Estimation of snag carbon transfer rates by ecozone and lead species for forests in Canada

Hilger, Arlene; Shaw, Cindy; Metsaranta, Juha M.; Kurz, Werner A.

doi:10.1890/11-2277.1

Cited by 31 publications

(38 citation statements)

References 44 publications

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“…In this respect, the data situation in North America is much better. A good overview is given, for example, in Hilger et al (2012) and Dixon (2015). According to Hilger et al (2012), Engelmann spruce (Picea engelmannii Parry ex Engelm.)…”

Section: Discussionmentioning

confidence: 99%

Time since death and decay rate constants of Norway spruce and European larch deadwood in subalpine forests determined using dendrochronology and radiocarbon dating

et al. 2016

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Abstract. Due to the large size (e.g. sections of tree trunks) and highly heterogeneous spatial distribution of deadwood, the timescales involved in the coarse woody debris (CWD) decay of Picea abies (L.) Karst. and Larix decidua Mill. in Alpine forests are largely unknown. We investigated the CWD decay dynamics in an Alpine valley in Italy using the chronosequence approach and the five-decay class system that is based on a macromorphological assessment. For the decay classes 1-3, most of the dendrochronological samples were cross-dated to assess the time that had elapsed since tree death, but for decay classes 4 and 5 (poorly preserved tree rings) radiocarbon dating was used. In addition, density, cellulose, and lignin data were measured for the dated CWD. The decay rate constants for spruce and larch were estimated on the basis of the density loss using a single negative exponential model, a regression approach, and the stagebased matrix model. In the decay classes 1-3, the ages of the CWD were similar and varied between 1 and 54 years for spruce and 3 and 40 years for larch, with no significant differences between the classes; classes 1-3 are therefore not indicative of deadwood age. This seems to be due to a time lag between the death of a standing tree and its contact with the soil. We found distinct tree-species-specific differences in decay classes 4 and 5, with larch CWD reaching an average age of 210 years in class 5 and spruce only 77 years. The mean CWD rate constants were estimated to be in the range 0.018 to 0.022 y −1 for spruce and to about 0.012 y −1 for larch. Snapshot sampling (chronosequences) may overestimate the age and mean residence time of CWD. No sampling bias was, however, detectable using the stage-based matrix model. Cellulose and lignin time trends could be derived on the basis of the ages of the CWD. The half-lives for cellulose were 21 years for spruce and 50 years for larch. The half-life of lignin is considerably higher and may be more than 100 years in larch CWD. Consequently, the decay of Picea abies and Larix decidua is very low. Several uncertainties, however, remain: 14 C dating of CWD from decay classes 4 and 5 and having a pre-bomb age is often difficult (large age range due to methodological constraints) and fall rates of both European larch and Norway spruce are missing.

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Section: Discussionmentioning

confidence: 99%

Time since death and decay rate constants of Norway spruce and European larch deadwood in subalpine forests determined using dendrochronology and radiocarbon dating

et al. 2016

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“…A parameter stratification that accounts for effects related to tree species and soil taxonomy may be a potentially useful approach (Shaw et al 2008(Shaw et al , 2015. Such parameters exist for the transfer of standing dead trees to coarse woody debris (Hilger et al 2012) but are not yet implemented in a national-scale analysis. Decomposition rates simulated here are not sensitive to water stress, although several potential modifiers have been tested and a modified parameterization is available .…”

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%

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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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“…Decomposition often begins while the tree is still standing (Boddy, 2001;Harmon et al, 1986;Whittaker et al, 1979). Standing dead (SD) trees store a significant amount of carbon and provide essential habitat for wildlife, but also present potential safety and fire hazards (Hilger et al, 2012;Keen, 1955;Knapp, 2015;Raphael and White, 1984). Thus, SD trees play an important role in the ecology and management of forests.…”

Section: Introductionmentioning

confidence: 99%

Decay patterns and carbon density of standing dead trees in California mixed conifer forests

Cousins

Sanders

York

2015

Forest Ecology and Management

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Estimation of snag carbon transfer rates by ecozone and lead species for forests in Canada

Cited by 31 publications

References 44 publications

Time since death and decay rate constants of Norway spruce and European larch deadwood in subalpine forests determined using dendrochronology and radiocarbon dating

Time since death and decay rate constants of Norway spruce and European larch deadwood in subalpine forests determined using dendrochronology and radiocarbon dating

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

Decay patterns and carbon density of standing dead trees in California mixed conifer forests

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