Dataset Information

Soil water content effects on net ecosystem CO2 exchange and actual evapotranspiration in a Mediterranean semiarid savanna of Central Chile.

ABSTRACT: Biosphere-atmosphere water and carbon fluxes depend on ecosystem structure, and their magnitudes and seasonal behavior are driven by environmental and biological factors. We studied the seasonal behavior of net ecosystem CO2 exchange (NEE), Gross Primary Productivity (GPP), Ecosystem Respiration (RE), and actual evapotranspiration (ETa) obtained by eddy covariance measurements during two years in a Mediterranean Acacia savanna ecosystem (Acacia caven) in Central Chile. The annual carbon balance was -53?g?C?m-2 in 2011 and -111?g?C?m-2 in 2012, showing that the ecosystem acts as a net sink of CO2, notwithstanding water limitations on photosynthesis observed in this particularly dry period. Total annual ETa was of 128?mm in 2011 and 139?mm in 2012. Both NEE and ETa exhibited strong seasonality with peak values recorded in the winter season (July to September), as a result of ecosystem phenology, soil water content and rainfall occurrence. Consequently, the maximum carbon assimilation rate occurred in wintertime. Results show that soil water content is a major driver of GPP and RE, defining their seasonal patterns and the annual carbon assimilation capacity of the ecosystem, and also modulating the effect that solar radiation and air temperature have on NEE components at shorter time scales.

SUBMITTER: Meza FJ

PROVIDER: S-EPMC5988705 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Soil water content effects on net ecosystem CO<sub>2</sub> exchange and actual evapotranspiration in a Mediterranean semiarid savanna of Central Chile.

Meza Francisco J FJ Montes Carlo C Bravo-Martínez Felipe F Serrano-Ortiz Penélope P Kowalski Andrew S AS

Scientific reports 20180605 1

Biosphere-atmosphere water and carbon fluxes depend on ecosystem structure, and their magnitudes and seasonal behavior are driven by environmental and biological factors. We studied the seasonal behavior of net ecosystem CO<sub>2</sub> exchange (NEE), Gross Primary Productivity (GPP), Ecosystem Respiration (RE), and actual evapotranspiration (ETa) obtained by eddy covariance measurements during two years in a Mediterranean Acacia savanna ecosystem (Acacia caven) in Central Chile. The annual carb ...[more]

PMID: 29872104

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Project description:Carbon dioxide (CO2) exchange between the atmosphere and grassland ecosystems is very important for the global carbon balance. To assess the CO2 flux and its relationship to environmental factors, the eddy covariance method was used to evaluate the diurnal cycle and seasonal pattern of the net ecosystem CO2 exchange (NEE) of a cultivated pasture in the Three-River Source Region (TRSR) on the Qinghai-Tibetan Plateau from January 1 to December 31, 2008. The diurnal variations in the NEE and ecosystem respiration (Re) during the growing season exhibited single-peak patterns, the maximum and minimum CO2 uptake observed during the noon hours and night; and the maximum and minimum Re took place in the afternoon and early morning, respectively. The minimum hourly NEE rate and the maximum hourly Re rate were -7.89 and 5.03 μmol CO2 m-2 s-1, respectively. The NEE and Re showed clear seasonal variations, with lower values in winter and higher values in the peak growth period. The highest daily values for C uptake and Re were observed on August 12 (-2.91 g C m-2 d-1) and July 28 (5.04 g C m-2 day-1), respectively. The annual total NEE and Re were -140.01 and 403.57 g C m-2 year-1, respectively. The apparent quantum yield (α) was -0.0275 μmol μmol-1 for the entire growing period, and the α values for the pasture's light response curve varied with the leaf area index (LAI), air temperature (Ta), soil water content (SWC) and vapor pressure deficit (VPD). Piecewise regression results indicated that the optimum Ta and VPD for the daytime NEE were 14.1°C and 0.65 kPa, respectively. The daytime NEE decreased with increasing SWC, and the temperature sensitivity of respiration (Q10) was 3.0 during the growing season, which was controlled by the SWC conditions. Path analysis suggested that the soil temperature at a depth of 5 cm (Tsoil) was the most important environmental factor affecting daily variations in NEE during the growing season, and the photosynthetic photon flux density (PPFD) was the major limiting factor for this cultivated pasture.

Project description:Forests play a crucial role in the global carbon (C) cycle by storing and sequestering a substantial amount of C in the terrestrial biosphere. Due to temporal dynamics in climate and vegetation activity, there are significant regional variations in carbon dioxide (CO2) fluxes between the biosphere and atmosphere in forests that are affecting the global C cycle. Current forest CO2 flux dynamics are controlled by instantaneous climate, soil, and vegetation conditions, which carry legacy effects from disturbances and extreme climate events. Our level of understanding from the legacies of these processes on net CO2 fluxes is still limited due to their complexities and their long-term effects. Here, we combined remote sensing, climate, and eddy-covariance flux data to study net ecosystem CO2 exchange (NEE) at 185 forest sites globally. Instead of commonly used non-dynamic statistical methods, we employed a type of recurrent neural network (RNN), called Long Short-Term Memory network (LSTM) that captures information from the vegetation and climate's temporal dynamics. The resulting data-driven model integrates interannual and seasonal variations of climate and vegetation by using Landsat and climate data at each site. The presented LSTM algorithm was able to effectively describe the overall seasonal variability (Nash-Sutcliffe efficiency, NSE = 0.66) and across-site (NSE = 0.42) variations in NEE, while it had less success in predicting specific seasonal and interannual anomalies (NSE = 0.07). This analysis demonstrated that an LSTM approach with embedded climate and vegetation memory effects outperformed a non-dynamic statistical model (i.e. Random Forest) for estimating NEE. Additionally, it is shown that the vegetation mean seasonal cycle embeds most of the information content to realistically explain the spatial and seasonal variations in NEE. These findings show the relevance of capturing memory effects from both climate and vegetation in quantifying spatio-temporal variations in forest NEE.

Project description:BackgroundPeatlands are an important component of Canada's landscape, however there is little information on their national-scale net emissions of carbon dioxide [Net Ecosystem Exchange (NEE)] and methane (CH4). This study compiled results for peatland NEE and CH4 emissions from chamber and eddy covariance studies across Canada. The data were summarized by bog, poor fen and rich-intermediate fen categories for the seven major peatland containing terrestrial ecozones (Atlantic Maritime, Mixedwood Plains, Boreal Shield, Boreal Plains, Hudson Plains, Taiga Shield, Taiga Plains) that comprise >?96% of all peatlands nationally. Reports of multiple years of data from a single site were averaged and different microforms (e.g., hummock or hollow) within these peatland types were kept separate. A new peatlands map was created from forest composition and structure information that distinguishes bog from rich and poor fen. National Forest Inventory k-NN forest structure maps, bioclimatic variables (mean diurnal range and seasonality of temperatures) and ground surface slope were used to construct the new map. The Earth Observation for Sustainable Development map of wetlands was used to identify open peatlands with minor tree cover.ResultsThe new map was combined with averages of observed NEE and CH4 emissions to estimate a growing season integrated NEE (±?SE) at -?108.8 (±?41.3) Mt CO2 season-1 and CH4 emission at 4.1 (±?1.5) Mt CH4 season-1 for the seven ecozones. Converting CH4 to CO2 equivalent (CO2e; Global Warming Potential of 25 over 100 years) resulted in a total net sink of -?7.0 (±?77.6) Mt CO2e season-1 for Canada. Boreal Plains peatlands contributed most to the NEE sink due to high CO2 uptake rates and large peatland areas, while Boreal Shield peatlands contributed most to CH4 emissions due to moderate emission rates and large peatland areas. Assuming a winter CO2 emission of 0.9 g CO2 m-2 day-1 creates an annual CO2 source (24.2 Mt CO2 year-1) and assuming a winter CH4 emission of 7 mg CH4 m-2 day-1 inflates the total net source to 151.8 Mt CO2e year-1.ConclusionsThis analysis improves upon previous basic, aspatial estimates and discusses the potential sources of the high uncertainty in spatially integrated fluxes, indicating a need for continued monitoring and refined maps of peatland distribution for national carbon and greenhouse gas flux estimation.

Dataset Information

Soil water content effects on net ecosystem CO2 exchange and actual evapotranspiration in a Mediterranean semiarid savanna of Central Chile.

Publications

Soil water content effects on net ecosystem CO<sub>2</sub> exchange and actual evapotranspiration in a Mediterranean semiarid savanna of Central Chile.

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