RAC

RAC simulates and analyzes the rearing cycles of four Mediterranean aquaculture species (finfish and shellfish) at individual and population scales to evaluate growth, metabolism, and production under environmental forcings, and is implemented in R.

Key Features:

• Implemented in R: Provided as an R software package for computational simulation and analysis.
• Species-specific simulation: Simulates rearing cycles for four key Mediterranean aquaculture species (finfish and shellfish).
• Scale flexibility: Supports simulations at individual-organism and farm/population scales.
• Validated mathematical models: Incorporates mathematical models of growth and metabolism that have been validated in prior literature.
• Environmental forcing functions: Integrates water temperature and food quality/quantity as explicit forcing variables.
• Demo datasets and husbandry parameters: Includes demo environmental forcing datasets and husbandry parameter sets representative of Mediterranean aquaculture.
• Integration with remote sensing and operational oceanography: Enables incorporation of remote sensing and operational oceanography data as external environmental inputs.
• Proof-of-concept test cases: Has been applied in three test cases demonstrating applicability to real-world scenarios.

Scientific Applications:

• Growth and metabolism analysis: Quantifies effects of environmental variables on individual growth trajectories and metabolic rates.
• Rearing optimization and husbandry evaluation: Assesses impacts of husbandry parameters and environmental forcings to inform rearing conditions and production efficiency.
• Population dynamics and sustainability assessment: Simulates farm-level population dynamics to evaluate sustainability and aquaculture impacts.
• Integration with remote sensing for environmental forcing: Uses operational oceanography and remote sensing data to refine environmental inputs for simulations.
• Case-study validation: Supports proof-of-concept analyses as demonstrated by three test cases.

Methodology:

Implemented in R and based on mathematical models of growth and metabolism validated in prior research; the models incorporate environmental forcing functions (water temperature, food quality/quantity) and accept species-specific parameters, demo datasets, and husbandry parameters for simulations at individual and population scales, with capability to integrate remote sensing and operational oceanography data.