OCNet

OCNet generates Optimal Channel Networks (OCNs), oriented spanning trees that reproduce the scaling features of natural river networks for use as realistic network analogues in hydrology, ecology, and epidemiology.

Key Features:

• Generation of OCNs: Generates Optimal Channel Networks as oriented spanning trees that reproduce the structural scaling features observed in natural stream networks.
• Random search process: Employs a random search process to produce multiple network replicas spanning the same surface area.
• Elevational gradient generation: Derives elevational gradients from the optimal network configuration to produce three-dimensional landscapes for spatial analyses.
• Network aggregation and metrics: Aggregates OCNs into an arbitrary number of nodes and computes network metrics and descriptors and provides functions for visualizing network features.

Scientific Applications:

• Hydrology: Analyze scaling properties and structural organization of river networks to study hydrological patterns.
• Freshwater ecology and evolution: Model connectivity in dendritic river systems to study metapopulation dynamics and biodiversity patterns.
• Epidemiology and invasive species: Simulate spatial processes affecting pathogen spread and invasive riverine species using metapopulation and network-based models.
• Landscape generation: Produce three-dimensional riverine and terrestrial landscapes for spatially explicit ecological and evolutionary studies.

Methodology:

OCNet generates oriented spanning trees (OCNs) that mimic real-world scaling features, uses a random search process to create multiple network replicas across the same surface area, derives elevational gradients from the optimal network configuration to create 3D landscapes, and aggregates networks into arbitrary node counts to compute network metrics and descriptors.