Data & Tools

This page highlights infrastructure I have helped build for the field, including open demographic databases, analytical R packages, and publicly available teaching resources.

R packages

I develop and maintain R tools for demographic analysis and simulation:

  • Rcompadre: an R interface to the COMPADRE and COMADRE databases, enabling users to access, filter, and work with large collections of matrix population models. GitHub | CRAN
  • Rage: tools for calculating life-history traits from matrix population models, including survival, reproductive, and life-table analyses. GitHub | CRAN
  • mpmsim: tools for simulating matrix population models under user-defined demographic scenarios for teaching, sensitivity analysis, and methods development. GitHub | CRAN

Demographic databases

COMPADRE (plants) and COMADRE (animals) are open, curated repositories of matrix population models used in comparative demography worldwide. I have co-led both projects since 2010 alongside Rob Salguero-Gómez. Together these databases contain thousands of population models from hundreds of species and underpin a large and growing body of comparative demographic research. Access both databases at compadre-db.org.

Open science and archived code

I maintain code and software openly through GitHub, and archive project outputs on Zenodo and the Open Science Forum where possible to support reproducibility, transparency, and reuse. This reflects a broader commitment to open science as a practice rather than just a principle — from version-controlled analysis pipelines and documented workflows to openly published course materials and archived datasets. Shared code is written with reuse in mind, and where possible I aim to make analysis reproducible from raw data to final output. See GitHub for current repositories.

Teaching books and apps

I have developed open, freely available course books and interactive Shiny applications for two core courses at the University of Southern Denmark. These resources are publicly accessible and have been used by students and researchers beyond SDU. The Shiny app suites allow students to explore demographic and statistical concepts interactively, without requiring programming experience, making quantitative methods more approachable at early stages of training.