The Pogo Pathology or Where Did All Those Cats Come From?!!

cat-island-japan-image-1A pathology can be thought of as a deviation from a normal, healthy condition.  In a real sense pathology is the antithesis of sustainability or resilience.  Ironically, there are pathologies associated with sustainability and resilience programs…programs that have turned out worse after we’ve gotten our hands on them.

We are incessant meddlers, in both man-made and natural systems.  And sometimes things go wrong, sometimes pogo[1]horribly wrong even with the best intentions.  More complexity increases the ways things can go wrong and shortens out response time.  We design flood control programs that cause catastrophic flooding.  Natural Resource Managers introduce predators into environments where they ravage ecosystems. Regulators encourage competition and efficiency in banking and “too big to fail” banks nearly cause the collapse of the global financial system.  Our success in reducing forest fires leads to massive conflagrations far worse than had we left well enough alone. You get the picture?  If I were Pogo I would be sitting there with a double barrel shotgun yelling: “Get outta my swamp! All you do is screw things up!”

When One Face Palm Won’t Cut It – In 1949 five domestic cats were introduced to Marion Island to deal with a mouse population out of control. The cats were not neutered.


By 1977 their population had grown to around 3,500 and developed a taste for the native birds threatening to drive them to extinction. A similar situation prevailed in Macquarie Island (Tasmania).  Cats (unneutered) were introduced to kill rats, mice and rabbits. And it worked until they multiplied like crazy and started eating the endangered birds they were supposed to protect. 3,000 cats were culled from the population and, as typical for a complex adaptive system, the island ecosystem did just that, it adapted.

True to form, the rabbit population ballooned to 130,000 causing tremendous damage to vegetation while the rat population grew likewise, developing a taste for bird chicks.


In April 20014 after 3 years of monitoring with no sign of surviving individual rabbits, rats, or mice, the project was declared a success.

As a species we are ill-suited to deal with the increased uncertainty and complexity. This is especially true when seeking sustainability and resilience, which involve dealing with complex adaptive systems — either natural or man-made. In retrospect some of these concepts from complexity may have come in handy.

Perhaps the most grievous error was assuming the “Engineer’s View of Resilience.” Here management assume equilibrium, stability, or stationarity, and we engineer/design solutions anticipating equilibrium.  Our paradigm seeks efficiency and constancy, and assumes predictability.  They favor the Gaussian/normal distribution, and were obviously absent from engineering or “B” school the day exponential distributions were introduced. Cats no nothing of statistical distributions, Gaussian or otherwise.  Aside from eating, sleeping and playing, cats produce kittens.  Fertile cats, introduced into a closed ecosystem without predator species, produce lots and lots of kittens, and do so at a non-linear rate…or damn fast.


Axioms We Will Explore
We need to think about things a bit differently than we are used to.  Let’s start with some axioms…rules of thumb.  You may have favorites in this list, so let me know and we can begin there.

kindness“First Do No Harm”  “Primum Non Nocere.” Taken from medical ethics it means it may be better not to do something, or even to do nothing, than to risk causing more harm than good. This advice is antithetical to type “A” personalities.

The technique of Failure Mode & Effect Analysis borrowed from Risk Management may be helpful here. How might things go wrong? Spend some time thinking about this. How do you do that? Get people who do NOT think like you on the team. Diversity is about more than political correctness.President Kennedy used these techniques:

  • Focusing on the problem as a whole
  • Surface underlying assumptions about the problem/opportunity
  • If everybody agrees, then something is wrong
  • Seek to synthesizes input from a variety of sources
  • Slow down (yes, I know, this is a rough one)

I think one of the most grievous elements of decision making is how we value speed in arriving at a solution. You don;t get extra credit for “solving” the problem quickly. Decide in haste, repent at leisure. which brings us to the next point…all solutions are hypothetical.

“Sustainability Policies Are Hypotheses”  Hypotheses suggest tentative relationships. We have limited information and limited understanding of the variables and how they interact.  These interactions are also dynamical so proposed solutions become all the more tentative.  Two wonderful questions to keep in mind:

1) how do I know the solution is working; and

2) how do I turn it off if it fails or goes out of control.

Doubt, Due Diligence & Complementary Solutions  Falsification was a technique made popular by the philosopher Karl Popper. In practicing sustainability and resilience we are also practicing science. Our hypothetical policies need to be subjected to harsh criticism, with us being the harshest critiques.Taking the Devil’s Advocate Position and try proving the argument false!
I guarantee you will get new insights. Make it part of your due diligence.

 Never be satisfied with only one answer.  Niels Bohr, one of the fathers of quantum physics, believed that a single explanation cannot exhaust the richness of experience but rather other, complementary or even paradoxical explanations be present.

Notes to NGOs and Granting Foundations: You may grant between several thousand to several hundred thousand dollars for resilience or sustainability projects. While positive results are always welcome, the value of negative results could, in the long run, prove much more valuable.  Foundations must not only be the advocate of sustainable and resilient work, but of the highest quality of science.

“Question Authority” Sustainability and resilience issues are extra-normal. Nobody knows anything for sure.

Many of the problems, and their tentative solutions, are relatively new and novel. Basically, they haven’t been around long enough for “experts” to develop the depth. New variables pop out of nowhere and interact in ways we haven’t seen before.

Experts thrive and flourish working in a “command & control” (aka federal government). The Florida Everglades is a case in point. Efforts to “develop” the Everglades sought to harmonize three very different variables: agriculture, urbanization, and conservation. We’ve drained it; and then constructed a massive infrastructure to control flooding and mitigate damage from Hurricanes. The results: we have significantly reduced the area of natural habitat, created dramatic declines in water quality, and made the region increasingly vulnerable to extreme weather conditions.  For a detailed discussion see “Resilience Thinking” by Brian Walker.  Expert opinion, backed up with models, sand tables and simulations played a part in creating a mess in Pogo’s backyard. That brings us to the next axiom…be suspicious of the tools in the experts’ tool box.

 “Be Suspicious of Models, Simulations and Quants”  Better to read the entrails of a freshly killed goat than the output of a quantitative model, especially simulations. At least later you can eat the goat.

It’s not the data that will kill you, it’s the underlying assumptions.  “You don’t like the results?  Okay, we’ll tweak the assumptions.” Predictive Analytics faces similar pitfalls.  Sustainability projects can often be contentious and political. Opposing sides often bring in consultants (aka hired guns) who produce different findings while looking at the same issue.

I guarantee you the “quants” will get it wrong and, anyway, nobody will be able to understand it to begin with. In all seriousness, you need a stable environment where historic statistics continue to be relevant to dynamically changing markets, technologies and human behavior. We can produce extremely precise forecasts for daily electricity usage. On the other hand, we haven’t seen much success in quantitative systems designed to “Beat The (Wall) Street”or break the bank in Las Vegas.  Randomness and indeterminacy are, unfortunately, facts of life.

“Question Received Knowledge”
We teach invincibility.  We teach that everything is possible, that science conquers all, that nature is ours for domination.

We reward expertise in executing processes or templates. We teach “the model” and its application in an environment of low uncertainty and low complexity. Remember what Thomas Kuhn said about “received knowledge” in Structures of Scientific Revolutions? No? Not a big surprise. Kuhn is rarely taught to undergraduate or masters students; and for that matter, most PhD’s skate by with some dopey “research methods” class that neglects to teach epistemology. Read Kuhn if you want an “ah huh” moment.

The simple explanation, in case you’re not interested in reading Kuhn, is that professionals become path dependent…in the way they think, in their assumptions about how things work, and with the models that have consistently shown success. All well and good until the environment changes; and what worked so well in the past becomes less and less irrelevant to the evolving problems at hand. Today’s environment is quickly becoming more and more complex, and with it more and more uncertainty.

“Learn About Complexity & Uncertainty”

We are dealing with ecosystems, be that a rain forest or city. These are complex adaptive systems. Brian Walker, an Australian environmental scientist, wrote an exceptional book called “Resilience Thinking.” It is very accessible and a quick read. I have also done work in sustainability and resilience. If I can be of help, give a call or email.  Happy to chat.

John Marke 636-458-1917,


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