4.7 Article

From beef cattle to sheep under global warming? An analysis of adaptation by livestock species choice in South America

期刊

ECOLOGICAL ECONOMICS
卷 69, 期 12, 页码 2486-2494

出版社

ELSEVIER
DOI: 10.1016/j.ecolecon.2010.07.025

关键词

Climate change; Climate variability; Adaptation; Livestock species choice; South America

资金

  1. World Bank

向作者/读者索取更多资源

This paper examines how South American farmers' choices of livestock species vary across the range of climate and in turn infer from them as to what would happen under climate changes. We examine the choice of five primary species using a multinomial logit model with and without climate variability measures based on 1300 livestock farm surveys in seven countries. The results indicate that climate variables are highly significant determinants of primary species choice after controlling for soils, geography, household characteristics, and country fixed effects. We find the probability of adopting any livestock increases with warming, but decreases when it becomes too wet. The impacts of climate change would vary by species and climate scenarios. For example, under a hot and dry CCC scenario by 2060, beef cattle decrease by 3.2%, dairy cattle by 2.3%, pigs by 0.5%, and chickens by 0.9%, which is offset by a large increase in sheep by 7%. These adaptive changes vary again by country. Large changes are observed in the Andean countries. Under the hot dry scenario, daily cattle increase in Uruguay and Argentina, but decrease elsewhere. The increase in sheep occurs mostly in the Andes mountain countries such as Chile, Colombia, Ecuador, and Venezuela. Under a milder and wetter scenario, beef cattle choice declines in Colombia. Ecuador, and Venezuela, but increases in Argentina and Chile. Sheep increase in Colombia and Venezuela, but decrease in the high mountains of Chile where chickens are chosen more frequently. (C) 2010 Elsevier B.V. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据