Taiwan Strait Research Articles

Collaborative Scheduling of Mass Rescue Operations at Sea

The continued growth of the global cruise market has posed a major challenge to maritime search and rescue, as available rescue resources are limited compared to the scale of passenger ship disasters. To bridge the gap between the number of passengers in distress and the availability of rescue resources, this paper develops a two-stage Mass Rescue Operation (MRO) decision support model (MRO model) to fully utilize the available multiple rescue resources. Based on the combinatorial optimization theory, in the MRO model we consider the rescue capacity of multiple rescue resources and the synergy between them, the accident types and the marine environment conditions to optimize two objectives (rescue time and number of rescue resources dispatched) in two stages. In the first stage, the objective is to minimize the rescue time by Classical Selection Sort Algorithm. In the second stage, the rescue time and the number of rescue resources are simultaneously optimized by Simulated Annealing Arithmetic (SAA) integrated with Genetic Algorithm (GA). Furthermore, considering the actual role of helicopters in MROs, the MRO model is enhanced to schedule helicopters mandatorily or non-mandatorily. Finally, the MRO model was verified by simulating accidents in the Taiwan Strait. The simulation results show that compared with the first stage, the rescue time in the second stage model is saved by up to 16.18% and the number of rescue resources is reduced by up to 45.16%.

Compound Tropical Cyclone Heat (TC‐Heat) Hazard in Hong Kong: Amplifying Urban Heat Extremes With Storm Position‐Driven Peripheral Warming and Urban Footprint

AbstractCompound hazards involving tropical cyclones and extreme heat (“TC‐heat”) have rarely been examined in prior research. Peripheral subsidence associated with cyclones can warm an area to varying degrees, depending on the cyclone's strength and position. Meanwhile, the peripheral airflow also overwhelmed the land‐sea breeze circulation system in coastal cities and favored downwind urbanized heat advection on the Southern China coastline. Here, we systematically applied ERA5 global reanalysis data, local surface‐level observations, MODIS‐based land‐cover data and HYSPLIT backward trajectories to evaluate how the position of distant TCs may divert the monsoon system and foster the surface heat advection from upwind urban agglomerate amplifying air temperature in downwind coastline. The analysis suggests when a distant TC is situated in a favorable area (the vicinity of Taiwan and Luzon Strait) at roughly 500–1,250 km to the east of Hong Kong, it forms a unique meteorological condition which allows the surface heat transport from the Greater Bay Area to Hong Kong, reflecting that regional build‐up of heat could be an important mechanism for producing local heat extremes.

Dissolved Nitrous Oxide and Methane in the Taiwan Strait: Distribution, Seasonal Variation, and Emission

AbstractThe global ocean plays an important role in the overall budgets of nitrous oxide (N2O) and methane (CH4), especially in continental estuaries and shelf areas. Four cruises were conducted between 2021 and 2022, covering the spring, summer, and fall seasons, to study the spatial and seasonal characteristics of N2O and CH4 distributions and emissions in the Taiwan Strait (TWS). The surface N2O and CH4 concentrations gradually decreased from the coast to the open sea, with maximum values (14.3 and 15.6 nmol L−1) occurring near the Jiulong and Minjiang estuaries, respectively. The mean surface N2O concentration (8.2 nmol L−1) was highest in the spring and approximately the same in the summer as in the fall. The mean surface concentrations of CH4 (8.8 nmol L−1) were greater in summer than in spring and fall, probably because of the high freshwater input in summer. Except for several stations in fall, surface waters were oversaturated with N2O and CH4 relative to the atmosphere in other seasons, and the TWS was a net source of atmospheric N2O and CH4 in the spring, summer, and fall. In situ production is the main source of N2O and CH4 in the TWS, with nitrification being the dominant mechanism of N2O production in the TWS. In contrast, physical influences (riverine inputs and water mass mixing) reshape the distributions of N2O and CH4. The annual emissions of N2O and CH4 from the TWS were estimated to be 0.9 × 10−3 ± 2.9 × 10−3 Tg yr−1 and 1.6 × 10−3 ± 3.0 × 10−3 Tg yr−1, respectively. Taken together, the TWS accounts for 0.025% of the surface area of the world's oceans and 0.022% ± 0.07% and 0.017% ± 0.033% of global oceanic N2O and CH4 emissions, respectively.

Evaluating constraints on offshore wind farm installation across the Taiwan Strait by exploring the influence of El Niño-Southern Oscillation on weather window assessment

The transition to renewable energy sources, such as offshore wind farms, is essential in mitigating climate change. Taiwan has set ambitious targets to harness wind energy from the Taiwan Strait, but offshore wind farm installations are highly dependent on weather conditions, particularly wind speeds. This study examines the relationship between the El Niño-Southern Oscillation (ENSO) and offshore wind farm installation by assessing weather windows—periods with wind speeds below 12 meters per second at a height of 100 meters for at least 12 hours. Our analysis shows that during La Niña years, the number of feasible weather windows decreases by up to 40%, particularly between October and June, compared to neutral and El Niño years. This decrease can be as high as fourfold in December, significantly impacting installation schedules. Seasonal variations are also notable, with wind speeds exceeding 12 m/s in winter 66.4% of the time, compared to 29.4% in spring, making spring and summer the most favorable periods for installation. However, even during these favorable seasons, La Niña years can bring higher wind speeds, necessitating careful planning. These results underscore the importance of integrating ENSO forecasts into project planning to avoid installation delays and optimize installation timelines. By leveraging seasonal and interannual climate variability predictions, decision-makers can improve the resilience of offshore wind farm projects and ensure efficient energy transition strategies.

East Asian monsoon and Pacific basin dynamics jointly regulate boreal winter marine cold spells in the Taiwan Strait

Marine cold spells (MCSs), characterized by pronounced seawater temperature declines, are representative marine responses to atmospheric and climatic extremes. Notably, during the boreal winter, MCSs in the Taiwan Strait (TS) have caused substantial economic losses due to the concurrence of juvenile development stages in mariculture and labor shortages during China’s New Year vacation. Understanding the spatio-temporal features of MCSs and the underlying mechanisms is imperative for mitigating the associated economic detriments. This study, for the first time, delineates two MCS hotspots in the northeastern and western TS, based on various sea surface temperature datasets. Our findings reveal a notable frequency and intensity of MCSs in the 1980s, followed by a period of suppressed phase, reaching a historic low point in 2002. However, contrary to expectations of the overall trend of global warming, MCSs have experienced a resurgence since 2002, with a pronounced focus on the western coast of the TS. Diagnostic analyses suggest that the Winter East Asian Monsoon-driven cold current and the Pacific basin scale dynamic-forced warm current jointly regulated the spatio-temporal features of the MCSs. This study contributes a novel perspective on the impacts of climate change on extreme marine events along subtropical coastal areas.

Aftermath of the Fourth Taiwan Strait Crisis: Media Discourse Analysis of Taiwan and India’s Perception of China’s Threat

This study examines Taiwan and India’s media discourse and political elite statements from 1 July 2022 to 1 October 2023, starting from the fourth Taiwan Strait crisis in 2022. We conducted a discourse analysis of over 121,901 news texts using extensive data analysis and text-mining software. Additionally, our research team conducted expert focus group discussions with renowned think tanks and research centres in New Delhi, India. Building upon the data text analysis findings, we further explored India’s stance on the Taiwan Strait conflict, its perception of the Chinese threat and the impact of the ongoing ‘new normal’ crisis on India’s Indo-Pacific strategic layout. The aim was to uncover common security needs and intersecting interests between the two countries, considering their different national interests and geopolitical considerations. Based on the analysis of textual mining and expert discussions, this study reveals the following: First, India is concerned about the current situation in the Taiwan Strait. Second, the current tensions in the Taiwan Strait will influence India’s strategic layout. Third, there is a growing consensus within India regarding the Chinese threat. In light of these findings, this study suggests that Taiwan and India share interests in democratic values, maritime traffic security and high-tech industry supply chains. Taiwan possesses expertise in China studies and a deep understanding of China’s military threat, while Taiwan and India possess specific technological capabilities. Based on these foundations, there are potential opportunities for further dialogue, exchange and cooperation in relevant fields between India and Taiwan.

Taiwan Strait: An ocean‐current‐dominated shallow‐water setting with a river‐fed detached muddy contourite deposit

Taiwan Strait: An ocean‐current‐dominated shallow‐water setting with a river‐fed detached muddy contourite deposit

Long-range transport and source apportionment of marine fine particles in the Taiwan Strait and South China Sea Intersection: Spatiotemporal variations and chemical fingerprints

This study aims to investigate the spatiotemporal variation, chemical characteristics and source apportionment of marine fine particles (PM2.5), and to analyze the transport route towards the intersectional region of the Taiwan Strait and South China Sea. Sampling of PM2.5 was conducted simultaneously at Penghu and Dongsha Islands for 14 consecutive days each quarter from summer 2019 to spring 2020. PM2.5 samples were then returned for conditioning, weighting, and chemical analysis. The chemical mass balance (CMB) receptor model was used to identify the potential PM2.5 sources. It results show that the lowest PM2.5 concentrations were observed in summer, with a gradual increase starting fall, influenced by Asia Northeastern Monsoons (ANMs) transporting particles from the north to Penghu and Dongsha Islands. The most abundant water-soluble ionic species in PM2.5 were SO42−, NO3− and NH4+, catalogued as the secondary inorganic aerosols (SIAs). Meanwhile, the most abundant metals in PM2.5 were crustal elements (Mg, K, Ca, Fe, and Al), while the concentrations of trace metals (V, Cr, Mn, Ni, As, Cd, and Pb), mainly from anthropogenic sources, also increased from fall onwards. Organic carbon (OC) was the main species of carbonaceous content of PM2.5 in all seasons, and OC/EC ratios increased during the seasons with prevailing northeastern winds. Anhydrosugar, concentrations in winter and spring were generally higher than those in summer and fall, indicating significant biomass burning occurring in winter and spring. Correlation analysis showed a high correlation between PM2.5 concentrations and chemical composition between two subtropical islands. The correlation of chemical composition for different transportation routes revealed that northern routes had a higher correction than southern routes. Overall, the cross-boundary PM, accounted for 28.4–61.0% and 36.4–76.8% at Penghu and Dongsha Islands, respectively, significantly impacted local air quality, particularly at Dongsha Islands.

Climate change drives fish communities: Changing multiple facets of fish biodiversity in the Northwest Pacific Ocean

Global marine biodiversity is experiencing significant alterations due to climate change. Incorporating phylogenetic and functional diversity may provide novel insights into these impacts. This study used an ensemble model approach (random forest and boosted regression tree), to predict the habitat distribution of 47 fish species in the Northwestern Pacific under contemporary (2000–2014) and future scenarios (2040–2050, 2090–2100). We first examined the relationship between eleven functional traits and habitat changes, predicting the spatial distribution of functional traits within fish communities. A significant correlation was observed between temperature preference and habitat changes, highlighting the vulnerability of cold-water species and potential advantages for warm-water species in the future. Moreover, fish communities exhibited a spatial gradient distribution with southern regions characterized by shorter-lived and earlier maturity, contrasting with longer-lived and later maturity species in the north. Secondly, to assess the impact of climate change on marine biodiversity, we explored the taxonomic, phylogenetic, and functional diversity under contemporary and future scenarios, revealing higher indices in the East China Sea (ECS) and the coastal sea of Japan, with the Taiwan Strait emerging as a contemporary biodiversity hotspot. In future scenarios, the three biodiversity indices would decline in the Yellow Sea and ECS, but increase in the sea beyond the continental shelf, coastal sea of Hokkaido, and Sea of Okhotsk. Lastly, we explored processes and mechanisms in the change of community composition. By quantifying β-diversity, we identified species loss (nestedness) as the primary driver of fish community change by 2040–2050, with species replacement (turnover) predicted to become dominant in the far future. Our results explore the potential changes in multiple facets of fish biodiversity, providing crucial insights for policymakers aiming to protect fish resources and biodiversity.

Analysis of spatial structure and singularity of microbial biogeochemical anomalies in the Taiwan Strait Basin

The abundance of specific hydrocarbon-oxidizing bacteria (MV value) in surface soil is closely linked to the concentration of thermogenic light hydrocarbons found in the underlying layers. The identification of these bacteria using specific detection techniques offers unique insights into microbiological anomalies associated with oil and gas, underscoring the significance of delineating microbiological geochemical anomalies in the exploration process. Accurate determination of the anomaly range is crucial for forecasting potential oil and gas reservoirs. In this study, a variety of fractal and geological statistical methods were employed to analyze microbiological geochemical data from the Taiwan Strait Basin. The multifractal approach allows for the simultaneous assessment of spatial autocorrelation and singularity in geochemical fields, with the fractal distribution reflecting the localized enrichment and depletion patterns of microbiological geochemical elements in rocks and other substrates. Geological statistical methods, such as the variation function, enable the assessment of spatial autocorrelation in geochemical and geophysical fields. The results indicate that microbiological anomalies in the Jiulongjiang Depression are mainly concentrated in the southwestern part of the study area, with some anomalies also observed in the central region. Conversely, microbiological anomalies in the Jinjiang Depression are predominantly located in the southern portion of the study area. Microbiological anomalies in the study area (Jinjiang Depression and Jiulongjiang Depression) exhibit a northeast-southwest strip distribution, aligning with the trend of the depressions and faults, suggesting that faults could influence the distribution of oil and gas resources in the region. Based on microbiological statistical analyses, the Jiulongjiang Depression shows better potential for oil and gas prospects compared to the Jinjiang Depression, guiding future research efforts in the Jiulongjiang Depression.

Allies in the Making: India’s Strategic Partnerships in the Indo-Pacific Strategy

This research explores and analyzes India’s evolving strategic partnerships in the Indo-Pacific region, particularly in the context of increasing Chinese assertiveness and global geopolitical shifts. The current geopolitical landscape, marked by Chinese activities along the Indian border, in the Taiwan Strait, and throughout the Indo-Pacific, underscores the urgent need for cooperation among like-minded nations on regional and global issues. Central to this study is examining the significant transformations in India’s foreign policy since the 1990s. This includes an analysis of the Look East Policy as India’s strategic response to the post-Cold War era, its evolution into the Act East Policy, and India’s emerging role on the international stage through active participation in the Indo-Pacific Strategy. These components collectively underscore India’s strategic realignment and its broader implications on regional dynamics and global diplomacy. Subsequently, the research delves into the burgeoning strategic collaboration between India and Taiwan, focusing on initiating strategic dialogues and progressing from democratic partners to crucial collaborators in constructing the Indo-Pacific supply chain. Furthermore, the research will analyze India’s strategic responses amid increasing tensions in the Taiwan Strait, exploring how it navigates the complex diplomatic and security challenges presented by its One China stance. This includes examining India’s maneuvers within the broader geopolitical framework of the region, highlighting its efforts to balance national security interests with diplomatic engagements.

Spatiotemporal dynamics of dinoflagellate communities in the Taiwan Strait and their correlations with micro-eukaryotic and bacterial communities

Dinoflagellate blooms have negative adverse effects on marine ecosystems. However, our knowledge about the spatiotemporal distribution of dinoflagellate communities and their correlations with micro-eukaryotic and bacterial communities is still rare. Here, the sediment micro-eukaryotic and bacterial communities were explored in the Taiwan Strait (TWS) by 16S and 18S rRNA gene high-throughput sequencing. We found that the dinoflagellates were the most abundant algal group in TWS, and their relative abundance was higher in spring and autumn than in summer. Moreover, the species richness and community composition of dinoflagellates showed strong seasonal patterns. NO3-N and NH4-N had the strongest correlations with the spatiotemporal dynamics of community composition of dinoflagellates. The dinoflagellates had a significantly wider niche breadth than other algal groups for NH4-N, NO3-N and NO2-N, and therefore potentially contributed to a wider distribution range and high abundance in TWS. In addition, the dinoflagellates had stronger impacts on microeukaryotes than on bacteria for both community composition and species richness. However, the dinoflagellates showed close coexistence with bacteria but loose coexistence with microeukaryotes in spring co-occurrence networks. This close coexistence suggests the potentially strong synergy effects between dinoflagellates and bacteria in spring dinoflagellate blooms in TWS. Overall, this study revealed the distribution mechanisms of dinoflagellates in TWS based on niche breadth and also unveiled the different effects of dinoflagellates on micro-eukaryotic and bacterial communities.

Nutrient depletion and phytoplankton shifts driven by the Pearl River plume in the Taiwan Strait

The intrusion of the Pearl River plume into the Taiwan Strait provides a unique case study that challenges traditional assumptions about the impacts of nutrient-rich river plumes on coastal phytoplankton communities. In this study, we conducted a detailed analysis of nutrient dynamics and phytoplankton composition within the Taiwan Strait, focusing on the effects of the Pearl River plume. Our findings reveal significant nutrient depletion, particularly of nitrogen, in the surface waters as the plume extends seaward, resulting in nitrogen limitation and a marked reduction in phytoplankton biomass. Vertical stratification within the Taiwan Strait creates distinct ecological niches, with the mid-layer supporting a deep chlorophyll maximum and the surface layer becoming dominated by the picophytoplankton Synechococcus. This shift from diatom-dominated communities to Synechococcus dominance has far-reaching implications for carbon cycling and food web dynamics in the region. Our results suggest that the Pearl River plume’s influence on the Taiwan Strait represents a departure from the typical nutrient enrichment associated with river plumes, highlighting the complexity of coastal biogeochemical processes.

Effects of Stratification on Wind‐Driven Upwelling Over a Coastal Valley

AbstractIn‐situ observations indicate variations in stratified conditions over the coastal valley off the Sansha Bay in the northwestern Taiwan Strait across different years. However, dynamic processes and mechanisms governing the upwelling process over the valley, as influenced by stratification, are still unknown. By employing idealized numerical simulations, we demonstrate that compared to the unstratified case, the surface offshore flow intensifies, upwelling flux and net cross‐shore transport are enhanced, upwelling area expands, and the cross‐shore velocity structure is modified over the valley under stratified conditions. The primary factor controlling the vertical velocity within the valley is the relative vorticity change along a streamline (RVC). Further decomposition of the RVC reveals that the depth‐averaged alongshore velocity () and the depth‐averaged alongshore gradient of vorticity () primarily modulate the magnitude and spatial distribution of the vertical velocity. The negative zone of the expands in the valley, resulting in a larger upwelling area. The magnitude of the in the upper layer is slightly enhanced. The combined influence of these two factors leads to increased upwelling flux in the valley under stratified conditions. The net upslope motion over the valley is intensified under stratified conditions. The augmented advection of relative potential vorticity, originating from the increased amplitude of coastal trapped lee waves, primarily contributes to the enhanced net cross‐shore transport in the valley.

The cost of green: Analyzing the economic feasibility of hydrogen production from offshore wind power

Wind energy is a cornerstone for enhancing grid stability and augmenting energy storage solutions, especially through its synergy with green hydrogen production. While substantial research has analyzed the economic dynamics of offshore wind and green hydrogen, the impact of offshore distances on hydrogen production costs remains underexplored. This study introduces a novel, globally applicable modeling framework for the Levelized Cost of Hydrogen (LCOH), illustrated using the strategically significant Taiwan Strait as a case study. By employing net present value analysis, we compare centralized, distributed, and onshore hydrogen production scenarios, documenting the lowest current LCOH values at $10.27, $10.31, and $11.32 per kg of hydrogen respectively. These findings highlight the cost-effectiveness of the centralized configuration and emphasize the significant costs linked to transmission infrastructure in onshore setups. Looking ahead to 2035, our framework predicts substantial reductions in LCOH, with low-cost scenarios forecasting profitability at just $9 per kilogram of hydrogen. Powered by the universally accessible ERA5 reanalysis dataset, our approach supports analogous assessments worldwide, thereby aiding strategic planning and the deployment of renewable technologies. In-depth sensitivity and Monte Carlo analyses further enhance our understanding of the impacts of offshore distance and other key factors, bolstering the economic evaluation of green hydrogen production. This comprehensive methodology not only assesses present capabilities but also facilitates broad application, fostering the strategic development of renewable technologies globally

Analysis of the Impact of Taiwan Strait Tensions on South Korea-China Maritime Disputes

Analysis of the Impact of Taiwan Strait Tensions on South Korea-China Maritime Disputes

Unsupervised Machine Learning-Based Singularity Models: A Case Study of the Taiwan Strait Basin

The identification of geochemical anomalies in oil and gas indicators is a fundamental task in oil and gas exploration, as the process of oil and gas accumulation is a low probability event. Machine learning algorithms for anomaly detection are applicable to the identification of oil and gas geochemical anomalies related to oil and gas accumulation. However, when using oil and gas indicators for anomaly detection, the diversity of these indicators often leads to the influence of the indicator redundancy on the identification of such features. Therefore, it is particularly important to select appropriate oil and gas indicators for anomaly detection. In this study, a hybrid model combining unsupervised machine learning methods and singularity analysis methods was used to evaluate oil and gas indicator anomalies using geochemical data from the Taiwan Strait Basin. The models used in this study include the singularity index model (LSP), the principal component model combined with the singularity index model (PCA and LSP), and the cluster analysis combined with the principal component model and the singularity index model (CLA-PCA-LSP). PCA models can reduce the dimensions of the data and retain as much information as possible. CLA divides data samples into different groups, so that samples within the same group are more similar and samples between different groups are less similar. LSP is mainly used for measuring the setting and singular degree of local anomalies in multi-scale geochemistry, geophysics, and other types of local anomalies, and it has a unique advantage in extracting low and weak anomalies and nonlinear characteristics. The results of the study show that the results obtained using the CLA-PCA-LSP hybrid model are very similar to those obtained by performing PCA on the entire index and then calculating the singularity index. This also verifies that, for the study areas of the Jiulongjiang Depression and Jinjiang Depression, we can select oil and gas indicators that are favorable for exploration analysis, without including all indicators in the analysis scope, thereby improving the computational efficiency. The application of a singularity analysis method and generalized self-similarity principle in extracting the geochemical information of oil and gas indicators in the Taiwan Strait Basin highlights key technologies such as the identification of weak anomalies, decomposition of composite anomalies, and integration of spatial information. The combination anomalies delineated by the singularity analysis method and S-A method not only reflect the spatial relationship with known oil and gas reservoir distribution, but also show the multiple combination anomalies in unknown areas, providing favorable guidance for the next exploration direction in the Taiwan Strait Basin.

Identifying the spatio-temporal distribution characteristics of offshore wind turbines in China from Sentinel-1 imagery using deep learning

ABSTRACT Offshore wind power is a crucial clean energy source for coastal countries and advances blue economies. Accurate spatial mapping of offshore wind turbines supports energy assessment and the sustainable development of marine resources. Offshore wind power has developed rapidly in China, but the spatiotemporal distribution characteristics of offshore wind turbines and farms remain poorly understood. Extracting nearshore small targets from Sentinel-1 synthetic aperture radar images remain challenging due to noise from the rough sea surface background and the diverse substrate types in offshore wind turbine (OWT) distributions. Here, to address these issues, we first created a dataset of China’s offshore wind turbines (COWTs) that contained typical substrate types (e.g. seawater and tidal flats). Then, a deep learning model integrating an attention mechanism and receptive fields was used to accurately detect COWTs. The well-trained model was used to detect the changes in COWTs from 2015 to 2022. Our model detected an increase in the number of offshore wind farms in China from 7 to 114 (clusters counted as an offshore wind farm), while COWTs increased from 305 to 6451 from 2015 to 2022. The Taiwan Strait exhibited the highest wind speeds, yet the Jiangsu and Guangdong regions had the most installed turbines. Over 90% of COWTs were located in areas with offshore wind energy resources less than 500 W/m3, indicating a mismatch between COWT installation and wind resource distribution. This study demonstrated temporal and geographical generalizability, which is promising for global wind power detection. Our analysis of spatiotemporal variation in COWTs facilitates informed decision-making for future field establishment and sustainable marine planning.

Economic Globalization Under a New Cold War: Taiwan's Ambiguous and Critical Role

Abstract Producing 92 percent of the world's high-end chips, a critical component for the United States and a strategic asset China aims to control, Taiwan plays an important role in the New Cold War amid escalating tensions in the Taiwan Strait. Several conclusions emerge from the analysis of this role. First, improved communication among the United States, China, and Taiwan is essential. Second, a peaceful Taiwan Strait benefits all parties, as a Chinese invasion of Taiwan would have catastrophic global repercussions. Third, the future of Taiwan's status and the world economy heavily depends on the evolution of U.S.–China relations and whether China opts for aggressive or peaceful policies.

Influence of increasing noise at the offshore wind farm area on fish vocalization phenology: A long-term marine acoustical monitoring off the foremost offshore wind farm in Taiwan

The rapid increase of offshore projects at Taiwan Strait in recent decade has been debated for elevated noise levels. However, there are no studies on long-term assessment of noise levels and impact of noise on marine organisms. The passive acoustic monitoring was conducted at the foremost wind farm area in Taiwan to assess the sound levels and the impact of noise on fish vocalization behavior. Predominately, in the soundscape around the Taiwan Strait, two chorusing types (Type 1 and Type 2) from the Sciaenid family of fishes exist. Ambient sound levels significantly increased from 2014 to 2019, while the chorusing Types 1 and 2 were observed in a lower percentage of the recordings. Additionally, chorusing peak intensity and duration significantly reduced over the years for both choruses. This is the first field-based evidence to demonstrate the consequences of increasing anthropogenic noise having the potential to alter the vocalization behavior of the fish.