Open AccessPaths to computational fluency for natural resource educators, researchers, and managers
Author(s) -
Erickson Richard A.,
Burnett Jessica L.,
Wiltermuth Mark T.,
Bulliner Edward A.,
Hsu Leslie
Publication year - 2021
Publication title -
natural resource modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.28
H-Index - 32
eISSN - 1939-7445
pISSN - 0890-8575
DOI - 10.1111/nrm.12318
Subject(s) - fluency , computer science , computational model , resource (disambiguation) , natural resource management , computational resource , natural resource , management science , knowledge management , resource management (computing) , data science , artificial intelligence , computational complexity theory , engineering , mathematics education , psychology , algorithm , computer network , ecology , biology
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.