Nitrous oxide and methane emissions from cattle manure heaps in Kenya
Notice bibliographique
Résumé
Agricultural greenhouse gas (GHG) emissions in Africa contribute 15 % to the global total agricultural emissions, which is in the same range as agricultural emissions from Europe. The majority of these agricultural GHG emissions is attributed to livestock farming (up to 80 % at national scale), of which 10-25 % originate from livestock manure. At the same time, livestock production is essential for the livelihoods of millions of people in Sub-Saharan Africa (SSA), where 45-80 % of livestock production occurs in smallholder systems. With the growing population in SSA, the demand for livestock products is expected to increase, and – without low-emission manure management – a rise in manure-borne GHG emissions will occur. However, reliable in situ measurements from SSA are scarce, leading to substantial uncertainties in agricultural GHG budgets and making assessments of potential mitigation options difficult. Here we present results from two cattle manure incubation experiments in Kenya, using manure from Boran (Bos indicus) cattle, a breed common in East Africa that were fed with typical feeds used in SSA smallholder farms. Manure was collected and piled in heaps (solid storage), the most common form of manure storage in Kenyan smallholder systems, and CH4 and N2O emissions were measured over 140 days. In the first trial, cattle were fed a diet that either met their maintenance-energy requirements (i.e. animals received enough food to support their metabolism), or a diet at sub-maintenance energy levels to simulate common conditions in smallholder farming systems, particularly during the dry seasons. Cumulative manure N2O emissions from the sub-maintenance diet (i.e. the “hungry” cows) were lower than from cattle fed at maintenance energy levels. These lower N2O emission likely resulted from lower N concentration and a wider C:N ratio in the manure than in the “better fed” animals. Furthermore, the urine-N:faecal-N ratio in the “hungry” cows decreased, indicating a shift from urine-N (mostly inorganic N) to faecal-N (mostly organic N), which further backs the lower observed N2O emissions. Both N2O as well as CH4 emissions from manure were lower than the IPCC default emission factors for solid storage in tropical regions across all diets tested. In the second trial, Boran cattle were fed with three different tropical forage grasses common in Kenya: Napier (Pennisetum purpureum), Rhodes (Gloris gayana), and Brachiaria (Brachiaria brizantha). Manure from the Rhodes grass diet had the lowest N concentration and also the lowest cumulative CH4 emissions, while N2O emissions did not differ between diets. Similar to the sub-maintenance feeding trial, total CH4 and N2O emissions were lower than the IPCC default factors. Taken together, these results are an important step towards reducing the uncertainties in GHG emissions from agriculture in SSA. Furthermore, if African nations use IPCC default values for their national GHG reporting on livestock, emissions are likely to be overestimated, highlighting the importance and benefits of localized data from Africa.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».