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Monitoring of the salmon stocksof the Teno and Näätämö river systems is based on long term data collection on juvenile salmon production, biological characteristics of the spawning stock, origin of salmon (wild/reared) and statistics on fishery and catches. Information on other fish species than salmon is also available.
- To support the further development of a geocryological database for the Usa Basin (East-European Russian Arctic), including key characteristics of permafrost such as distribution, coverage, temperature, active layer, etc. - To create GIS-based permafrost maps at the scale of 1:1,000,000 for the entire Usa Basin and at 1:100,000 for selected key sites. - To reconstruct the history of permafrost dynamics at key sites in the region over the last thousands of years using palaeoecological analysis and radiocarbon dating of peat deposits, and over the last few decades using remote sensing imagery and/or monitoring (base case scenario). - To predict permafrost dynamics at key sites in the region under future conditions of climate change (20-100 yrs), using a 1-dimensional permafrost model (future global change scenario). - To assess the effects of permafrost dynamics under base case and global change scenarios on urban, industrial and transportation infrastructure in the Usa Basin. Research activities Based on several representative sites, late Holocene permafrost dynamics will be characterized using palaeoecological techniques. Variability in permafrost conditions over the last few decades will be studied based on the available data from long-term monitoring station records and from a time series of remote sensing images (optional). Mathematical modelling of permafrost dynamics will be carried out for at least two sites and a forecast of permafrost degradation in the area under anticipated climate warming will be developed. The likely effects of permafrost degradation upon regional infrastructure (inhabited localities, heat and power engineering, coal and ore mines, oil and gas extracting complex, pipelines and railways) will be analyzed using a GIS approach. GIS data layers on permafrost dynamics and infrastructure will be compared in order to delimitate high risk areas based on existing infrastructure and anticipated permafrost degradation. Hereafter, the created GIS may serve as a basis for more detailed forecasting of permafrost dynamics under both natural and anthropogenic climate changes in lowland and alpine areas of the East-European Russian Arctic.