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  • Other Sources  (2)
  • 333.91  (1)
  • Bland–Altman  (1)
  • Blackwell Publishing Ltd  (2)
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  • 1
    Publication Date: 2021-06-28
    Description: Efforts to collaboratively manage the risk of flooding are ultimately based on individuals learning about risks, the decision process, and the effectiveness of decisions made in prior situations. This article argues that much can be learned about a governance setting by explicitly evaluating the relationships through which influential individuals and their immediate contacts receive and send information to one another. We define these individuals as “brokers,” and the networks that emerge from their interactions as “learning spaces.” The aim of this article is to develop strategies to identify and evaluate the properties of a broker's learning space that are indicative of a collaborative flood risk management arrangement. The first part of this article introduces a set of indicators, and presents strategies to employ this list so as to systematically identify brokers, and compare their learning spaces. The second part outlines the lessons from an evaluation that explored cases in two distinct flood risk management settings in Germany. The results show differences in the observed brokers' learning spaces. The contacts and interactions of the broker in Baden‐Württemberg imply a collaborative setting. In contrast, learning space of the broker in North Rhine‐Westphalia lacks the same level of diversity and polycentricity.
    Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Description: MWK Baden‐Württemberg
    Keywords: 333.91 ; brokerage ; collaborative water governance ; comanagement ; comparative analysis ; social networks
    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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