Quanqin Shao

The Performances of MODIS-GPP and -ET Products in China and Their Sensitivity to Input Data (FPAR/LAI)

The aims are to validate and assess the performances of MODIS gross primary production (MODIS-GPP) and evapotranspiration (MODIS-ET) products in Chinas different land cover types and their sensitivity to remote sensing input data. In this study, MODIS-GPP and -ET are evaluated using flux derived/measured data from eight sites of ChinaFLUX. Results show that MODIS-GPP generally underestimates GPP (R 2 is 0.58, bias is −6.7 gC/m 2 /8-day and RMSE is 19.4 gC/m 2 /8-day) at all sites and MODIS-ET overestimates ET (R 2 is 0.36, bias is 6 mm/8-day and RMSE is 11 mm/8-day) when comparing with derived GPP and measured ET, respectively. For evergreen forests, MODIS-GPP gives a poor performance with R 2 varying from 0.03 to 0.44; in contrast, MODIS-ET provides more reliable results. In croplands, MODIS-GPP can explain 80% of GPP variance, but it overestimates flux derived GPP in non-growing season and underestimates flux derived GPP in growing season; similar overestimations also presented in MODIS-ET. For grasslands and mixed forests, MODIS-GPP and -ET perform good estimating accuracy. By designing four experimental groups and taking GPP simulation as an example, we suggest that the maximum light use efficiency of croplands should be optimized, and the differences of meteorological data have little impact on GPP estimation, whereas remote sensing leaf area index/fraction of photo-synthetically active radiation (LAI/FPAR) can greatly affect GPP/ET estimations for all land cover types. Thus, accurate remote sensing parameters are important for achieving reliable estimations.

Effects of plateau pika (Ochotona curzoniae) on net ecosystem carbon exchange of grassland in the Three Rivers Headwaters region, Qinghai-Tibet, China

Background and aimBecause the indigenous burrowing lagomorph plateau pika (Ochotona curzoniae) is considered to have negative ecological impacts on alpine meadow steppe grasslands of the Headwaters Region of the Yellow, Yangtze and Mekong Rivers we investigated its effects on ecosystem productivity and soil properties, and especially net ecosystem carbon flux.MethodsWe measured net ecosystem CO2 exchange (NEE) and its components gross ecosystem productivity (GEP) and ecosystem respiration (ER) at peak aboveground biomass by the chamber method with reference to plant and soil characteristics of areas of alpine meadow steppe with different densities of pika burrows.ResultsHigher burrow density decreased NEE, GEP and ER. Above-ground biomass, species number, plant cover and leaf area index decreased with increasing pika density. Higher burrow density was associated with lower soil moisture and higher soil temperature. Responses of NEE were related to changes of abiotic and biotic factors affecting its two components. NEE was positively related to soil moisture, soil ammonium nitrogen, plant cover, leaf area index and above-ground biomass but was negatively correlated with higher soil nitrate nitrogen.ConclusionDecrease of NEE by plateau pika may reduce the carbon sink balance of Qinghai-Tibet plateau grassland. Such effects may be influenced by grazing pressure from domestic livestock, population levels of natural predators, and climate change.

Effects of grassland restoration programs on ecosystems in arid and semiarid China.

We explored the ecological effects of grassland restoration programs using satellite imagery and field plots sampling data and analyzing the patterns and mechanisms of land cover change and vegetation activities in arid and semiarid China during the period from 1982 to 2008. The grassland cover in the 1980s, 2000 and 2005 was compared before and after the restoration programs. The variability of net primary production (NPP) and rain use efficiency (RUE) were analyzed as indicators of vegetation productivity. Our study showed that changes in grassland cover were closely related to the relative area of farmland, with increases in grassland being caused by returning farmland to grassland and decreases being caused by reclamation for agriculture. The results of NPP and RUE measurements over the past 30 years showed systematic increases in the area of grassland in most regions, especially from 2000 to 2008. This fact was reflected by intensified vegetation activity and cannot be completely explained by the warmer and wetter climate, which suggested a contribution from restored, ungrazed grasslands. Our analysis indicates that both vegetation activity and grassland cover increased in regions in which grassland and rangeland restoration programs were implemented.

Analysis of net primary productivity of terrestrial vegetation on the Qinghai-Tibet Plateau, based on MODIS remote sensing data

GLO-PEM is driven by soil moisture data of AMSR-E and PAR (Photosynthetically active radiation) which is retrieved from MODIS atmospheric data product in this paper. Using remote sensing data can overcome uncertainty brought from interpolation of precipitation and PAR. Comparing with observed radiation data, PAR retrieved by remote sensing is in high accuracy in this study. RMSE is 9 and 19.68 W m−2 and R2 is 0.89 and 0.67 respectively. As a result of GLO-PEM, annual total amount of NPP of Qinghai-Tibet Plateau is 0.37 Pg C a−1 in 2005–2008. There is a significant linear relationship between field and simulated NPP. Determination coefficient reached 0.93. NPP is decrease from southeast to northwest in the Qinghai-Tibet Plateau. NPP changes from 0 to 1500 g C m−2 a−1. There is different limit factors of vegetation growth in west and east plateau. In the west of 450 mm rainfall line, the limit factors is precipitation. In the east of 450 mm rainfall line, temperature is the dominated factor of vegetation growth.

Effects of an ecological conservation and restoration project in the Three-River Source Region, China

The first-stage of an ecological conservation and restoration project in the Three-River Source Region (TRSR), China, has been in progress for eight years. However, because the ecological effects of this project remain unknown, decision making for future project implementation is hindered. Thus, in this study, we developed an index system to evaluate the effects of the ecological restoration project, by integrating field observations, remote sensing, and process-based models. Effects were assessed using trend analyses of ecosystem structures and services. Results showed positive trends in the TRSR since the beginning of the project, but not yet a return to the optima of the 1970s. Specifically, while continued degradation in grassland has been initially contained, results are still far from the desired objective, ‘grassland coverage increasing by an average of 20%–40%’. In contrast, wetlands and water bodies have generally been restored, while the water conservation and water supply capacity of watersheds have increased. Indeed, the volume of water conservation achieved in the project meets the objective of a 1.32 billion m3 increase. The effects of ecological restoration inside project regions was more significant than outside, and, in addition to climate change projects, we concluded that the implementation of ecological conservation and restoration projects has substantially contributed to vegetation restoration. Nevertheless, the degradation of grasslands has not been fundamentally reversed, and to date the project has not prevented increasing soil erosion. In sum, the effects and challenges of this first-stage project highlight the necessity of continuous and long-term ecosystem conservation efforts in this region.

Using multi-model ensembles to improve the simulated effects of land use/cover change on temperature: a case study over northeast China

Abstract Rather than simulating the effects of land use and land cover change (LUCC) on the climate using one climate model, as in many previous studies, three regional climate models (Regional Climate Model, version 3; the Weather Research and Forecasting model; and the Regional Integrated Environmental Model System) were used in the present study to simulate changes in temperature due to LUCC. Two experiments (CTL and NE) were designed and run using the three regional climate models. The CTL experiment was used to compare the simulations of the different models and served to illustrate the improvement that could be achieved as a result of employing a multi-model ensemble. The NE experiment was used to evaluate the changes in temperature caused by LUCC in northeast China between 1981 and 2000. The results of the CTL simulations showed that changes in temperature were simulated well by the three regional climate models; however, the simulated temperatures were different, dependent on the model used. The multi-model ensembles [the arithmetic ensemble mean (AEM) and Bayesian model averaging (BMA)] attained better results than any individual model. Of the two ensemble methods, BMA performed better than the AEM. The effects of LUCC on the climate in northeast China were assessed by the differences between the CTL and NE simulations for every RCM and the ensemble simulations. The BMA simulations produced more reasonable results than the other simulations. Based on the results, we can state with some confidence that LUCC in northeast China over the 20-year period studied caused a decrease in temperature, because of an expansion of arable land.

Runoff characteristics in flood and dry seasons based on wavelet analysis in the source regions of the Yangtze and Yellow rivers

By decomposing and reconstructing the runoff information from 1965 to 2007 of the hydrologic stations of Tuotuo River and Zhimenda in the source region of the Yangtze River, and Jimai and Tangnaihai in the source region of the Yellow River with db3 wavelet, runoff of different hydrologic stations tends to be declining in the seasons of spring flood, summer flood and dry ones except for that in Tuotuo River. The declining flood/dry seasons series was summer > spring > dry; while runoff of Tuotuo River was always increasing in different stages from 1965 to 2007 with a higher increase rate in summer flood seasons than that in spring ones. Complex Morlet wavelet was selected to detect runoff periodicity of the four hydrologic stations mentioned above. Over all seasons the periodicity was 11–12 years in the source region of the Yellow River. For the source region of the Yangtze River the periodicity was 4–6 years in the spring flood seasons and 13–14 years in the summer flood seasons. The differences of variations of flow periodicity between the upper catchment areas of the Yellow River and the Yangtze River and between seasons were considered in relation to glacial melt and annual snowfall and rainfall as providers of water for runoff.

Influence of Land Use Patterns on Evapotranspiration and Its Components in a Temperate Grassland Ecosystem

To better understand variation in response of components of ecosystem evapotranspiration (ET) to grassland use differences, we selected three typical land use patterns in a temperate steppe area: grazed steppe (G), steppe with grazers excluded (GE), and steppe cultivated to cropland (C). ET was divided into its components evaporation (E) and canopy transpiration (T) using herbicide and a chamber attached to a portable infrared gas analyzer (Li-6400). The results indicated that daily water consumption by ET in G was 3.30 kg m−2 d−1; compared with G, ET increased significantly in GE at 13.4% and showed a trend of 6.73% increase in C. Daily water consumption by E increased 24.3% in GE relative to G, and C showed 20.2% more than GE. At 0.46, E/ET in C was significantly higher than G at 0.35. Air temperature and the vapor pressure deficit were closely correlated with variation in diurnal ET, E, and T. The leaf area index (LAI) was also positively correlated with daily ET and E varied among grassland use patterns and explained variation in E/ET (81%). Thus, variation in LAI strongly influences the overall magnitude of ecosystem ET and the composition of its components under different grassland use patterns.

Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar

Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass (R2 = 0.340, root-mean-square error (RMSE) = 81.89 g·m−2, and relative error of 14.1%). The improvement of multiple regressions to the R2 and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (<100 m). These findings are helpful for modeling stable regressions to estimate grassland biomass using lidar returns.

Improving Carbon Mitigation Potential through Grassland Ecosystem Restoration under Climatic Change in Northeastern Tibetan Plateau

To protect the water tower’s ecosystem environment and conserve biodiversity, China has been implementing a huge payment program for ecosystem services in the three rivers source region. We explored here the dynamics of grassland degradation and restoration from 1990 to 2012 and its relationships with climate mitigation in the TRSR to provide a definite answer as to the forcing and response of grassland degradation and restoration to climate change. Then we estimated its potential of climate mitigation benefits to address the question of whether ecological restoration could be effective in reversing the decline of ecosystem carbon mitigation service. The trend of average annual temperature and precipitation observed by meteorological stations were approximately increased. Compared before and after 2004, the area of grassland degradation was increased slightly. However, nearly one-third of degraded grassland showed improvement, and the grassland vegetation coverage showed significant increase. Comparing current grassland vegetation coverage with healthy vegetation cover with the same grass type, nearly half of the area still needs to further restore vegetation cover. The grassland degradation resulted in significant carbon emissions, but the restoration to its healthy status has been estimated to be technical mitigation potential.