Publications by: Lucie Hazen

PLoS ONE
September, 2010

Connie Y. Kot, Ei Fujioka, Lucie J. Hazen, Benjamin D. Best, Andrew J. Read, Patrick N. Halpin

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.

Oceanography
June, 2009

Patrick N. Halpin, Andrew J. Read, Ei Fujioka, Ben D. Best, Ben Donnelly, Lucie J. Hazen, Connie Kot, Kim Urian, Erin LaBrecque, Andrew Dimatteo, Jesse Cleary, Caroline Good, Larry B. Crowder, K. David Hyrenbach

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.

Ecological Informatics
October, 2007

Benjamin D. Best, Patrick N. Halpin, Ei Fujioka, Andrew J. Read, Song S. Qian, Lucie J. Hazen, Robert S. Schick

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.