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    Dear Christopher,<br>
    <br>
    there are probably multiple ways to do what you're describing, but I
    guess your modelling choices also depend on what you want to
    achieve. Is it the population trends you are interested in, and/or
    the population structure of non-flowering, male and female flowering
    individuals? If you are just interested in seed production and
    assume that pollen is not limiting, a size-dependent
    female-flowering probability in the F matrix might be enough. You
    would then have a size-structured model and no need for additional
    states. I guess you could even translate the stable size
    distribution to proportions males and females. However, if you do
    need males as a state, the options you describe should work: either
    model a series of conditional probabilities as functions of the
    previous state and size of individuals, or use multinomial models.
    The number of needed parameters will increase rapidly if you want
    both size and state transitions to depend on both previous size and
    previous stage. Or are you interested to include 'marriage
    functions' as well? Not sure if you could include those with just
    size as a continuous state variable and size-dependent male and
    female flowering probabilities. Anyone?<br>
    <br>
    As for IPMpack: we now do accomodate simple age x size IPMs, but I
    don't think you can make such a complicated size x flowering stage
    IPM with IPMpack functions only. Probably (as often when you want to
    include very complex life histories) you will have to develop code
    to construct your own IPM. However, it is often very useful to use
    bits and pieces of IPMpack to achieve this (e.g. by using IPMpack
    functions to create survival, growth and fecundity objects for
    subsets of individuals). <br>
    <br>
    best wishes,<br>
    Eelke<br>
    <br>
    <br>
    <div class="moz-cite-prefix">On 09-Jun-14 8:03 PM, Christopher
      Heckel wrote:<br>
    </div>
    <blockquote cite="mid:1402337029788.78084@hillsdale.edu" type="cite">
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          <p>Hello all,</p>
          <p><br>
          </p>
          <p><span dir="ltr"><font color="black"
                face="Calibri,Arial,Helvetica,sans-serif" size="3"><span
                  style="font-size:12pt;background-color:white;">I would
                  like to use IPMs to model the population dynamics of a
                  plant that is not only an iteroparous perennial, but
                  also exhibits size-dependent gender switching. 
                  Generally for this species (<em>Arisaema triphyllum</em>)
                  plants progress from non-flowering to male-flowering
                  to female-flowering over the course of several years
                  depending mainly on biomass accumulation.  However,
                  plants also can retrogress to previous states; for
                  example, a plant that was female in year t could
                  return as male in year t+1. 
                </span></font></span></p>
          <p><br>
          </p>
          <p>My questions:</p>
          <p><br>
          </p>
          <p>1. I think I need to set this up as a stage-size-dependent
            IPM but I am unsure how to allow individuals to move back
            and forth between stages.</p>
          <p><br>
          </p>
          <p>2. I can use polytomous logistic regression to find
            size-based transition probabilities among the three stages
            with greater power compared to a series of binomial logistic
            regressions.</p>
          <p>    a. Is polytomous log-reg appropriate for this?</p>
          <p>    b. Could IPMpack tools handle this?</p>
          <p><br>
          </p>
          <p>Thanks to all for any suggestions to help get me moving
            forward.</p>
          <p><br>
          </p>
          <p>Christopher Heckel<br>
          </p>
          <p><br>
          </p>
          <p>PhD candidate<br>
          </p>
          <p>University of Pittsburgh<br>
          </p>
          <p><br>
          </p>
          <p><br>
          </p>
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      <pre wrap="">_______________________________________________
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</pre>
    </blockquote>
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