基于数字相机图像的西藏当雄高寒草地群落物候模拟

物候现象是环境条件季节和年际变化最直观、敏感的综合指示器, 其发生时间不仅反映了陆地生态系统短期的动态特征, 其微小的变化还会对陆地生态系统产生重要的反馈作用。高寒草地是青藏高原分布广泛、极具代表性的植被类型, 准确地获取高寒草地群落的物候特征, 对于理解和预测气候变化对青藏高原生态系统的影响具有重要意义。该文以西藏当雄高寒草地为研究对象, 探讨了近地面数字相机图像在高寒草地群落季相监测中的作用, 结果如下: 1)通过比较不同绿度指数的差别, 确定了准确表征高寒草地植被群落季相变化的绿度指数——绝对绿度指数(2G_RB);2)结合土壤含水量数据, 通过线性回归分析得知高寒草地植被群落生长过程与表层(≤10 cm)土壤含水量的变化较为一致(R2> 0.70); 3)通过对比分析, 发现降水在高寒草地群落季相"变绿"过程中具有"触发"作用。研究表明, 数字相机技术可作为物候监测手段, 实现高寒草地植被群落季相的实时、连续获取, 为更好地揭示气候变化影响下景观尺度季相演变特征, 诊断地方、区域和全球尺度上生态系统对气候变化的快速响应提供了有效的手段。

Simulations of phenology in alpine grassland communities in Damxung, Xizang, based on digital camera images

Aims Phenology refers to periodic appearances of life-cycle events. It is crucial for predicting plant phenological responses to climate change and for identifying the period of carbon-uptake. Tracking the real-time canopy status accurately, especially in harsh environments, is becoming a large challenge for understanding and modeling vegetation-climate interactions. Our objective focuses on how to obtain relatively accurate real-time canopy status in Qinghai-Xizang Plateau using digital camera images.
Methods A standard, commercially available webcam was mounted at the top of the eddy covariance tower at the Damxung Rangeland Station. Images were collected every half an hour from 9:30 a.m. to 5:00 p.m. local time each day. We extracted red, green, and blue color channel brightness data for a region-of-interest (ROI) from each image (ROI, the subset of image, can better describe the target’s characters). The size of ROI is 100:180] and 10:380]), and it composed the different greenness indices according to the equations. We confirmed the best one that can reflect the size of leaf area index and variations in chlorophyll content by comparing different indices.
Important findings The absolute greenness index (2G_RB) is able to describe the canopy status qualitatively and quantitatively and is powerful in tracking community phenological stages. This indicates that digital cameras can be used in monitoring real-time phenology of alpine grassland community. Linear regression analysis of soil moisture indicates greenness is best explained by surface soil moisture (≤10 cm). By comparing canopy phenological events with conventional meteorological data, we also speculate that precipitation plays a critical role in triggering the spring phenological response in semiarid alpine grassland.