Assignment: Using your flowchart and pseudocode developed last week for the larval bloater model in the Rice et al 1993 paper, create python code to simulate the results observed in the paper, except you will start with 500 individual larvae instead of 4000. Specifically, you will recreate figure 1 (using the initial growth rates only), you will recreate table 1 for survival rates (just from one simulation, not 30, so you will not need a standard deviation) and will also create a second table that is setup the same way as table 1, but reports the final lengths. Write a paragraph to explain the simulation results (in your own words), what does varying growth rate mean for the survival of a cohort of larval bloaters? How do your simulations compare to the Rice Paper?Please include your code as an
Project 1 – Individual Based Model. Due March 18 Midnight Assignment: Using your flowchart and pseudocode developed last week for the larval bloater model in the Rice et al 1993 paper, create python code to simulate the results observed in the paper, except you will start with 500 individual larvae instead of 4000. Specifically, you will recreate figure 1 (using the initial growth rates only), you will recreate table 1 for survival rates (just from one simulation, not 30, so you will not need a standard deviation) and will also create a second table that is setup the same way as table 1, but reports the final lengths. Write a paragraph to explain the simulation results (in your own words), what does varying growth rate mean for the survival of a cohort of larval bloaters? How do your simulations compare to the Rice Paper? Please include your code as an appendix. Production, Marine Larval Retention or Dispersal, and Recruitment of Amphidromous Hawaiian Gobioids: Issues and Implications Rice Model • 60 day simulation • Single cohort of larval prey • Like a bloater • Initial length of 12 mm • Growth rate (mm/day) • Predators • Like a yearling alewife • 90 mm • Eaten • Encountered, attacked and captured • Combination is vulnerability Predation • Encountered, attacked, captured • Combination is vulnerability • Shape is controversial • Encounter and attack assumed constant • Because constant predator size • Set to 0.2 • Capture decreases with increasing prey to predator sizes • P(cap) = -0.33 + 0.15*length ratio • Monotonically decreasing vulnerability with prey size • See humps for low mobility prey or slower moving ambush predators P( ca pt ur e) Length Ratio Computations • Number of larvae • Initial length • Growth rate • Each day • Compare random number to 0.2 • if less then compare random number to P(cap) • if less then eaten • Update larva length • All normal distributions • Growth truncated at 0 and 1 Simulations • 4000 initial larva • Sometimes 10,000 • 1000 with no predation • 3 growth rates with 2 levels of variability • Mean: 0.2, 0.4, 0.6 mm/day • SD: 0.04, 0.08, 0.16 mm/day • Without and with predation Conclusions • Mean growth rate and growth rate variation among individuals interact strongly with size- dependent mortality to affect the number, growth rates and lengths of survivors • Survivors represent a small fraction of atypical individuals • Vast mortality experienced by a cohort is random, selection occurred after 95% of the mortality had taken place RiceModel Predation Computations Simulations Slide Number 5 Slide Number 6 Slide Number 7 Conclusions