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Record W4200384083 · doi:10.3390/fire4040095

The Footprint of Wildfires on Mediterranean Forest Ecosystem Services in Vesuvius National Park

2021· article· en· W4200384083 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFire · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsEcosystem servicesNational parkEcosystemProvisioningEnvironmental resource managementMediterranean climateGeographyDisturbance (geology)Environmental scienceAgroforestryEcology

Abstract

fetched live from OpenAlex

Wildfires are one of the most important natural disturbances in vegetation biomes. In recent decades, both the number and severity of fires have significantly increased in Mediterranean forests, frequently resulting in catastrophic events. In this scenario, we aimed to explore the flow of ecosystem services and their related economic value that was disrupted by human-induced megafires in the Mediterranean forest of Vesuvius National Park in the summer of 2017. We adopted an innovative approach by merging two methodologies: an ecological approach to evaluate the status of the forest ecosystem after the wildfires and an economics methodology to estimate the monetary value of the interruption to ecosystem services. Losses related to the following six services were estimated: woody biomass, soil erosion control, habitat maintenance, pollination, carbon stock, and ecotourism. In 2017, 3350 ha of forest (88% of the total forested area of Vesuvius National Park) burnt over a period of 49 days. The total estimated monetary loss amounted to €14.363 M, 56.9% of which comprised of provisioning ecosystem services, while 34.7% encompassed maintenance and regulation services, and 8.5% were so-called cultural services. Suppression costs accounted for 16% of the total estimated economic loss of ecosystem services. Our results provide useful insights for decision-makers when allocating financial resources, suggesting that they should invest in fire prevention rather than fire suppression and post-fire restoration. This explicit valuation of the footprint of the wildfires, although not exhaustive, can also lead to greater awareness among the public regarding the benefits conferred by Mediterranean forest ecosystems. This is the first study to economically evaluate the interruption of ecosystem services after megafires in the Mediterranean basin.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.218
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it