<b>Soil nitrogen reduces ectomycorrhizal diversity and drives lineage-dependent arbuscular mycorrhizal responses in Australian temperate forests</b>

Outputs are written to each pipeline's output/ directory. See bioinformatics/README.md for pipeline details.</li><li>bioinformatics/envs/ — Conda environment specifications for the pipelines.</li></ul></li><li>generated_data/ — Contains all data required to reproduce the primary results from the manuscript, including the site metadata, extracted site covariates, and the OTU tables, taxonomy and model outputs the figure scripts read.</li><li>code/ — Alpha-diversity modelling, threshold indicator taxa analysis, phylogenetic signal analysis, and figure generation (see "Reproducing the analysis" below).</li><li>code/00_georef_covars/ — Builds the georeferenced covariate layer used by the diversity models: computes and predicts AM/EcM tree basal area and richness surfaces from national forest inventory data via INLA/SPDE, then extracts bioclim, aridity, soil, and those predicted surfaces at each sample site.</li></ul><h3 dir="ltr">Reproducing the analysis</h3><p dir="ltr">The primary figures reproduce from generated_data/ alone (step 6).

Earlier steps rebuild those inputs from the raw sequence data included here.</p><ol><li>bioinformatics/am/, bioinformatics/ecm/ — Trim, denoise, classify and cluster the raw reads into OTU tables and taxonomy. Run from each pipeline's own directory; outputs are written to bioinformatics/am/output/ and bioinformatics/ecm/output/.</li><li>code/00_georef_covars/01a_compute_mycorrhizal_dominance.R → 01b_predict_mycorrhizal_dominance.R → 01c_compute_mycorrhizal_richness.R → 01d_predict_mycorrhizal_richness.R → 01e_extract_georeferenced_covariates.R — Compute and extract AM/EcM tree basal-area and richness covariates.

These scripts read national tree inventory data and georeferenced climate, soil and ecoregion layers that are third-party products and are not redistributed here; see the script headers for their sources. The extracted site-level result of this step is provided in generated_data/sample_covariates.txt, so the remaining steps can be run without it.</li><li>code/01a_alpha_diversity_amf.R, 01b_alpha_diversity_g_amf.R, 01c_alpha_diversity_m_amf.R, 01d_alpha_diversity_emf.R, 01e_prepare_generated_data.R — Causal-model estimation of the mineral-nitrogen effect on alpha diversity and relative abundance for AMF and EMF.</li><li>code/02a_titan_amf.R, 02b_titan_emf.R — Threshold indicator taxa analysis (TITAN2) identifying nitrogen-sensitive taxa for each guild.</li><li>code/03_phylogenetic_analysis.R — Tests whether nitrogen-response indicators are phylogenetically clustered (SES-MPD/SES-MNTD) within each guild.</li><li>code/figure_1.R – figure_6.R — Generate the manuscript's primary figures.

These read only from generated_data/ and can be run directly on a fresh download.</li></ol><p dir="ltr">Steps 3 to 5 expect the pipeline outputs from step 1 and the covariates from step 2 in a top-level data/ directory. Assemble that directory from the bioinformatics output/ folders before running them.</p><h3 dir="ltr">Related resources</h3><ul><li>Version-controlled code and generated data: <a href="github.com/LukeLikesDirt/Mycorrhiza-AusTemperateForests" target="_blank">github.com/LukeLikesDirt/Mycorrhiza-AusTemperateForests</a></li></ul><h3 dir="ltr">Licence</h3><p dir="ltr">Creative Commons Attribution 4.0 International (CC BY 4.0).</p>