Cross-regional modelling of fire occurrence in the Alps and the Mediterranean Basin
| Autor: | G. Boris Pezzatti, Harald Vacik, Juli G. Pausas, Harald Bugmann, Gunnar Petter, Çağatay Tavşanoğlu, İsmail Bekar |
|---|---|
| Přispěvatelé: | Bekar, Ismail, Pausas, J. G., Bekar, Ismail [0000-0002-2899-5025], Pausas, J. G. [0000-0003-3533-5786] |
| Rok vydání: | 2020 |
| Předmět: |
040101 forestry
Spatial resolution 010504 meteorology & atmospheric sciences Ecology Transferability Climate change Predictive capability Forestry Provisioning 04 agricultural and veterinary sciences 01 natural sciences Mediterranean Basin Grain size Environmental niche modelling Ecosystem services Fire ignition 0401 agriculture forestry and fisheries Environmental science Physical geography Maxent Scale (map) Species distribution mode 0105 earth and related environmental sciences |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname |
| ISSN: | 1049-8001 |
| Popis: | In recent decades, changes in fire activity have been observed in Europe. Fires can have large consequences for the provisioning of ecosystem services and for human well-being. Therefore, understanding the drivers of fire occurrence and improving the predictive capability of fire occurrence models is of utmost importance. So far, most studies have focused on individual regions with rather low spatial resolution, and have lacked the ability to apply the models in different regions. Here, a species distribution modelling approach (Maxent) was used to model fire occurrence in four regions across the Mediterranean Basin and the Alps using several environmental variables at two spatial resolutions. Additionally, a cross-regional model was developed and spatial transferability tested. Most models showed good performance, with fine resolution models always featuring somewhat higher performance than coarse resolution models. When transferred across regions, the performance of regional models was good only under similar environmental conditions. The cross-regional model showed a higher performance than the regional models in the transfer tests. The results suggest that a cross-regional approach is most robust when aiming to use fire occurrence models at the regional scale but beyond current environmental conditions, for example in scenario analyses of the impacts of climate change. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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