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QMaxent Manual

Welcome to the QMaxent user manual. QMaxent integrates the elapid Python library into QGIS to deliver the full Maxent species distribution modeling (SDM) workflow — training, spatial cross-validation, jackknife variable importance, projection, and survey planning — through a familiar bilingual interface.

Where to start

If this is your first visit:

  1. Read Introduction for the 2-minute orientation
  2. Install the plugin → Installation
  3. Set up Python dependencies → Dependencies
  4. Download the bundled example data → Example datasets
  5. Walk through your first model in 5 minutes → Quick start

If you already use QMaxent and want to dig into a specific feature, the User guide chapters mirror the plugin's five tabs one-for-one. Each can be read on its own.

If you want to see the tool put through its paces on real datasets, the Worked examples cover three case studies of increasing complexity, including a reproduction of the Lee et al. (2025) fairy pitta study published in Global Ecology and Conservation.

Conventions used in this manual

  • Bold marks UI labels (buttons, tabs, menu items) you click.
  • monospace marks file paths, code, and parameter values you type.
  • Numbered tabs (①, ②, …) refer to the QMaxent Analysis dock tabs.
  • Inline citations like (Phillips et al. 2017) point to entries in the References chapter.
  • Sidebar boxes flag warnings (⚠), tips (💡), and notes worth a second glance — but most of the manual is plain prose; we do not use boxes decoratively.

Citation

If you use QMaxent in your research, please cite the software using the metadata in the repository's CITATION.cff. The same metadata is rendered live on the project home page at osgeokr.github.io/qmaxent and in the References chapter of this manual.