Morphometric data to describe phenotypical variation across Pygmy and Marbled newts (genus Triturus)
Data files
Dec 11, 2024 version files 564.98 KB
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newts-SSD_common_slopes_test_boot.R
3.92 KB
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newts-SSD_female_male_slope_boot.R
4.05 KB
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newts-SSD_locality_data.txt
257.35 KB
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newts-SSD_mean_values_species_sex.txt
1.21 KB
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newts-SSD_raw_data.txt
280.18 KB
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newts-SSD_rr_test_boot.R
4.53 KB
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newts-SSD_ttest.R
4.27 KB
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README.md
9.48 KB
Abstract
An extensive dataset on the external morphology of pygmy and marbled newts was used to explore the static allometry of sexual size dimorphism (SSD) and Rensch’s rule (RR). Females were larger in trunk and head sizes, whereas males had longer limbs and digits. Divergences in trunk and head dimensions between sexes were achieved along a common allometric slope rather than by a change in the slope’s direction, most often through a shift in the intercept. Sexual dimorphism in finger and toe length was unrelated to body size. The change in SSD with a change in body size (RR) was confirmed for female-biased traits. RR was unrelated to changes in static allometric slopes.
README: Morphometric data to describe phenotypical variation across Pygmy and Marbled newts (genus Triturus)
https://doi.org/10.5061/dryad.w6m905qzm
From the paper Allometry, sexual dimorphism, and Rensch’s rule in pygmy and marbled newts (Journal of Evolutionary Biology, voae150, https://doi.org/10.1093/jeb/voae150)
Authors:
Ana Ivanović, Faculty of Biology, University of Belgrade, Belgrade, Serbia, ana@bio.bg.ac.rs
Tijana Vučić, Naturalis Biodiversity Center, Leiden, The Netherlands, Institute of Biology, Leiden University, Leiden, The Netherlands, Faculty of Biology, University of Belgrade, Belgrade, Serbia, tijana.vucic@naturalis.nl
Jan W. Arntzen, Naturalis Biodiversity Center, Leiden, The Netherlands, Institute of Biology, Leiden University, Leiden, The Netherlands, pim.arntzen@gmail.com
Brief summary: |
---|
--- An extensive dataset on the external morphology of pygmy and marbled newts was used to explore the static allometry of sexual size dimorphism (SSD) and Rensch’s rule (RR). |
--- Females were larger in trunk and head sizes, whereas males had longer limbs and digits. |
--- Divergences in trunk and head dimensions between sexes were achieved along a common allometric slope rather than by a change in the slope’s direction, most often through a shift in the intercept. |
--- Sexual dimorphism in finger and toe length was unrelated to body size. |
--- The change in SSD with a change in body size (RR) was confirmed for female-biased traits. |
--- RR was unrelated to changes in static allometric slopes. |
Data collection: J. W. Arntzen |
Code: T. Vučić |
We have submitted data and R scripts used for each of the analysis in the study “Allometry, sexual dimorphism, and Rensch’s rule in pygmy and marbled newts”, and file that contains morphometric data as well as additional information for geographic information of populations used in the study. |
Data files:
1) raw data – newts-SSD_raw_data.txt;
2) mean values per (sub)species and sex – newts-SSD_mean_values_species_sex.txt.
R scripts:
1) T-tests to assess the significance of differences in mean trait size between the sexes – newts-SSD_ttest.R;
2) Standardized major axis (SMA) analysis to test the allometric relationships between females and males within (sub)species for analyzed traits with bootstrap to calculate 95% CIs for the values of allometric slopes – newts-SSD_female_male_slope_boot.R
3) Standardized major axis (SMA) analysis to test Rensch’s rule (RR) with bootstrap to calculate 95% CIs for the values of allometric slopes – newts-SSD_rr_test_boot.R
4) Standardized major axis (SMA) analysis to test for common slopes across taxa and
between pairs of taxa with bootstrap to calculate 95% CIs for the values of allometric slopes – newts-SSD_common_slopes_test_boot.R
Additional information:
1) Morphometric data with additional geographic information: Locality and coordinates of populations – newts-SSD_locality_data.txt
## Description of the data and file structure
### newts-SSD_raw_data.txt
The dataset contains raw measures of eight morphometric traits (in mm) and their log values. This dataset was used to analyse: differences in mean trait size between the sexes (R script: newts-SSD_ttest.R), allometric relationships between females and males (R script: newts-SSD_female_male_slope_boot.R) and common slopes across taxa (R script: newts-SSD_common_slopes_test_boot.R).
Species: Triturus species
Subspecies: subspecies of Triturus species
Sex: measured individuals were adults – males and females
SubspSex: combined information on subspecies and sex
All measures are in milimeters (mm)
SVl: snout-vent length, as representative of overall body size was measured from the tip of the snout up to and including to the insertion of hind limbs
Ild: interlimb distance
FLl: forelimb length
TFl: third finger length
HLl: hindlimb length
FTl: fourth toe length
Hw: head width
Hl: head length
### newts-SSD_mean_values_species_sex.txt
The dataset contains mean values of eight morphometric traits (in mm) per (sub)species and sex values. This dataset was used to test Rensch’s rule (R script: newts-SSD_rr_test_boot.R).
All measures are in milimeters (mm)
Abberevations:
SVl: snout-vent length
Ild: interlimb distance
FLl: forelimb length
TFl: third finger length
HLl: hindlimb length
FTl: fourth toe length
Hw: head width
Hl: head length
F: female
M: male
### newts-SSD_locality_data.txt
This file contains additional data – geographic information:
Locality number: the ordinal number of population
Locality name: geographic information
Country: Country of origin
Longitude
Latitude
Species: Triturus species
Subspecies: subspecies of Triturus species
Sex: measured individuals were adults – males and females
All measures are in milimeters (mm)
Abberevations:
SVl: snout-vent length
Ild: interlimb distance
FLl: forelimb length
TFl: third finger length
HLl: hindlimb length
FTl: fourth toe length
Hw: head width
Hl: head length
log values of measurements
## Code/Software
All R scripts were created using R version 4.4.1 (2024-06-14 ucrt). Packages used:
1) smatr v. 3.4.8 (Warton, David I., Duursma, Remko A., Falster, Daniel S. and Taskinen, S. (2012) smatr 3 - an R package for estimation and inference about allometric lines Methods in Ecology and Evolution, 3(2), 257-259)
2) boot v. 1.3.31 (Canty, A. and Ripley, B. (2024). boot: Bootstrap R (S-Plus) Functions. R package version 1.3-31)
### newts-SSD_ttest.R
This R script performs a series of t-tests to assess the significance of differences in mean trait size between the sexes. The data file used for analysis is newts-SSD_raw_data.txt. No additional packages are required, as the t.test() function is available in base R.
### newts-SSD_female_male_slope_boot.R
This R script performs a standardized major axis (SMA) analysis to test the allometric relationships between females and males within (sub)species for the analyzed traits, using bootstrap to calculate 95% confidence intervals (CIs) for the values of allometric slopes. The data file used for analysis is newts-SSD_raw_data.txt. The analysis utilizes the smatr and boot packages.
###newts-SSD_rr_test_boot.R
This R script performs a standardized major axis (SMA) analysis to test Rensch’s rule (RR) using bootstrap to calculate 95% CIs for the values of allometric slopes. The data file used for analysis is newts-SSD_mean_values_species_sex.txt. The analysis utilizes the smatr and boot packages.
###newts-SSD_common_slopes_test_boot.R
This R script performs a standardized major axis (SMA) analysis to test for common slopes across taxa and between pairs of taxa using bootstrap to calculate 95% CIs for the values of allometric slopes. The data file used for analysis is newts-SSD_raw_data.txt. The analysis utilizes the smatr and boot packages.
Methods
Five (sub)species of T. marmoratus species group were analysed: two subspecies of the marbled newts – T. marmoratus harmannis (338 females and 247 males from 46 populations) and T. m. marmoratus (80 females and 70 males from five populations) and three taxa of pygmy newts namely T. p. pygmaeus (26 males and 24 females from five populations), T. pygmaeus lusitanicus (317 females and 254 males from 38 populations) and T. rudolfi (126 females and 125 males from six populations). A sample of the even larger crested newt T. cristatus (15 males, 30 females from one population) was included for comparison. Hybrid populations were excluded (Arntzen, 2018, 2024ab). All measured individuals were adults. The following eight morphometric traits were analyzed: snout-vent length (SVl), as representative of overall body size was measured from the tip of the snout up to and including to the insertion of hind limbs, interlimb distance (ILd), head width (Hw), head length (Hl), forelimb length (FLl), third finger length (TFl), hindlimb length (HLl) and fourth toe length (FTl). Snout-vent length as here measured purposely excludes the cloaca, the size of which is season dependent. That measure largely corresponds to the more commonly used measure up to the cloacal slit (e.g. Reinhard and Kupfer, 2015). The analysed dataset is compilation of published data (2018, 2024b, 2024c) and newly collected ones, and cover the entire distribution range (Arntzen, 2024cd).
All statistical analyses were conducted using R (R Core Team, 2022). The significance of differences in mean trait size between the sexes was tested by t-tests using the t.test function. The allometric relationships between females and males within (sub)species and among (sub)species, as well as RR were explored using SMA with the smatr package (Warton et al., 2012; 2018). First, we plotted trait measures versus SVl (all log-transformed) for each (sub)species and sex separately using sma function. The strength of the association between SVl and the specified trait was estimated by the square of Pearson’s correlation coefficient (r2). The statistical significance of the fitted allometric slope for each sex and (sub)species was estimated by the sample correlation between residuals and fitted values. We subsequently tested whether the allometric slope is non-isometric (b ≠ 1). Differentiation of the sexes was explored by testing for differences in the direction of allometric slopes (Figure 1, pattern A). When no differences were found, we tested for lateral shifts that led to a change in elevation (pattern B), shifts along the common allometric slope (pattern C), or both (pattern D).
We tested for RR using again the sma function. The log-transformed mean values for specific traits in females versus males for each (sub)species were plotted and tested for isometry (b = 1). To test for common slopes across taxa and between pairs of taxa, we used the slope.com function. First, we calculated the common slope for each of traits for all six taxa with pooled males and females as these have common slopes (Table 1) and estimated its statistical significance based on the (Bartlett-corrected) likelihood ratio statistic testing for common slope (Warton and Weber, 2002; Warton et al., 2006; Taskinen and Warton, 2013). We did post-hoc multiple comparisons of slopes by calculating the common slope for pairs of taxa for each trait. Interpretation of all statistical tests was done using the standard Bonferroni correction for multiple comparisons.
To calculate 95% confidence intervals for the values of allometric slopes in all aforementioned tests we used boot package (Davidson and Hinkley, 1997; Canty and Ripley, 2024). We defined bootstrap function and than used replicate function to create bootstrap samples. Confidence intervals were calculated by using quantile function.