Diapause and bet‐hedging strategies in insects: a meta‐analysis of reaction norm shapes

Oikos ◽  
2021 ◽  
Author(s):  
Jens Joschinski ◽  
Dries Bonte
Keyword(s):  
Meta Analysis ◽  
Reaction Norm ◽  
Bet Hedging ◽  
Hedging Strategies

scholarly journals Diapause is not selected as a bet-hedging strategy in insects: a meta-analysis of reaction norm shapes

2019 ◽  
Author(s):  
Jens Joschinski ◽  
Dries Bonte
Keyword(s):  
Climate Change ◽  
Phenotypic Plasticity ◽  
Meta Analysis ◽  
Reaction Norm ◽  
Geographic Range ◽  
Bet Hedging ◽  
Hedging Strategy ◽  
Apparent Lack ◽  
Environmental Predictability ◽  
Hedging Strategies

AbstractMany organisms escape from lethal climatological conditions by entering a resistant resting stage called diapause, which needs to be optimally timed with seasonal change. As climate change exerts selection pressure on phenology, the evolution of mean diapause timing, but also of phenotypic plasticity and bet-hedging strategies is expected. Especially the latter as a strategy to cope with unpredictability is little considered in the context of climate change.Contemporary patterns of phenological strategies across a geographic range may provide information about their evolvability. We thus extracted 458 diapause reaction norms from 60 studies. First, we correlated mean diapause timing with mean winter onset. Then we partitioned the reaction norm variance into a temporal component (phenotypic plasticity) and among-offspring variance (diversified bet-hedging) and correlated this variance composition with predictability of winter onset. Mean diapause timing correlated reasonably well with mean winter onset, except for populations at high latitudes, which apparently failed to track early onsets. Variance among offspring was, however, limited and correlated only weakly with environmental predictability, indicating little scope for bet-hedging. The apparent lack of phenological bet-hedging strategies may pose a risk in a less predictable climate, but we also highlight the need for more data on alternative strategies.

Evaluating agricultural bet-hedging strategies in the Kona Field System: New high-precision230Th/U and14C dates and plant microfossil data from Kealakekua, Hawai‘i Island

2016 ◽  
Vol 52 (1) ◽  
pp. 70-80 ◽  
Author(s):  
MARK D. McCOY ◽  
MARA A. MULROONEY ◽  
MARK HORROCKS ◽  
HAI CHENG ◽  
THEGN N. LADEFOGED
Keyword(s):  
Bet Hedging ◽  
Field System ◽  
Hedging Strategies ◽  
Plant Microfossil

scholarly journals Seasonality and competition select for variable germination behavior in perennials

2022 ◽  
Author(s):  
Hanna ten Brink ◽  
Thomas Ray Haaland ◽  
Oystein Hjorthol Opedal
Keyword(s):  
Simulation Models ◽  
Population Variation ◽  
Priority Effects ◽  
Bet Hedging ◽  
Environmental Predictability ◽  
Hedging Strategies ◽  
Unpredictable Environments ◽  
Evolutionary Simulation ◽  
Negative Frequency Dependent Selection ◽  
Germination Timing

The common occurrence of within-population variation in germination behavior and associated traits such as seed size has long fascinated evolutionary ecologists. In annuals, unpredictable environments are known to select for bet-hedging strategies causing variation in dormancy duration and germination strategies. Variation in germination timing and associated traits is also commonly observed in perennials, and often tracks gradients of environmental predictability. Although bet-hedging is thought to occur less frequently in long-lived organisms, these observations suggest a role of bet-hedging strategies in perennials occupying unpredictable environments. We use complementary numerical and evolutionary simulation models of within- and among-individual variation in germination behavior in seasonal environments to show how bet-hedging interacts with density dependence, life-history traits, and priority effects due to competitive differences among germination strategies. We reveal substantial scope for bet-hedging to produce variation in germination behavior in long-lived plants, when "false starts" to the growing season results in either competitive advantages or increased mortality risk for alternative germination strategies. Additionally, we find that two distinct germination strategies can evolve and coexist through negative frequency-dependent selection. These models extend insights from bet-hedging theory to perennials and explore how competitive communities may be affected by ongoing changes in climate and seasonality patterns.

scholarly journals A continuum of biological adaptations to environmental fluctuation

2019 ◽  
Vol 286 (1912) ◽  
pp. 20191623 ◽  
Author(s):  
Ming Liu ◽  
Dustin R. Rubenstein ◽  
Wei-Chung Liu ◽  
Sheng-Feng Shen
Keyword(s):  
Overlapping Generations ◽  
Bet Hedging ◽  
Environmental Fluctuation ◽  
Infinite Population ◽  
Biological Adaptation ◽  
Hedging Strategies ◽  
Wide Range ◽  
Population Sizes ◽  
Environmental Unpredictability ◽  
Per Capita

Bet-hedging—a strategy that reduces fitness variance at the expense of lower mean fitness among different generations—is thought to evolve as a biological adaptation to environmental unpredictability. Despite widespread use of the bet-hedging concept, most theoretical treatments have largely made unrealistic demographic assumptions, such as non-overlapping generations and fixed or infinite population sizes. Here, we extend the concept to consider overlapping generations by defining bet-hedging as a strategy with lower variance and mean per capita growth rate across different environments. We also define an opposing strategy—the rising-tide—that has higher mean but also higher variance in per capita growth. These alternative strategies lie along a continuum of biological adaptions to environmental fluctuation. Using stochastic Lotka–Volterra models to explore the evolution of the rising-tide versus bet-hedging strategies, we show that both the mean environmental conditions and the temporal scales of their fluctuations, as well as whether population dynamics are discrete or continuous, are crucial in shaping the type of strategy that evolves in fluctuating environments. Our model demonstrates that there are likely to be a wide range of ways that organisms with overlapping generations respond to environmental unpredictability beyond the classic bet-hedging concept.

scholarly journals Ecological niche and bet-hedging strategies for Triodia (R.Br.) seed germination

2017 ◽  
Vol 121 (2) ◽  
pp. 367-375 ◽  
Author(s):  
Wolfgang Lewandrowski ◽  
Todd E Erickson ◽  
Emma L Dalziell ◽  
Jason C Stevens
Keyword(s):  
Seed Germination ◽  
Ecological Niche ◽  
Bet Hedging ◽  
Hedging Strategies

scholarly journals Modes of response to environmental change and the elusive empirical evidence for bet hedging

2011 ◽  
Vol 278 (1712) ◽  
pp. 1601-1609 ◽  
Author(s):  
Andrew M. Simons
Keyword(s):  
Environmental Change ◽  
Empirical Evidence ◽  
Natural Environments ◽  
Bet Hedging ◽  
Fluctuating Selection ◽  
Hedging Strategies ◽  
Evolutionary Response ◽  
Human Decision ◽  
Response To Environmental Change

Uncertainty is a problem not only in human decision-making, but is a prevalent quality of natural environments and thus requires evolutionary response. Unpredictable natural selection is expected to result in the evolution of bet-hedging strategies, which are adaptations to long-term fluctuating selection. Despite a recent surge of interest in bet hedging, its study remains mired in conceptual and practical difficulties, compounded by confusion over what constitutes evidence for its existence. Here, I attempt to resolve misunderstandings about bet hedging and its relationship with other modes of response to environmental change, identify the challenges inherent to its study and assess the state of existing empirical evidence. The variety and distribution of plausible bet-hedging traits found across 16 phyla in over 100 studies suggest their ubiquity. Thus, bet hedging should be considered a specific mode of response to environmental change. However, the distribution of bet-hedging studies across evidence categories—defined according to potential strength—is heavily skewed towards weaker categories, underscoring the need for direct appraisals of the adaptive significance of putative bet-hedging traits in nature.

scholarly journals Stochasticity in the Genotype-Phenotype Map: Implications for the Robustness and Persistence of Bet-Hedging

2016 ◽  
Author(s):  
Daniel Nichol ◽  
Mark Robertson-Tessi ◽  
Peter Jeavons ◽  
Alexander RA Anderson
Keyword(s):  
Treatment Resistance ◽  
Molecular Switch ◽  
Phenotypic Heterogeneity ◽  
Driver Mutations ◽  
Phenotypic Change ◽  
Bet Hedging ◽  
Genetic Characteristics ◽  
Hedging Strategies ◽  
Genes And Environment ◽  
The Impact

For the last few decades modern biology has focused on quantifying, understanding and mapping the genetic characteristics of cells. This genotype-driven perspective has led to significant advances in our understanding and treatment of diseases such as cancer e.g. the discovery of driver mutations and the development of molecularly-targeted therapeutics. However, this perspective has largely ignored the functional outcome of genetic changes: the cellular phenotype. In part, this is simply because phenotypes are neither easy to define or measure as they critically depend on both genotype and context. Heterogeneity at the gene scale has been known for sometime, and there has been significant effort invested in trying to find patterns within it, but much less is understood about how this heterogeneity manifests itself in phenotypic change, i.e. the genotype-phenotype map (GP-map). This mapping is not one-to-one but many-to-many and is fundamentally the junction at which both genes and environment meet to produce phenotypes. Many genotypes produce similar phenotypes, and multiple phenotypes can emerge from a single genotype. To further complicate matters, genetically identical cells in uniform environments still exhibit phenotypic heterogeneity. Therefore a central open question in biology today is how can we connect the abundance of genomic data with cell phenotypic behaviour, this is especially pertinent to the issue of treatment resistance as many therapies act on cellular phenotypes. Our focus here is to tackle the GP-map question through the use of the simplest functional mapping we can define that also captures phenotypic heterogeneity: a molecular switch. Molecular switches are ubiquitous in biology, observed in many organisms and naturally map molecular components to decisions (i.e. phenotypes). Often stochastic in nature, such switches can be the difference between life or death in environments that fluctuate unpredictably, since they will ensure that at least some offspring are adapted to future environments. For convenience we use Chemical Reaction Networks (CRNs) to define the map of gene products to phenotypes, allowing us to investigate the impact of distinct mappings (CRNs) and perturbations to them. We observe that key biological properties naturally emerge, including both robustness and persistence. Robustness may explain why such bet hedging strategies are common in biology, and not readily destroyed through mutation. Whereas persistence may explain the apparent paradox of bet-hedging - why does phenotypic hedging exist in environments beneficial to only one of the phenotypes, when selection necessarily acts against it? The structure of the molecular switch, itself subject to selection, can slow the loss of hedging to ensure a survival mechanism even against environmental catastrophes which are very rare. Critically, these properties when taken together have profound and significant implications for the emergence of treatment resistance, since the timescale of extinction depends heavily on the underlying GP-map.

scholarly journals Systemic aneuploidization events drive phenotype switching in Saccharomyces cerevisiae

2021 ◽  
Author(s):  
Lydia R Heasley ◽  
Juan Lucas Argueso
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Colony Morphology ◽  
Whole Genome Sequence ◽  
Bet Hedging ◽  
Wild Type ◽  
Environmental Pressures ◽  
Hedging Strategies ◽  
Species Evolution ◽  
Phenotype Switching ◽  
New Perspective

How cells leverage their phenotypic potential to adapt and survive in a changing environment is a complex biological problem, with important implications for pathogenesis and species evolution. One particularly fascinating adaptive approach is the bet hedging strategy known as phenotype switching, which introduces phenotypic variation into a population through stochastic processes. Phenotype switching has long been observed in species across the tree of life, yet the mechanistic causes of switching in these organisms have remained difficult to define. Here we describe the causative basis of colony morphology phenotype switching which occurs among cells of the pathogenic isolate of Saccharomyces cerevisiae, YJM311. From clonal populations of YJM311 cells grown in identical conditions, we identified colonies which displayed altered colony architectures, yet could revert to the wild-type morphology after passaging. Whole genome sequence analysis revealed that these variant clones had all acquired whole chromosome copy number alterations (i.e., aneuploidies). Cumulatively, the variant clones we characterized harbored an exceptional spectrum of karyotypic alterations, with individual variants carrying between 1 and 16 aneuploidies. Most variants harbored unique collections of aneuploidies, indicating that numerous distinct karyotypes could manifest in the same morphological variation. Intriguingly, the genomic stability of these newly aneuploid variant clones modulated how often cells reverted back to the wild-type phenotypic state. We found that such revertant switches were also driven by chromosome missegregation events, and in some cases occurred through a return to euploidy. Together, our results demonstrate that colony morphology switching in this yeast strain is driven by stochastic and systemic aneuploidization events. These findings add an important new perspective to our current understanding of phenotype switching and bet hedging strategies, as well as how environmental pressures perpetuate organismal adaption and genome evolution.

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