Echo-sounder Buoys Research Articles

Spatial and temporal variation of biomass density beneath drifting fish‐aggregating devices in the western and central Pacific Ocean

AbstractWe analyzed three‐dimensional (3‐D) spatial and temporal variation of biomass density associated with drifting fish aggregating devices (dFADs) in the western and central Pacific Ocean. Detection depth of dFAD echosounder buoys was divided into three layers, for estimation of biomass density in each layer based on detected water volume. Temporal variation and spatial distribution of biomass density in each layer were compared. Similarity of biomass density gravity center shifts in each layer were assessed using the dynamic time warping (DTW) regularization algorithm. Biomass density varied regularly over ~1 month, with the 2nd and 3rd layers delayed ~14 days compared to the 1st layer. Biomass distribution range and density values were higher in the 1st layer than the 2nd and 3rd layers, but locations of maximum biomass density were close. The distribution of biomass density gravity centers between adjacent water layers were similar, with gravity centers of the 2nd and 3rd layers shifted over time in relationd to the 1st layer. Our study demonstrated that the aggregation behavior of species from different water layers attracted by dFADs were related, and emphasized the necessity for ecosystem‐based fisheries management.

Aggregation dynamics of tropical tunas around drifting floating objects based on large-scale echo-sounder data

Based on data gathered by echo-sounder buoys attached to drifting fish-aggregating devices (dFADs) across tropical oceans, we applied a machine learning protocol to examine the temporal trends of tuna-school associations with drifting objects both in comparison to previous studies, and in the context of the ‘ecological trap’ theory. Using a binary output, metrics typically used in the literature were adapted to account for the fact that the entire tuna aggregation under the dFAD was considered. The median time it took tuna to colonize the dFADs for the first time varied between 25 and 43 d, depending on the ocean, and the longest soak and colonization times were registered in the Pacific Ocean. The continuous residence times of tuna schools were generally shorter than continuous absence times (median values: 5-7 and 9-11 d, respectively), in line with the results found by previous studies. Using a regression output, 2 novel metrics, namely aggregation time and disaggregation time, were estimated to obtain further insight into the symmetry of the aggregation process. Across all oceans, the time it took for tuna aggregations to depart from individual dFADs was not significantly longer than the time it took for the aggregations to form. This does not align with what would be expected if the association were ‘strong and long-lasting’ as proposed by one of the aspects of the ‘ecological trap’ theory. The value of these results in the context of the reasons driving the aggregation process is discussed, and further analyses to enrich and make use of this data source are proposed.

Tun-AI: Using echosounder buoy technology to study tuna behaviour at sea

Tun-AI: Using echosounder buoy technology to study tuna behaviour at sea

TUN-AI: Tuna biomass estimation with Machine Learning models trained on oceanography and echosounder FAD data

The use of dFADs by tuna purse-seine fisheries is widespread across oceans, and the echo-sounder buoys attached to these dFADs provide fishermen with estimates of tuna biomass aggregated to them. This information has potential for gaining insight into tuna behaviour and abundance, but has traditionally been difficult to process and use. The current study combines FAD logbook data, oceanographic data and echo-sounder buoy data to evaluate different Machine Learning models and establish a pipeline, named TUN-AI, for processing echo-sounder buoy data and estimating tuna biomass (in metric tons, t) at various levels of complexity: binary classification, ternary classification and regression. Models were trained and tested on over 5000 sets and over 6000 deployments. Of all the models evaluated, the best performing one uses a 3-day window of echo-sounder data, oceanographic data and position/time derived features. This model is able to estimate if tuna biomass was higher than 10 t or lower than 10 t with an F1-score of 0.925. When directly estimating tuna biomass, the best model (Gradient Boosting) has an error (MAE) of 21.6 t and a relative error (SMAPE) of 29.5%, when evaluated over sets. All models tested improved when enriched with oceanographic and position-derived features, highlighting the importance of these features when using echo-sounder buoy data. Potential applications of this methodology, and future improvements, are discussed.

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.

Quantifying the increase in fishing efficiency due to the use of drifting FADs equipped with echosounders in tropical tuna purse seine fisheries

Abstract Numerous pelagic species are known to associate with floating objects (FOBs), including tropical tunas. Purse seiners use this behaviour to facilitate the capture of tropical tunas by deploying artificial drifting fish aggregating devices (dFADs). One major recent change has been the integration of echosounders in satellite-tracked GPS buoys attached to FOBs, allowing fishers to remotely estimate fishable biomass. Understanding the effects of this new technology on catch of the three main tuna species (yellowfin tuna, Thunnus albacares; bigeye tuna, Thunnus obesus; and skipjack tuna, Katsuwonus pelamis) is important to accurately correct for this change in catch-per-unit-effort (CPUE) indices used for stock assessments. We analysed catch data from the French purse seine fleet for the period 2010–2017 in the Indian Ocean to assess the impact of this fleet’s switch to echosounder buoys around 2012. Results indicate that echosounders do not increase the probability a set will be succesful, but they have a positive effect on catch per set, with catches on average increasing by ≈2−2.5 tonnes per set (≈10%) when made on the vessel's own dFADs equipped with an echosounder buoy. Increases were due to a decrease in sets below ≈25 tonnes and an increase in those greater than ≈25 tonnes, with a non-linear transition around this threshold. This increase explains the considerable investment of purse seiners in echosounder buoys, but also raises concerns about bias in stock size estimates based on CPUE if we do not correct for this fishing efficiency increase.

Tuna aggregation dynamics at Drifting Fish Aggregating Devices: a view through the eyes of commercial echosounder buoys

Abstract This study addresses novel questions on the dynamics of tuna aggregations around floating objects, using echosounder buoys data collected throughout the drifts of newly deployed Drifting Fish Aggregating Devices (DFADs) in the Atlantic Ocean (AO) and Indian Ocean (IO). Time series of presence/absence of tunas were obtained by supervised classification of acoustic data. To avoid biases related to the variability in individual DFAD soak times, a new approach was developed to estimate the average colonization time of new DFADs by tuna aggregations. We showed that tunas colonize DFADs after an average of 16 days in the AO, and 40 days in the IO. Moreover, the analysis indicated that the time span during which tuna aggregations occupy DFADs is driven by a time-independent process with short- and long-term residence modes. On average, DFADs were continuously occupied by tuna aggregations for 6 and 9 days in the IO and AO, respectively. The time between two consecutive aggregations at the same DFAD averaged 9 days in the IO and 5 days in the AO. Throughout their soak time after being colonized, DFADs remained occupied for a larger proportion of time in the AO (63%) than in the IO (45%).

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.

The use of echo-sounder buoys in Mediterranean Sea: A new technological approach for a sustainable FADs fishery

In the Mediterranean Sea, dolphinfish fishery has employed a great number of anchored Fish Aggregating Devices (FADs) arranged in lines, that represents a threat to navigation and to the marine environment and is economically disadvantageous to fishers. In this research, echo-sounder buoys were tested for the first time in the Mediterranean, and it was evaluated if this technological method can be useful to studies aimed to reduce the impact of FADs from the perspective of sustainable fishery.The study was carried out in November and December 2015 in a Tyrrhenian area where echo-sounder buoys were tied to anchored and drifting FADs and aggregated biomass estimates were recorded daily. Comparisons were made to evaluate whether there are: a relation between the number of anchored FADs and associated biomass; and differences, in terms of aggregated biomass, between anchored and drifting FADs.No clear correlation was found between the number of anchored FADs and biomass, while the drifting FADs showed a greater power of attraction than the anchored FADs. Anyway, the echo-sounder buoys may be suitable for future studies. It was highlighted that their simple use in the Mediterranean FADs fishery could facilitate a reduction of the high number of anchored FADs.

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.

Evolution and current state of the technology of echo-sounder buoys used by Spanish tropical tuna purse seiners in the Atlantic, Indian and Pacific Oceans

Despite important technological changes in the tropical tuna purse seine fishery industry since the 1980s, the influence of these changes on the fleet efficiency and behaviour has not yet been investigated in depth. In this study, the practical use, fishing strategy and state of echo-sounder buoy technology applications were studied using personal interviews over three consecutive years (2010–2012) with approximately half of the Spanish tropical tuna purse seine fishing masters and licensed captains operating in the Atlantic, Pacific and Indian Oceans. The results suggested that echo-sounder buoys have significantly impacted drifting fish aggregating device (DFAD) fishing strategies since their introduction into the fishery in the last decade, favouring the expansion of DFAD fishing grounds. In addition, fishers are starting to be able to remotely discriminate species, which increases the fleet efficiency. Additionally, the number of echo-sounder buoys used by each vessel has been increasing each year, which demonstrates the utility of the information provided by this tool for the Spanish fleet. Various aspects of these devices’ use, consequences for fishing strategy, search time, nominal effort and potential future applications are discussed.

Silent ships do not always encounter more fish (revisited): comparison of acoustic backscatter from walleye pollock recorded by a noise-reduced and a conventional research vessel in the eastern Bering Sea

Abstract De Robertis, A., and Wilson, C. D. 2011. Silent ships do not always encounter more fish (revisited): comparison of acoustic backscatter from walleye pollock recorded by a noise-reduced and a conventional research vessel in the eastern Bering Sea. – ICES Journal of Marine Science, 68: 2229–2239. Vessel-induced avoidance behaviour is potentially a major source of error in surveys of fish populations. Noise-reduced research vessels have been constructed in an effort to minimize fish reactions to auditory stimuli produced by survey vessels. Here, measurements of acoustic backscatter from walleye pollock (Theragra chalcogramma) made on the eastern Bering Sea Shelf from the conventional NOAA ship “Miller Freeman” (MF) are compared with similar measurements made on the noise-reduced NOAA ship “Oscar Dyson” (OD). As in a previous study, acoustic abundance measurements from these vessels were equivalent during daylight, when large-scale acoustic surveying is conducted. However, significant differences were observed at night: on average, 44% more pollock backscatter was observed from OD than MF. Observations with a free-drifting echosounder buoy suggest that the night-time discrepancy is attributable to a stronger behavioural response to the passage of the louder MF, and a resulting decrease in pollock target strength. Pollock did not exhibit a strong reaction to the passage of OD. These observations are consistent with previous comparisons of these vessels, which show that with vessel differences, the noise-reduced OD detects more pollock.