Tissue regeneration and wound healing remain extremely understudied in elasmobranchs as many wounds are recorded through one-off opportunistic observations with an inability for long-term monitoring of individuals. This study demonstrates partial fin regeneration of a silky shark (Carcharhinus falciformis) almost one year after a traumatic injury that resulted in a 20.8% loss of the first dorsal fin. The shark was photographed 332 days after the recorded injury with a newly shaped dorsal fin that had healed to 87% of the original size. Photographs provided by divers allowed for accurate measurements of fin growth, confirming an approximate 10.7% increase in fin area, indicative of tissue regeneration. Wound healing rate was calculated to conclude that the initial wound reached complete closure by day 42, which is analogous with other elasmobranch healing rates. Prior to this study, only one other record of dorsal fin regeneration had been documented in a whale shark. This provides the first evidence of dorsal fin regeneration in a silky shark and contributes to the limited studies of wound healing rates in sharks. This newfound insight into tissue regeneration and wound healing underscores the importance of further research to understand how they respond to traumatic injury in the face of mounting environmental challenges, both natural and anthropogenic. Additionally, this study exemplifies the power of collaboration between researchers and the public, including photographers and divers, to expand the scope of research studies and bridge the gap between science and society.

Chelsea Black

Resilience in the Depths: First Example of Fin Regeneration in a Silky Shark (Carcharhinus falciformis) following Traumatic Injury

Peru’s industrial fishery centers on the Peruvian anchoveta (Engraulis ringens), which is highly productive due to the marine conditions of the Humboldt Current. However, like elsewhere, the country’s marine fishing industry is linked to climate change. The objective of this study is to analyze the relationship between industrial marine fishing and climate change in Peru. Correlation and linear regression methods were used. A key variable of climate change is the sea surface temperature (SST). The study found that in Peru during 1997-2020, the higher the SST, the lower the industrial fishing catch (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="18.648pt" style="vertical-align:-0.4673595pt" id="M1" height="8.85534pt" version="1.1" viewBox="-0.0498162 -8.38798 18.648 8.85534"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-223" d="M545 106L524 126C493 85 467 65 455 65C438 65 427 113 405 238C448 295 498 362 543 439L533 448L478 435C453 386 423 331 398 295H395C370 404 347 448 282 448C169 448 23 309 23 153C23 54 65 -12 128 -12C203 -12 283 70 339 155H341C360 29 380 -12 411 -12C444 -12 491 11 545 106ZM333 204C265 95 210 54 169 54C137 54 113 96 113 171C113 302 191 405 252 405C301 405 318 306 333 204Z"/></g><g transform="matrix(.013,0,0,-0.013,11.017,0)"><path id="g117-34" d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"/></g></svg><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="16.283pt" style="vertical-align:-0.4673595pt" height="8.85534pt" version="1.1" viewBox="22.230183800000002 -8.38798 16.283 8.85534"><g transform="matrix(.013,0,0,-0.013,22.28,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g><g transform="matrix(.013,0,0,-0.013,28.52,0)"><path id="g121-35" d="M594 629L561 652L159 -9L190 -32L594 629ZM194 635C92 635 49 534 49 453C49 374 92 272 193 272C295 272 338 374 338 454S295 635 194 635ZM193 605C257 605 265 504 265 453C265 405 257 302 194 302C133 302 122 403 122 454S133 605 193 605ZM567 351C465 351 421 250 421 169C421 90 465 -12 566 -12S710 90 710 170S667 351 567 351ZM566 322C628 322 637 221 637 169C637 121 628 18 567 18S494 119 494 170C494 223 506 322 566 322Z"/></g></svg>). There is also evidence of an inverse correlation between sea level and industrial catch; i.e., sea level rise would alter marine ecosystems. A positive correlation between landings of industrial marine fishing and exports for nonfood purposes was corroborated, especially fishmeal. The study concludes that the industrial Peruvian anchoveta catch is negatively affected by SST, fishing effort (search time in hours), and catch per unit of effort (CPUE). For the sustainability of Peru’s industrial fishery, climate change adaptation measures, such as a reduction of fishing effort and research on alternative production of fishmeal with unmodified natural inputs without or in combination with anchoveta, should be implemented. For the future, a change in fishing policies is required that replaces anchoveta for fishmeal with a warm-water marine species during strong El Niño events.

Edelina Coayla

Ysabel Bedón

Tomás Rosales

Luis Jiménez

Industrial Marine Fishing in the Face of Climate Change in Peru

In the Sandha river of Bangladesh, we investigated the temporal and geographical fluctuation in species of fish composition and diversity. The extent of our understanding of the fish variety in this river varies greatly on both a temporal and a geographical scale. From July 2021 to June 2022, fish specimens were gathered from five stations using various conventional fishing methods. During the study period, 5118 individuals from 67 species were collected which include 8 orders, 24 families, and 54 genera. Cypriniformes made up the majority of the order (32.84%), whereas Beloniformes and Tetraodontiformes made up the least number of species (1.49% each). Six species were listed as endangered (8.96%), seven as vulnerable (10.45%), nine as near threatened (13.43%), forty-three as least concern (64.18%), one with data deficient (1.49%), and one as not evaluated (1.49%) in Bangladesh. In order to quantify the temporal and geographical changes in community composition, diversity indices were calculated and put to use. Three (temperature, humidity, and rainfall) out of the four environmental factors (temperature, humidity, rainfall, and photoperiod) had a big impact on how species were distributed. At a similarity level of 79% and 75.5% separation, 2 substantial clusters were seen in the case of stations and 2 large clusters were detected in the case of months, respectively. However, at a similarity threshold of 20% separation, three different groups of fish species were found. Our research offers the most recent status data on fish distribution in the Sandha river. The knowledge acquired from this research is crucial for creating protection and management plans that will promote the long-term viability of fishery resources in the Sandha river and its nearby coastal tributaries.

Md. Rahamat Ullah

Md. Monjurul Hasan

Mohammad Ashraful Alam

Jannatun Nayeem Neela

Maksudul Islam

Md. Moniruzzaman

Md. Arifur Rahman

Md. Ariful Alam

Diversity of Fish Species in relation to Climatological Fluctuations in a Coastal River of Bangladesh

Chlorophyll-a (Chl-a) and its correlation with different parameters are one of the major indicators to understand marine ecosystems. This study was conducted to explore the seasonal and spatial variability of Chl-a at three different stations (onshore, midshore, and offshore) across the maritime boundary of Bangladesh in the northern BoB with its response to the surface current speed and recent ENSO (El Niño/La Niña-Southern Oscillation) events by using satellite data. Moderate resolution imaging spectroradiometer (MODIS) aqua satellite level-3 data of Chl-a was used in this study. Ocean currents datasets were obtained from the Asia-Pacific Data Research Center (APDRC) live access service, LAS8.6.13 of NOAA (National Oceanic and Atmospheric Administration), whereas the SST anomalies dataset was collected from NOAA Climate Prediction Center. This study revealed that the onshore region showed the highest (1.121 mgm-3) abundance of Chl-a, whereas the offshore region showed the lowest (0.136 mgm-3). The offshore and midshore regions showed a homogenous distribution of Chl-a, whereas the observed trend of seasonal fluctuation was southwest monsoon > postmonsoon > northeast monsoon > premonsoon. There is a seasonal variation in the relationship between Chl-a and surface current speed, with moderate correlations during northeast (Dec-Feb) and premonsoon (Mar-May). The effect of ENSO on Chl-a was observed as insignificant (<svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="19.289pt" style="vertical-align:-0.6370001pt" id="M1" height="9.2729pt" version="1.1" viewBox="-0.0498162 -8.6359 19.289 9.2729"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-81" d="M600 480C600 590 528 650 384 650H143L137 622C222 614 225 607 210 531L130 127C113 41 106 36 23 28L17 0H294L300 28C204 36 195 42 212 127L243 284L314 263C327 263 339 263 352 264C465 271 600 337 600 480ZM508 481C508 351 402 304 329 304C289 304 265 311 250 317L295 559C302 594 310 606 323 611C335 616 350 619 367 619C455 619 508 573 508 481Z"/></g><g transform="matrix(.013,0,0,-0.013,11.658,0)"><path id="g117-92" d="M512 230V281L75 514V456L453 256V254L75 55V-3L512 230Z"/></g></svg><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="21.918pt" style="vertical-align:-0.6370001pt" height="9.2729pt" version="1.1" viewBox="22.8711838 -8.6359 21.918 9.2729"><g transform="matrix(.013,0,0,-0.013,22.921,0)"><path id="g113-49" d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"/></g><g transform="matrix(.013,0,0,-0.013,29.161,0)"><path id="g113-47" d="M113 -12C146 -12 170 11 170 46C170 78 146 103 114 103S58 78 58 46C58 11 82 -12 113 -12Z"/></g><g transform="matrix(.013,0,0,-0.013,32.125,0)"><use xlink:href="#g113-49"/></g><g transform="matrix(.013,0,0,-0.013,38.365,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g></svg>) in the northern BoB. However, Chl-a variability in response to ENSO events across the northern region of BoB requires more investigation.

Tamanna Fardoshi

Md Rony Golder

Muhammad Abdur Rouf

Md Masud-Ul-Alam

Seasonal and Spatial Variability of Chlorophyll-a in Response to ENSO and Ocean Current in the Maritime Boundary of Bangladesh

Skipjack tuna (Katsuwonus pelamis) is the most dominating tuna species caught in the Indian Ocean. However, tuna fishermen in the Indian Ocean still face difficulties determining potential skipjack tuna fishing grounds due to limited geographic information. An attempt to improve information regarding potential skipjack tuna fishing grounds is through modeling the SST, SSC, SSH, and SSS oceanographic parameters with skipjack tuna distribution using GIS. The characteristics of the skipjack tuna habitat can be found through the generalized additive model (GAM) statistical analysis using data of skipjack tuna catch and oceanographic parameters from satellite imagery. The integrated GIS and GAM methods can improve the study of the habitat of skipjack tuna species. Therefore, this research is aimed at analyzing the condition and SST, SSC, SSH, and SSS variations in 2016-2021 in the South Java Sea; at predicting the correlation of SST, SSC, SSH, and SSS towards skipjack tuna catch in 2016-2021 in the South Java Sea using GAM; and at creating a map of skipjack tuna seasonal migration zones. The data included skipjack tuna catches, number of trips, and skipjack tuna fishing coordinates in 2016-2021 from PPS Cilacap and PPP Pondokdadap. The oceanographic parameter data in 2016-2021 was derived from Aqua MODIS level 3 (SST and SSC) and CMEMS (SSH and SSS) satellite imagery. The results showed that the average values of oceanographic parameters at skipjack tuna fishing ground coordinates in the South Java Sea (2016-2021) were SST (26.050-30.816°C), SSC (0.094-0.564 mg/m3), SSH (0.268-0.639 m), and SSS (33.075-34.514 psu). The best GAM modeling was the combination of four oceanographic parameter variables with an AIC value of 45357.92. Skipjack tuna in the South Java Sea migrates southeast during the west monsoon season to the first transitional season and tends to migrate northwest during the east monsoon season to the second transitional season.

Bambang Semedi

Hardoko Hardoko

Citra Satrya Utama Dewi

Nova Dewi Safitri Syam’s

Novia Fara Diza

Gerardus David Ady Purnama Bayuaji

Seasonal Migration Zone of Skipjack Tuna (Katsuwonus pelamis) in the South Java Sea Using Multisensor Satellite Remote Sensing

Sea urchin population demographics can respond to changes in keystone species abundances, with the magnitude of these responses varying depending on environmental influences. In this study, sea urchin populations were surveyed across 15 Aleutian archipelago islands over a 30-year period to understand how patterns of sea urchin demography (density, biomass, and size structure) varied through different ecological regimes that were caused by changes in the abundance of sea otters, a keystone species in this system. To examine long-term changes in sea urchin demographics, four time periods across the recent decline of sea otters were examined: during sea otter presence (1987-1994), nearing absence at the end of the decline (1997-2000), 10 years postdecline (2008-2010), and 15-20 years following the loss of sea otters from the ecosystem (2014-2017). Our results show that when sea otters were broadly present, sea urchin demographics were generally similar across the archipelago, with few urchins that had large-sized bodies. During this time, bottom-up environmental controls were muted relative to top-down forces from keystone predation. However, as sea otters declined and remained absent from the system, abiotic factors became more influential on sea urchin biomass, density, and size structure. In particular, differences among island groups during these periods were correlated with variation in ocean temperature, bathymetric complexity, and habitat availability. Sea urchin recruitment also varied among island groups, corresponding to ecoregions delineated by oceanic passes across the archipelago. The functional extinction of sea otters revealed an increasing influence of abiotic forcing in the absence of top-down control. This study further highlights the importance of understanding how keystone predators regulate herbivore demographics.

B. P. Weitzman

B. Konar

M. S. Edwards

D. B. Rasher

M. C. Kenner

M. T. Tinker

J. A. Estes

Changes in Abiotic Drivers of Green Sea Urchin Demographics following the Loss of a Keystone Predator

About this journal

Journal of Marine Sciences publishes original research articles as well as review articles&nbsp;in all areas of marine sciences including marine biology, oceanography, hydrology, coastal processes, technological developments, climate change, and policy.

Journal profile

Meet the editorial board

Journal of Marine Sciences maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor spotlight

Submit your proposal

Do you think there is an emerging area of research that really needs to be highlighted? Or an existing research area that has been overlooked or would benefit from deeper investigation? Raise the profile of a research area by leading a Special Issue.

Special Issues

Author guidelines

Editorial board

Databases and indexing

Journal of Marine Sciences - Table of contents 2023

title

Journal of Marine Sciences publishes original research articles as well as review articles in all areas of marine sciences including marine biology, oceanography, hydrology, coastal processes, technological developments, climate change, and policy.

Journal of Marine Sciences