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  • 11
    Publication Date: 2024-01-10
    Keywords: 11-CH-02II; 11-CH-02III; 11-CH-06I; 11-CH-06III; 11-CH-12I; 11-CH-12II; 11-CH-17I; 11-CH-17II; 12-KO-02; 12-KO-03; 12-KO-04; 12-KO-05; 13-TY-02-VI; 13-TY-02-VII; 14-OM-02-V1; 14-OM-02-V2; 14-OM-11-V3; 14-OM-20-V4; 14-OM-TRANS1; 14-OM-TRANS2; 14-OM-TRANS3; 14-OM-TRANS4; 14-OM-TRANS5; 14-OM-TRANS6; 14-OM-TRANS6-7; 16-KP-01-EN18001; 16-KP-01-EN18002; 16-KP-01-EN18003; 16-KP-01-EN18004; 16-KP-01-EN18005; 16-KP-01-EN18006; 16-KP-01-EN18007; 16-KP-01-EN18008; 16-KP-01-EN18009; 16-KP-01-EN18010; 16-KP-01-EN18011; 16-KP-01-EN18012; 16-KP-01-EN18013; 16-KP-01-EN18014; 16-KP-01-EN18015; 16-KP-01-EN18016; 16-KP-01-EN18017; 16-KP-01-EN18018; 16-KP-01-EN18019; 16-KP-01-EN18020; 16-KP-01-EN18021; 16-KP-01-EN18022; 16-KP-01-EN18023; 16-KP-01-EN18024; 16-KP-01-EN18025; 16-KP-01-EN18026; 16-KP-01-EN18027; 16-KP-04-EN18051; 16-KP-04-EN18052; 16-KP-04-EN18053; 16-KP-04-EN18054; 16-KP-04-EN18055; 16-KP-V01; 16-KP-V02; 16-KP-V03; 16-KP-V04; 16-KP-V05; 16-KP-V06; 16-KP-V07; 16-KP-V08; 16-KP-V09; 16-KP-V10; 16-KP-V11; 16-KP-V12; 16-KP-V13; 16-KP-V14; 16-KP-V15; 16-KP-V16; 16-KP-V17; 16-KP-V18; 16-KP-V19; 16-KP-V20; 16-KP-V21; 16-KP-V22; 16-KP-V23; 16-KP-V24; 16-KP-V25; 16-KP-V26; 16-KP-V27; 16-KP-V28; 16-KP-V29; 16-KP-V30; 16-KP-V31; 16-KP-V32; 16-KP-V33; 16-KP-V34; 16-KP-V35; 16-KP-V36; 16-KP-V37; 16-KP-V38; 16-KP-V39; 16-KP-V40; 16-KP-V41; 16-KP-V42; 16-KP-V43; 16-KP-V44; 16-KP-V45; 16-KP-V46; 16-KP-V47; 16-KP-V48; 16-KP-V49; 16-KP-V50; 16-KP-V51; 16-KP-V52; 16-KP-V53; 16-KP-V54; 16-KP-V55; 16-KP-V56; 16-KP-V57; 16-KP-V58; 18-BIL-00-EN18000; 18-BIL-01-EN18028; 18-BIL-01-EN18029; 18-BIL-02-EN18030; 18-BIL-02-EN18031; 18-BIL-02-EN18032; 18-BIL-02-EN18033; 18-BIL-02-EN18034; 18-BIL-02-EN18035; 18-LD-VP012-Tit-Ary; Area; Area/locality; AWI_Envi; AWI Arctic Land Expedition; B19-T1; B19-T2; Batagay 2019; Campaign; Central Yakutia; Chatanga2011; Chukotka; Chukotka 2018; Comment; DATE/TIME; ELEVATION; EN18061; EN18062; EN18063; EN18064; EN18065; EN18066; EN18067; EN18068; EN18069; EN18070_centre; EN18070_edge; EN18070_end; EN18070_transition; EN18071; EN18072; EN18073; EN18074; EN18075; EN18076; EN18077; EN18078; EN18079; EN18080; EN18081; EN18082; EN18083; EN21201; EN21202; EN21203; EN21204; EN21205; EN21206; EN21207; EN21208; EN21209; EN21210; EN21211; EN21212; EN21213; EN21214; EN21215; EN21216; EN21217; EN21218; EN21219; EN21220; EN21221; EN21222; EN21223; EN21224; EN21225; EN21226; EN21227; EN21228; EN21229; EN21230; EN21231; EN21232; EN21233; EN21234; EN21235; EN21236; EN21237; EN21238; EN21239; EN21240; EN21241; EN21242; EN21243; EN21244; EN21245; EN21246; EN21247; EN21248; EN21249; EN21250; EN21251; EN21252; EN21253; EN21254; EN21255; EN21256; EN21257; EN21258; EN21259; EN21260; EN21261; EN21262; EN21263; EN21264; Event label; Forest; Forest type; FTa; FTc; FTe; Genus; Gini coefficient; HAND; Height, maximum; Height, quantile; Individual Trees; Keperveem_2016; Kolyma, Russia; Kytalyk-Pokhodsk_2012, Kolyma2012; LATITUDE; Lena 2018; LONGITUDE; Mean values; Median values; MULT; Multiple investigations; Number of species; Number of trees; Omoloy2014; Plot; Polar Terrestrial Environmental Systems @ AWI; Principal investigator; Quantile (25th); Quantile (75th); Quantile (90th); Quantile (98th); Reference/source; RU-Land_2011_Khatanga; RU-Land_2012_Kytalyk_Kolyma; RU-Land_2013_Taymyr; RU-Land_2014_Omoloy; RU-Land_2016_Keperveem; RU-Land_2018_Chukotka; RU-Land_2018_Lena; RU-Land_2018_Yakutia; RU-Land_2019_Batagay; RU-Land_2021_Yakutia; Sampling by hand; Shannon Diversity Index; Siberia; Site; Taymyr; Taymyr2013; Tree, basal area, at base; Tree, basal area, at breast height; Tree, volume, conical; Tree, volume, smallian; Tree density; Tree height; Trees, basal area; Trees, volume, conical; Trees, volume, smallian; TY04VI; TY04VII; TY07VI; TY07VII; TY09VI; TY09VII; Vegetation survey; VEGSUR; Yakutia
    Type: Dataset
    Format: text/tab-separated-values, 7323 data points
    Location Call Number Limitation Availability
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  • 12
    Publication Date: 2024-01-10
    Description: The data set presents more than 32,000 of about 40,000 trees, which were surveyed during several Russian-German expeditions by the North-Eastern Federal University Yakutsk and the Alfred-Wegener-Institute Potsdam in the North-East of the Russian Federation between the years 2011 and 2021. The purpose was to gather information on trees and forests in this region, which was then used to understand tree line migration, stand infilling and natural disturbance and succession processes and to initialize and validate a forest model. Trees are located on more than 160 vegetation plots, each of which has a size of several hundred square meters. For every tree, height was estimated, and the species recorded, while a few individuals were subject to more detailed inventory. This table contains every standing tree of at least 40 cm height that was encountered on the vegetation plots described in the Plot Data Base. It partially overlaps with the dataset “Tree data set from forest inventories in north-eastern Siberia - Tree measurements.” (doi: 10.1594/PANGAEA.949861), which additionally contains details on small or lying deadwood.
    Keywords: 11-CH-02II; 11-CH-02III; 11-CH-06I; 11-CH-06III; 11-CH-12I; 11-CH-12II; 11-CH-17I; 11-CH-17II; 13-TY-02-VI; 13-TY-02-VII; 13-TY-04-VI; 13-TY-04-VII; 13-TY-07-VI; 13-TY-07-VII; 13-TY-09-VI; 13-TY-09-VII; 14-OM-02-V1; 14-OM-02-V2; 14-OM-20-V4; 16-KP-01-EN18001; 16-KP-01-EN18003; 16-KP-01-EN18004; 16-KP-01-EN18005; 16-KP-01-EN18006; 16-KP-01-EN18007; 16-KP-01-EN18009; 16-KP-01-EN18010; 16-KP-01-EN18012; 16-KP-01-EN18014; 16-KP-01-EN18021; 16-KP-01-EN18024; 16-KP-01-EN18025; 16-KP-01-EN18026; 16-KP-01-EN18027; 16-KP-V01; 16-KP-V02; 16-KP-V03; 16-KP-V04; 16-KP-V05; 16-KP-V06; 16-KP-V08; 16-KP-V10; 16-KP-V11; 16-KP-V12; 16-KP-V13; 16-KP-V14; 16-KP-V15; 16-KP-V16; 16-KP-V17; 16-KP-V18; 16-KP-V19; 16-KP-V20; 16-KP-V21; 16-KP-V22; 16-KP-V26; 16-KP-V27; 16-KP-V28; 16-KP-V29; 16-KP-V30; 16-KP-V31; 16-KP-V32; 16-KP-V34; 16-KP-V35; 16-KP-V36; 16-KP-V37; 16-KP-V38; 16-KP-V39; 18-BIL-00-EN18000; 18-BIL-01-EN18028; 18-BIL-01-EN18029; 18-BIL-02-EN18030; 18-BIL-02-EN18031; 18-BIL-02-EN18032; 18-BIL-02-EN18034; 18-BIL-02-EN18035; AWI_Envi; AWI Arctic Land Expedition; Campaign; Central Yakutia; Chatanga2011; Chukotka; Chukotka 2018; Comment; DATE/TIME; EN18061; EN18062; EN18063; EN18064; EN18065; EN18066; EN18067; EN18068; EN18069; EN18070_centre; EN18070_edge; EN18070_transition; EN18071; EN18072; EN18073; EN18074; EN18075; EN18076; EN18077; EN18078; EN18079; EN18080; EN18081; EN18082; EN18083; EN21202; EN21203; EN21204; EN21205; EN21206; EN21207; EN21209; EN21211; EN21212; EN21213; EN21215; EN21217; EN21219; EN21221; EN21222; EN21223; EN21225; EN21226; EN21227; EN21228; EN21229; EN21230; EN21231; EN21232; EN21233; EN21234; EN21235; EN21236; EN21237; EN21238; EN21239; EN21240; EN21241; EN21242; EN21244; EN21245; EN21246; EN21247; EN21248; EN21249; EN21250; EN21251; EN21252; EN21253; EN21254; EN21255; EN21256; EN21258; EN21259; EN21260; EN21261; Event label; Field observation; Forest; Genus; Growth form; HAND; Individual Trees; Keperveem_2016; LATITUDE; Latitude, center; LONGITUDE; Longitude, center; Maximum; Omoloy2014; Polar Terrestrial Environmental Systems @ AWI; Principal investigator; RU-Land_2011_Khatanga; RU-Land_2013_Taymyr; RU-Land_2014_Omoloy; RU-Land_2016_Keperveem; RU-Land_2018_Chukotka; RU-Land_2018_Yakutia; RU-Land_2021_Yakutia; Sampling by hand; Siberia; Species; Subsample ID; Taymyr; Taymyr2013; Tree, basal area, at base; Tree, basal area, at breast height; Tree, crown base; Tree, diameter, at base; Tree, survey protocol; Tree, volume, conical; Tree, volume, smallian; Tree crown diameter; Tree height; Tree ID; Trees, diameter at breast height; Vegetation survey; VEGSUR; Vitality; Yakutia
    Type: Dataset
    Format: text/tab-separated-values, 578779 data points
    Location Call Number Limitation Availability
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  • 13
    Publication Date: 2024-03-06
    Keywords: 13-TY-01; 13-TY-02; 13-TY-03; 13-TY-04; 13-TY-05; 13-TY-06; 13-TY-08; 13-TY-09; 13-TY-10; 13-TY-11; 13-TY-12; 13-TY-13; 13-TY-14; 13-TY-15; 13-TY-16; 13-TY-17; 13-TY-18; 13-TY-19; 13-TY-20; 13-TY-21; 13-TY-22; 13-TY-23; 13-TY-24; 13-TY-25; 13-TY-26; 13-TY-27; 13-TY-28; 13-TY-29; 13-TY-30; 13-TY-31; 13-TY-32; Alnus; Androsace-type; Apiaceae; Artemisia; AWI_PerDyn; AWI Arctic Land Expedition; Betula; Brassicaceae; Cassiope; Cerastium-type; Chenopodiaceae; Corylus; Counting, palynology; Cyperaceae; Date/Time of event; DEPTH, sediment/rock; Elevation of event; Epilobium; Event label; Fabaceae; Fenestrate undifferentiated; Filipendula; Galium; HAND; Juniperus; Lamiaceae; Larix; Latitude of event; Ledum; Liguliflorae; Liliaceae; Longitude of event; Marker, found; Parnassia; Pedicularis; Permafrost Research (Periglacial Dynamics) @ AWI; Pinaceae; Poaceae; Polemonium; Pollen, total; Populus; Potentilla-type; Ranunculus acris-type; Ranunculus arvensis-type; Rhinanthus group; Rosaceae; Rubus; RU-Land_2013_Taymyr; Rumex; Salix; Sampling by hand; Saussurea-type; Saxifraga; Senecio-type; Silene-type; Taymyr2013; Thalictrum; Vaccinium; Valeriana
    Type: Dataset
    Format: text/tab-separated-values, 1395 data points
    Location Call Number Limitation Availability
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  • 14
    Publication Date: 2024-02-16
    Keywords: 11-CH-02II; 11-CH-02III; 11-CH-06I; 11-CH-06III; 11-CH-06-IV; 11-CH-06-V; 11-CH-12I; 11-CH-12II; 11-CH-17I; 11-CH-17II; 11-CH-P3-I; 12-KO-02; 12-KO-03; 12-KO-04; 13-TY-02-VI; 13-TY-02-VII; 13-TY-04-VI; 13-TY-04-VII; 13-TY-07-VI; 13-TY-07-VII; 13-TY-09-VI; 13-TY-09-VII; 14-OM-02-V1; 14-OM-02-V2; 14-OM-20-V4; 14-OM-TRANS1; 14-OM-TRANS2; 14-OM-TRANS3; 14-OM-TRANS4; 14-OM-TRANS5; 14-OM-TRANS6; 14-OM-TRANS6-7; 16-KP-01-EN18001; 16-KP-01-EN18003; 16-KP-01-EN18004; 16-KP-01-EN18005; 16-KP-01-EN18006; 16-KP-01-EN18007; 16-KP-01-EN18008; 16-KP-01-EN18009; 16-KP-01-EN18010; 16-KP-01-EN18011; 16-KP-01-EN18012; 16-KP-01-EN18013; 16-KP-01-EN18014; 16-KP-01-EN18015; 16-KP-01-EN18016; 16-KP-01-EN18017; 16-KP-01-EN18021; 16-KP-01-EN18022; 16-KP-01-EN18023; 16-KP-01-EN18024; 16-KP-01-EN18025; 16-KP-01-EN18026; 16-KP-01-EN18027; 16-KP-V01; 16-KP-V02; 16-KP-V03; 16-KP-V04; 16-KP-V05; 16-KP-V06; 16-KP-V07; 16-KP-V08; 16-KP-V09; 16-KP-V10; 16-KP-V11; 16-KP-V12; 16-KP-V13; 16-KP-V14; 16-KP-V15; 16-KP-V16; 16-KP-V17; 16-KP-V18; 16-KP-V19; 16-KP-V20; 16-KP-V21; 16-KP-V22; 16-KP-V23; 16-KP-V24; 16-KP-V25; 16-KP-V26; 16-KP-V27; 16-KP-V28; 16-KP-V29; 16-KP-V30; 16-KP-V31; 16-KP-V32; 16-KP-V33; 16-KP-V34; 16-KP-V35; 16-KP-V36; 16-KP-V37; 16-KP-V38; 16-KP-V39; 18-BIL-00-EN18000; 18-BIL-01-EN18028; 18-BIL-01-EN18029; 18-BIL-02-EN18030; 18-BIL-02-EN18031; 18-BIL-02-EN18032; 18-BIL-02-EN18033; 18-BIL-02-EN18034; 18-BIL-02-EN18035; 18-LD-VP012-Tit-Ary; AWI_Envi; AWI Arctic Land Expedition; B19-T1; B19-T2; Batagay 2019; Campaign; Central Yakutia; CH06LP02; Chatanga2011; Chukotka; Chukotka 2018; Comment; DATE/TIME; EN18061; EN18062; EN18063; EN18064; EN18065; EN18066; EN18067; EN18067-70; EN18067-70 Lager Mirny Weatherstation near; EN18068; EN18069; EN18070_centre; EN18070_edge; EN18070_transition; EN18071; EN18072; EN18073; EN18074; EN18075; EN18076; EN18077; EN18078; EN18079; EN18080; EN18081; EN18082; EN18083; EN21201; EN21202; EN21203; EN21204; EN21205; EN21206; EN21207; EN21209; EN21211; EN21212; EN21213; EN21215; EN21217; EN21219; EN21221; EN21222; EN21223; EN21225; EN21226; EN21227; EN21228; EN21229; EN21230; EN21231; EN21232; EN21233; EN21234; EN21235; EN21236; EN21237; EN21238; EN21239; EN21240; EN21241; EN21242; EN21244; EN21245; EN21246; EN21247; EN21248; EN21249; EN21250; EN21251; EN21252; EN21253; EN21254; EN21255; EN21256; EN21258; EN21259; EN21260; EN21261; Event label; Forest; Genus; Growth form; HAND; Individual Trees; Keperveem_2016; Kolyma, Russia; Kytalyk-Pokhodsk_2012, Kolyma2012; LATITUDE; Latitude, center; Lena 2018; LONGITUDE; Longitude, center; MULT; Multiple investigations; Omoloy2014; Polar Terrestrial Environmental Systems @ AWI; Principal investigator; RU-Land_2011_Khatanga; RU-Land_2012_Kytalyk_Kolyma; RU-Land_2013_Taymyr; RU-Land_2014_Omoloy; RU-Land_2016_Keperveem; RU-Land_2018_Chukotka; RU-Land_2018_Lena; RU-Land_2018_Yakutia; RU-Land_2019_Batagay; RU-Land_2021_Yakutia; Sampling by hand; Siberia; Species; Subsample ID; Taymyr; Taymyr2013; Tree, basal area, at base; Tree, basal area, at breast height; Tree, crown base; Tree, diameter, at base; Tree, survey protocol; Tree, volume, conical; Tree, volume, smallian; Tree crown diameter; Tree height; Tree ID; Trees, diameter at breast height; Vegetation survey; VEGSUR; Village_Khayyr; Village Khayyr, Ust-Yansky Ulus; Vitality; Yakutia
    Type: Dataset
    Format: text/tab-separated-values, 762029 data points
    Location Call Number Limitation Availability
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  • 15
    Publication Date: 2024-04-20
    Description: The data set presents about 40,000 trees which where surveyed during several Russian-German expeditions by North-Eastern Federal University Yakutsk and Alfred-Wegener-Institute Potsdam to the North-East of the Russian Federation between the years 2011 and 2021. The purpose was to gather information on trees and forests in this region, which was then used to understand tree line migration, stand infilling and natural disturbance and succession processes and to initialize and validate a forest model. Trees are located on more than 160 vegetation plots, each of which has a size of several hundred square meters. For every tree, height was estimated, and the species recorded. Some individuals were subject to more detailed inventory, including diameters at base and at breast height, crown diameters, and other information.
    Keywords: AWI_Envi; Chukotka; Forest; Individual Trees; Polar Terrestrial Environmental Systems @ AWI; Siberia; Taymyr; Yakutia
    Type: Dataset
    Format: application/zip, 3 datasets
    Location Call Number Limitation Availability
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  • 16
    Publication Date: 2024-02-16
    Description: The data set presents more than 12,000 of about 40,000 trees, which were surveyed during several Russian-German expeditions by the North-Eastern Federal University Yakutsk and the Alfred-Wegener-Institute Potsdam in the North-East of the Russian Federation between the years 2011 and 2021. The purpose was to gather information on trees and forests in this region, which was then used to understand tree line migration, stand infilling and natural disturbance and succession processes and to initialize and validate a forest model. Trees are located on more than 160 vegetation plots, each of which has a size of several hundred square meters. For every tree, height was estimated, and the species recorded. Some individuals were subject to more detailed inventory, including diameters at base and at breast height, crown diameters, and other information. This table partially overlaps with the data set: “Tree data set from forest inventories in north-eastern Siberia - Tree heights.” (doi: 10.1594/PANGAEA.949863), but includes all tree measurements as well as all inventoried trees, which were not included in the Tree heights dataset due to small or lying deadwood.
    Keywords: 11-CH-06I; 11-CH-06III; 11-CH-06-IV; 11-CH-06-V; 11-CH-12I; 11-CH-12II; 11-CH-17I; 11-CH-17II; 11-CH-P3-I; 12-KO-02; 12-KO-03; 12-KO-04; 13-TY-02-VI; 13-TY-02-VII; 13-TY-04-VI; 13-TY-04-VII; 13-TY-07-VI; 13-TY-07-VII; 13-TY-09-VI; 13-TY-09-VII; 14-OM-02-V1; 14-OM-02-V2; 14-OM-20-V4; 14-OM-TRANS2; 14-OM-TRANS3; 14-OM-TRANS4; 14-OM-TRANS5; 14-OM-TRANS6; 14-OM-TRANS6-7; 16-KP-01-EN18001; 16-KP-01-EN18003; 16-KP-01-EN18004; 16-KP-01-EN18005; 16-KP-01-EN18006; 16-KP-01-EN18007; 16-KP-01-EN18008; 16-KP-01-EN18009; 16-KP-01-EN18010; 16-KP-01-EN18011; 16-KP-01-EN18012; 16-KP-01-EN18013; 16-KP-01-EN18014; 16-KP-01-EN18015; 16-KP-01-EN18016; 16-KP-01-EN18017; 16-KP-01-EN18021; 16-KP-01-EN18022; 16-KP-01-EN18023; 16-KP-01-EN18024; 16-KP-01-EN18025; 16-KP-01-EN18026; 16-KP-01-EN18027; 16-KP-V01; 16-KP-V02; 16-KP-V03; 16-KP-V04; 16-KP-V05; 16-KP-V06; 16-KP-V07; 16-KP-V08; 16-KP-V09; 16-KP-V10; 16-KP-V11; 16-KP-V12; 16-KP-V13; 16-KP-V14; 16-KP-V15; 16-KP-V16; 16-KP-V17; 16-KP-V18; 16-KP-V19; 16-KP-V20; 16-KP-V26; 16-KP-V27; 16-KP-V28; 16-KP-V29; 16-KP-V30; 16-KP-V31; 16-KP-V32; 16-KP-V33; 16-KP-V34; 16-KP-V35; 16-KP-V36; 16-KP-V37; 16-KP-V38; 16-KP-V39; 18-BIL-00-EN18000; 18-BIL-01-EN18028; 18-BIL-01-EN18029; 18-BIL-02-EN18030; 18-BIL-02-EN18031; 18-BIL-02-EN18032; 18-BIL-02-EN18033; 18-BIL-02-EN18034; 18-BIL-02-EN18035; 18-LD-VP012-Tit-Ary; AWI_Envi; AWI Arctic Land Expedition; B19-T1; B19-T2; Batagay 2019; Campaign; Central Yakutia; CH06LP02; Chatanga2011; Chukotka; Chukotka 2018; Comment; DATE/TIME; EN18061; EN18062; EN18063; EN18064; EN18065; EN18066; EN18067; EN18067-70; EN18067-70 Lager Mirny Weatherstation near; EN18068; EN18069; EN18070_centre; EN18070_edge; EN18071; EN18072; EN18073; EN18074; EN18075; EN18076; EN18077; EN18078; EN18079; EN18080; EN18081; EN18083; EN21247; EN21249; EN21250; EN21251; EN21252; Event label; Field observation; Forest; Genus; Growth form; HAND; Individual Trees; Keperveem_2016; Kolyma, Russia; Kytalyk-Pokhodsk_2012, Kolyma2012; LATITUDE; Latitude, center; Lena 2018; LONGITUDE; Longitude, center; Maximum; MULT; Multiple investigations; Omoloy2014; Polar Terrestrial Environmental Systems @ AWI; Principal investigator; RU-Land_2011_Khatanga; RU-Land_2012_Kytalyk_Kolyma; RU-Land_2013_Taymyr; RU-Land_2014_Omoloy; RU-Land_2016_Keperveem; RU-Land_2018_Chukotka; RU-Land_2018_Lena; RU-Land_2018_Yakutia; RU-Land_2019_Batagay; RU-Land_2021_Yakutia; Sampling by hand; Siberia; Species; Subsample ID; Taymyr; Taymyr2013; Tree, basal area, at base; Tree, basal area, at breast height; Tree, crown base; Tree, diameter, at base; Tree, survey protocol; Tree, volume, conical; Tree, volume, smallian; Tree crown diameter; Tree height; Tree ID; Trees, diameter at breast height; Vegetation survey; VEGSUR; Vitality; Yakutia
    Type: Dataset
    Format: text/tab-separated-values, 183236 data points
    Location Call Number Limitation Availability
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  • 17
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    In:  EPIC311th International Conference on Permafrost (ICOP), 2016-06-20-2016-06-24
    Publication Date: 2016-08-14
    Description: Current climatic changes, mostly triggered by global warming, influence broad parts of the northern latitudes all over the world, and reliable assessments of present and past vegetation are highly relevant to predict the future development of Arctic ecosystems. The northernmost Siberian arcto-boreal treeline areas in the Taymyr lowlands may be particularly affected by climatic changes, with latitudinal shifts of the treeline ecotone and resulting vegetation changes from tundra to taiga. Obtaining reliable information about present vegetation composition in such remote arctic locations is difficult, as vegetation surveys in the field can typically only be carried out during brief visits, and the flowering season is short. Although these techniques are time consuming, methods like vegetation assessment by ground surveys or palynological analyses are common tools to evaluate floral composition and provide valuable, complimentary information. While vegetation surveys mainly provide information about the status quo, pollen analyses also allow investigation of vegetation back in time. In recent years, sedimentary DNA has emerged as an additional and effective tool to improve knowledge about past vegetation. DNA metabarcoding of lake sediments and sediment cores has become more and more relevant as a tool for such research, but an explicit assessment of lake sediment DNA data in comparison to data obtained from pollen and vegetation surveys is still lacking. Here, we present a study comparing these three vegetation assessment methods for 31 lakes within a 300 km transect in arctic Siberia, reaching from Tundra, through the treeline area, to the light Taiga. Surface sediments of lakes were taken, subsampled for DNA and pollen analyses and processed in the respective laboratories. Together with six representative vegetation surveys, we present results of this comparative study. Our results show that taxa assigned by DNA sequence analyses are comparable to those found in the pollen and vegetation analyses. Overall, the DNA provides a higher taxonomical level of identification, while the pollen grains mainly identify to genus level. Compared to the vegetation survey, pollen and DNA provide more information, as they are able to track vegetation elements, which could not been surveyed at the time of the year the surveys were carried out. The results show that the combination and comparison of pollen, DNA and vegetation seems to serve as a calibration set for future investigations of such remote and highly dynamic ecosystems. Our investigation draws a multidisciplinary, comprehensive image of the current composition of the Siberian lowland vegetation by combining well established and promising, newly emerging methods.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 18
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    Unknown
    In:  EPIC319th Conference of the International Union for Quaternary Research (INQUA), Nagoya, Japan, 2015-07-26-2015-08-02
    Publication Date: 2016-08-14
    Description: Arctic environments are one of the most climatically influenced areas worldwide. These influences are currently causing major changes in vegetation composition, for example in the Taymyr lowlands, which harbour the northernmost boreal-arctic treeline areas of the world. The most dominant species of the treeline ecotone in this region are Larix gmelinii, Betula nana and Alnus viridis. They are presently shifting in density and range, and have done so multiple times throughout the Holocene. To understand the vegetation changes it is necessary to investigate the current state, before deducing changes for other time phases of the Holocene. To this end a field campaign was carried out at the Taymyr lowlands in 2013 to perform a multidisciplinary investigation by combining methods from vegetation mapping, palynological records and sedimentary DNA metabarcoding. We sampled lake sediments and mapped the vegetation along a transect spanning the treeline ecotone, with changing vegetation composition and density. Our results of the surveyed vegetation will help to investigate the current state of vegetation and will also be used as calibration of the pollen and DNA metabarcoding records. The comparison of the vegetation and pollen record will allow the assessment of over- or underrepresentation of certain taxa within the pollen signal, and this will enable a more secure interpretation of historic pollen records. We will also test this for the DNA metabarcoding data, which has not yet been systematically done for lake sediments in arctic latitudes. This multidisciplinary investigation will draw a more comprehensive image of the current vegetation composition at the Taymyr lowlands than has been possible to date, and will enable a more secure interpretation of historical vegetation change in this highly dynamic area.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 19
    Publication Date: 2017-07-13
    Description: Sedimentary ancient DNA is becoming more widely used in paleoeocology, as methods for sampling of sediments, as well as for extraction and sequencing of sedimentary ancient DNA have become more efficient and retrieval success has increased. To date, investigations of ancient DNA have concentrated on sites with low temperatures, as these display optimal preservation conditions. Remote, high latitude sites are ideal to track environmental changes that are not directly induced by human activity. Current climate changes are causing particularly strong ecosystem perturbations in the Arctic, and sedimentary archives allow a comparison of the current situation with past changes throughout the Holocene. Sites from temperate and tropical regions have been studied to a lesser extent, but are important for the analysis of human history and anthropogenic ecosystem modifications. Preservation conditions are less optimal, but ancient DNA has been retrieved on centennial to millenial timescales - corresponding to a period of time, in which anthropogenic impact has been strongest. Given good preservation conditions coupled with adequate precautions to ensure clean subsampling of the inside of sediment cores and for work with ancient DNA, a high diversity of authentic taxa can be retrieved. Plant DNA metabarcoding of Arctic lake sediment cores and ancient permafrost from Siberia can yield, for example, up to over 90 or 100 plant taxa from single samples, including both terrestrial and aquatic taxa, as well as bryophytes. Inferences of spatial and temporal vegetation change correspond very well to those from pollen, and DNA can potentially offer a higher degree of resolution. Using the same approaches as for Arctic samples, we are currently investigating a sediment core from Lake Barombi Mbo in Cameroon, concentrating on samples spanning the Holocene. Here, we give an overview of our approaches and comparatively assess the potential of sedimentary DNA as a paleoecological tool in different settings.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
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  • 20
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    Unknown
    Universität Potsdam
    In:  EPIC3Universität Potsdam, 146 p.
    Publication Date: 2017-07-18
    Repository Name: EPIC Alfred Wegener Institut
    Type: Thesis , notRev
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