The Application Of Observing System Data In California Current Ecosystem Assessments


Title: The Application Of Observing System Data In California Current Ecosystem Assessments
Publication Date:
March 01, 2010
Document Number: ONMS-10-01
Pages: 120
Sponsoring Organization:
Technology Type:

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Brown, J.; Pavia, R.; King, C.; DeVogelaere, A. (2010). The Application Of Observing System Data In California Current Ecosystem Assessments. Report by National Marine Sanctuaries and National Oceanic and Atmospheric Administration (NOAA). pp 120.

Ecosystem-based management requires comprehensive assessments of the ecosystem to establish a feedback loop on the conditions in the systems under management. These assessments require observing data that reflect the pressures and ecosystem indicators of concern to managers. This report examines ongoing ecosystem assessment and modeling efforts in the California Current Ecosystem (hereafter referred to as ‘ecosystem assessments’) in the context of NOAA’s model for Integrated Ecosystem Assessment (IEA) development. The goals of this effort are to 1) examine the ecosystem assessments in the context of a DPSIR (Driver, Pressure, State, Impact, Response) approach; and 2) identify ocean observing datasets in use by current assessments to identify gaps in the data and services available to support future assessments.


The purpose, scale, and drivers for 10 selected assessments were compared with the ocean observing data sources used in their development. These 10 assessments vary in the spatial scope of the assessment from the California Current Ecosystem scale to the local scale. A more detailed comparison of the California Current IEA, Module 1 and Northern California Current Ecosystem, Atlantis model was then undertaken to highlight their use of drivers, pressures, and indicators.


Five Sanctuary condition reports, assessments for individual sanctuaries, were examined in depth to understand the relationship between drivers, pressures and responses in the context of management requirements. The sources of data used to evaluate indicators of those responses were then identified. This provided a link between a pressure-state-response model of IEA development and ocean observing data sets. The final step was to examine observing datasets being used by one or more assessment efforts in the California Current Ecosystem. This work provides an assessment of how existing ocean observing efforts are informing assessments efforts in the California Current Ecosystem and where gaps exist.


We identified four datasets available through the Pacific Coast Ocean Observing System that are being used by both large and small-scale assessment efforts. However, the overwhelming majority of the datasets identified in this analysis were used by either small or large-spatial scale assessment efforts but not both. A very large gap exists for data describing the level of human activities that impact the marine environment. In addition, the authors identify a need for more data collected at the sub-regional and local level. Currently, in no single sub-region are data available for all the physical, chemical, and especially biological indicators required for comprehensive analyses.


This review recognized four key barriers to fully exploiting ocean-observing data for ecosystem-based management: data discovery, data access, integrating disparate data, and closing the gap between data needs and data collection. One of the key challenges to IEA application in ecosystem-based management is the lack of available data. Even if there were no barriers to discovering, accessing, and integrating existing data, effectively developing management alternatives and monitoring effectiveness requires investments in data collection and analysis. In many cases, the necessary data are not available, significantly hampering our ability for taking ecosystem-relevant management actions and increasing uncertainty in outcomes. Resource managers must make the best decisions possible with available information. This requirement to move forward, even with data gaps highlights the importance of maximizing the use of what we do have through data management, improved accessibility, improved integration and compatibility, and more comprehensive analysis.

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