BehaviourPaper_notes.rmd

# Outline and results from behavioural experiments

# 1. Mating behaviours with or without spider present:

```{r, include=F, warning=F, echo=F}
source("../mating_under_predation/Unsafe_Sex_Rcode.R")
```

## Courtship:

### Proportion of time courting in 15 minutes
```{r, warning=F}
#summary(courtship_model1)
print(gg_courtProp2)
```

### Number of Courtship Bouts

```{r, warning=F}
#summary(courtship_model2)
print(gg_courtcount2)
```

## Copulation

### Copulation occurance proportion
```{r, warning=F}
#summary(copprop_mod)
print(gg_copprop2)
```

### Copulation Latency
```{r, warning=F}
#summary(copul_lat_mod)
print(gg_coplat2)
```

### Copulation Duration
```{r, warning=F}
#summary(copul_dur_Mod)
print(gg_copdur2)
```

```{r, include=F, warning=FALSE, echo=F}
rm(list=ls())
```


# 2. Evolved Population Mating Behaviour:
```{r, include=F, warning=F, echo=F}
setwd("/Users/paulknoops/Bioinformatics/R-projects_git/LongTermEvolution_Data-Code/PredationCourtship/scripts")
source('AP_EvolvedPopulationAnalysis.R')
```

Age Bins correspond to different age range of flies:
```
1 = 1–3 days
2 = 4–7 days
3 = 8–11 days
4 = 12–15 days
```

All behaviours recored without predators present.

### Courtship latency:
Model:
```
mod_court <- lmer(Rel_Court_lat ~ 1 + Treatment*AgeBin + 
                    (1|Date) + (1|Treatment:Rep), 
                  data = AP_Data)
```
```{r, warning=F}
#summary(mod_court)
print(latenCourt2)
```

### Copulation Latency
```
mod_copl_plot <- lmer(Rel_Cop_lat ~ 1+ Treatment*AgeBin + 
                        (1|Date) + (1|Treatment:Rep), 
                      data = AP_Data)
```
```{r, warning=F}
#summary(mod_copl_plot)
print(LatenCop2)
```

### Copulation Duration: 
```
mod_copd_plot <- lmer(Rel_Cop_dur ~ 1+ Treatment*AgeBin + 
                        (1|Date) + (1|Treatment:Rep), 
                      data = AP_Data)
```
```{r, warning=F}
#summary(mod_copd_plot)
print(DuratCop2)

```

### Copulation Occurance (count)

Proportion of copulations occuring in the experimental time
```
mod_cop_count <- glmer(Copulation ~ 1 + Treatment*AgeBin + 
                         (1|Date) + (1|Treatment:Rep), 
                      family = "binomial", 
                       data = AP_Data)
## Did not work:
                       
mod_cop_count_glm <- glm(Copulation ~ 1 + Treatment*AgeBin, 
                         family = "binomial", 
                         data = AP_Data)
```
```{r, warning=F}
#summary(mod_cop_count_glm)
print(propCop3)
```

```{r, include=F, warning=FALSE, echo=F}
rm(list=ls())
```

# 3. Activity of evolved and "wild" flies:

Activity measured with the DAM. Plots show the trends in acticity over 24 hours (spline) with light and dark times (light = yellow box).

Also plot of hourly activity in different light phases.

```{r, include=F, warning=F, echo=F}
setwd('/Users/paulknoops/Bioinformatics/R-projects_git/LongTermEvolution_Data-Code/Predation_ActivityAggregation/scripts')
source("Analysis_activityData.R")
source("Activity_allData_Plots.R")
```


### Evolved Population Plots:
Evolved population activity (with no cues present)

Model:
```
mod_trial_2 <- lmer(Hourly_activity ~ sin(hour2) + cos(hour2) + Treatment + Treatment:Population + light + light:Treatment + start_day + monitor
                        + (1 + light | individual), data=dat.hourly)
```
```{r, warning=F}
#summary(mod_trial_2)
print(Evolve_plot3)
print(LT_plot2)
```

### Exp3: Cricket vs. Spider fed Cricket vs. Fly vs. Spider fed flies
Complex cues: Two predator treatments based on diet (Spider fed cricket and spdier fed flies) and two controls (crickets and flies).

Model:
```
Exp3_mod_spli_2 <- lmer(activity_counts ~ sin(hour2) + cos(hour2) + Treatment*light + monitor
                        + (1 + light | individual), data=Exp3_hour)
```

```{r, warning=F}
#summary(Exp3_mod_spli_2)
print(Exp3_plot3)
print(plot_Exp3_2)
```


### Exp 2: Spiders vs. Crickets
Spider conditioned vials vs. Cricket conditioned vials

Model:
```
Exp2_mod_spli_2 <- lmer(activity_counts ~ sin(hour2) + cos(hour2) + Treatment*light + monitor
                        + (1 + light | individual), data=Exp2_hour)
```
```{r, warning=F}
#summary(Exp2_mod_spli_2)

print(Exp2_plot3)

print(plot_Exp2_2)
```


### Spider vs. Control:

Spider conditioned vials vs. controls

Model:
```
spider_mod_spli_2 <- lmer(activity_counts ~ Treatment*light + sin(hour2) + cos(hour2)  + monitor
                        + (1 + light | individual), data=act_hour)
```

```{r, warning=F}
#summary(spider_mod_spli_2)

print(spider_plot3)

print(spi_plot2)

```

### Mantid vs. Control:

Vials conditioned with Mantid cues compared to control (no cues)

Model:
```
mantid_mod_spli_2 <- lmer(activity_counts ~ Treatment*light + sin(hour2) + cos(hour2)  + monitor
                          + (1 + light | individual), data=Mantid_hour)
```

```{r, warning=F}
#summary(mantid_mod_spli_2)

print(mantid_plot3)
print(Man_plot2)
```


```{r, include=F, warning=FALSE, echo=F}
rm(list=ls())
```


#3. Light vs. Dark Courtship Behaviour:
```{r, include=F, warning=F, echo=F}
setwd("/Users/paulknoops/Bioinformatics/R-projects_git/Reuven_L-D_courtshipEvolvedPop")
source('/Users/paulknoops/Bioinformatics/R-projects_git/Reuven_L-D_courtshipEvolvedPop/L-D_courtshipAnalysis.R')
```

Proportion of courtship time in 15 minutes: Light phase vs. Dark phase of the 3 experimental evolution populations.

Model:
```
stuff2 <- lmer(P_court ~ Treatment*Phase + Observer + (1|Day) + (1|Treatment:Population), data=court)
```

```{r, warning=F}
#summary(stuff2)
print(stuff_plot3)
```

```{r, include=F, warning=FALSE, echo=F}
rm(list=ls())
```