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results show that RACZ restricts crediting to genuinely vulnerable areas in intact regions while capturing extensive
risk in heavily fragmented frontiers. Therefore, this ecologically grounded approach complements core principles of
the Integrity Council for the Voluntary Carbon Market by improving environmental integrity and credibility in carbon
accounting through aligning credit zones with spatial degradation risk.

INTRODUCTION
Nature-based climate solutions, particularly the conservation and restoration of forests, are recognized as a
cornerstone of any viable strategy to meet the climate mitigation targets, with the potential to provide over a
third of the cost-effective CO mitigation needed by 2030 . In terms of conservation scope, most
[1]
2
methodologies still treat deforestation as the most relevant disturbance and assume that emissions occur only
where forests are directly cleared. Most carbon accounting frameworks such as REDD+ have mainly focused
on projecting deforestation to define highly flexible, while easily inflated, baselines , which are often based
[1-4]
on simple correlations or historical transitions rather than ecological processes . Of the deforestation
[5]
baselines found to be inflated, only 25% of the resulting avoided-deforestation credits led to actual emission
reductions .
[5,6]
Recent commentaries and syntheses argue that restoring trust in carbon markets requires more transparent
and evidence-based quantification . This matters “now” because carbon market legitimacy has become a
[4]
binding constraint: when integrity is questioned, demand softens, pricing becomes volatile, and high-quality
projects struggle to compete in an increasingly skeptical environment. Recent market analyses indicate that
high-integrity credits typically trade at price premiums of three to five times those of lower-quality
offsets—often around US$ 15 t CO compared to US$ 3-5 t CO —reflecting buyer preference for reduced
-1
-1
2
2
uncertainty and more defensible climate claims . Parallel methodological critiques identify structural
[7,8]
reasons for inflated crediting under commonly used REDD+ baseline approaches [9,10] . Approximately 78% of
over-crediting is due to the various ex ante modeling approaches used in certified valuations, with
considerable uncertainty surrounding this allocation being acknowledged [4,11] . Together, these studies
highlight the same practical point for developers and standards: credibility increasingly relies on whether a
method can distinguish truly threatened forests from relatively stable ones and assign credit accordingly.

A central gap emerges at the interface between current ecological understanding and operational carbon
methodologies. Most REDD+ approaches estimate avoided emissions primarily by projecting future
deforestation and applying risk models tuned to the probability of forest loss. That logic is appropriate for
deforestation, but it tends to treat remaining forest as uniformly “safe” unless it is predicted to be
cleared—thereby under-representing a second, increasingly well-documented pathway of carbon loss:
degradation inside standing forests driven by fragmentation and proximity to anthropogenic edges. Carbon
losses derived from the edge effect induced by fragmentation affect 97% of global forest area [12,13] and may
account for up to one-third of losses resulting from deforestation . Consequently, forests adjacent to
[14]
deforested regions can function as chronic sources of carbon emissions, with cumulative biomass losses
working as an additional unquantified flux, that can counteract carbon emissions avoided by reducing
deforestation [14,15] . Indeed, studies have demonstrated that degradation is not a peripheral or secondary
impact but rather a primary driver of carbon loss, potentially exceeding emissions from deforestation [16,17] .

This effect is not fortuitous. A growing body of empirical evidence shows that forest degradation driven by
proximity to deforestation has substantial impacts on biodiversity, vegetation structure, and aboveground
biomass [18-22] . Edge-induced microclimatic changes—such as increased temperature, reduced humidity, and
greater wind exposure—elevate physiological stress and mortality among large, high-biomass trees, leading
to shifts in species composition, lower wood density, reduced carbon storage, and declining ecosystem