Effects of low wildfire burn severity due to pre-fire shrub thinning on the chaparral soil bacteriome in the Santa Monica Mountains of Southern California
Notice bibliographique
Résumé
ABSTRACT Our objective was to study the longitudinal effect of decreased burn severity due to vegetation-type conversion (VTC) induced by chaparral shrub thinning prior to the Woolsey wildfire (November 2018) on soil chemistry and bacteriome composition and function. We compared soils from two study sites on the Malibu campus of Pepperdine University in the Santa Monica Mountains: one site had dense, unaltered chaparral shrubland and experienced a 4.5-fold increase in vegetation burn severity (high severity burn) compared to an adjacent altered site where the vegetative fuel load was 80% less prior to the fire (low severity burn). We analyzed soil nutrient concentrations and pH in 2019 and 2021 and soil respiration, measured by CO 2 efflux, in 2019, 2020, and 2021. DNA was isolated from soil samples collected in 2019, 2020, 2021, and 2023 for Illumina Miseq paired-end 16S V3-V4 sequencing. We predicted the functional bacteriome from the 16S data using PICRUSt2. Relative to high severity soils, low severity soils showed decreased nutrient concentrations, pH, and % organic matter in 2019. The low severity burned site showed greater compositional stability over time, with increased pyrophilous taxa in 2021 and 2023 ( Massilia , Conexibacter , etc.). High severity burned soils showed decreased metabolic capacity over time. We identified correlations between bacterial taxa and diversity and functional pathways, which remained only in the high severity soil samples after stratification. Our findings contribute to an improved understanding of bacterial succession in soil from sites that experienced VTC prior to wildfire, highlighting microbial ecological implications for fire management strategies. IMPORTANCE Along with increased fire frequency, the wildfire-urban interface has been expanding, requiring the need for fire mitigation strategies, such as pre-fire vegetation thinning near urban structures. Pre-fire vegetation thinning contributes to vegetation-type conversion and decreases burn severity, but its effect on the soil microenvironment is largely unknown. Here, we compared soil sites that experienced burns of different severity due to pre-fire vegetation thinning and vegetation-type conversion at one site but not the other. We identified changes in soil chemistry and longitudinal shifts in soil bacterial abundance and metabolic capacity that are associated with decreased burn severity due to pre-fire vegetation-type conversion. Our work contributes to improved understanding of the effects of pre-fire vegetation thinning to manage wildfire impact on urban structures on the soil microenvironment. These findings demonstrate ecological implications for fire management strategies and recovery of the chaparral ecosystems following wildfire.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».