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Maximum Entropy Modeling the Distribution Area of Morchella Dill. ex Pers. Species in China under Changing Climate

SIMPLE SUMMARY: Climate change has always been a noticeable factor in the research of species distribution. In recent decades, the habitats of species have been gradually destroyed due to the changing climate. Thus, in order to predict how climate change will influence the survival and suitable habi...

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Autores principales: Cao, Yu-Ting, Lu, Zhao-Ping, Gao, Xin-Yu, Liu, Mi-Li, Sa, Wei, Liang, Jian, Wang, Le, Yin, Wei, Shang, Qian-Han, Li, Zhong-Hu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9312065/
https://www.ncbi.nlm.nih.gov/pubmed/36101408
http://dx.doi.org/10.3390/biology11071027
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author Cao, Yu-Ting
Lu, Zhao-Ping
Gao, Xin-Yu
Liu, Mi-Li
Sa, Wei
Liang, Jian
Wang, Le
Yin, Wei
Shang, Qian-Han
Li, Zhong-Hu
author_facet Cao, Yu-Ting
Lu, Zhao-Ping
Gao, Xin-Yu
Liu, Mi-Li
Sa, Wei
Liang, Jian
Wang, Le
Yin, Wei
Shang, Qian-Han
Li, Zhong-Hu
author_sort Cao, Yu-Ting
collection PubMed
description SIMPLE SUMMARY: Climate change has always been a noticeable factor in the research of species distribution. In recent decades, the habitats of species have been gradually destroyed due to the changing climate. Thus, in order to predict how climate change will influence the survival and suitable habitats of wild Morchella Dill. ex Pers. species in China, we used a maximum entropy model to simulate the changes in its distribution area from historical periods to future periods. Our results illustrate that precipitation, elevation and temperature are indispensable factors affecting the presence and suitable habitats of wild Morchella species. Furthermore, this research showed us a promising trend that, regardless of which scenario, the suitable area of the species will increase to a certain scale in the near future. Based on these findings, we could explore and design an optimal scheme for the conservation of wild Morchella resources. ABSTRACT: Morchella is a kind of precious edible, medicinal fungi with a series of important effects, including anti-tumor and anti-oxidation effects. Based on the data of 18 environmental variables and the distribution sites of wild Morchella species, this study used a maximum entropy (MaxEnt) model to predict the changes in the geographic distribution of Morchella species in different historical periods (the Last Glacial Maximum (LGM), Mid Holocene (MH), current, 2050s and 2070s). The results revealed that the area under the curve (AUC) values of the receiver operating characteristic curves of different periods were all relatively high (>0.83), indicating that the results of the maximum entropy model are good. Species distribution modeling showed that the major factors influencing the geographical distribution of Morchella species were the precipitation of the driest quarter (Bio17), elevation, the mean temperature of the coldest quarter (Bio11) and the annual mean temperature (Bio1). The simulation of geographic distribution suggested that the current suitable habitat of Morchella was mainly located in Yunnan, Sichuan, Gansu, Shaanxi, Xinjiang Uygur Autonomous Region (XUAR) and other provinces in China. Compared with current times, the suitable area in Northwest and Northeast China decreased in the LGM and MH periods. As for the future periods, the suitable habitats all increased under the different scenarios compared with those in contemporary times, showing a trend of expansion to Northeast and Northwest China. These results could provide a theoretical basis for the protection, rational exploitation and utilization of wild Morchella resources under scenarios of climate change.
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spelling pubmed-93120652022-07-26 Maximum Entropy Modeling the Distribution Area of Morchella Dill. ex Pers. Species in China under Changing Climate Cao, Yu-Ting Lu, Zhao-Ping Gao, Xin-Yu Liu, Mi-Li Sa, Wei Liang, Jian Wang, Le Yin, Wei Shang, Qian-Han Li, Zhong-Hu Biology (Basel) Article SIMPLE SUMMARY: Climate change has always been a noticeable factor in the research of species distribution. In recent decades, the habitats of species have been gradually destroyed due to the changing climate. Thus, in order to predict how climate change will influence the survival and suitable habitats of wild Morchella Dill. ex Pers. species in China, we used a maximum entropy model to simulate the changes in its distribution area from historical periods to future periods. Our results illustrate that precipitation, elevation and temperature are indispensable factors affecting the presence and suitable habitats of wild Morchella species. Furthermore, this research showed us a promising trend that, regardless of which scenario, the suitable area of the species will increase to a certain scale in the near future. Based on these findings, we could explore and design an optimal scheme for the conservation of wild Morchella resources. ABSTRACT: Morchella is a kind of precious edible, medicinal fungi with a series of important effects, including anti-tumor and anti-oxidation effects. Based on the data of 18 environmental variables and the distribution sites of wild Morchella species, this study used a maximum entropy (MaxEnt) model to predict the changes in the geographic distribution of Morchella species in different historical periods (the Last Glacial Maximum (LGM), Mid Holocene (MH), current, 2050s and 2070s). The results revealed that the area under the curve (AUC) values of the receiver operating characteristic curves of different periods were all relatively high (>0.83), indicating that the results of the maximum entropy model are good. Species distribution modeling showed that the major factors influencing the geographical distribution of Morchella species were the precipitation of the driest quarter (Bio17), elevation, the mean temperature of the coldest quarter (Bio11) and the annual mean temperature (Bio1). The simulation of geographic distribution suggested that the current suitable habitat of Morchella was mainly located in Yunnan, Sichuan, Gansu, Shaanxi, Xinjiang Uygur Autonomous Region (XUAR) and other provinces in China. Compared with current times, the suitable area in Northwest and Northeast China decreased in the LGM and MH periods. As for the future periods, the suitable habitats all increased under the different scenarios compared with those in contemporary times, showing a trend of expansion to Northeast and Northwest China. These results could provide a theoretical basis for the protection, rational exploitation and utilization of wild Morchella resources under scenarios of climate change. MDPI 2022-07-08 /pmc/articles/PMC9312065/ /pubmed/36101408 http://dx.doi.org/10.3390/biology11071027 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cao, Yu-Ting
Lu, Zhao-Ping
Gao, Xin-Yu
Liu, Mi-Li
Sa, Wei
Liang, Jian
Wang, Le
Yin, Wei
Shang, Qian-Han
Li, Zhong-Hu
Maximum Entropy Modeling the Distribution Area of Morchella Dill. ex Pers. Species in China under Changing Climate
title Maximum Entropy Modeling the Distribution Area of Morchella Dill. ex Pers. Species in China under Changing Climate
title_full Maximum Entropy Modeling the Distribution Area of Morchella Dill. ex Pers. Species in China under Changing Climate
title_fullStr Maximum Entropy Modeling the Distribution Area of Morchella Dill. ex Pers. Species in China under Changing Climate
title_full_unstemmed Maximum Entropy Modeling the Distribution Area of Morchella Dill. ex Pers. Species in China under Changing Climate
title_short Maximum Entropy Modeling the Distribution Area of Morchella Dill. ex Pers. Species in China under Changing Climate
title_sort maximum entropy modeling the distribution area of morchella dill. ex pers. species in china under changing climate
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9312065/
https://www.ncbi.nlm.nih.gov/pubmed/36101408
http://dx.doi.org/10.3390/biology11071027
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