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ARS Home » Plains Area » Las Cruces, New Mexico » Range Management Research » Research » Publications at this Location » Publication #337118
Title: Building software tools to help contextualize and interpret monitoring data

Author
item Stauffer, Nelson
item Karl, Jason

Submitted to: Society for Range Management Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 1/9/2017
Publication Date: 1/29/2017
Citation: Stauffer, N.G., Karl, J.W. 2017. Building software tools to help contextualize and interpret monitoring data [abstract]. Society for Range Management. Jan 29-Feb 02, 2017, St. George, Utah.

Interpretive Summary:

Technical Abstract: Even modest monitoring efforts at landscape scales produce large volumes of data.These are most useful if they can be interpreted relative to land potential or other similar sites. However, for many ecological systems reference conditions may not be defined or are poorly described, which hinders understanding what values for a monitoring indicator are acceptable. One solution for this problem is to mine existing monitoring data to examine the distribution of the indicator values across sites and compare the distributions of subsets of the data against each other. In the case of the BLM’s Terrestrial Assessment, Inventory, and Monitoring Database (TerrADat), pre-computed indicator values are available for thousands of monitoring locations.  By grouping these data by geographic region, land potential (e.g. ecological site), or other factors, indicator values in TerrADat can be visualized and analyzed to determine potential indicator ranges, supporting management decisions even though none of the monitoring locations are designated as reference. We have developed a web-based statistical tool which streamlines histogram-based exploration of TerrADat, giving users a graphical interface to select survey locations to include and which indicators to use. Users can select data from TerrADat to plot using either an uploaded polygon shapefile to restrict spatially or by metadata queries. Figures can include multiple subsets of TerrADat to compare distributions of indicators between landscape units, e.g. ecological sites or grazing allotments. Additionally, the tool dynamically adapts its output to reflect common sense visualization rules for clarity. Visualizing indicator value ranges from similar areas can allow users to see, if not how conditions compare to reference, at least how conditions compare to the greater context on the landscape. This can be used to help support decisions about prioritization of management effort or as evidence toward defining what reference conditions are for portions of the landscape.