Yongtao He

Changes in individual plant traits and biomass allocation in alpine meadow with elevation variation on the Qinghai-Tibetan Plateau

Plant traits and individual plant biomass allocation of 57 perennial herbaceous species, belonging to three common functional groups (forbs, grasses and sedges) at subalpine (3700 m ASL), alpine (4300 m ASL) and subnival (⩾5000 m ASL) sites were examined to test the hypothesis that at high altitudes, plants reduce the proportion of aboveground parts and allocate more biomass to belowground parts, especially storage organs, as altitude increases, so as to geminate and resist environmental stress. However, results indicate that some divergence in biomass allocation exists among organs. With increasing altitude, the mean fractions of total biomass allocated to aboveground parts decreased. The mean fractions of total biomass allocation to storage organs at the subalpine site (7%±2% S.E.) were distinct from those at the alpine (23%±6%) and subnival (21%±6%) sites, while the proportions of green leaves at all altitudes remained almost constant. At 4300 m and 5000 m, the mean fractions of flower stems decreased by 45% and 41%, respectively, while fine roots increased by 86% and 102%, respectively. Specific leaf areas and leaf areas of forbs and grasses deceased with rising elevation, while sedges showed opposite trends. For all three functional groups, leaf area ratio and leaf area root mass ratio decreased, while fine root biomass increased at higher altitudes. Biomass allocation patterns of alpine plants were characterized by a reduction in aboveground reproductive organs and enlargement of fine roots, while the proportion of leaves remained stable. It was beneficial for high altitude plants to compensate carbon gain and nutrient uptake under low temperature and limited nutrients by stabilizing biomass investment to photosynthetic structures and increasing the absorption surface area of fine roots. In contrast to forbs and grasses that had high mycorrhizal infection, sedges had higher single leaf area and more root fraction, especially fine roots.

Calibration of MODIS-based gross primary production over an alpine meadow on the Tibetan Plateau

Moderate-resolution imaging spectroradiometer (MODIS) gross primary production (GPP) was compared with estimated GPP (GPP_EC) from eddy covariance measurements over an alpine meadow on the Tibetan Plateau in 2005–2007. The MODIS GPP (GPP_MOD17A2) with a bias of −0.38 g C m−2 d−1 (i.e., about −40.58% of the mean of the GPP_EC) strongly underestimated the GPP_EC for the alpine meadow. The MODIS GPP was recalibrated using measured surface meteorological data, including photosynthetically active radiation (PAR), daily minimum air temperature (Tamin) and daytime mean vapor pressure deficit (VPD), revised fractional photosynthetically active radiation (FPAR), and the revised maximum light use efficiency (LUEmax) of 0.81 g C MJ−1 (compared with the default value of 0.68 g C MJ−1 for grassland in the MODIS GPP algorithm) for the alpine meadow. The MODIS-based FPAR was about 14.70% larger than the surface-estimated FPAR using surface-measured leaf area index (LAI) data. Additionally, the temporal resolution of surface-measured LAI data was relatively low. Therefore, the linear relationship between surface-measured LAI and MODIS-based LAI was established (R2 > 0.80, P < 0.001). Then the revised MODIS LAI datasets were used to calculate the revised FPAR. The revised LUEmax was optimized from the MOD17A2 algorithm using daily surface measurements, including LAI, PAR, VPD, Tamin and GPP_EC. The calibrated MOD17A2 algorithm could explain 88% of GPP_EC variance for the alpine meadow. The bias between GPP_MOD17A2 and calculated GPP from the MOD17A2 algorithm using surface-measured PAR, Tamin, and VPD, MODIS-based FPAR, and the default LUEmax of 0.68 g C MJ−1 was −0.17 g C m−2 d−1 (i.e., about −17.60% of the mean of the GPP_EC). The underestimation of LUEmax caused a 13.78% underestimation of GPP. In contrast, the overestimation of FPAR resulted in a 7.17% overestimation of GPP. The net effect of meteorology data and FPAR resulted in a 13.84% underestimation of GPP. These results showed that MODIS-based meteorology data, FPAR, and LUEmax for the alpine meadow needed to be adjusted.

Direct and indirect effects of climatic variations on the interannual variability in net ecosystem exchange across terrestrial ecosystems

Climatic variables not only directly affect the interannual variability (IAV) in net ecosystem exchange of CO2 (NEE) but also indirectly drive it by changing the physiological parameters. Identifying these direct and indirect paths can reveal the underlying mechanisms of carbon (C) dynamics. In this study, we applied a path analysis using flux data from 65 sites to quantify the direct and indirect climatic effects on IAV in NEE and to evaluate the potential relationships among the climatic variables and physiological parameters that represent physiology and phenology of ecosystems. We found that the maximum photosynthetic rate was the most important factor for the IAV in gross primary productivity (GPP), which was mainly induced by the variation in vapour pressure deficit. For ecosystem respiration (RE), the most important drivers were GPP and the reference respiratory rate. The biome type regulated the direct and indirect paths, with distinctive differences between forests and non-forests, evergreen needleleaf forests and deciduous broadleaf forests, and between grasslands and croplands. Different paths were also found among wet, moist and dry ecosystems. However, the climatic variables can only partly explain the IAV in physiological parameters, suggesting that the latter may also result from other biotic and disturbance factors. In addition, the climatic variables related to NEE were not necessarily the same as those related to GPP and RE, indicating the emerging difficulty encountered when studying the IAV in NEE. Overall, our results highlight the contribution of certain physiological parameters to the IAV in C fluxes and the importance of biome type and multi-year water conditions, which should receive more attention in future experimental and modelling research.

Tower-Based Validation and Improvement of MODIS Gross Primary Production in an Alpine Swamp Meadow on the Tibetan Plateau

Alpine swamp meadow on the Tibetan Plateau is among the most sensitive areas to climate change. Accurate quantification of the GPP in alpine swamp meadow can benefit our understanding of the global carbon cycle. The 8-day MODerate resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) products (GPP_MOD) provide a pathway to estimate GPP in this remote ecosystem. However, the accuracy of the GPP_MOD estimation in this representative alpine swamp meadow is still unknown. Here five years GPP_MOD was validated using GPP derived from the eddy covariance flux measurements (GPP_EC) from 2009 to 2013. Our results indicated that the GPP_EC was strongly underestimated by GPP_MOD with a daily mean less than 40% of EC measurements. To reduce this error, the ground meteorological and vegetation leaf area index (LAIG) measurements were used to revise the key inputs, the maximum light use efficiency (emax) and the fractional photosynthetically active radiation (FPARM) in the MOD17 algorithm. Using two approaches to determine the site-specific emax value, we suggested that the suitable emax was about 1.61 g C MJ−1 for this alpine swamp meadow which was considerably larger than the default 0.68 g C MJ−1 for grassland. The FPARM underestimated 22.2% of the actual FPAR (FPARG) simulated from the LAIG during the whole study period. Model comparisons showed that the large inaccuracies of GPP_MOD were mainly caused by the underestimation of the emax and followed by that of the undervalued FPAR. However, the DAO meteorology data in the MOD17 algorithm did not exert a significant affection in the MODIS GPP underestimations. Therefore, site-specific optimized parameters inputs, especially the emax and FPARG, are necessary to improve the performance of the MOD17 algorithm in GPP estimation, in which the calibrated MOD17A2 algorithm (GPP_MODR3) could explain 91.6% of GPP_EC variance for the alpine swamp meadow.

Variation of biomass and morphology of the cushion plant Androsace tapete along an elevational gradient in the Tibetan Plateau

Alpine ecosystems are among those biomes that are most vulnerable to climate change. Cushion plants are an important life form of alpine ecosystems and will likely play a critical role for the resilience of these habitats to climate change. We studied cushion size distribution and different measures of the compactness of cushions (biomass and rosette density, leaf area index) of the cushion plant, Androsace tapete along an elevational gradient from 4500 to 5200 m a. s. l. in the Nyainqentanglha Mountains of the central Tibetan Plateau. Cushion size distribution, total cover, and compactness of cushions varied substantially along the elevational gradient. At the driest site at low elevation we found the lowest total cushion cover, a particularly high proportion of very small cushions, and the most compact cushions (highest rosette and biomass densities, and leaf area index (LAI) per cushion). Our results indicate that in the semi-arid Tibetan Plateau water availability is the more important climate factor than temperature affecting cushion plant traits and morphology.

Validation of collection of 6 MODIS/Terra and MODIS/Aqua gross primary production in an alpine meadow of the Northern Tibetan Plateau

ABSTRACT Moderate Resolution Imaging Spectroradiometer (MODIS) continuously monitors gross primary production (GPP), which is an extremely important component of carbon cycling, at the global scale. Uncertainties about MODIS GPP limit our ability to accurately quantify GPP at the regional scales. The Collection 6 MODIS/Terra and MODIS/Aqua GPP products (i.e. MOD17A2H and MYD17A2H) were compared with the estimated GPP (GPPEC) by eddy covariance measurements in an alpine meadow in the Northern Tibetan Plateau during three consecutive growing seasons of 2005–2007. The Collection 6 MODIS/Terra and MODIS/Aqua fractional photosynthetically active radiation (FPAR) products (i.e. MOD15A2H and MYD15A2H) were also validated. The MOD17A2H and MYD17A2H products tended to overestimate GPPEC by 2.17% and 7.35% in 2005–2007, respectively, although these differences were not significant. The MOD15A2H and MYD15A2H products also tended to overestimate ground-based FPAR (FPARG) by 20.31% and 24.73% in 2005–2007, respectively. The overestimation of FPAR resulted in about 17.51–23.97% overestimation of GPPEC. The default maximum light-use efficiency (εmax) of 0.86 g C MJ−1 only underestimated the ground-based εmax (0.88 g C MJ−1) by 2.27%, which in turn resulted in about 2.13–2.72% underestimation of GPPEC. The meteorology data errors only caused about 0.48–1.06% underestimation of GPPEC. Therefore, although MODIS Collection 6 GPP had a very high accuracy, the input parameters had relative greater errors in the alpine meadow of the Northern Tibetan Plateau. The differences between MODIS GPP and GPPEC mainly resulted from FPAR, followed by εmax and meteorological data.

The Soil Drying Along the Increase of Warming Masks the Relation between Temperature and Soil Respiration in an Alpine Meadow of Northern Tibet

ABSTRACT A warming experiment with two magnitudes was performed in an alpine meadow of Northern Tibet since late June, 2013. Open top chambers (OTCs) with two top diameters (0.60 m and 1.00 m) were used to increase soil temperature. Soil respiration (Rs) was measured during the growing season in 2013–2014. The OTCs with top diameters of 1.00 m and 0.60 m increased soil temperature by 1.30 and 3.10oC, respectively, during the whole study period, but decreased soil moisture by 0.02 and 0.05 m3 m-3, respectively. However, the two patters of OTCs did not affect Rs . These results implied that a higher warming did not result in a higher Rs but a greater soil drying. Therefore, a higher warming may not cause a higher soil respiration, which was most likely due to the fact that a higher warming may result in a greater soil drying.

Modeling Net Ecosystem Carbon Exchange of Alpine Grasslands with a Satellite-Driven Model

Estimate of net ecosystem carbon exchange (NEE) between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP) and ecosystem respiration (Reco) has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model.

Ecological Restoration in the Typical Areas

Human activities are strongly regional and targeted, and usually tightly bound to the regional natural resources, the needs of social economic development, and ecological fragility, which cause typical regional ecosystem degradation problems. For serious degradation areas, it is an effective way to carry out regional ecological restoration and construction for restoration ecology study, which is the key to promote sustainable development and ecological security, and also the urgent requirement for the current reality. According to the demand of regional sustainable development, this chapter focused on ecological deterioration, and restoration and construction in typical areas. The chapter specially made thematic discussions on new progression in degradation problems of developing and utilizing the resource, ecological restoration practices, theory, techniques, mode, and management. This chapter was trying to provide experience and lessons, macro guidance and decision-making reference for ecological restoration in typical areas. From the regional cases of this chapter, we can see that regional ecological restoration and construction is intricate. Finally, it is necessary to point out that there are many regional ecological restoration cases, here just introduce several cases in western fragile region. The ecological restoration cases revealed in this chapter are just the first attempt to conclude the past experiences in China, which are initial identification for correlated theories and methods.

Satellite-Based Inversion and Field Validation of Autotrophic and Heterotrophic Respiration in an Alpine Meadow on the Tibetan Plateau

Alpine meadow ecosystem is among the highest soil carbon density and the most sensitive ecosystem to climate change. Partitioning autotrophic (Ra) and heterotrophic components (Rm) of ecosystem respiration (Re) is critical to evaluating climate change effects on ecosystem carbon cycling. Here we introduce a satellite-based method, combining MODerate resolution Imaging Spectroradiometer (MODIS) products, eddy covariance (EC) and chamber-based Re components measurements, for estimating carbon dynamics and partitioning of Re from 2009 to 2011 in a typical alpine meadow on the Tibetan Plateau. Six satellite-based gross primary production (GPP) models were employed and compared with GPP_EC, all of which appeared to well explain the temporal GPP_EC trends. However, MODIS versions 6 GPP product (GPP_MOD) and GPP estimation from vegetation photosynthesis model (GPP_VPM) provided the most reliable GPP estimation magnitudes with less than 10% of relative predictive error (RPE) compared to GPP_EC. Thus, they together with MODIS products and GPP_EC were used to estimate Re using the satellite-based method. All satellite-based Re estimations generated an alternative estimation of Re_EC with negligible root mean square errors (RMSEs, g C m−2 day−1) either in the growing season (0.12) or not (0.08). Moreover, chamber-based Re measurements showed that autotrophic contributions to Re (Ra/Re) could be effectively reflected by all these three satellite-based Re partitions. Results showed that the Ra contribution of Re were 27% (10–48%), 43% (22–59%) and 56% (33–76%) from 2009 to 2011, respectively, of which inter-annual variation is mainly attributed to soil water dynamics. This study showed annual temperature sensitivity of Ra (Q10,Ra) with an average of 5.20 was significantly higher than that of Q10,Rm (1.50), and also the inter-annual variation of Q10,Ra (4.14–7.31) was larger than Q10,Rm (1.42–1.60). Therefore, our results suggest that the response of Ra to temperature change is stronger than that of Rm in this alpine meadow.