Eric F. Lambin

A safe operating space for humanity

Identifying and quantifying planetary boundaries that must not be transgressed could help prevent human activities from causing unacceptable environmental change, argue Johan Rockstrom and colleagues.

The causes of land-use and land-cover change: moving beyond the myths

Common understanding of the causes of land-use and land-cover change is dominated by simplifications which, in turn, underlie many environment-development policies. This article tracks some of the major myths on driving forces of land-cover change and proposes alternative pathways of change that are better supported by case study evidence. Cases reviewed support the conclusion that neither population nor poverty alone constitute the sole and major underlying causes of land-cover change worldwide. Rather, peoples’ responses to economic opportunities, as mediated by institutional factors, drive land-cover changes. Opportunities and

Proximate Causes and Underlying Driving Forces of Tropical Deforestation

Articles O ne of the primary causes of global environmental change is tropical deforestation, but the question of what factors drive deforestation remains largely unanswered (NRC 1999). Various hypotheses have produced rich arguments , but empirical evidence on the causes of deforestation continues to be largely based on cross-national statistical In some cases, these analyses are based on debatable data on rates of forest cover change (Palo 1999). The two major, mutually exclusive—and still unsatisfactory—explanations for tropical deforestation are single-factor causation and irre-ducible complexity. On the one hand, proponents of single-factor causation suggest various primary causes, such as shift-On the other hand, correlations between deforestation and multiple causative factors are many and varied , revealing no distinct pattern In addition to chronicling these attempts to identify general causes of deforestation through global-scale statistical analyses, the literature is rich in local-scale case studies investigating the causes and processes of forest cover change in specific localities. Our aim with this study is to generate from local-scale case studies a general understanding of the prox-imate causes and underlying driving forces of tropical deforestation while preserving the descriptive richness of these studies. Proximate causes are human activities or immediate actions at the local level, such as agricultural expansion, that originate from intended land use and directly impact forest cover. Underlying driving forces are fundamental social processes, such as human population dynamics or agricultural policies, that underpin the proximate causes and either operate at the local level or have an indirect impact from the national or global level. We analyzed the frequency of proximate causes and underlying driving forces of deforestation, including their interactions , as reported in 152 subnational case studies. We show that tropical deforestation is driven by identifiable regional patterns of causal factor synergies, of which the most prominent are economic factors, institutions, national policies, and remote influences (at the underlying level) driving agricultural expansion, wood extraction, and infrastructure extension (at the proximate level). Our findings reveal that prior stud-Helmut Geist (e-mail: geist@geog.ucl.ac.be) is a postdoctoral researcher (geography) in the field of human drivers of global environmental change and executive director of the Land Use and Cover Change (LUCC) core project of the International Geosphere-Biosphere Eric Lambin is a professor of geography with research interests in remote sensing and human ecology applied to studies of deforestation, desertification, and bio-mass burning in tropical regions. He is the chair of the IGBP and IHDP …

Digital change detection methods in ecosystem monitoring: a review

Techniques based on multi-temporal, multi-spectral, satellite-sensor-acquired data have demonstrated potential as a means to detect, identify, map and monitor ecosystem changes, irrespective of their causal agents. This review paper, which summarizes the methods and the results of digital change detection in the optical/infrared domain, has as its primary objective a synthesis of the state of the art today. It approaches digital change detection from three angles. First, the different perspectives from which the variability in ecosystems and the change events have been dealt with are summarized. Change detection between pairs of images (bi-temporal) as well as between time profiles of imagery derived indicators (temporal trajectories), and, where relevant, the appropriate choices for digital imagery acquisition timing and change interval length definition, are discussed. Second, pre-processing routines either to establish a more direct linkage between remote sensing data and biophysical phenomena, or to temporally mosaic imagery and extract time profiles, are reviewed. Third, the actual change detection methods themselves are categorized in an analytical framework and critically evaluated. Ultimately, the paper highlights how some of these methodological aspects are being fine-tuned as this review is being written, and we summarize the new developments that can be expected in the near future. The review highlights the high complementarity between different change detection methods.

Global land use change, economic globalization, and the looming land scarcity

A central challenge for sustainability is how to preserve forest ecosystems and the services that they provide us while enhancing food production. This challenge for developing countries confronts the force of economic globalization, which seeks cropland that is shrinking in availability and triggers deforestation. Four mechanisms—the displacement, rebound, cascade, and remittance effects—that are amplified by economic globalization accelerate land conversion. A few developing countries have managed a land use transition over the recent decades that simultaneously increased their forest cover and agricultural production. These countries have relied on various mixes of agricultural intensification, land use zoning, forest protection, increased reliance on imported food and wood products, the creation of off-farm jobs, foreign capital investments, and remittances. Sound policies and innovations can therefore reconcile forest preservation with food production. Globalization can be harnessed to increase land use efficiency rather than leading to uncontrolled land use expansion. To do so, land systems should be understood and modeled as open systems with large flows of goods, people, and capital that connect local land use with global-scale factors.

The emergence of land change science for global environmental change and sustainability

Land change science has emerged as a fundamental component of global environmental change and sustainability research. This interdisciplinary field seeks to understand the dynamics of land cover and land use as a coupled human–environment system to address theory, concepts, models, and applications relevant to environmental and societal problems, including the intersection of the two. The major components and advances in land change are addressed: observation and monitoring; understanding the coupled system—causes, impacts, and consequences; modeling; and synthesis issues. The six articles of the special feature are introduced and situated within these components of study.

Predicting land-use change

Land use change modelling, especially if done in a spatially-explicit, integrated and multi-scale manner, is an important technique for the projection of alternative pathways into the future, for conducting experiments that test our understanding of key processes in land use changes. Land-use change models should represent part of the complexity of land use systems. They offer the possibility to test the sensitivity of land use patterns to changes in selected variables. They also allow testing of the stability of linked social and ecological systems, through scenario building. To assess current progress in this field, a workshop on spatially explicit land-use/land-cover models was organised within the scope of the Land-Use and Land Cover Change project (LUCC). The main developments presented in this special issue concern progress in: 1) Modelling of drivers of land-use change; 2) modelling of scale dependency of drivers of land use change; 3) modelling progress in predicting location versus quantity of land-use change; 4) the incorporation of biophysical feedbacks in land-use change models.

Are agricultural land-use models able to predict changes in land-use intensity?

Land-use and land-cover change research needs to pay more attention to processes of land-cover modification, and especially to agricultural land intensification. The objective of this paper is to review the different modelling approaches that have been used in land-use/land-cover change research from the perspective of their utility for the study and prediction of changes in land-use intensification. After clarifying the main concepts used, the different modelling approaches that have been used to study land-use change are examined, case study evidence on processes and drivers of land-use intensification are discussed, and a conclusion is provided on the present ability to predict changes in land-use intensity. The analysis suggests there are differences in the capability of different modelling approaches to assess changing levels of intensification: dynamic, process-based simulation models appear to be better suited to predict changes in land-use intensity than empirical, stochastic or static optimisation models. However, some stochastic and optimisation methods may be useful in describing the decision-making processes that drive land management. Case study evidence highlight the uncertainties and surprises inherent in the processes of land-use intensification. This can both inform model development and reveal a wider range of possible futures than is evident from modelling alone. Case studies also highlight the importance of decision-making by land managers when facing a range of response options. Thus, the ability to model decision-making processes is probably more important in land-use intensification studies then the broad category of model used. For this reason, landscape change models operating at an aggregated level have not been used to predict intensification. In the future, an integrated approach to modelling - that is multidisciplinary and cross-sectoral combining elements of different modelling techniques - will probably best serve the objective of improving understanding of land-use change processes including intensification. This is because intensification is a function of the management of physical resources, within the context of the prevailing social and economic drivers. Some of the factors that should be considered when developing future land-use change models are: the geographic and socio-economic context of a particular study, the spatial scale and its influence on the modelling approach, temporal issues such as dynamic versus equilibrium models, thresholds and surprises associated with rapid changes, and system feedbacks. In industrialised regions, predicting land-use intensification requires a better handling of the links between the agriculture and forestry sectors to the energy sector, of technological innovation, and of the impact of agri-environment policies. For developing countries, better representation of urbanisation and its various impacts on land-use changes at rural-urban interfaces, of transport infrastructure and market change will be required. Given the impossibility of specific predictions of these driving forces, most of the modelling work will be aimed at scenario analysis

Land-Cover-Change Trajectories in Southern Cameroon

The objective of this study is to better understand the complexity of deforestation processes in southern Cameroon by testing a multivariate, spatial model of land-cover change trajectories associated with deforestation. The spatial model integrates a spectrum of independent variables that characterize land rent on a spatially explicit basis. The use of a time series of high-spatial-resolution remote sensing images (Landsat MSS and SPOT XS), spanning two decades, allows a thorough validation of spatial projections of future deforestation. Remote sensing observations reveal a continuous trend of forest clearing and forest degradation in southern regions of Cameroon, but with a highly fluctuating rate. A significant proportion of the areas subject to a land-cover conversion experienced other changes in the following years. The study also demonstrates that modeling land-cover change trajectories over several observation years allows a better projection of areas with a high probability of change in land-cover than projecting such areas on the basis of observations from the previous time period alone. Statistical results suggest that, in our southern Cameroon study area, roads mostly increased the accessibility of the forest for migrants rather than providing incentives for a transformation of local subsistence agriculture into market-oriented farming systems. The spatial model developed in this study allows simulations of likely impacts of human actions, leading to a transformation of the landscape (e.g., road projects) on key landscape attributes (e.g., biodiversity). Currently, several road projects or major logging concessions exist in southern Cameroon.

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.