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Christina Lebonville
Classical Paper Trace
11/18/05
In an attempt to model the underlying processes directing plant life history trait evolution,
J.P. Grime proposed in 1977 that life history traits followed predictable patterns along stress and
disturbance gradients (Grime 1977). The foundation for Grime’s model, and many models
thereafter, was the life history evolution theory proposed by MacArthur and Wilson (1967) a
decade earlier. Based on their research, they proposed that there exist two distinct types of
organisms: K-selected and r-selected species. K-selected species are long lived, large bodied
organisms that grow slowly and invest little in reproduction. R-selected species, on the other
hand, are short lived, small-bodied organisms, that grow rapidly and invest much in
reproduction. According to this model, density-dependent effects were the driving force behind
which selection an organism experienced, and not environmental factors. Grime, like many
others at the time, found that the uni-dimensional nature of the r- and K-selection model was too
general to describe the complex nature of adaptation and so composed his own model which
allowed for an intermediate between r- and K-selection - competition. Grime described three
types of species that are found under varying levels of stress and disturbance- Competitive,
Ruderal (equivalent somewhat to r-selected), and Stress-tolerant (equivalent somewhat to Kselected) species. Under conditions of high stress, which include but are not limited to nutrient
shortage, low light, sub-optimal temperatures, and growth inhibiting toxins, plants are more
likely to have slow growth rates, little devotion to seed production, and often evergreen, leathery
or needle-like leaves. These organisms, Grime labeled Stress-tolerant. However, it is because of
these adaptations, which conserve resources rather than exploit them, that species exhibiting
these tolerances are less suited for competition than species that are not adapted to cope with
environmental stress. Contrarily, species found in low stress and disturbance environments
generally are able to utilize the availability of nutrients in order to grow rapidly and avoid
resource pre-emption by their competitors. Organisms adapted under these conditions, Grime
called Competitive. At the same point, species that live in environments with frequent
disturbances make rapid reproduction a priority in order to replenish their population quickly but
as a result may not be strong competitors or stress-tolerators. These were therefore the Ruderal
species in Grime’s model. Thus, due to trade-offs between resource allocation toward fast
growth, reproduction, or stress-tolerance, the three species types emerge.
Grime calls his model, which describes the three main types of organisms that exist under
varying combinations of stress and disturbance, the Competition-Ruderal-Stress-tolerant (CRS)
model of plant life history strategy selection (Grime 1977).
Since Grime’s proposal, countless experiments have been performed to test the
predictions of the CRS model. In a study by Wilson and Keddy (1986) of plants grown under
high and low-nutrient conditions caused by wave exposure upon the shores of lakes, it was found
that superior competitors were found in areas with low levels of stress and disturbance. More
recently, Schoennagel (2004) found that ruderal species tended to be more abundant in areas
with shorter fire disturbance intervals while declining as the fire interval was increased. Thus the
predictions of Grime’s model were observed for these particular studies.
Conversely, Antos (2005) studied the life histories of trees in a productive forest and
observed results that seemed to contradict the CRS model. The only limiting factor in this
environment was light due to the dense canopy and yet this was previously considered to be a
competitive issue, not one of stress. The life history strategies of the trees studied, however,
showed incredibly slow growth and longevity- two traits associated with the stress-tolerating life
history. Another issue was that these same slow growing trees were capable of rapid growth as
they formed much of the canopy of the forest. This indicated high phenotypic plasticity, which
is associated with competitive, fast growing species who can adapt more rapidly to
environmental change. Similarly, it has been found that ruderal species, under stress, exhibit
rapid early growth and early flowering, seemingly evident of stress avoidance rather than
tolerance according to some(Stanton 2000). These same results were also obtained by a
competitive study (Miller 1995) despite Grime’s implications that stress and competition should
cause opposing selective forces. A study by Emery (2001) found that under non-nutrient tidal
stress, good stress tolerators were also the competitive dominants, again seemingly contradicting
the CRS model.
To counter the limitations found in Grime’s CRS model as evidenced by the experiments
previously described, many other theories of life history evolution have been constructed.
Greenslade (1983), like Grime, was frustrated by the difficulties found in a two category model
and added his own third selection pressure which he called adversity, or A-selection.
Greenslade’s idea of A-selection pushed K-selected species into an intermediate form while Aselected species represent a further extreme than the K-selection that exist under extreme
conditions, which is why Greenslade refered to A-selection as beyond K-selection.
David Tilman thought that the competitive side of the CRS model ignored an important
distinction – competition for above ground versus below ground resources which would affect
the traits observed (Tilman 1985). For example, competition for light would promote the
accumulation of above ground biomass in order to maximize the amount of this limiting resource
that can be acquired. Competition for nitrogen, however, would promote the development and
growth of extensive root systems for more efficient nutrient uptake. Since, when faced with both
above ground and below ground resources, a plant cannot devote sufficient energy to each and
still successfully compete for both, there is a trade-off between which resource a plant will adapt
to maximize the intake of. Thus, the nature of the limiting resource should be considered a
major axis in determining life history traits. Tilman describes findings by Chapin (1980) that
indicate that in very poor soils, more resources are devoted to below ground development than
plants found in nutrient-rich soils. This distinction, Tilman implies, is not covered sufficiently
by Grime’s CRS model and a third axis describing this important gradient should be included in
a model that describes the evolution of life history traits – he calls this idea his resource-ratio
hypothesis.
Shortly thereafter, a man named Southwood (1988) attempted to reconcile the differences
found in the many models that described trait evolution. He argued that the so-called
“differences” between each of the models was more of a difference in orientation and
terminology rather than contradictory ideas. Adversity, as described by Greenslade, was
equivalent to stress. Productivity, as described by Hildrew and Townsend (source uncited),
being inversely related to stress/adversity, essentially also described the stress/adversity axis in
reverse. In sum, if the models are combined, there are three axes that can describe the main
trends of each. Those axes are adversity, disturbance, and a diagonal axis describing the impact
of biotic agents. This third axis essentially describes the interaction between organisms in
competition, predation, and so on. With adversity increasing on the x-axis and disturbance
decreasing on the y-axis, Southwood describes a very general trend of life history traits. For
example, in low adversity and disturbance environments, this model predicts that offspring
would be medium or small, life-span would be medium, stress tolerance low, and investment in
defense medium. On the opposite end with high adversity and disturbance, offspring would be
medium and large, life-span would be medium, stress tolerance high, and investment in defense
high. Southwood called his model the habitat template model, after the idea that environment
forms a template to which the species within arrange themselves (generally it is called the
Southwood-Greenslade model because of Greenslade’s similar conclusions). In addition to
attempting to form his own life history trait model, a compendium of previously proposed
models, Southwood also made assertions as to what the true master model would need to
include. He emphasized the multiple paths that organisms can take under varying conditions.
Individual organisms need to have the freedom to follow one out of a possibility of paths since
different organisms experience the environment differently as well as genetic constraints and
stoichasticity must also be taken into account. In addition, he thought that other, more
complicated trade-offs needed to be included in the model. Traits like migration, dormancy, and
other complex traits were not to be excluded. Southwood viewed a comprehensive life history
trait model to be like a “periodic table” where the evolutionary outcome for many different
environmental conditions would be listed.
Since Southwood’s description of the “periodic table” was introduced, few actual
attempts at creating such a table have been made. Instead, the focus has been on creating models
for individual case studies of interest and not on creating full-scale templets to describe the
whole of evolutionary traits (Korfiatis and Stamou 1999). What this generally entails is using
the classical models as a starting point for designing and testing a specific model. Where the
classical models do not fit the observations, the model is modified so that it better fits the data.
A current example of this is the study of Ladd and Facelli on tree seedling establishment through
examining the interactions of resource ability, species identity, competition, and herbivory
effects. What they found was that herbivory effects and competition effects were so similar to
each other that they could be confounded in experiments. Since Grime’s CRS model defined
herbivory as a form of disturbance, the fact that competition and disturbance effects would be
confounded if Grime’s model was used led Ladd and his collegues to adopt Southwood and
Greenslade’s habitat template model for their particular study where herbivory would be defined
under biotic interactions along with competition. In this case study, each model was considered
and though they don’t necessarily disagree or contradict each other, as Southwood (1988)
asserted, one model was able to organize the findings more appropriately so that predictions
could be made. Other examples of this are illustrated in the studies by Emery (2001) and Antos
(2005) which were described previously to investigate the application of Grime’s CRS model
(see pp. 2-3). As far as modern application of the r- and K-selection model, its true value is
mainly in its description of density-dependent selection mechanisms (Boyce 1984), since it is
accepted that environmental factors play a large role in life history trait evolution – a role the rest
of the models described recognized.
Despite the fact that templet models have become more localized and less generally
applicable, some recent studies have attempted to decode and investigate the master model or
“periodic table” of life history trait evolution. Ingeniously, Ignacio Ribera (2001) and his
colleagues decided to test whether any model had the potential to describe natural systems by
using an indirect analysis: ordination. As most of the models describe the relationship between
organisms and their environment being the driving force behind the evolution of life traits,
Ribera collected trait data for many different ground beetles and attempted to correlate this data
with environmental data. What he found was that there was a highly significant relationship
between morphological traits and life histories and the environmental factors measured. The
strongest environmental correlations were with disturbance as measured by a land management
index (indicating land usage) and stress or habitat adversity as measured by elevation and
vegetation structure. Ribera considered the main ordination axis equivalent to the diagonal axis
in Southwood’s habitat template model.
Endeavors to arrange and predict life history trait evolution began with MacArthur and
Wilson’s r- and K-selection in 1967, evolved additional complexity with Grime’s CRS model in
1977 along with Greenslade’s adversity selection and Tilman’s resource-ratio model in the early
to mid 80’s, and finally became a conglomerate of theories with Southwood and Greenslade’s
habitat template model in 1988. Since then, efforts have been focused on generating localized
models to describe specific systems using the classic models as a starting point as in the studies
by Emery (2001), Antos (2005), and Ladd (2005). Yet, there are some who delve into piecing
together the “periodic table”, as Southwood put it, of life history trait evolution. In order to
weave together this tapestry of predictions, more investigations must be made. Questions still
exist about the ability of some species to be both successful competitiors and stress tolerators
while others can only master either alone. What defining characteristics or environmental factors
contribute to this dual adaptation? Along Southwood’s proposals, more studies need to be made
on complex trade-offs like migration and dormancy. Since plant traits are almost described as
being a behavior of sorts, what elements of animal behavior traits can be described by
environmental factors? This includes but is not limited to altruism, eating one’s own young, and
mate selection. Though many of these characteristics have been investigated and explained
based on genetic considerations, are there trade-offs that make these traits more likely to be
present in some environments despite advantages or disadvantages to maximum fecundity.
When the scope is altered to include more traits, will a model be able to describe and predict and
yet still be comprehendible by investigators? Is it better to reduce the scope to best fit specific
case studies while losing the generality that allows models to be useful in many different cases?
These last few questions are unfortunately not limited to the prediction of life history traits but
all of biology as well. With the diversity, complexity, and stoichasticity of natural systems, we
ourselves have a trade-off between knowing absolutely everything and knowing enough to get by
for a while.
Works Cited
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ancient montane forest: stress tolerators in a productive habitat. Journal of Ecology 93:
536-543.
Boyce, M.S. 1984. Restitution of r- and K-selection as a model of density-dependent natural
selection. Annual Review of Ecology and Systematics 15: 427-447.
Chapin, F.S., III. 1980. The mineral nutrition of wild plants. Annual Review of Ecological
Systems 11: 233-260.
Emery, Nancy C., Patrick J. Ewanchuk, and Mark D. Bertness. 2001. Competition and saltmarsh plant zonation: stress tolerators may be dominant competitors. Ecology 82(9):
2471-2485.
Greenslade, P.J.M. 1983. Adversity selection and the habitat templet. The American Naturalist
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Grime, J.P. 1977 Evidence for the existence of three primary strategies in plants and its relevance
to ecological and evolutionary theory. The American Naturalist 111(982): 1169-1194.
Korfiatis, K.J. and G.P. Stamou. 1999. Habitat templets and the changing worldview of
ecology. Biology and Philosophy 14: 375-393.
MacArthur, R.H. and E.D. Wilson. 1967. The theory of island biogeography. Princeton
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Miller, T.E. 1995. Evolution of Brassica rapa L. (Cruciferae) populations in intra- and
interspecific competition. Evolution 49: 1125-1133.
Ribera, Ignacio, Sylvain Doledec, Iain S. Downie, and Garth N. Foster. 2001. Effect of land
disturbance and stress on species traits of ground beetle assemblages. Ecology 82(4):
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Schoennagel, T., D.M. Waller, MG. Turner, and W.H. Romme. 2004. The effect of fire interval
on post-fire understorey communities in Yellowstone National Park. Journal of
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Stanton, M.L., B.A. Roy, and D.A. Thiede. 2000. Evolution in stressful environments. I.
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Tilman, David. 1985. The resource-ratio hypothesis of plant succession. The American
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