Work

Long-Term Spatiotemporal Patterns and Driving Mechanisms of Net Ecosystem Productivity on the Qinghai–Tibetan Plateau Based on the Optimal Multivariate-Stratification Geographical Detector Model

Year: 2026

Type: article

Abstract: As a globally climate-sensitive region and ecological security barrier, the spatiotemporal dynamics of net ecosystem productivity (NEP) on the Qinghai–Tibetan Plateau are of great significance for understanding carbon cycling in alpine ecosystems. However, due to insufficient representation of parameter heterogeneity in models and unclear nonlinear attribution of complex environmental factors, substantial uncertainties remain in the spatiotemporal patterns and driving mechanisms of NEP in this region. Therefore, this study first employed an improved Carnegie–Ames–Stanford Approach (CASA) model to assess NEP on the Qinghai–Tibetan Plateau from 2000 to 2022 and characterize its spatiotemporal evolution, and subsequently applied the optimal multivariate-stratification geographical detector (OMGD) to quantify the independent and synergistic driving effects of hydrothermal conditions, extreme climate events, and human activities on NEP variations. The results indicate that: (1) from 2000 to 2022, vegetation NEP on the Qinghai–Tibetan Plateau exhibited a southeast-to-northwest decreasing spatial heterogeneity pattern, with a multi-year mean value of 219.61 g C·m−2; (2) during the study period, NEP showed an overall increasing trend (at a rate of 1.596 g C·m−2·yr−1), with 52.5% of the region experiencing significant increases, primarily concentrated in the central–eastern humid regions and alpine meadow areas; and (3) among individual factors, the growing season length was the primary driver of NEP, in addition to temperature and precipitation, while human activities exerted negligible influence; under interaction effects, the hydrothermal synergistic enhancement (0.79 < q < 0.89) exhibited the highest explanatory power. These results show that carbon sequestration in alpine ecosystems is governed by nonlinear hydrothermal interactions and provide a scientific basis for assessing carbon sink resilience in the “Asian Water Tower” under global warming.

Source: Land

DOI: 10.3390/land15081528

Authors: Yizhou Li, Hanfei Wang, Feng Liu, Xiaoheng Wang, Hao Li

Institution: Sichuan Agricultural University

Language: English

Topic: Remote Sensing in Agriculture

Subfield: Ecology

Field: Environmental Science

Domain: Physical Sciences

SDGs: Climate action, Life on land

Open Access status: gold

Estimated APC paid: $3,137