library(plotrix) #manually enter data d <- data.frame( Bee_group = c("Bombus", "Dark", "Green", "Lasioglossum"), Efficiency = c(106.86207, 81.50000, 80.66667, 59.27586), Eff_SE = c(15.56551, 20.12130, 17.97529, 12.25689), Visitation = c(2.8333333, 0.2222222, 2.2222222, 5.6666667), Visit_SE = c(0.8333333, 0.1008317, 0.7119684, 1.0966378) ) #create a grid with value x (visitation), y (efficiency) and z = x*y. grid = expand.grid(list(x=seq(0, 8, 0.1), y=seq(0, 175, 1))) grid$z = grid$x * grid$y #use loess to have z in a matrix format. total.loess = loess(data=grid, z ~ x * y, degree=2, span=0.01) z = predict(total.loess, newdata = grid) #Plot the surface image(seq(0, 8, 0.1), seq(0, 175, 1), z, xlab = "", ylab = "", main = "Tomato pollination landscape", col = sort(heat.colors(10, 0.5), decreasing= TRUE), las = 1) box() #Plot the position of the different groups on top par(new = TRUE) x = c(0,8) y = c(0,175) plot(x,y, type = "n",axes= FALSE, ylab = "Quality", xlab = "Quantity", las = 1, xlim = c(0.1,7.9), ylim = c(0.1,174)) for(i in 1:4){ arrows(d[i,4]-d[i,5],d[i,2],d[i,4]+d[i,5],d[i,2], length=.05,angle=90,code=3, col = i) arrows(d[i,4],d[i,2]+d[i,3],d[i,4],d[i,2]-d[i,3], length=.05,angle=90,code=3, col = i) #alternative with elipses #draw.ellipse(d[i,4],d[i,2], a = d[i,5], b = d[i,3], border = i, # col = NULL, lty = 1, lwd = 1) } legend(x= 5 ,y= 175 ,legend= d[,1], lty= 1, col= c(1:4), cex = 0.7)
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