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Traditional approaches to ecological land classification (ELC) can be enhanced by integrating, a priori, data describing disturbances (natural and human), in addition to the usual vegetation, climate, and physical environment data. To develop this new ELC model, we studied an area of about 175,000� km² in the Abies balsamea–Betula papyrifera and Picea mariana-feathermoss bioclimatic domains of the boreal forest of Québec, in eastern Canada. Forest inventory plots and maps produced by the Ministère des Ressources naturelles du Québec from 1970 to 2000 were used to characterize 606 ecological districts (average area 200� km²) according to three vegetation themes (tree species, forest types, and potential vegetation-successional stages) and four sets of explanatory variables (climate, physical environment, natural and human disturbances). Redundancy, cluster (K-means) and variation partitioning analyses were used to delineate, describe, and compare homogeneous vegetation landscapes. The resulting ELC is hierarchical with three levels of observation. Among the 14 homogeneous landscapes composing the most detailed level, some are dominated by relatively young forests originating from fires dating back to the period centered on 1921. In others, forest stands are older (fires from the period centered on 1851), some are under the influence of insect outbreaks and fires (southern part), while the rest are strongly affected by human activities and Populus tremuloides expansion. For all the study area and for parts of it, partitioning reveals that natural disturbance is the dominant data set explaining spatial variation in vegetation. However, the combination of natural disturbances, climate, physical environment and human disturbances always explains a high proportion of variation. Our approach, called “ecological land classification of homogeneous vegetation landscapes”, is more comprehensive than previous ELCs in that it combines the concepts and goals of both landscape ecology and ecosystem-based management.
