Data from: Sugar-rich resources mediate geographic morphological variation in a dominant, neotropical savanna ant
Abstract
Aim: Trait variation across geographic gradients can reveal how species respond to different environmental settings, which is crucial under the growing threat of climate change. Although on the basis of evolutionary theory, the patterns and drivers of intraspecific functional variation remain largely underexplored. In ants, pilosity and body size are morphological traits associated to thermoregulation and heat tolerance, which are critical concerns in the context of global warming. Here, we focused on the dominant ant Camponotus crassus to investigate trait variation and its potential drivers across a latitudinal gradient in the Brazilian Cerrado savanna.
Location: Brazilian Cerrado savanna
Taxon: Camponotus crassus Mayr, 1862 (Hymenoptera: Formicidae)
Methods: We measured mesosoma pilosity and body size of C. crassus across multiple sites, and evaluated their relationship with temperature, rainfall, solar radiation, vegetation, and sugar-rich resource variables. We also assessed morphological and genetic covariation to search for possible phenotypic plasticity or adaptation in C. crassus.
Results: Only sugar-rich resources were found to significantly influence C. crassus pilosity. Specifically, a negative relationship between ant pilosity and sugar-rich resources (i.e. proportion of plants with extrafloral nectaries and hemipteran trophobionts) was found. No covariation between pilosity and genetic dissimilarities was observed, suggesting phenotypic plasticity. None of the variables were significant to predict body size, while this trait positively covary with genetics.
Main conclusions: Our findings suggest resource availability as a critical factor for species thermoregulation under environmental change, a hypothesis previously reported in the literature. We emphasize the importance of examining intraspecific variation and phenotypic plasticity across large geographic scales, particularly under the scenario of rapid global change, and the current threat to Cerrado savanna. Our work covers a still poorly investigated aspect of intraspecific variation of tropical eusocial insects, and sheds new light on trait variation associated with large geographical gradients and resource availability in a major ecosystem.
https://doi.org/10.5061/dryad.4xgxd25mp
Description of the data and file structure
Between November 2012 and April 2013, woody plants at seven sites of Cerrado sensu stricto were searched for ant-plant interactions. In each locality, 5 transects of 200 m were established, at least 1 km apart from one another. Transects were divided into 20 plots of 10 m length and data were collected in 10 alternate plots. Each transect was characterized by its climatic, vegetational and resource variables. For morphological characterization and Single Nucleotide Polymorphisms (SNPs) genotyping, we selected *Camponotus crassus *specimens from samples collected during fieldwork. For data collection details, please see Material and Methods.
Files and variables
File: Data.xlsx
Description: Local, ID, and coordinates of transects (used as sample unit for analyses). For each transect is also available the operational explanatory variables, including temperature, rainfall, solar radiation, vegetation, and sugar-rich resources availability. *Camponotus crassus *response variables (mean pilosity and body size per transect) are also available.
Variables:
transecto = transect ID
local = sampling site. Bra = Brasília; Can = Canastra; Cip = Cipó; Iti = Itirapina; Ser = Serra Azul; Ema = Emas; Vea = Veadeiros
Lat = transect latitude (unit: decimal degree; WGS94)
Long = transect longitude (unit: decimal degree; WGS94)
nobs = number of measured C. crassus per transect
mean_pilosity = mean pilosity (unit: mean number of hair crossing mesosoma profile)
cv_pilosity = coefficient of variation of pilosity
mean_hairdensity = mean hair density (unit: mean number of hair crossing mesosoma profile/mm2)
cv_hairdensity = coefficient of variation of hair density
mean_lw = mean Weber’s length (unit: mm)
cv_lw = coefficient of variation of Weber’s length
DSH = Mean plant diameter at soil height (unit: mm)
Height = Mean plant height (unit: cm)
Density = Mean vegetation density (unit: mean number of plants/m2)
% EFN = Proportion of plants with extrafloral nectaries
% Trophobionts = Proportion of plants with trophobionts
DNIy = Annual direct normal irradiation (unit: kWh/m2)
DIFy = Annual diffuse horizontal irradiation (unit: in kWh/m2)
Bio1 = Annual mean temperature (unit: °C × 10)
Bio4 = Temperature seasonality (unit: standard deviation ×100)
Bio12 = Annual precipitation (unit: mm)
Bio15 = Precipitation seasonality (unit: coefficient of variation)
mean_pilosity.gen = mean pilosity considering only the individuals with SNP data (unit: mean number of hair crossing mesosoma profile)
mean_hairdensity.gen = mean hair density considering only the individuals with SNP data (unit: mean number of hair crossing mesosoma profile/mm2)
mean_lw.gen = mean Weber’s length considering only the individuals with SNP data (unit: mm)