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Sökning: WFRF:(Noe Julia Le)

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1.
  • Kehoe, Laura, et al. (författare)
  • Make EU trade with Brazil sustainable
  • 2019
  • Ingår i: Science. - : American Association for the Advancement of Science (AAAS). - 0036-8075 .- 1095-9203. ; 364:6438, s. 341-
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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2.
  • Billen, Gilles, et al. (författare)
  • Reshaping the European agro-food system and closing its nitrogen cycle: The potential of combining dietary change, agroecology, and circularity
  • 2021
  • Ingår i: One Earth. - : Elsevier BV. - 2590-3322 .- 2590-3330. ; 4:6, s. 839-850
  • Forskningsöversikt (refereegranskat)abstract
    • After World War II, the evolution of Europe's agro-food system has been marked by intensified use of synthetic fertilizers, territorial specialization, and integration in global food and feed markets. This evolution led to increased nitrogen (N) losses to aquatic environments and the atmosphere, which, despite increasing environmental regulations, continues to harm ecosystems and human well-being. Here, we explore how these N losses can be drastically reduced in a scenario synergistically operating three levers: (1) a dietary change toward less animal products and an efficient recycling of human excreta; (2) the generalization of region-specific organic crop rotation systems involving N2-fixing legumes, making it possible to do without synthetic N fertilizers; and (3) the reconnection of livestock with cropping systems allowing optimal use of manure. This scenario demonstrates the possibility to feed the projected European population in 2050 without imports of feed and with half the current level of environmental N losses.
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3.
  • Le Noë, Julia, et al. (författare)
  • Soil organic carbon models need independent time-series validation for reliable prediction
  • 2023
  • Ingår i: Communications Earth & Environment. - 2662-4435. ; 4:1
  • Tidskriftsartikel (refereegranskat)abstract
    • Numerical models are crucial to understand and/or predict past and future soil organic carbon dynamics. For those models aiming at prediction, validation is a critical step to gain confidence in projections. With a comprehensive review of ~250 models, we assess how models are validated depending on their objectives and features, discuss how validation of predictive models can be improved. We find a critical lack of independent validation using observed time series. Conducting such validations should be a priority to improve the model reliability. Approximately 60% of the models we analysed are not designed for predictions, but rather for conceptual understanding of soil processes. These models provide important insights by identifying key processes and alternative formalisms that can be relevant for predictive models. We argue that combining independent validation based on observed time series and improved information flow between predictive and conceptual models will increase reliability in predictions.
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