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Wild-caught fish are a bioavailable source of nutritious food that, if managed strategically, could enhance diet quality for billions of people. However, optimising nutrient production from the sea has not been a priority, hindering development of nutrition-sensitive policies. With fisheries management increasingly effective at rebuilding stocks and regulating sustainable fishing, we can now begin to integrate nutritional outcomes within existing management frameworks. Here, we develop a conceptual foundation for managing fisheries for multispecies Maximum Nutrient Yield (mMNY). We empirically test our approach using size-based models of North Sea and Baltic Sea fisheries and show that mMNY is predicted by the relative contribution of nutritious species to total catch and their vulnerability to fishing, leading to trade-offs between catch and specific nutrients. Simulated nutrient yield curves suggest that vitamin D, which is deficient in Northern European diets, was underfished at fishing levels that returned maximum catch weights. Analysis of global catch data shows there is scope for nutrient yields from most of the world's marine fisheries to be enhanced through nutrient-sensitive fisheries management. With nutrient composition data now widely available, we expect our mMNY framework to motivate development of nutrient-based reference points in specific contexts, such as data-limited fisheries. Managing for mMNY alongside policies that promote access to fish could help close nutrient gaps for coastal populations, maximising the contribution of wild-caught fish to global food and nutrition security.

Diet specificity is likely to be the key predictor of a predator's vulnerability to changing habitat and prey conditions. Understanding the degree to which predatory coral reef fishes adjust or maintain prey choice, in response to declines in coral cover and changes in prey availability, is critical for predicting how they may respond to reef habitat degradation. Here, we use stable isotope analyses to characterize the trophic structure of predator–prey interactions on coral reefs of the Keppel Island Group on the southern Great Barrier Reef, Australia. These reefs, previously typified by exceptionally high coral cover, have recently lost much of their coral cover due to coral bleaching and frequent inundation by sediment‐laden, freshwater flood plumes associated with increased rainfall patterns. Long‐term monitoring of these reefs demonstrates that, as coral cover declined, there has been a decrease in prey biomass, and a shift in dominant prey species from pelagic plankton‐feeding damselfishes to territorial benthic algal‐feeding damselfishes, resulting in differences in the principal carbon pathways in the food web. Using isotopes, we tested whether this changing prey availability could be detected in the diet of a mesopredator (coral grouper, Plectropomus maculatus). The δ13C signature in grouper tissue in the Keppel Islands shifted from a more pelagic to a more benthic signal, demonstrating a change in carbon sources aligning with the change in prey availability due to habitat degradation. Grouper with a more benthic carbon signature were also feeding at a lower trophic level, indicating a shortening in food chains. Further, we found a decline in the coral grouper population accompanying a decrease in total available prey biomass. Thus, while the ability to adapt diets could ameliorate the short‐term impacts of habitat degradation on mesopredators, long‐term effects may negatively impact mesopredator populations and alter the trophic structure of coral reef food webs.

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty.

Summary 1. In light of the continuing biodiversity crisis, the need for high-resolution, broad-scale ecological data is particularly acute. The expansive scale of volunteer data collection programmes provides an opportunity to address this challenge, however, protocols used to collect such data are typically less standardized than those used by professional scientists. Although previous studies have established that different protocols can lead to different results, it remains unclear how relevant these differences are to specific study goals, such as biodiversity assessment. 2. This study uses both null model and Bayesian occupancy approaches to examine the capacity of a widely used volunteer survey protocol, the roving diver transect, to detect patterns of marine fish diversity. Richness estimates are compared with those obtained using the conventional belt transects favoured in many peer reviewed studies, examining the power of both protocols to detect statistically significant differences between survey sites and quantifying differences in detectability. 3. Pairwise site comparisons of a-diversity (i.e. within site diversity) were consistent between protocols, particularly for species totals. 4. The roving diver transect protocol detected a substantially larger number of species than the belt transect protocol, due to notably higher detectability, even after controlling for confounding factors. Both protocols detected the same species pool, although the species richness among observations was higher for the belt protocol at certain sites. 5. The significance of pairwise site b-diversity (i.e. differentiation between sites) comparisons differed between the protocols and care should be exercised, when using either protocol, when studying variation in species composition. 6. These results provide vital information for managers and researchers considering the use of volunteer data or protocols for the purpose of biodiversity assessment in aquatic systems, helping to quantify the value of thousands of existing survey records. The larger number of species detected by the volunteer protocol suggests this protocol may be advantageous with regards to the completion of taxonomic lists.

Coral reef fisheries support the livelihoods of millions of people but have been severely and negatively affected by anthropogenic activities. We conducted a systematic review of published data on the biomass of coral reef fishes to explore how the condition of reef fisheries is related to the density of local human populations, proximity of the reef to markets, and key environmental variables (including broad geomorphologic reef type, reef area, and net productivity). When only population density and environmental covariates were considered, high variability in fisheries conditions at low human population densities resulted in relatively weak explanatory models. The presence or absence of human settlements, habitat type, and distance to fish markets provided a much stronger explanatory model for the condition of reef fisheries. Fish biomass remained relatively low within 14 km of markets, then biomass increased exponentially as distance from reefs to markets increased. Our results suggest the need for an increased science and policy focus on markets as both a key driver of the condition of reef fisheries and a potential source of solutions.

Cost-effective proxies of biodiversity and species abundance, applicable across a range of spatial scales, are needed for setting conservation priorities and planning action. We outline a rapid, efficient, and low-cost measure of spectral signal from digital habitat images that, being an effective proxy for habitat complexity, correlates with species diversity and requires little image processing or interpretation. We validated this method for coral reefs of the Great Barrier Reef (GBR), Australia, across a range of spatial scales (1 m to 10 km), using digital photographs of benthic communities at the transect scale and high-resolution Landsat satellite images at the reef scale. We calculated an index of image-derived spatial heterogeneity, the mean information gain (MIG), for each scale and related it to univariate (species richness and total abundance summed across species) and multivariate (species abundance matrix) measures of fish community structure, using two techniques that account for the hierarchical structure of the data: hierarchical (mixed-effect) linear models and distance-based partial redundancy analysis. Over the length and breadth of the GBR, MIG alone explained up to 29% of deviance in fish species richness, 33% in total fish abundance, and 25% in fish community structure at multiple scales, thus demonstrating the possibility of easily and rapidly exploiting spatial information contained in digital images to complement existing methods for inferring diversity and abundance patterns among fish communities. Thus, the spectral signal of unprocessed remotely sensed images provides an efficient and low-cost way to optimize the design of surveys used in conservation planning. In data-sparse situations, this simple approach also offers a viable method for rapid assessment of potential local biodiversity, particularly where there is little local capacity in terms of skills or resources for mounting in-depth biodiversity surveys.

With rapidly increasing rates of contemporary extinction, predicting extinction vulnerability and identifying how multiple stressors drive non-random species loss have become key challenges in ecology. These assessments are crucial for avoiding the loss of key functional groups that sustain ecosystem processes and services. We developed a novel predictive framework of species extinction vulnerability and applied it to coral reef fishes. Although relatively few coral reef fishes are at risk of global extinction from climate disturbances, a negative convex relationship between fish species locally vulnerable to climate change vs. fisheries exploitation indicates that the entire community is vulnerable on the many reefs where both stressors co-occur. Fishes involved in maintaining key ecosystem functions are more at risk from fishing than climate disturbances. This finding is encouraging as local and regional commitment to fisheries management action can maintain reef ecosystem functions pending progress towards the more complex global problem of stabilizing the climate.

A recent literature review reported negative relationships between diet discrimination factors (DDFs = X(fish) - X(food) ; X = δ(15) N or δ(13) C) and the values of δ(15) N and δ(13) C in the food of wild organisms but there has been no laboratory-based confirmation of these relationships to date. Laboratory reared guppies (Poecilia reticulata) fed a series of diets with a range of δ(13) C (-22.9 to -6.6‰) and δ(15) N (6.5 to 1586‰) values were used to magnify diet-tissue dynamics in order to calculate DDFs once the fish had achieved equilibrium with each of the diets. Values of DDFs range widely for δ(15) N (7.1 to -849‰) and δ(13) C (1.1 to -7.0‰) and showed a strong negative correlation with the stable isotope value in the food for δ(15) N (slope = -0.59 ± 0.02, r(2) = 0.95) and δ(13) C (slope = -0.56 ± 0.02, r(2) = 0.94). Based on these relationships, the magnitude of DDF change over environmentally relevant values of δ(15) N or δ(13) C would be significant and could confound the interpretation of stable isotopes in the environment. Using highly enriched experimental diets, our study adds to a growing number of studies that undermine the consistent trophic enrichment paradigm with results that demonstrate the currently poor mechanistic understanding of how DDFs arise. The results of our study highlight that the magnitude of the stable isotope values in prey must be considered when choosing DDF values. Future laboratory studies should therefore be directed at uncovering the mechanistic basis of DDFs and, like others before, we recommend the determination of diet-dependent DDFs under laboratory conditions before modeling dietary proportions or calculating trophic positions.

Aim Quantifying and predicting change in large ecosystems is an important research objective for applied ecologists as human disturbance effects become increasingly evident at regional and global scales. However, studies used to make inferences about large-scale change are frequently of uneven quality and few in number, having been undertaken to study local, rather than global, change. Our aim is to improve the quality of inferences that can be made in meta-analyses of large-scale disturbance by integrating studies of varying quality in a unified modelling framework that is informative for both local and regional management. Innovation Here we improve conventionally structured meta-analysis methods by including imputation of unknown study variances and the use of Bayesian factor potentials. The approach is a coherent framework for integrating data of varying quality across multiple studies while facilitating belief statements about the uncertainty in parameter estimates and the probable outcome of future events. The approach is applied to a regional meta-analysis of the effects of loss of coral cover on species richness and the abundance of coral-dependent fishes in the western Indian Ocean (WIO) before and after a mass bleaching event in 1998. Main conclusions Our Bayesian approach to meta-analysis provided greater precision of parameter estimates than conventional weighted linear regression meta-analytical techniques, allowing us to integrate all available data from 66 available study locations in the WIO across multiple scales. The approach thereby: (1) estimated uncertainty in site-level estimates of change, (2) provided a regional estimate for future change at any given site in the WIO, and (3) provided a probabilistic belief framework for future management of reef resources at both local and regional scales.

Diet-tissue fractionation factors and metabolic turnover rates of delta15N and delta13C were assessed in laboratory-reared black fly (Simulium vittatum IS-7) larvae fed isotopically distinct diets. Five treatments consisted of using food with different delta15N signatures throughout the experiments (19-26 days), a sixth shifted from a low to high delta15N signature diet (uptake) on day 14, and the last shifted from a high to low delta15N signature diet (elimination) on day 14. In the larvae, diet-tissue fractionation factors for delta13C, which were in steady state with food, ranged from -0.61 to 2.0, with a median of 1.87. The delta15N diet-tissue fractionation factors were mostly negative, ranging from +2.85 to -24.96 per thousand, with a single positive value from the elimination treatment in which larval delta15N did not achieve steady state with the food. Diet-tissue fractionation factors also had a significant negative relationship (r2 = 0.98) with delta15N values in the food suggesting that nitrogen diet-tissue fractionation factors are 15N concentration-dependent. The delta15N of shed head capsules and feces were enriched in 15N and could be mechanisms for elimination of 15N by the larvae. For delta15N, metabolic turnover values based on the Hesslein model were highly consistent (0.40 to 0.43 delta15N*day(-1)) between uptake and elimination phases and across experiments and were an order of magnitude greater than growth rates. The rapid turnover of nitrogen in black fly larvae, which was orders of magnitude greater than measured in vertebrates, makes them an excellent indicator of short-term changes in nitrogen inputs to aquatic systems.

Stable isotope analysis (SIA) is recognized as a powerful analytical tool with numerous ecological applications. This has been highlighted by the increase in popularity of the isotope ratio mass spectrometry (IRMS) technique and the large number of studies reporting isotopic data. Comparisons of new isotopic data with previously published results and the use of large volumes of isotopic ratios in meta-analyses to explain isotopic variance are commonplace. Such data often originate from different IRMS instruments and are assumed to be readily comparable as all instruments are calibrated to International Atomic Energy Agency (IAEA) standards. To test the validity of this assumption, we analyzed a single ecological sample (homogenized cod muscle, Gadus morhua) on eight anonymous IRMS instruments and found significant variation in both δ15N and δ13C. We used a one-way analysis of variance (ANOVA) with random effects to estimate the average variability of laboratory results within and among instruments. Overall, 74% of variation in δ15N and 35% of variation in δ13C of a single ecological sample was explained by differences in the IRMS instrument used. In light of these findings, researchers are encouraged to submit their own sample reference to provide an independent check on variation between runs and between instruments; consistent discrepancies between instruments should be corrected through linear regression. Comparisons of data obtained from multiple instruments should acknowledge inter-instrument variation as a potential source of error.

Identifying the rates of recovery of fish in no-take areas is fundamental to designing protected area networks, managing fisheries, estimating yields, identifying ecological interactions, and informing stakeholders about the outcomes of this management. Here we study the recovery of coral reef fishes through 37 years of protection using a space-for-time chronosequence of four marine national parks in Kenya. Using AIC model selection techniques, we assessed recovery trends using five ecologically meaningful production models: asymptotic, Ricker, logistic, linear, and exponential. There were clear recovery trends with time for species richness, total and size class density, and wet masses at the level of the taxonomic family. Species richness recovered rapidly to an asymptote at 10 years. The two main herbivorous families displayed differing responses to protection, scarids recovering rapidly, but then exhibiting some decline while acanthurids recovered more slowly and steadily throughout the study. Recovery of the two invertebrate-eating groups suggested competitive interactions over resources, with the labrids recovering more rapidly before a decline and the balistids demonstrating a slower logistic recovery. Remaining families displayed differing trends with time, with a general pattern of decline in smaller size classes or small-bodied species after an initial recovery, which suggests that some species- and size-related competitive and predatory control occurs in older closures. There appears to be an ecological succession of dominance with an initial rapid rise in labrids and scarids, followed by a slower rise in balistids and acanthurids, an associated decline in sea urchins, and an ultimate dominance in calcifying algae. Our results indicate that the unfished ''equilibrium'' biomass of the fish assemblage .10 cm is 1100-1200 kg/ha, but these small parks (,10 km 2 ) are likely to underestimate pre- human influence values due to edge effects and the rarity of taxa with large area requirement, such as apex predators, including sharks.

The authors provide corrections for two equation errors, one in the main manuscript text and one in Supplementary Material File S4 of Hussey et al. (2014). A spelling mistake in one of the figure axes is also corrected. The errors are as follows: 1. Within the main manuscript (page 241; bottom of text column two), the following equation to calculate trophic position (TP) using a scaled Δ15N framework based on a dietary δ15N value‐dependent Δ15N model was presented; TP=log(δ15Nlim−δ15Nbase)−log(δ15Nlim−δ15NTP)k The TP of the baseline organism was omitted from this equation and must be added to obtain an absolute TP value for the organism of interest. The corrected equation is consequently; TP=log(δ15Nlim−δ15Nbase)−log(δ15Nlim−δ15NTP)k+TPbase where TPbase is the trophic position of the consumer used to define δ15Nbase (i.e. TP = 2 or 3). 2. In the supplementary material file titled, ‘ele12226‐sup‐0004‐SupplementaryMaterialS4’, equation (S3) was written as follows which is incorrect; k=−log(β0−δ15Nlim)−δ15Nlim The above equation has now been corrected to; k=−logβ0−δ15Nlim−δ15Nlim following the same equation presented in the manuscript text (page 242; top of text column one). In addition, the equations in Supplementary Material File S4 have been reordered; the above equation is now listed as (S4). The corrected Supplementary Material File S4 has been provided as the online Supporting Information of this corrigendum (entitled ‘ele_12270‐sup‐0001‐SupplementaryMaterialS4 CORRECTED’) 3. In Figure 6, a spelling mistake in the x‐axis legends of (a), (c), (e) and (g) reads ‘basline organism’ and should be corrected to ‘baseline organism’.