The dataset includes twenty-two permanent plot data (30 ha in total) from species-rich forest ecosystems in south china. Data from the fully mapped plots includes all live trees larger than 1 cm, and each individual tree was tagged, numbered, mapped and their species and diameters at breast height (measured at 1.3 m above ground level; dbh) were recorded.

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 in Panama, in R format. The column 'sp' in this table is a code identifying the species in the full census tables (marena.full and marena.stem, components 1-4 and 5-8 above). RoutputFull.pdf: Detailed documentation of the 'full' tables in Rdata format (components 1-4 above). RoutputStem.pdf: Detailed documentation of the 'stem' tables in Rdata format (component 5-8 above). PanamaPlot.txt: Locations of all tree plots and inventories in Panama.

This data set of leaf, stem, and root biomass for various plant taxa was compiled from the primary literature of the 20th century with a significant portion derived from Cannell (1982). Recent allometric additions include measurements made by Niklas and colleagues (Niklas, 2003). This is a unique data set with which to evaluate allometric patterns of standing biomass within and across the broad spectrum of vascular plant species. Despite its importance to ecology, global climate research, and evolutionary and ecological theory, the general principles underlying how plant metabolic production is allocated to above- and below-ground biomass remain unclear. The resulting uncertainty severely limits the accuracy of models for many ecologically and evolutionarily important phenomena across taxonomically diverse communities. Thus, although quantitative assessments of biomass allocation patterns are central to biology, theoretical or empirical assessments of these patterns remain contentious.

The Biomass Plot Library is a collation of stem inventory data across federal, state and local government departments, universities, private companies and other agencies. It was motivated by the need for calibration/validation data to underpin national mapping of above-ground biomass from integration of Landsat time-series, ICESat/GLAS lidar, and ALOS PALSAR bacscatter data under the auspices of the JAXA Kyoto & Carbon (K&C) Initiative (Armston et al., 2016). At the time of Version 1.0 publication 1,073,837 hugs of 839,866 trees across 1,467 species had been collated. This has resulted from 16,391 visits to 12,663 sites across most of Australia's bioregions. Data provided for each project by the various source organisation were imported to a PostGIS database in their native form and then translated to a common set of tree, plot and site level observations with explicit plot footprints where available. Data can be downloaded from https://field.jrsrp.com/ by selecting the combinations Tree biomass and Site Level, Tree Biomass and Tree Level.

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.

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.

The LTERN Tropical Rainforest Plot Network Rainforest Tree Demographic Data contains stem measurement data for 1 of 20, 0.5 ha (100 m x 50 m) permanent rainforest plots in Northern Queensland, Australia from 2011 to 2013.

This is part of a much larger dataset that spans from 1971 to 2013 that is managed by CSIRO. This data publication refers specifically to observations made at Plot EP30, and this data is accessible as a composite data package at the following location:

Metcalfe, D; Murphy, H; Bradford, M; Hogan, D; Ford, A (2014): Tropical Rainforest Plot Network: Rainforest Tree Demographic Data, Northern Queensland, Australia, 2011-2013. Long Term Ecological Research Network. http://www.ltern.org.au/knb/metacat/ltern2.90.42/html

The CSIRO permanent rainforest plots are located within 60 km of the north Queensland coast between Mackay (21.5ºS, 149ºE) and the Iron Range on Cape York Peninsula (12.5ºS, 143ºE). The plots have a rainfall range of 1200 to 3500 mm, represent eleven vegetation types, six parent materials, and range from 15 m to 1200 m above sea level. Except for minor disturbances associated with selective logging on two plots, the plots were established in old growth forest and all plots have thereafter been protected. Plots were regularly censused and at each census the diameter at breast height (DBH) of all stems ≥10 cm DBH is recorded. Due to the wide geographical range of the plots, no species dominate, although the families Lauraceae, Rutaceae and Myrtaceae contribute a large number of species. The data collected from the 20 plots provides an insight into the floristical composition, structure and long term forest dynamics of Australian tropical rainforests and allows direct comparisons to be made with long-term monitoring plots at a global scale (Bradford, M.G., Murphy, H.T., Ford, A.J., Hogan, D. and Metcalfe, D.J. (2014). Long term stem inventory data from tropical rainforest plots in Australia. Ecology 95:2362. https://rainforest-crc.jcu.edu.au/publications/permanent_plots1.pdf. This is part of a much larger dataset that spans from 2004 to 2014; a synopsis of related data packages which have been collected as part of the Tropical Rainforest Plot Network’s full program is provided at http://www.ltern.org.au/index.php/ltern-plot-networks/tropical-rainforest.

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.

Multi-Agency Ground Plot (MAGPlot) database (DB) is a pan-Canadian forest ground-plot data repository. The database synthesize forest ground plot data from various agencies, including the National Forest Inventory (NFI) and 12 Canadian jurisdictions: Alberta (AB), British Columbia (BC), Manitoba (MB), New Brunswick (NB), Newfoundland and Labrador (NL), Nova Scotia (NS), Northwest Territories (NT), Ontario (ON), Prince Edward Island (PE), Quebec (QC), Saskatchewan (SK), and Yukon Territory (YT), contributed in their original format. These datasets underwent data cleaning and quality assessment using the set of rules and standards set by the contributors and associated documentations, and were standardized, harmonized, and integrated into a single, centralized, and analysis-ready database. The primary objective of the MAGPlot project is to collate and harmonize forest ground plot data and to present the data in a findable, accessible, interoperable, and reusable (FAIR) format for pan-Canadian forest research. The current version includes both historical and contemporary forest ground plot data provided by data contributors. The standardized and harmonized dataset includes eight data tables (five site related and three tree measurement tables) in a relational database schema. Site-related tables contain information on geographical locations, treatments (e.g. stand tending, regeneration, and cutting), and disturbances caused by abiotic factors (e.g., weather, wildfires) or biotic factors (e.g., disease, insects, animals). Tree-related tables, on the other hand, focus on measured tree attributes, including biophysical and growth parameters (e.g., DBH, height, crown class), species, status, stem conditions (e.g., broken or dead tops), and health conditions. While most contributors provided large and small tree plot measurements, only NFI, AB, MB, and SK contributed datasets reported at regeneration plot level (e.g., stem count, regeneration species). Future versions are expected to include updated and/or new measurement records as well as additional tables and measured and compiled (e.g., tree volume and biomass) attributes. MAGPlot is hosted through Canada’s National Forest Information System (https://nfi.nfis.org/en/maps). --------------------------------------------------- LATEST SITE TREATMENTS LAYER: --------------------------------------------------- Shows the most recently applied treatment class for each MAGPlot site. These treatment classes are broad categories, with more specific treatment details available in the full dataset. ----------- NOTES: ----------- The MAGPlot release (v1.0 and v1.1) does not include NL and SK datasets due to pending Data Sharing Agreements, ongoing data processing, or restrictions on third-party sharing. These datasets will be included in future releases. While certain jurisdictions permit open or public data sharing, given that requestor signs and adheres the Data Use agreement, there are some jurisdictions that require a jurisdiction-specific request form to be signed in addition to the Data Use Agreement form. For the MAGPlot Data Dictionary, other metadata, datasets available for open sharing (with approximate locations), data requests (for other datasets or exact coordinates), and available data visualization products, please check all the folders in the “Data and Resources” section below. Coordinates in web services have been randomized within 5km of true location to preserve site integrity Access the WMS (Web Map Service) layers from the “Data and Resources” section below. A data request must be submitted to access historical datasets, datasets restricted by data-use agreements, or exact plot coordinates using the link below. NFI Data Request Form: https://nfi.nfis.org/en/datarequestform --------------------------------- ACKNOWLEDGEMENT: --------------------------------- We acknowledge and recognize the following agencies that have contributed data to the MAGPlot database: Government of Alberta - Ministry of Agriculture, Forestry, and Rural Economic Development - Forest Stewardship and Trade Branch Government of British Columbia - Ministry of Forests - Forest Analysis and Inventory Branch Government of Manitoba - Ministry of Economic, Development, Investment, Trade, and Natural Resources - Forestry and Peatlands Branch Government of New Brunswick - Ministry of Natural Resources and Energy Development - Forestry Division, Forest Planning and Stewardship Branch Government of Newfoundland & Labrador - Department of Fisheries, Forestry and Agriculture - Forestry Branch Government of Nova Scotia - Ministry of Natural Resources and Renewables - Department of Natural Resources and Renewables Government of Northwest Territories - Department of Environment & Climate Change - Forest Management Division Government of Ontario - Ministry of Natural Resources and Forestry - Science and Research Branch, Forest Resources Inventory Unit Government of Prince Edward Island - Department of Environment, Energy, and Climate Action - Forests, Fish, and Wildlife Division Government of Quebec - Ministry of Natural Resources and Forests - Forestry Sector Government of Saskatchewan - Ministry of Environment - Forest Service Branch Government of Yukon - Ministry of Energy, Mines, and Resources - Forest Management Branch Government of Canada - Natural Resources Canada - Canadian Forest Service - National Forest Inventory Projects Office

File List CSIRO_permanent_plots.zip (MD5: 05f273b3cf0c52a747bd64f383f8f3a4) CSIRO_Permanent_Rainforest_Plots_of_North_Queensland.html

  Description
    We present repeated stem measurement data from 20 0.5-ha (100 × 50 m) permanent rain forest plots in northern Queensland, Australia from 1971 to 2013. The plots have a rainfall range of 1200 to 3500 mm, represent 11 vegetation types, six parent materials, and range from 15 to 1200 m above sea level. Except for minor disturbances associated with selective logging on two plots, the plots were established in old growth forest and all plots have thereafter been protected. Plots were regularly censused and at each census the diameter at breast height (DBH) of all stems ≥10 cm DBH were recorded. Data is presented for 10998 individual stems with plot stem densities at establishment ranging from 476 to 1104 stems/ha. Due to the wide geographical range of the plots, no species dominate, although the families Lauraceae, Rutaceae, and Myrtaceae contribute a large number of species. Basal area values at establishment ranged from 28.6 to 63.3 m²/ha and showed no trend of increasing or decreasing over time due mainly to regular disturbance and recovery from natural events such as cyclones. In addition to stems ≥10 cm DBH data, we present height data, floristic data from understory stems (≥50 cm height to

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.

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.

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 18 Cove 218 Gradient 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.

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 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 **** billion U.S. dollars. It is estimated that in FY 2024 it will reach **** billion U.S. dollars.

This dataset contains all the data and code needed to reproduce the analyses in the manuscript: Penn, H. J., & Read, Q. D. (2023). Stem borer herbivory dependent on interactions of sugarcane variety, associated traits, and presence of prior borer damage. Pest Management Science. https://doi.org/10.1002/ps.7843 Included are two .Rmd notebooks containing all code required to reproduce the analyses in the manuscript, two .html file of rendered notebook output, three .csv data files that are loaded and analyzed, and a .zip file of intermediate R objects that are generated during the model fitting and variable selection process. Notebook files

01_boring_analysis.Rmd: This RMarkdown notebook contains R code to read and process the raw data, create exploratory data visualizations and tables, fit a Bayesian generalized linear mixed model, extract output from the statistical model, and create graphs and tables summarizing the model output including marginal means for different varieties and contrasts between crop years. 02_trait_covariate_analysis.Rmd: This RMarkdown notebook contains R code to read raw variety-level trait data, perform feature selection based on correlations between traits, fit another generalized linear mixed model using traits as predictors, and create graphs and tables from that model output including marginal means by categorical trait and marginal trends by continuous trait.

HTML files These HTML files contain the rendered output of the two RMarkdown notebooks. They were generated by Quentin Read on 2023-08-30 and 2023-08-15.

01_boring_analysis.html 02_trait_covariate_analysis.html

CSV data files These files contain the raw data. To recreate the notebook output the CSV files should be at the file path project/data/ relative to where the notebook is run. Columns are described below.

BoredInternodes_26April2022_no format.csv: primary data file with sugarcane borer (SCB) damage

Columns A-C are the year, date, and location. All location values are the same. Column D identifies which experiment the data point was collected from. Column E, Stubble, indicates the crop year (plant cane or first stubble) Column F indicates the variety Column G indicates the plot (integer ID) Column H indicates the stalk within each plot (integer ID) Column I, # Internodes, indicates how many internodes were on the stalk Columns J-AM are numbered 1-30 and indicate whether SCB damage was observed on that internode (0 if no, 1 if yes, blank cell if that internode was not present on the stalk) Column AN indicates the experimental treatment for those rows that are part of a manipulative experiment Column AO contains notes

variety_lookup.csv: summary information for the 16 varieties analyzed in this study

Column A is the variety name Column B is the total number of stalks assessed for SCB damage for that variety across all years Column C is the number of years that variety is present in the data Column D, Stubble, indicates which crop years were sampled for that variety ("PC" if only plant cane, "PC, 1S" if there are data for both plant cane and first stubble crop years) Column E, SCB resistance, is a categorical designation with four values: susceptible, moderately susceptible, moderately resistant, resistant Column F is the literature reference for the SCB resistance value

Select_variety_traits_12Dec2022.csv: variety-level traits for the 16 varieties analyzed in this study

Column A is the variety name Column B is the SCB resistance designation as an integer Column C is the categorical SCB resistance designation (see above) Columns D-I are continuous traits from year 1 (plant cane), including sugar (Mg/ha), biomass or aboveground cane production (Mg/ha), TRS or theoretically recoverable sugar (g/kg), stalk weight of individual stalks (kg), stalk population density (stalks/ha), and fiber content of stalk (percent). Columns J-O are the same continuous traits from year 2 (first stubble) Columns P-V are categorical traits (in some cases continuous traits binned into categories): maturity timing, amount of stalk wax, amount of leaf sheath wax, amount of leaf sheath hair, tightness of leaf sheath, whether leaf sheath becomes necrotic with age, and amount of collar hair.

ZIP file of intermediate R objects To recreate the notebook output without having to run computationally intensive steps, unzip the archive. The fitted model objects should be at the file path project/ relative to where the notebook is run.

intermediate_R_objects.zip: This file contains intermediate R objects that are generated during the model fitting and variable selection process. You may use the R objects in the .zip file if you would like to reproduce final output including figures and tables without having to refit the computationally intensive statistical models.

binom_fit_intxns_updated_only5yrs.rds: fitted brms model object for the main statistical model binom_fit_reduced.rds: fitted brms model object for the trait covariate analysis marginal_trends.RData: calculated values of the estimated marginal trends with respect to year and previous damage marginal_trend_trs.rds: calculated values of the estimated marginal trend with respect to TRS marginal_trend_fib.rds: calculated values of the estimated marginal trend with respect to fiber content Resources in this dataset:Resource Title: Sugarcane borer damage data by internode, 1993-2021. File Name: BoredInternodes_26April2022_no format.csvResource Title: Summary information for the 16 sugarcane varieties analyzed. File Name: variety_lookup.csvResource Title: Variety-level traits for the 16 sugarcane varieties analyzed. File Name: Select_variety_traits_12Dec2022.csvResource Title: RMarkdown notebook 2: trait covariate analysis. File Name: 02_trait_covariate_analysis.RmdResource Title: Rendered HTML output of notebook 2. File Name: 02_trait_covariate_analysis.htmlResource Title: RMarkdown notebook 1: main analysis. File Name: 01_boring_analysis.RmdResource Title: Rendered HTML output of notebook 1. File Name: 01_boring_analysis.htmlResource Title: Intermediate R objects. File Name: intermediate_R_objects.zip

The purpose of the SNF study was to improve our understanding of the relationship between remotely sensed observations and important biophysical parameters in the boreal forest. A key element of the experiment was the development of methodologies to measure forest stand characteristics to determine values of importance to both remote sensing and ecology. Parameters studied were biomass, leaf area index, above ground net primary productivity, bark area index and ground coverage by vegetation. Thirty two quaking aspen and thirty one black spruce sites were studied. Sites were chosen in uniform stands of aspen or spruce. The dominant species in the site constituted over 80 percent, and usually over 95 percent, of the total tree density and basal area. Aspen stands were chosen to represent the full range of age and stem density of essentially pure aspen, of nearly complete canopy closure, and greater than two meters in height. Spruce stands ranged from very sparse stands on bog sites, to dense, closed stands on more productive peatlands. Use of multiple plots within each site allowed estimation of the importance of spatial variation in stand parameters. Within each plot, all woody stems greater than two meters in height were recorded by species and the following dimensions were measured: diameter breast height, height of the tree, height of the first live branch, and depth of crown. For each plot, a two meter diameter subplot was defined at the center of each plot. Within this subplot, the percent of ground coverage by plants under one meter in height was determined by species. These data, averaged for the five plots in each site, are presented in the SNF Forest Understory Cover Data (Table) data set in tabular format, e.g. plant species with a count for that species at each site. The same data are presented in this data set (i.e., SNF Forest Understory Cover Data) but are arranged with a row for each species and site and a percent ground coverage for each combination.

Bahrain Exports of cloves (whole fruit, cloves and stems) to Iraq was US$1.06 Thousand during 2023, according to the United Nations COMTRADE database on international trade. Bahrain Exports of cloves (whole fruit, cloves and stems) to Iraq - data, historical chart and statistics - was last updated on November of 2025.

This dataset includes measurements of stem radial growth 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 December 2014 until October 2018. 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/c8bc6982-d4de-4e6f-aadb-08aac877b263