Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.
Information on the spatial distribution of past vegetation on local, regional and global scales is increasingly used within climate modelling, nature conservancy and archaeology. It is possible to obtain such information from fossil pollen records in lakes and bogs using the landscape reconstruction algorithm (LRA) and its two models, REVEALS and LOVE. These models assume that reliable pollen productivity estimates (PPEs) are available for the plant taxa involved in the quantitative reconstructions of past vegetation, and that PPEs are constant through time. This paper presents and discusses the PPEs for 15 tree and 18 herb taxa obtained in nine study areas of Europe. Observed differences in PPEs between regions may be explained by methodological issues and environmental variables, of which climate and related factors such as reproduction strategies and growth forms appear to be the most important. An evaluation of the PPEs at hand so far suggests that they can be used in modelling applications and quantitative reconstructions of past
We present the first step to quantitatively reconstruct vegetation cover in central Europe. Modern vegetation and pollen deposition were compared for 20 small to medium sized lakes and their catchments on the Swiss Plateau, a relatively flat region between the Jura Mountains and the Alps. To correct for the pollen dispersal bias in pollen assemblages, vegetation abundance was distance-weighted using three different approaches. The Relevant Source Area of Pollen (RSAP) and pollen productivity of 13 plant taxa were estimated using three different submodels of the Extended R-Value model (ERV-model). RSAP was 800 m regardless of the applied distance-weighting or ERV submodel. Pollen Productivity Estimates (PPE) varied from 10 to < 0.1 among pollen taxa and differed slightly between the models. Relative to grasses most trees were higher pollen producers and some were equal producers, whereas the herb taxa showed lower PPE. Generally, PPE from lowland Switzerland differ from those found in other European regions. Sampling strategies of vegetation and pollen samples are a likely cause for this variation. However, pollen productivity is also influenced by regionally different factors, such as climate, vegetation structure, geology and soil types. In addition, differences at genus or species level may occur between areas. Our comparison between the different regions in Europe shows that PPE of one region may not be directly applicable to other regions.
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