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Quantifying the spatial impact of exotic plant invasion on ecosystem functioning - From the leaf to landscape level (DFG-Project)


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Exotic invasive species represent a major threat to earths biodiversity, since they substantially alter biogeochemical cycles of ecosystems with large impacts on ecosystem functioning. However, to date, explicitly quantifying such impacts remains challenging. One reason is the lack of adequate methodology to capture the spatial dimension of ecosystem changes associated with biological invasion. Conventional ecophysiological approaches are largely restricted to comparing neighbouring plant individuals and tend to neglect the spatial dimension. Landscape ecology, although operating on larger spatial scales, is typically limited to measurements of patterns and processes above the organism level, such as species distribution and propagation speed.

The central aim of this project is to link ecophysiology with landscape ecology, thus moving towards an integrated understanding of the spatial aspect of plant invasions, enabling the quantification of exotic species impacts across spatial scales. A highly suitable technology to address this purpose is hyperspectral remote sensing, which allows for quantifying alterations in native species biochemistry on the leaf level using spectral measurements while allowing to scale up to the landscape level using aerial images.

Utilizing the case study of the N2-fixing leguminous tree Acacia longifolia, a problematic invader in coastal regions of Portugal and many ecosystems worldwide, we will develop new methodology for quantifying changes in ecosystem functioning after plant invasion from the leaf to the landscape scale, by: (1) calibrating physiological and biochemical leaf properties and foliar 13C and 15N stable isotopic signatures with spectral characteristics at the leaf level; (2) assessing the threshold of impact of A. longifolia in the surrounding vegetation at the stand-level using spectral methods; and (3) mapping the distribution of A. longifolia and dominant native vegetation types on the landscape scale using hyperspectral aerial images. Finally (4), we will synthesize our findings in a predictive model which will enable us to assess the impact of an invasive species on native species physiology and on ecosystem functioning at the landscape scale.

This project builds on an extensive data set including hyperspectral aerial images and LiDAR data from a EUFAR flight campaign at the study site in 2011. Moreover, extensive knowledge on the invasive A. longifolia and native Mediterranean vegetation is available from over 10 years of prior research.

Our interdisciplinary approach will bring science significantly further in evaluating the spatial dimension of invasive species impacts and in quantifying changes in ecosystem functioning. Furthermore, by linking landscape ecology and ecophysiology, this project is highly relevant for plant ecology beyond invasion biology and will significantly enrich our understanding of the significance of accounting for spatial scales in ecological studies.