Juliacon 2024

SpeciesDistributionModels.jl: an SDM workflow
07-12, 15:50–16:00 (Europe/Amsterdam), While Loop (4.2)

Species distribution modelling is the ecological discipline of predicting species occurrence in time and space. SDMs are used for biodiversity conservation, predicting invasions, and anticipating the effects of climate change.

This talk will present a species distribution modelling workflow in Julia, using SpeciesDistributionModels.jl and packages from the EcoJulia and JuliaGeo ecosystems to extract data, fit a model ensemble, and predict distributions in just a few lines of code.


The accessibility of species distribution modelling techniques through R packages such as sdm and biomod2 has hugely contributed to their popularity. The paper that introduces maxent (https://doi.org/10.1016/j.ecolmodel.2005.03.026), one of the most popular algorithms for species distribution modelling, has been cited over 18 thousand times.

SpeciesDistributionModels.jl is designed to be as user-friendly as existing R-based platforms, but with the power of Julia. It builds on the MLJ ecosystem can be extended with any MLJ-compatible model that accepts a binary response variable. It also integrates with Rasters.jl and Makie.jl to predict with geospatial inputs and outputs and for easy visualisation of model evaluation.

The speed-up provided by Julia opens up new possibilities to explore and visualise SDMs, like using Shapley values for more adequately explain the contributions of predictor variables and interactive plotting.

This talk will show a typical SDM workflow using SpeciesDistributionModels.jl and discuss the advantages of using Julia for SDMs.

Rafael is an Ecologist at the Center for Macroecology, Climate and Evolution in Copenhagen. He works on process-based ecological models of species distributions, dispersal, threats and extinction, and contributes to a variety of geospatial, modelling and visualization packages.

https://github.com/rafaqz

This speaker also appears in:

I am a PhD student at the University of Copenhagen, working on vector-borne disease modelling.