Evaluation of simulated estimates of forest ecosystem carbon stocks using ground plot data from Canada's National Forest Inventory

Shaw, Cindy; Hilger, Arlene; Metsaranta, Juha M.; Kurz, Werner A.; Russo, Glenda; Eichel, F.; Stinson, G.; Smyth, Calvin M.; Filiatrault, Michelle

doi:10.1016/j.ecolmodel.2013.10.005

Cited by 48 publications

(45 citation statements)

References 48 publications

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“…We found that it would be necessary to assume positive correlations to obtain CIs approximating the results from the uncertainty simulations, whereas the parameters for the uncertainty analysis were drawn independently. The positive correlations inherent in the structure of models can cause the error in the size of a pool originating in an upstream pool to be transferred to a downstream pool regardless of the dependence between the parameters controlling input or output rates from those pools (Shaw et al 2014). Estimated uncertainty could also have been influenced by the spatial stratification of model parameters relative to how they vary in the real world.…”

Section: Dom C Modelling Parametersmentioning

confidence: 99%

“…Estimated uncertainty could also have been influenced by the spatial stratification of model parameters relative to how they vary in the real world. In the CBM-CFS3, default values for these parameters are typically constant across all spatial strata (Kurz et al 2009) but are known to be influenced by factors that vary across these strata, including tree species and soil type (Shaw et al 2008(Shaw et al , 2014(Shaw et al , 2015Hilger et al 2012). In addition, the degree of agreement between model-predicted C stocks and C stocks measured at ground plots of Canada's National Forest Inventory (NFI) varies greatly by species and modelling pool (Shaw et al 2014).…”

Section: Dom C Modelling Parametersmentioning

confidence: 99%

“…In addition, the degree of agreement between model-predicted C stocks and C stocks measured at ground plots of Canada's National Forest Inventory (NFI) varies greatly by species and modelling pool (Shaw et al 2014). Thus, our assumption of independence across spatial strata, even though the default parameter values and their uncertainties were the same across all strata, was likely justified because parameter errors are unlikely to be correlated across all of Canada due to variability related to tree species and soil type (Shaw et al 2008(Shaw et al , 2014(Shaw et al , 2015Hilger et al 2012).…”

Section: Dom C Modelling Parametersmentioning

confidence: 99%

“…When used, "bias" refers to differences between the central tendencies of the uncertainty simulations, relative to those derived under a set of default assumptions. Plot-scale model accuracy can be assessed by evaluation against independent ground data ( Shaw et al 2014). For landscapes, it can be examined indirectly through model intercomparison (Wang et al 2011;Raczka et al 2013).…”

Section: Conceptual Considerationsmentioning

confidence: 99%

“…In the CBM-CFS3, default values for these parameters are typically constant across all spatial strata (Kurz et al 2009) but are known to be influenced by factors that vary across these strata, including tree species and soil type (Shaw et al 2008(Shaw et al , 2014(Shaw et al , 2015Hilger et al 2012). In addition, the degree of agreement between model-predicted C stocks and C stocks measured at ground plots of Canada's National Forest Inventory (NFI) varies greatly by species and modelling pool (Shaw et al 2014). Thus, our assumption of independence across spatial strata, even though the default parameter values and their uncertainties were the same across all strata, was likely justified because parameter errors are unlikely to be correlated across all of Canada due to variability related to tree species and soil type (Shaw et al 2008(Shaw et al , 2014(Shaw et al , 2015Hilger et al 2012).…”

Section: Dom C Modelling Parametersmentioning

confidence: 99%

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Uncertainty of inventory-based estimates of the carbon dynamics of Canada’s managed forest (1990–2014)

et al. 2017

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Canada's National Forest Carbon Monitoring Accounting and Reporting System (NFCMARS) quantifies the carbon (C) dynamics and greenhouse gas (GHG) emissions and removals of Canada's managed forest to fulfill reporting obligations under international climate conventions. Countries are also requested to assess the uncertainty associated with these estimates, which we report here. We used Monte Carlo simulation to quantify uncertainty of carbon stock and flux estimates from the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3), the core ecosystem model of the NFCMARS. We evaluated the impacts of model algorithms, parameters, and the input data used to describe forest characteristics and disturbance rates. Under our assumptions, 95% confidence interval widths averaged 16.2 Pg C (+8.3 and -7.9 Pg C, or ±15%) for total ecosystem C stock and 32.2 Tg C·year −1 (+16.6 and -15.6 Tg C·year −1 ) for net biome production relative to an overall simulation median of -0.8 Tg C·year −1 from 1990 to 2014. The largest sources of uncertainty were related to factors determining biomass increment and the parameters used to model soil and dead organic matter C dynamics. Opportunities to reduce uncertainty and associated research challenges were identified.Key words: climate change, greenhouse gas inventory, forest carbon, boreal forest, mitigation, adaptation.Résumé : Le Système national de surveillance, de comptabilisation et de production de rapports concernant le carbone des forêts (SNSCPRCF) quantifie les changements dans les stocks de carbone (C) ainsi que les émissions et absorptions de gaz à effet de serre (GES) des forêts aménagées du Canada pour s'acquitter de l'obligation en matière de production de rapports dans le cadre des conventions internationales sur le climat. Les pays ont aussi l'obligation d'évaluer l'incertitude associée à ces estimations que nous rapportons dans cet article. Nous avons utilisé une simulation de Monte Carlo pour quantifier l'incertitude des stocks et des flux de carbone à partir du modèle du bilan du carbone du secteur forestier canadien (MBC-SFC3), le modèle d'écosystème à la base du SNSCPRCF. Nous avons évalué les impacts des algorithmes, des paramètres et des données d'entrée du modèle servant à décrire les caractéristiques et les taux de perturbation de la forêt. En fonction de nos hypothèses, l'étendue de l'intervalle de confiance à 95 % atteignait en moyenne 16,2 Pg C (+8,3 et -7,9 Pg C, ou ±15 %) pour le stock total de C de l'écosystème et 32,2 Tg C·an -1 (+16,6 et -15,6 Tg C·an -1 ) pour la production nette du biome relativement à une valeur médiane de -0,8 Tg C·an -1 pour les simulations de 1990 à 2014. Les plus importantes sources d'incertitude étaient reliées aux facteurs qui déterminent l'accroissement de la biomasse et aux paramètres utilisés pour modéliser la dynamique du C dans le sol et la matière organique morte. Les opportunités de réduire l'incertitude et les défis que cela représente pour la recherche sont identifiés. [Traduit par la Rédaction] Mots-clés : ch...

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Section: Dom C Modelling Parametersmentioning

confidence: 99%

Section: Dom C Modelling Parametersmentioning

confidence: 99%

Section: Dom C Modelling Parametersmentioning

confidence: 99%

Section: Conceptual Considerationsmentioning

confidence: 99%

Section: Dom C Modelling Parametersmentioning

confidence: 99%

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Uncertainty of inventory-based estimates of the carbon dynamics of Canada’s managed forest (1990–2014)

et al. 2017

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Afforestation of Former Asbestos Mines in Quebec, Canada

Bélanger,

Grimond,

Khlifa

et al. 2024

Biodiversity and Ecosystem Services on Post‐Industrial Land

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Stump harvesting for bioenergy: A review of climatic and environmental impacts in northern Europe and America

Persson

Egnell²

2018

WIREs Energy & Environment

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Stump harvesting is defined as an intensification of forest management in comparison with stem-only harvesting and removal of tops and branches. It increases soil mixing and the proportion of bare soil. In contrast to earlier hypotheses, stump harvesting was found to reduce emissions of carbon dioxide (CO 2 ), nitrous oxide, and methane in the short term. In the long term, heterotrophic soil CO 2 evolution is reduced. Both model and empirical studies indicate that stump removal can reduce the soil organic carbon (SOC) pool in the short term, but long-term experiments (32-39 years) could not verify any SOC decline. Life cycle assessment studies showed that stumps as fuel resulted in markedly lower emissions of CO 2 into the atmosphere, viewed over a whole forest rotation compared to heating by natural gas and coal. Stump removal does not seem to affect timber production in the next forest rotation and often reduces the infection rate of root rot. It increases the natural regeneration of birch and pine, it can increase nitrate leaching at N-rich sites, and it can increase the number of water-filled cavities where methylmercury is formed. Stump extraction decreases the amount of dwarf shrubs in young clearcuts, but after 1-2 decades, these species are generally recovered. Many species dependent on dead wood are adversely affected by intense stump harvest. Model studies suggest that the risk of species extinction is small when only 10% of the total clear-cut area in the forest landscape is stump harvested, but the risk of extinction rises at increasing extraction intensities.

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Evaluation of simulated estimates of forest ecosystem carbon stocks using ground plot data from Canada's National Forest Inventory

Cited by 48 publications

References 48 publications

Uncertainty of inventory-based estimates of the carbon dynamics of Canada’s managed forest (1990–2014)

Uncertainty of inventory-based estimates of the carbon dynamics of Canada’s managed forest (1990–2014)

Afforestation of Former Asbestos Mines in Quebec, Canada

Stump harvesting for bioenergy: A review of climatic and environmental impacts in northern Europe and America

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