Description: The neritic-oceanic squid Illex argentinus supports one of the largest fisheries in the Southwest Atlantic. It is characterized by extensive migrations across the Patagonian Shelf and complex population structure comprising distinct seasonal spawning groups. To address uncertainty as to the demographic independence of these groups that may compromise sustainable management, a multidisciplinary approach was applied integrating statolith ageing with genome-wide single-nucleotide polymorphism (SNP) analysis. To obtain complete coverage of the spawning groups, sampling was carried out at multiple times during the 2020 fishing season and covered a large proportion of the species' range across the Patagonian Shelf. Statolith and microstructure analysis revealed three distinct seasonal spawning groups of winter-, spring-, and summer-hatched individuals. Subgroups were identified within each seasonal group, with statolith microstructure indicating differences in environmental conditions during ontogeny. Analysis of 〉10 000 SNPs reported no evidence of neutral or non-neutral genetic structure among the various groups. These findings indicate that I. argentinus across the Patagonian Shelf belong to one genetic population and a collaborative management strategy involving international stakeholders is required. The connectivity among spawning groups may represent a "bet-hedging" mechanism important for population resilience.

Description: The development and physiology of herring larvae were monitored for individuals reared in control and combined warming-acidification crossed with different food quality treatments. The experiment revealed that warming and acidification triggers a stress response at the molecular level and decrease herring larvae size-at-stage. Global change puts coastal systems under pressure, affecting the ecology and physiology of marine organisms. In particular, fish larvae are sensitive to environmental conditions, and their fitness is an important determinant of fish stock recruitment and fluctuations. To assess the combined effects of warming, acidification and change in food quality, herring larvae were reared in a control scenario (11 & DEG;C*pH 8.0) and a scenario predicted for 2100 (14 & DEG;C*pH 7.6) crossed with two feeding treatments (enriched in phosphorus and docosahexaenoic acid or not). The experiment lasted from hatching to the beginning of the post-flexion stage (i.e. all fins present) corresponding to 47 days post-hatch (dph) at 14 & DEG;C and 60 dph at 11 & DEG;C. Length and stage development were monitored throughout the experiment and the expression of genes involved in growth, metabolic pathways and stress responses were analysed for stage 3 larvae (flexion of the notochord). Although the growth rate was unaffected by acidification and temperature changes, the development was accelerated in the 2100 scenario, where larvae reached the last developmental stage at a smaller size (-8%). We observed no mortality related to treatments and no effect of food quality on the development of herring larvae. However, gene expression analyses revealed that heat shock transcripts expression was higher in the warmer and more acidic treatment. Our findings suggest that the predicted warming and acidification environment are stressful for herring larvae, inducing a decrease in size-at-stage at a precise period of ontogeny. This could either negatively affect survival and recruitment via the extension of the predation window or positively increase the survival by reducing the larval stage duration.

Description: The publication provides a summary on the state of the climate indicators in 2021 including global temperatures trends and its distribution around the globe; most recent finding on Green House Gases concentration, Ocean indicators; Cryosphere with a particular emphasis on Arctic and Antarctic sea ice, greenland ice sheet and glaciers and snow cover; Stratospheric Ozone; analysis of major drivers of inter-annual climate variability during the year including the El Niño Souther Oscillation and other Ocean and Atmshperic indices; global precipitation distribution over land; extreme events including those related to tropical cyclones and wind storms; flooding, drought and extreme heat and cold events. The publication also provides most recent finding on climate related risks and impacts including on food security, humanitarian and population displacement aspects and impact on ecosystems.

Description: Biological invasions are a global challenge that has received insufficient attention. Recently available cost syntheses have provided policy- and decision makers with reliable and up-to-date information on the economic impacts of biological invasions, aiming to motivate effective management. The resultant InvaCost database is now publicly and freely accessible and enables rapid extraction of monetary cost information. This has facilitated knowledge sharing, developed a more integrated and multidisciplinary network of researchers, and forged multidisciplinary collaborations among diverse organizations and stakeholders. Over 50 scientific publications so far have used the database and have provided detailed assessments of invasion costs across geographic, taxonomic, and spatiotemporal scales. These studies have provided important information that can guide future policy and legislative decisions on the management of biological invasions while simultaneously attracting public and media attention. We provide an overview of the improved availability, reliability, standardization, and defragmentation of monetary costs; discuss how this has enhanced invasion science as a discipline; and outline directions for future development.

Description: Host-microbe interactions play crucial roles in marine ecosystems. However, we still have very little understanding of the mechanisms that govern these relationships, the evolutionary processes that shape them, and their ecological consequences. The holobiont concept is a renewed paradigm in biology that can help to describe and understand these complex systems. It posits that a host and its associated microbiota with which it interacts, form a holobiont, and have to be studied together as a coherent biological and functional unit to understand its biology, ecology, and evolution. Here we discuss critical concepts and opportunities in marine holobiont research and identify key challenges in the field. We highlight the potential economic, sociological, and environmental impacts of the holobiont concept in marine biological, evolutionary, and environmental sciences. Given the connectivity and the unexplored biodiversity specific to marine ecosystems, a deeper understanding of such complex systems requires further technological and conceptual advances, e.g., the development of controlled experimental model systems for holobionts from all major lineages and the modeling of (info)chemical-mediated interactions between organisms. Here we propose that one significant challenge is to bridge cross-disciplinary research on tractable model systems in order to address key ecological and evolutionary questions. This first step is crucial to decipher the main drivers of the dynamics and evolution of holobionts and to account for the holobiont concept in applied areas, such as the conservation, management, and exploitation of marine ecosystems and resources, where practical solutions to predict and mitigate the impact of human activities are more important than ever.

Description: Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific disciplines. We first highlight why machine learning is needed in marine ecology. Then we provide a quick primer on machine learning techniques and vocabulary. We built a database of & SIM;1000 publications that implement such techniques to analyse marine ecology data. For various data types (images, optical spectra, acoustics, omics, geolocations, biogeochemical profiles, and satellite imagery), we present a historical perspective on applications that proved influential, can serve as templates for new work, or represent the diversity of approaches. Then, we illustrate how machine learning can be used to better understand ecological systems, by combining various sources of marine data. Through this coverage of the literature, we demonstrate an increase in the proportion of marine ecology studies that use machine learning, the pervasiveness of images as a data source, the dominance of machine learning for classification-type problems, and a shift towards deep learning for all data types. This overview is meant to guide researchers who wish to apply machine learning methods to their marine datasets.

Description: Biological invasions are a major component of anthropogenic environmental change, incurring substantial economic costs across all sectors of society and ecosystems. There have been recent syntheses of costs for a number of countries using the newly compiled InvaCost database, but New Zealand—a country renowned for its approach to invasive species management—has so far not been examined. Here we analyse reported economic damage and management costs incurred by biological invasions in New Zealand from 1968 to 2020. In total, US$69 billion (NZ$97 billion) is currently reported over this ∼50-year period, with approximately US$9 billion of this considered highly reliable, observed (c.f. projected) costs. Most (82%) of these observed economic costs are associated with damage, with comparatively little invested in management (18%). Reported costs are increasing over time, with damage averaging US$120 million per year and exceeding management expenditure in all decades. Where specified, most reported costs are from terrestrial plants and animals, with damages principally borne by primary industries such as agriculture and forestry. Management costs are more often associated with interventions by authorities and stakeholders. Relative to other countries present in the InvaCost database, New Zealand was found to spend considerably more than expected from its Gross Domestic Product on pre- and post-invasion management costs. However, some known ecologically (c.f. economically) impactful invasive species are notably absent from estimated damage costs, and management costs are not reported for a number of game animals and agricultural pathogens. Given these gaps for known and potentially damaging invaders, we urge improved cost reporting at the national scale, including improving public accessibility through increased access and digitisation of records, particularly in overlooked socioeconomic sectors and habitats. This also further highlights the importance of investment in management to curtail future damages across all sectors.

Description: The Ægir Ridge System (ARS) is an ancient extinct spreading axis in the Nordic seas extending from the upper slope east of Iceland (∼550 m depth), as part of its Exclusive Economic Zone (EEZ), to a depth of ∼3,800 m in the Norwegian basin. Geomorphologically a rift valley, the ARS has a canyon-like structure that may promote increased diversity and faunal density. The main objective of this study was to characterize benthic habitats and related macro- and megabenthic communities along the ARS, and the influence of water mass variables and depth on them. During the IceAGE3 expedition (Icelandic marine Animals: Genetics and Ecology) on RV Sonne in June 2020, benthic communities of the ARS were surveyed by means of a remotely-operated vehicle (ROV) and epibenthic sledge (EBS). For this purpose, two working areas were selected, including abyssal stations in the northeast and bathyal stations in the southwest of the ARS. Video and still images of the seabed were usedtoqualitatively describebenthic habitats based on the presence of habitat-forming taxa and the physical environment. Patterns of diversity and community composition of the soft-sediment macrofauna, retrieved from the EBS, were analyzed in a semiquantitative manner. These biological data were complemented by producing high-resolution bathymetric maps using the vessel’s multi-beam echosounder system. As suspected, we were able to identify differences in species composition and number of macro- and megafaunal communities associated with a depth gradient. A biological canyon effect became evident in dense aggregates of megafaunal filter feeders and elevated macrofaunal densities. Analysis of videos and still images from the ROV transects also led to the discovery of a number ofVulnerable Marine Ecosystems (VMEs) dominated by sponges and soft corals characteristic of the Arctic region. Directions for future research encompass a more detailed, quantitative study of the megafauna and more coherent sampling over the entire depth range in order to fully capture the diversity of the habitats and biota of the region. The presence of sensitive biogenic habitats, alongside seemingly high biodiversity and naturalness are supportive of ongoing considerations of designating part of the ARS as an “Ecologically and Biologically Significant Area” (EBSA).