Lichen assemblages, beta diversity and inventory representation in southern Peruvian drylands: data, R code and reproducible outputs

Research compendium supporting the manuscript “Taxon turnover and sector identity constrain the representativeness of lichen inventories in southern Peruvian drylands”. Version 1.1.0 preserves the raw data, registered corrections and spatial-quality-control decisions published in Version 1.0.1 and adds an exhaustive inventory-representation extension. All 127 non-empty combinations of the seven occupied sectors were evaluated independently for 53 morphotaxa, 30 confirmed species and 33 genera. The extension reports the complete minimum, median and maximum observed-pool coverage for each sector count; distinguishes favourable from guaranteed coverage thresholds; and evaluates leave-one-sector-out sensitivity at all three taxonomic resolutions. For all morphotaxa, favourable combinations first reached 80%, 90%, 95% and 100% observed-pool coverage with four, five, six and seven sectors, respectively. These are retrospective favourable minima, not optimisation results or generally sufficient sample sizes. No sector count below seven guaranteed even 80% coverage across all possible selections. Excluding Tacahuay retained only 32 of 53 morphotaxa (60.4%). The archive contains immutable raw data; contextual and analysis-ready data; complete R scripts and configuration files; quality-control records; publication-ready figures and tables; editable Word tables; serialized R objects; session information; a SHA-256 manifest; and complete execution outputs. The documented design comprises eight surveyed sectors, 40 stations and 200 sampling units. Seven sectors yielded lichen detections; Amoquinto remains a documented zero-detection outcome and is excluded from composition and combination analyses. The regional checklist contains 53 lichen morphotaxa. Version 1.0.1 corrected the spatial treatment of station CHA05 without overwriting the source coordinate. Its field-notebook elevation is retained, whereas its analysis-ready coordinate and raster-derived descriptors remain unavailable. Biological composition records from CHA05 remain in non-spatial analyses. Data, documentation and generated outputs are licensed under the Creative Commons Attribution 4.0 International license. R source code is licensed under the MIT License.