Forecasting ecosystem outcomes of global change can be improved by integrating evolutionary biology and ecosystem science

Abstract

Aspects of global change including rising seas, warming, increased atmospheric greenhouse gas concentrations, and shifting precipitation regimes can elicit rapid evolution of foundation species (i.e., species that play a vital role in structuring and modifying ecosystems), potentially altering important ecosystem processes including carbon (C) cycling, C storage, nutrient uptake, and nutrient removal. This supposition derives from evidence that heritable traits can influence a range of ecosystem attributes (Whitlock, 2014) and evidence that aspects of global change can act as selective agents on heritable traits (Ravenscroft et al., 2015), giving rise to organismal evolution on an ecological timescale. Yet rapid evolution has largely been neglected in studies of ecosystem responses to global change. Recent work illustrating the importance of addressing this deficit (Vahsen et al., 2023) points to the merits of integrative eco-evolutionary approaches to further understand whether and how evolutionary responses to global change alter ecosystem properties and processes.

Common garden experiments have demonstrated that many species exhibit heritable variation in traits that underlie organismal capacity (e.g., temperature tolerance, salinity tolerance, etc.) to respond to pressures like warming (Mozdzer et al., 2016), elevated carbon dioxide (CO₂) (Nakamura et al., 2011), nitrogen enrichment (Kettenring et al., 2011), and interactions thereof (i.e., co-occurring pressures), indicating the potential for selection-driven evolution (i.e., Darwinian evolution). Responses to selection are expected to be contingent on strength of the pressure(s), concurrent biological factors like competition, and genetic factors like trait covariance (Moran and Kubiske, 2013). An increasing number of studies, some involving novel modes of investigation, provide evidence of rapid evolution in response to global change pressures (Kasada and Yoshida, 2020). For example, a century-long record of evolution reconstructed by “resurrecting” soil-stored seeds of the sedge Schoenoplectus americanus found that shifts in functional traits tightly linked to marsh accretion and C cycling (Rasse et al., 2005) have paralleled changes in precipitation and estuarine salinity in Chesapeake Bay, USA over time (Blum et al., 2021).

An ecosystem attribute or process can be altered by organismal evolution if differences in the expression of a heritable phenotypic trait result in different functional outcomes (Whitham et al., 2003; Whitlock, 2014). In coastal marshes and some riparian ecosystems, heritable traits in smooth cordgrass (Spartina alterniflora) and cottonwoods (Populus spp.) can influence the accumulation of soil organic matter (Schweitzer et al., 2004) and microbial community composition (Lumibao et al., 2020). Heritable traits in plants also can influence other aspects of C cycling including C gain (Souza et al., 2011), gross and net primary productivity (Crutsinger et al., 2009), net ecosystem CO₂ exchange (Breza et al., 2012), and decomposition (Hines et al., 2014), highlighting that changes in heritable trait variation can shift C cycling and storage. This was well illustrated in Vahsen et al. (2023), which relied on a “resurrection” approach that combined a common garden experiment with predictive ecosystem modeling to examine how trait evolution can alter C accumulation and accretion in coastal marshes. Thus far, however, efforts have fallen short of answering the question: “Can global change alter ecosystem processes by eliciting organismal evolution?”

Determining whether evolutionary responses to global change elicit substantive ecosystem outcomes requires integrative approaches that reveal mechanistic and causal linkages between global change, organismal evolution, and ecosystem attributes of interest. Undertaking coordinated studies can ensure (1) that observable effects are attributable to global change; (2) that global change is eliciting genetically-based responses; and (3) that genetically-based responses manifest substantive ecosystem change (Figure 1).

Determining whether ecosystem structure and function hinge on eco-evolutionary dynamics requires disentangling and determining the influence on key ecosystem processes of (1) heritable phenotypic responses including heritable plasticity (Vahsen et al., 2023); (2) nonheritable phenotypic plasticity; and (3) environmental forcing (i.e., global change pressures). Expanding on the Hairston et al. (2005) approach for partitioning rapid evolution from other factors, Ellner et al. (2011) demonstrated that retrospective analyses of empirical studies can illustrate whether rapid evolution is a dominant factor driving demographic, community, and ecosystem change. Although there is inherent difficulty working with nonmodel organisms (i.e., species with a long life span, long time to reproduction, uncharacterized genome), combining classic quantitative genetics approaches with genomics-based approaches is another powerful method for determining whether and what traits (inclusive of plasticity) might be responding to selection (Cocciardi et al., 2024). This could be accomplished by conducting a genome-wide association study to characterize the underlying genomic architecture (i.e., single locus or multilocus) of a trait that is shown to be highly heritable through a sibling or half-sibling common garden experiment alongside a study characterizing genomic variation across time in a long-term global change experiment. Designing investigations to concurrently examine community and ecosystem outcomes of heritable phenotypic variation of foundation species, focusing on ecosystem processes (e.g., C cycling), can likewise be a powerful approach for determining whether and how responses to selection manifest consequential ecosystem change.

Considering that population-level changes can be observable over relatively short time intervals (i.e., within a few years), future experiments should be designed to investigate whether and how individual responses might lead to population-level changes. Likewise, coordinated measures of ecosystem conditions and functions over time can reveal outcomes of individual and population-level change. Deliberately establishing long-term experiments around the principles of coordinated measurement can shed light on how individual change can give rise to higher order differences over time. Additionally, retrospective examination of multidecadal data sets from long-term ecological research networks (LTERNs) can aid in answering questions on ecosystem outcomes of heritable trait variation (Cocciardi et al., 2024). These long-term data sets can also be leveraged to inform future long-term experimentation to further explore how other processes, like gene flow and genetic drift, might mediate the potential importance of selection (Figure 1). We acknowledge our model is an oversimplification, and leaves out epigenetic change, which is an important mechanism of change, but is outside of the scope of this Mendelian approach.

Perhaps the largest challenge (yet arguably most important) to be tackled is the integration of evolutionary processes into models of ecosystem processes and Earth system models. Global C-cycle models, for example, are currently based on data from natural communities and are largely derived from inferences about plastic response of populations from exposure experiments, potentially ignoring rapid organismal evolution. Further efforts should be made to incorporate organismal evolution into C-cycle models to better predict responses to a rapidly changing planet. The potential influence of plant evolution on the global C budget is illustrated by recent work showing that even minor shifts in C-relevant plant traits, such as a 1% increase in rooting depth over only 4% of arable land, could offset all annual CO₂ production from fossil fuel emissions (Kell, 2011). Efforts to develop, demonstrate, and validate modeling frameworks that join together an applied ecosystem model and a model of Darwinian trait evolution (Vahsen, 2023) could provide novel scaffolds for investigating how plasticity and evolution shape C-cycling dynamics. Improved understanding of C cycling might also inform efforts to develop C markets, including financial tools and policies intended to foster C sequestration through strategies such as the creation and restoration of wetlands given their disproportionally large effect on C sequestration (Mcleod et al., 2011). Furthermore, future research should aim to identify if, and how, shifts in heritable trait variation can act as drivers of evolutionary imperilment or evolutionary rescue. Vahsen et al. (2023) demonstrated that differences in heritable traits like belowground biomass allocation drastically shift model predictions of marsh accretion and by extension, marsh persistence under different near-future scenarios of sea level rise. Furthermore, selective breeding, or screening of natural populations for unique traits, could also be a strategy for accelerating restoration projects in a rapidly changing environment. Future efforts might also consider investigating complex eco-evolutionary feedback that propagate across successive levels of organization (i.e., populations, assemblages, communities, etc.), or investigate epigenetic processes, to gain a more comprehensive understanding of how global change can alter ecosystem processes.

T.J.M. was responsible for conceptualization, methodology, investigation, resources, writing (original draft), writing (review and editing), supervision, project administration, and funding acquisition. B.R.D. was responsible for investigation, writing (original draft), writing (review and editing), visualization, and project administration. M.J.B. was responsible for conceptualization, methodology, investigation, resources, writing (original draft), writing (review and editing), supervision, project administration, and funding acquisition. M.K.M. was responsible for conceptualization, methodology, investigation, resources, writing (original draft), writing (review and editing), supervision, project administration, funding acquisition.