• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

当前和未来气候情景下中国稻水象甲的潜在分布预测

Potential Distribution Prediction of Retz. in China Under Current and Future Climate Scenarios.

作者信息

Dong Zhang-Hong, Jiang Hua, Zhang Wei, Wu Jianhua, Yang Yanping, Yang Taoming, Zhao Jiangping, Luo Cunzhen, Yang Xiaoxia, Li Guilin

机构信息

Forestry and Grassland Technique Extention Station of Baoshan City Baoshan China.

Forestry and Grassland Scientific Research Institute of Baoshan City Baoshan China.

出版信息

Ecol Evol. 2025 Jan 28;15(2):e70908. doi: 10.1002/ece3.70908. eCollection 2025 Feb.

DOI:10.1002/ece3.70908
PMID:39896773
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11775412/
Abstract

Climate change in the future could potentially expand, shrink, or alter the habitats of numerous species, leading to changes in their spatial distributions. Predicting suitable areas for cultivating medicinal plants through modeling has become an effective tool for assessing site suitability and conserving medicinal plant resources. Utilizing GIS and MaxEnt model, we predicted the spatial distribution of Retz. in China for the current and for the future (2050s and 2070s) under the RCP4.5 and RCP8.5 representative concentration pathways. In this study, we utilized 73 occurrence records and incorporated eight environmental factors from WorldClim for the modeling process. The findings revealed that the evaluation of the model's performance was based on the area under the curve (AUC) of the receiver operating characteristic (ROC). All AUC values exceeded 0.9, classifying these models as "Excellent." Additionally, the jackknife test analysis revealed that the main influential variables were bio11 and bio4. Under the present climate conditions, the estimated total suitable habitat for is approximately 29.14 × 10 km, representing around 2.78% of China's total land area. Within these suitable regions, high suitability, medium suitability, and low suitability areas make up 0.39%, 0.54%, and 1.85% of the total area, respectively. According to future climate, the potential growth range of is expected to expand due to climate variability, showing a significant pattern of expansion towards the north and east within China. In the 2050s and 2070s, the total area of regions with high suitability, medium suitability, and low suitability under RCP4.5 and RCP8.5 will increase compared to the current distribution. This study will provide theoretical suggestions for preservation, management, and sustainable utilization of resources.

摘要

未来的气候变化可能会扩大、缩小或改变众多物种的栖息地,导致其空间分布发生变化。通过建模预测药用植物的适宜种植区域已成为评估场地适宜性和保护药用植物资源的有效工具。利用地理信息系统(GIS)和最大熵(MaxEnt)模型,我们在代表性浓度路径RCP4.5和RCP8.5下,预测了当前以及未来(2050年代和2070年代)中国某植物(原文未明确写出植物名称,用“某植物”暂代)的空间分布。在本研究中,我们利用73个出现记录,并纳入了来自WorldClim的八个环境因子用于建模过程。研究结果表明,模型性能评估基于接收器操作特征(ROC)曲线下的面积(AUC)。所有AUC值均超过0.9,将这些模型归类为“优秀”。此外,刀切法检验分析表明,主要影响变量是生物11和生物4。在当前气候条件下,某植物的适宜栖息地总面积估计约为29.14×10平方千米,约占中国陆地总面积的2.78%。在这些适宜区域内,高适宜性、中等适宜性和低适宜性区域分别占总面积的0.39%、0.54%和1.85%。根据未来气候情况,由于气候变异性,某植物的潜在生长范围预计将扩大,在中国境内呈现出显著的向北和向东扩展的趋势。在2050年代和2070年代,与当前分布相比,RCP4.5和RCP8.5下高适宜性、中等适宜性和低适宜性区域的总面积将增加。本研究将为某植物资源的保护、管理和可持续利用提供理论建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/bf314051c89d/ECE3-15-e70908-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/cdc780946e1a/ECE3-15-e70908-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/6b1eecb79293/ECE3-15-e70908-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/c95b9532a4fd/ECE3-15-e70908-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/eada186abf32/ECE3-15-e70908-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/1b7cdc2e8621/ECE3-15-e70908-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/60d26a988008/ECE3-15-e70908-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/74b856cf8a62/ECE3-15-e70908-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/bf314051c89d/ECE3-15-e70908-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/cdc780946e1a/ECE3-15-e70908-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/6b1eecb79293/ECE3-15-e70908-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/c95b9532a4fd/ECE3-15-e70908-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/eada186abf32/ECE3-15-e70908-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/1b7cdc2e8621/ECE3-15-e70908-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/60d26a988008/ECE3-15-e70908-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/74b856cf8a62/ECE3-15-e70908-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c759/11775412/bf314051c89d/ECE3-15-e70908-g004.jpg

相似文献

1
Potential Distribution Prediction of Retz. in China Under Current and Future Climate Scenarios.当前和未来气候情景下中国稻水象甲的潜在分布预测
Ecol Evol. 2025 Jan 28;15(2):e70908. doi: 10.1002/ece3.70908. eCollection 2025 Feb.
2
Modeling coffee (Coffea arabica L.) climate suitability under current and future scenario in Jimma zone, Ethiopia.在埃塞俄比亚吉马地区,对当前和未来情景下咖啡(阿拉比卡咖啡)气候适宜性进行建模。
Environ Monit Assess. 2022 Mar 11;194(4):271. doi: 10.1007/s10661-022-09895-9.
3
Current and future distribution of in China under climate change adopting the MaxEnt model.采用最大熵模型预测气候变化下 在中国的当前及未来分布。 (原文中“of”后缺少具体内容)
Front Plant Sci. 2024 Jun 3;15:1394799. doi: 10.3389/fpls.2024.1394799. eCollection 2024.
4
The ecological suitability area of (Thunb.) Sch.-Bip. under future climate change in China based on MaxEnt modeling.基于最大熵模型的中国未来气候变化下(Thunb.)Sch.-Bip. 的生态适宜区
Ecol Evol. 2024 Jan 23;14(1):e10848. doi: 10.1002/ece3.10848. eCollection 2024 Jan.
5
Predicting the distributions of (Hymenoptera: Bethylidae) under climate change in China.预测气候变化下中国(膜翅目:肿腿蜂科)的分布情况。
Ecol Evol. 2022 Oct 5;12(10):e9410. doi: 10.1002/ece3.9410. eCollection 2022 Oct.
6
Assessing the Potential Distribution of (Coleoptera: Cerambycidae) in China Under Climate Change Using Species Distribution Models.利用物种分布模型评估气候变化下 (鞘翅目:天牛科) 在中国的潜在分布
Ecol Evol. 2025 Apr 14;15(4):e71303. doi: 10.1002/ece3.71303. eCollection 2025 Apr.
7
The optimized Maxent model reveals the pattern of distribution and changes in the suitable cultivation areas for being driven by climate change.优化后的最大熵模型揭示了气候变化驱动下适宜种植区的分布格局和变化情况。
Ecol Evol. 2024 Jul 17;14(7):e70015. doi: 10.1002/ece3.70015. eCollection 2024 Jul.
8
Modeling potential distribution of newly recorded ant, Brachyponera nigrita using Maxent under climate change in Pothwar region, Pakistan.利用 Maxent 模型在气候变化下对巴基斯坦波特瓦尔地区新记录的蚂蚁 Brachyponera nigrita 的潜在分布进行建模。
PLoS One. 2022 Jan 19;17(1):e0262451. doi: 10.1371/journal.pone.0262451. eCollection 2022.
9
Predicting the Impact of Climate Change on the Distribution of North China Leopards () in Gansu Province Using MaxEnt Modeling.利用最大熵模型预测气候变化对甘肃省华北豹分布的影响
Biology (Basel). 2025 Jan 26;14(2):126. doi: 10.3390/biology14020126.
10
MaxEnt model strategies to studying current and future potential land suitability dynamics of wheat, soybean and rice cultivation under climatic change scenarios in East Asia.最大熵模型策略在东亚气候变化情景下研究小麦、大豆和水稻种植的当前和未来潜在土地适宜性动态。
PLoS One. 2023 Dec 21;18(12):e0296182. doi: 10.1371/journal.pone.0296182. eCollection 2023.

引用本文的文献

1
Climate Change Drives Northwestward Migration of : A Multi-Scenario MaxEnt Modeling Approach.气候变化驱动[具体物种]向西北迁移:一种多情景最大熵建模方法 。 需注意,原文中“:”前缺少具体所指物种名称。
Plants (Basel). 2025 Aug 15;14(16):2539. doi: 10.3390/plants14162539.
2
Assessing Climate Change Impacts on Distribution Dynamics of in China Through MaxEnt Modeling.通过最大熵模型评估气候变化对中国[物种名称缺失]分布动态的影响
Ecol Evol. 2025 Jun 24;15(6):e71664. doi: 10.1002/ece3.71664. eCollection 2025 Jun.
3
A Vanishing Imprint? Modeling the Present and Future Distribution of the Enigmatic Lam., a Mediterranean Sporadic Tree Species.

本文引用的文献

1
Prediction of the potentially suitable areas of in China based on future climate change using the optimized MaxEnt model.基于未来气候变化,利用优化的最大熵模型预测中国[具体事物未给出]的潜在适宜区域。
Ecol Evol. 2023 Oct 19;13(10):e10597. doi: 10.1002/ece3.10597. eCollection 2023 Oct.
2
Prediction of potential distribution areas and priority protected areas of based on Maxent model and Marxan model.基于最大熵模型和马克思an模型预测[具体物种或事物]的潜在分布区域和优先保护区。 (注:原文中“based on Maxent model and Marxan model.”前缺少具体所指对象,翻译时补充了[具体物种或事物]使句子完整通顺)
Front Plant Sci. 2023 Jul 24;14:1200796. doi: 10.3389/fpls.2023.1200796. eCollection 2023.
3
一个正在消失的印记?对地中海地区偶见树种神秘的拉蒙树当前及未来分布进行建模。
Ecol Evol. 2025 May 26;15(5):e71482. doi: 10.1002/ece3.71482. eCollection 2025 May.
Predicting the current and future distributions of Pennisetum alopecuroides (L.) in China under climate change based on the MaxEnt model.
基于 MaxEnt 模型预测中国气候变化下狼尾草(Pennisetum alopecuroides (L.))的当前和未来分布。
PLoS One. 2023 Apr 4;18(4):e0281254. doi: 10.1371/journal.pone.0281254. eCollection 2023.
4
Predicting the Potential Suitable Climate for Coconut ( L.) Cultivation in India under Climate Change Scenarios Using the MaxEnt Model.利用最大熵模型预测气候变化情景下印度椰子(L.)种植的潜在适宜气候
Plants (Basel). 2022 Mar 9;11(6):731. doi: 10.3390/plants11060731.
5
Prevention is better than cure: Integrating habitat suitability and invasion threat to assess global biological invasion risk by insect pests under climate change.预防胜于治疗:整合栖息地适宜性和入侵威胁评估气候变化下害虫的全球生物入侵风险。
Pest Manag Sci. 2021 Oct;77(10):4510-4520. doi: 10.1002/ps.6486. Epub 2021 Jun 11.
6
Predicting distribution of Zanthoxylum bungeanum Maxim. in China.预测中国花椒属植物的分布。
BMC Ecol. 2020 Aug 11;20(1):46. doi: 10.1186/s12898-020-00314-6.
7
Scientists' warning on invasive alien species.科学家对入侵外来物种发出警告。
Biol Rev Camb Philos Soc. 2020 Dec;95(6):1511-1534. doi: 10.1111/brv.12627. Epub 2020 Jun 25.
8
Climate change is predicted to disrupt patterns of local adaptation in wild and cultivated maize.气候变化预计会打乱野生和栽培玉米的局部适应模式。
Proc Biol Sci. 2019 Jul 10;286(1906):20190486. doi: 10.1098/rspb.2019.0486.
9
[Prediction on spatial migration of suitable distribution of Elaeagnus mollis under climate change conditions in Shanxi Province, China].[气候变化条件下中国山西省翅果油树适生分布空间迁移预测]
Ying Yong Sheng Tai Xue Bao. 2019 Feb 20;30(2):496-502. doi: 10.13287/j.1001-9332.201902.040.
10
Modelling the effects of climate change on the distribution of benthic indicator species in the Eastern Mediterranean Sea.模拟气候变化对东地中海底栖指示物种分布的影响。
Sci Total Environ. 2019 Jun 1;667:16-24. doi: 10.1016/j.scitotenv.2019.02.338. Epub 2019 Feb 24.