Age years

Fig. 3.9. Survivorship curve of Drummond phlox (Phlox drummondii) shown on arithmetic and logorithmic scales (data from Leverich and Levin, 1979).

re u

E 60

E 60


Fig. 3.10. Idealized survivorship curves shown on: (a) log scale, and (b) arithmetic scale. Type I shows low early mortality and high late mortality. Type II shows constant mortality rate over time. Type III shows high early mortality and low mortality late in life.


Fig. 3.10. Idealized survivorship curves shown on: (a) log scale, and (b) arithmetic scale. Type I shows low early mortality and high late mortality. Type II shows constant mortality rate over time. Type III shows high early mortality and low mortality late in life.

tion? The answer is that there is a lot of valuable information in the variability of a population and that by reducing this to a mean value we lose information (Hutchings, 1997). Populations may have the same mean values but different structure; for example, the four populations shown in Fig. 3.11 have the same mean stem diameter (x=20 cm) but the proportion of individuals in each size class differs. The fate of these populations will most likely differ.

Another reason we may be interested in the structure of a population is that it is a way to identify specific individuals of interest. For example, we may only be only interested in plants of a certain size (age or stage). If we know, for example, that only individuals above a specific size will impact crop yield, then we can focus our research on the larger age classes. Recognizing population structure helps us to focus on specific individuals within a population, and it gives us a glimpse of possible population dynamics to come.

Life History Strategies in Plants: Population Structure and Life Cycles

A strategy is 'a grouping of similar or analogous genetic characteristics which recurs widely among species or populations and causes them to exhibit similarities in ecology' (Grime et al., 1990). The term 'strategy' is sometimes criticized because it is anthropomorphic (has human attributes) and teleo-logical (has a purpose) (Grime et al., 1990); however, few suitable alternative terms exist




















o ti








Tree trunk diameter (cm)

Fig. 3.11. Age structure of four imaginary populations, each with the same mean age (x = 20), but differing age distributions.

(e.g. 'set of traits', 'syndrome'). Life history comprises both the general description of a life cycle of a plant (annual, biennial, perennial) and all of the more specific aspects of life cycles within population (age, stage, size).

Many individuals, populations and species have adapted or been genetically constrained to adopt similar life histories to survive. Such common patterns of life histories suggest that there are general 'life history strategies'. There is no one optimum plant strategy that maximizes survival in all situations. If there were, there would be only one plant species. Environmental conditions vary drastically over time and space, and therefore different traits will be favoured in different situations and at different times. Based on life history strategies, we can make general predictions about what traits are likely to allow individuals, populations or species to exist under different environmental conditions.

r- and K- selection

One way to classify plants by life history strategy is to refer to them as being V or 'K' selected (e.g. Beeby, 1994). Following disturbances, the species that will recolonize most rapidly are generally small annuals that have a rapid growth rate, reproduce early and produce many small seeds. This set of traits allows the species to arrive, germinate, establish and reproduce quickly. Therefore, if further disturbance occurs, there will be seed available to re-establish. This specific set of traits is called an 'r-strat-egy'; the 'r' refers to the high intrinsic rate of population growth displayed by species with this strategy. In situations where disturbance is infrequent, and environmental conditions are relatively stable, traits such as large size, longevity, delayed reproduction are favoured. Plants with this set of traits are 'K-strategists' because the populations are theoretically maintained at or near the carrying capacity (K). Table 3.3 summarizes characteristics found in r- and K-strategists.

Table 3.3. Features of r- and K-selected species (adapted from Pianka, 1970).

/-selected species

K-selected species



Survivorship Population size

Life span

Body size


Rate of development



Unpredictable and/or variable; uncertain

Occasional catastrophic mortality, density dependent

Usually Deevy Type III

Variable over time, often below carrying capacity

Short, usually <1 year


Often low


Usually early, monocarpic Produce many, small offspring Productivity

Predictable or constant; more certain

Mortality rate lower and more constant, density independent

Usually Deevy Type I or II

Constant over time, often at or near the carrying capacity

Long, usually >1 year


Often intense Slow

Usually late, polycarpic Produce few, large offspring Efficiency

Many plants cannot be divided neatly into r- or K-strategies because they represent ends on a continuum; most plants actually use both strategies in the appropriate environmental conditions. Although valuable as a tool, it is naïve to use r- and K-selection as the sole criteria in predicting the potential colonization ability or the weediness of a plant.

The contrast between r- and K-selection is clearly illustrated by two different varieties of barnyardgrass (Echinochloa crus-galli) in California (Barrett and Wilson, 1983). E. crus-galli var. crus-galli has numerous, small dormant seeds. This allows it to survive in unpredictable, heterogeneous habitats and hence it is more cosmopolitan. E. crus-galli var. oryzicola does not exhibit dormancy; it has large seeds that germinate with the rice crop (Oryza sativa), and large, vigorous seedlings. It is, therefore, more K-selected as it is adapted to homogeneous, predictable environments (rice paddies) and it is the more noxious variety of weed in rice paddies. However, it is restricted to this habitat and is less of a problem worldwide than E. crus-galli var. crus-galli.

Agricultural weeds are commonly characterized as being r-selected. These weeds are adapted to frequent disturbance through tillage, herbicides or other agronomic practices. Their life span is short, reproduction is early, fecundity is high and seeds are small (Pianka, 1970). Nevertheless, it would be wrong to state that all agricultural weeds are r-selected. There is a degree of stability in the regularity of disturbance, and so some K-selected species also persist. Such species may be perennial weeds with polycarpic reproduction, and few seeds with abundant nutrient reserves. With the increase of no-till farming, K-selected weeds may increase in agriculture systems (Swanton et al., 1993; Buhler et al., 1994).

A weed may be anywhere on the spectrum between r- and K-selected. For example, johnsongrass (Sorghum halpense) and cocklebur (Xanthium strumarium) are two of the world's 'worst' agricultural weeds; however, johnsongrass is K-selected and cocklebur is r-selected (Holm et al., 1977; Radosevich and Holt, 1984). Additionally, despite being r-selected (in general), cockle-bur is an effective competitor (for water) and undergoes both early and late germination, characteristics not traditionally associated with r-selected species (Pianka, 1970; Scott and Geddes, 1979).

C-S-R selection

Because many plants may exhibit a 'compromise' of r/K-selected attributes, a modified theory of plant strategy and selection was developed (Grime, 1977, 1979). Grime used characteristics of the established phase of the life cycle to characterize plants based

Relative importance of stress

Relative importance of stress

(b) Annual herbs

Biennial herbs Perennial herbs and ferns

(b) Annual herbs

Biennial herbs Perennial herbs and ferns

Trees and shrubs



Trees and shrubs



Fig. 3.12. The C-S-R model showing: (a) the location of the three main strategy types (C= competitors, S= stress tolerators, R= disturbance tolerant ruderals) and secondary strategies, and (b) the placement of various types of vascular and non-vascular plants along the three axes (redrawn from Grime, 1977).

Fig. 3.12. The C-S-R model showing: (a) the location of the three main strategy types (C= competitors, S= stress tolerators, R= disturbance tolerant ruderals) and secondary strategies, and (b) the placement of various types of vascular and non-vascular plants along the three axes (redrawn from Grime, 1977).

on their ability to withstand competitors, disturbance and stress. In his triangular conceptual model, the corners represent ruder-als (disturbance tolerators) (R), competitors (C) or stress-tolerators (S) (Fig. 3.12a). C-strategists maximize resource capture in undisturbed but productive habitats by increasing vegetative production and reducing allocation to reproduction. R-strategists maximize reproduction and growth, and are adapted to disturbed but potentially productive environments. These two strategies are somewhat analogous to K- and r-selec-tion, respectively. The S-strategists are adapted to stressful, harsh environments where disturbance is rare and competition is unimportant. By reducing vegetative growth and reproduction they maximize their survival.

Characterization of C, S and R species is

Table 3.4. Characteristics of competitive, stress-tolerant and ruderal plants (adapted from Grime, 1977).

Competitive C

Stress-tolerant S

Ruderal R


Life forms


Leaf form

Life history

Longevity of established phase Longevity of leaves and roots Frequency of flowering Annual production allocated to seeds Structures persisting in unfavourable conditions Regeneration strategies


Maximum potential relative growth rate Response to stress

Storage of mineral nutrients from photosynthesis



Palatability to unspecialized herbivores

Herbs, trees, shrubs Lichens, herbs, trees, shrubs

Leaves form high, dense Variable canopy, extensive lateral spread of roots and shoots Robust


Relatively short

Usually every year


Dormant buds and seeds

Vegetative growth, small seeds, persistent seed bank


Rapid response to maximize vegetative growth

Into vegetative structures, some stored for new growth in following season

Copious, often persistent


Often small, leathery or needle-like





Stress-tolerant leaves and roots

Vegetative growth, persistent seedling bank


Slow, limited response

Storage in leaves, stems, and/or roots

Sparse, sometimes persistent Low


Small stature, little lateral spread


Short Short

Produced early in life history Large

Dormant seeds

Small seeds, persistent seed bank


Rapid response to divert from vegetative growth to flowering


Sparse, not usually persistent Variable, often high based on a plant's morphology, physiology, life history and other traits (Table 3.4). Intermediate species are shown in the central region of the triangular model (Fig. 3.12b). Weeds are usually classified as rud-erals (R), or competitive ruderals (CR). Both strategies are adapted to productive habitats, but CR-strategists would be found in less frequently disturbed habitats than R-strategists who have short life spans which allow species to re-establish after disturbance. While Grime's strategies have been discussed widely in reference to weed species, some have pointed out its limitations (Tilman, 1987). Grime's model relies on a narrow definition of competition (Grace, 1991). This will be dealt with in the next chapter on competition.


Describing population dynamics, population structures, life cycles and life history strategies is difficult because of genetic and environmental variation and the complex interactions and combinations that can occur. This complexity is the reason why our convenient measures and descriptions of populations are often not adequate even if they do a reasonable job of approximating the real world. This complexity explains why:

• simple logistic and exponential equations do not adequately describe populations;

• spatial isolation within metapopulations influences survival and conservation decisions;

• classifying plant population structure by age, growth stage, size and life cycle can be difficult; and

• life history strategies are good rules of thumb but not all that accurate in predicting the population dynamics and impact of plants, especially weeds.

Population dynamics and structure are good concepts to understand, but they need to be developed and studied in the context of ecological interactions and genetic variation. This means it is not enough to understand the general patterns of populations. We should also understand how populations change with genetic diversity, variation in reproduction, and with the presence of competitors, herbivores and disease. In short, population dynamics and structure influence and are influenced by many other factors that we will be discussing in future chapters.


1. What is known about the population structure and dynamics of your selected species of weed? Suggest ways that that your species can be structured, i.e. by age, size, phenology. Describe the life history strategy of your species. Is it an r- or K-selected species - or somewhere in between? Place your species on Grime's C-S-R model and explain why you placed it there.

2. Describe the size distributions of the four populations shown in Fig. 3.11. Assuming that age is correlated with size, what is the likely fate of each of these populations? Explain why. Would your answer change if age were not correlated with size? Explain why.

3. How might metapopulation dynamics be considered in controlling a recently introduced invasive weed?

4. Explain what it means to have a Type I, II or III survivorship curve.

5. How might the carrying capacity (K) of a weed be modified by changes in management practices?

6. Explain why a plant's population size does not increase indefinitely.

General References

Beeby, A. (1994) Applying Ecology. Chapman and Hall, New York.

Cousens, R. and Mortimer, M. (1995) Dynamics of Weed Populations. Cambridge University Press, Cambridge.

Hanski, I. and Gilpin, M. (1991) Metapopulation dynamics: brief history and conceptual domain. Biological Journal of the Linnaean Society 42, 3-16.

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Boggs, K.W. and Story, J.M. (1987) The population age structure of spotted knapweed (Centaurea maculosa) in Montana. Weed Science 35, 194-198.

Buhler, D.D., Stoltenber, D.E., Becker, R.L. and Gunsolus, J.L. (1994) Perennial weed populations after 14 years of variable tillage and cropping practices. Weed Science 42, 205-209.

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