Dataset DOI: 10.5061/dryad.8w9ghx3zs

Description of the data and file structure

This dataset was collected as part of a study investigating color variation in the Blue Crawfish, Cambarus monongalensis, and how these colors may be perceived by both conspecifics and potential predators. In March and April 2024, 88 adult crayfish were collected from a population in Claysville, Pennsylvania, using daytime burrow excavation and nighttime hand collection during surface activity following rainfall. Each individual was sexed and measured for carapace length as an indicator of body size. Juveniles (carapace length <15 mm) were excluded to avoid ontogenetic variation.

Reflectance spectra were measured using an Ocean Optics Jaz UV/VIS spectrometer from three body regions: the dorsal carapace, the dorsal claw (manus), and the pollex. Four key colorimetric variables (mean brightness, chroma in blue and red regions, and hue) were extracted for each region. Additionally, reflectance spectra were recorded for common background substrates (e.g., brown leaves, green leaves, sand, burrow, and non-burrow soil) from the same habitat.

Files and variables

File Description

The file back_spec.csv contains spectral reflectance measurements for various background objects associated with Cambarus monongalensis habitats. Each column represents a different measurement, with the wl column indicating the specific wavelength of light in nanometers.

Variables:

• wl: Wavelength of light (in nanometers)

• Brownleaf: Measurements for brown leaves (5 replicates: 1.1 to 1.5)

• Greenleaf: Measurements for green leaves (5 replicates: 1.1 to 1.5)

• Sand: Measurements for sand (5 replicates: 1.1 to 1.5)

• Burrowmud: Measurements for mud from burrows (5 replicates: 1.1 to 1.5)

• Nonburrowmud: Measurements for mud not from burrows (5 replicates: 1.1 to 1.5)

File Description

The file final_merged_monongalensis_data.xls contains morphological, demographic, collection, and colorimetric data for individual Cambarus monongalensis crayfish. Each row corresponds to a single individual crayfish, and each column represents a different trait or measurement.

Blank cells in this dataset indicate missing or unavailable data. Unlike placeholders (e.g., “NA” or “null”), true blank values prevent analysis errors by ensuring compatibility with statistical software.

Data Structure

Crayfish_ID: Unique identifier or name for each crayfish individual.

Species: All entries are Cambarus monongalensis.

Collection_date: Date the crayfish was collected (YYYY-MM-DD).

Location: Collection location for the specimen.

Sex: Sex of the individual (Male or Female).

Demographic: Demographic category (Female, Male Form I, or Male Form II).

Carapace_length: Carapace length in millimeters (body size measurement).

Spec_data_collection_date: Date the spectral reflectance data were collected.

Individual: Filename under which the individual’s spectral data was saved.

Colorimetric Variables:

These variables summarize reflectance properties of different body regions across the light spectrum (typically 300–700 nm), using metrics from the pavo R package. Each is named using the format:

Metric_BodyRegion_LowerWavelength_UpperWavelength

B1: Mean brightness

B2: Brightness contrast

H1: Mean hue

H2: Hue contrast

S1: Mean chroma (saturation)

S2: Chroma contrast

Examples:

B1_carapace_300_700: Mean brightness of the carapace from 300–700 nm.

S2_claw_400_700: Chroma contrast in the claw from 400–700 nm.

H1_tip_300_700: Mean hue of the tip region from 300–700 nm.

For detailed definitions of colorimetric metrics, see: https://pavo.colrverse.com/reference/summary.rspec.html

The file Illumination.csv contains spectral irradiance data representing different natural light environments, as reported in Johnsen (2006): “Ecological importance of color in aquatic organisms: biology and evolution of light environments” (Annual Review of Ecology, Evolution, and Systematics). Each column represents a distinct illumination condition, and the wl column indicates the wavelength of light in nanometers.

Blank cells in this dataset indicate missing or unavailable data. Unlike placeholders (e.g., “NA” or “null”), true blank values prevent analysis errors by ensuring compatibility with statistical software.

Data Structure

wl: Wavelength of light (in nanometers)

Starlight (sunspot max): Spectral irradiance measured in forested starlight (max)

Starlight (sunspot min): Spectral irradiance measured in forested starlight (min)

Full Moon: Spectral irradiance of forested full moon

All irradiance values are in arbitrary units, normalized or scaled for comparative purposes, and measured across the visible and near-UV spectrum (approx. 300–700 nm).

Reference

Johnsen, S. (2006). Ecological importance of color in aquatic organisms: biology and evolution of light environments. Annual Review of Ecology, Evolution, and Systematics, 37, 57–88. https://pubmed.ncbi.nlm.nih.gov/16481568/

R Scripts:

Color_analysis_monongalensis.r

Purpose: Analyze color variation data using reflectance measurements.
Input File:

• final_merged_monongalensis_data.csv (contains merged reflectance/color data).
• Generates statistical summaries, visualizations (e.g., plots), or processed datasets

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Visual_modeling_monongalensis.r

Purpose: Models photoreceptor responses for varying environmental conditions (illumination, backgrounds).
Input Files:

• final_merged_monongalensis_data.csv (reflectance data).
• illumination.csv (illumination condition spectra data).
• back_spec.csv (background reflectance spectra).
• Various .csv files containing modeled photoreceptor sensitivities for different combinations of:
  • Visual systems
  • Illumination conditions (e.g., forest shade, daylight)
  • Background types (e.g., green leaf, sand)
• File Naming Convention:
  • Outputs are labeled systematically from the bootstrapping color distance modeling as [VisualSystem]. [Illumination]. [Background].csv* (e.g., *databootds.garter.starmax.sand.csv). dS.mean and dL.mean: Average short-term and long-term color distances, respectively.
  • dS.lwr / dS.upr and dL.lwr / dL.upr: Corresponding lower and upper bounds of 95% confidence intervals, indicating the precision of estimates.
  • All .csvs for different visual systems, illumination, and backgrounds for the visual modeling are in the vis.model.csv.files.zip file