Wenwen Cai

Severe summer heatwave and drought strongly reduced carbon uptake in Southern China

Increasing heatwave and drought events can potentially alter the carbon cycle. Few studies have investigated the impacts of hundred-year return heatwaves and droughts, as those events are rare. In the summer of 2013, southern China experienced its strongest drought and heatwave on record for the past 113 years. We show that the record-breaking heatwave and drought lasted two months (from July to August), significantly reduced the satellite-based vegetation index and gross primary production, substantially altered the regional carbon cycle, and produced the largest negative crop yield anomaly since 1960. The event resulted in a net reduction of 101.54 Tg C in carbon sequestration in the region during these two months, which was 39–53% of the annual net carbon sink of China’s terrestrial ecosystems (190–260 Tg C yr−1). Moreover, model experiments showed that heatwaves and droughts consistently decreased ecosystem vegetation primary production but had opposite impacts on ecosystem respiration (TER), with increased TER by 6.78 ± 2.15% and decreased TER by 15.34 ± 3.57% assuming only changed temperature and precipitation, respectively. In light of increasing frequency and severity of future heatwaves and droughts, our study highlights the importance of accounting for the impacts of heatwaves and droughts in assessing the carbon sequestration in terrestrial ecosystems.

Improved estimations of gross primary production using satellite-derived photosynthetically active radiation

Terrestrial vegetation gross primary production (GPP) is an important variable in determining the global carbon cycle as well as the interannual variability of the atmospheric CO2 concentration. The accuracy of GPP simulation is substantially affected by several critical model drivers, one of the most important of which is photosynthetically active radiation (PAR) which directly determines the photosynthesis processes of plants. In this study, we examined the impacts of uncertainties in radiation products on GPP estimates in China. Two satellite-based radiation products (GLASS and ISCCP), three reanalysis products (MERRA, ECMWF, and NCEP), and a blended product of reanalysis and observations (Princeton) were evaluated based on observations at hundreds of sites. The results revealed the highest accuracy for two satellite-based products over various temporal and spatial scales. The three reanalysis products and the Princeton product tended to overestimate radiation. The GPP simulation driven by the GLASS product exhibited the highest consistency with those derived from site observations. Model validation at 11 eddy covariance sites suggested the highest model performance when utilizing the GLASS product. Annual GPP in China driven by GLASS was 5.55 Pg C yr(-1), which was 68.85%-94.87% of those derived from the other products. The results implied that the high spatial resolution, satellite-derived GLASS PAR significantly decreased the uncertainty of the GPP estimates at the regional scale. Key Points To compare the performances of several major satellite-based and reanalysis PAR To investigate the uncertainty in PAR datasets at different spatial resolutions To quantify the impacts on GPP simulations due to uncertainties in PAR inputs

Large Differences in Terrestrial Vegetation Production Derived from Satellite-Based Light Use Efficiency Models

Terrestrial gross primary production (GPP) is the largest global CO2 flux and determines other ecosystem carbon cycle variables. Light use efficiency (LUE) models may have the most potential to adequately address the spatial and temporal dynamics of GPP, but recent studies have shown large model differences in GPP simulations. In this study, we investigated the GPP differences in the spatial and temporal patterns derived from seven widely used LUE models at the global scale. The result shows that the global annual GPP estimates over the period 2000–2010 varied from 95.10 to 139.71 Pg C∙yr−1 among models. The spatial and temporal variation of global GPP differs substantially between models, due to different model structures and dominant environmental drivers. In almost all models, water availability dominates the interannual variability of GPP over large vegetated areas. Solar radiation and air temperature are not the primary controlling factors for interannual variability of global GPP estimates for most models. The disagreement among the current LUE models highlights the need for further model improvement to quantify the global carbon cycle.

Inclusion of soil carbon lateral movement alters terrestrial carbon budget in China

The lateral movement of soil carbon has a profound effect on the carbon budget of terrestrial ecosystems; however, it has never been quantified in China, which is one of the strongest soil erosion areas in the world. In this study, we estimated that the overall soil erosion in China varies from 11.27 to 18.17 Pg yr−1 from 1982 to 2011, accounting for 7–21% of total soil erosion globally. Soil erosion induces a substantial lateral redistribution of soil organic carbon ranging from 0.64 to 1.04 Pg C yr−1. The erosion-induced carbon flux ranges from a 0.19 Pg C yr−1 carbon source to a 0.24 Pg C yr−1 carbon sink in the terrestrial ecosystem, which is potentially comparable in magnitude to previously estimated total carbon budget of China (0.19 to 0.26 Pg yr−1). Our results showed that the lateral movement of soil carbon strongly alters the carbon budget in China, and highlighted the urgent need to integrate the processes of soil erosion into the regional or global carbon cycle estimates.

Satellite-Based Analysis of Evapotranspiration and Water Balance in the Grassland Ecosystems of Dryland East Asia

The regression tree method is used to upscale evapotranspiration (ET) measurements at eddy-covariance (EC) towers to the grassland ecosystems over the Dryland East Asia (DEA). The regression tree model was driven by satellite and meteorology datasets, and explained 82% and 76% of the variations of ET observations in the calibration and validation datasets, respectively. The annual ET estimates ranged from 222.6 to 269.1 mm yr−1 over the DEA region with an average of 245.8 mm yr−1 from 1982 through 2009. Ecosystem ET showed decreased trends over 61% of the DEA region during this period, especially in most regions of Mongolia and eastern Inner Mongolia due to decreased precipitation. The increased ET occurred primarily in the western and southern DEA region. Over the entire study area, water balance (the difference between precipitation and ecosystem ET) decreased substantially during the summer and growing season. Precipitation reduction was an important cause for the severe water deficits. The drying trend occurring in the grassland ecosystems of the DEA region can exert profound impacts on a variety of terrestrial ecosystem processes and functions.

Global Validation of a Process-Based Model on Vegetation Gross Primary Production Using Eddy Covariance Observations

Gross Primary Production (GPP) is the largest flux in the global carbon cycle. However, large uncertainties in current global estimations persist. In this study, we examined the performance of a process-based model (Integrated BIosphere Simulator, IBIS) at 62 eddy covariance sites around the world. Our results indicated that the IBIS model explained 60% of the observed variation in daily GPP at all validation sites. Comparison with a satellite-based vegetation model (Eddy Covariance-Light Use Efficiency, EC-LUE) revealed that the IBIS simulations yielded comparable GPP results as the EC-LUE model. Global mean GPP estimated by the IBIS model was 107.50±1.37 Pg C year−1 (mean value ± standard deviation) across the vegetated area for the period 2000–2006, consistent with the results of the EC-LUE model (109.39±1.48 Pg C year−1). To evaluate the uncertainty introduced by the parameter Vcmax, which represents the maximum photosynthetic capacity, we inversed Vcmax using Markov Chain-Monte Carlo (MCMC) procedures. Using the inversed Vcmax values, the simulated global GPP increased by 16.5 Pg C year−1, indicating that IBIS model is sensitive to Vcmax, and large uncertainty exists in model parameterization.