Predicting the impact of climate change on the distribution of two relict Liriodendron species by coupling the MaxEnt model and actual physiological indicators in relation to stress tolerance.

Climate change Conservation Habitat shift and loss L. tulipifera Liriodendron chinense Physiological assessment

Journal

Journal of environmental management
ISSN: 1095-8630
Titre abrégé: J Environ Manage
Pays: England
ID NLM: 0401664

Informations de publication

Date de publication:
15 Nov 2022
Historique:
received: 12 05 2022
revised: 19 07 2022
accepted: 13 08 2022
pubmed: 3 9 2022
medline: 6 10 2022
entrez: 2 9 2022
Statut: ppublish

Résumé

Climate change has a crucial impact on the distributions of plants, especially relict species. Hence, predicting the potential impact of climate change on the distributions of relict plants is critical for their future conservation. Liriodendron plants are relict trees, and only two natural species have survived: L. chinense and L. tulipifera. However, the extent of the impact of future climate change on the distributions of these two Liriodendron species remains unclear. Therefore, we predicted the suitable habitat distributions of two Liriodendron species under present and future climate scenarios using MaxEnt modeling. The results showed that the area of suitable habitats for two Liriodendron species would significantly decrease. However, the two relict species presented different habitat shift patterns, with a local contraction of suitable habitat for L. chinense and a northward shift in suitable habitat for L. tulipifera, indicating that changes in environmental factors will affect the distributions of these species. Among the environmental factors assessed, May precipitation induced the largest impact on the L. chinense distribution, while L. tulipifera was significantly affected by precipitation in the driest quarter. Furthermore, to explore the relationship between habitat suitability and Liriodendron stress tolerance, we analyzed six physiological indicators of stress tolerance by sampling twelve provenances of L. chinense and five provenances of L. tulipifera. The composite index of six physiological indicators was significantly negatively correlated with the habitat suitability of the species. The stress tolerance of Liriodendron plants in highly suitable areas was lower than that in areas with moderate or low suitability. Overall, these findings improve our understanding of the ecological impacts of climate change, informing future conservation efforts for Liriodendron species.

Identifiants

pubmed: 36055092
pii: S0301-4797(22)01597-3
doi: 10.1016/j.jenvman.2022.116024
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

116024

Informations de copyright

Copyright © 2022 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Yufang Shen (Y)

Key Laboratory of Forest Genetics and Biotechnology of Ministry of Education, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China; College of Forestry, Nanjing Forestry University, Nanjing, 210037, China. Electronic address: shenyufang7045@163.com.

Zhonghua Tu (Z)

Key Laboratory of Forest Genetics and Biotechnology of Ministry of Education, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China; College of Forestry, Nanjing Forestry University, Nanjing, 210037, China. Electronic address: zhonghuatu@njfu.edu.cn.

Yali Zhang (Y)

College of Forestry, Nanjing Forestry University, Nanjing, 210037, China. Electronic address: zyl930624@163.com.

Weiping Zhong (W)

Key Laboratory of Forest Genetics and Biotechnology of Ministry of Education, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China; College of Forestry, Nanjing Forestry University, Nanjing, 210037, China. Electronic address: wiiping@163.com.

Hui Xia (H)

Key Laboratory of Forest Genetics and Biotechnology of Ministry of Education, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China; College of Forestry, Nanjing Forestry University, Nanjing, 210037, China. Electronic address: xiahui625649@163.com.

Ziyuan Hao (Z)

Key Laboratory of Forest Genetics and Biotechnology of Ministry of Education, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China; College of Forestry, Nanjing Forestry University, Nanjing, 210037, China. Electronic address: lxhzy1992@163.com.

Chengge Zhang (C)

Key Laboratory of Forest Genetics and Biotechnology of Ministry of Education, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China; College of Forestry, Nanjing Forestry University, Nanjing, 210037, China. Electronic address: cgzhang@njfu.edu.cn.

Huogen Li (H)

Key Laboratory of Forest Genetics and Biotechnology of Ministry of Education, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, 210037, China; College of Forestry, Nanjing Forestry University, Nanjing, 210037, China. Electronic address: hgli@njfu.edu.cn.

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