Revisiting the vulnerability of juvenile bigeye (Thunnus obesus) and yellowfin (T. albacares) tuna caught by purse-seine fisheries while associating with surface waters and floating objects.

Tuna fisheries catch over three million tonnes of skipjack tuna (Katsuwonus pelamis) each year, the majority of which come from purse-seine vessels targeting fish associated with man-made fish aggregating devices (FADs). A significant challenge for fisheries management is to maximize the efficiency of skipjack tuna catches whilst minimizing the bycatch of small and immature bigeye (Thunnus obesus) and yellowfin (T. albacares) tuna, for which long-term sustainability is uncertain in 75% of the world's stocks. To better manage the issues common with this fishing method, an improved understanding of tuna behaviour around FADs is necessary. We probabilistically classified the vertical behavioural patterns of 50 bigeye and 35 yellowfin tuna (mean fork length 72cm and 70cm, respectively) electronically tagged throughout the western and central Pacific Ocean into shallow and deep states, using a state-space modelling approach. The occurrence of surface-association behaviours, defined as an individual remaining in a shallow state for 24-hours, was examined in relation to known capture events and FAD density. In general, surface-association events for both species were short and lasted on average less than three days, although events as long as 28 days were observed, and were more common in yellowfin when in archipelagic waters. Events were longest immediately following tagging in 62% and 17% of bigeye and yellowfin, respectively. Surface-association behaviour was not generally estimated just prior to recapture, being either non-existent or shorter than two days for 85% of bigeye and 74% of yellowfin. Current management measures in purse-seine tuna fisheries involve periodic or spatial closures for FAD use. If the chief benefit to purse-seine fishers of surface-association around floating objects is in locating schools in horizontal space at short-term time-scales, rather than holding fish near the surface for extended periods, controlling the number of sets made on FADs should be explored further as an additional management tool.

Valuing biodiversity and ecosystem services: a useful way to manage and conserve marine resources?

Valuation of biodiversity and ecosystem services (ES) is widely recognized as a useful, though often controversial, approach to conservation and management. However, its use in the marine environment, hence evidence of its efficacy, lags behind that in terrestrial ecosystems. This largely reflects key challenges to marine conservation and management such as the practical difficulties in studying the ocean, complex governance issues and the historically-rooted separation of biodiversity conservation and resource management. Given these challenges together with the accelerating loss of marine biodiversity (and threats to the ES that this biodiversity supports), we ask whether valuation efforts for marine ecosystems are appropriate and effective. We compare three contrasting systems: the tropical Pacific, Southern Ocean and UK coastal seas. In doing so, we reveal a diversity in valuation approaches with different rates of progress and success. We also find a tendency to focus on specific ES (often the harvested species) rather than biodiversity. In light of our findings, we present a new conceptual view of valuation that should ideally be considered in decision-making. Accounting for the critical relationships between biodiversity and ES, together with an understanding of ecosystem structure and functioning, will enable the wider implications of marine conservation and management decisions to be evaluated. We recommend embedding valuation within existing management structures, rather than treating it as an alternative or additional mechanism. However, we caution that its uptake and efficacy will be compromised without the ability to develop and share best practice across regions.

Objective classification of latent behavioral states in bio-logging data using multivariate-normal hidden Markov models.

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.

The Gulf: a young sea in decline.

This review examines the substantial changes that have taken place in marine habitats and resources of the Gulf over the past decade. The habitats are especially interesting because of the naturally high levels of temperature and salinity stress they experience, which is important in a changing world climate. However, the extent of all natural habitats is changing and their condition deteriorating because of the rapid development of the region and, in some cases from severe, episodic warming episodes. Major impacts come from numerous industrial, infrastructure-based, and residential and tourism development activities, which together combine, synergistically in some cases, to cause the observed deterioration in most benthic habitats. Substantial sea bottom dredging for material and its deposition in shallow water to extend land or to form a basis for huge developments, directly removes large areas of shallow, productive habitat, though in some cases the most important effect is the accompanying sedimentation or changes to water flows and conditions. The large scale of the activities compared to the relatively shallow and small size of the water body is a particularly important issue. Important from the perspective of controlling damaging effects is the limited cross-border collaboration and even intra-country collaboration among government agencies and large projects. Along with the accumulative nature of impacts that occur, even where each project receives environmental assessment or attention, each is treated more or less alone, rarely in combination. However, their combination in such a small, biologically interacting sea exacerbates the overall deterioration. Very few similar areas exist which face such a high concentration of disturbance, and the prognosis for the Gulf continuing to provide abundant natural resources is poor.

Current and future sustainability of island coral reef fisheries.

Overexploitation is one of the principal threats to coral reef diversity, structure, function, and resilience [1, 2]. Although it is generally held that coral reef fisheries are unsustainable [3-5], little is known of the overall scale of exploitation or which reefs are overfished [6]. Here, on the basis of ecological footprints and a review of exploitation status [7, 8], we report widespread unsustainability of island coral reef fisheries. Over half (55%) of the 49 island countries considered are exploiting their coral reef fisheries in an unsustainable way. We estimate that total landings of coral reef fisheries are currently 64% higher than can be sustained. Consequently, the area of coral reef appropriated by fisheries exceeds the available effective area by approximately 75,000 km(2), or 3.7 times the area of Australia's Great Barrier Reef, and an extra 196,000 km(2) of coral reef may be required by 2050 to support the anticipated growth in human populations. The large overall imbalance between current and sustainable catches implies that management methods to reduce social and economic dependence on reef fisheries are essential to prevent the collapse of coral reef ecosystems while sustaining the well-being of burgeoning coastal populations.