Net ecosystem CO2 exchange and controlling factors in a steppe—Kobresia meadow on the Tibetan Plateau

Shi, Peili; Sun, Xiaomin; Xu, Lurong; Zhang, Xianzhou; He, Yongtao; Zhang, Dongqiu; Yu, Guirui

doi:10.1007/s11430-006-8207-4

Cited by 102 publications

(72 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…STE locates in the semi-arid region with a mean annual precipitation of only 350.9 mm and the precipitation distributed unevenly across seasons and years, which may be the main reason of the low performance in this vegetation type. The most likely reason for the low performance in MEA is its very sparse vegetation cover with the maximum leaf area index (LAI max ) of only 1.88 m 2 m −2 (Shi et al, 2006). Further application of the ReRSM was based on the model parameters retrieved from the site-years with less than 20% of the daily R e missing in each vegetation type to ensure the robust of the parameters ( Table 2).…”

Section: The Rersm Parameterization and Validationmentioning

confidence: 99%

A remote sensing model to estimate ecosystem respiration in Northern China and the Tibetan Plateau

Gao

et al. 2015

Ecological Modelling

Self Cite

View full text Add to dashboard Cite

a b s t r a c tEcosystem respiration (R e ) is rarely quantified from remote sensing data because satellite technique is incapable of observing the key processes associated with soil respiration. In this study, we develop a Remote Sensing Model for R e (ReRSM) by assuming that one part of R e is derived from current photosynthate with the respiratory rate coupling closely with gross primary production (GPP), and the other part of R e is derived from reserved ecosystem organic matter (including plant biomass, plant residues and soil organic matter) with the respiratory rate responding strongly to temperature change. The ReRSM is solely driven by the Enhanced Vegetation Index (EVI), the Land Surface Water Index (LSWI) and the Land Surface Temperature (LST) from MODIS data. Multi-year eddy CO 2 flux data of five vegetation types in Northern China and the Tibetan Plateau (including temperate mixed forest, temperate steppe, alpine shrubland, alpine marsh and alpine meadow-steppe) were used for model parameterization and validation. In most cases, the simulated R e agreed well with the observed R e in terms of seasonal and interannual variation irrespective of vegetation types. The ReRSM could explain approximately 93% of the variation in the observed R e across five vegetation types, with the root mean square error (RMSE) of 0.04 mol C m −2 d −1 and the modeling efficiency (EF) of 0.93. Model comparison showed that the performance of the ReRSM was comparable with that of the RECO in the studied five vegetation types, while the former had much fewer parameters than the latter. The ReRSM parameters showed good linear relationships with the mean annual satellite indices. With these linear functions, the ReRSM could explain approximately 90% of the variation in the observed R e across five vegetation types, with the RMSE of 0.05 mol C m −2 d −1 and the EF of 0.89. These analyses indicated that the ReRSM is a simple and alternative approach in R e estimation and has the potential of estimating spatial R e . However, the performance of ReRSM in other vegetation types or regions still needs a further study.

show abstract

Section: The Rersm Parameterization and Validationmentioning

confidence: 99%

A remote sensing model to estimate ecosystem respiration in Northern China and the Tibetan Plateau

Gao

et al. 2015

Ecological Modelling

Self Cite

View full text Add to dashboard Cite

show abstract

“…Table 1 provides extensive descriptions of the three sites. For further details about the study sites, refer to our previous papers (Fu et al, 2006b;Hao et al, 2007;Shi et al, 2006).…”

Section: Site Descriptionmentioning

confidence: 99%

“…Kato et al, 2004;Zhao et al, 2005;Shi et al, 2006;Hao et al, 2007;Wang et al, 2008), but none synthetically studied the CO 2 exchange and its relationship with environmental factors across different grassland types or biomes. In this study we presented measurements of CO 2 flux over three grassland ecosystems in China in 2004 and 2005.…”

Section: Introductionmentioning

confidence: 99%

Environmental influences on carbon dioxide fluxes over three grassland ecosystems in China

Zheng

et al. 2009

Biogeosciences

125

View full text Add to dashboard Cite

Abstract. This study compared carbon dioxide (CO 2 ) fluxes over three grassland ecosystems in China, including a temperate semiarid steppe in Inner Mongolia (NMG), an alpine shrub-meadow in Qinghai (HB), and an alpine meadowsteppe in Tibet (DX). Measurements were made in 2004 and 2005 using the eddy covariance technique. Objectives were to document the seasonality of the net ecosystem exchange of CO 2 (NEE) and its components, gross ecosystem photosynthesis (GEP), and ecosystem respiration (R eco ), and to examine how environmental factors affect the CO 2 exchange in these grassland ecosystems. The 2005 growing season (from May to September) was warmer than that of 2004 across the three sites, and precipitation in 2005 was less than that in 2004 at NMG and DX. The magnitude of CO 2 fluxes (daily and annual sums) was largest at HB, which also showed the highest temperature sensitivity of R eco among the three sites. A stepwise multiple regression analysis showed that the seasonal variation of GEP, R eco , and NEE of the alpine shrubmeadow was mainly controlled by air temperature, whereas leaf area index can likely explain the seasonal variation in GEP, R eco , and NEE of the temperate steppe. The CO 2 fluxes of the alpine meadow-steppe were jointly affected by soil moisture and air temperature. The alpine shrub-meadow acted as a net carbon sink over the two study years, whereas the temperate steppe and alpine meadow-steppe acted as net carbon sources. Both GEP and R eco were reduced by the summer and spring drought in 2005 at NMG and DX, respectively. The accumulated leaf area index during the growCorrespondence to: G. Yu (yugr@igsnrr.ac.cn) ing season (LAI sum ) played a key role in the interannual and intersite variation of annual GEP and R eco across the study sites and years, whereas soil moisture contributed most significantly to the variation in annual NEE. Because LAI sum was significantly correlated with soil moisture at a depth of 20 cm, we concluded that the available soil moisture other than annual precipitation was the most important factor controlling the variation in the CO 2 budgets of different grassland ecosystems in China.

show abstract

“…Temperate steppes and alpine meadows served as weak carbon sink (24±83, 45±59 g C m -2 yr -1 ). The grasslands in northern China probably served as a weak carbon source after disturbances, which differed substantially among ecosystems and years (Shi et al, 2006;Li et al, 2006;Fu et al, 2006Fu et al, , 2009Yu et al, 2013b).…”

Section: Evaluation Of Ecosystem Carbon Sink/source Based On Flux Meamentioning

confidence: 99%

Construction and progress of Chinese terrestrial ecosystem carbon, nitrogen and water fluxes coordinated observation

Wang

Chen

et al. 2016

J. Geogr. Sci.

Self Cite

View full text Add to dashboard Cite

Eddy Covariance technique (EC) achieves the direct measurement on ecosystem carbon, nitrogen and water fluxes, and it provides scientific data for accurately assessing ecosystem functions in mitigating global climate change. This paper briefly reviewed the construction and development of Chinese terrestrial ecosystem flux observation and research network (ChinaFLUX), and systematically introduced the design principle and technology of the terrestrial ecosystem carbon, nitrogen and water fluxes coordinated observation system of ChinaFLUX. In addition, this paper summarized the main progress of ChinaFLUX in the ecosystem carbon, nitrogen and water exchange and environmental controlling mechanisms, the spatial pattern of carbon, nitrogen and water fluxes and biogeographical mechanisms, and the regional terrestrial ecosystem carbon budget assessment. Finally, the prospects and emphases of the terrestrial ecosystem carbon, nitrogen and water fluxes coordinated observation of ChinaFLUX are put forward to provide theoretical references for the development of flux observation and research in China.

show abstract

Net ecosystem CO2 exchange and controlling factors in a steppe—Kobresia meadow on the Tibetan Plateau

Cited by 102 publications

References 24 publications

A remote sensing model to estimate ecosystem respiration in Northern China and the Tibetan Plateau

A remote sensing model to estimate ecosystem respiration in Northern China and the Tibetan Plateau

Environmental influences on carbon dioxide fluxes over three grassland ecosystems in China

Construction and progress of Chinese terrestrial ecosystem carbon, nitrogen and water fluxes coordinated observation

Contact Info

Product

Resources

About