Reliability of the data on tuna catches obtained from the dockside in Indonesia: A study of stakeholders’ perceptions

Mill, Aileen C.; Gray, Tim; Jiang, Mingguo; Arief, Hazmi; Brown, Arthur; Karman, Amirul; Polunin, Nicholas

doi:10.1016/j.marpol.2020.104242

Cited by 7 publications

(5 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Consequently, the fisheries data did not really present the actual condition. 19 Lack of enforcement actions towards SBT quota distribution will also impact data inaccuracy because of unreported fishing practices. The CCSBT report of compliance in 2019 mentioned the tagging issues to all SBT catches, 20 showing that the tuna associations were unable to control the number of tags circulated due to members not reporting the tag use.…”

Section: Tagging Obligationmentioning

confidence: 99%

Fishing Quota and International Obligation: Why Has Indonesia been Indicated as a Non-Compliant State

Indriyani

Rahim

Azmi

2021

Hasanuddin Law Rev.

View full text Add to dashboard Cite

Indonesia committed to conserving the tuna resources by participating in some RFMOs. From all regional organizations where Indonesia has been joined, the CCSBT is the unique one, due to it governs a single tuna species, which is called Southern Bluefin Tuna. This kind of tuna is essential for Indonesia because it is the world’s most expensive tuna and SBT migrates through Indonesian fisheries management zones and goes even further within the territorial waters, where the SBT spawning area is located. This natural characteristic distinguishes Indonesia from other Parties to CCSBT. Nevertheless, the Country has been dealing with its obligation to comply with national quota allocation. For some fishing season periods, the CCSBT indicated Indonesia as a non-compliant. By applying the qualitative approach, this study considers how Indonesia’s non-compliance has been addressed in fishing for shared fish stocks. The data collection was conducted through semi-structured interviews and legal analysis of law and policy instruments. This method leads the elaboration to reveal domestic factors affecting non-compliance by Indonesia. This study argues, the fisheries legislation should consider the provision concerning fishing for resources under quota system, hence, it will provide sufficient legal base to take enforcement measures towards non-compliance with fishing quota.

show abstract

Section: Tagging Obligationmentioning

confidence: 99%

Fishing Quota and International Obligation: Why Has Indonesia been Indicated as a Non-Compliant State

Indriyani

Rahim

Azmi

2021

Hasanuddin Law Rev.

View full text Add to dashboard Cite

show abstract

“…These problems occur due to a lack of fishers' awareness and weak government capabilities [5], including non-implemented standard operating procedures, the number of infrastructure facilities, and the capability of the enumerators [7]. Reliable and robust data will be used as input for sustainable fisheries management [8]. The improvement of data collection programs must continue to be developed [5,9,10].…”

Section: Introductionmentioning

confidence: 99%

The use of stereo cameras and artificial intelligence data to support capture fisheries landing data monitoring

Wibowo¹,

Hargiyatno²,

Faizah³

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Reliable data and data collection are important key factors in realizing sustainable fisheries management. Landing data collected by the fishing port authority through has issues with coverage and accuracy. The fast development of image processing and artificial intelligence (AI) analysis opens the possibilities of automatic catch monitoring and data collection in the fishing port. This paper aims to develop a catch data collection program in fishing ports based on stereo camera video monitoring which AI processes. The first version of the devices, FishQi-L (Fish Quantitative Intelligence in Landing site), was developed. FishQi-L consisted of a set stereo camera and a pre-programed JETSON Nano image/video processor. The stereo camera allows image size quantification, size estimation, and spatial mapping capabilities. FishQi-L was able to detect the character and dimensions of objects, the trial object in Pekalongan was “Basket” with mean average precision (mAP) of the detection was 84% and 0.4387 losses. To increase the accuracy and reliability of the systems, we need to increase the number of data and data training iterations.

show abstract

“…Data-poor species comprise >80% of global catch and almost two-thirds of species are overexploited (Costello et al, 2012; Guan, Chen, Boenish, Jin, & Shan, 2020). However, landings data are not consistent or reliable globally, particularly in countries with many landing sites and/or high levels of artisanal catch, particularly for sharks and their relatives (Khan et al, 2020; Okes & Sant, 2022; Ruano-Chamorro, Subida, & Fernández, 2017). Additionally, the catches of data-poor species, if characterised, are often reported as aggregates; grouped together by genus, family, or higher, giving little information on the catch of individual species (Cashion, Bailly, & Pauly, 2019; FAO, 2019).…”

Section: Introductionmentioning

confidence: 99%

M-Risk: A framework for assessing global fisheries management efficacy of sharks, rays, and chimaeras

Sherman

Sant

Simpfendorfer

et al. 2022

Preprint

View full text Add to dashboard Cite

Fisheries management is essential to guarantee sustainable capture of target species and avoid undesirable declines of incidentally captured species. A key challenge is halting and reversing declines of shark and ray species, and specifically assessing the degree to which management is sufficient to avoid declines in relatively data-poor fisheries. While ecological risk analyses focus on intrinsic 'productivity' and extrinsic 'susceptibility', one would ideally consider the influence of 'fisheries management'. Currently, there is no single management evaluation that can be applied to a combination of fishery types at the scale of individual country or Regional Fisheries Management Organisations (RFMOs). Here, we outline a management risk (M-Risk) framework for sharks, rays, and chimaeras used to evaluate species' risk to overfishing resulting from ineffective management. We illustrate our approach with application to one country (Ecuador) and RFMO (Inter-American Tropical Tuna Commission) and illustrate the variation in scores among species. We found that while both management units assessed had similar overall scores, the scores for individual attributes varied. Ecuador scored higher in reporting-related attributes, while the IATTC scored higher in attributes related to data collection and use. We evaluated whether management of individual species was sufficient for their relative sensitivity by combining the management risk score for each species with their intrinsic sensitivity to determine a final M-Risk score. This framework can be applied to determine which species face the greatest risk of overfishing and be used by fisheries managers to identify effective management policies by replicating regulations from countries with lower risk scores.

show abstract

Reliability of the data on tuna catches obtained from the dockside in Indonesia: A study of stakeholders’ perceptions

Cited by 7 publications

References 14 publications

Fishing Quota and International Obligation: Why Has Indonesia been Indicated as a Non-Compliant State

Fishing Quota and International Obligation: Why Has Indonesia been Indicated as a Non-Compliant State

The use of stereo cameras and artificial intelligence data to support capture fisheries landing data monitoring

M-Risk: A framework for assessing global fisheries management efficacy of sharks, rays, and chimaeras

Contact Info

Product

Resources

About