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Other literature type . 2025
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Project deliverable . 2025
License: CC BY
Data sources: Datacite
ZENODO
Project deliverable . 2025
License: CC BY
Data sources: Datacite
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D6.2 New supply chain modeling in GLOBIOM

Authors: Leclère, David; Di Fulvio, Fulvio; Meinhart, Bettina; Palazzo, Amanda; Lauri, Pekka; Hinkel, Niklas; Lessa Derci Augustynczik, Andrey;

D6.2 New supply chain modeling in GLOBIOM

Abstract

One of the objectives of the CLEVER project is to improve and mobilize modelling tools to explorethe effectiveness of innovative international trade and supply chain governance interventionson non-food biomass supply chains and biodiversity. This modelling component relies on theGLOBIOM land use model, which projects the dynamics of most important agricultural andforestry supply chains and their impacts on natural resources from the year 2000 into the futurewith a decadal time step (up to 2050 or even 2100). As compared to other forward-looking dynamic supply chains modelling tools, this model has arelatively broad and yet detailed modelling of supply chains, covering globally the consumerdemand for final products, trade and the supply of products at the scale of 59 market regionsand for more than 50 products. The modelling of each agricultural and forestry productionactivities and related land and water use is done at subnational scale, with a multiple crop,livestock and forestry management intensities and a detailed land cover and land use changerepresentation. A recent extension was allowed to cover blue food supply chains, i.e., fish andseafood. The modelling rests on a large number of datasets of various sources (e.g., fromcountry-level or regional-level price elasticities and official statistics, to high spatial resolutiondatasets such remote sensing-based land cover products and biophysical model outputs). Thestandard version of the model balances across several priorities (e.g., high level of detail inmodelled variables, use globally available data products, sufficiently low computation time) andis continuously updated as new datasets and methods become available, and specific modellinggoals are pursued. The planned model and scenario applications in CLEVER focus on the nexus of trade, supply chaingovernance and biodiversity impacts for three specific supply chains: soy – with a particularinterest in Brazil and the EU – , forest biomass – with a particular interest in Brazil and the EU –, and aquaculture and aquafeed (globally). In order to improve the underlying GLOBIOMmodelling framework for this, a number of activities are undertaken in Workpackage 6. Thisdeliverable reports on the supply chain modelling improvements (Task 6.2), with explicitintegration of the outputs of other tasks in WP6 such as new biophysical modelling outputs(Task6.1), and improved biodiversity modelling methods and data (Task 6.3). The deliverable is organized in three main sections. In the INTRODUCTION AND OBJECTIVESsection, we provide for each supply chain more background on the supply chain and its link tobiodiversity, planned scenario and model applications, and a synthetic description of the modelimprovement objectives. Then, the METHODS section provides more detailed information onthe status quo in the standard model version, the methods and data sources employed forimproving the model, and the scenarios used to illustrate the model improvements. TheILLUSTRATIVE PROJECTIONS AND DISCUSSION section then analyses for each supply chain theprojections of the improved model version for the illustrative scenario, before discussingachievements and potential further improvements within further Workpackage 6 andWorkpackage 7 activities.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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Related to Research communities
Italian National Biodiversity Future Center