Ants are widespread species of eusocial insects, and myrmecophily describes the species which are associated with ants. Many mites are myrmecophilous species and interact with hosts in many ways such as phoresis or parasitism. The relationship between ants and mites are interesting as parasitic species could be used to control the spread of invasive ant species. For this project, I reviewed the existing literature on myrmecophilous mites around the world and compiled a database of ant-mite associations, which I then used to characterize factors such as host specificity, attachment sites, and biogeographical patterns. This work demonstrates that existing research on myrmecophilous mites has been both geographically and taxonomically biased and highlights the need for much more comprehensive surveys of mites living in association with ants.
In Chapter 1, I summarize relevant past work on food and nest recruitment. Then I describe T. rugatulus and its recruitment behavior, tandem running, and I explain its suitability for these questions. In Chapter 2, I investigate whether food and nest recruiters behave differently. I report two novel behaviors used by recruiters during their interaction with nestmates. Food recruiters perform these behaviors more often than nest recruiters, suggesting that they convey information about target type. In Chapter 3, I investigate whether colonies respond to a tradeoff between foraging and emigration by allocating their workforce adaptively. I describe how colonies responded when I posed a tradeoff by manipulating colony need for food and shelter and presenting both resources simultaneously. Recruitment and visitation to each target partially matched the predictions of the tradeoff hypothesis. In Chapter 4, I address the tuned error hypothesis, which states that the error rate in recruitment is adaptively tuned to the patch area of the target. Food tandem leaders lost followers at a higher rate than nest tandem leaders. This supports the tuned error hypothesis, because food targets generally have larger patch areas than nest targets with small entrances.
This work shows that animal groups face tradeoffs as individual animals do. It also suggests that colonies spatially allocate their workforce according to resource type. Investigating recruitment for multiple resource types gives a better understanding of exploitation of each resource type, how colonies make collective decisions under conflicting goals, as well as how colonies manage the exploitation of multiple types of resources differently. This has implications for managing the health of economically important social insects such as honeybees or invasive fire ants.
Chapter 2 presents the first formal cladistic analysis on the group to redefine the New World tribes Lechriopini Lacordaire, 1865 and Zygopini, Lacordaire, 1865. An analysis of 75 taxa (65 ingroup) with 75 morphological characters yielded six equally parsimonious trees and synapomorphies that are used to reconstitute the tribes, resulting in the transfer of sixteen genera from the Zygopini to the Lechriopini and four generic transfers out of the Lechriopini to elsewhere in the Conoderinae.
Chapter 3 constitutes a taxonomic revision of the genus Trichodocerus Chevrolat, 1879, the sole genus in the tribe Trichodocerini Champion, 1906, which has had an uncertain phylogenetic placement in the Curculionidae but has most recently been treated in the Conoderinae. In addition to redescriptions of the three previously described species placed in the genus, twenty-four species are newly described and an identification key is provided for all recognized species groups and species.
Chapter 4 quantitatively tests the similarity in color pattern among species hypothesized to belong to several different mimicry complexes. The patterns of 160 species of conoderine weevils were evaluated for 15 categorical and continuous characters. Non-metric multidimensional scaling (NMDS) is used to visualize similarity by the proximity of individual species and clusters of species assigned to a mimicry complex in ordination space with clusters being statistically tested using permutational multivariate analysis of variance (PERMANOVA).