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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: 2023-11-17
    Description: 〈title xmlns:mml="http://www.w3.org/1998/Math/MathML"〉Abstract〈/title〉〈sec xmlns:mml="http://www.w3.org/1998/Math/MathML" id="ejss13362-sec-1003" xml:lang="en"〉 〈p xml:lang="en"〉Long‐term experiments (LTEs) have provided data to modellers and agronomists to investigate changes and dynamics of soil organic carbon (SOC) under different cropping systems. As treatment changes have occurred due to agricultural advancements, so too have analytical soil methods. This may lead to method bias over time, which could affect the robust interpretation of data and conclusions drawn. This study aims to quantify differences in SOC due to changes in dry combustion methods over time, using soil samples of a LTE established in 1963 that focuses on mineral and organic fertilizer management in the temperate zone of Northeast Germany. For this purpose, 1059 soil samples, collected between 1976 and 2008, have been analysed twice, once with their historical laboratory method right after sampling, and a second time in 2016 when all samples were analysed using the same elementary analyser. In 9 of 11 soil sampling campaigns, a paired 〈italic toggle="no"〉t〈/italic〉‐test provided evidence for significant differences in the historical SOC values when compared with the re‐analysed concentrations of the same LTE sample. In the sampling years 1988 and 2004, the historical analysis obtained about 0.9 g kg〈sup〉−1〈/sup〉 lower SOC compared with the re‐analysed one. For 1990 and 1998, this difference was about 0.4 g kg〈sup〉−1〈/sup〉. Correction factors, an approach often used to correct for different analytical techniques, could only be applied for 5 of 11 sampling campaigns to account for constant and proportional systematic method error. For this particular LTE, the interpretation of SOC changes due to agronomic management (here fertilization) deviates depending on the analytical method used, which may weaken the explanatory power of the historical data. We demonstrate that analytical method changes over time present one of many challenges in the interpretation of time series data of SOC dynamics. Therefore, LTE site managers need to ensure providing all necessary protocols and data in order to retrace method changes and if necessary recalculate SOC.〈/p〉 〈/sec〉〈sec xmlns:mml="http://www.w3.org/1998/Math/MathML" id="ejss13362-sec-0003" xml:lang="en"〉 〈title〉Highlights〈/title〉 〈p xml:lang="en"〉〈list list-type="bullet" id="ejss13362-list-0001"〉 〈list-item id="ejss13362-li-0001"〉〈p〉A total of 1059 LTE soil samples taken between 1976 and 2008 were re‐analysed for SOC in 2016〈/p〉〈/list-item〉 〈list-item id="ejss13362-li-0002"〉〈p〉Several methodological changes for SOC determination led to significant different SOC concentration in the same sample〈/p〉〈/list-item〉 〈list-item id="ejss13362-li-0003"〉〈p〉Interpretation and time series of LTE soil data suffer from consideration of analytical method changes and poor documentation of the same〈/p〉〈/list-item〉 〈list-item id="ejss13362-li-0004"〉〈p〉Soil archive establishment, thorough method protocols and diligent proficiency testing after soil method changes ameliorate the dilemma〈/p〉〈/list-item〉 〈/list〉〈/p〉 〈/sec〉
    Description: Brandenburger Staatsministerium für Wissenschaft, Forschung und Kultur http://dx.doi.org/10.13039/501100004581
    Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100004937
    Description: https://doi.org/10.4228/zalf-acge-b683
    Keywords: ddc:631.4 ; Bland–Altman ; carbon stocks ; data trueness ; Deming regression ; method bias ; soil archive ; soil survey
    Language: English
    Type: doc-type:article
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