r params$title
knitr::opts_chunk$set(echo = F, fig.height = 3, warning = F, message = F, results = 'asis')
suppressPackageStartupMessages({ library(ggplot2) library(dplyr) library(tidyr) library(MPAtools) library(reshape) library(stargazer) library(ggExtra) })
Este documento fue generado por el paquete MPAtools
, uno de los entregables del grupo TURFeffect. Los resultados presentados son una version preliminar del software que se esta desarrollando, y no recomendamos la toma de decisiones basado en la informacion aqui presentada
Acentos y caracteres especiales omitidos
Leyenda
peces = params$peces invertebrados = params$invertebrados pesca = params$pesca comunidad = params$comunidad reserva = params$reserva control = params$control Dp <- summary(turfeffect(density(peces, comunidad), reserva, control)) Sp <- summary(turfeffect(richness(peces, comunidad), reserva, control)) Bp <- summary(turfeffect(fish_biomass(peces, comunidad), reserva, control)) NT <- summary(turfeffect(trophic(peces, comunidad), reserva, control)) Di <- summary(turfeffect(density(invertebrados, comunidad), reserva, control)) lang <- filter(invertebrados, GeneroEspecie == "Panulirus argus") Nlang <- summary(turfeffect(density(lang, comunidad), reserva, control)) car <- filter(invertebrados, GeneroEspecie == "Strombus gigas") Ncar <- summary(turfeffect(density(car, comunidad), reserva, control)) lut <- filter(peces, Genero == "Lutjanus") Nlut <- summary(turfeffect(density(lut, comunidad), reserva, control)) Blut <- summary(turfeffect(fish_biomass(lut, comunidad), reserva, control)) ## Landings section arribos <- landings(data = pesca, site = coop, type = 'kg') arrG <- arribos %>% group_by(Ano) %>% summarize(Peso = sum(Peso)/1000) modG <- lm(Peso ~ Ano, arrG) arrM <- arribos %>% filter(NombreCientifico == "Epinephelus spp") %>% mutate(Peso = Peso/1000) modM <- lm(Peso ~ Ano, arrM) arrP <- arribos %>% filter(NombreCientifico == "Lutjanus aratus" | NombreCientifico == "Lutjanus cyanopterus" | NombreCientifico == "Lujanus griseus" | NombreCientifico == "Lutjanus spp." | NombreCientifico == "Lutjanus viridis" | NombreCientifico == "Lutjanus spp") %>% mutate(Peso = Peso /1000) modP <- lm(Peso ~ Ano, arrP) arrL <- arribos %>% filter(NombreCientifico == "Panulirus argus") %>% mutate(Peso = Peso /1000) modL <- lm(Peso ~ Ano, arrL) # Landings and price ingresos <- landings(data = pesca, site =coop, type = 'price') ingG <- ingresos %>% group_by(Ano) %>% summarize(Valor = sum(Precio)/1000) modG2 <- lm(Valor ~ Ano, ingG) ingM <- ingresos %>% filter(NombreCientifico == "Epinephelus spp") modM2 <- lm(Precio ~ Ano, ingM) ingP <- ingresos %>% filter(NombreCientifico == "Lutjanus aratus" | NombreCientifico == "Lutjanus cyanopterus" | NombreCientifico == "Lujanus griseus" | NombreCientifico == "Lutjanus spp." | NombreCientifico == "Lutjanus viridis" | NombreCientifico == "Lutjanus spp") %>% mutate(Precio = Precio /1000) modP2 <- lm(Precio ~ Ano, ingP) ingL <- ingresos %>% filter(NombreCientifico == "Panulirus argus") %>% mutate(Precio = Precio /1000) modL2 <- lm(Precio ~ Ano, ingL) ## summary <- list(Bio = list(P = list(Dp = score(x = data.frame(est = coefficients(Dp)[4], p = coefficients(Dp)[16])), Sp = score(x = data.frame(est = coefficients(Sp)[4], p = coefficients(Sp)[16])), Bp = score(x = data.frame(est = coefficients(Bp)[4], p = coefficients(Bp)[16])), NT = score(x = data.frame(est = coefficients(NT)[4], p = coefficients(NT)[16]))), I = list(Di = score(x = data.frame(est = coefficients(Di)[4], p = coefficients(Di)[16]))), O = list(L = score(x = data.frame(est = coefficients(Nlang)[4], p = coefficients(Nlang)[16])), C = score(x = data.frame(est = coefficients(Ncar)[4], p = coefficients(Ncar)[16])), P = score(x = data.frame(est = coefficients(Nlut)[4], p = coefficients(Nlut)[16])), Pb = score(x = data.frame(est = coefficients(Blut)[4], p = coefficients(Blut)[16])))), Soc = list(L = list(Lg = score(x = data.frame(est = coefficients(summary(modG))[2], p = coefficients(summary(modG))[8])), Lm = score(x = data.frame(est = coefficients(summary(modM))[2], p = coefficients(summary(modM))[8])), Lp = score(x = data.frame(est = coefficients(summary(modL))[2], p = coefficients(summary(modM))[8])), Ll = score(x = data.frame(est = coefficients(summary(modM))[2], p = coefficients(summary(modM))[8]))), V = list(Vg = score(x = data.frame(est = coefficients(summary(modG2))[2], p = coefficients(summary(modG2))[8])), Vm = score(x = data.frame(est = coefficients(summary(modM2))[2], p = coefficients(summary(modM2))[8])), Vp = score(x = data.frame(est = coefficients(summary(modL2))[2], p = coefficients(summary(modM2))[8])), Vl = score(x = data.frame(est = coefficients(summary(modM2))[2], p = coefficients(summary(modM2))[8])))), Gov = list(1))
Cat | Indicador | Valor |Cat | Indicador | Valor |
-------|-------------------------|----------------------------------------------|-------|-------------------------|----------------------------------------------|
Bio | Densidad Peces | r knitr::include_graphics(summary$Bio$P$Dp)
| Soc | Arribos totales | r knitr::include_graphics(summary$Soc$L$Lg)
Bio | Riqueza Peces | r knitr::include_graphics(summary$Bio$P$Sp)
| Soc | Arribos de mero | r knitr::include_graphics(summary$Soc$L$Lm)
Bio | Biomasa Peces | r knitr::include_graphics(summary$Bio$P$Bp)
| Soc | Arribos de pargos | r knitr::include_graphics(summary$Soc$L$Lp)
Bio | Nivel Trofico Peces | r knitr::include_graphics(summary$Bio$P$NT)
| Soc | Arribos de langosta | r knitr::include_graphics(summary$Soc$L$Ll)
Bio | Densidad Iinvertebrados | r knitr::include_graphics(summary$Bio$I$Di)
| Soc | Ingresos totales | r knitr::include_graphics(summary$Soc$V$Vg)
Bio | Densidad de langostas | r knitr::include_graphics(summary$Bio$O$L)
| Soc | Ingresos por mero | r knitr::include_graphics(summary$Soc$V$Vm)
Bio | Densidad de caracol rosa| r knitr::include_graphics(summary$Bio$O$C)
| Soc | Ingresos por pargos | r knitr::include_graphics(summary$Soc$V$Vp)
Bio | Densidad de pargos | r knitr::include_graphics(summary$Bio$O$P)
| Soc | Ingresos por langosta | r knitr::include_graphics(summary$Soc$V$Vl)
Bio | Biomasa de pargos | r knitr::include_graphics(summary$Bio$O$Pb)
| | |
Np <- density(data = peces, location = comunidad) mpa_plot3(Np, reserve = reserva, control = control, y.lab = "Densidad (org / m^2)")
stargazer(turfeffect(Np, reserve = reserva, control = control), dep.var.labels = "Densidad (org / transecto)", type = "html", dep.var.caption = "", report = "vc*", single.row = T, omit.stat = c("adj.rsq", "n"), digits = 2, df = F, covariate.labels = c("Ano", "Zona", "**Ano:Zona**", "Constante"), notes = "+p < 0.1, ++p<0.05, +++p<0.001", notes.append = FALSE, star.char = "+")
Sp <- richness(data = peces, location = comunidad) mpa_plot3(Sp, reserve = reserva, control = control, y.lab = "Riqueza (Sp. / transecto)")
stargazer(turfeffect(Sp, reserve = reserva, control = control), dep.var.labels = "Riqueza (Sp. / transecto)", type = "html", dep.var.caption = "", report = "vc*", single.row = T, omit.stat = c("adj.rsq", "n"), digits = 2, df = F, covariate.labels = c("Ano", "Zona", "**Ano:Zona**", "Constante"), notes = "+p < 0.1, ++p<0.05, +++p<0.001", notes.append = FALSE, star.char = "+")
Bp <- fish_biomass(data = peces, location = comunidad) mpa_plot3(Bp, reserve = reserva, control = control, y.lab = "Biomasa (Kg / transecto)")
stargazer(turfeffect(Bp, reserve = reserva, control = control), dep.var.labels = "Biomasa (Kg / transecto)", type = "html", dep.var.caption = "", report = "vc*", single.row = T, omit.stat = c("adj.rsq", "n"), digits = 2, df = F, covariate.labels = c("Ano", "Zona", "**Ano:Zona**", "Constante"), notes = "+p < 0.1, ++p<0.05, +++p<0.001", notes.append = FALSE, star.char = "+")
NTp <- trophic(data = peces, location = comunidad) mpa_plot3(NTp, reserve = reserva, control = control, y.lab = "Nivel trofico")
stargazer(turfeffect(NTp, reserve = reserva, control = control), dep.var.labels = "Nivel trofico", type = "html", dep.var.caption = "", report = "vc*", single.row = T, omit.stat = c("adj.rsq", "n"), digits = 2, df = F, covariate.labels = c("Ano", "Zona", "**Ano:Zona**", "Constante"), notes = "+p < 0.1, ++p<0.05, +++p<0.001", notes.append = FALSE, star.char = "+")
Ni <- density(data = invertebrados, location = comunidad) %>% filter(Sitio == reserva| Sitio == control) mpa_plot3(Ni, reserve = reserva, control = control, y.lab = "Densidad (org / transecto)")
stargazer(turfeffect(Ni, reserve = reserva, control = control), dep.var.labels = "Densidad (org / transecto)", type = "html", dep.var.caption = "", report = "vc*", single.row = T, omit.stat = c("adj.rsq", "n"), digits = 2, df = F, covariate.labels = c("Ano", "Zona", "**Ano:Zona**", "Constante"), notes = "+p < 0.1, ++p<0.05, +++p<0.001", notes.append = FALSE, star.char = "+")
lutjanus <- peces %>% filter(Genero == "Lutjanus") Nlut <- density(lutjanus, location = comunidad) mpa_plot3(Nlut, reserve = reserva, control = control, y.lab = "Densidad de pargos (org / transecto)")
stargazer(turfeffect(Nlut, reserve = reserva, control = control), dep.var.labels = "Densidad (org / transecto)", type = "html", dep.var.caption = "", report = "vc*", single.row = T, omit.stat = c("adj.rsq", "n"), digits = 2, df = F, covariate.labels = c("Ano", "Zona", "**Ano:Zona**", "Constante"), notes = "+p < 0.1, ++p<0.05, +++p<0.001", notes.append = FALSE, star.char = "+")
Blut <- fish_biomass(lutjanus, location = comunidad) mpa_plot3(Blut, reserve = reserva, control = control, y.lab = "Biomasa de pargos (Kg / transecto)")
stargazer(turfeffect(Blut, reserve = reserva, control = control), dep.var.labels = "Biomasa (Kg / transecto)", type = "html", dep.var.caption = "", report = "vc*", single.row = T, omit.stat = c("adj.rsq", "n"), digits = 2, df = F, covariate.labels = c("Ano", "Zona", "**Ano:Zona**", "Constante"), notes = "+p < 0.1, ++p<0.05, +++p<0.001", notes.append = FALSE, star.char = "+")
lang <- filter(invertebrados, GeneroEspecie == "Panulirus argus") Nlang <- density(lang, location = comunidad) mpa_plot3(Nlang, reserve = reserva, control = control, y.lab = "Densidad (langostas / transecto)")
stargazer(turfeffect(Nlang, reserve = reserva, control = control), dep.var.labels = "Densidad (org / transecto)", type = "html", dep.var.caption = "", report = "vc*", single.row = T, omit.stat = c("adj.rsq", "n"), digits = 2, df = F, covariate.labels = c("Ano", "Zona", "**Ano:Zona**", "Constante"), notes = "+p < 0.1, ++p<0.05, +++p<0.001", notes.append = FALSE, star.char = "+")
car <- filter(invertebrados, GeneroEspecie == "Strombus gigas") Ncar <- density(car, location = comunidad) mpa_plot3(Ncar, reserve = reserva, control = control, y.lab = "Densidad (caracoles / transecto)")
stargazer(turfeffect(Ncar, reserve = reserva, control = control), dep.var.labels = "Densidad (org / transecto)", type = "html", dep.var.caption = "", report = "vc*", single.row = T, omit.stat = c("adj.rsq", "n"), digits = 2, df = F, covariate.labels = c("Ano", "Zona", "**Ano:Zona**", "Constante"), notes = "+p < 0.1, ++p<0.05, +++p<0.001", notes.append = FALSE, star.char = "+")
# Data and models for this section were calculated at the beggining of the document
ggplot(arrG, aes(x = Ano, y = Peso)) + geom_point() + geom_abline(intercept = coef(summary(modG))[1], slope = coef(summary(modG))[2]) + theme_bw() + labs(x = "Ano", y = "Capturas (T)")
ggplot(arrM, aes(x = Ano, y = Peso)) + geom_point() + geom_abline(intercept = coef(summary(modM))[1], slope = coef(summary(modM))[2]) + theme_bw() + labs(x = "Ano", y = "Capturas (T)")
ggplot(arrP, aes(x = Ano, y = Peso)) + geom_point() + geom_abline(intercept = coef(summary(modP))[1], slope = coef(summary(modP))[2]) + theme_bw() + labs(x = "Ano", y = "Capturas (T)")
ggplot(arrL, aes(x = Ano, y = Peso)) + geom_point() + geom_abline(intercept = coef(summary(modL))[1], slope = coef(summary(modL))[2]) + theme_bw() + labs(x = "Ano", y = "Capturas (T)")
# Code for this section is at the begining of the document
ggplot(ingG, aes(x = Ano, y = Valor)) + geom_point() + geom_abline(intercept = coef(summary(modG2))[1], slope = coef(summary(modG2))[2]) + theme_bw() + labs(x = "Ano", y = "Ingresos (Miles de pesos)")
ggplot(ingM, aes(x = Ano, y = Precio)) + geom_point() + geom_abline(intercept = coef(summary(modM2))[1], slope = coef(summary(modM2))[2]) + theme_bw() + labs(x = "Ano", y = "Ingresos (Miles de pesos)")
ggplot(ingP, aes(x = Ano, y = Precio)) + geom_point() + geom_abline(intercept = coef(summary(modP2))[1], slope = coef(summary(modP2))[2]) + theme_bw() + labs(x = "Ano", y = "Ingresos (Miles de pesos)")
ggplot(ingL, aes(x = Ano, y = Precio)) + geom_point() + geom_abline(intercept = coef(summary(modL2))[1], slope = coef(summary(modL2))[2]) + theme_bw() + labs(x = "Ano", y = "Ingresos (Miles de pesos)")
#knowledge()
La informacion de gobernanza se presenta con propositos de realizar el ejercicio; de ninguna manera representa una evaluacion que pueda utilizarse para recomendaciones.
gov$Access.to.the.fishery[2]
gov$Number.of.fishers[1]
gov$Legal.recognition.of.reserve[2]
gov$Reserve.type[2]
gov$Illegal.harvesting[1] gov$Illegal.harvesting[2]
gov$Management.plan[1] gov$Management.plan[2]
gov$Reserve.enforcement[2]
gov$Reasoning.for.reserve.location[2]
gov$Type.of.fisher.organizations[2]
gov$Representation[1] gov$Representation[2]
R Core Team (2015). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
JJ Allaire, Joe Cheng, Yihui Xie, Jonathan McPherson, Winston Chang, Jeff Allen, Hadley Wickham, Aron Atkins and Rob Hyndman (2016). rmarkdown: Dynamic Documents for R. R package version 0.9.6. https://CRAN.R-project.org/package=rmarkdown
Hadley Wickham and Romain Francois (2016). dplyr: A Grammar of Data Manipulation. R package version 0.5.0. https://CRAN.R-project.org/package=dplyr
Hadley Wickham (2016). tidyr: Easily Tidy Data with spread()
and gather()
Functions. R package version 0.6.0. https://CRAN.R-project.org/package=tidyr
Hlavac, Marek (2015). stargazer: Well-Formatted Regression and Summary Statistics Tables. R package version 5.2. http://CRAN.R-project.org/package=stargazer
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