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Chemical variables - stream from Följemaden, C-stream-13
No full textManual grab samples from the stream for chemical analysis are taken on a biweekly basis during ice-free conditions, and on a monthly basis in the presence of stream ice.
Skogaryd Research Catchment (2025). Chemical variables - stream from Följemaden, C-stream-13, 2019-01-14–2019-12-30 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/XdFoL04iXS9UFE_Aob3IjHX
Meteorological data from Följesjön, C-mast-2-Fixed sensor
No full textAutomatic weather station data from locations within the distributed Swedish research infrastructure SITES. Check preview or file for the specific parameters included at this location. Data has been quality controlled and cleaned from outliers and other events producing unrealistic data. Gaps have not been filled.
Skogaryd Research Catchment (2025). Meteorological data from Följesjön, C-mast-2-Fixed sensor, 2023 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/Nt3mj9tlVnTv_A4i2HfVlSI
Meteorological data from Följesjön
No full textAutomatic weather station data from locations within the distributed Swedish research infrastructure SITES. Check preview or file for the specific parameters included at this location. Data has been quality controlled and cleaned from outliers and other events producing unrealistic data. Gaps have not been filled.
Skogaryd Research Catchment (2025). Meteorological data from Följesjön, 2021 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/Srw3SqZfm_i0tA4MuCzeLI6
DNA-sekvenseringsdata för "Stabilt klonalt bidrag från härstamningsbegränsade stamceller till mänsklig hematopoies"
No full textThis dataset contains three types of DNA sequencing data.
-Error-corrected DNA capture sequencing (ECTS)
-Bulk whole-exome sequencing (WES)
-Single-colony whole-genome sequencing (WGS)
All sequencing was performed on an Illumina NovaSeq 6000 at the National Genomics Infrastructure in
Stockholm, using paired-end sequencing mode.
ECTS
Bone marrow mononuclear cells isolated from all 93 healthy donors were subjected to ECTS for identification of somatic mutations targeted to 23 genes encompassing the most recurrently mutated genes reported in clonal hematopoiesis.
WES
BM MNC DNA isolated from the first visit from 20 healthy donors above 71 years was subjected bulk WES. Paired buccal swab DNA was used for normal controls.
Single colony WGS
DNA extracted from 333 genotyped single colonies and 10 control buccal swabs from 10 donors was subjected to WGS.
The dataset consists of three folders:
scWGS contains 343 files in CRAM format, totaling approximately 16.3 TiB (17.9 TB).
WES contains 40 files in CRAM format, totaling approximately 650 GiB (710 GB).
ECTS contains 117 files in CRAM format, totaling approximately 18 GiB (20 GB).Detta dataset innehåller tre typer av DNA-sekvenseringsdata.
-Error-corrected DNA capture sequencing (ECTS)
-Bulk whole-exome sequencing (WES)
-Single-colony whole-genome sequencing (WGS)
All sekvensering utfördes på en Illumina NovaSeq 6000 vid National Genomics Infrastructure i Stockholm, med hjälp av "paired-end sequencing mode".
ECTS
Mononukleära benmärgsceller isolerade från alla 93 friska donatorer utsattes för ECTS för identifiering av somatiska mutationer riktade mot 23 gener som omfattar de mest återkommande muterade generna som rapporterats i klonal hematopoes.
WES
BM MNC-DNA isolerat från det första besöket från 20 friska donatorer över 71 år utsattes för WES i bulk. Parat buckalt swab-DNA användes för normala kontroller.
Enkelkoloni WGS
DNA extraherat från 333 genotypade enskilda kolonier och 10 kontroll-buckala pinnprover från 10 donatorer genomgick WGS.
Datasetet består av tre mappar:
scWGS innehåller 343 filer i format CRAM totalt cirka 16.3 TiB (17.9 TB).
WES innehåller 40 filer i format CRAM totalt cirka 650 GiB (710 GB).
ECTS innehåller 117 filer i format CRAM totalt cirka 18 GiB (20 GB)
Obspack CO2 time-series result from Norunda (100.0 m)
No full textThis data file contains high accuracy European ObsPack observational timeseries in netCDF format of ambient mole fraction of co2 in dry air collected at Norunda (100.0 m). The measurements were calibrated using the WMO GAW calibration scale WMO CO2 X2019. Included are (all whenever available) historical PI QCed data, ICOS Level 2 data, ICOS FastTrack data and ICOS NRT data. It is part of the 2025.3 FastTrack update of the Globalview EU CO2 data product and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Metadata for the full co2 product release are available at https://commons.datacite.org/doi.org/10.18160/R0PE-1H0Z. Please also visit http://www.gml.noaa.gov/ccgg/obspack/ for more information. If you use these data in your research, please consider citing the full ObsPack release that this file is part of (https://commons.datacite.org/doi.org/10.18160/46ST-DEVK).
ICOS RI, Lehner, I., Molder, M. (2025). Obspack CO2 time-series result from Norunda (100.0 m), 2017-01-31–2025-10-01, European ObsPack, https://hdl.handle.net/11676/acR-EP32snHuEjJ10RDa2Kc
Obspack CO2 time-series result from Svartberget (150.0 m)
No full textThis data file contains high accuracy European ObsPack observational timeseries in netCDF format of ambient mole fraction of co2 in dry air collected at Svartberget (150.0 m). The measurements were calibrated using the WMO GAW calibration scale WMO CO2 X2019. Included are (all whenever available) historical PI QCed data, ICOS Level 2 data, ICOS FastTrack data and ICOS NRT data. It is part of the 2025.3 FastTrack update of the Globalview EU CO2 data product and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Metadata for the full co2 product release are available at https://commons.datacite.org/doi.org/10.18160/R0PE-1H0Z. Please also visit http://www.gml.noaa.gov/ccgg/obspack/ for more information. If you use these data in your research, please consider citing the full ObsPack release that this file is part of (https://commons.datacite.org/doi.org/10.18160/46ST-DEVK).
ICOS RI, Larmanou, E., Marklund, P., Ottosson-Löfvenius, M., Smith, P. (2025). Obspack CO2 time-series result from Svartberget (150.0 m), 2017-05-31–2025-10-01, European ObsPack, https://hdl.handle.net/11676/BbFBMDfkOhXBXtoUCp6RH1f
Obspack CH4 time-series result from Norunda (100.0 m)
No full textThis data file contains high accuracy European ObsPack observational timeseries in netCDF format of ambient mole fraction of ch4 in dry air collected at Norunda (100.0 m). The measurements were calibrated using the WMO GAW calibration scale WMO X2004A. Included are (all whenever available) historical PI QCed data, ICOS Level 2 data, ICOS FastTrack data and ICOS NRT data. It is part of the 2025.3 FastTrack update of the Globalview EU CH4 data product and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Metadata for the full ch4 product release are available at https://commons.datacite.org/doi.org/10.18160/3TB5-D6TM. Please also visit http://www.gml.noaa.gov/ccgg/obspack/ for more information. If you use these data in your research, please consider citing the full ObsPack release that this file is part of (https://commons.datacite.org/doi.org/10.18160/46ST-DEVK).
ICOS RI, Lehner, I., Molder, M. (2025). Obspack CH4 time-series result from Norunda (100.0 m), 2017-01-31–2025-10-02, European ObsPack, https://hdl.handle.net/11676/gc_RZMiBBWIgyR_sjKtJcN2
Obspack CO time-series result from Norunda (58.0 m)
No full textThis data file contains high accuracy European ObsPack observational timeseries in netCDF format of ambient mole fraction of co in dry air collected at Norunda (58.0 m). The measurements were calibrated using the WMO GAW calibration scale WMO X2014A. Included are (all whenever available) historical PI QCed data, ICOS Level 2 data, ICOS FastTrack data and ICOS NRT data. It is part of the 2025.3 FastTrack update of the Globalview EU CO data product and is intended for use in carbon cycle inverse modeling, model evaluation, and satellite validation studies. Metadata for the full co product release are available at https://commons.datacite.org/doi.org/10.18160/ZHZF-KXCQ. Please also visit http://www.gml.noaa.gov/ccgg/obspack/ for more information. If you use these data in your research, please consider citing the full ObsPack release that this file is part of (https://commons.datacite.org/doi.org/10.18160/46ST-DEVK).
ICOS RI, Lehner, I., Molder, M. (2025). Obspack CO time-series result from Norunda (58.0 m), 2017-04-01–2025-10-02, European ObsPack, https://hdl.handle.net/11676/kQhzHo9ulRbyUK3TDT-XfgY
Meteorological data from Erssjön, Floating platform
No full textAutomatic weather station data from locations within the distributed Swedish research infrastructure SITES. Check preview or file for the specific parameters included at this location. Data has been quality controlled and cleaned from outliers and other events producing unrealistic data. Gaps have not been filled.
Skogaryd Research Catchment (2025). Meteorological data from Erssjön, Floating platform, 2024 [Data set]. Swedish Infrastructure for Ecosystem Science (SITES). https://hdl.handle.net/11676.1/9tNJ7aaPkgcViNo01F02g0P
Nationell Riktad Skogsskadeinventering (NRS) - Barkborreskador på gran i Götaland och Svealand 2020
No full textInventories of forest damage are carried out within the Swedish University of Agricultural Sciences (SLU) Forests programme. An annual monitoring of the most important sources of forest damage is carried out by the Swedish National Forest inventory (NFI). Although the Swedish NFI is an objective and uniform inventory of forest damage in Swedish forests at national and regional scales, less common or less widespread occurrences of forests pests and pathogens are difficult to survey solely through large-scale monitoring programmes. There is a need for complementary inventories to facilitate timely delivery of relevant information.
Thus Target-tailored forest damage inventories (TFDI) aiming at providing data for operational decisions making at local level, and linked to specific damage events were introduced. TFDI’s are developed to give rapid response to requested information of specific damage outbreaks. The TFDIs are carried out in limited and concentrated samples, with flexible but robust methods and design. The data collected in the TFDI shall also be of such quality that it can be useful in research.
During 2020 TFDI carried out a sample inventory of the volume Norway spruce (Picea abies) damage by European spruce bark beetle (Ips typographus) in older spruce forest in the region of Götaland and Svealand excluding Gotland and Dalarna. This as a follow-up to the extremely hot and dry summer in 2018, which resulted in many drought stressed spruce trees that favored the spruce bark beetle. The spruce bark beetle populations, which were already high before, increased rapidly and have in recent years caused extensive damage to spruce in Götaland och Svealand. The inventory includes both standing infested trees as well as infested wind-felled trees and stumps from felled infested trees. The purpose of the inventory was to estimate the volume Norway spruce damage by the given bark beetles, but also to highlight geographical distribution and the appearance of the damage in different forest sites. The results from the inventory should be available for decisions making basis in forestry managements.
The inventory was stratified by an objective sample of all the National Forest Inventory permanent sample plots in Götaland and Svealand. Included plots within the sample was all older thinning forest and final felling mature forest consisting of at least 7/10 proportion of spruce. For the selection of plots LPM (local pivotal method, Grafström et al 2012) is used where the selection was spread based on the geographical position and the spruce volume of the sample plots. The radii of sample plots use for the damage inventory was 25 m, the area which was included for the described site. Other parts of the plot were not included in the inventory. The inventory only includes trees with fresh infestations (season 0) from infestations of the spruce bark beetle. Diameter at breast height was measured on damage trees and wind-felled trees. Diameter on stump from cut trees with fresh damage was measured. The dataset consist at plot level of 653 rows with 30 column, at tree level of 621 rows with 16 columns. The content and scope of the inventory has been developed in consultation with Swedish Forest Agency.
References:
Grafström, A., Lundström, N., & Schelin, L. (2012). Spatially Balanced Sampling through the Pivotal Method. Biometrics, 68(2), 514-520. Retrieved December 1, 2020, from https://doi.org/10.1111/j.1541-0420.2011.01699.x
Some assessed and used variables:
At sample plot level:
Plot area measured
The proportion of spruce at the sample plot
Maturity class
Number of infested trees
Logging
Sanitation
At tree level:
Is the tree dead or alive?
Position of tree – standing, wind-felled, stump
Diameter at breast height
Tree volume
See the document "Data_description" for more detailed information. As additional documentation, field instructions for the inventories are also provided, both for the specific inventory and for the National Forest Inventory (NFI). An English version of the National Forest Inventory field instruction is available for year 2021 only, which is why this is included here.Med hjälp av ett flexibelt inventeringskoncept inriktat på skogsskador kan Sveriges Lantbruksuniversitet (SLU) inom miljöanalysprogrammet Skog följa upp och presentera information om olika slags skogsskador. En årlig uppföljning av stora skadeutbrott i våra svenska skogar sker via Riksskogstaxeringens (RT) objektiva inventeringar. Men trots att vi här får en kontinuerlig uppföljning av de viktigaste skadesymptomen saknas ofta möjligheten att på ett lämpligt sätt följa upp regionala skadeutbrott.
Med fler förväntade skadeutbrott i klimatförändringarnas spår finns ett stigande behov av regional information med god precision. För att effektivisera övervakningen av skogsskador har Nationell Riktad Skogsskadeinventering (NRS) introducerats med skräddarsydda inventeringar riktade mot enskilda skadegörares utbrott. NRS ska kunna leverera underlag om en skadas status och omfattning, så att specifika operativa beslut kan fattas. Därför kan inriktningen av inventeringen variera beroende på vilka skador som för tillfället är mest relevanta och för vilka skador det finns uttalade behov av information. Inventeringen ska vara åtgärdsorienterad och snabbt kunna leverera resultat. Data som samlas in i NRS ska också vara av sådan kvalitet att de kan vara användbara inom forskningen.
Under 2020 har inom NRS genomförts en stickprovsinventering av volymen gran (Picea abies) angripen av granbarkborre (Ips typographus) i äldre granskog i Götaland exklusive Gotland och Svealand exklusive Dalarna. Detta som en uppföljning efter den extremt varma och torra sommaren 2018, vilket resulterade i många torkstressade granar som gynnade granbarkborren. Granbarkborrepopulationerna som redan innan var relativt höga ökade snabbt och har under senare år orsakat omfattande skador på gran i Götaland och Svealand. Inventeringen omfattar både stående angripna träd och vindfällen samt stubbar från avverkade angripna granar. Syftet med inventeringen var att skatta volym angripen gran, men också att belysa den geografiska fördelningen samt skadornas uppträdande på olika typer av mark och i olika typer av föryngringar. Resultaten från inventeringen ska kunna fungera som beslutsunderlag till möjliga skötselåtgärder.
Inventeringen stratifierades genom ett objektivt urval av Riksskogstaxeringens alla permanenta provytor i Götaland och Svealand. I urvalet ingick, alla ytor i äldre gallrings eller slutavverkningsmogen granskog (≥ 7/10 gran). För urval av ytor används LPM (local pivotal method, Grafström et al 2012) där urvalet spreds utifrån provytornas geografiska position och granvolym. Inventeringen utfördes på den del av en cirkelyta med 25 m radie, vars yta ingick i det beskrivna beståndet. Andra delar av cirkelytan ingick inte i inventeringen. På angripna stående träd och vindfällda träd har brösthöjdsdiameter uppmätts. På stubbar efter avverkade träd med färska angrepp har stubbdiameter uppmätts. Inventeringen omfattar enbart träd med färska angrepp (säsong 0) utav angrepp av granbarkborre. Totalt inventerades 653 provytor. Antalet inmätta angripna träd, vindfällen och stubbar var 621. Datafilerna innehåller på provytenivå 653 rader med 30 kolumner, på trädnivå 621 rader med 16 kolumner. Inventeringens innehåll och omfattning har tagits fram i samråd med Skogsstyrelsen.
Referenser:
Grafström, A., Lundström, N., & Schelin, L. (2012). Spatially Balanced Sampling through the Pivotal Method. Biometrics, 68(2), 514-520. Retrieved December 1, 2020, from https://doi.org/10.1111/j.1541-0420.2011.01699.x
Viktigaste inventerade bedömda variabler och beräknade variabler:
På ytnivå:
Inventerad areal
Grundytevägd granandel
Huggningsklass
Antal angripna träd
Avverkning
Sanering
På trädnivå:
Är trädet levande eller dött
Trädets position stående/vindfälle/stubbe
Brösthöjdsdiameter
Trädets volym
Se dokumentet "Databeskrivning" för mer detaljerad information. Som ytterligare dokumentation tillhandahålls också fältinstruktioner för inventeringarna, både för den specifika inventeringen och för Riksskogstaxeringen. En engelsk version av Riksskogstaxeringens fältinstruktion finns endast för år 2021 vilket är anledningen till att den är inkluderad här