Top-predator recovery abates geomorphic decline of a coastal ecosystem.

The recovery of top predators is thought to have cascading effects on vegetated ecosystems and their geomorphology1,2, but the evidence for this remains correlational and intensely debated3,4. Here we combine observational and experimental data to reveal that recolonization of sea otters in a US estuary generates a trophic cascade that facilitates coastal wetland plant biomass and suppresses the erosion of marsh edges-a process that otherwise leads to the severe loss of habitats and ecosystem services5,6. Monitoring of the Elkhorn Slough estuary over several decades suggested top-down control in the system, because the erosion of salt marsh edges has generally slowed with increasing sea otter abundance, despite the consistently increasing physical stress in the system (that is, nutrient loading, sea-level rise and tidal scour7-9). Predator-exclusion experiments in five marsh creeks revealed that sea otters suppress the abundance of burrowing crabs, a top-down effect that cascades to both increase marsh edge strength and reduce marsh erosion. Multi-creek surveys comparing marsh creeks pre- and post-sea otter colonization confirmed the presence of an interaction between the keystone sea otter, burrowing crabs and marsh creeks, demonstrating the spatial generality of predator control of ecosystem edge processes: densities of burrowing crabs and edge erosion have declined markedly in creeks that have high levels of sea otter recolonization. These results show that trophic downgrading could be a strong but underappreciated contributor to the loss of coastal wetlands, and suggest that restoring top predators can help to re-establish geomorphic stability.

Impact on species' online attention when named after celebrities.

Celebrities can generate substantial attention and influence public interest in species. Using a large-scale examination of publicly available data, we assessed whether species across 6 taxonomic groups received more page views on Wikipedia when the species was named after a celebrity than when it was not. We conducted our analysis for 4 increasingly strict thresholds of how many average daily Wikipedia page views a celebrity had (1, 10, 100, or 1000 views). Overall, we found a high probability (0.96-0.98) that species named after celebrities had more page views than their closest relatives that were not named after celebrities, irrespective of the celebrity threshold. The multiplicative effect on species' page views was larger but more uncertain as celebrity page-view thresholds increased. The range for thresholds of 1 to 1000 was 1.08 (95% credible interval [CI] 1.00-1.18) to 1.76 (95% CI 0.96-2.80), respectively. The hierarchical estimates for the taxa tended to be positive. The strongest effects were for invertebrates, followed by amphibians, reptiles, fish, and mammals, whereas the weakest effect was for birds at lower page-view thresholds. Our results suggest that naming species after celebrities could be particularly significant for those belonging to taxonomic groups that are generally less popular than others (e.g., invertebrates). Celebrities may further influence the effectiveness of this marketing strategy, depending on their likability and connection to the species named after them. Eponyms may serve as a reminder of the disproportionate power dynamics between populations and some namesakes' untenable actions. However, they also provide an opportunity to recognize remarkable individuals and promote equity, inclusivity, and diversity in taxonomic practice. We encourage taxonomists to examine whether naming threatened species after celebrities could affect conservation support, especially for species that are otherwise typically overlooked by the public.

Impacto sobre la atención virtual de una especie si lleva el nombre de una celebridad Resumen Las celebridades pueden generar atención considerable e influir sobre el interés público por las especies. Usamos un análisis a gran escala de datos con disponibilidad pública para evaluar si las especies de seis grupos taxonómicos recibían más visitas en Wikipedia cuando el nombre de la especie provenía del de una celebridad que cuando no. Realizamos nuestro análisis en cuatro umbrales cada vez más estrictos de cuántas visitas diarias en promedio tenía la página de Wikipedia de una celebridad (1, 10, 100 or 1000 visitas). En general, descubrimos una probabilidad alta (0.96­0.98) de que las especies con nombres de celebridades tuvieran más visitas que sus parientes más cercanos que no tenían un nombre así, sin importar el umbral de la celebridad. El efecto multiplicativo sobre las visitas a la página de la especie fue mayor pero más incierto si incrementaba el umbral de visitas de la celebridad. El rango para los umbrales de 1 a 1000 fue de 1.08 (95% intervalo creíble [IC] 1.00­1.18) a 1.76 (95% IC 0.96­2.80) respectivamente. Los estimados jerárquicos para los taxones tuvieron una tendencia positiva. Los efectos más fuertes se presentaron en los invertebrados, seguidos de los anfibios, reptiles, peces y mamíferos, mientras que el efecto más débil fue para las aves en los umbrales de menor número de visitas. Nuestros resultados sugieren que nombrar a una especie con el nombre de una celebridad podría ser particularmente importante para aquellas que pertenecen a grupos taxonómicos que generalmente suelen ser menos populares que otros (invertebrados). Las celebridades podrían influir todavía más en la efectividad de esta estrategia de marketing, dependiendo de su popularidad y la conexión con la especie que lleva su nombre. Los epónimos pueden funcionar como recordatorios de las dinámicas disparejas de poder entre las poblaciones y las acciones indefendibles de algunos homónimos. Sin embargo, los epónimos también proporcionan la oportunidad para reconocer individuos destacados y promover la equidad, inclusividad y diversidad en la práctica taxonómica. Alentamos a que los taxónomos analicen si nombrar a una especie amenazada con el nombre de una celebridad podría afectar el apoyo a su conservación, especialmente para las especies que de otra manera suelen ser ignoradas por el público.

Are we ready to track climate-driven shifts in marine species across international boundaries? - A global survey of scientific bottom trawl data.

Marine biota are redistributing at a rapid pace in response to climate change and shifting seascapes. While changes in fish populations and community structure threaten the sustainability of fisheries, our capacity to adapt by tracking and projecting marine species remains a challenge due to data discontinuities in biological observations, lack of data availability, and mismatch between data and real species distributions. To assess the extent of this challenge, we review the global status and accessibility of ongoing scientific bottom trawl surveys. In total, we gathered metadata for 283,925 samples from 95 surveys conducted regularly from 2001 to 2019. We identified that 59% of the metadata collected are not publicly available, highlighting that the availability of data is the most important challenge to assess species redistributions under global climate change. Given that the primary purpose of surveys is to provide independent data to inform stock assessment of commercially important populations, we further highlight that single surveys do not cover the full range of the main commercial demersal fish species. An average of 18 surveys is needed to cover at least 50% of species ranges, demonstrating the importance of combining multiple surveys to evaluate species range shifts. We assess the potential for combining surveys to track transboundary species redistributions and show that differences in sampling schemes and inconsistency in sampling can be overcome with spatio-temporal modeling to follow species density redistributions. In light of our global assessment, we establish a framework for improving the management and conservation of transboundary and migrating marine demersal species. We provide directions to improve data availability and encourage countries to share survey data, to assess species vulnerabilities, and to support management adaptation in a time of climate-driven ocean changes.

Quantifying the impact of COVID-19 control measures using a Bayesian model of physical distancing.

Extensive non-pharmaceutical and physical distancing measures are currently the primary interventions against coronavirus disease 2019 (COVID-19) worldwide. It is therefore urgent to estimate the impact such measures are having. We introduce a Bayesian epidemiological model in which a proportion of individuals are willing and able to participate in distancing, with the timing of distancing measures informed by survey data on attitudes to distancing and COVID-19. We fit our model to reported COVID-19 cases in British Columbia (BC), Canada, and five other jurisdictions, using an observation model that accounts for both underestimation and the delay between symptom onset and reporting. We estimated the impact that physical distancing (social distancing) has had on the contact rate and examined the projected impact of relaxing distancing measures. We found that, as of April 11 2020, distancing had a strong impact in BC, consistent with declines in reported cases and in hospitalization and intensive care unit numbers; individuals practising physical distancing experienced approximately 0.22 (0.11-0.34 90% CI [credible interval]) of their normal contact rate. The threshold above which prevalence was expected to grow was 0.55. We define the "contact ratio" to be the ratio of the estimated contact rate to the threshold rate at which cases are expected to grow; we estimated this contact ratio to be 0.40 (0.19-0.60) in BC. We developed an R package 'covidseir' to make our model available, and used it to quantify the impact of distancing in five additional jurisdictions. As of May 7, 2020, we estimated that New Zealand was well below its threshold value (contact ratio of 0.22 [0.11-0.34]), New York (0.60 [0.43-0.74]), Washington (0.84 [0.79-0.90]) and Florida (0.86 [0.76-0.96]) were progressively closer to theirs yet still below, but California (1.15 [1.07-1.23]) was above its threshold overall, with cases still rising. Accordingly, we found that BC, New Zealand, and New York may have had more room to relax distancing measures than the other jurisdictions, though this would need to be done cautiously and with total case volumes in mind. Our projections indicate that intermittent distancing measures-if sufficiently strong and robustly followed-could control COVID-19 transmission. This approach provides a useful tool for jurisdictions to monitor and assess current levels of distancing relative to their threshold, which will continue to be essential through subsequent waves of this pandemic.

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.

Benefits and risks of diversification for individual fishers.

Individuals relying on natural resource extraction for their livelihood face high income variability driven by a mix of environmental, biological, management, and economic factors. Key to managing these industries is identifying how regulatory actions and individual behavior affect income variability, financial risk, and, by extension, the economic stability and the sustainable use of natural resources. In commercial fisheries, communities and vessels fishing a greater diversity of species have less revenue variability than those fishing fewer species. However, it is unclear whether these benefits extend to the actions of individual fishers and how year-to-year changes in diversification affect revenue and revenue variability. Here, we evaluate two axes by which fishers in Alaska can diversify fishing activities. We show that, despite increasing specialization over the last 30 years, fishing a set of permits with higher species diversity reduces individual revenue variability, and fishing an additional permit is associated with higher revenue and lower variability. However, increasing species diversity within the constraints of existing permits has a fishery-dependent effect on revenue and is usually (87% probability) associated with increased revenue uncertainty the following year. Our results demonstrate that the most effective option for individuals to decrease revenue variability is to participate in additional or more diverse fisheries. However, this option is expensive, often limited by regulations such as catch share programs, and consequently unavailable to many individuals. With increasing climatic variability, it will be particularly important that individuals relying on natural resources for their livelihood have effective strategies to reduce financial risk.

Black swans in space: modeling spatiotemporal processes with extremes.

In ecological systems, extremes can happen in time, such as population crashes, or in space, such as rapid range contractions. However, current methods for joint inference about temporal and spatial dynamics (e.g., spatiotemporal modeling with Gaussian random fields) may perform poorly when underlying processes include extreme events. Here we introduce a model that allows for extremes to occur simultaneously in time and space. Our model is a Bayesian predictive-process GLMM (generalized linear mixed-effects model) that uses a multivariate-t distribution to describe spatial random effects. The approach is easily implemented with our flexible R package glmmfields. First, using simulated data, we demonstrate the ability to recapture spatiotemporal extremes, and explore the consequences of fitting models that ignore such extremes. Second, we predict tree mortality from mountain pine beetle (Dendroctonus ponderosae) outbreaks in the U.S. Pacific Northwest over the last 16 yr. We show that our approach provides more accurate and precise predictions compared to traditional spatiotemporal models when extremes are present. Our R package makes these models accessible to a wide range of ecologists and scientists in other disciplines interested in fitting spatiotemporal GLMMs, with and without extremes.

Weakened portfolio effects constrain management effectiveness for population aggregates.

Population diversity can reduce temporal variability in aggregate population abundances in a process known as the portfolio effect. Portfolio effects may weaken, however, due to greater synchrony among component populations. While weakened portfolio effects have been previously documented, the consequences of reduced stability on meeting conservation goals for population aggregates that are harvested (e.g., stock aggregates in fisheries) are rarely quantified. Here, we demonstrate how changes in variability within components, synchrony among components, and population productivity interact to influence the probability of achieving an array of management objectives for Fraser River sockeye salmon: a stock aggregate of high economic, ecological, and cultural value. We first present evidence that component variability and synchrony have increased over the last two decades, consistent with a weakening portfolio effect. We then parameterize a stochastic, closed-loop model that simulates the population dynamics of each stock, the fishery that harvests the stock aggregate, and the management framework used to establish mixed-stock exploitation rates. We find that while median aggregate abundance and catch through time were relatively insensitive to greater aggregate variability, catch stability and performance metrics associated with achieving management targets generally declined as component variability and synchrony increased. A notable exception we observed is that harvest control means that scale exploitation rates based on aggregate abundance may be more effective as synchrony increases. Reductions in productivity led to broad declines in performance, but also moderated the impacts of component variability and synchrony on the proportion of component stocks above management targets and catch stability. Our results suggest that even precautionary management strategies that account for declines in productivity may underestimate risk, particularly to socioeconomic objectives, if they fail to consider changes in aggregate variability. Adequately incorporating changes in portfolio effect strength may be particularly relevant when developing recovery strategies that are robust to climate change, which is likely to increase synchrony and component variability.

Unexpected resilience of a seagrass system exposed to global stressors.

Despite a growing interest in identifying tipping points in response to environmental change, our understanding of the ecological mechanisms underlying nonlinear ecosystem dynamics is limited. Ecosystems governed by strong species interactions can provide important insight into how nonlinear relationships between organisms and their environment propagate through ecosystems, and the potential for environmentally mediated species interactions to drive or protect against sudden ecosystem shifts. Here, we experimentally determine the functional relationships (i.e., the shapes of the relationships between predictor and response variables) of a seagrass assemblage with well-defined species interactions to ocean acidification (enrichment of CO2 ) in isolation and in combination with nutrient loading. We demonstrate that the effect of ocean acidification on grazer biomass (Phyllaplysia taylori and Idotea resecata) was quadratic, with the peak of grazer biomass at mid-pH levels. Algal grazing was negatively affected by nutrients, potentially due to low grazer affinity for macroalgae (Ulva intestinalis), as recruitment of both macroalgae and diatoms were favored in elevated nutrient conditions. This led to an exponential increase in macroalgal and epiphyte biomass with ocean acidification, regardless of nutrient concentration. When left unchecked, algae can cause declines in seagrass productivity and persistence through shading and competition. Despite quadratic and exponential functional relationships to stressors that could cause a nonlinear decrease in seagrass biomass, productivity of our model seagrass-the eelgrass (Zostera marina)- remained highly resilient to increasing acidification. These results suggest that important species interactions governing ecosystem dynamics may shift with environmental change, and ecosystem state may be decoupled from ecological responses at lower levels of organization.

The paradox of inverted biomass pyramids in kelp forest fish communities.

Theory predicts that bottom-heavy biomass pyramids or 'stacks' should predominate in real-world communities if trophic-level increases with body size (mean predator-to-prey mass ratio (PPMR) more than 1). However, recent research suggests that inverted biomass pyramids (IBPs) characterize relatively pristine reef fish communities. Here, we estimated the slope of a kelp forest fish community biomass spectrum from underwater visual surveys. The observed biomass spectrum slope is strongly positive, reflecting an IBP. This is incongruous with theory because this steep positive slope would only be expected if trophic position decreased with increasing body size (consumer-to-resource mass ratio, less than 1). We then used δ(15)N signatures of fish muscle tissue to quantify the relationship between trophic position and body size and instead detected strong evidence for the opposite, with PPMR ≈ 1650 (50% credible interval 280-12 000). The natural history of kelp forest reef fishes suggests that this paradox could arise from energetic subsidies in the form of movement of mobile consumers across habitats, and from seasonally pulsed production inputs at small body sizes. There were four to five times more biomass at large body sizes (1-2 kg) than would be expected in a closed steady-state community providing a measure of the magnitude of subsidies.

Marine extinction risk shaped by trait-environment interactions over 500 million years.

Perhaps the most pressing issue in predicting biotic responses to present and future global change is understanding how environmental factors shape the relationship between ecological traits and extinction risk. The fossil record provides millions of years of insight into how extinction selectivity (i.e., differential extinction risk) is shaped by interactions between ecological traits and environmental conditions. Numerous paleontological studies have examined trait-based extinction selectivity; however, the extent to which these patterns are shaped by environmental conditions is poorly understood due to a lack of quantitative synthesis across studies. We conducted a meta-analysis of published studies on fossil marine bivalves and gastropods that span 458 million years to uncover how global environmental and geochemical changes covary with trait-based extinction selectivity. We focused on geographic range size and life habit (i.e., infaunal vs. epifaunal), two of the most important and commonly examined predictors of extinction selectivity. We used geochemical proxies related to global climate, as well as indicators of ocean acidification, to infer average global environmental conditions. Life-habit selectivity is weakly dependent on environmental conditions, with infaunal species relatively buffered from extinction during warmer climate states. In contrast, the odds of taxa with broad geographic ranges surviving an extinction (>2500 km for genera, >500 km for species) are on average three times greater than narrow-ranging taxa (estimate of odds ratio: 2.8, 95% confidence interval = 2.3-3.5), regardless of the prevailing global environmental conditions. The environmental independence of geographic range size extinction selectivity emphasizes the critical role of geographic range size in setting conservation priorities.

Portfolio conservation of metapopulations under climate change.

Climate change is likely to lead to increasing population variability and extinction risk. Theoretically, greater population diversity should buffer against rising climate variability, and this theory is often invoked as a reason for greater conservation. However, this has rarely been quantified. Here we show how a portfolio approach to managing population diversity can inform metapopulation conservation priorities in a changing world. We develop a salmon metapopulation model in which productivity is driven by spatially distributed thermal tolerance and patterns of short- and long-term climate change. We then implement spatial conservation scenarios that control population carrying capacities and evaluate the metapopulation portfolios as a financial manager might: along axes of conservation risk and return. We show that preserving a diversity of thermal tolerances minimizes risk, given environmental stochasticity, and ensures persistence, given long-term environmental change. When the thermal tolerances of populations are unknown, doubling the number of populations conserved may nearly halve expected metapopulation variability. However, this reduction in variability can come at the expense of long-term persistence if climate change increasingly restricts available habitat, forcing ecological managers to balance society's desire for short-term stability and long-term viability. Our findings suggest the importance of conserving the processes that promote thermal-tolerance diversity, such as genetic diversity, habitat heterogeneity, and natural disturbance regimes, and demonstrate that diverse natural portfolios may be critical for metapopulation conservation in the face of increasing climate variability and change.

Top-down and bottom-up forces interact at thermal range extremes on American lobster.

Exploited marine populations are thought to be regulated by the effects of fishing, species interactions and climate. Yet, it is unclear how these forces interact and vary across a species' range. We conducted a meta-analysis of American lobster (Homarus americanus) abundance data throughout the entirety of the species' range, testing competing hypotheses about bottom-up (climate, temperature) vs. top-down (predation, fishing) regulation along a strong thermal gradient. Our results suggest an interaction between predation and thermal range - predation effects dominated at the cold and warm extremes, but not at the centre of the species' range. Similarly, there was consistent support for a positive climate effect on lobster recruitment at warm range extremes. In contrast, fishing effort followed, rather than led changes in lobster abundance over time. Our analysis suggests that the relative effects of top-down and bottom-up forcing in regulating marine populations may intensify at thermal range boundaries and weaken at the core of a species' range.

Climate warming mediates negative impacts of rapid pond drying for three amphibian species.

Anthropogenic climate change will present both opportunities and challenges for pool-breeding amphibians. Increased water temperature and accelerated drying may directly affect larval growth, development, and survival, yet the combined effects of these processes on larvae with future climate change remain poorly understood. Increased surface temperatures are projected to warm water and decrease water inputs, leading to earlier and faster wetland drying. So it is often assumed that larvae will experience negative synergistic impacts with combined warming and drying. However, an alternative hypothesis is that warming-induced increases in metabolic rate and aquatic resource availability might compensate for faster drying rates, generating antagonistic larval responses. We conducted a mesocosm experiment to test the individual and interactive effects of pool permanency (permanent vs. temporary) and water temperature (ambient vs. (+) -3 degrees C) on three anurans with fast-to-slow larval development rates (Great Basin spadefoot [Spea intermontana], Pacific chorus frog [Pseudacris regilla], and northern red-legged frog [Rana aurora]). We found that although tadpoles in warmed pools reached metamorphosis 15-17 days earlier, they did so with little cost (< 2 mm) to size, likely due to greater periphyton growth in warmed pools easing drying-induced resource competition. Warming and drying combined to act antagonistically on early growth (P = 0.06) and survival (P = 0.06), meaning the combined impact was less than the sum of the individual impacts. Warming and drying acted additively on time to and size at metamorphosis. These nonsynergistic impacts may result from cotolerance of larvae to warming and drying, as well as warming helping to offset negative impacts of drying. Our results indicate that combined pool warming and drying may not always be harmful for larval amphibians. However, they also demonstrate that antagonistic responses are difficult to predict, which poses a challenge to proactive conservation and management. Our study highlights the importance of considering the nature of multiple stressor interactions as amphibians are exposed to an increasing number of anthropogenic threats.

Chinook salmon depth distributions on the continental shelf are shaped by interactions between location, season, and individual condition.

BACKGROUND: Ecological and physical conditions vary with depth in aquatic ecosystems, resulting in gradients of habitat suitability. Although variation in vertical distributions among individuals provides evidence of habitat selection, it has been challenging to disentangle how processes at multiple spatio-temporal scales shape behaviour. METHODS: We collected thousands of observations of depth from > 300 acoustically tagged adult Chinook salmon Oncorhynchus tshawytscha, spanning multiple seasons and years. We used these data to parameterize a machine-learning model to disentangle the influence of spatial, temporal, and dynamic oceanographic variables while accounting for differences in individual condition and maturation stage. RESULTS: The top performing machine learning model used bathymetric depth ratio (i.e., individual depth relative to seafloor depth) as a response. We found that bathymetry, season, maturation stage, and spatial location most strongly influenced Chinook salmon depth. Chinook salmon bathymetric depth ratios were deepest in shallow water, during winter, and for immature individuals. We also identified non-linear interactions among covariates, resulting in spatially-varying effects of zooplankton concentration, lunar cycle, temperature and oxygen concentration. CONCLUSIONS: Our results suggest Chinook salmon vertical habitat use is a function of ecological interactions, not physiological constraints. Temporal and spatial variation in depth distributions could be used to guide management decisions intended to reduce fishery impacts on Chinook salmon. More generally, our findings demonstrate how complex interactions among bathymetry, seasonality, location, and life history stage regulate vertical habitat selection.

Species redistribution creates unequal outcomes for multispecies fisheries under projected climate change.

Climate change drives species distribution shifts, affecting the availability of resources people rely upon for food and livelihoods. These impacts are complex, manifest at local scales, and have diverse effects across multiple species. However, for wild capture fisheries, current understanding is dominated by predictions for individual species at coarse spatial scales. We show that species-specific responses to localized environmental changes will alter the collection of co-occurring species within established fishing footprints along the U.S. West Coast. We demonstrate that availability of the most economically valuable, primary target species is highly likely to decline coastwide in response to warming and reduced oxygen concentrations, while availability of the most abundant, secondary target species will potentially increase. A spatial reshuffling of primary and secondary target species suggests regionally heterogeneous opportunities for fishers to adapt by changing where or what they fish. Developing foresight into the collective responses of species at local scales will enable more effective and tangible adaptation pathways for fishing communities.

The shadow model: how and why small choices in spatially explicit species distribution models affect predictions.

The use of species distribution models (SDMs) has rapidly increased over the last decade, driven largely by increasing observational evidence of distributional shifts of terrestrial and aquatic populations. These models permit, for example, the quantification of range shifts, the estimation of species co-occurrence, and the association of habitat to species distribution and abundance. The increasing complexity of contemporary SDMs presents new challenges-as the choices among modeling options increase, it is essential to understand how these choices affect model outcomes. Using a combination of original analysis and literature review, we synthesize the effects of three common model choices in semi-parametric predictive process species distribution modeling: model structure, spatial extent of the data, and spatial scale of predictions. To illustrate the effects of these choices, we develop a case study centered around sablefish (Anoplopoma fimbria) distribution on the west coast of the USA. The three modeling choices represent decisions necessary in virtually all ecological applications of these methods, and are important because the consequences of these choices impact derived quantities of interest (e.g., estimates of population size and their management implications). Truncating the spatial extent of data near the observed range edge, or using a model that is misspecified in terms of covariates and spatial and spatiotemporal fields, led to bias in population biomass trends and mean distribution compared to estimates from models using the full dataset and appropriate model structure. In some cases, these suboptimal modeling decisions may be unavoidable, but understanding the tradeoffs of these choices and impacts on predictions is critical. We illustrate how seemingly small model choices, often made out of necessity or simplicity, can affect scientific advice informing management decisions-potentially leading to erroneous conclusions about changes in abundance or distribution and the precision of such estimates. For example, we show how incorrect decisions could cause overestimation of abundance, which could result in management advice resulting in overfishing. Based on these findings and literature gaps, we outline important frontiers in SDM development.

Quantifying transmissibility of SARS-CoV-2 and impact of intervention within long-term healthcare facilities.

Estimates of the basic reproduction number (R 0) for COVID-19 are particularly variable in the context of transmission within locations such as long-term healthcare (LTHC) facilities. We sought to characterize the heterogeneity of R 0 across known outbreaks within these facilities. We used a unique comprehensive dataset of all outbreaks that occurred within LTHC facilities in British Columbia, Canada as of 21 September 2020. We estimated R 0 in 18 LTHC outbreaks with a novel Bayesian hierarchical dynamic model of susceptible, exposed, infected and recovered individuals, incorporating heterogeneity of R 0 between facilities. We further compared these estimates to those obtained with standard methods that use the exponential growth rate and maximum likelihood. The total size of outbreaks varied dramatically, with range of attack rates 2%-86%. The Bayesian analysis provided an overall estimate of R 0 = 2.51 (90% credible interval 0.47-9.0), with individual facility estimates ranging between 0.56 and 9.17. Uncertainty in these estimates was more constrained than standard methods, particularly for smaller outbreaks informed by the population-level model. We further estimated that intervention led to 61% (52%-69%) of all potential cases being averted within the LTHC facilities, or 75% (68%-79%) when using a model with multi-level intervention effect. Understanding of transmission risks and impact of intervention are essential in planning during the ongoing global pandemic, particularly in high-risk environments such as LTHC facilities.

An integrated model of seasonal changes in stock composition and abundance with an application to Chinook salmon.

Population-specific spatial and temporal distribution data are necessary to identify mechanisms regulating abundance and to manage anthropogenic impacts. However the distributions of highly migratory species are often difficult to resolve, particularly when multiple populations' movements overlap. Here we present an integrated model to estimate spatially-stratified, seasonal trends in abundance and population composition, using data from extensive genetic sampling of commercial and recreational Chinook salmon (Oncorhynchus tshawytscha) fisheries in southern British Columbia. We use the model to estimate seasonal changes in population-specific standardized catch per unit effort (a proxy for abundance) across six marine regions, while accounting for annual variability in sampling effort and uncertain genetic stock assignment. We also share this model as an R package stockseasonr for application to other regions and species. Even at the relatively small spatial scales considered here, we found that patterns in seasonal abundance differed among regions and stocks. While certain locations were clearly migratory corridors, regions within the Salish Sea exhibited diverse, and often weak, seasonal patterns in abundance, emphasizing that they are important, year-round foraging habitats. Furthermore, we found evidence that stocks with similar freshwater life histories and adult run timing, as well as relatively proximate spawning locations, exhibited divergent distributions. Our findings highlight subtle, but important differences in how adult Chinook salmon use marine habitats. Down-scaled model outputs could be used to inform ecosystem-based management efforts by resolving the degree to which salmon overlap with other species of concern, as well as specific fisheries. More broadly, variation in stock-specific abundance among regions indicates efforts to identify mechanisms driving changes in size-at-maturity and natural mortality should account for distinct marine distributions.