Three Dog Star Night (Part 2)

Welcome back to our discussion on the Drake Equation and the Fermi Paradox! If you haven’t read part 1 already, it goes without saying that you should start there! This time around, we will be discussing what we know about habitable planets… or at least what we think we know. Strap in, friends. This is going to be a long one.

Before we proceed any further we need to introduce the concept of ‘filters’, i.e. factors that may inhibit the development of life and, ultimately, intelligent, detectable civilizations (IDCs) on a given planet. It is crucial to keep in mind that all proposed filters are not absolutes, rather they are speculative reasons why IDCs may be rare, thus resolving the Fermi Paradox. For convenience we can designate “Lesser” filters as those which eliminate 0% to 50% of all planets, “Minor” filters which eliminate 50% to 90%, “Major” filters which eliminate between 90% and 99.9999%, and finally “Great” filters which eliminate 99.9999% to 100% of planets. With this caveat in mind, we move on to our next parameter in the Drake Equation.

The Average Number of Habitable Planets per Star with Planets, ne

In order to determine what types of planets can support life, we first need to know what conditions are actually right for life, a difficult task given our current sample size of one. Of the eight planets in our solar system, only Earth is known to host any life at all. Though the emerging field of astrobiology is beginning to shed new light on the issues of whether or not life could have existed on Mars and Venus in the past or concurrently in the subsurface oceans of moons like Enceladus and Europa, the question remains open. Note that we are only looking for planets with the potential to support any life for this number, be it microbial or otherwise. We certainly do not expect microbes to start sending messages out into space, but the distinction between life and intelligent life is one that will be accounted for by subsequent numbers in our equation. This will allow us to save many of our potential filters for later and simply focus on habitability in all its possible forms. Sadly, those that remain are the ones we are most certain about.

We can begin to approach the problem by flipping it around, instead asking the reverse, “What conditions preclude life from developing?” If we focus exclusively on planets, our sample size has septupled since there are seven planets in our solar system that are known to not support life. Investigating the factors that prevented life from existing for a significant amount of time provides us with some starting filters which allow us to eliminate entire swaths of planets from the veritable zoo of those discovered.

Filter 1 – Location, location, location!

The clichéd real-estate adage provides us with our first filter. Since we are focusing solely on the Milky Way, we don’t need to worry about galaxy type. Our own existence is proof that our galaxy is among those that are right for hosting life, so we need not concern ourselves with filters like active galactic nuclei, galaxy mergers, etc. However many astronomers propose that a star system’s location within a galaxy is an important factor. There may very well be a so-called “habitable zone” on the galactic scale in addition to that found around the individual stars themselves. Close to the crowded galactic center a system is likely to be subjected to nearby supernovae, migrating black holes, asteroid/comet impacts, passing pulsars, and other devastating natural phenomena with the potential to sterilize entire planets. On the other hand, systems at the galaxy’s edge are unlikely to have enough nearby gas and dust to sufficiently drive the formation of stars and planets. The average stellar metallicity (how much of a star is composed of elements heavier than helium) declines as distance from the center increases, so stars near the galaxy’s edge are expected to have fewer rocky, potentially life-sustaining planets. As it turns out, this may not ultimately be the case as some data suggests rocky planets could be more common around lower-metallicity stars, but for now this will be our working assumption.

This limits the expected life-sustaining region of our galaxy to stars whose orbits lie from at least 1 to at most 10 kiloparsecs from the center. For reference the Milky Way has a radius of only about 15 kiloparsecs, and with a little data and some rough assumptions, one can calculate that only around 10% of all stars in our galaxy lie in this region. This number is still staggeringly large and includes, to first order, around 20-40 billion stars or so. Of those we can reasonably exclude the 10% of stars in our galaxy that are not on the main sequence. Given that the average number of planets per star may be as high as 10 on the extreme optimistic end, this leaves a maximum of about 360 billion planets to work with.

In addition to the galaxy, the stars themselves each have their own habitable zones, defined as the range of orbital distances within which liquid water could conceivably exist on the surface in large quantities. There are only three planets in our solar system that exist more or less within the sun’s habitable zone: Venus, Earth, and Mars. Of these three, Venus and Mars are each close to the edge of what can be considered the habitable zone, and given the concept’s speculative nature these boundaries could grow or shrink with new information. The most we can do right now is place an upper limit on this value of 6, based on research by Dr. Christa Van Laerhoven and her colleagues, though the actual number is almost certain to be lower. For simplicity, we can estimate the average number of planets in a star’s habitable zone to be 3. The size and location of the habitable zone is determined by the type of star. Large stars (O, B, and A types) account for only about 7% of all stars and tend to burn out too soon for complex life to really gain a foothold. It’s uncertain whether planets around smaller, red dwarf stars might host life. The data indicates the planets orbiting in their habitable zones may be tidally locked to the star just as the moon is to the Earth, with one side facing the star at all times. While this doesn’t preclude life from forming, it certainly makes things more difficult. Red dwarf stars may account for as much as 75% of the stars in our galaxy, so whether they should be included in the search for life is a crucial question that will hopefully be answered as more data becomes available. Nonetheless we have our next filter: of the main sequence stars, at most 93% of them are expected to be habitable.

There are without a doubt more particulars of planetary arrangement that come into play here, such as having a stable, mostly circular (low eccentricity) orbit, the role gas giants like Jupiter may play as cosmic vacuum cleaners, and more, but the only thing we know for sure regarding the rest of the Location Filter is that we just don’t know.

Filter 2 – Earth-Sized:

Planets that are too large tend to be gas or ice giants, with no solid surface and crushingly thick and turbulent atmospheres. Life could form here, but if it does, it’s likely the exception rather than the rule. At the same time, the cores of planets that are too small tend to cool too quickly and lose their magnetic fields and subsequently their atmosphere to stellar winds. Mars is a perfect example of this. Looking at the best current estimates, we can see that only around 1,237 of the 4,370 exoplanets discovered so far are “Earth-sized”, i.e. range from 0.8 to 2 Earth radii. We can be generous here and allow for the fact that exoplanet survey methods are biased towards larger planets by estimating that perhaps 40% of planets are Earth-sized.

Filter 3 – Atmospheres, Plate Tectonics, and Moons:

Being Earth-sized helps when holding onto an atmosphere, but this does us no good if it isn’t the right atmosphere, and we need look no further than our own solar system for the perfect illustration of this. Venus is 93% the mass of the Earth, yet its atmosphere is crushing at a choking 100 times the density of Earth’s. Unlike our own atmosphere which is about 70% Nitrogen, Venus’s atmosphere is more than 96% CO2, 30 times the CO2 concentration of our own atmosphere. This runaway greenhouse effect famously makes Venus the hottest planet in the solar system, with surface temperatures hot enough to melt lead. Unfortunately we have no real data for this yet as we lack the ability to reliably observe exoplanet atmospheres, though that is expected to change with the launch of the James Webb Space Telescope set to launch in October of 2021. For now, we will be generous and use our own solar system as the model by assuming that 50% Earth-sized planets do not have the right atmosphere for life.

Two other factors that make Earth, well, Earth-like are plate tectonics and our Moon. Plate tectonics play a crucial role in cycling numerous elements, including carbon and phosphorus, in and out of the environment. It’s thought that Earth’s water and the theoretical collision with a Mars-sized planet which formed the moon are two of the main factors that got plate tectonics going. Venus, which lacks both, shows no signs of tectonic activity, past or present, even though its core is known to still be molten and active. The Moon is somewhat of an anomaly in its own right. Of all the planetary moons in the solar system, it is by far the largest relative to the size of its host planet. Its existence helps to stabilize Earth’s axial tilt and over billions of years, through a quirk of angular momentum conservation, gradually slowed our planet’s initially brisk rotation to the 24 hour day/night cycle we experience today. It also generates tides and thus tidal pools, which some theories for abiogenesis claim provided the conditions for the origin of life on the early Earth. Again, we will be generous here and presume that 1 in 2 Earth-sized planets in the habitable zone of their star are actually Earth-like.

Filter 4 – Phosphorus Scarcity:

A recent study of two supernovae remnants, the Crab Nebula and Cassiopeia A, by Dr. Jane Greaves of Cardiff University and her team suggests that phosphorus may be produced in vastly different quantities during supernova nucleosynthesis. It’s somewhat common knowledge, even among the general public, that the Big Bang produced only Hydrogen, Helium, and a possibly a small amount of Lithium, and that all elements higher on the periodic table were produced in the cores of stars as byproducts of nuclear fusion, a process known as hydrostatic burning, but this is only half of the story. Stellar nucleosynthesis can only account for the production of a specific set of elements, most of which have an even number of protons due to their fusion being reliant on Helium and none of which are heavier than Zinc (element 30). All elements with more than 30 protons can only be naturally produced by what happens after stellar nucleosynthesis ends, in the explosive deaths of stars and the violent collisions of their remnants. As the star collapses infalling matter piles up and is “bounced” back out, producing large numbers of neutrons and sending shockwaves through the star’s layers which quickly fuse lighter elements into heavier ones through the process of rapid neutron capture, known as the r-process. In fact the majority of the elements trace their origins to events beyond the cores of main sequence stars as can be seen in the chart below. All of this results in massive discrepancies in universal abundances between elements, shown in the second image. Taking particular note of what the data shows regarding the six elements considered most critical for life: Hydrogen, Carbon, Nitrogen, Oxygen, Phosphorus, and Sulfur. Phosphorus in particular is required for the metabolic processes of all known cells (via ATP) and forms the backbone of both DNA and RNA, yet it is by far the least common of the six.

(By Cmglee – Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=31761437, based on data by Jennifer Johnson at Ohio State University)

The most likely production process involves a silicon-30 isotope capturing a neutron during the supernova, briefly becoming unstable silicon-31 before one of its neutrons emits an electron and an antineutrino to decay into a proton, transmuting the atom into phosphorus-31, the element’s only stable isotope. The problem is that silicon-30 is not the most abundant Si isotope, accounting for only about 3.1% of all naturally-occurring Silicon, and its cross-section for neutron capture is quite small, meaning a neutron has to hit it just right to get absorbed. Supernovae are not evenly distributed around the galaxy, and thus we already expect that phosphorus isn’t either. Should it be the case that Phosphorus is not a ubiquitous byproduct of supernova nucleosynthesis, the element will only be rarer and more unevenly distributed than previously thought. There could very well be entire swaths of the galaxy with virtually none at all.

While it might be possible for life to develop that does not rely on phosphorus, the chances of that actually happening are probably slim, and such life would be the exception rather than the rule. We ourselves are composed of approximately 1% phosphorus, the planet’s crust is about 0.1% phosphorus, and the entire solar system is roughly 0.0007% phosphorus by mass. On the scale of the entire universe, phosphorus only accounts for about three of every ten million atoms, or 0.00003%, and would have been even lower than that when our solar system began to form 5 billion years ago. Naturally, older star systems are expected to have less phosphorus on average as fewer phosphorus-producing supernovae would have occurred prior to their formation. Even our apparent relative abundance of phosphorus is so low that it presents a problem for scientists seeking to tease out the origins of life. Phosphorus also tends to bind into molecules that are heavier and thus would have sunk towards the core during the planet’s formation, though the collision which we think formed our Moon may have played a role here in dredging some up from the Earth’s interior. Its common compounds also tend to be insoluble in water which is problematic since life processes are pretty much predicated entirely on water solubility. Unlike the Earth’s carbon cycle which is relatively quick on geological timescales and involves the atmosphere as well as the planet’s interior, the phosphorus cycle is one of the slowest and independent of the atmosphere, so biologically-available Phosphorus is only refreshed by tectonic activity. That life should rely so ubiquitously on phosphorus despite its apparent scarcity tells us either that phosphorus-based life is easier to form than non-phosphorus-based life or that life based on phosphorus has an evolutionary advantage over life that is not. Possibly even both. Water is quite common in the universe, and so it may be that Phosphorus is what makes Earth truly unique among the planetary zoo.

Until there is conclusive evidence one way or another, we can take this potential filter with a grain of salt and estimate that only 50% of planets have a sufficient amount of Phosphorus present on the surface. We can now combine all our filters into one to calculate a final value for ne and find that several Lesser and Minor Filters have combined to form one Major Filter. With less optimistic estimates, such as excluding red dwarf stars, and a few more assumptions and factors accounted for, this has the potential to reach Great Filter status and serves as the foundation for the Rare Earth Hypothesis.

 

ne, Optimistic = 3 x 0.1 x 0.9 x 0.93 x 0.4 x 0.5 x 0.5 x 0.5 = 0.0125

ne, Rare Earth < 0.000001

 

For now, this is where we will leave the second half of our discussion of Drake’s equation. We can take all the factors we’ve discussed so far, multiply them together, and multiply this value by the length of time life has existed on Earth (3.5 billion years) to get a somewhat crude estimate for the number of planets in the galaxy which might contain life in any form.

NOptimistic = 131,250,000

NRare Earth < 10500

When compared against the hundred billion or so planets that are estimated to reside within the Milky Way, even our deliberately generous estimate indicates that only around 0.13% of planets harbor any life at all. If we apply the Rare Earth filter for ne, then only about 0.00001% of planets in the Milky Way are safe havens for life. These numbers will only diminish as we start accounting specifically for intelligent life in subsequent factors of the Drake Equation. After all, the Fermi Paradox is specifically about why we haven’t heard from any other intelligent life, not merely the chances that extraterrestrial life in general exists.

Next time we’ll be discussing that second half of the Drake Equation and the implications further proposed filters have for our chances of detecting intelligent life within the Milky Way. Unfortunately, the last three factors rely heavily on speculation in the absence of virtually any reliable data, and we will delve deep into some of that speculation in part 3. In part 4 we’ll discuss the final factor of the equation and run some example calculations before finally delving into what the Drake Equation actually is. In the meantime, if you’d like to try your hand at estimating the number of inhabited planets or intelligent civilizations in the universe, you can use this handy link for calculating the Drake Equation.

Your journey starts here! Let’s talk!

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  Timothy Durham was convicted of rape when a test showed his DNA genotype matched the DNA recovered from the crime scene. Eye witnesses testified that Durham was in a different state at the time of the incident, but he wasn’t exonerated from his 3000 year sentence until follow up DNA analysis showed that the preliminary forensic analysis used in the trial was misinterpreted (Thomas et al.). DNA testing serves an invaluable part in our criminal justice system, but it comes with complications and bias that can lead to wrongful convictions and misinformed juries.  

Background:

Forensic genetics aims to identify the origin of a biological sample. It can be traced back to Karl Landsteiner who discovered human ABO blood groups. With blood groups, suspects could be eliminated based on their blood type. For example, if a suspect had type A blood and there was type B blood left at the scene by the perpetrator, the investigators could rule out the suspect. Unfortunately, the reverse didn’t work. If the suspect and perpetrator both had the same blood type, it can’t be concluded that the suspect was guilty. Blood identifiers evolved into 8 distinct categories which improved the ability to eliminate suspects, but could only conclude that (if the system matched) it might be the perpetrator or this person might be related to the perpetrator (Jobling and Gill). The field evolved in the 1980s with the discovery of Minisatellites, lines of repetitive DNA that don’t encode proteins. Minisatellite patterns in DNA create what we know today as the DNA fingerprint, and it has a much higher accuracy rate than previous methods (Augustyn et al.). Around the same time, a breakthrough for victims of sexual assault was discovered. In the case of assault, bodily fluids of both the victim and the assaulter can get mixed. A process called differential lysis was created which could selectively increase the concentration of sperm in a fluid sample thereby allowing for accurate DNA testing (Jobling and Gill). Forensics evolved to use single-locus probe testing after several years because of its ease of interpretation. It looked at specific minisatellites that had high variability between subjects. This was the first DNA-based method to be used in a criminal investigation. Two murder homicides from several years apart were connected using DNA evidence. The evidence was then used to exonerate an innocent man, and the guilty party was found when he tried to evade mandatory DNA testing for all men in the small town. His guilt was then reinforced when the DNA profiles matched, and he gave a confession (Jobling and Gill). Finding DNA at a crime scene doesn’t guarantee that you’ll find a murderer. There are issues with non-pure samples and limited samples that make DNA work difficult, and accreditation of facilities and new techniques and take time (Jobling and Gill).  

Subjectivity of DNA Interpretation:

In a 2009 publication, the National Academy of Science discusses the possibility for subjective influence in lab based forensics. The interpretation bias happens in complex cases where, for example, there could be a mixture of DNA. A study published in 2011 looked specifically at this issue. A gang rape happened in Georgia, and the mixture in DNA from the case was used to prosecute one suspect after another suspect took a plea bargain to testify against him. With DNA mixtures, there are three possible conclusions: suspect excluded, suspect cannot be excluded, and inconclusive. If the suspect is excluded, it means that there’s little to no possibility that his DNA is part of the sample. If the suspect cannot be excluded, it means that there’s a possibility that his DNA is part of the sample. In the trial, the DNA examiners who knew the context of the case concluded that the suspect being prosecuted could not be excluded. The 2011 study gave the DNA evidence from this case and the DNA profiles of the suspects to 17 forensic examiners. These examiners had no context of the case, and they all worked independently. Of the 17, only 1 came to the same conclusion (suspect cannot be excluded) as the examiners who knew the context of the case. Twelve of the 17 concluded that the suspect who was prosecuted and convicted had no relation to the DNA found in the sample. Not only does this show that subjectivity occurs due to the context of the case, but the 17 examiners came up with different findings based on their past experiences meaning that not all DNA analysis is objective. Some organizations like the Scientific Working Group on DNA Analysis Methods say that quantitative statistical evidence should be presented with every categorical conclusion, but the US doesn’t require this (Dror and Hampikian).

False Positives:

There are two categories that cause wrongful identification in a DNA report: coincidental matches and false positives. Coincidental matches are DNA matches between two unrelated people. The probability of these matches is about 1 to 500,000 for white individuals and about 1 to 350,000 for black individuals. This small probability of coincidental matches makes people feel confident in DNA evidence. False positives, on the other hand, are matches between DNA and test DNA that result from issues in the forensics lab. There have been multiple cases of forensics labs accidentally switching victim and suspected rapist DNA which lead to convictions that were later overturned when the lab realized the error. There are also cases of misreading or misunderstanding a sample. In a case from 1993, a man was convicted of rape because someone interpreted a mixed sample of victim and perpetrator DNA as an individual sample. The conviction was again overturned. To prevent false convictions, retesting DNA is allowed, but it’s not an efficient solution. Many people are pushing for statistical information on the probability of false positives, so that the jurors can make accurate judgements based on DNA evidence (Thomas et al.).  

Conclusion:

DNA analysis is a useful tool for the criminal justice system, but subjectivity can be an issue in forensic testing. To combat wrongful convictions, there are organizations like The Innocence Project who use DNA testing to free the innocent, but reformed forensic testing standards should be put in place to prevent subjectivity and to ensure juries are correctly informed during trials. https://www.innocenceproject.org/    

Citation:

Augustyn , Adam, et al. “DNA Finerprinting.” Encyclopedia Britannica , 26 Apr. 2018, www.britannica.com/science/DNA-fingerprinting#ref153186. Dror, Itiel E., and Greg Hampikian. “Subjectivity and Bias in Forensic DNA Mixture Interpretation.” Science & Justice, vol. 51, no. 4, 2011, pp. 204–208., doi:10.1016/j.scijus.2011.08.004. Jobling, Mark A., and Peter Gill. “Encoded Evidence: DNA in Forensic Analysis.” Nature Reviews: Genetics, vol. 5, no. 10, Oct. 2004, pp. 739–751., doi:10.1038/nrg1455. Thompson, William C, et al. “How the Probability of a False Positive Affects the Value of DNA Evidence.” Journal of Forensic Sciences, vol. 48, no. 1, Jan. 2003, pp. 1–8., doi:10.1520/jfs2001171.