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数据驱动的场景分析支持碳智能农村景观的历史Silvoarable系统的复兴
Filippo Brandolini1,2, Angelo Gurgel3, Andrea Zerboni4
1Center for Sustainability Science and Strategy, Massachusetts Institute of Technology, 400 Main St, Cambridge, MA, 02142, USA. filbrand@mit.edu.
Scientific reports
|October 7, 2025
概括
农林,一个气候解决方案,在欧洲下降. 在意大利北部恢复传统的Silvoarable系统可以将碳捕获量提高12%,突出显示历史土地利用的价值.
科学领域:
- 环境科学 环境科学
- 农业科学 农业科学
- 气候科学 气候科学
背景情况:
- 基于自然的气候解决方案农林业在欧洲由于社会经济变化和土地密集化而下降.
- 传统的silvoarable系统在历史上具有重要意义,但在很大程度上被遗弃了.
- 随着农业林业实践的减少,单一农作物已经扩大.
研究的目的:
- 重建意大利北部传统农林系统的历史作用和碳储量.
- 为了建模历史土地利用变化对碳捕获的影响.
- 评估恢复农林林业的潜力,以期在未来缓解气候变化.
主要方法:
- 利用了长达一个世纪的土地使用记录 (1929-2024) 和历史来源.
- 集成的蒙特卡洛模拟和基于场景的建模用于碳库存估计.
- 分析了农林系统和单一种植扩张的程度.
主要成果:
- 历史上的银色可携带系统平均储存了75.4t C ha-1 (范围:50.4-101.6t C ha-1).
- 放弃农业林业实践导致其范围减少了97%.
- 修复可使用的系统可以将区域碳捕获量增加高达12%.
结论:
- 传统的农林系统具有重要的碳储存潜力.
- 修复可修剪的系统为缓解气候变化提供了一个可行的策略,可以与植树相提并论.
- 历史土地利用知识对于发展碳智能农业和弹性景观至关重要.
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