小气候
天蓬
温带气候
物候学
温带森林
温带雨林
树冠
生态学
环境科学
地理
大气科学
农林复合经营
林业
生物
生态系统
地质学
作者
Yanjun Su,Xiaoyong Wu,Chunyue Niu,Xiaoqiang Liu,Tianyu Hu,Yuhao Feng,Yingyi Zhao,Shuwen Liu,Zhonghua Liu,Guanhua Dai,Yao Zhang,Koenraad Van Meerbeek,Jin Wu,Lingli Liu,Qinghua Guo
标识
DOI:10.5194/egusphere-egu25-5554
摘要
Autumn phenology plays a critical role in shaping the carbon sequestration capacity of temperate forests. Notable local-scale variations in autumn phenology have drawn increasing attention recently, potentially introducing substantial uncertainty when predicting temperate forest productivity. Yet, the underpinning mechanisms driving these variations remain inadequately elucidated. While macroclimate conditions are traditionally recognized as primary determinants of autumn phenology, they fail to explain inter-crown variations occurring within the same macroclimate environment. Here, we hypothesize that canopy structure serves as a key determinant of the local-scale variations of autumn phenology in temperate forests by mediating microclimate conditions. To test this hypothesis, we develope microForest, a novel lightweight forest microclimate model capable of efficiently and accurately predicting under-canopy air temperature at high temporal and spatial resolutions using readily available remote sensing data and meteorological reanalysis products as inputs. Our results reveal significant and consistent relationships between canopy structure and autumn phenology across six temperate forest sites, induced by the regulation effect of canopy structure on microclimate conditions. Incorporating the identified “canopy structure-microclimate-autumn phenology” pathway into existing autumn phenology models significantly improves the prediction accuracy and reduces the projected delay in the start of autumn over the remainder of the century. These findings offer a new perspective for interpreting the local variations of autumn phenology in temperate forests and emphasize the urgent need to integrate the identified pathway into Earth system and vegetation models, especially considering the asynchronous changes of macroclimate and microclimate conditions.
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