Multi‐scaled drivers of rural prairie stream metabolism along human activity gradients
Notice bibliographique
Résumé
Summary 1. Stream metabolism is increasingly used for monitoring and assessment of the biological condition of aquatic ecosystems. However, distal environmental drivers, such as land use, are typically not well connected to the proximate controls, such as stream chemistry, that are usually invoked as driving metabolism. This is particularly true for North American prairie streams and for grassland streams worldwide. 2. Stream metabolism was measured at the outflow of 19 subcatchments of the Red River in southern Manitoba, Canada. Subcatchments represented gradients of nutrient‐producing human activities present in the region, that is, wastewater treatment (WWT), livestock production and crop cultivation. Stream metabolism was estimated at all sites using diel changes in dissolved oxygen (DO) concentration over 1 week in the middle of summer. Environmental parameters hypothesised to control stream metabolism were sampled across three spatial scales (stream reach, stream segment and catchment). Model selection using Akaike’s information criterion (AIC) was used to determine linkages between environmental parameters and measures of stream metabolism. 3. Estimated rates of metabolism were within the range of past studies of metabolism in prairie streams, although most streams had negative values of net ecosystem metabolism. However, production‐to‐respiration ratios were >0.5, at all but three sites suggesting that autochthonous production was an important source of organic matter. 4. The a priori model that best predicted gross primary production (GPP) was the intensity of nutrient‐producing human activities (i.e. WWT, livestock and crop cultivation) measured at the catchment scale. Ecosystem respiration (ER) was best predicted by the a priori model comprised of GPP, total nitrogen (TN) and total phosphorus (TP). However, model averaging revealed that prediction of ER could be improved by including riparian cover and removing TP from the model. The positive association between GPP and ER suggested that heterotrophic compartments of the ecosystem were modest contributors to variation in respiration rates. 5. Overall, this study suggests that variation of metabolism in prairie streams of southern Manitoba is controlled by human activities occurring at the catchment scale, a finding consistent with current hierarchically structured riverine paradigms. Moreover, increased understanding of the hierarchical structure of stream metabolism drivers will help to ensure that assessment results can be used more effectively to inform management strategies for prairie ecosystems.
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 ».