デジタル時代のカーボンファーミング：土壌炭素隔離、永続性、測定・報告・検証

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:土壌炭素隔離の測定・報告・検証における生物物理学的・会計的課題とデジタル技術の限界を整理する研究指針を提供する。

🏢実務担当者:カーボンファーミング事業のMRV設計において、現場再測定とデジタルツールの併用、保守的な不確実性評価、リバーサル条項の重要性を理解するのに役立つ。

🏛政策担当者:土壌炭素クレジット制度の設計において、永続性・リーケージ・非CO2ガスを含む包括的なMRV要件とデータ監査可能性の確保が不可欠であることを示唆する。

Carbon farming is increasingly promoted as a way to rebuild soil organic carbon while creating verifiable climate benefits and new farm income streams. Its credibility, however, depends on a chain of conditions that extends well beyond whether a practice can increase soil carbon at an experimental site. This critical narrative review evaluates the biophysical basis of agricultural soil carbon sequestration, the distinction between molecular persistence and project-level permanence, the measurement of stock change, and the rapidly developing role of digital technologies in measurement, reporting and verification (MRV). Literature published from 2000 to 6 July 2026 was examined, with earlier conceptual material considered only where necessary. Evidence was prioritised from peer-reviewed field studies, meta-analyses, methodological studies and authoritative technical frameworks. The evidence supports the capacity of cover crops, organic amendments, diversified rotations and some biochar applications to raise soil carbon under appropriate conditions, but effect sizes are strongly conditioned by baseline stocks, climate, texture, depth, carbon inputs, management history and system boundaries. Apparent gains can also arise from altered depth distribution or transferred organic matter rather than additional atmospheric carbon removal. Permanence is therefore a management and accounting property, not simply a property of chemically resistant carbon. Direct remeasurement remains the evidentiary anchor for stock-change assessment, yet high spatial variability and slow accumulation make short project periods statistically difficult. Fixed-depth accounting can bias comparisons when bulk density changes; equivalent-soil-mass approaches and explicit uncertainty analysis are more defensible. Remote sensing, digital soil mapping, spectroscopy, machine learning and process-based models can reduce transaction costs and improve stratification, activity monitoring and extrapolation, but they do not remove the need for field calibration, independent validation and periodic soil remeasurement. High-integrity carbon farming consequently requires hybrid MRV, conservative uncertainty treatment, transparent counterfactual baselines, reversal provisions, leakage and non-carbon greenhouse-gas accounting, auditable data lineage and safeguards for equitable participation. Digitalisation can make carbon farming more scalable, but only if it strengthens rather than substitutes for biophysical and governance integrity.

• openalex https://doi.org/10.9734/jabb/2026/v29i104418first seen 2026-09-14 04:45:23