WS3: An open-source Python framework for integrated simulation and optimization of forest landscape and wood supply systems

WS3 is an open-source Python framework that integrates Model I scheduling, carbon accounting, and raster allocation into a scriptable workflow for reproducible forest planning. It ingests Woodstock-format inventories, actions, and scenarios; defines an explicit data model; and automates aspatial–spatial conversion so harvest schedules can be mapped to disturbance footprints. A documented linkage to the Canadian Forest Service Carbon Budget Model (libCBM) provides carbon stock and flux estimates for libCBM-calibrated jurisdictions. We document a modular architecture that decouples inventory ingestion, linear programming (LP) scheduling, carbon accounting, and raster allocation. Users can combine heuristic and LP approaches and extend indicators. We provide a reproducible parity check against Woodstock on a toy dataset and scaling experiments that characterize runtime and memory envelopes from desktop to cluster deployments. The complete toolchain—source code, configuration files, and deterministic reproduction scripts—is released under the MIT license with an archived Zenodo DOI. We demonstrate WS3 on five timber supply areas in northeastern British Columbia (20.40 Mha combined); post hoc libCBM runs provide carbon trajectories and raster allocation produces disturbance footprints for downstream spatial simulators. The framework is intended as reusable informatics infrastructure for decision support under competing sustainability mandates. • Open-source Python framework for forest estate decision support. • Model I scheduling with transparent inputs and outputs. • libCBM linkage for carbon stock and flux accounting. • Hybrid aspatial-to-raster workflows with reproducible geospatial I/O. • Deterministic reproduction package and archived scaling benchmarks.