Drifting Fish Aggregating Devices Research Articles

Target strength measurements of yellowfin tuna (Thunnus albacares) and acoustic discrimination of three tropical tuna species

Abstract Tropical tuna fisheries support some of the largest artisanal and industrial fisheries worldwide. Approximately 37% of the tropical tuna catch by industrial purse seiners is obtained from tuna associated with drifting fish aggregating devices (DFADs), where three tuna species coexist: skipjack (Katsuwonus pelamis), bigeye (Thunnus obesus), and yellowfin tuna (Thunnus albacares), with stocks subject to different health status. Purse seine fishers heavily rely on acoustic technology to detect and assess the quantity of tuna at DFADs. Yet, accurately distinguishing between species using solely acoustic methods is limited by insufficient knowledge about each species' acoustic response across frequencies. This study was carried out on six swimbladdered individuals belonging to two sets with mean lengths of 51.9 ± 9.5 and 52.9 ± 2 cm. It focuses on the frequency response obtained from ex situ measurements of yellowfin tuna recorded at 38, 70, 120, and 200 kHz, which revealed a flat response across frequencies, with b20 values of −72.4 ± 9, −73.2 ± 8, -72.3 ± 8, and −72.3 ± 9 dB, respectively. These results, contrast with previous findings on bigeye and skipjack, demonstrating the discrimination potential of acoustics in these three species. To harness this potential, a discrimination algorithm was developed.

The challenge of assessing the effects of drifting fish aggregating devices on the behaviour and biology of tropical tuna

AbstractFishers have intensively used drifting fish aggregating devices (DFADs) over the last three decades to facilitate their catch of tropical tunas. DFADs increase purse‐seine efficiency, potentially increasing tuna fishing mortality. They could also have impacts on tuna natural mortality and reproductive potential, and assessing the consequences of their presence at sea on tuna populations is a challenge. The use of DFADs results in a major increase in the number of floating objects, which are spatially heterogeneous at sea. To date, no converging scientific results exist regarding the effects of DFADs on the large‐scale movements and behaviour of tuna, mainly due to the difficulty of disentangling the respective roles of DFADs and environmental factors. Some biological indices show that tuna condition is lower when associated to a floating object than in a free‐swimming school. However, it is not clear whether this is the cause or the consequence of the association nor if it has long‐term effects on individuals' fitness. Further scientific progress requires (i) the collection of time series of indicators to monitor habitat change, individual behaviour, individual fitness, and population dynamics and (ii) experimental studies to identify the underlying behavioural and biological processes involved in associative behaviour. The extent of the modification of the surface habitat by the massive deployment of DFADs and the current uncertainty of the possible long‐term consequences on the individual fitness and dynamics of tuna populations argue for the need for increased awareness of this issue by Regional Fisheries Management Organisations regulating tuna fishing.

How technical change has boosted fish aggregation device productivity in the Indian Ocean tuna fishery

Excess harvesting power can threaten the long-term sustainability of fisheries. Indicators of excess harvesting capacity must include input–output-based estimates of economic production efficiency. The increasing use of drifting Fish-Aggregating-Devices (DFADs) has boosted fishing productivity in high-seas tuna fisheries, perhaps beyond the biological capacity of the stocks, and is an object of global debate. We carried out a Data Envelopment Analysis (DEA) of relative changes in production efficiencies of the French purse-seine fleet targeting tropical tuna in the western Indian Ocean using two fishing strategies: (1) on floating objects (FOB) and (2) free swimming schools (FSC) using tuna catch and effort data spanning 1992–2019. We show that FOB fishing evolved dramatically through time with an estimated change of 3.6%yr−1 (8.0%yr−1 2007–2019), in contrast to 2.1%yr−1 for FSC. While the efficiency level in combining and using inputs has barely changed for FOB fishing, it means that all the growth in productivity comes from technical change for this strategy. The dynamics is different for the FSC with a mixture of innovation and higher efficiency. Immediate plans to improve input-based management in this region are needed to prevent further risks of overfishing to yellowfin (Thunnus albacares) and skipjack (Katsuwonus pelamis) tunas.

Developing a science-based framework for the management of drifting Fish Aggregating Devices

Fish Aggregating Devices (FADs) are man-made floating objects deployed by fishers to aggregate tuna and facilitate their catch. Currently, more than half of the global tropical tuna purse-seine catches occur at FADs. The fast development of the purse-seine fisheries operating on drifting FADs (DFADs) has raised concerns regarding their impacts on tuna populations, on non-target species like sharks, as well as on the pelagic and coastal habitats. Consequently, the management of DFAD fisheries is a priority for all tuna regional fisheries management organizations. Due to the little availability of science-based advice to support management decisions, resolutions on DFADs have been mainly based on precautionary principles. In this study we propose a science-based framework for the management of DFADs, relying on indicators and operating models. A set of models and indicators that help evaluate the ecological impacts of DFADs is presented, considering the case study of DFAD fisheries management in the Indian Ocean. The objective of this framework is to assess and predict the effects of DFADs on coastal and pelagic ecosystems, in order to support and/or evaluate past, present and future management actions.

No evidence from long-term analysis of yellowfin tuna condition that drifting fish aggregating devices act as ecological traps

Human-induced habitat modifications can severely impact the biology and behavior of wild species. Drifting fish aggregating devices (DFADs), used by industrial purse-seine tropical tuna fisheries, significantly increased the number of floating objects found in the open ocean, with which tropical tuna associate. This habitat change has raised concerns over the risk of modifying the behavior and altering the biology of tuna and other associated species (the so-called ecological trap hypothesis). Relying on a time-series from 1987-2019 of more than 25000 length-weight samples collected in the western Indian Ocean, we reject the hypothesis that the body condition (Le Cren’s relative condition factor, Kn) of yellowfin tuna Thunnus albacares decreased concurrently with the increased number of DFADs. This result suggests the absence of negative long-term impacts of DFADs on the condition of tuna. As other factors may have counteracted possible negative effects of DFADs, we recommend long-term monitoring of the habitat along with biological and behavioral parameters of tunas to detect any critical change.

A standard processing framework for the location data of satellite-linked buoys on drifting fish aggregating devices

Satellite-linked buoys used by tropical tuna purse-seine vessels on drifting fish aggregating devices (DFADs) provide a continuous stream of information on both the ocean characteristics and the presence and size of fish aggregations associated with DFADs, enabling the study of pelagic communities. This unprecedented amount of data is characterized by ocean-scale coverage with high spatial and temporal resolutions, but also by different data formats and specifications depending on buoy model and brand, as well as on the type of data exchange agreements into play. Their use for scientific and management purposes is therefore critically dependent on the abilities of algorithms to process heterogeneous data formats and resolutions. This paper proposes a unified set of algorithms for processing the buoys location data used by the two major purse seine fleets operating in the Atlantic and Indian oceans. Three main issues that need to be addressed prior to the exploitation of the data are identified (structural errors, data records on land and on-board vessels) and five specific filtering criteria are proposed to improve the data cleaning process and, hence, quality. Different filtering procedures are also compared, and their advantages and limitations are discussed.

Risks to large marine protected areas posed by drifting fish aggregation devices.

Mapping and predicting the potential risk of fishing activities to large marine protected areas (MPAs), where management capacity is low but fish biomass may be globally important, is vital to prioritizing enforcement and maximizing conservation benefits. Drifting fish aggregating devices (dFADs) are a highly effective fishing method employed in purse seine fisheries that attract and accumulate biomass fish, making fish easier to catch. However, dFADs are associated with several negative impacts, including high bycatch rates and lost or abandoned dFADs becoming beached on sensitive coastal areas (e.g., coral reefs). Using Lagrangian particle modeling, we determined the potential transit of dFADs in a large MPA around the Chagos Archipelago in the central Indian Ocean. We then quantified the risk of dFADs beaching on the archipelago's reefs and atolls and determined the potential for dFADs to pass through the MPA, accumulate biomass while within, and export it into areas where it can be legally fished (i.e., transit). Over one‐third (37.51%) of dFADs posed a risk of either beaching or transiting the MPA for >14 days, 17.70% posed a risk of beaching or transiting the MPA for >30 days, and 13.11% posed a risk of beaching or transiting the MPA for >40 days. Modeled dFADs deployed on the east and west of the perimeter were more likely to beach and have long transiting times (i.e., posed the highest risk). The Great Chagos Bank, the largest atoll in the archipelago, was the most likely site to be affected by dFADs beaching. Overall, understanding the interactions between static MPAs and drifting fishing gears is vital to developing suitable management plans to support enforcement of MPA boundaries and the functioning and sustainability of their associated biomass.

Machine learning to detect bycatch risk: Novel application to echosounder buoys data in tuna purse seine fisheries

The advent of big data and machine learning offers great promise for addressing conservation and management questions in the oceans. Yet, few applications of machine learning exist to mitigate the overexploitation of marine resources. Tropical tuna purse seine fisheries (TTPSF) are distributed worldwide and account for two thirds of the global tuna catch. In these fisheries, the use of Drifting Fish Aggregating Devices (DFADs)— n-made floating objects massively deployed by fishers to increase their tuna catches—results in the incidental catch of non-target species, termed bycatch. We explored the possibility of applying machine learning on echosounder buoys attached to DFADs, representing an unprecedented source of big data, for identifying high bycatch risk at DFADs. We trained random forests algorithms to differentiate between high and low bycatch occurrence based on matched echosounder and onboard observer data for the same DFADs (representing sample sizes of 838 and 2144 in the Atlantic and the Indian Ocean, respectively). Algorithms showed a better performance in the Atlantic Ocean (accuracy of 0.66 versus 0.58 in the Indian Ocean) and were best at detecting the “high bycatch” occurrence class. These results unravel the potential of machine learning applied to fishers' buoys data for bycatch reduction and improved selectivity in one of the largest fisheries worldwide.

Performance evaluation of a shallow prototype versus a standard depth traditional design drifting fish-aggregating device in the equatorial eastern Pacific tuna purse-seine fishery

An at-sea experiment was undertaken to evaluate the performance of 150 shallow depth (5 m) prototype drifting fish-aggregating devices (DFADs) with rope appendages, compared to 150 standard depth (∼ 40 m) traditional design DFADs with purse-seine net appendages, in the equatorial eastern Pacific Ocean tuna purse-seine fishery, seeking a solution to reduce purse-seine fishing mortality on undesirable sizes of bigeye tuna. Following concurrent deployments of the two DFAD types along transects, the average daily drift speeds were significantly different but similar as were the drift trajectories among the two DFAD types. Based on evaluations of the time-series of acoustic data from the echo-sounder buoys attached to the shallow and standard depth DFADs, the average time before aggregation by non-tuna species was 15.3 d (range: 3.2–65.5) and 18.2 d (range: 1.1–101.2), respectively, and the average time before aggregation by tuna species was 62.2 d (range: 3.3–248.3) and 70.2 d (range: 1.5–270.5), respectively. Analyses of the catch per set data for tunas and non-tuna species, using generalized additive mixed models with Bayesian inference, indicated no significant differences in catch rates from sets on shallow and standard depth DFADs. There was a similar proportion of bigeye tuna in the catch for purse-seine sets on the shallow and standard depth DFADs.

Seasonal Distribution of Tuna and Non-tuna Species Associated With Drifting Fish Aggregating Devices (DFADs) in the Western Indian Ocean Using Fishery-Independent Data

Man-made floating objects in the surface of tropical oceans, also called drifting fish aggregating devices (DFADs), attract tens of marine species, including tunas and non-tuna species. In the Indian Ocean, around 80% of the sets currently made by the EU purse-seine fleet are on DFADs. Due to the importance and value of this fishery, understanding the habitat characteristics and dynamics of pelagic species aggregated under DFADs is key to improve fishery management and fishing practices. This study implements Bayesian hierarchical spatial models to investigate tuna and non-tuna species seasonal distribution, based on fisheries-independent data derived from fishers’ echo-sounder buoys, environmental information (Sea Surface Temperature, Chlorophyll, Salinity, Eddie Kinetic Energy, Oxygen concentration, Sea Surface Height, Velocity and Heading) and DFAD variables (DFAD identification, days at sea). Results highlighted group-specific spatial distributions and habitat preferences, finding higher probability of tuna presence in warmer waters, with higher sea surface height and low eddy kinetic energy values. In contrast, highest probabilities of non-tuna species were found in colder and productive waters. Days at sea were relevant for both groups, with higher probabilities at objects with higher soak time. Our results also showed species-specific temporal distributions, suggesting that both tuna and non-tuna species may have different habitat preferences depending on the monsoon period. The new findings provided by this study will contribute to the understanding of the ecology and behavior of target and non-target species and their sustainable management.

Machine learning for characterizing tropical tuna aggregations under Drifting Fish Aggregating Devices (DFADs) from commercial echosounder buoys data

The use of echosounder buoys deployed in conjunction with Drifting Fish Aggregating Devices (DFADs) has progressively increased in the tropical tuna purse seine fishery since 2010 as a means of improving fishing efficiency. Given the broad distribution of DFADs, the acoustic data provided by echosounder buoys can provide an alternative to the conventional CPUE index for deriving trends on tropical tuna stocks. This study aims to derive reliable indices of presence of tunas (and abundance) using echosounder buoy data. A novel methodology is presented which utilizes random forest classification to translate the acoustic backscatter from the buoys into metrics of tuna presence and abundance. Training datasets were constructed by cross-referencing acoustic data with logbook and observer data which reported activities on DFADs (tuna catches, new deployments and visits of DFADs) in the Atlantic and Indian Oceans from 2013 to 2018. The analysis showed accuracies of 75 and 85 % for the recognition of the presence/absence of tuna aggregations under DFADs in the Atlantic and Indian Oceans, respectively. The acoustic data recorded at ocean-specific depths (6–45 m in the Atlantic and 30–150 m in the Indian Ocean) and periods (4 a.m.–4 p.m.) were identified by the algorithm as the most important explanatory variables for detecting the presence of tuna. The classification of size categories of tuna aggregations showed a global accuracy of nearly 50 % for both oceans. This study constitutes a milestone towards the use of echosounder buoys data for scientific purposes, including the development of promising fisheries-independent indices of abundance for tropical tunas.

Comparing the distribution of tropical tuna associated with drifting fish aggregating devices (DFADs) resulting from catch dependent and independent data

Species distribution models (SDMs) are used for a variety of scientific and management applications. For species associated with drifting fish aggregating devices (DFADs), such as tuna, spatial models can help tuna Regional Fisheries Management Organizations (t-RFMOs) understand their habitat characteristics and dynamics. DFADs are monitored and tracked with satellite linked echo-sounder buoys, which remotely provide fishers rough estimates of the abundance of fish underneath them. Although this type of catch-independent data has been recently used in scientific studies, SDMs using these data have never been compared with models using catch-dependent data (i.e. nominal catch data). This study investigates the results obtained with both data sources using Bayesian Hierarchical spatio-temporal models, allowing to analyze their advantages and disadvantages, as well as compare the predicted distributions. Although the two model outputs show, in general, similar areas of tuna presence under the DFADs, the most remarkable result of the comparison between the models derived from the two different data sources is the precision of the hotspots identified in the prediction maps. The maps obtained with acoustic data allow identifying areas of high probability of tuna presence under the DFADs with greater precision, whereas the maps derived from catch data do not allow observing any variation on a finer scale. The application of spatio-temporal models of tuna associated with DFADs using acoustic data provided by fishers’ echo-sounder buoys appears promising to identify the distribution dynamics of the species in a cost-effective way and may help designing integrated spatial programs for more efficient fishery management.

From fisheries to scientific data: A protocol to process information from fishers’ echo-sounder buoys

Most of the drifting fish aggregating devices (DFADs) used by the industrial tropical tuna purse seine fishery are deployed with satellite linked echo-sounder buoys. These buoys provide information on the accurate geo-location of the floating object and estimates of fish biomass aggregated along the trajectory of the DFAD. This huge amount of information is provided in large and complex datasets consisting in rough estimations of biomass, which are not originally intended to be used for scientific purposes but for fishing. This study establishes a standardized protocol for cleaning raw data from fishers' echo-sounders buoys prior to their use for scientific purposes, in which potential errors are eliminated. In addition, the main advantages and limitations of the data are analyzed and discussed. This paper provides the first step towards the use and better understanding of fishers' echo sounder buoys for scientific research.

Aggregation process of drifting fish aggregating devices (DFADs) in the Western Indian Ocean: Who arrives first, tuna or non-tuna species?

Floating objects drifting in the surface of tropical waters, also known as drifting fish aggregating devices (DFADs), attract hundreds of marine species, including tuna and non-tuna species. Industrial tropical purse seiners have been increasingly deploying artificial man-made DFADs equipped with satellite linked echo-sounder buoys, which provide fishers with information on the accurate geo-location of the object and rough estimates of the biomass aggregated underneath, to facilitate the catch of tuna. Although several hypotheses are under consideration to explain the aggregation and retention processes of pelagic species around DFADs, the reasons driving this associative behavior are uncertain. This study uses information from 962 echo-sounder buoys attached to virgin (i.e. newly deployed) DFADs deployed in the Western Indian Ocean between 2012 and 2015 by the Spanish fleet (42,322 days observations) to determine the first detection day of tuna and non-tuna species at DFAD and to model the aggregation processes of both species group using Generalize Additive Mixed Models. Moreover, different seasons, areas and depths of the DFAD underwater structure were considered in the analysis to account for potential spatio-temporal and structure differences. Results show that tuna species arrive at DFADs before non-tuna species (13.5±8.4 and 21.7±15.1 days, respectively), and provide evidence of the significant relationship between DFAD depth and detection time for tuna, suggesting faster tuna colonization in deeper objects. For non-tuna species, this relationship appeared to be not significant. The study also reveals both seasonal and spatial differences in the aggregation patterns for different species groups, suggesting that tuna and non-tuna species may have different aggregative behaviors depending on the spatio-temporal dynamic of DFADs. This work will contribute to the understanding of the fine and mesoscale ecology and behavior of target and non-target species around DFADs and will assist managers on the sustainability of exploited resources, helping to design spatio-temporal conservation management measures for tuna and non-tuna species.

Environmental preferences of tuna and non-tuna species associated with drifting fish aggregating devices (DFADs) in the Atlantic Ocean, ascertained through fishers’ echo-sounder buoys

Understanding the relationship between environmental variables and pelagic species concentrations and dynamics is helpful to improve fishery management, especially in a changing environment. Drifting fish aggregating device (DFAD)-associated tuna and non-tuna biomass data from the fishers’ echo-sounder buoys operating in the Atlantic Ocean have been modelled as functions of oceanographic (Sea Surface Temperature, Chlorophyll-a, Salinity, Sea Level Anomaly, Thermocline depth and gradient, Geostrophic current, Total Current, Depth) and DFAD variables (DFAD speed, bearing and soak time) using Generalized Additive Mixed Models (GAMMs). Biological interaction (presence of non-tuna species at DFADs) was also included in the tuna model, and found to be significant at this time scale. All variables were included in the analyses but only some of them were highly significant, and variable significance differed among fish groups. In general, most of the fish biomass distribution was explained by the ocean productivity and DFAD-variables. Indeed, this study revealed different environmental preferences for tunas and non-tuna species and suggested the existence of active habitat selection. This improved assessment of environmental and DFAD effects on tuna and non-tuna catchability in the purse seine tuna fishery will contribute to transfer of better scientific advice to regional tuna commissions for the management and conservation of exploited resources.

Diel behaviour of tuna and non-tuna species at drifting fish aggregating devices (DFADs) in the Western Indian Ocean, determined by fishers’ echo-sounder buoys

As tropical pelagic species are attracted by floating objects in the surface of the ocean, industrial purse seiners deploy thousands of man-made drifting fish aggregating devices (DFADs) to facilitate their catch of tunas. However, the sharp increase in the use of DFADs leads to some ecological concerns, such as producing higher amount of by-catch or alteration of natural behaviour of fish. We used fishers’ satellite-linked GPS buoys equipped with echo-sounders to continuously collect acoustic samples under remote DFADs and investigate the diel behaviour patterns of the associated fish (i.e., non-tuna species and small and large tunas) and their potential biological interactions. Results showed a strong correlation between the presence of non-tuna species and small tunas, and between small and large tunas. Diel biomass dynamics were highly variable and seem to be both species and region-specific, which may suggest adaptive behaviour patterns. Tuna associated with DFADs in the Somalia area showed a clear night-time associative behaviour. In contrast, tuna in the NW Seychelles associated with DFADs to a greater degree during daytime. In the Mozambique Channel, large tuna showed daytime associative behaviour, while small tuna showed a maximum biomass at sunrise, decreasing over the day. The associative behaviour of non-tuna species was slightly variable, being uniform near the equator or showing two peaks when increasing latitude. This study shows the importance and effect of biological factors on the associative behaviour of the fish and serves as a first step towards improving pre-set selectivity of purse seine fisheries using DFADs. The fish presence and density may improve DFAD attraction and detectability and the observed periodicity by species and area shows both similarities and differences with published literature.

A model based on data from echosounder buoys to estimate biomass of fish species associated with fish aggregating devices

Most of the drifting fish aggregating devices (DFADs) used in industrial tropical tuna purse seine fisheries are equipped with satellite linked echosounder buoys, which provide fishing crews with remote, accurate geolocation information and rough estimates of FAD-associated tuna biomass. One of the most common brands of echosounder buoys (SATLINK, Madrid, Spain) is currently calibrated for the target strength of skipjack tuna (Katsuwonus pelamis) and provides biomass data on. that species. Using that brand of echosounder buoy, we developed a new behavior-based approach to provide relative biomass estimates and a remote target classification of fish aggregations at FADs. The model is based on current knowledge of the vertical distribution of the main fish species associated with FADs, as well as on appropriate TS and weight values for different species and sizes, and is further based on parameter optimization against a set of fishing operations on DFADs. This model reduced the error variability in biomass estimates by about 60% and also reduced the ranges of underestimation. and overestimation by 55% and 75%, respectively. Similarly, the original coefficients of correlation and determination were also considerably improved from 0.50 and 0.25 to 0.90 and 0.82, respectively. We discuss how this new method opens new opportunities for scientific studies and has implications for sustainable fishing.

Marine turtle interaction with purse-seine fishery in the Atlantic and Indian oceans: Lessons for management

Bycatch of endangered marine turtles is a growing issue for the management of all fisheries, including the oceanic purse-seine fishery. The aim of this study was to assess the spatial and temporal variation in bycatch rates of these species in the entire European purse-seine fishery operating in the Atlantic and Indian oceans. The study was based on data collected through observer programs from 1995 to 2011. During that period, a total of 15 913 fishing sets were observed, including 6 515 on Drifting Fish Aggregating Devices (DFADs) and 9 398 on free swimming schools, representing a global coverage of 10.3% and 5.1% of the total fishing activity in the Atlantic and Indian Ocean, respectively. Moreover, from 2003 to 2011, 14 124 specific observations were carried out on DFADs to check turtle entanglement in the net covering DFADs. We found that the purse-seine fishery has a very low impact on marine turtles. We estimated that the annual number of individuals incidentally captured was 218 (SD = 150) and 250 (SD = 157) in the Atlantic and Indian Ocean, respectively, with more than 75% being released alive. The present study also investigated the impact of DFADs; which is considered a key conservation issue for this fishery. Drifting objects may play a key role in aggregating juveniles of marine turtles, implying the need for improving their construction to avoid entanglement (e.g. avoiding nets in the structure); however, based on our study it is not the main source of incidental captures of marine turtles in this fishery.

Global spatio-temporal patterns in tropical tuna purse seine fisheries on drifting fish aggregating devices (DFADs): Taking a historical perspective to inform current challenges

This study provides a historical overview of the use of drifting fish aggregating devices (DFADs) in purse seine fisheries since the early 1990s, using global tuna fisheries datasets from the four tuna Regional Fisheries Management Organizations (RFMOs). Tropical tuna purse seine fisheries typically target large yellowfin (Thunnus albacares) and bigeye (Thunnus obesus) tunas on free-swimming schools and skipjack (Katsuwonus pelamis )a nd juveniles of yellowfin and bigeye associated with drifting objects. DFADs have enabled global skipjack catches to markedly increase, and have also introduced major scientific issues for all tuna-RFMOs. In particular, they have strongly modified the fishing strategies of purse seiners that fish on a combination of free-swimming and DFAD-associated schools. Consequently, the cumulated search time traditionally used to quantify nominal fishing effort to assess the status of tuna stocks is inconsistent and cannot be used to derive time series of abundance indices from catch-per-unit of-effort (CPUE). In addition, the lack of information available on the construction, deployment, and use of DFADs has prevented effective monitoring of the fishing pressure over the last two decades exerted by purse seine fleets using this fishing mode. Juveniles of tropical tunas represent a substantial proportion of purse seine catch on DFADs in the three oceans, which has raised particular concern for some bigeye stocks that have been subject to overfishing in the past. Catches of juvenile tunas by DFAD fishing may also result in a decrease in recruitment for fisheries that target adult tunas such as longliners. In addition, some demographic parameters of tunas and other species associated with DFADs may be affected by the resultant habitat modification arising from the widespread deployment of DFADs. Evidence in the literature and provided by the ratio-estimator method suggest that fishing DFAD-associated schools may result in about 100 000 t of bycatch and discards annually. In addition, there is further potential for ghost fishing related mortality of sensitive species such as marine turtles and pelagic sharks. In this context and following a precautionary approach, we finally discuss the increasing need for all tuna-RFMOs to reduce, or at least monitor and control, the use of DFADs to mitigate their adverse effects not only on yellowfin and bigeye stocks but also on open-ocean ecosystems.

Diet of three large pelagic fishes associated with drifting fish aggregating devices (DFADs) in the western equatorial Indian Ocean

Several species of fish, aggregate around DFADs in marine tropical waters. We captured three predatory species: yellow fin tuna (Thunnus albacares), wahoo (Acanthocybium solandri) and dolphinfish (Coryphaena hippurus) from aggregations under DFADs in the Western Indian Ocean to characterize their diet and determine whether they fed on other DFAD associated organisms. Yellowfin tuna did not feed on DFAD–associated prey, while wahoo and dolphinfish did exploit resources aggregated by the DFADs, though they predominantly fed on other non–associated organisms. Opportunistic feeding on surface swarming stomatopod crustaceans was observed in yellowfin tuna and dolphinfish associated with FADs, but was not observed in wahoo.