Modelling effects of seasonal variation in water table depth on net ecosystem CO <sub>2</sub> exchange of a tropical peatland
Notice bibliographique
Résumé
Abstract. Seasonal variation in water table depth (WTD) determines the balance between aggradation and degradation of tropical peatlands. Longer dry seasons together with human interventions (e.g. drainage) can cause WTD drawdowns making tropical peatland C storage highly vulnerable. Better predictive capacity for effects of WTD on net CO2 exchange is thus essential to guide conservation of tropical peat deposits. Mathematical modelling of basic eco-hydrological processes under site-specific conditions can provide such predictive capacity. We hereby deploy a process-based mathematical model ecosys to study effects of seasonal variation in WTD on net ecosystem productivity (NEP) of a drainage affected tropical peat swamp forest at Palangkaraya, Indonesia. Simulated NEP suggested that the peatland was a C source (NEP ~ −2 g C m−2 d−1, where a negative sign represents a C source and a positive sign a C sink) during rainy seasons with shallow WTD, C neutral or a small sink (NEP ~ +1 g C m−2 d−1) during early dry seasons with intermediate WTD and a substantial C source (NEP ~ −4 g C m−2 d−1) during late dry seasons with deep WTD from 2002 to 2005. These values were corroborated by regressions (P < 0.0001) of hourly modelled vs. eddy covariance (EC) net ecosystem CO2 fluxes which yielded R2 > 0.8, intercepts approaching 0 and slopes approaching 1. We also simulated a gradual increase in annual NEP from 2002 (−609 g C m−2) to 2005 (−373 g C m−2) with decreasing WTD which was attributed to declines in duration and intensity of dry seasons following the El Niño event of 2002. This increase in modelled NEP was corroborated by EC-gap filled annual NEP estimates. Our modelling hypotheses suggested that (1) poor aeration in wet soils during shallow WTD caused slow nutrient (predominantly phosphorus) mineralization and consequent slow plant nutrient uptake that suppressed gross primary productivity (GPP) and hence NEP (2) better soil aeration during intermediate WTD enhanced nutrient mineralization and hence plant nutrient uptake, GPP and NEP and (3) deep WTD suppressed NEP through a combination of reduced GPP due to plant water stress and increased ecosystem respiration (Re) from enhanced deeper peat aeration. These WTD effects on NEP were modelled from basic eco-hydrological processes including microbial and root oxidation-reduction reactions driven by soil and root O2 transport and uptake which in turn drove soil and plant carbon, nitrogen and phosphorus transformations within a soil-plant-atmosphere water transfer scheme driven by water potential gradients. Including these processes in ecosystem models should therefore provide an improved predictive capacity for WTD management programs intended to reduce tropical peat degradation.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 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 ».