Search

Declines of Steller sea lion (Eumetopias jubatus) populations in the Aleutian Islands and Gulf of Alaska could be a consequence of physical oceanographic changes associated with the 1976-77 climate regime shift. Changes in ocean climate are hypothesized to have affected the quantity, quality, and accessibility of prey, which in turn may have affected the rates of birth and death of sea lions. Recent studies of the spatial and temporal variations in the ocean climate system of the North Pacific support this hypothesis. Ocean climate changes appear to have created adaptive opportunities for various species that are preyed upon by Steller sea lions at mid-trophic levels. The east-west asymmetry of the oceanic response to climate forcing after 1976-77 is consistent with both the temporal aspect (populations decreased after the late 1970s) and the spatial aspect of the decline (western, but not eastern, sea lion populations decreased). These broad-scale climate variations appear to be modulated by regionally sensitive biogeographic structures along the Aleutian Islands and Gulf of Alaska, which include a transition point from coastal to open-ocean conditions at Samalga Pass westward along the Aleutian Islands. These transition points delineate distinct clusterings of different combinations of prey species, which are in turn correlated with differential population sizes and trajectories of Steller sea lions. Archaeological records spanning 4000 yr further indicate that sea lion populations have experienced major shifts in abundance in the past. Shifts in ocean climate are the most parsimonious underlying explanation for the broad suite of ecosystem changes that have been observed in the North Pacific Ocean in recent decades. © 2007 Blackwell Publishing Ltd.

Seaweed farming is widely promoted as an approach to mitigating climate change despite limited data on carbon removal pathways and uncertainty around benefits and risks at operational scales. We explored the feasibility of climate change mitigation from seaweed farming by constructing five scenarios spanning a range of industry development in coastal British Columbia, Canada, a temperate region identified as highly suitable for seaweed farming. Depending on growth rates and the fate of farmed seaweed, our scenarios sequestered or avoided between 0.20 and 8.2 Tg CO 2 e year -1 , equivalent to 0.3% and 13% of annual greenhouse gas emissions in BC, respectively. Realisation of climate benefits required seaweed-based products to replace existing, more emissions-intensive products, as marine sequestration was relatively inefficient. Such products were also key to reducing the monetary cost of climate benefits, with product values exceeding production costs in only one of the scenarios we examined. However, model estimates have large uncertainties dominated by seaweed production and emissions avoided, making these key priorities for future research. Our results show that seaweed farming could make an economically feasible contribute to Canada's climate goals if markets for value-added seaweed based products are developed. Moreover, our model demonstrates the possibility for farmers, regulators, and researchers to accurately quantify the climate benefits of seaweed farming in their regional contexts., (© 2024. The Author(s).)

With climate, biodiversity and inequity crises squarely upon us, never has there been a more pressing time to rethink how we conceptualize, understand and manage our relationship with Earth's biodiversity. Here, we describe governance principles of 17 Indigenous Nations from the Northwest Coast of North America used to understand and steward relationships among all components of nature, including humans. We then chart the colonial origins of biodiversity science and use the complex case of sea otter recovery to illuminate how ancestral governance principles can be mobilized to characterize, manage and restore biodiversity in more inclusive, integrative and equitable ways. To enhance environmental sustainability, resilience and social justice amid today's crises, we need to broaden who benefits from and participates in the sciences of biodiversity by expanding the values and methodologies that shape such initiatives. In practice, biodiversity conservation and natural resource management need to shift from centralized, siloed approaches to those that can accommodate plurality in values, objectives, governance systems, legal traditions and ways of knowing. In doing so, developing solutions to our planetary crises becomes a shared responsibility. This article is part of the theme issue 'Detecting and attributing the causes of biodiversity change: needs, gaps and solutions'.

Understanding the cumulative effects of multiple stressors is a research priority in environmental science. Ecological models are a key component of tackling this challenge because they can simulate interactions between the components of an ecosystem. Here, we ask, how has the popular modeling platform Ecopath with Ecosim (EwE) been used to model human impacts related to climate change, land and sea use, pollution, and invasive species? We conducted a literature review encompassing 166 studies covering stressors other than fishing mostly in aquatic ecosystems. The most modeled stressors were physical climate change (60 studies), species introductions (22), habitat loss (21), and eutrophication (20), using a range of modeling techniques. Despite this comprehensive coverage, we identified four gaps that must be filled to harness the potential of EwE for studying multiple stressor effects. First, only 12% of studies investigated three or more stressors, with most studies focusing on single stressors. Furthermore, many studies modeled only one of many pathways through which each stressor is known to affect ecosystems. Second, various methods have been applied to define environmental response functions representing the effects of single stressors on species groups. These functions can have a large effect on the simulated ecological changes, but best practices for deriving them are yet to emerge. Third, human dimensions of environmental change - except for fisheries - were rarely considered. Fourth, only 3% of studies used statistical research designs that allow attribution of simulated ecosystem changes to stressors' direct effects and interactions, such as factorial (computational) experiments. None made full use of the statistical possibilities that arise when simulations can be repeated many times with controlled changes to the inputs. We argue that all four gaps are feasibly filled by integrating ecological modeling with advances in other subfields of environmental science and in computational statistics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

As the United Nations develops a post-2020 global biodiversity framework for the Convention on Biological Diversity, attention is focusing on how new goals and targets for ecosystem conservation might serve its vision of 'living in harmony with nature' 1,2 . Advancing dual imperatives to conserve biodiversity and sustain ecosystem services requires reliable and resilient generalizations and predictions about ecosystem responses to environmental change and management 3 . Ecosystems vary in their biota 4 , service provision 5 and relative exposure to risks 6 , yet there is no globally consistent classification of ecosystems that reflects functional responses to change and management. This hampers progress on developing conservation targets and sustainability goals. Here we present the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology, a conceptually robust, scalable, spatially explicit approach for generalizations and predictions about functions, biota, risks and management remedies across the entire biosphere. The outcome of a major cross-disciplinary collaboration, this novel framework places all of Earth's ecosystems into a unifying theoretical context to guide the transformation of ecosystem policy and management from global to local scales. This new information infrastructure will support knowledge transfer for ecosystem-specific management and restoration, globally standardized ecosystem risk assessments, natural capital accounting and progress on the post-2020 global biodiversity framework., (© 2022. The Author(s).)

Maps of bottom type are essential to the management of marine resources and biodiversity because of their foundational role in characterizing species' habitats. They are also urgently needed as countries work to define marine protected areas. Current approaches are time consuming, focus largely on grain size, and tend to overlook shallow waters. Our random forest classification of almost 200,000 observations of bottom type is a timely alternative, providing maps of coastal substrate at a combination of resolution and extents not previously achieved. We correlated the observations with depth, depth-derivatives, and estimates of energy to predict marine substrate at 100 m resolution for Canada's Pacific shelf, a study area of over 135,000 km2. We built five regional models with the same data at 20 m resolution. In addition to standard tests of model fit, we used three independent data sets to test model predictions. We also tested for regional, depth, and resolution effects. We guided our analysis by asking: 1) does weighting for prevalence improve model predictions? 2) does model resolution influence model performance? And 3) is model performance influenced by depth? All our models fit the build data well with true skill statistic (TSS) scores ranging from 0.56 to 0.64. Weighting models with class prevalence improved fit and the correspondence with known spatial features. Class-based metrics showed differences across both resolutions and spatial regions, indicating non-stationarity across these spatial categories. Predictive power was lower (TSS from 0.10 to 0.36) based on independent data evaluation. Model performance was also a function of depth and resolution, illustrating the challenge of accurately representing heterogeneity. Our work shows the value of regional analyses to assessing model stationarity and how independent data evaluation and the use of error metrics can improve understanding of model performance and sampling bias., Competing Interests: This funding does not alter our adherence to PLOS ONE policies on sharing data and materials. The specific roles of these authors are articulated in the ‘author contributions’ section.

Predator recovery often leads to ecosystem change that can trigger conflicts with more recently established human activities. In the eastern North Pacific, recovering sea otters are transforming coastal systems by reducing populations of benthic invertebrates and releasing kelp forests from grazing pressure. These changes threaten established shellfish fisheries and modify a variety of other ecosystem services. The diverse social and economic consequences of this trophic cascade are unknown, particularly across large regions. We developed and applied a trophic model to predict these impacts on four ecosystem services. Results suggest that sea otter presence yields 37% more total ecosystem biomass annually, increasing the value of finfish [+9.4 million Canadian dollars (CA$)], carbon sequestration (+2.2 million CA$), and ecotourism (+42.0 million CA$). To the extent that these benefits are realized, they will exceed the annual loss to invertebrate fisheries (-$7.3 million CA$). Recovery of keystone predators thus not only restores ecosystems but can also affect a range of social, economic, and ecological benefits for associated communities., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Predictive models are central to many scientific disciplines and vital for informing management in a rapidly changing world. However, limited understanding of the accuracy and precision of models transferred to novel conditions (their 'transferability') undermines confidence in their predictions. Here, 50 experts identified priority knowledge gaps which, if filled, will most improve model transfers. These are summarized into six technical and six fundamental challenges, which underlie the combined need to intensify research on the determinants of ecological predictability, including species traits and data quality, and develop best practices for transferring models. Of high importance is the identification of a widely applicable set of transferability metrics, with appropriate tools to quantify the sources and impacts of prediction uncertainty under novel conditions., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)

A leading hypothesis to explain the dramatic decline of Steller sea lions (Eumetopias jubatus) in western Alaska during the latter part of the 20th century is a change in prey availability due to commercial fisheries. We tested this hypothesis by exploring the relationships between sea lion population trends, fishery catches, and the prey biomass accessible to sea lions around 33 rookeries between 2000 and 2008. We focused on three commercially important species that have dominated the sea lion diet during the population decline: walleye pollock, Pacific cod and Atka mackerel. We estimated available prey biomass by removing fishery catches from predicted prey biomass distributions in the Aleutian Islands, Bering Sea and Gulf of Alaska; and modelled the likelihood of sea lions foraging at different distances from rookeries (accessibility) using satellite telemetry locations of tracked animals. We combined this accessibility model with the prey distributions to estimate the prey biomass accessible to sea lions by rookery. For each rookery, we compared sea lion population change to accessible prey biomass. Of 304 comparisons, we found 3 statistically significant relationships, all suggesting that sea lion populations increased with increasing prey accessibility. Given that the majority of comparisons showed no significant effect, it seems unlikely that the availability of pollock, cod or Atka mackerel was limiting sea lion populations in the 2000s.