How do understorey fires in deciduous forests affect soil properties? Insights from Eastern India
Notice bibliographique
Résumé
Understorey forest fires in tropical dry deciduous forests are an ecologically significant yet understudied phenomena, particularly in India, where such fires occur frequently but have been largely overlooked for decades. This study examines the effects of understorey fires on the physicochemical properties of in-situ lateritic soils (Haplustalfs, Paleustalfs, and Ustifluvents, as per USDA Soil Taxonomy) in the eastern Indian state of West Bengal. During the 2024 fire season (February–May), soil samples were collected from 12 sites, comparing burnt and unburnt patches at depths of 0–5 cm, 5–10 cm, and 10–20 cm. Fire temperatures recorded at three sites using infrared pyrometers ranged from approximately 500°C to 1100°C, with a fire spread rate of about 8 m/hr. The predominant soil textures in the study area are sandy clay loam and sandy loam. The results reveal that understorey fires significantly (p < 0.05) altered the topsoil (0–5 cm), increasing pH, electrical conductivity (EC), organic carbon (OC), nitrogen (N), potassium oxide (K₂O), and organic matter (OM), likely due to ash deposition and the partial combustion of organic material. We also observed a significant reduction of bulk density (BD) at the 0–5 cm depth in burnt areas, likely due to the loss of fine roots and soil moisture during the fire, which would cause loosening of the soil structure. However, no significant differences were observed in aggregate stability, Visual Evaluation of Soil Structure (VESS) scores, base cation concentrations (Ca, Mg, Na), phosphorus (P₂O₅) or cation exchange capacity (CEC) between burnt and unburnt sites. Minimal changes were recorded at depths beyond 5 cm, attributed to limited heat penetration and the absence of pyrogenic residues. These results diverge from the general understanding of fire effects on soil properties. In ecoregions dominated by highly flammable vegetation, such as coniferous forests and grasslands (e.g. in US, Canada or Australia), large-scale crown fires disrupt entire forest ecosystems and effectuate heat-induced alterations and nutrient volatilisation, which profoundly affect soil properties. On the contrary, understorey fires in deciduous forests primarily influence the forest floor, predominantly consuming low-lying vegetation, leaf litter, and organic matter, resulting in turn in immediate nutrient enrichment in the topsoil (0–5 cm), which may facilitate post-fire vegetation recovery. The observed soil changes are driven more by ash deposition and incomplete combustion of organic matter than by nutrient volatilisation, distinguishing them from the more intense fire behaviours elsewhere. These variations in fire intensity and behaviour likely explain the differences in soil responses. However, the long-term risks of ash depletion and nutrient loss through water-driven erosion pose significant concerns for post-fire forest landscapes, potentially degrading soil productivity, disrupting forest regeneration, and threatening overall ecosystem resilience. These findings emphasize the need for comprehensive research to fully comprehend the long-term implications of understorey fires in tropical dry deciduous forests.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 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 | 0,000 | 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 source (Gemma direct ou Codex distillé), 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 ».