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

download report

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

Sources of Fish Decline Habitat 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 N t+1 = N t + 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 ♀ born (= a cohort ) individuals newly • Determine the number of individuals that survive to each successive age (“x”) – S – The probability of survival from birth to age, “x”:

l

x

x

• The number of ♀ offspring produced per ♀ individual of age “x”:

m x

Life Table = collection of data on S x , l x , m x

• 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, R 0 = the number of ♀ progeny expected to accumulate during the entire lifetime of an average ♀ – Intrinsic growth rate, r – Reproductive Value ( V x ) = the expected number of future ♀ progeny for a ♀ of age “x” (relative to that of a newborn, = R 0 )

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