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Quantifizierung des räumlichen Einflusses exotischer invasiver Pflanzen auf Ökosystemfunktionen - von der Blatt- zur Landschaftebene

Fachliche Zuordnung Ökologie und Biodiversität der Pflanzen und Ökosysteme
Physische Geographie
Förderung Förderung von 2013 bis 2016
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 233885761
 
Erstellungsjahr 2018

Zusammenfassung der Projektergebnisse

Invasive species are a major threat to biodiversity worldwide, however, methods are lacking to trace spatial dimensions of invader impacts on biogeochemical cycles and the structure and function of ecosystems. The overall objective of this project was to quantify the impact of an N2-fixing exotic plant invader on ecosystem functioning in an interdisciplinary approach integrating leaf to landscape scales. This objective was reached by a multitude of different innovative studies, integrating plant biochemical processes with high-resolution remote sensing and spatial modelling tools. At the leaf and canopy scale, we applied spectroscopic measurements to predict a suit of leaf biochemical traits such as tannin, carbon and nitrogen, including δ13C as a proxy for water use efficiency and δ15N as a functional tracer for N input through N fixation. Interestingly, the invasive Acacia longifolia strongly differed in its biochemical and biophysical constituents from the native counterparts within the highly divers Mediterranean dune community. In particular, the distinct dissimilarity regarding leaf N content may provide an indicator of high impact on N cycling. These results emphasize the importance of trait-based approaches for invader monitoring and underline the great potential of optical measurements for impact- and trait assessments at larger spatial scales. At the community scale, we developed δ15N and δ13C isoscapes, i.e. the spatial analysis of isotope pattern within the native target species, as a novel tool to capture the spatial dimension of changes in ecosystem functioning resulting from both, natural heterogeneity of the native system and functional changes following plant invasion. Thereby, isoscapes enabled quantifying the spatial range of invader influence on plant-plant interaction, which shift from facilitation by N addition to competition for water with declining distance to the invader. Such spatially explicit assessments will improve knowledge on plant-plant interactions in complex natural environments. Furthermore, they can provide empirical data that are urgently needed to develop, parametrize, and validate multi-species models of plant-plant interactions and invader impact. Therefore, the isoscapes approach represents a step forward in integrating spatially explicit empirical data into community ecology. Finally, at the landscape scale, we were able, for the first time, to build predictive isoscape-models based on remotely sensed information and species distribution to identify and map heterogeneity in ecological processes as well as to quantify and predict the spatial influence of invasive species. At landscape scale, A. longifolia was detected with high accuracy even at early stages of invasion by hyperspectral and LiDAR data fusion based on predictors that relate to in situ observed ecophysiological properties of the invader. Moreover, based on the Near-Infrared Vegetation Index (NIRv), we found a significant increase of Gross Primary Production (GPP) beyond natural levels even when invader cover was low, which indicated a potential regime shift from a dune to a foresttype ecosystem. Thus, it demonstrates that early detection of high invader impact is feasible using earth observation. As invasion of N2-fixing woody plants endanger nutrient poor ecosystems worldwide, our remote sensing approach may open the door to new assessments of invasion impact across spatio-temporal scales in these systems. Finally, we integrated isoscape models and remote sensing data, i.e. spectral indices and invader maps derived from airborne hyperspectral and LiDAR data, to conduct a regional impact assessment. To this end, we could show that 50 % of impact on indices of photosynthesis and GPP occurs outside the canopies of A. longifolia. In sum, we showed that integrating ecophysiology, landscape ecology, remote sensing, and spatial modelling is a powerful interdisciplinary approach to elucidate ecological processes from leaf to landscape scale. Habfast-Prize for outstanding scientific work of a young scientist to Christine Hellmann, 2017

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