Patterns of logging in the last two decades in temperate forests of Russia

While the boreal forests have garnered much of the attention regarding land-cover change, a new focus on temperate forest cover change in the vast temperate forests of Russia reveals the important consequences of selective logging on forest cover and carbon storage estimation. SILVIS researcher Matthias Baumann is exploring how changing socio-economic and political conditions have created varied patterns of forest cover change and how selective logging in the temperate forests of Russia, an activity that is widespread and difficult to detect with remote sensing over wide areas, can lead to important consequences when estimating carbon stores in the vast temperate forests of Russia.

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Russian Collaborator Dmitry Aksenov showing regrowing forest
Because of their vast area, the forests of Russia are an important store of carbon that greatly impacts the global carbon budget. According to SILVIS lab Ph.D. student, Matthias Baumann, the temperate forests of Russia have been largely overlooked as carbon sequestration and land-cover change research has focused on boreal systems. Recent changes in use of the temperate forests in Russia has brought the need for accurate modeling of forest cover change to the forefront of land cover change modeling in this region that spans over 200 million hectares.

Since the collapse of the Soviet Union in 1991, economic drivers have led to increased use of the forest in rural areas of temperate Russia. First, the opening of markets in Russia led to investment and exploitation of the temperate forest primarily by foreign firms. Secondly, subsistence use of the forest in rural areas of temperate Russia has increased since the dissolution of the Soviet Union. The latter comes in the form of selective logging that has widespread, diffuse impacts on forest cover which over the entire extent of these vast forests can have an enormous influence on estimates of carbon sequestered there. Both of these drivers of forest change have consequences for climate modeling, carbon budget estimation, and accurate estimates of forest cover.

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Classification of a Landsat TM Time Series for the Vladimir Region to the northeast of Moscow
Baumann is exploring the changes in forest cover in temperate Russia before and after the fall of the Soviet Union. He will also refine methods for detecting and modeling selective logging from Landsat imagery, ultimately leading to better estimates of current carbon stocks and the effect of selective logging on these estimates using an ecosystem services approach. To accomplish the first objective he will classify forested and non-forested areas at five-year intervals from 1985-2005 for 9 Landsat footprints across the temperate forest region stretching from the western border of Russia to the Ural Mountains. In order to detect selective logging, Baumann will use dense time series (multiple images per year) of Landsat image stacks and a radiative transfer model to simulate intact forests and compare pixel-by-pixel changes in reflectance when simulated 'trees' are removed. To adjust these models he will visit partially harvested areas near Moscow and St. Petersburg, Russia during July and August of 2010 to validate and refine the models produced in the lab. The final objective and end result of this work on refining forest cover estimates will be to incorporate these new measurements of forest cover that incorporate selective logging in determining more accurate of carbon stores in these forests.

Thus far, Baumann's work has revealed a range of changes in forest cover across the sociopolitical transition period in Russia. Some areas have seen little or no change in forest cover, while in others such as the Vladimir region northeast of Moscow has experienced intensive logging between 1986 and 1990.