Populations Outline: Properties of populations Population growth Intraspecific population Metapopulation Readings: Ch. 9, 10, 11, 12

Definition Population is a group of individuals of the same species that inhabit a given area

Unitary organisms

Modular organisms

genet ramet

Distribution of a population

Red maple

Distribution of a population Moss (Tetraphis pellucida)

Abundance versus Population density

Patterns of dispersion

Effect of scale on pattern of dispersion

Populations have age structure

Determining age

wild turkeyquail grey squirelbat Determining age

Dispersal Movement of individuals in space Moving out of subpopulation = emigration Moving into a subpopulation = immigration Moving and returning= migration

Yellow-poplar

Ring-necked duck Gray whale

Gypsy-moth

POPULATION GROWTH

Darwin’s 1 st observation: All species have such great potential fertility that their population size would increase exponentially if all individuals that are born reproduce successfully.

Example of exponential growth: the ring-necked pheasant, Phasianus colchicus Native to Eurasia 1937: Eight birds introduced to Protection Island (Washington state) 1942: Population had increased to 1,325 birds (a 166-fold increase!)

 N/  t = (b - d) N t

Population Growth Models Assume no immigration or emigration Let N = population size Let  N/  t = change in population size/unit time = total # births - total # deaths Let mean birth rate per individual = b = # births / individual / unit time Let mean death rate per individual = d = probability of death for an individual / unit time  N/  t = bN - dN Let r = b-d

Population Growth Models r = instantaneous rate of increase a.k.a. per capita rate of increase Calculus notation is commonly used;  N/  t = dN/dt If r > 0, population will increase exponentially at rate, dN/dt, = rN For an exponentially growing population, the number of individuals at time t, N t = N 0 e (rt) where N o = initial population size and e = base of natural logarithms

Exponential growth model: N t = N 0 e (rt)

St. Paul reindeer

Life tables cohort - all individuals born within a period cohort life table – survivorship of a cohort over time

l x = represents the probability at birth of surviving to any given age Life tables

d x = represents the age-specific mortality Life tables

q x = represents the age-specific mortality rate Life tables

Mortality curves

sedum Mortality curves

Survivorship curves - plot of l x vs. time

Red deer

Theoretical survivorship curves

What happened to population in 1940s?

Human population growth

Darwin’s 2 nd observation: Populations tend to remain stable in size, except for seasonal fluctuations Darwin’s 3 rd observation: Environmental resources are limited

In real world, populations don’t increase exponentially for very long --> run out of resources An N increases, b decreases and/or d increases

Population limiting factors Density-dependent: effect intensifies as N increases. E.g.: 1.Intraspecific competition – Between members of same species 2.Toxic waste accumulation – E.g. yeast cells: produce ethanol as by- product of fermentation (see next slide) 3.Disease – Spreads more easily in crowded environments

Effect of crowding on birth rate

Effect of crowding on survivorship

Intraspecific population regulation

Carrying capacity, K = maximum number of individuals that a particular environment can support Take into account by the Logistic Growth Equation, dN/dt = rN (1-N/K)

Logistic model

Exponential vs. logistic model Gray squirrel

How good is the logistic model? Describes growth of simple organisms well, e.g. Paramecium in a lab Water fleas (Daphnia spp.): population initially overshoots K until individuals use up stored lipids --> crash down to K Song sparrows: populations crash frequently due to harsh winter conditions –N never have time to reach K –Population growth not well described by the logistic model

Life History Strategies When N is usually << K, natural selection favors adaptations that increase r --> lots of offspring = r selection –E.g. species that colonize short-lived environments When N is usually close to K, better to produce fewer, “better quality” (i.e. more competitive) offspring = K selection E.g species that live in stable, crowded environments

Density dependence

with Allee effect

American ginseng Density dependence with Allee effect

Types of competition Competition: individuals use a common resource that is in short supply relative to the number seeking it Intraspecific vs. interspecific Scramble vs. contest Exploitation vs. interference

Density effect on growth

Horseweed Density effect on growth Self thinning

Density effect on reproduction

Territoriality

Grasshopper sparrow Ammodramus savannarum

Banding study in California: 24% of current territory holders had been floaters for 2- 5 yrs. before acquiring a territory. White-crowned sparrow, Zonotrichia leucophrys

Uniform distribution of plants occurs due to the development of resource depletion zones around each individual

Population limiting factors Density-independent: effect does not depend on N. –E.g. weather / climate –Thrips insects: Feed on Australian crops (pest) Population growth very rapid in early summer Drops in late summer due to heat, dryness --> N never has time to get close to K

Density-independent factors

DRY Turbid WET Clear Density-independent factors

e.g. Dungeness crabs Density-dependent factors: competition; cannibalism Density-independent factors: water temperature

Metapopulations a population of populations Chapter 12

Metapopulation: A group of moderately isolated populations linked by dispersal

Criteria for a metapopulation 1.Habitat occurs in discrete patches 2.Patches are not so isolated as to prevent dispersal 3.Individual populations have a chance of going extinct 4.The dynamics of populations in different patches are not synchronized – i.e., they do not fluctuate or cycle in synchrony

Metapopulation dynamics: spatial scales 1.Local (within-patch) 2.Metapopulation (regional)  Shifting mosaic of occupied and unoccupied patches

Checkerspot butterfly

Levin’s model of metapopulation dynamics E - subpopulation extinction rate = eP e – probability of a patch going extinct/unit time P – proportion of occupied patches C – colonization rate = mP (1-P) m – dispersal rate (1-P) – unoccupied habitats

E = C equilibrium point, Where 0 = [mP(1-P)] - eP If C>E, P increases; If C<E, P decreases P equilibrium = 1-e/m

Bush cricket

Larger patches have larger populations (and therefore lower risk of extinction)

Skipper butterfly

Effect of habitat heterogeneity

Mainland-island population structure: one large population (low extinction risk) provides colonists for many small populations (high risk) Rescue effect: island recolonized from “mainland” High quality / permanent population = source population Temporary patches = sink populations Checker-spot butterfly

Skipper butterfly