Spatio-Temporal Fish Catch Assessments Using Fishing Vessel Trajectories and Coastal Fish Landing Data from around Jeju Island

While pressure on marine ecosystems leading to declines in global fish catches have been attributed to excessive fishing and to unregulated and unreported fishing, existing management practices have yet to fully address these declines. Estimation of spatial and temporal distribution of fisheries resources and the extent of fishing impacts on marine ecosystems using vessel trajectories has become central in recent studies. This study proposed the use of trajectories of 771 Korean coastal and offshore fishing vessels and one-year fish landing data to estimate variations in commercial fish species, vessel, and fishing gear activity distributions in the waters around Jeju island. A set of standards were applied to identify individual fishing tracks of major gears and uniformly distributed catch to fishing segments of trajectories to produce spatio-temporal distributions of catch, fishing activities, and vessel reliance on fishing grounds at a fine spatial scale. The method identified reference points that can inform management at local and regional scales. We discuss the opportunities of combining larger datasets collected over a longer period and applying predictive modeling techniques in making extensive assessments, including climate change impacts on fishing activities that can inform resource management and marine spatial planning.

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Estimating Fishing Effort and Spatio-Temporal Distribution of Longline Vessels in the Indian Ocean

Frontiers in Marine Science ◽

10.3389/fmars.2021.671036 ◽

2021 ◽

Vol 8 ◽

Author(s):

Febrianto W. Utama ◽

Xavier Hoenner ◽

Britta Denise Hardesty ◽

David Peel ◽

Jessica H. Ford ◽

...

Keyword(s):

Indian Ocean ◽

Temporal Distribution ◽

Fishing Effort ◽

Fishing Activity ◽

Widespread Occurrence ◽

Fisheries Resources ◽

Spatial Shift ◽

Landing Sites ◽

The Indian Ocean ◽

Spatio Temporal

Protein from fish is essential for feeding the world’s population and is increasingly recognized as critical for food security. To ensure that fisheries resources can be sustainably maintained, fisheries management must be appropriately implemented. When logbook and landing records data are not complete or are incorrect, it is challenging to have an accurate understanding of catch volume. Focusing on Indonesian longline vessels operating in the Indian Ocean from 2012–2019 (n = 1124 vessels), our aims were to (1) assess compliance through identification of landing sites and potentially illicit behavior inferred by interruptions in VMS transmission, and (2) understand how the fishery operates along with quantifying the spatio-temporal distribution of fishing intensity by applying a Hidden Markov Model, which automatically classified each VMS position as fishing, steaming and anchoring. We found vessel compliance gaps in 90% of vessels in the dataset. Compliance was questionable due both to the widespread occurrence of long intermissions in relaying VMS positions (mean = 17.8 h, n = 973 vessels) and the use of unauthorized landing sites. We also observed substantial changes in fishing effort locations among years. The introduction of regulatory measures during the study period banning transshipment and foreign vessels may be responsible for the spatial shift in fishing activity we observed, from encompassing nearly the whole Indian Ocean to more recent intense efforts off western Sumatra and northern Australia.

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Perceptions of system-identity and regime shift for marine ecosystems

ICES Journal of Marine Science ◽

10.1093/icesjms/fsz058 ◽

2019 ◽

Vol 76 (6) ◽

pp. 1736-1747 ◽

Cited By ~ 2

Author(s):

Ingrid van Putten ◽

Fabio Boschetti ◽

Scott Ling ◽

Shane A Richards

Keyword(s):

Regime Shift ◽

Cognitive Biases ◽

Marine Ecosystems ◽

Climate Impact ◽

Regime Shifts ◽

Reference Points ◽

Scientific Uncertainty ◽

Baseline Shift ◽

Spatio Temporal ◽

Evidenced Based

Abstract There is growing empirical evidence around the world demonstrating regime shifts of marine ecosystems. But generalizable criteria to detect and define regime shifts are elusive because of: (i) an incomplete scientific understanding of processes underlying regime shifts; (ii) because the baseline state and conditions are ill defined, and; (iii) due to an inherent ambiguity in the concept of system identity. We surveyed marine scientists in Tasmania, Australia, and determined the effect of changing conditions (including type of climate impact, species loss, species composition, spatio-temporal extent, and human intervention) on their perception of marine regime shift. We find, there is an objective difficulty in detecting regime shifts that goes beyond scientific uncertainty and there is disagreement on which configurations of change indeed constitute a regime shift. Furthermore, this difference of opinion was not related to the degree of confidence that scientists indicated when identifying regime shifts. This lack of consensus and seemingly unrelated scientific confidence, may be attributable to value ambiguity around people s attitudes, cognitive biases, and baseline shift. When applying evidenced-based reference points in well-reasoned Ecosystem Based Management, there should be scientific consensus on the manifestation and extent of specific regime shifts, and recognition of value ambiguities influencing scientific perceptions.

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Evaluation of the sensitivity of biological reference points to the spatio-temporal distribution of fishing effort when seasonal migrations are sex-specific

Fisheries Research ◽

10.1016/j.fishres.2013.10.022 ◽

2014 ◽

Vol 158 ◽

pp. 116-123 ◽

Cited By ~ 8

Author(s):

Hiroshi Okamura ◽

Murdoch K. McAllister ◽

Momoko Ichinokawa ◽

Lynne Yamanaka ◽

Kendra Holt

Keyword(s):

Temporal Distribution ◽

Fishing Effort ◽

Reference Points ◽

Seasonal Migrations ◽

Spatio Temporal

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SPATIO TEMPORAL DISTRIBUTION OF SMALL PELAGIC FISH IN THE JAVA SEA

Indonesian Fisheries Research Journal ◽

10.15578/ifrj.14.1.2008.21-35 ◽

2017 ◽

Vol 14 (1) ◽

pp. 21

Author(s):

Wijopriono Wijopriono

Keyword(s):

Fuel Consumption ◽

Temporal Distribution ◽

Pelagic Fish ◽

Small Pelagic Fish ◽

Commercial Fish ◽

Fish Schools ◽

Java Sea ◽

Spatio Temporal ◽

The Rich ◽

The Cost

Time spent in seeking fish schools and potential fishing areas is the main source of fuel consumption, and it is a significant factor in raising the cost of fishing operation. Therefore, knowledge of the distribution pattern lnd aggregations of commercial fish in space and time is of considerable financial value to the fishers anAlisnlng industry because it will assist them to reduce the time and fuel consumption of the boats in locating the rich fishing grounds.

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