Seasonal and inter-annual variations in CO2 fluxes over 10 years in an alpine shrubland on the Qinghai-Tibetan Plateau, China

Li, Hongqin; Zhang, Fawei; Li, Yingnian; Wang, Junbang; Zhang, Leiming; Zhao, Liang; Cao, Guangmin; Zhao, Xinquan; Du, Mingyuan

doi:10.1016/j.agrformet.2016.06.020

Cited by 79 publications

(66 citation statements)

References 40 publications

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“…Although LAI was not zero (ranging from 0.1 to 0.3) during the non growing season when there was nongreen flora, we retained this portion of the time series for data integrity but did not perform any relevant analysis during that time. The satellite‐LAI data for estimating green leaf quantity compared relatively favourable ( N = 30, R 2 = 0.73, p < .01) with the half‐monthly LAI of grassland measured through standard harvesting methods employing 50 × 50 cm quadrats with five replicates during the growing seasons of 2005 to 2007 (Li et al, ). Daily LAI was extrapolated by the Gaussian peak function (

italicLAI = {LAI}_{0} + ((), {LAI}_{\max} - {LAI}_{0}) e^{- \frac{{((), x - x_{c})}^{2}}{2 w^{2}}}

, where x is the corresponding day of MODIS LAI in that year, LAI 0 , LAI max , x c, and w are the fitted parameters, R 2 > 0.99, p < .001) for MODIS LAI each day of 1 year.…”

Section: Methodsmentioning

confidence: 99%

“…According to in situ observations of dominant plant phenological events, we defined regreen stage (May) and senescence stage (October) as the seasonal transition period between growing season and nongrowing season (Li et al, ). Then, we identified periods of LAI in the ranges <0.4, 0.4–1.0, and >1.0 m 2 /m 2 and classified these as nongrowing season, seasonal transition, and growing season, respectively.…”

Section: Methodsmentioning

confidence: 99%

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Net radiation rather than surface moisture limits evapotranspiration over a humid alpine meadow on the northeastern Qinghai‐Tibetan Plateau

Zhang

Wang

et al. 2017

Ecohydrology

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Accurately quantifying evapotranspiration (ET) is crucial to fully understanding regional water resource management and potential feedbacks to climate change in alpine grasslands. The quantitative relationships between ET and environmental controls were investigated by a continuous eddy covariance dataset from June 2014 to December 2016 over an alpine Kobresia meadow on the northeastern Qinghai‐Tibetan Plateau. The results showed that daily ET averaged 1.7± 1.5 mm/day (Mean ± 1 S.D.), with values of 2.9 ± 1.3, 1.6 ± 1.0, and 0.7± 0.6 mm/day during the growing season, seasonal transition period, and nongrowing season, respectively. Cumulative growing season ET was 63% of annual ET with little annual variability (349.9 ± 12.1 mm). Paired‐samples t‐test analysis indicated that monthly ET was larger than maximum potential ET derived from the FAO‐56 reference crop ET by 17% (p < .001, N = 12) in the growing season, likely because of high aerodynamic conductance, but was less than the minimum equilibrium ET by 19% (p < .001, N = 14) during the nongrowing season owing to limited surface moisture availability from the frozen soil. The structural equation models revealed that daily ET was mostly dominated by net radiation (the standardized coefficient of the total effect was 0.78). Soil surface moisture and leaf area index played secondary roles in daily ET variability during the nongrowing season and growing season, respectively. At an annual scale, the bulk surface conductance (8.25–10.65 mm/s), decoupling coefficient (0.43–0.48, 0.61 in the growing season), and the ratio of ET to equilibrium ET (1.08–1.33) were consistent with the strongly energy‐limited conditions in the alpine meadow. This study indicated that initial vegetation rehabilitation on the severely degraded meadow would be at the risk of rapid water consumption in humid alpine regions.

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italicLAI = {LAI}_{0} + ((), {LAI}_{\max} - {LAI}_{0}) e^{- \frac{{((), x - x_{c})}^{2}}{2 w^{2}}}

, where x is the corresponding day of MODIS LAI in that year, LAI 0 , LAI max , x c, and w are the fitted parameters, R 2 > 0.99, p < .001) for MODIS LAI each day of 1 year.…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Net radiation rather than surface moisture limits evapotranspiration over a humid alpine meadow on the northeastern Qinghai‐Tibetan Plateau

Zhang

Wang

et al. 2017

Ecohydrology

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“…The trees explain the variation of the response variable by repeatedly splitting the data into more homogeneous groups using combinations of explanatory variables. It can identify relatively important relevant variables regardless of the variable distribution and independence(Li et al, 2016;Zhang, Wu, et al, 2017) CART's ability to handle nonlinear relationships, strong interactions, and missing values made it a useful tool to analyze complex ecological data, especially in the synthesis of multisites The minimum number of data points in each leaf was set up to 15 to control the depth of the regression trees in this methodology. Predictor importance of all the explanatory variables was calculated to compare the relative predictive strength of all the variables.…”

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confidence: 99%

Seasonal variability of forest sensitivity to heat and drought stresses: A synthesis based on carbon fluxes from North American forest ecosystems

Arain

Black

et al. 2019

Global Change Biology

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Climate extremes such as heat waves and droughts are projected to occur more frequently with increasing temperature and an intensified hydrological cycle. It is important to understand and quantify how forest carbon fluxes respond to heat and drought stress. In this study, we developed a series of daily indices of sensitivity to heat and drought stress as indicated by air temperature (Ta) and evaporative fraction (EF). Using normalized daily carbon fluxes from the FLUXNET Network for 34 forest sites in North America, the seasonal pattern of sensitivities of net ecosystem productivity (NEP), gross ecosystem productivity (GEP) and ecosystem respiration (RE) in response to Ta and EF anomalies were compared for different forest types. The results showed that warm temperatures in spring had a positive effect on NEP in conifer forests but a negative impact in deciduous forests. GEP in conifer forests increased with higher temperature anomalies in spring but decreased in summer. The drought‐induced decrease in NEP, which mostly occurred in the deciduous forests, was mostly driven by the reduction in GEP. In conifer forests, drought had a similar dampening effect on both GEP and RE, therefore leading to a neutral NEP response. The NEP sensitivity to Ta anomalies increased with increasing mean annual temperature. Drier sites were less sensitive to drought stress in summer. Natural forests with older stand age tended to be more resilient to the climate stresses compared to managed younger forests. The results of the Classification and Regression Tree analysis showed that seasons and ecosystem productivity were the most powerful variables in explaining the variation of forest sensitivity to heat and drought stress. Our results implied that the magnitude and direction of carbon flux changes in response to climate extremes are highly dependent on the seasonal dynamics of forests and the timing of the climate extremes.

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“…Therefore, understanding NEE responses to environmental change, to ecosystem management and to site characteristics is essential for predicting future biogeochemical cycles (Law et al 2002;Pan et al 2014;Li et al 2016). To this end, processbased vegetation models (PVMs) of varying complexity are being used, operating at varying scales (Keenan et al 2012;Fischer et al 2014;Reyer 2015).…”

Section: Introductionmentioning

confidence: 99%

Combining multiple statistical methods to evaluate the performance of process-based vegetation models across three forest stands

Horemans¹,

Henrot

Delire³

et al. 2017

Central European Forestry Journal

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Process-based vegetation models are crucial tools to better understand biosphere-atmosphere exchanges and ecophysiological responses to climate change. In this contribution the performance of two global dynamic vegetation models, i.e. CARAIB and ISBA CC , and one stand-scale forest model, i.e. 4C, was compared to long-term observed net ecosystem carbon exchange (NEE) time series from eddy covariance monitoring stations at three old-grown European beech (Fagus sylvatica L.) forest stands. Residual analysis, wavelet analysis and singular spectrum analysis were used beside conventional scalar statistical measures to assess model performance with the aim of defining future targets for model improvement. We found that the most important errors for all three models occurred at the edges of the observed NEE distribution and the model errors were correlated with environmental variables on a daily scale. These observations point to possible projection issues under more extreme future climate conditions. Recurrent patterns in the residuals over the course of the year were linked to the approach to simulate phenology and physiological evolution during leaf development and senescence. Substantial model errors occurred on the multi-annual time scale, possibly caused by the lack of inclusion of management actions and disturbances. Other crucial processes defined were the forest structure and the vertical light partitioning through the canopy. Further, model errors were shown not to be transmitted from one time scale to another. We proved that models should be evaluated across multiple sites, preferably using multiple evaluation methods, to identify processes that request reconsideration.

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Seasonal and inter-annual variations in CO2 fluxes over 10 years in an alpine shrubland on the Qinghai-Tibetan Plateau, China

Cited by 79 publications

References 40 publications

Net radiation rather than surface moisture limits evapotranspiration over a humid alpine meadow on the northeastern Qinghai‐Tibetan Plateau

Net radiation rather than surface moisture limits evapotranspiration over a humid alpine meadow on the northeastern Qinghai‐Tibetan Plateau

Seasonal variability of forest sensitivity to heat and drought stresses: A synthesis based on carbon fluxes from North American forest ecosystems

Combining multiple statistical methods to evaluate the performance of process-based vegetation models across three forest stands

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