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To assess the risk of aerosol transmission of SARS-CoV-2, measurements of the airborne viral concentrations in proximity to infected individuals, the persistence of the virus in aerosols, and the d...

Developing a comprehensive portfolio of theoretically sound indicators is fundamental to effective place-based management of coastal ecosystems at a wide range of scales. We reviewed indicator deve...

Restoration of degraded coastal and estuarine habitats owing to human activities is a major global concern. In Puget Sound, Washington, U.S.A., removal of hard armor from beaches and intertidal zones has become a priority for state and local agencies. However, the effectiveness of these shoreline restoration programs for subtidal habitats and fish is unknown. We surveyed six restoration sites in Puget Sound over 2 years to evaluate associations between shoreline restoration and subtidal fish abundance. We measured the abundance of juvenile salmonids and forage fishes along armored, restored, and reference shorelines. Bayesian generalized linear models showed limited support for associations between shoreline restoration and these fishes in the 3-7 years since armor removal. Pacific herring were more abundant at reference shorelines; the shoreline effect for surf smelt varied by survey site. Shoreline restoration was not an important predictor of salmonid abundance; the best models for Chinook and chum salmon included predictors for survey site and eelgrass, respectively. The retention of survey site in several species' top models reveals the influence of the broader landscape context. We also found seasonal variation in abundance for chum salmon and surf smelt. Our results suggest that juvenile forage fish and salmonids in estuaries likely have unique responses to shoreline features, and that the positive effects of armor removal either do not extend into subtidal areas or are not detectable at local scales. To be most effective, coastal restoration programs should consider broader landscape patterns as well as species-specific habitat needs when prioritizing investments.

Forage fishes are ecologically and economically important in marine ecosystems worldwide and thus are a focal topic for ecosystem-based fisheries management. In the California Current Large Marine Ecosystem (CCLME), the community dynamics of forage populations have been studied at regional spatial scales, but not across regions. To evaluate indicators of the forage community at the ecosystem-wide scale, we examine temporal variability of forage assemblages in Northern (Oregon/Washington), Central (California; Point Reyes to Monterey Bay) and Southern (southern California) regions of the CCLME from 1998 through 2016 which include years with unprecedented climate variability. Forage communities fluctuated greatly between years within each region owing to regionally low abundances of common taxa in at least some years (e.g., rockfishes Sebastes spp. in each region). Comparison of species assemblages among regions indicate that that temporal shifts in assemblage structure were largely synchronous throughout the CCLME. However, dynamics of most individual taxa were out of phase between regions, indicating that different taxa drove the variability in each region. Within regions, taxa with similar adult ecological niches tended to co-vary, suggesting synchronous responses to environmental forcing. Major changes in forage assemblage structure are descriptively linked to large oceanographic perturbations such as the transition from El Nino to La Nina conditions in 1998, anomalous upwelling in 2005, and the onset of a large marine heatwave in fall-winter 2013–2014. Changes in forage assemblage structure are reflected in prey switching in the diet of California sea lions, Zalophus californianus, in the Southern region. The multivariate forage indices that we develop can serve as effective indicators of regional forage community composition shifts in the CCLME and provide managers with context on spatio-temporal changes in the structure of forage fish communities important to top predators in this system.

Estimating a population's growth rate and year‐to‐year variance is a key component of population viability analysis (PVA). However, standard PVA methods require time series of counts obtained using consistent survey methods over many years. In addition, it can be difficult to separate observation and process variance, which is critical for PVA. Time‐series analysis performed with multivariate autoregressive state‐space (MARSS) models is a flexible statistical framework that allows one to address many of these limitations. MARSS models allow one to combine surveys with different gears and across different sites for estimation of PVA parameters, and to implement replication, which reduces the variance‐separation problem and maximizes informational input for mean trend estimation. Even data that are fragmented with unknown error levels can be accommodated. We present a practical case study that illustrates MARSS analysis steps: data choice, model set‐up, model selection, and parameter estimation. Our case study is an analysis of the long‐term trends of rockfish in Puget Sound, Washington, based on citizen science scuba surveys, a fishery‐independent trawl survey, and recreational fishery surveys affected by bag‐limit reductions. The best‐supported models indicated that the recreational and trawl surveys tracked different, temporally independent assemblages that declined at similar rates (an average of −3.8% to −3.9% per year). The scuba survey tracked a separate increasing and temporally independent assemblage (an average of 4.1% per year). Three rockfishes (bocaccio, canary, and yelloweye) are listed in Puget Sound under the US Endangered Species Act (ESA). These species are associated with deep water, which the recreational and trawl surveys sample better than the scuba survey. All three ESA‐listed rockfishes declined as a proportion of recreational catch between the 1970s and 2010s, suggesting that they experienced similar or more severe reductions in abundance than the 3.8–3.9% per year declines that were estimated for rockfish populations sampled by the recreational and trawl surveys.

Coasts and estuaries contain among the most productive and ecologically important habitats in the world and face intense pressure from current and projected human activities, including coastal development. Seagrasses are a key habitat feature in many estuaries perceived to be in widespread decline owing to human actions. We use spatio-temporal models and a 41-year time-series from 100s of km of shoreline which includes over 160,000 observations from Puget Sound, Washington, USA to examine multi-scale trends and drivers of eelgrass (Zostera spp.) change in an urbanizing estuary. At whole estuary scale (100s of km) we find a stable and resilient eelgrass population despite a more than doubling of human population density and multiple major climactic stressors (e.g. ENSO events) over the period. However, the aggregate trend is not reflected at the site scale (10s of km), where some sites persistently increase while others decline. Site trends were spatially asynchronous; adjacent sites sometimes exhibited opposite trends over the same period. Substantial change in eelgrass occurred at the sub-site (0.1 km) scale, including both complete local loss and dramatic increase of eelgrass. Metrics of local human development including shoreline armoring, upland development (imperviousness), and human density provide no explanatory power for eelgrass population change at any spatial scale. Our results suggest that the appropriate scale for understanding eelgrass change is smaller than typically assumed (approximately 1 to 3 km scale) and contrasts strongly with previous work. Synthesis. Despite ongoing conservation concern over seagrasses worldwide, eelgrass in Puget Sound has been highly resilient to both anthropogenic and environmental change over four decades. Our work provides general methods that can be applied to understand spatial and temporal scales of change and can be used to assess hypothesized drivers of change. This article is protected by copyright. All rights reserved.

The complexity of ecosystem-based management (EBM) of natural resources has given rise to research frameworks such as integrated ecosystem assessments (IEA) that pull together large amounts of diverse information from physical, ecological, and social domains. Conceptual models are valuable tools for assimilating and simplifying this information to convey our understanding of ecosystem structure and functioning. Qualitative network models (QNMs) may allow us to conduct dynamic simulations of conceptual models to explore natural–social relationships, compare management strategies, and identify tradeoffs. We used previously developed QNM methods to perform simulations based on conceptual models of the California Current ecosystem's pelagic communities and related human activities and values. Assumptions about community structure and trophic interactions influenced the outcomes of the QNMs. In simulations where we applied unfavorable environmental conditions for production of salmon (Oncorhynchus spp....

Improved understanding and management of social-ecological systems (SES) requires collaboration between biophysical and social scientists; however, issues related to research philosophy and approaches, the nature of data, and language hinder interdisciplinary science. Here, we discuss how we used conceptual models to promote interdisciplinary dialogue in support of integrated ecosystem assessments (IEAs) in the California Current ecosystem. Initial con-ceptualizations of the California Current IEA were based on the Driver-Pressure-State-Impact-Response framework. This initial framing was biophysically centered, with humans primarily incorporated as impacts on the system. We wished to move from a conceptualization that portrayed an antagonistic relationship between humans and nature to one that integrated humans and social systems into the IEA framework. We propose a new conceptualization of the California Current that functions across temporal and spatial scales, captures the diverse relationships...

Despite the significant advances in making monthly or seasonal forecasts of weather, ocean hypoxia, harmful algal blooms and marine pathogens, few such forecasting efforts have extended to the ecology of upper trophic level marine species. Here, we test our ability to use short-term (up to 9 months) predictions of ocean conditions to create a novel forecast of the spatial distribution of Pacific sardine, Sardinops sagax. Predictions of ocean conditions are derived using the output from the Climate Forecast System (CFS) model downscaled through the Regional Ocean Modeling System (ROMS). Using generalized additive models (GAMs), we estimated significant relationships between sardine presence in a test year (2009) and salinity and temperature. The model, fitted to 2009 data, had a moderate skill [area under the curve (AUC) = 0.67] in predicting 2009 sardine distributions, 5–8 months in advance. Preliminary tests indicate that the model also had the skill to predict sardine presence in August 2013 (AUC = 0.85) and August 2014 (AUC = 0.96), 4–5 months in advance. The approach could be used to provide fishery managers with an early warning of distributional shifts of this species, which migrates from the U.S.–Mexico border to as far north as British Columbia, Canada, in summers with warm water and other favorable ocean conditions. We expect seasonal and monthly forecasts of ocean conditions to be broadly useful for predicting spatial distributions of other pelagic and midwater species.

Long-term mechanistic research and monitoring provides integral science support for ecosystem-based management (EBM) of resources, activities and services. Decades of oceanographic and ecological research by Bill Peterson and colleagues along the Newport Hydrographic Line (NH Line) provides essential context for understanding and managing Pacific salmon Oncorhynchus spp. and other marine resources in the California Current ecosystem. This research program helped federal scientists convey the significance of the northeast Pacific marine heatwave (2013–2016) to fisheries managers and stakeholders. Particularly illustrative were shifts in the composition of the copepod community, which reflected feeding conditions for Pacific salmon and other consumers. We identify six traits of the dataset produced by Peterson and colleagues that have made it especially valuable for informing management: (i) it has generated robust ecosystem indicators; (ii) it is long-term; (iii) it is associated with meaningful ecological mechanisms; (iv) it relates to ecosystem components of high societal value; (v) it can represent processes and lags at meaningful temporal scales; and (vi) it is part of a broader, integrative science effort. This research effort underscores the importance of developing and sustaining long-term mechanistic research and monitoring along the U.S. West Coast and elsewhere in the world.

The recovery of predators has the potential to restore ecosystems and fundamentally alter the services they provide. One iconic example of this is keystone predation by sea otters in the Northeast Pacific. Here, we combine spatial time series of sea otter abundance, canopy kelp area, and benthic invertebrate abundance from Washington State, USA, to examine the shifting consequences of sea otter reintroduction for kelp and kelp forest communities. We leverage the spatial variation in sea otter recovery to understand connections between sea otters and the kelp forest community. Sea otter increases created a pronounced decline in sea otter prey—particularly kelp-grazing sea urchins—and led to an expansion of canopy kelps from the late 1980s until roughly 2000. However, while sea otter and kelp population growth rates were positively correlated prior to 2002, this association disappeared over the last two decades. This disconnect occurred despite surveys showing that sea otter prey have continued to decline. Kelp area trends are decoupled from both sea otter and benthic invertebrate abundance at current densities. Variability in kelp abundance has declined in the most recent 15 years, as it has the synchrony in kelp abundance among sites. Together, these findings suggest that initial nearshore community responses to sea otter population expansion follow predictably from trophic cascade theory, but now, other factors may be as or more important in influencing community dynamics. Thus, the utility of sea otter predation in ecosystem restoration must be considered within the context of complex and shifting environmental conditions.

Stable isotopes are used to address a wide range of ecological questions and can help researchers and managers better understand the movement and trophic ecology of sharks. Here, we review how shark studies from the Northeast Pacific Ocean (NEP) have employed stable isotopes to estimate trophic level and diet composition and infer movement and habitat-use patterns. To date, the number of NEP shark studies that have used stable isotopes is limited, suggesting that the approach is underutilized. To aid shark researchers in understanding the strengths and limitations of the approach, we provide a brief overview of carbon and nitrogen stable isotope trophic discrimination properties (e.g., change in δ

Stable isotopes are used to address a wide range of ecological questions and can help researchers and managers better understand the movement and trophic ecology of sharks. Here, we review how shark studies from the Northeast Pacific Ocean (NEP) have employed stable isotopes to estimate trophic level and diet composition and infer movement and habitat-use patterns. To date, the number of NEP shark studies that have used stable isotopes is limited, suggesting that the approach is underutilized. To aid shark researchers in understanding the strengths and limitations of the approach, we provide a brief overview of carbon and nitrogen stable isotope trophic discrimination properties (e.g., change in δ15N between predator and prey), tissue sample preparation methods specific to elasmobranchs, and methodological considerations for the estimation of trophic level and diet composition. We suggest that stable isotopes are a potentially powerful tool for addressing basic questions about shark ecology and are perhaps most valuable when combined and analysed with other data types (e.g., stomach contents, tagging data, or other intrinsic biogeochemical markers).

Nearshore habitats play a vital role in the life cycles of many marine fishes. These habitats are particularly important for Pacific herring Clupea pallasii, which rely on submerged vegetation in the shallow subtidal for spawning habitat and egg incubation. However, little is known about spatial or temporal variation in egg success or how spawning habitat may affect herring early life history. We estimated herring egg loss rates across multiple spawning vegetations in 5 subpopulations of Pacific herring in Puget Sound (USA), an urbanized estuarine system. We found enormous variation in herring egg loss among subpopulations (range of daily loss rates: 5 to 70%) and in egg loss of eggs reared under common garden conditions (range of cumulative loss: 20 to 100%). Egg loss varied by subpopulation but not by spawning vegetation type. Exploratory analyses suggest both wave height and land use patterns may affect hatch success. Using historical survey data, we found that a large proportion of spawning habitat available to Puget Sound herring remains unused each year. Furthermore, we found limited evidence that eggs were deposited dis- proportionally on particular vegetation types; only the non-indigenous brown algae Sargassum mu- ticum was spawned on more than expected by chance. Our results demonstrate that Puget Sound herring are not limited by the amount of available suitable spawning vegetation, and that native vegetation is not preferred over other vegetation types for herring spawning. Rather, it appears that other terrestrial or marine variables are likely determinants of herring egg loss.

In the face of increasing threats to biodiversity, the advancement of methods for surveying biological communities is a major priority for ecologists. Recent advances in molecular biological technologies have made it possible to detect and sequence DNA from environmental samples (environmental DNA or eDNA); however, eDNA techniques have not yet seen widespread adoption as a routine method for biological surveillance primarily due to gaps in our understanding of the dynamics of eDNA in space and time. In order to identify the effective spatial scale of this approach in a dynamic marine environment, we collected marine surface water samples from transects ranging from the intertidal zone to four kilometers from shore. Using PCR primers that target a diverse assemblage of metazoans, we amplified a region of mitochondrial 16S rDNA from the samples and sequenced the products on an Illumina platform in order to detect communities and quantify their spatial patterns using a variety of statistical tools. We find evidence for multiple, discrete eDNA communities in this habitat, and show that these communities decrease in similarity as they become further apart. Offshore communities tend to be richer but less even than those inshore, though diversity was not spatially autocorrelated. Taxon-specific relative abundance coincided with our expectations of spatial distribution in taxa lacking a microscopic, pelagic life-history stage, though most of the taxa detected do not meet these criteria. Finally, we use carefully replicated laboratory procedures to show that laboratory treatments were remarkably similar in most cases, while allowing us to detect a faulty replicate, emphasizing the importance of replication to metabarcoding studies. While there is much work to be done before eDNA techniques can be confidently deployed as a standard method for ecological monitoring, this study serves as a first analysis of diversity at the fine spatial scales relevant to marine ecologists and confirms the promise of eDNA in dynamic environments.

Resource managers at the state, federal, and tribal levels make decisions on a weekly to quarterly basis, and fishers operate on a similar timeframe. To determine the potential of a support tool for these efforts, a seasonal forecast system is experimented with here. JISAO’s Seasonal Coastal Ocean Prediction of the Ecosystem (J-SCOPE) features dynamical downscaling of regional ocean conditions in Washington and Oregon waters using a combination of a high-resolution regional model with biogeochemistry and forecasts from NOAA’s Climate Forecast System (CFS). Model performance and predictability were examined for sea surface temperature (SST), bottom temperature, bottom oxygen, pH, and aragonite saturation state through model hindcasts, reforecast, and forecast comparisons with observations. Results indicate J-SCOPE forecasts have measurable skill on seasonal timescales. Experiments suggest that seasonal forecasting of ocean conditions important for fisheries is possible with the right combination of components. Those components include regional predictability on seasonal timescales of the physical environment from a large-scale model, a high-resolution regional model with biogeochemistry that simulates seasonal conditions in hindcasts, a relationship with local stakeholders, and a real-time observational network. Multiple efforts and approaches in different regions would advance knowledge to provide additional tools to fishers and other stakeholders.

Environmental DNA (eDNA), genetic material recovered from an environmental medium such as soil, water, or feces, reflects the membership of the ecological community present in the sampled environment. As such, eDNA is a potentially rich source of data for basic ecology, conservation, and management, because it offers the prospect of quantitatively reconstructing whole ecological communities from easily obtained samples. However, like all sampling methods, eDNA sequencing is subject to methodological limitations that can generate biased descriptions of ecological communities. Here, we demonstrate parallels between eDNA sampling and traditional sampling techniques, and use these parallels to offer a statistical structure for framing the challenges faced by eDNA and for illuminating the gaps in our current knowledge. Although the current state of knowledge on some of these steps precludes a full estimate of biomass for each taxon in a sampled eDNA community, we provide a map that illustrates potential methods for bridging these gaps. Additionally, we use an original data set to estimate the relative abundances of taxon-specific template DNA prior to PCR, given the abundance of DNA sequences recovered post-PCR-and-sequencing, a critical step in the chain of eDNA inference. While we focus on the use of eDNA samples to determine the relative abundance of taxa within a community, our approach also applies to single-taxon applications (including applications using qPCR), studies of diversity, and studies focused on occurrence. By grounding inferences about eDNA community composition in a rigorous statistical framework, and by making these inferences explicit, we hope to improve the inferential potential for the emerging field of community-level eDNA analysis.

The development of targets is foundational in conservation. Although progress has been made in setting targets, the diverse linkages among ecological and social components make target setting for coupled social-ecological systems extremely challenging. Developing integrated social-ecological targets is difficult because it forces policy makers to consider how management actions propagate throughout social-ecological systems, and because ultimately it is society, not scientists, that defines targets. We developed an interdisciplinary approach for identifying management targets and illustrate this approach using an example motivated by Puget Sound, USA. Our approach blends ecological modeling with empirical social science to articulate trade-offs and reveal societal preferences for different social-ecological states. The framework aims to place information in the hands of decision makers and promote discussion in the appropriate forums. Our ultimate objective is to encourage the informed participation of citizens in the development of social-ecological targets that reflect their values while also protecting key ecosystem attributes.