Habitat characteristics of skipjack tuna ( Katsuwonus pelamis ) in the western North Pacific: a remote sensing perspective

MUGO, ROBINSON; SAITOH, SEI‐ICHI; NIHIRA, AKIRA; KUROYAMA, TADAAKI

doi:10.1111/j.1365-2419.2010.00552.x

Cited by 149Marine and fisheries researchOceanographic and Atmospheric ProcessesFish Ecology and Management Studies

Habitat characteristics of skipjack tuna ( Katsuwonus pelamis ) in the western North Pacific: a remote sensing perspective

MUGO, ROBINSON, SAITOH, SEI‐ICHI, NIHIRA, AKIRA, KUROYAMA, TADAAKI·2010·Fisheries Oceanography

DOI 10.1111/j.1365-2419.2010.00552.x

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Abstract

Skipjack tuna habitat in the western North Pacific was studied from satellite remotely sensed environment and catch data, using generalized additive models and geographic information systems. Weekly resolved remotely sensed sea surface temperature, surface chlorophyll, sea surface height anomalies and eddy kinetic energy data were used for the year 2004. Fifteen generalized additive models were constructed with skipjack catch per unit effort as a response variable, and sea surface temperature, sea surface height anomalies and eddy kinetic energy as model covariates to assess the effect of environment on catch per unit effort (skipjack tuna abundance). Model selection was based on significance of model terms, reduction in Akaike’s Information Criterion, and increase in cumulative deviance explained. The model selected was used to predict skipjack tuna catch per unit effort using monthly resolved environmental data for assessing model performance and to visualize the basin scale distribution of skipjack tuna habitat. Predicted values were validated using a linear model. Based on the four‐parameter model, skipjack tuna habitat selection was significantly ( P < 0.01) influenced by sea surface temperatures ranging from 20.5 to 26°C, relatively oligotrophic waters (surface chlorophyll 0.08–0.18, 0.22–0.27 and 0.3–0.37 mg m −3 ), zero to positive anomalies (surface height anomalies 0–50 cm), and low to moderate eddy kinetic energy (0–200 and 700–2500 cm 2 s –2 ). Predicted catch per unit effort showed a trend consistent with the north–south migration of skipjack tuna. Validation of predicted catch per unit effort with that observed, pooled monthly, was significant ( P < 0.01, r 2 = 0.64). Sea surface temperature explained the highest deviance in generalized additive models and was therefore considered the best habitat predictor.

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Skipjack tuna habitat selection is significantly influenced by SST ranging from 20.5 to 26°C in the Pacific Ocean.
“Based on the oceanic parameter model, skipjack tuna habitat selection was significantly (p < 0.01) influenced by SST ranging from 20.5 to 26°C in the Pacific Ocean (Mugo et al. 2010).”
From El Niño Southern Oscillation (ENSO) impact on tuna fisheries in Indian Ocean (2014) · cites this paper as Mugo et al. 2010
GAMs have been previously used to study habitat preferences of many tuna species using fishery data, larval survey data, and electronic tagging data.
“GAMs have been previously used to study habitat preferences of many tuna species using fishery data (Lan et al., 2013;Maury et al., 2001;Mugo et al., 2010;Sagarminaga and Arrizabalaga 2010), larval survey data (Rooker et al., 2013) as well as electronic tagging data (Hazen et al., 2013).”
From Global habitat preferences of commercially valuable tuna (2015) · cites this paper as Mugo et al., 2010
Some environmental variables (e.g., temperature, DCHL) have been used in previous studies, but description of habitat preferences based on other variables (e.g., MLD, ZOO) is rarely found in the literature.
“Some of these variables (e.g.temperature, DCHL) have been used in previous studies (e.g.Sagarminaga and Arrizabalaga 2010;Mugo et al., 2010), but description of the habitat preferences based on other variables (e.g.MLD, ZOO) is rarely found in the literature.”
From Global habitat preferences of commercially valuable tuna (2015) · cites this paper as Mugo et al., 2010
Skipjack tuna prefer zero to positive SSH anomalies.
“skipjack preference for zero to positive anomalies (Mugo et al., 2010).”
From Global habitat preferences of commercially valuable tuna (2015) · cites this paper as Mugo et al., 2010

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Effects of environmental variations on the abundance of western winter-spring cohort of neon flying squid (Ommastrephes bartramii) in the Northwest Pacific Ocean
Yu, W., Chen, X.-J., Chen, Y., Yi, Q., & Zhang, Y. (2015) · Acta Oceanologica Sinica · doi:10.1007/s13131-015-0707-7 · Cited by 15
“The generalized additive model (GAM) was frequently used to evaluate the influences of environmental conditions on the fish abundance (Tian et al., 2009; Mugo et al., 2010).”
Method
Consecutive extraction of neutral and polar lipids from skipjack tuna (Katsuwonus pelamis) byproducts using supercritical carbon dioxide
Shin, Y.-R., Roy, V., Park, J.-S., Zhang, W., & Chun, B.-S. (2024) · Journal of Supercritical Fluids · doi:10.1016/j.supflu.2024.106175 · Cited by 14
Probable association between Anisakis infection in the muscle of skipjack tuna (Katsuwonus pelamis) and human anisakiasis in Tokyo, Japan.
Murata, R., Suzuki, J., Kodo, Y., Kobayashi, K., Sadamasu, K., Takano, T., Iwaki, T., Waki, T., & Ogawa, K. (2020) · Journal of food microbiology · doi:10.1016/j.ijfoodmicro.2020.108930 · Cited by 14
Application of the random forest algorithm for mapping potential fishing zones of Rastrelliger kanagurta off the east coast of peninsular Malaysia
Tan, M.-K., & Mustapha, M. A. (2023) · Regional Studies in Marine Science · doi:10.1016/j.rsma.2023.102881 · Cited by 13 · see citing works
Environmental influences on seasonal movement patterns and regional fidelity of striped marlin Kajikia audax in the Pacific Ocean
Su, N., Sun, C., Punt, A. E., Yeh, S., & DiNardo, G. T. (2014) · Fisheries Research · doi:10.1016/j.fishres.2014.07.017 · Cited by 15 · see citing works
Mapping spatial-temporal skipjack tuna habitat as a reference for Fish Aggregating Devices (FADs) settings in Makassar Strait, Indonesia
Hidayat, R., Zainuddin, M., Mallawa, A., Mustapha, M. A., & Putri, A. R. S. (2021) · Biodiversitas Journal of Biological Diversity · doi:10.13057/biodiv/d220905 · Cited by 13 · see citing works
“The assessment is accurate when the AIC value gets the smallest value of all the models tested (Johnson and Omland 2004; Mugo et al. 2010).”
Method
Analysis of the effect of ENSO and IOD on the productivity of yellowfin tuna (Thunnus albacares) in the South Indian Ocean, East Java, Indonesia
Sambah, A. B., NOOR’IZZAH, A., Intyas, C., Widhiyanuriyawan, D., Affandy, D. P., & Wijaya, A. (2023) · Biodiversitas Journal of Biological Diversity · doi:10.13057/biodiv/d240522 · Cited by 12 · see citing works
“The lower AIC value indicates higher significance (Mugo et al. 2010; Setiawati et al. 2015).”
Background
Modelling the impacts of climate change on skipjack tuna ( Katsuwonus pelamis ) in the Mozambique Channel
Nataniel, A. N., Pennino, M. G., López, J., & Soto, M. (2021) · Fisheries Oceanography · doi:10.1111/fog.12568 · Cited by 11 · see citing works
Prediction of potential fishing zones for mackerel tuna (Euthynnus sp) in Bali Strait using remotely sensed data
Syah, A. F., Ramdani, L. W., & Suniada, K. I. (2020) · IOP Conference Series: Earth and Environment · doi:10.1088/1755-1315/500/1/012070 · Cited by 12
Application of remotely sensed satellite data to identify Skipjack Tuna distributions and abundance in the coastal waters of Bone Gulf
Putri, A., & Zainuddin, M. (2019) · IOP Conference Series: Earth and Environment · doi:10.1088/1755-1315/241/1/012012 · Cited by 12
“So that, their movement and vulnerability were affected by their preferred habitat [5].”
BackgroundMethod
Identifying the key factors influencing spatial and temporal variations of regional coastal fishing activities
Chen, R., Wang, Y., XiaoQing, W., & Gao, Z. (2023) · Ocean & Coastal Management · doi:10.1016/j.ocecoaman.2023.106940 · Cited by 11 · see citing works
Satellite-derived prediction on habitat modelling of skipjack tuna (Katsuwonus pelamis) in the Makassar Strait, Indonesia
Syamsuddin, M., Subiyanto, S., Bratasena, T., Syamsudin, F., Purba, N. P., Ihsan, Y. N., Puspita, A., Zainuddin, M., & Nofrita, N. (2024) · Geocarto International · doi:10.1080/10106049.2024.2408281 · Cited by 11 · see citing works
“Higher values of SSH are favored in skipjack tuna habitats, and they correspond to increased skipjack rates (Surahman and Paembonan 2016; Mugo et al. 2010).”
Habitat modeling of mature albacore (Thunnus alalunga) tuna in the Indian Ocean
Mondal, S., & Lee, M. (2023) · Frontiers in Marine Science · doi:10.3389/fmars.2023.1258535 · Cited by 14 · see citing works
Eddy Vertical Structure in Southern Java Indian Ocean: Identification using Automated Eddies Detection
Tussadiah, A., Syamsuddin, M., Pranowo, W. S., Purba, N. P., & Riyantini, I. (2016) · doi:10.21275/v5i3.nov162003 · Cited by 11
Influence of temperature on hatching success of skipjack tuna (Katsuwonus pelamis): Implications for spawning availability of warm habitats
Fujioka, K., Aoki, Y., Tsuda, Y., Okamoto, K., Tsuchida, H., Sasaki, A., & Kiyofuji, H. (2024) · Journal of Fish Biology · doi:10.1111/jfb.15767 · Cited by 8 · see citing works
Spatiotemporal Patterns in the Distribution of Albacore, Bigeye, Skipjack, and Yellowfin Tuna Species within the Exclusive Economic Zones of Tonga for the Years 2002 to 2018
Vaihola, S., Yemane, D., & Kininmonth, S. (2023) · Diversity · doi:10.3390/d15101091 · Cited by 10 · see citing works
Impact of Climate Changes on Skipjack tuna (Katsuwonus pelamis) catch during May-July in the Makassar Strait
Putri, A. R. S., & Zainuddin, M. (2019) · IOP Conference Series: Earth and Environment · doi:10.1088/1755-1315/253/1/012046 · Cited by 10
Utilization of Scatterplot Smoothers to Understand the Environmental Preference of Bigeye Tuna in the Southern Waters off Java-Bali: Satellite Remote Sensing Approach
Setiawati, M. D., & Tanaka, T. (2017) · Fishes · doi:10.3390/fishes2010002 · Cited by 10 · see citing works
An ensemble analysis to predict future habitats of striped marlin (Kajikia audax) in the North Pacific Ocean
Su, N., Sun, C., Punt, A. E., Yeh, S., DiNardo, G. T., & Chang, Y. (2013) · ICES Journal of Marine Science · doi:10.1093/icesjms/fss191 · Cited by 11 · see citing works
“, 2011), while a small constant was added to address this issue in some studies (e.g. Howell and Kobayashi, 2006; Mugo et al., 2010), including”
Background
Real-time multi-month forecasting of skipjack tuna (Katsuwonus pelamis) habitat in the western and central Pacific Ocean for improved fishing efficiency and fisheries management
Wu, X.-H., Chang, Y., Liao, T.-Y., Ding, M.-M., & Ke, C.-C. (2023) · ICES Journal of Marine Science · doi:10.1093/icesjms/fsad159 · Cited by 9
Pemetaan Zona Potensial Penangkapan Ikan Tongkol di Perairan Teluk Banten
Nagi, A., Napitupulu, G., Radjawane, I., Nurdjaman, S., Supriadi, D., & Nurhayati, D. (2023) · BULETIN OSEANOGRAFI MARINA · doi:10.14710/buloma.v12i3.50374 · Cited by 9
“Sebaran parameter SPL dan klorofil-a di suatu perairan berbeda-beda, dengan perbedaan tersebut dapat membentuk pola sebaran parameter SPL dan klorofil-a secara temporal dan spasial (Mugo et al. , 2010).”
The use of statistical models in identifying skipjack tuna habitat characteristics during the Southeast Monsoon in the Bone Gulf, Indonesia
Hasyim, S., Hidayat, R., Farhum, S. A., & Zainuddin, M. (2022) · Biodiversitas Journal of Biological Diversity · doi:10.13057/biodiv/d230459 · Cited by 9 · see citing works
“Skipjack tuna distribution in the Northern Pacific Ocean near Japan waters had SST and SSC optimal values of 20.5-26°C and 0.3-0.37 mgm-3, respectively, according to Mugo et al. (2010).”
BackgroundInfluential
Hotspot Habitat Modeling of Skipjack Tuna (Katsuwonus pelamis) in the Indian Ocean by Using Multisatellite Remote Sensing
Vayghan, A. H., & Lee, M.-A. (2022) · Turkish Journal of Fisheries and Aquatic Sciences · doi:10.4194/trjfas19107 · Cited by 9 · see citing works
“SKJ movement varies widely and is reportedly affected by large-scale oceanographic variabilities such as ocean currents, sea surface temperature (SST), sea surface chlorophyll-a (SSC), and sea surface height (SSH; McKechnie et al., 2016; Mugo et al., 2010; Mugo and Saitoh 2020).”
Background
Mapping potential fishing zones for skipjack tuna in the southern Makassar Strait, Indonesia, using Pelagic Habitat Index (PHI)
Putri, A. R. S., Zainuddin, M., Musbir, M., Hidayat, R., & Mustapha, M. A. (2021) · Biodiversitas Journal of Biological Diversity · doi:10.13057/biodiv/d220758 · Cited by 9 · see citing works
“Sea surface temperature (SST) is a limiting factor for the physiology, abundance, and distribution of skipjack tuna (Mugo et al. 2010; Muhling et al. 2015; Nurdin et al. 2017; Putri et al. 2018a; Schaefer and Fuller 2019; Ashida 2020) and also indirectly encourages migration patterns (Fromentin et…”
BackgroundResultInfluential
THE EFFECT OF OCEANOGRAPHIC FACTORS ON SKIPJACK TUNA FAD VS FREE SCHOOL CATCH IN THE BONE BAY, INDONESIA: AN IMPORTANT STEP TOWARD FISHING MANAGEMENT
Zainuddin, M., Safruddin, Ridwan, M., Putri, A. R. S., & Hidayat, R. (2019) · E-Journal Ilmu dan Teknologi Kelautan Tropis · doi:10.29244/jitkt.v11i1.24775 · Cited by 9
“Skipjack migration route and its habitat in the western North Pacific Ocean corresponds to the movement of optimum ranges of the oceanographic features (Mugo et al., 2010).”
Background
Fishing Area Prediction Using Scene-Based Ensemble Models
Alfatinah, A., Chu, H., Tatas, T., & Patra, S. R. (2023) · Journal of Marine Science and Engineering · doi:10.3390/jmse11071398 · Cited by 10 · see citing works
An overview Assessment of the Effectiveness of Satellite Images and Remote Sensing in Predicting Potential Fishing Grounds and its Applicability for Rastrelliger kanagurta in the Malaysian EEZ off the South China Sea
Kamaruzzaman, Y. N., & Mustapha, M. A. (2023) · Reviews in Fisheries Science & Aquaculture · doi:10.1080/23308249.2023.2183341 · Cited by 8 · see citing works
How climate change and climate variability affected trip distance of a commercial fishery
Chan, H.-L. (2023) · PLOS Climate · doi:10.1371/journal.pclm.0000143 · Cited by 8 · see citing works
Using geostatistical analysis for simultaneous estimation of isoscapes and ontogenetic shifts in isotope ratios of highly migratory marine fish
Matsubayashi, J., Kimura, K., Ohkouchi, N., Ogawa, N., Ishikawa, N., Chikaraishi, Y., Tsuda, Y., & Minami, H. (2022) · Frontiers in Marine Science · doi:10.3389/fmars.2022.1049056 · Cited by 8
“0°C (Mugo et al., 2010) and can maintain its body temperature higher than that of ambient water (Barrett and Hester, 1964; Stevens et al.”
Background
Mapping distribution patterns of skipjack tuna during January-May in the Makassar Strait
Zainuddin, M., Amir, M. I., Bone, A., Farhum, S. A., Hidayat, R., Putri, A. R. S., Mallawa, A., Safruddin, & Ridwan, M. (2019) · IOP Conference Series: Earth and Environment · doi:10.1088/1755-1315/370/1/012004 · Cited by 8
Remote Chlorophyll-a and SST to Determination of Fish Potential Area in Makassar Strait Waters Using MODIS Satellite Data
Selao, A., Malik, A. A., Yani, F. I., Mallawa, A., & Safruddin (2019) · IOP Conference Series: Earth and Environment · doi:10.1088/1755-1315/270/1/012047 · Cited by 8
The habitat preference of commercial tuna species based on a daily environmental database approach in the tropical region of the Eastern Indian Ocean Off Java-Bali Waters
Setiawati, M. D., Rachman, H. A., As-syakur, A. R., Setiawan, R., Syahailatua, A., & Wouthuyzen, S. (2024) · Deep-sea research. Part II, Topical studies in oceanography · doi:10.1016/j.dsr2.2024.105400 · Cited by 7 · see citing works
Potential fishing grounds of Skipjack tuna (Katsuwonus pelamis) in western water of Sumatera using remotely sensed data and maximum entropy model
Syah, A. F., Ni’am, A., & Jatisworo, D. (2023) · IOP Conference Series: Earth and Environment · doi:10.1088/1755-1315/1251/1/012066 · Cited by 7
Application of Generalized Additive Model for Identification of Potential Fishing Zones Using Aqua and Terra MODIS Imagery Data
Sasmito, B., Bashit, N., Arinda, B. R., & Sukmono, A. (2022) · Journal of Applied Geospatial Information · doi:10.30871/jagi.v6i1.3962 · Cited by 7
“Akaike Information Criterion (AIC), Cumulative Deviance Explained (CDE), and the significance of the predictor terms in selecting the best model.”
MethodInfluential
Modeling Mackerel Tuna (Euthynnus affinis) Habitat in Southern Coast of Java: Influence of Seasonal Upwelling and Negative IOD
Koropitan, A., Kholilullah, I., & Yusfiandayani, R. (2021) · Hayati Journal of Biosciences · doi:10.4308/hjb.28.4.271-285 · Cited by 7
“This approach was employed as informed by Mugo et al. (2010), Howell and Kobayashi (2006), and Zagaglia et al. (2004).”
Method
Using satellite remote sensing to improve the prediction of scallop condition in their natural environment: Case study for Georges Bank, Canada
Liu, X., Devred, E., Johnson, C., Keith, D. W., & Sameoto, J. (2021) · doi:10.1016/j.rse.2020.112251 · Cited by 7
Detection of cyclonic and anti-cyclonic eddy in relation to potential Skipjack Tuna fishing ground in Makassar Strait
Hidayat, R., & Zainuddin, M. (2019) · IOP Conference Series: Earth and Environment · doi:10.1088/1755-1315/241/1/012011 · Cited by 7
“Indirectly the temperature rise will affect the eddy rotation [8].”
Background
ROLE OF SUB SURFACE TEMPERATURE, SALINITY AND CHLOROPHYLL TO ALBACORE TUNA ABUNDANCE IN INDIAN OCEAN
Novianto, D., & Susilo, E. (2016) · Indonesian Fisheries Research Journal · doi:10.15578/ifrj.22.1.2016.17-26 · Cited by 8 · see citing works
Monitoring Protected Areas from Space
Pettorelli, N., Wegmann, M., Gurney, L., & Dubois, G. (2016) · doi:10.1002/9781118338117.ch14 · Cited by 7 · see citing works
El Niño Southern Oscillation and spatial-temporal variability of the nominal performances of swordfish (Xiphias gladius) in the southeastern Pacific
Espíndola, F., Yáñez, E., & Barbieri, M. A. (2011) · doi:10.4067/s0718-19572011000200012 · Cited by 7
Region Proposal and Regression Network for Fishing Spots Detection From Sea Environment
Fu, A., Patil, K., & Iiyama, M. (2021) · IEEE Access · doi:10.1109/access.2021.3077514 · Cited by 7 · see citing works
“There are some related work like random forest classification using SST and Chlorophyll to address this problem [3]–[14].”
Method
Seasonal variability of high‐latitude foraging grounds for Atlantic bluefin tuna ( Thunnus thynnus )
McNicholas, G. E., Jackson, A. L., Brodie, S. J., O’Neill, R., O’Maoiléidigh, N., Drumm, A., Cooney, J., Maxwell, H., Block, B. A., Castleton, M., et al. (2024) · Diversity and Distributions · doi:10.1111/ddi.13865 · Cited by 5 · see citing works
“Pacific (Mugo et al., 2010).”
Satellite and historical data, and statistical modeling to predict potential fishing zones for dolphinfish, Coryphaena hippurus (Perciformes: Coryphaenidae) in Colombian Pacific
Arias, A. M., Salcedo, L. G. G., Martínez, I. F. B., & Selvaraj, J. J. (2022) · Revista de Biología Tropical · doi:10.15517/rev.biol.trop..v70i1.47375 · Cited by 6 · see citing works
“(2003) suggested specific large-scale changes on the fish habitat in the equatorial Pacific by means of SST effects, which could explain the distribution of available habitats for pelagic fishes on higher latitudes due to the increase of temperature by global warming (Cheung et al., 2009; Mugo et al., 2010).”
Background
Effect of oceanographic conditions on skipjack tuna catches from FAD versus free-swimming school fishing in the Makassar Strait
Putri, A. R. S., Zainuddin, M., Musbir, M., Mustapha, M. A., & Hidayat, R. (2019) · IOP Conference Series: Earth and Environment · doi:10.1088/1755-1315/370/1/012008 · Cited by 6
“General Additive Model (GAM) This study used a general additive model (GAM) analysis to identify the effect of oceanographic conditions on skipjack tuna catches around FADs versus free-swimming schools in the Makassar Strait [14,15].”
Method
IDENTIFIKASI STRUKTUR STOK IKAN CAKALANG (Katsuwonus pelamis Linnaeus, 1758) DI SAMUDRA HINDIA (WPP NRI 573) MENGGUNAKAN ANALISIS BENTUK OTOLITH
Wujdi, A., Setyadji, B., & Nugroho, S. C. (2017) · Jurnal Penelitian Perikanan Indonesia · doi:10.15578/jppi.23.2.2017.77-88 · Cited by 6 · see citing works
“Sebagai konsekuensinya, distribusi spasial ikan cakalang bersifat musiman dan berpola tahunan (Mugo et al., 2010) dan hal ini terkait dengan dinamika faktor lingkungan khususnya lokasi tempat mencari makan atau biasa disebut forage habitat (Andrade & Garcia, 1999).”
Background
Development of a three-dimensional growth prediction model for the Japanese scallop in Funka Bay, Japan, using OGCM and MODIS
Yang, L., Saitoh, S., Ihara, Y., Nakada, S., Kanamori, M., Xun, Z., Baba, K., Ishikawa, Y., & Hirawake, T. (2015) · doi:10.1093/icesjms/fsv153 · Cited by 6
Self-citation

Authors: MUGO, R., SAITOH, S., NIHIRA, A., & KUROYAMA, T.
Affiliations: Hokkaido University (JP)
Corresponding author: MUGO, ROBINSON
ORCID: MUGO, ROBINSON
SAITOH, SEI‐ICHI
Venue: Fisheries Oceanography
Publisher: Wiley
Published: 2010-08-04
Volume: 19
Issue: 5
Pages: 382-396
ISSN: 1054-6006 (ISSN-L)
1365-2419
DOI: 10.1111/j.1365-2419.2010.00552.x
OpenAlex: W2163333500
Cited by: 149
References: 0
Citations by year: 2026: 3 · 2025: 13 · 2024: 8 · 2023: 21 · 2022: 12 · 2021: 12 · 2020: 15 · 2019: 17 · 2018: 3 · 2017: 8 · 2016: 8 · 2015: 6 · 2014: 5 · 2013: 8 · 2012: 5
FWCI: 5.19
Type: journal article
Language: en
Open access: closed
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations: Fisheries Oceanography (publishedVersion)
Topics: Physical Sciences › Environmental Science › Global and Planetary Change › Marine and fisheries research
Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
Physical Sciences › Environmental Science › Nature and Landscape Conservation › Fish Ecology and Management Studies
Keywords: skipjack tuna, fish habitat, western North Pacific, sea surface temperature, surface chlorophyll, sea level anomalies, eddy kinetic energy, catch per unit effort, habitat selection, tuna migration, satellite remote sensing, generalized additive models

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Habitat characteristics of skipjack tuna ( Katsuwonus pelamis ) in the western North Pacific: a remote sensing perspective

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