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Representing methane emissions from wet tropical forest soils using microbial functional groups constrained by soil diffusivi...

Publication Type
Journal
Journal Name
Biogeosciences
Publication Date
Page Numbers
1769 to 1786
Volume
18
Issue
5

Tropical ecosystems contribute significantly to global emissions of methane (CH4), and landscape topography influences the rate of CH4 emissions from wet tropical forest soils. However, extreme events such as drought can alter normal topographic patterns of emissions. Here we explain the dynamics of CH4 emissions during normal and drought conditions across a catena in the Luquillo Experimental Forest, Puerto Rico. Valley soils served as the major source of CH4 emissions in a normal precipitation year (2016), but drought recovery in 2015 resulted in dramatic pulses in CH4 emissions from all topographic positions. Geochemical parameters including (i) dissolved organic carbon (C), acetate, and soil pH and (ii) hydrological parameters like soil moisture and oxygen (O2) concentrations varied across the catena. During the drought, soil moisture decreased in the slope and ridge, and O2 concentrations increased in the valley. We simulated the dynamics of CH4 emissions with the Microbial Model for Methane Dynamics-Dual Arrhenius and Michaelis–Menten (M3D-DAMM), which couples a microbial functional group CH4 model with a diffusivity module for solute and gas transport within soil microsites. Contrasting patterns of soil moisture, O2, acetate, and associated changes in soil pH with topography regulated simulated CH4 emissions, but emissions were also altered by rate-limited diffusion in soil microsites. Changes in simulated available substrate for CH4 production (acetate, CO2, and H2) and oxidation (O2 and CH4) increased the predicted biomass of methanotrophs during the drought event and methanogens during drought recovery, which in turn affected net emissions of CH4. A variance-based sensitivity analysis suggested that parameters related to aceticlastic methanogenesis and methanotrophy were most critical to simulate net CH4 emissions. This study enhanced the predictive capability for CH4 emissions associated with complex topography and drought in wet tropical forest soils.