NOAA National Marine Fisheries Service

Research that combines all available studies of biological responses to regional and global climate change shows that 81–83% of all observations were consistent with the expected impacts of climate change. These findings were replicated across taxa and oceanic basins. Past meta-analyses of the response of marine organisms to climate change have examined a limited range of locations1,2, taxonomic groups2,3,4 and/or biological responses5,6. This has precluded a robust overview of the effect of climate change in the global ocean. Here, we synthesized all available studies of the consistency of marine ecological observations with expectations under climate change. This yielded a meta-database of 1,735 marine biological responses for which either regional or global climate change was considered as a driver. Included were instances of marine taxa responding as expected, in a manner inconsistent with expectations, and taxa demonstrating no response. From this database, 81–83% of all observations for distribution, phenology, community composition, abundance, demography and calcification across taxa and ocean basins were consistent with the expected impacts of climate change. Of the species responding to climate change, rates of distribution shifts were, on average, consistent with those required to track ocean surface temperature changes. Conversely, we did not find a relationship between regional shifts in spring phenology and the seasonality of temperature. Rates of observed shifts in species’ distributions and phenology are comparable to, or greater, than those for terrestrial systems.

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.

NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10 000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.

The rapid expansion of human activities threatens ocean-wide biodiversity. Numerous marine animal populations have declined, yet it remains unclear whether these trends are symptomatic of a chronic accumulation of global marine extinction risk. We present the first systematic analysis of threat for a globally distributed lineage of 1,041 chondrichthyan fishes-sharks, rays, and chimaeras. We estimate that one-quarter are threatened according to IUCN Red List criteria due to overfishing (targeted and incidental). Large-bodied, shallow-water species are at greatest risk and five out of the seven most threatened families are rays. Overall chondrichthyan extinction risk is substantially higher than for most other vertebrates, and only one-third of species are considered safe. Population depletion has occurred throughout the world's ice-free waters, but is particularly prevalent in the Indo-Pacific Biodiversity Triangle and Mediterranean Sea. Improved management of fisheries and trade is urgently needed to avoid extinctions and promote population recovery. DOI: http://dx.doi.org/10.7554/eLife.00590.001.

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.

Assessing Biodiversity Declines Understanding human impact on biodiversity depends on sound quantitative projection. Pereira et al. (p. 1496 , published online 26 October) review quantitative scenarios that have been developed for four main areas of concern: species extinctions, species abundances and community structure, habitat loss and degradation, and shifts in the distribution of species and biomes. Declines in biodiversity are projected for the whole of the 21st century in all scenarios, but with a wide range of variation. Hoffmann et al. (p. 1503 , published online 26 October) draw on the results of five decades' worth of data collection, managed by the International Union for Conservation of Nature Species Survival Commission. A comprehensive synthesis of the conservation status of the world's vertebrates, based on an analysis of 25,780 species (approximately half of total vertebrate diversity), is presented: Approximately 20% of all vertebrate species are at risk of extinction in the wild, and 11% of threatened birds and 17% of threatened mammals have moved closer to extinction over time. Despite these trends, overall declines would have been significantly worse in the absence of conservation actions.

The study and implementation of no-take marine reserves have increased rapidly over the past decade, providing ample data on the biological effects of reserve protection for a wide range of geographic locations and organisms. The plethora of new studies affords the opportunity to reevaluate previous findings and address formerly unanswered questions with extensive data syntheses. Our results show, on average, positive effects of reserve protection on the biomass, numerical density, species richness, and size of organisms within their boundaries which are remarkably similar to those of past syntheses despite a near doubling of data. New analyses indicate that (1) these results do not appear to be an artifact of reserves being sited in better locations; (2) results do not appear to be driven by displaced fishing effort outside of reserves; (3) contrary to often-made assertions, reserves have similar if not greater positive effects in temperate settings, at least for reef ecosystems; (4) even small reserves can produce significant biological responses irrespective of latitude, although more data are needed to test whether reserve effects scale with reserve size; and (5) effects of reserves vary for different taxonomic groups and for taxa with various characteristics, and not all species increase in response to reserve protection. There is considerable variation in the responses documented across all the reserves in our data set -variability which cannot be entirely explained by which species were studied. We suggest that reserve characteristics and context, particularly the intensity of fishing outside the reserve and inside the reserve before implementation, play key roles in determining the direction and magnitude of the reserve response. However, despite considerable variability, positive responses are far more common than no differences or negative responses, validating the potential for well designed and enforced reserves to serve as globally important conservation and management tools.

Tire tread particles turn streams toxic For coho salmon in the U.S. Pacific Northwest, returning to spawn in urban and suburban streams can be deadly. Regular acute mortality events are tied, in particular, to stormwater runoff, but the identity of the causative toxicant(s) has not been known. Starting from leachate from new and aged tire tread wear particles, Tian et al. followed toxic fractions through chromatography steps, eventually isolating a single molecule that could induce acute toxicity at threshold concentrations of ∼1 microgram per liter. The compound, called 6PPD-quinone, is an oxidation product of an additive intended to prevent damage to tire rubber from ozone. Measurements from road runoff and immediate receiving waters show concentrations of 6PPD-quinone high enough to account for the acute toxicity events. Science , this issue p. 185

The ongoing evolution of tracer mixing models has resulted in a confusing array of software tools that differ in terms of data inputs, model assumptions, and associated analytic products. Here we introduce MixSIAR, an inclusive, rich, and flexible Bayesian tracer (e.g., stable isotope) mixing model framework implemented as an open-source R package. Using MixSIAR as a foundation, we provide guidance for the implementation of mixing model analyses. We begin by outlining the practical differences between mixture data error structure formulations and relate these error structures to common mixing model study designs in ecology. Because Bayesian mixing models afford the option to specify informative priors on source proportion contributions, we outline methods for establishing prior distributions and discuss the influence of prior specification on model outputs. We also discuss the options available for source data inputs (raw data versus summary statistics) and provide guidance for combining sources. We then describe a key advantage of MixSIAR over previous mixing model software—the ability to include fixed and random effects as covariates explaining variability in mixture proportions and calculate relative support for multiple models via information criteria. We present a case study of Alligator mississippiensis diet partitioning to demonstrate the power of this approach. Finally, we conclude with a discussion of limitations to mixing model applications. Through MixSIAR, we have consolidated the disparate array of mixing model tools into a single platform, diversified the set of available parameterizations, and provided developers a platform upon which to continue improving mixing model analyses in the future.

Stable isotopes are a powerful tool for ecologists, often used to assess contributions of different sources to a mixture (e.g. prey to a consumer). Mixing models use stable isotope data to estimate the contribution of sources to a mixture. Uncertainty associated with mixing models is often substantial, but has not yet been fully incorporated in models. We developed a Bayesian-mixing model that estimates probability distributions of source contributions to a mixture while explicitly accounting for uncertainty associated with multiple sources, fractionation and isotope signatures. This model also allows for optional incorporation of informative prior information in analyses. We demonstrate our model using a predator-prey case study. Accounting for uncertainty in mixing model inputs can change the variability, magnitude and rank order of estimates of prey (source) contributions to the predator (mixture). Isotope mixing models need to fully account for uncertainty in order to accurately estimate source contributions.

In many marine species, high levels of gene flow ensure that the genetic signal from population differentiation is weak. As a consequence, various errors associated with estimating population genetic parameters that might normally be safely ignored assume a relatively greater importance. This fact has important implications for the use of genetic data to address two common questions in fishery conservation and management: (1) How many stocks of a given species are there? and (2) How much gene flow occurs among stocks? This article discusses strategies to maximize the signal:noise ratio in genetic studies of marine species and suggests a quantitative method to correct for bias due to a common sampling problem. For many marine species, however, genetic methods alone cannot fully resolve these key management questions because the amount of migration necessary to eliminate most genetic evidence of stock structure (only a handful of individuals per generation) will generally be inconsequential as a force for rebuilding depleted populations on a time scale of interest to humans. These limitations emphasize the importance of understanding the biology and life history of the target species-first, to guide design of the sampling program, and second, so that additional information can be used to supplement indirect estimates of migration rates based on genetic data.

A mechanism exists whereby global greenhouse warning could, by intensifying the alongshore wind stress on the ocean surface, lead to acceleration of coastal upwelling. Evidence from several different regions suggests that the major coastal upwelling systems of the world have been growing in upwelling intensity as greenhouse gases have accumulated in the earth's atmosphere. Thus the cool foggy summer conditions that typify the coastlands of northern California and other similar upwelling regions might, under global warming, become even more pronounced. Effects of enhanced upwelling on the marine ecosystem are uncertain but potentially dramatic.

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.

Stable isotope mixing models are increasingly used to quantify consumer diets, but may be misused and misinterpreted. We address major challenges to their effective application. Mixing models have increased rapidly in sophistication. Current models estimate probability distributions of source contributions, have user-friendly interfaces, and incorporate complexities such as variability in isotope signatures, discrimination factors, hierarchical variance structure, covariates, and concentration dependence. For proper implementation of mixing models, we offer the following suggestions. First, mixing models can only be as good as the study and data. Studies should have clear questions, be informed by knowledge of the system, and have strong sampling designs to effectively characterize isotope variability of consumers and resources on proper spatio-temporal scales. Second, studies should use models appropriate for the question and recognize their assumptions and limitations. Decisions about source grouping or incorporation of concentration dependence can influence results. Third, studies should be careful about interpretation of model outputs. Mixing models generally estimate proportions of assimilated resources with substantial uncertainty distributions. Last, common sense, such as graphing data before analyzing, is essential to maximize usefulness of these tools. We hope these suggestions for effective implementation of stable isotope mixing models will aid continued development and application of this field.

Climate change is a pervasive and growing global threat to biodiversity and ecosystems. Here, we present the most up-to-date assessment of climate change impacts on biodiversity, ecosystems, and ecosystem services in the U.S. and implications for natural resource management. We draw from the 4th National Climate Assessment to summarize observed and projected changes to ecosystems and biodiversity, explore linkages to important ecosystem services, and discuss associated challenges and opportunities for natural resource management. We find that species are responding to climate change through changes in morphology and behavior, phenology, and geographic range shifts, and these changes are mediated by plastic and evolutionary responses. Responses by species and populations, combined with direct effects of climate change on ecosystems (including more extreme events), are resulting in widespread changes in productivity, species interactions, vulnerability to biological invasions, and other emergent properties. Collectively, these impacts alter the benefits and services that natural ecosystems can provide to society. Although not all impacts are negative, even positive changes can require costly societal adjustments. Natural resource managers need proactive, flexible adaptation strategies that consider historical and future outlooks to minimize costs over the long term. Many organizations are beginning to explore these approaches, but implementation is not yet prevalent or systematic across the nation.

Abstract As the number of fish reproduction studies has proliferated, so has the number of gonadal classification schemes and terms. This has made it difficult for both scientists and resource managers to communicate and for comparisons to be made among studies. We propose the adoption of a simple, universal terminology for the phases in the reproductive cycle, which can be applied to all male and female elasmobranch and teleost fishes. These phases were chosen because they define key milestones in the reproductive cycle; the phases include immature, developing, spawning capable, regressing, and regenerating. Although the temporal sequence of events during gamete development in each phase may vary among species, each phase has specific histological and physiological markers and is conceptually universal. The immature phase can occur only once. The developing phase signals entry into the gonadotropin-dependent stage of oogenesis and spermatogenesis and ultimately results in gonadal growth. The spawning capable phase includes (1) those fish with gamete development that is sufficiently advanced to allow for spawning within the current reproductive cycle and (2) batch-spawning females that show signs of previous spawns (i.e., postovulatory follicle complex) and that are also capable of additional spawns during the current cycle. Within the spawning capable phase, an actively spawning subphase is defined that corresponds to hydration and ovulation in females and spermiation in males. The regressing phase indicates completion of the reproductive cycle and, for many fish, completion of the spawning season. Fish in the regenerating phase are sexually mature but reproductively inactive. Species-specific histological criteria or classes can be incorporated within each of the universal phases, allowing for more specific divisions (subphases) while preserving the overall reproductive terminology for comparative purposes. This terminology can easily be modified for fishes with alternate reproductive strategies, such as hermaphrodites (addition of a transition phase) and livebearers (addition of a gestation phase).

In this paper, we review recent advances in stable isotope mixing models (SIMMs) and place them into an overarching Bayesian statistical framework, which allows for several useful extensions. SIMMs are used to quantify the proportional contributions of various sources to a mixture. The most widely used application is quantifying the diet of organisms based on the food sources they have been observed to consume. At the centre of the multivariate statistical model we propose is a compositional mixture of the food sources corrected for various metabolic factors. The compositional component of our model is based on the isometric log‐ratio transform. Through this transform, we can apply a range of time series and non‐parametric smoothing relationships. We illustrate our models with three case studies based on real animal dietary behaviour. Copyright © 2013 John Wiley & Sons, Ltd.

▪ Abstract Inbreeding depression is of major concern in the management and conservation of endangered species. Inbreeding appears universally to reduce fitness, but its magnitude and specific effects are highly variable because they depend on the genetic constitution of the species or populations and on how these genotypes interact with the environment. Recent natural experiments are consistent with greater inbreeding depression in more stressful environments. In small populations of randomly mating individuals, such as are characteristic of many endangered species, all individuals may suffer from inbreeding depression because of the cumulative effects of genetic drift that decrease the fitness of all individuals in the population. In three recent cases, introductions into populations with low fitness appeared to restore fitness to levels similar to those before the effects of genetic drift. Inbreeding depression may potentially be reduced, or purged, by breeding related individuals. However, the Speke's gazelle example, often cited as a demonstration of reduction of inbreeding depression, appears to be the result of a temporal change in fitness in inbred individuals and not a reduction in inbreeding depression. Down, July 17, 1870 My Dear Lubbock, …In England and many parts of Europe the marriages of cousins are objected to from their supposed injurious consequences: but this belief rests on no direct evidence. It is therefore manifestly desirable that the belief should be either proved false, or should be confirmed, so that in this latter case the marriages of cousins might be discouraged… It is moreover, much to be wished that the truth of the often repeated assertion that consanguineous marriages lead to deafness and dumbness, blindness, &c, should be ascertained: and all such assertions could be easily tested by the returns from a single census. Believe me, Yours very sincerely, Charles Darwin

The scale and drivers of marine biodiversity loss are being revealed by the International Union for Conservation of Nature (IUCN) Red List assessment process. We present the first global reassessment of 1,199 species in Class Chondrichthyes-sharks, rays, and chimeras. The first global assessment (in 2014) concluded that one-quarter (24%) of species were threatened. Now, 391 (32.6%) species are threatened with extinction. When this percentage of threat is applied to Data Deficient species, more than one-third (37.5%) of chondrichthyans are estimated to be threatened, with much of this change resulting from new information. Three species are Critically Endangered (Possibly Extinct), representing possibly the first global marine fish extinctions due to overfishing. Consequently, the chondrichthyan extinction rate is potentially 25 extinctions per million species years, comparable to that of terrestrial vertebrates. Overfishing is the universal threat affecting all 391 threatened species and is the sole threat for 67.3% of species and interacts with three other threats for the remaining third: loss and degradation of habitat (31.2% of threatened species), climate change (10.2%), and pollution (6.9%). Species are disproportionately threatened in tropical and subtropical coastal waters. Science-based limits on fishing, effective marine protected areas, and approaches that reduce or eliminate fishing mortality are urgently needed to minimize mortality of threatened species and ensure sustainable catch and trade of others. Immediate action is essential to prevent further extinctions and protect the potential for food security and ecosystem functions provided by this iconic lineage of predators.

Genetic methods are routinely used to estimate contemporary effective population size (N e) in natural populations, but the vast majority of applications have used only the temporal (two-sample) method. We use simulated data to evaluate how highly polymorphic molecular markers affect precision and bias in the single-sample method based on linkage disequilibrium (LD). Results of this study are as follows: (1) Low-frequency alleles upwardly bias [Formula: see text], but a simple rule can reduce bias to <about 10% without sacrificing much precision. (2) With datasets routinely available today (10-20 loci with 10 alleles; 50 individuals), precise estimates can be obtained for relatively small populations (N e < 200), and small populations are not likely to be mistaken for large ones. However, it is very difficult to obtain reliable estimates for large populations. (3) With 'microsatellite' data, the LD method has greater precision than the temporal method, unless the latter is based on samples taken many generations apart. Our results indicate the LD method has widespread applicability to conservation (which typically focuses on small populations) and the study of evolutionary processes in local populations. Considerable opportunity exists to extract more information about N e in nature by wider use of single-sample estimators and by combining estimates from different methods.