Did microbes cause the Great Dying?

In one of my very first posts almost a decade ago, I wrote about the end-Permian extinction 250 million years ago, which was the greatest mass extinction thus far. In that post I covered research that had ruled out an asteroid impact and found evidence of global warming, possibly due to volcanos, as a cause. Now, a recent paper in PNAS proposes that a horizontal gene transfer event from bacteria to archaea may have been the main cause for the increase of methane and CO2. This paper is one of the best papers I have read in a long time, combining geological field work, mathematical modeling, biochemistry, metabolism, and evolutionary phylogenetic analysis to make a compelling argument for their hypothesis.

Their case hinges on several pieces of evidence. The first comes from well-dated carbon isotopic records from China.  The data shows a steep plunge in the isotopic ratio (i.e ratio between the less abundant but heavier carbon 13 and the lighter more abundant carbon 12) in the inorganic carbonate reservoir with a moderate increase in the organic reservoir. In the earth’s carbon cycle, the organic reservoir comes from the conversion of atmospheric CO2 into carbohydrates via photosynthesis, which prefers carbon 12 to carbon 13. Organic carbon is returned to inorganic form through oxidation by animals eating photosynthetic organisms or by the burning of stored carbon like trees or coal. A steep drop in the isotopic ratio means that there was an extra surge of carbon 12 into the inorganic reservoir. Using a mathematical model, the authors show that in order to explain the steep drop, the inorganic reservoir must have grown superexponentially (faster than exponential). This requires some runaway positive feedback loop that is difficult to explain by geological processes such as volcanic activity, but is something that life is really good at.

The increased methane would have been oxidized to CO2 by other microbes, which would have lowered the oxygen concentration. This would allow for more efficient fermentation and thus more acetate fuel for the archaea to make more methane. The authors showed in another simple mathematical model how this positive feedback loop could lead to superexponential growth. Methane and CO2 are both greenhouse gases and their increase would have caused significant global warming. Anaerobic methane oxidation could also lead to the release of poisonous hydrogen sulfide.

They then considered what microbe could have been responsible. They realized that during the late Permian, a lot of organic material was being deposited in the sediment. The organic reservoir (i.e. fossil fuels, methane hydrates, soil organic matter, peat, etc) was much larger back then than today, as if someone or something used it up at some point. One of the end products of fermentation of this matter would be acetate and that is something archaea like to eat and convert to methane. There are two types of archaea that can do this and one is much more efficient than the other at high acetate concentrations. This increased efficiency was also shown recently to have arisen by a horizontal gene transfer event from a bacterium. A phylogenetic analysis of all known archaea showed that the progenitor of the efficient methanogenic one likely arose 250 million years ago.

The final piece of evidence is that the archaea need nickel to make methane. The authors then looked at the nickel concentrations in their Chinese geological samples and found a sharp increase in nickel immediately before the steep drop in the isotopic ratio. They postulate that the source of the nickel was the massive Siberian volcano eruptions at that time (and previously proposed as the cause of the increased methane and CO2).

This scenario required the unlikely coincidence of several events –  lots of excess organic fuel, low oxygen (and sulfate), increased nickel, and a horizontal gene transfer event. If any of these were missing, the Great Dying may not have taken place. However, given that there have been only 5 mass extinctions, although we may be currently inducing the 6th, low probability events may be required for such calamitous events. This paper should also give us some pause about introducing genetically modified organisms into the environment. While most will probably be harmless, you never know when one will be the match that lights the fire.

 

 

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What is the difference between math, science and philsophy?

I’ve been listening to the Philosophy Bites podcast recently. One from a few years ago consisted of answers from philosopher’s to the question posed on the spot and without time for deep reflection: What is Philosophy? Some managed to give precise answers, but many struggled. I think one source of conflict they faced as they answered was that they didn’t know how to separate the question of what philosophers actually do from they should be doing. However, I think that a clear distinction between science, math and philosophy as methodologies can be specified precisely. I also think that this is important because practitioner’s in each subject should be aware of what methodology they are actually using and what is appropriate for whatever problem they are working on.

Here are my definitions: Math explores the consequences of rules or assumptions, science is the empirical study of measurable things, and philosophy examines things that cannot be resolved by mathematics or empiricism. With these definitions, practitioner’s of any discipline may use either math, science, or philosophy to help answer whatever question they may be addressing. Scientists need mathematics to work out the consequences of their assumptions and philosophy to help delineate phenomena. Mathematicians need science and philosophy to provide assumptions or rules to analyze. Philosophers need mathematics to sort out arguments and science to test hypotheses experimentally.

Those skeptical of philosophy may suggest that anything that cannot be addressed by math or science has no practical value. However, with these definitions, even the most hardened mathematician or scientist may be practicing philosophy without even knowing it. Atheists like Richard Dawkins should realize that part of their position is based on philosophy and not science. The only truly logical position to take with respect to God is agnosticism. It may be probable that there is not a God that intervenes directly in our lives and that probability may be high but it is not a provable fact. To be an atheist is to put some cutoff on the posterior probability for the existence of God and that cutoff is based on philosophy not science.

While most scientists and mathematicians are cognizant that moral issues may be pertinent to their work (e.g. animal experimentation), they may be less cognizant of what I believe is an equally important philosophical issue , which is the ontological question. Ontology is a philosophical term for the study of what exists. To many pragmatically minded people, this may sound like an ethereal topic (or worse adjective) that has no place in the hard sciences. However, as I pointed out in an earlier post, we can put labels on at most a countably infinite number of things out of an uncountable number of possibilities and for most purposes, our ontological list of things is finite. We thus have to choose and although some of these choices are guided by how we as human agents interact with the world, others will be arbitrary. Determining ontology will involve aspects of philosophy, science and math.

Mathematicians face the ontological problem daily when they decide on what areas to work in and what theorems to prove. The possibilities in mathematics are infinite so it is almost certain that if we were to rerun history some if not many fields would not be reinvented. While scientists may have fewer degrees of freedom to choose from they are also making choices and these choices tend to be confined by history. The ontological problem shows up anytime we try to define a phenomenon. The classification of cognitive disorders is a pure exercise in ontology. Authors of the DSM IV have attempted to be as empirical and objective as possible but there is still plenty of philosophy in their designations of psychiatric conditions. While most string theorists accept that their discipline is mostly mathematical, they should also realize that it is very philosophical. A theory of everything includes the ontology by definition.

Subjects traditionally within the realm of philosophy also have mathematical and scientific aspects. Our morals and values have certainly been shaped by evolution and biological constraints. We should completely rethink our legal philosophy based on what we now know about neuroscience (e.g. see here). The same goes for any discussion of consciousness, the mind-body problem, and free will. To me the real problem with free will isn’t whether or not it exists but rather who or what exactly is exercising that free will and this can be looked at empirically.

So next time when you sit down to solve a problem, think about whether it is one of mathematics, science or philosophy.

The blinking-dot paradox of consciousness

Suppose you could measure the activity of every neuron in the brain of an awake and behaving person, including all sensory and motor neurons. You could then represent the firing pattern of these neurons on a screen with a hundred billion pixels (or as many as needed). Each pixel would be identified with a neuron and the activity of the brain would be represented by blinking dots of light. The question then is whether or not the array of blinking dots is conscious (provided the original person was conscious). If you believe that everything about consciousness is represented by neuronal spikes, then you would be forced to answer yes. On the other hand, you must then acknowledge that a television screen simply outputting entries from a table is also conscious.

There are several layers to this possible paradox. The first is whether or not all the information required to fully decode the brain and emulate consciousness is in the spiking patterns of the neurons in the brain. It could be that you need the information contained in all the physical processes in the brain such as the movement of  ions and water molecules, conformational changes of ion channels, receptor trafficking, blood flow, glial cells, and so forth. The question is then what resolution is required. If there is some short distance cut-off so you could discretize the events then you could always construct a bigger screen with trillions of trillions of pixels and be faced with the same question. But suppose that there is no cut-off so you need an uncountable amount of information. Then consciousness would not be a computable phenomenon and there is no hope in ever understanding it. Also, at a small enough scale (Planck length) you would be forced to include quantum gravity effects as well, in which case Roger Penrose may have been on to something after all.

The second issue is whether or not there is a difference between a neural computation and reading from a table. Presumably, the spiking events in the brain are due to the extremely complex dynamics of synaptically coupled neurons in the presence of environmental inputs. Is there something intrinsically different between a numerical simulation of a brain model from reading the entries of a list? Would one exhibit consciousness while the other not? To make matters even more confusing, suppose you have a computer running a simulation of a brain. The firing of the neurons are now encoded by the states of various electronic components like transistors. Does this means that the circuits in the computer become conscious when the simulation is running? What if the computer were simultaneously running other programs, like a web browser, or even another brain simulation?  In a computer, the execution of a program is not tied to specific electronic components.  Transistors just change states as instructions arrive so when a computer is running multiple programs, the transistors simulating the brain are not conserved.  How then do they stay coherent to form a conscious perception?  In a normal computer operation, the results are fed to an output, which is then interpreted by us.  In a simulation of the brain, there is no output, there is just the simulation. Questions like these make me question my once unwavering faith in the monistic (i.e. not dualistic) theory of the brain.