Electronic flowers attempt to attract pollinators.

The Mathematics of How Plants Combat Pollen Scarcity with Self-Pollination

Through innovative eco-evolutionary models, Kuangyi Xu offers fresh insights into how plants could self-rescue in times of pollen scarcity by balancing the benefits and costs of self-fertilization.

As pollinators become more scarce, plants may resort to self-fertilizationβ€”a survival strategy that comes with its own mixed bag of outcomes. However, according to a new study in The American Naturalist, this isn’t necessarily a dead end for plants. The study, by Kuangyi Xu, suggests that plants could self-rescue in the face of dwindling pollen availability. Through sophisticated eco-evolutionary modelling, Xu reveals conditions under which self-fertilization, driven by immediate adaptation or gradual evolution, becomes a lifeline for struggling plant populations. Intriguingly, these plants might not only ensure their survival but could be actively purging harmful genetic errors from their DNA.

Xu’s work uncovers a fascinating plant paradox. As they battle with pollen shortages due to environmental shifts, the rise in self-fertilization could be both a boon and a bane for their survival. The models Xu presents suggest that the frequency of self-pollination – the ‘selfing rate’ – is a vital component in this balancing act.

On one side of the coin, heightened self-fertilization provides immediate reproductive insurance, a form of DIY continuity for plant species. But on the other side, this could expose harmful recessive mutations, undermining plant health and reducing chances of survival. There can also be costs in using pollen for self-fertilization when you’ve had your pollen waiting for ages, and no pollinator has turned up.

Xu’s research suggests that the magic recipe for plant survival is a moderate level of self-fertilization, achievable either through immediate adaptation or slow evolution. The need for self-fertilization rises in tandem with the severity of pollen scarcity.

Adding a new twist to the tale, Xu posits that under mild pollen limitation, the primary benefit of self-fertilization may not be reproductive assurance but the elimination of harmful genetic elements. Under severe pollen limitation, both benefits kick into play, hinting at a wonderfully intricate and nuanced survival strategy in the plant world.

Moreover, Xu found that smaller plant populations require a lesser increase in self-fertilization to endure, suggesting that the size of a plant population has a significant role in determining the optimal ‘selfing rate’. In an increasingly challenging world for plant reproduction, they could adopt self-fertilization as a delicate survival strategy.

Pollen scarcity, often triggered by human activity and dwindling pollinator populations, dramatically hampers a plant’s ability to reproduce. When such changes occur, we typically expect evolution to favour characteristics that enhance a plant’s mating potential and survival chances. Increases in selfing rates have been noted in response to different environmental shifts like human disturbances, habitat fragmentation, and extreme weather conditions. But there’s a catch.

While self-fertilization can boost survival odds in a demanding environment, it has its downside: it can lead to inbreeding depression, where offspring suffer from reduced health due to exposure to harmful recessive mutations. While selfing aids in immediate reproduction, it may also weaken future generations. Thus, balancing the benefits of self-fertilization and the costs of inbreeding depression is crucial for survival.

There are two main routes through which selfing rates can rise – evolutionary changes (long-term genetic adjustments) and phenotypic plasticity (instant response to environmental stress). Both these mechanisms have their pros and cons, and their effects on the survival of plant populations are not fully understood. Xu’s research helps bridge this knowledge gap, comparing the effects of both mechanisms on plant survival under different levels of pollen scarcity.

Using mathematical models and computer simulations, Xu provides deeper insight into how plant populations adapt to hurdles like reduced pollen availability. One of these models generates a ‘survival probability’ β€” an estimate of how likely the population is to persist over a specific time frame.

Deleterious mutations that are more recessive cause higher inbreeding depression, leading to a stronger initial fitness reduction and taking longer to be purged in mixed-mating populations. Meanwhile, smaller-effect harmful mutations are purged more slowly and cause a stronger fitness reduction under the evolution of a higher selfing rate. In general, immediate adaptation through plasticity seems more beneficial to population survival than evolution, but sometimes a mix of both may provide the highest survival probability.

The strength of mating system plasticity often varies between populations (Koski et al. 2019Eckert et al. 2011), but the evolution of mating system plasticity is under-investigated, despite some studies on some special mechanisms of plasticity such as delayed selfing (reviewed in Goodwillie and Weber (2018)). The current results suggest it is important for studies of the evolution of plasticity to incorporate interactions between inbreeding depression, genetic load, and stochastic dynamics of pollen limitation.

Xu 2023


Xu, K. (2023) “Population rescue through an increase of the selfing rate under pollen limitation: plasticity vs. evolution,” The American Naturalist. Available at: https://doi.org/10.1086/725425.

Dale Maylea

Dale Maylea was a system for adding value to press releases. Then he was a manual algorithm for blogging any papers that Alun Salt thinks are interesting. Now he's an AI-assisted pen name. The idea being telling people about an interesting paper NOW beats telling people about an interesting paper at some time in the future, when there's time to sit down and take things slowly. We use the pen name to keep track of what is being written and how. You can read more about our relationship with AI.

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