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Implementing climate change projections in System Dynamics models
Desertification is the degradation of drylands, which occupy an increasing proportion of the Earth's surface due to global warming. It is currently the most extensive biome on Earth, occupying 45% and one out of every three inhabitants of the planet live in them. One of the most effective ways...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925954/ https://www.ncbi.nlm.nih.gov/pubmed/36798836 http://dx.doi.org/10.1016/j.mex.2023.102044 |
Sumario: | Desertification is the degradation of drylands, which occupy an increasing proportion of the Earth's surface due to global warming. It is currently the most extensive biome on Earth, occupying 45% and one out of every three inhabitants of the planet live in them. One of the most effective ways to face desertification, as Land Degradation Neutrality points out, is prevention. For this purpose, simulation models are very useful tools. Specifically, System Dynamics models are particularly effective, since they allow bringing together the biophysical and socioeconomic variables involved in the formation of the problem. These integrative models, coupled with other tools such as sensitivity analyses, are used to generate desertification early warning indicators. The objective of this programming routine is to implement climate change scenarios in these simulation models. The script presented here was used to evaluate the sensitivity of dehesa rangelands productivity to the increase in the frequency and intensity of droughts due to climate change. • Integrated simulation models are useful tools to understand complex socioecosystems. • Land-use changes foster the alteration of key hydro-bio-geochemical processes. • By means of automated import processes and data analysis programming, it is possible to implement desertification early warning systems. |
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