The Evolution of Eusociality in Insects

Epigenetics in Social Insects: A New Direction for Understanding the Evolution of Castes

Originally written April, 2012 by Bryan White

Article 1 Source:

Epigenetics is a new field of biology that deals with an only recently discovered method of DNA inactivation called DNA methylation. DNA methylation is the process in which sections of DNA are methylated and primarily occurs on cytosines, although they could occur on any nucleotide. In this paper, the current state and understanding of DNA methylation and how it relates to the development and evolution of insect castes (particularly in the eusocial insect groups) is reviewed. Methylation is not the only possible epigenetic mechanism. DNA acetylation (the addition of acetyl molecules) is also possible, as well as ubiquitination (the addition of the ubiquitin protein).  However, DNA methylation is probably the most common. The end result of DNA methylation is the existence of a secondary language on top of the DNA language that can be modified by environmental factors, can be passed on to the next generation, and influence the development of offspring. DNA methylation can also have an evolutionary affect by increasing the rate of mutations in genes that are methylated for multiple generations, for genes that are inactivated can accumulate stop codons and other deleterious mutations. Based on this, the authors hypothesize that DNA methylation is potentially the primary method for caste selection in eusocial insects.

Epigenetics brings a whole new aspect to the table for understanding how castes evolved, and how castes are regulated (should a larva develop into a queen or worker?) in eusocial systems. In hymenopteran eusocial species, there is typically a vast amount of physical diversity amongst castes (workers, soldiers, queens and male drones), and workers have found it hard to explain this diversity using only genetic methods. This is largely due to the fact that it is well known that the development and selection of what a larva will develop into is environmentally based, but scientists do not have a clear idea of exactly how that developmental “decision” is enforced. Epigenetics stands as a good explanation for how environmental factors can influence larval development, and the authors suggest this probably carried out by the presence of DNA methylation genes such as DNMT3, coincidentally which Drosophila is lacking and so was thought unimportant. The direct connection between the expression of DNMT3 and the genes that are methylated is a new, expanding area of research.

Another one of the difficulties in understanding the evolution of eusociality has been trying to explain its evolution in terms of kin selection, specifically that haplodiploid species exhibit on average 75% more genetic relatedness of sisters than other species. The benefits of a haplodiploidy system as an example of kin selection theory were that it provided a strict means for both the regulation of sexual dimorphism (males are made up of only the queen’s genome) and suggested some involvement in the development of castes. However, epigenetics and DNA methylation offers a much better explanation for the existence of both large amounts of sexual dimorphism and phenotypic plasticity. DNA methylation has been found in many eusocial hymenopteran species, as well as primitively social hymenopterans, suggesting that DNA methylation is both a heavily conserved trait and is correlated to sociality, phenotypic plasticity and sexual dimorphism. Better understanding the phylogenetic location of insect groups that make use of DNA methylation can probably elucidate the question as to whether or not DNA methylation is the sole (or primary) source of caste determination.

The authors also attempt to lay out a conceptual framework for future studies, however I found their model unclear. What the authors seem to suggest is that eusociality is correlated with DNA methylation, but not a requirement. They do, however, do a good job outlining the specific areas of DNA methylation that need to be explored and understood to eliminate other possible explanations for the correlation between DNA methylation and eusociality, such as understanding the mechanistic effects that DNA methylation has on gene splicing and whether or not it is possible for eusocial insects to exhibit caste differentiation without DNA methylation genes.

Article 2 Source:

In this article the researchers hypothesize that up until this date, all progress on kin selection theory has largely been abstract in nature and not provided any concrete evidence for the theory. They argue that, in order for kin selection theory to be fulfilled in an empirical system, several stringent conditions must be met.

First, all interactions that are measured must be “additive and pairwise”, that is, they must only affect the pair of individuals involved in the interaction. This means that synergistic effects, such as the simultaneous cooperation of more than two individuals, are unable to be measured or incorporated into any mathematical model of kin selection.

Second, they argue that kin selection theory can only be applied to a very limited subset of population structures due to the requirement of global updating of interactions wherein global updating is the idea that any two individuals are competing uniformly for reproduction regardless of their geographic proximity to each other.

Third, they argue that if these two requirements are met, and they can only be met in some limited, artificial world, then when these requirements are met that the organismal interactions within that aforementioned world are also acting according to the conditions of natural selection theory, and that kin selection theory does not provide any additional biological information.

Finally, the authors also argue that the apparent simplicity of kin selection theory compared to that of natural selection theory is an illusion. Since the primary component of kin selection theory is the calculation of inclusive fitness, and the calculation of inclusive fitness requires the state of “all individuals whose fitness is affected by an action, not only those whose payoff is changed” to be known, then in effect kin selection theory is requiring the same information to be known as natural selection theory the state of all individuals affected rather than only those whose payoff (fitness) is increased.

In order to overcome the limitations imposed by kin selection theory, the authors propose a general, multi-level model of natural selection theory using only the general principals of population genetics. This model is used to explain how eusociality might evolve in five distinct evolutionary stages.

First, an organism must reach a state where there are clear groups within a population. Groups typically form around resources, nest sites, when parents and offspring stay together, or when flocks go to known breeding grounds.

Second, these groups begin to accumulate traits, otherwise known as pre-adaptations, that will increase the overall cohesion and cooperation of these groups. One such pre-adaptation is when a parent places large numbers of paralyzed prey around her eggs so that when the eggs hatch they will have a food source readily available, and then she moves on to create another nest. The next step towards eusociality would be for the parent to stay near the nest and guard the eggs until they are hatched. However, at this stage, the offspring will still leave the nest and so will the parent –  there is still dispersion.

Third is the evolution of clearly eusocial alleles, that is, traits that enforce the primary traits of eusociality. The key traits here are for individuals to stay in the nest instead of dispersing, and then other cooperative pre-adaptations can come into play.

Fourth is probably what can be called the optimization stage in which these eusocial alleles can be selected upon to reinforce the nest/colony structure.

Fifth is the final phase and selection now operates on the colonies instead of the individual organisms, and the evolution of more derived traits such as castes (workers/soldiers), fungal farming, aphid farming, and other highly cooperative activities. Here the authors have outlined the framework through which future studies can be conducted, most likely which will be a combination of behavioral ecology and phylogenetics. My criticisms of this paper can only be restricted to the authors’ use of the words “primitive” and “advanced”, which are common misnomers in evolutionary biology. A better term should be less derived or more derived, in reference to the ancestral state. For instance, the caste system of most ants is more derived compared to the loose grouping structure of some wasps.

Oceans Around the World – The Sunda and Sahul Shelves

Notes on several key papers regarding biodiversity hotspots in and around the Sunda Shelf.

Article 1: Crandall 2008

Vicariance patterns as a result of Pleistocene sea-level changes in the Sunda Shelf area should be present in both invertebrates and their ectosymbionts. Highly variable results across many different studies have spurred the authors to explore a more closely linked hypothesis: That patterns of genetic variation found in marine invertebrates (in this case, two seastars) should closely match that of their ectosymbionts (a mollusk and crustacean). Most of the four species did show at least some genetic structure, but it was not concordant across species, with each species displaying a different pattern of range expansion most likely due to differences in dispersal, and adult survivability.


Map of Sunda and Sahul.

Map of Sunda and Sahul. CC 3.0 By Maximilian Dörrbecker (Chumwa). Wikimedia Commons.

Article 2: Crandall 2012

Sea-level changes during the end of the Last Glacial Maximum (LGM) should correspond closely with population range expansions of marine species. Prior to sea-level rises, the Sunda shelf and neighboring shelves were well above the ocean. Beginning roughly 20,000 years ago sea-levels began to rise rapidly, covering the Sunda shelf under water and facilitating the rapid expansion of marine species into this new habitat. The authors suggest that since the genetic signal of this sea-level rise is present in so many species, this event can be used as a means of calibrating the heterogeneous rate of mutation rates of lineages through time, that is, that younger lineages tend to have higher mutation rates. The authors proclaim strong support for the idea of time dependency of molecular clocks. This is an important understanding because correlating the time of geologic events with species/population events is a critical aspect of marine phylogeography.

Article 3: Kraus 2012

Here the authors investigate a genus of freshwater crab, Parathelphusa, for its historical biogeographic distributions in the Sunda region and the relation of those distributions to Pleistocene sea-level changes. The authors suggest that if Pleistocene-aged sea-level changes are responsible for the diversification of Parathelphusa clades throughout the Sunda region, then the rate of speciation should have greatly increased during that time. However, the authors find that most clades have Miocene or Pliocene origins, all with origins from Borneo although some speciation events did occur during the end of the Pleistocene, although rarely and via sporadic dispersal events as there have been no recent land-bridge connections.

Undergraduate Thesis: Effects of Artificial Moonlight on the Foraging Behavior of Mojave Desert Rodents

Effects of Artificial Moonlight on the Foraging Behavior of Mojave Desert Rodents

An Undergraduate Thesis Project
By Bryan White


Desert rodent communities are extremely diverse, which has prompted researchers to ask how so many species can coexist on similar, limited resources. Differences in foraging preferences associated with predator avoidance may contribute to coexistence. I determined how the foraging behavior of Mojave Desert rodents, especially pocket mice (Chaetodipus), were influenced by the increase in perceived predation risk associated with moonlight, which I simulated using artificial illumination. Millet (6.00 g) was mixed into trays filled with 2 L of pre-sifted sand. Seed trays were placed at stations located at different distances (2-82 m) from Coleman camping lanterns, and in either open or shrub microhabitats, so that rodents could choose to forage from resource patches with different levels of perceived risk. I also live-trapped rodents to identify likely foragers near the lanterns, and to determine the diversity and abundance of rodents in the area. Background illumination levels were recorded with using a Lux meter. I predicted that the amount of seeds removed would be highest at seed trays farthest from lanterns and under shrubs, and lowest at stations closest to lanterns and in open microhabitats. Surprisingly, I found no effect of distance, microhabitat, or illumination level on the amount of seeds removed by rodents.

Merriam's Kangaroo Rat

Merriam’s Kangaroo Rat. Photo CC 4.0 By Bcexp. Wikimedia Commons.


Desert rodents are intriguing animals because of their ability to survive in extremely harsh climates where resources are limited. Desert rodent communities are extremely diverse, which has prompted researchers to ask how so many species can coexist on the same resources, seeds (Brown 1988). In the Mojave Desert, for example, six different genera (Ammospermophilus, Chaetodipus, Dipodomys, Neotoma, Onychomys, Perognathus, Peromyscus), representing three rodent families (Heteromyidae, Muridae, Sciuridae) can all be captured in roughly the same area (Stevens et al. 2009). Most explanations suggest that animals reduce competition via resource partitioning, but differences in predator avoidance abilities may also contribute to coexistence (Kotler 1984).

It is widely accepted that desert rodents differ in their microhabitat preferences, and that these preferences reflect differences in the ability of rodents to detect and avoid predators, including owls, mammalian carnivores, and snakes. For example, quadrupedal rodents such as pocket mice (Chaetodipus, Perognathus), tend to forage in the cover of large shrubs, whereas bipedal rodents such as kangaroo rats (Dipodomys) are often found in open microhabitats between shrubs (Kotler 1984). Kangaroo rats are adapted to forage in open microhabitats in which there is little cover from visual predators (Thompson 1982; Kotler 1984). These adaptations include hopping locomotion, the ability to hear very low frequency sounds (1-3 kHz), and dorsally located eyes that should aid in spotting predators (Thompson 1982; Kotler 1984). Predation rates on rodents by owls are higher both in open microhabitats and (in a separate experiment) during periods of full moon, when levels of illumination might make movements more conspicuous (Kotler 1988). In contrast, pocket mice lack these morphological specializations, but presumably can move more efficiently beneath the denser shrub canopy (Thompson 1982). Interestingly, owls and rattlesnakes, the two most important rodent predators in the Mojave Desert, may have different effects on microhabitat use by rodents. Owls directly affect the perception of risk by desert rodents (Kotler 1988), which is higher in open microhabitats (Brown et al. 1988). The presence of rattlesnakes, which tend to hide near shrubs to wait for prey and to avoid being eaten themselves, decreased foraging of kangaroo rats in shrub microhabitats, although only during summer, when snakes are active (Bouskila 1995).

Mojave desert rattlesnake

Mojave Green Rattlesnake. Predator of Kangaroo rats. Public Domain By Lvthn13. Wikimedia Commons.

The response of rodents to predation risk has traditionally been measured in 2 ways: analysis of microhabitat characteristics at locations where rodents are captured, and foraging experiments to estimate differences in seed removal rates associated with different microhabitats. Optimal foraging theory states that animals will forage in an area until the costs of continued foraging, including perceived predation risk, outweigh the benefits (Morris 1997). The giving-up density (GUD), the density of seeds remaining in an artificial seed patch after a foraging bout, reflects this quitting harvest rate, and thus provides an index of an animal’s perceived risk and foraging costs associated with particular microhabitats (Brown et al. 1988). Both methods have been used to study how moonlight intensity affects rodent activity. Kotler (1984) found that increased illumination, simulated by camping lanterns, decreased captures in open microhabitats for some species and shifted habitat use for others in the Great Basin. Others have reported that bright moonlight reduces overall rodent activity aboveground (Brown et al. 1988).

I modified Kotler’s (1984) approach to investigate the possible effects of artificial illumination on foraging behavior of rodents in shrub and open microhabitats in the Mojave Desert. Rather than studying shifts in captures in different microhabitats, I measured seed removal rates in artificial seed trays placed at different distances from an artificial light source, a gas-powered Coleman lantern. I also quantified variation in light levels at varying distances from the lantern and in the open and beneath shrubs to understand better how actual light levels differ between these microhabitats. I predicted that seed removal rates would be lower (and GUDs higher) in trays close to the lanterns, where illumination was greatest, than at trays where there was only natural light. I also expected that rodents would remove relatively more seeds from trays beneath shrubs than in open microhabitats, especially near the lanterns, where the difference in illumination would be greatest.


My study site was conducted approximately 5 km NW of the Desert Studies Center, Zzyzx, California, during the months of June and July 2010. The site was a broadly sloping bajada at the base of an alluvial fan. Vegetation consisted mostly of creosote bush (Larrea tridentata), burrobush (Ambrosia dumosa) and desert holly (Atriplex hymenelytra), with scattered forbs and grasses. The substrate was a mixture of medium-size to small rocks and gravel, with some sandy washes. Shrub microhabitats were considered to be any shrub that appeared large enough to provide adequate canopy cover over a seed tray. Open microhabitats were locations that were at least 1 m from shrubs.

Creosote bush, Mojave Desert

Creosote bush, Mojave Desert. Public Domain By Klokeid. Wikimedia Commons.

To determine which rodent species were present at my site and foraging in seed trays, I set large Sherman live traps on the night prior to foraging trials. Traps were baited with commercial bird seed that had been microwaved for 5 min to prevent germination. During June, 30 traps were placed at same locations as the seed trays. During July, trapping was done in a 7 x 7 grid (49 traps separated by 10 m) in the area where seed trays were placed.

Artificial seed trays were houseplant saucers (6 cm deep and 32.5 cm in diameter) buried so that edges were flush with the ground. When set, each tray contained 6.00 g of millet mixed in 2 L of pre-sifted, fine sand. In June, I placed trays 2, 12 and 22 m points along 2 parallel lines extending out from a central Coleman (Dual Fuel) camping lantern. This was repeated 3 times at 50-m intervals, for a total of 30 trays. In July, I placed 32 trays from (2 m to 72 m at 10 m increments) in four different directions extending out from two centrally-placed lanterns. Two lanterns were used in the second design in an attempt to increase illumination levels. At a given location, seed trays were randomly assigned to be either in a shrub or open microhabitat. One additional tray was covered with hardware cloth to prevent foraging and was used as a control to quantify changes in weight of seeds due to moisture overnight (Stapp and Lindquist 2007).

Trays were set out at dusk. I allowed rodents to forage in seed trays for approximately 4 h. The remaining seeds and sand were collected from trays and taken back to the Desert Studies Center lab, where the sand was sifted to remove seeds. The seed was cleared of debris and weighed using a precision scale to estimate the amount of seeds removed. Seed trays were considered to have been foraged if the amount of seed removed differed by 2% of control trays from that night.

At the beginning of each foraging trial, I measured light intensity using an Extech 401036 light meter. Illumination was measured by placing the light meter on the seed tray so that the light receptor faced straight up. This measured the ambient light in the area, as opposed to the relative intensity that a rodent may perceive being emitted from a light source (either the moon and stars or lantern). I assumed that rodents look to their immediate surroundings, rather than some distant light source, to decide the relative risk of the potential foraging patches. Trials were conducted under similar background moon conditions (waxing gibbous).

All statistical analyses were conducted in Microsoft Excel (2007) Data Analysis Toolpack and Minitab 15 (Minitab Inc. 2007).


Based on a total trapping effort of 64-trap-nights over the 2 trapping sessions, pocket mice Chaetodipus (17 individuals of 2 species, C. penicellatus, C. formosus, that were not distinguished) were the most abundant rodents, followed by Merriam’s kangaroo rat (D. merriami, 6 individuals) and the desert woodrat (Neotoma lepida, 1 individual). I therefore assumed that most trays were visited by pocket mice.

A total of 62 seed trays were set out during the 2 trials. During the June trials, 3 of 30 trays (1 shrub, 2 open, 1 spilled) were considered to have not been foraged, whereas in July, more than 2/3 (22/32) of the trays were not foraged (10 shrub, 12 open, 1 spilled). Only results from seed trays that were considered foraged were included in the analysis. Combining across all distances and trials, there was no significant difference in the amount of seeds removed in shrub and open microhabitats during June or July (Fig.1; P > 0.05). Combining both trials, the amount of seed removed was not related to distance from the lanterns in either open (Fig. 2; R2 = 0.007, P = 0.745, DF = 15) or shrub (Fig. 2; R2 = 0.15, P = 0.0936, DF = 18) microhabitats.

Illumination levels were highest in seeds trays near the lanterns, but declined considerably by 12 m from the lanterns (Fig. 3). Shrub and open trays were exposed to similar light levels.

Surprisingly, illumination did not influence seed removal rate in the way that I predicted. At all levels of illumination and in both shrub and open microhabitats, rodents consumed most of the seeds in the trays (Fig. 4). In fact, the amount of seeds removed was lowest and most variable at the lowest light intensities.


I found no evidence to support my hypothesis that rodents would spend more time foraging in darker, shrub microhabitats, where risk of predation would presumably be lower. This was particularly surprising because pocket mice were the most common rodents I captured at my study sites and probably were responsible for most of the foraging in seed trays. Pocket mice are quadrupedal and generally prefer the cover of shrubs (Kotler 1988), and therefore would be expected to be sensitive to predation risk. My results differ from those of Kotler (1984), who found, based on live-trapping, that rodents, including quadrupedal species, increased their use of shrub microhabitats in the presence of artificial illumination. However, Kotler (1984) also found that seed enrichments increased the use of the open microhabitat by kangaroo rats. This suggests that, in my study, while pocket mice may have focused their foraging efforts on removing seeds from under shrubs, kangaroo rats may have been opportunistically foraging in brighter areas, and due to its larger body size and bipedal locomotion, consistently removed large amounts of seeds from those trays.

The fact that rodents ate nearly all the seeds in seed trays at all distances from the lanterns and irrespective of illumination levels suggests that the bright light associated with the lanterns did not deter them from foraging. In fact, rodents removed the smallest amounts of seed in trays at the darkest light levels, including some beneath shrubs (Fig. 4). This suggests that factors other than illumination and microhabitat influenced foraging behavior at these low light levels. It also suggests that rodents can find a large amount of dispersed seed (6 g) in a relatively short time. It is possible that multiple rodents visited a given tray, but I was not able to determine the number of rodents using each tray.

If I were to repeat this study, I would increase the number of replicate seed trays and use the same experimental design throughout. I also would keep a record of whether there are tracks in trays as an index of foraging. Another way to improve my experimental design would be to video record seed trays to know how many animals and of which species visited a seed tray during a foraging bout.

Literature Cited

Bouskila, A. (1995). Interactions between predation risk and competition: A field study of kangaroo rats and snakes. Ecology, 76(1), 165-178.

Brown, J. S., Kotler, B. P., Smith, R. J., & Wirthz, W. O.,II. (1988). The effects of owl predation on the foraging behavior of heteromyid rodents. Oecologia, 76(3), 408-415.

Kotler, B. P. (1984). Risk of predation and the structure of desert rodent communities. Ecology, 65(3), 689-701.

Kotler, B. P. (1988). Environmental heterogeneity and the coexistence of desert rodents. Annual Review of Ecology and Systematics, 19, 281-307.

Morris, D. W. (1997). Optimally foraging deer mice in prairie mosaics: A test of habitat theory and absence of landscape effects. Oikos, 80(1), 31-42.

Stevens, R. D., & Tello, J. S. (2009). Micro- and macrohabitat associations in mojave desert rodent communities. Journal of Mammalogy, 90(2), 388-403.

Stapp, P. and Lindquist, M (2007). Roadside foraging by kangaroo rats in a grazed short-grass prairie landscape. Western North American Naturalist, 67(3), 368-377.

Thompson, S. D. (1982). Microhabitat utilization and foraging behavior of bipedal and quadrupedal heteromyid rodents. Ecology, 63(5), 1303-1312.