Livestock grazing and vegetative filter strip buffer effects on runoff sediment, nitrate, and phosphorus losses
Notice bibliographique
Résumé
Livestock grazing in the Midwestern United States can result in significant levels of runoff sediment and nutrient losses to surface water resources. Some of these contaminants can increase stream eutrophication and are suspected of contributing to hypoxic conditions in the Gulf of Mexico. This research quantified effects of livestock grazing management practices and vegetative filter strip buffers on runoff depth and mass losses of total solids, nitrate-nitrogen (NO<sub>3</sub>-N), and ortho-phosphorus (PO<sub>4</sub>-P) under natural hydrologic conditions. Runoff data were collected from 12 rainfall events during 2001 to 2003 at an Iowa State University research farm in central Iowa, United States. Three vegetative buffers (paddock area:vegetative buffer area ratios of 1:0.2, 1:0.1, and 1:0 no buffer [control]) and three grazing management practices (continuous, rotational, and no grazing [control]) comprised nine treatment combinations (vegetative buffer ratio/grazing management practice) replicated in three 1.35 ha (3.34 ac) plot areas. The total 4.05 ha (10.02 ac) study area also included nine 0.4 ha (1.0 ac) paddocks and 27 vegetative buffer runoff collection units distributed in a randomized complete block design. The study site was established on uneven terrain with a maximum of 15% slopes and consisted of approximately 100% cool-season smooth bromegrass. Average paddock and vegetative buffer plant tiller densities estimated during the 2003 project season were approximately 62 million and 93 million tillers ha<sup>−1</sup> (153 million and 230 million tillers ac<sup>−1</sup>), respectively. Runoff sample collection pipe leakage discovered and corrected during 2001 possibly reduced runoff depth and affected runoff contaminant mass losses data values. Consequently, 2001 runoff analysis results were limited to treatment comparisons within the 2001 season and were not compared with 2002 and 2003 data. Analysis results from 2001 showed no significant differences in average losses of runoff, total solids, NO<sub>3</sub>-N, and PO<sub>4</sub>-P among the nine vegetative buffer/grazing practice treatment combinations. Results from 2002 indicated significantly higher losses of runoff and total solids from 1:0 no buffer/rotational grazing and 1:0 no buffer/continuous grazing treatment combination plots, respectively, compared among other 2002 season treatment combinations. The 2003 results showed significantly higher runoff and total solids losses from 1:0 no buffer/no grazing treatment combination plots compared among all 2003 treatment combinations and from 1:0.1 vegetative buffer/no grazing treatment combination plots compared among all 2003 treatment combinations and with respective 2002 treatment combinations. However, the 2003 results indicated effective vegetative buffer performance with significantly lower runoff, total solids, and NO<sub>3</sub>-N losses from the larger 1:0.2 buffer area compared among the smaller 1:0.1 buffer area and 1:0 no buffer treatment combinations. The 2003 results also indicated a highly significant increase in losses of NO<sub>3</sub>-N from 1:0.1 buffer/no grazing treatment combination plots compared among other 2003 season treatment combinations and with respective 2002 treatment combinations. Overall results from this study suggest a shift from significantly higher 2002 season plot losses of continuous and rotational grazing treatment combinations to significantly higher 2003 season losses of no grazing treatment combinations. We speculate this shift to significantly higher runoff and contaminant losses from no grazing treatment combination plots during 2003 reflects the variability inherent to a complex and dynamic soil-water environment of livestock grazing areas. However, we also hypothesize the environmental conditions that largely consisted of a dense perennial cool-season grass type, high-relief landscape, and relatively high total rainfall depth may not necessarily include livestock grazing activities.
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 ».