Changes In Vegetation Activity Research Articles

Vegetation Greening, Extended Growing Seasons, and Temperature Feedbacks in Warming Temperate Grasslands of China

Abstract Vegetation activity and phenology are significantly affected by climate change, and changes in vegetation activity and phenology can in turn affect regional or global climate patterns. As one of the world’s great biomes, temperate grasslands have undergone remarkable changes in recent decades, but the connections between vegetation activity and phenology changes and regional climate there have remained unclear. Using the observation minus reanalysis (OMR) method, this study investigated the possible effects of vegetation activity and vegetation growing season changes on air temperatures in temperate grasslands of China. The results showed that average NDVI of the temperate grassland significantly increased by 0.011 decade−1 for the growing season during 1982–2015. The growing season started earlier and ended later, resulting in an extension. Increased vegetation activity during spring and autumn significantly warmed spring and autumn air temperatures by reducing albedo. By contrast, summer greening had no significant effect on summer temperature, due to the opposing effects of decreased albedo and enhanced evapotranspiration on temperature. The earlier start and later end of the growing season contributed to warmer spring and autumn air temperatures. As phenological changes had no significant effect on summer temperature, the extended growing season warmed air temperature. Our results suggest that the climate change–induced increasing vegetation activity and extended growing seasons can further aggravate regional warming in temperate grasslands of China, implying that the effects of vegetation activity and phenology changes on regional climate should be considered in climate models for accurately simulating climate change in temperate grasslands.

Vegetation activity enhanced in India during the COVID-19 lockdowns: evidence from satellite data

The Severe Acute Respiratory Syndrome-COronaVIrus Diseases 2019 (SARS-COVID-19) has sternly affected the entire world in terms of human health, loss of lives, and huge economic losses. However, pandemic-triggered lockdown (LD) events (as a preventive measure) have compelled to stop or reduce major economic activities, exerting positive impacts on the terrestrial environment. We deployed a variety of satellite products (i.e., normalized difference vegetation index (NDVI), solar-induced chlorophyll fluorescence (SIF), and aerosol optical depth (AOD)) along with gridded climatic dataset (temperature (TEMP), precipitation (PREC), and net radiation (NR)) to quantify the changes in vegetation activity (greenness and productivity) during the LD period over the Indian biogeographic provinces (BGPs) as compared to the average conditions over the previous three years (2017-2019). The analysis of the NDVI and SIF data revealed that vegetation greenness and productivity significantly enhanced during LD periods (by up to 37 to 55%, respectively). The influence of climatic drivers (PREC, TEMP, and NR) on vegetation activity was also investigated. We found that the enhancement in the vegetation activity (over BGPs) during the LD period was not entirely driven by the climatic parameters, and was therefore inferred to be also influenced by the LD events. Moreover, vegetation activity around the mining clusters were largely improved during the LD period (by up to 78%) over the coal mining, followed by iron ore mining (up to 63%), and stone mining (up to 41%) clusters) regions. In a nutshell, it can be deliberated that COVID-triggered preventive measures (i.e., country-level LD, travel bans, industry ban, curtail in mining capacity, among others) likely enhanced vegetation health and productivity. Thereby, regulatory measures can be seen as a viable option for improving the terrestrial environmental conditions in the context of climate change in the near future.

Increased association between climate change and vegetation index variation promotes the coupling of dominant factors and vegetation growth

Vegetation productivity dynamics are closely related to climate change, and water availability determines vegetation growth in water-limited ecosystems. Nevertheless, how changes in the interactions between climatic factors and vegetation activity variation regulate the relationship between their trends remains unclear. The Normalized Difference Vegetation Index (NDVI) is an effective proxy of vegetation growth. First, we investigated the NDVI trends, and the results revealed a vegetation activity with weaker greening and greater spatial heterogeneity after an obvious land-cover breakpoint in 1999 compared with that before 1999 in northwest China. Notably, the Loess Plateau greatly led the greenness trends, but the Tibet Plateau showed mean browning after 1999, which implied that the coupling of climate change and vegetation trends varied with spatio-temporal changes. Subsequently, using the Geographical Detector Method (GDM), we quantified and compared the association between climate change and the interannual variability of NDVI in the two stages. Vegetation productivity variation is more closely related to changes in climatic factors after 1999 compared with that before 1999. Precipitation (PPT) and vapor pressure deficit (VPD) are the primary constraints to vegetation growth in both stages. Patterns in NDVI trend increases are consistent with those of increased PPT and decreased VPD and vice versa after 1999. However, the same patterns were not observed before 1999 because of the weak association between climate change and NDVI variation. This implicated a great significance of the association between climate change and changes in vegetation activity for the prediction of potential carbon sequestration due to the shift of dominant factors and their trends under future climate change.

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

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

Benchtop μXRF as a tool for speleothem trace elemental analysis: Validation, limitations and application on an Eemian to early Weichselian (125–97 ka) stalagmite from Belgium

Variations of trace element (e.g. Mg, Sr, Ba, Fe, Zn etc.) concentrations along a speleothem's growth axis constitute important paleoclimate proxies. The use of laboratory micro X-ray fluorescence spectrometry as a fast and cheap alternative for conventional mass spectrometry techniques for trace element analysis on speleothems has been explored in the past and yielded satisfactory results. However, within the speleothem community there is need for an in-depth investigation of the full potential of this analytical technique. Compared to other types of paleoclimate archives, benchtop (μ)XRF analysis on speleothems is analytically more challenging because of the high-crystalline speleothem matrix and the low abundance of the elements of interest. In this study, several speleothem samples with differences in mineralogy (calcite versus aragonite) and composition are investigated. Various instrumental parameters are tested and recommendations are made for future studies applying (μ)XRF analysis to speleothems. Quantification based on a multiple standard calibration and an assessment of the error is carried out. Through validation with mass spectrometry techniques, it is confirmed that benchtop μXRF devises are able to generate speleothem trace element records. Successful results were obtained for Sr, Mg and Fe, while Zn and Ba were quantified in samples characterized by high concentrations. Nevertheless, caution has to be taken when interpreting the results, due to the presence of diffraction caused by the crystallinity of the samples. The elements which provide reliable results are sample specific and depend on the type of matrix and elemental abundance. These findings are applied on an Eemian to early Weichselian stalagmite from the Han-sur-Lesse Cave, Belgium. Time series were constructed for Mg and Sr, creating a multiproxy dataset together with previously obtained stable isotope (δ13C and δ18O) ratios, growth-rate and stalagmite morphology. It appears that Mg and Sr are not primarily controlled by prior calcite precipitation, but rather by changes in vegetation activity above the cave.

Assessing the Impacts of Extreme Climate Events on Vegetation Activity in the North South Transect of Eastern China (NSTEC)

Extreme climate events frequently exert serious effects on terrestrial vegetation activity. However, these effects are still uncertain in widely distributed areas with different climate zones. Transect analysis is important to understand how terrestrial vegetation responds to climate change, especially extreme climate events, by substituting space for time. In this paper, seven extreme climate indices and the Normalized Difference Vegetation Index (NDVI) are employed to examine changes in the extreme climate events and vegetation activity. To reduce the uncertainty of the NDVI, two satellite-derived NDVI datasets, including the third generation Global Inventory Monitoring and Modeling System (GIMMS-3g) NDVI dataset and the NDVI from the National Oceanic and Atmospheric Administration (NOAA) satellites on Star Web Servers (SWS), were employed to capture changes in vegetation activity. The impacts of climate extremes on vegetation activity were then assessed over the period of 1982–2012 using the North–South Transect of Eastern China (NSTEC) as a case. The results show that vegetation activity was overall strengthened from 1982 to 2012 in the NSTEC. In addition, extreme high temperature events revealed an increased trend of approximately 5.15 days per decade, while a weakened trend (not significant) was found in extreme cold temperature events. The strengthened vegetation activities could be associated with enhanced extreme high temperature events and weakened extreme cold temperature events over the past decades in most of the NSTEC. Despite this, inversed changes were also found locally between vegetation activity and extreme climate events (e.g., in the Northeast Plain). These phenomena could be associated with differences in vegetation type, human activity, as well as the combined effects of the frequency and intensity of extreme climate events. This study highlights the importance of accounting for the vital roles of extreme climate effects on vegetation activity.

Elevation-dependent decline in vegetation greening rate driven by increasing dryness based on three satellite NDVI datasets on the Tibetan Plateau

Abstract In northern high-latitude regions, amplified vegetation greening has been observed due to a larger warming rate than the rate at low latitudes. Similarly, on the Tibetan Plateau (TP), the warming rate is larger at high elevation than that at low elevation. Our results show that large discrepancies exist in the trends in the satellite-derived Normalized Difference Vegetation Index (NDVI) during 2000–2012, indicating the importance of using three satellite-derived NDVI datasets (Global Inventory Modeling and Mapping Studies, Moderate Resolution Imaging Spectroradiometer and SPOT) in the evaluation of vegetation activity on the TP. Based on three NDVI datasets, during 2000–2012, rising temperature drove the regional vegetation greening across the TP, but the vegetation greening rate contrasted with that of elevation-dependent warming. Here, with simultaneous use of climate observation data, we found that declining water availability with rising elevation may restrict and offset the positive effect of rising temperature on vegetation greening, resulting in the declining rate of vegetation greening as elevation increases on the TP. Our results highlight the significant influence of precipitation on elevation-dependent changes in vegetation activity in rapidly warming mountain ecosystems.

MODIS detection of vegetation changes and investigation of causal factors in Poyang Lake basin, China for 2001–2015

In recent decades, vegetation has shown an overall greening trend in response to rising global temperatures. At the same time, vegetation browning is still worthy of attention, particularly in humid regions with dense vegetation coverage. This study used 15 years (2001–2015) of Terra Moderate-resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data in an effort to detect the overall trends and abrupt changes in vegetation activity over the Poyang Lake basin, which is a typical humid region that contains the largest freshwater lake in China. MODIS NDVI data showed a vegetation greening trend over 94.9% of the basin land. Although the basin has been extensively afforested since the 1980s, there was still a vegetation browning trend over 5.1% of the basin land area, primarily as a result of urbanization. Abrupt vegetation decreases were observed over 7.9% of the basin land area from 2004 to 2012. Most of the decreases were likely caused by the nationwide snow storms in early 2008 and the widespread insect outbreaks as a result of abnormal hydrometeorological conditions. Abrupt vegetation increases were observed over 1.6% of the basin land area in the same period. Most of the increases were likely attributed to the continued efforts of afforestation that transformed large woody savanna lands to mixed forests. The results provided spatial details, time nodes and causal factors of vegetation changes, particularly vegetation decreases, which will benefit government organizations when taking remedial measures.

Seasonal and interannual changes in vegetation activity of tropical forests in Southeast Asia

Tropical vegetation has been suggested to be vulnerable to future climate change. At the regional scale, few studies have focused on the fluctuations of vegetation activity of tropical forests in Southeast Asia, which is an important area of tropical vegetation. Here, we investigated the spatio-temporal variability of vegetation photosynthetic activity in Southeast Asia using three independent satellite-derived Normalized Difference Vegetation Index (NDVI) products (Global Inventory Modeling and Mapping Studies group using data from Advanced Very High Resolution Radiometer (GIMMS AVHRR) NDVI3g, Système Pour l’Observation de la Terre VEGETATION (SPOT-VGT), and MODerate resolution Imaging Spectroradiometer (MODIS)). We also used the recently developed Sun-Induced chlorophyll Fluorescence (SIF) from the Greenhouse gases Observing SATellite (GOSAT), a proxy of actual photosynthesis, as a complement to NDVI. In forests with pronounced wet-dry seasonal cycle (the north and south regions of Southeast Asia), we found consistent relationships between NDVI and climate factors (precipitation, temperature and solar radiation). At the seasonal scale, all of the datasets showed that the NDVI continuously decreased during the dry season, particularly in deciduous forests (DF). Similarly, SIF in the north region also displayed a decreasing trend during the dry season, although the magnitude of the decrease was relatively small compared to that of the NDVI. This result is in contrast to that reported for the Amazon forest where a significant increase in vegetation greenness during the dry season has been observed. During the wet season, different seasonal variations were observed between SIF and the NDVI in the north region. For both evergreen forests (EF) and DF, the maximum SIF was observed in the months with the maximum precipitation, while the maximum NDVI value was observed at the end of the wet season. At the interannual scale, NDVI decrease nonlinearly along drought severity in dry seasons. During wet seasons, the greenness is insensitive to droughts but more related to radiation. Our results demonstrate that forests in Southeast Asia are water-limited during the dry season, indicating a vulnerability to future increase in the intensity of El Nino events and to temperature-driven increases in evapotranspiration.

植被对不同时间尺度干旱事件的响应特征及成因分析

PDF HTML阅读 XML下载 导出引用 引用提醒 植被对不同时间尺度干旱事件的响应特征及成因分析 DOI: 10.5846/stxb201506111182 作者: 作者单位: 中山大学水资源与环境系,中山大学水资源与环境系,中山大学水资源与环境系,中山大学水资源与环境系,中山大学 作者简介: 通讯作者: 中图分类号: 基金项目: 国家杰出青年科学基金项目（51425903）；香港特别行政区研究资助局资助项目（CUHK441313）；中山大学滨海小流域自然地理综合过程观测与实验平台建设资助项目（2012年度）；中央高校基本科研业务费专项资金资助项目；广东省教育部产学研结合项目（2012B091100471） Vegetation responses to drought at different time scales in China Author: Affiliation: Department of Water Resources and Environment,Sun Yat-sen University,Department of Water Resources and Environment,Sun Yat-sen University,Department of Water Resources and Environment,Sun Yat-sen University,Department of Water Resources and Environment,Sun Yat-sen University, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:利用标准化降雨蒸散发指数（SPEI）与归一化植被指数（NDVI）系统研究了中国不同区域、不同土地利用类型的植被对不同时间尺度干旱事件的响应特征，并对成因做出探讨。研究表明：（1）全国大部分区域NDVI与SPEI呈显著正相关，表明中国大部分区域植被生物量变化受干旱时空特征的影响。而沿北纬30度附近的长江流域区域，尤其是长江流域东南部、珠江流域下游等降水相对丰沛区域；黑龙江东北部及长白山地区、四川西部等高寒区域，NDVI与SPEI表现出弱相关性，受干旱影响较小；（2）多年平均水平衡是影响植被对干旱响应的关键因素，土壤水分变化是植被活力与生物量变化的关键影响因子。多年平均日照时数较长的区域，植被变化受干旱影响较大。从对干旱影响敏感性程度来讲，越是水量丰沛的区域，植被受干旱的影响越小，其中，草地对干旱的影响最为敏感，其次为灌木与森林。 Abstract:NDVI and SPEI drought index are collected and analyzed to investigate vegetation responses to drought regimes at different time scales in different regions and vegetation types across China, and the causes of changes are discussed. The results show that: 1) SPEI and NDVI are significantly positively correlated in most regions of China, indicating that the changes in vegetation biomass are influenced mainly by spatiotemporal characteristics of available water. The southeastern Yangtze River basin and the lower Pearl River basin are characterized by abundant precipitation and vegetation that is not sensitive to drought. The northeastern Heilongjiang Province, the Changbai Mountains, and the western Sichuan Province are characterized by weak correlation between NDVI and SPEI, indicating small effect of drought on vegetation. (2) The effects of the average water balance, average annual rainfall, average annual effective accumulated temperature, and average daily sunshine hours on correlations between NDVI and SPEI show that the average water balance is the key factor behind the changes in vegetation vigor. Hence, it can be concluded that change in soil moisture is the key factor determining the changes in vegetation activity and biomass. Regional precipitation or water balance is related significantly to the correlation between SPEI and NDVI, whereas vegetation in the regions with longer sunshine hours is more sensitive to droughts. In general, grasslands are the most sensitive to droughts, followed shrubs and forest. 参考文献 相似文献 引证文献

Multiple afforestation programs accelerate the greenness in the ‘Three North’ region of China from 1982 to 2013

China has launched multiple afforestation programs since 1978, including the ‘Three North’ Shelterbelt Development Program (TNSDP), the Beijing–Tianjin Sand Source Control Program (BSSCP), the Nature Forest Conservation Program (NFCP), and the Grain to Green Program (GTGP). These programs focus on local environment restoration by planting trees in semi-arid and arid regions and by protecting natural forests. However, the effectiveness of these programs has been questioned by several previous studies. Here, we report an increasing trend of greenness in this region using the satellite-retrieved normalized difference vegetation index (NDVI) from GIMMS, GIMMS-3g and MODIS datasets in the past 32 years. The NDVI increase for the ‘Three North’ region was 0.28%–0.38%yr−1 in 1982–2000 and 0.86%–1.12%yr−1 in 2000–2013, which is much higher than the country's means of 0.060%–0.063%yr−1 and 0.27%–0.30%yr−1, respectively. Most of the increase occurred in low and sparsely vegetated areas; and enlarged the moderate vegetated area (growing season mean NDVI above 0.5) from 16.5% to 25.7% for the two time periods, respectively. We also analyzed changes in the length of the growing season and the climate conditions including temperature, precipitation and two drought indices. However, these environmental factors cannot completely explain the changes in vegetation activity. Our study suggests these multiple afforestation programs contributed to the accelerated greening trend in the ‘Three North’ region and highlight the importance of human intervention in regional vegetation growth under climate change condition.

Spatio-Temporal Changes in Vegetation Activity and Its Driving Factors during the Growing Season in China from 1982 to 2011

Using National Oceanographic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) and Climatic Research Unit (CRU) climate datasets, we analyzed interannual trends in the growing-season Normalized Difference Vegetation Index (NDVI) in China from 1982 to 2011, as well as the effects of climatic variables and human activities on vegetation variation. Growing-season (period between the onset and end of plant growth) NDVI significantly increased (p < 0.01) on a national scale and showed positive trends in 52.76% of the study area. A multiple regression model was used to investigate the response of vegetation to climatic factors during recent and previous time intervals. The interactions between growing-season NDVI and climatic variables were more complex than expected, and a lag existed between climatic factors and their effects on NDVI. The regression residuals were used to show that over 6% of the study area experienced significantly human-induced vegetation variations (p < 0.05). These regions were mostly located in densely populated, reclaimed agriculture, afforestation, and conservation areas. Similar conclusions were drawn based on land-use change over the study period.

Spatial and Temporal Patterns of Global NDVI Trends: Correlations with Climate and Human Factors

Changes in vegetation activity are driven by multiple natural and anthropogenic factors, which can be reflected by Normalized Difference Vegetation Index (NDVI) derived from satellites. In this paper, NDVI trends from 1982 to 2012 are first estimated by the Theil–Sen median slope method to explore their spatial and temporal patterns. Then, the impact of climate variables and human activity on the observed NDVI trends is analyzed. Our results show that on average, NDVI increased by 0.46 × 10−3 per year from 1982 to 2012 globally with decadal variations. For most regions of the world, a greening (increasing)–browning (decreasing)–greening (G-B-G) trend is observed over the periods 1982–2004, 1995–2004, and 2005–2012, respectively. A positive partial correlation of NDVI and temperature is observed in the first period but it decreases and occasionally becomes negative in the following periods, especially in the Humid Temperate and Dry Domain Regions. This suggests a weakened effect of temperature on vegetation growth. Precipitation, on the other hand, is found to have a positive impact on the NDVI trend. This effect becomes stronger in the third period of 1995–2004, especially in the Dry Domain Region. Anthropogenic effects and human activities, derived here from the Human Footprint Dataset and the associated Human Influence Index (HII), have varied impacts on the magnitude (absolute value) of the NDVI trends across continents. Significant positive effects are found in Asia, Africa, and Europe, suggesting that intensive human activity could accelerate the change in NDVI and vegetation. A more accurate attribution of vegetation change to specific climatic and anthropogenic factors is instrumental to understand vegetation dynamics and requires further research.

Three decades of multi-dimensional change in global leaf phenology

Our knowledge of long-term changes in vegetation activity is incomplete, hindering understanding of Earth system dynamics. A comprehensive global assessment of vegetation phenology now shows that vegetation activity changed severely on 54% of the global land surface between 1981 and 2012.

Vegetation productivity patterns at high northern latitudes: a multi-sensor satellite data assessment.

Satellite-derived indices of photosynthetic activity are the primary data source used to study changes in global vegetation productivity over recent decades. Creating coherent, long-term records of vegetation activity from legacy satellite data sets requires addressing many factors that introduce uncertainties into vegetation index time series. We compared long-term changes in vegetation productivity at high northern latitudes (>50°N), estimated as trends in growing season NDVI derived from the most widely used global NDVI data sets. The comparison included the AVHRR-based GIMMS-NDVI version G (GIMMSg) series, and its recent successor version 3g (GIMMS3g), as well as the shorter NDVI records generated from the more modern sensors, SeaWiFS, SPOT-VGT, and MODIS. The data sets from the latter two sensors were provided in a form that reduces the effects of surface reflectance associated with solar and view angles. Our analysis revealed large geographic areas, totaling 40% of the study area, where all data sets indicated similar changes in vegetation productivity over their common temporal record, as well as areas where data sets showed conflicting patterns. The newer, GIMMS3g data set showed statistically significant (α = 0.05) increases in vegetation productivity (greening) in over 15% of the study area, not seen in its predecessor (GIMMSg), whereas the reverse was rare (<3%). The latter has implications for earlier reports on changes in vegetation activity based on GIMMSg, particularly in Eurasia where greening is especially pronounced in the GIMMS3g data. Our findings highlight both critical uncertainties and areas of confidence in the assessment of ecosystem-response to climate change using satellite-derived indices of photosynthetic activity. Broader efforts are required to evaluate NDVI time series against field measurements of vegetation growth, primary productivity, recruitment, mortality, and other biological processes in order to better understand ecosystem responses to environmental change over large areas.

Spatial relationship between climatologies and changes in global vegetation activity

Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land-cover and climate-related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature. However, little remains known about the processes underlying these changes at large spatial scales. In this study, we aimed at quantifying the spatial relationship between changes in potential climatic growth constraints (i.e. temperature, precipitation and incident solar radiation) and changes in vegetation activity (1982-2008). We demonstrate an additive spatial model with 0.5° resolution, consisting of a regression component representing climate-associated effects and a spatially correlated field representing the combined influence of other factors, including land-use change. Little over 50% of the spatial variance could be attributed to changes in climatologies; conspicuously, many greening trends and browning hotspots in Argentina and Australia. The nonassociated model component may contain large-scale human interventions, feedback mechanisms or natural effects, which were not captured by the climatologies. Browning hotspots in this component were especially found in subequatorial Africa. On the scale of land-cover types, strongest relationships between climatologies and vegetation activity were found in forests, including indications for browning under warming conditions (analogous to the divergence issue discussed in dendroclimatology).

Are ecological gradients in seasonal Q10 of soil respiration explained by climate or by vegetation seasonality?

Abstract Soil respiration (SR) is highly sensitive to future climate change, and particularly to global warming. However, considerable uncertainties remain associated with the temperature sensitivity of SR and its controlling processes. Using 384 field measurement data from 114 published papers and one book, this study quantifies the variation in the seasonal Q10 values of soil respiration, the multiplier by which respiration rates increase for a 10 °C increase in temperature, and its drivers across different sites. No significant correlation between Q10 and mean annual temperature or mean annual precipitation is found when statistically controlling seasonal changes in vegetation activity, deduced from satellite vegetation greenness index observations (normalized difference vegetation index, or NDVI). In contrast, the seasonal amplitude of NDVI is significantly and positively correlated with the apparent Q10 of SR. This result indicates that the variations of seasonal vegetation activity exert dominant control over the variations of the apparent Q10 of SR across different sites, highlighting the ecological linkage between plant physiological processes and soil processes. It further implies that the seasonal variation of vegetation activity may thus dominate the apparent seasonal temperature sensitivity. We conclude that the apparent Q10 value of SR estimated from field measurements is generally larger than the intrinsic temperature sensitivity of soil organic matter decomposition, and thus cautions should be taken when applying apparent Q10 values directly in ecosystem models. Our regression analysis further shows that when the amplitude of NDVI variation approximates 0 (and thus when the seasonality in vegetation activity is marginal), the residual Q10 of SR for soil temperature measured at 5 cm depth is about 1.5.

Interannual covariability between actual evapotranspiration and PAL and GIMMS NDVIs of northern Asia

This study examined the covariability between interannual changes in the normalized difference vegetation index (NDVI) and actual evapotranspiration (ET). To reduce possible uncertainty in the NDVI time series, two NDVI datasets derived from Pathfinder AVHRR Land (PAL) data and the Global Inventory Monitoring and Modeling Studies (GIMMS) group were used. Analyses were conducted using data over northern Asia from 1982 to 2000. Interannual changes over 19 years in the PAL-NDVI and GIMMS-NDVI were compared with interannual changes in ET estimated from model-assimilated atmospheric data and gridded precipitation data. For both NDVI datasets, the annual maximum correlation with ET occurred in June, which is the beginning of the vegetation growing season. The PAL and GIMMS datasets showed a significant, positive correlation between interannual changes in the NDVI and ET over most of the vegetated land area in June. These results suggest that interannual changes in vegetation activity predominantly control interannual changes in ET in June. Based on analyses of interannual changes in temperature, precipitation, and the NDVI in June, the study area can be roughly divided into two regions, the warmth-dominated northernmost region and the wetness-dominated southern region, indicating that interannual changes in vegetation and the resultant interannual changes in ET are controlled by warmth and wetness in these two regions, respectively.

Land‐cover change and vegetation dynamics across Africa

Using improved metrics and recently available MODerate resolution Imaging Spectrometer (MODIS) data, we examined the magnitude, extent, and nature of changes in photosynthetic activity and its timing across Sub‐Saharan Africa. Changes in overall vegetation activity and shifts in its timing have considerable implications for a variety of processes including surface‐atmosphere energy exchanges, terrestrial sources and sinks of carbon, the contribution of local evapotranspiration to the water cycle, disturbance regimes such as fires and pests, and the food security of societies using these ecosystems. While previous studies have examined broad‐scale trends in phenology or provided more detailed estimates of land‐cover conversion in the tropics, less is known of the year‐to‐year dynamics of vegetation. Here we quantified the overall changes in vegetation activity for each year between 2000 and 2004 and examined the proportion linked to differences in phenology and overall photosynthetic activity. In addition, we examined the nature of these changes in terms of frequency and duration, the proportion per ecosystem, identified areas of intensive change, and discuss the potential consequences of these changes. We found that most interannual change was not from shifts in timing or phenology, but rather largely due to differences in the amount of annual photosynthetic activity. In fact, there was as much as a 5% annual difference in vegetation activity across the continent. The changes were likely climate driven with particular vegetation types most susceptible to interannual change with high spatial and temporal variability found across the continent.