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

Research compendium supporting the manuscript “Among-sector turnover dominates lichen beta diversity in southern Peruvian drylands: implications for inventory design”. Version 1.0.1 incorporates post-publication spatial quality control for CHA05. The originally recorded coordinate is preserved in the raw data but classified as spatially unresolved in the analysis-ready data. Its field-notebook elevation (3,620 m a.s.l.) is retained, whereas ALOS elevation and WorldClim MAT and MAP are reported as unavailable. CHA05 is excluded from maps, spatial-distance calculations and raster-derived environmental descriptors, while its five confirmed quadrats and biological observations are retained. 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 archive was executed with pipeline v8.3.0 and passed 17/17 validation checks. Biological results are unchanged relative to version 1.0.0. Among the 34 stations with validated coordinates, the maximum within-sector separation is 4,504 m in Alto Coscore. Field records confirmed that five quadrats were inspected at every station and that the 29 exact-match pairs (58 rows) represent observations from distinct quadrats. These records were therefore retained as separate sampling observations. The documented sampling framework comprises 40 stations and 200 sampling units, with 35 occupied stations and 175 occupied sampling units included in composition-based analyses. The regional checklist contains 53 lichen morphotaxa. Original unit-level records from the zero-detection Amoquinto sector were not recovered, and this limitation remains documented. Figure 1A requires external GIS layers and photographs that are not included in this analytical archive. 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.