Automated modeling of ecosystem CO 2 fluxes based on periodic closed chamber measurements: A standardized conceptual and practical approach

Hoffmann, Mathias; Jurisch, Nicole; Borraz, Elisa Albiac; Hagemann, Ulrike; Drösler, Matthias; Sommer, Michael; Augustin, Jürgen

doi:10.1016/j.agrformet.2014.09.005

Cited by 84 publications

(106 citation statements)

References 52 publications

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“…To account for measurement gaps and to obtain cumulative NEE values, empirical models were derived based on nighttime R eco and daytime NEE measurements following Hoffmann et al (2015). For R eco , temperature-dependent Arrhenius-type models were used and fitted for recorded air as well as soil temperatures in different depths (Lloyd and Taylor, 1994;Eq.…”

Section: Co 2 Flux Calculation and Gap Fillingmentioning

confidence: 99%

“…Because GPP was parameterized based on PAR records inside but modeled with PAR records outside the chamber, no PAR correction in terms of reduced light transmission was needed. Uncertainty of annual CO 2 exchange was quantified using a comprehensive error prediction algorithm described in detail by Hoffmann et al (2015).…”

Section: Co 2 Flux Calculation and Gap Fillingmentioning

confidence: 99%

“…An adaptation of the modular R program script, described in detail by Hoffmann et al (2015), was used for stepwise data processing. The atmospheric sign convention was used for the components of gaseous C exchange (ecosystem respiration (R eco ; sum of autotrophic and heterotrophic respiration), gross primary production (GPP) and NEE), whereas positive values for NECB indicate a gain and negative values a loss in SOC.…”

Section: Co 2 Flux Calculation and Gap Fillingmentioning

confidence: 99%

“…Out of the four R eco models (one model for air temperature; soil temperature at 2, 5 and 10 cm depth) obtained for nighttime R eco measurements of a certain period, the model with the lowest Akaike information criterion (AIC) was used. GPP fluxes were derived using a PAR-dependent, rectangular hyperbolic light-response function based on the Michaelis-Menten kinetic (Elsgaard et al, 2012;Hoffmann et al, 2015;Wang et al, 2013;Eq. 3).…”

Section: Co 2 Flux Calculation and Gap Fillingmentioning

confidence: 99%

“…Uncertainty prediction for NECB derived by the C budget method was performed according to Hoffmann et al (2015), following the law of error propagation. To test for differences in topsoil SOC (SOC Ap ) and Nt stocks in soil resampling performed after soil manipulation in 2010 and 2014, a paired t test was applied.…”

Section: Uncertainty Prediction and Statistical Analysismentioning

confidence: 99%

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Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

et al. 2017

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Abstract. Carbon (C) sequestration in soils plays a key role in the global C cycle. It is therefore crucial to adequately monitor dynamics in soil organic carbon ( SOC) stocks when aiming to reveal underlying processes and potential drivers. However, small-scale spatial (10-30 m) and temporal changes in SOC stocks, particularly pronounced in arable lands, are hard to assess. The main reasons for this are limitations of the well-established methods. On the one hand, repeated soil inventories, often used in long-term field trials, reveal spatial patterns and trends in SOC but require a longer observation period and a sufficient number of repetitions. On the other hand, eddy covariance measurements of C fluxes towards a complete C budget of the soil-plant-atmosphere system may help to obtain temporal SOC patterns but lack small-scale spatial resolution.To overcome these limitations, this study presents a reliable method to detect both short-term temporal dynamics as well as small-scale spatial differences of SOC using measurements of the net ecosystem carbon balance (NECB) as a proxy. To estimate the NECB, a combination of automatic chamber (AC) measurements of CO 2 exchange and empirically modeled aboveground biomass development (NPP shoot ) were used. To verify our method, results were compared with SOC observed by soil resampling.Soil resampling and AC measurements were performed from 2010 to 2014 at a colluvial depression located in the hummocky ground moraine landscape of northeastern Germany. The measurement site is characterized by a variable groundwater level (GWL) and pronounced small-scale spatial heterogeneity regarding SOC and nitrogen (Nt) stocks. Tendencies and magnitude of SOC values derived by AC measurements and repeated soil inventories corresponded well. The period of maximum plant growth was identified as being most important for the development of spatial differences in annual SOC. Hence, we were able to confirm that AC-based C budgets are able to reveal small-scale spatial differences and short-term temporal dynamics of SOC.

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Section: Co 2 Flux Calculation and Gap Fillingmentioning

confidence: 99%

Section: Co 2 Flux Calculation and Gap Fillingmentioning

confidence: 99%

Section: Co 2 Flux Calculation and Gap Fillingmentioning

confidence: 99%

Section: Co 2 Flux Calculation and Gap Fillingmentioning

confidence: 99%

Section: Uncertainty Prediction and Statistical Analysismentioning

confidence: 99%

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Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

et al. 2017

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Global Research Alliance N₂O chamber methodology guidelines: Guidelines for gap‐filling missing measurements

et al. 2020

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Nitrous oxide (N 2 O) is a potent greenhouse gas that is primarily emitted from agriculture. Sampling limitations have generally resulted in discontinuous N 2 O observations over the course of any given year. The status quo for interpolating between sampling points has been to use a simple linear interpolation. This can be problematic with N 2 O emissions, since they are highly variable and sampling bias around these peak emission periods can have dramatic impacts on cumulative emissions. Here, we outline five gap-filling practices: linear interpolation, generalized additive models (GAMs), autoregressive integrated moving average (ARIMA), random forest (RF), and neural networks (NNs) that have been used for gap-filling soil N 2 O emissions. To facilitate the use of improved gap-filling methods, we describe the five methods and then provide strengths and challenges or weaknesses of each method so that model selection can be improved. We then outline a protocol that details data organization and selection, splitting of data into training and testing datasets, building and testing models, and reporting results. Use of advanced gap-filling methods within a standardized protocol is likely to increase transparency, improve emission estimates, reduce uncertainty, and increase capacity to quantify the impact of mitigation practices.

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A simple method to assess the impact of sealing, headspace mixing and pressure vent on airtightness of manually closed chambers

Hoffmann

Pehle

Huth

et al. 2017

J. Plant Nutr. Soil Sci.

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Within a full‐factorial laboratory experiment, three different designs and two modifications of typical manual closed chamber setups were tested for sealing integrity. Tests were performed using a simple method, based on injections of single CO2 pulses. Chamber designs differed in V:A‐ratio and chamber‐collar sealing (water, rubber‐foam, rubber‐tube). All chambers were tested with and without pressure vent and fan. Our results indicate significant differences in sealing integrity due to chamber‐collar sealing strategy. Especially rubber sealing turned out to be characterized by a certain non‐reliability. The effect of vent and fan, however, was of minor importance. The proposed setup is an effective way to assess the airtightness of manual chambers for subsequent field studies.

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Automated modeling of ecosystem CO 2 fluxes based on periodic closed chamber measurements: A standardized conceptual and practical approach

Cited by 84 publications

References 52 publications

Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

Global Research Alliance N₂O chamber methodology guidelines: Guidelines for gap‐filling missing measurements

A simple method to assess the impact of sealing, headspace mixing and pressure vent on airtightness of manually closed chambers

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Automated modeling of ecosystem CO 2 fluxes based on periodic closed chamber measurements: A standardized conceptual and practical approach

Cited by 84 publications

References 52 publications

Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

Detecting small-scale spatial heterogeneity and temporal dynamics of soil organic carbon (SOC) stocks: a comparison between automatic chamber-derived C budgets and repeated soil inventories

Global Research Alliance N2O chamber methodology guidelines: Guidelines for gap‐filling missing measurements

A simple method to assess the impact of sealing, headspace mixing and pressure vent on airtightness of manually closed chambers

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Product

Resources

About

Global Research Alliance N₂O chamber methodology guidelines: Guidelines for gap‐filling missing measurements