Presence, Absence, and Abundance in Publicly Available Data: Advances in the Data Inclusion Paradigm in OBIS-USA

Abigail Benson, USGS Central Region Offices Denver, Denver, CO, United States and Sky Bristol, USGS Headquarters, Reston, VA, United States
Biological diversity at all levels including genetic, species, and ecosystem, promotes stability in ecosystem function in marine environments and the services they provide. Despite this knowledge, baseline observation measurements for marine species are not readily available for consumption. Similarly, marine species observation data spanning regional spatial scales and long-term temporal scales are also unavailable, which is detrimental for management planning and decision making. The Ocean Biogeographic Information System (OBIS) provides the framework and access to marine species occurrence data that underpins biological diversity analyses at these broader temporal and spatial scales necessary for aiding management decisions. OBIS (OBIS: is a distributed data system which was developed to host the data resulting from the Census of Marine Life. OBIS-USA ( is a national member node of OBIS serving species observations recorded in U.S. Waters or collected with U.S. funding. Hosted and maintained by the U.S. Geological Survey, OBIS-USA integrates and standardizes marine species observation data from multiple sources and provides those data to OBIS. In January 2011, OBIS-USA contained 6.5 million occurrence records. In recent years, OBIS-USA shifted to an enhanced observation data model shifting from occurrences to observations, and leading to the addition of 19 million absence records putting total observations over 28 million, from 174 contributing datasets and 148 data providers. The current OBIS-USA data model, the Darwin Core Marine BioGeography Common Terms extension (, captures species presence, absence, and abundance, in addition to other measurements and observations of marine species. Inclusion of presence, absence, and abundance observations facilitates more robust modeling techniques such as species distribution modeling, saturated and nested models, and better diversity index calculations. With better and more accurate species distribution models and diversity indices, conservation and management actions will be easier to ascertain and implement at broader spatial scales.