Introduction to DivInsight

library(DivInsight)
data("Colombia")

This is an introduction to the ‘DivInsight’ package.

We use ‘DivInsight’ to repurpose historical occurrence taxon data for further analysis.

Included in the package is the Colombia dataset, which contains occurrence data for the taxon ‘Formicidae’ at the Family level from 2000 to 2023. This data was queried from the Global Biodiversity Information Facility (GBIF) database using the rgbif package.

Each row of the occurrence dataframe has data for one observed individual. The dataset has many variables but the most important ones for the functions in this package pertain to taxa names, coordinate location, and dates of the observations.

head(Colombia[c(2:4, 31:32, 45)], 10)
#> # A tibble: 10 × 6
#>    scientificName        decimalLatitude decimalLongitude family genus eventDate
#>    <chr>                           <dbl>            <dbl> <chr>  <chr> <chr>    
#>  1 Hylomyrma transversa…          2.18              -71.2 Formi… Hylo… 2000-01-…
#>  2 Carebara Westwood, 1…          4.53              -75.6 Formi… Care… 2000-01-…
#>  3 Dolichoderus bispino…          2.18              -73.8 Formi… Doli… 2000-01-…
#>  4 Cephalotes marginatu…          0.0667            -72.4 Formi… Ceph… 2000-01-…
#>  5 Pheidole Westwood, 1…          4.36              -75.7 Formi… Phei… 2000-01-…
#>  6 Pheidole Westwood, 1…          4.36              -75.7 Formi… Phei… 2000-01-…
#>  7 Pheidole Westwood, 1…          4.36              -75.7 Formi… Phei… 2000-01-…
#>  8 Pheidole Westwood, 1…          4.36              -75.7 Formi… Phei… 2000-01-…
#>  9 Pheidole Westwood, 1…          4.36              -75.7 Formi… Phei… 2000-01-…
#> 10 Pheidole Westwood, 1…          0.248             -72.9 Formi… Phei… 2000-01-…

We can subset the Colombia dataset then perform the most important function in the package clusterise_sites() to cluster data by date and produce centered coordinates for each cluster.

These clusters of data can be considered sites.

# subset the dataframe by province name 
Colombia_Meta <- subset(Colombia, stateProvince == "Meta")

# cluster occurrence data by date and generate centred coordinates for each site
clusterised_Meta <- clusterise_sites(
  
  dataframe = Colombia_Meta,
  cluster_min_length = 30
  
)

Once the data has been ‘clusterised’ a dataframe, where each row pertains to a site, can be produced by using generate_stats(). This information includes date of observations, centred coordinates, and diversity indices. These indices include Species Richness (S), Shannon Diversity (H), Simpson Diversity (D), Inverse Simpson (Dinv), Margalef’s Diversity (d), and Pielou’s Evenness (J).

# generate stats 
stats_Meta <- generate_stats(clusterised_Meta)

# view the stats table
print(stats_Meta)
#>    longitude latitude site_group       date year month day  country
#> 1  -73.46702 4.058576          1 2000-10-01 2000    10   1 Colombia
#> 2  -73.46702 4.058576          1 2000-10-06 2000    10   6 Colombia
#> 3  -71.71407 4.322192          1 2012-05-01 2012     5   1 Colombia
#> 4  -72.96847 4.295741          1 2013-02-10 2013     2  10 Colombia
#> 5  -72.96847 4.295741          1 2013-02-11 2013     2  11 Colombia
#> 6  -72.96847 4.295741          1 2013-02-12 2013     2  12 Colombia
#> 7  -72.96847 4.295741          1 2013-02-13 2013     2  13 Colombia
#> 8  -72.97906 4.287842          1 2013-02-15 2013     2  15 Colombia
#> 9  -72.97054 4.288258          1 2013-02-16 2013     2  16 Colombia
#> 10 -72.97906 4.287842          1 2013-02-17 2013     2  17 Colombia
#> 11 -72.97466 4.285456          1 2013-02-18 2013     2  18 Colombia
#> 12 -72.96518 4.273713          1 2013-02-21 2013     2  21 Colombia
#> 13 -72.96660 4.272737          1 2013-02-22 2013     2  22 Colombia
#> 14 -72.96733 4.273370          1 2013-02-23 2013     2  23 Colombia
#> 15 -72.97047 4.275363          1 2013-02-24 2013     2  24 Colombia
#> 16 -72.96566 4.458016          1 2013-03-03 2013     3   3 Colombia
#> 17 -72.96566 4.458016          1 2013-03-04 2013     3   4 Colombia
#> 18 -72.96566 4.458016          1 2013-03-05 2013     3   5 Colombia
#> 19 -72.96566 4.458016          1 2013-03-06 2013     3   6 Colombia
#> 20 -72.96038 4.401621          1 2013-03-08 2013     3   8 Colombia
#> 21 -72.96413 4.403583          1 2013-03-09 2013     3   9 Colombia
#> 22 -72.96038 4.401621          1 2013-03-10 2013     3  10 Colombia
#> 23 -72.81086 4.357411          1 2013-03-11 2013     3  11 Colombia
#> 24 -72.97800 4.445970          1 2013-03-13 2013     3  13 Colombia
#> 25 -72.97800 4.445970          1 2013-03-14 2013     3  14 Colombia
#> 26 -72.97800 4.445970          1 2013-03-15 2013     3  15 Colombia
#> 27 -72.97800 4.445970          1 2013-03-16 2013     3  16 Colombia
#> 28 -71.81433 4.530222          1 2015-09-16 2015     9  16 Colombia
#> 29 -72.36711 4.377956          1 2015-10-13 2015    10  13 Colombia
#> 30 -73.06123 4.134214          1 2015-11-19 2015    11  19 Colombia
#> 31 -73.06123 4.134213          1 2016-02-15 2016     2  15 Colombia
#> 32 -73.20257 4.042752          1 2016-02-20 2016     2  20 Colombia
#> 33 -72.91989 4.225658          1 2016-02-24 2016     2  24 Colombia
#> 34 -73.58081 4.077551          1 2016-03-21 2016     3  21 Colombia
#> 35 -73.61314 4.094075          1 2016-04-12 2016     4  12 Colombia
#> 36 -73.47471 4.073413          1 2016-05-24 2016     5  24 Colombia
#> 37 -73.47267 4.073333          1 2016-06-13 2016     6  13 Colombia
#> 38 -73.47267 4.073333          1 2016-08-03 2016     8   3 Colombia
#> 39 -72.02722 4.171914          1 2017-05-22 2017     5  22 Colombia
#> 40 -73.40181 3.531730          1 2017-08-28 2017     8  28 Colombia
#> 41 -73.40181 3.531730          1 2019-04-08 2019     4   8 Colombia
#> 42 -71.43081 3.814218          1 2021-06-26 2021     6  26 Colombia
#> 43 -71.39631 3.821191          1 2021-06-27 2021     6  27 Colombia
#> 44 -71.52242 3.857269          1 2021-06-29 2021     6  29 Colombia
#> 45 -73.58722 3.884813          1 2021-07-07 2021     7   7 Colombia
#> 46 -73.36824 4.083131          1 2022-11-09 2022    11   9 Colombia
#> 47 -73.38409 4.080567          1 2022-11-11 2022    11  11 Colombia
#> 48 -73.37865 4.091503          1 2022-11-14 2022    11  14 Colombia
#>    stateProvince  kingdom     phylum   class  S         H          D      Dinv
#> 1           Meta Animalia Arthropoda Insecta  6 1.4554681 0.72163265  3.592375
#> 2           Meta Animalia Arthropoda Insecta 14 1.9166250 0.79163828  4.799346
#> 3           Meta Animalia Arthropoda Insecta 39 3.2055799 0.93252811 14.820988
#> 4           Meta Animalia Arthropoda Insecta 39 3.0140953 0.92458580 13.260102
#> 5           Meta Animalia Arthropoda Insecta 38 3.0036330 0.92388605 13.138196
#> 6           Meta Animalia Arthropoda Insecta 36 2.9239033 0.91554923 11.841218
#> 7           Meta Animalia Arthropoda Insecta 29 2.6783249 0.89443445  9.472788
#> 8           Meta Animalia Arthropoda Insecta 46 2.8900896 0.89944368  9.944676
#> 9           Meta Animalia Arthropoda Insecta 38 2.8284995 0.90380918 10.396003
#> 10          Meta Animalia Arthropoda Insecta 36 2.8605812 0.90954877 11.055682
#> 11          Meta Animalia Arthropoda Insecta 40 2.9372944 0.90670360 10.718527
#> 12          Meta Animalia Arthropoda Insecta 41 3.0222843 0.91674944 12.011932
#> 13          Meta Animalia Arthropoda Insecta 37 3.0079504 0.92719723 13.735741
#> 14          Meta Animalia Arthropoda Insecta 28 2.8212660 0.91321303 11.522468
#> 15          Meta Animalia Arthropoda Insecta 32 2.9894666 0.92975386 14.235658
#> 16          Meta Animalia Arthropoda Insecta 41 2.9208988 0.90771986 10.836568
#> 17          Meta Animalia Arthropoda Insecta 34 2.8824013 0.89953361  9.953577
#> 18          Meta Animalia Arthropoda Insecta 23 2.7431849 0.91005291 11.117647
#> 19          Meta Animalia Arthropoda Insecta 29 2.8735577 0.91852679 12.273973
#> 20          Meta Animalia Arthropoda Insecta 26 2.8644476 0.91440114 11.682399
#> 21          Meta Animalia Arthropoda Insecta 29 2.8614421 0.91626298 11.942149
#> 22          Meta Animalia Arthropoda Insecta 22 2.7231352 0.90634755 10.677778
#> 23          Meta Animalia Arthropoda Insecta 24 2.6264652 0.88439688  8.650286
#> 24          Meta Animalia Arthropoda Insecta 29 2.7966825 0.90751038 10.812024
#> 25          Meta Animalia Arthropoda Insecta 23 2.4984047 0.88042624  8.363039
#> 26          Meta Animalia Arthropoda Insecta 29 2.6708233 0.89128837  9.198648
#> 27          Meta Animalia Arthropoda Insecta 37 2.8380258 0.90012856 10.012872
#> 28          Meta Animalia Arthropoda Insecta 24 2.6942649 0.91520000 11.792453
#> 29          Meta Animalia Arthropoda Insecta 41 3.1788165 0.93347953 15.032967
#> 30          Meta Animalia Arthropoda Insecta 46 2.9783477 0.89543679  9.563593
#> 31          Meta Animalia Arthropoda Insecta 23 2.7363603 0.92062958 12.599152
#> 32          Meta Animalia Arthropoda Insecta 44 2.8179889 0.87304462  7.876783
#> 33          Meta Animalia Arthropoda Insecta 34 2.9850803 0.91651056 11.977563
#> 34          Meta Animalia Arthropoda Insecta 26 2.9013485 0.93008091 14.302245
#> 35          Meta Animalia Arthropoda Insecta 20 2.6732659 0.91438763 11.680556
#> 36          Meta Animalia Arthropoda Insecta 14 2.4354516 0.89640441  9.652921
#> 37          Meta Animalia Arthropoda Insecta 16 2.5922425 0.91358025 11.571429
#> 38          Meta Animalia Arthropoda Insecta 14 2.4592217 0.89990817  9.990826
#> 39          Meta Animalia Arthropoda Insecta 28 2.6557610 0.89420647  9.452374
#> 40          Meta Animalia Arthropoda Insecta  3 0.2287207 0.09399167  1.103743
#> 41          Meta Animalia Arthropoda Insecta  2 0.3144922 0.17233560  1.208219
#> 42          Meta Animalia Arthropoda Insecta 19 2.6588110 0.91257244 11.438040
#> 43          Meta Animalia Arthropoda Insecta 22 2.9475759 0.93990930 16.641509
#> 44          Meta Animalia Arthropoda Insecta 59 3.7035920 0.96465093 28.289286
#> 45          Meta Animalia Arthropoda Insecta 44 3.6045092 0.96810019 31.348148
#> 46          Meta Animalia Arthropoda Insecta 54 3.7640463 0.97139200 34.955257
#> 47          Meta Animalia Arthropoda Insecta 57 3.7593478 0.96989166 33.213389
#> 48          Meta Animalia Arthropoda Insecta 31 3.2345501 0.95361578 21.559055
#>             d         J day_length
#> 1   1.4063321 0.8123122   12.08078
#> 2   2.5400578 0.7262537   12.06269
#> 3   8.2879541 0.8749900   12.27170
#> 4   6.8336946 0.8227227   11.96557
#> 5   7.0876395 0.8257215   11.96886
#> 6   6.9048454 0.8159307   11.97218
#> 7   5.5807132 0.7953934   11.97554
#> 8   7.7844658 0.7548603   11.98260
#> 9   6.6311454 0.7775760   11.98603
#> 10  6.5514433 0.7982604   11.98952
#> 11  7.4327847 0.7962566   11.99309
#> 12  7.6006754 0.8138483   12.00404
#> 13  7.0096209 0.8330154   12.00766
#> 14  5.6107576 0.8466665   12.01126
#> 15  6.3994225 0.8625777   12.01485
#> 16  7.5076820 0.7865469   12.03781
#> 17  6.7274519 0.8173870   12.04176
#> 18  5.3099890 0.8748812   12.04572
#> 19  5.9340906 0.8533725   12.04970
#> 20  5.3289589 0.8791782   12.05838
#> 21  6.3025429 0.8497745   12.06232
#> 22  5.0882763 0.8809763   12.06631
#> 23  5.1501283 0.8264382   12.07071
#> 24  5.9229327 0.8305426   12.07797
#> 25  4.7080689 0.7968137   12.08203
#> 26  5.7255626 0.7931656   12.08609
#> 27  7.0506041 0.7859569   12.09016
#> 28  4.4532339 0.8477719   12.14299
#> 29  7.3673703 0.8559997   12.03578
#> 30  8.1266541 0.7779124   11.92493
#> 31  4.0858056 0.8727046   11.98731
#> 32  7.6215364 0.7446743   12.00658
#> 33  6.4630537 0.8465046   12.01598
#> 34  5.5421810 0.8905042   12.11436
#> 35  4.6792924 0.8923581   12.19693
#> 36  3.2743184 0.9228491   12.32601
#> 37  4.1858297 0.9349539   12.35485
#> 38  3.7179957 0.9318561   12.28806
#> 39  4.7309407 0.7969982   12.32417
#> 40  0.5385650 0.2081906   12.19631
#> 41  0.2675464 0.4537163   12.16923
#> 42  3.7218674 0.9029941   12.34179
#> 43  4.7395325 0.9535863   12.34184
#> 44  9.8724568 0.9082913   12.34298
#> 45  9.5095114 0.9525181   12.33762
#> 46 10.9769172 0.9436103   11.95340
#> 47 11.5791430 0.9298294   11.94793
#> 48  6.9701548 0.9419226   11.93942

A chart can be produced to show date against diversity.

# plot trend charts 
plot_sites_trend_H(clusterised_object = clusterised_Meta, 
                   main_title = "Formicidae Diversity in the Meta Province")