18 Aug 2023
 | 18 Aug 2023
Status: this preprint is open for discussion.

The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible and integrated plankton community modeling environment in Python

Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico

Abstract. Plankton community modeling is a critical tool for understanding the processes that shape marine ecosystems and their impacts on global biogeochemical cycles. These models can be of variable ecological, physiological and physical complexity. Many published models are either not publicly available or implemented in monolithic and inflexible code, thus hampering adoption, collaboration, and reproducibility of results. Here we present Phydra, an open-source library for plankton community modelling, and Xarray-simlab-ODE (XSO), a modular framework for efficient, flexible, and reproducible model development based on ordinary differential equations. Both tools are written in Python. Phydra provides pre-built models and model components that can be modified and assembled to develop plankton community models of various levels of ecological complexity. The components can be created, adapted and modified using standard variable types provided by the XSO framework. XSO is embedded in the Python scientific ecosystem and is integrated with tools for data analysis and visualization. To demonstrate the range of applicability and how Phydra and XSO can be used to develop and execute models, we present three applications: (1) a highly simplified nutrient-phytoplankton (NP) model in a chemostat setting, (2) a nutrient-phytoplankton-zooplankton-detritus (NPZD) model in a zero-dimensional pelagic ocean setting, and (3) a size-structured plankton community model that resolves 50 phytoplankton and 50 zooplankton size classes with functional traits determined by allometric relationships. The applications presented here are available as interactive Jupyter notebooks and can be used by the scientific community to build, modify, and run plankton community models based on differential equations for a diverse range of scientific pursuits.

Benjamin Post et al.

Status: open (until 13 Oct 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2023-1697', Anonymous Referee #1, 13 Sep 2023 reply
  • RC2: 'Comment on egusphere-2023-1697', Anonymous Referee #2, 22 Sep 2023 reply

Benjamin Post et al.

Model code and software

Xarray-simlab-ODE Benjamin Post

Phydra Benjamin Post

Benjamin Post et al.


Total article views: 229 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
169 51 9 229 3 3
  • HTML: 169
  • PDF: 51
  • XML: 9
  • Total: 229
  • BibTeX: 3
  • EndNote: 3
Views and downloads (calculated since 18 Aug 2023)
Cumulative views and downloads (calculated since 18 Aug 2023)

Viewed (geographical distribution)

Total article views: 223 (including HTML, PDF, and XML) Thereof 223 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 30 Sep 2023
Short summary
Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool-set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool-set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models, to find the most appropriate one.