Rainfall frequency and soil water availability regulate soil methane and nitrous oxide fluxes from a native forest exposed to elevated carbon dioxide

Abstract

Free‐air carbon dioxide enrichment (FACE) experiments in terrestrial ecosystems have demonstrated ecological responses of key ecosystem processes to rising atmospheric carbon dioxide (CO2). However, CO2 fertilization responses in field conditions have seldom included methane (CH4) and nitrous oxide (N2O), particularly in natural and mature forests, which are expected to have an important role in climate change mitigation. Herein, we aimed to capture the effect of elevated CO2 (eCO2; ambient vs. +150 ppm) on long‐term temporal dynamics of CH4 and N2O fluxes, followed by identification of climo‐edaphic factors explaining feedback responses. To achieve this, continuous monitoring of greenhouse gas (GHG) fluxes using a manual chamber technique, over a 3‐year period was implemented in a mature dryland Eucalypt forest FACE (EucFACE) facility in Australia. The relationship between CH4 and N2O fluxes with rainfall indices and soil properties was also explored since they directly impact the microbial communities in the soil responsible for CH4 and N2O net emissions. Our results showed that in 3 years of eCO2 treatment, the amount and frequency of rainfall predicted GHG emissions in this native forest. We also found a significant reduction in CH4 sink (15%–25%) for some of the years as well as an overall treatment effect index reduction in N2O emissions under eCO2. Higher frequency of rain events with lower intensity led to highest CH4 sink followed by lowest N2O emissions due to fewer wet–dry cycles. Of all the environmental variables included, soil moisture, rainfall and pH were the main predictors of net CH4 and N2O emissions. Methane flux was also strongly influenced by soil texture. Our findings highlight the need to account for reduced forest CH4 sink under eCO2 in dryland ecosystems, which has implications for GHG budget predictions under future climate conditions. A free Plain Language Summary can be found within the Supporting Information of this article.

Responses of Soil Microbial Survival Strategies and Functional Changes to Wet–Dry Cycle Events

“…The intensity of the transition from wet to dry soil generally leads to changes in pH [46]. However, in our three sample plots, although pH differed, there was no significant difference.…”

“…mays-G. max rotation, showing significant differences between the sample plots. Wet soils showed increased soil carbon mineralization and TC content, which explains the higher TC content of the MPS sample plot than that of the RPS sample plot in this study [46]. The higher TOC content in the SPS sample plot was probably due to the "legacy effect" of the accumulation of plant litter and root exudates after two years of O. sativa cultivation [48].…”

Soil greenhouse gas (N2O, CO2 and CH4) fluxes from cropland agroforestry and monoculture systems

“…This is in line with the previous studies that have demonstrated soil moisture was the dominant controlling factor in soil CH4 fluxes from forests (Veldkamp et al, 2013;Rehschuh et al, 2019;Tchiofo Lontsi et al, 2020) and cropping systems (Koga et al, 2004;. The regulation of soil moisture on soil CH4 uptake rates can be explained by influencing gas diffusivity (i.e., oxygen and CH4) from the atmosphere into the soil, and further affect CH4 oxidation and methanogenic activity (Keller and Reiners, 1994;Veldkamp et al, 2013;Martins et al, 2021). Even though we detected significant correlations between soil temperature and CH4 fluxes in the loam Phaeozem and sandy Arenosol soils, the variation in CH4 fluxes might not be explained by soil temperature but instead due to its indirect effect on soil moisture, which was reflected by the negative relationships between soil temperature and WFPS, and the negative relationships between soil CH4 and CO2 fluxes at our sites (Table S3.1).…”

Ignoring the Effects of Photovoltaic Array Deployment on Greenhouse Gas Emissions May Lead to Overestimation of the Contribution of Photovoltaic Power Generation to Greenhouse Gas Reduction

“…In addition, we used structural equation models (SEMs; Grace, 2006) to examine direct and indirect mechanisms that regulate GHG fluxes using the lavaan SEM package in R. All SEM analyses were conducted independently for each GHG flux, and the conceptual model of hypothetical relationships based on theoretical knowledge was developed. Each model’s overall goodness-of-fit was tested using the chi-square test ( c 2 ; the good fit of the model when 0 ≤ c 2 ≤ 2 and 0 ≤ p ≤ 1), the root mean square error of approximation (rmsea; the good fit of the model when 0 ≤ rmsea ≤ 0.05), the standardized root mean square residual (srmr; the good fit of the model when 0 ≤ srmr ≤ 0.05), and the comparative fit index (cfi; the good fit of the model when 0.97 ≤ cfi ≤ 1). , …”

“…Each model's overall goodness-of-fit was tested using the chisquare test (c 2 ; the good fit of the model when 0 ≤ c 2 ≤ 2 and 0 ≤ p ≤ 1), the root mean square error of approximation (rmsea; the good fit of the model when 0 ≤ rmsea ≤ 0.05), the standardized root mean square residual (srmr; the good fit of the model when 0 ≤ srmr ≤ 0.05), and the comparative fit index (cfi; the good fit of the model when 0.97 ≤ cfi ≤ 1). 58,59 ■ RESULTS AND DISCUSSION Effect of the Solar Park on the Air Microclimates, Soil Properties, and Vegetation Characteristics. This study revealed that PV arrays changed the air microclimates (Figure 2), soil properties (Figure 3), and vegetation characteristics (Table 1) during the operation period of the solar park hosting the grassland vegetation, which supports our first hypothesis.…”