青藏高原草地物候变化对碳收支的影响效应和途径

Vegetation phenology is a key factor in mediating carbon budget of terrestrial ecosystem. Moreover, the influences of vegetation phenology dynamics on carbon budget exhibit significant regional differences. The unique alpine grassland ecosystem on the Tibetan Plateau is characterized by a frigid and dry climate, in which the effects and pathways of phenological influences on carbon budget has yet not been clearly revealed. Based on the carbon flux phenology, the project aims to select the optimal scheme for phenology estimation from multiple remote sensing data and multiple extraction methods. Meanwhile, the TEM model will be optimized by integrating the ground observational flux, biomass and field-measured eco-physiological data. Through improving the simulation of phenological indices and carbon fluxes, it is effective to analyze the relationship between them at the regional scale. Then, the spatial variations in the responses of carbon budget to the start, end and length of growing season will be revealed. The project will further explore the possible effects of phenological influences on carbon budget and build the corresponding conceptual models. Moreover, the influence pathways of phenology on carbon budget will be clarified by comparing the magnitudes in responses of carbon budget components. This project can deepen the understanding of biological mechanisms in affecting carbon cycle for the alpine grassland ecosystem, and also can provide scientific guidance for the grassland ecosystem management to cope with climate change.

植物物候是影响陆地生态系统碳收支的关键因素，而且植物物候变化对碳收支的影响具有显著的区域差异。青藏高原高寒草地气候寒冷干旱，生态系统独特，其碳收支变化的物候影响效应和途径尚未明晰。本项目基于地面通量观测的物候针对多源遥感数据多物候识别方法筛选出高寒草地的最优物候遥感识别结果；同时结合地面通量观测数据、生物量数据、野外测定的生理生态参数对TEM碳循环模型进行优化。通过提高物候以及碳通量的模拟精度使其得以实现有效的区域尺度扩展，进而在区域尺度上揭示生长季始末期以及生长季长度变化对碳收支影响的空间格局，探究研究区域内物候变化对碳收支的可能影响效应并构建概念模型，通过比较碳收支组分对物候变化的响应强度厘清物候变化影响碳收支的途径。本项目可深化对高寒草地碳循环生物影响机制的认知，为应对气候变化的高寒草地生态系统管理提供科学依据。

植物物候是影响陆地生态系统碳收支的关键因素，而且植物物候变化对碳收支的影响具有显著的区域差异。青藏高原高寒草地气候寒冷干旱，生态系统独特，其碳收支变化的物候影响效应和途径尚未明晰。本项目首先基于地面物候观测数据评价了遥感物候识别方法对青藏高原高寒草地物候的识别效果；然后对植被生产力模型进行了本地参数优化，模拟了青藏高原高寒草地的植被生产力；最后探究了青藏高原高寒草地物候变化对植被生产力的影响效应。本项目研究发现采用最大曲率变化方法对归一化差值植被指数（NDVI）进行青藏高原高寒草地生长季始期（SOS）识别具有较好效果，但所有方法对高寒草地生长季末期（EOG）的遥感识别效果不佳，存在非常大的误差。此外，研究发现目前的碳循环机理模型在模拟植被固碳响应昼夜温度方面表现较弱，其原因在于模型主要由平均温度驱动，而不是昼夜温度。本研究对植被生产力光能利用率模型进行了青藏高原本地优化，通过改进温度限制条件以及最大光能利用率等参数提高了生产力模拟精度。基于上述研究，本项目生成了青藏高原高寒草地的草地物候和生产力数据，并分析了高寒草地物候变化对植被生产力的影响。研究发现高寒草地返青提前有利于促进春季净初级生产力（NPP）增加，但促进效应在夏季有所减弱，且抑制秋季NPP。随降水增加，春季NPP对返青提前的响应更加强烈。在缺水限制条件下，返青提前对生长季后期碳积累的滞后抑制效应更加凸显。本项目的研究有利于促进对高寒生态系统碳循环过程和驱动机制的深化认知。