scholarly journals EFFECTS OF FARGESIA NITIDA ON REGENERATION OF ABIES FAXONIANASEEDLINGS NEAR THE EDGE OF SUBALPINE DARK CONIFEROUS FOREST

2007 ◽  
Vol 31 (2) ◽  
pp. 283-290 ◽  
Author(s):  
LI Yuan ◽  
◽  
TAO Jian-Ping ◽  
WANG Yong-Jian ◽  
YU Xiao-Hong ◽  
...  
Keyword(s):  
Coniferous Forest ◽  
Abies Faxoniana ◽  
Dark Coniferous Forest ◽  
Fargesia Nitida

Meadows of the North-Eastern Altai

2002 ◽  
pp. 22-31 ◽  
Author(s):  
T. V. Maltseva ◽  
N. I. Makunina
Keyword(s):  
Coniferous Forest ◽  
Wet Meadows ◽  
Abies Sibirica ◽  
Dark Coniferous Forest ◽  
Hay Meadows ◽  
The North ◽  
North Eastern ◽  
Humid Area ◽  
River Valleys

The North-Eastern Altai is an ultra-humid area with climax vegetation represented by tall-herb fir (Abies sibirica) dark-coniferous forest. Its meadows belong to the class Molinio-Arrhenatheretea. The typical asso­ciation Aegopodio podagrariae—Dactyletum glomeratae originates in the watershed clearings after climax forests whereas ass. Hyperici perforati—Agrostietum giganteaereplaces the previous one under mowing and grazing. The Molinietalia wet meadows are widespread in the river valleys. The meadows of ass. Cirsio heterophylli—Calama­grostietum langsdorffii occur on wet soils in small depressions and along floodplain mire margins, and ass. Ca­rici ovalis—Deschampsietum cespitosae comprises typical floodplain hay-meadows on moist, nutrient-rich soils.

scholarly journals Vegetation responses to interglacial warming in the Arctic: examples from Lake El'gygytgyn, Far East Russian Arctic

2013 ◽  
Vol 9 (3) ◽  
pp. 1211-1219 ◽  
Author(s):  
A. V. Lozhkin ◽  
P. M. Anderson
Keyword(s):  
Deciduous Forest ◽  
Russian Far East ◽  
Coniferous Forest ◽  
Far East ◽  
The Arctic ◽  
Dark Coniferous Forest ◽  
Vegetation Responses ◽  
Wide Range ◽  
Lake El’Gygytgyn ◽  
Shrub Tundra

Abstract. Preliminary analyses of Lake El'gygytgyn sediment indicate a wide range of ecosystem responses to warmer than present climates. While palynological work describing all interglacial vegetation is ongoing, sufficient data exist to compare recent warm events (the postglacial thermal maximum, PGTM, and marine isotope stage, MIS5) with "super" interglaciations (MIS11, MIS31). Palynological assemblages associated with these climatic optima suggest two types of vegetation responses: one dominated by deciduous taxa (PGTM, MIS5) and the second by evergreen conifers (MIS11, MIS31). MIS11 forests show a similarity to modern Picea–Larix–Betula–Alnus forests of Siberia. While dark coniferous forest also characterizes MIS31, the pollen taxa show an affinity to the boreal forest of the lower Amur valley (southern Russian Far East). Despite vegetation differences during these thermal maxima, all glacial–interglacial transitions are alike, being dominated by deciduous woody taxa. Initially Betula shrub tundra established and was replaced by tundra with tree-sized shrubs (PGTM), Betula woodland (MIS5), or Betula–Larix (MIS11, MIS31) forest. The consistent occurrence of deciduous forest and/or high shrub tundra before the incidence of maximum warmth underscores the importance of this biome for modeling efforts. The El'gygytgyn data also suggest a possible elimination or massive reduction of Arctic plant communities under extreme warm-earth scenarios.

Consume of soil seeds ofBetula albo-sinensisandAbies faxonianain different natural successional stages of subalpine dark coniferous forest in western Sichuan, China

2012 ◽  
Vol 32 (11) ◽  
pp. 3323-3333
Author(s):  
马姜明 MA Jiangming ◽  
刘世荣 LIU Shirong ◽  
史作民 SHI Zuomin ◽  
刘兴良 LIU Xingliang
Keyword(s):  
Coniferous Forest ◽  
Western Sichuan ◽  
Dark Coniferous Forest ◽  
Successional Stages

Woody debris storage and its distribution of dark coniferous forest in the alpine-gorge area

2016 ◽  
Vol 36 (5) ◽  
Author(s):  
肖洒 XIAO Sa ◽  
吴福忠 WU Fuzhong ◽  
杨万勤 YANG wanqin ◽  
常晨晖 CHANG Chenhui ◽  
李俊 LI Jun ◽  
...  
Keyword(s):  
Woody Debris ◽  
Coniferous Forest ◽  
Dark Coniferous Forest

scholarly journals Face DetectNet: face detection via fully-convolutional network

2019 ◽  
Vol 43 (2) ◽  
pp. 238-244 ◽  
Author(s):  
A.V. Lapko ◽  
V.A. Lapko
Keyword(s):  
Remote Sensing ◽  
Pattern Recognition ◽  
Spectral Data ◽  
Coniferous Forest ◽  
Remote Sensing Data ◽  
Random Variable ◽  
Dry Forest ◽  
Convolutional Network ◽  
Dark Coniferous Forest ◽  
Forest Condition

The paper deals with a new method of testing hypotheses for the distribution of multidimensional remote sensing spectral data. The proposed technique is based on the use of nonparametric algorithms for pattern recognition. Testing the hypothesis of the identity of two laws of distributions of multidimensional random variables is replaced by testing a hypothesis stating that the pattern recognition error equals 0.5. The application of this technique allows doing without the decomposition of the random variable domain into multidimensional intervals, which is typical for the Pearson criterion. Its effectiveness is confirmed by the results of testing the hypotheses of the distribution of spectral data of remote sensing in forestry. The analysis of the distribution laws for the following types of forestry is carried out: dark coniferous forest, damaged and dry forest stands. The initial information was obtained from the southern Siberia remote sensing data using six spectral channels of Landsat. The results of the research form a basis for a set of significant spectral features when dealing with forest condition monitoring.

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