DOI: 10.5061/dryad.sj3tx96f2
title: Data from: Wildfires induce a reduction in body size and morphological variation of an insular endemic insect

description: Anthropogentic disturbance is known to affect population sizes and genetic
 population structure of many biotas. Wildfires are a major disturbance in
 many regions of the world, particularly in Mediterranean regions and on
 the Atlantic islands. Populations of many insects, such as the Madeiran
 Green Bush-Cricket (Psalmatophanes barretoi), are threated by wildfies.
 However, the effects of wildfires on genetic structure and diversity as
 well as morphological variation of the populations reamins little
 understood. Therefore, we studied genetic diversity, structure, and
 potential bottlenecks of this species using microsatellites. We also
 studied morphological variation and fluctuating asymmetry within and
 between populations to unravel potential effects of wildfires. We did not
 find any evidence for genetic differentiation of populations, but some
 populations had high heterozygosity excess, regardless of burning.
 Morphological variation in burnt areas was lower than in non-burnt areas.
 Flucturating Asymmetry of the wing length was significantly higher in
 burnt areas. Our results show that even genetically well-connected
 populations may suffer from bottlenecks leading to reduced morphological
 variation after disturbance.
description: <strong>Geography of the sampling and studied
 regions</strong> We sampled individuals of
 <em>P. barretoi</em> from the known populations of this
 species (Rhee <em>et al.</em>, 2023) in burnt and unburnt
 areas across the whole island of Madeira (Figure 2). Data on wildfires
 between 2006 and 2019 were obtained from the Institute of Forests and
 Nature Conservation in Madeira (IFCN). We divided the sampling localities
 into three different categories according to their fire severities
 (“Unburnt”, “Partially burnt” and “Completely Burnt Regions”) based on
 their overlap with the fire polygons visually for genetic analysis (Figure
 2). The study sites Machico and Santana, Seixal and Fanal did not
 experience any recent wildfires (“Unburnt Regions”), the study site
 Ribeira da Vacca and Amparo had wildfires (“Burnt Regions”), the sites
 Serra de Agua and Vagum, and Paul da Serra burnt partially (“Partially
 Burnt Regions”). We also assigned each individual to the fire history of
 its locality in two categories (burnt or not) based on their overlap with
 the fire polygons and the sampling coordinates in Arc GIS Pro for the
 morphological analysis (Esri, 2003, see Rhee <em>et al.</em>
 2023). Altitude (m) above sea level was determined in EU-DEM v1.0 based on
 25 m raster plots (Copernicus Land Monitoring Service) as a digital
 surface elevation model. All GIS and geographic visualisation were carried
 out with ArcGIS Pro (Esiri, 2023).
 <strong>Sampling and morphology
 measurements</strong> Specimens were sampled from
 6 August to 2 September 2020 (n = 39) and from 12 July to 6 September 2021
 (n = 86). Areas which burnt between 2016 and 2019 were not sampled, as
 these recent fires had stronger effects on the populations of this species
 than those between 2006 and 2015 (Rhee et al., 2023). As the species is
 listed as Vulnerable on the IUCN Red List of Threatened Species (Hochkirch
 et al., 2016), most individuals were released after measurement of
 morphological traits and a minimum invasive genetic sampling was conducted
 (single hind legs, which are readily autotomized when catching
 bush-crickets). Pronotum length, width, hind femur length, body weight,
 and body length are widely used to measure body size and fitness in
 Orthoptera (Del Castillo and Gwynne, 2007; Gwynne and Bailey, 1988;
 Montealegre‐Z, 2009; Montealegre‐Z et al., 2017) (Figure 1). Therefore, we
 measured these traits in all specimens (n = 125). As wing dimensions may
 be crucial for recolonisation and play an important role for sound
 production, we also measured length and width of the left fore wing. As a
 measure of fluctuating asymmetry, we measured the length of both fore
 wings in the 2021 samples (n = 83 after exclusion of one population with a
 low sample size of wing length data). Wing length was measured after
 bending both wings vertically straight from the pronotum. All traits were
 measured by a digital sliding calliper (Digital Caliper DC01, Tack Life).
 Fluctuating asymmetry (FA) between the left and right wing was calculated
 using the modified formula by Anciães and Marini (2000) and Henriques and
 Cornelissen (2019): FA = (Right wing - Left wing)/
 [(Right wing – Left wing)/2] The body weight was
 measured with a spring balance (PESOLA micro-line 20010). We reared
 animals to measure body size and body weight twice (once on the capture
 day and once four days later) and later calculated the average, as these
 two traits are very flexible and depend upon feeding and
 oviposition. <strong>Genetic
 analysis</strong> We extracted DNA from the hind
 leg tissues of 123 samples using the DNeasy Blood & Tissue Kit,
 following the manufacturers protocol (Qiagen, Leipzig in Germany).
 Microsatellite markers were not available for this and related species.
 Therefore, we identified microsatellites in the species and designed the
 primers first. To design primers, we created the
 genomic library of the species by using the Illuminia miseq 500 cycle Nano
 kit (Illumina, San Diego, California, the United States of America) for
 shotgun sequencing (i.e. Tru seq sequencing). After that, we filtered
 microsatellites in the library with the Msatcommander program (Faircloth,
 2008). Only tri- and tetranucleotide repeats were searched and used, as
 these nucleotides are easier to score (Tsukagoshi and Abe, 2023). From
 these nucleotides, we screened twenty-four loci and found seven
 polymorphic primers (M74, M109, M170, M182, M145, M164 and M186) based on
 five individuals (Supplemental Table 1). For the rest of the samples, we
 amplified these seven microsatellite markers with two multiplex PCR
 reactions (Supplemental Table 1). For the PCR reactions, we mixed the
 multiplex master mix following the protocol per each individual and
 primer: 15 ml multiplex mix kit, 7.8 ml water, 3 ml primer (10 µmol
 concentration) and 4.5 ml DNA. The first multiplex reaction was for three
 markers (M145, M164 and M186, annealing temperature 56°C) with 35 cycles
 and the second reaction was for four markers (M74, M109, M170 and M182,
 annealing temperature 59°C) with 34 cycles (Supplemental Table 1). All
 primers were labelled with the dye FAM, except for M186 and M182 labelled
 with PET (Supplemental Table 1). All fragment analyses were carried out by
 Macrogene (Macrogene Europe B.V.). For scoring the genotypes of each
 marker and individual, we used the GeneMapper software 5 (Applied
 Biosystem).
description: # Data from: Wildfires induce a reduction in body size and morphological
 variation of an insular endemic insect
 [https://doi.org/10.5061/dryad.sj3tx96f2](https://doi.org/10.5061/dryad.sj3tx96f2) ## Description of the data and file structure These are the data from Rhee et al. (2025). Other information, including the software used, is available in detail in Rhee et al. (2025). The supplemental figures (Supplemental figures (Revised).pdf) contain box plots about the relationship between burn status and morphological traits, and the graphical results of STRUCTURE analysis. The supplemental tables (Supplemental table (Revised).pdf) include tables about information of microsatellite markers and the ANOVA results of the relationship between burnt status and morphological traits. Rhee, H., Naber, S., Krehenwinkel, H. & Hochkirch, A. (2025) Wildfires induce a reduction in body size and morphological variation of an insular endemic insect. Ecological Entomology, 1–10. Available from: [https://doi.org/](https://doi.org/) 10.1111/een.13418 ### Files and variables #### File: Individual\_Microsatellite.xlsx **Description:** The genetic data from Rhee et al. (2025). Due to measuring heterozygosity, each locus has two alleles always. n/a indicates the samples from 2021. ##### Variables * Specimen: A name of each specimen. * Population: A sampling area of each specimen. * M74(1): Fragment sizes of a microsatellite locus (M74) of each individual. * M74(2): Fragment sizes of a microsatellite locus (M74) of each individual. * M109(1): Fragment sizes of a microsatellite locus (M109) of each individual. * M109(2): Fragment sizes of a microsatellite locus (M109) of each individual. * M170(1): Fragment sizes of a microsatellite locus (M170) of each individual. * M170(2): Fragment sizes of a microsatellite locus (M170) of each individual. * M182(1): Fragment sizes of a microsatellite locus (M182) of each individual. * M182(2): Fragment sizes of a microsatellite locus (M182) of each individual. * M145(1): Fragment sizes of a microsatellite locus (M145) of each individual. * M145(2): Fragment sizes of a microsatellite locus (M145) of each individual. * M164(1): Fragment sizes of a microsatellite locus (M164) of each individual. * M164(2): Fragment sizes of a microsatellite locus (M164) of each individual. * M186(1): Fragment sizes of a microsatellite locus (M186) of each individual. * M186(2): Fragment sizes of a microsatellite locus (M186) of each individual. * Heterozygosity: The proportion of heterozygous of each individual from all loci. #### File: morph\_all.txt **Description:** The morphological data for PCA. ##### Variables * Pronotum_length: Pronotum length (mm) of each individual. * Pronotum_Width: Pronotum width (mm) of each individual. * Femur_length: Femur length (mm) of each individual. * Wing_width: Wing width (mm) of each individual. * Body_length: Body length (mm) of each individual. * Body_weight: Body weight (g) of each individual. #### File: env\_all.txt **Description:** The environmental data for PCA. ##### Variables * Altitude: Altitude variation (m) of sampled areas of each individual. * Burned: The burnt status of sampling areas with binormal values. * Unburned: The burnt status of sampling areas with binormal values. #### File: PCA\_values\_for\_anova\_and\_variance.xlsx **Description:** The first component PCA values of the morphological variables of each individual for ANOVA and variance test. ##### Variables * Dim.1: The first component PCA values of the morphological variables of each individual. * Area: Burnt status. * Altitude: Altitude (m) variation of sampled areas of each individual. #### File: Morphology\_Data(2020\_2021).xlsx **Description:** The morphological data in 2020 and 2021 from Rhee et al. (2025) ##### Variables * ID: An name of each individual * GPS: Geographical coordinates of each individual. * Pronotum length: Pronotum length (mm) of each individual. * Pronotum width: Pronotum width (mm) of each individual. * Femur length: Femur length (mm) of each individual. * Wing width: Wing width (mm) of each individual. * Body length first: The first measurement of body length (mm) of each individual. * Body length second: The second measurement of body length (mm) of each individual 4 days later. * Weight first: The first measurement of body weight (g) of each individual. * Weight second: The second measurement of body weight (g) of each individual 4 days later. * Population: A sampling area of each individual. * Y: Longitude of geographical coordinates of each individual. * X: Latitude of geographical coordinates of each individual. * Altitude: Altitude variation (m) of sampling areas of each individual. * Body length: The mean between Body length first and second. * Body weight: The mean between Weight first and second. * Burn status: Burnt status of each sampling area. #### File: Data\_2021.xlsx **Description:** The morphological data in 2021 from Rhee et al. (2025) ##### Variables * ID: An name of each individual * GPS: Geographical coordinates of each individual. * Pronotum length: Pronotum length (mm) of each individual. * Pronotum width: Pronotum width (mm) of each individual. * Femur length: Femur length (mm) of each individual. * Wing width: Wing width (mm) of each individual. * Wing left: Left wing length (mm) of each individual. * Wing right: Right wing length (mm) of each individual. * Body length first: The first measurement of body length (mm) of each individual. * Body length second: The second measurement of body length (mm) of each individual 4 days later. * Weight first: The first measurement of body weight (g) of each individual. * Weight second: The second measurement of body weight (g) of each individual 4 days later. * Population: A sampling area of each individual. * Y: Longitude of geographical coordinates of each individual. * X: Latitude of geographical coordinates of each individual. * Altitude: Altitude variation (m) of sampling areas of each individual. * Body length: The mean between Body length first and second. * Body weight: The mean between Weight first and second. * Asymmetry: Asymmetry between left and right wing of each individual. * Burn status: Burn status of each sampling area. Rhee, H., Naber, S., Krehenwinkel, H. & Hochkirch, A. (2025) Wildfires induce a reduction in body size and morphological variation of an insular endemic insect. Ecological Entomology, 1–10. Available from: [https://doi.org/](https://doi.org/) 10.1111/een.13418 ## Code/software The R file "Morpholgy_MANOVA and ANOVA.R" contains a script about statistical analysis for morphological data. The R file " PCA_testing.R" contains a script about statistical analysis relating to Principle Component Analysis (PCA). The detailed information about statistical analysis is in Rhee et al. (2025). All other software analysis are described in Rhee et al. (2025) in detail clearly. Rhee, H., Naber, S., Krehenwinkel, H. & Hochkirch, A. (2025) Wildfires induce a reduction in body size and morphological variation of an insular endemic insect. Ecological Entomology, 1–10. Available from: [https://doi.org/](https://doi.org/) 10.1111/een.13418