Marine protected areas (MPAs) are critical in safeguarding biodiversity and ecosystem functions under climate change. The long-term effectiveness of these static conservation measures will depend on how well they represent current and future ocean changes. Here, we use the Climate Risk Index for Biodiversity to assess the vulnerability representation of marine ecosystems within the Canadian marine conservation network (CMCN) under two divergent emissions scenarios. We found that MPAs best represent climate vulnerability in Atlantic Canada (85% representativity overall, and 93% in the Gulf of Saint Lawrence under low emissions), followed by the Pacific (78%) and Arctic (63%; lowest in the Eastern Arctic (41% under high emissions) regions). Notably, MPAs with lower climate vulnerability are proportionally overrepresented in the CMCN. Broad-scale geographic targets employed in the Scotian Shelf-Bay of Fundy network planning process achieve over 90% representativity of climate vulnerabilities, underscoring the importance of ensuring habitat representativity and geographic distribution in conservation planning to enhance climate resilience, even if not explicitly prioritized. Moving towards Canada’s target to protect 30% of its waters by 2030, prioritizing representativity and designation of MPAs in currently underrepresented climate-vulnerable regions may be crucial to enhancing the resilience of the CMCN amidst an ever-changing climate.

A global decline in seagrass populations has led to renewed calls for their conservation as important providers of biogenic and foraging habitat, shoreline stabilisation, and carbon storage. Eelgrass (Zostera marina) occupies the largest geographic range among seagrass species spanning a commensurately broad spectrum of environmental conditions. However, relatively little is known about their fine-scale genetic structure and broad-scale genomic signatures of environmental adaptation, and in Canada, eelgrass is considered a single phylogroup despite occurring across three oceans. We used a pooled whole-genome re-sequencing approach to characterise population structure, gene flow, and adaptation of 23 eelgrass populations ranging from the Northeast United States, to Atlantic, subarctic, and Pacific Canada. We identified over 500,000 SNPs, which when mapped to a chromosome-level genome assembly revealed six broad clades of eelgrass across the study area, with pairwise FST ranging from 0 among neighbouring populations to 0.54 between Pacific and Atlantic coasts. Genetic diversity was highest in the Pacific and lowest in the Arctic, consistent with colonisation of the Arctic and Atlantic oceans from the Pacific. Using redundancy analyses and two climate change projection scenarios, we found that subarctic populations are more vulnerable to climate change through genomic offset predictions. Conservation planning in Canada should ensure that representative populations from each identified clade are included within a national network so that latent genetic diversity is protected, and gene flow is maintained. Northern populations, in particular, may require stronger protective measures given their susceptibility to change climate.

Climate change is a looming threat to marine life, creating an urgent need to develop climate-informed conservation strategies. The Climate Risk Index for Biodiversity was designed to assess the climate risk for marine species in a manner that supports decision-making. Yet, its regional application remains to be explored. Here, we use it to evaluate climate risk for ~2000 species in the northwest Atlantic Ocean, a marine warming hotspot, to explore its capacity to inform climate-considered fisheries management. Under high emissions, harvested species, especially those with the highest economic value, have a disproportionate risk of projected exposure to hazardous climate conditions but benefit the most from emission mitigation. By mapping critical risk areas for 90 fish stocks, we pinpoint locations likely to require additional intervention, such as in the southern Gulf of St. Lawrence for Atlantic cod. Finally, we demonstrate how evaluating climate risk geographically and understanding how it arises can support short- and long-term fisheries management and conservation objectives under climate change.

The Eastern Shore Islands (ESI) archipelago on the Scotian Shelf supports a rich variety of biogenic habitats and associated diversity of coastal species. The unique and complex geometry of the ESI coastline has a significant impact on circulation and, correspondingly, influences the dispersal of nearshore organisms. For many coastal areas, the ability to accurately resolve the dispersal processes is contingent on the availability of oceanographic models that can resolve fine-scale coastal boundary conditions, including coastlines and bathymetric features. We applied a high-resolution ocean circulation model and Lagrangian particle tracking in the ESI to simulate dispersal of nearshore organisms. Our results revealed predominant southwest-northeast transport that was associated with a nearshore reversal flow. While transport among different zones of the study region is mainly determined by residual currents over the long term, tidal currents dominate patterns of particle dispersal over shorter time scales. An analysis of Lagrangian coherent structures found that they were consistently associated with the mouths of bays, demonstrating that the islands and associated oceanographic processes promote self-retention. These results highlight how complex coastlines and associated oceanographic processes promote retention and underline the need to resolve these fine-scale physical and oceanographic features when estimating biophysical dispersal in the coastal environment.

Monitoring biological diversity is essential for monitoring ecosystem health and evaluating conservation efforts. Environmental DNA metabarcoding has emerged as a powerful, scalable, and minimally invasive tool for assessing biodiversity. In this study, we evaluate the performance of an autonomous eDNA sampling platform deployed over a nine-week period and compare it with a traditional filter-at-sample (F AS) sampling protocol. Our results show that the autonomous sampling platform consistently captures and preserves DNA with comparable effectiveness to conventional in-situ filtering and preservation at −80°C. Using two eDNA markers, we found that fish communities (12S marker) identified by both sampling methods largely overlapped, while invertebrate detections (COI marker) differed between methods, likely due to differences in filter specifications. These findings demonstrate that the autonomous samplers worked effectively in comparison to traditional methods, highlighting their potential to expand the temporal and spatial coverage of eDNA-based biodiversity monitoring. The ability of these samplers to facilitate long-term and continuous sampling in challenging environments shows promise for advancing eDNA applications in diverse and remote settings. Further research is needed to assess their performance in deeper waters and over extended periods, particularly to evaluate eDNA preservation at ambient ocean temperatures.

Species are already on the move as waters warm. Conservation plans need to take this into account. Species are already on the move as waters warm. Conservation plans need to take this into account.

Abstract Understanding how marine organisms adapt to local environments is crucial for predicting how populations will respond to global climate change. The genomic basis, environmental factors and evolutionary processes involved in local adaptation are however not well understood. Here we use Atlantic herring, an abundant, migratory and widely distributed marine fish with substantial genomic resources, as a model organism to evaluate local adaptation. We examined genomic variation and its correlation with environmental variables across a broad environmental gradient, for 15 spawning aggregations in Atlantic Canada and the United States. We then compared our results with available genomic data of northeast Atlantic populations. We confirmed that population structure lies in a fraction of the genome including likely adaptive genetic variants of functional importance. We discovered 10 highly differentiated genomic regions distributed across four chromosomes. Nine regions show strong association with seasonal reproduction. One region, corresponding to a known inversion on chromosome 12, underlies a latitudinal pattern discriminating populations north and south of a biogeographic transition zone on the Scotian Shelf. Genome–environment associations indicate that winter seawater temperature best correlates with the latitudinal pattern of this inversion. The variation at two so‐called ‘islands of divergence’ related to seasonal reproduction appear to be private to the northwest Atlantic. Populations in the northwest and northeast Atlantic share variation at four of these divergent regions, simultaneously displaying significant diversity in haplotype composition at another four regions, which includes an undescribed structural variant approximately 7.7 Mb long on chromosome 8. Our results suggest that the timing and geographic location of spawning and early development may be under diverse selective pressures related to allelic fitness across environments. Our study highlights the role of genomic architecture, ancestral haplotypes and selection in maintaining adaptive divergence in species with large population sizes and presumably high gene flow.

Species with widespread distributions play a crucial role in our understanding of climate change impacts on population structure. In marine species, population structure is often governed by both high connectivity potential and selection across strong environmental gradients. Despite the complexity of factors influencing marine populations, studying species with broad distribution can provide valuable insights into the relative importance of these factors and the consequences of climate-induced alterations across environmental gradients. We used the northern shrimp Pandalus borealis and its wide latitudinal distribution to identify current drivers of population structure and predict the species' vulnerability to climate change. A total of 1514 individuals sampled across 24° latitude were genotyped at high geographic (54 stations) and genetic (14,331 SNPs) resolutions to assess genetic variation and environmental correlations. Four populations were identified in addition to finer substructure associated with local adaptation. Geographic patterns of neutral population structure reflected predominant oceanographic currents, while a significant proportion of the genetic variation was associated with gradients in salinity and temperature. Adaptive landscapes generated using climate projections suggest a larger genomic offset in the southern extent of the P. borealis range, where shrimp had the largest adaptive standing genetic variation. Our genomic results combined with recent observations point to further deterioration in southern regions and an impending vulnerable status in the regions at higher latitudes for P. borealis. They also provide rare insights into the drivers of population structure and climatic vulnerability of a widespread meroplanktonic species, which is crucial to understanding future challenges associated with invertebrates essential to ecosystem functioning.

Human activities threaten Earth's biodiversity and its contributions to human well-being. In the ocean, our poor understanding of how biodiversity is distributed limits its management and protection, necessitating reliance on weak abiotic proxies. Here, we propose a scientific framework for assessing marine biodiversity at multiple spatial scales, which exposes gaps in biodiversity knowledge and protection. The framework prioritizes ecologically and societally important taxa, characteristics of effective networks, and existing data. Applying the framework to assess biodiversity inside and outside US marine protected areas, we reveal that these areas contain a fraction of the biodiversity found in US waters. We show that none of the nation's 24 marine ecoregions meet all criteria for an effective protection network and that biodiversity coverage in protected areas varies among regions and taxa. This marine biodiversity assessment highlights concrete recommendations for more strategic protection and validates a scientific framework generalizable to other spatial management uses.

As climate change transforms marine environments globally, species distributions correspondingly shift to locations where conditions have become or remain favourable. The ability to model these distributional shifts has been facilitated by species distribution models (SDMs). However, current SDM approaches have largely ignored climate‐driven changes in species interactions, which ultimately can have an important influence on species distributions. In this study, we utilize a long‐term, large‐scale dataset spanning 48 years and approximately 30 degrees latitude across the Canadian Atlantic shelf. We examine how climate influences the distribution and predation patterns of two invertebrates, northern shrimp Pandalus borealis and snow crab Chionoecetes opilio , aiming to evaluate the impacts of climate change on prey distributions. We found that both invertebrate species have a pronounced predicted response to climate change, with a northern shift in the distribution of northern shrimp and an overall reduction in abundance of both snow crab and shrimp associated with warming temperatures. Including predatory interactions as predictors in the SDMs (either directly via predator densities or via estimated predation rates) improved prediction accuracy for northern shrimp but not for snow crab. This is consistent with the ecology of these two species, as northern shrimp is more vulnerable to predation than snow crab. We found that the projections of future northern shrimp distributions are sensitive to the predicted spatial distribution and abundance of predators, highlighting the inherent complexity of predicting species response to climate change. Collectively, these results contribute to a broader literature that seeks to improve the capabilities of models to predict the effects of species interactions on species distributions under changing ecological conditions.

Marine Protected Areas (MPAs) are conservation tools that promote biodiversity by regulating human impacts. However, because MPAs are fixed in space and, by design, difficult to change, climate change may challenge their long-term effectiveness. It is therefore imperative to consider anticipated ecological changes in their design. We predict the time of emergence (ToE: year when temperatures will exceed a species’ tolerance) of 30 fish and invertebrate species in the Scotian Shelf-Bay of Fundy draft network of conservation areas based on climate projections under two contrasting emission scenarios (RCP 2.6 and RCP 8.5). We demonstrate a strong Southwest-to-Northeast gradient of change under both scenarios. Cold water-associated species had earlier ToEs, particularly in southwesterly areas. Under low emissions, 20.0% of habitat and 12.6% of species emerged from the network as a whole by 2100. Under high emissions, 51% of habitat and 42% of species emerged. These impacts are expected within the next 30–50 years in some southwestern areas. The magnitude and velocity of change will be tempered by reduced emissions. Our identification of high- and low-risk areas for species of direct and indirect conservation interest can support decisions regarding site and network design (and designation scheduling), promoting climate resilience.

Ongoing effects of climate change create a dual challenge of shifting distributions of organisms and concerns about the fate of organic carbon in nature. Marine sediments store vast amounts of organic carbon, but the fate of that material hinges on the biology of organisms associated with the seafloor and how they influence rates of carbon decomposition and burial. Shifts in large megafauna that disturb and thus help to oxygenate sediments could have important ramifications regarding whether sediments release or store carbon for long periods of time. We consider snow crab and lobster, two commercially important seafloor species in the Northeastern Atlantic, and the potential effects of ongoing changes in their distributions and that of their fisheries for future climate scenarios. These ongoing biogeographic shifts, considered in tandem with areas of seabed legislatively protected from fishing impacts and thus not confounded by cumulative effects of fishing gear disturbance, offer an opportunity to study how newly arrived species that disturb large areas of the seafloor might influence the global carbon cycle.

With the influence of climate change on marine systems expanding, climate adaptation will be fundamental for the future of fisheries management. An exponential increase in Atlantic halibut Hippoglossus hippoglossus landings over the past decade has coincided with warming ocean temperatures. Here, we explore how historical changes in abundance have been linked to changing thermal habitat conditions and project trends with a warming climate under different emissions scenarios. From 1990 to 2018, available thermal habitat increased by 11.6 ± 7.35% and growing degree days have increased by 13.5 ± 7.86 °C·days across the region. With warming, the probability of occurrence is projected to increase up to 20.5% in Canada by 2085 under RCP 8.5 for Atlantic halibut. Our results suggest that shifting patterns of halibut distribution and abundance are linked to thermal conditions and that continued warming will likely continue to enhance habitat conditions, leading to increased abundance in the Canadian range. Collectively, these results illustrate the influence of shifting environmental conditions on population dynamics and emphasize the importance of adaptive management practices in a dynamic future climate.

Marine Protected Areas require comprehensive monitoring to ensure objectives are achieved; however, monitoring natural ecosystems at scale is challenged by the biodiversity it aims to measure. Environmental DNA (eDNA) metabarcoding holds promise to address this monitoring challenge. We conducted paired sampling at 54 sites for fish and invertebrate assemblages in the Northwest Atlantic using groundfish trawls and eDNA metabarcoding of benthic seawater using four genetic markers (12S rRNA, 16S rRNA, 18S rRNA, and CO1). Compared to trawling, eDNA detected similar patterns of species turnover, larger estimates of gamma diversity, and smaller estimates of alpha diversity. A total of 63.6% (42/66) of fish species captured by trawling were detected by eDNA, along with an additional 26 species. Of the 24 missed detections by eDNA, 12 were inevitable as they lacked reference sequences. Excluding taxa assigned to higher than species level and those without a species name, 23.6% (17/72) of invertebrate species captured by trawling were detected by CO1, which detected an additional 98 species. We demonstrate that eDNA is capable of detecting patterns of community assemblage and species turnover in an offshore environment, emphasizing its strong potential for a non-invasive, comprehensive, and scalable tool for biodiversity monitoring supporting marine conservation programmes.

ContextPrioritizing regions that facilitate connectivity among populations is an essential principle for conservation planning. However, the lack of conspicuous geographical and environmental features that constrain dispersal and gene flow throughout life history challenges the characterization of dispersal pathways within a three-dimensional marine realm.ObjectivesTo elucidate regions of high connectivity value in the marine environment, we develop a novel approach that integrates estimates of spatial genetic structure with representation of regions of high dispersal potential for meroplankton, incorporating elements of pelagic larval and benthic adult life history.MethodsSpatial patterns of connectivity were characterized using circuit theory as an inverse function oceanographic- and habitat-based resistance to movement. We integrate emergent spatial patterns of connectivity with population genetic data to account for realized patterns of gene flow across a seascape. We apply this approach to four broadly distributed species in the Northwest Atlantic.ResultsEstimates of resistance to gene flow revealed multiple connectivity barriers not observed in oceanographic or habitat models. Comparison of isolation-by-distance versus isolation-by-resistance revealed genetic variation was best explained by seascape resistance in three of four species, supporting the resistance-based assessments of connectivity. Our approach identified areas of high and low connectivity value for each species, with overlap generally associated with geographic pinch points and areas of low genetic exchange.ConclusionsBy integrating spatial interpolations of gene flow and estimated pathways for dispersal, we develop a novel area-based metric of connectivity that considers life-history based structural constraints to dispersal and observed genetic variation. Outputs from this workflow can reveal regions of connectivity for conservation planning.

Marine Protected Areas (MPAs) have been adopted globally as a tool to combat biodiversity loss and restore marine ecosystems. Successful application of MPAs will be predicated on the ability to monitor biodiversity in a synoptic and noninvasive manner. Environmental DNA (eDNA) methods have important advantages over traditional biodiversity survey methods for monitoring conservation areas. To evaluate the efficacy of eDNA metabarcoding for fish biodiversity monitoring, we sampled 19 coastal eelgrass (Zostera marina) beds in Canada, as eelgrass beds are known for high biodiversity and significant conservation value. At each site, beach seines were used to survey fish and water samples were collected contemporaneously for eDNA metabarcoding. In total, beach seining caught 32 672 individuals across 59 fish taxa, and eDNA detected 129 fish taxa. eDNA captured site-level variation and detected higher species richness at both site and regional levels compared to seining. eDNA abundance had a positive association with capture abundance. Collectively these results highlight how eDNA metabarcoding offers an efficient approach for monitoring fish biodiversity in coastal eelgrass beds, thus providing a valuable and noninvasive tool for MPA planning and coastal monitoring.

Baseline data on the distribution and extent of biogenic habitat-forming species at a high spatial resolution are essential to inform habitat management strategies, preserve ecosystem integrity, and achieve effective conservation objectives in the nearshore. Model-based approaches to map suitable habitat for these species are a key tool to address this need, filling in gaps where observations are otherwise unavailable and remote sensing methods are limited by turbid waters or cannot be applied at scale. We developed a high resolution (35 m) ensemble species distribution model to predict the distribution of eelgrass (Zostera marina) along the Atlantic coast of Nova Scotia, Canada where the observational coverage of eelgrass occurrence is sparse and nearshore waters are optically complex. Our ensemble model was derived as a performance-weighted average prediction of 7 different modeling methods fit to 6 physical predictors (substrate type, depth, wave exposure, slope, and two bathymetric position indices) and evaluated with a 5-fold spatially-blocked cross-validation procedure. The ensemble model showed moderate predictive performance (Area Under the Receiver-Operating Characteristic Curve (AUC) = 0.803 ± 0.061, True Skill Statistic (TSS) = 0.531 ± 0.100; mean ± SD), high sensitivity (92.0 ± 4.5), and offered some improvement over individual models. Substrate type, depth, and relative wave exposure were the most influential predictors associated with eelgrass occurrence, where the highest probabilities were associated with sandy and sandy-mud sediments, depths ranging 0 m – 4 m, and low to intermediate wave exposure. Within our study region, we predicted a total extent of suitable eelgrass habitat of 38,130 ha. We found suitable habitat was particularly extensive within the long narrow inlets and extensive shallow flats of the South Shore, Eastern Shore, and Bras d’Or Lakes. We also identified substantial overlap of eelgrass habitat with previously identified Ecologically and Biologically Significant Areas that guide regional conservation planning while also highlighting areas of greater prediction uncertainty arising from disagreement among modeling methods. By offering improved sensitivity and insights into the fine-scale regional distribution of a habitat-forming species with associated uncertainties, our ensemble-based modeling approach provides improved support to numerous nearshore applications including conservation planning and restoration, marine spatial and emergency response planning, environmental impact assessments, and fish habitat protection.

Climate change and biodiversity loss are twin crises that are driving global marine conservation efforts. However, if unaccounted for, climate change can undermine the efficacy of such efforts. Despite this, integration of climate change adaptation and resilience into spatial marine conservation and management has been limited in Canada and elsewhere. With climate change impacts becoming increasingly severe, now is the time to anticipate and reduce impacts wherever possible. We provide five recommendations for an inclusive, proactive, climate-ready approach for Canada’s growing marine conservation network: (1) integrating climate-resilience as a universal objective of the Canadian Marine Conservation Network, creating and implementing (2) national transdisciplinary working groups with representation from all knowledge holders and (3) necessary tools that integrate climate change into conservation design, (4) defining operational and climate-relevant monitoring and management objectives, and (5) strengthening communication and increasing knowledge exchange around the roles and benefits of protected areas within government and towards the public. Canada’s extensive marine and coastal areas reflect national and international responsibility to engage on this issue. Canada is well positioned to assume a leading role in climate change adaptation for marine conservation and help accelerate progress towards international commitments around mitigating ongoing biodiversity loss and climate change.

A key component of the global blue economy strategy is the sustainable extraction of marine resources and conservation of marine environments through networks of marine protected areas (MPAs). Connectivity and representativity are essential factors that underlie successful implementation of MPA networks, which can safeguard biological diversity and ecosystem function, and ultimately support the blue economy strategy by balancing ocean use with conservation. New "big data" omics approaches, including genomics and transcriptomics, are becoming essential tools for the development and maintenance of MPA networks. Current molecular omics techniques, including population-scale genome sequencing, have direct applications for assessing population connectivity and for evaluating how genetic variation is represented within and among MPAs. Effective baseline characterization and long-term, scalable, and comprehensive monitoring are essential for successful MPA management, and omics approaches hold great promise to characterize the full range of marine life, spanning the microbiome to megafauna across a range of environmental conditions (shallow sea to the deep ocean). Omics tools, such as eDNA metabarcoding can provide a cost-effective basis for biodiversity monitoring in large and remote conservation areas. Here we provide an overview of current omics applications for conservation planning and monitoring, with a focus on metabarcoding, metagenomics, and population genomics. Emerging approaches, including whole-genome sequencing, characterization of genomic architecture, epigenomics, and genomic vulnerability to climate change are also reviewed. We demonstrate that the operationalization of omics tools can enhance the design, monitoring, and management of MPAs and thus will play an important role in a modern and comprehensive blue economy strategy.

There has been a proliferation of climate change vulnerability assessments of species, yet possibly due to their limited reproducibility, scalability, and interpretability, their operational use in applied decision-making remains paradoxically low. We use a newly developed Climate Risk Index for Biodiversity to evaluate the climate vulnerability and risk for ∼2,000 species across three ecosystems and 90 fish stocks in the northwest Atlantic Ocean, a documented global warming hotspot. We found that harvested and commercially valuable species were at significantly greater risk of exposure to hazardous climate conditions than non-harvested species, and emissions mitigation disproportionately reduced their projected exposure risk and cumulative climate risk. Of the 90 fish stocks we evaluated, 41% were at high climate risk, but this proportion dropped to 25% under emissions mitigation. Our structured framework demonstrates how climate risk can be operationalized to support short- and long-term fisheries objectives to enhance marine fisheries’ climate readiness and resilience.