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A central and classic question in ecology is what causes populations to fluctuate in abundance. Understanding the interaction between natural drivers of fluctuating populations and human exploitation is an issue of paramount importance for conservation and natural resource management. Three main hypotheses have been proposed to explain fluctuations: (i) species interactions, such as predator-prey interactions, cause fluctuations, (ii) strongly nonlinear single-species dynamics cause fluctuations, and (iii) environmental variation cause fluctuations. We combine a general fisheries model with data from a global sample of fish species to assess how two of these hypothesis, nonlinear single-species dynamics and environmental variation, interact with human exploitation to affect the variability of fish populations. In contrast with recent analyses that suggest fishing drives increased fluctuations by changing intrinsic nonlinear dynamics, we show that single-species nonlinear dynamics alone, both in the presence and absence of fisheries, are unlikely to drive deterministic fluctuations in fish; nearly all fish populations fall into regions of stable dynamics. However, adding environmental variation dramatically alters the consequences of exploitation on the temporal variability of populations. In a variable environment, (i) the addition of mortality from fishing leads to increased temporal variability for all species examined, (ii) variability in recruitment rates of juveniles contributes substantially more to fluctuations than variation in adult mortality, and (iii) the correlation structure of juvenile and adult vital rates plays an important and underappreciated role in determining population fluctuations. Our results are robust to alternative model formulations and to a range of environmental autocorrelation.

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.

The West Coast of the U.S. has a vast offshore wind energy (OWE) electricity generation potential with value on the order of billions of USD, and pressure is mounting to develop large OWE projects. However, this seascape has numerous existing resource extraction uses, including a multi-billion dollar commercial fishing industry, which create the potential for conflict. To date, spatially explicit comparisons of OWE and commercial fisheries value have not been done, but are essential for marine spatial planning and for investigating the tradeoffs of OWE development on existing marine uses. In this analysis, we generate maps of OWE levelized cost of energy and of total economic activity generated by the top eight commercial fishing targets that account for the vast majority (~84%) of landed revenue off the U.S. West Coast. We quantify spatial overlap between these two ocean uses and use multiobjective optimization to develop tradeoff frontiers to investigate implications for both sectors from established state goals or mandates for OWE power generation capacity. There are clear differences in the exposure of each fishery in their traditional fishing grounds as a function of differing OWE capacity goals and outcomes vary depending on whether OWE development goals are achieved at a state-by-state level or a region-wide level. Responsible siting of OWE projects includes careful consideration of existing commercial fishing activities, and responsible transition to renewable energies on the West Coast and elsewhere accounts for the socio-economic consequences of the total economic activity associated with each fishery.

Identifying the existence and magnitude of density dependence is one of the oldest concerns in ecology. Ecologists have aimed to estimate density dependence in population and community data by fitting a simple autoregressive (Gompertz) model for density dependence to time series of abundance for an entire population. However, it is increasingly recognized that spatial heterogeneity in population densities has implications for population and community dynamics. We therefore adapt the Gompertz model to approximate local densities over continuous space instead of population-wide abundance, and allow productivity to vary spatially using Gaussian random fields. We then show that the conventional (nonspatial) Gompertz model can result in biased estimates of density dependence (e.g., identifying oscillatory dynamics when not present) if densities vary spatially. By contrast, the spatial Gompertz model provides accurate and precise estimates of density dependence for a variety of simulation scenarios and data availabilities. These results are corroborated when comparing spatial and nonspatial models for data from 10 years and ~100 sampling stations for three long-lived rockfishes ( Sebastes spp.) off the California, USA coast. In this case, the nonspatial model estimates implausible oscillatory dynamics on an annual time scale, while the spatial model estimates strong autocorrelation and is supported by model selection tools. We conclude by discussing the importance of improved data archiving techniques, so that spatial models can be used to reexamine classic questions regarding the existence and magnitude of density dependence in wild populations.

Given the rapid rise of environmental DNA (eDNA) surveys in ecology and environmental science, it is important to be able to compare the results of these surveys to traditional methods of measuring biodiversity. Here we compare samples from a traditional method (a manual tow-net) to companion eDNA samples sequenced at three different genetic loci. We find only partial taxonomic overlap among the resulting datasets, with each reflecting a portion of the larger suite of taxa present in the sampled nearshore marine environment. In the larger context of eDNA sequencing surveys, our results suggest that primer amplification bias drives much of the taxonomic bias in eDNA detection, and that the baseline probability of detecting any given taxon with a broad-spectrum primer set is likely to be low. Whether catching fish with different nets or using different PCR primer sets, multiple data types can provide complementary views of a common ecosystem. However, it remains difficult to cross-validate eDNA sequencing techniques in the field, either for presence/absence or for abundance, particularly for primer sets that target very wide taxonomic ranges. Finally, our results highlight the breadth of diversity in a single habitat, and although eDNA does capture a richer sample of the community than traditional methods of sampling, a large number of eDNA primer sets focusing on different subsets of the biota would be necessary to survey any ecological community in a reasonably comprehensive way.

1. 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. 2. 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 multiscale trends and drivers of eelgrass (Zostera spp.) change in an urbanizing estuary. 3. 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. 4. Site trends were spatially asynchronous; adjacent sites sometimes exhibited opposite trends over the same period. Substantial change in eelgrass occurred at the subsite (0-1 km) scale, including both complete local loss and dramatic increase of eelgrass. 5. Metrics of local human development including shoreline armouring, upland development (imperviousness) and human density provide no explanatory power for eelgrass population change at any spatial scale. 6. 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. 7. Synthesis. Despite ongoing conservation concern over seagrasses world-wide, 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.

For over a century, hatchery programs have been used to subsidize natural salmon populations in order to increase fisheries opportunities and, more recently, to conserve declining natural populations. While an extensive literature has described the impacts of large‐scale hatchery operations on freshwater ecosystems, less attention has been given to ecosystem interactions within the marine environment. We analyzed records of hatchery‐released Chinook salmon in the Salish Sea to assess temporal and spatial changes in hatchery practices since 1950, with the goal of identifying potential implications for ecosystem dynamics and conservation efforts in the region. Over the past 65 yr, we found significant changes in the size and time at which juvenile salmon are released, resulting in decreased diversity of these traits. Research suggests that predation on juvenile salmon by other fish, avian, and marine mammal species could be size‐dependent, and our results indicate that current hatchery practices are releasing Chinook salmon in the size range preferred by these predators. With current marine survival rates at chronically low levels, and increasing demand for hatchery subsidies, it is important to consider how modifying existing hatchery programs intended to reduce homogenization may promote more natural marine food web dynamics, with potential benefits to both hatchery and natural Chinook populations.

Despite decades of work in environmental science and ecology, estimating human influences on ecosystems remains challenging. This is partly due to complex chains of causation among ecosystem elements, exacerbated by the difficulty of collecting biological data at sufficient spatial, temporal, and taxonomic scales. Here, we demonstrate the utility of environmental DNA (eDNA) for quantifying associations between human land use and changes in an adjacent ecosystem. We analyze metazoan eDNA sequences from water sampled in nearshore marine eelgrass communities and assess the relationship between these ecological communities and the degree of urbanization in the surrounding watershed. Counter to conventional wisdom, we find strongly increasing richness and decreasing beta diversity with greater urbanization, and similar trends in the diversity of life histories with urbanization. We also find evidence that urbanization influences nearshore communities at local (hundreds of meters) rather than regional (tens of km) scales. Given that different survey methods sample different components of an ecosystem, we then discuss the advantages of eDNA—which we use here to detect hundreds of taxa simultaneously—as a complement to traditional ecological sampling, particularly in the context of broad ecological assessments where exhaustive manual sampling is impractical. Genetic data are a powerful means of uncovering human-ecosystem interactions that might otherwise remain hidden; nevertheless, no sampling method reveals the whole of a biological community.

1. Theory and previous studies have shown that commercial fishers with a diversified catch across multiple species may experience benefits such as increased revenue and reduced variability in revenue. However, fishers can only increase the species diversity of their catch if they own fishing permits that allow multiple species to be targeted, or if they own multiple single-species permits. Individuals holding a single permit can only increase catch diversity within the confines of their permit (e.g. by fishing longer or over a broader spatial area). 2. Using a large dataset of individual salmon fishers in Alaska, we build a Bayesian variance function regression model to understand how diversification impacts revenue and revenue variability, and how these effects have evolved since the 1970s. 3. Applying these models to six salmon fisheries that encompass a broad geographic range and a variety of harvesting methods and species, we find that the majority of these fisheries have experienced reduced catch diversity through time and increasing benefits of specialization on mean individual revenues. 4. One factor that has been hypothesized to reduce catch diversity in salmon fisheries is large-scale hatchery production. While our results suggest negative correlations between hatchery returns and catch diversity for some fisheries, we find little evidence for a change in variability of annual catches associated with increased hatchery production. 5. Synthesis and applications. Despite general trends towards more specialization among commercial fishers in Alaska, and more fishers exclusively targeting salmon, we find that catching fewer species can have positive effects on revenue. With increasing specialization, it is important to understand how individuals buffer against risk, as well as any barriers that prevent diversification. In addition to being affected by environmental variability, fishers are also affected by economic factors including demand and prices offered by processors. Life-history variation in the species targeted may also play a role. Individuals participating in Alaskan fisheries with high contributions of pink salmon — which have the shortest life cycles of all Pacific salmon — also have the highest variability in year-to-year revenue.

Generalist predators can contribute to extinction risk of imperiled prey populations even through incidental predation. Quantifying predation on small populations is important to manage their recovery, however predation is often challenging to observe directly. Recovery of prey tags at predator colonies can indirectly provide minimum estimates of predation, however overall predation rates often remain unquantifiable because an unknown proportion of tags are deposited off-colony. Here, we estimated overall predation rates on threatened wild juvenile steelhead ( Oncorhynchus mykiss ) by generalist adult Western Gulls ( Larus occidentalis ) in six central California (USA) watersheds. We estimated predation rates by gulls from the recapture of PIT (passive integrated transponder) tags that were originally inserted into steelhead and were subsequently deposited at a Western Gull breeding colony, Año Nuevo Island (ANI). We combined three independent datasets to isolate different processes: (1) the probability a tagged steelhead was consumed during predation, (2) the probability a consumed tag was transported to ANI, and (3) the probability a transported tag was detected at ANI. Together, these datasets parameterized a hierarchical Bayesian model to quantify overall predation rates while accounting for tag loss between when prey were tagged and subsequent tag detection at ANI. Results from the model suggest that low recovery rates of PIT tags from steelhead at ANI were mostly driven by low probabilities of transportation (≤0.167) of consumed tags to ANI. Low transportation probabilities equate to high per-capita probabilities of predation (≥0.306/yr) at the three watersheds in closest proximity to ANI, whereas predation rates were uncertain at watersheds farther from ANI due to very low transportation rates. This study provides the first overall estimate of Western Gull predation rates on threatened wild juvenile steelhead and suggests gull predation on salmonids is a larger source of mortality than was previously estimated from minimum predation rates. This study thus represents an important example of high rates of incidental predation by a generalist consumer on an imperiled prey and provides a quantitative framework to inform robust estimates of predation rates on small populations that can be applied to other systems where direct observation of predation is not feasible.