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.