1,982 research outputs found

    Statistical uncertainty of eddy flux–based estimates of gross ecosystem carbon exchange at Howland Forest, Maine

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    We present an uncertainty analysis of gross ecosystem carbon exchange (GEE) estimates derived from 7 years of continuous eddy covariance measurements of forest-atmosphere CO2fluxes at Howland Forest, Maine, USA. These data, which have high temporal resolution, can be used to validate process modeling analyses, remote sensing assessments, and field surveys. However, separation of tower-based net ecosystem exchange (NEE) into its components (respiration losses and photosynthetic uptake) requires at least one application of a model, which is usually a regression model fitted to nighttime data and extrapolated for all daytime intervals. In addition, the existence of a significant amount of missing data in eddy flux time series requires a model for daytime NEE as well. Statistical approaches for analytically specifying prediction intervals associated with a regression require, among other things, constant variance of the data, normally distributed residuals, and linearizable regression models. Because the NEE data do not conform to these criteria, we used a Monte Carlo approach (bootstrapping) to quantify the statistical uncertainty of GEE estimates and present this uncertainty in the form of 90% prediction limits. We explore two examples of regression models for modeling respiration and daytime NEE: (1) a simple, physiologically based model from the literature and (2) a nonlinear regression model based on an artificial neural network. We find that uncertainty at the half-hourly timescale is generally on the order of the observations themselves (i.e., ∌100%) but is much less at annual timescales (∌10%). On the other hand, this small absolute uncertainty is commensurate with the interannual variability in estimated GEE. The largest uncertainty is associated with choice of model type, which raises basic questions about the relative roles of models and data

    Upscaling key ecosystem functions across the conterminous United States by a water-centric ecosystem model

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    We developed a water-centric monthly scale simulation model (WaSSI-C) by integrating empirical water and carbon flux measurements from the FLUXNET network and an existing water supply and demand accounting model (WaSSI). The WaSSI-C model was evaluated with basin-scale evapotranspiration (ET), gross ecosystem productivity (GEP), and net ecosystem exchange (NEE) estimates by multiple independent methods across 2103 eight-digit Hydrologic Unit Code watersheds in the conterminous United States from 2001 to 2006. Our results indicate that WaSSI-C captured the spatial and temporal variability and the effects of large droughts on key ecosystem fluxes. Our modeled mean (±standard deviation in space) ET (556 ± 228 mm yr−1) compared well to Moderate Resolution Imaging Spectroradiometer (MODIS) based (527 ± 251 mm yr−1) and watershed water balance based ET (571 ± 242 mm yr−1). Our mean annual GEP estimates (1362 ± 688 g C m−2 yr−1) compared well (R2 = 0.83) to estimates (1194 ± 649 g C m−2 yr−1) by eddy flux-based EC-MOD model, but both methods led significantly higher (25–30%) values than the standard MODIS product (904 ± 467 g C m−2 yr−1). Among the 18 water resource regions, the southeast ranked the highest in terms of its water yield and carbon sequestration capacity. When all ecosystems were considered, the mean NEE (−353 ± 298 g C m−2 yr−1) predicted by this study was 60% higher than EC-MOD\u27s estimate (−220 ± 225 g C m−2 yr−1) in absolute magnitude, suggesting overall high uncertainty in quantifying NEE at a large scale. Our water-centric model offers a new tool for examining the trade-offs between regional water and carbon resources under a changing environment

    Benthic oxygen exchange in a live coralline algal bed and an adjacent sandy habitat: an eddy covariance study

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    Coralline algal (maerl) beds are widespread, slow-growing, structurally complex perennial habitats that support high biodiversity, yet are significantly understudied compared to seagrass beds or kelp forests. We present the first eddy covariance (EC) study on a live maerl bed, assessing the community benthic gross primary productivity (GPP), respiration (R), and net ecosystem metabolism (NEM) derived from diel EC time series collected during 5 seasonal measurement campaigns in temperate Loch Sween, Scotland. Measurements were also carried out at an adjacent (~20 m distant) permeable sandy habitat. The O2 exchange rate was highly dynamic, driven by light availability and the ambient tidally-driven flow velocity. Linear relationships between the EC O2 fluxes and available light indicate that the benthic phototrophic communities were lightlimited. Compensation irradiance (Ec) varied seasonally and was typically ~1.8-fold lower at the maerl bed compared to the sand. Substantial GPP was evident at both sites; however, the maerl bed and the sand habitat were net heterotrophic during each sampling campaign. Additional inputs of ~4 and ~7 mol m-2 yr-1 of carbon at the maerl bed and sand site, respectively, were required to sustain the benthic O2 demand. Thus, the 2 benthic habitats efficiently entrap organic carbon and are sinks of organic material in the coastal zone. Parallel deployment of 0.1 m2 benthic chambers during nighttime revealed O2 uptake rates that varied by up to ~8-fold between replicate chambers (from -0.4 to -3.0 mmol O2 m-2 h-1; n = 4). However, despite extensive O2 flux variability on meter horizontal scales, mean rates of O2 uptake as resolved in parallel by chambers and EC were typically within 20% of one another

    Comparing ecosystem and soil respiration : Review and key challenges of tower-based and soil measurements

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    The net ecosystem exchange (NEE) is the difference between ecosystem CO2 assimilation and CO2 losses to the atmosphere. Ecosystem respiration (R-eco), the efflux of CO2 from the ecosystem to the atmosphere, includes the soil-to-atmosphere carbon flux (i.e., soil respiration; R-soil) and aboveground plant respiration. Therefore, R-soil is a fraction of R-eco and theoretically has to be smaller than R-eco at daily, seasonal, and annual scales. However, several studies estimating R-eco with the eddy covariance technique and measuring R-soll within the footprint of the tower have reported higher R-soil than R-eco, at different time scales. Here, we compare four different and contrasting ecosystems (from forest to grasslands, and from boreal to semiarid) to test if measurements of R-eco are consistently higher than R-soil. In general, both fluxes showed similar temporal patterns, but R-eco, was not consistently higher than R-soil from daily to annual scales across sites. We identified several issues that apply for measuring NEE and measuring/upscaling R-soil that could result in an underestimation of R-eco and/or an overestimation of R-soil. These issues are discussed based on (a) nighttime measurements of NEE, (b) R-soil measurements, and (c) the interpretation of the functional relationships of these fluxes with temperature (i.e., Q(10)). We highlight that there is still a need for better integration of R-soil with eddy covariance measurements to address challenges related to the spatial and temporal variability of R-eco, and R-soil.Peer reviewe

    Carbon and water fluxes in a boreal forest ecosystem

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    Modeling seasonal to annual carbon balance of Mer Bleue Bog, Ontario, Canada

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    Northern peatlands contain enormous quantities of organic carbon within a few meters of the atmosphere and play a significant role in the planetary carbon balance. We have developed a new, process-oriented model of the contemporary carbon balance of northern peatlands, the Peatland Carbon Simulator (PCARS). Components of PCARS are (1) vascular and nonvascular plant photosynthesis and respiration, net aboveground and belowground production, and litterfall; (2) aerobic and anaerobic decomposition of peat; (3) production, oxidation, and emission of methane; and (4) dissolved organic carbon loss with drainage water. PCARS has an hourly time step and requires air and soil temperatures, incoming radiation, water table depth, and horizontal drainage as drivers. Simulations predict a complete peatland C balance for one season to several years. A 3-year simulation was conducted for Mer Bleue Bog, near Ottawa, Ontario, and results were compared with multiyear eddy covariance tower CO2 flux and ancillary measurements from the site. Seasonal patterns and the general magnitude of net ecosystem exchange of CO2 were similar for PCARS and the tower data, though PCARS was generally biased toward net ecosystem respiration (i.e., carbon loss). Gross photosynthesis rates (calculated directly in PCARS, empirically inferred from tower data) were in good accord, so the discrepancy between model and measurement was likely related to autotrophic and/or heterotrophic respiration. Modeled and measured methane emission rates were quite low. PCARS has been designed to link with the Canadian Land Surface Scheme (CLASS) land surface model and a global climate model (GCM) to examine climate-peatland carbon feedbacks at regional scales in future analyses

    PyörrekovarianssimenetelmÀllÀ mitattujen mÀntymetsÀn ja ilmakehÀn vÀlisen hiilidioksidi- sekÀ energiavoiden epÀvarmuustekijÀt

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    This thesis is a study of the uncertainties related to the eddy covariance measurement technique on a forest ecosystem that is located in HyytiĂ€lĂ€, Southern Finland. The aim of this study is to analyze carbon dioxide and energy fluxes measured at two vertically displaced eddy covariance set-ups. In particular, to determine if the observed deviations between the set-ups could be linked with micrometeorological or biological variations or if they are resulted just by the stochastic nature of turbulence. The magnitude of uncertainties linked to eddy covariance technique are still under discussion and this thesis attempts to shed a light on these questions. The analysis is done to half hourly mean flux and meteorological data that was measured at the HyytiĂ€lĂ€ SMEAR II –site in 2015 at the heights of 23.3 m and 33.0 m. Monthly, diurnal and cumulative variations of the fluxes are analyzed. A footprint model is used to analyze the flux correlation with the underlying vegetation. The flux dependence on atmospheric stability is also determined. The analysis shows that the annual cumulative difference of net ecosystem exchange (CO_2 exchange) between the two measurement heights is estimated to be 49 gC m^(-2) year^(-1) (17 % difference). The annual cumulative evapotranspiration difference is estimated to be 105 mm (29 % difference). There are no significant differences between the sensible heat fluxes. The difference between the measurement heights does not seem to influence significantly the flux estimations made with the eddy covariance method. However, the measurement results for latent heat flux acquired from the 33.0 m set-up are continuously smaller than those of the 23.3 m set-up.TĂ€ssĂ€ Pro gradu -tutkielmassa tutkitaan pyörrekovarianssimenetelmĂ€llĂ€ mitattujen suomalaisen mĂ€ntymetsĂ€n ja ilmakehĂ€n vĂ€lisen hiilidioksidin, vesihöyryn sekĂ€ havaittavan lĂ€mmön voita, ja pyritÀÀn selvittĂ€mÀÀn mittauksiin liittyvien virhelĂ€hteiden suuruudet. Voihin liittyvien virheiden suuruutta analysoidaan vertailemalla saman mittaustornin kahdelta eri korkeudelta saatuja mittaustuloksia. Analyysissa pyritÀÀn identifioimaan mikĂ€li tuloksissa havaittavat eroavaisuudet aiheutuvat mikrometeorologisista ja biologisista muuttujista vai turbulenttisten virtausten kaoottisuudesta johtuvista mittausvirheistĂ€. PyörrekovarianssimenetelmĂ€n virhelĂ€hteet ovat osana aktiivista tieteellistĂ€ keskustelua, jossa pyritÀÀn parantamaan meteorologisia mittausmenetelmiĂ€. Tutkimus tehtiin kĂ€yttĂ€mĂ€llĂ€ meteorologista aineistoa sekĂ€ vuoaineistoa, joka on kerĂ€tty HyytiĂ€lĂ€n SMEAR II -metsĂ€ntutkimusasemalla vuonna 2015. Mittaukset tehtiin 23,3 m sekĂ€ 33,0 m korkeudella maanpinnasta. Vuoaineistoa tarkastellaan aina pĂ€ivittĂ€isestĂ€ vaihtelusta koko vuoden kestĂ€vÀÀn kumulatiiviseen analyysiin. Aineistolle tehdÀÀn myös sekĂ€ meteorologisiin muuttujiin ettĂ€ kasvillisuusjakaumaan perustuva tarkastelu. Tutkimuksessa havaittiin mittauskorkeuksien vĂ€lisen kumulatiivisten hiilidioksidivoiden eron suuruudeksi 49 gC m^(-2) vuodessa (17 % erotus). Kokonaishaihdunnan kumulatiivisen eron arvioidaan olevan 105 mm vuodessa (29 % erotus). Havaittavan lĂ€mmön voissa ei ilmennyt merkittĂ€vÀÀ eroa mittauskorkeuksien vĂ€lillĂ€. Hiilidioksidivuossa tai havaittavan lĂ€mmön vuossa ei havaita merkittĂ€vÀÀ eroa, joka aiheutuisi kĂ€ytettĂ€vistĂ€ mittauskorkeuksista. Kuitenkin latentin lĂ€mmön vuossa ero on havaittavissa, sillĂ€ 33,0 m mittaustulokset ovat jatkuvasti pienempiĂ€ kuin 23,3 m vastaavat tulokset
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