Comparative assessment of LFA and RHA metrics in explaining ecosystem functions and multifunctionality across bioclimatic rangelands
バイオクライメティックな放牧地における生態系機能と多機能性の説明におけるLFAおよびRHAメトリクスの比較評価 (AI 翻訳)
Zahra Heidari Ghahfarrokhi, Pejman Tahmasebi, Ali Asghar Naghipour
🤖 gxceed AI 要約
日本語
イランの5つの生物気候帯の放牧地を対象に、生態系機能（地上部バイオマス、土壌保全係数、土壌有機炭素、土壌呼吸、微生物バイオマス炭素）と多機能性を、RHAおよびLFAという2つの評価手法で比較検討した。線形モデルの説明力(R²)は対象機能数に応じて増加するが地域差が大きく、地中海・半乾燥地域では構造指標が高い説明力を示した。機能と指標の組み合わせによりモニタリング効率向上が期待される。
English
Across five bioclimatic rangelands in Iran, this study compares Rangeland Health Assessment (RHA) and Landscape Function Analysis (LFA) metrics in explaining ecosystem functions (e.g., soil organic carbon, biomass, soil respiration) and multifunctionality. Model explanatory power generally rose with the number of functions included, with structural indicators performing best in Mediterranean and Semi-steppe regions. The findings support targeted, low-cost monitoring combos for adaptive rangeland management under climate change.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本では直接的なGX題材ではないが、生態系機能の簡易評価手法は自然資本勘定や生物多様性保全、土壌炭素蓄積のモニタリングに応用でき、今後拡大する自然関連開示(TNFD等)にも示唆を与える。
In the global GX context
This paper provides empirical evidence on linking low-cost field indicators (RHA/LFA) to ecosystem multifunctionality, relevant for natural capital accounting, soil carbon monitoring, and TNFD or ISSB nature-related disclosure frameworks. It offers a methodological example for integrating ecosystem function metrics into national monitoring systems under diverse climate zones.
👥 読者別の含意
🔬研究者:Methodological insight on how structural indicators (RHA/LFA) can predict multifunctionality and how explanatory power varies across bioclimatic regions.
🏢実務担当者:Land managers and sustainability teams can adopt the highlighted indicator combinations for efficient ecosystem condition and soil carbon monitoring.
🏛政策担当者:Supports integrating rapid field-assessments into national rangeland monitoring frameworks aligned with climate and biodiversity targets.
📄 Abstract（原文）
Rangelands provide essential ecological functions such as biomass production, carbon and water regulation, nutrient cycling, and biodiversity conservation, yet their integrity is increasingly threatened by climate change and grazing pressures. Reliable assessment of ecosystem functions (aboveground biomass, soil conservation factor, soil organic carbon, soil respiration, and microbial biomass carbon) and multifunctionality is therefore critical for sustainable management. This study comparatively evaluated two widely used assessment approaches, the Rangeland Health Assessment (RHA) and Landscape Function Analysis (LFA), across five bioclimatic rangelands in Iran. Ecosystem multifunctionality was quantified using standardized measures of key functions, and linear models were applied to examine the explanatory power of RHA and LFA metrics. Results showed that the explanatory power of models (R²) generally increased with the number of functions included, although the magnitude of this increase varied across regions and metrics. Structural indicators such as rangeland health, soil/site stability, and hydrologic function showed the highest ability to explain multifunctionality in Mediterranean and Semi-steppe regions. In contrast, Desert and Cold regions exhibited weaker and more variable relationships. Overall, the findings demonstrate that targeted combinations of key functions, together with sensitive structural indicators, can substantially improve monitoring efficiency and provide a robust scientific basis for rangeland management under diverse climatic conditions.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1038/s41598-026-61607-2first seen 2026-07-31 05:16:40
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