The collapse of eastern Bering Sea snow crab.

The snow crab is an iconic species in the Bering Sea that supports an economically important fishery and undergoes extensive monitoring and management. Since 2018, more than 10 billion snow crab have disappeared from the eastern Bering Sea, and the population collapsed to historical lows in 2021. We link this collapse to a marine heatwave in the eastern Bering Sea during 2018 and 2019. Calculated caloric requirements, reduced spatial distribution, and observed body conditions suggest that starvation played a role in the collapse. The mortality event appears to be one of the largest reported losses of motile marine macrofauna to marine heatwaves globally.

Non-stationary and interactive effects of climate and competition on pink salmon productivity.

Pacific salmon (Oncorhynchus spp.) are exposed to increased environmental change and multiple human stressors. To anticipate future impacts of global change and to improve sustainable resource management, it is critical to understand how wild salmon populations respond to stressors associated with human-caused changes such as climate warming and ocean acidification, as well as competition in the ocean, which is intensified by the large-scale production and release of hatchery reared salmon. Pink salmon (O. gorbuscha) are a keystone species in the North Pacific Ocean and support highly valuable commercial fisheries. We investigated the joint effects of changes in ocean conditions and salmon abundances on the productivity of wild pink salmon. Our analysis focused on Prince William Sound in Alaska, because the region accounts for ~50% of the global production of hatchery pink salmon with local hatcheries releasing 600-700 million pink salmon fry annually. Using 60 years of data on wild pink salmon abundances, hatchery releases, and ecological conditions in the ocean, we find evidence that hatchery pink salmon releases negatively affect wild pink salmon productivity, likely through competition between wild and hatchery juveniles in nearshore marine habitats. We find no evidence for effects of ocean acidification on pink salmon productivity. However, a change in the leading mode of North Pacific climate in 1988-1989 weakened the temperature-productivity relationship and altered the strength of intraspecific density dependence. Therefore, our results suggest non-stationary (i.e., time varying) and interactive effects of ocean climate and competition on pink salmon productivity. Our findings further highlight the need for salmon management to consider potential adverse effects of large-scale hatchery production within the context of ocean change.

Using a climate attribution statistic to inform judgments about changing fisheries sustainability.

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.

Empirical orthogonal function regression: Linking population biology to spatial varying environmental conditions using climate projections.

Ecologists and oceanographers inform population and ecosystem management by identifying the physical drivers of ecological dynamics. However, different research communities use different analytical tools where, for example, physical oceanographers often apply rank-reduction techniques (a.k.a. empirical orthogonal functions [EOF]) to identify indicators that represent dominant modes of physical variability, whereas population ecologists use dynamical models that incorporate physical indicators as covariates. Simultaneously modeling physical and biological processes would have several benefits, including improved communication across sub-fields; more efficient use of limited data; and the ability to compare importance of physical and biological drivers for population dynamics. Here, we develop a new statistical technique, EOF regression, which jointly models population-scale dynamics and spatially distributed physical dynamics. EOF regression is fitted using maximum-likelihood techniques and applies a generalized EOF analysis to environmental measurements, estimates one or more time series representing modes of environmental variability, and simultaneously estimates the association of this time series with biological measurements. By doing so, it identifies a spatial map of environmental conditions that are best correlated with annual variability in the biological process. We demonstrate this method using a linear (Ricker) model for early-life survival ("recruitment") of three groundfish species in the eastern Bering Sea from 1982 to 2016, combined with measurements and end-of-century projections for bottom and sea surface temperature. Results suggest that (a) we can forecast biological dynamics while applying delta-correction and statistical downscaling to calibrate measurements and projected physical variables, (b) physical drivers are statistically significant for Pacific cod and walleye pollock recruitment, (c) separately analyzing physical and biological variables fails to identify the significant association for walleye pollock, and (d) cod and pollock will likely have reduced recruitment given forecasted temperatures over future decades.

The changing physical and ecological meanings of North Pacific Ocean climate indices.

Climate change is likely to change the relationships between commonly used climate indices and underlying patterns of climate variability, but this complexity is rarely considered in studies using climate indices. Here, we show that the physical and ecological conditions mapping onto the Pacific Decadal Oscillation (PDO) index and North Pacific Gyre Oscillation (NPGO) index have changed over multidecadal timescales. These changes apparently began around a 1988/1989 North Pacific climate shift that was marked by abrupt northeast Pacific warming, declining temporal variance in the Aleutian Low (a leading atmospheric driver of the PDO), and increasing correlation between the PDO and NPGO patterns. Sea level pressure and surface temperature patterns associated with each climate index changed after 1988/1989, indicating that identical index values reflect different states of basin-scale climate over time. The PDO and NPGO also show time-dependent skill as indices of regional northeast Pacific ecosystem variability. Since the late 1980s, both indices have become less relevant to physical-ecological variability in regional ecosystems from the Bering Sea to the southern California Current. Users of these climate indices should be aware of nonstationary relationships with underlying climate variability within the historical record, and the potential for further nonstationarity with ongoing climate change.

Nonstationary environmental and community relationships in the North Pacific Ocean.

Common approaches for summarizing multivariate environmental or community data assume that relationships among variables are stationary over time, and this assumption is often not tested. Here we test the hypothesis that relationships among environmental and community time series are nonstationary in the Gulf of Alaska ecosystem (North Pacific Ocean) over multidecadal time scales. Dynamic factor analysis (DFA) is applied to environmental and community data from before and after 1988/1989, corresponding to the timing of an abrupt decline in temporal variance of the Aleutian Low atmospheric pattern, a leading driver of Gulf of Alaska climate. Results show that covariance among local atmosphere and ocean environmental variables weakened simultaneous to the decline in Aleutian Low variance. At the same time, community-wide responses of 14 fish and crustacean populations to physical forcing weakened, as indicated by nonstationary environment-biology regression coefficients. In line with theoretical predictions, this loss of a shared response to environmental variability was accompanied by weakening community covariance. Individual populations also showed nonstationary relationships with shared trends of community variability. We conclude that assumptions of fixed environmental and community relationships are likely to produce mistaken inference in this ecosystem. Similar concerns may apply in other ecosystems subject to changing climate patterns.

Non-stationary climate-salmon relationships in the Gulf of Alaska.

Studies of climate effects on ecology often account for non-stationarity in individual physical and biological variables, but rarely allow for non-stationary relationships among variables. Here, we show that non-stationary relationships among physical and biological variables are central to understanding climate effects on salmon (Onchorynchus spp.) in the Gulf of Alaska during 1965-2012. The relative importance of two leading patterns in North Pacific climate, the Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO), changed around 1988/1989 as reflected by changing correlations with leading axes of sea surface temperature variability. Simultaneously, relationships between the PDO and Gulf of Alaska environmental variables weakened, and long-standing temperature-salmon and PDO-salmon covariance declined to zero. We propose a mechanistic explanation for changing climate-salmon relationships in terms of non-stationary atmosphere-ocean interactions coinciding with changing PDO-NPGO relative importance. We also show that regression models assuming stationary climate-salmon relationships are inappropriate over the multidecadal time scale we consider. Relaxing assumptions of stationary relationships markedly improved modelling of climate effects on salmon catches and productivity. Attempts to understand the implications of changing climate patterns in other ecosystems might also be aided by the application of models that allow associations among environmental and biological variables to change over time.

Correction: Evaluating signals of oil spill impacts, climate, and species interactions in Pacific herring and Pacific salmon populations in Prince William Sound and Copper River, Alaska.

[This corrects the article DOI: 10.1371/journal.pone.0172898.].

Evaluating signals of oil spill impacts, climate, and species interactions in Pacific herring and Pacific salmon populations in Prince William Sound and Copper River, Alaska.

The Exxon Valdez oil spill occurred in March 1989 in Prince William Sound, Alaska, and was one of the worst environmental disasters on record in the United States. Despite long-term data collection over the nearly three decades since the spill, tremendous uncertainty remains as to how significantly the spill affected fishery resources. Pacific herring (Clupea pallasii) and some wild Pacific salmon populations (Oncorhynchus spp.) in Prince William Sound declined in the early 1990s, and have not returned to the population sizes observed in the 1980s. Discerning if, or how much of, this decline resulted from the oil spill has been difficult because a number of other physical and ecological drivers are confounded temporally with the spill; some of these drivers include environmental variability or changing climate regimes, increased production of hatchery salmon in the region, and increases in populations of potential predators. Using data pre- and post-spill, we applied time-series methods to evaluate support for whether and how herring and salmon productivity has been affected by each of five drivers: (1) density dependence, (2) the EVOS event, (3) changing environmental conditions, (4) interspecific competition on juvenile fish, and (5) predation and competition from adult fish or, in the case of herring, humpback whales. Our results showed support for intraspecific density-dependent effects in herring, sockeye, and Chinook salmon, with little overall support for an oil spill effect. Of the salmon species, the largest driver was the negative impact of adult pink salmon returns on sockeye salmon productivity. Herring productivity was most strongly affected by changing environmental conditions; specifically, freshwater discharge into the Gulf of Alaska was linked to a series of recruitment failures-before, during, and after EVOS. These results highlight the need to better understand long terms impacts of pink salmon on food webs, as well as the interactions between nearshore species and freshwater inputs, particularly as they relate to climate change and increasing water temperatures.

Reassessing regime shifts in the North Pacific: incremental climate change and commercial fishing are necessary for explaining decadal-scale biological variability.

In areas of the North Pacific that are largely free of overfishing, climate regime shifts - abrupt changes in modes of low-frequency climate variability - are seen as the dominant drivers of decadal-scale ecological variability. We assessed the ability of leading modes of climate variability [Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO), Arctic Oscillation (AO), Pacific-North American Pattern (PNA), North Pacific Index (NPI), El Niño-Southern Oscillation (ENSO)] to explain decadal-scale (1965-2008) patterns of climatic and biological variability across two North Pacific ecosystems (Gulf of Alaska and Bering Sea). Our response variables were the first principle component (PC1) of four regional climate parameters [sea surface temperature (SST), sea level pressure (SLP), freshwater input, ice cover], and PCs 1-2 of 36 biological time series [production or abundance for populations of salmon (Oncorhynchus spp.), groundfish, herring (Clupea pallasii), shrimp, and jellyfish]. We found that the climate modes alone could not explain ecological variability in the study region. Both linear models (for climate PC1) and generalized additive models (for biology PC1-2) invoking only the climate modes produced residuals with significant temporal trends, indicating that the models failed to capture coherent patterns of ecological variability. However, when the residual climate trend and a time series of commercial fishery catches were used as additional candidate variables, resulting models of biology PC1-2 satisfied assumptions of independent residuals and out-performed models constructed from the climate modes alone in terms of predictive power. As measured by effect size and Akaike weights, the residual climate trend was the most important variable for explaining biology PC1 variability, and commercial catch the most important variable for biology PC2. Patterns of climate sensitivity and exploitation history for taxa strongly associated with biology PC1-2 suggest plausible mechanistic explanations for these modeling results. Our findings suggest that, even in the absence of overfishing and in areas strongly influenced by internal climate variability, climate regime shift effects can only be understood in the context of other ecosystem perturbations.

Rising catch variability preceded historical fisheries collapses in Alaska.

Statistical indicators such as rising variance and rising skewness in key system parameters may provide early warning of "regime shifts" in communities and populations. However, the utility of these indicators has rarely been tested in the large, complex ecosystems that are of most interest to managers. Crustacean fisheries in the Gulf of Alaska and Bering Sea experienced a series of collapses beginning in the 1970s, and we used spatially resolved catch data from these fisheries to test the predictions that increasing variability and skewness would precede stock collapse. Our data set consisted of catch data from 14 fisheries (12 collapsing and two non-collapsing), spanning 278 cumulative years. Our sampling unit for analysis was the Alaska Department of Fish and Game statistical reporting area (mean n for individual fisheries = 42 areas, range 7-81). We found that spatial variability in catches increased prior to stock collapse: a random-effects model estimating trend in variability across all 12 collapsing fisheries showed strong evidence of increasing variability prior to collapse. Individual trends in variability were statistically significant for only four of the 12 collapsing fisheries, suggesting that rising variability might be most effective as an indicator when information from multiple populations is available. Analyzing data across multiple fisheries allowed us to detect increasing variability 1-4 years prior to collapse, and trends in variability were significantly different for collapsing and non-collapsing fisheries. In spite of theoretical expectations, we found no evidence of pre-collapse increases in catch skewness. Further, while models generally predict that rising variability should be a transient phenomenon around collapse points, increased variability was a persistent feature of collapsed fisheries in our study. We conclude that this result is more consistent with fishing effects as the cause of increased catch variability, rather than the critical slowing down that is the driver of increased variability in regime shift models. While our results support the use of rising spatial variability as a leading indicator of regime shifts, the failure of our data to support other model-derived predictions underscores the need for empirical validation before these indicators can be used with confidence by ecosystem managers.

Increased spatial variance accompanies reorganization of two continental shelf ecosystems.

Phase transitions between alternate stable states in marine ecosystems lead to disruptive changes in ecosystem services, especially fisheries productivity. We used trawl survey data spanning phase transitions in the North Pacific (Gulf of Alaska) and the North Atlantic (Scotian Shelf) to test for increases in ecosystem variability that might provide early warning of such transitions. In both time series, elevated spatial variability in a measure of community composition (ratio of cod [Gadus sp.] abundance to prey abundance) accompanied transitions between ecosystem states, and variability was negatively correlated with distance from the ecosystem transition point. In the Gulf of Alaska, where the phase transition was apparently the result of a sudden perturbation (climate regime shift), variance increased one year before the transition in mean state occurred. On the Scotian Shelf, where ecosystem reorganization was the result of persistent overfishing, a significant increase in variance occurred three years before the transition in mean state was detected. However, we could not reject the alternate explanation that increased variance may also have simply been inherent to the final stable state in that ecosystem. Increased variance has been previously observed around transition points in models, but rarely in real ecosystems, and our results demonstrate the possible management value in tracking the variance of key parameters in exploited ecosystems.

Sea ice retreat alters the biogeography of the Bering Sea continental shelf.

Seasonal ice cover creates a pool of cold bottom water on the eastern Bering Sea continental shelf each winter. The southern edge of this cold pool, which defines the ecotone between arctic and subarctic communities, has retreated approximately 230 km northward since the early 1980s. Bottom trawl surveys of fish and invertebrates in the southeastern Bering Sea (1982-2006) show a coincident reorganization in community composition by latitude. Survey catches show community-wide northward distribution shifts, and the area formerly covered by the cold pool has seen increases in total biomass, species richness, and average trophic level as subarctic fauna have colonized newly favorable habitats. Warming climate has immediate management implications, as 57% of variability in commercial snow crab (Chionoecetes opilio) catch is explained by winter sea ice extent. Several measures of community distribution and structure show linear relationships with bottom temperature, suggesting warming climate as the primary cause of changing biogeography. However, residual variability in distribution not explained by climate shows a strong temporal trend, suggesting that internal community dynamics also contribute to changing biogeography. Variability among taxa in their response to temperature was not explained by commercial status or life history traits, suggesting that species-specific responses to future warming will be difficult to predict.

Oscillating trophic control induces community reorganization in a marine ecosystem.

Understanding how climate regulates trophic control may help to elucidate the causes of transitions between alternate ecosystem states following climate regime shifts. We used a 34-year time series of the abundance of Pacific cod (Gadus macrocephalus) and five prey species to show that the nature of trophic control in a North Pacific ecosystem depends on climate state. Rapid warming in the 1970s caused an oscillation between bottom-up and top-down control. This shift to top-down control apparently contributed to the transition from an initial, prey-rich ecosystem state to the final, prey-poor state. However, top-down control could not be detected in the final state without reference to the initial state and transition period. Complete understanding of trophic control in ecosystems capable of transitions between alternate states may therefore require observations spanning more than one state.

Response of pigeon guillemots to variable abundance of high-lipid and low-lipid prey.

Populations of the pigeon guillemot (Cepphus columba) and other piscivores have been in decline for several decades in the Gulf of Alaska and Bering Sea, and a decline in abundance of lipid-rich schooling fishes is hypothesized as the major cause. We tested this hypothesis by studying the breeding biology of pigeon guillemots during 1995-1999 while simultaneously measuring prey abundance with beach seines and bottom trawls. Our study area (Kachemak Bay, Alaska) comprises two oceanographically distinct areas. Populations of a lipid-rich schooling fish, Pacific sand lance (Ammodytes hexapterus), were higher in the warmer Inner Bay than in the colder Outer Bay, and sand lance abundance was higher during warm years. Populations of low-lipid content demersal fishes were similar between areas. Chick survival to age 15 days was 47% higher in the Inner Bay (high-lipid diet) than in the Outer Bay (low-lipid diet), and estimated reproductive success (chicks fledged nest-1) was 62% higher in the Inner Bay than in the Outer Bay. Chick provisioning rate (kJ chick-1 h-1) increased with the proportion of sand lance in the diet (r 2=0.21), as did growth rate (g day-1) of younger (beta) chicks in two-chick broods (r 2=0.14). Pigeon guillemots in the Inner Bay switched to demersal prey during years of below-average sand lance abundance, and these birds reacted to 38-fold interannual changes in sand lance abundance with reductions in beta chick growth rates, with no decline in beta chick survival. In contrast, the proportion of nests experiencing brood reduction in the Outer Bay (demersal diet) increased >300% during years of below-average demersal abundance, although demersal fish abundance varied only 4-fold among years. Our results support the hypothesis that recovery of pigeon guillemot populations from the effects of the Exxon Valdez oil spill is limited by availability of lipid-rich prey.