spacc: Fast Spatial Species Accumulation Curves

High-performance spatial species accumulation curves using fixed-focus spatially constrained rarefaction, nearest-centroid expansion, and nearest-neighbor walks with a C++ backend for speed. Supports Hill numbers (q=0,1,2), beta diversity partitioning (turnover/nestedness) at site and pooled resolution, coverage-based rarefaction and extrapolation of alpha and beta diversity, phylogenetic diversity (PD; Faith's PD, EvoHeritage, mean pairwise distance, mean nearest taxon distance), functional diversity accumulation including aggregated functional diversity and intraspecific trait variation, phylogenetic and functional redundancy, interaction network accumulation, diversity-area relationships (DAR), endemism-area curves, sampling-effort correction and fragmentation analysis, species-area relationship (SAR) models based on extreme value theory (EVT), and area-based richness extrapolation via the total-species curve. Total richness is also estimated from frequency counts, including the accumulation rate curve estimator and an estimator for sites sampled without replacement, and shift-and-rotate null models test the position of a sampling design. Multiple starting points (seeds) provide uncertainty quantification. Methods are described in Chao et al. (2014) <doi:10.1890/13-0133.1>, Baselga (2010) <doi:10.1111/j.1466-8238.2009.00490.x>, Chao and Jost (2012) <doi:10.1890/11-1952.1>, Faith (1992) <doi:10.1016/0006-3207(92)91201-3>, Ma (2018) <doi:10.1002/ece3.4425>, Borda-de-Agua et al. (2025) <doi:10.1038/s41467-025-59239-7>, Hanski et al. (2013) <doi:10.1073/pnas.1311190110>, Jost (2007) <doi:10.1890/06-1736.1>, Ugland et al. (2003) <doi:10.1046/j.1365-2656.2003.00748.x>, Chao et al. (2023) <doi:10.1002/ecm.1588>, Chiu (2023) <doi:10.1111/2041-210X.14146>, Chiu et al. (2023) <doi:10.1098/rstb.2022.0183>, Rosindell et al. (2024) <doi:10.1093/sysbio/syad072>, Wojcik et al. (2024) <doi:10.1111/2041-210X.14470>, Ridder et al. (2024) <doi:10.1111/2041-210X.14443>, Jones et al. (2025) <doi:10.1111/ddi.70080>, and Shestopaloff (2025) <doi:10.1007/s10651-025-00644-y>.

Version: 0.11.0
Depends: R (≥ 3.5)
Imports: Rcpp, RcppParallel, stats, parallel
LinkingTo: Rcpp, RcppParallel
Suggests: testthat (≥ 3.0.0), knitr, rmarkdown, svglite, ggplot2, cli, sf, areaOfEffect, ape, iNEXT, iNEXT.3D, iNEXT.beta3D, betapart, cluster, vegan
Published: 2026-10-11
DOI: 10.32614/CRAN.package.spacc
Author: Gilles Colling ORCID iD [aut, cre, cph], Marius Muja [ctb, cph] (nanoflann library (inst/include/nanoflann.hpp, BSD license)), David G. Lowe [ctb, cph] (nanoflann library (inst/include/nanoflann.hpp, BSD license)), Jose Luis Blanco [ctb, cph] (nanoflann library (inst/include/nanoflann.hpp, BSD license))
Maintainer: Gilles Colling <gilles.colling051 at gmail.com>
BugReports: https://github.com/gcol33/spacc/issues
License: MIT + file LICENSE
Copyright: See inst/COPYRIGHTS for the copyright holders of the bundled nanoflann library.
spacc copyright details
URL: https://gillescolling.com/spacc/, https://github.com/gcol33/spacc
NeedsCompilation: yes
SystemRequirements: GNU make
Language: en-US
Citation: spacc citation info
Materials: README, NEWS
CRAN checks: spacc results

Documentation:

Reference manual: spacc.html , spacc.pdf
Vignettes: Community Assembly and Turnover (source, R code)
Diversity Accumulation (source, R code)
Extrapolation and Species-Area Models (source, R code)
Getting Started with spacc (source, R code)
Rarefaction and Standardization (source, R code)
Richness Estimation and Completeness (source, R code)
Spatial Analysis: Endemism, Fragmentation, and SAR (source, R code)
Methods and Algorithms (source, R code)

Downloads:

Package source: spacc_0.11.0.tar.gz
Windows binaries: r-devel: spacc_0.8.3.zip, r-release: spacc_0.8.3.zip, r-oldrel: spacc_0.8.3.zip
macOS binaries: r-release (arm64): spacc_0.11.0.tgz, r-oldrel (arm64): spacc_0.11.0.tgz, r-release (x86_64): spacc_0.11.0.tgz, r-oldrel (x86_64): spacc_0.8.3.tgz
Old sources: spacc archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=spacc to link to this page.