Search

Forests play a crucial role in South Korea's carbon neutrality goal and require sustainable management strategies to overcome age-class imbalances. The Generic Carbon Budget Model (GCBM) offers a spatially explicit approach to simulate carbon dynamics at a regional scale. In this study, we utilized the GCBM to analyze the carbon budget of forests in South Korea and produce spatiotemporal maps for distribution of the forest biomass. The growth parameters of five representative tree species (Pinus densiflora Siebold & Zucc., Larix kaempferi Carr., Pinus koraiensis Siebold & Zucc., Quercus mongolica Fisch. ex Ledeb., Quercus variabilis Blume), which are the main species in South Korea, were used to operate the model. In addition, spatial data for harvest and thinning management activities were used to analyze the effects of anthropogenic activities. In 2020, the aboveground and belowground biomass were 112.98 and 22.84 tC ha−1, and the net primary productivity was 8.30 tC ha−1 year−1. These results were verified using comparison with statistics, a literature review, and MODIS NPP. In particular, broadleaf is higher than conifer forest in net primary production. The Canadian GCBM with Korean forest inventory data and yield curves successfully estimated the aboveground and belowground biomass of forests in South Korea. Our study demonstrates that these estimates can be mapped in detail, thereby supporting decision-makers and stakeholders in analyzing the carbon budget of the forests in South Korea and developing novel schemes that can serve regional and national aims related to forest management, wood utilization, and ecological preservation. Further studies are needed to improve the initialization of dead organic matter pools, given the large-scale afforestation efforts in recent decades that have established South Korea's forests on predominantly non-forest sites. [ABSTRACT FROM AUTHOR]

Managing forests and forest products has substantial potential to help mitigate climate change but the cost has not been extensively examined in Canada. We estimated the cost of seven forest-related mitigation strategies in Canada's 230 million hectares of managed forest, divided into 32 spatial units. For each strategy and spatial unit, we determined forest sector mitigation cost per tonne (t) using estimated impacts on forest sector greenhouse gas emissions and removals and net revenue. National cost curves showed that mitigation averaged 11.0 Mt C[O.sub.2]e x [year.sup.-1] in 2015-2050 at costs below $50 x t C[O.sub.2]e x [year.sup.-1] for a strategy of increased recovery of harvested biomass, increased salvage, extraction of harvest residues for bioenergy, and increased production of longer lived products. We also examined national portfolios in which the strategy selected for each spatial unit (from among the seven examined) was chosen to maximize mitigation or minimize costs. At low levels of mitigation, portfolios chosen to minimize costs were much cheaper than those that maximized mitigation, but overall, they yielded less than half the total mitigation of the latter portfolios. Choosing strategies to maximize mitigation in 2015-2050 yielded an average of 16.5 Mt-year-1 at costs below $50 x t C[O.sub.2]e x [year.sup.-1]. Our analysis suggests that forest-related strategies may be cost-effective choices to help achieve long-term emission reductions in Canada. Key words: Canada, cost, climate change mitigation, forest management, harvested wood products. L'amenagement des forets et les produits forestiers ont un potentiel considerable pour attenuer les changements climatiques, mais au Canada peu d'etudes ont examine les couts associes a ces mesures. Nous avons estime le cout de sept strategies d'attenuation en milieu forestier dans les 230 millions d'hectares de forets amenagees du Canada divisees en 32 unites spatiales. Pour chaque strategie et chaque unite spatiale, nous avons determine le cout par tonne (t) de l'attenuation due au secteur forestier en ayant recours a l'estimation des impacts sur l'emission et l'absorption de gaz a effet de serre et sur le revenu net associes au secteur forestier. Selon les courbes de cout nationales, le niveau d'attenuation atteindrait en moyenne 11,0 Mt eq. C[O.sub.2] x [an.sup.-1] de 2015 a 2050 a un cout de moins de 50 $-t eq. [C[O.sub.2].sup.-1] pour une strategie qui inclut la recuperation accrue de la biomasse recoltee, une plus grande recuperation, la recolte des residus forestiers pour la bioenergie et une augmentation de la production de produits qui ont une plus longue duree de vie. Nous avons aussi evalue les portefeuilles nationaux dans lesquels la strategie selectionnee pour chaque unite spatiale (parmi les sept strategies etudiees) a ete choisie pour maximiser l'attenuation et minimiser les couts. Pour des niveaux d'attenuation faibles, les portefeuilles qui ont ete retenus pour minimiser les couts etaient beaucoup moins dispendieux que ceux qui maximisaient l'attenuation, mais globalement ils ont produit moins de la moitie de l'attenuation totale. Choisir des strategies qui maximisent l'attenuation de 2015 a 2050 entrainerait une reduction moyenne des emissions de 16,5 Mt x [an.sup.-1] a un cout de moins de 50 $-t eq. [C[O.sub.2].sup.-1]. Notre analyse indique que les strategies en lien avec le secteur forestier peuvent etre des choix rentables pour atteindre les objectifs a long terme de reduction des emissions au Canada. [Traduit par la Redaction] Mots-cles: Canada, cout, attenuation des changements climatiques, amenagement forestier, recolte de produits forestiers., 1. Introduction Management of forests and forest products has substantial global potential to mitigate climate change by reducing greenhouse gas (GHG) emissions or increasing carbon sequestration (Barker et al. 2007; [...]

In the context of the Kyoto Protocol, the mandatory accounting of Afforestation and Reforestation (AR) activities requires estimating the forest carbon (C) stock changes for any direct human-induced expansion of forest since 1990. We used the Carbon Budget Model (CBM) to estimate C stock changes and emissions from fires on AR lands at country level. Italy was chosen because it has one of the highest annual rates of AR in Europe and the same model was recently applied to Italy’s forest management area. We considered the time period 1990-2020 with two case studies reflecting different average annual rates of AR: 78 kha yr-1, based on the 2013 Italian National Inventory Report (NIR, official estimates), and 28 kha yr-1, based on the Italian Land Use Inventory System (IUTI estimates). We compared these two different AR rates with eight regional forest inventories and three independent local studies. The average annual C stock change estimated by CBM, excluding harvest or natural disturbances, was equal to 1738 Gg C yr-1 (official estimates) and 630 Gg C yr-1 (IUTI estimates). Results for the official estimates are consistent with the estimates reported by Italy to the KP for the period 2008-2010; for 2011 our estimates are about 20% higher than the country’s data, probably due to different assumptions on the fire disturbances, the AR rate and the dead wood and litter pools. Furthermore, our analysis suggests that: (i) the impact on the AR sink of different assumptions of species composition is small; (ii) the amount of harvest provided by AR has been negligible for the past (< 3%) and is expected to be small in the near future (up to 8% in 2020); (iii) forest fires up to 2011 had a small impact on the AR sink (on average, < 100 Gg C yr-1). Finally the comparison of the historical AR rates reported by NIR and IUTI with other independent sources gives mixed results: the regional inventories support the AR rates reported by the NIR, while some local studies suggest AR rates somehow intermediate between NIR and IUTI. In conclusion, this study suggests that the CBM can be applied at country level to estimate the C stock changes resulting from AR, including the effect of harvest and fires, though only a comparison with results based on direct field measurements could verify the model’s capability to estimate the real C stock change.

As the focus of climate policy shifts from pledges to implementation, there is a growing need to track progress on climate change mitigation at the country level, particularly for the land-use sector. Despite new tools and models providing unprecedented monitoring opportunities, striking differences remain in estimations of anthropogenic land-use CO 2 fluxes between, on the one hand, the national greenhouse gas inventories (NGHGIs) used to assess compliance with national climate targets under the Paris Agreement and, on the other hand, the Global Carbon Budget and Intergovernmental Panel on Climate Change (IPCC) assessment reports, both based on global bookkeeping models (BMs). Recent studies have shown that these differences are mainly due to inconsistent definitions of anthropogenic CO 2 fluxes in managed forests. Countries assume larger areas of forest to be managed than BMs do, due to a broader definition of managed land in NGHGIs. Additionally, the fraction of the land sink caused by indirect effects of human-induced environmental change (e.g. fertilisation effect on vegetation growth due to increased atmospheric CO 2 concentration) on managed lands is treated as non-anthropogenic by BMs but as anthropogenic in most NGHGIs. We implement an approach that adds the CO 2 sink caused by environmental change in countries' managed forests (estimated by 16 dynamic global vegetation models, DGVMs) to the land-use fluxes from three BMs. This sum is conceptually more comparable to NGHGIs and is thus expected to be quantitatively more similar. Our analysis uses updated and more comprehensive data from NGHGIs than previous studies and provides model results at a greater level of disaggregation in terms of regions, countries and land categories (i.e. forest land, deforestation, organic soils, other land uses). Our results confirm a large difference (6.7 GtCO 2 yr -1) in global land-use CO 2 fluxes between the ensemble mean of the BMs, which estimate a source of 4.8 GtCO 2 yr -1 for the period 2000–2020, and NGHGIs, which estimate a sink of -1.9 GtCO 2 yr -1 in the same period. Most of the gap is found on forest land (3.5 GtCO 2 yr -1), with differences also for deforestation (2.4 GtCO 2 yr -1), for fluxes from other land uses (1.0 GtCO 2 yr -1) and to a lesser extent for fluxes from organic soils (0.2 GtCO 2 yr -1). By adding the DGVM ensemble mean sink arising from environmental change in managed forests (-6.4 GtCO 2 yr -1) to BM estimates, the gap between BMs and NGHGIs becomes substantially smaller both globally (residual gap: 0.3 GtCO 2 yr -1) and in most regions and countries. However, some discrepancies remain and deserve further investigation. For example, the BMs generally provide higher emissions from deforestation than NGHGIs and, when adjusted with the sink in managed forests estimated by DGVMs, yield a sink that is often greater than NGHGIs. In summary, this study provides a blueprint for harmonising the estimations of anthropogenic land-use fluxes, allowing for detailed comparisons between global models and national inventories at global, regional and country levels. This is crucial to increase confidence in land-use emissions estimates, support investments in land-based mitigation strategies and assess the countries' collective progress under the Global Stocktake of the Paris Agreement. Data from this study are openly available online via the Zenodo portal (Grassi et al., 2023) at 10.5281/zenodo.7650360. [ABSTRACT FROM AUTHOR]

Mosses play a key role in the carbon (C) cycle of upland black spruce (Picea mariana (Mill.) BSP) forests; however, national reporting models such as the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) do not include mosses. This study examined whether widely available plot-level merchantable tree volume could predict, for black spruce ecosystems in Canada's boreal forest, the relative proportions of sphagnum and feather moss ground cover and moss net primary productivity (NPP). A field study found that merchantable tree volume was significantly related to tree canopy openness ([R.sup.2] = 0.61, P < 0.001), which could then be used to model the relative ground cover of feather moss ([R.sup.2] = 0.5, P < 0.001) and sphagnum ([R.sup.2] = 0.45, P < 0.001) and NPP of feather moss ([R.sup.2] = 0.41, P < 0.001) and sphagnum ([R.sup.2] = 0.28, P < 0.001). The resulting MOSS-C submodel increased the accuracy of the CBM-CFS3's prediction of organic-horizon C five-fold and could explain large-scale variation in sites dominated by sphagnum with large organic layer C pools but not fine-scale variation in dryer sites. To improve MOSS-C accuracy, future studies should focus on varying decomposition and fire regime parameters based on regional climate or plot-level vegetation parameters. Key words: moss carbon, carbon model, black spruce, sphagnum, feather moss. Les mousses jouent un role cle dans le cycle du carbone (C) des forets d'epinette noire (Picea mariana (Mill.) BSP). Toutefois, les modeles a l'echelle nationale, comme le modele du bilan du carbone du Secteur forestier canadien (MBC-SFC3), n'incluent pas les mousses. Cette etude vise a determiner si les donnees largement disponibles de volume marchand des arbres a l'echelle de la placette peuvent predire les proportions relatives du couvert de sphaignes et de mousses hypnacees ainsi que la productivite primaire nette (PPN) des mousses dans les ecosystemes d'epinette noire de la foret boreale canadienne. Une etude de terrain a montre que le volume marchand des arbres etait significativement relie a l'ouverture du couvert dominant ([R.sup.2] = 0,61, P Mots-cles: carbone des mousses, modele de carbone, epinette noire, sphaignes, mousses hypnacees., Introduction The boreal biome contains approximately 40% of the global terrestrial pool of carbon (C) (McGuire et al. 2001). In Canada, black spruce (Picea mariana (Mill.) BSP) forests are very [...]

Deforestation is the direct human-induced conversion of forest to nonforest land uses. It is important for nations to understand and report the extent of their deforestation. Because of the vastness of Canada's forest and the rare and spatially diverse nature of its deforestation, a sampling approach in which deforestation is mapped and then scaled up to represent deforestation for different regions was needed. The effectiveness of different sample designs in capturing the area of deforestation was evaluated using a Monte Carlo approach in which alternate sample designs were applied to simulated forest landscapes representative of different regions and deforestation patterns in Canada. Sampling error as expressed by the standard error in the estimated deforestation level for the sample divided by actual deforestation of the simulated landscape was used as a measure of sample design performance. Results indicated that sampling error was dependent on the characteristics of the deforestation (e.g., amount, shape, size, and distribution). For example, as mean event size increases or the proportion of linear deforestation events (e.g., roads and corridors) decreases, the required sampling intensity to reach a certain level of sampling error increases, and landscapes with a small number of very large events required the largest sampling intensity. To achieve a relative sampling error target (standard error/sample mean) of 10%, given sample designs of square plots on a systematic grid, a sample of 15%-25% of a landscape will be required for most Canadian landscapes, given a 10-year mapping time frame (interval between samples) and assuming a deforestation rate of 0.025% per annum. With mapping over a 5-year period, the required sampling intensity rises to 20%-40%. Also discussed are the consequences of the sampling error of different designs on the uncertainty in estimated greenhouse gas emission resulting from deforestation. Key words: deforestation, sample design, monitoring, greenhouse gas emissions, CBM-CFS3. La deforestation est la conversion anthropique directe de la foret a des usages non forestiers des terres. Il est important pour les nations de comprendre et de rapporter l'ampleur de leur deforestation. A cause de l'immensite de la foret canadienne et etant donne la rarete et la diversite spatiale de sa deforestation, il etait necessaire de mettre au point une methode d'echantillonnage qui permet de cartographier la deforestation, puis de changer d'echelle pour representer la deforestation dans differentes regions. L'efficacite de differents plans d'echantillonnage a determiner l'aire de deforestation a ete evaluee a l'aide d'une methode de Monte Carlo dans laquelle differents plans d'echantillonnage ont ete appliques pour simuler des paysages forestiers representatifs de differentes regions et de divers schemas de deforestation au Canada. Comme mesure de la performance du plan d'echantillonnage, nous avons utilise l'erreur d'echantillonnage exprimee par l'erreur-type du niveau de deforestation estime pour l'echantillon, divisee par la deforestation reelle du paysage simule. Les resultats indiquent que l'erreur d'echantillonnage etait dependante des caracteristiques de la deforestation (c.-a-d. la quantite, la forme, la taille et la distribution). Par exemple, avec l'augmentation de la taille moyenne des evenements ou la diminution de la proportion des evenements de deforestation lineaire (c.-a-d. les routes et les corridors), l'intensite d'echantillonnage requise pour atteindre un certain niveau d'erreur d'echantillonnage augmente et les paysages avec un petit nombre d'evenements tres vastes necessitaient la plus forte intensite d'echantillonnage. Pour atteindre une cible d'erreur relative d'echantillonnage (rapport de l'erreur-type sur la moyenne de l'echantillon) de 10 % a l'aide de plans d'echantillonnage systematique en grille avec des placettes carrees, un echantillon de 15 a 25 % d'un paysage sera necessaire pour la plupart des paysages canadiens avec un calendrier cartographique de 10 ans (intervalle de temps entre les echantillons) et en assumant un taux de deforestation annuel de 0,025 %. Si la cartographie est realisee sur une periode de cinq ans, l'intensite d'echantillonnage requise augmente et se situe entre 20 et 40 %. Nous discutons aussi des consequences de l'erreur d'echantillonnage de differents plans sur l'incertitude des emissions estimees de gaz a effet de serre provenant de la deforestation. [Traduit par la Redaction] Mots-cles: deforestation, plan d'echantillonnage, surveillance, emissions de gaz a effet de serre, CBM-CFS3., Introduction Deforestation can have important negative impacts on landscapes, habitats, and hydrological and biogeochemical cycles. Globally, deforestation accounts for approximately 8% of anthropogenic carbon emissions (Le Quere et al. 2014). [...]