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.