NOAA National Marine Fisheries Service Alaska Fisheries Science Center

Many of the worlds fish populationsare overexploited, and the ecosystemsthat sustain them are degraded(1). Unintended consequences of fishing, includinghabitat destruction, incidental mortalityof nontarget species, evolutionary shiftsin population demographics, and changes inthe function and structure of ecosystems, arebeing increasingly recognized.Fisheries management to date has oftenbeen ineffective; it focuses on maximizingthe catch of a single target species and oftenignores habitat, predators, and prey ofthe target species and other ecosystemcomponents and interactions. The indirectsocial and economic costs of the focus onsingle species can be substantial. For example,over 90% of the annual mortality ofwhite marlin, a species petitioned for listingunder the U.S. Endangered SpeciesAct, occurs through incidental catch inswordfish and tuna longline fisheries. Thisthreatens a recreational fishing industryworth up to U.S.$2 billion annually (2).To address the critical need for a moreeffective and holistic management approach,a variety of advisory panels (39)have recommended ecosystem considerationsbe considered broadly and consistentlyin managing fisheries. Ecosystem-basedfishery management (EBFM) is a new directionfor fishery management, essentiallyreversing the order of management prioritiesto start with the ecosystem ratherthan the target species.The overall objective of EBFM is tosustain healthy marine ecosystems and thefisheries they support. In particular, EBFMshould (i) avoid degradation of ecosystems,as measured by indicators of environmentalquality and system status; (ii)minimize the risk of irreversible change tonatural assemblages of species and ecosystemprocesses; (iii) obtain and maintainlong-term socioeconomic benefits withoutcompromising the ecosystem; and (iv) generateknowledge of ecosystem processessufficient to understand the likely consequencesof human actions. Where knowledgeis insufficient, robust and precautionaryfishery management measures that favorthe ecosystem should be adopted.We need to derive and develop communityand system-level standards, referencepoints, and control rules analogous to singlespeciesdecision criteria (1012). We maywant to ensure that total biomass removed byall fisheries in an ecosystem does not exceeda total amount of system productivity, afteraccounting for the requirements of otherecosystem components (e.g., nontargetspecies, protected species, habitat considerations,and various trophic interactions).Maintaining system characteristics withincertain bounds may protect ecosystem resilienceand avoid irreversible changes.EBFM must delineate all marine habitatsutilized by humans in the context ofvulnerability to fishing-induced and otherhuman impacts, identify the potential irreversibilityof those impacts, and elucidatehabitats critical to species for vital populationprocesses. Protecting essential habitatfor fish and other important ecosystemcomponents from destructive fishing practicesincreases fish diversity and abundance(13, 14). Thus, ocean zoning, inwhich type and level of allowable humanactivity are specified spatially and temporally,will be a critical element of EBFM.The impacts of fisheries on endangeredand protected species, including ecologicalprocesses that are essential for their recovery,should be managed through an EBFMapproach. Single-species management hasbeen successful at reducing incidentalcatch of protected species in some cases(e.g., with turtle excluder devices intrawls), but EBFM would also manage indirecteffects (e.g., protecting forage fishnear sea lion rookeries).Another goal of EBFM is to reduce excessivelevels of bycatch (i.e., killing ofnontarget species or undersized individualsof the target species), because juvenile lifestages and unmarketable species often playimportant roles in the ecosystem (15, 16).Globally, discards in commercial fisherieshave been estimated at 27.0 million metrictons, accounting for about one-fourth ofthe worlds marine fish catch (17). Bycatchproblems can be ameliorated throughocean zoning that would prohibit use ofnonselective or destructive gear in criticalareas, as well as through the development and deployment of more selective and less damaging fishing technologies.

1.Distance sampling is a widely used technique for estimating the size or density of biological populations. Many distance sampling designs and most analyses use the software Distance.2.We briefly review distance sampling and its assumptions, outline the history, structure and capabilities of Distance, and provide hints on its use.3.Good survey design is a crucial prerequisite for obtaining reliable results. Distance has a survey design engine, with a built-in geographic information system, that allows properties of different proposed designs to be examined via simulation, and survey plans to be generated.4.A first step in analysis of distance sampling data is modelling the probability of detection. Distance contains three increasingly sophisticated analysis engines for this: conventional distance sampling, which models detection probability as a function of distance from the transect and assumes all objects at zero distance are detected; multiple-covariate distance sampling, which allows covariates in addition to distance; and mark-recapture distance sampling, which relaxes the assumption of certain detection at zero distance.5.All three engines allow estimation of density or abundance, stratified if required, with associated measures of precision calculated either analytically or via the bootstrap.6.Advanced analysis topics covered include the use of multipliers to allow analysis of indirect surveys (such as dung or nest surveys), the density surface modelling analysis engine for spatial and habitat modelling, and information about accessing the analysis engines directly from other software.7.Synthesis and applications. Distance sampling is a key method for producing abundance and density estimates in challenging field conditions. The theory underlying the methods continues to expand to cope with realistic estimation situations. In step with theoretical developments, state-of-the-art software that implements these methods is described that makes the methods accessible to practising ecologists.

Many criteria for statistical parameter estimation, such as maximum likelihood, are formulated as a nonlinear optimization problem. Automatic Differentiation Model Builder (ADMB) is a programming framework based on automatic differentiation, aimed at highly nonlinear models with a large number of parameters. The benefits of using AD are computational efficiency and high numerical accuracy, both crucial in many practical problems. We describe the basic components and the underlying philosophy of ADMB, with an emphasis on functionality found in no other statistical software. One example of such a feature is the generic implementation of Laplace approximation of high-dimensional integrals for use in latent variable models. We also review the literature in which ADMB has been used, and discuss future development of ADMB as an open source project. Overall, the main advantages of ADMB are flexibility, speed, precision, stability and built-in methods to quantify uncertainty.

The ecosystem response to the 1989 spill of oil from the Exxon Valdez into Prince William Sound, Alaska, shows that current practices for assessing ecological risks of oil in the oceans and, by extension, other toxic sources should be changed. Previously, it was assumed that impacts to populations derive almost exclusively from acute mortality. However, in the Alaskan coastal ecosystem, unexpected persistence of toxic subsurface oil and chronic exposures, even at sublethal levels, have continued to affect wildlife. Delayed population reductions and cascades of indirect effects postponed recovery. Development of ecosystem-based toxicology is required to understand and ultimately predict chronic, delayed, and indirect long-term risks and impacts.

Quasi-Poisson and negative binomial regression models have equal numbers of parameters, and either could be used for overdispersed count data. While they often give similar results, there can be striking differences in estimating the effects of covariates. We explain when and why such differences occur. The variance of a quasi-Poisson model is a linear function of the mean while the variance of a negative binomial model is a quadratic function of the mean. These variance relationships affect the weights in the iteratively weighted least-squares algorithm of fitting models to data. Because the variance is a function of the mean, large and small counts get weighted differently in quasi-Poisson and negative binomial regression. We provide an example using harbor seal counts from aerial surveys. These counts are affected by date, time of day, and time relative to low tide. We present results on a data set that showed a dramatic difference on estimating abundance of harbor seals when using quasi-Poisson vs. negative binomial regression. This difference is described and explained in light of the different weighting used in each regression method. A general understanding of weighting can help ecologists choose between these two methods.

Until recently, northern Bering Sea ecosystems were characterized by extensive seasonal sea ice cover, high water column and sediment carbon production, and tight pelagic-benthic coupling of organic production. Here, we show that these ecosystems are shifting away from these characteristics. Changes in biological communities are contemporaneous with shifts in regional atmospheric and hydrographic forcing. In the past decade, geographic displacement of marine mammal population distributions has coincided with a reduction of benthic prey populations, an increase in pelagic fish, a reduction in sea ice, and an increase in air and ocean temperatures. These changes now observed on the shallow shelf of the northern Bering Sea should be expected to affect a much broader portion of the Pacific-influenced sector of the Arctic Ocean.

We propose a continuous-time version of the correlated random walk model for animal telemetry data. The continuous-time formulation allows data that have been nonuniformly collected over time to be modeled without subsampling, interpolation, or aggregation to obtain a set of locations uniformly spaced in time. The model is derived from a continuous-time Ornstein-Uhlenbeck velocity process that is integrated to form a location process. The continuous-time model was placed into a state-space framework to allow parameter estimation and location predictions from observed animal locations. Two previously unpublished marine mammal telemetry data sets were analyzed to illustrate use of the model, by-products available from the analysis, and different modifications which are possible. A harbor seal data set was analyzed with a model that incorporates the proportion of each hour spent on land. Also, a northern fur seal pup data set was analyzed with a random drift component to account for directed travel and ocean currents.

A bstract A simulation method was developed for identifying populations with levels of human‐caused mortality that could lead to depletion, taking into account the uncertainty of available information. A mortality limit (termed the Potential Biological Removal, PBR , under the U. S. Marine Mammal Protection Act) was calculated as the product of a minimum population estimate ( N MIN ), one‐half of the maximum net productivity rate ( R MAX ), and a recovery factor ( F R ). Mortality limits were evaluated based on whether at least 95% of the simulated populations met two criteria: (1) that populations starting at the maximum net productivity level ( MNPL ) stayed there or above after 20 yr, and (2) that populations starting at 30% of carrying‐capacity ( K ) recovered to at least MNPL after 100 yr. Simulations of populations that experienced mortality equal to the PBR indicated that using approximately the 20th percentile (the lower 60% log‐normal confidence limit) of the abundance estimate for N MIN met the criteria for both cetaceans (assuming R MAX = 0.04) and pinnipeds (assuming R MAX = 0.12). Additional simulations that included plausible levels of bias in the available information indicated that using a value of 0.5 for F R would meet both criteria during these “bias trials.” It is concluded that any marine mammal population with an estimate of human‐caused mortality that is greater than its PBR has a level of mortality that could lead to the depletion of the population. The simulation methods were also used to show how mortality limits could be calculated to meet conservation goals other than the U. S. goal of maintaining populations above MNPL .

Baleen whales (Mysticeti) communicate using low-frequency acoustic signals. These long-wavelength sounds can be detected over hundreds of kilometres, potentially allowing contact over large distances. Low-frequency noise from large ships (20-200 Hz) overlaps acoustic signals used by baleen whales, and increased levels of underwater noise have been documented in areas with high shipping traffic. Reported responses of whales to increased noise include: habitat displacement, behavioural changes and alterations in the intensity, frequency and intervals of calls. However, it has been unclear whether exposure to noise results in physiological responses that may lead to significant consequences for individuals or populations. Here, we show that reduced ship traffic in the Bay of Fundy, Canada, following the events of 11 September 2001, resulted in a 6 dB decrease in underwater noise with a significant reduction below 150 Hz. This noise reduction was associated with decreased baseline levels of stress-related faecal hormone metabolites (glucocorticoids) in North Atlantic right whales (Eubalaena glacialis). This is the first evidence that exposure to low-frequency ship noise may be associated with chronic stress in whales, and has implications for all baleen whales in heavy ship traffic areas, and for recovery of this endangered right whale population.

Accounting for a warming ocean Fisheries provide food and support livelihoods across the world. They are also under extreme pressure, with many stocks overfished and poorly managed. Climate change will add to the burden fish stocks bear, but such impacts remain largely unknown. Free et al. used temperature-specific models and hindcasting across fish stocks to determine the degree to which warming has, and will, affect fish species (see the Perspective by Plagányi). They found that an overall reduction in yield has occurred over the past 80 years. Furthermore, although some species are predicted to respond positively to warming waters, the majority will experience a negative impact on growth. As our world warms, responsible and active management of fisheries harvests will become even more important. Science , this issue p. 979 ; see also p. 930

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 189:117-123 (1999) - doi:10.3354/meps189117 Community reorganization in the Gulf of Alaska following ocean climate regime shift Paul J. Anderson1,*, John F. Piatt2 1National Marine Fisheries Service, Alaska Fisheries Science Center, 301 Research Court, Kodiak, Alaska 99615, USA 2U.S. Geological Survey, Alaska Biological Research Center, 1011 E. Tudor Rd., Anchorage, Alaska 99503, USA *E-mail: paul.j.anderson@noaa.gov ABSTRACT: A shift in ocean climate during the late 1970s triggered a reorganization of community structure in the Gulf of Alaska ecosystem, as evidenced in changing catch composition on long-term (1953 to 1997) small-mesh trawl surveys. Forage species such as pandalid shrimp and capelin declined because of recruitment failure and predation, and populations have not yet recovered. Total trawl catch biomass declined >50% and remained low through the 1980s. In contrast, recruitment of high trophic-level groundfish improved during the 1980s, yielding a >250% increase in catch biomass during the 1990s. This trophic reorganization apparently had negative effects on piscivorous sea birds and marine mammals. KEY WORDS: Shrimp · Capelin · Forage fish · Gulf of Alaska · Groundfish · Climate change Full text in pdf format PreviousNextExport citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 189. Publication date: November 26, 1999 Print ISSN:0171-8630; Online ISSN:1616-1599 Copyright © 1999 Inter-Research.

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

Substantial changes in population size, age structure, and urbanization are expected in many parts of the world this century. Although such changes can affect energy use and greenhouse gas emissions, emissions scenario analyses have either left them out or treated them in a fragmentary or overly simplified manner. We carry out a comprehensive assessment of the implications of demographic change for global emissions of carbon dioxide. Using an energy-economic growth model that accounts for a range of demographic dynamics, we show that slowing population growth could provide 16-29% of the emissions reductions suggested to be necessary by 2050 to avoid dangerous climate change. We also find that aging and urbanization can substantially influence emissions in particular world regions.

Winter mortality has been documented in a large number of freshwater fish populations, and a smaller, but increasing, number of marine and estuarine fishes. The impacted populations include a number of important North American and European resource species, yet the sources of winter mortality remain unidentified in most populations where it has been documented. Among the potential sources, thermal stress and starvation have received the most research attention. Other sources including predation and pathogens have significant impacts but have received insufficient attention to date. Designs of more recent laboratory experiments have reflected recognition of the potential for interactions among these co‐occurring stressors. Geographic patterns in winter mortality are, in some cases, linked to latitudinal clines in winter severity and variability. However, for many freshwater species in particular, the effects of local community structure (predators and prey) may overwhelm latitudinal patterns. Marine (and estuarine) systems differ from freshwater systems in several aspects important to overwintering fishes, the most important being the lack of isolating barriers in the ocean. While open population boundaries allow fish to adopt migration strategies minimizing exposure to thermal stresses, they may retard rates of evolution to local environments. Geographic patterns in the occurrence and causes of winter mortality are ultimately determined by the interaction of regional and local factors. Winter mortality impacts population dynamics through episodic depressions in stock size and regulation of annual cohort strength. While the former tends to act in a density‐independent manner, the latter can be density dependent, as most sources of mortality tend to select against the smallest members of the cohort and population. Most stock assessment and management regimes have yet to explicitly incorporate the variability in winter mortality. Potential management responses include postponement of cohort evaluation (to after first winter of life), harvest restrictions following mortality events and habitat enhancement. Future research should place more emphasis on the ecological aspects of winter mortality including the influences of food‐web structure on starvation and predation. Beyond illuminating an understudied life‐history phase, studies of overwintering ecology are integral to contemporary issues in fisheries ecology including ecosystem management, habitat evaluation, and impacts of climate change.

Seasonal ice cover creates a pool of cold bottom water on the eastern Bering Sea continental shelf each winter. The southern edge of this cold pool, which defines the ecotone between arctic and subarctic communities, has retreated approximately 230 km northward since the early 1980s. Bottom trawl surveys of fish and invertebrates in the southeastern Bering Sea (1982-2006) show a coincident reorganization in community composition by latitude. Survey catches show community-wide northward distribution shifts, and the area formerly covered by the cold pool has seen increases in total biomass, species richness, and average trophic level as subarctic fauna have colonized newly favorable habitats. Warming climate has immediate management implications, as 57% of variability in commercial snow crab (Chionoecetes opilio) catch is explained by winter sea ice extent. Several measures of community distribution and structure show linear relationships with bottom temperature, suggesting warming climate as the primary cause of changing biogeography. However, residual variability in distribution not explained by climate shows a strong temporal trend, suggesting that internal community dynamics also contribute to changing biogeography. Variability among taxa in their response to temperature was not explained by commercial status or life history traits, suggesting that species-specific responses to future warming will be difficult to predict.

Evolutionary selection has refined the life histories of seven species (three cetacean [narwhal, beluga, and bowhead whales], three pinniped [walrus, ringed, and bearded seals], and the polar bear) to spatial and temporal domains influenced by the seasonal extremes and variability of sea ice, temperature, and day length that define the Arctic. Recent changes in Arctic climate may challenge the adaptive capability of these species. Nine other species (five cetacean [fin, humpback, minke, gray, and killer whales] and four pinniped [harp, hooded, ribbon, and spotted seals]) seasonally occupy Arctic and subarctic habitats and may be poised to encroach into more northern latitudes and to remain there longer, thereby competing with extant Arctic species. A synthesis of the impacts of climate change on all these species hinges on sea ice, in its role as: (1) platform, (2) marine ecosystem foundation, and (3) barrier to non-ice-adapted marine mammals and human commercial activities. Therefore, impacts are categorized for: (1) ice-obligate species that rely on sea ice platforms, (2) ice-associated species that are adapted to sea ice-dominated ecosystems, and (3) seasonally migrant species for which sea ice can act as a barrier. An assessment of resilience is far more speculative, as any number of scenarios can be envisioned, most of them involving potential trophic cascades and anticipated human perturbations. Here we provide resilience scenarios for the three ice-related species categories relative to four regions defined by projections of sea ice reductions by 2050 and extant shelf oceanography. These resilience scenarios suggest that: (1) some populations of ice-obligate marine mammals will survive in two regions with sea ice refugia, while other stocks may adapt to ice-free coastal habitats, (2) ice-associated species may find suitable feeding opportunities within the two regions with sea ice refugia and, if capable of shifting among available prey, may benefit from extended foraging periods in formerly ice-covered seas, but (3) they may face increasing competition from seasonally migrant species, which will likely infiltrate Arctic habitats. The means to track and assess Arctic ecosystem change using sentinel marine mammal species are suggested to offer a framework for scientific investigation and responsible resource management.

Abstract Pacific herring eggs were exposed for 16 d to weathered Alaska North Slope crude oil. Exposure to an initial aqueous concentration of 0.7 parts per billion (ppb) polynuclear aromatic hydrocarbons (PAHs) caused malformations, genetic damage, mortality, and decreased size and inhibited swimming. Total aqueous PAH concentrations as low as 0.4 ppb caused sublethal responses such as yolk sac edema and immaturity consistent with premature hatching. Responses to less weathered oil, which had relatively lower proportions of high molecular weight PAH, generally paralleled those of more weathered oil, but lowest observed effective concentrations (LOECs) were higher (9.1 ppb), demonstrating the importance of composition. The LOEC for more weathered oil (0.4 ppb) was similar to that observed in pink salmon (1.0 ppb), a species with a very different development rate; by inference, other species may be similarly sensitive to weathered oil. Our methods simulated conditions observed in Prince William Sound (PWS) following the Exxon Valdez oil (EVO) spill. Biological effects were identical to those observed in embryolarval herring from PWS in 1989 and support the conclusion that EVO caused significant damage to herring in PWS. Previous demonstration by our laboratory that most malformed or precocious larvae die corroborates the decreased larval production measured after the spill.

A major reorganization of the North‐east Pacific biota transpired following a climatic `regime shift' in the mid 1970s. In this paper, we characterize the effects of interdecadal climate forcing on the oceanic ecosystems of the NE Pacific Ocean. We consider the concept of scale in terms of both time and space within the North Pacific ecosystem and develop a conceptual model to illustrate how climate variability is linked to ecosystem change. Next we describe a number of recent studies relating climate to marine ecosystem dynamics in the NE Pacific Ocean. These studies have focused on most major components of marine ecosystems – primary and secondary producers, forage species, and several levels of predators. They have been undertaken at different time and space scales. However, taken together, they reveal a more coherent picture of how decadal‐scale climate forcing may affect the large oceanic ecosystems of the NE Pacific. Finally, we synthesize the insight gained from interpreting these studies. Several general conclusions can be drawn. 1 There are large‐scale, low‐frequency, and sometimes very rapid changes in the distribution of atmospheric pressure over the North Pacific which are, in turn, reflected in ocean properties and circulation. 2 Oceanic ecosystems respond on similar time and space scales to variations in physical conditions. 3 Linkages between the atmosphere/ocean physics and biological responses are often different across time and space scales. 4 While the cases presented here demonstrate oceanic ecosystem response to climate forcing, they provide only hints of the mechanisms of interaction. 5 A model whereby ecosystem response to specified climate variation can be successfully predicted will be difficult to achieve because of scale mismatches and nonlinearities in the atmosphere–ocean–biosphere system.

Killer whales ( Orcinus orca ) currently comprise a single, cosmopolitan species with a diverse diet. However, studies over the last 30 yr have revealed populations of sympatric “ecotypes” with discrete prey preferences, morphology, and behaviors. Although these ecotypes avoid social interactions and are not known to interbreed, genetic studies to date have found extremely low levels of diversity in the mitochondrial control region, and few clear phylogeographic patterns worldwide. This low level of diversity is likely due to low mitochondrial mutation rates that are common to cetaceans. Using killer whales as a case study, we have developed a method to readily sequence, assemble, and analyze complete mitochondrial genomes from large numbers of samples to more accurately assess phylogeography and estimate divergence times. This represents an important tool for wildlife management, not only for killer whales but for many marine taxa. We used high-throughput sequencing to survey whole mitochondrial genome variation of 139 samples from the North Pacific, North Atlantic, and southern oceans. Phylogenetic analysis indicated that each of the known ecotypes represents a strongly supported clade with divergence times ranging from ∼150,000 to 700,000 yr ago. We recommend that three named ecotypes be elevated to full species, and that the remaining types be recognized as subspecies pending additional data. Establishing appropriate taxonomic designations will greatly aid in understanding the ecological impacts and conservation needs of these important marine predators. We predict that phylogeographic mitogenomics will become an important tool for improved statistical phylogeography and more precise estimates of divergence times.

This review considers the effect of anthropogenic sound on beaked whales2. Two major conclusions are presented: (1) gas-bubble disease, induced in supersaturated tissue by a behavioural response to acoustic exposure, is a plausible pathologic mechanism for the morbidity and mortality seen in cetaceans associated with sonar exposure and merits further investigation; and (2) current monitoring and mitigation methods for beaked whales are ineffective for detecting these animals and protecting them from adverse sound exposure. In addition, four major research priorities, needed to address information gaps on the impacts of sound on beaked whales, are identified: (1) controlled exposure experiments to assess beaked whale responses to known sound stimuli; (2) investigation of physiology, anatomy, pathobiology and behaviour of beaked whales; (3) assessment of baseline diving behaviour and physiology of beaked whales; and (4) a retrospective review of beaked whale strandings.