User:Carl Boettiger/Notebook/Stochastic Population Dynamics/2010/05/26

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Rethinking Beetles Noise

  • Noise in the larval class is damped by Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \partial_L f_L } and grows proportional to its intrinsic variation and the contribution of other classes through their derivatives of Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle f_L } , that is, Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \partial_E f_l } as well as the sum of its intrinsic rates (essentially whichever is larger). Taking E dynamics to be fast we might reduce to a continous time LPA model:
Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \begin{align} & \dot L = a_e \frac{bA - c_{ea} A - c_{el} L}{a_e + \mu_e} - a_l - \mu_l \\ & \dot P = a_l L - \mu_p P - a_p P \\ & \dot A = a_p P - \mu_a A \end{align} }

and the larval fluctuations are essentially:

Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \begin{align} \sigma^2_L &= \frac{\nu + \beta_L}{2 \partial_L f_L} \\ \nu &= \frac{ 2(\partial_A f_L)^2 \sigma_A^2 }{\partial_L f_L + \partial_A f_A} \\ \partial_A L &= \frac{a_e (b - c_{ea} ) }{a_e + \mu_e} \end{align} }

where Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \beta_i } is the intrinsic noise of the age class. Hence a class i which propagates large noise to another class j has a large Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \partial_i f_j } . If this term is a linear transition Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \lambda X_i } , then the same term appears in Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle f_i } and hence damps the noise Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \sigma_i^2 } and cancels out. Hence noise must propagate into a class through nonlinear transition rates OR through an asymmetry in the transition (i.e. the c_1, c_2 large noise example in the generalized crowley).


Compare to noise in Eggs:

Failed to parse (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://api.formulasearchengine.com/v1/":): {\displaystyle \sigma^2_E = \frac{ \frac{ (\sigma_L^2 c_{el} +\sigma_A^2 c_{ea} )E^2 }{\mu_A + \mu_L + a_L}+ \beta_E/2}{\mu_E + c_{ea} A + c_{el} L + a_e} }


Adding age delay to beetle dynamics

Current formulation has used exponential waiting times between stages. By subdividing the classes (increasing the system dimension size) and creating single jump within-state transitions, these become gamma-distributed waiting times. Adding ten steps to each phase and a little parameter fiddling introduces sustained oscillations. (Version-stable code).


Age delay.png


beetle_pars <- c(b=5, ue= 0, ul = 0.001, up = 0.00001, ua = 0.01, ae = 1.3, al = .1, ap = 1.5, cle = .2, cap = .1, cae = 5, V=100)

Xo[1] = 100

  • Implementation still needs trouble-shooting, variance dynamics don't seem to be being computed correctly. done
  • Adult class doesn't need multiple stages. done
  • Code should allow for a general k classes rather than a fixed 10 classes. done

and now we have noise in oscillatory, gamma-waiting model:

Oscillate noise.png


Misc / Code notes

  • R-evolution parallelizes the variance dynamics calculation (perhaps the matrix multiplication step?) and is probably responsible for the openmp parallelization working.
  • article on cloud computing vs grid. reminds me to include questions on cloud computing in the CSGF survey.
  • Should also take a closer read of the recent: Kendall BE, Wittmann ME. A stochastic model for annual reproductive success. The American naturalist. 2010;175(4):461-8. Available at: http://www.ncbi.nlm.nih.gov/pubmed/20163244.