
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Issues and challenges in landscape models for agriculture: from the representation of agroecosystems to the design of management strategies

Agroecosystems produce food and many other services that are crucial for human well-being. Given the scales at which the processes underlying these services take place, agricultural landscapes appear as appropriate spatial units for their evaluation and management. The design of sustainable agricultural landscapes that value these services has thus become a pressing issue but faces major challenges stemming from the diversity of processes, their interactions and the number of scales at stake. Agricultural landscape modelling can provide a key contribution to this design but must still overcome several difficulties to offer reliable tools for decision makers. Our study aimed at shedding light on the main scientific and technical difficulties that make the building of landscape models that may efficiently inform decision-makers a complex task, as well as translating them in terms of challenges that can be further investigated and discussed. We examine current issues and challenges and indicate future research needs to overcome the scientific and technical obstacles in the development of useful agricultural landscape models. We highlight research perspectives to better couple landscape patterns and process models and account for feedbacks, integrate the decisions of multiple stakeholders, consider the spatial and temporal heterogeneity of data and processes, explore alternative landscape organisations and assess multiobjective performance. Coping with the issues and challenges discussed in this paper should improve our understanding of agroecosystems and give rise to new hypotheses, thereby informing future research.
- National Research Institute for Agriculture, Food and Environment France
- Aster Canada
- Agrocampus Ouest France
- Université de Rennes 1 France
- University of Montpellier France
agroecosystem, 710, 333, [STAT.AP] Statistics [stat]/Applications [stat.AP], [SDE.ES] Environmental Sciences/Environment and Society, management strategies, stakeholder decision, [SDE.ES]Environmental Sciences/Environment and Society, [STAT.AP]Statistics [stat]/Applications [stat.AP], inference, simulation model, spatial heterogeneity, sustainability, [SDE.ES]Environmental Sciences/Environmental and Society, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
agroecosystem, 710, 333, [STAT.AP] Statistics [stat]/Applications [stat.AP], [SDE.ES] Environmental Sciences/Environment and Society, management strategies, stakeholder decision, [SDE.ES]Environmental Sciences/Environment and Society, [STAT.AP]Statistics [stat]/Applications [stat.AP], inference, simulation model, spatial heterogeneity, sustainability, [SDE.ES]Environmental Sciences/Environmental and Society, [SDE.BE] Environmental Sciences/Biodiversity and Ecology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
citations 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).14 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.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
