For forest sustainability and vulnerability assessment, the landscape scale is considered to be more and more relevant as the stand level approaches its known limitations. This review, which describes the main forest landscape simulation tools used in the 20 European case studies of the European project "Future-oriented integrated management of European forest landscapes" (INTEGRAL), gives an update on existing decision support tools to run landscape simulation from Mediterranean to boreal ecosystems. The main growth models and software available in Europe are described, and the strengths and weaknesses of different approaches are discussed. Trades-offs between input efforts and output are illustrated. Recommendations for the selection of a forest landscape simulator are given. The paper concludes by describing the need to have tools that are able to cope with climate change and the need to build more robust indicators for assessment of forest landscape sustainability and vulnerability.

To anticipate European climate scenarios for the end of the century, we explored the climate gradient within the REINFFORCE (RÉseau INFrastructure de recherche pour le suivi et l’adaptation des FORêts au Changement climatiquE) arboreta network, established in 38 sites between latitudes 37° and 57°, where 33 tree species are represented. We aim to determine which climatic variables best explain their survival and growth, and identify those species that are more tolerant of climate variation and those of which the growth and survival future climate might constrain. We used empirical models to determine the best climatic predictor variables that explain tree survival and growth. Precipitation-transfer distance was most important for the survival of broadleaved species, whereas growing-season-degree days best explained conifer-tree survival. Growth (annual height increment) was mainly explained by a derived annual dryness index (ADI) for both conifers and broadleaved trees. Species that showed the greatest variation in survival and growth in response to climatic variation included Betula pendula Roth, Pinus elliottii Engelm., and Thuja plicata Donn ex D.Don, and those that were least affected included Quercus shumardii Buckland and Pinus nigra J.F.Arnold. We also demonstrated that provenance differences were significant for Pinus pinea L., Quercus robur L., and Ceratonia siliqua L. Here, we demonstrate the usefulness of infrastructures along a climatic gradient like REINFFORCE to determine major tendencies of tree species responding to climate changes.

In land surface models, vegetation is often described using plant functional types (PFTs), a classification that aggregates plant species into a few groups based on similar characteristics. Within-PFT variability of these characteristics can introduce considerable uncertainty in the simulation of water fluxes in forests. Our objectives were to (i) compare the variability of the annual maximum leaf area index (LAImax) within and between PFTs and (ii) assess whether this variability leads to significant differences in simulated water fluxes at a regional scale. We classified our study region in southwestern Quebec (Canada) into three PFTs (evergreen needleleaf, deciduous broadleaf, and mixed forests) and characterized LAImax using remotely sensed MODIS-LAI data. We simulated water fluxes with the Canadian Land Surface Scheme (CLASS) and performed a sensitivity analysis. We found that within-PFT variability of LAImax was 1.7 times more important than variability between PFTs, with similar mean values for the two dominant PFTs, deciduous broadleaf forests (6.6 m2·m−2) and mixed forests (6.3 m2·m−2). In CLASS, varying LAImax within the observed range of values (4.0–7.5 m2·m−2) led to changes of less than 2% in mean evapotranspiration. Overall, LAImax is likely not an important driver of the spatial variability of water fluxes at the regional level.

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