Commit c1376250 by patrick.lambert

### 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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