基于MaxEnt模型分析全球气候变化对中国沿海带鱼潜在分布的影响

doi:10.11978/2024241

热带海洋学报 ›› 2025, Vol. 44 ›› Issue (5): 77-85.doi: 10.11978/2024241CSTR: 32234.14.2024241

基于MaxEnt模型分析全球气候变化对中国沿海带鱼潜在分布的影响

冯战权(), 苏冒亮, 杜媛媛, 钟友凌, 张俊彬()

深圳大学生命与海洋科学学院, 深圳市海洋生物资源与生态环境重点实验室, 广东深圳 518060

收稿日期:2024-12-28 修回日期:2025-03-18 出版日期:2025-09-10 发布日期:2025-10-14
通讯作者: 张俊彬
作者简介:
冯战权, 男, 山东省菏泽市人, 硕士研究生, 从事水生生物学研究。email: fzq388027@163.com
基金资助:
深圳市可持续发展专项(2023N066); 国家自然科学基金项目(41976108)

MaxEnt model predicting potential distribution of Trichiurus japonicus in the coastal waters of China under global climate change

FENG Zhanquan(), SU Maoliang, DU Yuanyuan, ZHONG Youling, ZHANG Junbin()

Shenzhen Key Laboratory of Marine Bioresource & Eco-Environmental Science, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518060, China

Received:2024-12-28 Revised:2025-03-18 Online:2025-09-10 Published:2025-10-14
Contact: ZHANG Junbin
Supported by:
Sustainable Development Program of Shenzhen(2023N066); National Natural Science Foundation of China(41976108)

摘要/Abstract

摘要：

在全球气候变化的大背景下, 物种分布格局的变迁已成为科学界关注的焦点。文章依据政府间气候变化专门委员会 (Intergovernmental Panel on Climate Change, IPCC)关于全球气候变化的分析, 运用最大熵模型(maximum entropy, MaxEnt)与地理信息系统(geographic information system, GIS)技术, 对中国沿海的带鱼(Trichiurus japonicus)在不同共享社会经济路径(shared socioeconomic pathways, SSPs)情景下的潜在适生区分布进行深入分析, 识别了影响其分布的关键环境因素, 并预测了在不同SSPs情景下带鱼未来栖息地的变化趋势。研究数据基于全球生物多样性信息机构(Global Biodiversity Information Facility, GBIF)和世界鱼类数据库(Fishbase)提供的70个有效物种分布记录, 以及海洋生物气候与环境分析栅格数据库(Biological Ocean Rasters for Analyses of Climate and Environment, Bio-ORACLE)提供的13个海洋环境变量。模型的准确度通过受试者工作特征曲线(receiver operating characteristic, ROC)进行验证, 模型的平均曲线下面积(area under the curve, AUC)值为0.913, 表明模型具有出色的预测性能。研究发现, 带鱼在我国四大海域均有适宜的栖息地, 其中中高适宜分布区占总预测区域的11.96%; 温度、叶绿素浓度和初级生产力是影响带鱼分布的关键环境因素, 且底层环境变量的贡献普遍高于表层环境变量; 预测未来随着气候变化, 带鱼的适生区总体呈现扩大趋势, 在SSP5-8.5情景下扩张最为显著, 主要表现为向黄渤海等高纬度区域扩展, 而在南海北部湾等低纬度区域则有所收缩。

关键词: 带鱼, 最大熵模型, 海洋环境因子, 潜在栖息地, 气候变化

Abstract:

This study predicted the potential distribution of Trichiurus japonicus along China’s coastal waters under the influence of global climate change, using the maximum entropy (MaxEnt) model integrated with Geographic Information System (GIS) techniques. Species occurrence data (70 valid points) were obtained from Global Biodiversity Information Facility (GBIF) and FishBase, while environmental variables were sourced from Bio-ORACLE. Model performance was evaluated using the Receiver Operating Characteristic (ROC) curve, yielding a high accuracy (0.913) of Area Under the Curve (AUC). Our results indicated that suitable habitats for T. japonicus are distributed across China’s four major marine regions, with medium-to-high suitability areas accounting for 11.96% of the total predicted area. Temperature, chlorophyll concentration, and primary productivity were identified as key environmental factors affecting hairtail distribution. Model projections under different shared socioeconomic pathway (SSP) scenarios suggested an expansion of suitable habitats with a potential northward shift towards the Yellow Sea and Bohai Sea, while contracting in the waters of South China such as Beibu Gulf in the future.

Key words: Trichiurus japonicus, MaxEnt model, marine environmental factors, potential habitat, global climate change

中图分类号:

P735.121

冯战权, 苏冒亮, 杜媛媛, 钟友凌, 张俊彬. 基于MaxEnt模型分析全球气候变化对中国沿海带鱼潜在分布的影响[J]. 热带海洋学报, 2025, 44(5): 77-85.

FENG Zhanquan, SU Maoliang, DU Yuanyuan, ZHONG Youling, ZHANG Junbin. MaxEnt model predicting potential distribution of Trichiurus japonicus in the coastal waters of China under global climate change[J]. Journal of Tropical Oceanography, 2025, 44(5): 77-85.

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因子序号	环境因子	单位
bio_1	底层海流方向bot current direction	°
bio_2	底层海流速度bot current velocity	m·s^-1
bio_3	底层溶解氧bot dissolved oxygen	mmol·m^-3
bio_4	底层初级生产力bot primary productivity	mmol·m^-3
bio_5	底层盐度bot salinity	‰
bio_6	底层温度bot temperature	℃
bio_7	表层叶绿素surf chlorophyll	mg·m^-3
bio_8	表层海流方向surf current direction	°
bio_9	表层海流速度surf current velocity	m·s^-1
bio_10	表层溶解氧surf dissolved oxygen	mmol·m^-3
bio_11	表层初级生产力surf primary productivity	mmol·m^-3
bio_12	表层盐度surf salinity	‰
bio_13	表层温度surf temperature	℃

区域	现在/%	SSP1-1.9/%	SSP2-4.5/%	SSP5-8.5/%
不适宜区(0~MPT)	16.03	19.58	22.17	10.79
边缘适生区(MPT~10P)	52.10	48.00	45.85	56.07
低适生区(10P~0.5)	19.90	18.99	18.25	19.63
中适生区(0.5~0.75)	11.47	12.76	12.98	12.22
高适生区(0.75~1)	0.49	0.68	0.75	1.29

基于MaxEnt模型分析全球气候变化对中国沿海带鱼潜在分布的影响

MaxEnt model predicting potential distribution of Trichiurus japonicus in the coastal waters of China under global climate change

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