Data from: The extension of internal humidity levels beyond the soil surface facilitates mound expansion in Macrotermes
Calovi, Daniel S. et al. (2020), Data from: The extension of internal humidity levels beyond the soil surface facilitates mound expansion in Macrotermes, Dryad, Dataset, https://doi.org/10.5061/dryad.xd2547ddr
The data contained in this archive refer to three graphs contained in the publication.
Relative humidity on mound active build sites
We recorded relative humidity at build sites with active termite workers on the mound surface. For estimating humidity during mound expansion, a minimum of two STH75 sensors were used (to ensure a reliable reading), placed close together on the end of a rigid stick. Humidity readings were taken from three locations on the expanding build of three mounds: 0.5cm above the furthest extent of the expanding rim of a soil crest, at the level of the soil crest, and between crests, within a protected trough (Figure 2C). In three trials for each of the same mounds above, airflow of 0.8m/s as measured by handheld anemometer (Proster Trading LTD., PSTTL145US) was artificially applied, blowing laterally across the build site.
As can be seen in the file "OnMoundData_FanExperiments_ShieldAndUnshieldedExperiments.xlsx", statistical test was a t-test on the measured values presented there.
Soil transport on shielded and unshield on mound active build sites
Three pairs of plastic cups were affixed to active building sites on three mounds of M. michaelseni. Any existing fresh depositions were scraped away, and the cups were placed over the holes exposed, held in place with a wire tent peg, and left for 12 hours (Figure 3A, B). One cup of each pair was left whole, while the other was perforated with a 1cm hole in the top surface and a pair of 1cm slits running around 80% of the cup’s circumference, 1cm from the base of the cup, to facilitate the escape of excess water vapour. The soil deposited was collected and air-dried.
Dry masses (found in the file OnMoundData_Shield_Unshielded_Experiments.csv) were compared via an anova test of two linear mixed models: a null model with only colony as a random effect and a model with treatment as a fixed effect and colony as a random one. All analysis were made with R and the lme4 package. Algorithm supplied below.
All.data<-read.table('OnMoundData_Shield_Unshielded_ExperimentsB.csv',header = TRUE,sep = ',',stringsAsFactors=TRUE)
model.null <-lmer(Weight ~ (1| Colony),data= All.data,REML=FALSE);
model.Shield <-lmer(Weight ~ Shielded + (1| Colony),data= All.data,REML=FALSE);
tab_model(model.Shield,show.p = FALSE)
Construction in a humidity-controlled environment
We used a feedback loop between a mist humidifier and humidity sensors to keep a set relative humidity inside an acrylic chamber (220mm x 220mm x 260mm), (Figure 4D). Inside this chamber we placed a plastic cylinder packed with nest soil in its solid Atterberg liquid/plastic transitional state (approximately 25% water by weight) [ASTM Standard D 4318 test] capped off with an acrylic plate. The acrylic plate contained a 5 mm diameter hole in its centre, which supplied the only access by worker termites to the wet soil below, and a 3d printed ring structure around it to confine termites placed on top of the acrylic plate. In this set up termites were obliged to transport the soil from the cylinder below onto the acrylic plate, and by measuring the weight of the plate before and after the experiments, we could know exactly how much soil the termites transported during the duration of the experiment.
We selected two different relative humidity settings for these experiments - a high setting of 80% RH (measured during experiments at 81.3% ± 3.2% RH, T = 26.79°C +/- 0.37), and a low setting of 40% RH (measured during experiments at 39.9± 5.2% RH, T = 27.63°C +/- 0.41) . For each treatment, we performed experiments on three different colonies, with three replicas per colony. For every colony, we extracted termites and soil from the respective mound, then termites were stored in a closed container lined with wet paper towels. For the cylinders, we sieved the soil through 1mm mesh to remove large particulates, and for each colony soil cylinders were prepared together so that the soil water content was constant within same-colony experiments. At the beginning of each experiment, we weighed the plate, affixed it to a cylinder of soil, then placed 35 major workers on top and put it in a humid or dry setting for four hours. Once finished, we detached the mud cylinder from the plate, and removed any termites on the plate with forceps. We then placed all plates inside a food dehydrator, weighing them every 2 hours as water evaporated. We recorded the dry mass after successive weight measurements of a plate showed identical mass, indicating maximal water loss.
Data can be foun on the file HumidityControlledEnviroment.csv. We used a linear mixed-model testing colony as a random effect for the measured dry mass. Additional measurements were made with a simple T-test. The linear mixed-model was performed with R and the lme4 package. Algorithm for the linear-mixed model and the SI figure supplied below.
All.data<-read.table('HumidityControlledEnviroment.csv',header = TRUE,sep = ',',stringsAsFactors=TRUE)
model.null <-lmer(weight ~ (1| Colony),data= M.data,REML=FALSE);
model.Humidity <-lmer(weight ~ Humidity + (1| Colony),data= M.data,REML=FALSE);
tab_model(model.Humidity,show.p = FALSE)
# Create a blank dataset with the Humiditys we want
Pred.Hum <- expand.grid(Humidity = seq(33, 92, 1), weight = 0)
# Create matrix of relevant effect sizes
MM <- model.matrix(terms(model.Humidity), Pred.Hum)
# Calculate weight based on the relevant effect sizes
Pred.Hum$weight <- MM %*% fixef(model.Humidity)
pvar.Pred.Hum <- diag(MM %*% tcrossprod(vcov(model.Humidity), MM))
# Add standard errors to the dataframe
Pred.Hum <- data.frame(Pred.Hum,
plo = Pred.Hum$weight - 1.96*sqrt(pvar.Pred.Hum),
phi = Pred.Hum$weight + 1.96*sqrt(pvar.Pred.Hum))
(mm_basic <- ggplot(M.data, aes(Humidity, weight)) +
geom_ribbon(data = Pred.Hum, mapping = aes(x = Humidity, ymin = plo, ymax = phi),
fill = "rosybrown1", alpha = 0.4) +
geom_line(data = Pred.Hum, mapping = aes(x = Humidity),size=2) +
geom_point(data = M.data, aes(colour = Colony,size=Species),size=5) +
labs(title = "Weight as a function of humidity",
x = "Humidity (%RH)", y = "Weight (g)") +
scale_y_continuous( limits =c(0,11))+
theme(panel.grid = element_blank(),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12),
plot.title = element_text(size = 14, hjust = 0.5, face = "bold"),
plot.margin = unit(c(0.5,0.5,0.5,0.5), units = , "cm"),
legend.text = element_text(size = 11),
legend.title = element_text(face = "bold"),
legend.position = "bottom",
legend.box.background = element_rect(color = "grey", size = 0.3)))
For the construction in a humidity-controlled environment, trial CHD03 was not analyzed digitally, it's values of area and volume are missing.
National Institute of General Medical Sciences of the National Institutes of Health, Award: R01GM112633