Author Archives: tobyhector
Science Drinks kicked off with Gregor explaining exciting progress he has made in his honours project work. Gregor is using mapping techniques (GIS) to examine the phenology of dance flies across the UK, trying to find whether there is a difference in emergence times across dance fly species which display both conventional and reversed sex roles.
Luc then presented to the group a paper recently accepted in Evolution looking at age-dependent performance and senescence in sport (Lailvaux, Wilson & Kasumovic 2014). The authors used an extensive dataset on male and female professional basketball players to investigate sex differences in ageing and performance. The main results included a trend for earlier senescence in males, and evidence that different male performance traits showed varying rates of senescence. The Science Drinks group discussed the paper at length, especially how aspects of the data and game were controlled for in the analyses.
Whilst the paper made me realise how very little I know about basketball it prompted a long discussion about the use of sport stats (of which there are apparently huge repositories for some sports) in scientific analyses. Luc explained his ongoing interest in analysing sumo wrestling statistics and then went on to describe a paper he co-authored in 2004. This paper used data from cricket (the sport not the insect) to show that there was evidence of negative-frequency dependent success of left-handed batsman in the 2003 cricket World Cup. After the group chatted about cricket for a while I added both cricket and sumo wrestling to the quickly growing list of sports I know absolutely nothing about! The discussion then moved on to the group pondering what other sports may have large and detailed datasets, collected and published by enthusiasts, that could be used to answer biological questions.
Adam was next to speak and gave us a very interesting introduction to his work. His main interests are senescence and menopause in mammals and he currently uses a large dataset of human birth and death records to answer questions in this field. This dataset was collected from pre-industrial Finnish church records that are apparently extensive and very detailed. He is currently using the dataset to try and find the effect that number of children has on maternal fitness and survival. An issue that he has found in this system is that if a mother died, her offspring often died soon after, meaning the causal relationship is reversed (a lack of maternal care affects child survival, rather than the birth of children affecting mothers). The challenge of disentangling complex causal relationships appears to be a persistent problem for life history research.
Finally, Stuart talked us through some thoughts he was having in his own field of study using Daphnia to look at host-parasite coevolution. A major interest of his currently surrounds the idea that not every parasite will successfully infect a host and will instead simply pass through the host’s digestive system unharmed. He is looking into the cost of a failed infection on the parasite and how this affects both host and parasite population dynamics and coevolution.
Arnold & Duvall (1994) use mathematical modeling and statistical analysis of classic data such as those collected by Bateman (1984) to analyse how the strength of sexual selection can be used to explain diversity in mating systems.
The previous papers (by Bateman 1948, Trivers 1972, and Emlen & Oring 1977), discussed in previous posts, had set the stage for more empirical and theoretical work attempting to explain the evolution of mating systems. Arnold & Duvall (1994) suggested that although there had been many important articles contributing to different aspects of mating system theory, including Bateman’s classic work on the relationship between fecundity and mating success, there was no formal theoretical and analytical framework that integrated all the research.
The authors reaffirm that the relationship between mating success and fecundity (based on Bateman’s original work) is a key driver of mating system evolution. One of the paper’s main themes is based on a now well-accepted idea articulated in the early 1980’s (Lande and Arnold 1983), that selection can be seen as the statistical relationship between certain traits and fitness. To integrate this analytic approach with the study of mating systems, Arnold and Duvall propose a 4 tiered hierarchical framework including the traits that influence fitness. This conceptual model illustrates the direct and indirect relationships between traits and fitness measures, and allows formal testing of the pathways that affect fitness components. Traits that have the most direct effect on fitness are assigned rank one, while more indirect agents have higher ranks (2, 3 or 4) depending on the number of presumed mediating factors that relate them with fitness (Figure 1.).
Luc noted that creating thought maps or path diagrams similar to this figure, which describe the important relationships or factors within a system, could be very useful in allowing us to visualize and understand the important questions in our own research. These conceptual diagrams often further allow one to make the statistical associations between correlated components of a system more explicit.
Arnold and Duvall explain how the ‘selection gradients’ illustrated as arrows in Figure 1 can be quantified using multiple regression of fitness on estimates of the traits presumed to be under selection. Each aforementioned selection gradient is the partial standardized regression coefficient in a multiple regression including other aspects of the phenotype. Multiple regression can therefore be used to estimate the total combined selection on all the various traits affecting fitness, including the sexual selection component that affects reproductive fitness.
The authors explain that linear regression is appropriate in the estimation of selection gradients even if the fits are nonlinear. This is now an accepted convention when trying to measure strength of selection on a trait, however Luc suggested that, notwithstanding Arnold and Duvall’s logic about the nature of evolutionary genetic change and its relationship with the well-established body of work on selection analysis, we should neverthelessalways question exactly what coefficients mean when they come from a model that might have a poor fit.
The authors further discuss how estimates of selection gradients can be used to test sexual selection theory, by integrating different aspects of mating systems such as nuptial gifts or parental care, to examine the strength of selection on males and females. They argue that their approach quantifies differences in the strength of selection (regression slopes) between males and females, which is useful for testing theory on mating systems.
They illustrate their analysis using several examples of mating systems, including one in which males provide nuptial gifts to females. In this case, models showed that there should be a small increase in female’s selection gradient (strength of sexual selection) for each multiple mating (as a result of the benefits to gaining extra gifts and therefore nutrition), and that the greater the nutritional benefit of the gift, the greater the strength of sexual selection will be.
Arnold and Duvall finally use models involving encounter rate, similar to the ideas proposed by Emlen and Oring (1977), and show that these can also be used to measure the strength of selection on fitness based traits. They do however contest Emlen and Oring’s (1977) assertion about the most useful metric for describing or determining mating systems. Whereas Emlen and Oring argue that the operational sex ratio (the average over time of the number of sexually active males to the number of females capable of insemination) is the most useful indicator of the mating system, Arnold and Duvall reason that the breeding sex ratio (the ratio of breeding males to breeding females, including the zero fecundity class for each sex) is more appropriate. This may be something to think about for some members of our lab who are looking at malaise trap samples to determine the adult operational sex ratios and mating rates of dance flies.
Ultimately the authors claim that it is the disparity in selection gradients that determines which sex competes for access to the other. While sexual selection due to competition will therefore determine a species’ mating system, it seems logical that a species mating system will also influence the level of selection in a cyclical fashion. This reminds us of Trivers (1972), who noted the cyclical relationship between mate competition and parental investment in his own analysis of what determines the sex roles.
Dr Luc Bussière
Dr Timothy Paine
Dr Moha Abdelaziz Mohammed
Dr Evangelos Spyrakos
Tuesday saw the second biweekly “Science Drinks” of the semester. These events consist of staff and students from many scientific backgrounds in Biological and Environmental Science getting together to discuss cool science over beer (or a soft drink of your choice). The only requirement for attending is to bring along a science question, conundrum or interesting story or paper. I will give a brief synopsis below outlining some of the anecdotes, stories and discussions that took place in our session on Oct 8.
The evening started (after a trip to the bar) with Luc telling us all about the strange and wonderful swarming habits of the Mormon cricket (really a katydid!). These large insects form huge aggregations and ‘march’ through western North America eating everything in their way. This behaviour is apparently driven by the desire for food and salt leading them to try and catch the katydid in front (and stay ahead of the hungry katydid behind!). Luc went on to tell us how it is Mormon belief that when these swarms came to ‘plague’ them, God sent seagulls that ate until they vomited allowing them, as the story goes, to continue eating the crickets. It’s a nice story, although the vomit may have a little more to do with the katydids repugnant taste.
In the first Science Drinks of the semester, two weeks ago, Tim made the bold suggestion that humans have no muscles in their fingers. This was idea was promptly shot down by most of the group. However after some quick research and lots time squeezing and staring at our fingers we discovered that he was in fact correct. Apologies were given to Tim and the rest of us learned something quite interesting about our fingers.
Three researchers who were new to Science Drinks then gave brief descriptions of their interests and work.
Jen described how she uses mathematics to model protandry in natural systems. This lead to a lengthy discussion about the possibility that protandry is a sexually antagonistic trait.
Moha gave us an outline of his work on the Brassicaceae genus Erysimum. He works on mainland North America and several islands comparing how ecological and genetic mechanisms cause speciation and radiation. One of his main interests is the potential impact of plant-pollinator interactions on these processes. Interestingly he commented that just a single plant species might have up to 150 different pollinator species from 6 orders associated with it.
Evangelos gave an outline of his work looking at light penetration into lakes using satellite imaging. He then went on to explain to us biologists the applications of applied physics, such as playing pool.
The first paper of the night was presented to us by Gregor. The paper written by Healy et al., was titled: Metabolic rate and body size are linked with perception of temporal information. The article was intriguing to all and led to a lengthy discussion into the potential mechanisms for such increased visual perception speeds. Gregor also highlighted that in the literature, regions of insect eyes that have greater perception speeds (associated with mate assessment) are often called “love spots”. This hypothesis of ‘slow motion’ vision could have an interesting implication for my own work on acute visual zones in the eyes of male dance flies.
We then pondered the potential for sexual dimorphism in sensory perception systems due to different energetic requirements between males and females. The reasoning was that “females are egg machines” and so males may have higher levels of energy to expend on the metabolic costs needed for greater sensory perception speeds.
Healy, K., McNally, L., Ruxton, G.D., Cooper, N. & Jackson, A.L. (2013). Metabolic rate and body size are linked with perception of temporal information. Animal Behaviour, 86, 685-696.
Link to paper: HERE
The second paper was presented by Tom and was titled ‘Repeatability of behaviour: a meta-analysis’. This paper made some interesting suggestions about the repeatability of behaviours and the recording of behaviours both in laboratory and field experiments. Key points included the authors’ findings that male behaviours were typically more repeatable than female behaviours, possibly because females are more variable in their mate choice (maybe due to some system of learning). The important difference between process and measurement error was also discussed.
Bell, A.M., Hankison, S.J. & Laskowski, K.L. (2009). The repeatability of behaviour: a meta-analysis. Animal Behaviour, 77, 771-783.
Link to paper: HERE
We finally discussed the importance of fitting appropriate lines and error bars to graphs. Most importantly, when a variable has a definite top or bottom bound (such as data which can only be between zero and one), an error bar should not extend higher or lower than the point to which the data is limited.