López Espinoza, Gina Marcela: Field-based evidence of root plasticity under abiotic stresses and tillage. - Bonn, 2026. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5-88042
@phdthesis{handle:20.500.11811/13902,
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5-88042,
doi: https://doi.org/10.48565/bonndoc-786,
author = {{Gina Marcela López Espinoza}},
title = {Field-based evidence of root plasticity under abiotic stresses and tillage},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2026,
month = feb,

note = {Modern agriculture faces the dual challenge of increasing food productivity while preserving soil health and biodiversity under a changing climate. Roots are central to this dilemma, as they dictate nutrient uptake, soil stability, and carbon sequestration. However, current crop–soil models often rely on rigid, fixed parameters that fail to account for root plasticity: the plant's ability to shift its architecture in response to stress. This thesis quantifies how nutrient deficiencies, tillage, and climate pressures (warming, drought, and elevated CO2) reshape root-to-shoot allocation to determine if current process-based crop models can accurately capture these dynamics.
Through systematic reviews and field experiments, the research demonstrates that nitrogen and phosphorus deficiencies significantly reduce total root length and biomass, yet drive an increase in relative biomass allocation below ground, raising root-to-shoot ratios by up to 51%. Conversely, higher temperatures tend to reduce this investment, while the impacts of tillage are minimal. When testing these findings against simulations in crop models such as MONICA, AgroC, STICS, and LINTUL5/Slim, the results reveal a significant "plasticity gap." While models handle CO2 and tillage effects reasonably well, they consistently undervalue the impact of drought and nitrogen stress on carbon partitioning.
These findings highlight a critical need to move beyond static allocation rules in agricultural modeling. To improve predictions for food security and carbon storage, future work must integrate high-frequency root data and stress-specific routines into simulation tools. By bridging the gap between field-observed plasticity and digital modeling, we can better predict how crops will behave in increasingly unpredictable environments, ultimately supporting more resilient farming systems.},

url = {https://hdl.handle.net/20.500.11811/13902}
}

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