Tag Archives: economic interactions

NRC Report on Land Change Modeling

Essential reading for all you land change modelers out there!

The report Advancing Land Change Modeling: Opportunities and Research Requirements was released recently in pre-publication format via the National Academies Press web site: http://www.nap.edu/catalog.php?record_id=18385 Additional report info can be found here as well: http://dels.nas.edu/Report/report/18385. The study committee included several geographers, assessed the current state of land-change modeling, and identified opportunities for future developments in these models.

Urban development, agriculture, and energy production are just a few of the ways that human activities are continually changing and reshaping the Earth’s surface. Land-change models (LCMs) are important tools for understanding and managing present and future landscape conditions, from an individual parcel of land in a city to the vast expanses of forests around the world. A recent explosion in the number and types of land observations, model approaches, and computational infrastructure has ushered in a new generation of land change models capable of informing decision making at a greater level of detail. This National Research Council report, produced at the request of the U.S. Geological Survey and NASA, evaluates the various land-change modeling approaches and their applications, and how they might be improved to better assist science, policy, and decision makers.

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Exploring Land-Livelihood Transitions

Figure5_rev (2)Rural livelihoods are changing rapidly with economic globalization and global environmental change, which have direct impacts to environmental and socio-economic suitability. All too often the most vulnerable communities – those with the least resources – face the greatest transitions triggered by changing local and global conditions. Those communities also have livelihoods tied to the land, which may lead to environmental degradation and/or fail to support livelihoods in the future. We must advance our understanding of the causes and consequences of land-livelihood transitions in order to avoid maladapted responses that can lead to a loss of land-livelihood sustainability.

My colleagues and I recently published an article in PLoS ONE that explores these issues with an innovative, generalized agent-based model. Because human decision-making drives land-livelihood transitions, a process-level explanation of adaptive responses is needed to explore the conditions under which land-livelihood transitions emerge. In the short-term, this approach advances the use of agent-based virtual laboratories in sustainability research. In coming generations of this modeling approach, we hope to use model insights to devise effective policy interventions aimed at the decision-making level for supporting sustainability .

Complexity in land-livelihood systems

China_FarmerRural livelihoods are inextricably linked to sustainable land-use, and vice versa.

This message seems to be popping-up continuously and forcefully in much of the research articles I’ve been reading lately. And I agree – certainly land-use lies at the heart of the sustainability question, since it is a means of food and income production as well as a main source of impacts to ecosystems. Something I read far less often (still looking if you have suggestions!) is a holistic framework for understanding the complex causes and consequences of land-use and livelihood changes.

The factors driving rural household land-use and livelihood decisions are incredibly complex –  originating and acting both locally and globally, and often creating both rapid and slow changes in incentives and constraints. For example, see this post about both fast and gradual changes occurring in Chinese food systems. Researchers, practitioners, and policy-makers alike are thus left with huge gaps in understanding of how land-use and livelihood changes come about, and you can forget about accurately predicting such changes and how they might influence environmental and/or livelihood sustainability.

Thinking about this challenge led me back to some of my earlier work in complex system science. In particular, I revisited one of my earlier papers about ‘induced coupling‘ – an idea that faster and slower processes sometimes become ‘coupled’ and lead to dramatic systemic changes. So I tried my hand at throwing together a simple version of what this might look like for a coupled land-livelihood system.HCSM_LLS

The red, downward arrows represent ‘entrainment’, or ‘slaving’, of the dynamics of lower-level variables by higher-level variables. The green, upward arrows represent processes of ‘self-organization’, or ‘revolt’, in which the dynamics of lower-level variables influence those of higher-level variables. Dashed arrows represent processes that link variables operating at the same time scales. If you would like to know more about this type of framework, referred to as hierarchical complex systems modeling, I will direct you to work by my friends and colleagues Brad Werner and Dylan McNamara (2007).

Now, the recognition that processes, or ‘drivers’, across multiple scales influence land-use and livelihood decisions is nothing new. However, rarely are temporal scales used as the organizing framework. This viewpoint has the potential to explain why certain drivers have different influences in different contexts due to the relative frequencies of interacting processes.

OK, great … so what? Beyond the potential to advance our fundamental understanding of the causes and consequences of livelihood and land-use changes, such a perspective could help craft policy interventions that address not only short-term needs of rural land-users, but also the effects of long-term challenges to sustainability and well-being.

As always, please feel free to yell at me on twitter @nickmags13 if you disagree, or if you prefer to disagree with me on a more regular basis don’t hesitate to follow this blog or subscribe to the RSS feed or email list. 😉

Homo economicus is (mostly) dead

Source: Economists.com/blogs/freeexchange.

Source: Economists.com/blogs/freeexchange.

Do I detect a change in the winds of mainstream economics?

A recent article in the Economist gives me hope. It suggests that ideas of non-rational, adaptive, and distributed decision-making – which have been topics of research in agent-based modeling, psychology, neuroscience, anthropology, and behavioral economics for some time – are now starting to seep into the consciousness of mainstream economics.

Describing Daniel McFadden’s recent work titled “The New Science of Pleasure“, the article details how concepts from psychology, such as prospect theory, are casting renewed doubt on the validity of mainstream economics’ hallmark theory of consumer choice. Indeed, mainstream economic theory has come under fire recently in the wake of economic recession stemming from “irrational” financial decisions, which many economists failed to predict or reconcile with their models and theories.

In all fairness, many mainstream economists would readily offer that their models are unrealistic in many ways, and are useful for understanding how economic systems tend towards rationale outcomes in the long-term. True enough. What this article argues, however, is that the assumptions that underlie mainstream economic models and theory can also lead to unrealistic worldviews and policy recommendations.  For example, ‘more choice is good’, but sometimes this can lead to sub-optimal (i.e. not rational) choices because the consumer is overwhelmed with options. From the article, “Explicitly modelling the process of making a choice might prompt economists to take a more ambiguous view of an abundance of choices.”

And this line of reasoning leads to agent-based modeling as a potential tool to understand how choices are made: what psychological elements influence decisions, how those psychological influence vary with individual heterogeneity characteristics, and how decisions are enacted into behavior.

A parting shot from the article: “This is undoubtedly messier than standard economics. So is real life.”

Agent-Based Models in the Real World

thought_process1A recently published News Feature in Proceedings of the National Academy of Sciences by Robert Frederick, titled Agents of Influence, discusses the advancing state of agent-based models (ABMs) and their growing use to inform business and policy decisions. Businesses are employing ABMs to find new efficiencies in complex supply chains, and research efforts to create million-agent models of the economy may soon offer insight into the dynamics of our financial systems and broader economy.

What I like most about this article is that it illustrates how ABMs and complexity thinking are beginning to make their way out of academics and into the real world. A recent example is how Southwest Airlines used ABMs to find more efficient cargo shipping routes, saving the airline millions of dollars. ABMs as virtual laboratories are getting attention, too. The article describes how these models enable decision-makers to explore the consequences of particular business or policy decisions though a range of possible scenarios.

The message is clear: representing heterogeneous, distributed decision-making creates more realistic models, and is enabling researchers, businesses, and policy-makers to navigate complex systems like never before.

Importantly, Frederick does not shy away from the limitations of such models. What is gained in realism by using ABMs often comes at the cost of having to make numerous simplifying assumptions about human behavior. After all, an ABM is only as good as its description of human decision-making processes, which are notoriously unpredictable.

A great closing quote: “Ultimately, … none of these [ABMs] will offer iron-clad predictions, because they have to make simplifying assumptions about human behavior. The true test will be whether those assumptions, and the resulting outputs of the models, convince policymakers to act on their advice.”

Linking management decisions and shoreline dynamics

OBX_erosion

Source: USGS

Shoreline communities along the U.S. Atlantic Coast have a long history of enduring costly and widespread impacts from tropical storms and long-term erosion. Unfortunately, such impacts are likely to worsen with sea-level rise in the future. These impacts are unavoidable – but how we respond to them is up to us. In their new article titled “A coupled physical and economic model of the response of coastal real estate to climate risk,” recently published in Nature Climate Change, Drs. Dylan McNamara and Andrew Keeler address just this aspect of long-term coastline change.

Using coupled agent-based and coastal processes models, they explore the mechanisms underlying shoreline defense decisions in response to long-term sea-level rise and erosion. Those decisions in turn are dependent on property values and individual beliefs of potential impacts. A particularly innovative feature of their model is that collective mitigation actions are determined endogenously through an iterative referendum. Collective action problems become apparent as believers and non-believers of climate risk predictions must decide on community-level adaptation strategies.

The authors find that property owners that disregard predictions of climate change-induced coastal risks tend to be the ones that own property in the riskiest locations, and thus disproportionately receive public disaster assistance funds. In addition, the model is also able to estimate time before abandonment of coastal communities subject to a combination of sea-level rise and erosion.

Many research efforts into climate change adaptation emphasize the physical impacts of climate related hazards. However, this is only one – and arguably the less important – aspect of climate change adaptation. The fate of human-environment systems is largely determined by our decisions of how to respond to changing economic and environmental conditions.

This model gets it right. Explicit consideration of human decision-making, and its underlying motivations, is essential if we are to form realistic expectations of likely future states and formulate successful adaptation strategies.

I look forward to seeing future contributions from these authors!

About the Agent-Based Virutal Labs (ABVLs) blog

Welcome to the Agent-Based Virtual Labs blog!Landscape_fig

This blog will cover issues relating broadly to the social, economic, and cultural interactions that are  changing the planet’s surface and climate. In particular, these issues will be explored with posts relating to agent-based modeling (ABM), and how ABMs can be used as virtual laboratories to ask questions about peoples’ motivations for observed behaviors that would be impossible to ask any other way. Along the way, topics informing the creation, use, and testing of ABMs will be included, as well as my areas of application of ABVLs such as land-use change, livelihoods in developing countries, and sustainability.

This blog will also be a hub of information for those interested in ABMs or my subject areas of interest. Following the navigation menu will lead you to collections of links for learning and teaching resources, other ABVLs-relevant blogs, and my research topics. Also, at regular intervals, posts will appear that contain an annotated list of links dedicated to topics ‘trending’ in the ABVLs world.

I hope you enjoy and please drop me a line!