Forest biomass is an essential indicator for monitoring the Earth’s ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS). However, RS methods require extant, up-to-date, reliable, representative and comparable in situ data for calibration and validation. Here, we present the Forest Observation System (FOS) initiative, an international cooperation to establish and maintain a global in situ forest biomass database. AGB and canopy height estimates with their associated uncertainties are derived at a 0.25 ha scale from field measurements made in permanent research plots across the world’s forests. All plot estimates are geolocated and have a size that allows for direct comparison with many RS measurements. The FOS offers the potential to improve the accuracy of RS-based biomass products while developing new synergies between the RS and ground-based ecosystem research communities.

Linking vegetation, soil biota, and soil carbon stocks in forests has a high predictive value. The specific aim of this study was to identify the relationships between vegetation, earthworms, and soil carbon stocks in nine types of forests dominating autonomous landscape positions in a coniferous–broadleaf forest zone of the European part of Russia. Mountain forests were selected in the Northwest Caucasus, while plain forests were selected in Bryansk Polesie and on the Moskva-Oka plain. One-way analysis of variance (ANOVA) and v-tests were used to assess the impact of different factors on soil C stocks. To assess the contribution of vegetation, litter quality, and earthworms to variation of carbon stocks in organic (FH-layer) and mineral layer (0–50 cm), the method of hierarchical partitioning was performed. The highest C stocks in the organic horizons were associated with the low-quality litter, i.e., with a low base saturation, high acidity, and wide C/N ratio. The highest soil C stocks in the mineral layers were found in mixed forests with the highest richness of plant species, producing litterfall of different quality. The С stock in the organic horizon was negatively related to the biomass of worms that process the litter, while the carbon stock in the mineral layers was positively related to the biomass of worms whose life activity is related to the mineral layers. These findings demonstrated the substantial influence of plants producing a litter of different quality, and of earthworms, belonging to different functional groups, on soil С stocks in coniferous–broadleaf forests.

Background: One of the key forest characteristics is the biodiversity, particularly the diversity of trees which are forest ecosystem engineers. Nowadays the most worldwide common approach for assessment of forest conditions and dynamics is based on the systematic monitoring, performed at a set of regularly structured plots. To fulfill the existing gap in this sort of knowledge on the Russian forests, an extensive study of tree species diversity on a regular network was conducted in north-west of Russia. Methods: The study used the ICP Forests monitoring network that spans over 1700 km along the western Russian border from forest-tundra in the north to broadleaved-coniferous forests in the south. Tree data were collected at 710 sites that were assigned along a regular grid. We performed series of statistical analyses of the tree species distribution and diversity in relation to environmental and anthropogenic factors. Results: According to the Maxent species distribution modelling results only Pinus sylvestris, Betula sp. and Picea abies have the potential to grow throughout the study area. The locally maximum tree species diversity varies along the latitudinal gradient from 1 to 3 species in the north to 5-7 species in the south. Monocultural stands are relatively abundant across the study area, being especially common in the south taiga. The prevailing part of the monocultural stands is represented by Scots pine (72%). The age distribution of dominant trees has a clear connection with the intensity of forest use. We found that recent wildfire events had only little effect on tree diversity in the study area. Conclusions: We demonstrated that ICP Forests monitoring network enables to successfully establish the main qualitative and quantitative relations of the spatial variation of tree species diversity to climatic, landscape, soil and anthropogenic factors. Analysis of the influence of these factors on tree species distribution allowed us to conclude that with the continuing trend of reducing the frequency and intensity of fires, Norway spruce will further replace Scots pine and Betula sp. in the north-western Russia. Extending the monitoring network, especially adding the time-series context, could provide novel appealing opportunities for forest dynamics projection and sustainable management.

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