SSNdesign

SSNdesign optimizes sampling designs in stream networks to support efficient monitoring of freshwater conditions and biodiversity using pseudo-Bayesian optimal and adaptive sampling methodologies.

Key Features:

• R package implementation: Provided as an R package for computational implementation of sampling-design methods.
• Pseudo-Bayesian optimal and adaptive sampling: Implements pseudo-Bayesian optimal design and adaptive sampling methodologies for site selection.
• Geostatistical models for stream networks: Builds on geostatistical models tailored to stream network data.
• Network-aware modeling: Accounts for stream network properties including branching structure, flow connectivity, directionality, and varying flow volumes.
• Advanced design theory: Incorporates mathematical design-theory approaches to optimize sampling efficiency.
• Integration with open-source software: Designed to interoperate with existing open-source analytical tools.

Scientific Applications:

• Freshwater monitoring: Applied to design sampling schemes for freshwater and stream condition monitoring programs.
• Biodiversity and trend detection: Supports placement of sampling sites to improve detection of biodiversity trends in stream networks.
• Performance demonstration: Case studies using real-world data from Queensland, Australia showed performance superior to random and spatially balanced survey designs.

Methodology:

Uses pseudo-Bayesian optimal and adaptive sampling methodologies, geostatistical models developed for stream-network data, and advanced design theory while explicitly accounting for branching structure, flow connectivity, directionality, and varying flow volumes.