This dataset is an artificial dataset of the dataset of the temporary trial plot in Neusorgefeld 5138 from the VERMOS project. The original dataset is significantly larger, the adaptation was made for a planned publication by Chris Wudel and was also carried out by him.

Abstract: These are results from a network of 65 tree census plots in Panama. At each, every individual stem in a rectangular area of specified size is given a unique number and identified to species, then stem diameter measured in one or more censuses. Data from these numerous plots and inventories were collected following the same methods as, and species identity harmonized with, the 50-ha long-term tree census at Barro Colorado Island. Precise location of every site, elevation, and estimated rainfall (for many sites) are also included. These data were gathered over many years, starting in 1994 and continuing to the present, by principal investigators R. Condit, R. Perez, S. Lao, and S. Aguilar. Funding has been provided by many organizations.

Description:

marenaRecent.full.Rdata5Jan2013.zip: A zip archive holding one R Analytical Table, a version of the Marena plots' census data in R format, designed for data analysis. This and all other tables labelled 'full' have one record per individual tree found in that census. Detailed documentations of the 'full' tables is given in RoutputFull.pdf (see component 10 below); an additional column 'plot' is included because the table includes records from many different locations. Plot coordinates are given in PanamaPlot.txt (component 12 below). This one file, 'marenaRecent.full1.rdata', has data from the latest census at 60 different plots. These are the best data to use if only a single plot census is needed. marena2cns.full.Rdata5Jan2013.zip: R Analytical Tables of the style 'full' for 44 plots with two censuses: 'marena2cns.full1.rdata' for the first census and 'marena2cns.full2.rdata' for the second census. These 44 plots are a subset of the 60 found in marenaRecent.full (component 1): the 44 that have been censused two or more times. These are the best data to use if two plot censuses are needed. marena3cns.full.Rdata5Jan2013.zip. R Analytical Tables of the style 'full' for nine plots with three censuses: 'marena3cns.full1.rdata' for the first census through 'marena2cns.full3.rdata' for the third census. These nine plots are a subset of the 44 found in marena2cns.full (component 2): the nine that have been censused three or more times. These are the best data to use if three plot censuses are needed. marena4cns.full.Rdata5Jan2013.zip. R Analytical Tables of the style 'full' for six plots with four censuses: 'marena4cns.full1.rdata' for the first census through 'marena4cns.full4.rdata' for the fourth census. These six plots are a subset of the nine found in marena3cns.full (component 3): the six that have been censused four or more times. These are the best data to use if four plot censuses are needed. marenaRecent.stem.Rdata5Jan2013.zip. A zip archive holding one R Analytical Table, a version of the Marena plots' census data in R format. These are designed for data analysis. This one file, 'marenaRecent.full1.rdata', has data from the latest census at 60 different plots. The table has one record per individual stem, necessary because some individual trees have more than one stem. Detailed documentations of these tables is given in RoutputFull.pdf (see component 11 below); an additional column 'plot' is included because the table includes records from many different locations. Plot coordinates are given in PanamaPlot.txt (component 12 below). These are the best data to use if only a single plot census is needed, and individual stems are desired. marena2cns.stem.Rdata5Jan2013.zip. R Analytical Tables of the style 'stem' for 44 plots with two censuses: 'marena2cns.stem1.rdata' for the first census and 'marena3cns.stem2.rdata' for the second census. These 44 plots are a subset of the 60 found in marenaRecent.stem (component 1): the 44 that have been censused two or more times. These are the best data to use if two plot censuses are needed, and individual stems are desired. marena3cns.stem.Rdata5Jan2013.zip. R Analytical Tables of the style 'stem' for nine plots with three censuses: 'marena3cns.stem1.rdata' for the first census through 'marena3cns.stem3.rdata' for the third census. These nine plots are a subset of the 44 found in marena2cns.stem (component 6): the nine that have been censused three or more times. These are the best data to use if three plot censuses are needed, and individual stems are desired. marena4cns.stem.Rdata5Jan2013.zip. R Analytical Tables of the style 'stem' for six plots with four censuses: 'marena3cns.stem1.rdata' for the first census through 'marena3cns.stem3.rdata' for the third census. These six plots are a subset of the nine found in marena3cns.stem (component 7): the six that have been censused four or more times. These are the best data to use if four plot censuses are needed, and individual stems are desired. bci.spptable.rdata. A list of the 1414 species found across all tree plots and inventories i... Visit https://dataone.org/datasets/urn%3Auuid%3A07030ed9-e51f-4ffa-a4b5-921392681123 for complete metadata about this dataset.

The LTERN Desert Uplands Plot Network Vegetation Survey data contains presence data, species richness data and structural data for 50 permanent 1 hectare plots in Northern Queensland, Australia. This package contains data collected in 2013, a subset of a much larger dataset stretching from 2004 to 2016. The CSIRO permanent plots are situated in Tropical Ironbark Woodlands, and extend across four leasehold cattle properties that lie within an area approximately 50 km by 50 km. The plots represent three vegetation management strategies, namely: 1) clearing (where all trees and shrubs are removed); 2) thinning (where ground and midstorey vegetation is removed); and 3) unmodified native woodlands where significant thinning or clearing has not occurred. The Desert Uplands research plots commenced in 2004, and have been revisited in 2005, 2006, 2008, 2013, 2014 and 2016. A synopsis of related data packages which have been collected as part of the Desert Uplands Plot Network’s full program is provided at http://www.ltern.org.au/index.php/ltern-plot-networks/desert-uplands

The LTERN Desert Uplands Plot Network Vegetation Survey Data contains presence data, species richness data and structural data for 1 of 60 (50 after 2008) permanent 1 hectare plots in Northern Queensland, Australia. This data publication refers specifically to observations made at Plot PENR08, and this data is accessible as a composite data package at the following location: Metcalfe, D; Vanderduys, E (2014): Desert Uplands Plot Network: Vegetation Survey (Presence Data, Species Richness and Stem and Hollow Counts), Northern Queensland, Australia, 2013. Long Term Ecological Research Network. http://www.ltern.org.au/knb/metacat/ltern2.143.33/html The CSIRO permanent plots are situated in Tropical Ironbark Woodlands, and extend across four leasehold cattle properties that lie within an area approximately 50km by 50km. The plots represent three vegetation management strategies, namely: 1) clearing (where all trees and shrubs are removed); 2) thinning (where ground and midstorey vegetation is removed); and 3) unmodified native woodlands where significant thinning or clearing has not occurred. The Desert Uplands research plots commenced in 2004, and have been revisited in 2005, 2006, 2008 and 2013. A synopsis of related data packages which have been collected as part of the Desert Uplands Plot Network’s full program is provided at http://www.ltern.org.au/index.php/ltern-plot-networks/desert-uplands

Yield data (diameter breast height and tree height) of a mixed stand in the Tharandt Forest, Germany. The data was collected for the establishment of a marteloscope site within the I+ network of the European Forest Institute.

R Analytical Tables: Tree and Stem These are 16 tables in R format, 8 tables in the tree format, one table per census, and 8 more in the stem format. They are named bci.tree1 through bci.tree8 and bci.stem1 through bci.stem8, with the number corresponding to a census. Every tree table includes a record for every tree appearing in the 50-ha plot across all censuses, with one row per tree and one table per census. Trees not yet censused and dead trees are included, allowing the fate of every tree to be tallied in every census. The rows in every tree table are in exactly the same order, so the 8 tree tables are effectively a single giant table, with columns for every one of the 8 censuses. They are divided into separate tables for easier access. Moreover, each individual census table is self-contained, and if a user needs only one census, then only that one census table is necessary. For most purposes the most recent, bci.tree8, should serve for a single census. The 8 stem tables form a parallel set having one row for every stem ever censused. In the tree tables, if stemID matches for a given tree in 2 censuses, then it is certain that the same stem was measured in both censuses. If the stemID differs between censuses, it often means that the first stem broke and a new stem was measured. However, in trees with 2 or more stems, it was not always possible to identify stems with certainty across censuses prior to 2010, because stem tags were not used. This means that there are cases where the stemID changes even though the stem(s) really did persist. The cleanest way to assess growth is to use only those cases where the stemID matches between censuses. It is also necessary to check the HOM (height-of-measurement) in case it changes between censuses. In the stem tables, records on matching rows are guaranteed to be the same stem, but the HOM might change. The 8 tree tables are zipped into the single file bci.tree.zip, and the 8 stem tables into bci.stem.zip. Columns in R Analytical Tables: Tree and Stem treeID: The unique tree identifier in the database. Guarantees a tree match. stemID: The unique stem identifier in the database. Guarantees a stem match. tag: Tag number on the tree (occasionally negative where a tag was duplicated by mistake). StemTag: Tag number on the individual stem, if present. sp: The species mnemonic. See the R Species Table for full Latin names. quadrat: Quadrat designation, as a 2-digit row number then 2-digit column number on a 20x20 m grid. gx: The x coordinate within the plot, meters from the west border of the plot, always in [0,1000). gy: The y coordinate, meters from the south border, always in [0,500). dbh: Diameter (mm) of one stem on the tree, the stem whose stemID is given. hom: The height-of-measure, meters above the ground, where the dbh was measured. ExactDate: The date on which a tree was measured. date: Integer date for easy calculation of time interval between censuses (the number of days since 1 Jan 1960). codes: The codes describing the measurement as recorded in the field. See Condit (1998) for a description of field codes. For analyses, status codes should be used, not field codes. status: A status code for the tree or stem. See the section below, Status Codes for Analyses. DFstatus: Alternate stem status, redundant relative to status. nostems: The number of living stems on the date of measurement. agb: Above-ground-biomass of all stems on the tree, in Mg (= metric tons), or for the individual stem. Note that agb=0 for dead trees. ba: Basal area of all stems on the tree, in square meters. Note that ba=0 for dead trees. Status Codes for Analyses These indicate whether a tree (stem) is alive (A) or dead (D), with some further complications. Status A=alive is assigned to a tree if it has any living stem or sprout. Status D=dead is only used when an entire tree is dead. A third status is P=prior, necessary because each of the analytical tables has a record for every tree (or stem). Thus, there must be records in early censuses for trees that recruited in later censuses, and these trees have status P. In a complete life cycle, a tree begins with status P, becomes A, then D; for many trees, the cycle includes only P to A, or A to D, or just A over all 8 censues. Additional status codes are necessary because a stem can be dead while the tree is still alive, and for rare cases where trees were missed during a census or recorded as dead once then later alive. Status Codes for Analyses (the status column in R Analytical Tables) A: Alive, applied to either the tree or stem. D: Dead, meaning the entire tree is dead, ie with no living stems or sprouts. P: Prior, applied to a tree (or stem) in censuses prior to its appearance in the plot. M: Missing, indicating that the tree was skipped by mistake during the census, so it could have been alive or dead. AD: A seldom-used code, applied when a tree was noted as d...

The dataset contains stem respiration (ppm) of 320 trees with DBH (Diameter at breast height) > 26 cm, measured with the EGM-4 (Environmental Gas Monitor for CO2). Data were collected on October 2019. In relation to the soil respiration dataset, it contains soil respiration (µmol CO2m-2 s-1) of different type of collars placed on the forest floor, and measured with the LI – 8100 A soil respiration system. Data were collected from June 2017 to October 2019. In both activities, leak tests were done before collections. All research was conducted in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. Full details about this dataset can be found at https://doi.org/10.5285/591e3708-7ff1-483b-9156-15c721c00daf

Description

SAFE Intensive Carbon Plots, part of the Global Ecosystem Monitoring (GEM) network, see http://gem.tropicalforests.ox.ac.uk/Stem respiration is measured on approximately 50 stems pre plot (typically two stems per subplot, but varies), using 11 cm diameter PVC collars glued on the stem at 140 cm height.The collars often fall or leak, or the trees die, so the number of measurements per day is almost always <50.The aim is to measure monthly, but in practice the measurement interval is almost always longer (problems with access, staffing and instruments)Data from late 2011 or early 2012, except from the two Danum plots (DC1 and DC2), which were set up in March 2015.The values represent the flux per unit stem area (not scaled to the whole tree).EGM-4 infrared CO2 analyser and SRC-1 respiration chamber (PP Systems).Chamber closure time is 124 seconds, CO2 concentration inside the chamber is recorded every 5 s. Flux is calculated from the linear change in concentration in the chamber headspace, and corrected for collar height (5 cm) and air temperature.The stem respiration data can be linked to other data (census, species, traits) collected from the same stems by the stem tag number.Constants for calculating fluxes 0.106 Collar diameter, m 0.008824734 Collar area, m2 0.05 Collar height, m 0.0012287 Chamber volume, incl. top part of the adapter (as in GEM manual) 0.000441237 Extra airspace of the collar, m3 0.001669937 Total chamber headspace, m3 101,325 pressure 8.314472 R 273.15 Temperature to Kelvins 12.01 Molar mass of carbon 2592000 seconds --> months pV=nRT ideal gas law n=pV/(RT) n=m/M mass mole m=n*M m=MpV/(RT)

Projects

This dataset was collected as part of the following projects:

https://safeproject.net/projects/project_view/113

Funding

These data were collected as part of research funded by:

Sime Darby Foundation (Grant , SAFE Core data )

European Research Council Advanced Investigator Grant, GEM-TRAIT (Grant , Grant number 321131 )

NERC Human-Modified Tropical Forests Programme: Biodiversity And Land-use Impacts on tropical ecosystem function (BALI) Project (Grant , NE/K016369/1 )

NERC standard grant: The multi-year impacts of the 2015/2016 El Niño on the carbon cycle of tropical forests worldwide (Grant , NE/P001092/1 )

HSBC Malaysia (Grant )

The University of Zurich (Grant )

This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.

Permits

These data were collected under permit from the following authorities:

Sabah Biodiversity Centre (SABC) ( Research licence JKM/MBs.1000-2/2 JLD.6 (76))

Files

This dataset consists of 1 file: SAFE_StemRespiration_SAFEdatabase_2024-07-22.xlsx

SAFE_StemRespiration_SAFEdatabase_2024-07-22.xlsx

This file contains dataset metadata and 1 data tables:

Stem respiration flux data

Worksheet: data

Description: Stem respiration flux data

Number of fields: 18

Number of data rows: 10414

ForestType: Old-growth or Logged (type: categorical)

SAFEPlotName: SAFE plot name, as in the SAFE Gazetteer (type: location)

Plot: Plot name used in field wrok (type: id)

ForestPlotsCode: Plot code in the ForestPlots database (this should be used in publications, instead of plot name). (type: id)

Date: Date of measurement (type: date)

Observers: Observers (type: comments)

Subplot: Subplot number within each plot, 1-25 (type: id)

StemTagNumber: Stem tag number (ID), unique within plot but NOT across plots (type: id)

EGM_RecordNumber: EGM record number in raw flux file (type: id)

AirT: Air temperature (type: numeric)

Remarks: Comments reguarding measurements. This includes collar quality, if measurements are repeated, or if tree is dead (type: comments)

Slope: Slope of the linear regression between time (seconds) from the chamber closure and CO2 concentration (parts per million, ppm) in the chamber headspace. (type: numeric)

AirT_Use: Air temperature (type: numeric)

Flux_g_C_m2ofStemArea_month: Flux corverted from ppm s-1 to Mg carbon per hectare per month. See conversion below. (type: numeric)

Quality: 1 - good flux; 0 - missing data or bad measurement; 2 - outlier (type: numeric)

Year: Year of measurement (type: id)

Month: Month of measurement (type: id)

Day: Day of measurement (type: id)

Extents

Date range: 2011-08-26 to 2019-09-11

Latitudinal extent: 4.5° to 5.07°

Longitudinal extent: 116.75° to 117.82°

Height and dry mass of all live and dead stems of Spartina alterniflora, along with flowering data, were determined from one plot and individual stem heights from two additional plots at three Louisiana salt marshes near LUMCON's DeFelice Marine Center in Cocodrie, LA. Stem heights were sampled from all three plots at each site monthly, but masses were determined from a single clipped plot at each site every other month (6 times per year) throughout the study period. This dataset is a continuation of datasets R1.x139.143:0053 (DOI: 10.7266/N72V2D1T) and R4.x264.000:0006 (DOI: 10.7266/N7TM7858) that covered 2013-2014 and 2015, respectively.

Abstract:The 50-hectare plot at Barro Colorado Island, Panama, is a 1000 meter by 500 meter rectangle of forest inside of which all woody trees and shrubs with stems at least 1 cm in stem diameter have been censused. Every individual tree in the 50 hectares was permanently numbered with an aluminum tag in 1982, and every individual has been revisited six times since (in 1985, 1990, 1995, 2000, 2005, and 2010). In each census, every tree was measured, mapped and identified to species. Details of the census method are presented in Condit (Tropical forest census plots: Methods and results from Barro Colorado Island, Panama and a comparison with other plots; Springer-Verlag, 1998), and a description of the seven-census results in Condit, Chisholm, and Hubbell (Thirty years of forest census at Barro Colorado and the Importance of Immigration in maintaining diversity; PLoS ONE, 7:e49826, 2012).Description:CITATION TO DATABASE: Condit, R., Lao, S., Pérez, R., Dolins, S.B., Foster, R.B. Hubbell, S.P. 2012. Barro Colorado Forest Census Plot Data, 2012 Version. DOI http://dx.doi.org/10.5479/data.bci.20130603 CO-AUTHORS: Stephen Hubbell and Richard Condit have been principal investigators of the project for over 30 years. They are fully responsible for the field methods and data quality. As such, both request that data users contact them and invite them to be co-authors on publications relying on the data. More recent versions of the data, often with important updates, can be requested directly from R. Condit (conditr@gmail.com). ACKNOWLEDGMENTS: The following should be acknowledged in publications for contributions to the 50-ha plot project: R. Foster as plot founder and the first botanist able to identify so many trees in a diverse forest; R. Pérez and S. Aguilar for species identification; S. Lao for data management; S. Dolins for database design; plus hundreds of field workers for the census work, now over 2 million tree measurements; the National Science Foundation, Smithsonian Tropical Research Institute, and MacArthur Foundation for the bulk of the financial support. File 1. RoutputFull.pdf: Detailed documentation of the 'full' tables in Rdata format (File 5). File 2. RoutputStem.pdf: Detailed documentation of the 'stem' tables in Rdata format (File 7). File 3. ViewFullTable.zip: A zip archive with a single ascii text file named ViewFullTable.txt holding a table with all census data from the BCI 50-ha plot. Each row is a single measurement of a single stem, with columns indicating the census, date, species name, plus tree and stem identifiers; all seven censuses are included. A full description of all columns in the table can be found at http://dx.doi.org/10.5479/data.bci.20130604 (ViewFullTable, pp. 21-22 of the pdf). File 4. ViewTax.txt: An ascii text table with information on all tree species recorded in the 50-ha plot. There are columns with taxonomics names (family, genus, species, and subspecies), plus the taxonomic authority. The column 'Mnemonic' gives a shortened code identifying each species, a code used in the R tables (Files 5, 7). The column 'IDLevel' indicates the depth to which the species is identified: if IDLevel='species', it is a fully identified, but if IDLevel='genus', the genus is known but not the species. IDLevel can also be 'family', or 'none' in case the species is not even known to family. File 5. bci.full.Rdata31Aug2012.zip: A zip archive holding seven R Analytical Tables, versions of the BCI 50 ha plot census data in R format. These are designed for data analysis. There are seven files, one for each of the 7 censuses: 'bci.full1.rdata' for the first census through 'bci.full7.rdata' for the seventh census. Each of the seven files is a table having one record per individual tree, and each includes a record for every tree found over the entire seven censuses (i.e. whether or not they were observed alive in the given census, there is a record). Detailed documentation of these tables is given in RoutputFull.pdf (File 1). File 6. bci.spptable.rdata: A list of the 1064 species found across all tree plots and inventories in Panama, in R format. This is a superset of species found in the BCI censuses: every BCI species is included, plus additional species never observed at BCI. The column 'sp' in this table is a code identifying the species in the R census tables (File 5, 7), and matching 'mnemomic' in ViewFullTable (File 3). File 7. bci.stem.Rdata31Aug2012.zip: A zip archive holding seven R Analytical Tables, versions of the BCI 50 ha plot census data in R format. These are designed for data analysis. There are seven files, one for each of the 7 censuses: 'bci.stem1.rdata' for the first census through 'bci.stem7.rdata' for the seventh census. Each of the seven files is a table having one record per individual stem, necessary because some individual trees have more than one stem. Each includes a record for every stem found over the entire seven censuses (i.e. whether or not they were observed alive in the given census, there is a record). Detailed documentation of these tables is given in RoutputStem.pdf (File 2). File 8. TSMAttributes.txt: An ascii text table giving full descriptions of measurement codes, which are also referred to as TSMCodes. These short codes are used in the column 'code' in R tables and in the column 'ListOfTSM' in ViewFullTable.txt, in both cases with individual codes separated by commas. File 9. bci_31August2012_mysql.zip: A zip archive holding one file, 'bci.sql', which is a mysqldump of the complete MySQL database (version 5.0.95, http://www.mysql.com) created 31 August 2012. The database includes data collected from seven censuses of the BCI 50 ha plot plus censuses of many additional plots elsewhere in Panama, plus transects where only species identifications were collected and trees were not tagged nor measurements made. Detailed documentation of all tables within the database can be found at (http://dx.doi.org/10.5479/data.bci.20130604). This version of the data is intended for experienced SQL users; for most, the R Analytical Tables in Rtables.zip are more useful.

Tree stem temperature is currently being collected to determine both diurnal and seasonal variation in tree stem temperatures for all species and sizes present at the Coweeta Watershed 27 Ridge Climate 77 Station Plot. The purpose of the data is to characterize the tree stem temperature regimes as they relate to tree stem respiration. Data will continue to be collected until approximately December 1997. Data will then be subsequently summarized and published.

This dataset includes measurements of soil respiration in 20 plots (250 x 10 m each) in the Brazilian Amazon. Study plots were distributed across a gradient of forest disturbance, including: undisturbed primary forests , logged primary forests, logged-and-burned primary forests, and secondary forests. Data were collected from January 2015 until November 2017. In December 2015, during the El Niño-mediated drought, eight of our study plots were affected by understory fires. Full details about this dataset can be found at https://doi.org/10.5285/e5f361b3-b434-4d11-9407-e5f48fe442b0

The LTERN Desert Uplands Plot Network Vegetation Survey Data contains presence data, species richness data and structural data for 1 of 60 (50 after 2008) permanent 1 hectare plots in Northern Queensland, Australia. This data publication refers specifically to observations made at Plot TIMA17, and this data is accessible as a composite data package at the following location: Metcalfe, D; Vanderduys, E (2014): Desert Uplands Plot Network: Vegetation Survey (Presence Data, Species Richness and Stem and Hollow Counts), Northern Queensland, Australia, 2013. Long Term Ecological Research Network. http://www.ltern.org.au/knb/metacat/ltern2.143.33/html The CSIRO permanent plots are situated in Tropical Ironbark Woodlands, and extend across four leasehold cattle properties that lie within an area approximately 50km by 50km. The plots represent three vegetation management strategies, namely: 1) clearing (where all trees and shrubs are removed); 2) thinning (where ground and midstorey vegetation is removed); and 3) unmodified native woodlands where significant thinning or clearing has not occurred. The Desert Uplands research plots commenced in 2004, and have been revisited in 2005, 2006, 2008 and 2013. A synopsis of related data packages which have been collected as part of the Desert Uplands Plot Network’s full program is provided at http://www.ltern.org.au/index.php/ltern-plot-networks/desert-uplands

Tree stem temperature is currently being collected to determine both diurnal and seasonal variation in tree stem temperatures for all species and sizes present at the Coweeta Watershed 2 Ridge Carbon Flux Plot. The purpose of the data is to characterize the tree stem temperature regimes as they relate to tree stem respiration. Data will continue to be collected until approximately December 1997. Data will then be subsequently summarized and published.

This data contains stem diameter, height measurement and above ground living biomass calculations for stems located in the Alice Mulga core 1ha plot, from 2014 - present.

This occurrence dataset provides primary data on repeated tree measurement of two inventories on the permanent sampling plot (8.8 ha) established in the old-growth polydominant broadleaved forest stand in the “Kaluzhskie Zaseki” State Nature Reserve (center of the European part of Russian Federation). The time span between the inventories was 30 years, and a total of more than 11 000 stems were included in the study (11 tree species and 3 genera). During the measurements, the tree species (for some trees only genus was determined), stem diameter at breast height of 1.3 m (DBH), and life status were recorded for every individual stem, and some additional attributes were determined for some trees. Field data were digitized and compiled into the PostgreSQL database. Deep data cleaning and validation (with documentation of changes) has been performed before data standardization according to the Darwin Core standard.

Представлены первичные данные двух перечетов деревьев, выполненных на постоянной пробной площади (8.8 га), заложенной в старовозрастном полидоминантном широколиственном лесу в заповеднике “Калужские засеки”. Перечеты выполнены с разницей в 30 лет, всего исследовано более 11 000 учетных единиц (деревья 11-ти видов и 3-х родов). Для каждой учетной единицы определяли вид, диаметр на высоте 1.3 м и статус, для части деревьев также измеряли дополнительные характеристики. Все полевые данные были оцифрованы и организованы в базу данных в среде PostgreSQL. Перед стандартизацией данных в соответствии с Darwin Core выполнена их тщательная проверка, все внесенные изменения документированы.

This graph shows the total stem cell research funding by the National Institutes for Health (NIH) from FY 2013 to FY 2025. In fiscal year 2015, stem cell research funding by the NIH was around 1.43 billion U.S. dollars. It is estimated that in FY 2024 it will reach 2.22 billion U.S. dollars.

The LTERN Desert Uplands Plot Network Vegetation Survey Data contains presence data, species richness data and structural data for 1 of 60 (50 after 2008) permanent 1 hectare plots in Northern Queensland, Australia. This data publication refers specifically to observations made at Plot WOUR12, and this data is accessible as a composite data package at the following location: Metcalfe, D; Vanderduys, E (2014): Desert Uplands Plot Network: Vegetation Survey (Presence Data, Species Richness and Stem and Hollow Counts), Northern Queensland, Australia, 2013. Long Term Ecological Research Network. http://www.ltern.org.au/knb/metacat/ltern2.143.33/html The CSIRO permanent plots are situated in Tropical Ironbark Woodlands, and extend across four leasehold cattle properties that lie within an area approximately 50km by 50km. The plots represent three vegetation management strategies, namely: 1) clearing (where all trees and shrubs are removed); 2) thinning (where ground and midstorey vegetation is removed); and 3) unmodified native woodlands where significant thinning or clearing has not occurred. The Desert Uplands research plots commenced in 2004, and have been revisited in 2005, 2006, 2008 and 2013. A synopsis of related data packages which have been collected as part of the Desert Uplands Plot Network’s full program is provided at http://www.ltern.org.au/index.php/ltern-plot-networks/desert-uplands