DOI: 10.5061/dryad.4qrfj6qr3
title: Spectral, thermal and physiological data used for modeling

description: This dataset contains three complementary data types collected to
 investigate plant physiological responses and spectral properties in
 native vegetation of Western Australia between September 2018 and December
 2019. Spectral reflectance: Raw measurements from an ASD FieldSpec4 leaf
 clip are provided as .asd.sco files, which can be imported into R as
 tables. Each file reports reflectance values across wavelengths from
 350–2500 nm. For each sampling date, a corresponding CSV file lists plant
 codes and sampling order. Plant codes follow the format species
 initials–campaign number–replicate (e.g., et-1-1 represents Eucalyptus
 todtiana, campaign 1, replicate 1). Thermal imagery: Thermal images were
 captured to estimate stomatal conductance. Each image includes a
 timestamp, which can be linked to plant codes using the accompanying
 physiological dataset. Physiological data: Spreadsheets summarize
 leaf-level physiological traits for each sampling campaign, including
 stomatal conductance, water potential, and associated thermal image
 timestamps for cross-referencing. These data enable analyses of leaf
 spectral signatures, thermal responses, and physiological traits under
 seasonal conditions, supporting research in plant ecophysiology, remote
 sensing calibration, and drought stress assessment. All data are
 anonymized and pertain to plant measurements only; no legal or ethical
 restrictions apply.
description: ## Spectral, Thermal, and Physiological Data for Plant Condition
 Assessment Access this dataset on Dryad (Dataset DOI:
 [10.5061/dryad.4qrfj6qr3)](https://doi.org/10.5061/dryad.4qrfj6qr3) ##
 **Summary Description** This dataset contains three complementary data
 types collected from native vegetation in Western Australia between
 September 2018 and December 2019. The data were acquired to investigate
 relationships between remotely sensed indicators (spectral reflectance and
 thermal imagery) and plant physiological traits under seasonal conditions.
 These data support research in plant ecophysiology, remote sensing
 calibration, and drought stress assessment. The dataset includes: Spectral
 reflectance measurements from ASD FieldSpec4 (350–2500 nm) Thermal imagery
 for stomatal conductance estimation Physiological measurements (e.g., leaf
 water potential, relative water content) All data are anonymized and
 pertain to plant measurements only; no legal or ethical restrictions
 apply. ### **Description of the Data and File Structure** The dataset is
 provided as a compressed folder: File: Tracking_plant_condition_Dryad.zip
 This folder contains three subdirectories: **1. Physiological_for_dryad**
 Content: Excel spreadsheets summarizing physiological traits for each
 sampling campaign. Variables and Units: rwc – Relative Water Content (%)
 lwc – Leaf Water Content (g g⁻¹) lwp – Leaf Water Potential (MPa) ewt –
 Equivalent Water Thickness (g cm⁻²) plant - code of the plant sampled.
 Iincludes species (et (Eucalytpus todtiana)/bm (Banksia menziesii)/jf
 (Jacksonia floribunda)/hs (Hibbertia subavinata)/ po (Pattersonia
 occidentalis, as well as sampling round (first number) and replicated
 number (second round). For example, "et-1-1" is the first
 replicate sampled in the first round of sampling of a Eucalyptus todtiana
 plant). fresh weight - weight (in g) of the leaf in the time of sampling.
 full turgor weight - weight (in g) of the leaf after overnight petiole
 immersion in deionized water. dry weight - weight (in g) of the leaf after
 48 hours of drying at 70 degrees Celsius. time of lwp - time of leaf water
 potential measure stomatal conductance (ab) - stomatal conductance (in
 mmol water per square centimeter) in the abaxial side of the leaf stomatal
 conductance (ad) - stomatal conductance (in mmol water per square
 centimeter) in the adaxial side of the leaf total conductance - stomatal
 conductance (ab) + stomatal conductance (ad) wind - wind speed (in m/s)
 right next to the leaf at the time of thermal image reference T -
 temperature of a reference plate that was used as a sanity check of
 thermal images (not used in analysis) time of thermal - time of thermal
 image (used to match the plant code with the thermal images in the
 "thermal_for_dryad" folder). date - date of sampling area - area
 (in square centimeters) of the sampled leaf fv/fm - maximum quantum
 efficiency of Photosystem II (PSII) in dark-adapted sampled leaves pi -
 measure of plant photosynthetic apparatus vitality and efficiency, which
 integrates information from several key stages of the photosynthetic
 energy flow. Provided by the fluorometer together with fv/fm, but not used
 for analysis. Additional Information: Each row corresponds to a sampled
 plant. Columns include plant code, sampling date, and timestamp of
 associated thermal image. **2. Spectral_for_dryad** **Content:** Raw ASD
 FieldSpec4 output files (.asd.sco) organized by sampling date. Folder
 names correspond to the following sampling rounds (which can then be
 linked to the plant codes):    1- Sept2018     2- Nov2018   3- Jan2019  
 4- Mar2019 + Mar2019_2   5- May2019   6- Aug2019   7-Oct2019   8- Dec2019
 Description: In each folder (all starting with name "Hanson",
 which corresponds to a uniformal site name), I stored the reflectance
 measures from the ASD FieldSpec4 spectroradiometer. Each file contains
 reflectance values for wavelengths from 350–2500 nm. There are 3 types of
 files in the "Hanson" folders: the original ASD reflectance
 files (with no extension, which can be opened and plotted only with ASD
 software RS3 or ViewSpec Pro), the splice-corrected ASD files (SCO Files,
 which are a post-processed version of the original ASD files in which
 small shifts in reflectance values in wavelengths that occur at transition
 between sensor types have been corrected, with extension *asd.sco* or
 *XXX.sco, *which can be opened and plotted only with ASD software RS3 or
 ViewSpec Pro), and a *txt* version of this latter file (Text File), which
 is ultimately what is used for analysis and read in R). If you don't
 have access to RS3 or ViewSpec Pro, that is not a problem, since the txt
 files contain exaclty the same data (reflectance value for each wavelength
 a 1 nm resolution), and you can open them in any text editor
 (notepad/word), as well as in R, which is what I used for this study and
 what I recommend if you want to use these data. In some folders, there are
 also PDF documents where the spectral signature of some of the measures
 was plotted and shown as an example (some correspond to plant level
 measures that were not used for the study). The spectroradiometer takes 5
 measures per sample (which need to be averaged). That was done by
 following the plant order outlined in the csv files provided in the same
 folder (eg "Sept2018"), named "plant_order" and a
 date. The date coincides with the folders with the spectral data (for
 instance, plant_order_18_sept_2018.csv has the plant order of measures
 that are stored in the folder "Hanson_18-09-18". This responds
 to the fact that the spectroradiometer interface doesn't allow to
 store a custom name for each measure (such as a plant code), so that match
 has to be done a posteriori). In these same folders there are also two
 types of R files: the R code that was used to create the spectral averages
 for each plant (R Files) and the output R tables (R Data Files). All
 analysis was done in R version 3.4.1. Format: all spectral files in a text
 format that can be read with many open-source software, such as excel,
 notepad and R. Software: all data was processed in R version 3.4.1. **3.
 Thermal_for_dryad** Content: Thermal images captured for stomatal
 conductance modeling. Folders in this section are named according to the
 date in which they were collected. But the most important thing here is to
 focus on the "Date modified" field for each one of the thermal
 image files (in IS2 format). This will tell you which sample that picture
 corresponds to, by matching it with the "date" and "time of
 thermal" fields in the "Physiological_for_dryad" excel
 spreadsheets.  Format and software: all thermal images are in IS2 format
 and can be opened with the opensource and free software SmartView from the
 Fluke thermal camera maker (available here
 [https://www.fluke.com/en/support/software-downloads/software-for-fluke-infrared-cameras#smartview-classic](https://www.fluke.com/en/support/software-downloads/software-for-fluke-infrared-cameras#smartview-classic)). ### **Missing Data Codes:** NA indicates missing measurements. Sharing/Access Information ### **Other publicly accessible locations:** None ### **Data was derived from the following sources:** Original field measurements (no external sources). ### **Code/Software** Analysis Environment: R (version 3.4.1)