Evidence map›Paper›PMID 41127812›Full record

ArticleMethodsX2025

Post-fire environmental assessment: a participatory multi-criteria approach for estimating soil erosion risk and vegetation recovery potential.

Irina Cristal, Pere Pons, Marina Palmero-Iniesta, Elena Puigdemasa

Abstract read
In one paragraph

Article in MethodsX, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Irina CristalAnimal Biology Lab and BioLand, Department of Environmental Sciences, University of Girona, Girona, Spain.
Pere PonsAnimal Biology Lab and BioLand, Department of Environmental Sciences, University of Girona, Girona, Spain.
Marina Palmero-IniestaAnimal Biology Lab and BioLand, Department of Environmental Sciences, University of Girona, Girona, Spain.
Elena PuigdemasaAnimal Biology Lab and BioLand, Department of Environmental Sciences, University of Girona, Girona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although often perceived as destructive, wildfires play a vital ecological role in maintaining the function and biodiversity of fire-adapted ecosystems. However, increasing frequency, intensity, and altered seasonality of fires impede ecosystem recovery by depleting seed banks and disrupting plant maturation cycles. Post-fire soil erosion, usually triggered by the first rains after a fire event, exacerbates these challenges by accelerating nutrient loss and hindering vegetation regeneration, which can lead to ecosystem degradation. To address this risk, it is important to understand the ecosystems' responses to fire. Here, we outline a post-fire ecosystem assessment framework that applies geo-spatial data and participatory multi-criteria analysis (MCA) based on expert judgement and local knowledge. Our methodology includes:•Identifying key factors influencing post-fire soil erosion and vegetation recovery•Assessing and mapping postfire soil erosion risk and vegetation recovery potential•Validating the framework with field data and checking the stability of MCA parameters through sensitivity analysis.This paper extends the original research article by Cristal et al. (2025), offering a comprehensive guide for researchers and environmental professionals on applying participatory MCA in post-fire environmental impact assessments.

Indexed as

AHPAnalytical hierarchy processMCASoil erosion susceptibilityVegetation regenerationWildfire impact assessment

Identifiers

PMID41127812
PMCPMC12538923

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.