DOI: 10.5061/dryad.gf1vhhn0n
title: Data From: Hyperspectral leaf reflectance of grasses varies with evolutionary lineage more than with site

description: Understanding whether spectra-trait relationships are specific to
 photosynthetic pathway (C3 or C4), grass lineages (tribes or subfamily),
 or across-site environmental differences is important for using
 hyperspectral reflectance to predict plant responses to environmental
 changes across large landscapes. This dataset includes (a)
 leaf-level reflectance spectra from grass species from five
 grass-dominated National Ecological Observatory Network (NEON) and/or
 Long-term Ecological Research (LTER) sites in North America, and (b)
 structural, biochemical, and physiological leaf traits for many of these
 same grass species. 
description: # Hyperspectral leaf reflectance of grasses varies with evolutionary
 lineage more than with site Dataset DOI:
 [10.5061/dryad.gf1vhhn0n](10.5061/dryad.gf1vhhn0n) ## Description of the
 data and file structure Data for the manuscript titled "Hyperspectral
 leaf reflectance of grasses varies with evolutionary lineage more than
 with site," by Pau et. al., from the journal *Ecosphere.* ### Files
 and variables #### File: GrassSpecies-Traits.csv **Description:** 12
 Structural, Biochemical, and Physiological Traits for Grass Species across
 Sites. Please refer to methods section of paper for full description of
 plant functional traits. A cell value of "null" indicates that a
 measurement could not be obtained. ##### Variables * Site: CPER (Colorado
 Plains Experimental Range), KONZ (Konza Prairie Biological Station), WOOD
 (Chase Lake National Wildlife Refuge), Jornada (Jornada Experimental
 Range), CDCR (Cedar Creek Ecosystem Science Reserve) * Species: binomial
 Latin nomenclature * Transect: * Subfamily: subfamily * Tribe: tribe *
 LFT: Lineage functional types that break out Andropogoneae from the
 subfamily Panicoideae * Photosynthetic Pathway: C3 or C4 * Replicate:
 replicate * Leaf_Area (cm2): leaf area  * Fresh_Thickness (cm): fresh leaf
 thickness, thickness of leaf in field conditions * Wet_Thickness (cm): wet
 leaf thickness, thickness of leaf when fully hydrated * Wet_Mass (g): leaf
 wet mass * Dry_Mass (g): leaf dry mass * SLA (cm2 g-1): specific leaf area
 = ratio of leaf area to leaf dry mass * LDMC: Leaf dry matter content =
 ratio of leaf dry mass to leaf wet mass * %C: leaf percent Carbon * %N:
 leaf percent Nitrogen * \_N15: isotopic ratio of Nitrogen-15 to
 Nitrogen-14 * \_C13: isotopic ratio of Carbon-13 to Carbon-12  * C:N:
 ratio of carbon to nitrogen in the leaf * Vcmax25 (_mol m_2 s_1): maximum
 rate of carboxylation of the enzyme Rubisco * Jmax25 (_mol electrons):
 maximum rate of electron transport during light reactions of
 photosynthesis #### File: GrassSpecies-Spectra.csv
 **Description:** Spectral (reflectance) Measurements for Grass Species
 across Sites. ##### Variables * SPECIES: binomial Latin nomenclature *
 SITE: CPER (Colorado Plains Experimental Range), KONZ (Konza Prairie
 Biological Station), WOOD (Chase Lake National Wildlife Refuge), Jornada
 (Jornada Experimental Range), CDCR (Cedar Creek Ecosystem Science Reserve)
 * C4_C3: Photosynthetic Pathway (C3 or C4) * LFT: Lineage functional types
 that break out Andropogoneae from the subfamily Panicoideae * SUBFAM:
 subfamily * TRIBE: tribe * X1 - X2001: reflectance values from 400nm to
 2400nm, every 1nm ## Code/software The code and software listed below are
 described in detail in the manuscript methods. In summary, we used: * the
 "hsdar" package (Lehnert et al. 2019) in R (R Core Team 2022) to
 analyze spectral data. - the "plantecophys" package (Duursma
 2015) in R (R Core Team 2022) to fit A-Ci curves and to correct Vcmax25
 and Jmax25 to a standard temperature of 25C. * the "vegan"
 package (Oksanen et al. 2019; version 2), including the functions
 "varpart" and "rda," in R (R Core Team 2022) to
 analyze the relative effects of tribe, photosynthetic pathway, and site on
 spectra. - the "pls" package (Mevik and Wehrens 2007) in R (R
 Core Team 2023) to assess how well leaf spectral reflectance could predict
 leaf traits. ## Access information Other publicly accessible locations of
 the data: * NA Data was derived from the following sources: * NA