COGNITIVE PERFORMANCE AND THE EVOLUTION OF MULTIPLE BEHAVIORAL DISPLAY TRAITS

Males of many species have complex behavioral sexual displays and it is possible that these displays indicate aspects about male quality because of their relationship with cognitive ability. However, the relationship between behavioral display traits, cognitive ability, and reproductive success has received little attention. Satin bowerbirds, Ptilonorhynchus violaceus, are an excellent species for studying this relationship because their complex male courtship suggests a selective advantage to individuals with superior cognitive abilities. Here I show that cognitive performance can have important effects on mating success and the quality of behavioral displays. First, I present males with two novel problem solving tests and find that males who are better at solving these problems have higher mating success, establishing a link between male cognitive ability and sexual attractiveness. Second, I add four additional cognitive tests to expand the diversity of cognitive abilities tested and construct two measures of general cognitive ability using these data: the scores from an analysis that best explains covariation among performance on the different cognitive tests (g), and the average rank score on these cognitive tests ("IQ"). I show that these measures of general cognitive ability, as well as the majority of the independent cognitive tests, are positively associated with mating success. Third, I construct a different composite measure of male cognitive ability using an analysis that determines the combination of cognitive traits that make males most successful in attracting females (f). I show that this measure is significantly associated with my measures of general cognitive ability, suggesting that evolution of cognitive ability in bowerbirds is possible if there is sufficient heritability. I construct three different aggregate measures of male display quality (produced from four behavioral display traits) and find that they are all associated with f and with mating success. Finally, I show some support for the hypothesis that separate display traits may indicate different aspects of male cognitive ability. These results suggest that behavioral display traits may have a special role in sexual selection because of their connection to cognitive ability. Overall, this research highlights the importance of considering the interrelationship between cognitive ability and sexual selection

Sperm-mediated Effects of Predation Risk on Reproduction in Male Threespined Sticklebacks

Threespined sticklebacks, Gasterosteus aculeatus, exhibit male-only parental care, but will decrease paternal care if exposed to predators while given care or if their mate has had prior experiences with predators. The offspring will experience lasting effects based on the experience of their parents (behavior-mediated transgenerational plasticity). While other studies have concluded that male exposure to predators prior to fertilization (sperm-mediated transgenerational plasticity) impacts offspring, whether sperm-mediated effects exist in sticklebacks, and for how many generations the effects persist is unknown. Courtship trials with both predator exposed and predator unexposed females with six male treatment groups shows significant impact of maternal grandfather predation exposure, suggesting that daughters of predator-exposed fathers are passing down cues to their sons

Replacing sources with sinks: when do populations go down the drain? Restor

Abstract We investigate the scenario in which some amount of higher quality habitat is destroyed and is then replaced by some undetermined amount of lower quality habitat. We examined how much low-quality habitat would need to be created to maintain the equilibrium population abundance in the entire geographic area. Using a source-sink model, we find that (1) the number of hectares of created habitat per hectare of destroyed habitat must equal the ratio of the high-quality habitat's productivity to the low-quality habitat's productivity, however, (2) if the created habitat is a sink, then there is a threshold fraction of destroyed high-quality habitat below which the initial population abundance cannot be maintained through the creation of habitat. We illustrate these results using data on Redwinged Blackbirds (Agelaius phoeniceus) in two different regions where high-quality habitat is being replaced by or converted into lower quality habitat

Landscape transcriptomics as a tool for addressing global change effects across diverse species

Landscape transcriptomics is an emerging field studying how genome-wide expression patterns reflect dynamic landscape-scale environmental drivers, including habitat, weather, climate, and contaminants, and the subsequent effects on organismal function. This field is benefitting from advancing and increasingly accessible molecular technologies, which in turn are allowing the necessary characterization of transcriptomes from wild individuals distributed across natural landscapes. This research is especially important given the rapid pace of anthropogenic environmental change and potential impacts that span levels of biological organization. We discuss three major themes in landscape transcriptomic research: connecting transcriptome variation across landscapes to environmental variation, generating and testing hypotheses about the mechanisms and evolution of transcriptomic responses to the environment, and applying this knowledge to species conservation and management. We discuss challenges associated with this approach and suggest potential solutions. We conclude that landscape transcriptomics has great promise for addressing fundamental questions in organismal biology, ecology, and evolution, while providing tools needed for conservation and management of species

Sensory Communication

Contains table of contents on Section 2, an introduction, reports on eleven research projects and a list of publications.National Institutes of Health Grant 5 R01 DC00117National Institutes of Health Grant 5 R01 DC00270National Institutes of Health Contract 2 P01 DC00361National Institutes of Health Grant 5 R01 DC00100National Institutes of Health Contract 7 R29 DC00428National Institutes of Health Grant 2 R01 DC00126U.S. Air Force - Office of Scientific Research Grant AFOSR 90-0200U.S. Navy - Office of Naval Research Grant N00014-90-J-1935National Institutes of Health Grant 5 R29 DC00625U.S. Navy - Office of Naval Research Grant N00014-91-J-1454U.S. Navy - Office of Naval Research Grant N00014-92-J-181

Sensory Communication

Contains table of contents for Section 2, an introduction and reports on twelve research projects.National Institutes of Health Grant 5 R01 DC00117National Institutes of Health Contract 2 P01 DC00361National Institutes of Health Grant 5 R01 DC00126National Institutes of Health Grant R01-DC00270U.S. Air Force - Office of Scientific Research Contract AFOSR-90-0200National Institutes of Health Grant R29-DC00625U.S. Navy - Office of Naval Research Grant N00014-88-K-0604U.S. Navy - Office of Naval Research Grant N00014-91-J-1454U.S. Navy - Office of Naval Research Grant N00014-92-J-1814U.S. Navy - Naval Training Systems Center Contract N61339-93-M-1213U.S. Navy - Naval Training Systems Center Contract N61339-93-C-0055U.S. Navy - Naval Training Systems Center Contract N61339-93-C-0083U.S. Navy - Office of Naval Research Grant N00014-92-J-4005U.S. Navy - Office of Naval Research Grant N00014-93-1-119

Aggression R Script

This is the script we used to process JWatcher files to ultimately calculate a summary aggression score for each male. The script is commented, but note that it is currently very specific to our purposes

All the R Functions

This provides R functions to aid analysis of selection. They were written fairly generically so should be easy to utilize in your research

Parenting Heritability

4 data files required to replicate our analyses, including: "Nesting Data Fathers.csv", "Nesting Data Sons.csv", "Size Data Fathers.csv", and "Size Data Sons.csv

Parenting Heritability Data and Analysis Files

4 data files, a metadata file describing the columns in these files, and an analysis script file that can be used to recreate all analyses and figures