9 19 2014 oyster bay fall maintenance

Kamilche wa

High 60s low 70s cloudy to mostly sunny

Participants: Sean Bennett,  Jonathan Allen,  and Jake heare.

Took live dead counts for all remaining trays. Then moved remaining oysters from trays to new hexagonal hanging cages. Then tied the cages together and hung them off the same hanging ropes. Very high survival in all trays, less than 2% mortality. Food growth in all trays. Some oysters look market size now. Mussel incursion was much better than expected with very little in most trays. More red rock crabs than I expected but seemed to have little effect on survival. Also lots of oyster spat in all trays. Collected spat for DNA workup if desired.

Numbers as follow

1S9-12
Live.           3
Dead.         3
Sampled     3

1H13-16
Live.           12
Dead.          2
Sample.      12

1N1-4
Live.           72
Dead.         0
Sample.      20

1H5-8
Live.          49
Dead.         7
Sample.      13

1S1-4
Live.          80
Dead.         4
Sample.      24

1S13-16
Live.          71
Dead.          2
Sample.      23

1N5-8
Live.          51
Dead.         0
Sample.      10

1H9-12.     
Live.          80
Dead.         3
Sample.      15

1H1-4
Live.         67
Dead.        3
Sample.     10

1N9-12
Live.          77
Dead.         1
Sample.      20

Pics below. 1S1-4 tray with 3 live on it is actually 1S9-12. 

9 14 2014 Kaplan Meier Graphs Improved

KMgraphsWorking.R

Jake H

Sun Sep 14 14:41:29 2014

library(survival)

## Loading required package: splines

kmdab=read.csv("KMdataDabob.csv")
names(kmdab)    

## [1] "Animal"     "Population" "Death"      "Status"

with(kmdab, tapply(Death[Status==1],Population[Status==1],mean))

##     H     N     S 
## 4.385 4.522 4.715

with(kmdab, tapply(Death[Status==1],Population[Status==1],var))

##      H      N      S 
## 0.4524 0.9786 1.6039

fit1=with(kmdab,survfit(Surv(Death,Status)~Population))
plot(fit1, col=c(1:3), xlab="Survival Time from Outplant in Months", ylab="% Surviving")
legend("bottomleft", title="Population", c("Dabob","Fidalgo","Oyster Bay"), fill=c(1:3))

kmman=read.csv("KMdataMan.csv")
names(kmman)

## [1] "Animal"     "Population" "Death"      "Status"

with(kmman, tapply(Death[Status==1],Population[Status==1],mean))

##      H      N      S 
## 10.540  9.368  9.197

with(kmman, tapply(Death[Status==1],Population[Status==1],var))

##     H     N     S 
## 1.519 6.468 6.321

fit2=with(kmman, survfit(Surv(Death,Status)~Population))
plot(fit2, col=c(1:3), xlab="Survival Time from Outplant in Months", ylab="% Surviving")
legend("bottomleft", title="Population", c("Dabob","Fidalgo","Oyster Bay"), fill=c(1:3))

kmfid=read.csv("KMdataFid.csv")
with(kmfid, tapply(Death[Status==1],Population[Status==1],mean))

##     H     N     S 
## 5.921 5.754 6.897

with(kmfid, tapply(Death[Status==1],Population[Status==1],var))

##     H     N     S 
## 2.554 2.189 3.989

fit3=with(kmfid, survfit(Surv(Death,Status)~Population))
plot(fit3, col=c(1:3), xlab="Survival Time from Outplant in Months", ylab="% Surviving")
legend("bottomleft", title="Population", c("Dabob","Fidalgo","Oyster Bay"), fill=c(1:3))

kmoys=read.csv("KMdataOys.csv")
with(kmoys, tapply(Death[Status==1],Population[Status==1],mean))

##     H     N     S 
## 7.550 8.069 8.396

with(kmoys, tapply(Death[Status==1],Population[Status==1],var))

##     H     N     S 
## 7.774 5.805 5.814

fit4=with(kmoys, survfit(Surv(Death,Status)~Population))
plot(fit4, col=c(1:3), xlab="Survival Time from Outplant in Months", ylab="% Surviving")
legend("bottomleft", title="Population", c("Dabob","Fidalgo","Oyster Bay"), fill=c(1:3))