Environmental change is occurring at unprecedented rates in many marine ecosystems. Yet, environmental effects on fish populations are commonly assumed to be constant across time. In this study, I ...tested whether relationships between ocean conditions and productivity of North American sockeye salmon (Oncorhynchus nerka) stocks have changed over the past six decades. Specifically, I evaluated the evidence for non‐stationary relationships between three widely used ocean indices and productivity of 45 sockeye salmon stocks using hierarchical Bayesian models. The ocean indices investigated were the Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), and sea surface temperature (SST). I found partial support for time‐varying salmon–ocean relationships. Non‐stationary relationships were strongest for the NPGO and weaker for the SST and PDO indices. Productivity–NPGO correlations tended to shift gradually over time with opposite trends for stocks in British Columbia (B.C.) and western Alaska; for B.C. stocks, the NPGO correlations shifted from significantly negative prior to 1980 to significantly positive after 1990, whereas for western Alaska stocks, the correlations shifted from positive to negative. Productivity–SST correlations showed declining trends for B.C. and Gulf of Alaska stocks, that is, correlations became more negative (B.C.) or less positive (Gulf of Alaska) over time. For the PDO, correlations weakened during the 1980s for western Alaska and B.C. stocks. Overall, these results provide evidence for time‐varying relationships between salmon productivity and environmental conditions over six decades, highlighting the need to recognize that historical responses of salmon populations to environmental change may not be indicative of future responses.
Sockeye salmon (Oncorhynchus nerka) stocks throughout the southern part of their North American range have experienced declines in productivity over the past two decades. In this study, we tested the ...hypothesis that pink (O. gorbuscha) and chum (O. keta) salmon stocks have also experienced recent declines in productivity by investigating temporal and spatial trends in productivity of 99 wild North American pink and chum salmon stocks. We used a combination of population dynamics and time series models to quantify individual stock trends as well as common temporal trends in pink and chum salmon productivity across local, regional, and continental spatial scales. Our results indicated widespread declines in productivity of wild chum salmon stocks throughout Washington (WA) and British Columbia (BC) with 81% of stocks showing recent declines in productivity, although the exact form of the trends varied among regions. For pink salmon, the majority of stocks in WA and BC (65%) did not have strong temporal trends in productivity; however, all stocks that did have trends in productivity showed declining productivity since at least brood year 1996. We found weaker evidence of widespread declines in productivity for Alaska pink and chum salmon, with some regions and stocks showing declines in productivity (e.g., Kodiak chum salmon stocks) and others showing increases (e.g., Alaska Peninsula pink salmon stocks). We also found strong positive covariation between stock productivity series at the regional spatial scale for both pink and chum salmon, along with evidence that this regional-scale positive covariation has become stronger since the early 1990s in WA and BC. In general, our results suggest that common processes operating at the regional or multi-regional spatial scales drive productivity of pink and chum salmon stocks in western North America and that the effects of these process on productivity may change over time.
Abstract
We apply climate attribution techniques to sea surface temperature time series from five regional North Pacific ecosystems to track the growth in human influence on ocean temperatures over ...the past seven decades (1950–2022). Using Bayesian estimates of the Fraction of Attributable Risk (FAR) and Risk Ratio (RR) derived from 23 global climate models, we show that human influence on regional ocean temperatures could first be detected in the 1970s and grew until 2014–2020 temperatures showed overwhelming evidence of human contribution. For the entire North Pacific, FAR and RR values show that temperatures have reached levels that were likely impossible in the preindustrial climate, indicating that the question of attribution is already obsolete at the basin scale. Regional results indicate the strongest evidence for human influence in the northernmost ecosystems (Eastern Bering Sea and Gulf of Alaska), though all regions showed FAR values > 0.98 for at least one year. Extreme regional SST values that were expected every 1000–10 000 years in the preindustrial climate are expected every 5–40 years in the current climate. We use the Gulf of Alaska sockeye salmon fishery to show how attribution time series may be used to contextualize the impacts of human-induced ocean warming on ecosystem services. We link negative warming effects on sockeye fishery catches to increasing human influence on regional temperatures (increasing FAR values), and we find that sockeye salmon migrating to sea in years with the strongest evidence for human effects on temperature (FAR ⩾ 0.98) produce catches 1.4 standard deviations below the long-term log mean. Attribution time series may be helpful indicators for better defining the human role in observed climate change impacts, and may thus help researchers, managers, and stakeholders to better understand and plan for the effects of climate change.
Sustainability-maintaining catches within the historical range of socially and ecologically acceptable values-is key to fisheries success. Climate change may rapidly threaten sustainability, and ...recognizing these instances is important for effective climate adaptation. Here, we present one approach for evaluating changing sustainability under a changing climate. We use Bayesian regression models to compare fish population processes under historical climate norms and emerging anthropogenic extremes. To define anthropogenic extremes we use the Fraction of Attributable Risk (FAR), which estimates the proportion of risk for extreme ocean temperatures that can be attributed to human influence. We illustrate our approach with estimates of recruitment (production of young fish, a key determinant of sustainability) for two exploited fishes (Pacific cod Gadus macrocephalus and walleye pollock G. chalcogrammus) in a rapidly warming ecosystem, the Gulf of Alaska. We show that recruitment distributions for both species have shifted towards zero during anthropogenic climate extremes. Predictions based on the projected incidence of anthropogenic temperature extremes indicate that expected recruitment, and therefore fisheries sustainability, is markedly lower in the current climate than during recent decades. Using FAR to analyze changing population processes may help fisheries managers and stakeholders to recognize situations when historical sustainability expectations should be reevaluated.
Pacific salmon productivity is influenced by ocean conditions and interspecific interactions, yet their combined effects are poorly understood. Using data from 47 North American sockeye salmon ...(Oncorhynchus nerka) populations, we present evidence that the magnitude and direction of climate and competition effects vary over large spatial scales. In the south, a warm ocean and abundant salmon competitors combined to strongly reduce sockeye productivity, whereas in the north, a warm ocean substantially increased productivity and offset the negative effects of competition at sea. From 2005 to 2015, the approximately 82 million adult pink salmon (Oncorhynchus gorbuscha) produced annually from hatcheries were estimated to have reduced the productivity of southern sockeye salmon by ∼15%, on average. In contrast, for sockeye at the northwestern end of their range, the same level of hatchery production was predicted to have reduced the positive effects of a warming ocean by ∼50% (from a ∼10% to a ∼5% increase in productivity, on average). These findings reveal spatially dependent effects of climate and competition on sockeye productivity and highlight the need for international discussions about large-scale hatchery production.
We used changing relationships between primary climate variables and the Pacific Decadal Oscillation (PDO) index to quantify novel climate conditions during rapid warming of the Gulf of Alaska in ...2014–2019. Using Bayesian regression, we show that the PDO had a weaker relationship with North Pacific sea‐level pressure than in previous decades and was associated with warmer regional temperatures, reduced wind mixing, and weaker alongshore transport. Climate conditions mapping onto the PDO during 2014–2019 appear to be unique in the historical record. The potential for surprising ecological responses to novel climates is highlighted by a switch to unique, negative correlations between the PDO and salmon production, contrasting with positive or neutral correlations during previous decades. Novel climates are emerging globally, and tracking changing associations between primary variables and climate indices may be a useful approach for quantifying both the degree of climate novelty and the potential for surprising ecological responses.
Plain Language Summary
Novel climates, or combinations of climate conditions that have not been previously observed in a particular place, can cause surprising outcomes for ecosystem services like fisheries production. We found that during an extreme Gulf of Alaska warming event in 2014–2019, correlations changed between the Pacific Decadal Oscillation index and a variety of climate variables. Compared with previous decades, the Pacific Decadal Oscillation was associated with a weaker Aleutian Low, warmer ocean temperatures, weaker wind‐driven mixing of the ocean, and weaker large‐scale ocean currents. These individual atmosphere and ocean variables are all important to salmon survival, but this particular combination of those variables had never previously been observed. We also found that the Pacific Decadal Oscillation took on a novel, negative correlation with salmon fisheries production, which is markedly different from the neutral or positive correlations seen in earlier decades. Tracking changing relationships between a climate index, primary climate variables, and salmon catches allowed us to measure the degree of novelty in Gulf of Alaska climate and to summarize the impact of novel conditions on an important ecosystem service. This same general approach may be applicable to the problem of understanding novel climates in other ecosystems.
Key Points
Changing relationships between primary climate variables and the PDO index indicate the presence of a novel climate in the Gulf of Alaska
This novel climate had a surprising ecosystem impact, indicated by a change in sign of PDO‐salmon correlations
Tracking changing relationships between primary climate variables and climate indices may be broadly useful for measuring climate novelty
The Pacific cod (Gadus macrocephalus) fishery recently collapsed in the Gulf of Alaska after a series of marine heatwaves that began in 2014. To gauge the likelihood of population recovery following ...these extreme warming events, we investigate potential thermal stress on age-0 cohorts through a comprehensive analysis of juvenile cod abundance, condition, growth, and survival data collected from 15 years of beach seine surveys. Abundance was strongly negatively related to ocean temperature during the egg and larval phase (winter–spring), but age-0 cod were larger in the early summer following warm winter–spring temperatures. Body condition indices suggest that warm summers may improve energetic reserves prior to the first winter; however, there was no summer temperature effect on post-settlement growth or survival. Spatial differences in abundance, condition, or growth were not detected, and density-dependent effects were either weak or positive. While the positive effects of increased summer temperatures on juvenile condition may benefit overwintering survival, they cannot compensate for high pre-settlement mortality from warming winter–spring temperatures. We conclude the critical thermal bottleneck for juvenile abundance occurs pre-settlement.
Environmental conditions can have spatially complex effects on the dynamics of marine fish stocks that change across life-history stages. Yet the potential for non-stationary environmental effects ...across multiple dimensions, e.g. space and ontogeny, are rarely considered. In this study, we examined the evidence for spatial and ontogenetic non-stationary temperature effects on Pacific hake Merluccius productus biomass along the west coast of North America. Specifically, we used Bayesian additive models to estimate the effects of temperature on Pacific hake biomass distribution and whether the effects change across space or life-history stage. We found latitudinal differences in the effects of temperature on mature Pacific hake distribution (i.e. age 3 and older); warmer than average subsurface temperatures were associated with higher biomass north of Vancouver Island, but lower biomass offshore of Washington and southern Vancouver Island. In contrast, immature Pacific hake distribution (i.e. age 2) was better explained by a nonlinear temperature effect; cooler than average temperatures were associated with higher biomass coastwide. Together, our results suggest that Pacific hake distribution is driven by interactions between age composition and environmental conditions and highlight the importance of accounting for varying environmental effects across multiple dimensions.
Projecting the future distributions of commercially and ecologically important species has become a critical approach for ecosystem managers to strategically anticipate change, but large ...uncertainties in projections limit climate adaptation planning. Although distribution projections are primarily used to understand the scope of potential change—rather than accurately predict specific outcomes—it is nonetheless essential to understand where and why projections can give implausible results and to identify which processes contribute to uncertainty. Here, we use a series of simulated species distributions, an ensemble of 252 species distribution models, and an ensemble of three regional ocean climate projections, to isolate the influences of uncertainty from earth system model spread and from ecological modeling. The simulations encompass marine species with different functional traits and ecological preferences to more broadly address resource manager and fishery stakeholder needs, and provide a simulated true state with which to evaluate projections. We present our results relative to the degree of environmental extrapolation from historical conditions, which helps facilitate interpretation by ecological modelers working in diverse systems. We found uncertainty associated with species distribution models can exceed uncertainty generated from diverging earth system models (up to 70% of total uncertainty by 2100), and that this result was consistent across species traits. Species distribution model uncertainty increased through time and was primarily related to the degree to which models extrapolated into novel environmental conditions but moderated by how well models captured the underlying dynamics driving species distributions. The predictive power of simulated species distribution models remained relatively high in the first 30 years of projections, in alignment with the time period in which stakeholders make strategic decisions based on climate information. By understanding sources of uncertainty, and how they change at different forecast horizons, we provide recommendations for projecting species distribution models under global climate change.
Projecting the future distributions of species has become critical for climate adaption planning, but we don't have a precise understanding of how accurate projections can be without waiting decades for validation. Here, we model simulated species responses under climate change to quantify and understand sources of uncertainty, and how they change at different forecast horizons. We provide recommendations for projecting species distribution models under global climate change.
We investigated spatial and temporal components of phytoplankton dynamics in the Northeast Pacific Ocean to better understand the mechanisms linking biological oceanographic conditions to ...productivity of 27 pink salmon (Oncorhynchus gorbuscha) stocks. Specifically, we used spatial covariance functions in combination with multistock spawner–recruit analyses to model relationships among satellite-derived chlorophyll a concentrations, initiation date of the spring phytoplankton bloom, and salmon productivity. For all variables, positive spatial covariation was strongest at the regional scale (0–800 km) with no covariation beyond 1500 km. Spring bloom timing was significantly correlated with salmon productivity for both northern (Alaska) and southern (British Columbia) populations, although the correlations were opposite in sign. An early spring bloom was associated with higher productivity for northern populations and lower productivity for southern populations. Furthermore, the spring bloom initiation date was always a better predictor of salmon productivity than mean chlorophyll a concentration. Our results suggest that changes in spring bloom timing resulting from natural climate variability or anthropogenic climate change could potentially cause latitudinal shifts in salmon productivity.
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