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

Abstract

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 (Q 10,Ra ) with an average of 5.20 was significantly higher than that of Q 10,Rm (1.50), and also the inter-annual variation of Q 10,Ra (4.14-7.31) was larger than Q 10,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.

Has the Dominant Climatic Driver for the Carbon Budget of Alpine Grassland Shifted from Temperature to Precipitation on the Qinghai–Tibet Plateau?

“…This technique is increasingly used for the calibration and validation of ecosystem models [44,45]. To calibrate and validate the model, 40 site-years of NEP data, 26 site-years of GPP data, and 22 site-years of ER data from 21 eddy covariance (EC) observation sites (16 sites on meadow and 5 sites on steppe) (Figure 1a) were collected from previous research [5,44,46,47] and the National Tibetan Plateau Data Center (https://data.tpdc.ac.cn/home , accessed on 22 March 2022). The linear fitting method was employed to test the agreement between simulated results and the EC data, and R 2 and 95% confidence bands were used to characterize the degree of fitting (Figure 2).…”

Dynamic Threshold of Carbon Phenology in Two Cold Temperate Grasslands in China

“…To avoid potential influences from instrument malfunction, rainfall, dew or cobwebs, human disturbance, and near-static atmospheric conditions, raw measurements were processed and filled according to ChinaFLUX data processing [47,48], which included despiking, coordinate rotation, air density corrections, outlier rejection, and friction velocity threshold (u*) corrections [49]. Based on flux measurements and the exponential relationship between ecosystem respiration (Re) and soil temperature, daytime NEE was partitioned into EC-based GPP as carbon assimilation and Re as carbon emission during daytime (NEE = GPP + Re) [50,51].…”