Predicting organismal response to marine heatwaves using dynamic thermal tolerance landscape models.

Marine heatwaves (MHWs) can cause thermal stress in marine organisms, experienced as extreme 'pulses' against the gradual trend of anthropogenic warming. When thermal stress exceeds organismal capacity to maintain homeostasis, organism survival becomes time-limited and can result in mass mortality events. Current methods of detecting and categorizing MHWs rely on statistical analysis of historic climatology and do not consider biological effects as a basis of MHW severity. The re-emergence of ectotherm thermal tolerance landscape models provides a physiological framework for assessing the lethal effects of MHWs by accounting for both the magnitude and duration of extreme heat events. Here, we used a simulation approach to understand the effects of a suite of MHW profiles on organism survival probability across (1) three thermal tolerance adaptive strategies, (2) interannual temperature variation and (3) seasonal timing of MHWs. We identified survival isoclines across MHW magnitude and duration where acute (short duration-high magnitude) and chronic (long duration-low magnitude) events had equivalent lethal effects on marine organisms. While most research attention has focused on chronic MHW events, we show similar lethal effects can be experienced by more common but neglected acute marine heat spikes. Critically, a statistical definition of MHWs does not accurately categorize biological mortality. By letting organism responses define the extremeness of a MHW event, we can build a mechanistic understanding of MHW effects from a physiological basis. Organism responses can then be transferred across scales of ecological organization and better predict marine ecosystem shifts to MHWs.

The unintended consequences of inconsistent closure policies and mobility restrictions during epidemics.

Background: Controlling the spread of infectious diseases-even when safe, transmission-blocking vaccines are available-may require the effective use of non-pharmaceutical interventions (NPIs), e.g., mask wearing, testing, limits on group sizes, venue closure. During the SARS-CoV-2 pandemic, many countries implemented NPIs inconsistently in space and time. This inconsistency was especially pronounced for policies in the United States of America (US) related to venue closure. Methods: Here, we investigate the impact of inconsistent policies associated with venue closure using mathematical modeling and high-resolution human mobility, Google search, and county-level SARS-CoV-2 incidence data from the USA. Specifically, we look at high-resolution location data and perform a US-county-level analysis of nearly 8 million SARS-CoV-2 cases and 150 million location visits, including 120 million church visitors across 184,677 churches, 14 million grocery visitors across 7662 grocery stores, and 13.5 million gym visitors across 5483 gyms. Results: Analyzing the interaction between venue closure and changing mobility using a mathematical model shows that, across a broad range of model parameters, inconsistent or partial closure can be worse in terms of disease transmission as compared to scenarios with no closures at all. Importantly, changes in mobility patterns due to epidemic control measures can lead to increase in the future number of cases. In the most severe cases, individuals traveling to neighboring jurisdictions with different closure policies can result in an outbreak that would otherwise have been contained. To motivate our mathematical models, we turn to mobility data and find that while stay-at-home orders and closures decreased contacts in most areas of the USA, some specific activities and venues saw an increase in attendance and an increase in the distance visitors traveled to attend. We support this finding using search query data, which clearly shows a shift in information seeking behavior concurrent with the changing mobility patterns. Conclusions: While coarse-grained observations are not sufficient to validate our models, taken together, they highlight the potential unintended consequences of inconsistent epidemic control policies related to venue closure and stress the importance of balancing the societal needs of a population with the risk of an outbreak growing into a large epidemic. Supplementary Information: The online version contains supplementary material available at 10.1186/s44263-023-00028-z.

The direct and indirect effects of a global pandemic on US fishers and seafood workers.

The United States' fishing and seafood industries experienced major shifts in consumer demand and social-distancing restrictions starting in March 2020, when the early stages of the COVID-19 pandemic were unfolding. However, the specific effects on fishers and seafood processors are less well known. Fishermen and seafood workers are potentially at risk during a pandemic given existing tight working quarters, seasonal work, and long hours. To address these concerns, and given a lack of data on the sector, we reviewed news articles, scientific articles, and white papers to assess the various effects of COVID-19 on US seafood workers. Here, we show that most COVID-19 cases among seafood workers occurred during summer 2020 and during the beginning of 2021. These cases were documented across coastal areas, with Alaska experiencing the largest number of cases and outbreaks. Seafood workers were about twice as likely to contract COVID-19 as workers in other parts of the overall US food system. We also documented a number of indirect effects of the pandemic. New social-distancing restrictions and policies limited crew size, resulting in longer hours and more physical taxation. Because of changes in demand and the closure of some processing plants because of COVID-19 outbreaks, economic consequences of the pandemic were a primary concern for fishers and seafood workers, and safety measures allowed for seafood price variation and losses throughout the pandemic. We also highlight a number of inequities in COVID-19 responses within the seafood sector, both along racial and gender lines. All of these conditions point to the diverse direct and indirect effects of the COVID-19 pandemic on fishers and seafood workers. We hope this work sets the foundation for future work on the seafood sector in relation to the COVID-19 pandemic, improving the overall workplace, and collecting systematic social and economic data on workers.

Effects of climate-change-driven gradual and acute temperature changes on shark and ray species.

Climate change is altering distributions and abundances of marine species through both gradual and acute changes in temperature and productivity. Due to their high mobility and metabolic rates, elasmobranchs (sharks and rays) are likely to redistribute across latitudes and depths as they thermoregulate, but little is known about their responses to these climatic changes, which could vary widely across this diverse group of species. Here, we assessed how species with differing mobility and ecology responded to gradual changes in daily sea surface temperature (SST) and acute temperature anomalies, caused by the El Niño-Southern Oscillation (ENSO), at Cocos Island, Costa Rica, the site of multiple marine heatwaves. We used generalized linear mixed models to analyse 34,342 records of relative abundance or frequency of occurrence for seven shark and ray species collected in 27 years (1993-2019) by a dive company. We compared effect sizes for SST and the Oceanic Niño Index across the different species, which vary widely in body size and mobility. Large, mobile species responded strongly but inconsistently to temperature. For scalloped hammerhead sharks Sphyrna lewini, a 1℃ rise in SST reduced counts by over 14%, and dropped the occurrence of their large schools by almost one-fifth (19.4%). Mobula ray occurrence also declined substantially with a few degrees rise in SST, whereas tiger shark Galeocerdo cuvier occurrence sharply increased. These species also had divergent responses to the ENSO: S. lewini and G. cuvier were sighted with greater frequency during La Niña events, and their abundance dropped considerably during El Niño events-over a twofold decline between a strong La Niña and strong El Niño for S. lewini. In contrast, Mobula rays showed little response to ENSO. The smaller and sedentary Triaenodon obesus exhibited the weakest response of all species to both SST and the ENSO, reflecting its lower metabolic rates and mobility. Climate change will continue to impact elasmobranchs, even for smaller and more localized species, with the potential to impact the effectiveness of marine protected areas (MPAs). Our results compel further work on the diversity of elasmobranch responses to environmental change.

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.

State-level variation of initial COVID-19 dynamics in the United States.

During an epidemic, metrics such as R0, doubling time, and case fatality rates are important in understanding and predicting the course of an epidemic. However, if collected over country or regional scales, these metrics hide important smaller-scale, local dynamics. We examine how commonly used epidemiological metrics differ for each individual state within the United States during the initial COVID-19 outbreak. We found that the detected case number and trajectory of early detected cases differ considerably between states. We then test for correlations with testing protocols, interventions and population characteristics. We find that epidemic dynamics were most strongly associated with non-pharmaceutical government actions during the early phase of the epidemic. In particular, early social distancing restrictions, particularly on restaurant operations, was correlated with increased doubling times. Interestingly, we also found that states with little tolerance for deviance from enforced rules saw faster early epidemic growth. Together with other correlates such as population density, our results highlight the different factors involved in the heterogeneity in the early spread of COVID-19 throughout the United States. Although individual states are clearly not independent, they can serve as small, natural experiments in how different demographic patterns and government responses can impact the course of an epidemic.

The unintended consequences of inconsistent pandemic control policies.

Controlling the spread of COVID-19 - even after a licensed vaccine is available - requires the effective use of non-pharmaceutical interventions, e.g., physical distancing, limits on group sizes, mask wearing, etc1-7. To date, such interventions have not been uniformly and/or systematically implemented across the United States of America (US)8. For example, even when under strict stay-at-home orders, numerous jurisdictions in the US granted exceptions and/or were in close proximity to locations with entirely different regulations in place. Here, we investigate the impact of such geographic inconsistencies in epidemic control policies by coupling high-resolution mobility, search, and COVID case data to a mathematical model of SARS-CoV-2 transmission. Our results show that while stay-at-home orders decrease contacts in most areas of the US, some specific activities and venues often see an increase in attendance. As an example, over the month of March 2020, between 10 and 30% of churches in the US saw increases in attendance; even as the total number of visits to churches declined nationally. This heterogeneity, where certain venues see substantial increases in attendance while others close, suggests that closure can cause individuals to find an open venue, even if that requires longer-distance travel. And, indeed, the average distance travelled to churches in the US rose by 13% over the same period, and over the summer, churches with more than 50 average weekly visitors saw an increase of 81% in distance visitors had to travel to attend. Strikingly, our mathematical model reveals that, across a broad range of model parameters, partial measures can often be worse than no measures at all. In the most severe cases, individuals not complying with policies by traveling to neighboring jurisdictions can create epidemics when the outbreak would otherwise have been contained. Indeed, using county-level COVID-19 data, we show that mobility from high-incidence to low-incidence associated with travel for venues like churches, parks, and gyms consistently precedes rising case numbers in the low-incidence counties. Taken together, our data analysis of nearly 120 million church visitors across 184,677 churches, 14 million grocery visitors across 7,662 grocery stores, 13.5 million gym visitors across 5,483 gyms, 7.7 million cases across 3,195 counties, and modeling results highlight the potential unintended consequences of inconsistent epidemic control policies and stress the importance of balancing the societal needs of a population with the risk of an outbreak growing into a large epidemic, and the urgent need for centralized implementation and enforcement of non-pharmaceutical interventions.

Success and failure of ecological management is highly variable in an experimental test.

When managing natural systems, the importance of recognizing the role of uncertainty has been formalized as the precautionary approach. However, it is difficult to determine the role of stochasticity in the success or failure of management because there is almost always no replication; typically, only a single observation exists for a particular site or management strategy. Yet, assessing the role of stochasticity is important for providing a strong foundation for the precautionary approach, and learning from past outcomes is critical for implementing adaptive management of species or ecosystems. In addition, adaptive management relies on being able to implement a variety of strategies in order to learn-an often difficult task in natural systems. Here, we show that there is large, stochastically driven variability in success for management treatments to control an invasive species, particularly for moderate, and more feasible, management strategies. This is exactly where the precautionary approach should be important. Even when combining management strategies, we show that moderate effort in management either fails or is highly variable in its success. This variability allows some management treatments to, on average, meet their target, even when failure is probable. Our study is an important quantitative replicated experimental test of the precautionary approach and can serve as a way to understand the variability in management outcomes in natural systems which have the potential to be more variable than our tightly controlled system.

Site-selection bias and apparent population declines in long-term studies.

Detecting population declines is a critical task for conservation biology. Logistical difficulties and the spatiotemporal variability of populations make estimation of population declines difficult. For statistical reasons, estimates of population decline may be biased when study sites are chosen based on abundance of the focal species. In this situation, apparent population declines are likely to be detected even if there is no decline. This site-selection bias is mentioned in the literature but is not well known. We used simulations and real population data to examine the effects of site-selection biases on inferences about population trends. We used a left-censoring method to detect population-size patterns consistent with site-selection bias. The site-selection bias is an important consideration for conservation biologists, and we offer suggestions for minimizing or mitigating it in study design and analysis. Article impact statement: Estimates of population declines are biased if studies begin in large populations, and time-series data show a signature of such an effect.

Sesgos en la Selección de Sitios y las Declinaciones Poblacionales Aparentes en los Estudios a Largo Plazo Resumen La detección de las declinaciones poblacionales es una tarea muy importante para la biología de la conservación. Las dificultades logísticas y la variabilidad espacio-temporal de las poblaciones complican la estimación de las declinaciones poblacionales. Por razones estadísticas, las estimaciones de las declinaciones poblacionales pueden estar sesgadas cuando se eligen los sitios de estudio con base en la abundancia de la especie focal. En esta situación, las declinaciones poblacionales aparentes probablemente sean detectadas sin que exista dicha declinación. Este sesgo en la selección del sitio está mencionado en la literatura, pero sabe poco sobre él. Usamos simulaciones y datos de poblaciones reales para examinar los efectos que tienen los sesgos en la selección de sitio sobre las inferencias que se tienen sobre las tendencias poblacionales. Usamos un método censurado por la izquierda para detectar los patrones en el tamaño poblacional consistentes con el sesgo en la selección de sitios. Este sesgo es una consideración importante para los biólogos de la conservación y ofrecemos sugerencias para minimizarlo o mitigarlo en el análisis y diseño de los estudios.

The role of spatial structure in the collapse of regional metapopulations.

Many wildlife populations are either naturally, or as a result of human land use, patchily distributed in space. The degree of fragmentation-specifically the remaining patch sizes and habitat configuration-is an important part of population dynamics. Demographic stochasticity is also likely to play an important role in patchy habitats that host small local populations. We develop a simulation model to evaluate the significance of demographic stochasticity and the role fragmentation plays in the determination of population dynamics and the risk of extinction of populations on habitat patches. Our model is formulated as a Markov-chain stochastic process on a finite, spatially explicit array of patches in which probability of successful dispersal is a function of interpatch distance. Unlike past work, we explicitly model local population dynamics and examine how these scale up to the entire population. As a test case, we apply the model to the American pika (Ochotona princeps) population living on the ore dumps in the ghost mining town of Bodie, California. This population has been studied nearly continuously for over four decades and has been of conservation concern as the southern half of the population declined precipitously beginning in 1989. Our model suggests that both the specific configuration of habitat and landscape heterogeneity are necessary and sufficient predictors of the eventual extinction of the southern constellation of patches. This example has important implications, as it suggests that fragmentation alone can lead to regional extinctions within metapopulations.

Shifting elasmobranch community assemblage at Cocos Island--an isolated marine protected area.

Fishing pressure has increased the extinction risk of many elasmobranch (shark and ray) species. Although many countries have established no-take marine reserves, a paucity of monitoring data means it is still unclear if reserves are effectively protecting these species. We examined data collected by a small group of divers over the past 21 years at one of the world's oldest marine protected areas (MPAs), Cocos Island National Park, Costa Rica. We used mixed effects models to determine trends in relative abundance, or probability of occurrence, of 12 monitored elasmobranch species while accounting for variation among observers and from abiotic factors. Eight of 12 species declined significantly over the past 2 decades. We documented decreases in relative abundance for 6 species, including the iconic scalloped hammerhead shark (Sphyrna lewini) (-45%), whitetip reef shark (Triaenodon obesus) (-77%), mobula ray (Mobula spp.) (-78%), and manta ray (Manta birostris) (-89%), and decreases in the probability of occurrence for 2 other species. Several of these species have small home ranges and should be better protected by an MPA, which underscores the notion that declines of marine megafauna will continue unabated in MPAs unless there is adequate enforcement effort to control fishing. In addition, probability of occurrence at Cocos Island of tiger (Galeocerdo cuvier), Galapagos (Carcharhinus galapagensis), blacktip (Carcharhinus limbatus), and whale (Rhincodon typus) sharks increased significantly. The effectiveness of MPAs cannot be evaluated by examining single species because population responses can vary depending on life history traits and vulnerability to fishing pressure.

Modificación del Ensamble de Comunidades de Elasmobranquios en la Isla de Cocos, un Área Marina Protegida Aislada Resumen La presión de la pesca ha incrementado el riesgo de extinción de muchas especies de elasmobranquios (tiburones y rayas). Aunque muchos países han establecido áreas de no-pesca, una escasez de datos de monitoreo implica que todavía no está claro si estas reservas están protegiendo efectivamente a estas especies. Examinamos datos colectados por un pequeño grupo de buzos a lo largo de los últimos 21 años en una de las áreas marinas protegidas (AMP) más vieja del mundo: Parque Nacional Isla de Cocos, Costa Rica. Usamos modelos de efectos mixtos para determinar tendencias en la abundancia relativa, o probabilidad de caso, de doce especies monitoreadas de elasmobranquios compensando la variación entre observadores y de factores abióticos. Ocho de las doce especies declinaron significativamente a lo largo de las últimas dos décadas. Documentamos disminuciones en la abundancia relativa de seis especies, incluidos el tiburón martillo (Sphyrna lewini) (−45%), el tiburón de arrecife de punta blanca (Triaenodon obesus) (−77%), la manta (Mobula spp.) (−78%) y la mantarraya (Manta birostris) (−89%); así como disminuciones en la probabilidad de caso de otras dos especies. Muchas de estas especies tienen extensiones de hábitat pequeñas y deberían estar mejor protegidas por una AMP, lo que enfatiza la noción de que las declinaciones de megafauna marina continuarán sin cesar en las AMP a menos de que exista un esfuerzo adecuado de control de pesca. Además de esto, la probabilidad de ocurrencia en la Isla de Cocos de de los tiburones tigre (Galeocerdo cuvier), de las Galápagos (Carcharhinus galapagensis), de punta negra (Carcharhinus limbatus) y ballena (Rhincodon typus) incrementó significativamente. La efectividad de las AMP no puede ser evaluada examinando a una sola especie porque las respuestas poblacionales pueden variar dependiendo de las características de la historia de vida y de la vulnerabilidad a la presión de la pesca.

Modeling the population dynamics of lemon sharks.

BACKGROUND: Long-lived marine megavertebrates (e.g. sharks, turtles, mammals, and seabirds) are inherently vulnerable to anthropogenic mortality. Although some mathematical models have been applied successfully to manage these animals, more detailed treatments are often needed to assess potential drivers of population dynamics. In particular, factors such as age-structure, density-dependent feedbacks on reproduction, and demographic stochasticity are important for understanding population trends, but are often difficult to assess. Lemon sharks (Negaprion brevirostris) have a pelagic adult phase that makes them logistically difficult to study. However, juveniles use coastal nursery areas where their densities can be high. RESULTS: We use a stage-structured, Markov-chain stochastic model to describe lemon shark population dynamics from a 17-year longitudinal dataset at a coastal nursery area at Bimini, Bahamas. We found that the interaction between delayed breeding, density-dependence, and demographic stochasticity accounts for 33 to 49% of the variance in population size. CONCLUSIONS: Demographic stochasticity contributed all random effects in this model, suggesting that the existence of unmodeled environmental factors may be driving the majority of interannual population fluctuations. In addition, we are able to use our model to estimate the natural mortality rate of older age classes of lemon sharks that are difficult to study. Further, we use our model to examine what effect the length of a time series plays on deciphering ecological patterns. We find that-even with a relatively long time series-our sampling still misses important rare events. Our approach can be used more broadly to infer population dynamics of other large vertebrates in which age structure and demographic stochasticity are important. REVIEWERS: This article was reviewed by Yang Kuang, Christine Jacob, and Ollivier Hyrien.