Imaging spectroscopy as a tool for mapping Ellenberg indicator values.

Published online
02 Nov 2005
Content type
Journal article
Journal title
Journal of Applied Ecology
DOI
10.1111/j.1365-2664.2005.01064.x

Author(s)
Schmidtlein, S.
Contact email(s)
sebastian.schmidtlein@uni-bayreuth.de

Publication language
English
Location
Austria & Europe

Abstract

Maps of averaged plant indicator values can supply spatially explicit information about environmental gradients and are therefore tools of broad relevance in applied ecology. However, field-based mapping demands extensive sampling and thus most assessments are at the level of plots rather than covering a whole area. To address these limitations, this study evaluated the potential of remote sensing to produce Ellenberg indicator maps. The area investigated was situated in the Berchtesgaden National Park, a part of the northern Alps near Salzburg, Austria. It is a montane pasture at an altitude of 1300-1650 m asl. Ellenberg indicator values for water supply, soil pH and soil fertility were derived using species data from vegetation plots in montane rangeland. The extrapolation of these data was accomplished by partial least-squares (PLS) regression between indicator values and plot reflectance values extracted from airborne 'hyperspectral' imagery. Applying the regression to the imagery resulted in three largely accurate maps giving the spatial distribution of certain soil attributes as indicated by Ellenberg values (R2=0.58-0.68 in cross-validation). Mean indicator values express floristic composition as a single, comparable, continuous and mappable variable. This makes them an appealing tool for vegetation monitoring. Imaging spectroscopy provides fast access to spatially contiguous and explicit information about soil conditions as indicated by plants. The technique allows the investigation to advance beyond plots and supplies indicator maps at a stand-level resolution. The mapped gradients of environmental attributes are of direct relevance to plant growth. The maps depict life-span growth conditions rather than 'snap-shots' given by measurements that are often limited in space and time, cost intensive and difficult to implement.

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