Paths to computational fluency for natural resource educators, researchers, and managers. (29th June 2021)

• Record Type: Journal Article
• Authors: Erickson, Richard A.; Burnett, Jessica L.; Wiltermuth, Mark T.; Bulliner, Edward A.; Hsu, Leslie
• Other Names: Blackwood Julie guestEditor.; Robertson Suzanne guestEditor.
• Is Part Of: Natural resource modelling. Volume 34:Number 3(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-06-29
• Subjects: natural resource education -- open science -- reproducible results; Conservation of natural resources -- Mathematical models -- Periodicals; Ecology -- Mathematical models -- Periodicals; 371.397
• DOI: 10.1111/nrm.12318
• Languages: English
• ISSNs: 0890-8575

Abstract

Abstract: Natural resource management and supporting research teams need computational fluency in the data and model‐rich 21st century. Computational fluency describes the ability of practitioners and scientists to conduct research and represent natural systems within the computer's environment. Advancement in information synthesis for natural resource management requires more sophisticated computational approaches, as well as reproducible, reusable, extensible, and transferable methods. Despite this importance, many new and current natural resource practitioners lack computational fluency and no common set of recommended resources and practices exist for learning these skills. Broadly, attaining computational fluency entails moving beyond the simple use of computers to applying sound computational principles and methods and including computational experts (such as computer scientists) on research teams. Our path for computational fluency includes using open‐source tools when possible; reproducible data management, statistics, and modeling; understanding and applying the benefits of basic computer programming to carry out more complex procedures; tracking code with version control; working in controlled computer environments; and using advanced computing resources. Considerations for Resource Managers Natural resource management increasingly uses computer‐generated results to inform and guide decision making. Open science requires that these data and software be reproducible. In turn, open science promotes computational fluency among natural resource managers, researchers, and educators. Based upon our experiences and perspectives working to support natural resource professionals, many natural resource managers would like to attain computationally fluency, yet lack formal training. We provide a path to computational fluency that emphasizes: using open‐source tools when possible; reproducible data management, statistics, and modeling; understanding and applying the basic computer programming philosophy to carry out both simple and more complex procedures; tracking code with version control; working in controlled computer environments; and using advanced computing resources. Natural resource managers, educators, and researchers can use their computationally fluency skills to promote open science in their own work.