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Kuo-Wei Lan
Department of Environmental Biology and Fisheries Science, College of Ocean Science and Resources, National Taiwan Ocean University, Taiwan

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Original research article
Published: 13 April 2021 in Frontiers in Marine Science
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How top predators behave and are distributed depend on the conditions in their marine ecosystem through bottom−up forcing; this is because where and when these predators can feed and spawn are limited and change often. This study investigated how the catch rates of immature and mature cohorts of bigeye tuna (BET) varied across space and time; this was achieved by analyzing data on the Taiwanese longline fishery in the western and central Pacific Ocean (WCPO). We also conducted a case study on the time series patterns of BET cohorts to explore the processes that underlie the bottom-up control of the pelagic ecosystem that are influenced by decadal climate events. Wavelet analysis results revealed crucial synchronous shifts in the connection between the pelagic ecosystems at low trophic levels in relation to the immature BET cohort. Many variables exhibited decreasing trends after 2004–2005, and we followed the Pacific Decadal Oscillation (PDO) as a bottom-up control regulator. The results indicated that low recruitment into the mature cohort occurs 3 years after a decrease in the immature cohort’s food stocks, as indicated by a 3-year lag in our results. This finding demonstrated that, by exploring the connection between low-trophic-level species and top predators at various life stages, we can better understand how climate change affects the distribution and abundance of predator fish.

ACS Style

Kuo-Wei Lan; Yan-Lun Wu; Lu-Chi Chen; Muhamad Naimullah; Tzu-Hsiang Lin. Effects of Climate Change in Marine Ecosystems Based on the Spatiotemporal Age Structure of Top Predators: A Case Study of Bigeye Tuna in the Pacific Ocean. Frontiers in Marine Science 2021, 8, 1 .

AMA Style

Kuo-Wei Lan, Yan-Lun Wu, Lu-Chi Chen, Muhamad Naimullah, Tzu-Hsiang Lin. Effects of Climate Change in Marine Ecosystems Based on the Spatiotemporal Age Structure of Top Predators: A Case Study of Bigeye Tuna in the Pacific Ocean. Frontiers in Marine Science. 2021; 8 ():1.

Chicago/Turabian Style

Kuo-Wei Lan; Yan-Lun Wu; Lu-Chi Chen; Muhamad Naimullah; Tzu-Hsiang Lin. 2021. "Effects of Climate Change in Marine Ecosystems Based on the Spatiotemporal Age Structure of Top Predators: A Case Study of Bigeye Tuna in the Pacific Ocean." Frontiers in Marine Science 8, no. : 1.

Journal article
Published: 19 February 2021 in Remote Sensing
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The Taiwan Bank (TB) is located in the southern Taiwan Strait, where the marine environments are affected by South China Sea Warm Current and Kuroshio Branch Current in summer. The bottom water flows upward along the edge of the continental shelf, forming an upwelling region that is an essential high-productivity fishing ground. Using trophic dynamic theory, fishery resources can be converted into primary production required (PPR) by primary production, which indicates the environmental tolerance of marine ecosystems. This study calculated the PPR of benthic and pelagic species, sea surface temperature (SST), upwelling size, and net primary production (NPP) to analyze fishery resource structure and the spatial distribution of PPR in upwelling, non-upwelling, and thermal front (frontal) areas of the TB in summer. Pelagic species, predominated by those in the Scombridae, Carangidae families and Trachurus japonicus, accounted for 77% of PPR (67% of the total catch). The benthic species were dominated by Mene maculata and members of the Loliginidae family. The upwelling intensity was the strongest in June and weakest in August. Generalized additive models revealed that the benthic species PPR in frontal habitats had the highest deviance explained (28.5%). Moreover, frontal habitats were influenced by NPP, which was also the main factor affecting the PPR of benthic species in all three habitats. Pelagic species were affected by high NPP, as well as low SST and negative values of the multivariate El Niño–Southern Oscillation (ENSO) index in upwelling habitats (16.9%) and non-upwelling habitats (11.5%). The composition of pelagic species varied by habitat; this variation can be ascribed to impacts from the ENSO. No significant differences were noted in benthic species composition. Overall, pelagic species resources are susceptible to climate change, whereas benthic species are mostly insensitive to climatic factors and are more affected by NPP.

ACS Style

Po-Yuan Hsiao; Teruhisa Shimada; Kuo-Wei Lan; Ming-An Lee; Cheng-Hsin Liao. Assessing Summertime Primary Production Required in Changed Marine Environments in Upwelling Ecosystems Around the Taiwan Bank. Remote Sensing 2021, 13, 765 .

AMA Style

Po-Yuan Hsiao, Teruhisa Shimada, Kuo-Wei Lan, Ming-An Lee, Cheng-Hsin Liao. Assessing Summertime Primary Production Required in Changed Marine Environments in Upwelling Ecosystems Around the Taiwan Bank. Remote Sensing. 2021; 13 (4):765.

Chicago/Turabian Style

Po-Yuan Hsiao; Teruhisa Shimada; Kuo-Wei Lan; Ming-An Lee; Cheng-Hsin Liao. 2021. "Assessing Summertime Primary Production Required in Changed Marine Environments in Upwelling Ecosystems Around the Taiwan Bank." Remote Sensing 13, no. 4: 765.

Journal article
Published: 20 August 2020 in Remote Sensing
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Despite numerous studies on the effect of a cold weather disaster on fisheries in 2008, no operational systems have been developed to monitor the threat of such an event to mariculturists in the Penghu Islands (PHI) region of Taiwan. The present study employed a suitable aquaculture site selection map of the inner bay of the PHI to reduce aquaculture losses and mortality rates of cobia (Rachycentron canadum) during extreme events. Daily marine environmental data, including sea surface temperature (SST), chlorophyll-a concentration (chl-a), and wind speed in the winter, were collected. An extreme event was defined as a period of over 11 days in a month of strong winds (>6 m/s). Four parameters in the PHI inner bay, including SST, cold-water intrusion days, chl-a, and offshore distance to the PHI coastline, were used to evaluate suitable aquaculture sites for cobia culture. The results indicated that La Niña events could not be used as a factor to detect cold-water intrusion events and select suitable aquaculture sites in the PHI. The evaluated suitable aquaculture site selection map, obtained using an arithmetic mean model and a geometric mean model, revealed that the avoidance sites during extreme events were concentrated in the northern and northwestern PHI. Suitable areas were concentrated in the southeastern areas. We further suggested that commercial cobia aquaculture operations in the PHI inner bay could be moved to the suitable sites in southeastern PHI during extreme events.

ACS Style

Yan-Lun Wu; Ming-An Lee; Lu-Chi Chen; Jui-Wen Chan; Kuo-Wei Lan. Evaluating a Suitable Aquaculture Site Selection Model for Cobia (Rachycentron canadum) during Extreme Events in the Inner Bay of the Penghu Islands, Taiwan. Remote Sensing 2020, 12, 2689 .

AMA Style

Yan-Lun Wu, Ming-An Lee, Lu-Chi Chen, Jui-Wen Chan, Kuo-Wei Lan. Evaluating a Suitable Aquaculture Site Selection Model for Cobia (Rachycentron canadum) during Extreme Events in the Inner Bay of the Penghu Islands, Taiwan. Remote Sensing. 2020; 12 (17):2689.

Chicago/Turabian Style

Yan-Lun Wu; Ming-An Lee; Lu-Chi Chen; Jui-Wen Chan; Kuo-Wei Lan. 2020. "Evaluating a Suitable Aquaculture Site Selection Model for Cobia (Rachycentron canadum) during Extreme Events in the Inner Bay of the Penghu Islands, Taiwan." Remote Sensing 12, no. 17: 2689.

Journal article
Published: 11 July 2020 in Remote Sensing
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Information regarding the oceanic environment is crucial for determining species distributions and their habitat preferences. However, in studies on crustaceans, especially swimming crabs, such information remains poorly utilized, and its effects on crab communities in the Taiwan Strait (TS) has not been well documented. The purpose of this study was to understand the relationship between the catch rates of three swimming crab species and environmental factors in the TS. We fitted generalized additive models (GAMs) to logbooks and voyage data recorder data from Taiwanese crab vessels (2011–2015), developed a species distribution model, and predicted catch rates for these three swimming crab species based on the GAM output. The chlorophyll-a (Chl-a) concentration was related to the high catch rates of Chrybdis feriatus and Portunus sanguinolentus, whereas bottom temperature (BT) was related to high catch rates of Portunus pelagicus. The variance percentages for each crab species indicated that high catch rates of C. feriatus and P. sanguinolentus occurred in a Chl-a concentration > 0.5 mg/m3, whereas P. pelagicus catch rates exhibited negative correlations with BTs > 25 °C. The model predicted high catch rates of C. feriatus in the north of the TS during autumn and winter, whereas P. pelagicus was observed to the south during summer and autumn. P. sanguinolentus was predicted to be widely distributed around the TS and distributed further to the northern area during autumn and winter. These findings revealed that each species responds to spatiotemporal environmental variations. Understanding the distributions and habitats of these three crabs is vital in fisheries resource management and conservation planning.

ACS Style

Muhamad Naimullah; Kuo-Wei Lan; Cheng-Hsin Liao; Po-Yuan Hsiao; Yen-Rong Liang; Ting-Chen Chiu. Association of Environmental Factors in the Taiwan Strait with Distributions and Habitat Characteristics of Three Swimming Crabs. Remote Sensing 2020, 12, 2231 .

AMA Style

Muhamad Naimullah, Kuo-Wei Lan, Cheng-Hsin Liao, Po-Yuan Hsiao, Yen-Rong Liang, Ting-Chen Chiu. Association of Environmental Factors in the Taiwan Strait with Distributions and Habitat Characteristics of Three Swimming Crabs. Remote Sensing. 2020; 12 (14):2231.

Chicago/Turabian Style

Muhamad Naimullah; Kuo-Wei Lan; Cheng-Hsin Liao; Po-Yuan Hsiao; Yen-Rong Liang; Ting-Chen Chiu. 2020. "Association of Environmental Factors in the Taiwan Strait with Distributions and Habitat Characteristics of Three Swimming Crabs." Remote Sensing 12, no. 14: 2231.

Journal article
Published: 19 May 2020 in Remote Sensing
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Basin-scale sampling for high frequency oceanic primary production (PP) is available from satellites and must achieve a strong match-up with in situ observations. This study evaluated a regionally high-resolution satellite-derived PP using a vertically generalized production model (VGPM) with in situ PP. The aim was to compare the root mean square difference (RMSD) and relative percent bias (Bias) in different water masses around Taiwan. Determined using light–dark bottle methods, the spatial distribution of VGPM derived from different Chl-a data of MODIS Aqua (PPA), MODIS Terra (PPT), and averaged MODIS Aqua and Terra (PPA&T) exhibited similar seasonal patterns with in situ PP. The three types of satellite-derived PPs were linearly correlated with in situ PPs, the coefficients of which were higher throughout the year in PPA&T (r2 = 0.61) than in PPA (r2 = 0.42) and PPT (r2 = 0.38), respectively. The seasonal RMSR and bias for the satellite-derived PPs were in the range of 0.03 to 0.09 and −0.14 to −0.39, respectively, which suggests the PPA&T produces slightly more accurate PP measurements than PPA and PPT. On the basis of environmental conditions, the subareas were further divided into China Coast water, Taiwan Strait water, Northeastern upwelling water, and Kuroshio water. The VPGM PP in the four subareas displayed similar features to Chl-a variations, with the highest PP in the China Coast water and lowest PP in the Kuroshio water. The RMSD was higher in the Kuroshio water with an almost negative bias. The PPA exhibited significant correlations with in situ PP in the subareas; however, the sampling locations were insufficient to yield significant results in the China Coast water.

ACS Style

Kuo-Wei Lan; Li-Jhih Lian; Chun-Huei Li; Po-Yuan Hsiao; Sha-Yan Cheng. Validation of a Primary Production Algorithm of Vertically Generalized Production Model Derived from Multi-Satellite Data around the Waters of Taiwan. Remote Sensing 2020, 12, 1627 .

AMA Style

Kuo-Wei Lan, Li-Jhih Lian, Chun-Huei Li, Po-Yuan Hsiao, Sha-Yan Cheng. Validation of a Primary Production Algorithm of Vertically Generalized Production Model Derived from Multi-Satellite Data around the Waters of Taiwan. Remote Sensing. 2020; 12 (10):1627.

Chicago/Turabian Style

Kuo-Wei Lan; Li-Jhih Lian; Chun-Huei Li; Po-Yuan Hsiao; Sha-Yan Cheng. 2020. "Validation of a Primary Production Algorithm of Vertically Generalized Production Model Derived from Multi-Satellite Data around the Waters of Taiwan." Remote Sensing 12, no. 10: 1627.

Journal article
Published: 01 May 2020 in Deep Sea Research Part II: Topical Studies in Oceanography
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The yellowfin tuna (Thunnus albacares; YFT) is a crucial species because it is the second most fished tuna globally. In this study, we analyzed the standardized catch per unit effort (CPUE) to determine the influence of climate indices on YFT distribution and fishing vessel dynamics. The standardized CPUE in the western Pacific Ocean was significantly correlated to the Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO) with a 1–5 year lag. These CPUE-climate index relationships were also observed in other ocean basins but with lower significant correlations. The Atlantic Multidecadal Oscillation (AMO) and standardized CPUE were significantly negatively correlated in the Atlantic, eastern Pacific, and western Pacific Oceans and positively correlated in the eastern Indian Ocean with a 1–5 year lag. The wavelet analysis revealed approximately 8–16-year periodicity across 1971 to 2010 between the standardized YFT CPUE and multidecadal climate indices (AMO, PDO, and NPGO). This finding suggests that decadal climate indices affect both YFT regional distributions and the long-term availability to fisheries, which may affect overall abundance. Two interannual climate indices, the Indian Ocean Dipole (IOD) and Oceanic Niño Index (ONI), were significantly correlated with the center of gravity of fishing grounds in the adjacent ocean basin. Furthermore, the influence of climate indices on the longitudinal centers of gravity was mostly limited to adjacent basins, which suggests that climate phenomena have wide-reaching teleconnections that affect large areas across and between basins.

ACS Style

Yan-Lun Wu; Kuo-Wei Lan; Yong-Jun Tian. Determining the effect of multiscale climate indices on the global yellowfin tuna (Thunnus albacares) population using a time series analysis. Deep Sea Research Part II: Topical Studies in Oceanography 2020, 175, 104808 .

AMA Style

Yan-Lun Wu, Kuo-Wei Lan, Yong-Jun Tian. Determining the effect of multiscale climate indices on the global yellowfin tuna (Thunnus albacares) population using a time series analysis. Deep Sea Research Part II: Topical Studies in Oceanography. 2020; 175 ():104808.

Chicago/Turabian Style

Yan-Lun Wu; Kuo-Wei Lan; Yong-Jun Tian. 2020. "Determining the effect of multiscale climate indices on the global yellowfin tuna (Thunnus albacares) population using a time series analysis." Deep Sea Research Part II: Topical Studies in Oceanography 175, no. : 104808.

Journal article
Published: 24 October 2019 in Deep Sea Research Part II: Topical Studies in Oceanography
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Using Taiwanese longline fishery data, this study investigated the influence of climate variability and environmental conditions in the Indian Ocean on the catch rates and distribution of immature and mature cohorts of yellowfin tuna. The variations in the seasonal distribution of immature and mature cohorts suggest that yellowfin tuna move extensively from the Arabian Sea and Bay of Bengal to the coastal waters of Somalia and around Madagascar in the Indian Ocean. The high recruitments of the immature cohort were found in 1998–2002, and the catch rate of the immature and mature cohorts revealed positive associations with periodicities of approximately 3–4 years. We found that the distributions and catch rates of the two cohorts were sensitive to variations in climatic and marine environments. Sea surface temperature was the most influential environmental variable for both cohorts, and Chl-a was not statistically significant for the immature cohort. There was a significant negative correlation between the catch rate of the immature and mature cohort and Indian Ocean Dipoles (IODs), with periodicities of approximately 3 years during the study period, and had periodicities of approximately 1–3 years with El Niño/Southern Oscillation (ENSO) events. Furthermore, the influence of IODs exhibited greater variance than that of ENSO events, and the influence of ENSO was only evident near the Arabian Sea. The influence of concurrent positive IOD and El Niño events led to lower catch rates for the mature cohort in 2008–2009 in the northwestern Indian Ocean.

ACS Style

Kuo-Wei Lan; Yi-Jay Chang; Yan-Lun Wu. Influence of oceanographic and climatic variability on the catch rate of yellowfin tuna (Thunnus albacares) cohorts in the Indian Ocean. Deep Sea Research Part II: Topical Studies in Oceanography 2019, 175, 104681 .

AMA Style

Kuo-Wei Lan, Yi-Jay Chang, Yan-Lun Wu. Influence of oceanographic and climatic variability on the catch rate of yellowfin tuna (Thunnus albacares) cohorts in the Indian Ocean. Deep Sea Research Part II: Topical Studies in Oceanography. 2019; 175 ():104681.

Chicago/Turabian Style

Kuo-Wei Lan; Yi-Jay Chang; Yan-Lun Wu. 2019. "Influence of oceanographic and climatic variability on the catch rate of yellowfin tuna (Thunnus albacares) cohorts in the Indian Ocean." Deep Sea Research Part II: Topical Studies in Oceanography 175, no. : 104681.

Article
Published: 09 August 2018 in Marine and Coastal Fisheries
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Predictions from species distribution models are used to parameterize the environmental factors that influence the biology, distribution, and habitats of a species of interest. We fitted generalized additive models (GAMs) to spatiotemporal fishery data from torchlight fishing (2009–2013) to investigate the catch rates of swordtip squid Uroteuthis edulis in relation to changes in oceanographic conditions within the southern East China Sea, and we developed a habitat preference model. A high Jensen–Shannon divergence (JSD) value is considered to be an index of a thermal front. The results obtained using the selected GAMs revealed that the explained deviance in the catch rates pertaining to the oceanographic conditions was 45.10% throughout the year. All variables examined—sea surface temperature (SST), chlorophyll‐a, sea surface height anomaly, and JSD—were statistically significant predictors (P < 0.05), and JSD explained the greatest amount of deviance (17.70%). The model predicted relatively high abundance of swordtip squid at 27–28°N in the southern East China Sea during spring and a decrease from June to August. The high abundance occurred again in September and extended southwestwardly to a region including coastal mainland China. These results demonstrated that high swordtip squid abundance occurred in an SST range of 20.0–26.0°C and a JSD range of 0.35–0.50 during spring around 27–28°N, and movement toward the southwest corresponded with shifts in the Kuroshio front (26°C isotherm) in summer and autumn.

ACS Style

Cheng-Hsin Liao; Kuo-Wei Lan; Hsin-Ying Ho; Kae-Yih Wang; Yan-Lun Wu. Variation in the Catch Rate and Distribution of Swordtip SquidUroteuthis edulisAssociated with Factors of the Oceanic Environment in the Southern East China Sea. Marine and Coastal Fisheries 2018, 10, 452 -464.

AMA Style

Cheng-Hsin Liao, Kuo-Wei Lan, Hsin-Ying Ho, Kae-Yih Wang, Yan-Lun Wu. Variation in the Catch Rate and Distribution of Swordtip SquidUroteuthis edulisAssociated with Factors of the Oceanic Environment in the Southern East China Sea. Marine and Coastal Fisheries. 2018; 10 (4):452-464.

Chicago/Turabian Style

Cheng-Hsin Liao; Kuo-Wei Lan; Hsin-Ying Ho; Kae-Yih Wang; Yan-Lun Wu. 2018. "Variation in the Catch Rate and Distribution of Swordtip SquidUroteuthis edulisAssociated with Factors of the Oceanic Environment in the Southern East China Sea." Marine and Coastal Fisheries 10, no. 4: 452-464.

Original article
Published: 01 June 2018 in Fisheries Oceanography
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The environmental processes associated with variability in the catch rates of bigeye tuna in the Atlantic Ocean are largely unexplored. This study used generalized additive models (GAMs) fitted to Taiwanese longline fishery data from 1990 to 2009 and investigated the association between environmental variables and catch rates to identify the processes influencing bigeye tuna distribution in the Atlantic Ocean. The present findings reveal that the year (temporal factor), latitude and longitude (spatial factors), and major regular longline target species of albacore catches are significant for the standardization of bigeye tuna catch rates in the Atlantic Ocean. The standardized catch rates and distribution of bigeye tuna were found to be related to environmental and climatic variation. The model selection processes showed that the selected GAMs explained 70% of the cumulative deviance in the entire Atlantic Ocean. Regarding environmental factors, the depth of the 20 degree isotherm (D20) substantially contributed to the explained deviance; other important factors were sea surface temperature (SST) and sea surface height deviation (SSHD). The potential fishing grounds were observed with SSTs of 22–28°C, a D20 shallower than 150 m and negative SSHDs in the Atlantic Ocean. The higher predicted catch rates were increased in the positive northern tropical Atlantic and negative North Atlantic Oscillation events with a higher SST and shallow D20, suggesting that climatic oscillations affect the population abundance and distribution of bigeye tuna.

ACS Style

Kuo-Wei Lan; Ming-An Lee; Chin-Pei Chou; Ali Haghi Vayghan. Association between the interannual variation in the oceanic environment and catch rates of bigeye tuna (Thunnus obesus) in the Atlantic Ocean. Fisheries Oceanography 2018, 27, 395 -407.

AMA Style

Kuo-Wei Lan, Ming-An Lee, Chin-Pei Chou, Ali Haghi Vayghan. Association between the interannual variation in the oceanic environment and catch rates of bigeye tuna (Thunnus obesus) in the Atlantic Ocean. Fisheries Oceanography. 2018; 27 (5):395-407.

Chicago/Turabian Style

Kuo-Wei Lan; Ming-An Lee; Chin-Pei Chou; Ali Haghi Vayghan. 2018. "Association between the interannual variation in the oceanic environment and catch rates of bigeye tuna (Thunnus obesus) in the Atlantic Ocean." Fisheries Oceanography 27, no. 5: 395-407.

Journal article
Published: 05 May 2017 in Remote Sensing
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Changes in marine environments affect fishery resources at different spatial and temporal scales in marine ecosystems. Predictions from species distribution models are available to parameterize the environmental characteristics that influence the biology, range, and habitats of the species of interest. This study used generalized additive models (GAMs) fitted to two spatiotemporal fishery data sources, namely 1° spatial grid and observer record longline fishery data from 2006 to 2010, to investigate the relationship between catch rates of yellowfin tuna and oceanographic conditions by using multispectral satellite images and to develop a habitat preference model. The results revealed that the cumulative deviances obtained using the selected GAMs were 33.6% and 16.5% in the 1° spatial grid and observer record data, respectively. The environmental factors in the study were significant in the selected GAMs, and sea surface temperature explained the highest deviance. The results suggest that areas with a higher sea surface temperature, a sea surface height anomaly of approximately −10.0 to 20 cm, and a chlorophyll-a concentration of approximately 0.05–0.25 mg/m3 yield higher catch rates of yellowfin tuna. The 1° spatial grid data had higher cumulative deviances, and the predicted relative catch rates also exhibited a high correlation with observed catch rates. However, the maps of observer record data showed the high-quality spatial resolutions of the predicted relative catch rates in the close-view maps. Thus, these results suggest that models of catch rates of the 1° spatial grid data that incorporate relevant environmental variables can be used to infer possible responses in the distribution of highly migratory species, and the observer record data can be used to detect subtle changes in the target fishing grounds.

ACS Style

Kuo-Wei Lan; Teruhisa Shimada; Ming-An Lee; Nan-Jay Su; Yi Chang. Using Remote-Sensing Environmental and Fishery Data to Map Potential Yellowfin Tuna Habitats in the Tropical Pacific Ocean. Remote Sensing 2017, 9, 444 .

AMA Style

Kuo-Wei Lan, Teruhisa Shimada, Ming-An Lee, Nan-Jay Su, Yi Chang. Using Remote-Sensing Environmental and Fishery Data to Map Potential Yellowfin Tuna Habitats in the Tropical Pacific Ocean. Remote Sensing. 2017; 9 (5):444.

Chicago/Turabian Style

Kuo-Wei Lan; Teruhisa Shimada; Ming-An Lee; Nan-Jay Su; Yi Chang. 2017. "Using Remote-Sensing Environmental and Fishery Data to Map Potential Yellowfin Tuna Habitats in the Tropical Pacific Ocean." Remote Sensing 9, no. 5: 444.

Journal article
Published: 16 March 2016 in Sustainability
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In this study, we analyzed the fish species composition data of coastal capture fisheries in Taiwan between 1963 and 2010. The purpose of the analysis was to understand the long-term changes in marine ecosystems. A ratio-to-moving average method was used in conjunction with adjusted seasonal indices to determine the seasonality of individual catch items and to examine the trends shown by the species with the same seasonality. Over the 48-year timespan of the data, 31 species, i.e., 64% of the total number of species, were identified as seasonal migrants. The catch ratio for species showing a single peak in the spring increased steadily over time; however, those species with a single peak in the winter decreased. The catch ratio for those species with dual peaks in both summer and fall varied greatly before 1978. Increasing trends began in the 1980s and accelerated until 1998. As a result of this increase, the previous concentration of the fishing season in the winter months became highly diffuse. Additionally, the winter and/or spring species continued to decrease year after year as the summer and/or autumn species gradually came to dominate the catch. This change in fishing seasonality is likely not an anthropogenic effect. However, the change coincides with trends in sea surface temperature fluctuations. Such variation may not only cause structural change in marine ecosystems but can also significantly impact the economy and the livelihoods of those associated with the fishing trade.

ACS Style

Ching-Hsien Ho; Hsueh-Jung Lu; Jia-Sin He; Kuo-Wei Lan; Jyun-Long Chen. Changes in Patterns of Seasonality Shown by Migratory Fish under Global Warming: Evidence from Catch Data of Taiwan’s Coastal Fisheries. Sustainability 2016, 8, 273 .

AMA Style

Ching-Hsien Ho, Hsueh-Jung Lu, Jia-Sin He, Kuo-Wei Lan, Jyun-Long Chen. Changes in Patterns of Seasonality Shown by Migratory Fish under Global Warming: Evidence from Catch Data of Taiwan’s Coastal Fisheries. Sustainability. 2016; 8 (3):273.

Chicago/Turabian Style

Ching-Hsien Ho; Hsueh-Jung Lu; Jia-Sin He; Kuo-Wei Lan; Jyun-Long Chen. 2016. "Changes in Patterns of Seasonality Shown by Migratory Fish under Global Warming: Evidence from Catch Data of Taiwan’s Coastal Fisheries." Sustainability 8, no. 3: 273.