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Overfishing is the most significant threat facing sharks and rays. Given the growth in consumption of seafood, combined with the compounding effects of habitat loss, climate change, and pollution, there is a need to identify recovery paths, particularly in poorly managed and poorly monitored fisheries. Here, we document conservation through fisheries management success for 11 coastal sharks in US waters by comparing population trends through a Bayesian state-space model before and after the implementation of the 1993 Fisheries Management Plan for Sharks. We took advantage of the spatial and temporal gradients in fishing exposure and fisheries management in the Western Atlantic to analyze the effect on the Red List status of all 26 wide-ranging coastal sharks and rays. We show that extinction risk was greater where fishing pressure was higher, but this was offset by the strength of management engagement (indicated by strength of National and Regional Plan of Action for sharks and rays). The regional Red List Index (which tracks changes in extinction risk through time) declined in all regions until the 1980s but then improved in the North and Central Atlantic such that the average extinction risk is currently half that in the Southwest. Many sharks and rays are wide ranging, and successful fisheries management in one country can be undone by poorly regulated or unregulated fishing elsewhere. Our study underscores that well-enforced, science-based management of carefully monitored fisheries can achieve conservation success, even for slow-growing species.

Here, we summarise the extinction risk of the sharks and rays endemic to coastal, shelf, and slope waters of the southwest Indian Ocean and adjacent waters (SWIO+, Namibia to Kenya, including SWIO islands). This region is a hotspot of endemic and evolutionarily distinct sharks and rays. Nearly one-fifth (n = 13 of 70, 18.6%) of endemic sharks and rays are threatened, of these: one is Critically Endangered, five are Endangered, and seven are Vulnerable. A further seven (10.0%) are Near Threatened, 33 (47.1%) are Least Concern, and 17 (24.3%) are Data Deficient. While the primary threat is overfishing, there are the first signs that climate change is contributing to elevated extinction risk through habitat reduction and inshore distributional shifts. By backcasting their status, few endemic species were threatened in 1980, but this changed soon after the emergence of targeted shark and ray fisheries. South Africa has the highest national conservation responsibility, followed by Mozambique and Madagascar. Yet, while fisheries management and enforcement have improved in South Africa over recent decades, substantial improvements are urgently needed elsewhere. To avoid extinction and ensure robust populations of the region's endemic sharks and rays and maintain ecosystem functionality, there is an urgent need for the strict protection of Critically Endangered and Endangered species and sustainable management of Vulnerable, Near Threatened, and Least Concern species, underpinned by species-level data collection and reduction of incidental catch. [ABSTRACT FROM AUTHOR]

The Precautionary Approach to Fisheries Management requires an assessment of the impact of uncertainty on the risk of achieving management objectives. However, the main quantities, such as spawning stock biomass (SSB) and fish mortality (F), used in management metrics cannot be directly observed. This requires the use of models to provide guidance, for which there are three paradigms: the best assessment, model ensemble, and Management Strategy Evaluation (MSE). It is important to validate the models used to provide advice. In this study, we demonstrate how stock assessment models can be validated using a diagnostic toolbox, with a specific focus on prediction skill. Prediction skill measures the precision of a predicted value, which is unknown to the model, in relation to its observed value. By evaluating the accuracy of model predictions against observed data, prediction skill establishes an objective framework for accepting or rejecting model hypotheses, as well as for assigning weights to models within an ensemble. Our analysis uncovers the limitations of traditional stock assessment methods. Through the quantification of uncertainties and the integration of multiple models, our objective is to improve the reliability of management advice considering the complex interplay of factors that influence the dynamics of fish stocks. [ABSTRACT FROM AUTHOR]

Overfishing is the primary cause of marine defaunation, yet declines in and increasing extinction risks of individual species are difficult to measure, particularly for the largest predators found in the high seas.sup.1-3. Here we calculate two well-established indicators to track progress towards Aichi Biodiversity Targets and Sustainable Development Goals.sup.4,5: the Living Planet Index (a measure of changes in abundance aggregated from 57 abundance time-series datasets for 18 oceanic shark and ray species) and the Red List Index (a measure of change in extinction risk calculated for all 31 oceanic species of sharks and rays). We find that, since 1970, the global abundance of oceanic sharks and rays has declined by 71% owing to an 18-fold increase in relative fishing pressure. This depletion has increased the global extinction risk to the point at which three-quarters of the species comprising this functionally important assemblage are threatened with extinction. Strict prohibitions and precautionary science-based catch limits are urgently needed to avert population collapse.sup.6,7, avoid the disruption of ecological functions and promote species recovery.sup.8,9. The global abundance of oceanic sharks and rays has decreased by 71% since 1970 and 24 species are threatened with extinction owing to a concomitant increase in fishing pressure., Author(s): Nathan Pacoureau [sup.1] , Cassandra L. Rigby [sup.2] , Peter M. Kyne [sup.3] , Richard B. Sherley [sup.4] , Henning Winker [sup.5] [sup.6] , John K. Carlson [sup.7] , [...]

In the face of biodiversity loss worldwide, it is paramount to quantify species' extinction risk to guide conservation efforts. The International Union for the Conservation of Nature (IUCN)'s Red List is considered the global standard for evaluating extinction risks. IUCN criteria also inform national extinction risk assessments. Bayesian models, including the state‐of‐the‐art JARA ('Just Another Red List Assessment') tool, deliver probabilistic statements about species falling into extinction risk categories, thereby enabling characterisation and communication of uncertainty in extinction risk assessments.We coupled the state‐of‐the‐art VAST ('Vector Autoregressive Spatio‐Temporal') modelling tool and JARA, for better informed Red List assessments of marine fishes. In this framework, VAST is fitted to scientific survey catch rate data to provide indices to JARA whose uncertainty is propagated to JARA outcomes suggesting extinction risk categories (under the population reduction criterion). In addition, VAST delivers a valuable habitat assessment to better understand what may be driving extinction risk in the study region. Here, we demonstrate the coupled VAST‐JARA modelling framework by applying it to five contrasting North Sea species, with or without a quantitative stock assessment and with different conservation statuses according to the latest global Red List assessments.The North Sea application coupled with previous assessments and studies suggest that, among the three elasmobranchs, starry ray is in most need of urgent research (and conservation actions where appropriate), followed by spurdog, while lesser‐spotted dogfish is increasing in biomass. Moreover, both the VAST‐JARA modelling framework and previous research indicate that, while European plaice is not of conservation concern, cod has likely met the IUCN criteria for being listed as Endangered recently.Synthesis and applications. The predictions of the VAST‐JARA modelling framework for North Sea species, including JARA output and VAST habitat assessment, constitute valuable supporting information to make interpretations based on Red List guidelines, which will help decision‐makers in their next North Sea Red List assessment. We foresee applications of the modelling framework to assist Red List assessments of numerous marine fishes worldwide. Our modelling framework has many potential advantageous uses, including informing resource management about climate change impacts on species' extinction risks. [ABSTRACT FROM AUTHOR]

Larger and older fish contribute disproportionately to spawning and play an important role in the replenishment of exploited stocks. Fishing often removes specific size‐ and age‐classes, with direct impacts on stock productivity and population resilience. Despite this, fisheries advice is commonly based on estimates of spawning stock biomass (SSB) and fishing mortality (F) and makes little reference to the importance of size and/or age structure. Consequently, there is a need for indicators of size and/or age structure to better inform fisheries management and help assess global sustainability goals. Here, we introduce a new age‐based indicator ABIMSY that monitors age structure relative to the equilibrium age structure at FMSY. We apply this new indicator to 72 commercially important stocks in the Northeast Atlantic, covering 26 species, which collectively contributed 86% of all commercial catches in the region in 2019. We estimate that 62% (45 stocks) currently have proportionally fewer older fish relative to FMSY conditions, whereas 38% (27 stocks) have proportionally more older fish; we also note patterns with respect to geographic area and taxonomic family. Simulation testing demonstrated that ABIMSY is responsive to overfishing and generally tracks (with high sensitivity and specificity) a common measure of stock depletion, SSB relative to BMSY. Throughout, we show that ABIMSY provides information on the age structure of exploited stocks that is complementary to conventional reference points for SSB and F. Further, the framework used to estimate ABIMSY make it well placed for integration into current advisory frameworks on fisheries management. [ABSTRACT FROM AUTHOR]

Estimating trends in abundance from fishery catch rates is one of the oldest endeavors in fisheries science. However, many jurisdictions do not analyze fishery catch rates due to concerns that these data confound changes in fishing behavior (adjustments in fishing location or gear operation) with trends in abundance. In response, we developed a spatial dynamic factor analysis (SDFA) model that decomposes covariation in multispecies catch rates into components representing spatial variation and fishing behavior. SDFA estimates spatiotemporal variation in fish density for multiple species and accounts for fisher behavior at large spatial scales (i.e., choice of fishing location) while controlling for fisher behavior at fine spatial scales (e.g., daily timing of fishing activity). We first use a multispecies simulation experiment to show that SDFA decreases bias in abundance indices relative to ignoring spatial adjustments and fishing tactics. We then present results for a case study involving petrale sole (Eopsetta jordani) in the California Current, for which SDFA estimates initially stable and then increasing abundance for the period 1986-2003, in accordance with fishery-independent survey and stock assessment estimates. L'estimation des tendances d'abondance a partir de taux de prises des peches est une des pratiques les plus anciennes des sciences halieutiques. De nombreux pays n'analysent cependant pas les taux de prises des peches parce que ces donnees pourraient ne pas distinguer les modifications des comportements de peche (ajustements du lieu de peche ou de l'utilisation d'engins) des tendances d'abondance. Nous avons donc developpe un modele d'analyse des facteurs de dynamique spatiale (SDFA) qui decompose la covariation des taux de prises multiespeces en differentes composantes representant la variation spatiale et le comportement de peche. La SDFA estime les variations spatiotemporelles de densite de poissons pour des especes multiples et tient compte du comportement de peche a de grandes echelles spatiales (c.-a-d., le choix du lieu de peche), tout en controlant pour le comportement des pecheurs a petites echelles spatiales (p. ex. l'heure du jour de l'activite de peche). Nous utilisons d'abord une experience de simulation multiespeces pour demontrer que la SDFA reduit le biais dans les indices d'abondance par rapport a la non-prise en compte des ajustements spatiaux et des tactiques de peche. Nous presentons ensuite les resultats pour une etude de cas portant sur la platija prtrale (Eopsetta jordani) dans le courant de Californie, pour laquelle la SDFA estime une abondance initialement stable, puis croissante pour la periode 1986-2002, ce qui concorde avec les estimations tirees devaluations independantes de la peche et devaluations des stocks. [Traduit par la Redaction], Introduction Many developed and developing countries collect detailed information from fishers regarding the location, timing, and catches from fishing operations. This fishing information is typically used to estimate total catch [...]

Following an introduction to the nature of fisheries catches and their information content, a new development of CMSY, a data-limited stock assessment method for fishes and invertebrates, is presented. This new version, CMSY++, overcomes several of the deficiencies of CMSY, which itself improved upon the "Catch-MSY" method published by S. Martell and R. Froese in 2013. The catch-only application of CMSY++ uses a Bayesian implementation of a modified Schaefer model, which also allows the fitting of abundance indices should such information be available. In the absence of historical catch time series and abundance indices, CMSY++ depends strongly on the provision of appropriate and informative priors for plausible ranges of initial and final stock depletion. An Artificial Neural Network (ANN) now assists in selecting objective priors for relative stock size based on patterns in 400 catch time series used for training. Regarding the cross-validation of the ANN predictions, of the 400 real stocks used in the training of ANN, 94% of final relative biomass (B/k) Bayesian (BSM) estimates were within the approximate 95% confidence limits of the respective CMSY++ estimate. Also, the equilibrium catch-biomass relations of the modified Schaefer model are compared with those of alternative surplus-production and age-structured models, suggesting that the latter two can be strongly biased towards underestimating the biomass required to sustain catches at low abundance. Numerous independent applications demonstrate how CMSY++ can incorporate, in addition to the required catch time series, both abundance data and a wide variety of ancillary information. We stress, however, the caveats and pitfalls of naively using the built-in prior options, which should instead be evaluated case-by-case and ideally be replaced by independent prior knowledge. [ABSTRACT FROM AUTHOR]

The fine-scale movement of Mustelus mustelus in relation to environmental conditions was investigated at various temporal scales with acoustic telemetry and temperature–depth transmitters inside a coastal marine protected area in South Africa. Twenty-four sharks were equipped with acoustic tags and logged by an array of 28 acoustic receivers from November 2006 to November 2008. Generalised additive and generalised additive mixed models (GAMMs) were used to explain patterns of movement in terms of the environmental conditions related to temperature, the rate of change of temperature, tidal flow, diel cycle and moon phase. The most important environmental parameters affecting movement and direction of movement were related to absolute temperature and changes in temperature at the position of the shark. The movement of M. mustelus was not affected by tide and only minimally affected by the diel cycle, suggesting behavioural thermoregulation as the ultimate cause of the movements. M. mustelus preferred temperatures from 18 to 22°C, as determined by GAMMs for environmental conditions experienced in summer. The combination of the thermal environment, rich feeding grounds and protective effect of the Langebaan Marine Protected Area may explain the high abundance and regular occurrence of M. mustelus within this marine protected area. The highly resident Mustelus mustelus from the Langebaan Marine Protected Area (MPA) have been protected from fishing activities for 30 years. Residency of M. mustelus inside the MPA is largely as a result of their movement to avoid warm and cold water outside their thermal preference. The influence of environmental conditions on how an MPA is used by this species emphasises the importance of considering environmental preferences in spatial conservation initiatives. [ABSTRACT FROM AUTHOR]

This study evaluates the relationship between both commercial and scientific spatial fisheries data and a new satellite‐based estimate of potential fish production (Ocean Productivity available to Fish, OPFish) in the European Seas. To construct OPFish, we used productivity frontal features derived from chlorophyll‐a horizontal gradients, which characterize 10%–20% of the global phytoplankton production that effectively fuels higher trophic levels. OPFish is relatively consistent with the spatial distribution of both pelagic and demersal fish landings and catches per unit of effort (LPUEs and CPUEs, respectively). An index of harvest relative to ocean productivity (HP index) is calculated by dividing these LPUEs or CPUEs with OPFish. The HP index reflects the intensity of fishing by gear type with regard to local fish production. Low HP levels indicate lower LPUEs or CPUEs than expected from oceanic production, suggesting over‐exploitation, while high HP levels imply more sustainable fishing. HP allows comparing the production‐dependent suitability of local fishing intensities. Our results from bottom trawl data highlight that over‐exploitation of demersal species from the shelves is twice as high in the Mediterranean Sea than in the North‐East Atlantic. The estimate of HP index by dominant pelagic and demersal gears suggests that midwater and bottom otter trawls are associated with the lowest and highest overfishing, respectively. The contrasts of fishing intensity at local scales captured by the HP index suggest that accounting for the local potential fish production can promote fisheries sustainability in the context of ecosystem‐based fisheries management as required by international marine policies. [ABSTRACT FROM AUTHOR]

The adoption of the Precautionary Approach requires providing advice that is robust to uncertainty. Therefore, when conducting stock assessment alternative, model structures and data sets are commonly considered. The primary diagnostics used to compare models are to examine residuals patterns to check goodness-of-fit and to conduct retrospective analysis to check the stability of estimates. However, residual patterns can be removed by adding more parameters than justified by the data, and retrospective patterns removed by ignoring the data. Therefore, neither alone can be used for validation, which requires assessing whether it is plausible that a system identical to the model generated the data. Therefore, we use hindcasting to estimate prediction skill, a measure of the accuracy of a predicted value unknown by the model relative to its observed value, to explore model misspecification and data conflicts. We compare alternative model structures based on integrated statistical and Bayesian state-space biomass dynamic models using, as an example, Indian Ocean yellowfin tuna. Validation is not a binary process (i.e. pass or fail) but a continuum; therefore, we discuss the use of prediction skill to identify alternative hypotheses, weight ensemble models and agree on reference sets of operating models when conducting Management Strategy Evaluation. [ABSTRACT FROM AUTHOR]

Mustelus mustelus from the Langebaan Marine Protected Area (LMPA) has been largely protected from fishing activities for the past 30 years; therefore, its biology represents those of an unfished stock. The reproductive biology, diet, growth and maturity of M. mustelus was studied in the Langebaan Lagoon region in the south-western Cape Coast of South Africa between 2007 and 2009. In total, 217 sharks (females: 381-1734 mm total length (TL); males: 467-1267 mm TL) were examined. Sharks in the Bay represented the largest specimens among six regions, globally. Female parturition, ovulating and mating occurred between November and December after a gestation period of 10-11 months. No ontogenetic shift in diet was evident, with the diet predominantly consisting of the following three species of crustaceans; Hymenosoma orbiculare, Upogebia africana and Callichirus kraussi. The von Bertalanffy growth parameters for combined sexes were L∞ = 1594 mm TL, k = 0.15 year-1, t0 = -2.01 year (n = 95). Possible age over-estimation was investigated using micro-computed tomography, which highlighted the existence of false check marks. This study indicated that the LMPA represents a pupping, nursery and feeding ground as well as a refuge area for the largest and oldest recorded smoothhound sharks globally, emphasising its importance in spatial conservation of this species. [ABSTRACT FROM AUTHOR]

Understanding changes in abundance is crucial for conservation, but population growth rates often vary over space and time. We use 40 years of count data (1979–2019) and Bayesian state‐space models to assess the African penguin Spheniscus demersus population under IUCN Red List Criterion A. We deconstruct the overall decline in time and space to identify where urgent conservation action is needed. The global African penguin population met the threshold for Endangered with a high probability (97%), having declined by almost 65% since 1989. An historical low of ~17,700 pairs bred in 2019. Annual changes were faster in the South African population (−4.2%, highest posterior density interval, HPDI: −7.8 to −0.6%) than the Namibian one (−0.3%, HPDI: −3.3 to +2.6%), and since 1999 were almost −10% at South African colonies north of Cape Town. Over the 40‐year period, the Eastern Cape colonies went from holding ~25% of the total penguin population to ~40% as numbers decreased more rapidly elsewhere. These changes coincided with an altered abundance and availability of the main prey of African penguins. Our results underline the dynamic nature of population declines in space as well as time and highlight which penguin colonies require urgent conservation attention. [ABSTRACT FROM AUTHOR]

The Law of the Sea and regional and national laws and agreements require exploited populations or stocks to be managed so that they can produce maximum sustainable yields. However, exploitation level and stock status are unknown for most stocks because the data required for full stock assessments are missing. This study presents a new method [abundance maximum sustainable yields (AMSY)] that estimates relative population size when no catch data are available using time series of catch-per-unit-effort or other relative abundance indices as the main input. AMSY predictions for relative stock size were not significantly different from the "true" values when compared with simulated data. Also, they were not significantly different from relative stock size estimated by data-rich models in 88% of the comparisons within 140 real stocks. Application of AMSY to 38 data-poor stocks showed the suitability of the method and led to the first assessments for 23 species. Given the lack of catch data as input, AMSY estimates of exploitation come with wide margins of uncertainty, which may not be suitable for management. However, AMSY seems to be well suited for estimating productivity as well as relative stock size and may, therefore, aid in the management of data-poor stocks. [ABSTRACT FROM AUTHOR]

The International Union for Conservation of Nature's (IUCN) Red List is the global standard for quantifying extinction risk but assessing population reduction (criterion A) of wide‐ranging, long‐lived marine taxa remains difficult and controversial. We show how Bayesian state–space models (BSSM), coupled with expert knowledge at IUCN Red List workshops, can combine regional abundance data into indices of global population change. To illustrate our approach, we provide examples of the process to assess four circumglobal sharks with differing temporal and spatial data‐deficiency: Blue Shark (Prionace glauca), Shortfin Mako (Isurus oxyrinchus), Dusky Shark (Carcharhinus obscurus), and Great Hammerhead (Sphyrna mokarran). For each species, the BSSM provided global population change estimates over three generation lengths bounded by uncertainty levels in intuitive outputs, enabling informed decisions on the status of each species. Integrating similar analyses into future workshops would help conservation practitioners ensure robust, consistent, and transparent Red List assessments for other long‐lived, wide‐ranging species. [ABSTRACT FROM AUTHOR]

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This study presents a new method (LBB) for the analysis of length frequency data from commercial catches. LBB works for species that grow throughout their lives, such as most commercially-important fish and invertebrates, and requires no input in addition to length frequency data. It estimates asymptotic length, length at first capture, relative natural mortality, and relative fishing mortality. Standard fisheries equations can then be used to approximate current exploited biomass relative to unexploited biomass. In addition, these parameters allow the estimation of length at first capture that would maximize catch and biomass for a given fishing effort, and estimation of a proxy for the relative biomass capable of producing maximum sustainable yields. Relative biomass estimates of LBB were not significantly different from the "true" values in simulated data and were similar to independent estimates from full stock assessments. LBB also presents a new indicator for assessing whether an observed size structure is indicative of a healthy stock. LBB results will obviously be misleading if the length frequency data do not represent the size composition of the exploited size range of the stock or if length frequencies resulting from the interplay of growth and mortality are masked by strong recruitment pulses. [ABSTRACT FROM AUTHOR]

This study presents a new, open-source modelling software entitled ‘Just Another Bayesian Biomass Assessment’ (JABBA). JABBA can be used for biomass dynamic stock assessment applications, and has emerged from the development of a Bayesian State-Space Surplus Production Model framework, already applied in stock assessments of sharks, tuna, and billfishes around the world. JABBA presents a unifying, flexible framework for biomass dynamic modelling, runs quickly, and generates reproducible stock status estimates and diagnostic tools. Specific emphasis has been placed on flexibility for specifying alternative scenarios, achieving high stability and improved convergence rates. Default JABBA features include: 1) an integrated state-space tool for averaging and automatically fitting multiple catch per unit effort (CPUE) time series; 2) data-weighting through estimation of additional observation variance for individual or grouped CPUE; 3) selection of Fox, Schaefer, or Pella-Tomlinson production functions; 4) options to fix or estimate process and observation variance components; 5) model diagnostic tools; 6) future projections for alternative catch regimes; and 7) a suite of inbuilt graphics illustrating model fit diagnostics and stock status results. As a case study, JABBA is applied to the 2017 assessment input data for South Atlantic swordfish ( Xiphias gladius ). We envision that JABBA will become a widely used, open-source stock assessment tool, readily improved and modified by the global scientific community. [ABSTRACT FROM AUTHOR]

Divergence in phenotypic traits may arise from the interaction of different evolutionary forces, including different kinds of selection (e.g., ecological), genetic drift, and phenotypic plasticity. Sensory systems play an important role in survival and reproduction, and divergent selection on such systems may result in lineage diversification. Such diversification could be largely influenced by selection in different environments as a result of isolation by environment (IbE). We investigated this process using geographic variation in the resting echolocation frequency of the horseshoe bat species, Rhinolophus damarensis, as a test case. Bats were sampled along a latitudinal gradient ranging from 16°S to 32°S in the arid western half of southern Africa. We measured body size and peak resting frequencies (RF) from handheld individual bats. Three hypotheses for the divergence in RF were tested: (1) James' Rule, (2) IbE, and (3) genetic drift through isolation by distance (IbD) to isolate the effects of body size, local climatic conditions, and geographic distance, respectively, on the resting frequency of R. damarensis. Our results did not support genetic drift because there was no correlation between RF variation and geographic distance. Our results also did not support James' Rule because there was no significant relationship between (1) geographic distances and RF, (2) body size and RF, or (3) body size and climatic variables. Instead, we found support for IbE in the form of a correlation between RF and both region and annual mean temperature, suggesting that RF variation may be the result of environmental discontinuities. The environmental discontinuities coincided with previously reported genetic divergence. Climatic gradients in conjunction with environmental discontinuities could lead to local adaptation in sensory signals and directed dispersal such that gene flow is restricted, allowing lineages to diverge. However, our study cannot exclude the role of processes like phenotypic plasticity in phenotypic variation. [ABSTRACT FROM AUTHOR]

Natural selection and drift can act on populations individually, simultaneously or in tandem and our understanding of phenotypic divergence depends on our ability to recognize the contribution of each. According to the quantitative theory of evolution, if an organism has diversified through neutral evolutionary processes (mutation and drift), variation of phenotypic characteristics between different geographic localities ( B) should be directly proportional to the variation within localities ( W), that is, B ∝ W. Significant deviations from this null model imply that non-neutral forces such as natural selection are acting on a phenotype. We investigated the relative contributions of drift and selection to intraspecific diversity using southern African horseshoe bats as a test case. We characterized phenotypic diversity across the distributional range of Rhinolophus simulator ( n = 101) and Rhinolophus swinnyi ( n = 125) using several traits associated with flight and echolocation. Our results suggest that geographic variation in both species was predominantly caused by disruptive natural selection ( B was not directly proportional to W). Evidence for correlated selection (co-selection) among traits further confirmed that our results were not compatible with drift. Selection rather than drift is likely the predominant evolutionary process shaping intraspecific variation in traits that strongly impact fitness. [ABSTRACT FROM AUTHOR]

This study presents a Monte Carlo method ( CMSY) for estimating fisheries reference points from catch, resilience and qualitative stock status information on data-limited stocks. It also presents a Bayesian state-space implementation of the Schaefer production model ( BSM), fitted to catch and biomass or catch-per-unit-of-effort ( CPUE) data. Special emphasis was given to derive informative priors for productivity, unexploited stock size, catchability and biomass from population dynamics theory. Both models gave good predictions of the maximum intrinsic rate of population increase r, unexploited stock size k and maximum sustainable yield MSY when validated against simulated data with known parameter values. CMSY provided, in addition, reasonable predictions of relative biomass and exploitation rate. Both models were evaluated against 128 real stocks, where estimates of biomass were available from full stock assessments. BSM estimates of r, k and MSY were used as benchmarks for the respective CMSY estimates and were not significantly different in 76% of the stocks. A similar test against 28 data-limited stocks, where CPUE instead of biomass was available, showed that BSM and CMSY estimates of r, k and MSY were not significantly different in 89% of the stocks. Both CMSY and BSM combine the production model with a simple stock-recruitment model, accounting for reduced recruitment at severely depleted stock sizes. [ABSTRACT FROM AUTHOR]

Minimizing the impact of fishing is an explicit goal in international agreements as well as in regional directives and national laws. To assist in practical implementation, three simple rules for fisheries management are proposed in this study: 1) take less than nature by ensuring that mortality caused by fishing is less than the natural rate of mortality; 2) maintain population sizes above half of natural abundance, at levels where populations are still likely to be able to fulfil their ecosystem functions as prey or predator; and 3) let fish grow and reproduce, by adjusting the size at first capture such that the mean length in the catch equals the length where the biomass of an unexploited cohort would be maximum ( Lopt). For rule 3), the basic equations describing growth in age-structured populations are re-examined and a new optimum length for first capture ( Lc_opt) is established. For a given rate of fishing mortality, Lc_opt keeps catch and profit near their theoretical optima while maintaining large population sizes. Application of the three rules would not only minimize the impact of fishing on commercial species, it may also achieve several goals of ecosystem-based fisheries management, such as rebuilding the biomass of prey and predator species in the system and reducing collateral impact of fishing, because with more fish in the water, shorter duration of gear deployment is needed for a given catch. The study also addresses typical criticisms of these common sense rules for fisheries management. [ABSTRACT FROM AUTHOR]

A simulation testing framework was developed to evaluate the efficacy of detecting population trends of two sampling methods used to monitor inshore fish populations: angling and baited remote underwater stereo-video systems (stereo-BRUVs). The study is based on data collected as part of a long-term monitoring program in the Tsitsikamma National Park marine protected area, South Africa. As a test scenario, declining population trajectories of the most abundant species, Chrysoblephus laticeps , were simulated by introducing consecutive years of reduced recruitment over periods of 10 and 20 years applying an age-structured operating model. The operating model was designed to generate method-specific relative abundance indices and length–frequency data, using parameters derived from existing data collected in the long-term monitoring program. These were then fitted with an age-structured estimation model. Estimated spawner-biomass depletion was compared to the ‘true’ simulated population to quantify method-specific accuracy and bias using root-mean-squared error. Due to higher data variability and inherent size selectivity of angling, stereo-BRUVs provided more accurate spawner-biomass trends when describing a distinct population decline over 10 and 20 years. Additionally, spawner-biomass was found to be a more accurate population estimate than relative abundance indices due to the inclusion of population size structure information. The study demonstrates the potential of using simulation testing to evaluate sampling methods, given that the process generates the ‘true’ population with a known abundance and size structure. [ABSTRACT FROM AUTHOR]

The approach to fisheries termed "balanced harvesting" (BH) calls for fishing across the widest possible range of species, stocks, and sizes in an ecosystem, in proportion to their natural productivity, so that the relative size and species composition is maintained. Such fishing is proposed to result in higher catches with less negative impact on exploited populations and ecosystems. This study examines the models and the empirical evidence put forward in support of BH. It finds that the models used unrealistic settings with regard to life history (peak of cohort biomass at small sizes), response to fishing (strong compensation of fishing mortality by reduced natural mortality), and economics (uniform high cost of fishing and same ex-vessel price for all species and sizes), and that empirical evidence of BH is scarce and questionable. It concludes that evolutionary theory, population dynamics theory, ecosystem models with realistic assumptions and settings, and widespread empirical evidence do not support the BH proposal. Rather, this body of evidence suggests that BH will not help but will hinder the policy changes needed for the rebuilding of ecosystems, healthy fish populations, and sustainable fisheries. [ABSTRACT FROM AUTHOR]

Geographic variation can be an indicator of still poorly understood evolutionary processes such as adaptation and drift. Sensory systems used in communication play a key role in mate choice and species recognition. Habitat-mediated (i.e. adaptive) differences in communication signals may therefore lead to diversification. We investigated geographic variation in echolocation calls of African horseshoe bats, Rhinolophus simulator and R. swinnyi in the context of two adaptive hypotheses: 1) James’ Rule and 2) the Sensory Drive Hypothesis. According to James’ Rule body-size should vary in response to relative humidity and temperature so that divergence in call frequency may therefore be the result of climate-mediated variation in body size because of the correlation between body size and call frequency. The Sensory Drive Hypothesis proposes that call frequency is a response to climate-induced differences in atmospheric attenuation and predicts that increases in atmospheric attenuation selects for calls of lower frequency. We measured the morphology and resting call frequency (RF) of 111 R. simulator and 126 R. swinnyi individuals across their distributional range to test the above hypotheses. Contrary to the prediction of James’ Rule, divergence in body size could not explain the variation in RF. Instead, acoustic divergence in RF was best predicted by latitude, geography and climate-induced differences in atmospheric attenuation, as predicted by the Sensory Drive Hypothesis. Although variation in RF was strongly influenced by temperature and humidity, other climatic variables (associated with latitude and altitude) as well as drift (as suggested by a positive correlation between call variation and geographic distance, especially in R. simulator) may also play an important role. [ABSTRACT FROM AUTHOR]

For the first time in South Africa, through a collaborative project of the Elwandle Node of the South African Environmental Observation Network (SAEON), the South African Institute for Aquatic Biodiversity (SAIAB), Rhodes University, the University of Western Australia, and Curtin University (Australia), stereo-BRUVs research on reef fish assemblages is being conducted within the Agulhas Ecoregion from the shallow subtidal area to the edge of the continental shelf. The purpose of this piece is to place in context the necessity of standardised research on the populations of reef fish across the continental shelf of South Africa, to put forward the case for employing stereo-BRUVs in this research, and to introduce the South African marine science community to the research possibilities available with stereo-camera systems [ABSTRACT FROM AUTHOR]

Abstract: The effect of variability in targeting needs to be removed from catch-per-unit-effort (CPUE) data to estimate reliable abundance indices for multispecies fisheries. We test a Generalized Additive Model (GAM) that includes principal component scores (PCs) derived from the species composition in the catch, called the ‘Direct Principal Component’ (DPC) procedure, for its ability to remove the effect of variable targeting. Biomass trends are simulated for two multispecies, multi-habitat fishery scenarios: (i) four species distributed differentially across two habitats and (ii) ten species distributed differentially across four habitats. Tweedie distributed CPUE records are generated from the biomass trends for a fishery with constant targeting (control scenarios) and time-varying targeting (test scenarios). The DPC procedure is simulation-tested for its ability to estimate the underlying biomass trends for all species relative to the non-standardized CPUE index. The DPC procedure proved to be more accurate compared to nominal CPUE trends in the test scenarios. Even in the control scenarios, the DPC procedure offers greater accuracy for the estimated year effect by removing substantial variation from the data, with a small penalty on the accuracy of the underlying abundance trend. However, caution is advised if the DPC-derived index diverges noticeably from alternative models despite no indications for shifts in targeting. A selection procedure based on eigenvalues of the PCs is suitable to identifying the best-performing number of PCs to include in the GAM. The DPC procedure should be applicable for a variety of multispecies fisheries. [Copyright &y& Elsevier]

It has been suggested that the invasive, omnivorous Clarias garipienus is capable of rapid invasions and long-term persistence in recently inhabited freshwater systems. To test this hypothesis, the life history of the established, extralimital Darlington Dam (33°10'31"S, 25°09'13"E) population was investigated. By counting post-fluorescent mark increments on otoliths from 21 chemically tagged wild fish recaptured 244-537 days later, the deposition of growth zones, comprising alternating opaque and translucent bands, was validated as annual. Examination of sectioned otoliths from 175 fish revealed that the oldest fish, two males of 840 and 1074 mm total length (TL), were 25 years old - 10 years older than previously described for any C. gariepinus population. The oldest female was 885 mm TL and 21 years old. Lengthat- age was subsequently described using the von Bertalanffy growth model. Combined-sex growth was best described as Lt = 931.7 ( 1 - exp(-0.15(t +2.43))) mm TL. Total mortality (Z) was calculated using catch curve analysis and the Chapman & Robson estimator to be 0.35/yr. The presence of specimens 15 years and older indicates that these fish established quickly and supports the finding that mortality rates are low, which, in turn, suggests likely long-term population persistence. [ABSTRACT FROM AUTHOR]

Shark attacks on humans are high profile events which can significantly influence policies related to the coastal zone. A shark warning system in South Africa, Shark Spotters, recorded 378 white shark (Carcharodon carcharias) sightings at two popular beaches, Fish Hoek and Muizenberg, during 3690 six-hour long spotting shifts, during the months September to May 2006 to 2011. The probabilities of shark sightings were related to environmental variables using Binomial Generalized Additive Mixed Models (GAMMs). Sea surface temperature was significant, with the probability of shark sightings increasing rapidly as SST exceeded 14°C and approached a maximum at 18°C, whereafter it remains high. An 8 times (Muizenberg) and 5 times (Fish Hoek) greater likelihood of sighting a shark was predicted at 18°C than at 14°C. Lunar phase was also significant with a prediction of 1.5 times (Muizenberg) and 4 times (Fish Hoek) greater likelihood of a shark sighting at new moon than at full moon. At Fish Hoek, the probability of sighting a shark was 1.6 times higher during the afternoon shift compared to the morning shift, but no diel effect was found at Muizenberg. A significant increase in the number of shark sightings was identified over the last three years, highlighting the need for ongoing research into shark attack mitigation. These patterns will be incorporated into shark awareness and bather safety campaigns in Cape Town. [ABSTRACT FROM AUTHOR]

Abstract: Abundance indices are difficult to derive from multispecies catch-per-unit-effort (CPUE) data as these critically rely on the ability to account for targeting behaviour that directs effort towards a particular target species or species-complex. We developed a novel standardization method that uses continuous principal component scores, derived from a Principal Component Analysis of the catch composition data, as non-linear predictor variables for targeted effort within a Generalized Additive Model (GAM) framework. This ‘Direct Principal Component’ method (DPC) is compared to a commonly used standardization approach, in which clusters of fishing tactics are identified from the catch composition and treated as categorical variables. We employed GAMs, which incorporate spatial, seasonal, and fishing power effects, to evaluate the statistical performance of the two alternative sets of covariates. The GAMs were applied to CPUE datasets from the South African hand-line fishery, covering three fishing regions over a period of 26 years, to provide abundance indices for two commercially important species, carpenter, Argyrozona argyrozona and silver kob, Argyrosomus inodorus. Results show that both approaches removed substantial variation from the CPUE data, but that the DPC approach was statistically superior as judged by the AIC, deviance explained and results from 10-fold bootstrap cross-validations. The DPC method represents a more direct approach, is less time-consuming and subjective and therefore considerably easier to implement. We present evidence that the DPC was able to account for substantial shifts in targeting without masking the year effect. The standardized CPUE time series showed positive responses for both species as total landings decreased due to forced effort reductions in 2000. The approach presented here has potentially unlocked useful information for stock assessment in the over two million individual catch records available for the South African hand-line fishery and similar multispecies fisheries. [Copyright &y& Elsevier]

The life history of an endemic riverine African cyprinid, Labeo capensis, that dominates the larger ichthyofauna in a large impoundment in the Orange River Basin four decades after damming, was investigated. Both sexes grew at a similar rate until the onset of maturation, after which male growth and survival rates declined. Male mortality rate was significantly higher than estimated for females explaining both the older ages attained by females (12 years) compared to males (9 years) and a female-dominated adult population. Maturation proceeded faster in males than in females, but was considerably delayed in both age and length. Female reproductive contribution was double that of males despite males maturing a year earlier. Intraspecific life history comparisons with riverine and early impoundment populations suggest that L. capensis has largely maintained its riverine life history characteristics. These characteristics are common in large fishes that are well-adapted to seasonal riverine environments, but often show high vulnerability to damming or overfishing. The absence of a directed fishery and the availability of periodic floodplains that form when marginal vegetation is inundated by either the unregulated inflow of the Orange River or local erratic rains is suggested to have played a vital role for the successful establishment of L. capensis within the impoundment. [ABSTRACT FROM AUTHOR]

The article presents a study which examines the population structure and life history of Cyprinus carpio, an invasive common carp, in a turbid African impoundment measuring 364 square-kilometer. The study uses astericus otoliths in age determination, macroscopic staging of fish gonads, and life history comparisons. The results of the study suggest rapid population growth potential of Cyprinus carpio in the impoundment due to fast growth, early maturity, and high natural mortality rates.

We tested the hypothesis that growth zones in the astericus otoliths of smallmouth yellowfish (Labeobarbus aeneus) and Orange River mudfish (Labeo capensis) were deposited annually. Two methods, fluorochrome marking and edge analysis of otoliths were used. For fluorochrome marking, specimens of both species were injected with 60 mg/kg fish mass oxytetracycline hydrochloride (OTC) and released into large earthen ponds under ambient conditions adjacent to Lake Gariep. Twenty-three L. aeneus and one L. capensis were recaptured 10-14 months later. Edge analysis was based on the optical interpretation of L. aeneus (n = 342) and L. capensis (n = 512) otolith margins collected between November 2006 and May 2008 from Lake Gariep. The frequency distribution of opaque margins over time was fitted using a binomial periodic regression. The estimated cycle length was not significantly different from a hypothesized 12 months for both species. The number of growth zones distal to the OTC mark was consistent with findings from the edge analysis, providing evidence that growth zones in astericus otoliths of both species can be interpreted as annuli. [ABSTRACT FROM AUTHOR]

In a recent publication (Froese et al., ICES Journal of Marine Science; 73: 1640-1650), we presented a critique of the balanced harvesting (BH) approach to fishing. A short section dealt with the size-spectrum models used to justify BH, wherein we pointed out the lack of realism of these models, which mostly represented ecosystems as consisting of a single cannibalistic species. Andersen et al. (ICES Journal of Marine Science; 73: 1651-1655) commented on our paper and suggested that we criticized size-spectrum models in general and that we supposedly made several erroneous statements. We stress that we only referred to the size-spectrum models that we cited, and we respond to each supposedly erroneous statement. We still believe that the size-spectrum models used to justify BH were highly unrealistic and not suitable for evaluating real-world fishing strategies. We agree with Andersen et al. that BH is unlikely to be a useful guiding principle for ecosystem-based fisheries management, for many reasons. The use of unrealistic models is one of them. [ABSTRACT FROM AUTHOR]

• The next generation of stock assessment models should offer a routine diagnostic toolbox. • Cookbook recipes are presented for implementing modern model diagnostics for integrated stock assessment models. • A process of interconnected diagnostic tests is introduced for model development and selection. • The accompanying, new R package 'ss3diags' enables efficient implementation of the presented diagnostics with Stock Synthesis. Integrated analysis has increasingly been the preferred approach for conducting stock assessments and providing the basis for management advice for fish and invertebrate stocks around the world. Many decisions are required when developing integrated stock assessments. For example, the analyst needs to decide whether the model fits the data, if the optimization was successful, if estimates are consistent retrospectively, and if the model is suitable to predict future stock responses to fishing. This study provides practical guidelines for implementing selected diagnostic tools that can assist analysts in identifying problems with model specifications and alternatives that can be explored to minimize or eliminate such problems. Emphasis is placed on reviewing the implementation and interpretation of contemporary model diagnostic tools. We first describe each diagnostic approach and its utility. We then proceed by providing a "cookbook recipe" on how to implement each of the diagnostics, together with an interpretation of the results, using two worked examples of integrated stock assessments with Stock Synthesis. Further, we provide a conceptual flow chart that lays out a generic process of model development and selection using the presented model diagnostics. Based on this, we propose the following four properties as objective criteria for evaluating the plausibility of a model: (1) model convergence, (2) fit to the data, (3) model consistency, and (4) prediction skill. It would greatly benefit the stock assessment community if the next generation of stock assessment models could include the diagnostic tests presented in this study as a set of open source tools. [ABSTRACT FROM AUTHOR]

Catch-only models (COMs) have been the focus of ongoing research into data-poor stock assessment methods. Two of the most recent models that are especially promising are (i) CMSY+, the latest refined version of CMSY that has progressed from Catch-MSY, and (ii) SRA+ (Stock Reduction Analysis Plus), one of the latest developments in the field. Comparing COMs and evaluating their relative performance is essential for determining the state of regional and global fisheries that may be lacking necessary data that would be required to run traditional assessment models. In this paper we interrogate how performance of COMs can be improved by incorporating additional sources of information. We evaluate the performance of COMs on a dataset of 48 data-rich ICES (International Council for the Exploration of Seas) stock assessments. As one measure of performance, we consider the ability of the model to correctly classify stock status using FAO's 3-tier classification that is also used for reporting on sustainable development goals to the UN. Both COMs showed notable bias when run with their inbuilt default heuristics, but as the quality of prior information increased, classification rates for the terminal year improved substantially. We conclude that although further COM refinements show some potential, most promising is the ongoing research into developing biomass or fishing effort priors for COMs in order to be able to reliably track stock status for the majority of the world's fisheries currently lacking stock assessments. [ABSTRACT FROM AUTHOR]