Model-based conservation planning of the genetic diversity of Phellodendron amurense Rupr due to climate change

被引:22
作者
Wan, Jizhong [1 ]
Wang, Chunjing [1 ]
Yu, Jinghua [1 ]
Nie, Siming [1 ]
Han, Shijie [2 ]
Zu, Yuangang [1 ]
Chen, Changmei [1 ]
Yuan, Shusheng [1 ]
Wang, Qinggui [3 ]
机构
[1] Northeast Forestry Univ, State Engn Lab Bioresource Ecoutilizat Heilongjia, Haerbin, Heilongjiang, Peoples R China
[2] Chinese Acad Sci, Inst Appl Ecol, Shenyang, Liaoning, Peoples R China
[3] Heilongjiang Univ, Coll Agr Resource & Environm, Haerbin, Heilongjiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Climate change; conservation areas; genetic diversity; Maxent; northeast China; Zonation; SPECIES DISTRIBUTION MODELS; BIODIVERSITY; FUTURE; CONSEQUENCES; REINTRODUCTION; PRIORITIZATION; POPULATIONS; ABUNDANCE; FITNESS; MAXENT;
D O I
10.1002/ece3.1133
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Climate change affects both habitat suitability and the genetic diversity of wild plants. Therefore, predicting and establishing the most effective and coherent conservation areas is essential for the conservation of genetic diversity in response to climate change. This is because genetic variance is a product not only of habitat suitability in conservation areas but also of efficient protection and management. Phellodendron amurense Rupr. is a tree species (family Rutaceae) that is endangered due to excessive and illegal harvesting for use in Chinese medicine. Here, we test a general computational method for the prediction of priority conservation areas (PCAs) by measuring the genetic diversity of P. amurense across the entirety of northeast China using a single strand repeat analysis of twenty microsatellite markers. Using computational modeling, we evaluated the geographical distribution of the species, both now and in different future climate change scenarios. Different populations were analyzed according to genetic diversity, and PCAs were identified using a spatial conservation prioritization framework. These conservation areas were optimized to account for the geographical distribution of P. amurense both now and in the future, to effectively promote gene flow, and to have a long period of validity. In situ and ex situ conservation, strategies for vulnerable populations were proposed. Three populations with low genetic diversity are predicted to be negatively affected by climate change, making conservation of genetic diversity challenging due to decreasing habitat suitability. Habitat suitability was important for the assessment of genetic variability in existing nature reserves, which were found to be much smaller than the proposed PCAs. Finally, a simple set of conservation measures was established through modeling. This combined molecular and computational ecology approach provides a framework for planning the protection of species endangered by climate change.
引用
收藏
页码:2884 / 2900
页数:17
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