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Hi Eelke,<br>
<br>
Thank you. I am interested in the population structure of
non-flowering, male, and female individuals because the multiple
populations that I have studied have very different sex-ratios. I
don't think at this time I need to include marriage functions
because seed production in this species can be pollen limited even
when there are high densities of males.<br>
<br>
I've begun writing code with the series of conditional probabilities
and there certainly are many parameters. I may be posting more
specific questions soon.<br>
<br>
Cheers,<br>
<br>
Christpher<br>
<div class="moz-cite-prefix">On 6/9/2014 5:37 PM, Eelke Jongejans
wrote:<br>
</div>
<blockquote cite="mid:53962907.3060307@science.ru.nl" type="cite">
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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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