Effect of biogenic structures on greenhouse gases emissions in wetlands of La Cruz Lagoon, Gulf of California, Sonora

Greenhouse gases (GHGs) are responsible for global warming, which has intensified due to human activities over the past few decades. Coastal wetlands—mangroves and salt marshes—represent an alternative for mitigating the negative effects of GHGs due to the ecosystem services they provide, especially carbon storage. However, they can act as sources or sinks of GHGs, but studies in Mexico are scarce and limited to the tropical and subtropical climates of the country, while the arid ecosystems of the northwest are understudied. This study was conducted in mangroves and salt marshes of Laguna La Cruz, Gulf of California, to understand the temporal and spatial dynamics, as well as the relationship between biogenic structures (crab burrows, and pneumatophores) and abiotic factors that influence GHG fluxes. Monthly measurements were taken during June, October, and November (2024) using static chambers coupled to an infrared spectrophotometer (FTIR, Gasmet DX4015) to simultaneously measure CO₂, CH₄, and N₂O. Eight chambers per site were used under three treatments: the presence of burrows, and pneumatophores, and the absence of these structures. Fluxes were estimated using the Rfluxes package, and data were analyzed using REML and PCA (RStudio 2024). CO₂, CH₄, and N₂O fluxes ranged from -53.53 to 437.13, -0.0899 to 0.0413, and -0.0325 to 0.0213 mg m^-2 h^-1, respectively. The most relevant factors for CO₂ and CH₄ were month, soil temperature, and biogenic structures. Biogenic structures facilitate the interaction between the soil and the atmosphere, while the month and soil temperature affect the metabolic activity of GHG-producing microorganisms. N₂O did not show a clear relationship with any of the studied variables. GHG fluxes showed temporal variation and seem to be influenced by the presence of biogenic structures. However, more samples are needed to understand the annual variation of GHG, as well as to consider other variables that better explain the N₂O variation.