Remotely sensed tracking data collected on animal movement is vastly underutilized due to a lack of statistical tools for appropriate analysis. Features of such data that make analysis particularly challenging include the presence of estimation errors that are non-Gaussian and vary in time, observations that occur irregularly in time, and complexity in the underlying behavioral processes. We develop a state-space framework that simultaneously deals with these features and demonstrate our method by analyzing three seal pathway data sets. We show how known information regarding error distributions can be used to improve inference of the underlying process(es) and demonstrate that our framework provides a powerful and flexible method for fitting different behavioral models to tracking data.

BACKGROUND:Global aquatic environments are changing profoundly as a result of human actions; consequently, so too are the ways in which organisms are distributing themselves through space and time. Our ability to predict organism and community responses to these alterations will be dependent on knowledge of animal movements, interactions, and how the physiological and environmental processes underlying them shape species distributions. These patterns and processes ultimately structure aquatic ecosystems and provide the wealth of ecosystem services upon which humans depend. Until recently, the vast size, opacity, and dynamic nature of the aquatic realm have impeded our efforts to understand these ecosystems. With rapid technological advancement over the past several decades, a suite of electronic tracking devices (e.g., acoustic and satellite transmitters) that can remotely monitor animals in these challenging environments are now available. Aquatic telemetry technology is rapidly accelerating our ability to observe animal behavior and distribution and, as a consequence, is fundamentally altering our understanding of the structure and function of global aquatic ecosystems. These advances provide the toolbox to define how future global aquatic management practices must evolve.

The study of animal movement and behavior is being revolutionized by technology, such as satellite tags and harmonic radar, that allows us to track the movements of individual animals. However, our ability to analyze and model such data has lagged behind the sophisticated collection methods. We review problems with current methods and suggest a more powerful and flexible approach, state‐space modeling, and we illustrate how these models can be posed in a meta‐analytic framework so that information from individual trajectories may be combined optimally. State‐space models enable us to deal with the complexity of modeling animals interacting with their environment but, unlike other methods, they allow simultaneous estimation of measurement error and process noise that are inherent in animal‐trajectory data. A Bayesian framework allows us to incorporate important prior information when available and also allows meta‐analytic techniques to be incorporated in a straightforward fashion. Meta‐analysis enables both individual and broader‐level inference from observations of multiple individual pathways. Our approach is powerful because it allows researchers to test hypotheses regarding animal movement, to connect theoretical models to data, and to use modern likelihood‐based estimation techniques, all under a single statistical framework.

Introduction 318Methods 321Catch data sources 321Typical trajectory of sea cucumber fisheries 321Drivers of sea cucumber fisheries 322Rate of development 324Distance from Asia 324 Sensitivity analyses 325 AbstractIn recent decades, invertebrate fisheries have expanded in catch and value worldwide. One increasingly harvested group is sea cucumbers (class Holothuroidea), which are highly valued in Asia and sold as trepang or bêche-de-mer. We compiled global landings, economic data, and country-specific assessment and management reports to synthesize global trends in sea cucumber fisheries, evaluate potential drivers, and test for local and global serial exploitation patterns. Although some sea cucumber fisheries have existed for centuries, catch trends of most individual fisheries followed boom-and-bust patterns since the 1950s, declining nearly as quickly as they expanded. New fisheries expanded five to six times faster in 1990 compared to 1960 and at an increasing distance from Asia, encompassing a global fishery by the 1990s. Global sea cucumber production was correlated to the Japanese yen at a leading lag. Regional assessments revealed that population declines from overfishing occurred in 81% of sea cucumber fisheries, average harvested body size declined in 35%, harvesters moved from near-to off-shore regions in 51% and from high-to low-value species in 76%. Thirty-eight per cent of sea cucumber fisheries remained unregulated, and illegal catches were of concern in half. Our results suggest that development patterns of sea cucumber fisheries are largely predictable, often unsustainable and frequently too rapid for effective management responses. We discuss potential ecosystem and human community consequences and urge for better monitoring and reporting of catch and abundance, proper scientific stock assessment and consideration of international trade regulations to ensure long-term and sustainable harvesting of sea cucumbers worldwide.

Marine mammals have greatly benefitted from a shift from resource exploitation towards conservation. Often lauded as symbols of conservation success, some marine mammal populations have shown remarkable recoveries after severe depletions. Others have remained at low abundance levels, continued to decline, or become extinct or extirpated. Here we provide a quantitative assessment of (1) publicly available population-level abundance data for marine mammals worldwide, (2) abundance trends and recovery status, and (3) historic population decline and recent recovery. We compiled 182 population abundance time series for 47 species and identified major data gaps. In order to compare across the largest possible set of time series with varying data quality, quantity and frequency, we considered an increase in population abundance as evidence of recovery. Using robust log-linear regression over three generations, we were able to classify abundance trends for 92 spatially non-overlapping populations as Significantly Increasing (42%), Significantly Decreasing (10%), Non-Significant Change (28%) and Unknown (20%). Our results were comparable to IUCN classifications for equivalent species. Among different groupings, pinnipeds and other marine mammals (sirenians, polar bears and otters) showed the highest proportion of recovering populations, likely benefiting from relatively fast life histories and nearshore habitats that provided visibility and protective management measures. Recovery was less frequent among cetaceans, but more common in coastal than offshore populations. For marine mammals with available historical abundance estimates (n = 47), larger historical population declines were associated with low or variable recent recoveries so far. Overall, our results show that many formerly depleted marine mammal populations are recovering. However, data-deficient populations and those with decreasing and non-significant trends require attention. In particular, increased study of populations with major data gaps, including offshore small cetaceans, cryptic species, and marine mammals in low latitudes and developing nations, is needed to better understand the status of marine mammal populations worldwide.

BackgroundWorldwide, finfish fisheries are receiving increasing assessment and regulation, slowly leading to more sustainable exploitation and rebuilding. In their wake, invertebrate fisheries are rapidly expanding with little scientific scrutiny despite increasing socio-economic importance.Methods and FindingsWe provide the first global evaluation of the trends, drivers, and population and ecosystem consequences of invertebrate fisheries based on a global catch database in combination with taxa-specific reviews. We also develop new methodologies to quantify temporal and spatial trends in resource status and fishery development. Since 1950, global invertebrate catches have increased 6-fold with 1.5 times more countries fishing and double the taxa reported. By 2004, 34% of invertebrate fisheries were over-exploited, collapsed, or closed. New fisheries have developed increasingly rapidly, with a decrease of 6 years (3 years) in time to peak from the 1950s to 1990s. Moreover, some fisheries have expanded further and further away from their driving market, encompassing a global fishery by the 1990s. 71% of taxa (53% of catches) are harvested with habitat-destructive gear, and many provide important ecosystem functions including habitat, filtration, and grazing.ConclusionsOur findings suggest that invertebrate species, which form an important component of the basis of marine food webs, are increasingly exploited with limited stock and ecosystem-impact assessments, and enhanced management attention is needed to avoid negative consequences for ocean ecosystems and human well-being.

BackgroundIncreasingly, underwater visual censuses (UVC) are used to assess fish populations. Several studies have demonstrated the effectiveness of protected areas for increasing fish abundance or provided insight into the natural abundance and structure of reef fish communities in remote areas. Recently, high apex predator densities (>100,000 individuals·km−2) and biomasses (>4 tonnes·ha−1) have been reported for some remote islands suggesting the occurrence of inverted trophic biomass pyramids. However, few studies have critically evaluated the methods used for sampling conspicuous and highly mobile fish such as sharks. Ideally, UVC are done instantaneously, however, researchers often count animals that enter the survey area after the survey has started, thus performing non-instantaneous UVC.Methodology/Principal FindingsWe developed a simulation model to evaluate counts obtained by divers deploying non-instantaneous belt-transect and stationary-point-count techniques. We assessed how fish speed and survey procedure (visibility, diver speed, survey time and dimensions) affect observed fish counts. Results indicate that the bias caused by fish speed alone is huge, while survey procedures had varying effects. Because the fastest fishes tend to be the largest, the bias would have significant implications on their biomass contribution. Therefore, caution is needed when describing abundance, biomass, and community structure based on non-instantaneous UVC, especially for highly mobile species such as sharks.Conclusions/SignificanceBased on our results, we urge that published literature state explicitly whether instantaneous counts were made and that survey procedures be accounted for when non-instantaneous counts are used. Using published density and biomass values of communities that include sharks we explore the effect of this bias and suggest that further investigation may be needed to determine pristine shark abundances and the existence of inverted biomass pyramids. Because such studies are used to make important management and conservation decisions, incorrect estimates of animal abundance and biomass have serious and significant implications.

State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results.