THE SUCESSION OF THE VEGETATION AND THE DYNAMICS OF THE VEGETATIVE SUBSTANCE WITH GROWING OF THE DUMPS OF THE FOREST-STEPPE ZONE OF THE MIDDLE SIBERIA SOUTH

The primary and secondary successions of the vegetation and the dynamics of the vegetative substance at the natural growing of the stripping rocks and at recultivated dumps (on the examples of the dumps of the coal strippings in the forest steppe zone of the Krasnoyarsk krai) are being describedAvailable from VNTIC / VNTIC - Scientific & Technical Information Centre of RussiaSIGLERURussian Federatio

Estimation of Biomass and Net Primary Production (NPP) in West Siberian Boreal Ecosystems: In Situ and Remote Sensing Methods

International audienc

Plant organic matter in palsa and khasyrei type mires: Direct observations in West Siberian Sub-Arctic

International audienceThis article presents the first results of long-term direct measurements of a few major components of carbon cycle in permafrost mire landforms in the sub-Arctic region of Western Siberia, Russia. It reveals the main features of geographical distribution of plant organic matter, including both the above-ground and below-ground fractions of live biomass, the biomass of dead roots (mortmass), and net primary production (NPP) in peat-accumulating flat palsa mires and in “khasyrei”—ecosystems of drained lakes in thermokarst depression on epigenetic permafrost. The study based on original methods of direct field measurements elaborated by authors for northern peatlands. In northern taiga, the NPP of palsa mires was found in the range of 300–580 g m$^{−2}$ yr$^{−1}$ and an average biomass of 1800 g m$^{−2}$ ; in khasyrei, it accounts for 1100 g m$^{−2}$ yr$^{−1}$ and 2000 g m$^{−2}$ of NPP and live biomass, respectively. In forest tundra, the live biomass of palsa mires was found in the range of 1000–1800 g m$^{−2}$ , and in khasyrei it was 2300 g m$^{−2}$ . The NPP of palsa mires were in the range of 400–560 g m$^{−2}$ yr$^{−1}$ , and in khasyrei it was 800 g m$^{−2}$ yr$^{−1}$ . Overall, we conclude that the south–north climatic gradient in Western Siberia is the main driver of plant organic matter accumulation. It was found different across mire ecosystems of the same types but located in different bioclimatic regions

Towards a more detailed representation of high-latitude vegetation in the global land surface model ORCHIDEE (ORC-HL-VEGv1.0)

International audienceSimulation of vegetation-climate feedbacks in high latitudes in the ORCHIDEE land surface model was improved by the addition of three new circumpolar plant functional types (PFTs), namely non-vascular plants representing bryophytes and lichens, Arctic shrubs and Arctic C 3 grasses. Non-vascular plants are assigned no stomatal con-ductance, very shallow roots, and can desiccate during dry episodes and become active again during wet periods, which gives them a larger phenological plasticity (i.e. adaptability and resilience to severe climatic constraints) compared to grasses and shrubs. Shrubs have a specific carbon allocation scheme, and differ from trees by their larger survival rates in winter, due to protection by snow. Arctic C 3 grasses have the same equations as in the original ORCHIDEE version , but different parameter values, optimised from in situ observations of biomass and net primary productivity (NPP) in Siberia. In situ observations of living biomass and productivity from Siberia were used to calibrate the parameters of the new PFTs using a Bayesian optimisation procedure. With the new PFTs, we obtain a lower NPP by 31 % (from 55 • N), as well as a lower roughness length (−41 %), transpi-ration (−33 %) and a higher winter albedo (by +3.6 %) due to increased snow cover. A simulation of the water balance and runoff and drainage in the high northern latitudes using the new PFTs results in an increase of fresh water discharge in the Arctic ocean by 11 % (+140 km 3 yr −1), owing to less evapotranspiration. Future developments should focus on the competition between these three PFTs and boreal tree PFTs, in order to simulate their area changes in response to climate change, and the effect of carbon-nitrogen interactions

Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management

International audienceGrassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5° by 0.5°. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 1901–2012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, rising CO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1  ×  106 km2 in 1901 to 12.3  ×  106 km2 in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and interannual variability of grassland productivity at global scale well and thus is appropriate for global applications presented here