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EcoPLOT: dynamic analysis of biogeochemical data.

Christopher D Sanchez1, J Benjamin Brown1, Omree Gal-Oz1

  • 1Lawrence Berkeley National Laboratory, Berkeley, CA 94710, USA.

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Summary

EcoPLOT is a new R-based web app for analyzing biogeochemical data. It uses machine learning to discover key drivers impacting plant, microbial, and soil dynamics interactively.

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Area of Science:

  • Environmental Science
  • Computational Biology
  • Data Science

Background:

  • Biogeochemical datasets are complex and require advanced analytical tools.
  • Understanding the drivers of environmental dynamics is crucial for ecological research.

Purpose of the Study:

  • To introduce EcoPLOT, a novel web application for interactive biogeochemical data analysis.
  • To enable the discovery of significant drivers impacting environmental, geochemical, and microbiome dynamics.

Main Methods:

  • Development of a web-app using the R language.
  • Integration of state-of-the-art statistical and graphical analysis tools.
  • Application of the iterative random forest machine learning algorithm for driver discovery.

Main Results:

  • EcoPLOT facilitates dynamic and interactive exploration of complex datasets.
  • The iterative random forest algorithm successfully identifies key drivers of environmental change.
  • The tool supports the analysis of plant, microbial, and soil dynamics.

Conclusions:

  • EcoPLOT provides a powerful and accessible platform for biogeochemical data analysis.
  • The application enhances the ability to uncover critical ecological drivers.
  • EcoPLOT is freely available for use on multiple operating systems.