White D H, Lubulwa G A, Menz K, Zuo H, Wint W, Slingenbergh J
ASIT Consulting, Hawker, ACT, Australia.
Environ Int. 2001 Sep;27(2-3):181-7. doi: 10.1016/s0160-4120(01)00080-0.
Investment in agricultural research in developing countries is being increasingly targeted at those agro-climatic zones and issues where the economic and environmental benefits may be expected to be greatest. This first requires that the zones themselves be defined, along with information on domestic livestock numbers and commodity output within agro-climatic zones in different countries. Different methods for classifying agro-climatic zones were compared. These included methods based on estimated length of growing period (LGP) using rainfall and temperature data, the ratio of precipitation to potential evapotranspiration (PET), and on more detailed agronomic models, remote sensing data and land use information. Zonation based on LGP has already been linked to existing national livestock data. By defining agro-climatic zones and relating concentrations of livestock populations to those of humans, it is possible to make realistic estimates of livestock populations and the production of livestock commodities for most developing countries. Detailed agro-climatic analyses of Mainland East Asia and Sri Lanka have recently been undertaken using the GROWEST agronomic model. Using this model as the basis of agro-climatic classification appears to be significantly superior, particularly in temperate environments, to approaches based solely on LGP. Different ways of subdividing countries and continents into agro-climatic or agro-ecological zones (AEZs) are reviewed in this paper. In addition, we show how the numbers of production and commodities from domestic livestock can be allocated to such zones. We also indicate how some of this information can be applied.
发展中国家对农业研究的投资越来越多地针对那些预计经济和环境效益最大的农业气候区及相关问题。这首先需要界定这些区域，以及不同国家农业气候区内家畜数量和商品产量的信息。对划分农业气候区的不同方法进行了比较。这些方法包括基于利用降雨和温度数据估算生长周期长度（LGP）的方法、降水与潜在蒸散量（PET）的比率，以及更详细的农艺模型、遥感数据和土地利用信息。基于LGP的分区已经与现有的国家家畜数据相关联。通过界定农业气候区，并将牲畜种群的集中情况与人类的集中情况联系起来，有可能对大多数发展中国家的牲畜种群和牲畜商品产量做出实际估计。最近利用GROWEST农艺模型对东亚大陆和斯里兰卡进行了详细的农业气候分析。以该模型作为农业气候分类的基础似乎明显优于仅基于LGP的方法，尤其是在温带环境中。本文回顾了将国家和大陆划分为农业气候区或农业生态区（AEZ）的不同方法。此外，我们展示了如何将国内家畜的生产数量和商品分配到这些区域。我们还指出了其中一些信息的应用方式。
