Models for Physiological and Genetic Adaptation to Variable Environments

Author(s):  
Brian P. Bradley
2020 ◽  
Vol 117 (11) ◽  
pp. 5943-5948 ◽  
Author(s):  
Nathan G. Walworth ◽  
Emily J. Zakem ◽  
John P. Dunne ◽  
Sinéad Collins ◽  
Naomi M. Levine

Marine microbes form the base of ocean food webs and drive ocean biogeochemical cycling. Yet little is known about the ability of microbial populations to adapt as they are advected through changing conditions. Here, we investigated the interplay between physical and biological timescales using a model of adaptation and an eddy-resolving ocean circulation climate model. Two criteria were identified that relate the timing and nature of adaptation to the ratio of physical to biological timescales. Genetic adaptation was impeded in highly variable regimes by nongenetic modifications but was promoted in more stable environments. An evolutionary trade-off emerged where greater short-term nongenetic transgenerational effects (low-γ strategy) enabled rapid responses to environmental fluctuations but delayed genetic adaptation, while fewer short-term transgenerational effects (high-γ strategy) allowed faster genetic adaptation but inhibited short-term responses. Our results demonstrate that the selective pressures for organisms within a single water mass vary based on differences in generation timescales resulting in different evolutionary strategies being favored. Organisms that experience more variable environments should favor a low-γ strategy. Furthermore, faster cell division rates should be a key factor in genetic adaptation in a changing ocean. Understanding and quantifying the relationship between evolutionary and physical timescales is critical for robust predictions of future microbial dynamics.


2019 ◽  
Author(s):  
Nathan G. Walworth ◽  
Emily J. Zakem ◽  
John P. Dunne ◽  
Sinéad Collins ◽  
Naomi M. Levine

AbstractMarine microbes form the base of ocean food webs and drive ocean biogeochemical cycling. Yet little is known about how microbial populations will evolve due to global change-driven shifts in ocean dynamics. Understanding adaptive timescales is critical where long-term trends (e.g. warming) are coupled to shorter-term advection dynamics that move organisms rapidly between ecoregions. Here we investigated the interplay between physical and biological timescales using a model of adaptation and an eddy-resolving ocean circulation climate model. Two criteria (α and β) were identified that relate physical and biological timescales and determine the timing and nature of adaptation. Genetic adaptation was impeded in highly variable regimes (α<1) but promoted in more stable environments (α>1). An evolutionary trade-off emerged where greater short-term transgenerational effects (low-β-strategy) enabled rapid responses to environmental fluctuations but delayed genetic adaptation, while fewer short-term transgenerational effects (high-β-strategy) allowed faster genetic adaptation but inhibited short-term responses. Our results suggest that organisms with faster growth rates are better positioned to adapt to rapidly changing ocean conditions and that more variable environments will favor a bet-hedging, low-β-strategy. Understanding the relationship between evolutionary and physical timescales is critical for robust predictions of future microbial dynamics.


Author(s):  
Andrew C. Dragunas ◽  
Tara Cornwell ◽  
Roberto Lopez-Rosado ◽  
Keith E. Gordon

2012 ◽  
Vol 42 (5) ◽  
pp. 970-985 ◽  
Author(s):  
Ola Ringdahl ◽  
Thomas Hellström ◽  
Ola Lindroos

In conventional mechanized cut-to-length systems, a harvester fells and cuts trees into logs that are stored on the ground until a forwarder picks them up and carries them to landing sites. A proposed improvement is to place logs directly into the load spaces of transporting machines as they are cut. Such integrated loading could result in cost reductions, shorter lead times from stump to landing, and lower fuel consumption. However, it might also create waiting times for the machines involved, whereas multifunctional machines are likely to be expensive. Thus, it is important to analyze whether or not the advantages of any changes outweigh the disadvantages. The conventional system was compared with four potential systems, including two with autonomous forwarders, using discrete-event simulation with stochastic elements in which harvests of more than 1000 final felling stands (containing in total 1.6 million m3) were simulated 35 times per system. The results indicate that harwarders have substantial potential (less expensive on ≥80% of the volume and fuel consumption decreased by ≥18%) and may become competitive if key innovations are developed. Systems with cooperating machines have considerably less potential, limited to very specific stand conditions. The results conform with expected difficulties in integrating processing and transporting machines’ work in variable environments.


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