Discussion
MacArthur asks, “Why would any individual ever migrate to a less favourable area? Why not stay put if it is better at home?” (MacArthur, 1972). Often times the environmental variability of each sub-habitat is unique and different from the others within the habitat. When this is the case, there is additional fitness if individuals have the ability to alter the dispersal rate from each habitat. This means that having site-specific dispersal rates is adaptive (Fig. 3). When environmental variability within each sub-habitat is considered, and individuals who are able to sense their location have an additional fitness, they benefit from the ability to alter their dispersal ratio in accordance with where they find themselves.
Populations existing within a widespread habitat will be subjected to different environmental conditions depending on where within that habitat they find themselves. To what degree can organisms have information about where they find themselves? Across some habitats, there are likely to be differences in environmental conditions, which will have a bearing on the fitness of a population. For instance, differences in temperature or rainfall will vary and can be used as clues to which sub-habitat an organism finds itself in. Plants and seeds, for instance, sense changes in temperature through the seasons and use these as cues to define their timing of flowering, germination and seedling emergence (Linkies et al. , 2010). Germination timing is controlled via dormancy cycling for which temperature and moisture are the two most important environmental cues (Finch-Savage and Footitt, 2017). A typical plant has over 600 receptor-like kinases (RLKs) involved in sensing specific molecules including from the environment; animals evolved only about 1% of this (Shiu and Bleecker, 2001). Although plants do not have a nervous system, they can sense their environment extremely well and integrate the environmental factors both long-term and short-term. Similar cues are used by the individual seed or plant to determine where they might find themselves within their habitat. Using these cues, individuals are able to produce site-specific offspring ratios, such as the example of Ae. arabicum (Lenseret al. , 2016).
Many species, including plant species, are limited to sensing in the emigration phase of dispersal where other species are able to also sense their environment during the transfer phase. In this way, they cannot sense the surrounding sub-habitats and make informed dispersal choices about the sub-habitat into which they ultimately immigrate. As a result, many species depend on the environmental clues in the emigration phase and so the risk of dispersing is much higher, because they cannot make an informed decision once they have dispersed. For this reason, it is crucial to sense the condition of the local environment to determine if the risk of entering a potentially worse sub-habitat is worth taking the chance. Adding the interactions between dispersal mechanisms and environmental conditions into models, such as the one presented in this paper, gives a fuller, more in-depth understanding into population dynamics and the consequences of the environment on dispersal (Seale and Nakayama, 2019).
If the future quality of the entire environment is highly predictable, it is possible to use cues to determine the next future state. In term of dispersal, the best strategy is then to somehow disperse offspring to the best sub-habitat. Often times, the future is uncertain and information about possible future states is unavailable. What we show here that, theoretically, even if that is the case, systematic differences between sub-habitats, be it either in the average quality or in its variability, can lead to adaptations that favour site-specific dispersal, provided the organism can get clues as to which sub-habitat they find themselves in. How they sense the environment is unimportant, so long as it provides information to help them determine in which sub-habitat they are in. In the case of Ae arabicum , for instance, the key difference between the high and low altitude environments might be in terms of competition and severity and unpredictability. There is no need to sense these factors directly: temperature, even though in itself potentially not the most important factor, gives a clue as to the likely altitude the organism finds itself and can therefore be used as a clue. Sensing provides the individual with enough information about the local environment to determine where they are, and site-specific dispersal allows the individual to alter their dispersal ratio in order to maximise the likelihood of the offspring surviving to the following year.
The importance of dispersal plasticity in response to local environmental variability is something seen across the kingdoms (Arendt, 2015). Poa alpina is an alpine species that persists in a highly variable environment. The species adopts a seed-reproduction strategy at lower elevations, and bulbil-reproduction strategy at higher elevations (Steiner et al. , 2012). This allows it to occupy a large ecological niche so that it can persist in multiple sub-habitats in case one or more of these sub-habitats become unfavourable. In many insect species, wing polymorphism dictates dispersal rates. In aphids, offspring are either winged or wingless, making them dispersing or non-dispersing. Competition, crowding and host condition appear to be the driving forces for the ratio of offspring dimorphism, all of which the maternal aphid is able to sense and respond to by producing wingless or winged offspring (Harrison, 1980). Cycles of bluebird species have been shown to be driven by maternal effects. Following the creation of a new environment by a wildfire, the area is colonised by mountain bluebirds (Sialia currucoides ). To compete with the mountain bluebirds, maternal western bluebirds (Sialia mexicana ) produce aggressive, dispersing offspring. Once the area is colonised by western bluebirds, nonaggressive, non-dispersing offspring are produced. Population density, resource limitations and competitive interactions all appear to be cues for maternal western bluebirds (Duckworth, Belloni and Anderson, 2015).
The habitat in which Ae. arabicum exists in the Anatolian Mountains can be roughly divided into two sub-habitats: high elevation, and low elevation (Velchev, 1984; Mohammadin et al. , 2017). At high elevation, the environment is dry, exposed, and rocky, with little to no competition. The exposure makes it prone to extreme weather conditions, and so the environmental variability is considered to be higher. At low elevation, the environment is overcrowded, shaded and highly competitive, with better availability of a steady water supply and nutrients. At this elevation, the environment is more competitive but generally sheltered, making the environment less variable year on year (Atalay, 2006). As well as this, there is also a temperature gradient along the elevation, as there is a drop of 3oC for each 300 metres above sea level (masl) climbed. Aethionema arabicum has been found growing between 0-3000 masl (Bhattacharya et al. , 2019). By sensing the environment into which the dispersing, indehiscent fruits (IND) disperse through this temperature gradient, the resultant plant grows and produces different ratios of dispersing to non-dispersing offspring (Lenser et al. , 2016; Arshad et al. , 2019).
The life-history of Ae. arabicum fits with the strategy observed in the model. There is a dramatic temperature difference along the elevation of the slopes on which they grow (Fig. 1 in Arshad et al., 2016 (Arshad et al. , 2019)). Aethionema arabicum has been shown to alter the ratio of IND and non-dispersing, dehiscent fruits (DEH) that it produces when the mother plant is grown at different temperatures during reproduction (Lenser et al. , 2016). In this way, the germination timing due to temperature differences (season, elevation) and the consequently distinct temperature during plant growth and reproduction both influence the final offspring ratio of the plant (Lenser et al. , 2016; Arshad et al. , 2019).
In a lower temperature regime during reproduction, the plant produces more IND fruits. Therefore, it can be suggested that at higher altitudes, Ae. arabicum plants will produce more of the dispersing morphs. This would mean they are able to take advantage of the dispersing adaptations of the IND fruit: it’s buoyant and aerodynamic nature. This would allow them to spread out across the mountain side in greater numbers and take advantage of wherever most is accommodating in the following year. At lower elevations, Ae. arabicum reduces the proportion of dispersal-type offspring with higher temperature and competition stress. However, in response to nutrient stress, Ae. arabicum increases the proportion of dispersal-type offspring (Bhattacharya et al. , 2019). Whether a plant emerges from an IND or DEH fruit does not seem to predict the ratio of dispersing to non-dispersing seeds that it will, in turn, produce. The plasticity is a response to the environmental conditions in which the plants are grown (Lenser et al. , 2016).
One way to efficiently alter the dispersal ratio is through heteromorphism. Heteromorphism was first described by Venable as “the production by single individuals of seeds of different form or behaviour” (Venable, 1985). In this context, behaviour refers to their ecological traits such as their dispersal mechanism. There is a fitness advantage of being able to detect location and therefore, evolving a method to respond by dispersing out of or remaining within the environment is crucial for many species. The main method of doing so for many species is heteromorphism: producing two or more offspring phenotypes that have no, or different methods of dispersal (Imbert, 2002).
One such model to describe the evolution of dispersal heteromorphism is by Venable (Venable, 1985). In this model, the production of two seed morphs in different year types is investigated. The two morphs have different mean and variance based on evolutionary constraints. Offspring morphs are adapted to perform in particular year types, causing more of one to be produced in its favourable year and more of the other to be produced in the opposing years. Evolutionary constraints between years lead to heteromorphism, which produce two offspring morphs that are better adapted to the evolutionary constraints. This is the generalised model used to describe the evolution of dispersal heteromorphism. Our model is an alternative that allows for severely fluctuating, multi-habitat environments. Furthermore, the model gives an explanation for the purpose of sensing in dispersal heteromorphism. Each individual produces two offspring morphs; neither is better adapted for a particular year type, but rather one type is able to disperse and the other is not. How much more or less the offspring disperse out of the sub-habitat is determined by where they are. In this way, our model shows the impact of difference in variability between multiple environments and how this leads to the evolution of sensing and site-specific dispersal plasticity.
Another method of responding to the environment is through responsive phenotype switching. This is where the individual senses an ambient environmental cue and switches its phenotype. However, this is costly because it relies on developing and maintaining machinery to detect environmental conditions. For organisms with a fast turnover rate, such as bacteria, switching rates that mimic the infrequent environmental variability can be favourable over sensing. This is called spontaneous stochastic switching. In environments where there is higher environmental variability, there is an additional benefit to responsive switching. On the other hand, if the environment is fairly constant and variability is infrequent or less, then the stochastic switching method is favoured, as the cost of sensory machinery is too high (Kussell and Leibler, 2005). This pattern mimics closely the pattern observed in our model.
In bet-hedging theory, geometric mean is used to describe fitness. Existing theories on bet-hedging assume that organisms respond to a single environmental variable, so that therefore the geometric mean of this variable can be used as a proxy for fitness. In an environment consisting of two distinct sub-habitats this is not possible as the growth rate of a population cannot be expressed as a simple geometric mean (Tuljapurkar, 1990). In this scenario, sensing doesn’t evolve, because no one sub-habitat is better than any other, as they are all statistically identical, and therefore having site-specific dispersal rates gives no advantage. However, when the environments are statistically variable across the years, and multiple variables for population growth rate are introduced, as in our model, the need to sense location and produce site-specific dispersal rates is adaptive. Although bet-hedging within our model is possible, the results from our model go beyond bet-hedging theory (supplementary material).
Results from the model show that the dispersal strategy best adopted by individuals differs dramatically depending on the environmental variability between multiple sub-habitats. Previous models of dispersal have overlooked the importance of altering the dispersal ratio, depending on the many sub-habitats in which an individual may find itself. This “one size fits all” approach should be reconsidered, as it does not match the life history of species persisting in highly variable environments. Although it has been suggested that climate variability influences aphid reproduction being sexual or asexual by parthenogenesis, this has largely been overlooked in most other species (Halkett et al. , 2004).
A higher incidence of extreme weather conditions are on the rise as a result of climate change. Droughts, heatwaves, flash flooding, heavy downpour and hurricanes are just some of the unpredictable weather phenomena putting species at risk. Especially species that have evolved in lowly variable, temperate climates (Michener et al. , 1997; Watson et al. , 1998; Easterling et al. , 2000; McLaughlinet al. , 2002; Ummenhofer and Meehl, 2017). In the case ofAe. Arabicum, in a mountainous habitat, the two sub-habitats will experience climate change differently, due to their size and topography. Higher up mountains and on mountaintops, the environment is more exposed, and so will be more affected by windstorms and precipitation, where further down, the plains are generally sheltered, but prone to flooding and erosion (Barry, 1992; Beniston, 2006). Sub-habitats experiencing differing environmental stresses like this is also common in coastal areas (Keddy, 1981).
Invasive species also put ecosystems at risk. Phenotypic plasticity is an important adaptation to invasive species, as it allows them to occur in a wide range of environments (Richards et al. , 2006). With environmental change brings new opportunities for invasive species to disperse into such locations and outcompete native species. Dispersal strategies responding plastically to environmental changes are commonly researched in animals, but rarely are for plants (Imbert and Ronce, 2001). This is because plants have been widely regarded as passive organisms to those outside of plant sciences. However, it has been recognised that plants are able to undergo site-specific dispersal and can manipulate the dispersal phenotypes of their offspring in response to their environment (Seale and Nakayama, 2019). With little knowledge on how plasticity or lack thereof will affect plant populations in the wake of environmental unpredictability, this could put many species at risk.
Individuals alter the dispersal ratio of their offspring in response to localised environmental variability to an evolutionary advantage. When a species is dispersing between a rock and a hard place, the optimal strategy is to sense the environment and alter the dispersal ratio of their offspring in response. In this way, the population is balanced within a highly variable environment with multiple differing sub-habitats, where they would otherwise go extinct if the population was restricted to one sub-habitat. With increasingly severe fluctuations in environmental variability comes an increase for the scope of this dispersal strategy. Species adopting this lifestyle are able to thrive in otherwise challenging environments. However, dispersal plasticity is widely under researched and underappreciated across all kingdoms and with a rapid increase in environmental variability, one can only speculate the impact on the natural world.