4.7 Article

Modeling the effects of climate change on the distribution of Tagetes lucida Cav. (Asteraceae)

期刊

GLOBAL ECOLOGY AND CONSERVATION
卷 20, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.gecco.2019.e00747

关键词

Pericon; Species distribution model; MaxEnt; Land use change

资金

  1. Step2 USDA Grant (University of Texas Rio Grande Valley 2018)
  2. USDA AFRI National Institute of Food and Agriculture program Training the next generation of agricultural scientists: coping with food security and climatic change challenges [2015-38422-24061]

向作者/读者索取更多资源

Climate change threatens the future distributions of native, tropical species all around the world as increasing global temperature and, in several regions decreasing precipitation cause less suitable habitat to become available. Of particular interest in this paper is to construct a model of the potential impact of climate change on the distribution of the Pericion or Mexican Mint Marigold, Tagetes lucida, a native medicinal plant of important cultural and economic value in Mexico. We projected the future distribution of this species using the maximum entropy algorithm (MaxEnt) and five bioclimatic variables. Models were created using three global circulation models (CM3, CMIP5, HADGEM) in the years 2050 and 2070 and using two climate change scenarios (RCP 4.5 and RCP 8.5). The final model had an AUC = 0.92 and pROC = 1.645, indicating statistically significant results. These future distributions were compared to a current vegetation and land use map of Mexico. Our results predicted that under future climate change scenarios, less suitable habitat will become available, causing the range of Tagetes lucida to contract and shift northward. Current suitable habitat is threatened by agriculture, deforestation, and overgrazing, leading to habitat fragmentation and potentially creating a barrier to northern dispersal. (c) 2019 The Authors. Published by Elsevier B.V.

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