rKIN

rKIN estimates isotopic niche size and overlap from stable isotope data using kernel-based and spatial metrics to quantify resource and habitat use by consumers.

Key Features:

• Integration of Spatial Metrics: Implements Minimum Convex Polygon (MCP) and Standard Ellipse Area (SEA) adapted for quantifying isotopic niches.
• Kernel Utilization Density (KUD): Uses Kernel Utilization Density estimators in bivariate isotopic spaces to accommodate non-normal distributions and often yield larger niche size estimates.
• Method Comparison: Enables direct comparison of niche size and overlap estimated by MCP, SEA, and KUD, accounting for MCP/SEA differences due to inclusion or exclusion of unused areas.
• Bandwidth Selection Methods: Supports reference, normal scale, plug-in, and biased cross-validation bandwidth selectors, with comparable results reported for sample sizes 10–40 and consistency observed for samples >15 individuals.
• Versatility Across Data Types: Applicable to other ecological axes such as principal component analysis (PCA) or multi-dimensional scaling (MDS) provided axes are convertible to Cartesian coordinates.

Scientific Applications:

• Isotopic niche dynamics: Detects shifts, expansions, and contractions in isotopic niches indicative of changes in resource use or habitat conditions.
• Quantification of resource and habitat use: Quantifies resource and habitat use by consumers using stable isotope data.
• Method performance assessment: Evaluates and compares the performance of MCP, SEA, and KUD estimators across datasets and sample sizes.

Methodology:

Computes isotopic niche size and overlap using a kernel-based approach (Kernel Utilization Density) alongside traditional spatial metrics (MCP, SEA) in bivariate isotopic space, with bandwidth selection via reference, normal scale, plug-in, or biased cross-validation to accommodate non-normal distributions.