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藻华关联:传播网络推断与极端生态环境反馈

Algal Bloom Ties: Spreading Network Inference and Extreme Eco-Environmental Feedback.

作者信息

Wang Haojiong, Galbraith Elroy, Convertino Matteo

机构信息

Laboratory of Information Communication Networks, Graduate School of Information Science and Technology, Hokkaido University, Sapporo 060-0814, Japan.

fuTuRE EcoSystems Lab (TREES), Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.

出版信息

Entropy (Basel). 2023 Apr 10;25(4):636. doi: 10.3390/e25040636.

Abstract

Coastal marine ecosystems worldwide are increasingly affected by tide alterations and anthropogenic disturbances affecting the water quality and leading to frequent algal blooms. Increased bloom persistence is a serious threat due to the long-lasting impacts on ecological processes and services, such as carbon cycling and sequestration. The exploration of eco-environmental feedback and algal bloom patterns remains challenging and poorly investigated, mostly due to the paucity of data and lack of model-free approaches to infer universal bloom dynamics. Florida Bay, taken as an epitome for biodiversity and blooms, has long experienced algal blooms in its central and western regions, and, in 2006, an unprecedented bloom occurred in the eastern habitats rich in corals and vulnerable habitats. With global aims, we analyze the occurrence of blooms in Florida Bay from three perspectives: (1) the spatial spreading networks of chlorophyll-a (CHLa) that pinpoint the source and unbalanced habitats; (2) the fluctuations of water quality factors pre- and post-bloom outbreaks to assess the environmental impacts of ecological imbalances and target the prevention and control of algal blooms; and (3) the topological co-evolution of biogeochemical and spreading networks to quantify ecosystem stability and the likelihood of ecological shifts toward endemic blooms in the long term. Here, we propose the transfer entropy (TE) difference to infer salient dynamical inter actions between the spatial areas and biogeochemical factors (ecosystem connectome) underpinning bloom emergence and spread as well as environmental effects. A Pareto principle, defining the top 20% of areal interactions, is found to identify bloom spreading and the salient eco-environmental interactions of CHLa associated with endemic and epidemic regimes. We quantify the spatial dynamics of algal blooms and, thus, obtain areas in critical need for ecological monitoring and potential bloom control. The results show that algal blooms are increasingly persistent over space with long-term negative effects on water quality factors, in particular, about how blooms affect temperature locally. A dichotomy is reported between spatial ecological corridors of spreading and biogeochemical networks as well as divergence from the optimal eco-organization: randomization of the former due to nutrient overload and temperature increase leads to scale-free CHLa spreading and extreme outbreaks a posteriori. Subsequently, the occurrence of blooms increases bloom persistence, turbidity and salinity with potentially strong ecological effects on highly biodiverse and vulnerable habitats, such as tidal flats, salt-marshes and mangroves. The probabilistic distribution of CHLa is found to be indicative of endemic and epidemic regimes, where the former sets the system to higher energy dissipation, larger instability and lower predictability. Algal blooms are important ecosystem regulators of nutrient cycles; however, chlorophyll-a outbreaks cause vast ecosystem impacts, such as aquatic species mortality and carbon flux alteration due to their effects on water turbidity, nutrient cycling (nitrogen and phosphorus in particular), salinity and temperature. Beyond compromising the local water quality, other socio-ecological services are also compromised at large scales, including carbon sequestration, which affects climate regulation from local to global environments. Yet, ecological assessment models, such as the one presented, inferring bloom regions and their stability to pinpoint risks, are in need of application in aquatic ecosystems, such as subtropical and tropical bays, to assess optimal preventive controls.

摘要

全球沿海海洋生态系统正日益受到潮汐变化和人为干扰的影响,这些干扰影响着水质并导致藻华频繁发生。藻华持续时间的增加是一个严重威胁,因为它会对生态过程和服务产生长期影响,如碳循环和碳固存。探索生态环境反馈和藻华模式仍然具有挑战性且研究不足,主要原因是数据匮乏以及缺乏无模型方法来推断普遍的藻华动态。佛罗里达湾作为生物多样性和藻华的一个缩影,其中部和西部地区长期经历藻华,并且在2006年,东部富含珊瑚的栖息地和脆弱栖息地发生了前所未有的藻华。基于全球目标,我们从三个角度分析佛罗里达湾藻华的发生情况:(1)叶绿素a(CHLa)的空间扩散网络,它能确定藻华的源头和失衡的栖息地;(2)藻华爆发前后水质因素的波动,以评估生态失衡对环境的影响,并确定藻华的预防和控制目标;(3)生物地球化学网络和扩散网络的拓扑共同演化,以量化生态系统稳定性以及长期内生态向地方性藻华转变的可能性。在这里,我们提出转移熵(TE)差异来推断支撑藻华出现、扩散以及环境影响的空间区域与生物地球化学因素(生态系统连接组)之间的显著动态相互作用。发现一个帕累托原则,即定义前20%的区域相互作用,可识别藻华扩散以及与地方性和流行状态相关的CHLa的显著生态环境相互作用。我们量化了藻华的空间动态,从而确定了急需进行生态监测和潜在藻华控制的区域。结果表明,藻华在空间上的持续性越来越强,对水质因素产生长期负面影响,特别是藻华对当地温度的影响。报告了扩散的空间生态走廊与生物地球化学网络之间的二分法,以及与最优生态组织的背离:前者由于营养物质过载和温度升高而随机化,导致无标度的CHLa扩散和事后的极端爆发。随后,藻华的发生增加了藻华的持续性、浊度和盐度,对潮间带、盐沼和红树林等生物多样性高且脆弱的栖息地可能产生强烈的生态影响。发现CHLa的概率分布可指示地方性和流行状态,其中前者使系统具有更高的能量耗散、更大的不稳定性和更低的可预测性。藻华是营养循环的重要生态系统调节者;然而,叶绿素a爆发会对生态系统产生巨大影响,如由于对水浊度、营养循环(特别是氮和磷)、盐度和温度的影响而导致水生物种死亡和碳通量改变。除了损害当地水质外,其他社会生态服务在大尺度上也受到损害,包括碳固存,这会影响从局部到全球环境的气候调节。然而,像本文所提出的这种推断藻华区域及其稳定性以确定风险的生态评估模型,需要应用于亚热带和热带海湾等水生生态系统,以评估最优预防控制措施。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8532/10138021/be6fd2e1ce94/entropy-25-00636-g001.jpg

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