Modelling Biogeochemical Pathway Cascades using Bayesian Hierarchical Models

Published:

Problem

Ecosystems operate through complex direct and indirect interactions—understanding how herbivory cascades through biogeochemical processes is critical but structurally and statistically challenging.
Goal: Model and disentangle direct and indirect pathways of ecosystem functioning using Bayesian hierarchical models, clarifying cascading effects in biogeochemical dynamics.

Approach

  • Compiled experiments and observations quantifying herbivory rates, plant defences, nutrient fluxes, and other ecosystem variables in montane rainforests.
  • Built Bayesian hierarchical models that capture:
    • Direct effects (e.g., plant defences → herbivory)
    • Indirect pathways (e.g., mediated through soil nutrient flux or climatic processes)
    • Random effects across geographical sites (hierarchical nesting).
  • Quantified cascading impacts via posterior analysis of structured pathway coefficients.

Stack

  • Hierarchical Bayesian modelling: direct and indirect effect estimation within structured ecological networks.
  • Biogeochemical pathway analysis: handling multiple response variables in a network framework.
  • Data workflows: data integration from field measurements, cleaning, reproducible analysis pipeline.
  • Implementation: executed in R for processing and visualisation, and JAGS for model specification, all under version control for transparency.

Results

  • Identified both direct herbivory and mediated biogeochemical effects contributing to ecosystem dynamics.
  • Generated quantitative estimates of pathway strengths and uncertainty, revealing cascading structuring across trophic and nutrient cycles.

Impact

  • Advanced understanding of ecosystem functioning by quantifying complex ecological cascades.
  • Provided a modelling framework transferable to similar tropical ecosystem studies and management scenarios.

Links & Resources

Role

  • Designed and specified the hierarchical modelling of cascading pathways.
  • Cleaned and structured multivariate field dataset.
  • Fitted Bayesian models, interpreted complex posterior relationships.
  • Wrote the manuscript and articulated the ecological implications.