Effective fisheries management instrumental in improving fish stock status.

Marine fish stocks are an important part of the world food system and are particularly important for many of the poorest people of the world. Most existing analyses suggest overfishing is increasing, and there is widespread concern that fish stocks are decreasing throughout most of the world. We assembled trends in abundance and harvest rate of stocks that are scientifically assessed, constituting half of the reported global marine fish catch. For these stocks, on average, abundance is increasing and is at proposed target levels. Compared with regions that are intensively managed, regions with less-developed fisheries management have, on average, 3-fold greater harvest rates and half the abundance as assessed stocks. Available evidence suggests that the regions without assessments of abundance have little fisheries management, and stocks are in poor shape. Increased application of area-appropriate fisheries science recommendations and management tools are still needed for sustaining fisheries in places where they are lacking.

Detecting, classifying, and counting blue whale calls with Siamese neural networks.

The goal of this project is to use acoustic signatures to detect, classify, and count the calls of four acoustic populations of blue whales so that, ultimately, the conservation status of each population can be better assessed. We used manual annotations from 350 h of audio recordings from the underwater hydrophones in the Indian Ocean to build a deep learning model to detect, classify, and count the calls from four acoustic song types. The method we used was Siamese neural networks (SNN), a class of neural network architectures that are used to find the similarity of the inputs by comparing their feature vectors, finding that they outperformed the more widely used convolutional neural networks (CNN). Specifically, the SNN outperform a CNN with 2% accuracy improvement in population classification and 1.7%-6.4% accuracy improvement in call count estimation for each blue whale population. In addition, even though we treat the call count estimation problem as a classification task and encode the number of calls in each spectrogram as a categorical variable, SNN surprisingly learned the ordinal relationship among them. SNN are robust and are shown here to be an effective way to automatically mine large acoustic datasets for blue whale calls.

Black-swan events in animal populations.

Black swans are improbable events that nonetheless occur-often with profound consequences. Such events drive important transitions in social systems (e.g., banking collapses) and physical systems (e.g., earthquakes), and yet it remains unclear the extent to which ecological population numbers buffer or suffer from such extremes. Here, we estimate the prevalence and direction of black-swan events (heavy-tailed process noise) in 609 animal populations after accounting for population dynamics (productivity, density dependence, and typical stochasticity). We find strong evidence for black-swan events in [Formula: see text]4% of populations. These events occur most frequently for birds (7%), mammals (5%), and insects (3%) and are not explained by any life-history covariates but tend to be driven by external perturbations such as climate, severe winters, predators, parasites, or the combined effect of multiple factors. Black-swan events manifest primarily as population die-offs and crashes (86%) rather than unexpected increases, and ignoring heavy-tailed process noise leads to an underestimate in the magnitude of population crashes. We suggest modelers consider heavy-tailed, downward-skewed probability distributions, such as the skewed Student [Formula: see text] used here, when making forecasts of population abundance. Our results demonstrate the importance of both modeling heavy-tailed downward events in populations, and developing conservation strategies that are robust to ecological surprises.

Global fishery prospects under contrasting management regimes.

Data from 4,713 fisheries worldwide, representing 78% of global reported fish catch, are analyzed to estimate the status, trends, and benefits of alternative approaches to recovering depleted fisheries. For each fishery, we estimate current biological status and forecast the impacts of contrasting management regimes on catch, profit, and biomass of fish in the sea. We estimate unique recovery targets and trajectories for each fishery, calculate the year-by-year effects of alternative recovery approaches, and model how alternative institutional reforms affect recovery outcomes. Current status is highly heterogeneous-the median fishery is in poor health (overfished, with further overfishing occurring), although 32% of fisheries are in good biological, although not necessarily economic, condition. Our business-as-usual scenario projects further divergence and continued collapse for many of the world's fisheries. Applying sound management reforms to global fisheries in our dataset could generate annual increases exceeding 16 million metric tons (MMT) in catch, $53 billion in profit, and 619 MMT in biomass relative to business as usual. We also find that, with appropriate reforms, recovery can happen quickly, with the median fishery taking under 10 y to reach recovery targets. Our results show that commonsense reforms to fishery management would dramatically improve overall fish abundance while increasing food security and profits.

The trophic fingerprint of marine fisheries.

Biodiversity indicators provide a vital window on the state of the planet, guiding policy development and management. The most widely adopted marine indicator is mean trophic level (MTL) from catches, intended to detect shifts from high-trophic-level predators to low-trophic-level invertebrates and plankton-feeders. This indicator underpins reported trends in human impacts, declining when predators collapse ("fishing down marine food webs") and when low-trophic-level fisheries expand ("fishing through marine food webs"). The assumption is that catch MTL measures changes in ecosystem MTL and biodiversity. Here we combine model predictions with global assessments of MTL from catches, trawl surveys and fisheries stock assessments and find that catch MTL does not reliably predict changes in marine ecosystems. Instead, catch MTL trends often diverge from ecosystem MTL trends obtained from surveys and assessments. In contrast to previous findings of rapid declines in catch MTL, we observe recent increases in catch, survey and assessment MTL. However, catches from most trophic levels are rising, which can intensify fishery collapses even when MTL trends are stable or increasing. To detect fishing impacts on marine biodiversity, we recommend greater efforts to measure true abundance trends for marine species, especially those most vulnerable to fishing.

Controlled experiment finds no detectable citation bump from Twitter promotion.

Multiple studies across a variety of scientific disciplines have shown that the number of times that a paper is shared on Twitter (now called X) is correlated with the number of citations that paper receives. However, these studies were not designed to answer whether tweeting about scientific papers causes an increase in citations, or whether they were simply highlighting that some papers have higher relevance, importance or quality and are therefore both tweeted about more and cited more. The authors of this study are leading science communicators on Twitter from several life science disciplines, with substantially higher follower counts than the average scientist, making us uniquely placed to address this question. We conducted a three-year-long controlled experiment, randomly selecting five articles published in the same month and journal, and randomly tweeting one while retaining the others as controls. This process was repeated for 10 articles from each of 11 journals, recording Altmetric scores, number of tweets, and citation counts before and after tweeting. Randomization tests revealed that tweeted articles were downloaded 2.6-3.9 times more often than controls immediately after tweeting, and retained significantly higher Altmetric scores (+81%) and number of tweets (+105%) three years after tweeting. However, while some tweeted papers were cited more than their respective control papers published in the same journal and month, the overall increase in citation counts after three years (+7% for Web of Science and +12% for Google Scholar) was not statistically significant (p > 0.15). Therefore while discussing science on social media has many professional and societal benefits (and has been a lot of fun), increasing the citation rate of a scientist's papers is likely not among them.

Global fishery development patterns are driven by profit but not trophic level.

Successful ocean management needs to consider not only fishing impacts but drivers of harvest. Consolidating post-1950 global catch and economic data, we assess which attributes of fisheries are good indicators for fishery development. Surprisingly, year of development and economic value are not correlated with fishery trophic levels. Instead, patterns emerge of profit-driven fishing for attributes related to costs and revenues. Post-1950 fisheries initially developed on shallow ranging species with large catch, high price, and big body size, and then expanded to less desirable species. Revenues expected from developed fisheries declined 95% from 1951 to 1999, and few high catch or valuable fishing opportunities remain. These results highlight the importance of economic attributes of species as leading indicators for harvest-related impacts in ocean ecosystems.

Environmental conditions and marine heatwaves influence blue whale foraging and reproductive effort.

Animal behavior is motivated by the fundamental need to feed and reproduce, and these behaviors can be inferred from spatiotemporal variations in biological signals such as vocalizations. Yet, linking foraging and reproductive effort to environmental drivers can be challenging for wide-ranging predator species. Blue whales are acoustically active marine predators that produce two distinct vocalizations: song and D calls. We examined environmental correlates of these vocalizations using continuous recordings from five hydrophones in the South Taranaki Bight region of Aotearoa New Zealand to investigate call behavior relative to ocean conditions and infer life history patterns. D calls were strongly correlated with oceanographic drivers of upwelling in spring and summer, indicating associations with foraging effort. In contrast, song displayed a highly seasonal pattern with peak intensity in fall, which aligned with the timing of conception inferred from whaling records. Finally, during a marine heatwave, reduced foraging (inferred from D calls) was followed by lower reproductive effort (inferred from song intensity).

Defining trade-offs among conservation, profitability, and food security in the California current bottom-trawl fishery.

Although it is recognized that marine wild-capture fisheries are an important source of food for much of the world, the cost of sustainable capture fisheries to species diversity is uncertain, and it is often questioned whether industrial fisheries can be managed sustainably. We evaluated the trade-off among sustainable food production, profitability, and conservation objectives in the groundfish bottom-trawl fishery off the U.S. West Coast, where depletion (i.e., reduction in abundance) of six rockfish species (Sebastes) is of particular concern. Trade-offs are inherent in this multispecies fishery because there is limited capacity to target species individually. From population models and catch of 34 stocks of bottom fish, we calculated the relation between harvest rate, long-term yield (i.e., total weight of fish caught), profit, and depletion of each species. In our models, annual ecosystem-wide yield from all 34 stocks was maximized with an overall 5.4% harvest rate, but profit was maximized at a 2.8% harvest rate. When we reduced harvest rates to the level (2.2% harvest rate) at which no stocks collapsed (<10% of unfished levels), biomass harvested was 76% of the maximum sustainable yield and profit 89% of maximum. A harvest rate under which no stocks fell below the biomass that produced maximum sustainable yield (1% harvest rate), resulted in 45% of potential yield and 67% of potential profit. Major reductions in catch in the late 1990s led to increase in the biomass of the most depleted stocks, but this rebuilding resulted in the loss of >30% of total sustainable yield, whereas yield lost from stock depletion was 3% of total sustainable yield. There are clear conservation benefits to lower harvest rates, but avoiding overfishing of all stocks in a multispecies fishery carries a substantial cost in terms of lost yield and profit.

Contrasting global trends in marine fishery status obtained from catches and from stock assessments.

There are differences in perception of the status of fisheries around the world that may partly stem from how data on trends in catches over time have been used. On the basis of catch trends, it has been suggested that about 70% of all stocks are overexploited due to unsustainable harvesting and 30% of all stocks have collapsed to <10% of unfished levels. Catch trends also suggest that over time an increasing number of stocks will be overexploited and collapsed. We evaluated how use of catch data affects assessment of fisheries stock status. We analyzed simulated random catch data with no trend. We examined well-studied stocks classified as collapsed on the basis of catch data to determine whether these stocks actually were collapsed. We also used stock assessments to compare stock status derived from catch data with status derived from biomass data. Status of stocks derived from catch trends was almost identical to what one would expect if catches were randomly generated with no trend. Most classifications of collapse assigned on the basis of catch data were due to taxonomic reclassification, regulatory changes in fisheries, and market changes. In our comparison of biomass data with catch trends, catch trends overestimated the percentage of overexploited and collapsed stocks. Although our biomass data were primarily from industrial fisheries in developed countries, the status of these stocks estimated from catch data was similar to the status of stocks in the rest of the world estimated from catch data. We conclude that at present 28-33% of all stocks are overexploited and 7-13% of all stocks are collapsed. Additionally, the proportion of fished stocks that are overexploited or collapsed has been fairly stable in recent years.

Chilean blue whales as a case study to illustrate methods to estimate abundance and evaluate conservation status of rare species.

Often abundance of rare species cannot be estimated with conventional design-based methods, so we illustrate with a population of blue whales (Balaenoptera musculus) a spatial model-based method to estimate abundance. We analyzed data from line-transect surveys of blue whales off the coast of Chile, where the population was hunted to low levels. Field protocols allowed deviation from planned track lines to collect identification photographs and tissue samples for genetic analyses, which resulted in an ad hoc sampling design with increased effort in areas of higher densities. Thus, we used spatial modeling methods to estimate abundance. Spatial models are increasingly being used to analyze data from surveys of marine, aquatic, and terrestrial species, but estimation of uncertainty from such models is often problematic. We developed a new, broadly applicable variance estimator that showed there were likely 303 whales (95% CI 176-625) in the study area. The survey did not span the whales' entire range, so this is a minimum estimate. We estimated current minimum abundance relative to pre-exploitation abundance (i.e., status) with a population dynamics model that incorporated our minimum abundance estimate, likely population growth rates from a meta-analysis of rates of increase in large baleen whales, and two alternative assumptions about historic catches. From this model, we estimated that the population was at a minimum of 16.5% (95% CI 7.3-34.4%) of pre-exploitation levels in 1998 under one catch assumption and 12.4% (CI 5.4-26.3%) of pre-exploitation levels under the other. Thus, although Chilean blue whales are probably still at a small fraction of pre-exploitation abundance, even these minimum abundance estimates demonstrate that their status is better than that of Antarctic blue whales, which are still <1% of pre-exploitation population size. We anticipate our methods will be broadly applicable in aquatic and terrestrial surveys for rarely encountered species, especially when the surveys are intended to maximize encounter rates and estimate abundance.

Early effects of COVID-19 on US fisheries and seafood consumption.

The US seafood sector is susceptible to shocks, both because of the seasonal nature of many of its domestic fisheries and its global position as a top importer and exporter of seafood. However, many data sets that could inform science and policy during an emerging event do not exist or are only released months or years later. Here, we synthesize multiple data sources from across the seafood supply chain, including unconventional real-time data sets, to show the relative initial responses and indicators of recovery during the COVID-19 pandemic. We synthesized news articles from January to September 2020 that reported effects of COVID-19 on the US seafood sector, including processor closures, shortened fishing seasons and loss of revenue. Concerning production and distribution, we assessed past and present landings and trade data and found substantial declines in fresh seafood catches (-40%), imports (-37%) and exports (-43%) relative to the previous year, while frozen seafood products were generally less affected. Google search trends and seafood market foot traffic data suggest consumer demand for seafood from restaurants dropped by upwards of 70% during lockdowns, with recovery varying by state. However, these declines were partially offset by an increase (270%) in delivery and takeout service searches. Our synthesis of open-access data sets and media reports shows widespread, but heterogeneous, ramifications of COVID-19 across the seafood sector, implying that policymakers should focus support on states and sub-sectors most affected by the pandemic: fishery-dependent communities, processors, and fisheries and aquaculture that focus on fresh products.

Shifting headlines? Size trends of newsworthy fishes.

The shifting baseline syndrome describes a gradual lowering of human cognitive baselines, as each generation accepts a lower standard of resource abundance or size as the new norm. There is strong empirical evidence of declining trends of abundance and body sizes of marine fish species reported from docks and markets. We asked whether these widespread trends in shrinking marine fish are detectable in popular English-language media, or whether news writers, like many marine stakeholders, are captive to shifting baselines. We collected 266 English-language news articles, printed between 1869 and 2015, which featured headlines that used a superlative adjective, such as 'giant', 'huge', or 'monster', to describe an individual fish caught. We combined the reported sizes of the captured fish with information on maximum species-specific recorded sizes to reconstruct trends of relative size (reported size divided by maximum size) of newsworthy fishes over time. We found some evidence of a shifting baseline syndrome in news media over the last 140 years: overall, the relative length of the largest fish worthy of a headline has declined over time. This pattern held for charismatic fish species (e.g. basking sharks, whale sharks, giant mantas), which are now reported in the media at smaller relative lengths than they were near the turn of the 20th century, and for the largest species under high risk of extinction. In contrast, there was no similar trend for pelagic gamefish and oceanic sharks, or for species under lower risk of extinction. While landing any individual of the large-bodied 'megafish' may be newsworthy in part because of their large size relative to other fish species, the 'megafish' covered in our dataset were small relative to their own species-on average only 56% of the species-specific maximum length. The continued use in the English-language media of superlatives to describe fish that are now a fraction of the maximum size they could reach, or a fraction of the size they used to be, does reflect a shifting baseline for some species. Given that media outlets are a powerful tool for shaping public perception and awareness of environmental issues, there is a real concern that such stories might be interpreted as meaning that superlatively large fish still abound.

Correction: Eco-Label Conveys Reliable Information on Fish Stock Health to Seafood Consumers.

[This corrects the article DOI: 10.1371/journal.pone.0043765.].

Bayesian stock assessment of Pacific herring in Prince William Sound, Alaska.

The Pacific herring (Clupea pallasii) population in Prince William Sound, Alaska crashed in 1993 and has yet to recover, affecting food web dynamics in the Sound and impacting Alaskan communities. To help researchers design and implement the most effective monitoring, management, and recovery programs, a Bayesian assessment of Prince William Sound herring was developed by reformulating the current model used by the Alaska Department of Fish and Game. The Bayesian model estimated pre-fishery spawning biomass of herring age-3 and older in 2013 to be a median of 19,410 mt (95% credibility interval 12,150-31,740 mt), with a 54% probability that biomass in 2013 was below the management limit used to regulate fisheries in Prince William Sound. The main advantages of the Bayesian model are that it can more objectively weight different datasets and provide estimates of uncertainty for model parameters and outputs, unlike the weighted sum-of-squares used in the original model. In addition, the revised model could be used to manage herring stocks with a decision rule that considers both stock status and the uncertainty in stock status.