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