Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models

Recent advances in technologies have lead to a vast influx of data on movements, based on discrete recorded position of animals or fishing boats, opening new horizons for future analyses. However, most of the potential interest of tracking data depends on the ability to develop suitable modelling strategies to analyze trajectories from discrete recorded positions. A serious modelling challenge is to infer the evolution of the true position and the associated spatio-temporal distribution of behavioural states using discrete, error-prone and incomplete observations. In this paper, a Bayesian Hierarchical Model (HBM) using Hidden Markov Process (HMP) is proposed as a template for analyzing fishing boats trajectories based on data available from satellite-based vessel monitoring systems (VMS). The analysis seeks to enhance the definition of the fishing pressure exerted on fish stocks, by discriminating between the different behavioural states of a fishing trip, and also by quantifying the relative importance of each of these states during a fishing trip. The HBM approach is tested to analyse the behaviour of pelagic trawlers in the Bay of Biscay. A hidden Markov chain with a regular discrete time step is used to model transitions between successive behavioural states (e.g., fishing, steaming, stopping (at Port or at sea)) of each vessel. The parameters of the movement process (speed and turning angles) are defined conditionally upon the behavioural states. Bayesian methods are used to integrate the available data (typically VMS position recorded at discrete time) and to draw inferences on any unknown parameters of the model. The model is first tested on simulated data with different parameters structures. Results provide insights on the potential of HBM with HMP to analyze VMS data. They show that if VMS positions are recorded synchronously with the instants at which the process switch from one behavioural state to another, the estimation method provides unbiased and precise inferences on behavioural states and on associated movement parameters. However, if the observations are not gathered with a sufficiently high frequency, the performance of the estimation method could be drastically impacted when the discrete observations are not synchronous with the switching instants. The model is then applied to real pathways to estimate variables of interest such as the number of operations per trip, time and distance spent fishing or travelling.     

Scale-invariant movements of fishermen: the same foraging strategy as natural predators.

We analyzed the movement of fishing vessels during fishing trips in order to understand how fishermen behave in space while searching for fish. For that purpose we used hourly geo-referenced positions of vessels, provided by a satellite vessel monitoring system, for the entire industrial fleet (809 vessels) of the world's largest single species fishery (Peruvian anchovy, Engraulis ringens) from December 1999 to March 2003. Observed trajectories of fishing vessels are well modeled by Lévy random walks, suggesting that fishermen use a stochastic search strategy which conforms to the same search statistics as non-human predators. We show that human skills (technology, communication, or others) do not result in the fishermen's spatial behavior being fundamentally different from that of animal predators. With respect to probability of prey encounter, our results suggest that fishermen, on average, evolved an optimal movement pattern (mu = 2.00) among the family of Lévy random walks. This Lagrangian approach opens several perspectives in terms of operational management of the pelagic fish stock.     

Optimization of an artificial neural network for identifying fishing set positions from VMS data: An example from the Peruvian anchovy purse seine fishery

The spatial behavior of numerous fishing fleets is nowadays well documented thanks to satellite Vessel Monitoring Systems (VMS). Vessel positions are recorded on a frequent and regular basis which opens promising perspectives for improving fishing effort estimation and management. However, no specific information is provided on whether the vessel is fishing or not. To answer that question, existing works on VMS data usually apply simple criteria (e.g. threshold on speed). Those simple criteria generally focus in detecting true positives (a true fishing set detected as a fishing set); conversely, estimation errors are given no attention. For our case study, the Peruvian anchovy fishery, those criteria overestimate the total number of fishing sets by 182%. To overcome this problem an artificial neural network (ANN) approach is presented here. In order to set both the optimal parameterization and use “rules” for this ANN, we perform an extensive sensitivity analysis on the optimization of (1) the internal structure and training algorithm of the ANN and (2) the “rules” used for choosing both the relative size and the composition of the databases (DBs) used for training and inferring with the ANN. The “optimized” ANN greatly improves the estimates of the number and location of fishing events. For our case study, ANN reduces the total estimation error on the number of fishing sets to 1% (in average) and obtains 76% of true positives. This spatially explicit information on effort, provided with error estimation, should greatly reduce misleading interpretations of catch per unit effort and thus significantly improve the adaptive management of fisheries. While fitted on Peruvian anchovy fishery data, this type of neural network approach has wider potential and could be implemented in any fishery relying on both VMS and at-sea observer data. In order to increase the accuracy of the ANN results, we also suggest some criteria for improving sampling design by at-sea observers and VMS data.     

Threats of illegal,unregulated, and unreported fishing to biodiversity and food security in the Republic of the Congo

Illegal, unregulated, and unreported (IUU) fishing poses a major threat to effective management of marine resources, affecting biodiversity and communities dependent on these coastal resources. Spatiotemporal patterns of industrial fisheries in developing countries are often poorly understood, and global efforts to describe spatial patterns of fishing vessel activity are currently based on automatic identification system (AIS) data. However, AIS is often not a legal requirement on fishing vessels, likely resulting in underestimates of the scale and distribution of legal and illegal fishing activity, which could have significant ramifications for targeted enforcement efforts and the management of fisheries resources. To help address this knowledge gap, we analyzed 3 years of vessel monitoring system (VMS) data in partnership with the national fisheries department in the Republic of the Congo to describe the behavior of national and distant-water industrial fleets operating in these waters. We found that the spatial footprint of the industrial fisheries fleet encompassed over one-quarter of the Exclusive Economic Zone. On average, 73% of fishing activity took place on the continental shelf (waters shallower than 200 m). Our findings highlight that VMS is not acting as a deterrent or being effectively used as a proactive management tool. As much as 33% (13% on average) of fishing effort occurred in prohibited areas set aside to protect biodiversity, including artisanal fisheries resources, and the distant-water fleet responsible for as much as 84% of this illegal activity. Given the growth in industrial and distant-water fleets across the region, as well as low levels of management and enforcement, these findings highlight that there is an urgent need for the global community to help strengthen regional and national capacity to analyze national scale data sets if efforts to combat IUU fishing are to be effective.     

Can Eco-Labels Tune a Market? Evidence from Dolphin-Safe Labeling

In this paper we test whether the dolphin-safe labels altered consumer purchases of tuna. We also provide a partial measure of the total welfare effects of the dolphin-safe labeling policy. The results confirm our hypothesis that the dolphin–tuna controversy and the subsequent implementation of dolphin-safe labeling affected consumer behavior. Further, the paper provides market-based evidence that consumers can respond to eco-labels; the dolphin-safe label increased the market share of canned tuna. The welfare analysis provides a partial measure of society's willingness to pay to avoid personally contributing to dolphin mortality as a result of tuna fishing.     

Tuna food habits related to the micronekton distribution in French Polynesia

Stomach content analyses are commonly used to study both fish feeding behaviour and trophic conditions. However, the interpretation of such data depends on fish foraging behaviour for a given environment and how representative the stomach contents are to the prey distribution. Tuna feeding behaviour was studied within the context of a research programme conducted in French Polynesia. Tuna prey distribution was characterised using acoustic measurements and pelagic trawls; thereafter, this distribution was compared with the stomach contents of tuna caught using an instrumented longline. Acoustic, pelagic trawling and stomach content analyses give complementary elements to describe the pelagic trophic habitat and to better understand tuna-prey relationships. The classic concept of a reduced food availability for tunas in the tropical pelagic environment seems relative. Tunas able to dive enough during daytime to exploit the migrant micronektonic species secure a source of regular food. This is particularly true of bigeye tuna (Thunnus obesus), which have ecophysiological capacities for this purpose. The behaviour of albacore tuna (T. alalunga), which dive >400 m in depth, remains less clear, as little is known about their vertical behaviour. Lastly, yellowfin tuna (T. albacares), which are distributed in more superficial waters, can better exploit the biomass of juvenile fish and crustaceans exported from the reefs. Analysis of the stomach fullness of tuna caught by longline, a passive gear, generally showed an empty state. This result suggests that most tuna foraging on large prey aggregations present in the study area are quickly satiated and escape longline capture and sampling. A consequence is that studies of tuna feeding behaviour based on longlining may be biased, particularly when large aggregations of prey are present such as in convergence zones. Another potential consequence is that longline tuna catch rates could differ according to prey richness. Longline tuna catch rates may sometimes reflect the relative abundance of prey rather than relative tuna abundance. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s00227-001-0776-3.     

Reproductive status and body condition of Atlantic bluefin tuna in the Gulf of Maine, 2000–2002

The reproductive status and body condition of 195 (≥185 cm curved fork length, CFL; assigned age 7 and above) Atlantic bluefin tuna were assessed in the Gulf of Maine during the commercial fishing season of June–October, 2000–2002. Given the distance between known spawning and feeding grounds, the prevailing paradigm for Atlantic bluefin tuna (Thunnus thynnus thynnus, L.) suggests that the most likely histological state for females arriving in the Gulf of Maine after spawning would be a resting or quiescent state with little or no perigonadal fat. Alternatively, the presence of mature or mature-inactive histological states in some females supports a more varied or individualistic model for bluefin reproduction. No relationship was found between body condition and reproductive status. Males were found in all reproductive stages, but were more likely to be in spawning condition (stages 4 and 5) or a mature-inactive state (stage 6) in June and July. Female bluefin tuna were found in stage 1 (immature or non-spawning) and stage 6 (mature-inactive). Stage 6 females were only present in June and July and smaller females (<235 cm CFL) were more likely to be in stage 6 than large females (>235 cm CFL) sampled during those same months. The presence of smaller females in stage 6 arriving at the same time as larger females in stage 1 indicates that Western Atlantic bluefin tuna may have an asynchronous reproductive schedule and may mature at a smaller size than the currently accepted paradigm suggests.     

Comparing interactive and automated mapping systems for supporting fisheries enforcement activities—a case study on vessel monitoring systems (VMS)

The conservation of wild fisheries resources in the face of an ever-increasing world demand for seafood requires the use of a number of management tools, including no-take zones, and gear, species, and temporal restrictions. One way of enforcing some of these regulations is through the use of Vessel Monitoring System (VMS) data that provides enforcement officers with the position of fishing vessels in the management area. The increasing volume of movement data collected using VMS calls for new methods that could help analysts extract useful knowledge from these large data sets. Various approaches have been proposed for visualizing and exploring movement data and detecting patterns within these data, but those approaches have generally not been tested in a real-world context or compared together, making their actual usability and utility unclear. This paper describes, compares, and assesses three such approaches in the context of fisheries enforcement: an existing system used for fisheries enforcement operations in Canada (VUE), a novel Hybrid Spatio-temporal Filtering (HSF) system developed by the authors, and an automated Behavioural Change Point Analysis (BCPA) system. A field trial was conducted with experienced fisheries enforcement officers to compare and contrast the benefits and drawbacks of the three approaches. While all three presented advantages and disadvantages, the interactivity of VUE and HSF were identified as desirable features, as they provide analysts with more control over the data, while allowing flexible data exploration. BCPA, while providing an automated approach to the data analysis, was pointed out as being too much of a “black box”, causing unease among the experts who require a level of transparency similar to that of legally admissible evidence. In the end, the experts suggested that the best approach would be to merge the analytical power of their existing VUE system with the exploratory power of the HSF system. This study provides insight into the value of using interactive mapping and filtering approaches in support of data analysis in the context of fisheries enforcement.     

Trends in the exploitation of South Atlantic shark populations

Approximately 25% of globally reported shark catches occur in Atlantic pelagic longline fisheries. Strong declines in shark populations have been detected in the North Atlantic, whereas in the South Atlantic the situation is less clear, although fishing effort has been increasing in this region since the late 1970s. We synthesized information on shark catch rates (based on 871,177 sharks caught on 86,492 longline sets) for the major species caught by multiple fleets in the South Atlantic between 1979 and 2011. We complied records from fishing logbooks of fishing companies, fishers, and onboard observers that were supplied to Brazilian institutions. By using exploratory data analysis and literature sources, we identified 3 phases of exploitation in these data (Supporting Information). From 1979 to 1997 (phase A), 5 fleets (40 vessels) fished mainly for tunas. From 1998 to 2008 (phase B), 20 fleets (100 vessels) fished for tunas, swordfishes, and sharks. From 2008 to 2011 (phase C), 3 fleets (30 vessels) fished for multiple species, but restrictive measures were implemented. We used generalized linear models to standardize catch rates and identify trends in each of these phases. Shark catch rates increased from 1979 to 1997, when fishing effort was low, decreased from 1998 to 2008, when fishing effort increased substantially, and remained stable or increased from 2008 to 2011, when fishing effort was again low. Our results indicate that most shark populations affected by longlines in the South Atlantic are currently depleted, but these populations may recover if fishing effort is reduced accordingly. In this context, it is problematic that comprehensive data collection, monitoring, and management of these fisheries ceased after 2012. Concurrently with the fact that Brazil is newly identified by FAO among the largest (and in fastest expansion) shark sub‐products consumer market worldwide.     

Trade-Offs in the Design of Fishery Closures: Management of Silky Shark Bycatch in the Eastern Pacific Ocean Tuna Fishery

Abstract:  Bycatch—the incidental catch of nontarget species—is a principal concern in marine conservation and fisheries management. In the eastern Pacific Ocean tuna fishery, a large fraction of nonmammal bycatch is captured by purse-seine gear when nets are deployed around floating objects. We examined the spatial distribution of a dominant species in this fishery's bycatch, the apex predator silky shark ( Carcharhinus falciformis ), from 1994 to 2005 to determine whether spatial closures, areas where fishing is prohibited, might effectively reduce the bycatch of this species. We then identified candidate locations for fishery closures that specifically considered the trade-off between bycatch reduction and the loss of tuna catch and evaluated ancillary conservation benefits to less commonly captured taxa. Smoothed spatial distributions of silky shark bycatch did not indicate persistent small areas of especially high bycatch for any size class of shark over the 12-year period. Nevertheless, bycatch of small silky sharks (<90 cm total length) was consistently higher north of the equator during all years. On the basis of this distribution, we evaluated nearly 100 candidate closure areas between 5°N and 15°N that could have reduced, by as much as 33%, the total silky shark bycatch while compromising only 12% of the tuna catch. Although silky sharks are the predominant species of elasmobranchs caught as bycatch in this fishery, closures also suggested reductions in the bycatch of other vulnerable taxa, including other shark species and turtles. Our technique provides an effective method with which to balance the costs and benefits of conservation in fisheries management. Spatial closures are a viable management tool, but implementation should be preceded by careful consideration of the consequences of fishing reallocation.     

Key Features and Context‐Dependence of Fishery‐Induced Trophic Cascades

Abstract: Trophic cascades triggered by fishing have profound implications for marine ecosystems and the socioeconomic systems that depend on them. With the number of reported cases quickly growing, key features and commonalities have emerged. Fishery‐induced trophic cascades often display differential response times and nonlinear trajectories among trophic levels and can be accompanied by shifts in alternative states. Furthermore, their magnitude appears to be context dependent, varying as a function of species diversity, regional oceanography, local physical disturbance, habitat complexity, and the nature of the fishery itself. To conserve and manage exploited marine ecosystems, there is a pressing need for an improved understanding of the conditions that promote or inhibit the cascading consequences of fishing. Future research should investigate how the trophic effects of fishing interact with other human disturbances, identify strongly interacting species and ecosystem features that confer resilience to exploitation, determine ranges of predator depletion that elicit trophic cascades, pinpoint antecedents that signal ecosystem state shifts, and quantify variation in trophic rates across oceanographic conditions. This information will advance predictive models designed to forecast the trophic effects of fishing and will allow managers to better anticipate and avoid fishery‐induced trophic cascades.     

Depth and muscle temperature of Pacific bluefin tuna examined with acoustic and pop-up satellite archival tags

Six Pacific bluefin tuna were tracked with ultrasonic telemetry and two with pop-up satellite archival tags (PSATs) in the eastern Pacific Ocean in 1997, 1998, and 1999. Both pressure and temperature ultrasonic transmitters were used to examine the behavior of the 2- to 4-year-old bluefin tuna. The bluefin spent over 80% of their time in the top 40 m of the water column and made occasional dives into deeper, cooler water. The mean slow-oxidative muscle temperatures of three fish instrumented with pressure and temperature transmitters were 22.0–26.1 °C in water temperatures that averaged 15.7–17.5 °C. The thermal excesses in slow-oxidative muscle averaged 6.2–8.6 °C. Variation in the temperature of the slow-oxidative muscle in the bluefin was not correlated with water temperature or swimming speeds. For comparison with the acoustic tracking data we examined the depth and ambient temperature of two Pacific bluefin tagged with pop-up satellite archival tags for 24 and 52 days. The PSAT data sets show depth and temperature distributions of the bluefin tuna similar to the acoustic data set. Swimming speeds calculated from horizontal distances with the acoustic data indicate the fish mean speeds were 1.1–1.4 fork lengths/s (FL s⁻¹). These Pacific bluefin spent the majority of their time in the top parts of the water column in the eastern Pacific Ocean in a pattern similar to that observed for yellowfin tuna. Received: 4 April 2000 / Accepted: 25 October 2000     

Horizontal movements and depth distribution of large adult yellowfin tuna (Thunnus albacares) near the Hawaiian Islands, recorded using ultrasonic telemetry: implications for the physiological ecology of pelagic fishes

We measured the horizontal and vertical movements of five adult yellowfin tuna (Thunnus albacares, estimated body mass 64 to 93 kg) near the main Hawaiian Islands, while simultaneously gathering data on oceanographic conditions and currents. Fish movements were recorded by means of ultrasonic depth-sensitive transmitters. Depth–temperature and depth–oxygen profiles were measured with vertical conductivity–temperature–depth (CTD) casts, and the current-velocity field was surveyed using an acoustic Doppler current profiler (ADCP). Large adult yellowfin tuna spent ≃60 to 80% of their time in or immediately below the relatively uniform-temperature surface-layer (i.e. above 100 m), a behavior pattern similar to that previously reported for juvenile yellowfin tuna, blue marlin (Makaira nigricans), and striped marlin (Tetrapturus audax) tracked in the same area. In all three species, maximum swimming depths appear to be limited by water temperatures 8 C° colder than the surface-layer water temperature. Therefore, neither large body mass, nor the ability to maintain elevated swimming-muscle temperatures due to the presence of vascular counter-current heat exchangers in tunas, appears to permit greater vertical mobility or the ability to remain for extended periods below the thermocline. In those areas where the decrease in oxygen with depth is not limiting, the vertical movements of yellowfin tuna, blue marlin and striped marlin all appear to be restricted by the effects of water temperature on cardiac muscle function. Like juvenile yellowfin tuna, but unlike blue marlin and striped marlin, adult yellowfin tuna remained within 18.5 km of the coast and became associated with floating objects, including anchored fish-aggregating devices (FADs) and the tracking vessel. Like juvenile yellowfin tuna, large adult yellowfin repeatedly re-visit the same FAD, and appear able to navigate precisely between FADs that are up to 18 km apart. The median speed over ground ranged from 72 to 154 cm s⁻¹. Neither speed nor direction was strongly influenced by currents. Received: 27 March 1998 / Accepted: 13 November 1998     

Analysis of the eastern Pacific yellowfin tuna fishery based on multiple management objectives

Vector optimization techniques were used to generate arbitrary segments of a policy frontier for a dynamic yellowfin tuna (Thunnus albacares) fishery model assuming fixed technology and considering four policy objectives: minimizing dolphin mortality, minimizing incidental catch (all species except dolphins), maximizing sustainable yield, and minimizing biological risk for the yellowfin tuna stock. Results show that along the policy frontier: (1) reducing incidental dolphin mortality increases the incidental catch of other species in a nonlinear way; (2) yield increases (subject to a biomass precautionary level) can only be obtained at the expense of higher levels of dolphin mortality and incidental catch; (3) biological risk increases as the level of tunas caught increases, but this increase depends on the type of fishery (longline fishing and three different modes of purse-seining: log-sets, dolphin-sets or school-sets) that dominates the fishing effort; (4) there is an indirect relationship between the dolphin mortality levels and those of biological risk; (5) there is a direct relationship between the incidental catch levels and biological risk. Catch obtained with dolphin-sets dominates the Pareto-optimal solutions with highest dolphin mortality levels but is associated with lower biological risk, whereas catch obtained with log-sets dominates in Pareto-optimal solutions with higher incidental catch and higher biological risk. In general, trade-offs or shadow prices among objectives are not linear, indicating that marginal costs vary along the policy frontier. Results of the trade-off analysis may provide useful information for decision-makers and other policy actors. Complete information about the preferences of the decision-makers regarding the objectives is necessary to recommend a specific management policy.     

A rapid ontogenetic shift in the diet of juvenile yellowfin tuna from Hawaii

Within the tropical and subtropical oceans, tuna forage opportunistically on a wide variety of prey. However, little is known about the trophic ecology of the smallest size classes which play an important role in stock assessments and fisheries management. The foraging behavior of yellowfin tuna, Thunnus albacares (23.5–154.0 cm FL), collected from nearshore Fish Aggregating Devices (FADs) around Oahu was studied using stable isotope and stomach contents analyses. Emphasis was placed on small juveniles. Yellowfin tuna changed their diets significantly between 45 and 50 cm forklength (ca. 1.5 kg). Smallest size classes fed on planktonic organisms inhabiting the shallow mixed layer, primarily larval stomatopod and decapod crustaceans, whereas larger tuna fed on teleosts and adult Oplophorus gracilirostris, a vertically migrating mesopelagic species of shrimp. When interpreting the variation in prey δ ¹⁵N values, we considered both their relative trophic position and δ ¹⁵N values of the nitrogen at the base of the food web. Based on the distinct diet shift of the yellowfin tuna, demonstrated by both isotope and stomach content analyses, we propose a critical mass threshold was reached at about 45 cm FL that enabled sufficient endothermic capability to allow tuna to access prey dwelling in deeper, colder water. These ontogenetic changes in foraging range and commensurate shift in diet of small tunas would affect their vulnerability to fishing pressure.     

Use of radar detectors to track attendance of albatrosses at fishing vessels

Despite international waters covering over 60% of the world's oceans, understanding of how fisheries in these regions shape ecosystem processes is surprisingly poor. Seabirds forage at fishing vessels, which has potentially deleterious effects for their population, but the extent of overlap and behavior in relation to ships is poorly known. Using novel biologging devices, which detect radar emissions and record the position of boats and seabirds, we measured the true extent of the overlap between seabirds and fishing vessels and generated estimates of the intensity of fishing and distribution of vessels in international waters. During breeding, wandering albatrosses (Diomedea exulans) from the Crozet Islands patrolled an area of over 10 million km² at distances up to 2500 km from the colony. Up to 79.5% of loggers attached to birds detected vessels. The extent of overlap between albatrosses and fisheries has widespread implications for bycatch risk in seabirds and reveals the areas of intense fishing throughout the ocean. We suggest that seabirds equipped with radar detectors are excellent monitors of the presence of vessels in the Southern Ocean and offer a new way to monitor the presence of illegal fisheries and to better understand the impact of fisheries on seabirds.     

Simulation model of universal law of school size distribution applied to southern bluefin tuna (Thunnus maccoyii) in the Great Australian Bight

A universal law of animal group size distribution correlates well to observed fish school size distribution from fisheries catch data. I applied the law to fisheries independent aerial survey data of southern bluefin tuna (Thunnus maccoyii) collected over a 10-year period in the Great Australian Bight. The law does not correlate to the observed school size distribution. A computer model originally demonstrated the formation of the universal law from simple rules. I redesigned this model as an individual-based simulation model calibrated from acoustic tag observations and state a mathematical formula for a resultant new family of transient group size distributions. The new formula correlates accurately to the simulation and to the aerial survey data. I use the mathematical model to estimate area of aggregation and total abundance. This approach is new as it does not seek stationary states of group size distribution and because it demonstrates a quantitative relationship between individual behaviour and group size distribution. This work elevates the pattern of group size distribution from a curiosity to a useful tool, and introduces a new family of transient distributions that may have a general application to other grouping phenomena.     

Simultaneous behavior of skipjack (Katsuwonus pelamis), bigeye (Thunnus obsesus), and yellowfin (T. albacares) tunas, within large multi-species aggregations associated with drifting fish aggregating devices (FADs) in the equatorial eastern Pacific Ocean

Ten separate experiments monitoring the simultaneous behaviors of 26 skipjack (Katsuwonus pelamis), 26 bigeye (Thunnus obesus), and 33 yellowfin (T. albacares) tunas within large multi-species aggregations associated with drifting fish aggregating devices (FADs) were investigated using ultrasonic telemetry in the equatorial eastern Pacific Ocean. Experiments were conducted during a research cruise aboard a chartered purse seine vessel. Purse seine sets were made on the tuna aggregations associated with FADs at the termination of six of the ten experiments. Seventeen of the 44 tagged tunas were not recaptured indicating the transient nature of the associative behavior of tunas with FADs. Although there was considerable overlap in the depths of the three species, by day and night, there were some species-specific differences and diel differences within species. While we documented spatial and temporal differences in the schooling behavior of the three tuna species, the differences do not appear sufficient such that modifications in purse seine fishing practices could effectively avoid the capture of small bigeye and yellowfin tunas, while optimizing the capture of skipjack tuna in purse seine sets on FADs.     

Time-Dependent Instantaneous Mortality Rates from Multiple Tagging Experiments with Exact Times of Release and Recovery

Instantaneous natural mortality rates and a nonparametric hunting mortality function are estimated from a multiple-year tagging experiment with arbitrary, time-dependent fishing or hunting mortality. Our theory allows animals to be tagged over a range of times in each year, and to take time to mix into the population. Animals are recovered by hunting or fishing, and death events from natural causes occur but are not observed. We combine a long-standing approach based on yearly totals, described by Brownie et al. (1985, Statistical Inference from Band Recovery Data: A Handbook, Second edition, United States Fish and Wildlife Service, Washington, Resource Publication, 156), with an exact-time-of-recovery approach originated by Hearn, Sandland and Hampton (1987, Journal du Conseil International pour l’Exploration de la Mer, 43, 107–117), who modeled times at liberty without regard to time of tagging. Our model allows for exact times of release and recovery, incomplete reporting of recoveries, and potential tag shedding. We apply our methods to data on the heavily exploited southern bluefin tuna (Thunnus maccoyii).     

Behavioural switching in a central place forager: patterns of diving behaviour in the macaroni penguin (Eudyptes chrysolophus)

Recording the activity of animals as they migrate or forage has proven hugely advantageous to understanding how animals use their environment. Where animals cannot be directly observed, the problem remains of how to identify distinct behaviours that represent an animal’s decision-making process. An excellent example of this problem is that of foraging penguins, which travel to sea to find prey to provision their young. Without direct sampling of the prey field, we cannot calibrate patterns of movement with prey capture, and therefore we cannot determine how different activities link to decision-making. To overcome this, we use a hidden markov model (HMM), which is a machine-learning technique that seeks to identify the underlying states of a system from observable outputs. We apply HMM to determine classes of behaviour from repetitive dives. We take dive data from 103 breeding macaroni penguins at Bird Island, South Georgia, for which we have measures of weight gain over a trip. We identify two classes of behaviour; those of short-shallow and long-deep dives. Using these two behaviours, we calculate the transition probabilities between these states and analyse these data to determine what predicts variation in the transition probabilities. We found that the stage of reproduction during a season, the sex and year of an individual influenced the probability of transition between long-deep and short-shallow sequential dives. We also found differences in the hourly transition rates between the four reproductive stages (incubation, broodguard, crèche and premoult) over a daily cycle. We conclude that this application of HMMs for behavioural switching is potentially useful for other species and other types of recorded behaviour.