ARS | Publication request: The devil is in the details: overcoming the challenge of implementing consistent ecosystem indicators for cross-scale ecosystem understanding

Submitted to: Ecological Informatics
Publication Type: Abstract Only
Publication Acceptance Date: November 15, 2010
Publication Date: December 13, 2010
Citation: Karl, J.W., Peters, D.C. 2010. The devil is in the details: overcoming the challenge of implementing consistent ecosystem indicators for cross-scale ecosystem understanding. Ecological Informatics [abstract]. 7th International Conference on Ecological Informatics (ISEI7), December 13-16, 2010, Ghent, Belgium. CDROM.

Technical Abstract: Addressing environmental challenges requires understanding and monitoring of ecosystem responses to direct and indirect human impacts from local to global scales. Because it is generally not possible to sample at a sufficiently high density across a large spatial extent with a single data program, achieving a cross-scale understanding of ecosystem responses to global change requires the collection and synthesis of data from a number of sources, including broad-scale monitoring efforts, sensor arrays, networks of long-term research sites, and locally-collected datasets. Previous studies have highlighted the importance of data accessibility, metadata and data ontologies, database structures, and scientific workflows for discovering and integrating data. However, two critical aspects of data semantics (consistency in definitions of basic ecosystem indicators observational units, compatibility of methods of measurement) can greatly affect the ability to combine datasets measuring the same attribute. Consistency and compatibility among datasets can be achieved if there is general agreement and coordination on how observational units are defined and measured. While the need for standard indicators and methods is broadly agreed upon, the coordination and implementation of such standards has proved challenging. We review different approaches to achieving consistency and compatibility in ecological data along a continuum of observer control, from completely dispersed, independent data collection without standard protocols across sites (e.g., U.S. Long Term Ecological Research sites) to a mix of independent and standardized data collections (e.g., EcoTrends Project) and then completely centralized data collection and storage according to formal protocols (e.g., U.S. Natural Resource Inventory, National Climate Data Center). In the context of a national, multi-scale monitoring effort being developed for the U.S. Bureau of Land Management, we then consider external factors that have necessitated adoption of standard indicators and methods and the impact these are having on the degree to which datasets can be integrated to answer questions across a range of spatial scales. Finally, we provide recommendations for implementing minimum standard indicators and methods for ecological data collection that can be supplemented for local needs. Improving data consistency and compatibility through standard indicators and methods will support a broad-scale framework for synthesis of ecological information that is necessary to link different sources of data across scales to address pressing environmental challenges at scales at which they are occurring.