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Aim: Understanding the spatial ecology of animal movements is a critical element in conserving long-lived, highly mobile marine species. Analyzing networks developed from movements of six sea turtle species reveals marine connectivity and can help prioritize conservation efforts. Location: Global. Methods: We collated telemetry data from 1235 individuals and reviewed the literature to determine our dataset's representativeness. We used the telemetry data to develop spatial networks at different scales to examine areas, connections, and their geographic arrangement. We used graph theory metrics to compare networks across regions and species and to identify the role of important areas and connections. Results: Relevant literature and citations for data used in this study had very little overlap. Network analysis showed that sampling effort influenced network structure, and the arrangement of areas and connections for most networks was complex. However, important areas and connections identified by graph theory metrics can be different than areas of high data density. For the global network, marine regions in the Mediterranean had high closeness, while links with high betweenness among marine regions in the South Atlantic were critical for maintaining connectivity. Comparisons among species-specific networks showed that functional connectivity was related to movement ecology, resulting in networks composed of different areas and links. Main conclusions: Network analysis identified the structure and functional connectivity of the sea turtles in our sample at multiple scales. These network characteristics could help guide the coordination of management strategies for wide-ranging animals throughout their geographic extent. Most networks had complex structures that can contribute to greater robustness but may be more difficult to manage changes when compared to simpler forms. Area-based conservation measures would benefit sea turtle populations when directed toward areas with high closeness dominating network function. Promoting seascape connectivity of links with high betweenness would decrease network vulnerability. © 2022 The Authors. Diversity and Distributions published by John Wiley & Sons Ltd.

International audience; The distributions of migratory species in the ocean span local, national and international jurisdictions. Across these ecologically interconnected regions, migratory marine species interact with anthropogenic stressors throughout their lives. Migratory connectivity, the geographical linking of individuals and populations throughout their migratory cycles, influences how spatial and temporal dynamics of stressors affect migratory animals and scale up to influence population abundance, distribution and species persistence. Population declines of many migratory marine species have led to calls for connectivity knowledge, especially insights from animal tracking studies, to be more systematically and synthetically incorporated into decision-making. Inclusion of migratory connectivity in the design of conservation and management measures is critical to ensure they are appropriate for the level of risk associated with various degrees of connectivity. Three mechanisms exist to incorporate migratory connectivity into international marine policy which guides conservation implementation: site-selection criteria, network design criteria and policy recommendations. Here, we review the concept of migratory connectivity and its use in international policy, and describe the Migratory Connectivity in the Ocean system, a migratory connectivity evidence-base for the ocean. We propose that without such collaboration focused on migratory connectivity, efforts to effectively conserve these critical species across jurisdictions will have limited effect.

Biological diversity is one of the most important measures for marine conservation in the high seas. However, data and tools to assess and quantify biodiversity in the high seas are still not well developed. This hinders the development of the open-access tools necessary to assess biodiversity across space and time. Here, we examine prototype online mapping and visualization tools we developed within the OBIS-SEAMAP data center, a thematic node of the Ocean Biogeo- graphic Information System (OBIS) specializing in marine mammal, seabird and sea turtle obser- vations, to facilitate spatiotemporal assessments of biodiversity in the high seas. Our aims are to (1) summarize basic data needs for assessing biodiversity issues in the high seas; (2) discuss tech- nical challenges to address such needs and establish a publicly accessible framework for biodiver- sity assessments; and (3) demonstrate how our prototype framework facilitates these assessments using a preliminary case study. We anticipate that this will serve as a model for marine researchers and managers to develop similar frameworks or improve the existing ones for ecological assess- ments. Of special importance is the application of these assessment tools to emerging high seas biodiversity identification processes such as the UN Convention on Biological Diversity, Ecologi- cally or Biologically Significant Marine Areas.

We successfully developed an extension of the OBIS-SEAMAP database, a global biogeographic database specializing in marine mammals, seabirds and sea turtles, to integrate passive acoustic monitoring (PAM) data with other commonly collected data types (i.e. line-transect visual sightings, animal telemetry, and photo-identification). As part of this effort, we made significant improvements in mapping and visualization tools for PAM data, including spatially and temporally interactive summary statistics, diel plots, temporal effort representation, and the unique rendering of PAM data to distinguish them from other data types. In this paper, we summarize technical challenges we overcame, report the methodologies and implementation of the integration, and conduct case studies using visual sightings and PAM data from bowhead whales and Risso's dolphins to demonstrate how the integrated database facilitates in-depth ecological assessments that form the foundation for spatially-explicit conservation efforts.

Spatially explicit conservation efforts to identify, designate, and prioritize protected areas or biologically significant areas require analyses beyond basic species distribution and abundance studies, including assessments of migration patterns, habitat use, and ecological drivers of behavior. With the advent of alternate survey methods and platforms within the marine environment (e.g. satellite telemetry, passive acoustics, photo identification, nesting site monitoring and genetic sampling) in addition to traditional shipboard or aerial visual surveys, researchers have been developing novel analytical and modeling methodologies to fulfill such in-depth ecological assessments. This trend has raised interests and needs not only in filling spatial, temporal and ‘ecological’ gaps but also in the synthesis of these disparate data from multiple methods/platforms. OBIS–SEAMAP, a thematic node of the Ocean Biogeographic Information System (OBIS) specializing on marine megavertebrates, takes a unique approach to data integration into the OBIS–SEAMAP database to enable novel applications of a global biogeographic database. In this paper, we summarize our efforts to accomplish this integration and to develop novel mapping and visualization tools available on the OBIS–SEAMAP web site. We also discuss advantages and implications of an integrated database in advancing ecological assessments and modeling efforts based on preliminary assessments of the OBIS–SEAMAP data and derived products. Finally, we make critical suggestions for the design and function of biogeographic databases to make contributed data more useful for conservation efforts.

Cetaceans are protected worldwide but vulnerable to incidental harm from an expanding array of human activities at sea. Managing potential hazards to these highly-mobile populations increasingly requires a detailed understanding of their seasonal distributions and habitats. Pursuant to the urgent need for this knowledge for the U.S. Atlantic and Gulf of Mexico, we integrated 23 years of aerial and shipboard cetacean surveys, linked them to environmental covariates obtained from remote sensing and ocean models, and built habitat-based density models for 26 species and 3 multi-species guilds using distance sampling methodology. In the Atlantic, for 11 well-known species, model predictions resembled seasonal movement patterns previously suggested in the literature. For these we produced monthly mean density maps. For lesser-known taxa, and in the Gulf of Mexico, where seasonal movements were less well described, we produced year-round mean density maps. The results revealed high regional differences in small delphinoid densities, confirmed the importance of the continental slope to large delphinoids and of canyons and seamounts to beaked and sperm whales, and quantified seasonal shifts in the densities of migratory baleen whales. The density maps, freely available online, are the first for these regions to be published in the peer-reviewed literature.

Across many scientific domains, the ability to aggregate disparate datasets enables more meaningful global analyses. Within marine biology, the Census of Marine Life served as the catalyst for such a global data aggregation effort. Under the Census framework, the Ocean Biogeographic Information System was established to coordinate an unprecedented aggregation of global marine biogeography data. The OBIS data system now contains 31.3 million observations, freely accessible through a geospatial portal. The challenges of storing, querying, disseminating, and mapping a global data collection of this complexity and magnitude are significant. In the face of declining performance and expanding feature requests, a redevelopment of the OBIS data system was undertaken. Following an Open Source philosophy, the OBIS technology stack was rebuilt using PostgreSQL, PostGIS, GeoServer and OpenLayers. This approach has markedly improved the performance and online user experience while maintaining a standards-compliant and interoperable framework. Due to the distributed nature of the project and increasing needs for storage, scalability and deployment flexibility, the entire hardware and software stack was built on a Cloud Computing environment. The flexibility of the platform, combined with the power of the application stack, enabled rapid re-development of the OBIS infrastructure, and ensured complete standards-compliance.

Recent expansion in the capabilities of passive acoustic monitoring of sound-producing animals is providing expansive data sets in many locations. These long-termdata sets will allowthe investigation of questions related to the ecology of sound-producing animals on time scales ranging fromdiel and seasonal to inter-annual and decadal. Analyses of these data often span multiple analysts from various research groups over several years of effort and, as a consequence, have begun to generate large amounts of scattered acoustic metadata. It has therefore become imperative to standardize the types of metadata being generated. A critical aspect of being able to learn from such large and varied acoustic data sets is providing consistent and transparent access that can enable the integration of various analysis efforts. This is juxtaposed with the need to include new information for specific research questions that evolve over time. Hence, a method is proposed for organizing acoustic metadata that addresses many of the problems associated with the retention of metadata from large passive acoustic data sets. A structure was developed for organizing acoustic metadata in a consistent manner, specifying required and optional terms to describe acoustic information derived from a recording. A client-server database was created to implement this data representation as a networked data service that can be accessed from several programming languages. Support for data import froma wide variety of sources such as spreadsheets and databases is provided. The implementation was extended to access Internet-available data products, permitting access to a variety of environmental information types (e.g. sea surface temperature, sunrise/sunset, etc.) fromawide range of sources as if they were part of the data service. This metadata service is in use at several institutions and has been used to track and analyze millions of acoustic detections from marine mammals, fish, elephants, and anthropogenic sound sources. Publisher PDF

The science needed to understand highly migratory marine mammal, sea bird, and sea turtle species is not adequately addressed by individual data collections developed for a single region or single time period. These data must be brought together into a common, global map based on a coherent, interoperable, and openly accessible information system. This need was clearly articulated by the National Oceanographic Partnership Program (NOPP) and the Alfred P. Sloan Foundation when they co-sponsored a new effort to directly address this issue in 2002. The result is OBIS-SEAMAP: the world data-center for marine mammal, sea bird, and sea turtle information. OBIS-SEAMAP brings together georeferenced distribution, abundance, and telemetry data with tools to query and assess these species in a dynamic and searchable environment. In a second round of NOPP support that began in 2007, the National Science Foundation is helping expand this effort into new technologies and data types. To date, the OBIS-SEAMAP information system includes more than 2.2 million observation records from over 230 data sets spanning 73 years (1935-2008), and growth of this data archive is accelerating. All of these data are provided by a growing international network of individual and institutional data providers.

Our ability to inform conservation and management of species is fundamentally limited by the availability of relevant biogeographic data, use of statistically robust predictive models, and presentation of results to decision makers. Despite the ubiquity of presence-only models, where available, survey effort should be included in the modeling process to limit spatial bias. The biogeographic archive therefore should be able to store and serve related spatial information such as lines of survey effort or polygons of the study area, best accomplished through geospatial web services such as the Open Geospatial Consortium (OGC) Web Feature Service (WFS). Ideally data could then be easily fetched by modelers into a scientific workflow, providing a visually intuitive, modular, reusable canvas for linking analytical processes without the need to code. Species distribution model results should be easily accessible to decision makers, such as through a web-based spatial decision support system (SDSS). With these principles in mind, we describe our progress to date serving marine animal biogeographic data from OBIS-SEAMAP ( http://seamap.env.duke.edu ), and consuming the data for predictive environmental modeling of cetaceans. Using geospatial web services to automate the scientific workflow process, marine mammal observations from OBIS-SEAMAP are used to sample through date-synchronous remotely sensed satellite data for building multivariate habitat models using a variety of statistical techniques (GLM, GAM, and CART). We developed custom scientific workflows using ESRI Model Builder, ArcGIS geoprocessor, R statistical package, Python scripting language, PostGIS geodatabase, and UMN MapServer. These model outputs are then passed to an SDSS with spatial summary capability. Custom products will be open-source and freely available. In the future, we hope to integrate technologies such as OGC WCS, OPeNDAP, and Kepler. The principles and lessons described here can be broadly applied to serving biogeographic data, species distribution modeling, and decision support within the ecological informatics community.

The Ocean Biogeographic Information System (OBIS) aims to integrate smaller, isolated datasets into a larger, more comprehensive picture of life in our oceans. Therefore, OBIS provides a gateway to many datasets containing information on where and when marine species have been observed. The datasets within OBIS are contributed by a network of hundreds of institutes, projects and individuals, all with the common goal to gain scientific knowledge and to make these data and knowledge easily available to the public. Until recently, OBIS had solely focused on biogeographic data, in the form of presence of marine species in space and time. Data collected for biological studies however often include more than just presence or abundance. Physical and chemical measurements are often taken concomitantly providing insights into the environmental conditions the species live in. Details on the nature of the sampling methods, equipment used and effort can also be of major importance. Based on requirements from the growing OBIS community for data archiving and scientific applications, OBIS completed the OBIS-ENV-DATA project in 2017 to enhance its data standard by accommodating additional data types (De Pooter et al. 2017). The proposed standard allows for the management of sampling methodology, animal tracking and telemetry data, and environmental measurements such as nutrient concentrations, sediment characteristics and other abiotic parameters measured during sampling. The new OBIS data standard builds on the Darwin Core Archive and on practices adopted by the Global Biodiversity Information Facility (GBIF). It consists of an Event Core in combination with an Occurrence Extension and an enhanced MeasurementOrFact Extension Fig. 1. This new structure enables the linkage of measurements or facts - quantitative or qualitative properties - to both sampling events and species occurrences, and includes additional fields for property standardization. The OBIS standard also embraces the use of the new Darwin Core term parentEventID, enabling a sampling event hierarchy. During the follow-up project "OBIS-Event Data", the format will be further fine-tuned during two workshops with two different communities of practice. The first workshop (April 2018) will focus on animal tagging and tracking data, while the second one (October 2018) will tackle macro- and meiobenthos data. The OBIS-Event Data project will also develop the first data products and applications based on the standard and make these tools part of the core OBIS data system output. We believe that the adoption of this new data standard by the international community will be key to improving the effectiveness of the knowledge base and will enhance integration and management of critical data needed to understand ecological and biological processes in the ocean.

The Ocean Biogeographic Information System (OBIS) is the world's most comprehensive online, open-access database of marine species distributions. OBIS grows with millions of new species observations every year. Contributions come from a network of hundreds of institutions, projects and individuals with common goals: to build a scientific knowledge base that is open to the public for scientific discovery and exploration and to detect trends and changes that inform society as essential elements in conservation management and sustainable development. Until now, OBIS has focused solely on the collection of biogeographic data (the presence of marine species in space and time) and operated with optimized data flows, quality control procedures and data standards specifically targeted to these data. Based on requirements from the growing OBIS community to manage datasets that combine biological, physical and chemical measurements, the OBIS-ENV-DATA pilot project was launched to develop a proposed standard and guidelines to make sure these combined datasets can stay together and are not, as is often the case, split and sent to different repositories. The proposal in this paper allows for the management of sampling methodology, animal tracking and telemetry data, biological measurements (e.g., body length, percent live cover, ...) as well as environmental measurements such as nutrient concentrations, sediment characteristics or other abiotic parameters measured during sampling to characterize the environment from which biogeographic data was collected. The recommended practice builds on the Darwin Core Archive (DwC-A) standard and on practices adopted by the Global Biodiversity Information Facility (GBIF). It consists of a DwC Event Core in combination with a DwC Occurrence Extension and a proposed enhancement to the DwC MeasurementOrFact Extension. This new structure enables the linkage of measurements or facts - quantitative and qualitative properties - to both sampling events and species occurrences, and includes additional fields for property standardization. We also embrace the use of the new parentEventID DwC term, which enables the creation of a sampling event hierarchy. We believe that the adoption of this recommended practice as a new data standard for managing and sharing biological and associated environmental datasets by IODE and the wider international scientific community would be key to improving the effectiveness of the knowledge base, and will enhance integration and management of critical data needed to understand ecological and biological processes in the ocean, and on land. Fil: De Pooter, Daphnis. Flanders Marine Institute; Bélgica Fil: Appeltans, Ward. UNESCO-IOC; Bélgica Fil: Bailly, Nicolas. Hellenic Centre for Marine Research, MedOBIS; Grecia Fil: Bristol, Sky. United States Geological Survey; Estados Unidos Fil: Deneudt, Klaas. Flanders Marine Institute; Bélgica Fil: Eliezer, Menashè. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Italia Fil: Fujioka, Ei. University Of Duke. Nicholas School Of Environment. Duke Marine Lab; Estados Unidos Fil: Giorgetti, Alessandra. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Italia Fil: Goldstein, Philip. University of Colorado Museum of Natural History, OBIS; Estados Unidos Fil: Lewis, Mirtha Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico. Centro para el Estudio de Sistemas Marinos; Argentina Fil: Lipizer, Marina. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Italia Fil: Mackay, Kevin. National Institute of Water and Atmospheric Research; Nueva Zelanda Fil: Marin, Maria Rosa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Centro Nacional Patagónico; Argentina Fil: Moncoiffé, Gwenaëlle. British Oceanographic Data Center; Reino Unido Fil: Nikolopoulou, Stamatina. Hellenic Centre for Marine Research, MedOBIS; Grecia Fil: Provoost, Pieter. UNESCO-IOC; Bélgica Fil: Rauch, Shannon. Woods Hole Oceanographic Institution; Estados Unidos Fil: Roubicek, Andres. CSIRO Oceans and Atmosphere; Australia Fil: Torres, Carlos. Universidad Autonoma de Baja California Sur; México Fil: van de Putte, Anton. Royal Belgian Institute for Natural Sciences; Bélgica Fil: Vandepitte, Leen. Flanders Marine Institute; Bélgica Fil: Vanhoorne, Bart. Flanders Marine Institute; Bélgica Fil: Vinci, Mateo. Istituto Nazionale di Oceanografia e di Geofisica Sperimentale; Italia Fil: Wambiji, Nina. Kenya Marine and Fisheries Research Institute; Kenia Fil: Watts, David. CSIRO Oceans and Atmosphere; Australia Fil: Klein Salas, Eduardo. Universidad Simon Bolivar; Venezuela Fil: Hernandez, Francisco. Flanders Marine Institute; Bélgica

The OBIS-SEAMAP project has acquired and served high-quality marine mammal, seabird, and sea turtle data to the public since its inception in 2002. As data accumulated, spatial and temporal biases resulted and a comprehensive gap analysis was needed in order to assess coverage to direct data acquisition for the OBIS-SEAMAP project and for taxa researchers should true gaps in knowledge exist. All datasets published on OBIS-SEAMAP up to February 2009 were summarized spatially and temporally. Seabirds comprised the greatest number of records, compared to the other two taxa, and most records were from shipboard surveys, compared to the other three platforms. Many of the point observations and polyline tracklines were located in northern and central Atlantic and the northeastern and central-eastern Pacific. The Southern Hemisphere generally had the lowest representation of data, with the least number of records in the southern Atlantic and western Pacific regions. Temporally, records of observations for all taxa were the lowest in fall although the number of animals sighted was lowest in the winter. Oceanographic coverage of observations varied by platform for each taxa, which showed that using two or more platforms represented habitat ranges better than using only one alone. Accessible and published datasets not already incorporated do exist within spatial and temporal gaps identified. Other related open-source data portals also contain data that fill gaps, emphasizing the importance of dedicated data exchange. Temporal and spatial gaps were mostly a result of data acquisition effort, development of regional partnerships and collaborations, and ease of field data collection. Future directions should include fostering partnerships with researchers in the Southern Hemisphere while targeting datasets containing species with limited representation. These results can facilitate prioritizing datasets needed to be represented and for planning research for true gaps in space and time.

We developed a data management, statistical modeling and decision support system describing habitat use of marine mammals in the North Atlantic and Gulf of Mexico. Our objective was to make this information available in a comprehensive manner to environmental planners and decision makers in the Navy and elsewhere. The system uses data on the distribution of marine mammals from dedicated surveys contained in the online OBIS-SEAMAP marine data archive. We used these data to develop predictive habitat models for guilds of marine mammals in these two regions. We delivered model outputs in an online, flexible Spatial Decision Support System (SDSS). The SDSS is a browser-based, interactive mapping application that enables users to view model results with original survey effort and marine mammal observations. In total, we generated 33 models, representing 16 cetacean guilds, using environmental data from the JPL physical oceanographic data archive. Predictive maps for the likelihood of encounter with marine mammals comprise the results, along with estimates of standard errors.

Our ability to understand, conserve, and manage the planet's marine biodiversity is fundamentally limited by the availability of relevant taxonomic, distribution, and abundance data. The Spatial Ecological Analysis of Marine Megavertebrate Animal Populations (SEAMAP) initiative is a taxon-specific geo-informatics facility of the Ocean Biogeographic Information System (OBIS) network. OBIS-SEAMAP has developed an expanding geo-database of marine mammal, seabird, and sea turtle distribution and abundance data globally. The OBIS-SEAMAP information system is intended to support research into the ecology and management of these important marine mega- vertebrates and augment public understanding of the ecology of marine megavertebrates by: (1) facilitating studies of impacts on threatened species, (2) testing hypotheses about biogeographic and biodiversity models, and (3) supporting modeling efforts to predict distributional changes in response to environmental change. To enhance the research and educational applications of this database, OBIS-SEAMAP provides a broad array of web-based products and services, including rich species profiles, compliant metadata, and interactive mapping services. This system takes advantage of recent technological advances in Geographic Information Systems (GIS), Internet data standards, and content management systems to stimulate a novel community-based approach to the develop- ment of a data commons for biogeographic and conservation research. To date, the global OBIS- SEAMAP database includes >1 million observation records from 163 datasets, spanning 71 yr (1935 to 2005) provided by a growing international network of data providers.