oystermapR - Predict and Map Oyster Growth Suitability from Environmental Data

Predicts spatial suitability for oyster growth from environmental survey data using rank-reciprocal weighted scoring. Users supply sensor data from Acoustic Doppler Current Profilers (ADCP), Conductivity-Temperature-Depth (CTD) sensors, bathymetric sonar, and sidescan sonar, specify a target species, and receive per-location suitability scores, a five-band 'GeoTIFF' heatmap for 'QGIS', contour lines, and a formatted PDF or HTML report. Supports seventeen species across global aquaculture regions, including Ostrea edulis, Magallana gigas, Crassostrea virginica, Crassostrea hongkongensis, and thirteen further species; see list_species(). Includes ocean acidification scoring via in-house aragonite saturation state (Omega_arag) calculation using Lueker et al. (2000) <doi:10.1016/S0304-4203(00)00022-0> and Mucci (1983) <doi:10.1357/002224083788520153> equilibrium constants (no external dependencies), variable impact diagnostics (variable_impact()), fine-scale habitat area analysis for restoration reporting in m2 with contiguous patch identification (area_summary()), tolerance curve visualisation (plot_tolerance()), season-aware scoring, tidal height correction, Bayesian tolerance parameter updating from field observations, spatial block cross-validation (Roberts et al., 2017, <doi:10.1111/ecog.02881>), permutation variable importance, wave exposure and sediment stability modules, Harmful Algal Bloom (HAB) risk and anthropogenic disturbance scoring with optional live International Council for the Exploration of the Sea (ICES) data integration, hybrid larval dispersal connectivity scoring (union-find Gaussian kernel plus optional 'OpenDrift' or Finite Volume Community Ocean Model ('FVCOM') connectivity matrix), batch multi-species comparison, and evidence-weighted scoring in which each variable's weight is its published rank multiplied by the measured reliability and realised spread of that layer, with the fraction of the species' evidence base the survey observed reported alongside the score rather than normalised away, and lineage-specific tolerance profiles for related populations, in which thinly sampled lineages borrow strength from relatives across a genetic distance matrix only where tolerance is shown to track relatedness, with inverse mapping of where each lineage is more likely to occur and which source population suits a site.