Sustainability, Vol. 17, Pages 11260: Linking Soil C:N Stoichiometry to Greenhouse Gas Balance: Implications for Ecosystem Sustainability in Temperate Forests

Fuente: Sustainability - Revista científica (MDPI)
Sustainability, Vol. 17, Pages 11260: Linking Soil C:N Stoichiometry to Greenhouse Gas Balance: Implications for Ecosystem Sustainability in Temperate Forests
Sustainability doi: 10.3390/su172411260
Authors:
Baolong Du
Nan Xu
Yuan Wang
Juexian Dong
Shaopeng Yu

Ecological stoichiometry offers a powerful framework for linking the elemental composition of ecosystems to their biogeochemical functions. However, whether soil stoichiometry directly controls greenhouse gas (GHG) emission ratios remains largely unexplored. This study provides a case study investigating the link between the soil carbon-to-nitrogen (C:N) mass ratio and the gaseous C:N molar emission ratio in three distinct temperate island-like forests (Larix gmelinii forest, LGF; Betula platyphylla forest, BPF; and a Populus-Betula mixed forest, PBMF) in the Qixing River Wetland. Using the static chamber–gas chromatography method, we measured soil fluxes of CO2, CH4, and N2O throughout the growing season. Our results revealed a strong, significant positive linear relationship (R2 = 0.99, p < 0.001) between the soil C:N ratio and the gaseous C:N emission ratio across all forest types. The LGF, possessing the highest soil C:N ratio, exhibited the highest gaseous C:N emission ratio, driven by substantial CO2 emissions (mean flux of 512.45 mg·m−2·h−1). Furthermore, the Larix gmelinii forest (LGF) exhibited the highest total Global Warming Potential (GWP), primarily driven by its significant CO2 emissions. In contrast, the PBMF was the strongest CH4 sink (−25.82 μg·m−2·h−1) and a N2O emission hotspot (15.24 μg·m−2·h−1), corresponding to its low soil C:N ratio. These findings provide strong evidence that soil elemental stoichiometry is a key driver regulating the functional signature of GHG emissions. This case study highlights the potential of using stoichiometric theory to develop predictive tools for assessing ecosystem sustainability and informing sustainable forest management strategies under climate change.