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Abstract Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case‐specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial‐ENzyme Decomposition model, this study aimed to test whether a common set of microbially‐relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two‐year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial‐relevant parameters for large‐scale soil model projections. 

Abstract Ecosystem functional responses such as soil CO₂emissions are constrained by microclimate, available carbon (C) substrates and their effects upon microbial activity. In tropical forests, phosphorus (P) is often considered as a limiting factor for plant growth, but it is still not clear whether P constrains microbial CO₂emissions from soils. In this study, we incubated seven tropical forest soils from Brazil and Puerto Rico with different nutrient addition treatments (no addition, Control; C, nitrogen (N) or P addition only; and combined C, N and P addition (CNP)). Cumulative soil CO₂emissions were fit with a Gompertz model to estimate potential maximum cumulative soil CO₂emission (C_m) and the rate of change of soil C decomposition (k). Quantitative polymerase chain reaction (qPCR) was conducted to quantify microbial biomass as bacteria and fungi. Results showed that P addition alone or in combination with C and N enhancedC_m, whereas N addition usually reducedC_m, and neither N nor P affected microbial biomass. Additions of CNP enhancedk, increased microbial abundances and altered fungal to bacterial ratios towards higher fungal abundance. Additions of CNP, however, tended to reduceC_mfor most soils when compared to C additions alone, suggesting that microbial growth associated with nutrient additions may have occurred at the expense of C decomposition. Overall, this study demonstrates that soil CO₂emission is more limited by P than N in tropical forest soils and those effects were stronger in soils low in P. HighlightsA laboratory incubation study was conducted with nitrogen, phosphorus or carbon addition to tropical forest soils. Soil CO₂emission was fitted with a Gompertz model and soil microbial abundance was quantified using qPCR. Phosphorus addition increased model parametersC_mand soil CO₂emission, particularly in the Puerto Rico soils. Soil CO₂emission was more limited by phosphorus than nitrogen in tropical forest soils.