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| dc.creator | Duane, Andrea | |
| dc.creator | Moghli, Aymen | |
| dc.creator | Coll Mir, Lluís | |
| dc.creator | Vega García, Cristina | |
| dc.date | 2025 | |
| dc.date.accessioned | 2025-11-03T12:17:36Z | |
| dc.date.available | 2025-11-03T12:17:36Z | |
| dc.identifier | https://doi.org/10.1016/j.apgeog.2025.103539 | |
| dc.identifier | 0143-6228 | |
| dc.identifier | https://hdl.handle.net/10459.1/468927 | |
| dc.identifier.uri | http://fima-docencia.ub.edu:8080/xmlui/handle/123456789/24544 | |
| dc.description | Very large wildfire events represent substantial social and ecological disturbances globally, with recent occurrences suggesting unprecedented scale and impact. What constitutes a large fire event in each territory varies regionally depending on biophysical attributes and fire management response. Despite the efforts made to provide standardized metrics across ecosystems, there remains a need for new methods to identify and evaluate fires that are contextually large. Here, we propose a framework to evaluate contextually large fires in Europe, considering them as fires larger than expected based on return period functions. Utilizing 23 years of data from the European Forest Fires Information System, we applied extreme value theory to compute fire return periods at the regional level (administrative units of approximately 17,600 km2). Results identified 115 regions out of 330 (35%) that experienced at least one contextually large fire, primarily in southern Europe, but also dispersed across the temperate and Atlantic biomes. While 32 contextually large fires were larger than 10,000 ha, 104 were smaller than 500 ha. The occurrence of contextually large fires shows a positive trend along the study period. This dataset provided valuable insights for assessing extreme wildfires, their distribution and their probabilities, facilitating effective risk mitigation strategies in Europe. | |
| dc.description | This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101037419 and from the Generalitat de Catalunya’s CERCA Programme. Andrea Duane also benefits from the funds of the Spanish Ministry of Science and Innovation (FJC2020-045980-I). | |
| dc.language | eng | |
| dc.publisher | Elsevier | |
| dc.relation | Reproducció del document publicat a https://doi.org/10.1016/j.apgeog.2025.103539 | |
| dc.relation | Applied Geography, 2025, vol. 176, núm. 103539, p. 1-10 | |
| dc.relation | info:eu-repo/grantAgreement/EC/H2020/101037419/EU/FIRE-RES | |
| dc.rights | cc-by (c) Duane et al., 2025 | |
| dc.rights | Attribution 4.0 International | |
| dc.rights | info:eu-repo/semantics/openAccess | |
| dc.rights | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Generalized extreme value | |
| dc.subject | NUTS-2 regions | |
| dc.subject | EFFIS | |
| dc.subject | Large wildfires | |
| dc.subject | Fire frequency | |
| dc.title | On the evidence of contextually large fires in Europe based on return period functions | |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion |
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