Modeling the location of the forest line in northeast European Russia with remotely sensed vegetation and GIS-based climate and terrain data

TY - JOUR

T1 - Modeling the location of the forest line in northeast European Russia with remotely sensed vegetation and GIS-based climate and terrain data

AU - Virtanen, Tarmo

AU - Mikkola, Kari

AU - Nikula, Ari

AU - Christensen, Jens H.

AU - Mazhitova, Galina G.

AU - Oberman, Naum G.

AU - Kuhry, Peter

PY - 2004/8/1

Y1 - 2004/8/1

N2 - GIS-based data sets were used to analyze the structure of the forest line at the landscape level in the lowlands of the Usa River Basin, in northeast European Russia. Vegetation zones in the area range from taiga in the south to forest-tundra and tundra in the north. We constructed logistic regression models to predict forest location at spatial scales varying from 1 X 1 km to 25 X 25 km grid cells. Forest location was explained by July mean temperature, ground temperature (permafrost), yearly minimum temperature, and a Topographic Wetness Index (soil moisture conditions). According to the models, the forest line follows the +13.9°C mean July temperature isoline, whereas in other parts of the Arctic it usually is located between +10 to +12°C. It is hypothesized that the anomalously high temperature isoline for the forest line in Northeast European Russia is due to the inability of local ecotypes of spruce to grow on permafrost terrain. Observed patterns depend on spatial scale, as the relative significance of the explanatory variables varies between models implemented at different scales. Developed models indicate that with climate warming of 3°C by the end of the 21st century temperature would not limit forest advance anywhere in our study area.

AB - GIS-based data sets were used to analyze the structure of the forest line at the landscape level in the lowlands of the Usa River Basin, in northeast European Russia. Vegetation zones in the area range from taiga in the south to forest-tundra and tundra in the north. We constructed logistic regression models to predict forest location at spatial scales varying from 1 X 1 km to 25 X 25 km grid cells. Forest location was explained by July mean temperature, ground temperature (permafrost), yearly minimum temperature, and a Topographic Wetness Index (soil moisture conditions). According to the models, the forest line follows the +13.9°C mean July temperature isoline, whereas in other parts of the Arctic it usually is located between +10 to +12°C. It is hypothesized that the anomalously high temperature isoline for the forest line in Northeast European Russia is due to the inability of local ecotypes of spruce to grow on permafrost terrain. Observed patterns depend on spatial scale, as the relative significance of the explanatory variables varies between models implemented at different scales. Developed models indicate that with climate warming of 3°C by the end of the 21st century temperature would not limit forest advance anywhere in our study area.

UR - http://www.scopus.com/inward/record.url?scp=12444319421&partnerID=8YFLogxK

M3 - Journal article

AN - SCOPUS:12444319421

SN - 1523-0430

VL - 36

SP - 314

EP - 322

JO - Arctic, Antarctic, and Alpine Research

JF - Arctic, Antarctic, and Alpine Research

IS - 3

ER -