exchange of water–heat between land and atmosphere, and hydrological processes. However, the mechanism of interaction between vegetation and local climate change in subtropical areas under climate warming and anthropogenic disturbances is poorly understood. We analyzed spatial–temporal trends of vegetation with moderate-resolution imaging spectroradiometer (MODIS) vegetation index datasets over three sections, namely urban, urban–rural fringe and wildland along an urban–wildland transect in a southern mega-city area in China from 2000–2008. The results show increased photosynthetic activity occurred in the wildland and the stable urban landscape in correspondence to the rising temperature, and a considerable decrease of vegetation activity in the urban–rural fringe area, apparently due to urban expansion. On analyzing the controlling factors of climate change and human drivers of vegetation cover change, we found that temperature contributed to vegetation growth more than precipitation and that rising temperature accelerated plant physiological activity. Meanwhile, human-induced dramatic modification of land cover, e.g. conversion of natural forest and cropland to built-up areas in the urban–rural fringe, has caused significant changes of green vegetation fraction and overall primary production, which may further influence local climate.

This study is presented within the context that climate warming and sea-ice decline has been occurring throughout much of the Arctic over the past several decades, and that terrestrial ecosystems at high latitudes are sensitive to the resultant alterations in surface temperatures. Results are from analyzing interannual satellite records of vegetation greenness across a bioclimate gradient of the Canadian Arctic over the period of 1982-2006. Here, we combine multi-scale sub-pixel analysis and remote sensing time-series analysis to investigate recent decadal changes in vegetation greenness along spatial gradients of summer temperature and vegetation. Linear autoregression temporal analysis of vegetation greenness was performed with relatively "pure" vegetation pixels of Advanced Very High Resolution Radiometer (AVHRR) data, spanning Low Arctic, High Arctic and polar desert ecosystems. Vegetation greenness generally increased over tundra ecosystems in the past two decades. Peak annual greenness increased 0.49-0.79%/yr over the High Arctic where prostrate dwarf shrubs, forbs, mosses and lichens dominate and 0.46-0.67%/yr over the Low Arctic where erect dwarf shrubs and graminoids dominate. However, magnitudes of vegetation greenness differ with length of time series and periods considered, indicating a nonlinear response of terrestrial ecosystems to climate change. The decadal increases of greenness reflect increasing vegetation production during the peak of the growing season, and were likely driven by the recent warming.