Peter H. Verburg

Framing Sustainability in a Telecoupled World

Interactions between distant places are increasingly widespread and influential, often leading to unexpected outcomes with profound implications for sustainability. Numerous sustainability studies have been conducted within a particular place with little attention to the impacts of distant interactions on sustainability in multiple places. Although distant forces have been studied, they are usually treated as exogenous variables and feedbacks have rarely been considered. To understand and integrate various distant interactions better, we propose an integrated framework based on telecoupling, an umbrella concept that refers to socioeconomic and environmental interactions over distances. The concept of telecoupling is a logical extension of research on coupled human and natural systems, in which interactions occur within particular geographic locations. The telecoupling framework contains five major interrelated components, i.e., coupled human and natural systems, flows, agents, causes, and effects. We illustrate the framework using two examples of distant interactions associated with trade of agricultural commodities and invasive species, highlight the implications of the framework, and discuss research needs and approaches to move research on telecouplings forward. The framework can help to analyze system components and their interrelationships, identify research gaps, detect hidden costs and untapped benefits, provide a useful means to incorporate feedbacks as well as trade-offs and synergies across multiple systems (sending, receiving, and spillover systems), and improve the understanding of distant interactions and the effectiveness of policies for socioeconomic and environmental sustainability from local to global levels.

Combining top-down and bottom-up dynamics in land use modeling: exploring the future of abandoned farmlands in Europe with the Dyna-CLUE model

Land use change is the result of interactions between processes operating at different scales. Simulation models at regional to global scales are often incapable of including locally determined processes of land use change. This paper introduces a modeling approach that integrates demand-driven changes in land area with locally determined conversion processes. The model is illustrated with an application for European land use. Interactions between changing demands for agricultural land and vegetation processes leading to the re-growth of (semi-) natural vegetation on abandoned farmland are explicitly addressed. Succession of natural vegetation is simulated based on the spatial variation in biophysical and management related conditions, while the dynamics of the agricultural area are determined by a global multi-sector model. The results allow an exploration of the future dynamics of European land use and landscapes. The model approach is similarly suitable for other regions and processes where large scale processes interact with local dynamics.

Used planet: A global history

Human use of land has transformed ecosystem pattern and process across most of the terrestrial biosphere, a global change often described as historically recent and potentially catastrophic for both humanity and the biosphere. Interdisciplinary paleoecological, archaeological, and historical studies challenge this view, indicating that land use has been extensive and sustained for millennia in some regions and that recent trends may represent as much a recovery as an acceleration. Here we synthesize recent scientific evidence and theory on the emergence, history, and future of land use as a process transforming the Earth System and use this to explain why relatively small human populations likely caused widespread and profound ecological changes more than 3,000 y ago, whereas the largest and wealthiest human populations in history are using less arable land per person every decade. Contrasting two spatially explicit global reconstructions of land-use history shows that reconstructions incorporating adaptive changes in land-use systems over time, including land-use intensification, offer a more spatially detailed and plausible assessment of our planets history, with a biosphere and perhaps even climate long ago affected by humans. Although land-use processes are now shifting rapidly from historical patterns in both type and scale, integrative global land-use models that incorporate dynamic adaptations in human–environment relationships help to advance our understanding of both past and future land-use changes, including their sustainability and potential global effects.

From land cover change to land function dynamics: A major challenge to improve land characterization

Land cover change has always had a central role in land change science. This central role is largely the result of the possibilities to map and characterize land cover based on observations and remote sensing. This paper argues that more attention should be given to land use and land functions and linkages between these. Consideration of land functions that provide a wide range of goods and services makes more integrated assessments of land change possible. The increasing attention to multifunctional land use is another incentive to develop methods to assess changes in land functions. A number of methods to quantify and map the spatial extent of land use and land functions are discussed and the implications for modeling are identified based on recent model approaches in land change science. The mixed use of land cover, land use and land function in maps and models leads to inconsistencies in land change assessments. Explicit attention to the non-linear relations between land cover, land use and land function is essential to consistently address land change. New methods to map and quantify land function dynamics will enhance our ability to understand and model land system change and adequately inform policies and planning.

A spatial explicit allocation procedure for modelling the pattern of land use change based upon actual land use

Modelling of land use changes as a function of its biophysical and socio-economic driving forces provides insights into the extent and location of land use changes and its effects. The CLUE modelling framework is a methodology to model near future land use changes based upon actual and past land use conditions. This paper describes how changes in land use are allocated in the model. A statistical analysis of the quantitative relationships between the actual land use distribution and (potential) driving forces or proxies of these forces underlies the allocation procedure. Based upon thus derived multiple regression equations, areas with potential for increase or decrease in cover percentage of a certain land use type are identified. Actual allocation is modified by autonomous developments and competition between land use types. A multi-scale approach is followed to account for the scale dependencies of driving factors of land use change. This approach provides a balance between bottom-up effects as result of local conditions and top-down effects as result of changes at national and regional scales. The modelling approach is illustrated with examples of scenario simulations of land use change in Ecuador.

Determinants of Land-Use Change Patterns in the Netherlands

Land-use-change patterns are the result of the complex interaction between the human and the physical environment. Case studies of the determinants of land-use change can help to analyse which theory is appropriate in a particular region and stimulate the development of new theoretic understandings. In this paper an empirical method is presented to analyse the pattern of land-use change that allows a wide range of factors, from different disciplines, to contribute to the explanation of land-use change. The method is applied to the Netherlands, based on an extensive database of land-use change and its potential determinants. Historic as well as recent land-use changes are studied. Historic land-use change is related mainly to the variation in the biophysical environment. Levels of explanation are low because of the inability to address the temporal variation in location factors. For the recent changes in land use high levels of explanation are obtained. The most important changes during this period are expansions of residential, industrial/commercial, and recreational areas. The location of these changes can be explained by a combination of accessibility measures, spatial policies, and neighbourhood interactions. On the basis of these results it is possible to define priority topics for in-depth analysis of land-use-change processes and suggest factors, relations, and processes that need to be included in dynamic land-use-change models that support land-use-planning policies.

A method to analyse neighbourhood characteristics of land use patterns

Abstract Neighbourhood interactions between land use types are often included in the spatially explicit analysis of land use change. Especially in the context of urban growth, neighbourhood interactions are often addressed both in theories for urban development and in dynamic models of (urban) land use change. Neighbourhood interactions are one of the main driving factors in a large group of land use change models based on cellular automata (CA). This paper introduces a method to analyse the neighbourhood characteristics of land use. For every location in a rectangular grid the enrichment of the neighbourhood by specific land use types is studied. An application of the method for the Netherlands indicates that different land use types have clearly distinct neighbourhood characteristics. Land use conversions can be explained, for a large part, by the occurrence of land uses in the neighbourhood. The neighbourhood characterization introduced in this paper can help to further unravel the processes of land use change allocation and assist in the definition of transition rules for cellular automata and other land use change models.

Simulating feedbacks in land use and land cover change models

In spite of the many advances in land use and land cover change modelling over the past decade many challenges remain. One of these challenges relates to the explicit treatment of feedback mechanisms in descriptive models of the land use system. This paper argues for model-based analysis to explore the role of feedback mechanisms as determinants of land use dynamics and system evolution. Different types of feedbacks in the land use system are discussed addressing interactions over scales of analysis, feedbacks between impacts and driving forces of land use change and feedbacks between agents and land units. The inclusion of feedbacks in land use models will require new methods for model parameterization and calibration, but will ultimately increase our understanding of land use system dynamics.

Trajectories of land use change in Europe: a model-based exploration of rural futures

Land use change is characterized by a high diversity of change trajectories depending on the local conditions, regional context and external influences. Policy intervention aims to counteract the negative consequences of these changes and provide incentives for positive developments. Region typologies are a common tool to cluster regions with similar characteristics and possibly similar policy needs. This paper provides a typology of land use change in Europe at a high spatial resolution based on a series of different scenarios of land use change for the period 2000–2030. A series of simulation models ranging from the global to the landscape level are used to translate scenario conditions in terms of demographic, economic and policy change into changes in European land use pattern. A typology developed based on these simulation results identifies the main trajectories of change across Europe: agricultural abandonment, agricultural expansion and urbanization. The results are combined with common typologies of landscape and rurality. The findings indicate that the typologies based on current landscape and ruralities are poor indicators of the land use dynamics simulated for the regions. It is advocated that typologies based on (simulated) future dynamics of land change are more appropriate to identify regions with potentially similar policy needs.

Land use change under conditions of high population pressure: the case of Java

A long history of increases in population pressure in Java has caused agricultural land use to expand and intensify. More recent land use changes caused the conversion of prime agricultural land into residential and industrial area. Results of a dynamic, regional-scale, land use change model are presented, defining the spatial distribution of these land use changes. The model is based on multi-scale modelling of the relations between land use and socio-economic and biophysical determinants. Historical validation showed that the model can adequately simulate the pattern of land use change. Future patterns of land use change between 1994 and 2010 are simulated assuming further urbanization. The results suggest that most intensive land use changes will occur in Javas lowland areas.