Projecting future aboveground carbon sequestration rate of alpine forest on the eastern Tibetan Plateau in response to climate change

Abstract

The aboveground carbon sequestration rate (ACSR) of forests serves as an indicator of their carbon sequestration capacity over time, providing insights into the potential carbon sequestration capacity of forest ecosystems. To explore the long-term Spatiotemporal variation of ACSR in the transitional ecotone of the eastern Tibetan Plateau under climate change scenarios, we utilized a forest landscape model that was parameterized with forest inventory data from the eastern Tibetan Plateau to simulate this ecological function changes. The study found that climate warming had significant effect on forests ACSR in different types of forests. ACSR was significantly reduced (p<0.05) in cold temperate coniferous and temperate coniferous forests, whereas it was significantly increased in deciduous broad-leaved forests. However, the impact of climate warming on evergreen broad-leaved forests was found to be negligible. At the species level, climate warming has mostly suppressed the ACSR of coniferous trees, except for Chinese hemlock. The main dominant species, spruce and fir, have been particularly affected. Conversely, the ACSR of most broad-leaved trees has increased due to climate warming. In addition, at the landscape scale, the ACSR within this region is expected to experience a steady decline after 2031s-2036s. Despite the effects of climate warming, this trend is projected to persist. In conclusion, the forests ACSR in this region will be significantly affected by future climate warming. Our research indicates that climate warming will have a noticeable suppressive effect on conifers. It is imperative that this factor be taken into account when devising forest management plans for the future in this region.

Study on Forest and Grassland Ecological Space Structure in Eyu Mining Area and Potential Alternatives for Enhancing Carbon Sequestration

“…Utilizing the Laplacian pyramid transform method, we performed data compression and redundancy removal, yielding three components: "brightness", "greenness", and "third component". The "third component" was selected as the wetness index due to its significance as an ecological indicator reflecting the changes in soil and vegetation moisture status in the environment, and its ability to better capture humidity changes in the ecological system [33]. The formula for calculating the wetness index (WET) is presented below (Formular (2)):…”