Nutrients and defoliation increase soil carbon inputs in grassland
Notice bibliographique
Résumé
Given the regulatory impact of resources and consumers on plant production, decomposition, and soil carbon sequestration, anthropogenic changes to nutrient inputs and grazing have likely transformed how grasslands process atmospheric CO2. The direction and magnitude of these changes, however, remain unclear in this system, whose soils contain -20% of the world's carbon pool. Nutrients stimulate production but can also increase tissue palatability and decomposition. Grazing variously affects tissue quality and quantity, decreasing, standing biomass, but potentially increasing leaf nutrient concentrations, root production, or investment in tissue defenses that slow litter decay. Here, we quantified individual and interactive impacts of nutrient addition and simulated grazing (mowing) on above- and belowground production, tissue quality, and soil carbon inputs in a western North American grassland with globally distributed agronomic species. Given that nutrients and grazing are often connected with increased root production and higher foliar tissue quality, we hypothesized that these treatments would combine to reduce inputs of recalcitrant-rich litter critical for C storage. This hypothesis was unsupported. Nutrients and defoliation combined to significantly increase belowground production but did not affect root tissue quality. There were no significant interactions between nutrients and defoliation for any measured response. Three years of nutrient addition increased root and shoot biomass by 37% and 23%, respectively, and had no impact on decomposition, resulting in a -15% increase in soil organic matter and soil carbon. Defoliation triggered a significant burst of short-lived lignin-rich roots, presumably a compensatory response to foliar loss, which increased root litter inputs by 33%. The majority of root and shoot responses were positively correlated, with aboveground biomass a reasonable proxy for whole plant responses. The exceptions were decomposition, with roots six times more decay resistant, and grazing impacts on tissue chemistry, with shoots undergoing significant alterations, while roots were unaffected. Because neither treatment affected concentrations of decay-resistant compounds in roots, the implied net effect is higher soil C inputs with potentially longer residency times. Areas managed with nutrients and moderate grazing in our study system could thus accumulate significantly more soil C than unmanaged areas, with a greater capacity to serve as sinks for atmospheric CO2.
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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 ».