GIS modeling of submerged macrophyte distribution using Generalized Additive Models

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Abstract

The distribution of submerged macrophytes in the littoral zone of Lake Geneva (Switzerland) was modeled from bathymetry, wave exposure, current strength, water quality, soil type and harvesting practice. Generalized Additive Models (GAM) were used to identify the responses of three Potamogeton species and Chara sp. to these environmental parameters. The maps of original data and the spatial predictions were processed in a Geographic Information System (GIS) database. The effect of the selected environmental variables on plant distribution is discussed in relation to species adaptive strategies. GIS and GAM appear as powerful tools to proceed from the description of species response curves to environmental gradients toward the spatial predictions of species distribution under changing environmental conditions.

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