Exploring subtle land use and land cover changes: a framework for future landscape studies

UMR AMAP, équipe 3International audienceLand cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling

A Holistic Landscape Description Reveals That Landscape Configuration Changes More over Time than Composition: Implications for Landscape Ecology Studies

International audienceBackground: Space-for-time substitution—that is, the assumption that spatial variations of a system can explain and predict the effect of temporal variations—is widely used in ecology. However, it is questionable whether it can validly be used to explain changes in biodiversity over time in response to land-cover changes.Hypothesis: ere, we hypothesize that different temporal vs spatial trajectories of landscape composition and configuration may limit space-for-time substitution in landscape ecology. Land-cover conversion changes not just the surface areas given over to particular types of land cover, but also affects isolation, patch size and heterogeneity. This means that a small change in land cover over time may have only minor repercussions on landscape composition but potentially major consequences for landscape configuration.Methods: sing land-cover maps of the Paris region for 1982 and 2003, we made a holistic description of the landscape disentangling landscape composition from configuration. After controlling for spatial variations, we analyzed and compared the amplitudes of changes in landscape composition and configuration over time.Results: For comparable spatial variations, landscape configuration varied more than twice as much as composition over time. Temporal changes in composition and configuration were not always spatially matched.Significance: The fact that landscape composition and configuration do not vary equally in space and time calls into question the use of space-for-time substitution in landscape ecology studies. The instability of landscapes over time appears to be attributable to configurational changes in the main. This may go some way to explaining why the landscape variables that account for changes over time in biodiversity are not the same ones that account for the spatial distribution of biodiversity

Evaluating the spatial uncertainty of future land abandonment in a mountain valley (Vicdessos, Pyrenees-France) : insights form model parameterization and experiments

International audienceEuropean mountains are particularly sensitive to climatic disruptions and land use changes. The latter leads to high rates of natural reforestation over the last 50 years. Faced with the challenge of predicting possible impacts on ecosystem services, LUCC models offer new opportunities for land managers to adapt or mitigate their strategies. Assessing the spatial uncertainty of future LUCC is crucial for the defintion of sustainable land use strategies. However, the sources of uncertainty may differ, including the input parameters, the model itself, and the wide range of possible futures. The aim of this paper is to propose a method to assess the probability of occurrence of future LUCC that combines the inherent uncertainty of model parameterization and the ensemble uncertainty of the future based scenarios. For this purpose, we used the Land Change Modeler tool to simulate future LUCC on a study site located in the Pyrenees Mountains (France) and 2 scenarios illustratins 2 land use strategies. The model was parameterized with the same driving factors used for its calibration. The defintion of static vs. dynamic and quantitative vs. qualitative (discretized) driving factors, and their combination resulted in 4 parameterizations. The combination of model outcomes produced maps of spatial uncertainty of future LUCC. This work involves literature to future-based LUCC studies. It goes beyond the uncertainty of simulation models by integrating the unceertainty of the future to provide maps to help decision makers and land managers

Monitoring and modelling landscape dynamics

International audienceChanges in land cover and land use are among the most pervasive and important sources of recent alterations of the Earth's land surface.This special issue also presents new directions in modelling landscape dynamics. Agent-based models have primarily been used to simulate local land use and land cover changes processes with a focus on decision making (Le 2008; Matthews et al. 2007; Parker et al. 2003; Bousquet and Le Page 2001)

From meta-studies to modeling: Using synthesis knowledge to build broadly applicable process-based land change models

International audienceThis paper explores how meta-studies can support the development of process-based land change models (LCMs) that can be applied across locations and scales. We describe a multi-step framework for model development and provide descriptions and examples of how meta-studies can be used in each step. We conclude that meta-studies best support the conceptualization and experimentation phases of the model development cycle, but cannot typically provide full model parameterizations. Moreover, meta-studies are particularly useful for developing agent-based LCMs that can be applied across a wide range of contexts, locations, and/or scales, because meta-studies provide both quantitative and qualitativedata needed to derive agent behaviors more readily than from case study or aggregate data sources alone. Recent land change synthesis studies provide sufficient topical breadth and depth to support the development of broadly applicable process-based LCMs, as well as the potential to accelerate the production of generalized knowledge through model-driven synthesis

Xerophthalmia in infants and liver failure

peer reviewe

Xerophthalmia in infants and liver failure

editorial reviewe

DOI: 10.1007/s10980-009-9417-x Monitoring and modelling landscape dynamics

Manuscript word count (including text, references, tables, and captions): 3033 word