Nexus Group, Laboratory of Information Communication Networks, Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan.
Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
PLoS One. 2021 Oct 20;16(10):e0246222. doi: 10.1371/journal.pone.0246222. eCollection 2021.
Fish ecosystems perform ecological functions that are critically important for the sustainability of marine ecosystems, such as global food security and carbon stock. During the 21st century, significant global warming caused by climate change has created pressing challenges for fish ecosystems that threaten species existence and global ecosystem health. Here, we study a coastal fish community in Maizuru Bay, Japan, and investigate the relationships between fluctuations of ST, abundance-based species interactions and salient fish biodiversity. Observations show that a local 20% increase in temperature from 2002 to 2014 underpins a long-term reduction in fish diversity (∼25%) played out by some native and invasive species (e.g. Chinese wrasse) becoming exceedingly abundant; this causes a large decay in commercially valuable species (e.g. Japanese anchovy) coupled to an increase in ecological productivity. The fish community is analyzed considering five temperature ranges to understand its atemporal seasonal sensitivity to ST changes, and long-term trends. An optimal information flow model is used to reconstruct species interaction networks that emerge as topologically different for distinct temperature ranges and species dynamics. Networks for low temperatures are more scale-free compared to ones for intermediate (15-20°C) temperatures in which the fish ecosystem experiences a first-order phase transition in interactions from locally stable to metastable and globally unstable for high temperatures states as suggested by abundance-spectrum transitions. The dynamic dominant eigenvalue of species interactions shows increasing instability for competitive species (spiking in summer due to intermediate-season critical transitions) leading to enhanced community variability and critical slowing down despite higher time-point resilience. Native competitive species whose abundance is distributed more exponentially have the highest total directed interactions and are keystone species (e.g. Wrasse and Horse mackerel) for the most salient links with cooperative decaying species. Competitive species, with higher eco-climatic memory and synchronization, are the most affected by temperature and play an important role in maintaining fish ecosystem stability via multitrophic cascades (via cooperative-competitive species imbalance), and as bioindicators of change. More climate-fitted species follow temperature increase causing larger divergence divergence between competitive and cooperative species. Decreasing dominant eigenvalues and lower relative network optimality for warmer oceans indicate fishery more attracted toward persistent oscillatory states, yet unpredictable, with lower cooperation, diversity and fish stock despite the increase in community abundance due to non-commercial and venomous species. We emphasize how changes in species interaction organization, primarily affected by temperature fluctuations, are the backbone of biodiversity dynamics and yet for functional diversity in contrast to taxonomic richness. Abundance and richness manifest gradual shifts while interactions show sudden shift. The work provides data-driven tools for analyzing and monitoring fish ecosystems under the pressure of global warming or other stressors. Abundance and interaction patterns derived by network-based analyses proved useful to assess ecosystem susceptibility and effective change, and formulate predictive dynamic information for science-based fishery policy aimed to maintain marine ecosystems stable and sustainable.
鱼类生态系统具有至关重要的生态功能,对海洋生态系统的可持续性,如全球粮食安全和碳储量,具有重要意义。在 21 世纪,气候变化引起的全球显著变暖给鱼类生态系统带来了紧迫的挑战,威胁到物种的生存和全球生态系统的健康。在这里,我们研究了日本舞鹤湾的一个沿海鱼类群落,并调查了 ST 波动、基于丰度的物种相互作用和显著鱼类生物多样性之间的关系。观测表明,2002 年至 2014 年,当地温度升高 20%,支撑着一些本地和入侵物种(如中国鲈鱼)的丰度长期减少(约 25%),这导致了商业价值物种(如日本沙丁鱼)的大量减少,同时生态生产力增加。为了了解鱼类群落对 ST 变化的无时间季节性敏感性和长期趋势,我们考虑了五个温度范围来分析鱼类群落。使用最优信息流模型来重建物种相互作用网络,这些网络在不同的温度范围和物种动态下呈现出拓扑上的不同。低温下的网络比中温(15-20°C)下的网络更具有无标度特性,在中温下,鱼类生态系统经历了从局部稳定到亚稳定和全球不稳定的一级相变,这表明丰度谱跃迁。物种相互作用的动态主导特征值对于竞争物种表现出越来越大的不稳定性(由于中间季节的关键转变,夏季出现峰值),导致群落变异性增加,临界减速,尽管时间点的弹性更高。丰度分布更呈指数型的本地竞争物种具有最高的总有向相互作用,并且是与合作衰减物种最显著的链接的关键物种(例如鲈鱼和鲭鱼)。受温度影响更大的竞争物种通过多营养级级联(通过合作-竞争物种失衡)和作为变化的生物指标,在维持鱼类生态系统稳定性方面发挥着重要作用。更多适应气候的物种随着温度的升高而出现,导致竞争物种和合作物种之间的差异更大。海洋变暖导致主导特征值降低和相对网络优化度降低,表明渔业更倾向于持久的振荡状态,尽管由于非商业和有毒物种的增加,群落丰度增加,但合作、多样性和鱼类种群减少,因此不可预测。我们强调了物种相互作用组织的变化如何主要受到温度波动的影响,这是生物多样性动态的核心,但与功能多样性相比,是分类丰富度的核心。丰度和丰富度表现出逐渐的变化,而相互作用则表现出突然的变化。该工作为在全球变暖或其他胁迫下分析和监测鱼类生态系统提供了数据驱动的工具。基于网络分析得出的丰度和相互作用模式被证明有助于评估生态系统的敏感性和有效变化,并为基于科学的渔业政策制定预测动态信息,以维持海洋生态系统的稳定和可持续性。