Sources of Fish Decline Habitat disruption Breeding areas Larval development areas Bottom structure.

Sources of Fish DeclineHabitat disruption

• Breeding areas

• Larval development areas

• Bottom structure

Not all patterns are negative

Population processes: aid to intelligent management?

• 1830’s – concerns about fluctuations in catch in North Sea

• Disbelief that humans could cause this• C. D. J. Petersen (Denmark) applied science

– mark-recapture to estimate population size– collected data on age-dependent reproduction– applied population model to predict connection

between fishing mortality & fish populations

• Criticized as “irrational” (not “profitable”)• Tested during WW I and WW II

What do we need to know?

• Demography: the study of processes affecting populations

• Processes adding to populations:– births, immigration

• Processes subtracting from populations:– death, emigration

• Base number of individuals • Whether the processes are constant through time

– could vary with season or other scales of time

– could vary with the density of individuals, which change over time

What if processes are constant?

• Population size in the next generation will depend on the base and the difference between births and deaths– assuming we have an isolated group of

individuals

Nt+1 = Nt + b – d

Exponential growth

What if processes vary with density?

• If populations get larger, what do you predict will happen to birth rates?

• If populations get larger, what do you predict will happen to death rates?

• How many individuals are added to the population when birth rates and death rates are equal?

“Logistic” growth pattern

Summary of population models

• The Logistic model of density dependence predicts maximal sustainable yield at ½ K

• “S-shape” curve of population growth may not be seen when– The response to density lags changes in the

environment– For populations with large excesses of births

(r>2) and where generations are distinct

Added realism: individuals vary in “b” and “d”

• Size (or age) influences– Reproductive capacity (# of offspring likely)– The risk of being eaten by a predator– The probability of being captured in a net

• Age-specific demographic processes– Fecundity– Survivorship

Age-specific parameters

• Start with a bunch of ♀ individuals newly born (= a cohort)

• Determine the number of individuals that survive to each successive age (“x”)

– Sx

– The probability of survival from birth to age, “x”: lx

• The number of ♀ offspring produced per

♀ individual of age “x”: mx

Life Table = collection of data on Sx, lx, mx

• We can then project how each cohort will contribute to the population through its lifetime

• Some values derived from a life table:– Net Reproductive Rate, R0 = the number of ♀

progeny expected to accumulate during the entire lifetime of an average ♀

– Intrinsic growth rate, r

– Reproductive Value (Vx) = the expected number of future ♀ progeny for a ♀ of age “x” (relative to that of a newborn, = R0)

The real world is not a set of simple equations

• Randomness is a factor– “Deterministic” models always follow the same

path given the same conditions– “Stochastic” models include chance

• How is this done?– Use an average value for a parameter– But for any generation, the value used can deviate

somewhat from that average– “Coefficient of Variation” and “distribution”

define the limits of deviation

Success of species-based management

What are the connections between food web and demographic approaches?

• What demographic parameters are influenced?

• Are models still useful and how?

An alternative to capture fisheries