An integrated index based on climatic constraints and soil quality to simulate vegetation productivity patterns

• Published in: Ecological indicators 2021-10, Vol.129, p.108015, Article 108015
• Main Authors: Geng, Shoubao, Li, Wei, Kang, Tingting, Shi, Peili, Zhu, Wanrui
• Format: Article
• Language: English
• Subjects: Climatic constraint; Soil quality; Spatial classification; the Taihang Mountains; Vegetation productivity pattern; Vegetation type; Water-temperature-soil index
• ISSN: 1470-160X; 1872-7034
• DOI: 10.1016/j.ecolind.2021.108015

•A simple metric WTSI was developed to simulate productivity patterns.•WTSI is highly effective to reflect the spatiotemporal patterns of productivity.•The importance of soil factors in vegetation productivity modeling.•WTSI variations along elevation gradients and among vegetation types were analyzed.•Strategies can be proposed via spatial classification of constraints on productivity. Vegetation productivity simulation at large scales has become an important issue as it reflects the spatial difference of ecosystem carbon sequestration. Vegetation productivity patterns are generally controlled by environmental factors such as climate and soil. However, most of the current models focus on climatic limitations on productivity, whereas soil restrictions have been rarely considered. Moreover, some models are too sophisticated to exert their applications. In this study, we integrated vapor pressure deficit, minimum temperature, and soil quality into a simple water-temperature-soil index (WTSI) to simulate vegetation productivity patterns, and identified the spatial classification of the three environmental constraints on productivity in the Taihang Mountains. Results showed that WTSI was significantly correlated with NDVI at both annual and seasonal scales and the integration of soil quality and climatic constraints could greatly increase the accuracy of productivity simulation except for summer, indicating that WTSI was highly effective to model vegetation productivity patterns. The spatial patterns of WTSI presented three distinct regions with a descending trend of the averaged WTSI values from the southern to the northern and then to the central part of the study area, suggesting that the constraints of water, temperature, and soil factors were minimum in the south but maximum in the center for vegetation. The seasonal dynamics of WTSI depended on the cyclic variations of hydrothermal conditions from nearly unconstrained in summer to almost completely restricted in winter for plant growth, with spring and autumn as transition periods. WTSI and NDVI generally had similar variation trends along elevation gradients but diverse performances among vegetation types with more consistencies for forests, shrubs, and steppes than meadows and crops. WTSI was significantly correlated with NDVI for all vegetation types with comparable correlation coefficients (R2) for forests (0.73), shrubs (0.70), and steppes (0.72), followed by crops (0.57) and meadows (0.41). RGB com