Intraspecific Competition.

BIOS 6150: Ecology 

Dr. Stephen Malcolm, Department of Biological Sciences 

• Week 3: Intraspecific Competition. 

• Lecture summary: 

• Definition. 

• Characteristics. 

• Scramble & contest. 

• Density dependence 

• k-values 

• Discrete & continuous 

models 

BIOS 6150: Ecology - Dr. S. Malcolm. Week 3: Intraspecific Competition Slide - 1

2. Competition: 

• Interactive process. 

• Product of combined demand for resources. 

• Leads to competition among individuals, 

either: 

• intraspecifically or, 

• interspecifically. 

• Results in a negative outcome for all 

competitors. 


3. Definition of Competition: 

• “competition is an interaction between 

individuals, brought about by a shared 

requirement for a resource [in limited supply], 

and leading to a reduction in the survivorship, 

growth and/or reproduction of at least some of 

the competing individuals concerned” 

(Begon et al., 2006, p. 132) 

• The ultimate effect of competition on an individual is a 

decreased fitness contribution to the next generation 

(fewer offspring) compared with what would have 

happened had there been no competitors. 


4. Four characteristics of intraspecific 

competition: 

• (1) Decrease in fitness: 

• The ultimate effect of competition is a decrease in the fitness of all 

interactants (thus it is a “-,-” interaction): 

• Often via decreased survivorship or fecundity. 

• Fitness reduction must be measurable to conclude that competition occurred. 

• (2) Limited supply of resources: 

• The resource for which individuals compete must be in limited supply. 

• (3) Reciprocity: 

• Even if the detectable competition is either mostly one-sided, or 

balanced, it must be reciprocal and have a negative impact on both 

interactants (symmetrical and asymmetrical). 

• (4) Density dependence: 

• The probability of an individual being adversely affected increases with 

increasing competitor density (in contrast to density independent effects). 


5. Extremes of intraspecific competition: 

• Scramble (exploitation) and contest 

(interference) competition were first 

described as simplistic extremes by 

Nicholson (1954) in Australia. 

• Mortality (% or k competition due to competition) or 

survivorship is plotted against logarithm of initial 

density to show degree of density dependence. 


6. Scramble & Contest Competition: 

• Scramble competition: 

• Nicholson described scramble competition for dungflies 

competing for the limited resources of cow feces. 

• Each member gathers a constant amount of resource at all densities. 

Thus at high density there is insufficient resource and the whole 

population dies (slope b = ∞). 

• Contest competition: 

• Where individuals of the population interfere or contest with 

each others abilities to harvest resources, some survive. 

• Exact density-dependent compensation is thus described by a 

mortality slope b = 1. 

• Figs. 5.1 & 5.2 from Begon et al. (2006) to show both kinds and 

negative effects of competition in single species populations. 


7. Density dependence: 

• Competition also increases with population 

density when mortality may increase or 

survivorship may decrease (Fig. 5.2). 

• The nature of density dependence can also 

change with increasing density from: 

• density independence, through, 

• undercompensating density dependence, to, 

• exactly compensating density dependence, to, 

• overcompensating density dependence 

(Figs 5.3, 5.4 & 6.5). 


8. Density dependence (continued): 

• So intensities of both kinds of intraspecific 

competition increase with population density and 

change from density independence to density 

dependence. 

• Thus density dependent birth and mortality rates lead to 

the regulation of population size at a stable equilibrium 

where births = deaths. 

• This is the carrying capacity (K) at the population size 

sustainable by available resources as shown in Figs. 5.7 & 5.8. 

• Density dependent population regulation generates the 

sigmoidal or S-shaped curve characteristic of intraspecific 

competition (see Fig 5.11). 


9. Density dependent growth: 

• In addition to effects on numbers, competition also 

negatively influences growth: 

• This in turn influences numbers through reduced per capita 

reproductive output. 

• Rates of growth and rates of development can be reduced 

as shown in Figs 6.14 & 5.12: 

• But the total population biomass can remain the same, despite 

individuals being smaller: 

• The “law of constant final yield” (exact compensation) 

• Reproductive allocation can also shift with changing 

resource availability (Figs. 6.16 & 5.15): 

• Within genets, tiller growth was less variable and more regulated 

than the genets themselves. 


10. k-values and density dependent 

mortality: 

• k-values of mortality due to competition can define competition 

according to the slope b of the relationship (Fig. 5.16) of 

k competition plotted against the logarithm of initial density 

(density before the effects of competition). 

• b = 0 density independence. 

• b < 1 undercompensating density dependence. 

• b = 1 (contest) exact density dependent compensation. 

• b > 1 overcompensating density dependence 

• b = ∞ (scramble) overcompensating density dependence 

• see Fig. 2-3 from Hassell (1976) of scramble and contest competition. 

• k-mortality is shown in Fig 5.16 & k-fecundity in Fig. 6.20. 


11. Discrete breeding season model of 

intraspecific competition: 

• Using: 

• R net reproductive rate 

• N t population size at time t 

• N t+1 population size at time t+1 

• In the absence of competition, the model describes 

population increase simply as: 

• N t+1 = N t R and 

• N t = N o R t 

• This gives the exponential population growth across discrete 

generations as in Fig. 5.18. 


12. Carrying capacity, limited resources 

and the effect of competition: 

• At high density when the ratio of N t /N t+1 = 1 this is 

by definition the carrying capacity K. 

• So in the presence of competition, the population 

rises to K as shown in Fig. 5.18. 

• according to: 

• N t+1 = N t R/1+(aN t ) 

• where a = (R-1)/K 

• so the unrealistic R in the first equation is now replaced by 

the more realistic R/(1 + aN t ) 

• as a and N t increase so does the effect of competition and R 

is decreased. 


13. Density dependence of the model: 

• The k-value for mortality 

due to competition is 

thus the difference 

between log N t R and 

log N t R/(1+aN t ) and 

plotting these k values 

against log 10 N t (Fig. 

5.20) shows that the 

model exactly 

compensates with a 

slope b = 1. 


14. Incorporation of variable density 

dependence with b: 

• A more realistic model of competition that 

incorporates a range of competitive regulation was 

derived by Maynard Smith & Slatkin (1973) in 

which they simply added the slope b of the k-value 

plotted against log initial density: 

• Nt+1 = NtR/1+(aNt ) b 

• in which b is the slope of mortality (k) against 

population size (log10Nt ) and, 

• a substitutes for (R-1)/K as before 

(see Figs. 5.21 & 6.26 for real data). 

• Also generates realistic ranges of population 

fluctuations (Fig. 5.22). 

--- equation 5.18 (p.148) 


15. Continuous breeding - the logistic equation: 

• The model above was for discrete time steps described by a 

“difference” equation. 

• For continuously breeding populations (birth and death 

continuous) we need a continuous form of the model using a 

“differential” equation. 

• So for exponential population increase the rate of population 

increase is dN/dt and this speed of change is described in 

the absence of competition by: 

• dN/dt = rN 

• where r is the intrinsic rate of natural increase which is lnR or lnR o /T 

• So the continuous equivalent to Fig. 5.18 is shown in Fig. 5.23 and 

this is the differential form of the difference equation N t = N o R t 


16. Logistic limitation to a carrying capacity: 

• The differential form of N t+1 = N t R/1+(aN t ) in 

Fig 5.18 is given by: 

dN/dt = rN((K - N)/K) 

• This is the famous logistic equation. 

• This shows that exponential increase is 

decreased to K by the logistic term (K - N)/K 


17. Asymmetrical competition: 

• Large vs small Impatiens in a woodland 

(Fig. 5.26): 

• Small plants did not grow and so the asymmetry 

increased with time. 

• Root vs shoot competition in morning glory 

Fig. 5.27 (Weiner expt.): 

• Root competition for nutrients resulted in most 

biomass reduction, but shoot competition for 

light generated most size inequality and increase 

in asymmetry. 


Figure 5.1: Intraspecific competition among cave 

beetles for cave cricket eggs (a) scramble or 

exploitation, (b) contest or interference. 


Figure 5.2: Survivorship of red deer on the island of 

Rhum declines with lower birth rate and increased 

density. 


Figure 5.3: 

Density dependent mortality in flour beetles changes from (1) density 

independence, to (2) undercompensating density dependence, to (3) 

overcompensating density dependence. 


Figure 5.4: Exact compensation in trout fry. 


Figure 6.5 (3 rd ed.): Density dependent mortality in 

soybeans leading to overcompensation with time. 


Figure 5.7: Density dependent birth and 

mortality rates. 


Figure 5.8: 

Differences between births and deaths (a), generate recruitment (b), 

and population increase to a carrying capacity (c). 


Figure 5.11: 

Examples of S-shaped population increase for (a) Rhizopertha 

beetles on wheat, (b) wildebeest after a rinderpest outbreak, and (c) 

willows after myxomatosis killed rabbit herbivores. 


Figure 6.14 (3 rd ed.): 

Effects of density on growth rate and size in (a) Rana tigrina frogs 

and (b) reindeer. 


Figure 5.12: Effects of intraspecific competition on growth and 

final biomass of populations of the limpet Patella cochlear. 


Figure 6.16 (3 rd ed. – see Fig. 5.14, 4 th ed.): 

“Constant final yield” 

of plants sown at a 

range of densities 

for (a) subterranean 

clover, (b, c) the 

dune annual Vulpia 

fasciculata. 


Figure 5.15: Intraspecific competition in rye 

grass regulates the number of modules (tillers). 


Figure 5.16: 

k-values to describe 

variable density 

dependent mortality in 

(a) a dune annual, (b) 

almond moth, (c) fruit 

fly, and (d) the moth 

Plodia interpunctella. 


Figure 2.3: (Hassell, 1976) 


Figure 6.20, 3 rd ed., see Fig. 5.17, 4 th ed.): 

k-values to describe 

density dependent 

reductions in 

fecundity in 

(a) limpets, 

(b) cabbage root fly, 

(c) grass mirid, and 

(d) plantain. 


Figure 5.18: Difference equation model to describe 

population increase in species with discrete generations. 

BIOS 6150: Ecology - Dr. S. Malcolm. Week 3: Intraspecific Competition Slide - 33 

11 

12 

16

Figure 5.21: Different intensities of intraspecific 

competition incorporated in equation 6.19. 


Figure 6.26 (3 rd ed.): 

Equation 5.18 fitted 

to data for different 

beetle species in the 

laboratory (a, b, c & 

e), and winter moths 

in the field (d). 


Figure 5.22: Range of population fluctuations for 

(a) values of b and R and (b) population size against 

time, generated by equation 6.19. 


Figure 5.23: Exponential and sigmoidal models of 

population increase against time for continuous breeding 

- the logistic model of population growth. 


Figure 5.26: 

Asymmetric 

competition in the 

woodland plant 

Impatiens pallida in 

SE Pennsylvania. 


Figure 5.27: Root vs shoot competition in 

morning glory vines, Ipomoea tricolor.

Intraspecific Competition.

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