Show corresponding legend for second geom_point()

Question

I am plotting three times with geom_point in the same plot but the second and third geom_point don't appear in the legend and I don't understand why. I looked at many posts but I can't find a solution that really works. My 2 original dataframes are different and I would prefer to keep it that way and not join them.

Either the cross (or the colour) appears on all the legend items or the second geom_point() is not mentionned to the legend. Here's my current code:

ggplot () +
  geom_point(data = data_1[data_1$River != "Roya",], aes(x = W_AC, y = BRI_mean_XS, shape = River, col = Type), size = 3) +
  geom_point(data = data_2, aes(x = W_m, y = BRI_norm, color = "Second geom_point "), shape = 4, size = 2.5) + 
  scale_shape_manual(values = c(15, 18, 17, 16)) +
  scale_colour_manual(values = c("blue4", "chocolate1", "darkcyan")) +
  geom_text(data = data_1[data_1$River != "Roya",], aes(x = W_AC, y = BRI_mean_XS, label = Year, vjust = -0.5, hjust = -0.5), show.legend = FALSE, size = 4) +
  scale_x_continuous(name = "aa") +
  scale_y_continuous(name = "bb") + 
  geom_point(data = data_1[data_1$River == "Roya",], aes(x = W_AC, y = BRI_mean_XS), shape = 16, col = "cornflowerblue", size = 3) +
  geom_text(data = data_1[data_1$River == "Roya",], aes(x = W_AC, y = BRI_mean_XS, label = Year, vjust = -0.5, hjust = -0.5), show.legend = F, size = 4) +
  theme_bw()

I tried also to specify the colour and shape in the scale_*_manual but the shape is not used in the plot. For example: scale_shape_manual(values = c(15, 18, 17, 16, 4)), 4 being for the second geom_point.

As I read on other posts, when values are specified in scale_*_manual, it should appear after in the legend but here it seems mixed up. Is it not possible to show a blue cross in the Type section or the River section ? Same for the third geom_point() (Roya) is it possible to draw a blue circle in the River section?

Here's a dput of my 2 dataframes:

data_1:

structure(list(River = c("Durance", "Durance", "Durance", "Durance",  "Roya", "Var", "Drac", "Drac", "Drac", "Drac", "Var", "Var",  "Mareta", "Mareta", "Mareta", "Mareta", "Var"), Type = c("Under restoration",  "Target", "Under restoration", "Target", "Witness", "Under restoration",  "Under restoration", "Target", "Under restoration", "Target",  "Target", "Under restoration", "Under restoration", "Under restoration",  "Target", "Target", "Under restoration"), Year = c(2017, 2017,  2012, 2012, 2018, 2005, 2011, 2011, 2018, 2018, 2012, 2018, 2005,  2013, 2005, 2013, 2012), BRI_mean_XS = c(0.0028, 0.0017, 0.0033, 
0.0018, 0.009, 0.0097, 0.0182, 0.0026, 0.0032, 0.0035, 0.0053, 
0.0016, 0.005, 0.0041, 0.0058, 0.0082, 0.0037), W_AC = c(296.522411128284, 
411.01376146789, 263.944186046512, 363.288990825688, 88.6420798065296, 
155.868223887175, 41.4430051813472, 138.772532188841, 105.525906735751, 
108.848484848485, 144.78431372549, 314.685764654033, 29.8791208791209, 
52.8, 33.6949152542373, 34.4661016949153, 149.838539375275)), row.names = c(NA, 
-17L), class = c("tbl_df", "tbl", "data.frame"))

data_2:

structure(list(SITE = c("AIGUES-C", "BUECH-AV", "ARRONDINE",  "ARVAN", "ASSE-BLIEUX", "ASSE-BLIEUX", "ASSE-AV", "ASSE-AM",  "ASSE-AM", "BES-BLEONE", "BES-BLEONE", "BES-DROME", "BES-DROME",  "BLEONE-AM", "BLEONE-AV", "BUECH-AV", "BUECH-AV", "DRANSE-MORZINE",  "DRANSE-MORZINE", "DROME-RECOUBEAU", "DROME-PONTQUART", "DROME-PONTQUART",  "EYGUES-R", "FIER", "GIFFRE", "JABRON", "PETIT-BUECH", "PETIT-BUECH",  "ROUBION", "SASSE", "SASSE", "SASSE", "SEVERAISSE", "SEVERAISSE",  "UBAYE", "VANCON", "VAR", "VENEON", "VERDON", "DRAC LIDAR1",  "DROME LIDAR1", "DROME LIDAR2", "DROME LIDAR3"), W_m = c(180, 
333.593594745271, 56, 78, 102, 58.8, 171.9, 202, 170, 132, 148,  76, 98, 99.9, 171.3, 214, 125, 63, 64, 137, 181, 39, 66, 91,  220, 120, 90, 103, 114, 182, 123, 139, 152, 38, 144, 58, 183,  193, 193,
103.3287640678, 170.959110791, 168.800988262, 133.13237116 ), BRI_norm = c(0.00238417932933424, 0.0019586918252209, 0.00592873427970417, 
0.00496998572378169, 0.00257768461027533, 0.00594823420965329, 
0.00196839869925125, 0.00110647254938539, 0.00129282468469599, 
0.00255415705319677, 0.00189636185539575, 0.00272918083912772, 
0.00362898036424863, 0.00240398604859984, 0.00158558538418367, 
0.00179786294819712, 0.0024557284827885, 0.00910376733031885, 
0.00534776094775883, 0.00392598083437978, 0.00240750522409946, 
0.00514878385829154, 0.00254279813562245, 0.00563806058644668, 
0.00119537585167636, 0.00458318564753459, 0.00595336684669024, 
0.00487895959784154, 0.00292014352039067, 0.00238157929363119, 
0.0025305005154242, 0.00243334672392244, 0.00211201916980846, 
0.007410716639085, 0.0035528851408779, 0.00991898865707844, 0.00350148630982832, 
0.00181290043814611, 0.00277563808425691, 0.00766507891511477, 
0.000968375521552066, 0.000999909065815609, 0.00107669687622853 )), row.names = c(NA, -43L), class = c("tbl_df", "tbl", "data.frame" ))

Answer 1

I'm really not a big fan of the following approach (it would be more idiomatic to solve this using appropriate mappings) but you could solve this quickly by overriding the color / shape aesthetics in River and Type legends to your liking:

1. Modify your third point layer by moving the shape aesthetic inside aes and map from River:

aes(x = W_AC, y = BRI_mean_XS, shape = River)

2. Adjust the shape scale such that Roya is represented by a circle (16):

scale_shape_manual(values = c(15, 18, 17, 16, 16))

3. Override the aesthetics in the legend using guides():

 + guides(
    color = guide_legend(
        override.aes = list(shape = c(4, 16, 16))
    ),
    shape = guide_legend(
        override.aes = list(color = c(rep("black", 3), "cornflowerblue", "black"))
    )
  )

Result: