Page 37 - 2417

Chaib et al. Carbon Footprints 2026, 5, 23 Page 13 of 23

external pressures. Such results align with recent evidence that carbon losses derived from the edge effect
induced by fragmentation affect 97% of global forest . By deriving the baseline solely from recent
[62]
transitions from natural forest to anthropic use in structurally similar territories and adjusting for
classification error using design-based area estimation, this dynamic baseline strengthens best practices for
uncertainty-aware deforestation baselines in smallholder landscapes [15,29] and promote the social equality as
well.

We further contrast our approach with consolidated jurisdictional frameworks. In consolidated REDD+
frameworks such as Verra’s VM0048 methodology and its VMD0055 module, project baselines for
[63]
[64]
avoiding unplanned deforestation are anchored in observed land-cover change but are constructed at much
larger jurisdictional scale as dynamic baselines that are periodically updated. Jurisdictional activity data on
unplanned deforestation are generated by the owner institution or contracted data service providers using
high-resolution satellite imagery, forest-cover benchmark maps and sample-based area estimation over a
recent historical reference period; The dynamic baseline implemented for Curiaú under our framework
follows the same broad principle of grounding baselines in observed deforestation but does so at a
micro-jurisdictional scale and with a fully ex post temporal framing tailored to smallholder mosaics. Instead
of receiving a multi-year allocation of jurisdictional activity data, Curiaú’s baseline is calculated directly from
last-year forest-to-anthropic transitions observed in a reference region of 47 other, socioeconomically
comparable smallholder territories. All underlying deforestation areas are first corrected using a
probability-based accuracy assessment of the 10 m land-cover maps, so that uncertainty is incorporated
through design-based area estimation rather than post hoc discounting of baseline activity data. Relative to
different REDD+ frameworks such as VM0048 and VMD0055, this approach appears to offer a
comparatively simple, equitable and transparent baseline that can be updated ex post year by year as new
land-cover data become available, while still aligning with emerging integrity expectations by anchoring
baselines dynamically in externally observed behavior beyond the project boundary and limiting the scope
for project-developer discretion in baseline setting.

This temporal design implies that each credited year is benchmarked against observed deforestation
dynamics within the same period, rather than against an aggregated historical average. While multi-year
reference periods can potentially reduce sensitivity to atypical conditions in individual years, they also
smooth temporal variability and introduce assumptions regarding the selection of historical windows. By
contrast, the annual ex post construction adopted here captures year-to-year fluctuations and provides real
carbon emission reduction directly.

Collectively, these design features reinforce the integrity of the carbon emission reduction. The combination
of a dynamic ex post baseline anchored in observed deforestation, locality-matched reference regions that
constrain discretionary baseline setting, and probability-based accuracy assessment with design-based area
estimation strengthens baseline credibility and data robustness in response to concerns that methodological
choices can inflate avoided-deforestation claims [26-28] .

Within the applied framework , livelihood vulnerability enters the additionality logic as a screening
[42]
condition that complements conventional additionality assessment procedures. As in established AFOLU
methodologies, additionality is demonstrated through the identification of plausible alternative land-use
scenarios with the application of structured additionality tests (e.g., barrier or investment analyses) [42,63] . The
inclusion of a vulnerability-based filter therefore introduces an additional layer that constrains eligibility to
contexts in which socio-economic limitations, restricted adaptive capacity and non-trivial deforestation
pressure coexist, increasing the likelihood that climate-finance revenues are materially relevant to land-use
decisions. In this sense, the framework differs from actor-neutral REDD+ approaches, including VM0048 ,
[63]