Glen Paul: G'day, and welcome to CSIROpod. I’m Glen Paul. You no doubt remember the childhood nursery rhyme about the old lady who swallowed a fly, then a spider to catch the fly, then a bird to catch the spider, and so on, describing in simplistic terms the food chain, that is, the organisms that contribute to the diet of the top consumer.
A food web on the other had is a diagram of the links amongst species in an ecosystem, essentially who eats what, and is similar to a social network, both being represented with nodes and dependencies. It’s now believed that techniques developed to study human social relationships can be used to analyse feeding relationships in nature, and techniques normally used to study who talks to who can be applied to different ecosystems to find out who eats who?
Joining me on the phone is CSIRO Environmental Statistician, Dr Grace Chiu, who recently released a Paper about using social network analysis to study food webs. So Grace, how do you use something that’s used to describe human interaction to then analyse the food web?
Dr Chiu: Well Glen, if you can imagine having any kind of interaction basically means you’re looking at the individuals connecting with each other, so whether it be looking at human interactions connecting with each other, or animals connecting with each other through feeding, essentially it’s the same idea.
Glen Paul: OK. I’m beginning to see how this might work. So how do you actually translate this then to the food web in nature? How does it work?
Dr Chiu: Now, how it works is a lot of times if you consider a set of individuals and they have interactions among each other, you would look at who’s instigating the interaction in the sense of friendship – typically something like I want to be friends with you Glen, so I ask you to be my friend, so it's a direction that comes from me to you.
With food webs it’s exactly the same. If I have a shark eating a seal, you can think of it as the seal sending itself to the shark’s stomach, and so the direction comes from the seal to the shark. Alternatively you might want to consider the shark instigating an attack to the seal, so the direction would go the other way. But conventionally it is whoever’s being consumed is the sender.
Glen Paul: OK, so you’re basically joining the dots?
Dr Chiu: Hmm.
Glen Paul: So to which ecosystems did you actually apply this method to?
Dr Chiu: In our paper, my co-author, Anton Westveld, and myself looked at eight very well studied food webs from the literature – one of them is from the U.S. being close to the Florida coast, another one is from the U.K., and there are other ones from other parts of the world, such as the Caribbean – so there are quite a few different geographical locations that we covered with the data that we considered in our Paper.
Glen Paul: Now I know there’s a social media aspect to this research, which sounds very novel, but can you tell me how does studying Facebook and Twitter let you know who’s eating who in the food web?
Dr Chiu: Now, Facebook and Twitter don’t necessarily tell us about who eats who – that's not really what Twitter and Facebook are about – except that if you consider the kind of interaction data that would arise from Facebook networks and Twitter networks, essentially it's the exact same kind of situation with food web interactions, or feeding interactions within food webs.
So in Twitter, let's say there is an originator of a tweet, somebody sends out a tweet, and then other people within the well defined network would tweet back potentially, and not only tweeting back, but also maybe tweeting to a whole bunch of other people who are following the originator’s tweets. And then one tweet leads to another, to another, to another, within the network, and the same kind of situation happens with food webs.
If I have a shark eating a seal, well then the seal may eat other kinds of animals, such as squid, or maybe vegetation. And the squid may eat something else, like krill, which is a tiny little shrimp like animal.
And the squid can also be eaten by other things, maybe other kinds of sharks. So again it’s one interaction leading to another, leading to another, but all of those interactions happen within the same network. So if you think of how one might study friendship in a social network such as Twitter, essentially the techniques can be equally applied to studying feeding interactions within the food web.
Glen Paul: I can certainly understand why sharks would want to follow as many seals as they could. So where did the idea for this come from?
Dr Chiu: The idea of using social network techniques, or social network analysis techniques, to study food webs is not a new idea. Actually there’s a lot of literature out there that has applied social network analyses to feeding interactions, but where it came about for us is that my co-author, Anton Westveld, he is a Statistician that studies mainly social sciences, whereas for me I’m a Statistician that studies environmental sciences.
So he was actually very familiar and has a lot of expertise in using statistical social network analysis tools to study social networks – in something like trade, where countries might export to other countries, and import from either the same countries, or other countries altogether; also military attacks, whether a certain country instigates an attack to another country, who are their allies – so he is an expert in that area.
Now for me, I know very little about social sciences, or applications in the social sciences, but I have always worked a lot in ecology, so when I first saw his work in the social sciences I thought, "Wow, that is totally applicable to food webs." So that’s when our work started.
Glen Paul: Hmm, and I can see it really wouldn’t be too much of a stretch to bring the two together. And if listeners would like to find out more they can find the Paper on the Proceedings of the National Academy of Science's U.S. website. Thanks for discussing it with me today, Grace.
Dr Chiu: Thank you so much, Glen.
Glen Paul: Dr Grace Chiu. For more information find us online at www.csiro.au. You can like us on Facebook, or follow us on Twitter at CSIROnews.