Mouserat

Systems Thinking and Climate Change

This week’s reading got me thinking about how the characteristics of systems can interact to affect a systems function or purpose. I work part-time at a company called the Institute for Social and Environmental Transition (ISET), located in the Sustainability Innovation Lab at Colorado (SILC). ISET works on a variety of projects helping local, regional and national governments plan for the future impacts of climate change.

Hierarchy, self-organization and resilience all are key components in our work. Many communities are seeking to increase their resilience in the face of climate change. This is unsurprising, as resilience is defined as “a system’s ability to survive and persist within a variable environment” (Meadows, 76). Increasing variation in temperature, precipitation, and extreme weather events resulting from climate change creates uncertainty in a variety of key areas, including food security, public health, and water scarcity. This means that communities must be ready to respond and adapt to sudden and long-term changes.

Systems thinking is essential in thinking about community resilience. Understanding the hierarchy of communities aggregating to the city, regional, and national scale can help the systems thinker understand the underlying cause of problems facing the community. It is also vital to understand how the community fits into its natural and built environments. For example, if a community’s water source is located downstream of a sewage treatment plant that overflows during severe storms, then the community’s resilience is decreased, since they are less able to respond to other storm impacts without access to clean water. The water treatment facility may be located in another city, which did not consider the consequences of building a sewage treatment plant upriver from the community in question. Meadows points out that “In hierarchical systems relationships within each subsystem are denser and stronger than relationships between subsystem” (Meadows, 83). Thus, it may be better to create ordinances regulating the siting of facilities upstream at the regional or national level, rather than relying on the community’s ability to prevent construction of sewage treatment plants upstream.

The ability to self-organize can also be important in a community ability to adapt and respond to climate change. Say the severe storm in the previous example floods the roads, preventing emergency supplies from reaching the community. A community that is able to create a system to share local resources until the roads are cleared will be more successful than one where the most impacted individuals must fend for themselves.

Question: What system traps might be identified in efforts to address climate change? How might we turn these into system opportunities?

The Trap of Expecting an Expected Outcome

http://thesheetnews.com/2011/09/02/lord-of-the-flies/

The best we can ever do is keep asking questions. To continually look for the novel or the overlooked. To not expect the answer we were expecting. These principals are just a few that come to mind when I am thinking about systems, either environmental, or political. As an ecologist, I have been charged with the responsibility to poke-holes in ideas, find flaws with hypotheses, and only stop researching when my Write in the Rain notebook has been pulled from my cold, dead hands.

Systems are complex beasts that can never be controlled; though they can be observed. The longer one observes the more complex the system inevitably becomes – think factorial. Specifically, I studied interactions of a micro-ecosystem on sage brush in the Eastern Sierra. The research was focused on one fruit fly, Eutreta diana. This all sounds simple enough, but pull back by one level of the hierarchy and we have to account for the sage brush itself, the water it drinks, the nutrients it eats, and the very specific phenols it produces. Add another level and we find ourselves looking at the mycorrhiza, and competition with nearby plants. Add a few more levels still: we can now see multiple sage brush ecosystems interaction with each other; with various populations of fruit flies interacting, equalizing the number of flies per system.  This hierarchy will expand indefinitely… where does it end?

We need limits to contain our systems. Without them chaos ensues, making it nearly impossible to see the interactions within the system! By breaking down this ecosystem into a handful of systems – the fly, the sagebrush, and the other insects – I was able to control the variables much easier. In one experiment I controlled the amount of water and nutrients a number of sagebrush received (some more, some less, some were status quo) to see how and if it effected the number of flies on each plant. We weren’t concerned with other plant species, other insects, or other populations, only the sage brush in a 100meter radius. After approximately 9 months controlling the sage brush nutrient and water intake we found that (drumroll, please) no matter how we controlled these variables, there was no significant change in the number of flies that were inhabiting the plants.

This was a total shock to me. Even more shocking was that an experiment that looked at the different phenols found that each specific phenol-mix released by a given plant had no effect on attracting the flies, regardless of how the choice assay was run, or which phenol was present. It seemed that none of our experiments that we had conducted over five field seasons yielded no significant response… except for one: flies seemed to be attracted to sage brush which other flies had already oviposited (laid eggs) on. Why?

Why do we fall into the trap of expecting an expected outcome? How do we create a more accurate model of our world?

Systems Reflection # 2

Alec Brazeau

        Meadows identifies successful systems as those that have at least one of the three following characteristics:  resilience, self-organization, and/or hierarchy.  Resiliency is defined as the ability of a system to bounce back (elasticity).  Self-organization applies to systems that are able to make themselves more complex through the use of feedback loops.  Finally, hierarchy refers to the structure that systems create within themselves using subsystems.

        I think that there are many examples of natural systems that have all three of these characteristics.  For example, imagine an ecosystem.  Through complex food chains the populations of each species remains in dynamic equilibrium.  This dynamic equilibrium is constantly re-correcting itself, creating resiliency within the ecosystem.  On the other hand, this resiliency can easily be interrupted by external pressures such as human development.  Evolution within an ecosystem overtime is an example of how that ecosystem self-organizes, or becomes more complex through feedback loops.  The ecosystems food chain is an example of the ecosystems hierarchy.  Predator-prey relationships are the interconnections between the ecosystems subsystems, which creates a hierarchical structure.

        There are also some great examples of complex human systems that have all three of these characteristics.  If we were to examine the U.S government as a system, these characteristics are easy to see.  The system has resiliency built into it through the concepts of checks and balances.  If one branch of the government oversteps, the other two can hold it back and keep the entire system in check.  The government also created a hierarchical structure through the use of each branch as an independent subsystem.  This structure was created using self-organization; when a problem arises, the government solves it through feedback loops.  Any executive agency can be used as an example of this.  The EPA was created when it was recognized that pollution was an issue, the TSA was created when air travel safety became a real concern.

        Despite these two examples, there are many complex systems that may be successful without having all three of these characteristics.  Can anyone think of an example of a successful complex system that is lacking one of these characteristics?

Busy as a Bee

Imagine a large community of families living together in harmony. Each individual in this community cooperates and communicates with the others to complete tasks that they are assigned to them. Survival of each individual would not be possible without the combined effort of the whole community.

Though this sounds a bit like a utopian community, it is in fact the basic structure for one of the most fascinating systems on earth- a honeybee colony. The three main ideas that govern systems- resilience, self-organization and hierarchy-can easily be applied to a bee colony. Resiliency, along with stability and productivity, are all important and necessary aspects of a system. Once a bee colony becomes overcrowded, the honeybees create a swarm with the old queen bee and half of the worker bees while a new queen stays behind with the remaining worker bees. The reason for this is so that the swarm can locate and move to a new site to start a colony. The action of swarming allows the bee colony to maintain stability and productivity, by splitting up the workers and choosing a new queen. The system is resilient by staying flexible to external changes, such as overcrowding.

Honeybees are social insects and rely heavily on communication and division of labor within their colony. Each type of honeybee, the queen, workers and drones, perform a specific set of tasks that benefit the group as a whole. Worker bees are the majority of the workforce and some of their tasks include cleaning the hive, feeding the others, caring for the queen, building beeswax combs, guarding the hive and searching for nectar. The main purpose of drones, the larger male bees of the colony, is to fertilize the queen and they do not perform any other tasks otherwise. The queen bee has two main functions in the colony, which is to reproduce and produce pheromones to keep the colony unified. This self-organization of a single colony allows the hive to act independently of other hives because of the rules and division of labor that govern it.

Lastly, the hierarchy in a bee colony is very apparent. The single queen bee is responsible for creating and establishing a strong colony and she is the only member to lay eggs. She does not “control” the hive per say but the other honeybees in the hive cater to her needs.

The resiliency, self-organization and hierarchy of a bee colony are what make it a highly effective and functional system. We could all definitely take a lesson or two from our captivating honeybee counterparts.

Question: How important/necessary is self-organization in a system?

"The Colony and Its Organization." MAAREC - Mid Atlantic Apiculture Research & Extension Consortium. N.p., 19 Oct. 2010. Web. 31 Jan. 2017.

The Nature of the Systems "Beast"

To finish a thought from last week's class, optimization in one part of a system might lead to sub-optimization in another. I immediately thought of a book I'm reading on triathlon training. It is best to have less flexibility in your ankles when it comes to running since it helps transfer your forward momentum more efficiently, however, during swimming you want more flexibility in your ankles to kick. Working on one sport might have trade-offs for another. Another aspect of triathlon training our reading has made me think of is limiters to performance. For example, being able to run for an extended period of time means you most likely have good aerobic endurance. Improving aerobic endurance by running further and further and by increasing training volume will only get you to a certain point of fitness, though. At some point, larger gains will happen by focusing on a limiter like muscle strength, anaerobic capacity or... eating less pizza and drinking less beer *sigh* than focusing on a strength.

A great example of a systems problem, which has actual relevance to socio-environmental systems, that our reading made me think of was incorporating renewables into the grid. Getting our electricity depends upon an intricate system that matches generation to demand while humming along at 60Hz. Extraordinarily, this system can accommodate electricity being generated by  anything from a 2 kW photo-voltaic system on someone's rooftop to a 500 MW coal-fired power plant dozens of miles away. While individual towns and cities have electric utilities that provide their generation, that is just one aspect of the entire national grid that has sub-systems working in hierarchies like Independent System Operators and Regional Transmission Operators built into it allowing for stable intermediate forms. Other aspects like day-ahead energy markets have optimized the economics of the system and brought prices down in many places by allowing for competition within the dispatch order. Entire agencies like Federal Energy Regulatory Commission and the North American Reliability Commission are responsible for regulating who contributes to the grid and making sure they operate reliably. Each subsystem has a niche in the grid enhancing its overall ability to function. This system works so well (besides because it has to) because each sub-system can make its own structure more complex and the hierarchy involved encourages specialization. Hopefully, this adaptability and autonomy will continue to allow additional renewables on the grid. When the electric industry first began, none of these subsystems existed. It was through a process of learning, adapting, and optimizing the system that we see the grid that is before us today. 

    Speaking of the early days of the electric industry, initial escalation between private and public utilities lead to a cycle of fierce competition, consolidation, and then a monopoly. From that escalation, state-protected monopolies and the regulatory compact was born. Many of these systems archetypes mentioned like escalation are attributed to a flaw in the political economist Adam Smith's theory on how individuals function within a system. According to Smith, "homo economicus acts with perfect optimality on complete information, and second that when many of the speicies homo economicus do that, their actions add up to the best possible outcome for everybody (107)." Unfortunately, this is fiction. Meadows claims, "We don't even interpret perfectly the imperfect information that we do have" (107). Our lens of subjectivity only lets in the information that supports our mental models, and after all our mental models of the world are not reality.

 

Question: Why is it that material by Libertarian think-tanks resoundingly cite Adam Smith's work when justifying competitive markets free of government regulation?

 

Jennifer Blog Post 2: Cracking the codes, breaking the traps.

In this week's reading, Meadows explores  archetypal problem-generating structures, revealing their inner systemic workings. Righteously, she says that understanding these structures is not enough.  We need to be able to avoid these traps, or see how to get ourselves out of them.

I agree, while also believing strongly that fully understanding these archetypal problem-generating structures, understanding them personally, painfully, with felt experience, is essential to the process of refuting, repudiating, and rectifying the trap.

Here's a recent example of a role-play that took place in my daughter's high school last fall, exploring some problem-generating structures of our society.

One day all the students in her Equity Class showed up, and most of the class-- all but 6 -- were told to wait quietly in the hallway.  They were given no explanation and were monitored for silence and compliance.  

The 6 students allowed into the classroom were shown to a large table, sketch pads, plates of cookies and drinks, colored markers, given detailed instructions on how to generate a plan for their community, with two instructors present to assist them.

After 10 minutes of standing in the hallway, another 6 students were allowed into the classroom.  In a separate section of the room, they were given a smaller table, water, no chairs, a smaller piece of paper, pencils, and limited instructions.  They were told to make a plan for their community.  

So it continued, until the final group entered the classroom, including Sage, had 10 minutes to work, had no snack, no water, no paper, and were told to make a plan for their community but were not allowed to talk to one another.

One of the most disturbing aspects of this role-play:  some students in the second group noticed the first group's cookies, and went to take some.  After less than 30 minutes into this role play, the students in the first group had internalized their stance as an oppressive elite, and refused to share their abundant cookies -- with their classmates!!

This is real.  I think of our school system: gated private schools for the elite, with resources, coaches, expectations and assumptions of power, privilege, and success. I remember schools in poor neighborhoods in the Bronx, where I worked in crowded classrooms; met bored, overwhelmed, and disengaged  teachers; and heard expectations that students would join the army upon graduating.

Even beyond these are the schools described vividly in crackingthecodes.org, where racist police discipline children with violence and use handcuffss.

Meadows condemns these system: "...some systems are more than surprising. They are perverse. These are the systems that are structured in ways that produce truly problematic behavior; they cause us great trouble."

It's necessary to get inside the perverse behaviors our systems are creating, to taste and feel this harm and trouble.

Then we will be willing to accept change, our scary friend, and disrupt these archetypal problem-generating structures that are imprisoning  so many of our fellow humans, the living beings on this earth, and ourselves. 

Systems and Us: Why?

Most systems are complex and unique, but three main characteristics seem to be present in all that work very well: resilience, self-organization, and hierarchy. Resilience measures the ability of a system to bounce back after being altered in some way. Self Organization describes the ability of a system to make itself more complex. Lastly, hierarchy explains the arrangement of systems and subsystems within a larger complex system.

Lets take myself as an example of, in my opinion, a well-functioning system. I was created using basic self-organizing principles and rules in the chemistry of DNA, RNA, and protein molecules. On a higher level, self-organization can be see in myself when I am learning and applying new sustainability practices in school. Next, resilience can be seen in the way I take care of my body. On a basic level my body has been learning to fight off disease since I was born, and with the help of vaccines is fairly resilient to most. On a higher level I have learned over time that my body functions better and is more resilient when I eat correctly, exercise, get enough sleep, and practice mindfulness/gratitude. Lastly, on a basic level hierarchy can be seen through the different organs in my body working to help my entire being function. On a higher level, hierarchy can be seen in the ways I organize learning different skills in order to achieve large goals.

While we understand that these three things help a system function smoothly, systems still surprise us. This is due to the following reasons: 1. Everything we know about the world is a model 2. Our self-made models usually have a strong congruence with the world 3. Our models fall short of representing the world fully because our knowledge is amazing, but our ignorance is so much more incredible. Of the examples described showing how and why we are still surprised by systems I found bounded rationality most interesting. This section depicted how we live in an exaggerated reality, focusing too much on the here and now as opposed to empirical data or experiences. People acting rationally in the short term for their best-interest are actually producing overall poor aggregate results. For example, if I take a nice long shower in the morning because its in my best self-interest, I'll be squeaky clean and happy. On the other hand, when everyone else in my home does this, there is not enough water for others to serve their own self-interests such as also taking a shower, or washing clothes.

Lastly, many things about systems that surprise us cannot, and should not, be eliminated. For example, delays, boundaries, and nonlinear characteristics are things we as people cannot control. On the other hand, some systems contain archetypes that create some problematic behaviors. These, we can and should do something about. Of the traps and opportunities that were described in this section, I found seeking the wrong goal to be the most fascinating. Coming from an economics background, global national product (GNP) is something I know well. As a goal, countries aim to increase their GNP, and when they do associate it with an increase of human welfare. GNP though, as the reading beautifully describes, does not account for how well a country does to implement environmentally friendly practices, the levels of happiness among it citizens, or even the quality of products streaming through our economy.

Question for the week: What is something you partook in today that served your immediate self-interests, but when considering the bigger picture will produce poor aggregate results for the community? Conversely, what is one thing you've done today that not only served your own immediate self-interests, but will also contribute to beneficial results for the community as a whole?

 

 

Systems Reflection Post #1

Alec Brazeau

        Systems have three essential parts: elements, interconnections, and purposes.  Elements are the easiest to identify, however they usually do not define the unique qualities of a system unless a change in elements results in a change in interconnections.  Changing up the interconnections, or the relationships between elements, usually changes system behavior.  The purpose of a system is not easy to identify; however it can be used to predict a systems behavior.  It is important to note that Meadows does not think anyone of these three parts is more important than the others.  According to Meadows, “To ask whether elements, interconnections, or purposes are most important in a system is to ask an unsystemic question,” (17).  An interesting concept that Meadows points out in this passage is that changing one leader at the top (an element) could change a countries direction, however the rest of the physical elements such as the land, people, etc. stay the same.  This is extremely pertinent in our country right now.  The new leader, Trump, has the ability to make the rest of the physical elements play his game.  However, due to the long life and slow changes that these physical elements have, the rate at which Trump can truly change the country is limited.

        Meadows also discusses stocks, flows, and feedback loops within systems.  An interesting relationship between stocks, inflows and outflows that is pointed out is that the existence of stock allows these flows to function and change independently.  This is because abrupt changes in inflow/outflow only results in gradual changes in stock.  One system that seems to slightly contradict this in my mind is the energy production and distribution system.  Storage is an issue for renewable energy sources due to their inconsistency.  In that sense, that system is lacking stock, and therefore the sudden fluxes in inflow and outflow are not independent.  The example that Meadows gave that appears relevant here is that “It would be hard to run an oil company if gasoline had to be produced at the refinery at exactly the rate the cars were burning it,” (24).  Storage (stock) appears to be key in all consumptive systems.

Question:  How can we change the interconnections within our political system in order to address climate change?  

Jennifer's Blog Post 1: Donella Meadows, Thinking in Systems, Chapters 1 and 2

Toward the end of her second chapter, A Brief Visit to the Systems Zoo (great title!), Meadows reveals the trick she's been describing in detail, with flows and stocks and feedback loops:

The trick, as with all the behavioral possibilities of complex systems, is to recognize what structures contain which latent behaviors, and what conditions release those behaviors—and, where possible, to arrange the structures and conditions to reduce the probability of destructive behaviors and to encourage the possibility of beneficial ones. (Meadows, p. 72)

The previous few pages graphically representthe results, over time, of a renewable resource or stock (fishes swimming and making baby fishes and growing and eating and frolicking in the sea), harvested by varying quantities of capital stock (fishing boats, nets, sonar).

Not everyone knows this, but I grew up in Massachusetts, on Cape Cod (named for a fish!), near the famous Georges Banks, one of the world's most important fishing resources (!), according to Wikipedia.  Early European settlers and fishers of North America describe this resource as so abundant that you could reach into the water with a basket, and pull the basket out, full of fish.

As Meadows describes, there are a few scenarios that can play out in a system that involves harvesting this renewable resource.  From page 71:

I’ve shown three sets of possible behaviors of this renewable resource system here:

• overshoot and adjustment to a sustainable equilibrium,
• overshoot beyond that equilibrium, followed by oscillation around it, and
• overshoot followed by collapse of the resource and the industry dependent on the resource.

Despite these readily comprehensible truths, a complete collapse of the 400 year-old Newfoundland cod fishery in 1992 led to a moratorium on fishing. It left more than 30,000 people without jobs as the industry dependent on the resource collapsed along with the cod population.

In 1972, Donella Meadows co-authored a controversial but compelling book that acknowledged The Limits to Growth. Some observers who've been made wise by experience are now working to remain inside the limits, and, like Bren Smith, are taking to heart the data that results from modelling this system.  A stable rate of capital stock (investment and annual reinvestment) leads to a harvest that is stable through time.  

As Meadows says, we have choices, and we can learn to choose wisely.  With or without painful experience as our teachers.

My favorite line in these first two chapters, the line that ignites my heart and soul and passion, that sparks  my hope, is this one: 

You can use the opportunities presented by a system’s momentum to guide it toward a good outcome —much as a judo expert uses the momentum of an opponent to achieve his or her own goals.

I want to understand our political, social, human systems better, so that I can better achieve my good goals.  Donella, I’m calling to your wise spirit, make me a Judo master now!  May we all of us become Judo masters!

Systems Through an Ecologist’s Lens

    As an ecologist I am trained to see how different species of plants and animals, as well as creeks, trees, and the rest of the biosphere interact with each other. Most of the time these ecosystems interact in a balanced state of equilibrium because they are closed: plants utilize what they need from soil and water, animals eat what they need, and the sun is always providing a constant source of heat and light. But what happens when too much of the water is utilized by an invasive species? Or, when humans begin to over-fish the stream? What happens when the system is no longer closed?

    The book “Thinking in Systems: a primer,” discusses what happens when a closed system, such as a fishery, is suddenly opened. The effects of over-fishing are not immediately noticeable by the casual onlooker, nor by the fish in the fishery (creek). This delay is called inertia and can be seen in almost every system. The fishery can continue to be over-fished at a constant rate for many years before there is any evidence of over fishing. An example that was mentioned in the book “The Sixth Extinction,” by Elizabeth Kolbert was that of the slow extermination of megafauna in the North American Continent. Kolbert’s argument was that even though there was a very small population of humans compared to that of, say a, Mastodon, the Mastodon has no natural predators, and a very slow replacement rate, therefore any level of hunting that might take place would eventually wipe-out the species. Humans would have no sense of the reduction in Mastodon population because the life-span of humans is too short. It would only be in the last few generations of human that someone would notice that the Mastodon was going extinct. (This is depicted in Meadow’s book fig. 41)

    As the population of Mastodon, or fish in a creek, begins to decline the system begins to change. To account for the level of hunting the Mastodon is experiencing, it would have to increase its birthrate to maintain its current population. Doing so would, despite being physically impossible, require an increased amount of food and water resources to nourish the young. As the Mastodon begins to require more resources, it will reduce the availability to other mammals who rely on the same resources. This feedback loop will eventually result in displacing other species.

    When thinking in systems it is important to remember that every action has a reaction that is not always equal nor opposite. A reduction in rain fall will reduce the available water for all the species. An increase in hunting of a species that is slow-to-reproduce will result in the reduction of that species’ population… and so on. It is also important to note that there is no way to fully account for every possible connection attached to a system. The best we can do is to always keep an eye opened to the inputs and outputs of a system.