Simulate
World.

Let’s take a deep breath and consider our world.

In 1967, ATS-3 transmitted one of the first color images of the whole Earth. Around this time, James Lovelock, who had worked with NASA’s Jet Propulsion Laboratory, was developing what became the Gaia hypothesis. Together with microbiologist Lynn Margulis, he explored how feedback between living things and their physical environment could help maintain conditions suitable for life.

As far as we know the thin surface of this Earth is the only place in the universe that has life. Beautiful for its own reasons, for its diversity and complexity, it may also be unique.

We are warmed by the same sun, breathe the same air. Simple acts such as eating food or drinking water are connected to an extraordinary chain of phenomena. Even our awareness is sensate, our reasoning and values are shaped by this world.

Yet each of our experiences are unique. We each touch a different part of the world and together those experiences may contribute to a larger picture. Some of us grew up near mountains, others in cities, some on the prairies, or in small towns or along coasts with beaches. As a result we each value different things.

The Rocky Mountains in Alberta provided the backdrop for my personal experiences. My appreciation for the world is shaped by these memories. This is a big part of what motivates my interest in these topics.

What are your most powerful memories? How many of your own most vivid memories and experiences are of times that you spent exploring, hiking, climbing, running outside? How many of these experiences do you remember as opposed to times at the office or working? Which would you like to protect most?

Do you feel our world is worth protecting? Is our world something you cherish and love? Or is it somehow damaged beyond repair? Do you think we have any power to save it? Or that we need to?

I feel it is important to stay focused on what we actually care about and what outcomes we wish for our world. The media and other voices have many dissonant opinions. In navigating these issues it helps to have defined our core values.

We hear a number of messages from the media. The first is that the Earth is a beautiful and special place. The second is that we, somehow, are responsible for destroying her. Think about the news stories or nature shows you read or watch every day. Are there any articles that talk about environmental crisis? What kinds of issues and topics do they focus on? What kinds of solutions do they focus on? How confident are you that we're going to tackle and solve the kinds of problems we are facing?

Ocean acidification, pollution, sea level rise, habitat loss, extreme weather, overpopulation, co2 buildup, drought, the great pacific plastic garbage gyre. We hear that corporate interests are cutting down the rainforests in the Amazon and Borneo, that monoculture farming is dangerous, that we’re relying on antibiotics too much, that low lying coastal regions are increasingly vulnerable to flood, that large scale refugee migrations may destabilize countries. We hear about tipping points and warnings that warming could release methane trapped in frozen sediments. The stories can leave us imagining a world that is no longer habitable. We also hear about “the sixth extinction”: the idea that human pressures could produce a mass extinction comparable in scale to the great losses in Earth’s past - be it a deified nature seeking revenge or just business as usual.

Even experts such as Stephen Hawking have urged us to consider humanity’s long-term survival beyond Earth. Elon Musk’s space ventures make the possibility of reaching Mars seem less remote. It’s clear that people we respect are concerned.

While you and I are hearing one message, other people are hearing a very different message. Some people hear that environmental radicals are blocking important economic projects such as the Keystone XL pipeline, or that needless worries over CO2 emissions are making it hard for businesses to succeed. Either way there is a sense of a hypothetical ‘other’ that we must fight who is also in some ways ourselves.

The question here is how does that make you feel? Is there a sense of frustration, or grief? Is there ambivalence? A sense of worry? Or do you just ignore it?

What I want to focus on here isn't the actual crisis itself but our response to it. Our response or lack thereof is ultimately all that matters. For whatever reasons there appears to be a certain kind of emotional reaction being produced. In many there's a kind of nihilism or melancholia; a sense of futility - in others other reactions. But few of us are unmoved.

For better or worse our emotions drive what we choose to reason about. Rationalism is rarely in opposition to emotion. We choose to get rational and pragmatic about things that we are passionate about, that we feel empowered to tackle. It is worth spending time with these emotions rather than trying to avoid them. By looking at how we feel, by creating valid emotional space around our own reactions, we can get clarity on how we choose to act. It is almost as if we need a planetary therapist.

Luckily for us just as we’re starting to have a real impact on the world, we’re also developing surprising powers. These are powers that are totally at odds with our sense of powerlessness.

This is also remarkably good timing. It could easily have been that humans overpopulated the world before we had technology, or that ideas like “electricity” just weren’t possible, that physics didn’t allow transistors or that environmental tipping points were reached sooner. It is an interesting coincidence that just as we’re starting to wreak global havoc we have the power to also effect global healing.

We’re entering an age of “civic applications”. Sometimes it feels like the only thing moving as fast as the crisis is the growth of our social networks. We have a new ability to react in concert on a large scale. For example in response to the 2010 Haiti earthquake there was a massive international grassroots community effort to help map streets and remotely direct emergency operations and logistics. We see civic applications like:
1. Ushahidi - an internet based emergency crisis response tool.
2. Wikipedia - of course.
3. Folding@home.
4. OpenStreetMap and projects like Green Map.
5. Code for America and their work.

Earth science has also blossomed. We’re beginning to understand the complexity and subtle interactions among natural forces in ways we did not before. In Louisiana, the Army Corps of Engineers’ Mississippi River–Gulf Outlet altered wetlands through dredging, erosion and saltwater intrusion. The ecological effects of the channel and the failures of flood protection during Hurricane Katrina are related concerns, but they are not the same mechanism.

These experiences show why infrastructure decisions need to account for the larger systems around them. With satellite data and better models, we have more tools for understanding the consequences before we act.

Moore’s law is acting in our favor. Machine computation, big data and computer simulations are able to simulate large scale outcomes of complex systems. Hybrid human/machine systems that combine human intuition with machine speed and memory are able to search large problem spaces for sweet spots faster than either could do alone. Being able to synthesize the input of many people also creates a possibility that more minds can participate in looking at and understanding the problems we are facing.

We have enough history as a planetary civilization to understand our impacts on our world. We’ve seen that side-effects can dominate over intended consequences. And we’ve succeeded on a global scale such as making substantial progress toward polio eradication through the Global Polio Eradication Initiative and phasing out the production and consumption of chlorofluorocarbons under the Montreal Protocol. We are struggling to unify around reduction of CO2 emissions. The Kyoto Protocol has not been enough to turn global emissions around. Countries are now putting forward new emissions pledges ahead of negotiations for a global agreement in Paris.

The reality of our impacts are more nuanced than can be described cogently using text. It's true that we are a predominant force on this planet. And it is true that our impacts are significant enough that they are becoming a part of the geological record. However we're not entirely a negative influence.

Reality as they say is 'complicated'. We can begin to approach an understanding by discussing the biggest topics, but small systems also have big impacts. Ultimately we'll need to bring new kinds of tools to bear on seeing our way through this issue clearly.

At the core of human impacts on earth is human population growth. As our populations grow we have more and more impact, consuming resources faster and rewriting landscapes to better fit our desires.

In 1798 Thomas Robert Malthus published 'An Essay on the Principle of Population'. He argued that population could grow faster than the means of subsistence, with hardship acting as a check on growth. Later ecological models also explore how populations interact with limited resources. But human ingenuity changes the relationship: improvements in agriculture can increase yields and alter the pressures we face.

What would it take to build a more accurate model? What are the key facts and issues that would better predict realistic outcomes? What kind of predictive power would such a model have? What would be the trust that people would have in such a model?

One of the main effects of human activity is global warming. Population, consumption and the technologies we use all shape our impact. Carbon Dioxide (CO2) from fossil fuel consumption and other human actions (such as deforestation and cement production) is altering the composition of the atmosphere and is a primary cause of global warming.

Fossil fuels supply much of the energy we use. Burning them releases carbon dioxide, a greenhouse gas that reduces the rate at which Earth loses heat to space. The natural greenhouse effect is one reason the Earth is habitable; adding more greenhouse gases changes that balance.

Concentrations of CO2 however have increased and the added greenhouse effect is warming the planet. This is one of the primary topics that Al Gore has been focusing on with his work on “An Inconvenient Truth” and is of grave concern to any of us who happen to live on this planet. The effects of warming, together with the direct effects of increased CO2, include:

1. Ocean heat absorption. The oceans may be moderating the warming trends overall by absorbing heat from the greenhouse effects. Since they have a vast thermal capacity they can store energy without it affecting us as “directly”.
A related but distinct effect is ocean acidification. CO2 in the atmosphere reacts with water to produce a weak acid H2CO3 (carbonic acid). This then dissociates into hydrogen ions and bicarbonate ions. The hydrogen ions increase ocean acidity. The average pH of today’s surface waters is about 8.1 - a decrease of 0.1 pH units over the last 200 years.
2. Coral Reef Death. Organisms that make calcium carbonate shells such as coral reefs, snails and sea urchins are affected directly by both water warming and ocean acidification. Overfishing, pollution and development also have a negative impact on reefs. Tropical coral reefs are the foundation of marine biodiversity, providing shelter and habitat for many other species. As well coral reefs provide economic benefits to fishermen and of course are beautiful in their own right. Continued warming and acidification threaten the survival of reef ecosystems. An estimated 16 percent of the world’s coral reefs were lost during the global 1998 bleaching event, which affected many regions, including the Seychelles.
3. Hurricane ferocity. One ingredient for hurricanes is warm water. Usually surface water temperatures need to be over 26 degrees Celsius (79 degrees Fahrenheit) for a hurricane to form. Science seems to support the notion that warmer temperatures caused by global warming may contribute to more intense hurricanes. Hurricanes can cause substantial damage, especially where coastal wetlands are degraded and flood defenses fail.
4. Forced plant and animal migrations. As temperatures increase plants and animals reproduce at increasingly extreme latitudes. In some cases due to geography they have no options and simply go extinct. Agricultural pests also migrate towards the poles as ideal habitats change. These changes affect us as well. For example, mountain pine beetle outbreaks in western Canada have transformed forests, with consequences for habitats, forestry and local communities.
5. Sea level rise. Warming seawater expands, and melting glaciers and ice sheets on land add water to the ocean. Rising seas increase the risks facing coastal communities.

Our planets oceans are carrying the brunt of this and to some degree are 'buffering' the impact such that we don't see the repercussions as quickly. It is also worth noting that the oceans also carry a number of other human impacts - in a sense they are allowing us to run our accounts negative and hide our debts for a while.

Aside from fossil fuel consumption humans also have other impacts on the planet at a large scale:

1. Ocean Fish Overconsumption. A widely discussed 2006 study projected the collapse of currently exploited fisheries by 2048 if the trends it analyzed continued. Here “collapse” meant catches falling below a tenth of their recorded maximum, not extinction of all ocean fish. The extrapolation has been debated, but overfishing, pollution and habitat loss remain serious concerns.

2. Fertilizers and pesticides. Fertilizers add nutrients to help crops grow; insecticides such as neonicotinoids control pests. Their effects extend beyond the field: excess nutrients can harm waterways, while pesticides can affect organisms other than their intended targets.

3. Honeybee Colony Collapse Disorder. Losses of managed honeybee colonies raise concerns for agriculture, alongside pressures on wild pollinators. Different pollinators face different combinations of disease, habitat loss and chemical exposure. On a similar note DDT (dichlorodiphenyltrichloroethane) is an insecticide which we did ban because of its impact on bird shell thickness which was putting wild bird populations at risk. Bald eagles accumulated DDT and its breakdown products through contaminated prey, particularly fish, contributing to eggshell thinning and reproductive failure. The hope is that we can understand these pressures well enough to protect pollinators and the ecosystems that depend on them.

4. Ocean pollution. Although long chain polymers such as plastic tend to be fairly inert there are unknown risks here as well. The Great Pacific Garbage Patch Gyre is an example of human pollution where there are exceptionally high concentrations of plastics, waste production sludge and other debris trapped in ocean convection currents. Much of the debris consists of dispersed, often very small plastic particles rather than a continuous floating mass. Fish, marine birds and animals consume marine debris and choke to death. On Midway, albatrosses also bring plastic debris back to their chicks while feeding them.

5. Pollution. There's a wide range of other kinds of pollution on land, not just landfill or CO2 production but phenomena such as mountaintop removal, fracking and stream pollution. Together these have significant impacts on wildlife populations.

6. Aquifer exhaustion. Farming communities have a hydraulic dependency on water reserves. Typically aquifers are used in times of drought but heavy pumping can compact susceptible sediments and permanently reduce an aquifer’s storage capacity. And we've been utilizing water resources close to maximum thresholds such that aquifers are always needed.

7. Invasive species.

8. Diversity Loss through habitat fragmentation, pollution and industrial farming practices. Disappearance of birds, frogs, fish and megafauna and their replacement with corn and other monoculture crops. Often it isn’t just any one thing but a combination of things that cause extinction events. Biodiversity is a key measure of resilience that defends against “black swan events”. Events of a magnitude that we cannot appreciate or understand them ahead of time. The best way to deal with these kinds of events is to have diverse resources such that at least some of us survive. It’s also similar to playing a giant game of Jenga with the environment. Loss of a key species can have surprising and unexpected effects as other species they rely on die off.

Not all trends are negative. Jesse Ausubel argues that higher agricultural yields and changes in consumption can reduce the amount of land needed for production, creating opportunities for nature to rebound. This is an argument about land sparing under particular conditions, not a claim that vegetation everywhere has recovered.

See Jesse Ausubel’s talk, Nature Rebounding (January 13, 2015).

In Hyperobjects: Philosophy and Ecology After the End of the World, Timothy Morton talks about objects which are simply too large for humans to see. Objects which exist on a physical or temporal scale so vast that we cannot comprehend them. The author characterizes Global Warming as one of these objects. Effectively he implies that we may need to revise our philosophical tools in order to be able to face these challenges.

The challenges we face can be 'existential'. They can reach beyond a single community to threaten humanity’s future. In Under a Green Sky, Peter Ward explores links between warming, oxygen-poor oceans and mass extinctions. One proposed mechanism involves toxic hydrogen sulfide released from oxygen-depleted seas, rather than a blanket of methane suffocating the planet.

The details matter, but there’s a broader point: some changes can set off feedbacks with consequences far beyond the event that begins them. We need ways to investigate those possibilities without confusing a proposed mechanism with a certain prediction.

There is also a somewhat pessimistic attitude that this is all normal. That the Earth is a chaotic system and that extinction events are totally normal. This is being labelled as “the sixth extinction”, just one more caused by similar kinds of self induced criticalities. There is a fatalism here, in some respects similar to the fatalism that many fledgling space going civilizations run up against a kind of 'Great Filter' and that this is why the stars are not filled with radio signals from other intelligent species.

We even have a label for our era in the grand scheme of things — calling it the 'Anthropocene'.

The Anthropocene is an informal term for a proposed epoch in which human activities have a significant global impact on Earth’s ecosystems and geology. Our actions may leave traces in the future geological record.

We have a planet-straddling civilization that transforms landscapes for food, dams and diverts rivers, and builds cities whose lights are visible from space. We’ve altered the composition of the atmosphere and are warming the planet.

Earth is about 4.54 billion years old, and life has existed for billions of those years. The research that reveals this history is the work of thousands of scientists over many generations: field studies, fossil discoveries, comparisons and continuing debate.

The Phanerozoic — the interval encompassing the familiar fossil record of abundant animal life — is divided into three eras: the Paleozoic, Mesozoic and Cenozoic. Their names mean ancient life, middle life and recent life.

The Paleozoic begins with the Cambrian diversification of animal life. Plants and animals later move onto land. The era ends with the Permian–Triassic mass extinction, the largest of the five major mass extinctions commonly recognized in the fossil record.

The Mesozoic begins with the Triassic. The first dinosaurs and early mammals appear during this era, and dinosaurs become prominent on land. Pangaea breaks apart. The era ends with the Cretaceous–Paleogene extinction, which eliminates the non-avian dinosaurs along with many other groups.

The Cenozoic is our era. Mammals and birds diversify into many of the ecological roles left open by that extinction. Human pressures now raise the possibility of another mass extinction. Declines in wildlife populations are alarming, but they should not be confused with a measured percentage of all species already extinct.

The five major events commonly discussed are the end-Ordovician, Late Devonian, end-Permian, end-Triassic and end-Cretaceous extinctions. They show that living systems can change profoundly — and that recovery can take far longer than a human civilization has existed.

We can think of our world as made up of stakeholders and their interests. Nature herself, the poor, the middle class, city level government, state and federal concerns. There are transnational corporations and the wealthy elite that ostensibly “own” on paper and with guns and structural violence the majority of the worlds resources.

Not all stakeholders need to necessarily participate in all decisions but regional stakeholders seem to be marginalized unduly. Different stakeholders have different goals, some are environmental, economic, political, social, humanist, utilitarian and the like.

The current decision making structures here in the west seems to be centered around an idea of representational voting in democratic regions, with autocratic dictatorships in other regions. Corporate interests seem to be the main decision making structure planet wide with law and policy steered in that direction (such as NAFTA and TPP). These corporate structures appear to be deeply interwoven into governance in such a way that it can be said that they effectively govern. But at the same time they don’t seem to be acting in an intelligent (or especially unified or responsive) way to ameliorate the environmental concerns.

In fact the decision making structures we do have seem to be flat out awful. The response to Hurricane Katrina is evidence of this. Disaster response also raises difficult questions about how outside agencies coordinate with local communities, as in Haiti. There's a good possibility that nobody actually knows what they're doing in fact and when dealing with the scope and scale of the crisis we're facing that the best response from the top down will be delays.

In June 2015, G7 leaders called for decarbonization of the global economy over the course of this century. This is a political declaration, not a binding worldwide treaty to eliminate all emissions by a fixed date. Generally speaking there’s no visible consistent or unified international response to the burgeoning crisis. In many cases we’re spending billions of dollars to pay for environmental damages caused by millions of dollars reaped in profit by private corporations.

We can critique governments and corporations but as well at the individual level there’s a wide range of passive responses that won't work:

1. Waiting for our governments to “do something”.

2. Hoping for energy alternatives to emerge quickly enough that we can stop using fossil fuels and possibly repair the earth and continue with business as usual.

3. Hoping for other technology to emerge quickly enough to save the world in some undefined way.

4. Trying to get off planet before the crisis really hits.

5. Life-boating; the wealthy are building retreats where they feel safer.

6. Denialism. Trying to claim nothing is happening and that everything is fine.

7. Geoengineering is being considered; this may also have dramatic side-effects.

8. Relying on isolated consumer gestures, such as avoiding plastic bags, without also organizing around larger collective decisions.

9. Hoping for a sudden “planetary awakening” of human consciousness.

There are “ideas” such as Cybernetics or even the Technocracy Movement (http://en.m.wikipedia.org/wiki/Technocracy_movement ) that were proposed years ago. I don’t yet see these ideas cohering into a widely shared strategy. People are still being split on hot button issues that map to their vested interests and are exhibiting avoidant behavior.

What we’re not seeing is a pragmatic, unified, planet wide push based on rigor, the best science, unified opinions and direct action.

What are reasonable predicted global outcomes for humanity over the long term? Basically - What is actually going to happen? One trajectory I fear looks something like this:

1. Fear, Uncertainty and Doubt continues to be manufactured by corporate and private interests over any outcomes that clash with the status quo or “business as usual”. Motives continue to be greenwashed and everything continues as is.

2. Collective decision making by real stakeholders continues to be ineffective.

3. An increasingly rapid degradation of quality of life occurs.

4. In the next 20~30 years we begin to hit “turning point” decisions. We choose to abandon entire cities, we choose to let people die, we begin “circling the wagons”.

5. Food security issues lead to a loss of confidence in governments. Incendiary civil war under social and political or religious pretexts expands. Intentional eco terrorism is used to starve opponents of resources. Full scale war even nuclear war occurs.

6. Easily obtained natural resources are exhausted.

7. Mega-extinction events begin to occur starting with sea-life.

8. Humans are forced to retreat to the poles.

9. A few wealthy humans are able to life-boat; leaving the planet.

10. A massive reduction in quality of life for the remaining.

11. Insufficient intellectual capital and natural resources left to try “grand solutions”.

This is a feared scenario, not an inevitable sequence or a calibrated forecast. Its emotional force is part of what drives my desire to find better ways to act together.

There isn’t an underlying consistent sense of “how to fix things”. As people most affected by environmental change we are all primary stakeholders. Yet we are in conflict with each other and unable to act in concert.

Some of us were raised with Thoreau, others with Ayn Rand. There’s a wide range of opinions about what nature is and how we should act. At the end of the day different people react in different ways, depending on their upbringing, their culture, their values.

Troublingly private interests with more focus are able to pursue their own short term interests. They foster fear, uncertainty and doubt and make short term profits despite the best interests of the majority stakeholders. Long term of course nobody actually wins.

The planet will persist, but that does not secure the futures of humans or the other species we care about. Our difficulty in acting together can magnify the dangers. We're acting like deer paralyzed in the headlights of an onrushing car; unable to understand or think fast enough to respond intelligently.

It makes sense that this is hard for us. At heart we are still in some respects just very smart monkeys. Thrown upwards in an evolutionary crescendo. An utterly confounding combination of instinct and godlike apprehension. Capable of great organization and great discord. Just as our world shaped us, we are now shaping it.

The evidence shows that we are poor decision makers. It’s not necessarily our fault. We’re simply not smart enough (yet) to deal with the complexity of the systems around us. While we can see fast events like literal forest fires, we have trouble seeing slower fires like Pine Beetle Infestations.

It’s like a 12 step program for civilization where we need to first acknowledge that it is impossible to understand the world, that it is impossible to reason fully about the outcomes of our actions, that the side-effects of our decisions tend to dominate over intended consequences.

This is a crisis of organization. Spurred by population growth, by our powers over nature, and by our limited ability to reason we now need to evolve new ways to think as communities.

Yet for better or worse we are the only thing that can save this world and we must find ways to organize to affect our future history. At some level this is probably one of the few jobs that matter. Saving money into a retirement fund seems meaningless in the light of a future that may not even exist.

The question is can a group of very small very smart monkeys learn to understand a huge planet well enough to protect it? Can we gather and organize our data, our understanding into a decision making structure that lets us both see and act better? Can monkeys organize such that they can avoid a crisis they cannot see, touch, smell, taste or bite? That is contrary to our instincts, contrary to our skills? Will we become a footnote in the fossil record or will we become something new?

Hacking the system

It appears that while we have planetary impacts we don’t yet have planetary level organization. We have simply outgrown our decision making structures.

Concepts such as representative democracy or capitalism just don’t seem to map to ideas such as local stewardship, longer term growth and investment in nature.

It feels like that solutions to the crisis will not come from the same patterns that created the crisis. We’re going to have to hack the system at some level. It’s going to mean structural change rather than procedural change. We’re going to have to build new systems right next to the old systems and start switching over.

How do we do this? How do we learn how to learn better? I personally feel the answer has to involve local decision making - that we have to find a way to give stewardship back to local stakeholders who are disempowered, mis-informed and checked out.

We have to find a way to give all stakeholders (including nature) a voice. We have to find different models of decision making that are bottom up, collaborative, that encourage understanding and participation rather than discourage it.

The goal is to provide people and communities with tools that allow them to simulate and predict the impact of new laws and policy on their regional social, economic and environmental landscape.

If you’ve played SimCity then you're familiar with the idea of digital simulations and models. Basically you take a small toy world, a stripped down and simplified version of the real world and start asking 'what if?'. And it turns out that this is good enough to often answer many questions, or at least reject some of the worst ideas.

Modern weather reporting is a good example of the power of digital simulation. At first we had Farmer's Almanacs that had a historical record of weather patterns. Now we have supercomputers that can do near term predictions with some accuracy - and we've come to rely on these models to make better decisions.

The problem is that while simulations are increasingly common they're not typically exposed to citizens. Right now they are the playthings of an elite. The idea is common (touched upon by many such as Buckminster Fuller with 'The World Game' or Mark Pesce in 'The Playful World' as well as by many others) but in practice such tools are not widespread.

We (and by this I mean ordinary citizens) should be able to use tools like this as a powerful lens for understanding our world. Rather than committing to one path, we can compare a range of scenarios and at least coarsely evaluate their possible outcomes to reject the most egregiously bad decisions. But we need to find ways to put these tools into the hands of the actual stakeholders: the people on the ground who are affected most by the decisions our governments make.

Digital models are not new. Larger corporations, policymakers and governments do have digital models of the predicted impacts of their decisions. Their planners are able to strategically look into the future to make the best decisions as the sum of all of their knowledge.

What we don't have is widespread access to civic digital models that ordinary people can inspect, use and challenge. As citizens we often read summaries of what scientists or planners think without getting to explore the models ourselves. We are not given an ability to participate in the decisions that affect us as stakeholders in the region. At best we get to vote based on the opinion supplied by experts.

The questions are how can we build civic grassroots models with real policy, real data? How can we allow ordinary citizens to simulate their bioregions, watersheds and ecosystems forwards in time? How can we give people tools to anticipate local events (even coarsely) on a broad scale rather than just react to them?

Simulating the effects of land-use laws, existing and proposed civic policy, natural phenomena and any other factors that contribute to regional outcomes is challenging. But it’s important to provide new tools for communities. The kinds of subjects that may be a part of the simulation include zoning laws for greywater collection, land use law, seasonal rainfall, the behavior of river systems, fishing, hydroelectric, farming, farming run-off, aquifer usage, dollar incomes, oil consumption and CO2 production. Participants should be able to extend the model and add more subjects as well.

These simulations should be open, public and free. Anybody should be able to contribute facts or relationships to the models. Anybody should be able to use or modify the models as they wish.

There will be many kinds of models, many kinds of simulations, written by different people. There’s no desire to write a single “solution”. But there will be an effort to share data. At the end of the day these will be civic resources: kind of like a real world version of SimCity. The hope will be that a community can use this to see itself better, enfranchise participation by the regional stakeholders and teach people about the complexity of local ecosystems.

It's worth noting that the goal isn't to actually 'solve problems' directly. If a community ratifies the cutting down of their own forests - so be it. The goal is to just empower people to make more complicated decisions together more effectively. At some level we have to let the regional stakeholders make their own decisions. A computer simulation can explore the possible outcomes of proposed policies and compare factors such as economic benefits and environmental costs. The assumptions and the weights given to those factors must remain open to debate. More importantly unexpected side-effects can be discovered and examined. It becomes harder for private interests to gain an advantage by concealing costs or withholding information.

Imagine an ordinary individual being able to present a case to city council for a watershed protection plan that included an actual simulation of that watershed and that could show both the intrinsic benefits of protecting the ecosystem and show how financial costs and rewards balance out.

Imagine being able to have a simulation of an entire town that could computationally project the outcome of specific policy changes such as laws regarding wildlife hunting permits, daylighting streams, farmland pesticide use and the like. New laws that had unforeseen side-effects might become more visible. Effectively this becomes a form of participatory budgeting, and offers a possibility of an enlightened civic debate.

Imagine simply being able to zoom into your bioregion and see the hidden systems at work, the input and outputs that define your community. Imagine being able to explore the future projected behavior of the system based on known relationships. Imagine being able to play with parameters, try out new relationships, or change assumptions and test outcomes.

At the core of a more rigorous approach to modeling civic issues is good data. This has multiple criteria:

Water Data. Water is such a critical component of an ecosystem model that it will show up in many of the examples as a core topic. It may need to be modeled especially accurately. The water cycle is complex. Heavy pumping can, for example, compact some aquifer systems and permanently reduce their storage capacity. And in some regions water shortages don’t start to take place until years into a drought due to the hydraulic nature of water reserves. Seasonal variations in water discharge into streams depend on snow melt the year before and a variety of other wind and weather conditions. Farms and urban centers use water at varying rates and in varying ways depending on assigned water rights. The migrations of fish up-river depend on many water factors; not just dams or fish ladders but also turbidity, temperature, salinity, log overhangs just to name a few.

Relationships. Unfortunately the relationships between data points are not documented as well as the data itself. There are seasonal datasets that show how complex systems behave over time but these just log historical events. It may be possible to derive relationships from these facts but that is still work that needs to be done.

Multiple data sources. Substantial data already exists describing hydrography, animal habitat, farming conditions, water rights and the like. Collecting available local facts, figures and relationships that describe the behavior of local watersheds, bioregions, the effects of law and policy on those regions and people is critical. This will be akin to an OpenStreetMap or Ordnance Survey. In the United States the Census Bureau and the United States Geological Survey provide data including roads, human populations, the National Hydrography Dataset and the Watershed Boundary Dataset. There are many other data sources as well.

Historical data. Simulations need to be calibrated against historical data and tested on observations not used to fit them. In the initial stages the goal isn’t necessarily accuracy however: it is to act as a way to cut away at the most egregious rhetoric, and as a teaching tool about the complexity of natural systems, the value of thinking in terms of whole systems, and the risks of unexpected side-effects.

Data resolution. Farms have certain production rates of certain kinds of crops. They also have certain inputs in terms of water and other resources. Energy generation such as hydroelectric, solar, coal each have initial costs and ongoing costs as well as yields. Urban centers consume resources at a certain rate - below that rate chaos ensues or populations begin to migrate or have diminished productivity. There will be many kinds of models at varying resolutions, with many kinds of data. All farms in a given model may only produce one output; or in other cases (such as modeling California Drought) it may be broken down into specific kinds of crops (such as grains, avocado and almonds).

Curated. People need to be able to take observed facts and relationships about a region and pour them into some kind of shared open database. This database needs to be similar to wikipedia in that it has to be open yet probably curated to avoid spam.

Pre-populated. The models should allow stakeholders to populate a scenario with their own data. However, as well, seeding the system with provided data helps novices participate more easily.

A civic approach also has demanding user interface requirements:

Simple. The user interfaces need to approach people at their own level. That means cartoonifying the data where needed if it is too complex for a certain audience. Different implementations of the simulations will probably address different audiences.

Simulate outcomes. People should be able to simulate forward in time the interaction of the facts and relationships to computationally simulate outcomes. This implies some kind of computational infrastructure. In an ideal world it would be distributed and run on individuals machines rather than on servers (in order to be more civic).

Multiple simulations. It likely will be many simulations written by many different people. It is unlikely that any single solution would dominate. Just as there are many applications for word-processing there are likely going to be many applications for modeling communities.

Varying accuracy. Accuracy of the simulations and models doesn’t have to be precise in initial implementations. The goal is mostly providing a framework for people to test their observations and ideas. The shift is to make assumptions and their consequences explicit. Stakeholders must be able to question the inputs, relationships and model structure, compare outputs with observations, and see where uncertainty remains. That already is a significant shift.

Some of the benefits that a civic modeling approach could provide include:

Engagement and learning. I see open digital models of communities as tools for citizen engagement in local politics. Tools that let people try out their own ideas have an effect of both educating and engaging citizens in effective ways. Citizen science tends to be deprecated in favor of paid expertise; this may sway the balance back towards open participation.

Level the playing field. I also see this as a way to level the playing field between private interests and the public. All too often private ventures are able to organize more effectively and pursue goals that are not always necessarily in the public interest. If ordinary citizens could have access to similar data and a similar understanding of regional issues they may be able to suggest alternatives.

More minds at the table. Right now most people are checked out of civic politics. They don’t participate in city council and it often feels like it is too much work to get involved. But more minds can provide more solutions. Our systems could benefit from more insight if there is an effective way to coordinate participation.

Memory storehouse. There’s so much local civic understanding that is in just a few peoples heads. The relationship between various pieces of land and the best uses for that land. The way things used to be, or the way things could be. A model acts like a kind of local wikipedia, it stores community knowledge in a way that is useful.

Aligning voices. Any proposition to include more people in local decision making has to also dampen the typical noise and furor of discussion. Decision by committee can be ineffective because it is hard to hear everybody and everybody has strongly divergent opinions. The benefit of a model is that although participants can explore arbitrary ideas - the system itself simulates the outcomes and imposes rigor. Effectively discourse shifts from head to head rhetoric to instead testing the merits of various models. Effectively it is like introducing a ball into a game, or a set of pieces. The discussion focuses around a target rather than at each other.

More decisions more often and more directly. In a representative democracy there’s substantial complexity around decision making. We tend to have a lot of formalisms to protect against voter fraud or intimidation, and there’s quite a bit of effort to convince stakeholders to vote a certain way. In a direct participation model voting could be more frequent and decisions could be easier to evaluate given that multiple models can be scored and tested and compared to each other. Models can make social, environmental and economic tradeoffs visible, but deciding how to value those outcomes remains a community decision. This means that more decisions can be made more often and civic policy can hew more closely to changing environmental conditions more quickly.

Complexity reduction. The world is actually too complicated to understand with our unaided senses. Side-effects often dominate. There is an information horizon which approaches us faster than our ability to process. Various stakeholders practice asymmetrical information warfare against each other to reap short term benefits at the expense of everybody else. The combination of human-machine hybrid reasoning helps us deal with larger problems. Machines provide brute force search power to explore large problem spaces and humans provide intuition to better find sweet spots in those large spaces.

Anticipatory Democracy and Durable Communities. A simulations based approach can provide a fresh alternative to traditional governance. At the end of the day the goal is to build intelligent durable communities that thrive and that in fact can anticipate from and benefit from change rather than merely react or merely sustain their own existence. There’s a possibility that these kinds of communities could make their local ecosystems much richer, much more diverse and more resilient to the inevitable black swan events that occur in our world. Most importantly it can enfranchise the real stakeholders, making it harder for private interests to conceal costs, and shift wealth production to being invested into local ecosystems rather than being extracted.

Balinese Water Temple Simulation

Probably one of my favorite examples of civic simulations and the power of modeling is the paper “Emergent Properties of Balinese Water Temple Networks: Coadaptation on a Rugged Fitness Landscape” by J. Stephen Lansing and James N. Kremer. Lansing was working in Bali during a time that the Balinese government was trying a new “intensive green agriculture”. The Green Revolution of the 1970’s brought a lot of new intensive farming techniques to communities around the world and for some reason these practices were failing in Bali. Lansing and Kremer built a computer simulation of the more traditional practices that the Balinese had been using and was able to show that the Green Revolution practices were actually not serving Bali. Their work showed why the coordination embodied in the water-temple networks mattered for irrigation and pest control:

https://www.youtube.com/watch?v=h9ozS8BKUFI

http://www.ft.com/cms/s/2/83df61cc-caf2-11e1-8872-00144feabdc0.html

https://doi.org/10.1525/aa.1993.95.1.02a00050

This is another compelling example of local decision making in Bali. In 'The Fish Bank', recorded by The Moth in November 2014, Jensi Sartin describes working with a fishing community to protect part of a reef so fish could grow and reproduce. His account connects ecological recovery with the knowledge and cooperation of local people.

https://www.youtube.com/watch?v=I2wOxzD4aJE

A good example of connected consequences is the reintroduction of wolves into Yellowstone National Park in 1995. Researchers have studied changes in elk, vegetation and other species through the idea of a “trophic cascade”: effects that pass through a food web. The story is more complicated than wolves simply changing the rivers. Hydrology, other animals, climate and the history of the landscape also matter.

If citizens in the Yellowstone bioregion had access to models that incorporated the facts, science and research of scientists in the region then they could have explored competing hypotheses and possible outcomes before acting, and tested those models against what happened afterwards.

Reintroducing wolves is contentious because some farmers feel that wolves are a net negative (in that they kill livestock). This is a good example of where a better shared understanding between all stakeholders at a grassroots level would allow certain kinds of non-obvious decisions to be better agreed upon.

https://www.youtube.com/watch?v=ysa5OBhXz-Q

The EcoTipping Points Project describes how villagers in Rajasthan’s Alwar district restored traditional earthen rainwater-harvesting structures, known as johads. In Gopalpura, work supported by Tarun Bharat Sangh helped water return to wells and encouraged further restoration. The practice spread to hundreds of villages, linking watershed recovery with community cooperation.

http://www.ecotippingpoints.org/our-stories/indepth/india-rajasthan-rainwater-harvest-restoration-groundwater-johad.html

This is an excellent example of how decisions can have impact at many levels. It also illuminates an often difficult to see association between poverty and environment. Environmental damage had deepened the pressures on their livelihoods. By finding ways to heal their watershed many of the traditions and values started to re-knit themselves back together.

There are many more examples of this kind of work throughout the world. One of the groups working on topics like this is https://www.digital-democracy.org/ .

In 2010 the Deepwater Horizon oil rig exploded and sank. Oil flowed into the Gulf of Mexico for 87 days, causing extensive environmental and economic damage. Response efforts included skimming, booms, controlled burns and chemical dispersants. The spill’s effects reached fishing communities, tourism and marine habitats.

The disaster raises a civic question: what information about the risks of drilling should have been available to people whose livelihoods were at stake? Rather than assuming which models BP possessed, we can ask what an open regional model might have made visible — the pathways of a spill, the limits of response measures, and the distribution of possible losses.

If local fishermen, tourist agencies and other stakeholders could examine those risks together, they might be better placed to challenge drilling proposals and argue for stronger safeguards. Models would not guarantee agreement or prevent every disaster, but they could make the stakes more legible.

The Grand Coulee Dam transformed the upper Columbia River. Its reservoir inundated places of great importance to Indigenous communities, including Kettle Falls. Built without fish passage, the dam cut off migrating salmon and steelhead from habitat upstream.

The economic benefits of irrigation and electricity were weighed against losses that were not valued equally. The Northwest Power and Conservation Council’s historical account describes Canadian officials discounting the loss of salmon because they saw no commercial fishery at stake. That accounting failed to recognize the full importance of the fish to Indigenous peoples and the river’s ecology.

Salmon connect rivers, land and the animals that feed on them. A decision about a dam can therefore reach far beyond the water held behind it. Understanding those connections is precisely the kind of task for which a shared regional model could be useful.

In 2013, Oakland reopened a section of the channel linking Lake Merritt with the Oakland Estuary. Lake Merritt is a tidal lagoon, but roads, culverts and control structures had constricted its connection to the bay. Removing a dam and tide gate improved circulation through the channel.

The project is a small example of how changing infrastructure can restore ecological connections inside a city. It also makes a good subject for a civic model: how do tidal exchange, water quality, habitat and public access interact?

Oregon’s proposed Nestlé bottled-water plant at Cascade Locks involves a contested water exchange between the city and the Oregon Department of Fish and Wildlife’s Oxbow Hatchery. The agency’s involvement in that exchange is not the same as approval of the entire plant. The proposal has been discussed in public meetings, while the adequacy of review and the public interest in the water remain disputed.

Is selling this particular water a good decision overall? Is there a water shortage? Who would benefit, and who would bear the risks? Are there unexpected consequences for wildlife or communities downstream? It’s a complex decision, and a model that lets people examine those tradeoffs could help the debate.

Case Study: California Drought

Drought combines shortages of precipitation and available water with the demands we place on that water. Heat can make those pressures worse.

This is a good example of a crisis to model for a number of reasons. The media presents it with a certain tone of hysteria and discord. Water is an intersectional topic that underpins many environmental, social and political issues each with its own stakeholders. California has extensive hydrological data that can help us compare policy scenarios, though predictions depend on model assumptions and data quality.

Solutions are many-fold and difficult to choose between. Desalination? Migration? Better conservation? The crisis is one of organization. Solving California water issues requires large scale social and political mobilization and that in turn requires consensus. Consensus building requires some kind of shared understanding presumably.

California has a unique water hydrography with highly managed water sources. Snowmelt from the Sierra Nevada, rainfall and groundwater all contribute to California’s water supply. Reservoirs, aqueducts and local systems connect those sources to ecosystems, hydropower, farms and towns. Hetch Hetchy is one part of that larger network, not the route taken by all of the state’s water. See also:

http://en.wikipedia.org/wiki/Water_in_California
http://en.wikipedia.org/wiki/California_State_Water_Project

A simplified digital model should make its limits clear and be compared against observations and more detailed models. It should show different stakeholder interests and should let us try out different scenarios.
A few measurements help establish the scale. They refer to different quantities and time periods, so they should not be treated as interchangeable measures of a single reserve.

Groundwater can buffer a drought, but sustained pumping can lower water tables and compact susceptible sediments. Storage lost through compaction may not be recoverable. Claims that the state has “one year of water left” also need care: water held in reservoirs is only one part of the supply.

The point of modeling is to make these distinctions usable. People need to compare demand, seasonal supply, environmental flows and long-term groundwater limits — and see who benefits or loses under different choices.

The Sacramento–San Joaquin Delta links two major rivers with San Francisco Bay. Its channels, wetlands, farms, levees and water-export infrastructure make it an intensely managed landscape. Many reclaimed islands lie below sea level and depend on levees.

Delta smelt are small fish native to the estuary. They generally live about a year, making them vulnerable to changes in habitat and conditions during a single breeding season. They are a different species from longfin smelt, whose life cycle is longer.

In 2015, efforts to protect delta smelt are part of a contentious debate over freshwater flows and water-project pumping. Habitat, water quality, food availability and other pressures interact with water diversions; no single statistic captures the whole problem.

This is a good example of why communities need shared models. A useful model would make the ecological assumptions and the costs of different choices visible, without pretending that it can decide how those costs should be shared.

http://news.nationalgeographic.com/2015/04/150403-smelt-california-bay-delta-extinction-endangered-species-drought-fish/

Participate!

What steps can we take to make this happen?

Collaborate! Help support the actual development of real world models with real world stakeholders. This includes funding and developers and leveraging the expertise of people who have built these kinds of simulations already.

Stakeholders. Know your place. Help find people that are facing the kinds of informational challenges that technology like this can help resolve. These people effectively become the seeds of the community and have to be chosen carefully.

Make. The best approach seems to be to build actual examples that showcase the ideas, to speak on these topics, get feedback and build a community of active participants to move this idea forward.