Customized software to streamline routine analyses for wildlife management

J. Joshua Nowak, Paul M. Lukacs, Mark A. Hurley, Andrew J. Lindbloom, Kevin A. Robling, Justin A. Gude, Hugh Robinson

    Research output: Contribution to journalArticlepeer-review

    Abstract

    It is widely recognized that modern computer software makes wildlife management and research easier and allows increasingly complex tasks to become routine. Unfortunately, data storage and reporting rarely keep pace with the rapid expansion of data analysis software. Such disconnects in workflow can lead to missed opportunities where data are not used fully and new information is slow to emerge. We present a server-based software system, PopR (https://popr.cfc.umt.edu), which merges wildlife management agency databases with state-of-the-art statistical software for real-time wildlife data analysis, population modeling, and reporting. The interface to PopR is a secure website allowing access from any location with internet access and from any platform (personal computer, smartphone, tablet, etc.). PopR connects to remote data sources through an application program interface. PopR implements Bayesian integrated population models combining multiple data sources. PopR also implements individual data source analyses such as survival, sightability, herd composition, and harvest, among other data sources. Finally, PopR generates reports and figures for rapid dissemination and incorporation of results into decision processes. PopR presents a seamless workflow from data to analysis to reporting.

    Original languageEnglish
    Pages (from-to)144-149
    Number of pages6
    JournalWildlife Society Bulletin
    Volume42
    Issue number1
    DOIs
    StatePublished - Mar 2018

    Keywords

    • cloud computing
    • cougar
    • deer
    • elk
    • integrated population model
    • structured decision-making
    • ungulate
    • wildlife management

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