DOI: 10.5068/d1fx0d
title: Data from: Harvester ant nest architecture is more strongly affected by intrinsic than extrinsic factors

description: Behavior is shaped by genes, environment, and evolutionary history in
 different ways. Nest architecture is an extended phenotype that results
 from the interaction between the behavior of animals and their
 environment. Nests built by ants are extended phenotypes that differ among
 species and among colonies within a species, but the source of these
 differences remains an open question. To investigate the impact of colony
 identity (genetics), evolutionary history (species), and the environment
 on nest architecture, we compared how two species of harvester ants
 construct their nests under different environmental conditions. For each
 species, we allowed workers from 4 colonies to excavate nests in
 environments that differed in temperature and humidity for seven days. We
 then created casts of each nest to compare nest structures among colonies,
 between species, and across environmental conditions. We found differences
 in nest structure among colonies of the same species and between species.
 Interestingly, however, environmental conditions did not have a strong
 influence on nest structure in either species. Our results suggest that
 extended phenotypes are shaped more strongly by internal factors, such as
 genes and evolutionary history, and are less plastic in response to the
 abiotic environment, like many physical and physiological phenotypes.
description: Animal collection and maintenance
 We collected and brought into the lab harvester ant workers from
 four different colonies from each of the two species <i>P.
 californicus </i>and <i>V. andrei</i> (N=8 colonies).
 <i>Pogonomyrmex californicus</i> workers were collected from
 colonies along the Red Rock Road in Red Rock Canyon Park in the Santa
 Monica Mountains. <i>Veromessor andrei </i>workers were
 collected from colonies on the southwest mesa at the UC Sedgwick Reserve
 in the Santa Ynez Valley. For each species, we identified the four most
 active colonies in the population to ensure that we could collect
 sufficient ants for all the experimental trials. We recorded the location
 of each colony so that we could return to them throughout the study. We
 collected ants multiple times throughout the eight weeks of the study
 (June to August 2020) and began the experiments 48 hours after each
 collection so that ants were housed in the lab for no more than 48 hours
 before beginning digging trials. To collect the ants we wore latex gloves
 and placed 100-120 workers in a plastic container that had a wet paper
 towel for moisture. In the lab, we placed ants from
 each of the eight colonies  in a separate plastic container with a lid and
 fluon along the walls to prevent ants from escaping. We supplied the
 workers with <i>ad libitum </i>water and 50% sugar water in
 glass tubes plugged with cotton to allow wicking of the fluid during the
 48 hours before the digging trials began and the 7 days of the trial
 itself. Experimental
 design We allowed 50 workers from each of the
 eight source colonies to excavate a nest in one of four environmental
 treatments (Figure 1): cold/dry, cold/wet, hot/dry, hot/wet. To control
 for the potential impact of the number of workers on nest size, we used
 groups of identical size (50 workers) in each experiment. Temperature and
 humidity were controlled using environmental chambers (Caron, model 6045)
 with ‘hot’ temperature set at 29.4 °C and ‘cold’ at 19.5 °C. The air
 temperature set in the environmental chamber was very similar to that
 inside the soil buckets (Mean 1.24°C difference, standard deviation 0.99;
 see supplementary materials, Table S4).  The ‘wet’ condition was 80%
 humidity and ‘dry’ was on average 23% humidity (range: 17-29%). The ‘dry’
 condition had some­ variability because of the technological limits of the
 environmental chambers. The two experimental temperature values and two
 experimental humidity values we tested represent the range of typical
 daytime conditions that the populations we collected ants from experience
 throughout the year (according to wunderground.com and Western Regional
 Climate Center, see supplementary materials). The ‘cold’ treatment
 represents average daytime highs during the coldest months (December
 -March) and the ‘hot’ treatment represents average daytime highs during
 the warmest months (July-October) at both field sites (Table S2). The
 ‘wet’ treatment represents the highest average humidity recorded at the
 two sites (Table S3) and the ‘dry’ treatment humidity was the driest
 conditions we could achieve in the environmental chambers.
 Nest excavation trials To
 allow ants to dig a nest, we placed the 50 workers in a five-gallon bucket
 filled with 47cm of Quikrete All-Purpose sand moistened with approximately
 150 mL water. We placed
 the maximum amount of sand possible in the buckets (47cm) without having
 ants escape. We used store-bought sand to provide all ant groups with
 controlled identical digging conditions. In preliminary trials, we found
 that the amount of sand we used needed to be moistened with approximately
 150 mL water to allow the ants to dig stable nest structures that can be
 casted and excavated. . To focus the digging of the ants at
 one location, and prevent them from digging multiple nest entrances, we
 covered the sand with a layer of hardened wax with one circular opening
 (7-10 mm diameter) in the center of the wax cover (Figure S2). This
 circular opening acted as the nest entrance. Throughout the nest
 excavation trials, we supplied the ants with <i>ad libitum
 </i>water and 50% sugar water in glass tubes plugged with cotton to
 allow wicking of the fluid. Ants were allowed to excavate a nest for seven
 days with a 12 hour day/night light regime. This experimental set up is
 similar to the one used in other studies of harvester ant nest excavation
 (Kwapich et al 2018). To create a cast of the excavated nest, at the end
 of the week of excavation, we evacuated workers from the nest by blowing
 air into the nest entrance. When most ants were evacuated, we poured
 melted wax down the nest entrance opening and after the wax hardened, we
 carefully dug out the cast for further quantification (Figure
 S2). Cast quantification
 To quantify the nest structures that the ants excavated we
 measured features of the tunnels, chambers, and of the entire nest, as
 described below. We then compared these features among colonies and
 between species, temperature, and humidity treatments.
 <i>Tunnel measurements</i> Tunnels
 are an important feature of the nest because they facilitate movement of
 ants and materials. To determine the capacity of each tunnel to transport
 material and ants we measured the length and circumference of each tunnel
 segment. We defined a tunnel segment as a tunnel connecting two nest
 features (chambers, junctions, nest entrance, or ends of cast). We laid a
 string along the tunnel segment and measured its length with a ruler to
 the nearest mm. To measure the circumference of each tunnel segment, we
 wrapped a string around the tunnel segment at each of its terminals and at
 its center, and then recorded the length of the string with a ruler to the
 nearest mm. We recorded the average of these three measurements as the
 tunnel circumference. <i>Chamber
 measurements</i> A chamber was defined as any
 section of the nest with a globular, rather than cylindrical, shape. To
 quantify the capacity of each chamber to house ants and other materials,
 we measured chamber circumference by wrapping a string around the
 chamber’s widest point and recording the length of the string with a ruler
 to the nearest mm.  <i>Global nest measurements
 </i> To quantify the global structure of each
 nest we used network analysis to quantify nest shape, combined nest-level
 tunnel and chamber measurements, and measured nest volume. All measures
 were aggregated using a PCA, as detailed below. We depicted each nest as a
 network of nodes representing chambers, junctions, and ends of the cast,
 connected by edges representing tunnels, as in (Buhl et al. 2004; Perna et
 al. 2008; Viana et al. 2013; Gautrais et al. 2014; Pinter-Wollman 2015)
 (see supplementary materials for examples). To characterize nest
 connectivity, which can impact a colony’s speed of recruitment to food
 (Pinter-Wollman 2015), we computed the average degree, which is the mean
 number of unique nodes that each node is connected to. To determine how
 well different nest elements are connected with one another, we calculated
 network density, which is the number of observed edges divided by the
 number of possible edges. To determine the distances between different
 nest elements, which can impact how quickly resources and information flow
 through the nest, we calculated average path length, which is the mean
 number of edges that connect all node pairs. To further quantify the
 potential for flow through the nest, we noted the presence or absence of
 cycles. A cycle is defined as a path along a network that returns to its
 starting node after passing through at least one other node (Balakrishan
 2011; Bender and Williamson 2010; Bollobás 1998; Gross and Yellen 2005;
 Newman 2018). Larger colonies have more cycles (Buhl et al. 2004) and
 colonies in nests with more cycles have faster recruitment to food
 (Pinter-Wollman 2015). We further calculated measures of
 nest size: total number of chambers, average circumference of all tunnel
 segments, total length of all tunnel segments, and nest volume. To obtain
 volumes we scanned each nest fragment individually using a professional
 structured light scanner (Artec Space Spider) with an accuracy of 100-200
 microns. To help the scanner detect the otherwise semi-translucent wax, we
 painted exposed sections of the wax in dark blue. We then manually aligned
 each digitized fragment with other fragments from the same nest using
 Artec Studio. Once each nest was aligned, we loaded models into Meshmixer
 to turn the disparate fragments into a single STL file. We imported the
 STL files into Meshlab, which provides volumetric measurement under the
 Mesh option. Data analysis:
 To aggregate the various global nest
 measures we used a Principal Component Analysis (PCA). In the PCA we
 included all measures listed in the “<i>Global nest
 measurements</i>”<i> </i>section above, except for the
 presence or absence of cycles, which is a binary variable and was thus
 analyzed separately. Each measure was scaled by subtracting its mean and
 dividing by its standard deviation before running the PCA. The first
 principal component explained 61.9% of the variance (Table S2) therefore
 we used it as a single measure of ‘nest size’ (Table S2, Figure
 S3). To determine
 the effect of species, colonies, and environmental conditions on the
 excavated nest tunnels, chambers, and global nest features, we conducted
 four separate ANOVAs and one logistic regression (for cycles in the nest).
 In each statistical test, the measures of tunnels (circumference or
 length), chambers (circumference), or global nest (nest size or
 presence/absence of cycles) were the dependent variables. We
 log-transformed the tunnel measures to meet the ANOVA assumptions;
 chambers and nest size measures met the ANOVA assumptions. All statistical
 models included species, colony ID nested within species, temperature, and
 humidity as independent variables. All statistical analysis was conducted
 in R version 4.0.3 (R Core Team 2020). The ANOVAs were conducted using the
 Anova() function from the package ‘car’ (Fox and Weisberg 2018). Data and
 analysis code are available in the supplementary materials.
 Nest excavation trials To
 allow ants to dig a nest, we placed the 50 workers in a five-gallon bucket
 filled with 47cm of Quikrete All-Purpose sand moistened with approximately
 150 mL water. We placed
 the maximum amount of sand possible in the buckets (47cm) without having
 ants escape. We used store-bought sand to provide all ant groups with
 controlled identical digging conditions. In preliminary trials, we found
 that the amount of sand we used needed to be moistened with approximately
 150 mL water to allow the ants to dig stable nest structures that can be
 casted and excavated. To focus the digging of the ants at one
 location, and prevent them from digging multiple nest entrances, we
 covered the sand with a layer of hardened wax with one circular opening
 (7-10 mm diameter) in the center of the wax cover (Figure S2). This
 circular opening acted as the nest entrance. Throughout the nest
 excavation trials, we supplied the ants with <i>ad libitum
 </i>water and 50% sugar water in glass tubes plugged with cotton to
 allow wicking of the fluid. Ants were allowed to excavate a nest for seven
 days with a 12 hour day/night light regime. This experimental set up is
 similar to the one used in other studies of harvester ant nest excavation
 (Kwapich et al 2018). To create a cast of the excavated nest, at the end
 of the week of excavation, we evacuated workers from the nest by blowing
 air into the nest entrance. When most ants were evacuated, we poured
 melted wax down the nest entrance opening and after the wax hardened, we
 carefully dug out the cast for further quantification (Figure
 S2). Cast quantification
 To quantify the nest structures that the ants excavated we
 measured features of the tunnels, chambers, and of the entire nest, as
 described below. We then compared these features among colonies and
 between species, temperature, and humidity treatments.
 <i>Tunnel measurements</i> Tunnels
 are an important feature of the nest because they facilitate movement of
 ants and materials. To determine the capacity of each tunnel to transport
 material and ants we measured the length and circumference of each tunnel
 segment. We defined a tunnel segment as a tunnel connecting two nest
 features (chambers, junctions, nest entrance, or ends of cast). We laid a
 string along the tunnel segment and measured its length with a ruler to
 the nearest mm. To measure the circumference of each tunnel segment, we
 wrapped a string around the tunnel segment at each of its terminals and at
 its center, and then recorded the length of the string with a ruler to the
 nearest mm. We recorded the average of these three measurements as the
 tunnel circumference. <i>Chamber
 measurements</i> A chamber was defined as any
 section of the nest with a globular, rather than cylindrical, shape. To
 quantify the capacity of each chamber to house ants and other materials,
 we measured chamber circumference by wrapping a string around the
 chamber’s widest point and recording the length of the string with a ruler
 to the nearest mm.  <i>Global nest measurements
 </i> To quantify the global structure of each
 nest we used network analysis to quantify nest shape, combined nest-level
 tunnel and chamber measurements, and measured nest volume. All measures
 were aggregated using a PCA, as detailed below. We depicted each nest as a
 network of nodes representing chambers, junctions, and ends of the cast,
 connected by edges representing tunnels, as in (Buhl et al. 2004; Perna et
 al. 2008; Viana et al. 2013; Gautrais et al. 2014; Pinter-Wollman 2015)
 (see supplementary materials for examples). To characterize nest
 connectivity, which can impact a colony’s speed of recruitment to food
 (Pinter-Wollman 2015), we computed the average degree, which is the mean
 number of unique nodes that each node is connected to. To determine how
 well different nest elements are connected with one another, we calculated
 network density, which is the number of observed edges divided by the
 number of possible edges. To determine the distances between different
 nest elements, which can impact how quickly resources and information flow
 through the nest, we calculated average path length, which is the mean
 number of edges that connect all node pairs. To further quantify the
 potential for flow through the nest, we noted the presence or absence of
 cycles. A cycle is defined as a path along a network that returns to its
 starting node after passing through at least one other node (Balakrishan
 2011; Bender and Williamson 2010; Bollobás 1998; Gross and Yellen 2005;
 Newman 2018). Larger colonies have more cycles (Buhl et al. 2004) and
 colonies in nests with more cycles have faster recruitment to food
 (Pinter-Wollman 2015). We further calculated measures of
 nest size: total number of chambers, average circumference of all tunnel
 segments, total length of all tunnel segments, and nest volume. To obtain
 volumes we scanned each nest fragment individually using a professional
 structured light scanner (Artec Space Spider) with an accuracy of 100-200
 microns. To help the scanner detect the otherwise semi-translucent wax, we
 painted exposed sections of the wax in dark blue. We then manually aligned
 each digitized fragment with other fragments from the same nest using
 Artec Studio. Once each nest was aligned, we loaded models into Meshmixer
 to turn the disparate fragments into a single STL file. We imported the
 STL files into Meshlab, which provides volumetric measurement under the
 Mesh option. Data analysis:
 To aggregate the various global nest
 measures we used a Principal Component Analysis (PCA). In the PCA we
 included all measures listed in the “<i>Global nest
 measurements</i>”<i> </i>section above, except for the
 presence or absence of cycles, which is a binary variable and was thus
 analyzed separately. Each measure was scaled by subtracting its mean and
 dividing by its standard deviation before running the PCA. The first
 principal component explained 61.9% of the variance (Table S2) therefore
 we used it as a single measure of ‘nest size’ (Table S2, Figure
 S3). To determine
 the effect of species, colonies, and environmental conditions on the
 excavated nest tunnels, chambers, and global nest features, we conducted
 four separate ANOVAs and one logistic regression (for cycles in the nest).
 In each statistical test, the measures of tunnels (circumference or
 length), chambers (circumference), or global nest (nest size or
 presence/absence of cycles) were the dependent variables. We
 log-transformed the tunnel measures to meet the ANOVA assumptions;
 chambers and nest size measures met the ANOVA assumptions. All statistical
 models included species, colony ID nested within species, temperature, and
 humidity as independent variables.. All statistical analysis was conducted
 in R version 4.0.3 (R Core Team 2020). The ANOVAs were conducted using the
 Anova() function from the package ‘car’ (Fox and Weisberg 2018). Data and
 analysis code are available in the supplementary materials.
description: README file includes instructions for using the dataset: code
 needed for analysis with documentation is included, as well as an Excel
 file containing the dataset and a ReadMe sheet explaining how to interpret
 the datasheets.