Articles containing the keyword 'taiga'

An equilibrium model driven by climatic parameters, the Siberian Vegetation Model, was used to estimate changes in the phytomass of Siberian vegetation under climate change scenarios (CO₂ doubling) from four general circulation models (GCM's) of the atmosphere. Ecosystems were classified using a three-dimensional climatic ordination of growing degree days (above a 5 °C threshold), Budyko's dryness index (based on radiation balance and annual precipitation), and Conrad's continentality index. Phytomass density was estimated using published data of Bazilevich covering all vegetation zones in Siberia. Under current climate, total phytomass of Siberia is estimated to be 74.1 ± 2.0 Pg (petagram = 1,015 g). Note that this estimate is based on the current forested percentage in each vegetation class compiled from forest inventory data.

Moderate warming associated with the GISS (Goddard Institute for Space Studies) and OSU (Oregon State Univ.) projections resulted in a 23–26 % increase in phytomass (to 91.3 ± 2.1 Pg and 93.6 ± 2.4 Pg, respectively), primarily due to an increase in the productive Southern Taiga and Sub-taiga classes. Greater warming associated with the GFDL (General Fluid Dynamics Laboratory) and UKMO (United Kingdom Meteorological Office) projections resulted in a small 3–7 % increase in phytomass (to 76.6 ± 1.3 Pg and 79.6 ± 1.2 Pg, respectively). A major component of predicted change using GFDL and UKMO is the introduction of a vast Temperate Forest-Steppe class covering nearly 40% of the area of Siberia, at the expense of Taiga; with current climate, this vegetation class is nearly non-existent in Siberia. In addition, Sub-boreal Forest-Steppe phytomass double with all GCM predictions. In all four climate change scenarios, the predicted phytomass stock of all colder, northern classes is reduced considerably (viz., Tundra, Fore Tundra, northern Taiga, and Middle Taiga). Phytomass in Sub-taiga increases greatly with all scenarios, from a doubling with GFDL to quadrupling with OSU and GISS. Overall, phytomass of the Taiga biome (Northern, Middle, Southern and Sub-taiga) increased 15% in the moderate OSU and GISS scenarios and decreased by a third in the warmer UKMO and GFDL projections. In addition, a sensitivity analysis found that the percentage of a vegetation class that is forested is a major factor determining phytomass distribution. From 25 to 50% more phytomass is predicted under climate change if the forested proportion corresponding to potential rather than current vegetation is assumed.

• Monserud, E-mail: rm@mm.unknown
• Denissenko, E-mail: od@mm.unknown
• Kolchugina, E-mail: tk@mm.unknown
• Tchebakova, E-mail: nt@mm.unknown

The study was made in the Ivalojoki and Oulankajoki valleys, consisting of terraces of well sorted sandy material aged 9500–300 B.P. The vegetation is characterized by dry and moderately dry forest types with Scots pine (Pinus sylvestris L.) as the dominant tree species. The study included: forest types, particle size and sorting of mineral horizons, thickness of horizons, amount of organic material, pH, electrical conductivity, and NH₄OAc (pH 4.56) extractable Fe, Al, P, K, Mg, Mn and Zn concentrations. The principal aim was to study the interrelationships between all these properties with special reference to the age of the soil.

The results allowed a distinction to be made between the following categories: (1) features typical of podsolization (e.g. increase in leaching of Fe and Al with age of soil from the A₂), (2) certain factors showing higher values in the north (Ivalo) than in the south (Oulanka), principally Fe and Mg, (3) declining trends in P, Mg, Mn and Zn concentrations with age, which may partly be due to the geological history, and (4) declining trends in amount of organic material and electrical conductivity with age, these both being factors arising from the geological history rather than from podzolization.

The PDF includes a summary in Finnish.

• Koutaniemi, E-mail: lk@mm.unknown
• Koponen, E-mail: rk@mm.unknown
• Rajanen, E-mail: kr@mm.unknown

• Volkova, Moscow South-West High School (No. 1543), 26 Bakinskikh komissarov str. 3–5, RU-119571 Moscow, Russia E-mail: avolkov@orc.ru
• Shipunov, Department of Biology, Minot State University, Minot, North Dakota, USA 58707 E-mail: dactylorhiza@gmail.com
• Borisova, Biological Department, Moscow State University, Vorobjevy Gory, RU-119899, Moscow, Russia E-mail: salixhastata@ya.ru
• Moseng, Minot High School, Minot, North Dakota, USA 58701 E-mail: dactylorhiza@gmail.com
• Ivens, Department of Biology, Minot State University, Minot, North Dakota, USA 58707 E-mail: dactylorhiza@gmail.com

The research was carried out in unmanaged middle-aged (75–85 years) Northern taiga Scots pine (Pinus sylvestris L.) forests in the Kola peninsula. It was established that forests of green moss-lichen and green moss site types are characterised by a predominance (65–70% by stand volume) of moderately and strongly weakened trees. Trees of differing vitality have significant differences in annual increment. Healthy trees had a radial increment (RI) 70–75% greater than that of dying trees, and a basal area increment (BAI) 85–90% greater. The dynamics of the RI and BAI of Scots pine trees for the 70-year period (from 1945 to 2015) is different. The RI of all individuals in the communities studied decreases consistently. The decrease is expressed more strongly in green moss Scots pine forests (80–95% from 1945 to 2015) compared to green moss-lichen forests (60–80%); it manifests itself more in strongly weakened and dying individuals (75–95%) than in healthy and moderately weakened ones (60–80%). Annual basal area increment in green moss Scots pine forests increases by 45–65% from stand establishment until the trees are 25 to 35 years old and subsequently decreases by 50–80% to 70–80 years of age. In green moss-lichen pine forests the BAI of Scots pine remains rather stable in healthy and moderately weakened trees and decreases in strongly weakened and dying individuals by 45% and 75–80%, respectively throughout the studied period.

• Katjutin, Komarov Botanical Institute of the Russian Academy of Sciences, Professora Popova str. 2, 197376, Saint-Petersburg, Russia E-mail: paurussia@binran.ru
• Stavrova, Komarov Botanical Institute of the Russian Academy of Sciences, Professora Popova str. 2, 197376, Saint-Petersburg, Russia E-mail: nstavrova@binran.ru
• Gorshkov, Komarov Botanical Institute of the Russian Academy of Sciences, Professora Popova str. 2, 197376, Saint-Petersburg, Russia; Saint-Petersburg State Forest Technical University, letter U, 5, Institutsky per., 194021, Saint-Petersburg, Russia E-mail: vgorshkov@binran.ru
• Lyanguzov, Saint-Petersburg State University, 7/9 Universitetskaya Emb., 199034, Saint-Petersburg, Russia E-mail: andrewlyanguzov@gmail.com
• Bakkal, Komarov Botanical Institute of the Russian Academy of Sciences, Professora Popova str. 2, 197376, Saint-Petersburg, Russia E-mail: bakkal@binran.ru
• Mikhailov, Komarov Botanical Institute of the Russian Academy of Sciences, Professora Popova str. 2, 197376, Saint-Petersburg, Russia E-mail: smikhailov@binran.ru