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Humans interact with the oceans in diverse and profound ways. The scope, magnitude, footprint and ultimate cumulative impacts of human activities can threaten ocean ecosystems and have changed over time, resulting in new challenges and threats to marine ecosystems. A fundamental gap in understanding how humanity is affecting the oceans is our limited knowledge about the pace of change in cumulative impact on ocean ecosystems from expanding human activities – and the patterns, locations and drivers of most significant change. To help address this, we combined high resolution, annual data on the intensity of 14 human stressors and their impact on 21 marine ecosystems over 11 years (2003–2013) to assess pace of change in cumulative impacts on global oceans, where and how much that pace differs across the ocean, and which stressors and their impacts contribute most to those changes. We found that most of the ocean (59%) is experiencing significantly increasing cumulative impact, in particular due to climate change but also from fishing, land-based pollution and shipping. Nearly all countries saw increases in cumulative impacts in their coastal waters, as did all ecosystems, with coral reefs, seagrasses and mangroves at most risk. Mitigation of stressors most contributing to increases in overall cumulative impacts is urgently needed to sustain healthy oceans.

Sustainability indices are proliferating, both to help synthesize scientific understanding and inform policy. However, it remains poorly understood how such indices are affected by underlying assumptions of the data and modelling approaches used to compute indicator values. Here, we focus on one such indicator, the fisheries goal within the Ocean Health Index (OHI), which evaluates the sustainable provision of food from wild fisheries. We quantify uncertainty in the fisheries goal status arising from the (a) approach for estimating missing data (i.e., fish stocks with no status) and (b) reliance on a data‐limited method (catch‐MSY) to estimate stock status (i.e., B/BMSY). We also compare several other models to estimate B/BMSY, including an ensemble approach, to determine whether alternative models might reduce uncertainty and bias. We find that the current OHI fisheries goal model results in overly optimistic fisheries goal statuses. Uncertainty and bias can be reduced by (a) using a mean (vs. median) gap‐filling approach to estimate missing stock scores and (b) estimating fisheries status using the central tendency from a simulated distribution of status scores generated by a bootstrap approach that incorporates error in B/BMSY. This multitiered approach to measure and describe uncertainty improves the transparency and interpretation of the indicator and allows us to better understand uncertainty around our OHI fisheries model and outputs for country‐level interpretation and use.

Effective management of marine systems requires quantitative tools that can assess the state of the marine social-ecological system and are responsive to management actions and pressures. We applied the Ocean Health Index (OHI) framework to retrospectively assess ocean health in British Columbia annually from 2001 to 2016 for eight goals that represent the values of British Columbia's coastal communities. We found overall ocean health improved over the study period, from 75 (out of 100) in 2001 to 83 in 2016, with scores for inhabited regions ranging from 68 (North Coast, 2002) to 87 (West Vancouver Island, 2011). Highest-scoring goals were Tourism & Recreation (average 94 over the period) and Habitat Services (100); lowest-scoring goals were Sense of Place (61) and Food Provision (64). Significant increases in scores over the time period occurred for Food Provision (+1.7 per year), Sense of Place (+1.4 per year), and Coastal Livelihoods (+0.6 per year), while Habitat Services (-0.01 per year) and Biodiversity (-0.09 per year) showed modest but statistically significant declines. From the results of our time-series analysis, we used the OHI framework to evaluate impacts of a range of management actions. Despite challenges in data availability, we found evidence for the ability of management to reduce pressures on several goals, suggesting the potential of OHI as a tool for assessing the effectiveness of marine resource management to improve ocean health. Our OHI assessment provides an important comprehensive evaluation of ocean health in British Columbia, and our open and transparent process highlights opportunities for improving accessibility of social and ecological data to inform future assessment and management of ocean health.

Many of the world's fisheries are unassessed, with little information about population status or risk of overfishing. Unassessed fisheries are particularly predominant in developing countries and in small-scale fisheries, where they are important for food security. Several catch-only methods based on time series of fishery catch and commonly available life-history traits have been developed to estimate stock status (defined as biomass relative to biomass at maximum sustainable yield: B/B-MSY). While their stock status performance has been extensively studied, performance of catch-only models as a management tool is unknown. We evaluated the extent to which a superensemble of three prominent catch-only models can provide a reliable basis for fisheries management and how performance compares across management strategies that control catch or fishing effort. We used a management strategy evaluation framework to determine whether a superensemble of catch-only models can reliably inform harvest control rules (HCRs). Across five simulated fish life histories and two harvest-dynamic types, catch-only models and HCR combinations reduced the risk of overfishing and increased the proportion of stocks above B-MSY compared to business as usual, though often resulted in poor yields. Precautionary HCRs based on fishing effort were robust and insensitive to error in catch-only models, while catch-based HCRs caused high probabilities of overfishing and more overfished populations. Catch-only methods tended to overestimate B/B-MSY for our simulated data sets. The catch-only superensemble combined with precautionary effort-based HCRs could be part of a stepping stone approach for managing some data-limited stocks while working towards more data-moderate assessment methods.

Marine social-ecological conditions in the Arctic are rapidly changing. With many transboundary issues, such as shifting ranges of fisheries, biodiversity loss, sea ice retreat, economic development and pollution, greater pan-Arctic assessment and co-management are necessary. We adapted the Ocean Health Index (OHI) to compile pan-Arctic data and evaluate ocean health for nine regions above the Arctic Circle to assess the extent to which pan-Arctic assessment is possible and identify broad social-ecological trends. While the quality and availability of data varied, we assessed and scored nine OHI goals, including the pressures and resilience measures acting upon them. Our results show the Arctic is sustainably delivering a range of benefits to people, but with room for improvement in all goals, particularly tourism, fisheries, and protected places. Successful management of biological resources and short-term positive impacts on biodiversity in response to climate change underlie these high goal scores. The OHI assesses the past and near-term future but does not account for medium- and long-term future risks associated with climate change, highlighting the need for ongoing monitoring, dynamic management, and strong action to mitigate its anticipated effects. A general increase in and standardisation of monitoring is urgently needed in the Arctic. Unified assessments, such as this one, can support national comparisons, data quality assessments, and discussions on the targeting of limited monitoring capabilities at the most pressing and urgent transboundary management challenges, which is a priority for achieving successful Arctic stewardship.

Fishery managers must often reconcile conflicting estimates of population status and trend. Superensemble models, commonly used in climate and weather forecasting, may provide an effective solution. This approach uses predictions from multiple models as covariates in an additional "superensemble" model fitted to known data. We evaluated the potential for ensemble averages and superensemble models (ensemble methods) to improve estimates of population status and trend for fisheries. We fit four widely applicable data-limited models that estimate stock biomass relative to equilibrium biomass at maximum sustainable yield (B/BMSY). We combined these estimates of recent fishery status and trends in B/BMSY with four ensemble methods: an ensemble average and three superensembles (a linear model, a random forest and a boosted regression tree). We trained our superensembles on 5,760 simulated stocks and tested them with cross-validation and against a global database of 249 stock assessments. Ensemble methods substantially improved estimates of population status and trend. Random forest and boosted regression trees performed the best at estimating population status: inaccuracy (median absolute proportional error) decreased from 0.42 -0.56 to 0.32 -0.33, rank-order correlation between predicted and true status improved from 0.02 - 0.32 to 0.44 - 0.48 and bias (median proportional error) declined from - 0.22 - 0.31 to - 0.12 - 0.03. We found similar improvements when predicting trend and when applying the simulation-trained superensembles to catch data for global fish stocks. Superensembles can optimally leverage multiple model predictions; however, they must be tested, formed from a diverse set of accurate models and built on a data set representative of the populations to which they are applied.

Summary Carbon offsetting—receiving credit for reducing, avoiding, or sequestering carbon—has become part of the portfolio of solutions to mitigate carbon emissions, and thus climate change, through policy and voluntary markets, primarily by land-based re- or afforestation and preservation [ 1 , 2 ]. However, land is limiting, creating interest in a rapidly growing aquatic farming sector of seaweed aquaculture [ 3 , 4 , 5 ]. Synthesizing data from scientific literature, we assess the extent and cost of scaling seaweed aquaculture to provide sufficient CO2eq sequestration for several climate change mitigation scenarios, with a focus on the food sector—a major source of greenhouse gases [ 6 ]. Given known ecological constraints (nutrients and temperature), we found a substantial suitable area (ca. 48 million km2) for seaweed farming, which is largely unfarmed. Within its own industry, seaweed could create a carbon-neutral aquaculture sector with just 14% (mean = 25%) of current seaweed production (0.001% of suitable area). At a much larger scale, we find seaweed culturing extremely unlikely to offset global agriculture, in part due to production growth and cost constraints. Yet offsetting agriculture appears more feasible at a regional level, especially areas with strong climate policy, such as California (0.065% of suitable area). Importantly, seaweed farming can provide other benefits to coastlines affected by eutrophic, hypoxic, and/or acidic conditions [ 7 , 8 ], creating opportunities for seaweed farming to act as “charismatic carbon” that serves multiple purposes. Seaweed offsetting is not the sole solution to climate change, but it provides an invaluable new tool for a more sustainable future.

The exploitation status of marine fisheries stocks worldwide is of critical importance for food security, ecosystem conservation, and fishery sustainability. Applying a suite of data-limited methods to global catch data, combined through an ensemble modeling approach, we provide quantitative estimates of exploitation status for 785 fish stocks. Fifty six percent (439 stocks) are below BMSY and of these, 261 are estimated to be below 80% of the BMSY level. While the 178 stocks above 80% of BMSY are conventionally considered “fully exploited”, stocks staying at this level for many years, forego substantial yield. Our results enable managers to consider more detailed information than simply a categorization of stocks as “fully” or “over” exploited. Our approach is reproducible, allows consistent application to a broad range of stocks, and can be easily updated as new data become available. Applied on an ongoing basis, this approach can provide critical, more detailed information for resource management for more exploited fish stocks than currently available. This article is protected by copyright. All rights reserved

Overfishing and degradation of the marine environment continue to plague coastal communities worldwide, with multiple diverse solutions being proposed. Territorial Use Rights for Fisheries (TURFs) is a fishery management approach that aligns fishers’ incentives with sustainability, while marine reserves have proven effective for ecosystem protection, and in some cases for fishery enhancement. These two management approaches are often used in isolation, leaving the potential utility of integrating them poorly understood. We examine cases where TURFs and marine reserves have been implemented together to create “TURF-reserves”. We compiled a database of 27 TURF-reserves and collected information on the governance, management, enforcement, fishing practices, fishing rights, regulations, and design attributes for each site. We address several research questions including: what species are managed with TURF-reserves, how are TURF-reserves created and who is involved in the process? Our findings show that the majority of surveyed TURF-reserves arose from previously established TURF systems that target a range of fisheries, and multiple entities play a role in TURF-reserve development and management. We also examine the differences between two TURF-reserve archetypes and find that those developed with a strong history of customary tenure share distinct qualities from those created in a more recently established, government-mandated system. Keywords: TURF, Marine reserve, TURF-reserve, Fisheries, Rights-based management

Introduction: Human impacts on Arctic marine ecosystems are increasing in extent and intensity as sea ice shrinks and utilization of marine resources expands. The effects of climate change are being felt across the arctic while stressors such as commercial fishing and shipping continue to grow as the Arctic becomes more accessible. Given these emerging changes, there is need for an assessment of the current cumulative impact of human activities to better anticipate and manage for a changing Arctic. Cumulative human impacts (CHI) assessments have been widely applied around the world in a variety of ecosystem types but have yet to incorporate temporal dynamics of individual stressors. Such dynamics are fundamental to Arctic ecosystems. Outcomes: Here, we present the first CHI assessment of an Arctic ecosystem to incorporate sea ice as a habitat and assess impact seasonality, using the Bering Strait Region (BSR) as a case study. We find that cumulative impacts differ seasonally, with lower impacts in winter and higher impacts in summer months. Large portions of the BSR have significantly different impacts within each season when compared to a mean annual cumulative impact map. Cumulative impacts also have great spatial variability, with Russian waters between 2.38 and 3.63 times as impacted as US waters. Conclusion: This assessment of seasonal and spatial cumulative impacts provides an understanding of the current reality in the BSR and can be used to support development and evaluation of future management scenarios that address expected impacts from climate change and increasing interest in the Arctic.

Growing international and national focus on quantitatively measuring and improving ocean health has increased the need for comprehensive, scientific, and repeated indicators to track progress towards achieving policy and societal goals. The Ocean Health Index (OHI) is one of the few indicators available for this purpose. Here we present results from five years of annual global assessment for 220 countries and territories, evaluating potential drivers and consequences of changes and presenting lessons learned about the challenges of using composite indicators to measure sustainability goals. Globally scores have shown little change, as would be expected. However, individual countries have seen notable increases or declines due in particular to improvements in the harvest and management of wild-caught fisheries, the creation of marine protected areas (MPAs), and decreases in natural product harvest. Rapid loss of sea ice and the consequent reduction of coastal protection from that sea ice was also responsible for declines in overall ocean health in many Arctic and sub-Arctic countries. The OHI performed reasonably well at predicting near-term future scores for many of the ten goals measured, but data gaps and limitations hindered these predictions for many other goals. Ultimately, all indicators face the substantial challenge of informing policy for progress toward broad goals and objectives with insufficient monitoring and assessment data. If countries and the global community hope to achieve and maintain healthy oceans, we will need to dedicate significant resources to measuring what we are trying to manage.

Reproducibility has long been a tenet of science but has been challenging to achieve-we learned this the hard way when our old approaches proved inadequate to efficiently reproduce our own work. Here we describe how several free software tools have fundamentally upgraded our approach to collaborative research, making our entire workflow more transparent and streamlined. By describing specific tools and how we incrementally began using them for the Ocean Health Index project, we hope to encourage others in the scientific community to do the same-so we can all produce better science in less time.

Species distribution data provide the foundation for a wide range of ecological research studies and conservation management decisions. Two major efforts to provide marine species distributions at a global scale are the International Union for Conservation of Nature (IUCN), which provides expert-generated range maps that outline the complete extent of a species' distribution; and AquaMaps, which provides model-generated species distribution maps that predict areas occupied by the species. Together these databases represent 24,586 species (93.1% within AquaMaps, 16.4% within IUCN), with only 2,330 shared species. Differences in intent and methodology can result in very different predictions of species distributions, which bear important implications for scientists and decision makers who rely upon these datasets when conducting research or informing conservation policy and management actions. Comparing distributions for the small subset of species with maps in both datasets, we found that AquaMaps and IUCN range maps show strong agreement for many well-studied species, but our analysis highlights several key examples in which introduced errors drive differences in predicted species ranges. In particular, we find that IUCN maps greatly overpredict coral presence into unsuitably deep waters, and we show that some AquaMaps computer-generated default maps (only 5.7% of which have been reviewed by experts) can produce odd discontinuities at the extremes of a species' predicted range. We illustrate the scientific and management implications of these tradeoffs by repeating a global analysis of gaps in coverage of marine protected areas, and find significantly different results depending on how the two datasets are used. By highlighting tradeoffs between the two datasets, we hope to encourage increased collaboration between taxa experts and large scale species distribution modeling efforts to further improve these foundational datasets, helping to better inform science and policy recommendations around understanding, managing, and protecting marine biodiversity.

Coral reef cryptofauna, which live hidden within reef framework structures, are con- sidered to be the most diverse group of coral reef metazoans. They likely comprise more biomass than all surface fauna, providing food sources for fishes and playing important roles as predators, herbivores, detritivores, filter feeders, and scavengers. In an era of global change, it is necessary to determine how these communities are structured across reef habitats as well as to understand how reef framework degradation will impact the cryptofauna and, by extension, ecosystem func- tion. Artificial reef framework units were constructed from coral rubble to approxi mate framework substrates. Forty replicates were subjected to treatments of differing porosity, flow, and coral cover in a fully crossed ANOVA design. After 2 mo in situ, all motile cryptofauna (>2 mm) were counted, weighed, and identified to the lowest possible level. A total of 11 309 specimens were col- lected, comprising >121 species from 6 separate phyla. Cryptofaunal abundances and biomass were higher in low-porosity crypts and biomass was greater in slow-flow environments, highlight- ing the importance of sheltered low-porosity habitats, such as back-reef rubble plains. The pres- ence of live coral was not found to have a significant effect on the motile cryptofauna occupying the dead coral framework below it, suggesting a high degree of resilience in how framework- dwelling fauna respond to coral mortality. These data support the assertion that artificial reefs are capable of facilitating the accumulation of a diverse cryptic community, independent of live coral, provided they contain suitably porous crypts.