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Wednesday, December 4, 2013 / Duncan Forgan

Are we in for a Really Bad Winter? Or how does long range forecasting work?

Duncan Forgan:

If you haven’t been following Research the Headlines, where Young Academy of Scotland members investigate how research is portrayed in the media, then check out one of my recent posts on weather forecasting. I’m managing their posts this month, so feel free to suggest any stories or topics you want us to cover!

Originally posted on :

At this time of year, the media is full of dire predictions for the upcoming winter.  The Daily Express’ recent headline stated that the Winter of 2013/14 was forecast to be ‘the worst in 100 years‘, with record snowfall and below-average temperatures from November onwards.  This headline came from long range forecasts given by Vantage Weather Services and Exacta Weather, private companies that generate forecasts independently from the more familiar Met Office.

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Tuesday, November 5, 2013 / Duncan Forgan

What if Civilisations Act Like Parasites? Implications for SETI

The parasitic alien civilisation in Independence Day

The parasitic alien civilisation in Independence Day

We have no way of knowing how an alien civilisation will act.  This is one of the biggest stumbling blocks of the Search for Extraterrestrial Intelligence.  After all, it’s very easy to explain away the lack of contact with alien life (Fermi’s Paradox) by simply saying “well, they don’t want to talk to us”, or “they’re not allowed to because of the Prime Directive“.  These sorts of arguments are the weakest solutions to Fermi’s Paradox, because they rely on knowledge we don’t have.

So how do we solve this conundrum? Sadly, we can’t – at least until we make first contact, that is.  So in the meantime, we are forced to play let’s pretend, and speculate on how alien civilisations will behave.  But we can still be sensible, and rein in our wilder ideas.  Ideally, our educated guesses should have a basis in something biological – not too Earth-centric, but in processes that we think must occur regardless of where life arises.

So Jonathan Starling and I turned to the concept of symbiosis.  Symbiosis describes the relationship between two different species.  These relationships can be broadly categorised as

  1. Parasitical – one species (the parasite) uses the other (the host) to its own advantage, having a negative effect on the host.
  2. Mutualist – both species benefit from the interaction.
  3. Commensalist – both species interact, and one benefits, but the host is not affected positively or negatively

We decided to model the interaction between a civilisation and its host planet in the same way, using my computer models of civilisation growth in the Milky Way, to see how this would affect the number of communicating species in the Galaxy.  Our simulated civilisations can either feast on their planets, destroying it as a deadly virus kills its host, or they can work with their environment, in a slower but more rewarding growth.

But what happens when the virus can jump from one host to the next? If a deadly virus has plenty of new hosts within close distance, it can kill its host and jump to the next without killing itself.  But if there are not enough new hosts, then the virus will die.

We added interplanetary and interstellar colonisation into the model to see how different species behaviours are transmitted into the Milky Way at large.  Does it pay to be a parasite, sucking your planet dry and moving on? Or do better behaved, less aggressive civilisations win the day?

The number of hosts/planets available to a civilisation will depend on how “near” they seem, which depends on how quickly the civilisation can travel.  A fast ship will be able to cross larger distances and “infect” planets more easily.  We ran the model several times, increasing the maximum colonisation speed from Voyager’s velocity, 10x Voyager’s velocity to 100x Voyager’s velocity.

These top speeds we are setting for these colonising species aren’t particularly high: Voyager is currently travelling at about a hundred thousandth of the speed of light.  A clever probe might be able to use gravitational slingshots to boost up to nearer a hundredth of the speed of light.

We found that if the civilisations can only colonise slowly, then it doesn’t pay to be a parasite.  As you can see from the graph, mutualists (blue) tend to do better than the parasites (red).

The number of civilisations in the Galaxy with time.  The red line shows the parasites, the blue the mutualists, and the black line is the total.

The number of civilisations in the Galaxy with time, in our model. The time parameter is scaled so that 1=the present, and 0=the Big Bang.  The red line shows the parasites, the blue the mutualists, and the black line is the total.

As we increase the velocity, we increase the number of available hosts, making it less costly to be a deadly parasite, until at 100x Voyager’s velocity, parasites dominate the Galaxy, colonising and destroying planets that would have hosted benevolent civilisations, before the good guys could even pick up tools.  This is analogous to invasions of species on Earth – sometimes, a species will enter a local ecosystem from outside and simply out-eat and out-breed its competitors.  In the UK, the grey squirrel’s dominance of the native red squirrel is a classic example.

Colonising at high speed allows the parasites to leave the mutualists behind and conquer the Galaxy.

Colonising at high speed allows the parasites to colonise mutualist planets before they develop civilisations, and conquer the Galaxy!

So what does this mean for the real world? Sadly, not as much as we would like.  This work is a speculative exercise in civilisation behaviour, a somewhat contrived numerical gedankenexperiment in a sandbox.   It doesn’t solve the problem of our ignorance of other civilisations’ behaviour.  It describes a (most likely fictional) Milky Way where civilisations develop one behaviour type very early in their existence, and don’t learn from their experiences.  The survival of the human race has depended (and will depend) on our ability to understand and move on from our mistakes!

But, the message of this experiment is important.  Once a parasitical civilisation passes the technological barriers to interstellar colonisation – at a speed that is relatively modest – then it will make its presence felt very quickly.  In this scenario, we must solve Fermi’s Paradox with one of the following possibilities:

i) Interstellar travel is impossible or very difficult;

ii) Parasitical civilisations have a very short lifetime – they either destroy their host and themselves, or they change their behaviour and stop being parasites

iii) Parasitical civilisations are not that common in the first place

Ultimately, Jonathan and I wanted to use this experiment to reflect on humanity’s relationship with the Earth.  Are we parasites, commensalists or mutualists? I’d love to know your thoughts in the comments below.

Monday, September 23, 2013 / Duncan Forgan

Search for Exomoons Around Kepler-22b Strikes Out (This Time)

It’s been a real pleasure to take my theoretical work on the habitability of exomoons out into reality, with the Hunt for Exomoons with Kepler (HEK) team. We’ve recently had this paper accepted for publication, where we used the Kepler Space Telescope’s data on Kepler-22b to search for an exomoon around it.

Image Credit: NASA/Ames/JPL-Caltech

Image Credit: NASA/Ames/JPL-Caltech

Kepler-22b was the first transiting exoplanet to be detected inside the habitable zone of its host star, a G type star very much like our Sun. As you no doubt know, the habitable zone is the region around a star where, if you placed a planet like the Earth, you would expect the surface water to be warm enough to be liquid, and potentially suitable for life. Sadly, Kepler-22b is not a planet like the Earth. We know this because its radius is 2.4 times that of the Earth (for comparison, Neptune is about 4 Earth Radii, and Jupiter is about 10 Earth Radii). We don’t know its mass for certain, but until now we knew that it couldn’t be any larger than 82 times that of the Earth(!).

It’s not clear at this point whether Kepler-22b is a really massive terrestrial planet, or a mini Neptune, but it’s clear that it’s not Earthlike, so its position in the habitable zone doesn’t mean very much for astrobiologists. However, if Kepler-22b had moons the same mass as the Earth, then those moons could themselves be habitable.

Exomoons are hard to detect directly, but they can be detected indirectly by studying their host planet in detail. If Kepler-22b has an exomoon of a sufficiently high mass, then we would be able to see the effects of the exomoon’s gravitational pull on the exoplanet in transit data. Transits rely on the planet obscuring starlight as it passes in front of it. The moon would show itself by subtly altering the time between individual transits, as well as how long the transits last for.

The HEK team have been searching the Kepler transit data for a few years without success (so far). This might sound a bit negative, but this lack of results still tell us something about how frequently moons of a given mass exist in the Galaxy. Kepler 22b is HEK’s first attempt to spot a moon in the habitable zone. A detection here would be pretty amazing…

Alas, we did not detect an exomoon around Kepler-22b – at least, no moon bigger than half an Earth mass. A non-detection is not as fun as a detection would have been, but a null result is a result nonetheless.  And don’t forget, the moons of our Solar System are nowhere near as big as half an Earth mass – Saturn’s moon Titan is about 0.02 Earth masses – so we can’t say for certain that Kepler-22b is moonless.  Also, this very in-depth analysis brings out extra info about Kepler-22b itself.  The upper limit for Kepler-22b’s mass is now a mere 53 Earth masses instead of 82, and its orbit is known to much greater certainty than it was before.

So why was I involved in this work? My job was to help the HEK team assess how well they can detect exomoons – in particular, how well they can determine if an exomoon is habitable. The team injected a fake moon into the transit data, and then used their software to see if they could find it. The algorithm they use doesn’t give data for one moon out as an answer – instead, it gives a whole selection of moons, with properties clustered around the “true” values. This is a way of expressing the uncertainty or error bars in the answer.

I took this selection of moons, and ran each one through the climate models I developed. This gives a series of climates, some warm, some hot and some cold. I also ran the “true” moon through the model, giving the “true” climate of the moon, which it turns out was warm.

Results from my analysis of the output of the HEK algorithm.  The "true" moon the HEK team injected into the data is warm, so the algorithm does pretty well!

Results from my analysis of the output of the HEK algorithm. In summary – the algorithm does a pretty good job!

I was pleased to find that the selection of moons produced by the algorithm produced climates that were on the whole very similar to the true climate. So, the algorithm does a very good job of determining an exomoon’s properties – good enough for us to be confident enough to determine if the moon could be habitable.

It’s just a shame there wasn’t a real moon for us to find…


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