INTRODUCTION
Microorganisms are key drivers of global biogeochemical cycles (Falkowski et al.2008). In terrestrial ecosystems, soil microbes decompose organic matter, returning carbon to the atmosphere as carbon dioxide (CO2) (Waksman & Starkey 1931).In vitro and in situ experiments suggest that changes in microbial decomposition with warming are an important feedback to climate (Davidson & Janssens 2006; Singh et al. 2010; Frey et al. 2013). Soil microbial populations may respond to increasing temperature through physiological mechanisms such as individual metabolic adjustment (Bradford et al. 2008; Tucker et al. 2013) and ecological mechanisms such as shifts in population abundance or community composition (Wei et al.2014; Creamer et al. 2015). Given the short generation time, large population sizes and genetic variation of many microbial organisms, evolutionary adaptive responses of microbial populations to warming are also likely (Padfield et al. 2016; Schaum et al. 2017). Indeed, rapid evolutionary adaptation of microbial populations to environmental change, especially temperature gradients (Bennett & Lenski 2007), is well documented in laboratory systems. However, the functional, ecosystem-level consequences of microbial adaptive evolution remain poorly understood, and how microbial evolutionary adaptation to warming may contribute to carbon-climate feedbacks is unknown (Monroe et al.2018).
Key to microbial decomposition of soil organic matter is the production by microbes of extracellular enzymes (exoenzymes), that diffuse locally in the soil and bind to soil organic matter compounds (Ratledge 1994). Because the fitness cost of exoenzyme production (Harder & Dijkhuizen 1983) (reduced allocation to growth, Fig. 1a) is paid by individual microbes whereas fitness benefits (larger resource pool) are received by microbial collectives (Velicer 2003), we expect genetic variation in exoenzyme production (Trivedi et al.2016) to be under strong selection (Rainey & Rainey 2003; Velicer 2003). Our objective is to evaluate how exoenzyme production responds to selection under environmental warming, and how the evolutionary response of exoenzyme production impacts decomposition and soil organic carbon stock (SOC). Our focus is on soil bacteria, which typically have a large potential for rapid evolutionary adaptation to environmental change (Koskella & Vos 2015).
To this end, we develop and analyze a novel ecosystem-evolutionary model, starting with an ecosystem model of microbe-enzyme decomposition first proposed by Allison et al. (2010) (Fig. 1a), and modified to take microbial evolutionary adaptation into account. Amongst ecosystem models of soil microbial decomposition (reviewed in Abs and Ferriere (2020)), Allison et al. ’s model is the simplest of theCDMZ type, where C denotes the size of a single pool of SOC, D , the size of the dissolved organic carbon (DOC) pool,M , the microbial biomass, and Z , the size of a single pool of exoenzymes. The focal microbial trait is the fraction of assimilated carbon allocated to exoenzyme production (Sinsabaugh & Moorhead 1994; Allison 2012; Steinweg et al. 2013), or ‘exoenzyme allocation fraction’, denoted by φ . The balance of assimilated carbon, 1 − φ , is allocated to microbial growth. The effect of temperature on soil microbial activity is mediated by enzymes kinetics, with exoenzymes driving the decomposition rate, and intra-cellular enzymes involved in resource uptake and microbial biomass synthesis. In general, as temperature increases, Allison et al .’s (2010) ecosystem model predicts a decline in equilibrium SOC due to faster enzyme kinetics, hence a positive feedback to atmospheric CO2 and warming.
To investigate how evolutionary adaptation to warming may affect decomposition, we account for the existence of heritable variation (Alster et al.2016; Trivedi et al. 2016) in the exoenzyme allocation fraction,φ . We then use evolutionary game theory and adaptive dynamics modeling (Geritzet al. 1998; Brännström et al. 2013) to derive the selection gradient of trait φ and compute the microbial evolutionarily stable strategy (ESS), φ *, at any given temperature. Changing temperature alters the selection gradient, henceφ *. Knowing how the evolutionarily stable trait value φ * changes as temperature increases, we can evaluate how the ecosystem equilibrium changes from both the direct effect of warming on enzyme kinetics, and the indirect effect mediated by microbial evolutionary adaptation to warming (Fig. 1b, c). By comparing the response of the SOC stock that our ecosystem evolutionary model predicts (EVOL response) to the response predicted by the ecosystem CDMZ model in the absence of evolution (ECOS response, assuming φ to be a fixed parameter), we can evaluate the contribution of microbial evolutionary adaptation (EVO effect) to the direction and magnitude of the SOC stock response to climate warming (Fig. 1b, c).
To illustrate how EVO effects may vary in real ecosystems, we use available data (Germanet al. 2012) on the decomposition kinetic parameters in five sites of increasing latitude and decreasing mean annual temperature. We evaluate ECOS and EVOL responses for each site, and compare them within and among sites. Our analysis identifies parameters and temperature dependencies that critically influence the strength of evolutionary effects. We discuss how these evolutionary effects relate to previous consideration of ‘adaptation’ in microbial responses to climate warming (Allisonet al. 2010; Wieder et al. 2013; Allison 2014). We also discuss how, in natural systems, evolutionary adaptation may interact with ecological responses such as species sorting and community shifts (O’Brienet al. 2013; Boon et al. 2014; Strauss 2014). We highlight how our results could inform future empirical work, and conclude with implications for Earth system modeling and forecasting.