Bio
Mr. Kenny McCune is a project data and solution engineer with a background in aquatic sciences and 10 years of experience collecting, managing, and analyzing data for water chemistry, macroinvertebrates, macrophytes, physical habitat, and geospatial data used in stream and estuarine habitat quality assessment. He is experienced in technical data management skills, including the development of data pipelines and database structures that efficiently transition data from field to database to analytical and modeling platforms.
Relevant Experience
Data Management
Data Management Compliance, Georgia — Managed databases and helped to drive data management regulatory compliance. Identified and consolidated ecological tools and data sets across regions into one central location.
Watershed Condition Assessment, California — Created and maintained scripts and data structures for extraction transformation and loading of watershed condition assessment metrics for California streams.
Flow Duration Indicators, California — Maintained databases and data pipelines for field-collected physical habitat and biological data used in developing an inventory of indicators of streamflow duration.
Hydrologic Modeling, California — Helped to manage input and output workflows for hydrologic models used to predict flow at ungauged streams. Coordinated cataloging of model inputs, transformations of model outputs, and metric calculations used for assessing ecologically relevant hydrology characteristics.
Bioassessment Indices Development, California — Developed data set generation, quality assurance, and analysis scripts to help with the development and improvement of multiple stream condition assessment tools. Data sets consisted of physical habitat measurements, water chemistry data, remotely sensed data, and biological data.
Environmental Monitoring
Seagrass Monitoring and Assessment, California — Developed and tested protocols for structural assessment of seagrass beds within embayments in southern California.
Water Quality Modeling
Stream Water Chemistry Modeling, California — Helped to create random forest models using remotely sensed data as predictors of water chemistry variables at unsampled locations.
Education & Credentials
M.S., Biology, California State University, Long Beach, California, 2022
B.S., Biological Science, California State University, Fullerton, California, 2015