Land Use Guide & Disclaimers

Land Use Methodology and Data Disclaimers

I. Introduction

The calculate_land_use() function in the herdr package provides an estimation of the total land area (in $m^2$) required to produce the feed consumed by a given livestock population.

This assessment is critical for understanding the environmental footprint and spatial efficiency of different production systems, allowing users to compare the “land cost” of different dietary strategies.

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II. Methodology

The model integrates animal nutritional requirements with crop productivity through a three-step calculation for each feed ingredient.

1. Inverse of Crop Yield

First, we calculate the land required per unit of feed: $$LandPerKg_{i} = \frac{1}{Yield_{i}}$$This expresses hectares required per kilogram of feed (ha/kg).

2. Economic Allocation Adjustment

This value is adjusted by an allocation factor to account for the share of land attributed to co-products (e.g., grain vs. straw): $$AdjustedLandPerKg_{i} = \frac{1}{Yield_{i}} \times Allocation_{i}$$

3. Total Land Use

Finally, the total land use is obtained by multiplying the annual feed consumption by the adjusted land requirement and converting hectares to square meters: $$LandUse_{i} = AnnualConsumption_{i} \times \left( \frac{1}{Yield_{i}} \times Allocation_{i} \right) \times 10,000$$

Where:

• AnnualConsumption: Total kg of dry matter (DM) consumed by the population per year.
• Yield: Productivity of the crop in kg DM per hectare (kg/ha).
• Allocation: Economic or physical factor (0 to 1) to account for co-products.
• 10,000: Conversion factor from hectares (ha) to square meters ($m^2$).

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III. Country-Specific Yield Assumption

The package uses a comprehensive FAO-based global database. However, for the calculation, the user must specify a single country via the crop_yield_country argument.

⚠️ Important Limitation: It is not possible to assign different countries of origin to individual ingredients within a single run. For example, you cannot specify that barley comes from Ukraine while maize comes from Spain. All ingredients will use the yields of the single selected country.

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IV. Data Sources and Disclaimers

The accuracy of land use estimation depends heavily on the underlying yield databases:

1. Official Crop Yields (FAOSTAT 2024): Yields for major crops (barley, maize, soya, etc.) represent standardized, country-level average yields reported by national authorities.
2. Non-Official Forage Yields: Forage data (grasses, alfalfa, silage) often lacks official global statistics. herdr includes compiled non-official values to provide broader coverage.

Users conducting high-precision analyses should cross-reference these values with local data sources where possible.

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V. The Mapping System

The mapping.csv file acts as a “translator” between your diets and the yield databases:

ingredient	yield_name	allocation
grass_fresh	Grass	1.0
barley_grain	Barley	0.8

• ingredient: The name used in your diet_ingredients.csv.
• yield_name: The exact key used to match the FAO or forage yield databases.
• allocation: The economic share (0 to 1) of land impact attributed to the feed.

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VI. Technical Implementation

You can call the function directly or as part of the full assessment. To find valid country names, check the fao_crop_yields.csv file in the package.

# Example: Calculating land use for a study based on Spanish productivity
results <- calculate_land_use(crop_yield_country = "Spain")