1983 Fiji Intersecting Economic Cultures

In 1983, I led a research team to Fiji to collect specimens of coral fish. Fiji is an ancient piece of a continent so has a different habitat and different geological history from the coral atolls in other island groups. The assistance of the Royal Ontario Museum, private donors, University at Suva, the Department of Fisheries, and many other organizations made it possible.

Buying bananas from Fiji roadside vendor

The slides shown here were taken in a variety of locations and for anyone who currently lives in Fiji it will probably be a bit difficult to recognize the locations. For the time we were there, we donned local clothing and lived with the local people on the various islands that we visited.

We travelled by van from Nandi to Suva and our first impressions were of interesting people and scenery. One of our first stops was to buy lunch from one of the local roadside vendors. Although we were travelling from Canada, we had lived in the West Indies for a while so were comfortable stopping and chatting to people along the way. Everyone we met was enthusiastic and interested in our little group. Unlike the coral islands of much of the rest of the Pacific this landscape was more like a countryside in South America or Africa with rolling hills dark earth and lush forests. Continue reading

The Fate of Individuals in Capitalism

You begin life in a capitalist system as an undifferentiated package of energy and skills — labour. Labour is an expendable resource in capitalism. If labour is cheap, or being replaced by machines, you do not want to be in the labour market. The imperative of the capitalist system is to increase profit. If your skills and energy are too expensive a commodity, the company will try to find the skills and energy elsewhere or pay you less. Today’s labour is cheap — there is lots of it around the world. In addition, technology continues to reduce the need for human employees.

Oh dear, oh dear, what to do?
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Determinants of Diversity (continued)

Determinants of Diversity (First Blog)

Hot and relevant news! Can we use this in the metaphor for economy? No reason why not, it mostly just confirms long-standing observations that diverse systems are stable.

Stefano Allesina and Si Tang, both of the University of Chicago published an article in Nature online (Feb 19) that revises the peculiarly troubling equation posited by Robert May (a physicist) in 1972. May’s simple model described the relationship between diversity and stability in a theoretical ecosystem based on random interactions among species. Ecologists had observed richer, more diverse environments to be inherently more stable while May’s model suggested that more species creates less stability.

Example of a highly diverse jungle; trees are the organic matrix in this system

I must admit at the time I was reminded of the engineering work that demonstrated bumble bees could not fly, and wondered why he had bothered to publish something that so obviously did not match the observations. My own work on organic matrices argued that more diversity tended to produce more stability, but only in the instances where there was an organic matrix that provided for extensive interactions that included but were not just predator-prey interactions and that were mediated by an organic matrix, not just a physical or non-biological matrix.

However, it turns out that May’s work could be useful and that it was based on some incorrect assumptions which Allesina and Tang (Nature Feb 19) were able to adjust. The results of Allesina and Tang’s network analyses demonstrate that stability in complex ecosystems is determined by the type of interaction among species including predation, competition, and mutualism as well as the strength of those interactions. They further determined that a stable system could comprise any number of species. If we add to that work the idea of an organic matrix that allows a diverse system to develop, we have a model that both describes and predicts at least some of the observed development, behaviour, and nature of complex biological ecosystems.

In an upcoming blog, I will investigate how we can use this in an economic system.

MegaCorporation Econosystems are like Ancient MegaFauna Ecosystems

The smallest dinosaurs were not actually very small, and most were pretty big, while some were huge. During the days of the megafauna, there were small creatures like insects, lizards, snakes, crustaceans, and many others, but the landscape was dominated by large animals.

Velociraptor, an example of ancient megafauna, photo from California Academy of Sciences

Some dinosaurs were herbivores, eating only plant material, others were entirely carnivorous acting as major predators, while still others were in between and omnivorous. We do not have really good descriptions of the landscape, but it was probably a mixture of forest and sweeping grasslands. The forest was mostly an open forest with some undergrowth, but only a few places were great tangles of jungle. We know from present day systems, that if you have large herds of megafauna roaming a savanah or grasslands, the herbivores stop tree growth by nipping off and eating the newly sprouting trees. So grasslands with large herbivores tend to last a long time. To get to this megafauna ecosystem required about 100 million years of evolution after the first plants and animals made their way onto the land from the water.
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Econosystems That are “Blowin’ in the Wind”

Primary production is the foundation for everything in the consumer arena. There is no other option. You can’t make something out of nothing. That is the lesson from nature and given that we ultimately are a part of nature, we are subject to the same rules. In a practical sense, what does this mean?

Corals like this one, are symbiotic with algal cells inside their bodies, and they also eat plankton.

Take the coral reef as an example. This is probably the single richest, most diverse, ecosystem in the underwater world. Yet they are all based in aquatic deserts. The waters are crystal clear because there is so little in them. Rich waters full of nutrients and plankton, are murky and coloured. Coral reefs have a huge organic matrix primarily made up of living coralline algae and coral, sponges, soft corals, and other living structures. It provides and amazing array of physical and biological niches for species to find ways to make a living. However, there is an important aspect of this wonderful place that is sometimes not well understood — and it is a perfect metaphor for some of the richest most diverse econosystems in the world as well. If we examine the trophic pyramid for a coral reef (here in very simplistic and diagrammatic form) we see a peculiar thing. The first diagram shows the contribution from primary producers using local resources.
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Zero is not Nothing

This morning I woke up with these thoughts buzzing around in my head, so I thought I would jot them down.

Zero is a state of being, it is not like -1 or +1 which are actual numbers. If I have a cookie and my brother takes away my cookie, the cookie still exists, it is just that I don’t have it. So I don’t have zero cookies, I am merely in a state of zero cookies, but that could change if I take the cookie back from my brother. If he beats me to it and eats the cookie before I can grab it back, the cookie still exists, it has just changed state (and I don’t want it anymore).

Zero always has a context. The scale on a thermometer in Celsius degrees registers a zero at the point of transition between ice and water, it is not a place where there is no temperature. Suppose I start with a box of ten shiny pebbles. If I remove 9 pebbles, the box has 1 pebble left, but I have 9 pebbles in my hand. If I remove the last pebble, the box has zero pebbles in it, but I have all ten pebbles. So there are never zero pebbles except in the context of the box.

Now money is different. It is not real, it is representational. So I can be at a state of -$1,000 and still have lots of actual dollar bills in my wallet. And I can still buy things using the money in my wallet. However, being in a state where I am both -ve and +ve means I am unstable. Whereas with cookies, I either have the cookie or I don’t.
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Tax Rates, Wealth, Job Creation, Fish Eggs and Baby Bunnies


A useful prediction from the ecosystem model of the economy is that an optimum degree of taxation will lead to an optimum level of diversity of lucrespecies in the system and an optimum use of the various resources, in this case including people who are not entrepreneurs or capitalists.

In the US Republican campaign we hear a great deal of complaining about the excessively high tax rates in the US and a suggestion on the parts of all the Republican candidates that they will bring down the tax rates. A quick look at this map demonstrates that the US already has one of the lowest tax rates as a percentage of their GDP of any country in the world.

via chartsbin.com
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Testing the Theory: Greece

Predicting the outcomes of the IMF and World Bank measures to be imposed on Greece based on an ecological rather than evolutionary economic model leads to some surprisingly different predictions than what the IMF and World Bank predict publicly.

Good science begins with a question which is then examined by the development of one or more hypotheses, each of which can be falsified by a test that can actually be carried out. For example a question might be: “Are all red things hot?” Is this a testable hypothesis? “All red things are hot.” Suppose we test by asking several thousand people if they agree with the hypothesis. We discover that 98% of the people we asked said yes, all red burners are hot and only 2% said no they are not all hot. Does this mean we have tested the hypothesis? Because the vast majority of people believe that all red burners are hot, does that mean all red burners are hot? Not in science. Opinion is of no value in science. Belief is of no value in science. In science only evidence matters. In the rest of life, opinion and belief can matter, but not in this test. In fact, our test of asking people’s opinion is not even a real test because we still have no idea if all red burners are hot.

Suppose we test by taking the temperature of thousands of red burners and find that they are all hot. Does this “prove” the hypothesis? Nope! If we test another one, it might be cold. Supposing instead we create the hypothesis that states: “Red is what makes a burner hot.” Now we can test it by painting a burner red. If the burner does not get hot, then redness does not cause hotness. OK, so that is a testable hypothesis because we can carry out an actual test to falsify it. The problem with the other test is that we would never know if we had examined every red burner.
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Testing the Bio Economy Metaphor

It is always easiest to start with something obvious and relatively small in scale.

Maybe we could start with slavery. Humans aren’t the first to do this of course, ants have been at it for literally millions of years. The simplest approach is to invade colonies to steal eggs or larvae, which they either eat or raise as slaves. Others attack to choose only the biggest and strongest adult workers. Sometimes the attacks are sneaky. The marauding queen slips past the battling workers and kills the defending queen. The killer queen smears herself with the dead queen’s phermones (kind of like perfume) to fool the local workers. The attacked colony then marches off behind the disguised queen to what will become their slave quarters. The slavemaking ant workers guard the slaves and maintain their eggs and larvae in slave hatcheries to make more slaves. The guards chase down and forcibly return any would-be escapees. The purpose of slavemaking is to expand the colony’s ability beyond what their own workers could perform.

Picture of a slave-ant
Clipart courtesy FCIT

Sometimes the slavemaking is taken to the extreme, such as in some Amazon ants, where the ants can no longer do any work by themselves — they can’t even feed themselves. Without slaves the colony would fail.

Is there a good example of slavemakers in modern human times? Yes, even today in many countries slaves are still used. But I want to look at a particular situation that is parallel to the ants.

The United States, like many countries in the world routinely used slaves to expand the performance of the colonies beyond the ability of the US local workers. Slave labour in the US probably became common sometime around 1650. Mostly but not entirely in the south, they came from Africa where slavemaking people invaded African villages to steal the children to be raised as slaves. Others attacked the villages to choose only the biggest and strongest adults to become slaves. Continue reading

Quick Sketch: The Key Economic Modellers

The following summarizes the key ideas that shape the manner in which the concept of nature and biology as actual or metaphorical factors governing economics. Hobbes began to distinguish between artificial and natural aspects of human behaviour.

John Locke

Locke extended these ideas, arguing there is a human right to defend life, health, liberty, and property. In addition, he claimed that nature has value in an economic system only if it is worked. But he understood that economy, like nature is a spontaneous, self-generating process. Adam Smith’s work distinguished the economy further noting potential that the aggregation of capital to create more powerful enterprises provides. Given the time and recent revolution, he felt that democracy was inherently good in combination with capitalism because it was founded on a decentralized economic system of independent enterprise and little interest in sharing wealth with people who are poor or needy. Karl Marx by contrast felt that ownership is not a natural right, and instead capitalism is an elitist concept to develop wealth at the expense of others. Marx advocated socialism or rule by the labouring classes. He predicted predicted a stateless, classless society – communism – that needed to be brought about by revolution.
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Management Strategies in Biology and the Economy

Given that people have tried to manage biological species, ecosystems, and biomes without sparkling success, it is doubtless likely that it will be equally difficult to manage lucrespecies, econosystems and economes. At the same time, it would be incorrect to suggest that all efforts to manage biological systems at some level have been total failures. A better description would probably be to suggest it is possible to influence biological systems.

Early attempts to manage wild animal species for improved and yet sustained harvest made the assumption that in most animals there is a overabundance of young. The best mathematical treatment of this was developed in Canada by Bill Ricker in 1954 (“Stock and recruitment,” J. Fisheries Res. Board Can., 11, 559-623). His model was simple in concept and elegantly easy to implement. I have simplified it immensely but in essences it goes like this. Each animal in a stable system needs to replace itself in its lifetime. All animals produce more young than is necessary to replace themselves. If the environment has more carrying capacity that the fish are using, the population grows. If the population is stable, the number of young surviving to adulthood equals the number of adults in the population. By harvesting adults, we can cause the population to increase the rate of survival to adulthood. By harvesting only the equivalent of the excess young, we can take the “maximum sustainable yield.” This was too aggressive and over the years, the regulations shifted to “optimum sustainable yield”, then this was too aggressive so they shifted to regulating the harvest based on the previous harvests and their trends. Ricker recognized the limitations of the idea, and made these comments: “Plotting net reproduction (reproductive potential of the adults obtained) against the density of stock which produced them, for a number of fish and invertebrate populations, gives a domed curve whose apex lies above the line representing replacement reproduction. At stock densities beyond the apex, reproduction declines either gradually or abruptly. This decline gives a population a tendency to oscillate in numbers; however, the oscillations are damped, not permanent, unless reproduction decreases quite rapidly and there is not too much mixing of generations in the breeding population. Removal of part of the adult stock reduces the amplitude of oscillations that may be in progress and, up to a point, increases reproduction.” This assumes a constant carrying capacity.

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Predicting in Econosystems

Milton Friedman

Sticking with the biology metaphor for economy, we have now defined economic evolution and its observed historical results. Clearly evolution is not really suitable to use as the analog for strategic modelling of economic systems with a view to predicting outcomes in a short span of time (years). Take capitalism for example. Despite the enthusiastic acceptance of the proposition by the picture they paint of nicely balance economic structure built entirely on a free-market economic system is just not what has been observed to happen. The basic problem is that evolution in economic terms operates at the level of the genetic structure of the entrepreneur as well as the accumulated knowledge and technology base.

We also defined the ecological base for economics, and this is a much more accurate model in predicting observed results in a capitalist system (a class of economic systems). This is because the competition in an ecosystem operates at the level of the individual entrepreneur, so that the individual reacts to and attempts to adjust to the conditions and competitors. At this level of competition it is the survival of the fittest individual entrepreneur or corporation, not the fittest set of genes in a group of entrepreneurs. The strategy of capitalism is to use the capital assets of a number of entrepreneurs to dominate the market by controlling the production and distribution of products so that the entrepreneurs can engage in an exchange of wealth. This strategy in an ecosystem model leads to the most successful corporations becoming larger either at the expense of others or by acquiring them or by merging with them. Fairly quickly, if there are no controls, only a few very large and generalized corporations will control most of the production and distribution in the entire econosystem. Continue reading

Recap: Parallel Biological and Economic Concepts

Let me recap the thinking so far. Economic evolution is a spontaneous undirected long-term process, stretching back at least 100,000 years. The process is one in which each type of economic system gradually developed. The next new system sprang from the previously existing species. The actual historical record of the times for the ancient evolutionary events are not easy to define, but archaeological evidence might suggest a shift from subsistence to bartering sometime about 70,000 years ago. Shortly after that it is likely that the earliest mass production of tools or tool parts began. As the trade become more intensely developed based on bartering, someone no doubt thought about representing a purchase so that it could be “ordered” and delivered later. Money and monetary systems probably were pretty well established at about the time the shift from nomadic, semi-nomadic, and migratory life styles intensified the agricultural aspects with a shift to primarily monetary systems perhaps 10,000 years ago. Massive accumulations of wealth by chiefs and rulers became too repressive for peaceful acceptance by the general population. Revolutions reduced the incidence of feudalism and dictatorships, allowing the potential for individual ownership. Although economic evolution still proceeds, just like biological evolution, it is too slow for us to see it happen in a lifetime.
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Naming Major Econonomes

Assuming we can continue the metaphor of biology and economics, the next stage is to identify major economes (parallel to biomes). The three major variables describing the typical conditions in which major economic systems are located and which by observation seem to determine the richness of the system are the latitude, the amount of biological cover from forest to desert, and the amount of infrastructure that has been built into the system. The infrastructure must in part be physical, but can also be connectivity in various ways from simple communication to secure banking operations.

Within each of the major economes, the productivity of the area and its sustainability as a series or constellation of economic systems within the econome is largely dependent on the amount of terraforming that has been done, the degree to which built infrastructure (physical or intangible) has been developed, and the degree to which the local economic system adds value to the resource locally.
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Organic and Commercial Matrices Enhance Diversity

An organic matrix in a biological ecosystem ecosystem is when part of the complexity of the environment is structurally the result of living organisms. The thesis in this blog is that a similar commercial matrix will enhance the diversity of lucrespecies.

A matrix as used in this context is a supporting or interweaving mechanism. A physical matrix in an ecosystem can be a variety of things, but in the simplest terms it is added complexity in the physical environment that allows more species to find ways to survive than would be able to survive without that complexity. A simple example is that a rocky shoreline and intertidal zone has a much greater diversity of species than a sandy beach and intertidal zone. The reason is in part because a rocky shore has more things to hang onto and more places to hide.

An organic matrix in an ecosystem is a living or once-living physical structure that adds physical complexity and because it is a living structure, it can interact with the other organisms in the system, adding further levels of potential habitat niches in the environment. In a previous blog, I mentioned examples such as coral reefs (coral and calcareous algae structures), forests (trees) and kelp forests (Kelp stands).
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