Population dynamics
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Transcript of Population dynamics
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POPULATION DYNAMICS
Zoo 511 Ecology of Fishes
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Today’s goals
Understand why and how population dynamics are important in fisheries ecology
Gain experience in a variety of mark-recapture methods
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“A population is a group of fish of the same species that are alive in a defined area at a given time” (Wootton 1990)
Population dynamics: changes in the number of individuals in a population or the vital rates of a population over time
What are population dynamics?
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Major role of ecology: understand change
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Why study population dynamics?
Often most relevant response to ecosystem manipulation/perturbation
Endangered species (population viability analysis, PVA)
Fisheries management (sustainable yield)
Understand ecosystem dynamics and ecological processes
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Why study population dynamics?
Often most relevant response to ecosystem manipulation/perturbation
Endangered species (population viability analysis, PVA)
Fisheries management (sustainable yield)
Understand ecosystem dynamics and ecological processes
PVA: Modeling the probability that a population will go extinct or drop below the minimum viable population size within a given number of years.
Atlantic salmon PVAFrom Legault 2004
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Why study population dynamics?
Often most relevant response to ecosystem manipulation/perturbation
Endangered species (population viability analysis, PVA)
Fisheries management (sustainable yield)
Understand ecosystem dynamics and ecological processes
from Hilborn and Walters 1992
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Why study population dynamics?
Often most relevant response to ecosystem manipulation/perturbation
Endangered species (population viability analysis, PVA)
Fisheries management (sustainable yield)
Understand ecosystem dynamics and ecological processesWhen do ecological shifts occur?Are they stable?
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How do populations change?
Population
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Density Dependence
Population Density
Rate of Change (per capita)
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Rate of population increase
Density independent
Density dependent
per
cap
ita
an
nu
al in
crease
N
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Small group exercise
Time
Pop
ulat
ion
dens
ity
?
Time
Pop
ulat
ion
dens
ity?
Density-dependent Density-independent
Population starts at low density.What happens to density over time
under density-dependent rate of increase?
What happens if rate of increase is density-independent?
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Logistic population growth
K= carrying capacityr0 = maximum rate of increase
dN/dt=r0N(1-N/K)
per
cap
ita a
nn
ual
incr
ease
NK
r0
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R-selected vs. K-selected
r-selected K-selected
Environment variable and/or unpredictable
constant and/or predictable
Lifespan short long
Growth rate fast slow
Fecundity high low
Natural mortality high low
Population dynamics unstable stable
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Nt+1 = Nt + B – D + I – E
B = births D = deaths I = immigration E = emigration
How do populations change?
DeathsPopulationBirths
Emigration
Immigration
Stocking
Angling
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Survival
Predation Disease Prey availability Competition for food Harvest
“Natural Mortality”
Age 1 Age 2 Age 3
Year 1
N1,1 N1,2 N1,3
Year 2
N2,1 N2,2 N2,3
Year 3
N3,1 N3,2 N3,3
S
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Survival
Eggs and larvae suffer the largest losses
HATCH Recruit!
2 cohorts each produce 10,000,000 eggs
90.5% survivorship/day yields 24,787 survivors at 60 days
95.1% survivorship/day yields 497,871 survivors at 60 days
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Recruitment
Can mean many things! Number of young-of-year (YOY) fish
entering population in a year Number of fish achieving age/size at which
they are vulnerable to fishing gear Somewhat arbitrary, varies among
populations Major goal of fish population dynamics:
understanding the relationship between stock size and recruitment
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What determines recruitment?-Stock size (number and size of females)
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What determines recruitment?
spawning stock biomass (SSB)
Ricker
Beverton-Holt
Density-independent
From: Wootton (1998). Ecology of teleost fishes.
Rec
ruit
men
t
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The problem? Stochasticity!
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From: Cushing (1996). Towards a science of recruitment in fishpopulations
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Highly variable recruitment results in naturally very variable catches
From: Jennings, Kaiser and Reynolds (2001). Marine Fisheries Ecology
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Population Abundance
On rare occasions, abundance can be measured directly Small enclosed systems Migration
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Catch per unit effort (CPUE)
Very coarse and very common index of abundance
Effort= 4 nets for 12 hours each= 48 net hours
Catch= 4 fish
CPUE=4/48=0.083
Effort= 4 nets for 12 hours each= 48 net hours
Catch=8 fish
CPUE=8/48=0.167
We conclude population 2 is 2X larger than population 1
1
2
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Population abundance
Density estimates (#/area) Eggs estimated with quadrats Pelagic larvae sampled with modified
plankton nets Juvenile and adult fish with nets, traps, hook
and line, or electrofishing Density is then used as index of
abundance, or multiplied by habitat area to get abundance estimate
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Depletion methods
*
*
*
*
N
Time (or pass)
Closed populationVulnerability constant for each passCollection efficiency constantOften not simple linear regression
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Mark recapture
M=5 C=4 R=2
N=population size=????
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Modified Petersen method
Assumptions: Closed population Equal catchability in first sample Marking does NOT influence catchability
Marked and unmarked fish mix randomly Mortality rates are equal
Marks are not lost
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How to avoid violation of assumptions? Two sampling gears Distribute marked individuals widely;
allow time for mixing Can be separated into different groups
Length Sex Geographic regions
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How many to mark/recapture? Requires some knowledge of population
size! Trade-off between precision and sample
size Population of 10,000: Mark 400 and
examine 600 for +/- 50% OR mark 1,000 and examine 1,500 for +/- 10%
Trade-off between marked and recapture sample size Population of 10,000: Mark 1,000 and
examine1,500 OR Mark 4,500 and examine 500
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Schnabel method
Closed population Equal catchabilty in first sample Marking does NOT influence catchability Multiple recaptures
Easier to pick up on violation of assumptions
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Jolly Seber method
Open populations Allows estimation of births and deaths
Three or more sampling periods needed Equal catchability of all individuals in all
samples Equal probability of survival Marks are not lost Sampling time is negligible compared to
intervals between samples
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Importance of uncertainty
Confidence intervals Long-term frequency, not probablity! 95% confidence intervals if you repeated
procedure an infinite number of times, 95% of the time the interval you create would contain the “true” value
Precision vs. accuracy
xx
x xx
x
x
x
x
xxxx x
xxxx
Accurate, not precise Not accurate, precise Accurate, precise
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Lets count some beans!