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Enregistrement W3047193266

Biodiversity - 2015: Manure usage in restoration of degraded crop land

2015· article· en· W3047193266 sur OpenAlexaboutno aff
Maysoon M. Mikha

Notice bibliographique

RevueJournal of Biodiversity & Endangered Species · 2015
Typearticle
Langueen
DomaineEarth and Planetary Sciences
ThématiqueAeolian processes and effects
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésLand degradationSoil retrogression and degradationAgroforestryEnvironmental scienceEnvironmental degradationDesertificationAridDeforestation (computer science)AgricultureGeographySoil waterEcologySoil scienceBiology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In the Great Plains of North America, soil degradation particularly by wind erosion became a problem in the late 18th and early 19th century soon after agriculture expanded to the semi-arid region and the land was broken from sod. Soil degradation is a consequence of anthropogenic activity and environmental disturbances that cause alteration in many aspects of soil properties and infl uence crop productivity. Zika and Erb (2009) estimated that annual dryland degradation could reduce global terrestrial net primary productivity by approximately 2%. Th e 2012 United Nation Convention to Combat Desertifi cation stated that the high susceptibility of dryland soils to degradation as a consequence of water defi ciency and drought conditions could infl uence global sustainability and food security (UNCCD, 2012). Furthermore, by 2030 as the world demand for food, energy, and water is anticipated to increase by 50, 45, and 30%, respectively; this requires more land and likely resulting in more land deforestation and ecological degradation (UNCCD, 2012). In the Great Plains of North America, soil degradation, particularly by wind erosion, became a problem in the late 18th and early 19th century soon aft er agriculture expanded to the semiarid region and the land was broken from sod (Stewart, 2004). Th e risk of soil degradation by erosion remained through most of the 20th century. Following World War I, large expanses of the Great Plains suff ered from wind erosion due to the expansion of cultivated land, moldboard plowing, and disking operations (Li et al., 2007) and wheat–fallow cropping systems (Janzen, 2001; Stewart, 2004). Consequently, some farmlands in the Great Plains Region lost their economical activity as a result of losing topsoil, rich with organic materials, to erosion induced by tillage and over-cultivation (Tanaka and Aase, 1989; Stewart, 2004). Topsoil thickness is one of the essential factors in evaluating soil quality and plant productivity (Izaurralde et al., 2006). Th e unique characteristics of topsoil positively influenced nutrient storage and cycling, water and energy transfer, and crop yield. Losing topsoil through erosion decreases the soil organic matter (SOM) pool and negatively infl uences soil properties, which reduce crop productivity (Tanaka and Aase, 1989; Stewart, 2004; Larney and Angers, 2012). The addition of organic amendment was found to not only increase SOM but also may decrease soil bulk density, increase soil hydraulic properties, and improve soil aggregation (Arriaga and Lowery, 2003; Mikha and Rice 2004). Furthermore, many years of organic amendment additions may infl uence soil Agronomy chemical properties and nutrient dynamics. Diacono and Montemurro (2010) reported that long-lasting applications of organic amendments can enhance soil organic carbon (SOC), available K, and extractable P. Annual solid feedlot manure applications over an 11-yr period in Alberta, Canada, increased soil chemical parameters, such as SOM, available P and N, electrical conductivity (EC), and sodium absorption ratio and decreased surface soil pH as the manure application rates increased (Chang et al., 1991). Soil pH decreased 0.3 to 0.7 units more in the surface 0- to 15-cm depth compared with deeper depths. On the other hand, manure additions increased soil pH in the surface 15cm compared with ammonium nitrate (NH4NO3) additions, which was attributed to the basic cations added by the manure (Eghball, 2002).Therefore, some farmlands lost top soil rich with organic materials and plant nutrients and consequently decrease their economic value. This study evaluates land productivity and changes in soil properties of eroded land influenced by (1) nitrogen types (manure vs. commercial fertilizer); (2) nitrogen rates (high vs. low) and (3) tillage practices (no-tillage vs. conventional tillage). Two eroded sites were chosen in central Great Plain Region, one site in Akron, CO with topsoil loss of approximately 17 to 20 cm and the second site located in Hays, KS with topsoil loss of approximately 25 cm. The Akron site was established in 2007 and the Hays site was established in 2006. The annual manure application range between 11 to 15 Mg manure per ha for the low N rate and approximately 22 to 30 Mg manure per ha for the high N rate. Throughout the first 5 years of the study period, weather patron specifically the precipitations affected the yield. The amount of rain and its distribution throughout the growing seasons and during the crop critical period in addition to the ambient temperature explained some yield response to the treatments. The least limiting Water Range (LLWR) was influenced by manure addition. The relationship between the LLWR and crop yields was stronger in Hays site than in Akron site. In Hays site, annual manure addition significantly altered soil chemical properties compared with commercial fertilizer especially at the top 15 cm. Soil organic C and changes in soil organic C were greatly influenced by manure addition. Soil inorganic N leaching was also detected during the winter months. Overall, the addition of organic amendments restored the productivity of eroded soil and improved some aspects of soil quality compared with commercial fertilizer. Apparently, more than 5 years are required to assess the treatment benefits on soil quality and productivity in such eroded land.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,031
Score d'incertitude au seuil0,414

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,042
Tête enseignante GPT0,223
Écart entre enseignants0,181 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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Même revueJournal of Biodiversity & Endangered SpeciesMême sujetAeolian processes and effectsTravaux en français237 207