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

该项目将使用地球观测数据，结合当地实地调查的真实情况，改进东非牲畜饲料的估计，以支持对畜牧业温室气体(GHG)排放量的更可靠估计。畜牧业是温室气体排放的主要来源，但它们的贡献程度存在争议。目前的数字在很大程度上依赖于对牲畜生产力和饮食构成的准确估计，而这些估计是不确定的。例如，粮农组织全球牲畜环境评估模型(GLEAM)使用来自GAEZ的作物分布和产量数据，以及按系统和国家估计的饲料篮数，主要来自“专家意见”。除了成分上的不确定性，Gleam目前还无法解释饲料供应的季节性。提高饲料篮估计的准确性并考虑季节性，将大大增强该模型提供畜牧业温室气体排放量的现实估计数的能力，特别是在低中等收入国家，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.