-In the Western and Central Pacific Ocean (WCPO), which accounts for over half of world tuna production, purse seine effort and catch on floating objects have increased significantly due to a rapid increase in the use of fixed and free-floating fish aggregation devices (FADs). FAD fishing has had an impact on the current status of the stocks of the three main target tunas in the equatorial WCPO, skipjack (Katsuwonus pelamis), yellowfin (Thunnus albacares) and bigeye (T. obesus). FADs have been shown to influence the behaviour and movement patterns of the three tuna species with the juveniles of each species occupying shallower habitats when associated with FADs. Aggregation of tunas around drifting objects increases their vulnerability to purse seine gear, particularly for juvenile and small size classes. Further to the impacts on the target stocks, the use of FADs has increased the vulnerability of other fishes to the purse seine method, including some shark and billfish species. Given the concern over FAD-related fishing effort on target and bycatch species, there is a need to understand how FAD use affects target and bycatch stocks. Science needs to better support management decisions are highlighted including the need to identify the magnitude of broader community-level affects.

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Foraging with tuna is a well-documented seabird strategy, referred to as facilitated foraging. However, despite this behaviour being considered almost obligatory in nutrient-poor tropical waters, little data exist on its relative importance to individual colonies. Therefore, to examine facilitated foraging under different patterns of nutrient availability, we tracked wedgetailed shearwaters Ardenna pacifica from 2 colonies, one tropical and one subtropical, situated in waters of contrasting productivity. Shearwater foraging behaviour was assessed relative to oceanographic covariates and predicted distributions for multiple tropical tuna species and ageclasses, simulated by an existing ecosystem model (SEAPODYM). Shearwaters from both colonies undertook long trips to deep, pelagic waters close to seamounts and foraged most often at fronts and eddies. Micronektonic and adult tuna age classes were highly correlated in space. Predation between these tuna age classes represents a likely source of facilitated foraging opportunities for shearwaters. At broad spatial scales, shearwaters consistently foraged in areas with higher predicted adult skipjack and micronektonic tuna densities and avoided adult bigeye tuna. At finer spatial scales, dynamic ocean features aggregated tuna of all sizes. Enhanced tuna density at these locations increased the likelihood of shearwater foraging activity. Long trips in the tropics targeted oligotrophic waters with higher tuna densities. Long trips in the subtropics targeted enhanced productivity, but in some years shifted to target the same oligotrophic, tuna-dense waters used by tropical conspecifics. We conclude that facilitated foraging with tuna is consistently important to the tropical breeding population and becomes increasingly important to the subtropical population in years of low marine productivity.

Abstract. Analysis of complex time-series data from ecological system study requires quantitative tools for objective description and classification. These tools must take into account largely ignored problems of bias in manual classification, autocorrelation, and noise. Here we describe a method using existing estimation techniques for multivariate-normal hidden Markov models (HMMs) to develop such a classification. We use high-resolution behavioral data from bio-loggers attached to free-roaming pelagic tuna as an example. Observed patterns are assumed to be generated by an unseen Markov process that switches between several multivariate-normal distributions.Our approach is assessed in two parts. The first uses simulation experiments, from which the ability of the HMM to estimate known parameter values is examined using artificial time series of data consistent with hypotheses about pelagic predator foraging ecology. The second is the application to time series of continuous vertical movement data from yellowfin and bigeye tuna taken from tuna tagging experiments. These data were compressed into summary metrics capturing the variation of patterns in diving behavior and formed into a multivariate time series used to estimate a HMM. Each observation was associated with covariate information incorporating the effect of day and night on behavioral switching.Known parameter values were well recovered by the HMMs in our simulation experiments, resulting in mean correct classification rates of 90-97%, although some variance-covariance parameters were estimated less accurately. HMMs with two distinct behavioral states were selected for every time series of real tuna data, predicting a shallow warm state, which was similar across all individuals, and a deep colder state, which was more variable. Marked diurnal behavioral switching was predicted, consistent with many previous empirical studies on tuna.HMMs provide easily interpretable models for the objective classification of many different types of noisy autocorrelated data, as typically found across a range of ecological systems. Summarizing time-series data into a multivariate assemblage of dimensions relevant to the desired classification provides a means to examine these data in an appropriate behavioral space. We discuss how outputs of these models can be applied to bio-logging and other imperfect behavioral data, providing easily interpretable models for hypothesis testing.