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What are some logic behind optimality modeling?
-Natural selection generates behavioral responses, maximizing fitness by balancing benefits against cost ( Evolutionary Economics)
What are some advantages associated with optimality modeling?
- -makes assumptions explicit
- - generating testable predictions
- - if the model doesn't fit they can suggest new hypothesis
what are some disadvantages of optimality modeling?
- behavior may not always be optimal
What are the elements of optimality model?
- -Decision variable (Behavioral option such as pursuing or not pursuing the prey)
- -currency( must correlate with fitness such as maximizing rate of net energy intake E/t)
- -assumption and constraints
- simplify to enable solution, but capture essence of problem
- intrinsic ( limitation in ability)
- extrinsic( imposed by environment, prey density of presence of predator)
what are some thoughts associated when Lion encounters Gazelles or Water buffalo?
- -pursue pray or not should it attack or search for another prey
- - maximize rate of energy intake
- - assumptions to consider is if prey are encountered sequentially, time spent searching and handling are independent, lions have perfect knowledge they know the profitability and density of prey.
what are variables associated with prey choice model?
- -E1 is energy provided by prey 1
- -h1 is time required to catch and consume each prey type
- -s1 is search time required to find prey. Search time depends on relative abundance of prey)
- - profitability = E/h
when is it useful for predator to eat the prey?
- current prey can be caught and eaten only if energy gained exceeds that expected if searching for the alternative.
- E Current/ h current > E other/ (S other+ h other)
- If Gazelle encountered
- E tg/h tg > E wb/ (S wb+ h wb) so S wb > (E wb / E tg)(h tg)- h wb
what are some predictions that can be made for prey choice model?
- always eat the most profitable prey type
- include the less profitable prey if S1> (e1/e2)h2- h1 where e1>e2
- also note that inclusion of less profitable prey does not depend on its abundance ( dictates search time)
- specialist in prey type 1 should switch and become more generalist both suddenly and completely when prey type one becomes rare.
what was the optimal diet intake or trout fishes?
Around 25 kj
what did the experiment on great tits and meal worms suggested?
In low density area , where the large prey and small prey frequency were the same, both were consumed equally, where as in the high density 3 there was a smaller portion of the large pray and larger portion of small prey , it was predicted that they would most likely consume the bigger prey , the result suggested the same thing but it was a little below predicted.
how can we decide to include a prey item or not when encountered?
- to include prey the profitability must exceed the net profitability of all higher rank preys.
- E3/h3> (e1+e23)/ (s1+h1+s2+h2)
what are reasons for partial preferences?
- -mistaking prey type
- -lack of complete information
- -simultaneous encounter with multiple prey
- - simple sampling rule for estimation encounter rate
- -variation in prey size or difficult to process prey
what part do red knots spend the most time on why looking and catching a prey
how does energy in a patch work ?
as time spend in a patch goes by gain in food increases to a certain point and then starts leveling off.
what are some components associated with patch choice model?
- when is it time to leave
- maximizing profitability
- time spent searching in patch and traveling between patches are independent
- foragers encounter patches sequentially
- energy gain in a patch and patch location are known
- also energy gain in patches shows diminishing return
what is the relationship between optimal search time in a patch and traveling between patches?
optimal search time in a patch is greater when travel time between patches is longer
what should be done if optimality fails?
- consider different currency ( maximize time and efficiency and minimize risk of starvation)
- include additional constraints (predation risk, min nutrient requirements and avoiding toxins)
- consider simpler decision rules