Ant community composition in 24 islands in the Thousands Island Lake, China.

https://emilio-berti.github.io/datasets/ants.zip

islands <- read.csv("islands.csv")
head(islands, 3)

  island longitude latitude
1     S1  118.8865 29.52810
2     S2  118.8525 29.49686
3     S3  118.9067 29.50562

• island is the ID of the island (as in the prevous figure).
• longitude and latitude are the coordinates of the islands.

traits <- read.csv("ant_traits.csv")
head(traits, 3)

  torax_length eye_width leg_length scape_length mandible_length
1    0.8844444  0.000000   1.458398    0.4617310       0.3879327
2    1.1768278  0.000000   1.552939    0.5216261       0.3639346
3    2.0600444  0.114711   1.361409    0.6837751       0.5864359

composition <- read.csv("ant_composition.csv")
composition[1:3, 1:4]

  island Aenictus_fuchuanensis Aenictus_laeviceps Anochetus_risii
1     S1                     1                  1               1
2    S10                     1                  1               1
3    S11                     0                  1               1

• island is the ID of the island (as in islands.csv)
• Other columns show the presence (1) or absence (0) of each species (one column = one species) in the islands.

Can you identify the general differences between ant species in morhpological traits?

Hint: Use a PCA approach (prcomp()) and the traits table (ant_traits.csv).

Can you arrange the islands in a plot ordering them by similarity in species composition?

Hint: Use a nMDS approach (MASS::isoMDS()) and the composition table (ant_composition.csv).

Tip: Because you have presence/absence data, distance between communities should be calculated using an appropriate method, such a the Jaccard dissimilarity. In R, this can be done specifying method = "binary" in dist(), e.g., dist(<table>, method = "binary").

Can you identify a spatial gradient in the dissimilarities of ant composition between islands?

Hint: Plot the nMDS axes against longitude and latitude from the islands table (islands.csv).

Can you identify the general differences between ant species in morhpological traits?

Can you identify the general differences between ant species in morhpological traits?

Hint: Use a PCA approach (prcomp()) and the traits table (ant_traits.csv).

pca_traits <- prcomp(traits, scale = TRUE, center = TRUE)
summary(pca_traits)

Importance of components:
                          PC1    PC2    PC3     PC4     PC5
Standard deviation     1.5656 1.0923 0.8970 0.66494 0.33020
Proportion of Variance 0.4903 0.2386 0.1609 0.08843 0.02181
Cumulative Proportion  0.4903 0.7289 0.8898 0.97819 1.00000

biplot(pca_traits, xlabs = rep("+", nrow(traits)), col = c("grey20", "blue"))

pairs(traits, pch = 20, cex = 1, lower.panel = panel.smooth, upper.panel = panel.cor)

Gradient from ants with short body but long mandibles to ants with long body but short mandibles to ants.

Can you arrange the islands in a plot ordering them by similarity in species composition?

jaccard <- dist(composition[, -1], method = "binary")
nMDS <- MASS::isoMDS(jaccard, k = 2)

The first 2 PCs explain 75% of the variability. I am happy with that and continue with only thos two PCs.

Gradient from ants with short body but long mandibles to ants with long body but short mandibles to ants.

Two species as example.

Can you arrange the islands in a plot ordering them by similarity in species composition?

We then can run a nMDS using MASS::isoMDS().

nMDS <- MASS::isoMDS(jaccard)

initial  value 27.717339 
iter   5 value 24.592216
final  value 24.496130 
converged

plot(nMDS$points, pch = 20, asp = 1)
text(nMDS$points, labels = composition[, 1], adj = c(0.5, -0.5))

Can you identify a spatial gradient in the dissimilarities of ant composition between islands?

And we obtain the ordering of the islands on a plot.

plot(nMDS$points, pch = 20, asp = 1)
text(nMDS$points, labels = composition[, 1], adj = c(0.5, -0.5))

Can you identify a spatial gradient in the dissimilarities of ant composition between islands?

No clear spatial pattern from this.