Category Archives: Sustainability

Human dimensions of environmental, economic, and social sustainability.

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. 😉

ABM and GLOBE Project Sessions at the Global Land Project’s 2014 Open Science Meeting

GLP_OSM2014The Global Land Project will hold its second Open Science Meeting (OSM) in Berlin from March 19-21, 2014. This will be a unique opportunity to hear about cutting-edge land and global environmental change research. A list of sessions was recently released here – check it out and see if anything peaks your interest. In particular, I will be co-chairing three sessions related to ABMs, synthesis, and/or GLOBE:

1. Research Session 0126: “Bridging local to global land change studies with the GLOBE online tool” (co-chaired with Erle Ellis)

2. World Cafe Workshop 0075: “From meta-analysis to modeling: understanding local land change globally” (co-chaired with Jasper van Vliet)

3. Short Training Session 0125: “The GLOBE project: evolving new global workflows for land change science” (co-chaired with Erle Ellis and the GLOBE Team)

I attended the first OSM in 2010 (wow, that long ago?!) held at Arizona State University, and it was a great meeting. Session content was exceptional and the meeting was not too big. I highly recommend getting to Berlin next year if you can!

Linking management decisions and shoreline dynamics


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!

Human decision-making in climate system models

GLP_reportOn November 28th, 2011, a workshop in Lake Crackenback, Australia was organized by Prof. Mark Rounsevell, CECS, University of Edinburgh, UK and sponsored by the Global Land Project (GLP) and Australia’s CSIRO. The aim of the workshop was to explore theoretical and modeling approaches for incorporating human decision-making into large-scale climate system models. This theme arose from the recognition that the cumulative effects of local land-use change contribute significantly to global environmental change, and land-use is the result of adaptive decision-making of land-users. In order to understand the linkages between climate systems and land-use, we must integrate decision-level, process-based models (for example, agent-based models) with large-scale climate models.

The perspectives, ideas, and contributions of workshop participants have been synthesized and released as a report from the GLP. A collaborative effort between regional and global climate modelers, land change scientists, and agent-based modelers, this report describes methods for up-scaling local land system models for integration with large-scale climate models.

Although there is much room for improvement in both climate system and agent-based modeling, the integration of these approaches is an important next step for creating realistic climate change scenarios that account for the adaptive responses of land-users.

New Paper: Pattern-Oriented Modeling in Multi-Scale ABMs of Land Change

TGIS_screen_captureA particular challenge of investigating the causes of land-use change is the multi-scale nature of factors that influence land-use decisions. In an increasingly globalized world, land-use choices and livelihood strategies are linked to local AND regional to global forces. But attempts to incorporate such multi-scale causation in land change models often run into significant knowledge and data gaps – especially when trying to link incomplete and/or low quality global data to individual agents’ decision-making processes.

Figure4_mainOne way forward, which my co-author Dr. Erle Ellis and I present in this new open-access article in Transactions in GIS, is to use pattern-oriented modeling (Grimm et al., 2005) within an agent-based virtual laboratory to experimentally bound the possible values of uncertain parameters. By targeting characteristic patterns tied to important individual- and landscape-level processes – the selection of which are informed by theory, data, or both – ABMs can be designed and tested to be more realistic despite data limitations. We propose that this experimental method can help overcome significant data gaps, and help land change scientists begin to quantify some global trends in local land change processes.

Comments welcome!


Local land-use and -cover changes (LUCCs) are the result of both the decisions and actions of individual land-users, and the larger global and regional economic, political, cultural, and environmental contexts in which land-use systems are embedded. However, the dearth of detailed empirical data and knowledge of the influences of global/regional forces on local land-use decisions is a substantial challenge to formulating multi-scale agent-based models (ABMs) of land change. Pattern-oriented modeling (POM) is a means to cope with such process and parameter uncertainty, and to design process-based land change models despite a lack of detailed process knowledge or empirical data. POM was applied to a simplified agent-based model of LUCC to design and test model relationships linking global market influence to agents’ land-use decisions within an example test site. Results demonstrated that evaluating alternative model parameterizations based on their ability to simultaneously reproduce target patterns led to more realistic land-use outcomes. This framework is promising as an agent-based virtual laboratory to test hypotheses of how and under what conditions driving forces of land change differ from a generalized model representation depending on the particular land-use system and location.

Friday Features

Welcome to Friday Features! Or something like that … name to be determined. Regardless of the name, here’s the deal: A couple times a month I will post a series of links – a sort of what’s “trending” in the world of agent-based modeling (ABM), land change science, and/or sustainability science. So, without further ado ….

Thought-provoking …

  • A Wired Science post about the legacy of medieval agricultural land-use patterns. An excellent example of how economic rationale manifests itself as striking land-use patterns. Source: Wired Science, Tim De Chant.
  • Another Wired Science post about land-use patterns. Clear evidence Brasíliafor the importance of institutions in shaping land-use patterns and the need to better model institutional agents – a common problem in the ABM world. Source: Wired Science, Betsy Mason.

Interesting academic articles …