Honglin He

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.

Uncertainty analysis of eddy flux measurements in typical ecosystems of ChinaFLUX

Fluxes of CO(2) (FCO(2)) and energy (latent heat, LE; sensible heat. H) exchange between ecosystems and atmosphere, as measured by the eddy covariance technique, represent a fundamental data source for global-change research. However, little is known about the uncertainties of flux measurements at an ecosystem level in China. Here, we use data from six eddy covariance tower sites in ChinaFLUX, including two forested sites, three grassland sites, and one agricultural site, to conduct a cross-site analysis of random flux errors (RFEs) of FCO(2). LE, and H. By using the daily-differencing approach, paired observations are obtained to characterize the random error in these measurements. Our results show that: (1) The RFEs of FCO(2), LE, and H in different ecosystems of ChinaFLUX closely follow a double-exponential (Laplace) distribution, presumably due to a superposition of Gaussian distribution for high flux magnitude. (2) The RFEs of FCO(2), LE, and H are not homogeneous and appear to be a linear function of flux magnitude. (3) Except for H. the RFEs of FCO(2) and LE exhibit a distinct seasonal pattern. For FCO(2), the dependence of RFEs on wind speed varies somewhat according to vegetation type, whereas for LE and H, there is no such dependence. The effect of temperature on RFEs is not statistically significant (P<0.05). Both the distribution and the relationship of RFEs with flux magnitude in ChinaFLUX are essentially in accord with those in AmeriFlux and CarboEurope

Impact of the Spatial Domain Size on the Performance of the T-s-VI Triangle Method in Terrestrial Evapotranspiration Estimation

This study aims to investigate the impact of the spatial size of the study domain on the performance of the triangle method using progressively smaller domains and Moderate Resolution Imaging Spectroradiometer (MODIS) observations in the Heihe River basin located in the arid region of northwestern China. Data from 10 clear-sky days during the growing season from April to September 2009 were used. Results show that different dry/wet edges in the surface temperature-vegetation index space directly led to the deviation of evapotranspiration (ET) estimates due to the variation of the spatial domain size. The slope and the intercept of the limiting edges are dependent on the range and the maximum of surface temperature over the spatial domain. The difference of the limiting edges between different domain sizes has little impact on the spatial pattern of ET estimates, with the Pearson correlation coefficient ranging from 0.94 to 1.0 for the 10 pairs of ET estimates at different domain scales. However, it has a larger impact on the degree of discrepancies in ET estimates between different domain sizes, with the maximum of 66 W∙m−2. The largest deviation of ET estimates between different domain sizes was found at the beginning of the growing season.

Modeling winter wheat phenology and carbon dioxide fluxes at the ecosystem scale based on digital photography and eddy covariance data

article Recent studies have shown that the greenness index derived from digital camera imagery has high spatial and temporal resolution. These findings indicate that it can not only provide a reasonable characterization of canopy seasonal variation but also make it possible to optimize ecological models. To examine this possi- bility, we evaluated the application of digital camera imagery for monitoring winter wheat phenology and modeling gross primary production (GPP). By combining the data for the green cover fraction and for GPP, we first compared 2 different indices (the ratio greenness index (green-to-red ratio, G/R) and the relative greenness index (green to sum value, G%)) extracted from digital images obtained repeatedly over time and confirmed that G/R was best suited for tracking canopy status. Second, the key phenological stages were estimated using a time series of G/R values. The mean difference between the observed phenological dates and the dates determined from field data was 3.3 days in 2011 and 4 days in 2012, suggesting that digital camera imagery can provide high-quality ground phenological data. Furthermore, we attempted to use the data (greenness index and meteorological data in 2011) to optimize a light use efficiency (LUE) model and to use the optimal parameters to simulate the daily GPP in 2012. A high correlation (R 2 = 0.90) was found between the values of LUE-based GPP and eddy covariance (EC) tower- based GPP, showing that the greenness index and meteorological data can be used to predict the daily GPP. This finding provides a new method for interpolating GPP data and an approach to the estimation of the temporal and spatial distributions of photosynthetic productivity. In this study, we expanded the potential use of the greenness index derived from digital camera imagery by combining it with the LUE model in an analysis of well-managed cropland. The successful application of digital

Fostering ecological data sharing: collaborations in the International Long Term Ecological Research Network

The International Long Term Ecological Research (ILTER) Network was established in 1993 and is now composed of thirty-eight national networks representing a diversity of ecosystems around the globe. Data generated by the ILTER Network are valuable for scientists addressing broad spatial and temporal scale research questions, but only if these data can be easily discovered, accessed, and understood. Challenges to publishing ILTER data have included unequal distribution among networks of information management expertise, user-friendly tools, and resources. Language and translation have also been issues. Despite these significant obstacles, ILTER information managers have formed grassroots partnerships and collaborated to provide information management training, adopt a common metadata standard, develop information management tools useful throughout the network, and organize scientist/information manager workshops that encourage scientists to share and integrate data. Throughout this article, we share lessons learned from the successes of these grassroots international partnerships to inform others who wish to collaborate internationally on projects that depend on data sharing entailing similar management challenges.

Spatial variation in annual actual evapotranspiration of terrestrial ecosystems in China: Results from eddy covariance measurements

Understanding the spatial variation in annual actual evapotranspiration (AET) and its influencing factors is crucial for a better understanding of hydrological processes and water resources management. By synthesizing ecosystem-level observations of eddy-covariance flux sites in China (a total of 61 sites), we constructed the most complete AET dataset in China up to now. Based on this dataset, we quantified the statistic characteristics of AET and water budgets (defined as the ratio of AET to annual mean precipitation (MAP), AET/MAP) of terrestrial ecosystems in China. Results showed that AET differed significantly among both different vegetation types and climate types in China, with overall mean AET of 534.7±232.8 mm yr-1. AET/MAP also differed significantly among different climate types, but there were no distinct differences in AET/MAP values across vegetation types, with mean AET/MAP of 0.82±0.28 for non-irrigated ecosystems. We further investigated how the main climatic factors and vegetation attributes control the spatial variation in AET. Our findings revealed that the spatial variation of AET in China was closely correlated with the geographical patterns of climate and vegetation, in which the effects of total annual net radiation (Rn), MAP and mean annual air temperature (MAT) were dominant. Thus, we proposed an empirical equation to describe the spatial patterns of AET in China, which could explain about 84% of the spatial variation in AET of terrestrial ecosystems in China. Based on the constructed dataset, we also evaluated the uncertainties of five published global evapotranspiration products in simulating site-specific AET in China. Results showed that large biases in site-specific AET values existed for all five global evapotranspiration products, which indicated that it is necessary to involve more observation data of China in their parameterization or validation, while our AET dataset would provide a data source for it.

Estimation of diffuse photosynthetically active radiation and the spatiotemporal variation analysis in China from 1981 to 2010

Photosynthetically active radiation (PAR) is the energy source of plant photosynthesis, and the diffuse component can enhance canopy light use efficiency, thereby increasing the carbon uptake. Therefore, diffuse PAR is an important driving factor of ecosystem productivity models. In this study, we estimated the diffuse PAR of over 700 meteorological sites in China from 1981 to 2010 using an empirical model based on observational data from Chinese Ecosystem Research Network (CERN) and China Meteorology Administration. Then we derived the spatial data set of 10 km monthly diffuse PAR using ANUSPLIN software, and analyzed the spatiotemporal variation characteristics of diffuse PAR through GIS and trend analysis techniques. The results showed that: (1) The spatial patterns of annual average diffuse PAR during 1981–2010 are heterogeneous across China, lower in the northeast and higher in the west and south. The nationwide average value for 30 years ranges from 6.66 mol m−2 d−1 to 15.27 mol m−2 d−1, and the value in summer is the biggest while the value in winter is the smallest. (2) There is an evident increasing trend of annual diffuse PAR during recent 30 years, with the increasing amplitude at 0.03 mol m−2 d−1/10a. But a significant declining trend is shown in the first 10 years, and obvious anomalies can be seen in 1982, 1983, 1991 and 1992. And there is a downtrend in spring and an uptrend in all the other seasons. (3) The spatial distribution of temporal variation rates of diffuse PAR is inhomogeneous across the country, generally decreasing in the north and increasing in the south.

Estimation of the North–South Transect of Eastern China forest biomass using remote sensing and forest inventory data

The assessment of forest biomass is required for the estimation of carbon sinks and a myriad other ecological and environmental factors. In this article, we combined satellite data (Thematic Mapper (TM) and Moderate Resolution Imaging Spectrometer (MODIS)), forest inventory data, and meteorological data to estimate forest biomass across the North–South Transect of Eastern China (NSTEC). We estimate that the total regional forest biomass was 2.306 × 109 Megagrams (Mg) in 2007, with a mean coniferous forest biomass density of 132.78 Mg ha−1 and a mean broadleaved forest biomass density of 142.32 Mg ha−1. The mean biomass density of the entire NSTEC was 129 Mg ha−1. Furthermore, we analysed the spatial distribution pattern of the forest biomass and the distribution of biomass along the latitudinal and longitudinal gradients. The biomass was higher in the south and east and lower in the north and west of the transect. In the northern part of the NSTEC, the forest biomass was positively correlated with longitude. However, in the southern part of the transect, the forest biomass was negatively correlated with latitude but positively correlated with longitude. The biomass had an increasing trend with increases in precipitation and temperature. The results of the study can provide useful information for future studies, including quantifying the regional carbon budget.

A multilingual metadata catalog for the ILTER ：Issues and approaches

article i nfo The International Long-Term Ecological Research (ILTER) Networks strategic plan calls for widespread data exchange among member networks to support broad scale synthetic studies of ecological systems. However, natural language differences are common among ILTER country networks and seriously inhibit the exchange, interpretation and proper use of ecological data. As a first step toward building a multilingual metadata catalog, the ILTER has adopted Ecological Metadata Language (EML) as its standard, and ILTER members are asked to share discovery level metadata in English. Presently, the burden of translation is on the data providers, who frequently have few resources for information management. Tools to assist with metadata capture and translation, such as localized metadata editors and a multilingual environmental thesaurus, are needed and will be developed in the near future. In the longer term, ILTER will cooperate with other communities to develop ontologies that may be used to automate the process of translation and will produce the most linguistically and semantically accurate metadata translations.

Evaluation of Water Use Efficiency Derived from MODIS Products against Eddy Variance Measurements in China

Water use efficiency (WUE) is a useful indicator to illustrate the interaction of carbon and water cycles in terrestrial ecosystems. MODIS gross primary production (GPP) and evapotranspiration (ET) products have been used to analyze the spatial and temporal patterns of WUE and their relationships with environmental factors at regional and global scales. Although MODIS GPP and ET products have been evaluated using eddy covariance flux measurements, the accuracy of WUE estimated from MODIS products has not been well quantified. In this paper, we evaluated WUE estimated from MODIS GPP and ET products against eddy covariance measurements of GPP and ET during 2003-2008 at eight sites of the Chinese flux observation and research network (ChinaFLUX) and conducted sensitivity analysis to investigate the possible key contributors to the bias of MODIS products. Results show that MODIS products underestimate eight-day water use efficiency in four forest ecosystems and one cropland ecosystem with the bias from 0.36--2.28 g.C.kg-1 H20, while overestimating it in three grassland ecosystems with the bias from 0.26-1.11 g. C . kg-1 H20. Mean annual WUE was underestimated by 14%-54% at four forest sites, 45% at one cropland site and 7% at an alpine grassland site, but overestimated by 66% and 9% at a temperate grassland site and an alpine meadow site, respectively. The underestimation of WUE by MODIS data results from underestimated GPP and overestimated ET at four forest sites, while MODIS WUE values are significantly overvalued mainly due to underestimated ET in the three grassland ecosystems. The maximum light use efficiency and fraction of photosynthetically-active radiation (FPAR) were the two most sensitive factors to the estimation of WUE derived from the MODIS GPP and ET algorithms. The error in meteorological data partly caused the overestimation of ET and accordingly underestimation in WUE in subtropical and tropical forests. The bias of MODIS-produced WUE was also derived from the uncertainties in eddy flux data due to gap-filling processes and unbalanced surface energy issue. Their contributions to the uncertainty in estimated WUE at both eight-day and annual scales still need to be further quantified.