Forage fish support the largest fisheries in the world but also play key roles in marine food webs by transferring energy from plankton to upper trophic-level predators, such as large fish, seabirds, and marine mammals. Fishing can, thereby, have far reaching consequences on marine food webs unless safeguards are in place to avoid depleting forage fish to dangerously low levels, where dependent predators are most vulnerable. However, disentangling the contributions of fishing vs. natural processes on population dynamics has been difficult because of the sensitivity of these stocks to environmental conditions. Here, we overcome this difficulty by collating population time series for forage fish populations that account for nearly two-thirds of global catch of forage fish to identify the fingerprint of fisheries on their population dynamics. Forage fish population collapses shared a set of common and unique characteristics: high fishing pressure for several years before collapse, a sharp drop in natural population productivity, and a lagged response to reduce fishing pressure. Lagged response to natural productivity declines can sharply amplify the magnitude of naturally occurring population fluctuations. Finally, we show that the magnitude and frequency of collapses are greater than expected from natural productivity characteristics and therefore, likely attributed to fishing. The durations of collapses, however, were not different from those expected based on natural productivity shifts. A risk-based management scheme that reduces fishing when populations become scarce would protect forage fish and their predators from collapse with little effect on long-term average catches.marine conservation | population collapse | fisheries | ecosystem-based management

The benefits and ecosystem services that humans derive from the oceans are threatened by numerous global change stressors, one of which is ocean acidification. Here, we describe the effects of ocean acidification on an upwelling system that already experiences inherently low pH conditions, the California Current. We used an end-to-end ecosystem model (Atlantis), forced by downscaled global climate models and informed by a meta-analysis of the pH sensitivities of local taxa, to investigate the direct and indirect effects of future pH on biomass and fisheries revenues. Our model projects a 0.2-unit drop in pH during the summer upwelling season from 2013 to 2063, which results in wide-ranging magnitudes of effects across guilds and functional groups. The most dramatic direct effects of future pH may be expected on epibenthic invertebrates (crabs, shrimps, benthic grazers, benthic detritivores, bivalves), and strong indirect effects expected on some demersal fish, sharks, and epibenthic invertebrates (Dungeness crab) because they consume species known to be sensitive to changing pH. The model's pelagic community, including marine mammals and seabirds, was much less influenced by future pH. Some functional groups were less affected to changing pH in the model than might be expected from experimental studies in the empirical literature due to high population productivity (e.g., copepods, pteropods). Model results suggest strong effects of reduced pH on nearshore state-managed invertebrate fisheries, but modest effects on the groundfish fishery because individual groundfish species exhibited diverse responses to changing pH. Our results provide a set of projections that generally support and build upon previous findings and set the stage for hypotheses to guide future modeling and experimental analysis on the effects of OA on marine ecosystems and fisheries.

Species are experiencing a suite of novel stressors from anthropogenic activities that have impacts at multiple scales. Vulnerability assessment is one tool to evaluate the likely impacts that these stressors pose to species so that high-vulnerability cases can be identified and prioritized for monitoring, protection, or mitigation. Commonly used semi-quantitative methods lack a framework to explicitly account for differences in exposure to stressors and organism responses across life stages. Here we propose a modification to commonly used spatial vulnerability assessment methods that includes such an approach, using ocean acidification in the California Current as an illustrative case study. Life stage considerations were included by assessing vulnerability of each life stage to ocean acidification and were used to estimate population vulnerability in two ways. We set population vulnerability equal to: (1) the maximum stage vulnerability and (2) a weighted mean across all stages, with weights calculated using Lefkovitch matrix models. Vulnerability was found to vary across life stages for the six species explored in this case study: two krill–Euphausia pacifica and Thysanoessa spinifera, pteropod–Limacina helicina, pink shrimp–Pandalus jordani, Dungeness crab–Metacarcinus magister and Pacific hake–Merluccius productus. The maximum vulnerability estimates ranged from larval to subadult and adult stages with no consistent stage having maximum vulnerability across species. Similarly, integrated vulnerability metrics varied greatly across species. A comparison showed that some species had vulnerabilities that were similar between the two metrics, while other species’ vulnerabilities varied substantially between the two metrics. These differences primarily resulted from cases where the most vulnerable stage had a low relative weight. We compare these methods and explore circumstances where each method may be appropriate.

Species, habitats, and ecosystems are increasingly exposed to multiple anthropogenic stressors, fueling a rapidly expanding research program to understand the cumulative impacts of these environmental modifications. Since the 1970s, a growing set of methods has been developed through two parallel, sometimes connected, streams of research within the applied and academic realms to assess cumulative effects. Past reviews of cumulative effects assessment (CEA) methods focused on approaches used by practitioners. Academic research has developed several distinct and novel approaches to conducting CEA. Understanding the suite of methods that exist will help practitioners and academics better address various ecological foci (physiological responses, population impacts, ecosystem impacts) and ecological complexities (synergistic effects, impacts across space and time). We reviewed 6 categories of methods (experimental, meta-analysis, single-species modeling, mapping, qualitative modeling, and multispecies modeling) and examined the ability of those methods to address different levels of complexity. We focused on research gaps and emerging priorities. We found that no single method assessed impacts across the 4 ecological foci and 6 ecological complexities considered. We propose that methods can be used in combination to improve understanding such that multimodel inference can provide a suite of comparable outputs, mapping methods can help prioritize localized models or experimental gaps, and future experiments can be paired from the outset with models they will inform.

Population endangerment typically arises from multiple, potentially interacting anthropogenic stressors. Extensive research has investigated the consequences of multiple stressors on organisms, frequently focusing on individual life stages. Less is known about population-level consequences of exposure to multiple stressors, especially when exposure varies through life. We provide the first theoretical basis for identifying species at risk of magnified effects from multiple stressors across life history. By applying a population modeling framework, we reveal conditions under which population responses from stressors applied to distinct life stages are either magnified (synergistic) or mitigated. We find that magnification or mitigation critically depends on the shape of density dependence, but not the life stage in which it occurs. Stressors are always magnified when density dependence is linear or concave, and magnified or mitigated when it is convex. Using Bayesian numerical methods, we estimated the shape of density dependence for eight species across diverse taxa, finding support for all three shapes.

Many of the world's ecosystems are experiencing a suite of changes from anthropogenic activities; the multiple stressors from those activities result in cumulative impacts. Understanding how these activities translate into ecological consequences is exceedingly challenging because of the inherent complexity within natural systems and the variability in how stressors act and how species respond. While there have been substantial advancements within the field of cumulative effects assessment to address these issues and improve our understanding of the consequences of our actions, many challenges remain. Here, we detail advances and remaining challenges, and propose five priorities for addressing these challenges in the near future. In particular, we suggest prioritizing risk-based approaches that account for uncertainty in our understanding and establishing an underlying theory for when we expect particular impacts to occur. We also propose the need for a defined subdiscipline focused on cumulative effects, to help reduce the silos of research that are often disconnected, and to work toward a common set of definitions, methods and the consistent use of open data.

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