Effects of elevated temperature and abnormal precipitation on soil carbon and nitrogen dynamics in a Pinus densiflora forest

Abstract

Forests have the largest terrestrial nutrient pools. The loss of soil carbon and nitrogen in forests under ongoing climate warming is subject to severe environmental degradation. To mitigate the negative effects of global warming on soil carbon and nitrogen in forest, it is important to obtain a better understanding of how elevated temperature and altered precipitation variability impact soil nutrient dynamics. To explore such interactions, we coupled an eco-hydrological model (Multi-Layer Canopy model, MLCan) with a biogeochemical model and applied the combined model to Pinus densiflora forest in Gwangneung Experimental Forest, South Korea, from 2004 to 2020. Our results showed that there was a time lag of 4 years to trigger soil organic carbon losses under the elevated temperature of +1.11°C during 2014–2020 compared to 2010–2013. A temperature rise over a prolonged period increased microbial biomass and activity, stimulating soil organic carbon decomposition. The combination of soil nitrate accumulation and exceptional but expected delay in heavy precipitation seasons of 2 months led to nitrate leaching four times higher than the average at 1 m depth in 2010. Reduced evapotranspiration and heavy precipitation during early fall caused intense subsurface water flux, resulting in a great increase in the risk of nitrate leaching. Our results highlight that the impacts of global warming on soil carbon decompositions has a time lag of 4 years and changes in precipitation characteristics will lead to excessive nitrate loss in P. densiflora forests under climate change.

Forest restoration decouple soil C:N:P stoichiometry but has little effects on microbial biodiversity globally

“…It has been shown that the warmer ecosystems tend to stimulate the decomposition rates and enzyme activity, which could further decrease soil C and N content. Meanwhile, the higher MAP may greatly enhance soil saturation and water logging, which may further cause nutrient losses through leaching (Chapin et al, 2011; Woo & Seo, 2022). In addition, our study found that MAT and MAP were positively correlated with bacterial Shannon, but negatively correlated with fungal Shannon during forest restoration (Figure 7).…”

Characterizing the Atmospheric Mn Cycle and Its Impact on Terrestrial Biogeochemistry

“…Because SOM decomposition has long been understood to be controlled by a combination of several different factors, Mn deposition cannot be interpreted separately from other commonly outlined predictors such as precipitation (moisture), temperature, and N deposition (Berg & Matzner, 1997; Frey et al., 2014; Hartley et al., 2021; Sierra et al., 2015; Woo & Seo, 2022; Zak et al., 2017; L. Zhang et al., 2019; F. Zhao et al., 2021). To include these potential constraints, simple and multilinear regression analyses were carried out with the addition of the three other factors: precipitation, temperature (long‐term mean data from Terrestrial Air Temperature and Precipitation: 1900–2014 Gridded Monthly Time Series data provided by the NOAA PSL, Boulder, Colorado, USA, from their website at https://psl.noaa.gov), and N deposition to test the significance of Mn deposition on topsoil C density.…”

“…Because SOM decomposition has long been understood to be controlled by a combination of several different factors, Mn deposition cannot be interpreted separately from other commonly outlined predictors such as precipitation (moisture), temperature, and N deposition (Berg & Matzner, 1997;Frey et al, 2014;Hartley et al, 2021;Sierra et al, 2015;Woo & Seo, 2022;Zak et al, 2017;L. Zhang et al, 2019;F.…”

Contactless estimation of soil moisture using leaky Rayleigh waves and a fully convolutional network

“…Soil moisture is a critical mediator that regulates the movement and distribution of water and heat energy. It is a widely used variable in multiple disciplines to assess and analyze various phenomena and processes, which include biogeochemical processes (Cain et al., 2022; Wang et al., 2020; Woo & Do, 2021; Woo & Seo, 2022), reservoir management (Devine & O'Geen, 2019; Heinzel et al., 2022), drought and flood (Eswar et al., 2018; del Pilar Jimenez‐Donaire et al., 2020; Lakshmi et al., 2004), irrigation scheduling (Nandan et al., 2021; Woo et al., 2022), and crop yield prediction (Champagne et al., 2019; Woo et al., 2021). Therefore, accurate measurement of soil moisture plays a vital role in Earth system science, ranging from estimating the molecular signatures of microbial decomposition to studying ecosystem responses to global warming (Songara & Patel, 2022).…”

“…It is a widely used variable in multiple disciplines to assess and analyze various phenomena and processes, which include biogeo-Abbreviations: CNN, convolutional neural network; CRNS, cosmic-ray neutron sensing; DNN, deep neural network; GPR, ground-penetrating radar; MEMS, micro-electromechanical systems; ML, machine learning; RMSE, root mean squared error; TOF, time of flight. chemical processes (Cain et al, 2022;Wang et al, 2020;Woo & Do, 2021;Woo & Seo, 2022), reservoir management (Devine & O'Geen, 2019;Heinzel et al, 2022), drought and flood (Eswar et al, 2018;del Pilar Jimenez-Donaire et al, 2020;Lakshmi et al, 2004), irrigation scheduling (Nandan et al, 2021;, and crop yield prediction (Champagne et al, 2019;. Therefore, accurate measurement of soil moisture plays a vital role in Earth system science, ranging from estimating the molecular signatures of microbial decomposition to studying ecosystem responses to global warming (Songara & Patel, 2022).…”