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  • 1
    Publication Date: 2024-01-26
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉The increasing demand for biomass for food, animal feed, fibre and bioenergy requires optimization of soil productivity, while at the same time, protecting other soil functions such as nutrient cycling and buffering, carbon storage, habitat for biological activity and water filter and storage. Therefore, one of the main challenges for sustainable agriculture is to produce high yields while maintaining all the other soil functions. Mechanistic simulation models are an essential tool to fully understand and predict the complex interactions between physical, biological and chemical processes of soils that generate those functions. We developed a soil model to simulate the impact of various agricultural management options and climate change on soil functions by integrating the relevant processes mechanistically and in a systemic way. As a special feature, we include the dynamics of soil structure induced by tillage and biological activity, which is especially relevant in arable soils. The model operates on a 1D soil profile consisting of a number of discrete layers with dynamic thickness. We demonstrate the model performance by simulating crop growth, root growth, nutrient and water uptake, nitrogen cycling, soil organic matter turnover, microbial activity, water distribution and soil structure dynamics in a long‐term field experiment including different crops and different types and levels of fertilization. The model is able to capture essential features that are measured regularly including crop yield, soil organic carbon, and soil nitrogen. In this way, the plausibility of the implemented processes and their interactions is confirmed. Furthermore, we present the results of explorative simulations comparing scenarios with and without tillage events to analyse the effect of soil structure on soil functions. Since the model is process‐based, we are confident that the model can also be used to predict quantities that have not been measured or to estimate the effect of management measures and climate states not yet been observed. The model thus has the potential to predict the site‐specific impact of management decisions on soil functions, which is of great importance for the development of a sustainable agriculture that is currently also on the agenda of the ‘Green Deal’ at the European level.〈/p〉
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347
    Description: https://git.ufz.de/bodium/bodium_v1.0
    Keywords: ddc:631.4 ; agriculture ; computational model ; simulation ; soil microbiology ; soil structure ; sustainable soil
    Language: English
    Type: doc-type:article
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  • 2
    Publication Date: 2024-03-18
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Temperature and soil moisture are known to control pesticide mineralization. Half‐life times (DT〈sub〉50〈/sub〉) derived from pesticide mineralization curves generally indicate longer residence times at low soil temperature and moisture but do not consider potential changes in the microbial allocation of pesticide‐derived carbon (C). We aimed to determine carbon use efficiency (CUE, formation of new biomass relative to total C uptake) to better understand microbial utilization of pesticide‐derived C under different environmental conditions and to support the conventional description of degradation dynamics based on mineralization. We performed a microcosm experiment at two MCPA (2‐methyl‐4‐chlorophenoxyacetic acid) concentrations (1 and 20 mg kg〈sup〉−1〈/sup〉) and defined 20°C/pF 1.8 as optimal and 10°C/pF 3.5 as limiting environmental conditions. After 4 weeks, 70% of the initially applied MCPA was mineralized under optimal conditions but MCPA mineralization reached less than 25% under limiting conditions. However, under limiting conditions, an increase in CUE was observed, indicating a shift towards anabolic utilization of MCPA‐derived C. In this case, increased C assimilation implied C storage or the formation of precursor compounds to support resistance mechanisms, rather than actual growth since we did not find an increase in the 〈italic toggle="no"〉tfdA〈/italic〉 gene relevant to MCPA degradation. We were able to confirm the assumption that under limiting conditions, C assimilation increases relative to mineralization and that C redistribution, may serve as an explanation for the difference between mineralization and MCPA dissipation‐derived degradation dynamics. In addition, by introducing CUE to the temperature‐ and moisture‐dependent degradation of pesticides, we can capture the underlying microbial constraints and adaptive mechanisms to changing environmental conditions.〈/p〉
    Description: 〈p xmlns:mml="http://www.w3.org/1998/Math/MathML" xml:lang="en"〉Changing environmental conditions alter the MCPA degradation dynamics and the allocation of pesticide‐derived carbon to anabolic or catabolic metabolism.〈boxed-text position="anchor" content-type="graphic" id="ejss13417-blkfxd-0001" xml:lang="en"〉 〈graphic position="anchor" id="jats-graphic-1" xlink:href="urn:x-wiley:13510754:media:ejss13417:ejss13417-toc-0001"〉 〈/graphic〉 〈/boxed-text〉〈/p〉
    Description: Collaborative Research Center 1253 CAMPOS (DFG)
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: DFG Priority Program 2322 “Soil System”
    Description: Ellrichshausen Foundation
    Description: Research Training Group “Integrated Hydrosystem modeling”
    Description: https://doi.org/10.5281/zenodo.5081655
    Keywords: ddc:631.4 ; anabolism ; carbon use efficiency ; catabolism ; effect of soil moisture and temperature ; gene‐centric process model ; MCPA biodegradation
    Language: English
    Type: doc-type:article
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