Annual variation of carbon flux and impact factors in the tropical seasonal rain forest of xishuangbanna, SW China

Zhang, Yiping; Sha, Liqing; Yu, Guirui; Song, Qinghai; Tang, Jianwei; Yang, Xiaodong; Wang, Yuesi; Zhang, Zheng; Zhao, Shuangju; Yang, Zhen; Sun, Xiaomin

doi:10.1007/s11430-006-8150-4

Cited by 16 publications

(13 citation statements)

References 24 publications

(35 reference statements)

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“…The stands are mainly broadleaf evergreen although there are some deciduous trees. Total canopy LAI is about 5·58 m 2 m −2 , with variations between 3·56 m 2 m −2 in the hot‐dry season of March and April and 6·34 m 2 m −2 in the rainy season of May through October (Zhang et al , 2006). More detailed descriptions of the vegetation at this site can be found in Cao et al (1996, 2006) and Zhu et al (2006).…”

Section: Methodsmentioning

confidence: 99%

Evapotranspiration of a tropical rain forest in Xishuangbanna, southwest China

Li¹,

Zhang²,

Wang³

et al. 2010

Hydrological Processes

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Abstract:The eddy covariance flux measurements from 2003 to 2006 at a tropical rain forest site in Xishuangbanna, southwest China, were used to study the ecosystem evapotranspiration (ET). During the four study years, the mean annual precipitation and air temperature were slightly lower than their long-term averages (1322 vs 1487 mm and 20Ð1 vs 21Ð7°C, respectively). Mean annual ET in the four study years was estimated at 1029 mm, accounted for 78% of the corresponding annual precipitation. Mean daily ecosystem ET was 2Ð6 mm day 1 during the dry season from November to April and was 3Ð1 mm day 1 during the rainy season from May to October. The ET diurnal variations in the cool-dry season (from November to February), the hot-dry season (March and April) and the rainy season had similar maximum values, although the soil water content, leaf area index (LAI) and climate conditions differed greatly. ET was mainly controlled by soil water availability in the hot-dry season, by LAI in the early rainy season (May and June) and by atmospheric conditions in the mid-to-late rainy season (from July to October) and the cool-dry season. The total ET was substantially higher than the corresponding precipitation in the dry season. The extra amount of water evapotranspirated in the dry season was mainly due to the depletion of soil water stored in the previous rainy season. Fog deposition during the dry season also played a role in providing water for ET. Our results indicated the importance of interannual interactions of water balance in the seasonal distribution of ecosystem ET at this site.

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Section: Methodsmentioning

confidence: 99%

Evapotranspiration of a tropical rain forest in Xishuangbanna, southwest China

Li¹,

Zhang²,

Wang³

et al. 2010

Hydrological Processes

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“…Assumptions regarding the effect of SWC on R S and using precipitation as proxy of SWC in R SG models also injects variability in R SG estimates (Jassal et al., ; Kirschbaum, ; Zhang et al., ). SWC is another important environmental factor that affects R S ; however, the relationship between SWC and R S is much more complex than the relationship between R S and temperature.…”

Section: Introductionmentioning

confidence: 99%

Constraining estimates of global soil respiration by quantifying sources of variability

Jian

Steele

Thomas

et al. 2018

Global Change Biology

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Quantifying global soil respiration (R ) and its response to temperature change are critical for predicting the turnover of terrestrial carbon stocks and their feedbacks to climate change. Currently, estimates of R range from 68 to 98 Pg C year , causing considerable uncertainty in the global carbon budget. We argue the source of this variability lies in the upscaling assumptions regarding the model format, data timescales, and precipitation component. To quantify the variability and constrain R , we developed R models using Random Forest and exponential models, and used different timescales (daily, monthly, and annual) of soil respiration (R ) and climate data to predict R . From the resulting R estimates (range = 66.62-100.72 Pg), we calculated variability associated with each assumption. Among model formats, using monthly R data rather than annual data decreased R by 7.43-9.46 Pg; however, R calculated from daily R data was only 1.83 Pg lower than the R from monthly data. Using mean annual precipitation and temperature data instead of monthly data caused +4.84 and -4.36 Pg C differences, respectively. If the timescale of R data is constant, R estimated by the first-order exponential (93.2 Pg) was greater than the Random Forest (78.76 Pg) or second-order exponential (76.18 Pg) estimates. These results highlight the importance of variation at subannual timescales for upscaling to R The results indicated R is lower than in recent papers and the current benchmark for land models (98 Pg C year ), and thus may change the predicted rates of terrestrial carbon turnover and the carbon to climate feedback as global temperatures rise.

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“…It is based on the principle that the vertical flux of an entity in the turbulent surface layer is proportional to the covariance of the vertical velocity and its concentration [97]. Over the last few years, EC measurements have provided vital information about terrestrial C balances on a variety of ecosystems such as boreal forests [98]; boreal and arctic peatlands [99][100][101]; tropical rainforest [102][103][104]; tropical savannah (e.g., [105]); tropical seasonal forest (e.g., [106,107]); tundra (e.g., [108,109]); tropical wetlands, mangrove, and tropical swamps [110]; temperate wetlands and peatlands [111][112][113]; temperate grasslands [114]; and even vegetated urban landscapes [79,115,116].…”

Section: Monitoring Carbon Cycling In Terrestrial Ecosystemsmentioning

confidence: 99%

Understanding the Terrestrial Carbon Cycle: An Ecohydrological Perspective

Govind

Kumari

2014

International Journal of Ecology

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The terrestrial carbon (C) cycle has a great role in influencing the climate with complex interactions that are spatially and temporally variable and scale-related. Hence, it is essential that we fully understand the scale-specific complexities of the terrestrial C-cycle towards (1) strategic design of monitoring and experimental initiatives and (2) also developing conceptualizations for modeling purposes. These complexities arise due to the nonlinear interactions of various components that govern the fluxes of mass and energy across the soil-plant-atmospheric continuum. Considering the critical role played by hydrological processes in governing the biogeochemical and plant physiological processes, a coupled representation of these three components (collectively referred to as ecohydrological approach) is critical to explain the complexity in the terrestrial C-cycling processes. In this regard, we synthesize the research works conducted in this broad area and bring them to a common platform with an ecohydrological spirit. This could aid in the development of novel concepts of nonlinear ecohydrological interactions and thereby help reduce the current uncertainties in the terrestrial C-cycling process. The usefulness of spatially explicit and process-based ecohydrological models that have tight coupling between hydrological, ecophysiological, and biogeochemical processes is also discussed.

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Annual variation of carbon flux and impact factors in the tropical seasonal rain forest of xishuangbanna, SW China

Cited by 16 publications

References 24 publications

Evapotranspiration of a tropical rain forest in Xishuangbanna, southwest China

Evapotranspiration of a tropical rain forest in Xishuangbanna, southwest China

Constraining estimates of global soil respiration by quantifying sources of variability

Understanding the Terrestrial Carbon Cycle: An Ecohydrological Perspective

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