模拟被忽视和未充分利用的作物,以实现未来的粮食弹性:一个区域的MaxEnt工作流程
Daniel J Winstead1, Michael G Jacobson1
1Department of Ecosystem Science and Management, College of Agriculture Science The Pennsylvania State University University Park Pennsylvania USA.
Plant-environment interactions (Hoboken, N.J.)
|March 2, 2026
概括
本研究引入了MaxEnt工作流程,用于预测适合于气候变化适应的被忽视和未充分利用的作物 (NUS). 它有助于确定适用于区域应用的弹性NUS品种,帮助小农在作物选择中获得帮助.
科学领域:
- 农业科学 农业科学
- 适应气候变化 适应气候变化
- 生物多样性研究 生物多样性研究
背景情况:
- 农业生物多样性对于气候变化抵御能力至关重要.
- 学术研究与农业生物多样性战略的实际应用之间存在差距.
- 被忽视和未充分利用的作物 (NUS) 提供了适应的潜力,但需要有针对性的识别.
研究的目的:
- 设计一个高通量MaxEnt工作流来预测合适的NUS.
- 确定能抵御气候变化影响的NUS候选人.
- 为了弥合NUS研究和小农的实地实施之间的差距.
主要方法:
- 开发了一种基于MaxEnt的工作流程,用于物种分布建模.
- 利用了地理空间数据和气候变化预测.
- 专注于用有限的发生数据预测作物适合性.
主要成果:
- 确定了对气候变化具有高弹性的潜在候选NUS.
- 证明气候变化对NUS的影响在地理上是多样化的.
- 该工作流有效地预测了当前和未来气候场景下的作物适应性.
结论:
- MaxEnt 工作流提供了一个可扩展的工具,用于识别可适应的 NUS.
- 地理空间分析是了解区域气候变化对作物的影响的关键.
- 这种工具使小农户能够做出明智的决定,为气候适应性增加作物多样化.
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