Ei Fujioka

Geospatial web services within a scientific workflow: Predicting marine mammal habitats in a dynamic environment

Abstract 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.

Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico

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.

Spatio-temporal gap analysis of OBIS-SEAMAP project data: assessment and way forward.

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.

Advancing Global Marine Biogeography Research with Open-source GIS Software and Cloud Computing

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.

Integration of passive acoustic monitoring data into OBIS-SEAMAP, a global biogeographic database, to advance spatially-explicit ecological assessments

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 Rissos dolphins to demonstrate how the integrated database facilitates in-depth ecological assessments that form the foundation for spatially-explicit conservation efforts.

Data integration for conservation: Leveraging multiple data types to advance ecological assessments and habitat modeling for marine megavertebrates using OBIS–SEAMAP

Abstract 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.

Management of acoustic metadata for bioacoustics

Abstract Recent expansion in the capabilities of passive acoustic monitoring of sound-producing animals is providing expansive data sets in many locations. These long-term data sets will allow the investigation of questions related to the ecology of sound-producing animals on time scales ranging from diel 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 from a 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.) from a wide 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.