Can models adequately reflect how long-term nitrogen enrichment alters the forest soil carbon cycle?

Abstract

Abstract. Changes in the nitrogen (N) status of forest ecosystems can directly and indirectly influence their carbon (C) sequestration potential by altering soil organic matter (SOM) decomposition, soil enzyme activity, and plant-soil interactions. However, model representation of linked C-N cycles and SOM decay are not well-validated against experimental data. Here, we use extensive data from the Fernow Experimental Forest long-term, whole-watershed N fertilization study to compare the response to N perturbations of two soil models that represent decomposition dynamics differently (first-order decay versus microbially-explicit reverse Michaelis-Menten kinetics). These two soil models were coupled to a common vegetation model which provided identical input data. Key responses to N additions measured at the study site included a shift in allocation to favor woody biomass over belowground carbon inputs, reductions in soil respiration, accumulation of particulate organic matter (POM), and an increase in soil C:N ratios. The vegetation model did not capture the often-observed shift in allocation with N additions, which resulted in poor predictions of the soil responses. We modified the plant C allocation scheme to favor wood production over fine root production with N additions, which significantly improved the vegetation and soil respiration responses. To elicit an increase in the soil C stocks and C:N ratios with N additions, as observed, we also modified the decay rates of the particulate organic matter (POM) in the soil models. With all of these modifications, only the microbially explicit model captured a positive soil C stock and C:N response in line with observations. Our results highlight the importance of accurately representing plant-soil interactions, such as rhizosphere priming, and their responses to environmental change.

Simulating Global Terrestrial Carbon and Nitrogen Biogeochemical Cycles with Implicit and Explicit Representations of Soil Microbial Activity

“…Notable features of MIMICS include the representation of metabolic and structural litter pools (LIT m and LIT s ), explicit representation of fast and slow growing microbial functional groups (MIC r and MIC K ), and the representation of physicochemically protected, chemically protected, and available soil organic matter pools (SOM p , SOM c , and SOM a ; Figure 1). The basic structure of the model has not been changed from the C-only version of MIMICS with addition of CN biogeochemistry described in Kyker-Snowman et al (2020) and Eastman et al (2023). As in our previous work (Wieder et al, 2018;Wieder et al, 2019) Litterfall inputs (I) in MIMICS and CASA are partitioned into litter pools based on chemical quality, specifically the weighted average lignin:N ratio of all litter inputs determines the fraction of metabolic litter (f MET ) as in Parton et al (1987) and applied by Wieder et al (2014).…”

“…The introduction of global-scale, microbial explicit soil biogeochemical models has opened new lines of research (Ye Huang et al, 2018;Sulman et al, 2014;Wieder et al, 2013;Wieder, Grandy, et al, 2015), but much of the work to date only focuses on the representation of soil C biogeochemistry. Results from ecosystem-scale simulations show the potential for models that explicitly simulate microbial-mineral interactions to advance understanding of coupled carbon-nitrogen (CN) dynamics (Eastman et al, 2023;Kyker-Snowman et al, 2020;Thum et al, 2019;. Now, application of microbial explicit CN soil models is feasible at global scales (Y.…”

Simulating Global Terrestrial Carbon and Nitrogen Biogeochemical Cycles With Implicit and Explicit Representations of Soil Microbial Activity

“…The introduction of global-scale, microbial explicit soil biogeochemical models has opened new lines of research (Huang et al, 2018;Sulman et al, 2014;Wieder et al, 2013;Wieder, Grandy, et al, 2015), but much of the work to date only focuses on the representation of soil C biogeochemistry. Results from ecosystemscale simulations show the potential for models that explicitly simulate microbial-mineral interactions to advance understanding of coupled carbon-nitrogen (CN) dynamics (Eastman et al, 2023;Kyker-Snowman et al, 2020;Thum et al, 2019;G. Wang et al, 2020;.…”

“…The introduction of global‐scale, microbial explicit soil biogeochemical models has opened new lines of research (Huang et al., 2018; Sulman et al., 2014; Wieder et al., 2013; Wieder, Grandy, et al., 2015), but much of the work to date only focuses on the representation of soil C biogeochemistry. Results from ecosystem‐scale simulations show the potential for models that explicitly simulate microbial‐mineral interactions to advance understanding of coupled carbon‐nitrogen (CN) dynamics (Eastman et al., 2023; Kyker‐Snowman et al., 2020; Thum et al., 2019; G. Wang et al., 2020; Y. Zhang et al., 2021). Now, application of microbial explicit CN soil models is feasible at global scales (Y. Huang et al., 2021; Sulman et al., 2019), although to date analyses of global terrestrial C and N dynamics from this class of models are sparse.…”

Ideas and perspectives: Beyond model evaluation – combining experiments and models to advance terrestrial ecosystem science

“…) and EME-model integration, including studies looking at new nutrient models Eastman et al, 2023;Li et al, 2022), the effects of root distribution of water availability response (Kulmatiski et al, 2023), carbon storage in grasslands (Wilcox et al, 2022) and extreme events (Holm et al, 2022).…”