Estimating livestock diets in support of improved estimation of greenhouse gas emissions for the livestock sector: a case study in East Africa

该项目将利用地球观测数据和当地实地调查数据，改进对东非牲畜饮食的估计，以支持对畜牧业绿色温室气体排放量进行更可靠的估计。畜牧业是温室气体排放的一个主要来源，但其贡献程度存在争议。目前的数字在很大程度上依赖于对牲畜生产力和饮食组成的准确估计，这些估计是不确定的。例如，粮农组织的全球牲畜环境评估模型（GLEAM）使用GAEZ的作物分布和产量数据，结合按系统和国家估计的饲料篮子，主要来自“专家意见”。除了成分的不确定性，GLEAM目前无法解释饲料供应的季节性。提高饲料篮估计的准确性和季节性的考虑将大大提高模型的能力，以提供畜牧业，特别是中低收入国家的温室气体排放的现实估计，并更好地估计不同干预措施的缓解潜力。

This project will use earth observation data combined with local ground truth from surveys to improve estimates of livestock diets in East Africa to support more robust estimates of Green House Gas (GHG) emissions from the livestock sector. Livestock are a key source of GHG emissions but the extent of their contribution is contested. Current numbers rely heavily on accurate estimates of livestock productivity and diet composition and these estimates are uncertain. For example, the FAO Global Livestock Environmental Assessment Model (GLEAM) uses crop distribution and yield data from GAEZ, in combination with feed baskets estimated by system and country, mostly derived from 'expert opinion'. As well as uncertainty in composition, GLEAM is currently unable to account for seasonality in feed availability. Improvement of the accuracy of feed basket estimation and accounting for seasonality would significantly enhance the ability of the model to provide realistic estimates of GHG emissions from the livestock sector, particularly in LMICs, and to better estimate the mitigation potential of different interventions.