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Dead wood, including coarse woody debris, CWD, and fine woody debris, FWD, plays a substantial role in forest ecosystem functioning. However, the amount and dynamics of dead wood in the forests of Northern Eurasia are poorly understood. The aim of this study was to develop a spatially distributed modelling system (limited to the territories of the former Soviet Union) to assess the amount and structure of dead wood by its components (including snags, logs, stumps, and the dry branches of living trees) based on the most comprehensive database of field measurements to date. The system is intended to be used to assess the dead wood volume and the amount of dead wood in carbon units as part of the carbon budget calculation of forests at different scales. It is presented using multi-dimensional regression equations of dead wood expansion factors (DWEF)—the ratio of the dead wood component volume to the growing stock volume of the stands. The system can be also used for the accounting of dead wood stock and its dynamics in national greenhouse gas inventories and UNFCCC reporting. The system's accuracy is satisfactory for the average level of disturbance regimes but it may require corrections for regions with accelerated disturbance regimes. [ABSTRACT FROM AUTHOR]

For 34 years since the 1986 nuclear disaster, the Chernobyl Exclusion Zone (ChEZ) landscapes have been protected with very limited human interventions. Natural afforestation has largely occurred throughout the abandoned farmlands, while natural disturbance regimes, which dominantly include wildfires, have become more frequent and severe in the last years. Here, we utilize the dense time series of Landsat satellite imagery (1986–2020) processed by using the temporal segmentation algorithm LandTrendr in order to derive a robust land cover and forest mask product for the ChEZ. Additionally, we carried out an analysis of land cover transitions on the former farmlands. The Random Forest classification model developed here has achieved overall accuracies of 80% (using training data for 2017) and 89% on a binary "forest/non-forest" validation (using data from 1988). The total forest cover area within the ChEZ has increased from 41% (in 1986) to 59% (in 2020). This forest gain can be explained by the afforestation that has occurred in abandoned farmlands, which compensates for forest cover losses due to large fire events in 1992, 2015–2016, and 2020. Most transitions from open landscapes to dense forest cover occurred after the year 2000 and are possibly linked to past forest management practices. We conclude that a consistent forest strategy, with the aid of remote monitoring, is required to efficiently manage new forests in the ChEZ in order to retain their ecosystem functions and to ensure sustainable habitats. [ABSTRACT FROM AUTHOR]

Research Highlights: A transparent approach to developing a forest reference emissions level (FREL) adjusted to future local developments in Southern Cameroon is demonstrated. Background and Objectives: Countries with low historical deforestation can adjust their forest reference (emission) level (FREL/FRL) upwards for REDD+ to account for likely future developments. Many countries, however, find it difficult to establish a credible adjusted reference level. This article demonstrates the establishment of a FREL for southern Cameroon adjusted to societal megatrends of strong population—and economic growth combined with rapid urbanization. It demonstrates what can be done with available information and data, but most importantly outlines pathways to further improve the quality of future FREL/FRL's in light of possibly accessing performance-based payments. Materials and Methods: The virtual FREL encompasses three main elements: Remotely sensed activity data; emission factors derived from the national forest inventory; and the adjustment of the reference level using a land use model of the agriculture sector. Sensitivity analysis is performed on all three elements using Monte Carlo methods. Results: Deforestation during the virtual reference period 2000–2015 is dominated by non-industrial agriculture (comprising both smallholders and local elites) and increases over time. The land use model projections are consistent with this trend, resulting in emissions that are on average 47% higher during the virtual performance period 2020–2030 than during the reference period 2000–2015. Monte Carlo analysis points to the adjustment term as the main driver of uncertainty in the FREL calculation. Conclusions: The available data is suitable for constructing a FREL for periodic reporting to the UNFCCC. Enhanced coherence of input data notably for activity data and adjustment is needed to apply for a performance-based payment scheme. Expanding the accounting framework to include forest degradation and forest gain are further priorities requiring future research. [ABSTRACT FROM AUTHOR]

Forests play an important role in regulating the carbon (C) cycle. The main objective of this study was to quantify the effects of South Korean national reforestation programs on carbon budgets. We estimated the changes in C stocks and annual C sequestration in the years 1961–2014 using Korea-specific models, a forest cover map (FCM), national forest inventory (NFI) data, and climate data. Furthermore, we examined the differences in C budgets between Cool forests (forests at elevations above 700 m) and forests in lower-altitude areas. Simulations including the effects of climate conditions on forest dynamics showed that the C stocks of the total forest area increased from 6.65 Tg C in 1961 to 476.21 Tg C in 2014. The model developed here showed a high degree of spatiotemporal reliability. The mean C stocks of the Cool forests and other forests increased from 4.03 and 0.43 Mg C ha−1, respectively, to 102.43 and 73.76 Mg C ha−1 at a rate of 1.82 and 1.36 Mg C ha−1 yr−1 during the same period. These results imply that, although the total Cool forest area of South Korea occupied only about 12.3% (772,788 ha) of the total forest area, the Cool forests play important roles in C balances and forest ecosystems in South Korea. Annual C sequestration totals are projected to decrease at a low rate in the near future because the overall growth rate of a mature forest decreases as the stand ages. Our results quantified forest C dynamics in South Korean forests before and after national reforestation programs. Furthermore, our results can help in development of regional and national forest management strategies to allow for sustainable development of society and to cope with climate change in South Korea. [ABSTRACT FROM AUTHOR]

The mid-latitude ecotone (MLE)—a transition zone between boreal and temperate forests, which includes the regions of Northeast Asia around 30°–60° N latitudes—delivers different ecosystem functions depending on different management activities. In this study, we assessed forest volume and net primary productivity changes in the MLE of Northeast Asia under different ecological characteristics, as well as various current management activities, using the BioGeoChemistry Management Model (BGC-MAN). We selected five pilot sites for pine (Scots pine and Korean red pine; Pinus sylvestris and P. densiflora), oak (Quercus spp.), and larch forests (Dahurian larch and Siberian larch; Larix gmelinii and L. sibirica), respectively, which covered the transition zone across the MLE from Lake Baikal, Russia to Kyushu, Japan, including Mongolia, Northeast China, and the Korean Peninsula. With site-specific information, soil characteristics, and management descriptions by forest species, we established their management characteristics as natural preserved forests, degraded forests, sandy and cold forest stands, and forests exposed to fires. We simulated forest volume (m3) and net primary productivity (Mg C ha−1) during 1960–2005 and compared the results with published literature. They were in the range of those specified in previous studies, with some site-levels under or over estimation, but unbiased estimates in their mean values for pine, oak, and larch forests. Annual rates of change in volume and net primary productivity differed by latitude, site conditions, and climatic characteristics. For larch forests, we identified a high mountain ecotype which warrants a separate model parameterization. We detected changes in forest ecosystems, explaining ecological transition in the Northeast Asian MLE. Under the transition, we need to resolve expected problems through appropriate forest management and social efforts. [ABSTRACT FROM AUTHOR]

Climate change continues to threaten forests and their ecosystem services while substantially altering natural disturbance regimes. Land cover changes and consequent management entail discrepancies in carbon sequestration provided by forest ecosystems and its accounting. Currently there is a lack of sufficient and harmonized data for Ukraine that can be used for the robust and spatially explicit assessment of forest provisioning and regulation of ecosystem services. In the frame of this research, we established an experimental polygon (area 45 km2) in Northern Ukraine aiming at estimating main forest carbon stocks and fluxes and determining the impact caused by natural disturbances and harvest for the study period of 2010–2015. Coupled field inventory and remote sensing data (RapidEye image for 2010 and SPOT 6 image for 2015) were used. Land cover classification and estimation of biomass and carbon pools were carried out using Random Forest and k-Nearest Neighbors (k-NN) method, respectively. Remote sensing data indicates a ca. 16% increase of carbon stock, while ground-based computations have shown only a ca. 1% increase. Net carbon fluxes for the study period are relatively even: 5.4 Gg C·year−1 and 5.6 Gg C C·year−1 for field and remote sensing data, respectively. Stand-replacing wildfires, as well as insect outbreaks and wind damage followed by salvage logging, and timber harvest have caused 21% of carbon emissions among all C sources within the experimental polygon during the study period. Hence, remote sensing data and non-parametric methods coupled with field data can serve as reliable tools for the precise estimation of forest carbon cycles on a regional spatial scale. However, featured land cover changes lead to unexpected biases in consistent assessment of forest biophysical parameters, while current management practices neglect natural forest dynamics and amplify negative impact of disturbances on ecosystem services. [ABSTRACT FROM AUTHOR]

Large-scale wildfires affect millions of hectares of land in Indonesia annually and produce severe smoke haze pollution and carbon emissions, with negative impacts on climate change, health, the economy and biodiversity. In this study, we apply a mechanistic fire model to estimate burned area in Indonesia for the first time. We use the Wildfire Climate Impacts and Adaptation Model (FLAM) that operates with a daily time step on the grid cell of 0.25 arc degrees, the same spatio-temporal resolution as in the Global Fire Emissions Database v4 (GFED). GFED data accumulated from 2000–2009 are used for calibrating spatially-explicit suppression efficiency in FLAM. Very low suppression levels are found in peatland of Kalimantan and Sumatra, where individual fires can burn for very long periods of time despite extensive rains and fire-fighting attempts. For 2010–2016, we validate FLAM estimated burned area temporally and spatially using annual GFED observations. From the validation for burned areas aggregated over Indonesia, we obtain Pearson’s correlation coefficient separately for wildfires and peat fires, which equals 0.988 in both cases. Spatial correlation analysis shows that in areas where around 70% is burned, the correlation coefficients are above 0.6, and in those where 30% is burned, above 0.9. [ABSTRACT FROM AUTHOR]

Biomass structure is an important feature of terrestrial vegetation. The parameters of forest biomass structure are important for forest monitoring, biomass modelling and the optimal utilization and management of forests. In this paper, we used the most comprehensive database of sample plots available to build a set of multi-dimensional regression models that describe the proportion of different live biomass fractions (i.e., the stem, branches, foliage, roots) of forest stands as a function of average stand age, density (relative stocking) and site quality for forests of the major tree species of northern Eurasia. Bootstrapping was used to determine the accuracy of the estimates and also provides the associated uncertainties in these estimates. The species-specific mean percentage errors were then calculated between the sample plot data and the model estimates, resulting in overall relative errors in the regression model of −0.6%, −1.0% and 11.6% for biomass conversion and expansion factor (BCEF), biomass expansion factor (BEF), and root-to-shoot ratio respectively. The equations were then applied to data obtained from the Russian State Forest Register (SFR) and a map of forest cover to produce spatially distributed estimators of biomass conversion and expansion factors and root-to-shoot ratios for Russian forests. The equations and the resulting maps can be used to convert growing stock volume to the components of both above-ground and below-ground live biomass. The new live biomass conversion factors can be used in different applications, in particular to substitute those that are currently used by Russia in national reporting to the UNFCCC (United Nations Framework Convention on Climate Change) and the FAO FRA (Food and Agriculture Organization’s Forest Resource Assessment), among others. [ABSTRACT FROM AUTHOR]

We conducted a feasibility study in Indochina (Cambodia, Laos, Myanmar, Thailand, and Vietnam) with the aim of promoting biomass and bioenergy markets, technology transfer, rural development, and income generation. Policy development is guided by the International Union of Forest Research Institutions (IUFRO) Task Force “Sustainable Forest Bioenergy Network”. In this paper, we highlight the achievements up to now and present results of a multi-stakeholder questionnaire in combination with a quantitative analysis of the National Bioenergy Development Plans (NBDPs). We found a gap between official documents and working group assessments. NBDPs are focused on the market development, technology transfer, and funding possibilities of a regional bioenergy strategy, while the respondents of a questionnaire (working groups) favored more altruistic goals, i.e., sustainable resource management, environmental protection and climate change mitigation, generation of rural income, and community involvement, etc. We therefore suggest the following measures to ensure regulations that support the original aims of the network (climate change mitigation, poverty alleviation, sustainable resource use, and diversification of energy generation): (i) Consideration of science-based evidence for drafting bioenergy policies, particularly in the field of biomass production and harvesting; (ii) invitation of stakeholders representing rural communities to participate in this process; (iii) development of sustainability criteria; (iv) feedback cycles ensuring more intensive discussion of policy drafts; (v) association of an international board of experts to provide scientifically sound feedback and input; and (vi) establishment of a local demonstration region, containing various steps in the biomass/bioenergy supply chain including transboundary collaboration in the ACMECS region. [ABSTRACT FROM AUTHOR]