Abstract

In this study, we investigate the responses of soil organic carbon (C) to nitrogen (N) and phosphorus (P) additions along a soil P stock gradient of five beech forest stands in Germany, using a modelling approach. Two different soil models with coupled C, N, and P cycles are used to simulate fertilization experiments conducted at the study sites. The first model, the stand-alone soil module of QUINCY (QUINCY-soil, Thum et al. 2019), is a conventional soil model that uses first-order kinetics to describe soil organic matter (SOM) turnover and represents microbial biomass only implicitly. The second model, the Jena Soil Model (JSM) (Yu et al. 2020), is a novel microbial soil model, which explicitly simulates microbial dynamics and describes the turnover of SOM as the consequence of several interactive processes, such as microbially mediated depolymerisation of litter and SOM, organo-mineral association, and vertical transport. We applied both site-level models to five study sites and compared the modeled soil profile with observations. In addition, model scenarios were conducted to simulate the fertilization of N and P, and we further evaluate the effect of soil P stock, plant litter quality, and SOM CNP stoichiometry, on the responses of soil (heterotrophic) respiration (Rs) to nutrient addition. We found that the fitness between simulated and observed SOM profiles (defined as normalized root mean square ratios, Knrmsr) were generally better in JSM than in QUINCY-soil (Knrmsr larger by 0.03±0.10 to 0.16±0.06 for various soil measurements at all sites); The general pattern of observed Rs responses to nutrient fertilization, that N addition decreases Rs whereas P addition increases it, can be reproduced by JSM but not by QUINCY-soil. Our results indicated that detailed explicit description of microbial processes and organo-mineral association is required to model plant-soil-microbial interactions, thus to better reproduce SOM profiles and their responses to nutrient additions. It highlights the need to better represent these processes in future model developments.

Highlights

  • Macronutrients such as nitrogen (N) and phosphorus (P) are capable of regulating major functions of higher plants (Engels et al, 2011; Hawkesford et al, 2012), and can affect the future forest carbon (C) balance (Fernández-Martínez et al, 2014; Wieder et al, 2015)

  • The simulated soil profiles of original (CK) and equal-litter (Lit-CK) control treatments for both Jena Soil Model (JSM) and QUINCY-soil model were compared with observed data (Figure 2). Both models were tuned to the VES site, JSM better represented the soil organic C (SOC), soil inorganic P (SIP), soil organic P (SOP), and soil organic matter (SOM) profile C:N ratio, as the Knrmsr values of JSM were greater than QUINCY-soil by 0.12, 0.16, 0.19, and 0.09, respectively (Supplementary Table S1)

  • The simulation results from CK treatment better reproduced topsoil C:P ratio and SIP content compared to the Lit-CK treatment, at the most P-poor site LUE, demonstrating the need to correctly account for litter P concentration in these simulations, and an adequate representation of this process across sites

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Summary

Introduction

Macronutrients such as nitrogen (N) and phosphorus (P) are capable of regulating major functions (e.g., photosynthesis and respiration) of higher plants (Engels et al, 2011; Hawkesford et al, 2012), and can affect the future forest carbon (C) balance (Fernández-Martínez et al, 2014; Wieder et al, 2015). A large number of studies have shown that changes of nutrient inputs (fertilization, deposition changes, nutrient stock gradients, etc.) can affect forest ecosystem C cycling by changing plant nutrient uptake, litter and soil organic matter (SOM) decomposition, and nutrient mineralization (see reviews of Johnson and Turner, 2019, Janssens et al, 2010 and references therein). These processes mostly occur belowground and are driven by interactions between plants, soil, and microorganisms (Capek et al, 2018; Mori et al, 2018). It remains to be tested if the microbial-explicit models can better reproduce interactions between C and nutrient cycling in soils, both along gradients in soil nutrient contents, or under fertilization or increased nutrient deposition

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