Marine Biodiversity Observation Network Research Articles

CONCEPTUAL FOUNDATIONS FOR THE USE OF GIS TECHNOLOGIES FOR THE STUDY OF COASTAL ECOSYSTEMS OF THE AZOV-BLACK SEA BASIN IN THE FRAMEWORK OF BLUE GROWTH

Topicality. The paper discusses the possibility of using modern GIS technologies for studying coastal ecosystems of the Azov-Black Sea basin within the framework of blue growth. Today, GIS technologies greatly facilitate the study of the impact of natural and anthropogenic factors on the natural environment. The development of these technologies has increased greatly in recent decades. Now they can be used as a separate and independent tool for research in various areas of production. Based on the results obtained on the basis of GIS technologies, it is possible to draw scientific conclusions or create and implement management decisions to maintain sustainable or resilient development of the state of the environment under significant environmental pressure. Also conduct an economic, environmental, social assessment of the consequences of anthropogenic and natural impacts on marine and coastal ecosystems and the terrestrial ecosystem.Aim and tasks. Scientific substantiation of the possibilities of using modern GIS technologies regarding the sustainable development of the coastal ecosystem of the Azov-Black Sea basin within the framework of blue growth was the aim of the study.Materials and Methods. The studies were based on coastal mapping methods. The classification of environmental parameters based on United States Geological Survey (USGS) data was the initial information. The ecological coastal classification (Ecological Coastal Units (ECU)) was developed by the US Geological Survey (USGS) in collaboration with Esri and the Marine Biodiversity Observation Network (MBON). These data were developed as part of a Group on Earth Observation (GEO) initiative called GEO Ecosystems (GEO ECO). They are linked to the GEO ECO task of developing global data on coastal ecosystems.Research results. The state of the coastal strip of the seas of Ukraine according to the classification of environmental parameters based on data from the United States Geological Survey (USGS) was described in this paper. It was stated that the ecological status of coastlines is classified into five ocean parameters, two land parameters and three coastal parameters. The research results showed that the ecological situation of the coastal strips of the seas of Ukraine generally corresponds to the second, third, sixth and fifteenth classes according to the ecological coastal classification.Conclusion. It is presented that the coastal strip classification method discussed in this paper based on US Geological Survey (USGS) data can serve as a very powerful tool in the process of managing coastal zones of the Azov-Black Sea basin. It has been established that GIS technologies at the current stage of development have very great potential for studying coastal ecosystems of the Azov-Black Sea basin within the framework of blue growth.

Towards a Distributed System for Essential Variables for the Southern Ocean

The Southern Ocean (SO), delinated to the north by the Antarctic convergence, is a unique environment that experiences rapid change in some areas while remaining relatively untouched by human activities. At the same time, these ecosystems are under severe threat from climate change and other stressors. While our understanding of SO biological processes (e.g., species distributions, feeding ecology, reproduction) has greatly improved in recent years, biological data for the region remains patchy, sparse, and unstandardised depending on the taxonomic group (Griffiths et al. 2014). Due to the scarcity of standardised observations and data, it is difficult to model and predict SO ecosystem responses to climate change, which is often accompanied by other anthropogenic pressures, such as fishing and tourism. Understanding the dynamics and change in the SO necessitates a comprehensive system of observations, data management, scientific analysis, and ensuing policy recommendations. It should be built as much as feasible from current platforms and standards, and it should be visible, verifiable and shared in accordance with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles (Van de Putte and Griffiths 2021). For this we need to identify the stakeholders' needs, sources of data, the algorithms for analysing the data and the infrastructure on which to run the algorithms (Benson and Brooks 2018). Existing synergistic methods for identifying selected variables for (life) monitoring include Essential Biodiversity Variables (EBVs; Pereira and Ferrier 2013), Essential Ocean Variables (EOVs; Miloslavich and Bax 2018), Essential Climate Variables (ECVs; Bojinski and Verstraete 2014), and ecosystem Essential Ocean Variables (eEOVs; Constable and Costa 2016). (For an overview see Muller-Karger and Miloslavich 2018.) These variables, can be integrated into the Southern Ocean Observation System (SOOS) and SOOSmap but also national or global systems (e.g., Group on Earth Observations-Biodiversty Observation Network (GEO-BON)). The resulting data products can in turn be used to inform policy makers. The use of Essential Variables (EVs) marks a significant step forward in the monitoring and assessment of SO ecosystems. However, these EVs will necessitate prioritising certain variables and data collection. Here we present the outcomes of a workshop organised in August 2023 that aimed to outline the set Essential Variables and workflows required for a distributed system that can translate biodiversity data (and environmental data) into policy-relevant data products. The goals of the workshop were: Create an inventory of EVs relevant for the Southern Ocean based on existing efforts by the GEO-BON and the Marine Biodiversity Observation Network (MBON). Identify data requirements and data gaps for calculating such EVs and prioritise EVs to work on. Identify existing workflows and tools. Develop a framework for developing the workflows required to turn public biodiversity data into relevant EVs. Create an inventory of EVs relevant for the Southern Ocean based on existing efforts by the GEO-BON and the Marine Biodiversity Observation Network (MBON). Identify data requirements and data gaps for calculating such EVs and prioritise EVs to work on. Identify existing workflows and tools. Develop a framework for developing the workflows required to turn public biodiversity data into relevant EVs.

Open Source Workshop to Mobilize Marine Biodiversity Data

The 2022 Marine Biological Data Mobilization Workshop was a collaborative effort between Ocean Biodiversity Information System-USA (OBIS-USA), Marine Biodiversity Observation Network, Hakai Institute, Integrated Ocean Observing System, and Ocean Tracking Network, and hosted to promote open data and software in marine biodiversity assessment. The workshop focused on the application of the Darwin Core data standard (Wieczorek et al. 2012) to extant data and the subsequent publication of data to the open access data infrastructures provided by OBIS and the Global Biodiversity Information Facility. The curriculum for this workshop was modeled using The Carpentries evidence-based best practices of teaching. The materials and website are openly available via GitHub and are free for re-use or adaptation under an MIT license. Some unconventional features of the workshop included: Much of the workshop time was allocated to breakout rooms and individual work. The use of concurrent, topical breakout rooms led by instructors in combination with “floating” specialist volunteers. A 100% open and free virtual workshop leveraging synchronous and asynchronous communications technologies including Slack, Zoom, and GitHub. All instructional steps were offered in both Python and R (dual-programming language materials). Much of the workshop time was allocated to breakout rooms and individual work. The use of concurrent, topical breakout rooms led by instructors in combination with “floating” specialist volunteers. A 100% open and free virtual workshop leveraging synchronous and asynchronous communications technologies including Slack, Zoom, and GitHub. All instructional steps were offered in both Python and R (dual-programming language materials). The workshop was attended internationally by 63 participants, with 48 attendees joining the associated Slack group. These new members have been invited to attend a monthly working group organized to address roadblocks to standardization and promote the mobilization of marine biological data. A pre- versus post-survey analysis showed substantial improvement to self-reported data science skill levels, a multitude of positive feedback was reported, and the workshop scored a perfect 100% standard Net Promoter Score (Reichheld 2003) with 16 “promoters”, 0 “detractors”, and a total of 25 respondents.

Reef larval recruitment in response to seascape dynamics in the SW Atlantic

Advances in satellite observation have improved our capacity to track changes in the ocean with numerous ecological and conservation applications, which are yet under-explored for coastal ecology. In this study, we assessed the spatio-temporal dynamics in invertebrate larval recruitment and the Seascape Pelagic Habitat Classification, a satellite remote-sensing product developed by the Marine Biodiversity Observation Network (MBON) and delivered by the US National Oceanic and Atmospheric Administration to monitor biodiversity globally. Our ultimate goal was to identify and predict changes in coastal benthic assemblages at tropical reefs in the SW Atlantic based on integrated pelagic conditions, testing the use of MBON Seascape categorization. Our results revealed that the pelagic Seascapes correlated with monthly and seasonal variations in recruitment rates and assemblage composition. Recruitment was strongly influenced by subtropical Seascapes and was reduced by the presence of warm waters with high-nutrient contents and phytoplankton blooms, which are likely to affect reef communities in the long term. Recruitment modeling indicates that Seascapes may be more efficient than sea surface temperature in predicting benthic larval dynamics. Based on historical Seascape patterns, we identified seven events that may have impacted benthic recruitment in this region during the last decades. These findings provide new insights into the application of novel satellite remote-sensing Seascape categorizations in benthic ecology and evidence how reef larval supply in the SW Atlantic could be impacted by recent and future ocean changes.

The Marine Biodiversity Observation Network Plankton Workshops: Plankton Ecosystem Function, Biodiversity, and Forecasting—Research Requirements and Applications

The Marine Biodiversity Observation Network Plankton Workshops: Plankton Ecosystem Function, Biodiversity, and Forecasting—Research Requirements and Applications

Robots Versus Humans: Automated Annotation Accurately Quantifies Essential Ocean Variables of Rocky Intertidal Functional Groups and Habitat State

Standardized methods for effectively and rapidly monitoring changes in the biodiversity of marine ecosystems are critical to assess status and trends in ways that are comparable between locations and over time. In intertidal and subtidal habitats, estimates of fractional cover and abundance of organisms are typically obtained with traditional quadrat-based methods, and collection of photoquadrat imagery is a standard practice. However, visual analysis of quadrats, either in the field or from photographs, can be very time-consuming. Cutting-edge machine learning tools are now being used to annotate species records from photoquadrat imagery automatically, significantly reducing processing time of image collections. However, it is not always clear whether information is lost, and if so to what degree, using automated approaches. In this study, we compared results from visual quadrats versus automated photoquadrat assessments of macroalgae and sessile organisms on rocky shores across the American continent, from Patagonia (Argentina), Galapagos Islands (Ecuador), Gorgona Island (Colombian Pacific), and the northeast coast of the United States (Gulf of Maine) using the automated software CoralNet. Photoquadrat imagery was collected at the same time as visual surveys following a protocol implemented across the Americas by the Marine Biodiversity Observation Network (MBON) Pole to Pole of the Americas program. Our results show that photoquadrat machine learning annotations can estimate percent cover levels of intertidal benthic cover categories and functional groups (algae, bare substrate, and invertebrate cover) nearly identical to those from visual quadrat analysis. We found no statistical differences of cover estimations of dominant groups in photoquadrat images annotated by humans and those processed in CoralNet (binomial generalized linear mixed model or GLMM). Differences between these analyses were not significant, resulting in a Bray-Curtis average distance of 0.13 (sd 0.11) for the full label set, and 0.12 (sd 0.14) for functional groups. This is the first time that CoralNet automated annotation software has been used to monitor “Invertebrate Abundance and Distribution” and “Macroalgal Canopy Cover and Composition” Essential Ocean Variables (EOVs) in intertidal habitats. We recommend its use for rapid, continuous surveys over expanded geographical scales and monitoring of intertidal areas globally.

Data Management and Interactive Visualizations for the Evolving Marine Biodiversity Observation Network

Assessing the current state of and predicting change in the ocean’s biological and ecosystem resources requires observations and research to safeguard these valuable public assets. The Marine Biodiversity Observation Network (MBON) partnered with the Global Ocean Observing System Biology and Ecosystems Panel and the Ocean Biodiversity Information System to address these needs through collaboration, data standardization, and data sharing. Here, we describe the generalized MBON data processing flow, which includes several steps to ensure that data are findable, accessible, interoperable, and reusable. By following this flow, data collected and managed by MBON have contributed to our understanding of the Global Ocean Observing System Essential Ocean Variables and demonstrated the value of web-based, interactive tools to explore and better understand environmental change. Although the MBON’s generalized data processing flow is already in practice, work remains in building ontologies for biological concepts, improving processing scripts for data standardization, and speeding up the data collection-to-sharing timeframe.

Integrating Biodiversity and Environmental Observations in Support of National Marine Sanctuary and Large Marine Ecosystem Assessments

Species and habitats are the subjects of legislation that mandates reporting of information on ecosystem conditions. Improvements in sensors, sampling platforms, information systems, and collaborations among experts and information users now enables more effective and up-to-date information to meet regional and national needs. Specifically, advances in environmental DNA (eDNA)-based assessments of biodiversity, community science data, various underwater imaging devices, and environmental, behavioral, and physiology observations from animal telemetry provide new opportunities to address multiple requirements for reporting status and trends, including insights into life in the deep ocean. Passive and active acoustic sensors help monitor marine life, boat traffic, and noise pollution. Satellites provide repeated, frequent, and long-term records of many relevant variables from global to local scales and, when combined with numerical computer simulations, allow planning for future scenarios. Metadata standards facilitate the transfer of data from machine to machine, thus streamlining assessments and forecasting and providing knowledge directly to the public. The Marine Biodiversity Observation Network (MBON) facilitates this exchange of information on life in the sea. The collaborative efforts of the Central and Northern California Ocean Observing System (CeNCOOS) of the US Integrated Ocean Observing System and its partners provide an example of a regional MBON process for information delivery. This includes linking policy and management needs, prioritizing observing data from various platforms and methods, streamlining data handling practices, and delivery of information for management such as for the Monterey Bay National Marine Sanctuary and the California Current Large Marine Ecosystem, with iterative process adaptation.

A Global Ecological Classification of Coastal Segment Units to Complement Marine Biodiversity Observation Network Assessments

A new data layer provides Coastal and Marine Ecological Classification Standard (CMECS) labels for global coastal segments at 1 km or shorter resolution. These characteristics are summarized for six US Marine Biodiversity Observation Network (MBON) sites and one MBON Pole to Pole of the Americas site in Argentina. The global coastlines CMECS classifications were produced from a partitioning of a 30 m Landsat-derived shoreline vector that was segmented into 4 million 1 km or shorter segments. Each segment was attributed with values from 10 variables that represent the ecological settings in which the coastline occurs, including properties of the adjacent water, adjacent land, and coastline itself. The 4 million segments were classified into 81,000 coastal segment units (CSUs) as unique combinations of variable classes. We summarize the process to develop the CSUs and derive summary descriptions for the seven MBON case study sites. We discuss the intended application of the new CSU data for research and management in coastal areas.

Observing Life in the Sea Using Environmental DNA

The use of environmental DNA (eDNA) for studying the ecology and variability of life in the sea is reviewed here in the context of US interagency Marine Biodiversity Observation Network (MBON) projects. Much of the information in this paper comes from samples collected within US National Marine Sanctuaries. The field of eDNA is relatively new but growing rapidly, and it has the potential to disrupt current paradigms developed on the basis of existing measurement methods. After a general review of the field, we provide specific examples of the type of information that eDNA provides regarding the changing distribution of life in the sea over space (horizontally and vertically) and time. We conclude that eDNA analyses yield results that are similar to those collected using traditional observation methods, are complementary to them, and because of the breadth of information provided, have the potential to improve conservation and management practices. Moreover, through technology development and standardization of methods, eDNA offers a means to scale biological observations globally to a level similar to those currently made for ocean physics and biogeochemistry. This scaling can ultimately result in a far better understanding of global marine biodiversity and contribute to better management and sustainable use of the world ocean. Improved information management systems that track methods and associated metadata, together with international coordination, will be needed to realize a global eDNA observation network.

Satellite Remote Sensing and the Marine Biodiversity Observation Network: Current Science and Future Steps

Coastal ecosystems are rapidly changing due to human-caused global warming, rising sea level, changing circulation patterns, sea ice loss, and acidification that in turn alter the productivity and composition of marine biological communities. In addition, regional pressures associated with growing human populations and economies result in changes in infrastructure, land use, and other development; greater extraction of fisheries and other natural resources; alteration of benthic seascapes; increased pollution; and eutrophication. Understanding biodiversity is fundamental to assessing and managing human activities that sustain ecosystem health and services and mitigate humankind’s indiscretions. Remote-sensing observations provide rapid and synoptic data for assessing biophysical interactions at multiple spatial and temporal scales and thus are useful for monitoring biodiversity in critical coastal zones. However, many challenges remain because of complex bio-optical signals, poor signal retrieval, and suboptimal algorithms. Here, we highlight four approaches in remote sensing that complement the Marine Biodiversity Observation Network (MBON). MBON observations help quantify plankton functional types, foundation species, and unique species habitat relationships, as well as inform species distribution models. In concert with in situ observations across multiple platforms, these efforts contribute to monitoring biodiversity changes in complex coastal regions by providing oceanographic context, contributing to algorithm and indicator development, and creating linkages between long-term ecological studies, the next generations of satellite sensors, and marine ecosystem management.

Species Archetype Models of Kelp Forest Communities Reveal Diverse Responses to Environmental Gradients

Assessing ecosystem integrity by monitoring populations and communities is an important management tool, but is often limited by the immense variety of species and the rarity of many of them. Grouping species by their responses to variation in the environment is one approach to choosing species to serve as effective indicators of community change. Moreover, identifying species that are characterized by similar archetypical responses to the environment increases the power to predict their occurrence and simplifies management of diverse species assemblages by focusing on a much smaller number of archetypes. To this end, we used the species archetype model (SAM) to fit generalized linear models of environmental covariates to species distribution data in order to identify environmentally correlated groups of kelp forest species in the Santa Barbara Channel region. Eighty-two species of macroalgae, invertebrates, and fish monitored in kelp forests across the channel were grouped into one of 10 archetypes based on their similar responses to environmental parameters, with water temperature emerging as one of the strongest drivers of archetype differences. Predictive maps of the distribution of species archetypes identified sites where multiple archetypes are common, indicating high diversity, as well as sites where rare species are more likely to occur. Potential indicator species were identified for each archetype. New monitoring efforts across the growing Marine Biodiversity Observation Network could use modeling approaches like SAM to guide their designs, optimizing the cost-to-benefit ratio of monitoring whole communities.

Optimizing Large-Scale Biodiversity Sampling Effort: Toward an Unbalanced Survey Design

Acquiring marine biodiversity data is difficult, costly, and time-consuming, making it challenging to understand the distribution and abundance of life in the ocean. Historically, approaches to biodiversity sampling over large geographic scales have advocated for equivalent effort across multiple sites to minimize comparative bias. When effort cannot be equalized, techniques such as rarefaction have been applied to minimize biases by reverting diversity estimates to equivalent numbers of samples or individuals. This often results in oversampling and wasted resources or inaccurately characterized communities due to undersampling. How, then, can we better determine an optimal survey design for characterizing species richness and community composition across a range of conditions and capacities without compromising taxonomic resolution and statistical power? Researchers in the Marine Biodiversity Observation Network Pole to Pole of the Americas (MBON Pole to Pole) are surveying rocky shore macroinvertebrates and algal communities spanning ~107° of latitude and 10 biogeographic ecoregions to address this question. Here, we apply existing techniques in the form of fixed-coverage subsampling and a complementary multivariate analysis to determine the optimal effort necessary for characterizing species richness and community composition across the network sampling sites. We show that oversampling for species richness varied between ~20% and 400% at over half of studied areas, while some locations were undersampled by up to 50%. Multivariate error analysis also revealed that most of the localities were oversampled by several-fold for benthic community composition. From this analysis, we advocate for an unbalanced sampling approach to support field programs in the collection of high-quality data, where preliminary information is used to set the minimum required effort to generate robust values of diversity and composition on a site-to-site basis. As part of this recommendation, we provide statistical tools in the open-source R statistical software to aid researchers in implementing optimization strategies and expanding the geographic footprint or sampling frequency of regional biodiversity survey programs.

Reef-Fish Abundance, Biomass, and Biodiversity Inside and Outside No-Take Marine Zones in the Florida Keys National Marine Sanctuary: 1999–2018

Observations from the Reef Visual Census program in the Florida Keys National Marine Sanctuary (FKNMS) between 1999 and 2018 were used as a US Marine Biodiversity Observation Network case study to assess whether differences in biodiversity metrics (abundance, biomass, richness, Simpson diversity, and functional diversity) occurred across regions with different habitat types (high-relief, linear, and patch reefs), protection levels (no-take and unprotected zones), and types of protected zones. Protected areas had higher reef-fish biomass compared to unprotected areas at the beginning of the observation period, but these metrics decreased over time. We did not detect an effect of size of no-take marine zones, but rather found that large (18.7 km2) and small (average of 0.85 km2) areas had similar reef-fish abundance, biomass, and diversity indices. High-relief reef habitats had the greatest reef-fish abundance (20%–30%) and species richness (~20%), and nearly twice the biomass of other habitat strata, but biomass decreased 20%–30% in linear and patch reefs after 2007. Although high-relief reefs are important for biodiversity conservation and restoration, policies should address the decline in fish abundance, biomass, and diversity observed throughout the FKNMS. Monitoring should be sustained to support policies and respond to changing conditions related to climate change and resource use.

Marine Life 2030: Forecasting Changes to Ocean Biodiversity to Inform Decision-Making: A Critical Role for the Marine Biodiversity Observation Network (MBON)

Abstract Marine Life 2030 is a program to establish the globally coordinated system to deliver actionable, transdisciplinary knowledge of ocean life to those who need it, promoting human well-being, sustainable development, and ocean conservation (Figure 1). The diversity of marine habitats and species is fundamental for human survival. Biodiversity provides opportunities for multiple fisheries, the tourism industry, and harbor medicines and materials. The Marine Biodiversity Observation Network (MBON) is the platform to build the community of practice to implement Marine Life 2030. MBON fosters collaborations to coordinate collection, sharing, and application of biodiversity information. Benefits of joining MBON include expanded capacity to address research goals, leveraging resources and best practices; linking natural and social sciences to answer policy questions; engaging diverse and early-career researchers; and addressing issues of concern to humanity.

Application of a Simple, Low-Cost, Low-Tech Method to Monitor Intertidal Rocky Shore Assemblages on a Broad Geographic Scale

Identifying susceptible regions where biodiversity changes occur at fast rates is essential in order to protect and ameliorate affected areas. Large-scale coastal monitoring programs that focus on long-term variability are scarce, yet the Marine Biodiversity Observation Network Pole to Pole is currently developing a regional collaboration throughout the American continent collecting biodiversity data in coastal habitats with a standardized systematic protocol. The use of photographic methods to collect assemblage data on intertidal rocky shores can be appropriate. The goal of this study was to analyze the performance of a simple, low-cost, non-destructive and low-tech photographic method on a broad geographical scale (∼ 2,000 km) of Atlantic Patagonian coastline. Concurrently, we aimed to identify indicators whose cover, presence or condition can be followed in time and used as beacons of change in biodiversity on these rocky intertidal shores. We also explored the potential relationships between assemblage structure and environmental variables, such as seascape classes. We identified and propose cover of mytilids, Corallina spp. and bare substrate as indicators of change due to their ecological relevance in intertidal assemblages and their visible and rapid response to human stressors or changes in environmental conditions. Finally, we illustrate the practicality and usefulness of remotely accessible environmental data, for instance the seascape classes approach as an integrative tool for large-scale rocky shore studies.

Biodiversity monitoring in rocky shores: Challenges of devising a globally applicable and cost-effective protocol

Large-scale coastal monitoring programs that focus on long-term inter-annual and seasonal community variability are rare mostly because they are costly, logistically complex and require coordination by groups of dedicated scientists. The Marine Biodiversity Observation Network (MBON) is currently developing a regional collaboration throughout the American continent to collect biological data in coastal habitats using common methodologies and sharing best practices. The goal of this paper is to compare two survey methods with contrasting field time demands (i.e. in situ collected data vs. photoquadrats), identify the scales at which they may differ, and determine the convenience and suitability for their use in large-scale standardized biodiversity studies on rocky intertidal shores. Visual quadrat (VQ) data collected in the field was compared with data obtained from photographs of those same quadrats (PQ) digitally analyzed at three intertidal levels within two sites during four different times of the year. Analysis by site showed a seasonal effect in all shore levels and an effect of methods only at the low intertidal level at both sites. The PQ method is a reliable, cheap and time efficient tool for the long-term study of rocky intertidal communities. It is capable of detecting the spatial and temporal variability as the VQ method at various scales including tidal height, time of the year and site. We suggest the use of the mid intertidal level as the standardized sampling zone across latitudes on the basis of having higher diversity than the high intertidal, more sampling time than the low intertidal level, and being more affected by climate change both through changes in the air (temperature and wind) and in the ocean (warming and acidification). This study provides empirical evidence that a simple, low-cost and low-tech method may offer the required information that large-scale monitoring programs need.

Mass Mortality of Foundation Species on Rocky Shores: Testing a Methodology for a Continental Monitoring Program

Global concern around substantial losses of biodiversity has led to the development of a number of monitoring programs. Networks were established to obtain appropriate data on the spatial and temporal variation of marine species on rocky shores. Recently, the Marine Biodiversity Observation Network Pole to Pole of the Americas (MBON P2P) program was established and is coordinating biodiversity surveys along coastal areas throughout the continent. The goal of this paper was to test the usefulness and adequacy of a methodology proposed for the MBON P2P program. Changes in benthic assemblage cover were studied on monitored sites in northern Patagonia before and after the 2019 austral summer. Long-term dynamics of mussel bed is described based on existing data. Results showed that assemblages before the 2019 austral summer were different from assemblages after it. Thus, a mussel mass mortality event could be detected with this methodology. It took less than a year for mussel cover to drop from 90 to almost 0%; even where substantial changes in mussel bed cover were not registered in the previous ~20 years at the study area. This simple methodology is an adequate tool for monitoring rocky intertidal habitats. Yearly monitoring is needed, as a minimum, to perceive this kind of process timely. Real-time detection offers the opportunity of properly understanding the causes that lead to the loss of key community components, such as these foundation species. Furthermore, it would provide early warning to decision-makers enhancing the chances of conservation of natural environments and their ecosystem services.

A Marine Biodiversity Observation Network for Genetic Monitoring of Hard-Bottom Communities (ARMS-MBON)

Marine hard-bottom communities are undergoing severe change under the influence of multiple drivers, notably climate change, extraction of natural resources, pollution and eutrophication, habitat degradation, and invasive species. Monitoring marine biodiversity in such habitats is, however, challenging as it typically involves expensive, non-standardized, and often destructive sampling methods that limit its scalability. Differences in monitoring approaches furthermore hinders inter-comparison among monitoring programs. Here, we announce a Marine Biodiversity Observation Network (MBON) consisting of Autonomous Reef Monitoring Structures (ARMS) with the aim to assess the status and changes in benthic fauna with genomic-based methods, notably DNA metabarcoding, in combination with image-based identifications. This article presents the results of a 30-month pilot phase in which we established an operational and geographically expansive ARMS-MBON. The network currently consists of 20 observatories distributed across European coastal waters and the polar regions, in which 134 ARMS have been deployed to date. Sampling takes place annually, either as short-term deployments during the summer or as long-term deployments starting in spring. The pilot phase was used to establish a common set of standards for field sampling, genetic analysis, data management, and legal compliance, which are presented here. We also tested the potential of ARMS for combining genetic and image-based identification methods in comparative studies of benthic diversity, as well as for detecting non-indigenous species. Results show that ARMS are suitable for monitoring hard-bottom environments as they provide genetic data that can be continuously enriched, re-analyzed, and integrated with conventional data to document benthic community composition and detect non-indigenous species. Finally, we provide guidelines to expand the network and present a sustainability plan as part of the European Marine Biological Resource Centre (www.embrc.eu).

Sandy Beach Macrofauna of Yucatán State (Mexico) and Oil Industry Development in the Gulf of Mexico: First Approach for Detecting Environmental Impacts

The biodiversity of the coastal ecosystems in the Gulf of Mexico is threatened by anthropogenic activities of various kinds. The predominant portion of the land-sea margin in the State of Yucatán consists of exposed sandy beaches. This ecosystem is threatened by several activities that vary in spatial scales, at a local: cargo/fishing ports, touristic facilities, maritime traffic, and domestic pollution; and at a larger scale: the forthcoming development of the oil industry. In the absence of information about the biodiversity of these beaches, we implement the Marine Biodiversity Observation Network Pole to Pole sampling protocol to (1) Quantify the spatial patterns of diversity of macrofauna along the beaches; (2) quantify current levels of pollution by hydrocarbons (aromatic and aliphatic); (3) estimate sampling effort for future environmental impact assessments. During November 2018, six localities along the coastline of Yucatán State were sampled following a spatial hierarchical design that included three sites at each locality, and 9-18 core samples in the intertidal strata of each site. As a result, 31 species of invertebrates were registered. The patterns of distribution and abundance of species showed that there was a base community structure along the entire coast dominated by four species. In general, the density of species was relatively low (2-4 species/0.01 m3) and the density of individuals was high (20-200 ind./0.01 m3). The beta diversity was higher between localities with good environmental health, but the estimated alpha diversities did not show a pattern regarding the health of the coast. Lastly, the overall number of species reported suggest that gamma diversity of the macrofauna in the beaches of Yucatán is within the highest known worldwide. Levels of hydrocarbons detected in this study are exceptionally low compared to those reported for other coastal areas of the Gulf of Mexico and are several orders of magnitude lower than those considered as lower-threshold values for marine sediments. The biological and chemical patterns reported here indicated that it is an appropriate moment to start long-term monitoring. The sampling design we suggest is based on statistical precision and internationally recognized protocols for assessment of marine diversity on sandy beaches.