Off-site Compensation

When biodiversity gains cannot be achieved on-site, compensation can be delivered at off-site locations. Off-site compensation includes an additional spatial risk multiplier that accounts for the reduced ecological benefit of delivering gains further from the impact site.

Spatial Risk Categories

The spatial risk multiplier depends on the distance between the impact site and the compensation site:

Category	Multiplier	ID
Inside LPA/NCA boundary	1.00	0
Neighbouring LPA/NCA	0.75	1
Beyond neighbouring LPA/NCA	0.50	2

Where:

LPA: Local Planning Authority
NCA: National Character Area

Off-site Creation

import pandas as pd
from bngmetric.creation import calculate_offsite_creation_bng_from_dataframe

offsite_creation = pd.DataFrame({
    'Habitat': ['Grassland - Lowland meadows', 'Wetland - Reedbeds'],
    'Condition': ['Good', 'Moderate'],
    'Area': [3.0, 2.0],
    'Strategic_Significance': [1.15, 1.0],
    'Spatial_Risk': ['Inside LPA/NCA', 'Neighbouring LPA/NCA']
})

units = calculate_offsite_creation_bng_from_dataframe(offsite_creation)
print(f"Off-site creation units: {units:.2f}")

Comparing On-site vs Off-site

from bngmetric.creation import (
    calculate_creation_bng_from_dataframe,
    calculate_offsite_creation_bng_from_dataframe
)

# Same habitat, same conditions
habitat_data = {
    'Habitat': ['Grassland - Lowland meadows'],
    'Condition': ['Good'],
    'Area': [3.0],
    'Strategic_Significance': [1.15]
}

onsite = pd.DataFrame(habitat_data)
onsite_units = calculate_creation_bng_from_dataframe(onsite)

# Off-site in neighbouring LPA
offsite = pd.DataFrame({
    **habitat_data,
    'Spatial_Risk': ['Neighbouring LPA/NCA']
})
offsite_units = calculate_offsite_creation_bng_from_dataframe(offsite)

print(f"On-site units: {onsite_units:.2f}")
print(f"Off-site units: {offsite_units:.2f}")
print(f"Reduction: {(1 - offsite_units/onsite_units)*100:.0f}%")

Off-site Enhancement

import pandas as pd
from bngmetric.enhancement import (
    calculate_offsite_enhancement_bng_from_dataframe,
    calculate_offsite_enhancement_uplift_from_dataframe
)

offsite_enhancement = pd.DataFrame({
    'Habitat': ['Grassland - Lowland meadows'],
    'Start_Condition': ['Poor'],
    'Target_Condition': ['Good'],
    'Area': [2.0],
    'Strategic_Significance': [1.15],
    'Spatial_Risk': ['Neighbouring LPA/NCA']
})

units = calculate_offsite_enhancement_bng_from_dataframe(offsite_enhancement)
uplift = calculate_offsite_enhancement_uplift_from_dataframe(offsite_enhancement)

print(f"Post-enhancement units: {units:.2f}")
print(f"Net uplift: {uplift:.2f}")

Using JAX Arrays

For programmatic access with JAX:

import jax.numpy as jnp
from bngmetric.creation import (
    calculate_batched_offsite_creation_bng_units,
    get_spatial_risk_multiplier
)
from bngmetric.constants import (
    HABITAT_TYPE_TO_ID,
    CONDITION_CATEGORY_TO_ID,
    SPATIAL_RISK_CATEGORY_TO_ID
)

habitat_ids = jnp.array([HABITAT_TYPE_TO_ID['Grassland - Lowland meadows']])
condition_ids = jnp.array([CONDITION_CATEGORY_TO_ID['Good']])
areas = jnp.array([3.0])
strategic = jnp.array([1.15])
spatial_risk = jnp.array([SPATIAL_RISK_CATEGORY_TO_ID['Neighbouring LPA/NCA']])

units = calculate_batched_offsite_creation_bng_units(
    habitat_ids, condition_ids, areas, strategic, spatial_risk
)

Intertidal Habitats

For intertidal habitats, spatial risk is based on Marine Plan Areas rather than LPA/NCA boundaries, but the multipliers are the same:

Inside Marine Plan Area: 1.00
Neighbouring Marine Plan Area: 0.75
Beyond neighbouring Marine Plan Area: 0.50

Use the same Spatial_Risk column values; the multipliers are identical.