Fu Gang

Satellite-Based Estimation of Gross Primary Production in an Alpine Swamp Meadow on the Tibetan Plateau: A Multi-Model Comparison

Abstract: Alpine swamp meadows on the Tibetan Plateau, with the highest soil organic carbon content across the globe, are extremely vulnerable to climate change. To accurately and continually quantify the gross primary production (GPP) is critical for understanding the dynamics of carbon cycles from site-scale to global scale. Eddy covariance technique (EC) provides the best approach to measure the site-specific carbon flux, while satellite-based models can estimate GPP from local, small scale sites to regional and global scales. However, the suitability of most satellite-based models for alpine swamp meadow is unknown. Here we tested the performance of four widely-used models, the MOD17 algorithm (MOD), the vegetation photosynthesis model (VPM), the photosynthetic capacity model (PCM), and the alpine vegetation model (AVM), in providing GPP estimations for a typical alpine swamp meadow as compared to the GPP estimations provided by EC-derived GPP. Our results indicated that all these models provided good descriptions of the intra-annual GPP patterns (R2>0.89, P<0.0001), but hardly agreed with the inter-annual GPP trends. VPM strongly underestimated the GPP of alpine swamp meadow, only accounting for 54.0% of GPP_EC. However, the other three satellite-based GPP models could serve as alternative tools for tower-based GPP observation. GPP estimated from AVM captured 94.5% of daily GPP_EC with the lowest average RMSE of 1.47 g C m-2. PCM slightly overestimated GPP by 12.0% while MODR slightly underestimated by 8.1% GPP compared to the daily GPP_EC. Our results suggested that GPP estimations for this alpine swamp meadow using AVM were superior to GPP estimations using the other relatively complex models.

Livestock Dynamic Responses to Climate Change in Alpine Grasslands on the Northern Tibetan Plateau: Forage Consumption and Time-Lag Effects

Abstract: Climate change and forage-intake are important components of livestock population systems, but our knowledge about the effects of changes in these properties on livestock is limited, particularly on the Northern Tibetan Plateau. Based on corresponding independent models (CASA and TEM), a human-induced NPP (NPPH) value and forage-intake threshold were obtained to determine their influences on livestock population fluctuation and regrowth on the plateau. The intake threshold value provided compatible results with livestock population performance. If the forage-intake was greater than the critical value of 1.9 (kg DM d-1 sheep-1), the livestock population increased; otherwise, the livestock population decreased. It takes four years to transfer a disturbance in primary productivity to the next trophic level. The relationships between livestock population and NPPH value determined population dynamics via the forage-intake value threshold. Improved knowledge on lag effects will advance our understanding of drivers of climatic changes on livestock population dynamics.

Modeling Aboveground Biomass Using MODIS Images and Climatic Data in Grasslands on the Tibetan Plateau

Abstract: Accurate quantification of aboveground biomass of grasslands in alpine regions plays an important role in accurate quantification of global carbon cycling. The monthly normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), mean air temperature (Ta), ≥5°C accumulated air temperature (AccT), total precipitation (TP), and the ratio of TP to AccT (TP/AccT) were used to model aboveground biomass (AGB) in grasslands on the Tibetan Plateau. Three stepwise multiple regression methods, including stepwise multiple regression of AGB with NDVI and EVI, stepwise multiple regression of AGB with Ta, AccT, TP and TP/AccT, and stepwise multiple regression of AGB with NDVI, EVI, Ta, AccT, TP and TP/AccT were compared. The mean absolute error (MAE) and root mean squared error (RMSE) values between estimated AGB by the NDVI and measured AGB were 31.05 g m-2 and 44.12 g m-2, and 95.43 g m-2 and 131.58 g m-2 in the meadow and steppe, respectively. The MAE and RMSE values between estimated AGB by the AccT and measured AGB were 33.61g m-2 and 48.04 g m-2 in the steppe, respectively. The MAE and RMSE values between estimated AGB by the vegetation index and climatic data and measured AGB were 28.09 g m-2 and 42.71 g m-2, and 35.86 g m-2 and 47.94 g m-2, in the meadow and steppe, respectively. The study finds that a combination of vegetation index and climatic data can improve the accuracy of estimates of AGB that are arrived at using the vegetation index or climatic data. The accuracy of estimates varied depending on the type of grassland.

Estimation of Daily Vapor Pressure Deficit Using MODIS Potential Evapotranspiration on the Tibetan Plateau

Abstract: Vapor pressure deficit (VPD) is an important parameter in modelling hydrologic cycles and vegetation productivity. Meteorological stations are scarce in remote areas, which often results in imprecise estimations of VPD on the Tibetan Plateau. Moderate Resolution Imaging Spectroradiometer (MODIS) provides evapotranspiration data, which may offer the possibility of scaling up VPD estimations on the Tibetan Plateau. However, no studies thus far have estimated VPD using MODIS evapotranspiration data on the Tibetan Plateau. Therefore, this study used MODIS potential evapotranspiration (PET) to estimate VPD in alpine meadows, alpine steppes, croplands, forests and shrublands for the year, spring, summer, autumn and winter in 2000–2012. A series of root-meansquared-error (RMSE) and mean-absolute-error (MAE) values were obtained for correlating measured VPD and estimated VPD using MODIS PET data for each listed time period and vegetation type: whole year (0.98–2.15 hPa and 0.68–1.44 hPa), spring (0.95–2.34 hPa and 0.72–1.54 hPa), summer (1.39–2.60 hPa and 0.89–1.96 hPa), autumn (0.78–1.93 hPa and 0.56–1.36 hPa), winter (0.48–1.40 hPa and 0.36–0.98 hPa), alpine steppes (0.48–1.39 hPa and 0.36–1.00 hPa), alpine meadows (0.58–1.39 hPa and 0.44–0.90 hPa), croplands (1.10–2.55 hPa and 0.82–1.74 hPa), shrublands (0.98–1.90 hPa and 0.78–1.37 hPa), and forests (1.40–2.60 hPa and 0.98–1.96 hPa), respectively. Therefore, MODIS PET may be used to estimate VPD, and better results may be obtained if future studies incorporate vegetation types and seasons when the VPD data are estimated using MODIS PET on the Tibetan Plateau.

The Effect of Higher Warming on Vegetation Indices and Biomass Production is Dampened by Greater Drying in an Alpine Meadow on the Northern Tibetan Plateau

Abstract: In order to understand whether or not the response of vegetation indices and biomass production to warming varies with warming magnitude, an experiment of field warming at two magnitudes was conducted in an alpine meadow on the northern Tibetan Plateau beginning in late June, 2013. The normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI) and soil adjusted vegetation index (SAVI) data were obtained using a Tetracam Agricultural Digital Camera in 2013–2014. The gross primary production (GPP) and aboveground plant biomass (AGB) were modeled using the surface measured NDVI and climatic data during the growing seasons (i.e. June–September) in 2013–2014. Both low and high warming significantly increased air temperature by 1.54 and 4.00°C, respectively, and significantly increased vapor pressure deficit by 0.13 and 0.31 kPa, respectively, in 2013–2014. There were no significant differences of GNDVI, AGB and ANPP among the three warming treatments. The high warming significantly reduced average NDVI by 23.3% (–0.06), while the low warming did not affect average NDVI. The low and high warming significantly decreased average SAVI by 19.0% (–0.04) and 27.4% (–0.05), respectively, and average GPP by 24.2% (i.e. 0.21 g C m-2 d-1) and 44.0% (i.e. 0.39 g C m-2 d-1), respectively. However, the differences of the average NDVI, SAVI, and GPP between low and high warming were negligible. Our findings suggest that a greater drying may dampen the effect of a higher warming on vegetation indices and biomass production in alpine meadow on the northern Tibetan Plateau.