META-ANALYSES: SEXUAL SELECTION AND AGING

BACKGROUND

Theory predicts that sexual selection affects the evolution of ageing and lifespan. Lots of individual experiments have now tested this idea. What we want to do is to put all of the results of these experiments together to see if across different species, sexual selection affects ageing and how.

Specifically, we could ask these questions:
1. Within species, do males that invest most in sexual competition (e.g. have the biggest antlers or brightest plumage) age more quickly?
2. Among species, do those that exhibit more intense sexual selection (e.g. species with harems) age faster? Does this happen in one or both sexes?
3. Since the intensity of sexual selection may generally be reflected in sexual dimorphism, does sexual dimorphism co-vary positively with dimorphism in mortality and ageing?
4. Which features of the ageing trajectory experience the strongest and most divergent patterns of selection in the sexes? This means do males and females differ in how quickly they age, or how old they are when ageing starts.
5. How does either sex manage reproductive effort over the life-course and how do these differences related to ageing & lifespan?

HOW CAN WE DO THIS?

In a perfect world, we want to collect studies that measure lifespan and aging (this is measured in lots of ways, usually by fitting different models that describe how the risk of dying increases over time) and reproductive effort in young and old animals for both males and females.
I think the kind of studies we can use will probably be one of these types:

1. Studies where experimenters artificially select on traits that we are interested in (e.g. lifespan, how attractive males are) in one sex and see what happens to other traits in both sexes. (Hunt et al. 2006)

2. Studies that measure age dependent reproductive effort in both sexes, ageing and lifespan. These might not apply any treatment at all. (Zajitschek et al. 2009; Archer et al. 2012)

3. Studies that relate ageing / lifespan to investment in a sexually selected trait. For example, studies that see how male antler size is associated with lifespan. These might not apply any treatment at all but might take advantage of natural variation in a particular trait.

Not all of these papers will have all the information we want, for example, the third type may only have information on male reproductive success and lifespan. That is ok, we can still work with this information.

HOW TO FIND THESE PAPERS

To find papers we can use we need to use very specific search terms in a search engine like Google Scholar. We need to record the search terms we use because these have to go in the methods section of your paper.
First, I would search for:

ageing OR aging OR senescence AND "sexual selection" AND gompertz OR weibull OR logistic OR makeham in GoogleScholar and ISI Web of Science from 2000 to today (these yellow bits are different ways of measuring aging) Hope that gives us loads of data but if not, expand:
ageing OR aging OR senescence AND "sexual selection" AND gompertz OR weibull OR logistic OR makeham OR lifespan OR longevity

You might want to do this year by year e.g. 2000-2000 so that you don't get too many papers in one go.

Once you have papers that we will use, you can look in their reference lists to see if there is anything else that is useful.

You can also look in key papers that talk about how sexual selection could affect aging (Bonduriansky et al. 2008; Adler & Bonduriansky 2011) and see which papers they cite that could be useful.

It is really, really important that you write down all the search terms and methods you use to find data. This will go in your paper in the methods section!

ONCE YOU HAVE FOUND PAPERS - WHAT DATA DO WE NEED?

It is kind of hard to predict exactly what data we will need to record until we know which papers are out there. But, I would guess you should collect these bits of information. I would also try hard to keep names consistent - it will make life easier when you analyze these data.

No# of Pages: 20 pages (5000 words)