MALPOLON: A Framework for Deep Species Distribution Modeling

TL;DR

MALPOLON is an open-source Python framework built on PyTorch that simplifies training and sharing deep species distribution models, making deep learning accessible to ecologists and researchers with minimal coding experience.

Contribution

It introduces a modular, user-friendly deep-SDM framework with extensive documentation, enabling easy experimentation and scalable training for ecologists and researchers.

Findings

Framework supports multi-GPU training and parallel computing.

Provides baseline models for benchmarking.

Facilitates testing deep learning approaches in species distribution modeling.

Abstract

This paper describes a deep-SDM framework, MALPOLON. Written in Python and built upon the PyTorch library, this framework aims to facilitate training and inferences of deep species distribution models (deep-SDM) and sharing for users with only general Python language skills (e.g., modeling ecologists) who are interested in testing deep learning approaches to build new SDMs. More advanced users can also benefit from the framework's modularity to run more specific experiments by overriding existing classes while taking advantage of press-button examples to train neural networks on multiple classification tasks using custom or provided raw and pre-processed datasets. The framework is open-sourced on GitHub and PyPi along with extensive documentation and examples of use in various scenarios. MALPOLON offers straightforward installation, YAML-based configuration, parallel computing, multi-GPU utilization, baseline and foundational models for benchmarking, and extensive tutorials/documentation, aiming to enhance accessibility and performance scalability for ecologists and researchers.