Cargando…
Identifying the natural reserve area of Cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in Xinjiang, China
Cistanche salsa (C. A. Mey.) G. Beck, a holoparasitic desert medicine plant with multiple hosts, is regarded as a potential future desert economic plant. However, as a result of excessive exploitation and poaching, its wild resources have become scarce. Thus, before developing its desert economic va...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9432852/ https://www.ncbi.nlm.nih.gov/pubmed/36061800 http://dx.doi.org/10.3389/fpls.2022.934959 |
_version_ | 1784780483007086592 |
---|---|
author | Shao, Minghao Fan, Jinglong Ma, Jinbiao Wang, Lei |
author_facet | Shao, Minghao Fan, Jinglong Ma, Jinbiao Wang, Lei |
author_sort | Shao, Minghao |
collection | PubMed |
description | Cistanche salsa (C. A. Mey.) G. Beck, a holoparasitic desert medicine plant with multiple hosts, is regarded as a potential future desert economic plant. However, as a result of excessive exploitation and poaching, its wild resources have become scarce. Thus, before developing its desert economic value, this plant has to be protected, and the identification of its natural reserve is currently the top priority. However, in previous nature reserve prediction studies, the influence of host plants has been overlooked, particularly in holoparasitic plants with multiple hosts. In this study, we sought to identify the conservation areas of wild C. salsa by considering multiple host–plant interactions and climate change conditions using the MaxEnt model. Additionally, a Principal Component Analysis (PCA) was used to reduce the autocorrelation between environmental variables. The effects of the natural distribution of the host plants in terms of natural distribution from the perspective of niche similarities and extrapolation detection were considered by filtering the most influential hosts: Krascheninnikovia ceratoides (Linnaeus), Gueldenstaedt, and Nitraria sibirica Pall. Additionally, the change trends in these hosts based on climate change conditions combined with the change trends in C. salsa were used to identify a core protection area of 126483.5 km(2). In this article, we corrected and tried to avoid some of the common mistakes found in species distribution models based on the findings of previous research and fully considered the effects of host plants for multiple-host holoparasitic plants to provide a new perspective on the prediction of holoparasitic plants and to provide scientific zoning for biodiversity conservation in desert ecosystems. This research will hopefully serve as a significant reference for decision-makers. |
format | Online Article Text |
id | pubmed-9432852 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-94328522022-09-01 Identifying the natural reserve area of Cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in Xinjiang, China Shao, Minghao Fan, Jinglong Ma, Jinbiao Wang, Lei Front Plant Sci Plant Science Cistanche salsa (C. A. Mey.) G. Beck, a holoparasitic desert medicine plant with multiple hosts, is regarded as a potential future desert economic plant. However, as a result of excessive exploitation and poaching, its wild resources have become scarce. Thus, before developing its desert economic value, this plant has to be protected, and the identification of its natural reserve is currently the top priority. However, in previous nature reserve prediction studies, the influence of host plants has been overlooked, particularly in holoparasitic plants with multiple hosts. In this study, we sought to identify the conservation areas of wild C. salsa by considering multiple host–plant interactions and climate change conditions using the MaxEnt model. Additionally, a Principal Component Analysis (PCA) was used to reduce the autocorrelation between environmental variables. The effects of the natural distribution of the host plants in terms of natural distribution from the perspective of niche similarities and extrapolation detection were considered by filtering the most influential hosts: Krascheninnikovia ceratoides (Linnaeus), Gueldenstaedt, and Nitraria sibirica Pall. Additionally, the change trends in these hosts based on climate change conditions combined with the change trends in C. salsa were used to identify a core protection area of 126483.5 km(2). In this article, we corrected and tried to avoid some of the common mistakes found in species distribution models based on the findings of previous research and fully considered the effects of host plants for multiple-host holoparasitic plants to provide a new perspective on the prediction of holoparasitic plants and to provide scientific zoning for biodiversity conservation in desert ecosystems. This research will hopefully serve as a significant reference for decision-makers. Frontiers Media S.A. 2022-08-17 /pmc/articles/PMC9432852/ /pubmed/36061800 http://dx.doi.org/10.3389/fpls.2022.934959 Text en Copyright © 2022 Shao, Fan, Ma and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Shao, Minghao Fan, Jinglong Ma, Jinbiao Wang, Lei Identifying the natural reserve area of Cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in Xinjiang, China |
title | Identifying the natural reserve area of Cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in Xinjiang, China |
title_full | Identifying the natural reserve area of Cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in Xinjiang, China |
title_fullStr | Identifying the natural reserve area of Cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in Xinjiang, China |
title_full_unstemmed | Identifying the natural reserve area of Cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in Xinjiang, China |
title_short | Identifying the natural reserve area of Cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in Xinjiang, China |
title_sort | identifying the natural reserve area of cistanche salsa under the effects of multiple host plants and climate change conditions using a maximum entropy model in xinjiang, china |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9432852/ https://www.ncbi.nlm.nih.gov/pubmed/36061800 http://dx.doi.org/10.3389/fpls.2022.934959 |
work_keys_str_mv | AT shaominghao identifyingthenaturalreserveareaofcistanchesalsaundertheeffectsofmultiplehostplantsandclimatechangeconditionsusingamaximumentropymodelinxinjiangchina AT fanjinglong identifyingthenaturalreserveareaofcistanchesalsaundertheeffectsofmultiplehostplantsandclimatechangeconditionsusingamaximumentropymodelinxinjiangchina AT majinbiao identifyingthenaturalreserveareaofcistanchesalsaundertheeffectsofmultiplehostplantsandclimatechangeconditionsusingamaximumentropymodelinxinjiangchina AT wanglei identifyingthenaturalreserveareaofcistanchesalsaundertheeffectsofmultiplehostplantsandclimatechangeconditionsusingamaximumentropymodelinxinjiangchina |