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Anita D. Bayer

Researcher at Karlsruhe Institute of Technology

Publications -  24
Citations -  1316

Anita D. Bayer is an academic researcher from Karlsruhe Institute of Technology. The author has contributed to research in topics: Soil carbon & Dynamic global vegetation model. The author has an hindex of 11, co-authored 19 publications receiving 930 citations. Previous affiliations of Anita D. Bayer include German Aerospace Center.

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A global spectral library to characterize the world’s soil

R. A. Viscarra Rossel, +41 more
TL;DR: In this article, the authors developed and analyzed a global soil visible-near infrared (vis-NIR) spectral library, which is currently the largest and most diverse database of its kind, and showed that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability.
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Pathways to bridge the biophysical realism gap in ecosystem services mapping approaches

TL;DR: This paper provides a synthesis of available approaches, models and tools, and data sources, that are able to better link ecosystem service mapping to current understanding of the role of ecosystem service providing organisms and land/seascape structure in ecosystem functioning and opens avenues for further model development using hybrid approaches tailored to available resources.
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Simulated carbon emissions from land-use change are substantially enhanced by accounting for agricultural management

TL;DR: In this article, the authors assess the effect of representing agricultural land management in a dynamic global vegetation model, and find that accounting for harvest, grazing and tillage resulted in cumulative E-LUC since 1850 ca. 70% larger than in simulations ignoring these processes, but also changed the timescale over which these emissions occurred and led to underestimation of the carbon sequestered by possible future reforestation actions.
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A Comparison of Feature-Based MLR and PLS Regression Techniques for the Prediction of Three Soil Constituents in a Degraded South African Ecosystem

TL;DR: Two approaches for the quantification of soil organic carbon, iron oxides, and clay content based on field and laboratory spectroscopy of natural surfaces are tested, developed based on extensive ground reference data of 163 sampled sites collected in the Thicket Biome, South Africa.