Mom, ecologist and data analyst turning environmental data into open and reproducible workflows.
After a long period of methodological contemplation — also known as postponing my GitHub organization — this space is finally becoming a public portfolio of my work with environmental data, spatial analysis and reproducible workflows in R.
Here I am gradually documenting selected projects, scripts and methods developed across research, environmental monitoring, teaching and applied data analysis.
I work with ecological and environmental data, using R, open tools and reproducible methods to organize, analyze and communicate information for research, technical reports, conservation and environmental management.
My work moves between data analysis, ecology, spatial thinking, data visualization, teaching and collaborative research. I care about clean scripts, well-documented methods and analyses that make sense beyond the code.
- Environmental and ecological data analysis
- Data cleaning, quality control and visualization
- R programming, teaching and data literacy
- Technical reports and environmental monitoring
- Ecosystem services, conservation and spatial planning
- Geospatial analysis and environmental modeling
- Collaborative research and consulting
- Open science and reproducible workflows
- Data analysis: R, tidyverse, dplyr, readr, lubridate, stringr
- Data visualization: ggplot2, Quarto, R Markdown
- Geospatial analysis: QGIS, sf, terra, raster
- Environmental modeling: InVEST, TauDEM
- Reproducibility: Git, GitHub, renv, structured project workflows
- Documented R scripts and project workflows
- Reproducible templates for analysis and reporting
- Data visualization outputs, maps and technical figures
- Open materials for learning and teaching R
- Research code related to ecology, conservation and environmental monitoring
- Notes on project organization, documentation and reproducibility