这篇研究使用数据驱动的卫星图像分析来绘制全球陆地表面物候（LSP）图，即地球植被年生长节奏的地理模式。作者旨在克服现有方法在表示复杂物候方面的局限性，特别是干旱和热带生态系统中的复杂物候，并利用新的遥感指标（如近红外植被反射率，NIRV）来提供全球一致的LSP多样性见解。研究发现，热带山脉和地中海气候区是物候异步性的热点地区，这种异步性主要由降水和最低温度的异步性驱动。最终，研究表明这种遥感方法可以预测开花物候和遗传分化中的异地异步现象，证实了LSP作为理解生态和进化动态的关键工具的价值。References: Terasaki Hart D E, Bùi T N, Di Maggio L, et al. Global phenology maps reveal the drivers and effects of seasonal asynchrony[J]. Nature, 2025: 1-8.
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