Functional traits and related environmental variables of 28 populations of Nuphar lutea
Data files
Nov 29, 2023 version files 85.21 KB
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Dalla_Vecchia_Nuphar_lutea_data.xlsx
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README.md
Abstract
This dataset includes 31 leaf functional traits, 2 genetic diversity metrics and 4 leaf reflectance measures on 28 wild populations of yellow water lily (Nuphar lutea). For each population (plot) coordinates, water depth, specific conductivity, nitrate, sediment organic matter and sediment total phosphorus contents are provided as well. The populations were located in 4 different lake systems in central and northern Italy. All the information on the methodology used to collect the data and can be found in the related paper.
README: Functional traits and related environmental variables of 28 populations of Nuphar lutea
https://doi.org/10.5061/dryad.wdbrv15vv
Description of the data and file structure
This dataset includes 31 leaf functional traits, 2 genetic diversity metrics and 4 leaf reflectance measures on 28 wild populations of yellow water lily (Nuphar lutea). For each population (plot) coordinates, water depth, specific conductivity, nitrate, sediment organic matter and sediment total phosphorus contents are provided as well. The populations were located in 4 different lake systems in central and northern Italy. The dataset includes a legend sheet with information on single traits and environmental variables, including units of measurement.
Structural traits (area, fresh and dry weight, dry matter content and specific area) were measured on 5 leaves from different individuals, while leaf pigments and phosphorus content were measured on 3 additional leaves. On each of these 8 leaves, reflectance spectra were measured and genetic analyses were performed. Therefore, in a plot each reflectance measure is coupled with the leaf traits on the same row. There is one value for each genetic diversity metric per plot as they are derived from the 8 leaves and refer to the genetic diversity within plot. Therefore, the missing values in the dataset derive from the sampling design of the study. Genetic analyses confirmed that all leaves were collected from different individuals.
All further information on the methodology used to collect the data and can be found in the related paper.