Affiliation:
1. Chongqing Engineering Research Center for Remote Sensing Big Data Application, Chongqing Jinfo Mountain National Field Scientific Observation and Research Station for Karst Ecosystem, School of Geographical Sciences, Southwest University, Chongqing 400715, China
2. State Key Lab for Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Abstract
The complexity of forest ecosystems leads to differences in the distribution patterns of different vegetation types along elevation gradients. This study aimed to explore the characteristics of AGB variations along elevation gradients for different forest types and tree species components in the Qinling–Daba Mountains. Based on 329 field vegetation survey plots, including four sampling transects and four representative mountains, individual tree AGB was calculated using allometric biomass equations. Further, generalized additive models (GAMs) were used to investigate the relationships between AGB and elevation for four forest types (broadleaf forests, coniferous forests, mixed coniferousbroadleaf forests, and shrublands) and three AGB components (total AGB (tAGB), broadleaf species AGB (bAGB), and coniferous species AGB (cAGB)) across eight vegetation survey regions. The results showed that the AGB of different forest types is significantly related to elevation (p < 0.05), with broadleaf forest AGB showing a unimodal pattern with elevation, coniferous forest and mixed forest AGB increasing with elevation, and shrubland AGB exhibiting a noticeable rise at higher elevations. The AGB components across different vegetation survey regions also showed significant relationships with elevation (p < 0.05), with broadleaf species AGB displaying a monotonically increasing trend in regions with a small elevation range and exhibiting a unimodal or bimodal distribution in regions with a large elevation range, while coniferous species AGB generally increased with elevation. Although elevation significantly influenced forest AGB, the variation in R2 values indicated that elevation is not the sole determinant of AGB variation. This study improves the understanding of spatial patterns of forest biomass along elevation gradients.