background knowledge expected

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Background knowledge expected Population growth models/equations exponential and geometric logistic Refer to 204 or 304 notes Molles Ecology Ch’s 10 and 11 Krebs Ecology Ch 11 Gotelli - Primer of Ecology (on reserve)

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Background knowledge expected. Population growth models/equations exponential and geometric logistic. Refer to 204 or 304 notes Molles Ecology Ch’s 10 and 11 Krebs Ecology Ch 11 Gotelli - Primer of Ecology (on reserve). The ecology of small populations. - PowerPoint PPT Presentation

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Page 1: Background knowledge expected

Background knowledge expected

Population growth models/equations

exponential and geometric

logistic

Refer to

204 or 304 notes

Molles Ecology Ch’s 10 and 11

Krebs Ecology Ch 11

Gotelli - Primer of Ecology (on reserve)

Page 2: Background knowledge expected

Habitat loss Pollution Overexploitation Exotic spp

Small fragmented isolated popn’s

InbreedingGenetic Variation

Reduced N Demographic stochasticity

Env variation

CatastrophesGenetic processes

Stochastic processes

The ecology of small populations

Page 3: Background knowledge expected

How do ecological processes impact small populations?

Stochasticity and population growth

Allee effects and population growth

Outline for this weeks lectures

Page 4: Background knowledge expected

Immigration +Emigration -

Birth (Natality) +

Death (Mortality)

-

Nt+1 = Nt +B-D+I-E

Population Nt

Demography has four components

Page 5: Background knowledge expected

Exponential population growth(population well below carrying capacity, continuous

reproduction closed pop’n)

Change in population at any time

dN = (b-d) N = r N where r =instantaneous rate of increasedt

∆t

∆N

Cumulative change in population Nt = N0ert

N0 initial popn size,

Nt pop’n size at time t

e is a constant, base of natural logs

Page 6: Background knowledge expected

Trajectories of exponential population growth

r > 0r = 0r < 0

N

t

Trend

Page 7: Background knowledge expected

Geometric population growth(population well below carrying capacity, seasonal reproduction)

Nt+1 = Nt +B-D+I-E

∆N = Nt+1 - Nt

= Nt +B-D+I-E - Nt

= B-D+I-E

Simplify - assume population is closed; I and E = 0

∆N = B-D

If B and D constant, pop’n changes by rd = discrete growth factor

Nt+1 = Nt +rd Nt

= Nt (1+ rd) Let 1+ rd = , the finite rate of increase

Nt+1 = Nt

Nt = t N0

Page 8: Background knowledge expected

DISCRETE vs CONTINUOUS POP’N GROWTH

Reduce the time interval between the teeth and the

Discrete model converges on continuous model

= er or Ln () = r

Following are equivalent r > 0 > 1

r = 0 = 1

r< 0 < 1

Trend

Page 9: Background knowledge expected

Geometric population growth(population well below carrying capacity, seasonal reproduction)

Nt+1 = (1+rdt) Nt

= (1+rdt) (1+rdt-1) Nt-1

= (1+rdt) (1+rdt-1) (1+rdt-2) Nt-2

= (1+rdt) (1+rdt-1) (1+rdt-2) (1+rdt-3) Nt-3

Add dataNt-3= 10rdt = 0.02

rdt-1 = - 0.02rdt-2 = 0.01rdt-3 = - 0.01

What is the average growth rate?

Page 10: Background knowledge expected

Geometric population growth(population well below carrying capacity, seasonal reproduction)

What is average growth rate?

= (1+0.02) + (1-0.02) + (1+0.01) + (1-0.01) = 14

Arithmetic mean

Predict Nt+1 given Nt-3 was 10

Page 11: Background knowledge expected

Geometric population growth(population well below carrying capacity, seasonal reproduction)

What is average growth rate?

Geometric mean = [(1+0.02) (1-0.02) (1+0.01) (1-0.01)]1/4 = 0.999875

KEYPOINTLong term growth is determined by the geometric not the arithmetic meanGeometric mean is always less than the arithmetic mean

Calculate Nt+1 using geometric mean

Nt+1 = 4 x 10

(0.999875)4 x10 = 9.95

Nt+1 = (1+0.02) (1-0.02) (1+0.01) (1-0.01) 10= 9.95

Page 12: Background knowledge expected

DETERMINISTIC POPULATION GROWTH

For a given No, r or rd and t The outcome is determined

Eastern North Pacific Gray whales Annual mortality rates est’d at 0.089Annual birth rates est’d at 0.13

rd=0.13-0.89 = 0.041 = 1.04

1967 shore surveys N = 10,000

Estimated numbers in 1968 N1= N0 = ?

Estimated numbers in 1990 N23= 23 N0 = (1.04)23.

10,000 = 24,462

Page 13: Background knowledge expected

DETERMINISTIC POPULATION GROWTH

For a given No, r or rd and t The outcome is determined

Page 14: Background knowledge expected

Population growth in eastern Pacific Gray Whales

- fitted a geometric growth curve between 1967-1980

- shore based surveys showed increases till mid 90’s

In USPacific Gray Whales were delisted in 1994

Page 15: Background knowledge expected

Mean r

\

SO what about variability in r due to good and bad years?ENVIRONMENTAL STOCHASTICITY

leads to uncertainty in racts on all individuals in same way

b-dBad 0 Good

Variance in r = 2e = ∑r2 -

(∑r)2

NN

Page 16: Background knowledge expected

Population growth + environmental stochasticity

Ln N

t

Deterministic1+r= 1.06, 2

e = 0

1+r= 1.06, 2e = 0.05

Expected

Expected rate of increase is r- 2e/2

Page 17: Background knowledge expected

Predicting the effects of greater environmental stochasticity

Onager (200kg)

Israel - extirpated early 1900’s

- reintroduced 1982-7

- currently N > 100

RS varies with Annual rainfall

Survival lower in droughts

Page 18: Background knowledge expected

Global climate change (GCC) is expected to

----> changes in mean environmental conditions

----> increases in variance (ie env.

stochasticity)

meandrought < 41 mm

Pre-GCC Post-GCC

Mean rainfall is the same BUT

Variance and drought frequency is greater in “post GCC”

Data from Negev

Page 19: Background knowledge expected

Simulating impact on populations via rainfall impact on RS Variance in rainfall

Low High

Number of quasi-extinctions

= times pop’n falls below 40

Page 20: Background knowledge expected

Simulating impact on populations adding impact on survival

CONC’nEnvironmental stochasticity can influence extinction risk

Page 21: Background knowledge expected

But what about variability due to chance events that act on individuals

Chance events can impactthe breeding performanceoffspring sex ratioand death of individuals

---> so population sizes can not be predicted precisely

Demographic stochasticity

Page 22: Background knowledge expected

Demographic stochasticity

Dusky seaside sparrowsubspeciesnon-migratorysalt marshes of southern Florida

decline DDTflooding habitat for mosquito controlHabitat loss - highway construction

1975 six left

All male

Dec 1990 declared extinct

Page 23: Background knowledge expected
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Extinction rates of birds as a function of population size over an 80-year period

0

30

60

1 10 100 1000 10,000

** *

**

***

10 breeding pairs – 39% went extinct10-100 pairs – 10% went extinct1000>pairs – none went extinct

*

Population Size (no. pairs)

% Extinction

Jones and Diamond. 1976. Condor 78:526-549

Page 27: Background knowledge expected

random variation in the fitness of individuals (2

d)

produces random fluctuations in population growth rate that are inversely proportional to N

demographic stochasticity = 2d/N

expected rate of increase is r - 2d/2N

Demographic stochasticity is density dependant

Page 28: Background knowledge expected

How does population size influence stochastic processes?

Demographic stochasticity varies with N

Environmental stochasticity is typically independent of N

Long term data fromGreat tits in Whytham Wood, UK

Page 29: Background knowledge expected

Partitioning variance

Species 2d 2

e Swallow 0.18 0.024Dipper 0.27 0.21Great tit 0.57 0.079Brown bear 0.16 0.003

in large populations N >> 2d / 2

e

Environmental stochasticity is more importantDemographic stochasticity can be ignored

Ncrit = 10 * 2d / 2

e (approx Ncrit = 100)

Page 30: Background knowledge expected

Stochasticity and population growth

N0= 50 = 1.03

Simulations - = 1.03, 2e = 0.04, 2

d = 1.0

N* = 2d /4

r - (2e /2)

N* Unstable eqm below which pop’n moves to

extinction

Page 31: Background knowledge expected

Environmental stochasticity-fluctuations in repro rate and probability of mortality imposed by good and bad years-act on all individuals in similar way-Strong affect on in all populations

Demographic stochasticity-chance events in reproduction (sex ratio,rs) or survival acting on individuals- strong affect on in small populations

Catastrophes -unpredictable events that have large effects on population size (eg drought, flood, hurricanes)-extreme form of environmental stochasticity

SUMMARY so far

Stochasticity can lead to extinctions even when the mean population growth rate is positive

Page 32: Background knowledge expected

Key points

Population growth is not deterministic

Stochasticity adds uncertainty

Stochasticity is expected to reduce population growth

Demographic stochasticity is density dependant and less important when N is large

Stochasticity can lead to extinctions even when growth rates are, on average, positive