Drought events and their effects on vegetation productivity in China

Many parts of the world have experienced frequent and severe droughts during the last few decades. Most previous studies examined the effects of specific drought events on vegetation productivity. In this study, we characterized the drought events in China from 1982 to 2012 and assessed their effects on vegetation productivity inferred from satellite data. We first assessed the occurrence, spatial extent, frequency, and severity of drought using the Palmer Drought Severity Index (PDSI). We then examined the impacts of droughts on China\u27s terrestrial ecosystems using the Normalized Difference Vegetation Index (NDVI). During the period 1982–2012, China\u27s land area (%) experiencing drought showed an insignificant trend. However, the drought conditions had been more severe over most regions in northern parts of China since the end of the 1990s, indicating that droughts hit these regions more frequently due to the drier climate. The severe droughts substantially reduced annual and seasonal NDVI. The magnitude and direction of the detrended NDVI under drought stress varied with season and vegetation type. The inconsistency between the regional means of PDSI and detrended NDVI could be attributed to different responses of vegetation to drought and the timing, duration, severity, and lag effects of droughts. The negative effects of droughts on vegetation productivity were partly offset by the enhancement of plant growth resulting from factors such as lower cloudiness, warming climate, and human activities (e.g., afforestation, improved agricultural management practices)

Trend of studies on carbon sequestration dynamics in the Himalaya hotspot region: A review

The present communication deals with the carbon dynamics in the Himalaya hotspot region. The Himalaya, a mountain range shared by Pakistan, India, Nepal, Bhutan and Myanmar, is one of the biologically richest regions in the world that play an important role as source and sink in global carbon cycle. The purpose of this paper was to review and provide available studies related to carbon sequestration in the Himalayas. The carbon in forest is stored in five different pools viz. above-ground biomass, below-ground biomass, litter, deadwood and soil organic carbon. Estimates of biomass, carbon stock and soil organic carbon contents by almost all forest types including agroforestry systems and plantations in the Himalaya hotspot have been documented in this communication. The net rate of carbon sequestrated by forest was reported to be 2.4 ±0.4 Pg C yr-1 on a global scale. The Indian Himalayan Region constitutes about 5.4 billion tonnes of C and sequesters about 65 million tonnes of C yr-1. We analysed more than 135 peer-reviewed journal articles related to biomass and carbon sequestration. The review identifies that the studies estimated 3697.05, 3898.10 and 4235.05 tonnes carbon per hectare for Western, Central and Eastern Himalayan region respectively. The research on the biomass/carbon estimation received attention as early as 1980s, but increased gradually after 2001. These findings would contribute to policy-makers with useful information for mitigation of CO2 emissions

Responses and adaptation strategies of terrestrial ecosystems to climate change

Terrestrial ecosystems are likely to be affected by climate change, as climate change-induced shift of water and heat stresses patterns will have significant impacts on species composition, habitat distribution, and ecosystem functions, and thereby weaken the terrestrial carbon (C) sink and threaten global food security and biofuel production. This thesis investigates the responses of terrestrial ecosystems to climate change and is structured in four main chapters.;The first chapter of the thesis is directed towards the impacts of snow variation on ecosystem phenology. Variations in seasonal snowfall regulate regional and global climatic systems and vegetation growth by changing energy budgets of the lower atmosphere and land surface. We investigated the effects of snow on the start of growing season (SGS) of temperate vegetation in China. Across the entire temperate region in China, the winter snow depth increased at a rate of 0.15 cm•yr-1 (p=0.07) during the period 1982-1998, and decreased at a rate of 0.36 cm•yr-1 (p=0.09) during the period 1998-2005. Correspondingly, the SGS advanced at a rate of 0.68 d•yr-1 (p\u3c0.01) during 1982 to 1998, and delayed at a rate of 2.13 d•yr-1 (p=0.07) during 1998 to 2005, against a warming trend throughout the entire study period of 1982-2005. Spring air temperature strongly regulated the SGS of both deciduous broad-leaf and coniferous forests; whilst the winter snow had a greater impact on the SGS of grassland and shrubs. Snow depth variation combined with air temperature contributed to the variability in the SGS of grassland and shrubs, as snow acted as an insulator and modulated the underground thermal conditions. Additionally, differences were seen between the impacts of winter snow depth and spring snow depth on the SGS; as snow depths increased, the effect associated went from delaying SGS to advancing SGS. The observed thresholds for these effects were snow depths of 6.8 cm (winter) and 4.0 cm (spring). The results of this study suggest that the response of the vegetation\u27s SGS to seasonal snow change may be attributed to the coupling effects of air temperature and snow depth associated with the soil thermal conditions.;The second chapter further addresses snow impacts on terrestrial ecosystem with focus on regional carbon exchange between atmosphere and biosphere. Winter snow has been suggested to regulate terrestrial carbon (C) cycling by modifying micro-climate, but the impacts of snow cover change on the annual C budget at the large scale are poorly understood. Our aim is to quantify the C balance under changing snow depth. Here, we used site-based eddy covariance flux data to investigate the relationship between snow cover depth and ecosystem respiration (Reco) during winter. We then used the Biome-BGC model to estimate the effect of reductions in winter snow cover on C balance of Northern forests in non-permafrost region. According to site observations, winter net ecosystem C exchange (NEE) ranged from 0.028-1.53 gC•m-2•day-1, accounting for 44 +/- 123% of the annual C budget. Model simulation showed that over the past 30 years, snow driven change in winter C fluxes reduced non-growing season CO2 emissions, enhancing the annual C sink of northern forests. Over the entire study area, simulated winter ecosystem respiration (Reco) significantly decreased by 0.33 gC•m-2•day -1•yr-1 in response to decreasing snow cover depth, which accounts for approximately 25% of the simulated annual C sink trend from 1982 to 2009. Soil temperature was primarily controlled by snow cover rather than by air temperature as snow served as an insulator to prevent chilling impacts. A shallow snow cover has less insulation potential, causing colder soil temperatures and potentially lower respiration rates. Both eddy covariance analysis and model-simulated results showed that both Reco and NEE were significantly and positively correlated with variation in soil temperature controlled by variation in snow depth. Overall, our results highlight that a decrease in winter snow cover restrains global warming through emitting less C to the atmosphere.;The third chapter focused on assessing drought\u27s impact on global terrestrial ecosystems. Drought can affect the structure, composition and function of terrestrial ecosystems, yet the drought impacts and post-drought recovery potential of different land cover types have not been extensively studied at a global scale. Here, we evaluated drought impacts on gross primary productivity (GPP), evapotranspiration (ET), and water use efficiency (WUE) of different global terrestrial ecosystems, as well as the drought-resilience of each ecosystem type during the period of 2000 to 2011. We found the rainfall and soil moisture during drought period were dramatically lower than these in non-drought period, while air temperatures were higher than normal during drought period with amplitudes varied by land cover types. The length of recovery days (LRD) presented an evident gradient of high (\u3e 60 days) in mid- latitude region and low (\u3c 60 days) in low (tropical area) and high (boreal area) latitude regions. As average GPP increased, the LRD showed a significantly decreasing trend among different land covers (R 2=0.53, p\u3c0.0001). Moreover, the most dramatic reduction of the drought-induced GPP was found in the mid-latitude region of north Hemisphere (48% reduction), followed by the low-latitude region of south Hemisphere (13% reduction). In contrast, a slightly enhanced GPP (10%) was showed in the tropical region under drought impact. Additionally, the highest drought-induced reduction of ET was found in the Mediterranean area, followed by Africa. The water use efficiency, however, showed a pattern of decreasing in the north Hemisphere and increasing in the south Hemisphere.;The last chapter compared the differences of performance in trading water for carbon in planted forest and natural forest, with specific focus on China. Planted forests have been widely established in China as an essential approach to improving the ecological environment and mitigating climate change. Large-scale forest planting programs, however, are rarely examined in the context of tradeoffs between carbon sequestration and water yield between planted and natural forests. We reconstructed evapotranspiration (ET) and gross primary production (GPP) data based on remote-sensing and ground observational data, and investigated the differences between natural and planted forests, in order to evaluate the suitability of tree-planting activity in different climate regions where the afforestation and reforestation programs have been extensively implemented during the past three decades in China. While the differences changed with latitude (and region), we found that, on average, planted forests consumed 5.79% (29.13mm) more water but sequestered 1.05% (-12.02 gC m-2 yr -1) less carbon than naturally generated forests, while the amplitudes of discrepancies varied with latitude. It is suggested that the most suitable lands in China for afforestation should be located in the moist south subtropical region (SSTP), followed by the mid-subtropical region (MSTP), to attain a high carbon sequestration potential while maintain a relatively low impact on regional water balance. The high hydrological impact zone, including the north subtropical region (NSTP), warm temperate region (WTEM), and temperate region (TEM) should be cautiously evaluated for future afforestation due to water yield reductions associated with plantations

Remote Sensing of Land Surface Phenology

Land surface phenology (LSP) uses remote sensing to monitor seasonal dynamics in vegetated land surfaces and retrieve phenological metrics (transition dates, rate of change, annual integrals, etc.). LSP has developed rapidly in the last few decades. Both regional and global LSP products have been routinely generated and play prominent roles in modeling crop yield, ecological surveillance, identifying invasive species, modeling the terrestrial biosphere, and assessing impacts on urban and natural ecosystems. Recent advances in field and spaceborne sensor technologies, as well as data fusion techniques, have enabled novel LSP retrieval algorithms that refine retrievals at even higher spatiotemporal resolutions, providing new insights into ecosystem dynamics. Meanwhile, rigorous assessment of the uncertainties in LSP retrievals is ongoing, and efforts to reduce these uncertainties represent an active research area. Open source software and hardware are in development, and have greatly facilitated the use of LSP metrics by scientists outside the remote sensing community. This reprint covers the latest developments in sensor technologies, LSP retrieval algorithms and validation strategies, and the use of LSP products in a variety of fields. It aims to summarize the ongoing diverse LSP developments and boost discussions on future research prospects

Comparison of Gross Primary Productivity Derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia

Gross primary production (GPP) plays an important role in the net ecosystem exchange of CO2 between the atmosphere and terrestrial ecosystems. It is particularly important to monitor GPP in Southeast Asia because of increasing rates of tropical forest degradation and deforestation in the region in recent decades. The newly available, improved, third generation Normalized Difference Vegetation Index (NDVI3g) from the Global Inventory Modelling and Mapping Studies (GIMMS) group provides a long temporal dataset, from July 1981 to December 2011, for terrestrial carbon cycle and climate response research. However, GIMMS NDVI3g-based GPP estimates are not yet available. We applied the GLOPEM-CEVSA model, which integrates an ecosystem process model and a production efficiency model, to estimate GPP in Southeast Asia based on three independent results of the fraction of photosynthetically active radiation absorbed by vegetation (FPAR) from GIMMS NDVI3g (GPPNDVI3g), GIMMS NDVI1g (GPPNDVI1g), and the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD15A2 FPAR product (GPPMOD15). The GPP results were validated using ground data from eddy flux towers located in different forest biomes, and comparisons were made among the three GPPs as well as the MOD17A2 GPP products (GPPMOD17). Based on validation with flux tower derived GPP estimates the results show that GPPNDVI3g is more accurate than GPPNDVI1g and is comparable in accuracy with GPPMOD15. In addition, GPPNDVI3g and GPPMOD15 have good spatial-temporal consistency. Our results indicate that GIMMS NDVI3g is an effective dataset for regional GPP simulation in Southeast Asia, capable of accurately tracking the variation and trends in long-term terrestrial ecosystem GPP dynamics

Aboveground net primary productivity of vegetation along a climate-related gradient in a Eurasian temperate grassland: spatiotemporal patterns and their relationships with climate factors

Accurate assessments of spatiotemporal patterns in net primary productivity and their links to climate are important to obtain a deeper understanding of the function, stability and sustainability of grassland ecosystems. We combined a satellite-derived NDVI time-series dataset and field-based samples to investigate spatiotemporal patterns in aboveground net primary productivity (ANPP), and we examined the effect of growing season air temperate (GST) and precipitation (GSP) on these patterns along a climaterelated gradient in an eastern Eurasian grassland. Our results indicated that the ANPP fluctuated with no significant trend during 2001-2012. The spatial distribution of ANPP was heterogeneous and decreased from northeast to southwest. The interannual changes in ANPP were mainly controlled by year-to-year GSP; a strong correlation of interannual variability between ANPP and GSP was observed. Similarly, GSP strongly influenced spatial variations in ANPP, and the slopes of fitted linear functions of the GSP-ANPP relationship increased from arid temperate desert grassland to humid meadow grassland. An exponential function could be used to fit the GSP-ANPP relationship for the entire region. An improved moisture index that combines the effects of GST and GSP better explained the variations in ANPP compared with GSP alone. In comparisons with the previous studies, we found that the relationships between spatiotemporal variations in ANPP and climate factors were probably scale dependent. We imply that the quantity and spatial range of analyzed samples contribute to these different results. Multi-scale studies are necessary to improve our knowledge of the response of grassland ANPP to climate change.ArticleENVIRONMENTAL EARTH SCIENCES.76(1):56(2017)journal articl

Forests and Carbon: A Synthesis of Science, Management, and Policy for Carbon Sequestration in Forests

The goal of this volume is to provide guidance for land managers and policymakers seeking to understand the complex science and policy of forest carbon as it relates to tangible problems of forest management and the more abstract problems of addressing drivers of deforestation and negotiating policy frameworks for reducing CO2 emissions from forests. It is the culmination of three graduate seminars at the Yale School of Forestry & Environmental Studies focused on carbon sequestration in forest ecosystems and their role in addressing climate change

Comparing Autumn Phenology Derived from Field Observations, Satellite Data, and Carbon Flux Measurements in a Northern Mixed Forest

In this project, autumn phenological transition dates and senescence rate (derived from field observation, satellite data and carbon flux measurements) are compared in a northern Wisconsin deciduous forest. Field data cover 2010 and 2012 for the northern site and 2010, 2012 and 2013 for the southern site, with leaf coloration and leaf fall recorded. Satellite indices are EVI and NDVI obtained from the MODIS V006 product via Google Earth Engine platform, covering 2000 to 2017. Carbon flux indices are NEE and GPP covering 1997 to 2017. Field data and normalized satellite data are fitted by a two-section logistic model while carbon data are fitted by a double-logistic model to derive three transition dates and senescence rate parameters. Comparison among these dates and parameters suggests: (a) Generally, the transition dates derived from NDVI is closest to the transitions of leaf coloration and leaf fall; (b) The senescence rate based on NDVI is also closest to the rate of leaf coloration and leaf fall; (c) In year-to-year comparisons, either NEE or GPP can be the least accurate approach in estimating leaf coloration and leaf fall progress; while in long-term comparisons, the accuracy order of EVI, NEE and GPP is variable; and (d) NDVI-based senescence rate is faster, while the senescence rate derived from the other three approaches don’t differ a lot. Speculations on the reasons for these findings are as follows: (a) canopy senescence is asynchronous, so the timing of first observed leaf coloration from above-canopy and below-canopy can be different; (b) Compared with NDVI, EVI is more sensitive to the subtle canopy change in early autumn and is less affected by soil noise in late autumn, resulting in longer senescence duration; (c) Photosynthesis starts to decrease before visual senescence due to environmental and leaf physiological change, which leads to the bias between field data and carbon data derived transition in early autumn; and (d) The life activities of shrubs and coniferous trees cause carbon exchange to continue changing after deciduous tree senescence terminates

Remote Sensing Methods and Applications for Detecting Change in Forest Ecosystems

Forest ecosystems are being altered by climate change, invasive species, and additional stressors. Our ability to detect these changes and quantify their impacts relies on detailed data across spatial and temporal scales. This dissertation expands the ecological utility of long-term satellite imagery by developing high quality forest mapping products and examining spatiotemporal changes in tree species abundance and phenology across the northeastern United States (US; the ‘Northeast’). Species/genus-level forest composition maps were developed by integrating field data and Landsat images to model abundance at a sub-pixel scale. These abundance maps were then used to 1) produce a more detailed, accurate forest classification compared to similar products and 2) construct a 30-year time-series of abundance for eight common species/genera. Analyzing the time-series data revealed significant abundance trends in notable species, including increases in American beech (Fagus grandifolia) at the expense of sugar maple (Acer saccharum). Climate was the dominant predictor of abundance trends, indicating climate change may be altering competitive relationships. Spatiotemporal trends in deciduous forest phenology – start and end of the growing season (SOS/EOS) – were examined based on MODIS imagery from 2001-2015. SOS exhibited a slight advancing trend across the Northeast, but with a distinct spatial pattern: eastern ecoregions showed advance and western ecoregions delay. EOS trended substantially later almost everywhere. SOS trends were linked to winter-spring temperature and precipitation trends; areas with higher elevation and fall precipitation anomalies had negative associations with EOS trends. Together, this work demonstrates the value of remote sensing in furthering our understanding of long-term forest responses to changing environmental conditions. By highlighting potential changes in forest composition and function, the research presented here can be used to develop forest conservation and management strategies in the Northeast