Plant diversity in sedimentary DNA obtained from high-latitude (Siberia) and high-altitude lakes (China)
Fuente:
PANGAEA
Salvato in:
| Autori principali: | , , , , , , , , , , |
|---|---|
| Natura: | Dataset Open Access |
| Lingua: | en |
| Pubblicazione: |
PANGAEA
2020
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1867171021572800512 |
|---|---|
| author | Stoof-Leichsenring, Kathleen Rosmarie Liu, Sisi Jia, Weihan Li, Kai Pestryakova, Luidmila A Mischke, Steffen Cao, Xianyong Li, Xingqi Ni, Jian Neuhaus, Stefan Herzschuh, Ulrike |
| author_facet | Stoof-Leichsenring, Kathleen Rosmarie Liu, Sisi Jia, Weihan Li, Kai Pestryakova, Luidmila A Mischke, Steffen Cao, Xianyong Li, Xingqi Ni, Jian Neuhaus, Stefan Herzschuh, Ulrike |
| collection | Datos científicos de ciencias marinas y ambientales |
| contents | Compilation of environmental data for the 262 investigated localities, which include additional intra-lake localities taken within three large lakes namely: 16-KP-01-L02 (9 samples), 16-KP-03-L10 (5 samples), 16-KP-04-L19 (4 samples). The table includes information about the geographic coordinates, elevation, type of sample material, geographic region, water depth (at which samples were taken), pH, water conductivity, mean annual precipitation (MAP), mean annual temperature (MAP), July and January mean temperature. Annual mean temperature, mean temperature in July and January, and mean annual precipitation were downloaded from WorldClim 2 (www.worldclim.org), and are based on the average climate data for the years 1970–2000 at a spatial resolution of 30 seconds (ca. 1 km^2^). The site-specific climate data was interpolated to the location area by using the R packages raster Hijmans 2020. Hijmans RJ (2020) raster: Geographic Data Analysis and Modeling. R package version 3.1-5. URL: https://CRAN.R-project.org/package=raster. Plant diversity in the Arctic and at high altitudes strongly depends on and rebounds to climatic and environmental variability and is nowadays tremendously impacted by recent climate warming. Therefore, past changes in plant diversity in the high Arctic and high-altitude regions are used to infer climatic and environmental changes through time and allow future predictions. Sedimentary DNA is an established proxy for the detection of local plant diversity in lake sediments, but still relationships between environmental conditions and preservation of the plant sedDNA proxy are far from being fully understood. Studying modern relationships between environmental conditions and plant sedDNA will improve our understanding under which conditions sedDNA is well-preserved helping to a.) evaluate suitable localities for sedDNA approaches, b.) provide analogues for preservation conditions and c.) conduct reconstruction of plant diversity and climate change. This study investigates modern plant diversity applying a plant-specific metabarcoding approach on sedimentary DNA (sedDNA) of surface sediment samples from 262 lake localities covering a large geographical, climatic and ecological gradient. Latitude ranges between 25°N and 73°N and longitude between 81°E and 161°E, including lowland lakes and elevated lakes up to 5168 m a.s.l. Further, our sampling localities cover a climatic gradient ranging in mean annual temperature between -15°C to +18°C and in mean annual precipitation between 36–935 mm. The localities in Siberia span over a large vegetational gradient including tundra, open woodland and boreal forest. Lake localities in China include alpine meadow, shrub, forest and steppe and also cultivated areas. The assessment of plant diversity in the underlying data set was conducted by a specific plant metabarcoding approach. |
| format | Dataset Open Access |
| id | pangaea_https___doi_org_10_1594_PANGAEA_920866 |
| institution | PANGAEA |
| language | en |
| publishDate | 2020 |
| publisher | PANGAEA |
| record_format | pangaea |
| spellingShingle | Plant diversity in sedimentary DNA obtained from high-latitude (Siberia) and high-altitude lakes (China) Stoof-Leichsenring, Kathleen Rosmarie Liu, Sisi Jia, Weihan Li, Kai Pestryakova, Luidmila A Mischke, Steffen Cao, Xianyong Li, Xingqi Ni, Jian Neuhaus, Stefan Herzschuh, Ulrike 05-LC-02; 05-LC-03; 05-LC-04; 05-LC-05; 05-LC-06; 05-LC-07; 05-LC-08; 05-LC-10; 05-LC-11; 05-Yak-03; 05-Yak-05; 05-Yak-06; 05-Yak-08; 05-Yak-10; 05-Yak-11; 05-Yak-14; 05-Yak-16; 05-Yak-17; 05-Yak-18; 05-Yak-19; 05-Yak-21; 05-Yak-23; 05-Yak-24; 05-Yak-25; 05-Yak-26; 05-Yak-27; 05-Yak-28; 07-SA-07; 07-SA-21; 07-SA-23; 07-SA-26; 07-SA-31; 07-SA-33; 07-SA-34; 08-KO-01; 08-KO-03; 08-KO-04; 08-KO-06; 08-KO-07; 08-KO-09; 08-KO-11; 08-KO-12; 08-KO-13; 08-KO-14; 08-KO-15; 08-KO-16; 08-KO-17; 08-KO-18; 08-KO-19; 08-KO-20; 08-KO-21; 08-KO-22; 08-KO-23; 08-KO-24; 08-KO-26; 08-KO-28; 08-KO-29; 08-KO-30; 08-KO-31; 08-KO-32; 08-KO-33; 09-TIK-03; 09-TIK-04; 09-TIK-05; 09-TIK-08; 09-TIK-09; 09-TIK-13; 09-TIK-14; 11-CH-02; 11-CH-05; 11-CH-06; 11-CH-09; 11-CH-10; 11-CH-11; 11-CH-12; 11-CH-13; 11-CH-14; 11-CH-15; 11-CH-17; 11-CH-18; 11-CH-19; 11-CH-20; 13-TY-01; 13-TY-02; 13-TY-03; 13-TY-04; 13-TY-05; 13-TY-06; 13-TY-07; 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; 14-OM-01; 14-OM-02; 14-OM-03; 14-OM-04; 14-OM-05; 14-OM-06; 14-OM-07; 16-KP-01-L01; 16-KP-01-L02; 16-KP-01-L02_2; 16-KP-01-L02_3; 16-KP-01-L02_4; 16-KP-01-L02_5; 16-KP-01-L02_6; 16-KP-01-L02_7; 16-KP-01-L02_8; 16-KP-01-L02_9; 16-KP-01-L03; 16-KP-01-L04; 16-KP-02-L05; 16-KP-02-L06; 16-KP-02-L07; 16-KP-02-L08; 16-KP-02-L09; 16-KP-03-L10; 16-KP-03-L10_2; 16-KP-03-L10_3; 16-KP-03-L10_4; 16-KP-03-L10_5; 16-KP-03-L11; 16-KP-03-L13; 16-KP-03-L14; 16-KP-03-L15; 16-KP-03-L16; 16-KP-03-L17; 16-KP-03-L18; 16-KP-04-L19; 16-KP-04-L19_1; 16-KP-04-L19_2; 16-KP-04-L19_4; 16-KP-04-L20; 16-KP-04-L21; 16-KP-04-L22; Ailike; Angrenjin_Co; Arctic; Argaa-Bere; AWI_Envi; AWI Arctic Land Expedition; B-6; Balybyrbym; Bamuco; based on WORLDCLIM data; Beringia/Kolyma_2008; Bosten; Byluyng Kjuel; Central and eastern Siberia; Chagan_nuur; Chatanga2011; Chloroplast DNA; Choktokhoi; Cona; Conductivity, electrical; Daihai; Dajiaco; Dali; Dazeco; DEPTH, water; Donggi-Cona; E_ling; EG; Ekman grab; Elevation of event; Elgene Kjuel; Event label; Gahai_DLH; Gahai_QHH; Hala; HAND; Jiang_Co; Jinzihai; Keluke; Keperveem_2016; Kh; Kocha; Kol_01; Kol_03; Kol_04; Kol_06; Kol_07; Kol_09; Kol_11; Kol_12; Kol_13; Kol_14; Kol_15; Kol_16; Kol_17; Kol_18; Kol_19; Kol_20; Kol_21; Kol_22; Kol_24; Kol_27; Kol_28; Kol_29; Kol_30; Kol_31; Kolyma River; Kubalakh; Kuhai; Kyunde; lakes; Lang_Co; Latitude of event; Location; Longitude of event; Metabarcoding; MULT; Multiple investigations; Northern China and Xingjiang; Ochugui-Kengerime; Oibon; Omoloy2014; Pengco; pH; Pipa; Plant diversity; Polar Terrestrial Environmental Systems @ AWI; Precipitation, annual mean; Qinghai-Lake; RU-Land_2005_Verkhoyansk; RU-Land_2007_Saskylakh; RU-Land_2008_Kolyma; RU-Land_2009_Lena-transect; RU-Land_2011_Khatanga; RU-Land_2013_Taymyr; RU-Land_2014_Omoloy; RU-Land_2016_Keperveem; S-02; S-03; S-06; S-07; S-08; S-09; S-10; S101; S105; S-12; S123; S133; S-14; S143; S-15; S16; S-16; S169; S-17; S200; S213; S-22; S229; S237; S244; S-25; S259; S-26; S263; S310; S344; S350; S358; S374; S379; S414; S417; S420; S434; S439; S440; S62; Sailimu; Sample ID; Sample material; Sampling by hand; Saskylakh2007; Saskylakh region (Sakha), Russia; Sedimentary DNA; Selinco; SET-01; SET-02; SET-03; SET-04; SET-05; SET-06; SET-07; SET-08; SET-09; SET-11; SET-12; SET-13; SET-14; SET-15; SET-16; SET-18; SET-19; SET-20; SET-21; SET-22; SET-23; SET-24; SET-25; SET-26; SET-27; SET-28; SET-29; SET-30; SET-31; SET-32; Shengco; Species dominance; Species present; Sugan; Taymyr2013; Temperature, air, January; Temperature, air, July; Temperature, annual mean; Tibet; Tibet Plateau; Tiksi2009; Toiogoi; Toson; trnL P6 loop; Tschukotka, Sibiria, Russia; Vegetation; Vegetation type; Water sampler, UWITEC; WSUWI; Wulungu; Xingxinghai; Yakutia2005; Zhaling; Zharinanmu_Co Compilation of environmental data for the 262 investigated localities, which include additional intra-lake localities taken within three large lakes namely: 16-KP-01-L02 (9 samples), 16-KP-03-L10 (5 samples), 16-KP-04-L19 (4 samples). The table includes information about the geographic coordinates, elevation, type of sample material, geographic region, water depth (at which samples were taken), pH, water conductivity, mean annual precipitation (MAP), mean annual temperature (MAP), July and January mean temperature. Annual mean temperature, mean temperature in July and January, and mean annual precipitation were downloaded from WorldClim 2 (www.worldclim.org), and are based on the average climate data for the years 1970–2000 at a spatial resolution of 30 seconds (ca. 1 km^2^). The site-specific climate data was interpolated to the location area by using the R packages raster Hijmans 2020. Hijmans RJ (2020) raster: Geographic Data Analysis and Modeling. R package version 3.1-5. URL: https://CRAN.R-project.org/package=raster. Plant diversity in the Arctic and at high altitudes strongly depends on and rebounds to climatic and environmental variability and is nowadays tremendously impacted by recent climate warming. Therefore, past changes in plant diversity in the high Arctic and high-altitude regions are used to infer climatic and environmental changes through time and allow future predictions. Sedimentary DNA is an established proxy for the detection of local plant diversity in lake sediments, but still relationships between environmental conditions and preservation of the plant sedDNA proxy are far from being fully understood. Studying modern relationships between environmental conditions and plant sedDNA will improve our understanding under which conditions sedDNA is well-preserved helping to a.) evaluate suitable localities for sedDNA approaches, b.) provide analogues for preservation conditions and c.) conduct reconstruction of plant diversity and climate change. This study investigates modern plant diversity applying a plant-specific metabarcoding approach on sedimentary DNA (sedDNA) of surface sediment samples from 262 lake localities covering a large geographical, climatic and ecological gradient. Latitude ranges between 25°N and 73°N and longitude between 81°E and 161°E, including lowland lakes and elevated lakes up to 5168 m a.s.l. Further, our sampling localities cover a climatic gradient ranging in mean annual temperature between -15°C to +18°C and in mean annual precipitation between 36–935 mm. The localities in Siberia span over a large vegetational gradient including tundra, open woodland and boreal forest. Lake localities in China include alpine meadow, shrub, forest and steppe and also cultivated areas. The assessment of plant diversity in the underlying data set was conducted by a specific plant metabarcoding approach. |
| title | Plant diversity in sedimentary DNA obtained from high-latitude (Siberia) and high-altitude lakes (China) |
| topic | 05-LC-02; 05-LC-03; 05-LC-04; 05-LC-05; 05-LC-06; 05-LC-07; 05-LC-08; 05-LC-10; 05-LC-11; 05-Yak-03; 05-Yak-05; 05-Yak-06; 05-Yak-08; 05-Yak-10; 05-Yak-11; 05-Yak-14; 05-Yak-16; 05-Yak-17; 05-Yak-18; 05-Yak-19; 05-Yak-21; 05-Yak-23; 05-Yak-24; 05-Yak-25; 05-Yak-26; 05-Yak-27; 05-Yak-28; 07-SA-07; 07-SA-21; 07-SA-23; 07-SA-26; 07-SA-31; 07-SA-33; 07-SA-34; 08-KO-01; 08-KO-03; 08-KO-04; 08-KO-06; 08-KO-07; 08-KO-09; 08-KO-11; 08-KO-12; 08-KO-13; 08-KO-14; 08-KO-15; 08-KO-16; 08-KO-17; 08-KO-18; 08-KO-19; 08-KO-20; 08-KO-21; 08-KO-22; 08-KO-23; 08-KO-24; 08-KO-26; 08-KO-28; 08-KO-29; 08-KO-30; 08-KO-31; 08-KO-32; 08-KO-33; 09-TIK-03; 09-TIK-04; 09-TIK-05; 09-TIK-08; 09-TIK-09; 09-TIK-13; 09-TIK-14; 11-CH-02; 11-CH-05; 11-CH-06; 11-CH-09; 11-CH-10; 11-CH-11; 11-CH-12; 11-CH-13; 11-CH-14; 11-CH-15; 11-CH-17; 11-CH-18; 11-CH-19; 11-CH-20; 13-TY-01; 13-TY-02; 13-TY-03; 13-TY-04; 13-TY-05; 13-TY-06; 13-TY-07; 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; 14-OM-01; 14-OM-02; 14-OM-03; 14-OM-04; 14-OM-05; 14-OM-06; 14-OM-07; 16-KP-01-L01; 16-KP-01-L02; 16-KP-01-L02_2; 16-KP-01-L02_3; 16-KP-01-L02_4; 16-KP-01-L02_5; 16-KP-01-L02_6; 16-KP-01-L02_7; 16-KP-01-L02_8; 16-KP-01-L02_9; 16-KP-01-L03; 16-KP-01-L04; 16-KP-02-L05; 16-KP-02-L06; 16-KP-02-L07; 16-KP-02-L08; 16-KP-02-L09; 16-KP-03-L10; 16-KP-03-L10_2; 16-KP-03-L10_3; 16-KP-03-L10_4; 16-KP-03-L10_5; 16-KP-03-L11; 16-KP-03-L13; 16-KP-03-L14; 16-KP-03-L15; 16-KP-03-L16; 16-KP-03-L17; 16-KP-03-L18; 16-KP-04-L19; 16-KP-04-L19_1; 16-KP-04-L19_2; 16-KP-04-L19_4; 16-KP-04-L20; 16-KP-04-L21; 16-KP-04-L22; Ailike; Angrenjin_Co; Arctic; Argaa-Bere; AWI_Envi; AWI Arctic Land Expedition; B-6; Balybyrbym; Bamuco; based on WORLDCLIM data; Beringia/Kolyma_2008; Bosten; Byluyng Kjuel; Central and eastern Siberia; Chagan_nuur; Chatanga2011; Chloroplast DNA; Choktokhoi; Cona; Conductivity, electrical; Daihai; Dajiaco; Dali; Dazeco; DEPTH, water; Donggi-Cona; E_ling; EG; Ekman grab; Elevation of event; Elgene Kjuel; Event label; Gahai_DLH; Gahai_QHH; Hala; HAND; Jiang_Co; Jinzihai; Keluke; Keperveem_2016; Kh; Kocha; Kol_01; Kol_03; Kol_04; Kol_06; Kol_07; Kol_09; Kol_11; Kol_12; Kol_13; Kol_14; Kol_15; Kol_16; Kol_17; Kol_18; Kol_19; Kol_20; Kol_21; Kol_22; Kol_24; Kol_27; Kol_28; Kol_29; Kol_30; Kol_31; Kolyma River; Kubalakh; Kuhai; Kyunde; lakes; Lang_Co; Latitude of event; Location; Longitude of event; Metabarcoding; MULT; Multiple investigations; Northern China and Xingjiang; Ochugui-Kengerime; Oibon; Omoloy2014; Pengco; pH; Pipa; Plant diversity; Polar Terrestrial Environmental Systems @ AWI; Precipitation, annual mean; Qinghai-Lake; RU-Land_2005_Verkhoyansk; RU-Land_2007_Saskylakh; RU-Land_2008_Kolyma; RU-Land_2009_Lena-transect; RU-Land_2011_Khatanga; RU-Land_2013_Taymyr; RU-Land_2014_Omoloy; RU-Land_2016_Keperveem; S-02; S-03; S-06; S-07; S-08; S-09; S-10; S101; S105; S-12; S123; S133; S-14; S143; S-15; S16; S-16; S169; S-17; S200; S213; S-22; S229; S237; S244; S-25; S259; S-26; S263; S310; S344; S350; S358; S374; S379; S414; S417; S420; S434; S439; S440; S62; Sailimu; Sample ID; Sample material; Sampling by hand; Saskylakh2007; Saskylakh region (Sakha), Russia; Sedimentary DNA; Selinco; SET-01; SET-02; SET-03; SET-04; SET-05; SET-06; SET-07; SET-08; SET-09; SET-11; SET-12; SET-13; SET-14; SET-15; SET-16; SET-18; SET-19; SET-20; SET-21; SET-22; SET-23; SET-24; SET-25; SET-26; SET-27; SET-28; SET-29; SET-30; SET-31; SET-32; Shengco; Species dominance; Species present; Sugan; Taymyr2013; Temperature, air, January; Temperature, air, July; Temperature, annual mean; Tibet; Tibet Plateau; Tiksi2009; Toiogoi; Toson; trnL P6 loop; Tschukotka, Sibiria, Russia; Vegetation; Vegetation type; Water sampler, UWITEC; WSUWI; Wulungu; Xingxinghai; Yakutia2005; Zhaling; Zharinanmu_Co |
| url | https://doi.org/10.1594/PANGAEA.920866 |