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  • PlantHub workflows
  • Dataset pre-processing
    • TRY - A database of plant functional traits
      • Batch pre-processing of categorical data from TRY
      • Prepare Dispersal syndrome data from TRY for use
      • Prepare Dispersal unit type data from TRY for use
      • Prepare Flower color data from TRY for use
      • Prepare Flower sex data from TRY for use
      • Prepare Fruit dehiscence type data from TRY for use
      • Prepare Fruit type data from TRY for use
      • Prepare Inflorescence type data from TRY for use
      • Prepare Leaf compoundness data from TRY for use
      • Prepare Leaf distribution along the shoot axis (arrangement type) data from TRY for use
      • Prepare Leaf margin type data from TRY for use
      • Prepare Leaf phenology type data from TRY for use
      • Prepare Leaf shape data from TRY for use
      • Prepare Leaf type data from TRY for use
      • Prepare Leaf venation type data from TRY for use
      • Prepare Leaflet number per leaf data from TRY for use
      • Prepare Mycorrhiza type data from TRY for use
      • Prepare Photosynthesis pathway data from TRY for use
      • Prepare Plant functional type (PFT) data from TRY for use
      • Prepare Plant growth form data from TRY for use
      • Prepare Plant growth rate data from TRY for use
      • Prepare Plant life form data from TRY for use
      • Prepare Plant life span (longevity) data from TRY for use
      • Prepare Plant nitrogen(N) fixation capacity data from TRY for use
      • Prepare Plant reproductive phenology timing (flowering time) data from TRY for use
      • Prepare Plant resprouting capacity data from TRY for use
      • Prepare Plant woodiness data from TRY for use
      • Prepare Pollination syndrome data from TRY for use
      • Prepare Root type, root architecture data from TRY for use
      • Prepare Seed storage behaviour data from TRY for use
      • Prepare Species genotype chromosome ploidy data from TRY for use
      • Prepare Species habitat characterization data from TRY for use
      • Prepare Species occurrence range: climate type data from TRY for use
      • Prepare Species occurrence range: native vs invasive data from TRY for use
      • Prepare Species tolerance to fire data from TRY for use
      • Prepare Species tolerance to frost data from TRY for use
      • Prepare Wood fibre types data from TRY for use
      • Prepare Wood growth ring distinction data from TRY for use
      • Prepare Wood vessel perforation plates data from TRY for use
    • sPlot - A global database on vegetation surveys
    • PhenObs - Phenological observations in botanical gardens
    • GloNAF - A global database of naturalized and alien flora
    • Taxonomic name resolution - gfö NFDI workshop at the gfö Macroecology meeting 2024
      • Taxonomic name parsing
      • Taxonomic name resolution
      • Vernacular name matching
  • Data cleaning, manipulation, visualization, and R library cheatsheets
    • Data cleaning
      • Outlier removal using normal distributions
    • Data manipulation
      • Digitize data from images
      • Image metadata editing
      • Microsoft PowerPoint - set font and language for a whole presentation
    • Data visualization
      • Create Digital Elevation Models using regional data
    • R library cheatsheets
      • RSelenium - Automating the control of web browsers
      • data.table - An extremely fast R library for basic dataset handling
  • Workflows from published studies
    • Citizen science observations encode global trait patterns
      • Preprocessing iNaturalist data
      • Packages
      • Link iNaturalist observations to TRY
      • sPlotOpen Preprocessing
      • Make trait maps
      • Compare sPlotOpen and iNaturalist trait maps
      • Density vs. Difference
      • Compare sPlotOpen to published trait maps
      • Compare sPlotOpen to published trait maps
      • Density of observations/plots in climate space
      • Differences among biomes
      • Growth forms coverage
      • Aggregate iNaturalist data in buffers around sPlot plots
      • Calculate correlation of sPlot CWM and iNaturalist averages
      • Comparing iNaturalist to Schiller maps
  • .md

Data manipulation

Contents

  • Contents

Data manipulation#

Contents#

Digitize data from images
Image metadata editing
Microsoft PowerPoint - set font and language for a whole presentation

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Outlier removal using normal distributions

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Digitize data from images
Contents
  • Contents

By David Schellenberger Costa, Sophie Wolf

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