Patterns and determinants of diversity and knowledge shortfalls of Mexican ants

Description of the data and file structure All maps: Results of the window-moving analysis at 2.5 (2_5arcmin), 5 (5_arcmin), 7.5 (7_5arcmin) and 10 (10_arcmin) arcminutes. Within each file there are different window settings, specifically the window widths of 5, 10, 15, 20, 25 and 30 (rows) to calculate the observed richness (first column; est_obs), the estimated richnes (second column; est_rich) and the estimated sample coverage (third column; est_sc) .csv databases: 1- occurrences_included_wo_duplicates.csv = This database contains the 52,689 ant records compiled for Mexico after removing the duplicates of the species within the same coordinate. 2.-Ocurrences_excluded.csv = This database contains the 85,403 of duplicated records removed after the cleaning pipeline (see methods section). 3.-full_records_with_status.csv = This database contains the 137,093 ant records compiled from the Kass data, AntWeb data and Dattilo et al., (2020) data and a column with the status whether the record was included or excluded for the analyses. Files and variables File: maps_2_5arcmin.pdf Description: moving-window analysis output using a raster cell of 2.5 arcmin File: maps_5arcmin.pdf Description: moving-window analysis output using a raster cell of 5 arcmin File: maps_7_5arcmin.pdf Description: moving-window analysis output using a raster cell of 7.5 arcmin File: maps_10arcmin.pdf Description: moving-window analysis output using a raster cell of 10 arcmin File: occurrences_excluded.csv Description: Variables lon_opt: Longitude in decimal degrees lat_opt: Latitude in decimal degrees species: Ant species name File: full_records_with_status.csv Description: Variables lon_opt: Longitude in decimal degrees lat_opt: Latitude in decimal degrees status: Whether that record was included or excluded from the formal analyses. species: Ant species name File: occurrences_included_wo_duplicates.csv Description: Variables lon_opt: Longitude in decimal degrees lat_opt: Latitude in decimal degrees species: Ant species name File: Inventory_completeness_sensitivity_analyses.pdf Description: Inventory completeness patterns calculated at different cell sizes (5, 10, 15, 20 arcmin) and considering different numbers of minimum records to avoid unreliable estimates. Code/software Methods for the occurrence data: We compiled Mexican ant occurrence records from three main sources: (1) the ant database used by Kass et al. (2022), (2) data from the Mexican dataset compiled by Dáttilo et al. (2020, n=21,680) and (3) new records added to AntWeb (antweb.org) since the Kass et al. (2022) publication (n=31,163). In the original paper, Kass et al. (2022) obtained their data from the Global Ant Bioinformatics (GABI), and we extracted only the data corresponding to Mexico. Besides, since AntWeb records often include undetermined morphotypes not yet resolved to species, we removed those identified only to the morphospecies level or with collector codes. After pooling all datasets, we performed quality control in the following sequence: (1) all occurrence records were visualized in ArcMap software to verify that points fell on land (not ocean); (2) species names were checked for taxonomic validity to avoid artificial inflation of richness and (3) duplicate records (same species at identical coordinates) were removed using the clean_dup function (threshold = 0) from the “ntbox” R package (Osorio-Olvera et al., 2020). This produced a comprehensive, taxonomically validated dataset of 52,690 ant occurrences across Mexico for downstream analyses. Methods for the moving-window analyses: We applied the rarefaction and extrapolation method of Chao & Jost, (2012), using Hill numbers (q=0) to estimate the observed and expected ant species richness within each five arc‑minute grid cell (~10 km at the equator). In the Hill‑number framework, the order parameter q controls the sensitivity of the diversity measure to species’ relative abundances (Hill, 1973). In this study, we focused only on q=0 (all species are weighted equally regardless of their frequency), reducing to simple species richness. We also calculated sample coverage, a measure of sampling completeness, for each community. Sample coverage represents the proportion of the assemblage accounted for by the detected species and therefore, a grid cell with a sample coverage approximating 0 reflects an undersampled community, while those nearing 1 reflect well-characterized assemblages. Expected richness was then calculated across grid cells by extrapolating observed values to maximum sample coverage (i.e, ~1).These three metrics (i.e., observed and expected richness and sample coverage) were calculated within each five arc-minute grid cell (~10 km at the equator) using a moving-window approach with a width of 25 grid cells (total area of ~62,500 km²). Various window sizes (5–30 grid cells) and raster resolutions (2.5–10 arc-minutes) were tested before selecting this setting, which was chosen to balance we think balanced the smoothness of the mapped predictions, and was an appropriate spatial resolution to define communities in our extent. To avoid unreliable estimates, we followed a similar methodology to Kusumoto et al. (2020) and some ant studies based on this criteria (Andrade-Silva et al., 2022; Kass et al., 2022) by omitting calculations for windows with too few grid cells containing occurrence points (in our case, < 2) or those with as many singletons as there were total occurrence points, though incorporating a no constraint to the number of species within a window. Access information Data was derived from the following sources: Kass, J. M., B. Guenard, K. L. Dudley, C. N. Jenkins, F. Azuma, B. L. Fisher, C. L. Parr, H. Gibb, J. T. Longino, P. S. Ward, A. Chao, D. Lubertazzi, M. Weiser, W. Jetz, R. Guralnick, R. Blatrix, J. Des Lauriers, D. A. Donoso, C. Georgiadis, K. Gomez, P. G. Hawkes, R. A. Johnson, J. E. Lattke, J. A. MacGown, W. Mackay, S. Robson, N. J. Sanders, R. R. Dunn, E. P. Economo, B. Guénard, K. L. Dudley, C. N. Jenkins, F. Azuma, B. L. Fisher, C. L. Parr, H. Gibb, J. T. Longino, and P. S. Ward. 2022. The global distribution of known and undiscovered ant biodiversity. Sci. Adv. 8:eabp9908. 10.1126/sciadv.abp9908. Dáttilo, W., M. Vásquez‐Bolaños, D. A. Ahuatzin, R. Antoniazzi, E. Chávez‐González, E. Corro, P. Luna, R. Guevara, F. Villalobos, and R. Madrigal‐Chavero. 2020. Mexico ants: incidence and abundance along the Nearctic–Neotropical interface. Ecology. 10.1002/ecy.2944. www.antweb.org