Category Archives: evolution

Matt Ridley — deep optimism at the Long Now

Matt Ridley explains why he is such an optimist at the Long Now.

Humanity’s lot has been improving for the last 10,000 years and he sees no reason this will stop, despite everyone’s claim that the world/civilization is going to heck in a handbasket.

He was a pessimist when he graduated college. He marks his conversion to the day he realized acid rain was not a problem.

Trade as the key thing which separates man from beast, and which powers all of our cultural growth.

His greatest concern is that religious fundamentalism will shut down trade and innovation. He is an athiest, though raised as an anglican. He considers this the mildest form of the virus, practically a vaccine.

Advertisements

The world’s oldest living organisms — Rachel Sussman

jomon sugi japanese cedar, the tree that launched the project. Photo by Sussman.

Rachel Sussman gives her talk at the long now. It might be easier to get the graphics from the TED version, then go to the LN version for the questions, which start from minute 41:15.

She finds three stratifications of organisms, by age. 2-5K, 10-20K, and 40K+ years.

Long-lived organisms tend to be extremophiles. Plants are heavily represented.

Ms. Sussman sells her prints via her website. I think she is also on kickstarter, but haven’t searched yet

The remarkable, yet not extraordinary, human brain as a scaled-up primate brain and its associated cost

Large brains appear several times in the mammalian radiation. Example species are illustrated for each major mammalian group. The mammalian radiation is based on the findings of Murphy et al. (18) and Kaas (19). Brain images are from the University of Wisconsin and Michigan State Comparative Mammalian Brain Collections (www.brainmuseum.org).

Herculano-Houzel S. The remarkable, yet not extraordinary, human brain as a
scaled-up primate brain and its associated cost
. Proc Natl Acad Sci U S A. 2012
Jun 26;109 Suppl 1:10661-8.

She review allometric scaling in mammals, noting first that it is more fine-grained than size alone by giving examples of animals with similar sized brains but different cognitive abilities. “The human cerebral cortex is 75.5% of the entire brain mass, other animals, primate and nonprimate, are not far behind: The cerebral cortex represents 73.0% of the entire brain mass in the chimpanzee (7), 74.5% in the horse, and 73.4% in the short-finned whale (3).” Both cows and chimps have brain mas of ~400g, and rhesus monkey and capybara have 70-80g.

She measures the proportionality between brain mass and number of brain neurons, for the whole brain and the cerebral cortex.
Brain mass to number of neurons:

  • rodents: exponential (1.5)
  • primates/insectivors: linear

i.e. 10x more neurons in a rat brain gives a 35x more massive brain.
Cerebral cortex to num neurons:

  • rodents: exponential (1.7)
  • insectivores: exponential (1.6)
  • primates: linear.

All species had linear scaling between both cerebellar and  for nonneuronal cell counts as a function of brain cell count.

The upshoot?
“A decrease in long-range connectivity, favoring local connectivity, in larger primate brains is expected from the nearly linear increase in cortical size as the brain gains neurons …
Neuronal connectivity in the cerebral cortex has properties of a small-world network, with mostly local connectivity and only a relatively small number of long-range connections”

And finally, the human brain is not an outlier in terms of num neurons/size, but rather what one would expect from a primate.

ABSTRACT:

Neuroscientists have become used to a number of “facts” about the human brain: It has 100 billion neurons and 10- to 50-fold more glial cells; it is the largest-than-expected for its body among primates and mammals in general, and therefore the most cognitively able; it consumes an outstanding 20% of the total body energy budget despite representing only 2% of body mass because of an increased metabolic need of its neurons; and it is endowed with an overdeveloped cerebral cortex, the largest compared with brain size. These facts led to the widespread notion that the human brain is literally extraordinary: an outlier among mammalian brains, defying evolutionary rules that apply to other species, with a uniqueness seemingly necessary to justify the superior cognitive abilities of humans over mammals with even larger brains. These facts, with deep implications for neurophysiology and evolutionary biology, are not grounded on solid evidence or sound assumptions, however. Our recent development of a method that allows rapid and reliable quantification of the numbers of cells that compose the whole brain has provided a means to verify these facts. Here, I review this recent evidence and argue that, with 86 billion neurons and just as many nonneuronal cells, the human brain is a scaled-up primate brain in its cellular composition and metabolic cost, with a relatively enlarged cerebral cortex that does not have a relatively larger number of brain neurons yet is remarkable in its cognitive abilities and metabolism simply because of its extremely large number of neurons.

Why the experts are always wrong

Berlin’s hedgehog and fox model has proved highly influential. Hedgehogs know one trick. An expert has a model of how the world works. Chances are this is a very good model. It had strong theoretical training and copious empirical support. It is, however, only a model. It does not contain things extraneous to the model. And it is those factors which lead to revolutionary regime change.

It has been shown that both speciation and businesses extinction rates follow exponential distributions. This is probably true for many more evolutionary systems.

The implication is that the causes of regime change are many, are non-cumulative, and non-casual. Non-casual in that the same event will cause a change one time, yet the same event will not cause a change the next time. Perhaps the system has adopted to the previous shock. “They’ll never hit us with an aircraft again!” (alt.: we will never again have an exploding aircraft…) Perhaps the larger environment had shifted. The last poor employment report coincided with a fall in the stock market; the current poor report was ignored.

We need experts. We need to know how things work. And often, the experts are right. We just can never know when they will be wrong, when the world has shifted such that their model loses it’s explanatory value.

Now, dear reader, the thoughts above are not new. I read them more elegantly expressed some months ago, and again before that. If you could track down another version of these sentiments, I would be most grateful.

World Without Us, World With Us — Alan Weisman

Alan Weisman discusses his book, World Without Us, at the Long Now.

He is mostly surprised at how quickly things would fall.  Manhattan, for example. The sewers would totally flood in 36 hours. This would corrode all the supporting structures (which are not designed to be wet), leading the streets above to collapse within, say, 20 years. The skyscrapers wouldn’t last much longer.

Weisman’s website has a slideshow offering a 15,00 year tour of Manhattan.. I prefer the version at urbanghostsmedia, which also includes text.

Picturefest clipped from various posts. All images linked to source article, though most appear to originate from the above mentioned slideshow.

gothamist.com

nyc.metblogs.com

daily mail (Canada)

urban ghosts (more images on the site)

mondolithic.com

War or Revolution Every 75 Years.

Paul Buchheit puts it on a 75 year cycle.

When Charles Dickens wrote “It was the best of times, it was the worst of times” to begin “A Tale of Two Cities,” he compared the years of the French Revolution to his own “present period.” Both were wracked with inequality. But he couldn’t have known that 75 years later inequality would cause the Great Depression. Or that 75 years after that, in our own present period, extreme inequality would return for a fourth time, to impact a much greater number of people. He probably didn’t know that the cycles of history seem to drag the developed world into desperate times about every 75 years, and then seek relief through war or revolution.

Compare to Strause-Howe (4th turning), who had a 80-90 year cycle.

None of them bring economics into the mix. What is the time it takes to build unstustainable debt? How does having a year of jubiliee every 50 years fix this?

 

 

 

 

 

 

Mark Pagel — Infinite Stupidity (how the internet makes us dumb)

MARK D. PAGEL is a Fellow of the Royal Society and Professor of Evolutionary Biology; Head of the Evolution Laboratory at the University of Reading; Author Oxford Encyclopaedia of Evolution; co-author of The Comparative Method in Evolutionary Biology. His forthcoming book is Wired for Culture: Origins of the Human Social Mind.

Mark Pagel discusses the evolution of ideas as part of the Edge Conversations series. This series includes a full transcript of the talk.

Professor Pagel begins with a review of evolution/life on earth, leading to the concept that social evolution (as opposed to genetic or epigenetic evolution) is unique to homo sapiens. Note that earlier hominoids never changed their toolkit, even over hundreds of thousands of years. Counterpoint: The Australian Aborigines, if we are to believe Wade Davis, also did not change their toolkit. Their culture was built upon preserving the traditional ways. Yet the aborigines are H. Sapiens.

So, he argues, humans are the only animals that show social learning. You might find counterexamples, which he dismisses as imitating behavior. Social learning requires understanding the purpose of the action. Counterpoint: octopus have shown some social learning, with a clear understanding of the purpose. But they are not social creatures, nor do they raise their young. This may be their limit on developing culture.

The downside, of course, is that social learning can also be called copying. And copying is much easier than innovating. This would give us an evolutionary bias towards copying over innovating.

If cultural evolution is seen as creating even larger groups, then this trend would accelerate. The number of innovators needed scales sublinearly with group size, simply because innovation is so rapidly spread via copying. The internet makes sharing trivial. Remember life before Google? Before Facebook let you see what all your connections were doing?

This sets up a duality. Nothing is more precious than an innovative idea; these are rare and difficult to bring into the world. Yet the ease with which they can be accessed makes them seem trivial, cheap.

It also means that the rewards of copying now far outweigh the rewards of innovation, just because copying is so fast and convenient compared to innovation.

Pagel supposes that the internet is domesticating us.

I disagree with Pagel’s comment that the internet is reducing innovation. Rather it speeds it. Innovation is the combining of old elements in new ways, and only very rarely creating a completely new element. By giving us such easy and rapid access to such a broad pool of ideas, it is easier to innovate since we don’t have to re-invent all of the pieces of the idea we ourselves are assembling.

He also notes that evolution requires both a sorting and a generative process. In biology, the sorting is natural selection, and the generative process is random errors in DNA copying. In sociology, the sorting is popularity, but the generative process is unknown. He asks if perhaps it also is only random. Some people only get lucky. Einstein claiming not to be smarter, only more curious. In other words, E. tried many more random ideas before hitting on the ones that worked.

And here again I wonder. How do you explain the creative leap, the “eureka” moment, the flash of intuition which marks the birth of a new idea? It still does not seem like a random combination of stuff that just by chance hit the jackpot.

See also my earlier posts:

Pagel’s presentation of Wired for Culture at the RSA, in which he argues that we evolved to protect our culture (not our self/clan/gene pool), and that we are slowly learning that cooperation achieves this better than competition.

And his article  Phylogenies reveal new interpretation of speciation and the red queen hypothesis, in which he argues that the observed exponential distribution of branch lengths in phylogenies suggests the causes of speciation are many and rare. It is not the cumulation of many small changes, but rather the one small change which comes at the right time in the right place.

Survival for lifestyle businesses

Some reflections on Adam Davidson’s article in the NYT magazine, Can Mom-and-Pop Shops Survive Extreme Gentrification?

The background is the gentrification of Greenwich Village. For more than a century, he writes, it was the perfect urban environment. Dense, walkable, cheap: a low barrier to entry if you had an idea, free exposure via walk-bys, and plentiful and diverse customers. Now it is gentrified: high barrier to entry, exposure matters less, and potential customers are more monophyletic.

So who has survived from the old regime? The mom-and-pops whose product prices rose with the gentrification. Coffeeshop which used to sell cheap beans now selling $26/pound PRY Selecto, a liquor store selling $2,000 bottles of Ch^ateau P’etrus.

Perhaps these small business survivors weren’t the smartest or fittest. They were run by unusually risk-averse businesspeople who sold a product whose value just happened to grow in lock step with the neighborhood.

The store exists to allow the proprietor to live, not to get rich. It isn’t maximizing revenue, but allowing the owner to do what they love.

Tricky way to make a living. Because if your business does not grow with the change in the neighborhood, you are out of luck.

Bacteria create electrical grids to share energy

Electrogenic bacteria wired up with pili

Earlier work (2011) has shown that bacteria can be used to extract hydrogen from water with an efficiency of 58-64%. Bacteria-enabled reverse-electrodialysis (BERED).

Now comes news that they can wire up their own electrical grids:

Japanese researchers have found that two species of bacteria can use minerals in the soil to transfer electrons over long distances, according to research published today (June 4) in Proceedings of the National Academy of Sciences. This creates currents between the species, and turns them into living electrical grids, allowing them to cooperate in breaking down chemicals in their environment that they could not metabolise individually.

hat tip to Ed Yong’s article in The Scientist

We know they share genes, now we know they share electricity.

Recall that electron relays are foundational to life’s chemistry. Metabolism is fueled by ripping electrons from food and donating them to oxygen. Bacteria can perform such transfer between cells/individuals, and even across species (leaky processes, black queen, gene transfer, …). This is know to occur via direct cell-to-cell contact.

The new finding is evidence to show that ferrous compounds in soil/sediment allow longer-range electron sharing. Further note that some bacteria (Geobacter sulfurreducens, for one) can produce magnetite nanoparticles– they can create their own “wires”.

Article abstract and citation info:

In anaerobic biota, reducing equivalents (electrons) are transferred between different species of microbes [interspecies electron transfer (IET)], establishing the basis of cooperative behaviors and community functions. IET mechanisms described so far are based on diffusion of redox chemical species and/or direct contact in cell aggregates. Here, we show another possibility that IET also occurs via electric currents through natural conductive minerals. Our investigation revealed that electrically conductive magnetite nanoparticles facilitated IET from Geobacter sulfurreducens to Thiobacillus denitrificans, accomplishing acetate oxidation coupled to nitrate reduction. This two-species cooperative catabolism also occurred, albeit one order of magnitude slower, in the presence of Fe ions that worked as diffusive redox species. Semiconductive and insulating iron-oxide nanoparticles did not accelerate the cooperative catabolism. Our results suggest that microbes use conductive mineral particles as conduits of electrons, resulting in efficient IET and cooperative catabolism. Furthermore, such natural mineral conduits are considered to provide ecological advantages for users, because their investments in IET can be reduced. Given that conductive minerals are ubiquitously and abundantly present in nature, electric interactions between microbes and conductive minerals may contribute greatly to the coupling of biogeochemical reactions.

S. Kato et al., “Microbial interspecies electron transfer via electric currents through conductive minerals,” Proceedings of the National Academy of Sciences, doi:10.1073/pnas.1117592109, 2012.

Sander van der Leeuw — The Archaeology of Innovation

Sander van der Leeuw at the Long Now on using archeology to trace the history of innovation.

I took more pages of notes on this talk than any previous. Even Stewart Brand was a bit in awe.

vdLeeuw likes to invert things. Examples: he does his digs from the bottom up. When asked why ancience kept records for so long, he asks why we throw records out so soon. He sees writing not as a way to increase communication, but rather as a way to communicate which allows one to not say what one does not want to say (by filtering out all the non-verbal cues).

Question: What is the change of change? What explains the hockey stick graph of human innovation?

Look at the limits of short term working memory. For chimps, it is 2 +/- 1 (evidence: only 75% can learn how to crack nuts using a rock and anvil). They reach this limit at age 2.

Modern humans are limited to 7 +/- 2. At age 5, the limit is 3, and it is maxed at age 14.

It took 1.5 million years to go from chimp-level to 7pm2, and has not moved from there in the 150K yrs since. Partly because biology is no longer a constraint, and the combinatorial explosion of possibilities when one can work w 7 objects.

Every society is an information society. Innovation is no longer biological but social.

One can observe the evolution in complexity in the archeological record. We start with stone tools, where we chip off flakes to form the tool. Next step: the chips are the tool, and the core is discarded. Then comes shaping objects: baskets, pottery. We develop agriculture, writing, then laws and administration, then empire.

This progression is summarized more eloquently here

… STWM increasing in step with mastery over 2D and 3D concepts (e.g., blade lines and spear heads) and eventually composition and staged manufactoring, i.e., the 4th dimension of time. … we arrived at our current biological evolutionary state around 10,000 years ago…

Innovation cycles can [now] be understood in the context of villages forming cities, and clusters of cities forming empires. … Cities require energy and in turn support innovation; Innovation allows growth, which increases energy demand…. Yet innovation leads to a cascade of new challenges …

The major innovations thus far have been our mastery over spatial and temporal dimensions (tools, writing, agriculture, etc) and our mastery of energy (Industrial Revolution). We are now in the beginning of an Information Revolution, which must provide new solutions to the problems generated by past innovations

— Alexander Pico @xanderpico

vdLeeuw now switches tack and talks about how civilizations fall. In hunter-gatherer society humans exerted no control over their environment. Risk was ever present, BUT known, understood, and non-cumulative. Some choose teutonically active regions as this actually preserved stability– the frequent disruptions prevented long-term changes as the system was frequently reset.

From the neolithic revolution (farming, 10K BC), we exert more control over the environment. This reduces the immediate risks but creates new long-term risks which are not known or even knowable until it is too late.

quotable: reducing frequent risks increases the probability of infrequent risk (by making non-cumulative events cumulative in effect ?)

 
To quore SB’s summary:

Around 1800, in Europe, energy constraints were finally conquered by the harvesting of fossil fuels. Humans only need 100 watts to survive, but every human now commands 10,000 watts. With that leverage we built a global civilization. The innovative power of urbanity has multiplied yet further with the coming of the Internet.

But we have become “disturbance dependent.” As our cities and density of communications grow, they create ever more difficult problems, for which we have to innovate ever more sophisticated solutions. Technology is “the biggest Ponzi scheme of all.”

As we become ever more adept at solving short-term problems, we shift the risk to long-term problems—such as climate change—which do not match the skills we have developed and know how to reward. We are headed into a trap of our own devising. To get out of it, if we can, will require a “battle with ourselves” to wholly redefine our social structures and institutions to master the long term

Thoughts inspired by the talk. He wonders what drove us from mobile bands to fixed settlement. My thought– WOMEN. They want to stay put.

More important, an analogy to my recent thoughts on the causes of speciation.
I want to model things in terms of cycles, but perhaps it isn’t a cycle, but exponential distributions with low variance?? The same process that drives speciation should also drive evolution of human culture. Can we create cultural phylogenies (allowing, of course, for HGT).