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Corsini et al. Carbon Footprints 2026, 5, 34 Page 3 of 20

function [23-25] . These effects commonly penetrate tens to hundreds of meters into forest interiors, depending
on fragment size, shape, and landscape configuration [20,26,27] , and often persist over decadal timescales due to
repeated edge exposure and structural instability [14,28,29] .

Landscape ecology provides a mechanistic explanation for how degradation occurs, depending critically on
landscape structure, including fragment size, shape, and connectivity [30,31] . These attributes modulate the
spatial spread of ecological disturbances, producing predictable distance-decay patterns across forest
mosaics [32,33] . In practical terms, two projects with identical “forest area” may have sharply different carbon
trajectories depending on how fragmented they are and how exposed their boundaries are to the
surrounding matrix—precisely the type of within-project heterogeneity that deforestation-only baselines
struggle to represent [24,34] . While typical REDD+ approaches identify how much deforestation is likely to
occur, they fail to capture the spatial pattern of disturbance propagation and the ecological vulnerability that
emerges from the area's characteristics and landscape context.

The influence of external disturbances typically diminishes with distance from their source due to barriers,
habitat heterogeneity, and energy dissipation, producing nonlinear distance-decay patterns [35,36] . Accordingly,
edge effects, microclimatic alterations, and other disturbance signals are commonly represented using
exponential or exponential-like functions [27,33,37,38] . Building on these principles, we developed a Risk-Adaptive
Conservation Zone (RACZ) model to delineate carbon crediting areas based on spatially structured
degradation risk. It captures the asymmetric and scale-dependent nature of edge-driven degradation, while
providing a mechanistic representation of how landscape structure mediates ecological responses, rather
than relying on purely statistical association [32,33] . This study shows that RACZ identifies where forest carbon
is plausibly threatened by deforestation-driven degradation, thus supporting conservative and transparent
decisions consistent with Integrity Council for the Voluntary Carbon Market (ICVCM) principles on
additionality, permanence, and robust quantification.

METHODS
RACZ model is a distance-dependent, ecologically informed framework. It integrates: (i) delineation of a
reference region (RR) surrounding the project area; (ii) quantification of external deforestation pressure; (iii)
distance-dependent risk modelling; and (iv) parametrization based on mechanistic principles governed by
landscape ecology. The model yields a dynamic internal buffer whose size varies locally in response to both
the spatial gradient of surrounding deforestation and the structural vulnerability of the project area.

Distance-dependent risk model
Degradation risk is modelled using a truncated exponential decay function [Figure 1], where the
independent variable d represents the Euclidean distance from the project boundary to the nearest deforested
pixel. This exponential formulation follows well-established distance-decay relationships in landscape
ecology, where the intensity of ecological processes decreases as a function of distance from disturbance
sources [27,30,39] . Empirical studies have consistently shown that proximity to forest edges influences
microclimatic conditions, biomass dynamics, and biodiversity patterns, with effects attenuating nonlinearly
with the distance [20,40,41] .

In this analysis, the dependent variable (R(d)) is the buffer radius, calculated for each point along the project
edge, from which a risk zone of variable size is defined.

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