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spacc 0.8.3

Documentation

• Expanded all seven vignettes from brief overviews into full worked guides (quickstart, diversity, rarefaction/standardization, community assembly, spatial analysis, extrapolation, richness estimation). Each now covers the underlying model, simulation with known ground truth, fitting, uncertainty, prediction/comparison, and practical guidance, and exercises the full exported API (including evenness(), diversityProfile(), spatialEigenvectors()/spatialPartition(), wavefront(), and compareModels()).

spacc 0.8.2

Improvements

• spaccDiversity() objects gain a dedicated plot() method with a metric-neutral default y-axis label (“Cumulative diversity”) and a ylab/title argument, so custom-metric curves are no longer labelled as species counts.

spacc 0.8.1

Improvements

• spaccPhylo() and spaccFunc() now accept non-integer abundances (e.g. cover or biomass) for Rao’s Q and FDis weighting. The phylogenetic and functional accumulation backends use double-precision community matrices instead of truncating to integers. Presence-based metrics (MPD/MNTD/PD/FRic) are unaffected.

spacc 0.8.0

New Features

Rao’s Quadratic Entropy (v0.8.0)

• spaccPhylo() and spaccFunc() gain a "rao" metric: abundance-weighted mean pairwise distance (phylogenetic cophenetic distance, or Euclidean trait distance), accumulated along the spatial curve.
• spaccPhylo() no longer binarises its input, so abundance data now weights Rao; presence metrics (MPD/MNTD/PD) are unchanged.
• Exact-math recovery tests against the Rao definition sum_i sum_j p_i p_j d_ij.

Custom Diversity Metrics (v0.8.0)

• spaccDiversity() accumulates any user-supplied index along a spatial ordering: at each step the cumulative community is passed to a function that returns a scalar. Supports knn, kncn, random, radius, and collector orderings, abundance or incidence input, and extra arguments.
• Returns a spacc_diversity object inheriting spacc, so the standard summary(), plot(), as.data.frame(), and predict() methods apply.

Arbitrary-Order Rarefaction (v0.8.0)

• rarefy() now accepts any q >= 0 (q = 0, 1, 2 keep their exact estimators; other orders report the Hill number of order q) instead of silently falling back to richness.

spacc 0.7.1

New Features

User-Defined Accumulation Order (v0.7.1)

• spacc() gains an order argument for supplying an explicit accumulation sequence, bypassing distance computation and seed sampling.
  • Accepts a single ordering vector, a list of vectors, or a matrix with one ordering per row (each row treated like a seed for uncertainty bounds).
  • Each ordering must be a permutation of seq_len(nrow(x)).
  • Backed by cpp_order_parallel(), which reuses the random-accumulation worker with caller-supplied orderings.

spacc 0.7.0

New Features

Hill Numbers (v0.2.0)

• spaccHill() - Spatial accumulation with Hill numbers (q = 0, 1, 2)
  • q = 0: Species richness
  • q = 1: Exponential Shannon entropy (effective common species)
  • q = 2: Inverse Simpson (effective dominant species)
• Extends iNEXT framework to spatial accumulation

Spatial Beta Diversity (v0.3.0)

• spaccBeta() - Beta diversity accumulation with partitioning
  • Total beta diversity (Sorensen or Jaccard)
  • Turnover component (species replacement)
  • Nestedness component (species loss)
• Based on Baselga (2010) framework

Coverage-Based Rarefaction (v0.4.0)

• spaccCoverage() - Track sample coverage during accumulation
• interpolateCoverage() - Interpolate richness at target coverage levels
• Implements Chao & Jost (2012) Good-Turing coverage estimator

Phylogenetic/Functional Diversity (v0.5.0)

• spaccPhylo() - Phylogenetic diversity accumulation
  • MPD: Mean Pairwise Distance
  • MNTD: Mean Nearest Taxon Distance
• spaccFunc() - Functional diversity accumulation
  • FDis: Functional Dispersion
  • FRic: Functional Richness (approximation)

Per-Site Metrics & Heatmaps (v0.6.0)

• spaccMetrics() - Extract accumulation metrics per site
  • slope_10, slope_25: Initial accumulation slopes
  • half_richness, richness_Npct: Sites to reach richness thresholds
  • auc: Area under accumulation curve
• as_sf() - Convert metrics to sf for spatial analysis
• Heatmap plotting via plot(type = "heatmap")

Spatial Support Integration (v0.7.0)

• New support parameter in spacc() for areaOfEffect integration
  • Accepts country names: spacc(species, coords, support = "France")
  • Accepts sf polygons or pre-computed aoe_result objects
• Seeds sampled from core sites only (inside support)
• Accumulation expands into halo sites (buffer zone) by default
• include_halo = FALSE for hard/political boundaries
• Eliminates edge effects at arbitrary administrative boundaries

Internal Changes

• New C++ implementations: hill.cpp, beta.cpp, coverage.cpp, phylo.cpp, metrics.cpp
• cpp_knn_parallel_seeds() - kNN with explicit seed indices
• Added sf, areaOfEffect, ape, iNEXT, betapart to Suggests

spacc 0.1.0

Initial release.

Features

Core Spatial Accumulation Methods

• spacc() - Main function with multiple spatial sampling methods:
  • knn: k-Nearest Neighbor (always visit closest unvisited)
  • kncn: k-Nearest Centroid Neighbor (visit closest to centroid)
  • random: Random order (null model)
  • radius: Expand by distance from seed
  • gaussian: Probabilistic selection weighted by distance
  • cone: Directional expansion within angular constraint
  • collector: Sites in data order

Additional Accumulation Methods

• wavefront() - Expanding radius accumulation
• distanceDecay() - Distance-decay relationships

Analytical Methods (No Simulation)

• coleman() - Coleman expected accumulation
• mao_tau() - Mao Tau (exact) expected accumulation
• collector() - Collector’s curve (data order)
• spatialRarefaction() - Spatially-constrained rarefaction

Analysis Functions

• extrapolate() - Fit asymptotic models (Michaelis-Menten, Lomolino, etc.)
• compare() - Statistical comparison between curves
• rarefy() - Rarefaction to common effort
• subsample() - Subsample sites spatially

Infrastructure

• C++ backend via Rcpp for performance
• Parallel processing via RcppParallel
• Haversine distance support for geographic coordinates

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.