Playa Decision Support System
In response to increasing demand for spatially explicit information and guidance regarding playa conservation, the Playa Lakes Joint Venture (PLJV) and its partners developed the Playa Decision Support System (Playa DSS), a GIS-based tool designed to maximize the conservation of playas by guiding land-use activities. The Playa DSS is intended for use by multiple stakeholder groups including natural resource professionals, land managers and developers, providing them with data and written guidance that can inform decisions that may impact playas and their associated wildlife in the six-state PLJV region, including parts of Colorado, Kansas, Nebraska, New Mexico, Oklahoma and Texas.
The goal of the Playa DSS is to guide conservation actions toward and potential negative impacts away from the most ecologically valuable playas. It prioritizes individual playas with regards to the specified land-use activity so that the end-user knows which playas are the most important to target with conservation programs or to avoid for development activities. The Playa DSS provides the end-user with three integrated tools:
- spatial data layers representing playa basins prioritized for land-use activities (avoid or conserve), clusters of playas, and large isolated playas;
- PDF maps displaying the above data layers for every county in the PLJV region; and
- a User’s Manual with written guidance on how to apply and interpret the data layers and maps.
The Playa DSS was developed on a state-by-state basis incorporating the expertise and recommendations of local working groups. Representatives from these working groups are from both the conservation community and from industry, providing various perspectives on the relationship between land-use activities and playa conservation in each state. Although the specific methods used to prioritize playas may vary slightly among states, the overall prioritization schema (e.g., Very High Priority to Low Priority) is consistent across the region such that the end-user can interpret data consistently across state boundaries.