Terasaki Hart Drew E, Bùi Thảo-Nguyên, Di Maggio Lauren, Wang Ian J
Department of Environmental Science, Policy, and Management, University of California, Berkeley, CA, USA.
The Nature Conservancy, Arlington, VA, USA.
Nature. 2025 Sep;645(8079):133-140. doi: 10.1038/s41586-025-09410-3. Epub 2025 Aug 27.
Terrestrial plant communities show great variation in their annual rhythms of growth, or seasonal phenology. The geographical patterns resulting from this variation, known as land surface phenology (LSP), contain valuable information for the study of ecosystem function, plant ecophysiology, landscape ecology and evolutionary biogeography. Yet globally consistent LSP mapping has been hampered by methods that struggle to represent the full range of seasonal phenologies occurring across terrestrial biomes, especially the subtle and complex phenologies of many arid and tropical ecosystems. Here, using a data-driven analysis of satellite imagery to map LSP worldwide, we provide insights into Earth's phenological diversity, documenting both intercontinental convergence between similar climates and regional heterogeneity associated with topoclimate, ecohydrology and vegetation structure. We then map spatial phenological asynchrony and the modes of asynchronous seasonality that control it, identifying hotspots of asynchrony in tropical mountains and Mediterranean climate regions and reporting evidence for the hypothesis that climatically similar sites exhibit greater phenological asynchrony within the tropics. Finally, we find that our global LSP map predicts complex geographical discontinuities in flowering phenology, genetic divergence and even harvest seasonality across a range of taxa, establishing remote sensing as a crucial tool for understanding the ecological and evolutionary consequences of allochrony by allopatry.
陆地植物群落的年度生长节律或季节性物候表现出很大差异。这种差异所产生的地理格局，即陆地表面物候（LSP），包含了用于研究生态系统功能、植物生态生理学、景观生态学和进化生物地理学的宝贵信息。然而，全球一致的LSP测绘一直受到一些方法的阻碍，这些方法难以呈现陆地生物群落中出现的所有季节性物候，特别是许多干旱和热带生态系统中微妙而复杂的物候。在此，我们通过对卫星图像进行数据驱动分析来绘制全球LSP图，从而深入了解地球的物候多样性，记录相似气候之间的洲际趋同以及与地形气候、生态水文学和植被结构相关的区域异质性。然后，我们绘制空间物候异步性及其控制的异步季节性模式，确定热带山区和地中海气候区域的异步热点，并报告证据支持以下假设：在热带地区，气候相似的地点表现出更大的物候异步性。最后，我们发现我们的全球LSP图预测了一系列分类群在开花物候、遗传分化甚至收获季节性方面复杂的地理间断，确立了遥感作为理解异域分布导致的物候不同步的生态和进化后果的关键工具。
