Ch. 19 Population Ecology

1. Ch. 19 Population Ecology

2. Population Ecology is the Study of How and Why Populations Change • A population is a group of individuals of a single species that occupy the same general area • Individuals in a population • rely on the same resources • are influenced by the same environmental factors • are likely to interact and breed with one another

3. Population Ecology is the Study of How and Why Populations Change • Population ecology is concerned with • the changes in population size • factors that regulate populations over time • Populations • increase through birth and immigration to an area • decrease through death and emigration out of an area.

4. Density and Dispersion Patterns are Important Population Variables • Population density is the number of individuals of a species per unit area or volume • Examples of population density include • the number of oak trees per square kilometer in a forest or • the number of earthworms per cubic meter in forest soil • Ecologists use a variety of sampling techniques to estimate population densities

5. Density and Dispersion Patterns are Important Population Variables • Within a population’s geographic range, local densities may vary greatly • The dispersion pattern of a population refers to the way individuals are spaced within their area

6. Density and Dispersion Patterns are Important Population Variables • Dispersion patterns can be clumped, uniform, or random • In a clumped dispersion pattern • resources are often unequally distributed • individuals are grouped in patches.

7. Density and Dispersion Patterns are Important Population Variables • In a uniform dispersion pattern, individuals are • most likely interacting and equally spaced in the environment

8. Density and Dispersion Patterns are Important Population Variables • In a random dispersion pattern, individuals are spaced in an unpredictable way, without a pattern, perhaps resulting from random dispersal of windblown seeds

9. Life Tables Track Survivorship in Populations • Life tables track survivorship, the chance of an individual in a given population surviving to various ages • Survivorship curves plot survivorship as the proportion of individuals from an initial population that are alive at each age • There are three main types of survivorship curves: • Type I survivorship curves • High survival in early and middle life, followed by a rapid decline in survival later in life • Typical of species that produce few offspring but care for them well • Ex’s. humans, large mammals

10. Life Tables Track Survivorship in Populations • Type II curves • Constant mortality rate/survival is experienced regardless of age; so survivorship is independent of age • Ex. birds, some lizards, rodents • Type III curves • Low survivorship for the very young followed by high survivorship for those individuals that survive to a certain age • Characteristic of species that produce a large number of offspring • Ex. most marine invertebrates, fish, sea turtles

11. 100 I 10 II Percentage of survivors (log scale) 1 III 0.1 Percentage of maximum life span

12. Few large offspring,low mortalityuntil old age I Figure 36.UN01 Percentage of survivors II Many smalloffspring,high mortality III Percentage of maximum life span

13. Population Growth Predicted by the Exponential Growth Model • Exponential growth model • The rate of population increase under ideal conditions is called exponential growth • It can be calculated using G = rN where • G is the growth rate of the population • N is the population size, and • r is the per capita rate of increase (the average contribution of each individual to population growth). • Eventually, one or more limiting factors will restrict population growth

15. Exponential Population Growth 500 450 400 350 300 250 200 150 100 50 0 G = rN Population size (N) 0 1 2 3 4 5 6 7 8 9 10 11 12 Time (months)

16. Population Growth Predicted by the Logistic Growth Model • Logistic growth model • Is a description of idealized population growth that is slowed bylimiting factorssuchas an increase in population size • Includes a new expression (K) that describes the effect of limiting factors on an increasing population size • K stands for carrying capacity, the maximum population size a particular environment can sustain.

17. 10 8 6 4 2 0 Breeding male fur seals(thousands) 1915 1925 1935 1945 Year Data from K. W. Kenyon et al., A population study of theAlaska fur-seal herd, Federal Government Series:Special Scientific Report—Wildlife 12 (1954).

18. G=rN A comparison of Exponential and Logistic Growth Models (K−N) Number of individuals (N) G=rN K K 0 Time

19. Multiple Factors May Limit Population Growth • The logistic growth model predicts that population growth will slow and eventually stop as population density increases • Density-dependent factors = limiting factors as a result of increased density • Ex. Intraspecific competition- competition between individuals of same species for limited resources (food, nutrients, nesting sites)

20. 6 5 4 3 2 1 0 Figure 36.5a-0 Mean number of offspring per female 0 10 20 30 40 50 60 70 80 Density of females Data from P. Arcese et al., Stability, Regulation, and the Determination of Abundancein an Insular Song Sparrow Population. Ecology 73: 805–882 (1992).

21. Kelp perch 1.0 0.8 0.6 0.4 0.2 0 Figure 36.5b-0 Proportional mortality 0 10 20 30 40 50 60 Kelp perch density (number/plot) Data from T. W. Anderson, Predator Responses, Prey Refuges, and Density-DependentMortality of a Marine Fish, Ecology 82: 245–257 (2001).

22. Some Populations have “boom-and-bust”Cycles • Some populations fluctuate in density with regularity • Boom-and-bust cycles may be due to • food shortages • predator-prey interactions • Ex. populations of the snowshoe hare and the lynx based on the number of pelts sold by trappers in northern Canada to the Hudson Bay Company over a period of nearly 100 years

23. Figure 36.6-0 160 Snowshoe hare 120 9 Lynx Hare population size(thousands) Lynx population size(thousands) 80 6 40 3 0 0 1925 1875 1850 1900 Year Data from C. Elton and M. Nicholson, The ten-year cycle in numbers of the lynx in Canada, Journal of AnimalEcology 11 : 215–244 (1942).

24. Some Populations have “boom-and-bust” Cycles • But what causes the boom-and-bust cycles of snowshoe hares? • One hypothesis proposed that when hares are abundant, they overgraze their winter food supply, resulting in high mortality. • Another hypothesis attributed hare population cycles to excessive predation.

25. Evolution Shapes Life Histories • The traits that affect an organism’s schedule of reproduction and death make up its life history • Key life history traits include • age of first reproduction • frequency of reproduction • number of offspring • amount of parental care

26. Evolution Shapes Life Histories • Populations with r-selected life history traits • grow rapidly in unpredictable environments, where resources are abundant • have a large number of offspring that develop and reach sexual maturity rapidly • offer little or no parental care

27. Evolution Shapes Life Histories • Populations with K-selected traits • tend to be long-lived animals (such as bears and elephants) that develop slowly and produce few, but well-cared-for, offspring • maintain relatively stable populations near carrying capacity • Most species fall between these two extremes