Data from: Plant-mycorrhizal fungus co-occurrence network lacks substantial structure

The data package contains five datasets:
- plant_spatial_presence_data
Spatial data of the plant species (presence(1)/absence(0)). The order of files (species names) follow the alphabetical order, as shown in Figure 1 of the manuscript.

- mycorrhiza_spatial_presence_data
AMF spatial data of the plant species (presence(1)/absence(0)). The order of files (species names) follow the alphabetical order, as shown in Figure 1 of the manuscript.

- null_models_plant_amf_co_occurrence
R script that includes three null models (fixed species presences, environmentally constrained and equiprobable null model). The script uses the data files of plants and AMF spatial data submitted here. It will calculate the different co-occurrence metrics (C-score, fij), asymmetry and nestedness of the different null matrices.

- abiotic_spatial_data
Spatial data of abiotic factors: pH and organic matter (OM).

- mutual_info_cluster
R script that calculates mutual information on the null matrices and the significant species co-occurrences. Input files necessary are the null matrices ("Pnullmatrices.RData" and "anullmatrices.RData") produced on the null model R script "null_models_plant_am_co_occurrence.R".

The data set used is spatially explicit and based on presence/absence of plant and AMF species. We test the significance of our observed pat-terns by using null models. Here we study a null model that incorporates the spatial autocorrelation of species patterns and we compare it with two non-spatial null models based on complete spatial randomness and environmental filtering, respectively. We use spatial overlap (i.e. species co-occurrence) to test the potential for associations between plant and AMF species and we develop novel metrics to estimate it.