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Dhillon, Maninder Singh ; Koellner, Thomas ; Asam, Sarah ; Bogenreuther, Jakob ; Dech, Stefan ; Gessner, Ursula ; Gruschwitz, Daniel ; Annuth, Sylvia Helena ; Kraus, Tanja ; Rummler, Thomas ; Schaefer, Christian ; Schönbrodt-Stitt, Sarah ; Steffan-Dewenter, Ingolf ; Wilde, Martina ; Ullmann, Tobias:
Landscape structure, climate variability, and soil quality shape crop biomass patterns in agricultural ecosystems of Bavaria.
In: Frontiers in Plant Science.
Bd. 16
(7 August 2025)
.
ISSN 1664-462X
DOI: https://doi.org/10.3389/fpls.2025.1630087
Abstract
Understanding how environmental variability shapes crop biomass is essential for improving yield stability and guiding climate-resilient agriculture. To address this, we compared biomass estimates from a semi-empirical light use efficiency (LUE) model with predictions from a machine learning–remote sensing framework that integrates environmental variables. We applied a combined LUE and random forest (RF) model to estimate the mean biomass of winter wheat and oilseed rape across Bavaria, Germany, from 2001 to 2019. Using a 5 km2 hexagon-based grid, we incorporated landscape metrics (land cover diversity, small woody features), topographic variables (elevation, slope, aspect), soil potential, and seasonal climate predictors (mean and standard deviation of temperature, precipitation, and solar radiation) across the growing season. The RF-based approach improved predictive accuracy over the LUE model alone, particularly for winter wheat. Biomass patterns were shaped by both landscape configuration and climatic conditions. Winter wheat biomass was more influenced by topographic and landscape features, while oilseed rape was more sensitive to solar radiation and soil properties. Moderately diverse landscapes supported higher biomass, whereas an extreme landscape fragmentation or high variability showed lower values. Temperature thresholds, above 21 °C for winter wheat and 12 °C for oilseed rape, were associated with biomass declines, indicating crop-specific sensitivities under Bavarian conditions. This hybrid modeling approach provides a transferable framework to map and understand crop biomass dynamics at scale. The findings offer region-specific insights that can support sustainable agricultural planning in the context of climate change.
Weitere Angaben
| Publikationsform: | Artikel in einer Zeitschrift |
|---|---|
| Begutachteter Beitrag: | Ja |
| Institutionen der Universität: | Fakultäten > Fakultät für Biologie, Chemie und Geowissenschaften > Fachgruppe Geowissenschaften > Professur Ecological Services > Professur Ecological Services - Univ.-Prof. Dr. Thomas Koellner Profilfelder > Advanced Fields > Ökologie und Umweltwissenschaften Forschungseinrichtungen > Zentrale wissenschaftliche Einrichtungen > Bayreuther Zentrum für Ökologie und Umweltforschung - BayCEER |
| Titel an der UBT entstanden: | Ja |
| Themengebiete aus DDC: | 500 Naturwissenschaften und Mathematik > 550 Geowissenschaften, Geologie |
| Eingestellt am: | 12 Aug 2025 07:05 |
| Letzte Änderung: | 12 Aug 2025 07:05 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/94458 |