Quantifying key indicators of essential biodiversity variables for mangrove species in response to hydro-meteorological factors

Hang Yao , Bolin Fu , Weiwei Sun , Yuyu Zhou , Yeqiao Wang , Weiguo Jiang , Hongchang He , Zhili Chen , Yiji Song
{"title":"Quantifying key indicators of essential biodiversity variables for mangrove species in response to hydro-meteorological factors","authors":"Hang Yao ,&nbsp;Bolin Fu ,&nbsp;Weiwei Sun ,&nbsp;Yuyu Zhou ,&nbsp;Yeqiao Wang ,&nbsp;Weiguo Jiang ,&nbsp;Hongchang He ,&nbsp;Zhili Chen ,&nbsp;Yiji Song","doi":"10.1016/j.jag.2025.104535","DOIUrl":null,"url":null,"abstract":"<div><div>Mangroves are critical for climate mitigation and biodiversity conservation, yet their spatiotemporal dynamics and physiological responses to hydrometeorological drivers remain poorly understood. This study extracted three essential biodiversity variables (area distribution, phenology, and physiological traits) and further revealed their dependencies on hydrometeorological conditions. We developed a continuous time-series monitoring method (CTSM) to enhance the Detect-Monitor-Predict detection framework for accurately tracking mangrove spatial succession in the Beibu Gulf from 2000 to 2021. We combined Continuous Change Detection and Classification with Harmonic Analysis of Time Series (HANTS) methods to capture the seasonal changes of physiological traits of dominant mangrove species. This study utilized HANTS-PLSR (partial least squares regression) response models and structural equation models to explore the seasonal responses of physiological trait to hydro-meteorological factors. The results indicated that (1) the improved detect component delineated fine-scale expansion patterns of mangroves, with area-hydrometeorology coupling evolving from uncoordinated to highly coordination during 2000–2021. (2) The start, peak and end of the growing season for mangroves are in March-April, June-September and January-February of the following year, respectively. The mangroves in different regions exhibit relatively delayed growth periods. (3) <em>Aegiceras corniculatum</em> exhibited bimodal phenological trajectories, contrasting with unimodal patterns in three co-occurring species. (4) The physiological traits displayed a positive correlation with water/air temperature and sunshine duration. The phenological changes of four mangrove species are driven by the interaction between hydrological and meteorological variables, with meteorological factors dominating (path coefficient &gt; 0.50, <em>p</em> &lt; 0.001). The findings provide insights into mangrove conservation and biodiversity monitoring.</div></div>","PeriodicalId":73423,"journal":{"name":"International journal of applied earth observation and geoinformation : ITC journal","volume":"139 ","pages":"Article 104535"},"PeriodicalIF":8.6000,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of applied earth observation and geoinformation : ITC journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569843225001827","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/17 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
引用次数: 0

Abstract

Mangroves are critical for climate mitigation and biodiversity conservation, yet their spatiotemporal dynamics and physiological responses to hydrometeorological drivers remain poorly understood. This study extracted three essential biodiversity variables (area distribution, phenology, and physiological traits) and further revealed their dependencies on hydrometeorological conditions. We developed a continuous time-series monitoring method (CTSM) to enhance the Detect-Monitor-Predict detection framework for accurately tracking mangrove spatial succession in the Beibu Gulf from 2000 to 2021. We combined Continuous Change Detection and Classification with Harmonic Analysis of Time Series (HANTS) methods to capture the seasonal changes of physiological traits of dominant mangrove species. This study utilized HANTS-PLSR (partial least squares regression) response models and structural equation models to explore the seasonal responses of physiological trait to hydro-meteorological factors. The results indicated that (1) the improved detect component delineated fine-scale expansion patterns of mangroves, with area-hydrometeorology coupling evolving from uncoordinated to highly coordination during 2000–2021. (2) The start, peak and end of the growing season for mangroves are in March-April, June-September and January-February of the following year, respectively. The mangroves in different regions exhibit relatively delayed growth periods. (3) Aegiceras corniculatum exhibited bimodal phenological trajectories, contrasting with unimodal patterns in three co-occurring species. (4) The physiological traits displayed a positive correlation with water/air temperature and sunshine duration. The phenological changes of four mangrove species are driven by the interaction between hydrological and meteorological variables, with meteorological factors dominating (path coefficient > 0.50, p < 0.001). The findings provide insights into mangrove conservation and biodiversity monitoring.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
水文气象因子对红树林生物多样性关键指标的响应
红树林对于减缓气候变化和保护生物多样性至关重要,但人们对其时空动态和对水文气象驱动因素的生理反应知之甚少。本研究提取了生物多样性的三个基本变量(面积分布、物候和生理性状),并进一步揭示了它们对水文气象条件的依赖关系。为完善2000 - 2021年北部湾红树林空间演替的Detect-Monitor-Predict检测框架,建立了一种连续时间序列监测方法(CTSM)。将连续变化检测与分类与时间序列谐波分析(HANTS)方法相结合,捕捉红树林优势种生理性状的季节变化。利用汉斯- plsr(偏最小二乘回归)响应模型和结构方程模型探讨了生理性状对水文气象因子的季节响应。结果表明:(1)改进的探测分量描绘了2000-2021年红树林的精细尺度扩展格局,区域-水文气象耦合从不协调向高度协调演变。(2)红树林生长季节的开始、高峰和结束分别为次年的3 - 4月、6 - 9月和1 - 2月。不同地区红树林的生长期相对较晚。(3)与3个共发生种的单峰物候模式相比,盾叶蝉的物候轨迹呈现双峰模式。(4)各生理性状与水/空气温度和日照时数呈正相关。4种红树林物候变化受水文和气象因子的共同作用驱动,气象因子占主导地位(路径系数>;0.50, p <;0.001)。这些发现为红树林保护和生物多样性监测提供了见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
International journal of applied earth observation and geoinformation : ITC journal
International journal of applied earth observation and geoinformation : ITC journal Global and Planetary Change, Management, Monitoring, Policy and Law, Earth-Surface Processes, Computers in Earth Sciences
CiteScore
12.00
自引率
0.00%
发文量
0
审稿时长
77 days
期刊介绍: The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.
期刊最新文献
Quantifying the ability of bidirectional reflectance distribution function (BRDF) model to Respond to soil moisture and the normalized difference vegetation index (NDVI) Evaluating Pléiades Neo capabilities for deriving rock glacier velocity Contrasting trends in climatic and ecohydrological aridity over one-fifth of global drylands Earth observation derived yield forecasting and estimation in low- and lower-middle-income countries dominated by smallholder agriculture: A review A global continuous 500 m nighttime light dataset (1992–2024) via NDVI-guided DMSP-OLS correction and U-TransNet cross-sensor harmonization
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1