What is biological betting coverage
Bet protection (biology) - Bayer filter
Biological betting protection occurs when organisms show decreased fitness in their typical conditions to improve fitness under stressful conditions. Biological betting was originally proposed to explain observation of a seed bank or reservoir of non-germinated seeds in the ground. For example, an annual plant's fitness for that year is maximized when all of the seeds germinate. However, when a drought occurs that kills germinated plants but not non-germinated seeds, plants with seeds that remain in the seed bank have a fitness advantage. Hence, it can be beneficial for plants to "hedge their bets" in the event of a drought by producing some seeds that germinate instantly and other seeds that lie dormant. Other examples of biological hedge betting are female multiple mating, foraging behavior in bumblebees, nutrient storage in rhizobia, and bacterial persistence in the presence of antibiotics.
There are three categories (strategies) of betting hedging: "conservative" betting hedging, "diversified" betting hedging and "adaptive coin tossing".
Conservative betting protection
In conservative betting, individuals lower their expected fitness in exchange for a lower variance in fitness. The idea of this strategy is that an organism "always plays it safe" by using the same successful, low risk strategy regardless of environmental conditions. An example of this would be an organism that produces clutches with a constant egg size that is not optimal for any environmental conditions, but leads to the lowest overall variance.
Diversified bet protection
In contrast to conservative betting hedging, diversified betting hedging occurs when individuals decrease their expected fitness in a given year while increasing the variance in survival between offspring. This strategy is based on the idea of not putting all your eggs in one basket. Individuals who implement this strategy are actually investing in several different strategies at the same time, resulting in little fluctuations in long-term success. This could be demonstrated by a series of eggs of different sizes, each optimal for a potential offspring environment. While this means that offspring who specialize in a different environment are less likely to survive to adulthood, it also protects against the possibility that no offspring will survive until the next year.
Adaptive coin toss
A person who uses this type of bet hedging will choose the strategy to use based on a prediction of the environment. Organisms that use this form of betting hedging make these predictions and choose strategies every year. For example, from year to year an organism can produce clutches with different egg sizes, which increases the variation in the success of the offspring between clutches. In contrast to conservative and diversified betting hedging strategies, the adaptive coin toss is not about minimizing the fitness fluctuations between the years.
In order to determine whether an allele is preferred for hedging bets, the long-term fitness of each allele must be compared. Especially in highly variable environments where betting hedging is likely to evolve, long-term fitness is best measured using the geometric mean, which is multiplicative rather than an additive mean such as the arithmetic mean. The geometric mean is very sensitive to small values. Even rare cases of zero suitability for a genotype will result in it having an expected geometric mean of zero. This makes it suitable for circumstances where a single genotype may have different fitness levels depending on the environmental conditions.
Betting hedging is a reaction to environmental changes. Adaptations that enable organisms to survive in fluctuating environmental conditions offer an evolutionary advantage. While a betting hedging feature may not be optimal for one environment, it is outweighed by the benefits of being more fit in a variety of environments. Therefore, the protection of alleles in more variable environments is preferred. In order for an allele to spread to hedge betting, it must persist in the typical environment through genetic drift long enough to allow alternative environments to emerge in which the betting hanger has an advantage over genotypes that are adapted to the previous environment. With many subsequent changes in environment, selection can lead to fixation of the allele.
A common example of the description of betting hedging is the comparison of arithmetic and geometric suitability between genotypes of specialists and betting. The following table shows the relative fitness of four phenotypes in "good" and "bad" years and their respective averages when "good" years occur 75% of the time and "bad" years 25% of the time.
|Year type||Good year |
|Bad year |
The specialist for a good year has the highest fitness during a good year, but is very bad during a bad year, while the opposite is true for a specialist for a bad year. The conservative betting maker does equally well in all years, and the diversified betting maker in this example uses the two specialty strategies 50% of the time. In good years they do better than the conservative betting hunter, but worse in a bad year.
In this example, the fitness within the specialist and betting hedging strategies is roughly the same, with the betting hedging companies exhibiting a significantly higher fitness than the specialists. While the specialist has the highest arithmetic mean for a good year, the betting hedging strategies are still preferred due to their higher geometric mean.
It's also important to understand that a strategy’s fitness depends on a variety of factors, such as the ratio of good to bad years and the relative fitness between good and bad years. Small changes in the strategies or in the environment with a large impact are optimal. In the example above, the diversified betting hedger outweighs the conservative betting hedger if he uses the special strategy more often for a good year. Conversely, if the specialist's relative fitness for a good year to a bad year was 0.35, this becomes the optimal strategy.
Betting hedging experiments with prokaryotic model organisms provide some of the simplest views for developing betting hedging. Since betting hedging involves stochastic alternation between phenotypes over generations, prokaryotes can represent this phenomenon quite well, as they can reproduce quickly enough to follow evolution in a single population over a short period of time. This rapid rate of reproduction made it possible to investigate betting hedging in laboratories by means of experimental evolution models. These models were used to infer the evolutionary origins of betting protection.
There are a variety of examples of betting hedging within Prokarya. In one example, the bacterium Sinorhizobium meliloti stores carbon and energy in a compound known as poly-3-hydroxybutyrate (PHB) to withstand carbon-deficient environments. When S. meliloti populations are starved, they show a hedge of bets by forming two non-identical daughter cells during the binary fission. The daughter cells have either low PHB levels or high PHB levels, which are better suited for short- and long-term starvation. It has been reported that the low PHB must compete effectively for resources to survive, while the high PHB cells can survive without food for over a year. In this example, the PHB phenotype is "bet-secured" because the survivability of the offspring depends largely on their environment, in which only one phenotype is likely to survive under certain conditions.
Another example of betting hedging occurs with Mycobacterium tuberculosis. In a given population of these bacteria, persistent cells exist with the ability to halt their growth, thereby preventing them from being affected by dramatic environmental changes. Once the persistent cells grow to form another population of their species that may or may not be antibiotic resistant, they both produce cells with normal cell growth and another population of persistent ones to continue this cycle if necessary. The ability to switch between the persistent and normal phenotype is one form of betting hedging.
The prokaryotic persistence as a method for securing bets is therefore important for the medical field due to the bacterial persistence. Since betting hedging is designed to produce genetically distinct offspring randomly in order to survive the disaster, it is difficult to develop treatments for bacterial infections, as betting hedging can ensure the survival of its species within the host regardless of any consideration on the antibiotic.
Eukaryotic betting hedging models, in contrast to prokaryotic models, are more likely to be used to study more complex evolutionary processes. In the context of eukaryotes, betting hedging is best used to analyze complex environmental factors that affect the selective pressures that underlie the betting hedging principle. However, because eukarya is a broad category, this section has been divided into the kingdoms of Animalia, Plantae, and Fungi.
divided. West Atlantic salmon (Salmo salar) has been thought to have major histocompatibility complex (MHC) dependent mating systems that have been shown to be important in determining disease resistance in offspring. There is evidence that selection for increased MHC diversity has a strong influence on mate choice, with the assumption that individuals are more likely to mate with individuals whose MHC is less similar to their own in order to produce variable offspring. In accordance with the betting hedging model, it was found that the reproductive success of mating Atlantic salmon pairs depends on the environment, with certain MHC constructs only being advantageous under certain environmental conditions. This thus supports the evidence that MHC diversity is critical to the long-term reproductive success of the parents, since the trade-off for an initial decline in short-term reproductive capacity is mediated by the survival of some of their offspring in a variable environment
A second example among vertebrates is the marsupial species Sminthopsis macrour, which uses a torpor strategy to reduce its metabolic rate in order to survive environmental changes. Reproductive hormone cycles have been shown to mediate the timing of freezing and reproduction, and in mice it has been shown to mediate this process completely and without concern for the environment. However, the marsupial species use an adaptive coin tossing mechanism in which neither solidification nor reproduction is affected by the manipulation of hormones, suggesting that this marsupial species is making a more active decision about when to better use torpor - Suitable for the unsafe environment, in which it lives.
It is known that many invertebrate species have different forms of betting coverage. Diaptomus sanguineus, an aquatic crustacean found in many ponds in the northeastern United States, is one of the best-studied examples of betting hedging. This species uses a form of diversified betting coverage called germ banking, where the timing of emergence is very different for offspring of a single clutch. This reduces the potential cost of a catastrophic event during a particularly vulnerable time in the development of the offspring. In Diaptomus sanguineus, germ banking occurs when parents produce dormant eggs before annual environmental shifts, which put them at increased risk for offspring development. In temporary ponds, for example, the Diaptomus sanguineus dormant egg production peaks just before the annual dry season in June, when the pond content decreases. In permanent ponds, dormant egg production increases in March, just before sunfish feeding activity increases annually. This example shows that germ banking can take different forms within a species depending on the environmental risk. The hedging of bets through variable breeding patterns of eggs can also be observed in other crustaceans.
Hedging of invertebrate bets has also been observed in the mating systems of some species of spiders. Female Sierra dome spiders (Linyphia litigiosa) are polyandric and mate with secondary males to make up for uncertainty about the quality of the primary partner. Primary male partners are of higher fitness than secondary male partners because primary partners must overcome intrasexual struggles before mating with a woman, while secondary male partners are selected by female choice. Scientists believe that multiple paternity developed in response to the fertilization of virgins by inferior secondary male partners who were not selected through intrasexual struggles. Women have developed a sperm primacy mechanism to maintain control over offspring paternity and improve offspring fitness. Further examination of the female genitalia has supported this hypothesis. The Sierra Dome spider displays this behavior as a form of genetic betting protection that reduces the risk of producing poor quality offspring and developing STDs. This form of betting protection differs significantly from most other forms of betting protection as it did not arise as a reaction to environmental conditions, but as a result of the species pairing system.
Betting hedging is used for fungi in a similar way to bacteria, but it is more complex for fungi. This phenomenon is beneficial for mushrooms, but in some cases it has harmful effects on humans, showing that betting hedging is of clinical importance. One study suggests that hedging bets through mechanisms similar to hedging bets on mushrooms can even contribute to cancer chemotherapy failure.
One way mushrooms use betting hedge is to display different colony morphologies as they grow on agar plates. This variation allows colonies with different morphologies, including resistances, that allow them to survive, thrive, and multiply in different conditions or environments. As a result, yeast infections can be more difficult to treat when it comes to hedging bets. For example, pathogenic yeast strains such as Candida albicans or Candida glabrata that use this strategy are resistant to treatments. These fungi are known to cause an infection called candidiasis.
is known. While hedging bets on Mushrooms is important, not much is known about the mechanics of the different strategies used by different species. Researchers have studied S.cerevisiae to determine the mechanism of betting hedging in this species. In S. cerevisiae, it was found that there were differences in the distribution of growth rates between yeast microcolonies and that slow growth was a predictor of heat stability. Tsl1 is a gene that has been identified as a factor in this resistance. It has been shown that the frequency of this gene correlates with the heat and stress resistance and thus the survival of the yeast microcolonies under harsh conditions using betting hedging. This shows that the use of Bet Hedging makes it more difficult to treat pathogenic strains of this yeast which are harmful to humans.
A group of researchers investigated a different way of hedging bets by examining the ascomycete fungus Neurospora crassa. It has been observed that this species produces ascospores with different dormant times, since non-dormant ascospores can be killed by heat, but dormant ascospores survive. The only downside is that it takes longer for the dormant ascopores to germinate.
Plants provide simple examples of how to study betting hedging in wildlife. They enable field studies, but without as many disruptive factors as animals. Studying closely related plant species can help us understand more about the circumstances under which betting hedging evolves.
The classic example of betting hedging, delayed seed germination, has been extensively studied in desert yearbooks. A four-year field study found that populations in historically worse (drier) environments had lower germination rates. They also found a wide range of germination dates and flexibility in germination for drier populations when exposed to rain, a phenomenon known as phenotypic plasticity. Other studies on desert yearbooks have also found an association between temporal variation and lower germination rates. One of these studies also found that the density of seeds in the seed bank affects germination rates.
The hedge of betting by a seed bank has also been linked to weed persistence. A study of twenty species of weeds showed that after 5 years the percentage of viable seeds increased with soil depth and germination rates decreased with soil depth (although the specific numbers varied between species). This indicates that in circumstances where the cost of hedging bets is lower, weeds will make higher hedging deals.
Taken together, these results provide clues about hedging bets in plants, but they also show the importance of competition and phenotypic plasticity that simple betting hedging models often ignore.
Previously, research on hedging bets with species in the archaeal domain has not been readily available.
Betting hedging has been used to explain the latency of herpes viruses. For example, the varicella zoster virus causes chickenpox when it is first infected and can cause shingles many years after the initial infection. The delay in which shingles occurs has been explained as a form of betting hedging.
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