GLADE 0.1.0

First public release of GLADE (Global Land, Agriculture, Diet and Emissions),
a global food-systems optimization model built on PyPSA and Snakemake.

Added

• Configuration-driven mixed-integer linear program covering the food supply
  chain from land and primary resources through crops, processing, livestock,
  trade, and human nutrition.
• Sub-national optimization regions created by clustering administrative units,
  connected through hub-based trade networks for crops, foods, and feeds.
• Spatially explicit crop production for 60+ crops with GAEZ-derived yield
  potentials, multi-cropping, irrigation, and rainfed/irrigated land classes.
• Livestock systems with grazing and feed-based pathways, including enteric
  fermentation, manure management, and manure-application emissions.
• Greenhouse-gas accounting (CO2, CH4, N2O aggregated to CO2-equivalent) for
  land-use change, spared-land sequestration, rice cultivation, fertilizer use,
  and residue incorporation, with configurable GWP factors.
• Nutritional and food-group constraints ensuring caloric and dietary adequacy
  per country, plus health-impact tracking by disease cluster.
• Reproducible Snakemake workflow with data retrieval, model build, scenario
  solve, analysis, and plotting targets, organized under results/{config}/.
• Five-stage calibration pipeline (feed, food waste, food demand, cost,
  production stability) with git-tracked artefacts and a tools/calibrate
  entrypoint.
• Manifest-based HPC cluster execution path for large scenario sweeps (e.g.
  global sensitivity analysis) without Snakemake DAG overhead.
• Automatic JSON-schema validation of configuration files.
• Comprehensive Sphinx documentation and tutorial notebooks, published to
  GitHub Pages.