Responses of a tundra system to warming using SCAMPS: a stoichiometrically coupled, acclimating microbe–plant–soil model

Abstract

Abstract. Soils, plants, and microbial communities respond to global change perturbations through coupled, nonlinear interactions. Dynamic ecological responses complicate projecting how global change disturbances will influence ecosystem processes, such as carbon (C) storage. We developed an ecosystem-scale model (Stoichiometrically Coupled, Acclimating Microbe-Plant-Soil model, SCAMPS) that simulates the dynamic feedbacks between aboveground and belowground communities that affect their shared soil environment. The belowground component of the model includes three classes of soil organic matter (SOM), three microbially synthesized extracellular enzyme classes specific to these SOM pools, and a microbial biomass pool with a variable C-to-N ratio (C:N). The plant biomass, which contributes to the SOM pools, flexibly allocates growth toward wood, root, and leaf biomass, based on nitrogen (N) uptake and shoot-to-root ratio. Unlike traditional ecosystem models, the microbial community can acclimate to changing soil resources by shifting its C:N between a lower C:N, faster turnover (bacteria-like) community, and a higher C:N, slower turnover (fungal-like) community. This stoichiometric flexibility allows for the microbial C and N use efficiency to vary, feeding back into system decomposition and productivity dynamics. These feedbacks regulate changes in extracellular enzyme synthesis, soil pool turnover rates, plant growth, and ecosystem C storage. We used SCAMPS to test the interactive effects of winter, summer, and year-round soil warming, in combination with microbial acclimation ability, on decomposition dynamics and plant growth in a tundra system.Over 50-year simulations, both the seasonality of warming and the ability of the microbial community to acclimate had strong effects on ecosystem C dynamics. Across all scenarios, warming increased plant biomass (and therefore litter inputs to the SOM), while the ability of the microbial community to acclimate increased soil C loss. Winter warming drove the largest ecosystem C losses when the microbial community could acclimate, and the largest ecosystem C gains when it could not acclimate. Similar to empirical studies of tundra warming, modeled summer warming had relatively negligible effects on soil C loss, regardless of acclimation ability. In contrast, winter and year-round warming drove marked soil C loss when decomposers could acclimate, despite also increasing plant biomass. These results suggest that incorporating dynamically interacting microbial and plant communities into ecosystem models might increase the ability to link ongoing global change field observations with macroscale projections of ecosystem biogeochemical cycling in systems under change.

Increasing soil carbon storage: mechanisms, effects of agricultural practices and proxies. A review

“…(Manzoni et al 2012;Mooshammer et al 2014;Geyer et al 2016;Lashermes et al 2016). Moreover, it is likely to change depending on the climatic and atmospheric conditions (Allison et al 2010;Schimel 2013;Sistla et al 2014).…”

Building Predictive Models for Diverse Microbial Communities in Soil

“…They have begun to include aspects of microbial functional diversity [Allison, 2005;Moorhead and Sinsabaugh, 2006] and explore responses to changing environmental conditions [Allison et al, 2010;Davidson et al, 2012;Sistla et al, 2014]. Newer models consider important microbial interactions with soil mineralogy Wieder et al, 2014].…”

“…Other trait-based models use a continuous approach rather than specifying guilds a priori. Sistla et al [2014] allowed the C:N ratio of the microbial biomass to vary based on carbon substrate and soil nitrogen availability. Lower C:N ratios corresponded to bacterially-dominated communities whereas higher ratios corresponded to fungal-dominated communities.…”

“…Stoichiometry may be specified as a fixed parameter [Kaiser et al, 2014] or vary within maximum and minimum limits [Allison, 2012;Sistla et al, 2014]. When metabolic processes result in biomass stoichiometry that deviates from the fixed value or exceeds the limits, the elements in excess are lost.…”

Comparing models of microbial–substrate interactions and their response to warming

“…The separation of microbial respiration into growth and maintenance terms is motivated by similar formulations in other microbial (Beefting et al, 1990;Van Bodegom, 2007), vegetation growth (Foley et al, 1996;Cannell and Thornley, 2000;Arora, 2002;Thornley, 2011;Pretzsch et al, 2014), and ecosystem-scale (Sistla et al, 2014) models. Growth respiration is applied after requirements for maintenance respirations are met and is proportional to newly built microbial tissues.…”