Direct measurements of carbon exchange at forest disturbance sites: a review of results with the eddy covariance method

Rebane, Sille; Jõgiste, Kalev; Põldveer, Eneli; Stanturf, John A.; Metslaid, Marek

doi:10.1080/02827581.2019.1659849

Cited by 21 publications

(15 citation statements)

References 106 publications

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“…Eddy covariance monitors carbon dynamics following high severity fires that destroy forest landscapes, in some cases approximating 100% deforestation. For example, [66] reports a switch to positive emissions following deforestation and clear cut with gradual annual increases in net forest carbon sequestration towards a switch back to negative emissions, a pattern reported by similar studies [65]- [69], a scenario precluded from detection and quantification employing CFCPs.…”

Section: Discussionmentioning

confidence: 60%

“…Note that NEE is equivalent but opposite in sign to NEP (NEP = ̶ NEE) assuming that inorganic C fluxes balance or are negligible [62]. In the case of REDD+ projects, eddy covariance is integrated with monitoring, reporting and verification (MRV) protocols, establishing methodological comparability across diverse REDD+ project types and baselines [45]- [47], [63]- [65], supporting the inclusion of REDD+ projects in this study, representing ~13% of projects analyzed and consistent with [15]. High frequency measurements for NEE detects decreasing or increasing project carbon emission scenarios averaged across hourly to annual intervals [25] that are not detectable by CFCP infrequent forest mensuration (e.g., 6 to 12 year intervals) [2].…”

Section: Methods For the Determination Of Forest Carbon Sequestrationmentioning

confidence: 99%

“…Forest carbon changes and offsets are based on the net balance of CO2 uptake and release between the forest and soils and the atmosphere over the project area. Project level NEE captures differing rates of uptake and release of CO2 relative to forest cover, seasonal changes, management, and disturbances including high-severity forest fires (e.g., ~100% forest destruction) across differing project scales covered by one or more eddy covariance systems [65]- [69]. NEE data are complemented by forest inventory data resulting from plot level [70] or remote sensing methods [7].…”

Section: Methods For the Determination Of Forest Carbon Sequestrationmentioning

confidence: 99%

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Commercial Forest Carbon Protocol Over-credit Bias Delimited by Zero-threshold Carbon Accounting

Marino¹,

Bautista²

2021

Preprint

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Despite the use of commercial forest carbon protocols (CFCPs) for more than two decades, claiming ~566 MMtCO2e and a market value of ~USD $15.7 billion, comparative analysis of CFCP methodology and offset results is limited. In this study, five widely used biometric-based CFCPs are characterized, and common characteristics and differences are identified. CFCP claims of net forest carbon sequestration are compared with results of directly measured CO2 by eddy covariance, a meteorological method integrating gross vertical fluxes of forest and soil carbon, and the only alternative non-biometric source of net forest carbon sequestration data available. We show here that CFCPs share a structural feature delimiting forest carbon values by zero-threshold carbon accounting (gC m-2 ≤ 0), a pattern opposite to natural emissions of forest CO2 exchange based on direct measurement and a fundamental biological constraint on net forest carbon storage (i.e., soil efflux, ecosystem respiration). Exclusion of forest CO2 sources to the atmosphere precludes net carbon accounting, resulting in unavoidable over-crediting of CFCP project offsets. CFCP carbon results are significantly different from global forest CO2 net ecosystem exchange population results (FluxNet2015 gC m-2) at the 95% to 99.99% confidence levels, inferring an annual median error of ~247% (gC m-2), consistent with over-crediting. Direct CO2 measurement provides an urgently needed alternative method for commercial forest carbon products that has the potential to harmonize global markets and catalyze the role of forests in managing climate change through nature-based solutions.

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Section: Discussionmentioning

confidence: 60%

Section: Methods For the Determination Of Forest Carbon Sequestrationmentioning

confidence: 99%

Section: Methods For the Determination Of Forest Carbon Sequestrationmentioning

confidence: 99%

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Commercial Forest Carbon Protocol Over-credit Bias Delimited by Zero-threshold Carbon Accounting

Marino¹,

Bautista²

2021

Preprint

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“…In this sense, applied studies assessing the C sink ability of vegetated areas in other study environments (e.g. forestry, urban green systems) on the basis of annual plant growth or gas interchange [21,[25][26][27][28][29] become relevant for this purpose.…”

Section: Introductionmentioning

confidence: 99%

Natural Carbon Sinks Linked to Pastoral Activity in S Spain: A Territorial Evaluation Methodology for Mediterranean Goat Grazing Systems

et al. 2021

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Exploring and developing new tools for the accounting and management of natural C sinks will provide a closer, more accurate option to remark the importance of such sinks in relation to livestock production, helping to support the persistence of some seriously endangered traditional, environmentally sustainable livestock farming. Following both precision and usability criteria, two main C sink databases covering the Andalusian region (S Spain) were developed from the Spanish Land Parcel Identification System (SIGPAC, coarse resolution) and the Spanish Information System on Land Cover (SIOSE, finer resolution) land use classes. Particular C sink factors based on growth rates for individual plant species were associated with detailed vegetation maps and, further, were linked to Land Use and Covers cartography across the region. In addition, eight ruminant farms were exhaustively studied in situ and used as a control. Results were compared with the obtained through the application of the developed C sink databases, and with the commonly used Petersen methodology. The sink capacity of vegetation associated with farms varied from 0.25 to 1.37 t CO2 ha−1 year−1, depending on the plant species composition and abundance. All the approaches showed significant differences from the control. C sink values were significantly higher when applying SIGPAC-based C sink database to farms, while values from the SIOSE and Petersen methodology approaches provided more moderate values, closer to the control. SIGPAC and Petersen approaches showed higher usability but presented lower precision due to a poor definition of plant cover. SIOSE-based C sink database provided suitable values able to be adapted to reality and used by farmers. In this regard, further research efforts to improve the adjustment of results and ease of use are required. The present approach means a methodological advance in the estimation of the C sink capacity associated with pastoral livestock farms, able to be incorporated into the CF calculation in contrasted areas worldwide, in the frame of the ‘eco-schemes’ being recently under development through the EU CAP.

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“…The magnitude, timing and duration of changes in the C cycle following disturbance vary among forests (Amiro et al 2010, Luo and Weng 2011, Coomes et al 2012, Hicke et al 2012, Gough et al 2013, Peters et al 2013, Vanderwel et al 2013, Flower and Gonzalez-Meler 2015Gu et al 2019). These responses may differ as a function of disturbance severity, type, and frequency along with the physical, structural, and biological properties of the affected ecosystem (Amiro et al, 2010;Williams et al, 2012;Scheuermann et al 2018;Rebane et al 2019;Fahey et al 2020;Atkins et al 2020a). Understanding which forest ecosystems are most vulnerable to disturbance and, conversely, what characteristics of an ecosystem confer C cycling stability, remains an important frontier crucial to forecasting changes in the terrestrial C sink in the face of rising global disturbance frequencies (Frelich and Reich, 1999;White and Jentsch, 2001;Johnstone et al 2010;.…”

Section: Introductionmentioning

confidence: 99%

The <i>fortedata</i> R package: open-science datasets from a manipulative experiment testing forest resilience

Atkins¹,

Agee²,

Barry³

et al. 2020

Preprint

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Abstract. The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. Package data consists of measurements of carbon pools and fluxes and ancillary measurements to help users analyse and interpret carbon cycling over time. Currently the package includes data and metadata from the first two years of FoRTE, and serves as a central, updatable resource for the FoRTE project team and is intended as a resource for external users over the course of the experiment and in perpetuity. Further, it supports all associated FoRTE publications, analyses, and modeling efforts. This increases efficiency, consistency, compatibility, and productivity, while minimizing duplicated effort and error propagation that can arise as a function of a large, distributed and collaborative effort. More broadly, fortedata represents an innovative, collaborative way of approaching science that unites and expedites the delivery of complementary datasets in near real time to the broader scientific community, increasing transparency and reproducibility of taxpayer-funded science. fortedata is available via GitHub: https://github.com/FoRTExperiment/fortedata and detailed documentation on the access, used, and applications of fortedata are available at: https://fortexperiment.github.io/fortedata/. The first public release, version 1.0.1 is also archived at: https://doi.org/10.5281/zenodo.3936146 (Atkins et al., 2020b). All level one data products are also available outside of the package as .csv files: https://doi.org/10.6084/m9.figshare.12292490.v3 (Atkins et al. 2020c).

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Direct measurements of carbon exchange at forest disturbance sites: a review of results with the eddy covariance method

Cited by 21 publications

References 106 publications

Commercial Forest Carbon Protocol Over-credit Bias Delimited by Zero-threshold Carbon Accounting

Commercial Forest Carbon Protocol Over-credit Bias Delimited by Zero-threshold Carbon Accounting

Natural Carbon Sinks Linked to Pastoral Activity in S Spain: A Territorial Evaluation Methodology for Mediterranean Goat Grazing Systems

The <i>fortedata</i> R package: open-science datasets from a manipulative experiment testing forest resilience

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Direct measurements of carbon exchange at forest disturbance sites: a review of results with the eddy covariance method

Cited by 21 publications

References 106 publications

Commercial Forest Carbon Protocol Over-credit Bias Delimited by Zero-threshold Carbon Accounting

Commercial Forest Carbon Protocol Over-credit Bias Delimited by Zero-threshold Carbon Accounting

Natural Carbon Sinks Linked to Pastoral Activity in S Spain: A Territorial Evaluation Methodology for Mediterranean Goat Grazing Systems

The &lt;i&gt;fortedata&lt;/i&gt; R package: open-science datasets from a manipulative experiment testing forest resilience

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Product

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About

The <i>fortedata</i> R package: open-science datasets from a manipulative experiment testing forest resilience