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1. Environmental connectivity influences the origination of adaptive processes

   Shea, John; Leither, Sydney; Foreback, Max; Dolson, Emily; Lalejini, Alexander (July 2024, MIT Press)

   Faíña, Andrés; Risi, Sebastian; Medvet, Eric; Stoy, Kasper; Chan, Bert; Miras, Karine; Zahadat, Payam; Grbic, Djordje; Nadizar, Giorgia (Ed.)

   Spatial structure is hypothesized to be an important factor in the origin of life, wherein encapsulated chemical reaction networks came together to form systems capable adaptive complexification via Darwinian evolution. In this work, we use a computational model to investigate how different patterns of environmental connectivity influence the emergence of adaptive processes in simulated systems of self-amplifying networks of interacting chemical reactions (autocatalytic cycles, “ACs”). Specifically, we measured the propensity for adaptive dynamics to emerge in communities with nine distinct patterns of inter-AC interactions, across ten different patterns of environmental connectivity. We found that the pattern of connectivity can dramatically influence the emergence of adaptive processes; however, the effect of any particular spatial pattern varied across systems of ACs. Relative to a well-mixed (fully connected) environment, each spatial structure that we investigated amplified adaptive processes for at least one system of ACs and suppressed adaptive processes for at least one other system. Our findings suggest that there may be no single environment that universally promotes the emergence of adaptive processes in a system of interacting components (e.g., ACs). Instead, the ideal environment for amplifying (or suppressing) adaptive dynamics will depend on the particularities of the system. 

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2. When will a changing climate outpace adaptive evolution?

   https://doi.org/10.1002/wcc.852  

   Martin, Ryan A.; da Silva, Carmen R. B.; Moore, Michael P.; Diamond, Sarah E. (June 2023, WIREs Climate Change)

   Abstract Decades of research have illuminated the underlying ingredients that determine the scope of evolutionary responses to climate change. The field of evolutionary biology therefore stands ready to take what it has learned about influences upon the rate of adaptive evolution—such as population demography, generation time, and standing genetic variation—and apply it to assess if and how populations can evolve fast enough to “keep pace” with climate change. Here, our review highlights what the field of evolutionary biology can contribute and what it still needs to learn to provide more mechanistic predictions of the winners and losers of climate change. We begin by developing broad predictions for contemporary evolution to climate change based on theory. We then discuss methods for assessing climate‐driven contemporary evolution, including quantitative genetic studies, experimental evolution, and space‐for‐time substitutions. After providing this mechanism‐focused overview of both the evidence for evolutionary responses to climate change and more specifically, evolving to keep pace with climate change, we next consider the factors that limit actual evolutionary responses. In this context, we consider the dual role of phenotypic plasticity in facilitating but also impeding evolutionary change. Finally, we detail how a deeper consideration of evolutionary constraints can improve forecasts of responses to climate change and therefore also inform conservation and management decisions. This article is categorized under:Climate, Ecology, and Conservation > Observed Ecological ChangesClimate, Ecology, and Conservation > Extinction RiskAssessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change 

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3. Adaptive Phenotypic Plasticity Stabilizes Evolution in Fluctuating Environments

   https://doi.org/10.3389/fevo.2021.715381  

   Lalejini, Alexander; Ferguson, Austin J.; Grant, Nkrumah A.; Ofria, Charles (August 2021, Frontiers in Ecology and Evolution)

   Fluctuating environmental conditions are ubiquitous in natural systems, and populations have evolved various strategies to cope with such fluctuations. The particular mechanisms that evolve profoundly influence subsequent evolutionary dynamics. One such mechanism is phenotypic plasticity, which is the ability of a single genotype to produce alternate phenotypes in an environmentally dependent context. Here, we use digital organisms (self-replicating computer programs) to investigate how adaptive phenotypic plasticity alters evolutionary dynamics and influences evolutionary outcomes in cyclically changing environments. Specifically, we examined the evolutionary histories of both plastic populations and non-plastic populations to ask: (1) Does adaptive plasticity promote or constrain evolutionary change? (2) Are plastic populations better able to evolve and then maintain novel traits? And (3), how does adaptive plasticity affect the potential for maladaptive alleles to accumulate in evolving genomes? We find that populations with adaptive phenotypic plasticity undergo less evolutionary change than non-plastic populations, which must rely on genetic variation from de novo mutations to continuously readapt to environmental fluctuations. Indeed, the non-plastic populations undergo more frequent selective sweeps and accumulate many more genetic changes. We find that the repeated selective sweeps in non-plastic populations drive the loss of beneficial traits and accumulation of maladaptive alleles, whereas phenotypic plasticity can stabilize populations against environmental fluctuations. This stabilization allows plastic populations to more easily retain novel adaptive traits than their non-plastic counterparts. In general, the evolution of adaptive phenotypic plasticity shifted evolutionary dynamics to be more similar to that of populations evolving in a static environment than to non-plastic populations evolving in an identical fluctuating environment. All natural environments subject populations to some form of change; our findings suggest that the stabilizing effect of phenotypic plasticity plays an important role in subsequent adaptive evolution. 

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4. Approaches to macroevolution: 1. General concepts and origin of variation.

   Jablonski, D. (July 2017, Evolutionary biology)

   Abstract Approaches to macroevolution require integration of its two fundamental components, i.e. the origin and the sorting of variation, in a hierarchical framework. Macroevolution occurs in multiple currencies that are only loosely correlated, notably taxonomic diversity, morphological disparity, and functional variety. The origin of variation within this conceptual framework is increasingly understood in developmental terms, with the semi-hierarchical structure of gene regulatory networks (GRNs, used here in a broad sense incorporating not just the genetic circuitry per se but the factors controlling the timing and location of gene expression and repression), the non-linear relation between magnitude of genetic change and the phenotypic results, the evolutionary potential of co-opting existing GRNs, and developmental responsiveness to nongenetic signals (i.e. epigenetics and plasticity), all requiring modification of standard microevolutionary models, and rendering difficult any simple definition of evolutionary novelty. The developmental factors underlying macroevolution create anisotropic probabilities—i.e., an uneven density distribution—of evolutionary change around any given phenotypic starting point, and the potential for coordinated changes among traits that can accommodate change via epigenetic mechanisms. From this standpoint, “punctuated equilibrium” and “phyletic gradualism” simply represent two cells in a matrix of evolutionary models of phenotypic change, and the origin of trends and evolutionary novelty are not simply functions of ecological opportunity. Over long timescales, contingency becomes especiallyimportant, and can be viewed in terms of macroevolutionary lags (the temporal separation between the origin of a trait or clade and subsequent diversification); such lags can arise by several mechanisms: as geological or phylogenetic artifacts, or when diversifications require synergistic interactions among traits, or between traits and external events. The temporal and spatial patterns of the origins of evolutionary novelties are a challenge to macroevolutionary theory; individual events can be described retrospectively, but a general model relating development, genetics, and ecology is needed. An accompanying paper (Jablonski in Evol Biol 2017) reviews diversity dynamics and the sorting of variation, with some general conclusions. 

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5. Universal rules of life: metabolic rates, biological times and the equal fitness paradigm

   https://doi.org/10.1111/ele.13715  

   Robert_Burger, Joseph; Hou, Chen; A_S_Hall, Charles; Brown, James_H; Chase, ed., Jonathan (April 2021, Ecology Letters)

   Abstract Here we review and extend the equal fitness paradigm (EFP) as an important step in developing and testing a synthetic theory of ecology and evolution based on energy and metabolism. The EFP states that all organisms are equally fit at steady state, because they allocate the same quantity of energy, ~ 22.4 kJ/g/generation to the production of offspring. On the one hand, the EFP may seem tautological, because equal fitness is necessary for the origin and persistence of biodiversity. On the other hand, the EFP reflects universal laws of life: how biological metabolism – the uptake, transformation and allocation of energy – links ecological and evolutionary patterns and processes across levels of organisation from: (1) structure and function of individual organisms, (2) life history and dynamics of populations, and (3) interactions and coevolution of species in ecosystems. The physics and biology of metabolism have facilitated the evolution of millions of species with idiosyncratic anatomy, physiology, behaviour and ecology but also with many shared traits and tradeoffs that reflect the single origin and universal rules of life. 

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