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Dairy Cattle Spain: North/South

Moderate_Example.Rmd

Basic Assessment: A Step-by-Step Guide

This guide will walk you through a Moderate Assessment for Mature Dairy Cattle in Spain (2015) using the multi-regional structure (North and South).

Note on File Locations: All files must be located in the user_data/ folder of your project.

📂 Folder Structure

  • User Files (Update these): livestock_census.csv, diet_profiles.csv, diet_ingredients.csv, livestock_definitions.csv, livestock_weights.csv, manure_management.csv.
  • In case of usage of the automatic cycle: reproduction_parameters.csv
  • Reference Files (Expert use only): feed_characteristics.csv, forage_yields.csv, mapping.csv, fao_crop_yields.csv, ipcc_coefficients.csv, ipcc_mm.csv.

Step 1: The Census

Open livestock_census.csv. For this example, we have split the Spanish dairy population into two climatic regions to improve precision.

animal_tag region subregion class_flex population
mature_dairy_cattle spain north 536987
mature_dairy_cattle spain south 311699

Step 2: Designing the Diet

The diet is defined by the user. In this dataset, we’ve identified differences in forage availability between the North and South.

A. Define the Profile (diet_profiles.csv)

Note that the forage_share is higher in the North (55%) compared to the South (50%).

diet_tag region subregion forage_share concentrate_share milk_share
diet_dairy_mature spain north 55 45 0
diet_dairy_mature spain south 50 50 0

B. Ingredient Breakdown (diet_ingredients.csv)

For each category (forage/concentrate), the ingredient_share must sum to 100%.

Example for Spain South (Concentrate portion):

diet_tag region subregion ingredient ingredient_share ingredient_type
diet_dairy_mature spain south corn_national 44.85 concentrate
diet_dairy_mature spain south soybean_meal_44_cp 17.12 concentrate
diet_dairy_mature spain south rapeseed_meal_00_33_cp 28.71 concentrate

Step 3: Animal Categories and Coefficients

Open livestock_definitions.csv. This file links your animal tags to the IPCC physiological equations.

animal_tag region subregion diet_tag c_pregnancy milk_yield fat_content animal_type
mature_dairy_cattle spain north diet_dairy_mature cattle and buffalo 8295.0 3.73 cattle
mature_dairy_cattle spain south diet_dairy_mature cattle and buffalo 9044.0 3.73 cattle

Step 4: Body Weights

Open livestock_weights.csv. Ensure the keys match the census. These weights are used to validate your dry matter intake (DMI) limits.

animal_tag region subregion adult_weight weight_gain average_weight
mature_dairy_cattle spain north 675 0 675
mature_dairy_cattle spain south 675 0 675

Step 5: Manure Management (manure_management.csv)

You can define multiple manure systems for the same animal by splitting the allocation (the sum per animal/region must be 1.0).

animal_tag region subregion system_base management_months system_climate allocation
mature_dairy_cattle spain north anaerobic_lagoon cool 0.0537
mature_dairy_cattle spain north liquid_slurry 3 cool 0.3432
mature_dairy_cattle spain north solid_storage cool 0.3551
mature_dairy_cattle spain south solid_storage cool 0.3551

Step 6: Running the Analysis

Once your CSVs are updated in the user_data/ folder, run the analysis. The package will automatically perform biological validations (like checking if your cow is eating more than 5.5% of its body weight).

library(herdr)

results <- generate_impact_assessment(
  automatic_cycle = FALSE)