Category Archives: Land-Use Change

Motivations for and consequences of human use of land.

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: Additional report info can be found here as well: 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.

Global Agro-Climatic Zones

If you are interesting in global patterns of agricultural change, as I am, you might find this recently published paper helpful for selecting the most appropriate global framework.

van Wart, J., van Bussel, L. G., Wolf, J., Licker, R., Grassini, P., Nelson, A., Boogaarde, H., Gerberf, J.,  Muellerf, N. D., Claessensg, L.,
van Ittersum, M. K. & Cassman, K. G. (2013). Use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Research.

Available here.

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!

Used Planet: A Global History

Are we living in the Anthropocene? Published Monday in the Proceedings of the National Academy of Sciences, USA, Erle Ellis and colleagues paint a picture of historical land-use that significantly shaped the Earth’s surface more than 3000 years ago.

See a blog post or media coverage in the New Scientist for more details and to download the paper.

Notes from AAG 2013

AAG2013Last week I attended the 2013 annual meeting of the Association of American Geographers in Los Angeles, CA. In particular, I attended the Land Systems Science Symposium and the Agent-Based and Cellular Automata Model for Geographical Systems sessions. It was great to catch-up with old friends and meet a few new colleagues. Now that the chaos of coming back to work after a week off has passed, I thought this would be a good time to reflect on the happenings of the conference.

Overall, I thought this was a much stronger meeting than last year’s. It was apparent from the Land Systems Science (LSS) Symposium that the field formerly known as “Land Change Science” is beginning to come into its own. The full scope of LSS was on display, as the first two days were dedicated to case studies from different world regions, followed on the last two days by LSS modeling, theory, and applications. I was also impressed by the agent-based modeling (ABM) sessions this year. I sense a real transition in ABM research, as the presentations demonstrated much deeper thinking about the implications of model result, and model building as an art and tool for learning. There also seemed to be a sense that ABM is no longer on the fringe – it’s no longer a new method and the ABM community can now discuss the challenges and weaknesses of ABM more comfortably. It was a sure sign that the ABM method and paradigm are maturing.

Several themes in particular caught my attention over the course of the week:

1. YAAWN – Yet Another Agent-based model … Whatever … Nevermind.

That clever acronym came courtesy of the organizers of the panel on ABMs and land-use change modeling organized by David O’Sullivan and Tom Evans. The general motivation for the title was the observation that the number for place-based, case-specific ABMs has exploded, and as a research community, it is worth asking, “What is the marginal gain from one more case-study ABM?” I, of course, was thrilled to hear such a question, as the drive for more systematic, generalized knowledge motivates my use of agent-based virtual laboratories. The question was posed to the panel, and I particularly liked Dan Brown‘s response. The message was that there will always be a role for case-study ABMs, but it is also necessary to balance the use of empirically detailed models with more abstracted models to build theory. This sentiment was reinforced by Sarah Metcalf, who argued that model hybridity was the next wave of ABM research.

2. Attempts to forge systematic ABM practice and knowledge.

Going along with the general observation of higher quality presentations, the thinking about ABM practice was notably deeper this year. I particularly enjoyed David O’Sullivan‘s presentation of creating a ‘pattern language’ for ABMs and cellular automata. The general idea is to create ‘building block’ models out of generalized processes/structures that facilitate the development of more complicated models. I found this idea analogous to Len Troncale‘s work with isomorphies and systems of systems processes theory. Another important question posed by James Millington was, “When should we use ABMs and how complex do they need to be?” Indeed, this is a fundamental question that should be revisited often.

3. Understanding model outcomes and variability.

Finally, another sign that the ABM field is maturing, there was much discussion about the importance of more thoroughly understanding uncertainty and variability in our models. Chris Bone presented an innovative temporal variant/invariant method for evaluating model performance, which shows much promise for deepening our understanding of the sources of variability within complex systems models.

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.


Food Systems in China


In honor of Chinese New Year this weekend, this post features an excellent video from The Perennial Plate that highlights two of my favorite things about China: the countryside and food. When you watch the video, you will see linkages between the Chinese passion for food, a rapidly changing agricultural economy, and underlying cultural stigmas associated with agricultural livelihoods. Interactions between these various elements are having profound impacts on rural livelihoods and land-use in the rapidly changing Chinese economy and culture.

A characteristic pattern of the new China, which struck me during my travels in the countryside and is apparent in this video as well, is the demographic disparity as one travels outside the cities. Older generations remain on the farm, work the land, and care for the young children, while many young adults travel to nearby cities in pursuit of higher wages. Such demographic patterns are reinforced by a long-held stigma against agricultural livelihoods and their association with a peasant’s social status.

Given my interest in sustainable agricultural practices and livelihoods, this video resonated with me personally, as well as reminding me of parallels with the many urban agriculture movements that have become so prevalent around the U.S. This story demonstrates the kind of new cultural and social linkages between urban and rural livelihoods that can be created in China as an adaptation (and perhaps reaction) to an increasingly urban and market-driven economy and society.

Tying into the themes of this blog – agent-based modeling and land-use change – the story told in this video is a reminder of the importance of the cultural and social contexts in which land-use and livelihood decisions are made. In particular, this is a vivid example of how cultural and socio-economic forces can create emergent urban-rural teleconnections that lead to new land-uses and livelihood strategies.

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.