Sustainable intensification of Brazilian pastures reconciles food security with large-scale soil carbon sequestration
ブラジルの牧草地の持続的集約化は、食料安全保障と大規模土壌炭素隔離を両立させる (AI 翻訳)
Stoécio Malta Ferreira Maia, Crislâny Canuto dos Santos, Lucas T. Greschuk, Marcelo Cavalcante, Maurício Roberto Cherubin, Cimélio Bayer, Carlos Eduardo Pellegrino Cerri
🤖 gxceed AI 要約
日本語
この研究は、ブラジルの牧草地の持続的集約化と回復が、牛肉生産を向上させながら気候変動緩和に貢献できることを初めて全国規模で評価した。放牧密度と土壌有機炭素の空間データを用いて、生産性ギャップと炭素隔離ポテンシャルを定量化。劣化牧草地の回復により20年間で598 Tg Cの隔離が可能であることを示した。持続的集約化は食料生産と気候目標の両立に有効な経路である。
English
This study provides the first national-scale assessment of how sustainable intensification and restoration of Brazilian pastures can simultaneously enhance beef production and contribute to climate mitigation. Using spatially explicit data, it quantifies productivity gaps and carbon sequestration potential, showing that restoring 89 million hectares of degraded pastures could sequester 598 Tg C over 20 years. The findings demonstrate a viable pathway to reconcile food security, land-use efficiency, and climate goals.
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
ブラジル特有の研究だが、衛星データと土壌炭素モデルを統合した手法は、日本の農地における炭素貯留ポテンシャル評価やJ-クレジット制度への応用が可能。ただし、日本の牧草地は限定的であり、直接的な政策連動は少ない。
In the global GX context
This study offers a methodological framework for assessing pasture-based carbon sequestration that could inform national greenhouse gas inventories and climate commitments. Globally, it provides evidence for the role of tropical grasslands in climate mitigation, relevant to Brazil's Nationally Determined Contribution and international carbon markets.
👥 読者別の含意
🔬研究者:Integrated modeling approach combining remote sensing and soil carbon data for national-scale carbon sequestration assessment.
🏛政策担当者:Quantifies the climate mitigation potential of pasture restoration, informing land-use policies and national climate targets.
📄 Abstract(原文)
Livestock production is a major contributor to land-use change and greenhouse gas emissions, yet it remains central to food security in many tropical countries. Brazil, the world's largest beef exporter, exemplifies this dual challenge: extensive pasturelands support national production, but widespread degradation limits productivity, accelerates soil carbon losses, and drives pressure for continued deforestation. This study provides the first integrated, national-scale assessment of how sustainable intensification and pasture restoration could simultaneously enhance beef production and contribute to climate mitigation across all Brazilian biomes. Using spatially explicit data on stocking rates, pasture condition, and soil organic carbon (SOC), we quantify productivity gaps and estimate the carbon sequestration potential associated with recovering degraded pastures. Specifically, we integrated municipal livestock records with remote sensing-derived maps and the SoilGrids platform to model regional production and land-use scenarios. Our results indicate that increasing stocking rates within existing pasture areas could raise national beef production by approximately 30% without expanding agricultural land. Alternatively, improved management could reduce pasture area requirements by up to 28% while maintaining current output. Restoring 89 million hectares of degraded pastures would sequester 598 Tg C over 20 years and avoid an additional 381 Tg C in losses, with sequestration rates varying by biome and degradation level. These findings demonstrate that sustainable intensification represents a viable pathway to reconcile food production, land-use efficiency, and climate mitigation. By quantifying the biophysical and territorial dimensions of this transition, our study provides evidence to inform Brazil's climate commitments and global efforts to decouple livestock production from environmental degradation. The results highlight the strategic role of tropical pasturelands in achieving large-scale soil carbon sequestration.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.jenvman.2026.130346first seen 2026-07-19 04:42:59
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