No abstract is provided for this article.
No abstract is provided for this article.
A model cluster for soil respiration assessment was developed. It is based on 3592 in-situ measurements and considered climatic parameters, soil and vegetation types, land use, vegetation productivity and disturbances. Heterotrophic efflux from Russian soil was assessed as 3.47 Pg C year -1 or 215 g C m -2 year -1 .
We provide four data records: 1.The reference data set as a comma-separated file ("reference_data_set.csv") with the following attributes: “ID” is a unique location identifier “Latitude, Longitude” are centroid coordinates of a 100m x 100m pixel. “Land_use_ID “is a land use class: 11 - Naturally regenerating forest without any signs of human activities, e.g., primary forests. 20 - Naturally regenerating forest with signs of human activities, e.g., logging, clear cuts etc. 31 - Planted forest. 32 - Short rotation plantations for timber. 40 - Oil palm plantations. 53 - Agroforestry. “Flag” identifies a data origin: 1- the crowdsourced locations, 2- the control data set, 0 – the additional experts' classifications following the opportunistic approach. 2. The 100 m forest management map in a geoTiff format with the classes presented - "FML_v3.2.tif ". 3. The predicted class probability from the Random Forest classification in a geoTiff format - "ProbaV_LC100_epoch2015_global_v2.0.3_forest-management--layer-proba_EPSG-4326.tif" 4. Validation data set as a comma-separated file ("validation_data_set.csv) with the following attributes: “ID” is a unique location identifier “pixel_center_x” , “pixel_center_y ” are centroid coordinates of a 100m x 100m pixel in lat/lon projection “first_landuse_class “is a land use class, as in (1). “second_landuse_class “is a second possible land use class, as in (1), identified in case it was difficult to assign one class with high confidence. 5. Original crowdsourced data set as a .csv table. 6. Compiled FAO FRA forest statistics and mapped classes by countries into one table (.csv format).
No abstract is provided for this article.
The flux of CO2 from the soil to the atmosphere–soil respiration (R S), is one of the least known components of the terrestrial carbon cycle. R S depends on many factors and varies substantially in time and space. High uncertainty of R S flux valuation leads to a wide range of reported carbon budget estimates for Russian forests. We developed a modeling system for assessing soil carbon stock and heterotrophic soil respiration based on a possible maximum of relevant input indicators. The most comprehensive databases of RS in situ measurements focused on Northern Eurasia (780 records for the region) has been used. A statistical model for assessing R S of Russian forests and its separation in autotrophic and heterotrophic parts were elaborated based on in situ measurements, climate parameters, soil and land cover datasets. The spatial resolution of the model is 1km2. Russian forest soil accumulated 144.5PgC (or 17.6kgCm−2) in 1m depth, including 8.3PgC (or 1.0kgCm−2) in the labile topsoil organic layer. The total heterotrophic soil respiration (RH) flux for the Russian forest is estimated at 1.7PgCyr−1 (206gCm−2 yr−1) that comprises 65% of Net Primary Production (NPP) and together with NPP is one of two major components of the net ecosystem carbon balance comprising on average 546TgCyr−1 (66gCm−2 yr−1) for 2007–2009. Interannual variability or R H in 1996–2005 was estimated at 4.1% for forests of the whole country and typically from 5 to 11% for large individual regions with an average linear trend +0.2% per year. The uncertainty of annual average of R H was estimated at 8% (confidential interval 0.9).
Russia’s boreal forests provide numerous important ecosystem functions and services, but they are being increasingly affected by climate change. This review presents an overview of observed and potential future climate change impacts on those forests with an emphasis on their aggregate carbon balance and processes driving changes therein. We summarize recent findings highlighting that radiation increases, temperature-driven longer growing seasons and increasing atmospheric CO2 concentrations generally enhance vegetation productivity, while heat waves and droughts tend to decrease it. Estimates of major carbon fluxes such as net biome production agree that the Russian forests as a whole currently act as a carbon sink, but these estimates differ in terms of the magnitude of the sink due to different methods and time periods used. Moreover, models project substantial distributional shifts of forest biomes, but they may overestimate the extent to which the boreal forest will shift poleward as past migration rates have been slow. While other impacts of current climate change are already substantial, and projected impacts could be both large-scale and disastrous, the likelihood for a tipping point behavior of Russia’s boreal forest is still unquantified. Other substantial research gaps include the large-scale effect of (climate-driven) disturbances such as fires and insect outbreaks, which are expected to increase in the future. We conclude that the impacts of climate change on Russia’s boreal forest are often superimposed by other environmental and societal changes in a complex way, and the interaction of these developments could exacerbate both existing and projected future challenges. Hence, development of adaptation and mitigation strategies for Russia’s forests is strongly advised.
