Growing Season Vegetation Research Articles

Contribution of Climatic Factors and Human Activities to Vegetation Changes in Arid Grassland

Clarifying the changing trend in vegetation and its affecting variables is extremely valuable for natural resource management. Vegetation changes in the Yinshanbeilu grassland region, which is situated in the centre of Inner Mongolia in northern China and is part of the arid steppe region, are extremely sensitive to climatic factors. In this study, we investigated the changes in vegetation in the Yinshanbeilu grassland zone from the year 2000 to 2020 using the Normalized Difference Vegetation Index (NDVI) data. The contribution of climatic conditions and human activities to the annual and growing season vegetation changes was quantified. The findings revealed that vegetation cover in the Yinshanbeilu grassland zone increased at a rate of 0.00267/a between 2000 and 2020. Throughout the year and during the growing season, precipitation had a greater influence on the growth of vegetation than other climatological factors. In most places, there was a significant positive correlation between the NDVI and precipitation, which negatively correlated with other climatic factors. The average rates at which precipitation, temperature, cumulative sunshine hours, and potential evapotranspiration contributed to changes in NDVI were 0.00173/a, −0.00027/a, 0.00006/a, and 0.00074/a, respectively, for the entire year, and 0.00180/a, −0.00001/a, 0.00021/a, and 0.00059/a for the growing season. The impact of climate change on vegetation activities was more pronounced, accounting for 84.76% of annual NDVI change and 97.36% of growing season NDVI change. Humans contributed 15.24% of total annual NDVI change and 2.64% of growing season NDVI change. This research’s findings serve as scientific support for preserving the environment in the Yinshanbeilu grassland region, as well as an essential reference for government decision making.

Winter snow cover influences growing-season vegetation productivity non-uniformly in the Northern Hemisphere

Ongoing changes in snow cover significantly affect vegetation productivity, but the actual effect of snow cover remains unclear due to a poor understanding of its lagged effect. Here, we used multisource datasets to investigate the lagged effect of snow cover on vegetation productivity in Northern Hemisphere ( > 40°N) ecosystems from 2000 to 2018. We found a widespread lagged effect of snow cover ( > 40%, P < 0.05) on growing season vegetation productivity (mean ~73-day lag). The effect of snow cover on vegetation productivity was underestimated by over 10% of the areas without considering regional lagged time differences. A longer lagged effect generally occurred in warm and humid areas, and areas with increased lagged time (66%) were greater than those with decreased trends. Moreover, changes in lagged effect were strongly driven by climate factors, followed by soil and topography factors. These findings emphasize the need to consider lagged time differences of snow cover when investigating snow-vegetation productivity interactions.

Resilience of riparian vegetation productivity to early 21st century drought in northern California, USA

AbstractDrought and intensive land use can interact as stressors on riparian vegetation, especially along rivers flowing through seasonally dry landscapes. Knowledge of past riparian vegetation response to drought and land use change can provide land managers with a better understanding of changes induced by upstream management actions, climate change, and chronic stressors. To investigate the response of riparian vegetation productivity to drought and land use, we developed a 21‐year time series (2000–2020) of growing season vegetation dynamics using near‐infrared reflectance of vegetation (NIRV) derived from satellite data across 30 watershed subbasins that drain into the San Francisco Bay Delta in central California, USA. We observed a strong response of riparian vegetation to drought, but rapid recovery and very few long‐term declines in productivity. At a local level, vegetation communities' response to drought and post‐drought productivity dynamics were highly variable across biophysical settings and land use gradients. Most of the riparian areas with long‐term declines in NIRV were located in the lower elevation Coast Range on the western side of the study area where there is little to no water engineering or agricultural irrigation runoff to subsidize riparian vegetation. Riparian areas with the greatest long‐term increase were along rivers draining the higher elevation Sierra Nevada range to the east. Our results suggest that river systems with a high proportion of water originating as snowmelt may be more buffered against long‐term drought‐driven declines in productivity than those dependent exclusively on winter rainfall. The long‐term increase in NIRV in the vast majority of riparian areas within our study area may also have been driven in part by increasing atmospheric CO2 concentrations, which have been shown to increase plant water use efficiency.

Effects of Vegetation Belt Movement on Wildfire in the Mongolian Plateau over the Past 40 Years

The frequency and intensity of fires are increasing because of warmer temperatures and increased droughts, as well as climate-change induced fuel distribution changes. Vegetation in environments, such as those in the mid-to-high latitudes and high elevations, moves to higher latitudes or elevations in response to global warming. Over the past 40 years, the Mongolian Plateau has been arid and semi-arid, with a decrease in growing season vegetation in the southwest and an increase in growing season vegetation in the northeast. The northward movement of vegetation has brought fires, especially in the Dornod, Sukhbaatar, and Kent provinces near the Kent Mountains, and has become more obvious in the past 20 years. The occurrence of a dead fuel index (DFI) with high probability is distributed in northern Mongolia, the border area between China and Mongolia, and the forest-side meadow-steppe region of the Greater Khingan Mountains. These findings suggest that vegetation is moving northward because of climate change and this presents a challenge of future warming spreading fire northward, adding material to the study of the relationship between the northward movement of global vegetation and fires.

Temporal and Spatial Variation in Vegetation Coverage and Its Response to Climatic Change in Marshes of Sanjiang Plain, China

Sanjiang Plain is the most extensive marsh distribution region in China. Marshes in this region can protect biodiversity, regulate climate, and provide habitats for wild animals and plants. The normalized difference vegetation index (NDVI) is a crucial indicator of vegetation coverage, which may reflect ecosystem structure and functional features. Clarifying the spatiotemporal change of marsh coverage and its climatic drivers is vital for observing and predicting vegetation change in Sanjiang Plain. Using meteorological dataand MODIS NDVI data from 2000 to 2020, we analyzed the spatiotemporal variation in marsh vegetation coverage and climatic change effects in Sanjiang Plain. We found that the growing season vegetation NDVI of marsh increased significantly at a rate of 0.011/decade, indicating that the marsh vegetation growth has obviously improved during the past 21 years. Furthermore, we found that the increase of minimum (Tmin) and maximum (Tmax) temperature in July can significantly promote the marsh plant growth, and increasing nighttime Tmin has a stronger impact on promoting the growth than increasing daytime Tmax in this month. In addition, the increase of daytime Tmax in August can promote the marsh vegetation growth, whereas the increasing precipitation in August was unfavorable for the growth in Sanjiang Plain.

Responses of autumn vegetation phenology to climate change and urbanization at northern middle and high latitudes

• Urbanization influences the vegetation EOS depending on the temperature context. • Urbanization induced advanced vegetation EOS by increasing nighttime temperature. • Strengthened urbanization weakens the effects of temperature on vegetation dormancy. Shifts in vegetation phenology caused by climate change and human activities play a crucial role in regulating global terrestrial ecosystems' nutrients and carbon cycling. However, the mechanism underlying autumn vegetation’s phenological reaction to urbanization remains unexplained. Using normalized difference vegetation index (NDVI) and a nighttime light remote sensing dataset, we examined the dynamics of the end of the growing season (EOS) and responses to climate change and urbanization from 1992 to 2015 across the northern middle and high latitudes (north of 30° N). EOS exhibited an advanced trend with a pace of −0.22 days/yr across the study area. The spatial proportion of advanced EOS was 62.66%, which was more pronounced north of 60° N. In most regions, increased precipitation delayed EOS, whereas daytime temperature (Tmax) and nighttime temperature (Tmin) exhibited the opposite impacts on EOS, which was related to water availability in the study area. In general, we found that higher urbanization could induce earlier EOS in warm regions (south of 46° N) and delay EOS in cold regions (north of 46° N). Urbanization could cause an increase in Tmin and Tmax, and EOS exhibited a significant negative sensitivity to Tmin across the urbanization levels, which decreased from −0.175 days/°C to −0.112 days/°C. Our results indicated that urbanization could advance the EOS by increasing Tmin, however, such a negative effect may be weakened with the development of urbanization. Our findings demonstrated the complicated influence mechanisms of autumn vegetation phenology induced by climate change and urbanization, which provides a unique perspective for exploring the contribution of growing season vegetation to the carbon sink and global carbon balance.

Seasonal Variation of Vegetation and Its Spatiotemporal Response to Climatic Factors in the Qilian Mountains, China

The purpose of this study is to reveal the seasonal difference in vegetation variation and its seasonal response to climate factors in the Qilian Mountains (QM) under the background of global warming. Based on the MOD13 A2 normalized difference vegetation index (NDVI) data and meteorological data, this study analyzed the spatiotemporal dynamics and stability of vegetation in different seasons by using the mean value method, trend analysis and stability analysis method, and discussed their seasonal responses to climatic factors based on the correlation analysis method. The results show that the vegetation cover in the QM experienced a significant upward trend in the past 21 years, but there were obvious spatial differences in vegetation change in different seasons. The growth rate of vegetation in summer was the fastest, and summer vegetation provided the most significant contribution to the growing season vegetation. The order of vegetation stability in the QM among the seasons was growing season &gt; summer &gt; spring &gt; autumn. The vegetation change was obviously affected by temperature in spring, while it was mainly controlled by precipitation in the growing season and summer. The response of vegetation to climatic factors was not significant in autumn. Our results can provide important data support for ecological protection in the QM and socioeconomic development in the Hexi Corridor.

Study on the influence of meteorological elements on growing season vegetation coverage in Xinjiang, China

&lt;abstract&gt;&lt;p&gt;Xinjiang is a typical arid and semi-arid Mountain basin system, which make the regional ecosystem extremely fragile. Studying the influence of climate on vegetation is conducive to qualitatively analyze the change trend of vegetation coverage in this region. Therefore, utilizing vegetation coverage and main meteorological elements (temperature, precipitation, relative humidity, sunshine hours) data in Xinjiang province, this paper carried out the influence of multiple meteorological elements on vegetation coverage changes, and constructed a model of the impact of multiple meteorological elements on the growing season vegetation coverage based on random forest. The model can better simulate the vegetation coverage in 2017 and 2018, with an average error of 0.027, in consequence it can well forecast whether the vegetation is high-density or low-density in this area. Correlation analysis and variable importance show that the critical meteorological factors affecting vegetation cover change are relative humidity and sunshine hours, accounting for 73% of the vegetation coverage area. The results are helpful to understand how meteorological factors affect the vegetation coverage, and then provide a theoretical reference for the construction of ecological security in Xinjiang.&lt;/p&gt;&lt;/abstract&gt;

Winter snow and spring temperature have differential effects on vegetation phenology and productivity across Arctic plant communities.

Tundra dominates two-thirds of the unglaciated, terrestrial Arctic. Although this region has experienced rapid and widespread changes in vegetation phenology and productivity over the last several decades, the specific climatic drivers responsible for this change remain poorly understood. Here we quantified the effect of winter snowpack and early spring temperature conditions on growing season vegetation phenology (timing of the start, peak, and end of the growing season) and productivity of the dominant tundra vegetation communities of Arctic Alaska. We used daily remotely sensed normalized difference vegetation index (NDVI), and daily snowpack and temperature variables produced by SnowModel and MicroMet, coupled physically based snow and meteorological modeling tools, to (1) determine the most important snowpack and thermal controls on tundra vegetation phenology and productivity and (2) describe the direction of these relationships within each vegetation community. Our results show that soil temperature under the snowpack, snowmelt timing, and air temperature following snowmelt are the most important drivers of growing season timing and productivity among Arctic vegetation communities. Air temperature after snowmelt was the most important control on timing of season start and end, with warmer conditions contributing to earlier phenology in all vegetation communities. In contrast, the controls on the timing of peak season and productivity also included snowmelt timing and soil temperature under the snowpack, dictated in part by the snow insulating capacity. The results of this novel analysis suggest that while future warming effects on phenology may be consistent across communities of the tundra biome, warming may result in divergent, community-specific productivity responses if coupled with reduced snow insulating capacity lowers winter soil temperature and potential nutrient cycling in the soil.

Growing Season Vegetation Dynamics Based on NDVI and the Driving Forces in Nepal during 1982-2015

Monitoring and attributing growing season vegetation dynamics have become crucial for maintaining the structure and function of the ecosystem. The objective of this research was to examine the spatial and temporal vegetation changes and explore their driving forces during growing season in Nepal. It also explored the variation of Normalized Difference Vegetation Index (NDVI) in different altitudes at each 100m interval. The National Oceanic and Atmospheric Administration (NOAA) NDVI, monthly temperature, precipitation and Shuttle Radar Topography Mission (SRTM) 90m Digital Elevation Model (DEM) were used. The linear regression model, Sen’s slope, Mann Kendall test and Pearson correlation between NDVI and climate, i.e., temperature and precipitation were computed. The driving forces were identified based on threshold segmentation method. Our results showed positive intensity of vegetation change. The NDVI has significantly increased at the rate of 0.001yr-1, 0.0005yr-1 and 0.002yr-1 in growing season, spring and autumn but it has insignificantly increased at the rate of 0.0003yr-1 in summer. In the meantime, growing season temperature has significantly increased with an average warming trend of 0.03&amp;deg;Cyr-1 but precipitation decreased at the rate of 2.76 mm yr-1 during 1982-2015. The NDVI increased in 84.20% (53.08% significant) of the area. The correlation between NDVI and temperature was found positive whereas correlation with precipitation was negative. Spatially, 84.05% of the study area found positive correlation between NDVI and temperature with 25.72% significance (p&lt;0.05) which was very less with precipitation. Our results demonstrate that NDVI was strongly correlated with temperature compared with precipitation. Beyond the climate, NDVI changes were also attributed to multi-control environments and ecological restoration in Nepal.

Increased future occurrences of the exceptional 2018\u20132019 Central European drought under global warming

Since the spring 2018, a large part of Europe has been in the midst of a record-setting drought. Using long-term observations, we demonstrate that the occurrence of the 2018–2019 (consecutive) summer drought is unprecedented in the last 250 years, and its combined impact on the growing season vegetation activities is stronger compared to the 2003 European drought. Using a suite of climate model simulation outputs, we underpin the role of anthropogenic warming on exacerbating the future risk of such a consecutive drought event. Under the highest Representative Concentration Pathway, (RCP 8.5), we notice a seven-fold increase in the occurrence of the consecutive droughts, with additional 40 (pm , 5) million ha of cultivated areas being affected by such droughts, during the second half of the twenty-first century. The occurrence is significantly reduced under low and medium scenarios (RCP 2.6 and RCP 4.5), suggesting that an effective mitigation strategy could aid in reducing the risk of future consecutive droughts.

Assessment of varying changes of vegetation and the response to climatic factors using GIMMS NDVI3g on the Tibetan Plateau.

Under the context of global climate change, vegetation on the Tibetan Plateau (TP) has experienced significant changes during the past three decades. In this study, the spatiotemporal changes of growing season vegetation index (GSVI) on the TP were analyzed using various methods from pixel level to ecoregion level. In addition, a relative importance approach was employed to investigate the regulating effect of temperature and precipitation on vegetation. During the period of 1982–2012, vegetation on the TP was generally experiencing a greening trend, but with pronounced fluctuations. The interannual variation of the long-term GSVI was most significant in the Qaidam Basin and southern forest. At ecoregion scale, vegetation in the arid and frigid arid zones showed a browning tendency, with other ecoregions presenting greener trends. Over a large proportion of the TP, there exist change points in the GSVI time series, which were mainly concentered around the year 1996 and 2000. The Hurst exponent identified that a majority (88%) of the vegetation on the plateau would maintain a persistent trend in the future, which would mainly consist of undetermined development and greening trends. TP vegetation during the 1990s experienced more greening than in the 1980s or 2000s according to the interdecadal analysis. The long-term change in growing season vegetation was most positively correlated with the temperature during the same period, followed by the temperature in the preseason and postseason periods. There were more negative relationships of vegetation change with precipitation than with temperature. The relative contribution of the temperature to the vegetation changes exhibited an opposite spatial pattern to that of precipitation. Overall, the findings in this work provide an essential archive of decade-scale vegetation dynamics that may be helpful for projecting the future ecosystem dynamics on the Tibetan Plateau, such as the consistent greening.

Relative Contribution of Growing Season Length and Amplitude to Long-Term Trend and Interannual Variability of Vegetation Productivity over Northeast China

In the context of global warming, the terrestrial ecosystem productivity over the Northern Hemisphere presents a substantially enhanced trend. The magnitude of summer vegetation maximum growth, known as peak growth, remains only partially understood for its role in regulating changes in vegetation productivity. This study aimed to estimate the spatiotemporal dynamics of the length of growing season (LOS) and maximum growth magnitude (MAG) over Northeast China (NEC) using a long-term satellite record of normalized difference vegetation index (NDVI) for the period 1982–2015, and quantifying their relative contribution to the long-term trend and inter-annual variability (IAV) of vegetation productivity. Firstly, the key phenological metrics, including MAG and start and end of growing season (SOS, EOS), were derived. Secondly, growing season vegetation productivity, measured as the Summary of Vegetation Index (VIsum), was obtained by cumulating NDVI values. Thirdly, the relative impacts of LOS and MAG on the trend and IAV in VIsum were explored using the relative importance (RI) method at pixel and vegetation cover type level. For the entire NEC, LOS, and MAG exhibited a slightly decreasing trend and a weak increasing trend, respectively, thus resulting in an insignificant change in VIsum. The temporal phases of VIsum presented a consistent pace with LOS, but changed asynchronously with MAG. There was an underlying cycle of about 10 years in the changes of LOS, MAG, and VIsum. At a regional scale, VIsum tended to maintain a rising trend in the northern coniferous forest and grassland in western and southern NEC. The spatial distribution of the temporal trends of LOS and MAG generally show a contrasting pattern, in which LOS duration is expected to shorten (negative trend) in the central cropland and in some southwestern grasslands (81.5% of the vegetated area), while MAG would increase (positive trend) in croplands, southern grasslands, and northern coniferous forests (16.5%). The correlation index for the entire NEC suggested that LOS was negatively associated with MAG, indicating that the extended vegetation growth duration would result in a lower growth peak and vice versa. Across the various vegetation types, LOS was a substantial factor in controlling both the trend and IAV of VIsum (RI = 75%). There was an opposite spatial pattern in the relative contribution of LOS and MAG to VIsum, where LOS dominated in the northern coniferous forests and in the eastern broadleaf forests, with MAG mainly impacting croplands and the western grasslands (RI = 27%). Although LOS was still the key factor controlling the trend and IAV of VIsum during the study period, this situation may change in the case peak growth amplitude gradually increases in the future.

Attribution of growing season vegetation activity to climate change and human activities in the Three-River Headwaters Region, China

AbstractOver the past century, vegetation change has been reported at global, national, and regional scales, accompanied by significant climate change and intensified human activities. Among the regions is the rangeland of the Three-River Headwaters Region (TRHR) in China. However, which factor dominates in causing vegetation change in this region is still under considerable debate, and how would the grasslands adapt to the changing environment is largely unknown. To address these issues, we attribute growing season vegetation activity to climate change and human activities, investigate the interactions among different driving variables, and explore the dynamic relationship between vegetation activity and the driving variables. We perform Mann–Kendall trend analysis, Pearson correlation analysis, and partial correlation analysis. The results indicate that the dominant factor for vegetation growth, during the period 1995–2014, was temperature for the southeastern and southern parts of the TRHR, precipitation for the western part, and solar radiation for the northeastern part. The regulation effects of temperature on precipitation and cloud cover contributed to vegetation growth, while grazing activity and population activity offset the positive contribution of climate change. The dynamic relationship between vegetation activity and the driving variables reflected the acclimatization and adaption processes of vegetation, which needs further investigation.

NDVI-based vegetation dynamics and its response to climate changes at Amur-Heilongjiang River Basin from 1982 to 2015

Vegetation in Northern Hemisphere, being sensitive to climate change, plays an important role in the carbon cycles between land and the atmosphere. The response of vegetation to climate change was analyzed at pixel, biome and regional scale in Amur-Heilongjiang River Basin (AHRB) for growing season, spring, summer and autumn using Normalized Difference Vegetation Index and gridded climate data for the period 1982–2015. NDVI and climate variables trend detection methods and correlation analysis were applied. The potential impacts of human activities on growing season NDVI dynamics were investigated further using residual trend analysis. Results showed that at river basin scale, growing season vegetation experienced a discontinuous greening trend with two reversals, demonstrating that NDVI initially increased to mid-1990s, then declined to mid-2000s, and finally rebounded to 2015. This may be attributed to the shifting between drought and wet trends, indicating growing season NDVI was mainly regulated by precipitation. Temperature was the dominant factor on affecting spring vegetation growth while autumn NDVI showed negative correlation with precipitation due to the relation of precipitation with sunshine hours available for photosynthesis. The response of vegetation growth to climatic variations varied among vegetation types. Grassland NDVI exhibited positive correlation with precipitation in all time ranges. NDVI of needleleaved forest, broadleaved forest, mixed forest and woodland were positively correlated with temperature in all seasons, while showing significant negative correlation with autumn precipitation. Residual trend analysis revealed that human activities might lead to the vegetation degradation in China farming zone of AHRB. Fires also play an important role in regulating vegetation dynamics in the region. Results of our analysis can be used by national governments from three countries of AHRB in managing and negotiating vegetation resources of the region.

Satellite‐Observed Major Greening and Biomass Increase in South China Karst During Recent Decade

AbstractAbove‐ground vegetation biomass is one of the major carbon sinks and provides both provisioning (e.g., forestry products) and regulating ecosystem services (by sequestering carbon). Continuing deforestation and climate change threaten this natural resource but can effectively be countered by national conservation policies. Here we present time series (1999–2017) derived from complementary satellite systems to describe a phenomenon of global significance: the greening of South China Karst. We find a major increase in growing season vegetation cover from 69% in 1999 to 81% in 2017 occurring over ~1.4 million km2. Over 1999–2012, we report one of the globally largest increases in biomass to occur in the South China Karst region (on average +4% over 0.9 million km2), which accounts for ~5% of the global areas characterized with increases in biomass. These increases in southern China's vegetation have occurred despite a decline in rainfall (−8%) and soil moisture (−5%) between 1999 and 2012 and are derived from effects of forestry and conservation activities at an unprecedented spatial scale in human history (~20,000 km2 yr−1 since 2002). These findings have major implications for the provisioning of ecosystem services not only for the Chinese karst ecosystem (e.g., carbon storage, water filtration, and timber production) but also for the study of global carbon cycles.

Global vegetation productivity response to climatic oscillations during the satellite era.

Climate control on global vegetation productivity patterns has intensified in response to recent global warming. Yet, the contributions of the leading internal climatic variations to global vegetation productivity are poorly understood. Here, we use 30years of global satellite observations to study climatic variations controls on continental and global vegetation productivity patterns. El Niño-Southern Oscillation (ENSO) phases (La Niña, neutral, and El Niño years) appear to be a weaker control on global-scale vegetation productivity than previously thought, although continental-scale responses are substantial. There is also clear evidence that other non-ENSO climatic variations have a strong control on spatial patterns of vegetation productivity mainly through their influence on temperature. Among the eight leading internal climatic variations, the East Atlantic/West Russia Pattern extensively controls the ensuing year vegetation productivity of the most productive tropical and temperate forest ecosystems of the Earth's vegetated surface through directionally consistent influence on vegetation greenness. The Community Climate System Model (CCSM4) simulations do not capture the observed patterns of vegetation productivity responses to internal climatic variations. Our analyses show the ubiquitous control of climatic variations on vegetation productivity and can further guide CCSM and other Earth system models developments to represent vegetation response patterns to unforced variability. Several winter time internal climatic variation indices show strong potentials on predicting growing season vegetation productivity two to six seasons ahead which enables national governments and farmers forecast crop yield to ensure supplies of affordable food, famine early warning, and plan management options to minimize yield losses ahead of time.

Changes in Growing Season Vegetation and Their Associated Driving Forces in China during 2001–2012

In recent decades, the monitoring of vegetation dynamics has become crucial because of its important role in terrestrial ecosystems. In this study, a satellite-derived normalized difference vegetation index (NDVI) was combined with climate factors to explore the spatiotemporal patterns of vegetation change during the growing season, as well as their driving forces in China from 2001 to 2012. Our results showed that the growing season NDVI increased continuously during 2001–2012, with a linear trend of 1.4%/10 years (p &lt; 0.01). The NDVI in north China mainly exhibited an increasing spatial trend, but this trend was generally decreasing in south China. The vegetation dynamics were mainly at a moderate intensity level in both the increasing and decreasing areas. The significantly increasing trend in the NDVI for arid and semi-arid areas of northwest China was attributed mainly to an increasing trend in the NDVI during the spring, whereas that for the north and northeast of China was due to an increasing trend in the NDVI during the summer and autumn. Different vegetation types exhibited great variation in their trends, where the grass-forb community had the highest linear trend of 2%/10 years (p &lt; 0.05), followed by meadow, and needle-leaf forest with the lowest increasing trend, i.e., a linear trend of 0.3%/10 years. Our results also suggested that the cumulative precipitation during the growing season had a dominant effect on the vegetation dynamics compared with temperature for all six vegetation types. In addition, the response of different vegetation types to climate variability exhibited considerable differences. In terms of anthropological activity, our statistical analyses showed that there was a strong correlation between the cumulative afforestation area and NDVI during the study period, especially in a pilot region for ecological restoration, thereby suggesting the important role of ecological restoration programs in ecological recovery throughout China in the last decade.

Evaporative cooling over the Tibetan Plateau induced by vegetation growth

In the Arctic, climate warming enhances vegetation activity by extending the length of the growing season and intensifying maximum rates of productivity. In turn, increased vegetation productivity reduces albedo, which causes a positive feedback on temperature. Over the Tibetan Plateau (TP), regional vegetation greening has also been observed in response to recent warming. Here, we show that in contrast to arctic regions, increased growing season vegetation activity over the TP may have attenuated surface warming. This negative feedback on growing season vegetation temperature is attributed to enhanced evapotranspiration (ET). The extra energy available at the surface, which results from lower albedo, is efficiently dissipated by evaporative cooling. The net effect is a decrease in daily maximum temperature and the diurnal temperature range, which is supported by statistical analyses of in situ observations and by decomposition of the surface energy budget. A daytime cooling effect from increased vegetation activity is also modeled from a set of regional weather research and forecasting (WRF) mesoscale model simulations, but with a magnitude smaller than observed, likely because the WRF model simulates a weaker ET enhancement. Our results suggest that actions to restore native grasslands in degraded areas, roughly one-third of the plateau, will both facilitate a sustainable ecological development in this region and have local climate cobenefits. More accurate simulations of the biophysical coupling between the land surface and the atmosphere are needed to help understand regional climate change over the TP, and possible larger scale feedbacks between climate in the TP and the Asian monsoon system.

Attribution of satellite-observed vegetation trends in a hyper-arid region of the Heihe River basin, Western China

Abstract. Terrestrial vegetation dynamics are closely influenced by both climate and by both climate and by land use and/or land cover change (LULCC) caused by human activities. Both can change over time in a monotonic way and it can be difficult to separate the effects of climate change from LULCC on vegetation. Here we attempt to attribute trends in the fractional green vegetation cover to climate variability and to human activity in Ejina Region, a hyper-arid landlocked region in northwest China. This region is dominated by extensive deserts with relatively small areas of irrigation located along the major water courses as is typical throughout much of Central Asia. Variations of fractional vegetation cover from 2000 to 2012 were determined using Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index data with 250 m spatial resolution over 16-day intervals. We found that the fractional vegetation cover in this hyper-arid region is very low but that the mean growing season vegetation cover has increased from 3.4% in 2000 to 4.5% in 2012. The largest contribution to the overall greening was due to changes in green vegetation cover of the extensive desert areas with a smaller contribution due to changes in the area of irrigated land. Comprehensive analysis with different precipitation data sources found that the greening of the desert was associated with increases in regional precipitation. We further report that the area of land irrigated each year can be predicted using the runoff gauged 1 year earlier. Taken together, water availability both from precipitation in the desert and runoff inflow for the irrigation agricultural lands can explain at least 52% of the total variance in regional vegetation cover from 2000 to 2010. The results demonstrate that it is possible to separate the satellite-observed changes in green vegetation cover into components due to climate and human modifications. Such results inform management on the implications for water allocation between oases in the middle and lower reaches and for water management in the Ejina oasis.