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

Net primary production of Chinese fir plantation ecosystems and its relationship to climate

Peer reviewe

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

Modeling Gross Primary Production of Agro-Forestry Ecosystems by Assimilation of Satellite-Derived Information in a Process-Based Model

In this paper we present results obtained in the framework of a regional-scale analysis of the carbon budget of poplar plantations in Northern Italy. We explored the ability of the process-based model BIOME-BGC to estimate the gross primary production (GPP) using an inverse modeling approach exploiting eddy covariance and satellite data. We firstly present a version of BIOME-BGC coupled with the radiative transfer models PROSPECT and SAILH (named PROSAILH-BGC) with the aims of i) improving the BIOME-BGC description of the radiative transfer regime within the canopy and ii) allowing the assimilation of remotely-sensed vegetation index time series, such as MODIS NDVI, into the model. Secondly, we present a two-step model inversion for optimization of model parameters. In the first step, some key ecophysiological parameters were optimized against data collected by an eddy covariance flux tower. In the second step, important information about phenological dates and about standing biomass were optimized against MODIS NDVI. Results obtained showed that the PROSAILH-BGC allowed simulation of MODIS NDVI with good accuracy and that we described better the canopy radiation regime. The inverse modeling approach was demonstrated to be useful for the optimization of ecophysiological model parameters, phenological dates and parameters related to the standing biomass, allowing good accuracy of daily and annual GPP predictions. In summary, this study showed that assimilation of eddy covariance and remote sensing data in a process model may provide important information for modeling gross primary production at regional scale

Soil drought anomalies in MODIS GPP of a Mediterranean broadleaved evergreen forest

The Moderate Resolution Imaging Spectroradiometer (MODIS) yields global operational estimates of terrestrial gross primary production (GPP). In this study, we compared MOD17A2 GPP with tower eddy flux-based estimates of GPP from 2001 to 2010 over an evergreen broad-leaf Mediterranean forest in Southern France with a significant summer drought period. The MOD17A2 GPP shows seasonal variations that are inconsistent with the tower GPP, with close-to-accurate winter estimates and significant discrepancies for summer estimates which are the least accurate. The analysis indicated that the MOD17A2 GPP has high bias relative to tower GPP during severe summer drought which we hypothesized caused by soil water limitation. Our investigation showed that there was a significant correlation (R-2 = 0.77, p < 0.0001) between the relative soil water content and the relative error of MOD17A2 GPP. Therefore, the relationship between the error and the measured relative soil water content could explain anomalies in MOD17A2 GPP. The results of this study indicate that careful consideration of the water conditions input to the MOD17A2 GPP algorithm on remote sensing is required in order to provide accurate predictions of GPP. Still, continued efforts are necessary to ascertain the most appropriate index, which characterizes soil water limitation in water-limited environments using remote sensing

Large Chinese land carbon sink estimated from atmospheric carbon dioxide data

Limiting the rise in global mean temperatures relies on reducing carbon dioxide (CO2) emissions and on the removal of CO2 by land carbon sinks. China is currently the single largest emitter of CO2, responsible for approximately 27 per cent (2.67 petagrams of carbon per year) of global fossil fuel emissions in 20171. Understanding of Chinese land biosphere fluxes has been hampered by sparse data coverage2–4, which has resulted in a wide range of a posteriori estimates of flux. Here we present recently available data on the atmospheric mole fraction of CO2, measured from six sites across China during 2009 to 2016. Using these data, we estimate a mean Chinese land biosphere sink of −1.11 ± 0.38 petagrams of carbon per year during 2010 to 2016, equivalent to about 45 per cent of our estimate of annual Chinese anthropogenic emissions over that period. Our estimate reflects a previously underestimated land carbon sink over southwest China (Yunnan, Guizhou and Guangxi provinces) throughout the year, and over northeast China (especially Heilongjiang and Jilin provinces) during summer months. These provinces have established a pattern of rapid afforestation of progressively larger regions5,6, with provincial forest areas increasing by between 0.04 million and 0.44 million hectares per year over the past 10 to 15 years. These large-scale changes reflect the expansion of fast-growing plantation forests that contribute to timber exports and the domestic production of paper7. Space-borne observations of vegetation greenness show a large increase with time over this study period, supporting the timing and increase in the land carbon sink over these afforestation regions