Changbai Mountain Forest Ecosystem Research Station - China

Basic Information
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Site Name
Changbai Mountain Forest Ecosystem Research Station
Short name
Changbai Mountain
Country
China
Site Manager
anzhi WANG
Site Description
Changbai mountain station is located in National Nature Reserve of Changbai Mountain,Jinlin Province.The zonal vegetation is broad leaved Korean pine forest,There are more than 1000 kinds of plants.The main forest types are broad leaved Korean pine forest,Spruce fir forest,betula ermanii forest,alpine tundra.
Last modified
2020-12-18 10:12:56

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General Characteristics and Status
Site Status
Operational
Year Established
1979
Affiliation and Network Specific Information
Affiliation
ILTER✔This site is a verified "ILTER" member.
CERN (LTER China)✔ (LTER-EAP-CN-17)This site is a verified "CERN (LTER China)" member.
GERI✔This site is a verified "GERI" member.
Photos
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Geographic
View in site map
Centroid/Representative Coordinates

Latitude: 42.4 Longitude: 128.1

Size
ca. 10.00ha
Elevation (min)
740.00msl
Elevation (max)
2200.00msl
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Site information [.json]

Centroid/representative coordinates [.shp] [.kml]
Bounding Box [.shp] [.kml]
Boundaries [.shp] [.kml]
GEO-BON Biome
Terrestrial
Biome
Mixed Forest
Ecosystem Type
Forest
Temperate broadleaf and mixed forests
EUNIS habitat
Woodland, forest and other wooded land (G)
Woodland, forest and other wooded land (G) » Mixed deciduous and coniferous woodland (G4)
Woodland, forest and other wooded land (G) » Mixed deciduous and coniferous woodland (G4) » Mixed forestry plantations (G4.F)
Air Temperature: Average Annual
3.60°C
Precipitation Annual
695.00mm
Site Type
Platform
Design of Experimentation
mainly experimentation
Scale of Experimentation
plot scale
Design of Observation
mainly observation
Scale of Observation
plot without link to explicit catchment
Permanent Power Supply
No
Equipment
Data infrastructure » Data services » Data portal
Accessible All Year
No
All parts of Site Accessible
No
Permanent Operation
No
General Data Policy
The data provider must be offered co-authorship for publications using this dataset at least within the metadata description
LTER Site Classification
Master