Using seed morphological traits to predict early performance using pelletized seed enhancement technologies in restoration practice
  • Description

    Manuscript, data, and code associated with a germination experiment using seed enhancement technologies in New South Wales, Australia. Two scripts provided for use in R 1. 'treatment_comparisons.txt' details treatment-wise comparisons of emergence, survival, and average time to emergence between treatments (1) bare seed and (2) pelletised replicates of native species 2. 'trait_script.txt' details comparisons of seed morphological traits as predictors of species performance using pellets Three major dataframes provided: Emergence_data.csv - raw emergence data from the experiment seed_traits_no_se.csv - average seed morphological trait information from x-ray images emergence_traits.csv- emergence speed data from species in the experiment Three supporting dataframes provided: Amenability.csv - characterised amenability results_bin.csv - dataframe based on treatment models to use in plotting results pairwise_letters.csv - dataframe based on treatment models to use in plotting results


    • Data publication title Using seed morphological traits to predict early performance using pelletized seed enhancement technologies in restoration practice
    • Description

      Manuscript, data, and code associated with a germination experiment using seed enhancement technologies in New South Wales, Australia. Two scripts provided for use in R 1. 'treatment_comparisons.txt' details treatment-wise comparisons of emergence, survival, and average time to emergence between treatments (1) bare seed and (2) pelletised replicates of native species 2. 'trait_script.txt' details comparisons of seed morphological traits as predictors of species performance using pellets Three major dataframes provided: Emergence_data.csv - raw emergence data from the experiment seed_traits_no_se.csv - average seed morphological trait information from x-ray images emergence_traits.csv- emergence speed data from species in the experiment Three supporting dataframes provided: Amenability.csv - characterised amenability results_bin.csv - dataframe based on treatment models to use in plotting results pairwise_letters.csv - dataframe based on treatment models to use in plotting results


    • Data type dataset
    • Keywords
      • germination biology
      • nature repair
      • plant conservation
      • seed handling
      • seed science
      • seed-based restoration
      • trait ecology
      • Hawkesbury Institute for the Environment
    • Funding source
      • Australian Research Council LP 200200688
    • Grant number(s)
      • -
    • FoR codes
      SEO codes
      Temporal (time) coverage
    • Start date
    • End date
    • Time period
       
      Spatial (location,mapping) coverage
    • Locations
      Data Locations

      Type Location Notes
      URL https://osf.io/5wc4q/
      The Data Manager is: Samantha Andres
      Access conditions Open
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      Citation Andres, Samantha; Lieurance, Paige; Mills , Charlotte H. ; Tetu, Sasha G. ; Gallagher, Rachael (2024): Using seed morphological traits to predict early performance using pelletized seed enhancement technologies in restoration practice. OSF. https://doi.org/10.17605/OSF.IO/5WC4Q