Commit c1376250 authored by patrick.lambert's avatar patrick.lambert
Browse files

amélioraition deathBasinW.Rmd

parent 12227561
......@@ -125,3 +125,4 @@ org.*
/src/main/java/species/Essai.java
/exploration/GR3D_Rdescription/.RData
/exploration/GR3D_Rdescription/.Rhistory
/exploration/GR3D_Rdescription/.~lock.*
......@@ -101,12 +101,12 @@ A strayers' mortality is added by considering a "death basin" with a constant we
$$
p_{j_1 \rightarrow j_2} = \frac {w_{j_1 \rightarrow j_2}} {w_{death} + w_{j_1}}
$$
With these equations, the strayer mortality rate $sm_{j_1}$ from a departure basin is given by:
## Two metrics to qualify the straying
The strayers mortality rate $sm_{j_1}$ from a departure basin caculate the portion of fish that ends in the death basin. It is given by:
$$ sm_{ j_1} = \frac {w_{death}} { w_{death}+w_{j_1} }$$
The efficiency for strayers $se_{j2}$ to reach a destination basin (considering abundance in the departure basin proportional to the surface area of this basin) can be computed with:
The efficiency for strayers $se_{j2}$ informs on the proportion of fish that are able to reach a destination basin considering abundance in departure basins proportional to surface area of these basins. It is computed with:
$$
se_{j_2} = \frac {\sum_{j_1}{A_{j_1} \cdot p_{j_1 \rightarrow j_2} }} {\sum_{j_1} {A_{j_1}}}
......@@ -141,7 +141,7 @@ dist = seq(1,500, 10)
dataKernel = data.frame(dist = dist, W = logitKernel(dist, alpha0, alpha1, meanInterDistance, standardDeviationInterDistance))
```
```{r drawKernelFunctionAA, echo =FALSE, warning = FALSE, include = TRUE, fig.cap="Kernel function for AA application"}
```{r drawKernelFunctionAA, echo =FALSE, warning = FALSE, include = TRUE, fig.cap = "Kernel function for AA application"}
dataKernel %>%
ggplot(aes(x=dist, y=W)) + geom_line() +
labs(x = 'distance between departure and destination basins (km)')
......@@ -196,14 +196,16 @@ resultAA <- extendedDistance %>% distinct(departure, sumW) %>%
resultAA
```
```{r strayerMortalityAA, fig.cap="Evolution of the mortality rate according to the latitude of the departure basin in the AA zone"}
```{r strayerMortalityAA, echo =FALSE, warning = FALSE, include = TRUE, fig.cap="Evolution of the mortality rate according to the latitude of the departure basin in the AA zone"}
resultAA %>% ggplot(aes(x = latitude, y = sm_departure)) +
geom_point() +
labs(x = "departure latitude (°)", y = "strayer mortality rate")
```
```{r stayerEfficiencyAA, fig.cap="Evolution of the strayers' efficiency according to the latitude of the destination basin in the AA zone"}
resultAA %>% ggplot(aes(x = latitude, y = se_destination)) + geom_point() + labs(x="destination latitude (°)", y = "strayer efficiency")
```{r stayerEfficiencyAA, echo =FALSE, warning = FALSE, include = TRUE, fig.cap="Evolution of the strayers' efficiency according to the latitude of the destination basin in the AA zone"}
resultAA %>% ggplot(aes(x = latitude, y = se_destination)) +
geom_point() +
labs(x="destination latitude (°)", y = "strayer efficiency")
```
## North East America NEA application
......@@ -246,12 +248,13 @@ resultNEA <- extendedDistance %>% distinct(departure, sumW) %>%
```
```{r, fig.cap="Evolution of strayers mortality according to depature basin latitude in the NEA zone"}
```{r strayerMortalityNEA, echo =FALSE, warning = FALSE, include = TRUE, fig.cap="Evolution of strayers mortality according to depature basin latitude in the NEA zone"}
resultNEA %>% ggplot(aes(x = latitude, y = sm_departure)) +
geom_point() + labs(x = "departure latitude (°)", y = "strayer mortality rate")
geom_point() +
labs(x = "departure latitude (°)", y = "strayer mortality rate")
```
```{r, fig.cap="Evolution of strayers efficiency according to destination basin latitude in the NEA zone"}
```{r strayerEfficiencyLatitudeNEA, echo =FALSE, warning = FALSE, include = TRUE, fig.cap="Evolution of strayers efficiency according to destination basin latitude in the NEA zone"}
resultNEA %>% ggplot(aes(x = latitude, y = se_destination)) +
geom_point() + labs(x = "destination latitude (°)", y = "strayer's efficiency")
# geom_text(aes(label = basin_name), hjust = 0, nudge_x = 0.5)
......@@ -282,14 +285,14 @@ extendedDistance = basinDistance %>%
mutate(p12 = W/(sumW + WDeathBasin))
```
```{r sm_fakeUniverse, include = TRUE, fig.cap="Evolution of strayer mortality according to latitude departure" }
```{r smFakeUniverse, echo =FALSE, warning = FALSE, include = TRUE, fig.cap = "Evolution of strayer mortality according to latitude departure"}
extendedDistance %>% distinct(departure, latitude_departure, sumW) %>%
mutate(sm_departure = WDeathBasin /(WDeathBasin + sumW)) %>%
ggplot(aes(x=latitude_departure, y = sm_departure)) + geom_point() + labs(x='latitude rank', y = 'strayer mortality rate') +
xlim(0,150) + ylim(0.0,.050)
```
```{r se_fakeUniverse, include = TRUE, fig.cap="Evolution of strayer efficiency according to departure latitude " }
```{r seFakeUniverse, echo =FALSE, warning = FALSE, include = TRUE, fig.cap="Evolution of strayer efficiency according to departure latitude " }
extendedDistance %>%
group_by(destination, latitude_destination) %>%
summarise(se_destination = mean(p12), .groups ='drop') %>%
......@@ -313,14 +316,14 @@ extendedSampledDistance = sampledBasinDistance %>%
mutate(p12 = W / (sumW + WDeathBasin))
```
```{r sm_sampledUniverse, include = TRUE, fig.cap="Evolution of strayer mortality according to latitude departure" }
```{r smSampledUniverse, echo =FALSE, warning = FALSE, include = TRUE, fig.cap="Evolution of strayer mortality according to latitude departure" }
extendedSampledDistance %>% distinct(departure, latitude_departure, sumW) %>%
mutate(sm_departure = WDeathBasin /(WDeathBasin + sumW)) %>%
ggplot(aes(x=latitude_departure, y = sm_departure)) + geom_point() + labs(x='latitude rank', y = 'strayer mortality rate') +
xlim(0,150) + ylim(0.0,.2)
```
```{r se_SampledUniverse, include = TRUE, fig.cap="Evolution of strayer efficiency according to latitude departure" }
```{r se_SampledUniverse, echo =FALSE, warning = FALSE, include = TRUE, fig.cap="Evolution of strayer efficiency according to latitude departure" }
extendedSampledDistance %>% group_by(destination, latitude_destination) %>%
summarise(se_destination = mean(p12), .groups ='drop') %>%
ggplot(aes(x=latitude_destination, y = se_destination)) + geom_point() + labs(x = 'latitude rank', y = 'strayer efficiency') +
......@@ -329,7 +332,7 @@ extendedSampledDistance %>% group_by(destination, latitude_destination) %>%
# Comparison with HaDiaD formulation
```{r HaDiaD, include = TRUE}
```{r HaDiaD, echo =FALSE, warning = FALSE, include = TRUE}
alpha_D = 0.0608
beta_D = 0.655
m = -log(0.464)/41
......@@ -339,8 +342,8 @@ tibble(distance = 0:500) %>% mutate(strayerMortalityRate = 1- strayerSurvival(di
ggplot(aes(x= distance, y =strayerMortalityRate)) + geom_point()
HADiaD %>% group_by(departure, latitude_departure) %>%
summarise(sumW=sum(W), sm_depature = weighted.mean(strayerMortalityRate, W) )%>%
ggplot(aes(x= latitude_departure, y =sm_depature)) + geom_point()
summarise(sumW=sum(W), sm_depature = weighted.mean(strayerMortalityRate, W) ) %>%
ggplot(aes(x = latitude_departure, y =sm_depature)) + geom_point()
```
......
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