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Spatially explicit information on forest management at a global scale is critical for understanding the status of forests, for planning sustainable forest management and restoration, and conservation activities. Here, we produce the first reference data set and a prototype of a globally consistent forest management map with high spatial detail on the most prevalent forest management classes such as intact forests, managed forests with natural regeneration, planted forests, plantation forest (rotation up to 15 years), oil palm plantations, and agroforestry. We developed the reference dataset of 226 K unique locations through a series of expert and crowdsourcing campaigns using Geo-Wiki ( https://www.geo-wiki.org/ ). We then combined the reference samples with time series from PROBA-V satellite imagery to create a global wall-to-wall map of forest management at a 100 m resolution for the year 2015, with forest management class accuracies ranging from 58% to 80%. The reference data set and the map present the status of forest ecosystems and can be used for investigating the value of forests for species, ecosystems and their services.
Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.
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.
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No abstract is provided for this article.
Current fire emission inventories apply universal emission factors (EFs) for the calculation of NOx emissions over large biomes such as boreal forest. However, recent satellite-based studies over tropical and subtropical regions have indicated spatio-temporal variations in EFs within specific biomes. In this study, satellite measurements of tropospheric NO2 vertical columns (TVC NO2) from the GOME-2 instrument and fire radiative power (FRP) from MODIS are used for the estimation of fire emission rates (FERs) of NOx over Eurasian and North American boreal forests. The retrieval of TVC NO2 is based on a stratospheric correction using simulated stratospheric NO2 instead of applying the reference sector method, which was used in a previous study. The model approach is more suitable for boreal latitudes. TVC NO2 and FRP are spatially aggregated to a 1° × 1° horizontal resolution and temporally averaged to monthly values. The conversion of the satellite-derived tropospheric NO2 columns into production rates of NOx from fire (Pf) is based on the NO2/NOx ratio as obtained from the MACC reanalysis data set and an assumed lifetime of NOx. A global land cover map is used to define boreal forests across these two regions in order to evaluate the FERs of NOx for this biome. The FERs of NOx, which are derived from the gradients of the linear relationship between Pf and FRP, are more than 30% lower for North American than for Eurasian boreal forest fires. We speculate that these discrepancies are mainly related to the variable nitrogen content in plant tissues, which is higher in deciduous forests dominating large parts in Eurasia. In order to compare the obtained values with EFs found in the literature, the FERs are converted into EFs. The satellite-based EFs of NOx are estimated at 0.83 and 0.61 g kg−1 for Eurasian and North American boreal forests, respectively, which is in good agreement with the value found in a recent emission factor compilation. However, recent fire emission inventories are based on EFs of NOx that are 3–5 times larger, which indicates that there are still large uncertainties in estimates of NOx from biomass burning, especially on the regional scale.
Forests play a significant role in the uptake of atmospheric carbon dioxide and carbon sequestration for a long time. In forests, the long-term carbon depositing mainly takes place in two pools: in tree biomass and in soil organic matter that have different...