kindisperse

kindisperse estimates dispersal kernels by identifying close-kin dyads from genome-wide sequence data and using their spatial distribution to infer dispersal parameters.

Key Features:

• Close-kin detection and dispersal estimation: Identifies close-kin dyads from genome-wide sequence data and estimates dispersal parameters from their spatial distribution.
• Broad applicability: Applies across taxa including mosquitoes (Aedes) and vertebrates such as Antechinus, accommodating diverse life stages and organismal life histories.
• Simulation capabilities: Implements simulations to assess performance of close-kin methodologies under varied dispersal scenarios and compares published methods, identifying approaches that produce unbiased estimates versus those yielding downward-biased estimates.
• Study design optimization: Provides guidelines on sample site size and shape and on the number of close kin required for accurate dispersal estimation.
• Adaptability: Supports analyses relevant to invasive pest monitoring and threatened species conservation and accommodates non-invasive DNA sampling techniques.

Scientific Applications:

• Ecological and evolutionary research: Infers movement and dispersal dynamics to inform studies of population structure and gene flow.
• Conservation biology: Supports non-invasive monitoring of threatened species to quantify dispersal and connectivity for management decisions.
• Invasion ecology: Quantifies dispersal kernels of invasive species to inform spread models and control strategies.

Methodology:

Identifies close kin from genome-wide sequence data; estimates dispersal parameters from the spatial distribution of close-kin dyads; employs simulation-based evaluation across differing dispersal kernel shapes and life histories; compares published close-kin estimation methods to assess bias.