Hi,
I am dealing with an analysis of local survival and dispersal of a bird population marked in site A in spring, and resighted in winter in site A, site B and site C.
I have 16 breeding season when chicks (only chicks) are marked and 16 correspondent wintering seasons.
When chicks are captured (and marked), some of them are sexed, so that I have sex uncertainty in my data set and this is also why I chose to use E-SURGE.
I have some difficulties on how to build the models.
I have defined 8 states (apart from dead state):
1-female chick site A (--> breeding seasons)
2-male chick site A (--> breeding seasons)
3-female site A (--> wintering seasons)
4-male site A (--> wintering seasons)
5-female site B (--> wintering seasons)
6-male site B (--> wintering seasons)
7-female site C (--> wintering seasons)
8-male site C (--> wintering seasons)
Moreover, there are four other possible events:
9-unknown sex chick site A (--> breeding seasons)
10-unknown sex site A (--> wintering seasons)
11-unknown sex site B (--> wintering seasons)
12-unknown sex site C (--> wintering seasons)
My data set is arranged in headed format (to allow this high number of events) and the first column represent the 1st breeding season, the second the 1st wintering season, the third the 2nd breeding season, the fourth the 2nd wintering season and so on.
In the 4th (t 7) and 10th (t 19) breeding seasons there was no breeding at all and no chicks were marked. Also, individuals in site B and C were not resighted before 3rd wintering season (t 6) and individuals in site B were not resighted in the 4th and 5th (t 8, 10) wintering season.
These are my matrices in GEPAT:
Initial State:
Really I would have set 9 columns (as there are 9 states including the dead state) but it appears a window saying "Dimensions of pattern matrices not allowed!!!"
Survival:
Transition:
Capture:
State Assignment:
Sometimes, like in this case, due to particular data structure or due to presence/absence of some specific data, I don’t understand how to deal with events for the parameters estimate both in GEMACO and in IVFV fixing parameters.
Two examples:
1) about the particular data structure, given the above-explained structure of data, events 1, 2 and 9 are present only in odd sessions and, viceversa, the others only in even sessions.
2) about the presence/absence of some data, events 5, 6, and 11 are not present in t(2,4,8,10) and events 7, 8, and 12 are not present in t(2,4).
QUESTIONS:
So, given these shortcuts:
“brt”=[t(1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31)]
“wrt”=[t(2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32)]
“brts”=[t(1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31)]
“wrts”=[t(2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32)]
1. In Initial State, does it make sense to define a sentence like this in GEMACO:
brt + wrts
and fix the last parameter in IVFV (corresponding to “wrts”) to zero?
2. In Survival, how would I define a state and time effect?
f(1,2).brt + f(3_8).wrt + others
and fix to zero (i) the last parameter corresponding to “others” (that should resume f(1 2).wrts + f(3:8).brts) and (ii) the parameters corresponding to “wrt” sessions with any data as for example f(1,2).t(7,19) when there were no captured chicks and f(5_8).t(2,4) and f(5,6). t(8,10) when there were no data about those events?
3. In Capture, again, time and state effect (age=1 in data input):
firste + nexte.f(3_8).wrt + others
and fix to zero (i) “others” as it should resume f(1,2).wrts + f(3_8).brts, and (ii) the parameters corresponding to “wrt” sessions when there were no data about events 5_8?
4. In State Assignment, again, time and state effect:
f(2,3).brt + f(4_9).wrt + others
Here the numbers are shifted of one right due to the structure of the matrix in GEPAT (1_8 == 2_9)
and fix to zero (i) others and (ii) parameters corresponding to “wrt” sessions when there were no data about events 3_8
Answers to these questions would help me a lot to better understand how E-SURGE works
Thanks for any help,
Simone