A programmable information system for management and analysis of aquatic species range data in California

  • Authors:

  • Nicholas R. Santos;Jacob V. E. Katz;Peter B. Moyle;Joshua H. Viers

  • Affiliations:

  • Center for Watershed Sciences, University of California, Davis, United States;Center for Watershed Sciences, University of California, Davis, United States and California Trout, United States;Center for Watershed Sciences, University of California, Davis, United States and Department of Wildlife, Fisheries, & Conservation Biology, University of California, Davis, United States;Center for Watershed Sciences, University of California, Davis, United States and School of Engineering, University of California, Merced, United States

  • Venue:
  • Environmental Modelling & Software
  • Year:
  • 2014

Quantified Score

Hi-index 0.00

Visualization

Abstract

The decline of species worldwide is both alarming and difficult to document due to a lack of reliable information on the geospatial extent and corresponding status of a given taxon. Freshwater habitats are disproportionately degraded globally with resultant declines in populations in freshwater fishes and subsequent retractions in biogeographic ranges. Conservation challenges in freshwater are compounded because aquatic taxa are inherently difficult to map. We addressed this problem for California freshwater fishes by developing the software and underlying database. The software consists of a Python program, database, and suite of tools using ESRI ArcGIS scripting interfaces to translate species range data into an electronic record set of occurrences housed in Microsoft Access. The system was designed to capture, store, map, and report on the spatial and temporal dynamics of targeted species by using standard spatial units as primary indexing objects to meet current natural resource management objectives. However, the software not only tracks the provenance of underlying empirical records through space and time, but also is robust to inferential modeling results and expert knowledge, which allows for future empirical discovery and validation. After importing and standardizing 274,555 records from 154 data layers, we found that most existing records are highly concentrated spatially, representing only 39% of the mapping domain. We also determined that most empirical records are skewed toward recreational fisheries, with few records documenting the range of native species found in California. Future biogeographic mapping efforts will be aided by the baseline data and updated range maps contained in the database. Although the system is currently used for the inventory and mapping of native freshwater fish species in California, the underlying informatics framework is agnostic to biological taxonomy or spatial realm allowing other to adapt the computer code and database for their own needs.