Import data

clean<-read.csv("/Users/Ang/Documents/Tesis New/Univariates/clean_all.csv")
#create P/A and Forest Type variables
clean$scirtids.pa = decostand(clean$Scirtids,"pa",na.rm=T)
clean$Type<-ifelse((clean$Size=="Intact"),"Continuous","Patch")
#remove NAs:
cl<-na.omit(clean)
#subset lates:
cl.late<-subset(cl, Time=="Late")

Scirtids abundance accross sampling Time:

Presence/absence

table(clean$scirtids.pa,clean$Time)
##    
##     Early Late
##   0   185  153
##   1     2   39

We found too few scirtids in early samples, so we stick to LATE samples from here on.

s.ab2<-summarySE(cl.late, measurevar="Scirtids", groupvars=c("Leaves","Size"))
s.ab2
##     Leaves   Size  N  Scirtids        sd        se        ci
## 1   Native Intact 40 0.5000000  2.407254 0.3806203 0.7698772
## 2   Native  Large 29 2.7586207  7.581251 1.4078030 2.8837537
## 3   Native  Small 30 3.6000000 13.652333 2.4925637 5.0978651
## 4 Standard Intact 37 1.2162162  4.583395 0.7535055 1.5281799
## 5 Standard  Large 30 0.8333333  2.666307 0.4867989 0.9956156
## 6 Standard  Small 26 0.9615385  2.999744 0.5882981 1.2116227

Scirtid Mean abundance (bars are Std.Error)

Scirtid Mean abund. (bars are 95% CI):

Not much difference within standard leaves, but with native leaves, Scirtid Abundance Increases in Small Fragments:

Is ABUNDANCE sign. sensitive to Forest Size?

# A poisson glmer attempt with SIZE 
ab1<-glmer(Scirtids~Leaves*Size+(1|Site),data=cl.late,family=poisson,control=glmerControl(optimizer="bobyqa"))
overdisp_fun(ab1)
##         chisq         ratio           rdf             p 
##  1.409400e+03  7.618379e+00  1.850000e+02 3.112149e-187
#crazily overdispersed!. So we move on to glmmADMB model with neg.binomial distribution:
ab2 <- glmmadmb(Scirtids~Leaves*Size+(1|Site),data=cl.late,zeroInflation=TRUE,     family="nbinom")
overdisp_fun(ab2)
##       chisq       ratio         rdf           p 
## 128.6148190   0.6952152 185.0000000   0.9994451
plot(resid(ab2)~fitted.values(ab2))

Anova(ab2)
## Analysis of Deviance Table (Type II tests)
## 
## Response: Scirtids
##              Df  Chisq Pr(>Chisq)  
## Leaves        1 1.1762    0.27812  
## Size          2 6.0468    0.04864 *
## Leaves:Size   2 5.2955    0.07081 .
## Residuals   183                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Yes. Scirtids are more abundant in small fragments.

Now contrasting patches versus intacts, using forest Type:

ab3 <- glmmadmb(Scirtids~Leaves*Type+(1|Site),data=cl.late,zeroInflation=TRUE,      family="nbinom")
overdisp_fun(ab3) 
##       chisq       ratio         rdf           p 
## 131.0729464   0.7009248 187.0000000   0.9993333
plot(resid(ab3)~fitted.values(ab3))

Anova(ab3)
## Analysis of Deviance Table (Type II tests)
## 
## Response: Scirtids
##              Df  Chisq Pr(>Chisq)  
## Leaves        1 0.7290    0.39320  
## Type          1 4.8181    0.02816 *
## Leaves:Type   1 3.5188    0.06068 .
## Residuals   185                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Scirtids more abundant in patches than continouus forest. Note margin.sign. interaction with leaflitter type

Q:Is PRESENCE sign. sensitive to forest Size??

pa1<- glmmadmb(scirtids.pa~Leaves*Size+(1|Site),data=cl.late,zeroInflation=TRUE,  family="binomial")
overdisp_fun(pa1) #decent ratio to work
##       chisq       ratio         rdf           p 
## 137.3478615   0.7424209 185.0000000   0.9964662
Anova(pa1)
## Analysis of Deviance Table (Type II tests)
## 
## Response: scirtids.pa
##              Df  Chisq Pr(>Chisq)  
## Leaves        1 1.0832    0.29799  
## Size          2 5.5737    0.06161 .
## Leaves:Size   2 3.0011    0.22301  
## Residuals   184                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

A: YES!

Now contrasting patches versus intacts, using TYPE:

# Forest type: Patches vs Continuous forest
pa2<- glmmadmb(scirtids.pa~Leaves*Type+(1|Site),data=cl.late,zeroInflation=TRUE,  family="binomial")
overdisp_fun(pa2) 
##       chisq       ratio         rdf           p 
## 137.2121193   0.7337546 187.0000000   0.9975335
#decent overdisp.Sign. effect of forest type:
Anova(pa2)
## Analysis of Deviance Table (Type II tests)
## 
## Response: scirtids.pa
##              Df  Chisq Pr(>Chisq)  
## Leaves        1 0.7938    0.37294  
## Type          1 4.3378    0.03728 *
## Leaves:Type   1 1.7803    0.18212  
## Residuals   186                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Marginally higher presence in patches than in intact forest