Livestock & Grazing

Overview

The livestock module models animal product production (meat, dairy, eggs) through two distinct production systems:

  • Grazing-based: Animals feed on managed grasslands

  • Feed-based: Animals consume crops as concentrated feed

Animal Products

The model includes five major animal product categories configured in config/default.yaml:

animal_products:
  include:
  - cattle meat
  - pig meat
  - chicken meat
  - dairy
  - eggs
  residue_crops:
  - banana
  - barley
  - chickpea
  - cowpea
  - dry-pea
  - dryland-rice
  - foxtail-millet
  - gram
  - maize
  - oat
  - pearl-millet
  - phaseolus-bean
  - pigeonpea
  - rye
  - sorghum
  - sugarcane
  - wetland-rice
  - wheat

grazing:
  enabled: true

Each product can be produced via either production system, with different feed requirements and efficiencies.

Production Systems

Grazing-Based Production

Concept: Animals graze on managed grasslands, converting grass biomass to animal products.

Inputs:

  • Land (per region and resource class, similar to cropland)

  • Managed grassland yields from ISIMIP LPJmL model

Process:

  1. Grassland yields (t dry matter/ha/year) are computed per region and resource class

  2. Feed conversion ratios translate grass biomass → animal products

  3. Land allocation to grazing competes with cropland expansion

Configuration: Enable/disable grazing with grazing.enabled: true

Feed-Based Production

Concept: Animals consume crops (grains, soybeans, etc.) as concentrated feed.

Inputs:

  • Crops from crop production buses

  • Feed conversion ratios (kg crop → kg animal product)

Process:

  1. Crops are allocated to animal feed (competing with direct human consumption)

  2. Feed conversion links transform crop inputs to animal products

  3. Multiple crops can contribute (e.g., maize + soybean for poultry)

Grassland Yields

Grazing supply is determined by managed grassland yields from the ISIMIP LPJmL historical simulation.

Data Source

Dataset: ISIMIP2b managed grassland yields (historical)

Resolution: 0.5° × 0.5° gridded annual yields

Variable: Above-ground dry matter production (t/ha/year)

Processing: workflow/scripts/build_grassland_yields.py

Aggregation follows the same resource class structure as crops:

  1. Load grassland yield NetCDF

  2. Aggregate by (region, resource_class) using area-weighted means

  3. Output CSV with yields in t/ha/year

Managed grassland yield potential

Global distribution of managed grassland yield potential (tonnes dry matter per hectare per year) from ISIMIP LPJmL historical simulations

Feed Conversion

The model uses feed conversion ratios to link feed inputs to animal outputs, with explicit categorization by feed quality to enable accurate CH₄ emissions tracking.

Feed System Architecture

The feed system uses eight distinct feed pools that combine animal type with feed quality:

  • Ruminant pools: ruminant_roughage, ruminant_forage, ruminant_grain, ruminant_protein

  • Monogastric pools: monogastric_low_quality, monogastric_grain, monogastric_energy, monogastric_protein

This categorization enables the model to:

  1. Differentiate methane emissions using GLEAM feed digestibility classes (roughage/forage vs. grain/protein)

  2. Route crops, residues, and processing byproducts to appropriate feed pools based on nutritional properties

  3. Model production system choices (e.g., roughage-dominated beef vs. high-grain finishing rations)

data/feed_properties.csv

Unified database mapping all feed items (crops and food byproducts) to feed categories and digestibility values. Columns:

  • feed_item: Item name (e.g., “maize”, “wheat bran”)

  • source_type: Either “crop” or “food” (byproduct)

  • feed_category: Feed quality category (forage, concentrate, or byproduct)

  • digestibility_ruminant: Digestible fraction for ruminants (0-1)

  • digestibility_monogastric: Digestible fraction for monogastrics (0-1)

  • ME_MJ_per_kg_DM: Metabolizable energy (MJ per kg dry matter) - for future use

  • CP_pct_DM: Crude protein (% of dry matter) - for future use

  • NDF_pct_DM: Neutral detergent fiber (% of dry matter) - for future use

  • notes: Description and source information

Feed categories:

  • Forage: High-fiber forages (grassland, silage, hay-type crops) - low digestibility, high CH₄

  • Concentrate: Energy/protein concentrates (grains, oilseeds, pulses) - high digestibility, low CH₄

  • Byproduct: Processing byproducts (brans, meals, hulls) - moderate digestibility, moderate CH₄

Typical items:

  • Roughage/forage: grassland forage, alfalfa, silage maize

  • Grain/energy: wheat, maize, soybean, dry pea

  • Byproducts/residues: wheat bran, rice bran, sunflower meal, crop residues (e.g., wheat straw, maize stover)

Byproducts from food processing (with source_type=food) are automatically excluded from human consumption and can only be used as animal feed.

Note

Current digestibility and nutritional values are mock data; to be replaced with actual feed value data from animal nutrition literature.

data/feed_to_animal_products.csv

Maps feed pool requirements to animal product yields. Columns:

  • product: Product name (e.g., “cattle meat”, “dairy”)

  • feed_category: Specific feed pool (e.g., ruminant_forage, ruminant_concentrate)

  • efficiency: Feed conversion efficiency (tonnes product per tonne feed DM)

  • notes: Description and source information

This structure allows modeling different production systems for the same product:

  • Grass-fed beef: cattle meat from ruminant_forage

  • Grain-finished beef: cattle meat from ruminant_concentrate

  • Pasture dairy: dairy from ruminant_forage

  • Intensive dairy: dairy from ruminant_concentrate

Note

Current values are mock data; to be replaced by actual feed conversion ratios.

Model Implementation

In workflow/scripts/build_model.py, livestock production is represented as multi-bus links:

Crop Residue Feed Supply

Crop residues (e.g., straw, stover, pulse haulms) are now generated explicitly using the new Snakemake rule build_crop_residue_yields:

  • Configuration: Select residue crops via animal_products.residue_crops in config/default.yaml. Only crops present in config.crops are processed.

  • Data sources: - GLEAM Supplement S1 Table S.3.1 (slope/intercept) and Tables 3.3 / 3.6 (FUE factors) - GLEAM feed codes → model mapping in data/gleam_feed_mapping.csv

  • Outputs: Per-crop CSVs at processing/{name}/crop_residue_yields/{crop}.csv with net dry-matter residue yields (t/ha) by region, resource class, and water supply.

  • Integration: build_model reads all residue CSVs, adds residue_{feed_item}_{country} buses, and attaches them as additional outputs on crop production links. Residues flow through the same feed supply logic as crops/foods and enter the appropriate feed pools.

Emissions from Livestock

Livestock production generates significant greenhouse gas emissions.

Enteric Fermentation (CH₄)

Ruminants (cattle, sheep) produce methane through digestive fermentation. The model uses a simplified IPCC Tier 2 approach based on methane yields (MY) per unit dry matter intake (DMI).

Methodology

Methane emissions are calculated as:

\[\text{CH}_4 = \text{DMI} \times \text{MY}\]
where:

  • DMI is dry matter intake (kg/day)

  • MY is methane yield (g CH₄ per kg DMI)

The methane yield depends on feed quality, specifically digestibility (DE%) and fiber content (NDF%). The IPCC provides differentiated conversion factors for various livestock categories and feeding systems.

IPCC Conversion Factors

The model uses methane yields from the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, Table 10.12:

Cattle/Buffalo Methane Conversion Factors (Ym)

Livestock category

Description

Feed Digestibility (DE %) and Neutral Detergent Fibre (NDF, % DMI)

MY g CH₄ kg DMI⁻¹

Ym³ (%)

Dairy cows and Buffalo

High-producing cows⁵ (>8500 kg/head/yr⁻¹)

DE ≥ 70 NDF ≤ 35

19.0

5.7

High-producing cows⁵ (>8500 kg/head/yr⁻¹)

DE ≥ 70 NDF ≥ 35

20.0

6.0

Medium producing cows (5000 – 8500 kg yr⁻¹)

DE 63-70 NDF > 37

21.0

6.3

Low producing cows (<5000 kg yr⁻¹)

DE ≤ 62 NDF >38

21.4

6.5

Non dairy and multi-purpose Cattle and Buffalo

> 75 % forage

DE ≤ 62

23.3

7.0

Rations of >75% high quality forage and/or mixed rations, forage of between 15 and 75% the total ration mixed with grain, and/or silage.

DE 62–71

21.0

6.3

Feedlot (all other grains, 0-15% forage)

DE ≥ 72

13.6

4.0

Feedlot (steam-flaked corn - 0- 10% forage)

DE ≥ 75

10.0

3.0

Source: IPCC (2019), Table 10.12 (Updated)

Notes:

  • ⁵ High-producing cows are defined as those yielding >8500 kg milk/head/year

  • Ym³ (%) represents the methane conversion factor (percentage of gross energy in feed converted to methane)

  • DE = Digestible Energy

  • NDF = Neutral Detergent Fibre

Implementation

The model implements IPCC Tier 2 methodology using feed quality-differentiated methane yields:

  • Feed is categorized into 6 pools combining animal type (ruminant/monogastric) with feed quality (forage/concentrate/byproduct)

  • Each feed category is assigned a specific MY value based on IPCC guidelines:

    • Forage (23.3 g CH₄/kg DMI): High-forage diets >75% forage, DE ≤ 62%

    • Byproduct (21.0 g CH₄/kg DMI): Mixed rations 15-75% forage + byproducts/grain, DE 62-71%

    • Concentrate (13.6 g CH₄/kg DMI): Feedlot/grain-based feeding 0-15% forage, DE ≥ 72%

  • Monogastric animals (pigs, poultry) produce minimal enteric methane (not modeled)

  • CH₄ emissions are calculated dynamically in add_feed_to_animal_product_links() based on DMI and feed category

data/enteric_methane_yields.csv

Simplified methane yield lookup table mapping feed categories to MY values. Columns:

  • feed_category: Feed quality category (forage, byproduct, concentrate)

  • MY_g_CH4_per_kg_DMI: Methane yield (g CH₄ per kg dry matter intake)

  • notes: IPCC source and diet description

Source: IPCC (2019), 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4, Table 10.12

The file contains only 3 rows - one for each feed quality category. The values are inferred from IPCC Table 10.12 cattle/buffalo categories based on forage percentage and digestibility.

Note

Future refinements could differentiate by production intensity (high/medium/low-producing dairy) and more detailed feed composition (NDF percentage).

Manure Management (N₂O, CH₄)

Manure storage and application releases:

  • N₂O: From nitrogen in manure (direct and indirect emissions)

  • CH₄: From anaerobic manure decomposition (especially in lagoons)

These are incorporated into the production link efficiencies, priced at the configured emissions.ghg_price (USD/tCO₂-eq; flows are scaled to MtCO₂-eq internally).

Configuration Parameters

animal_products:
  include:
  - cattle meat
  - pig meat
  - chicken meat
  - dairy
  - eggs
  residue_crops:
  - banana
  - barley
  - chickpea
  - cowpea
  - dry-pea
  - dryland-rice
  - foxtail-millet
  - gram
  - maize
  - oat
  - pearl-millet
  - phaseolus-bean
  - pigeonpea
  - rye
  - sorghum
  - sugarcane
  - wetland-rice
  - wheat

grazing:
  enabled: true

# --- section: food_groups ---
food_groups:
  whole_grains:
    min: 0
  grain:
    min: 0
  fruits:
    min: 0
  vegetables:
    min: 0
  legumes:
    min: 0
  nuts_seeds:
    min: 0
  starchy_vegetable:
    min: 0
  oil:
    min: 0
  red_meat:
    min: 0
  dairy:
    min: 0

# --- section: diet ---
diet:
  enforce_gdd_baseline: false
  baseline_age: "All ages"
  baseline_reference_year: null  # falls back to health.reference_year when null

Disabling grazing (enabled: false) forces all animal products to come from feed-based systems or imports, useful for exploring intensification scenarios. All food group minima are zero by default; raise food_groups.animal_protein.min_per_person_per_day (e.g., to 30 g) to enforce minimum consumption of animal-source foods.

Workflow Rules

build_grassland_yields

  • Input: ISIMIP grassland yield NetCDF, resource classes, regions

  • Output: processing/{name}/grassland_yields.csv

  • Script: workflow/scripts/build_grassland_yields.py

Livestock production is then integrated into the build_model rule using the grassland yields and feed conversion CSVs.