Removes or flags records within Artificial Hotspot Occurrence Inventory. Poorly geo-referenced occurrence records in biological databases are often erroneously geo-referenced to highly recurring coordinates that were assessed by Park et al 2022. See the reference for more details.
Usage
cc_aohi(
x,
lon = "decimalLongitude",
lat = "decimalLatitude",
species = "species",
taxa = c("Aves", "Insecta", "Mammalia", "Plantae"),
buffer = 10000,
geod = TRUE,
value = "clean",
verbose = TRUE
)Arguments
- x
data.frame. Containing geographical coordinates and species names.
- lon
character string. The column with the longitude coordinates. Default = “decimalLongitude”.
- lat
character string. The column with the latitude coordinates. Default = “decimalLatitude”.
- species
character string. The column with the species identity. Only required if verify = TRUE.
- taxa
Artificial Hotspot Occurrence Inventory (AHOI) were created based on four different taxa, birds, insecta, mammalia, and plantae. Users can choose to keep all, or any specific taxa subset to define the AHOI locations. Default is to keep all: c("Aves", "Insecta", "Mammalia", "Plantae").
- buffer
The buffer around each capital coordinate (the centre of the city), where records should be flagged as problematic. Units depend on geod. Default = 10 kilometres.
- geod
logical. If TRUE the radius around each capital is calculated based on a sphere, buffer is in meters and independent of latitude. If FALSE the radius is calculated assuming planar coordinates and varies slightly with latitude. Default = TRUE. See https://seethedatablog.wordpress.com/ for detail and credits.
- value
character string. Defining the output value. See value.
- verbose
logical. If TRUE reports the name of the test and the number of records flagged.
Value
Depending on the ‘value’ argument, either a data.frame
containing the records considered correct by the test (“clean”) or a logical vector (“flagged”), with TRUE = test passed and FALSE = test failed/potentially problematic . Default = “clean”.
Note
See https://ropensci.github.io/CoordinateCleaner/ for more details and tutorials.
References
Park, D. S., Xie, Y., Thammavong, H. T., Tulaiha, R., & Feng, X. (2023). Artificial Hotspot Occurrence Inventory (AHOI). Journal of Biogeography, 50, 441–449. doi:10.1111/jbi.14543
Examples
x <- data.frame(species = letters[1:10],
decimalLongitude = c(runif(99, -180, 180), -47.92),
decimalLatitude = c(runif(99, -90,90), -15.78))
cc_aohi(x)
#> Testing Artificial Hotspot Occurrence Inventory
#> Removed 0 records.
#> species decimalLongitude decimalLatitude
#> 1 a -150.9299505 -5.51082603
#> 2 b 120.3598934 55.02240553
#> 3 c 36.2739190 56.52923581
#> 4 d -123.4049611 -17.29601964
#> 5 e -177.3362012 -50.68241843
#> 6 f -12.0983410 -14.69494758
#> 7 g -0.8001401 30.39673460
#> 8 h -75.6837919 1.37705076
#> 9 i 83.8375153 28.86467517
#> 10 j 98.1077440 2.12243648
#> 11 a 134.8562379 60.39943866
#> 12 b -117.0213743 37.58060904
#> 13 c -167.6731202 67.35706936
#> 14 d -64.6611369 -87.93368317
#> 15 e -35.1618342 69.88492223
#> 16 f -109.5588595 89.34244540
#> 17 g -34.7262777 0.03447016
#> 18 h -157.0818754 -25.38593561
#> 19 i -40.0675273 49.48434401
#> 20 j 171.1972207 15.20554516
#> 21 a -75.6387737 24.11574678
#> 22 b 64.2169539 64.55990786
#> 23 c 84.7150556 12.04098097
#> 24 d -109.4555761 -44.46053652
#> 25 e 172.9942829 75.38457862
#> 26 f 86.9477505 66.12303687
#> 27 g -161.4793405 -45.26303456
#> 28 h 10.8764869 -17.48138187
#> 29 i 70.4965964 48.53343168
#> 30 j 67.8801612 -68.49263258
#> 31 a -168.7570829 -54.95490690
#> 32 b -98.7974876 -60.37753532
#> 33 c -71.7009098 29.37718463
#> 34 d 49.1276214 64.18350081
#> 35 e -7.5511621 76.77836071
#> 36 f -24.4183471 9.42796703
#> 37 g 74.3161816 13.87182499
#> 38 h 161.4875675 33.74059421
#> 39 i -115.0780435 -45.95071867
#> 40 j -101.9160445 -81.96891150
#> 41 a 64.8586503 73.77382020
#> 42 b -0.4155802 -77.27738054
#> 43 c 51.0045654 89.44046522
#> 44 d 57.7023657 20.13343514
#> 45 e -145.4313031 -58.93940777
#> 46 f 95.6160590 73.69937373
#> 47 g 97.0829295 -83.25878996
#> 48 h 176.6564324 16.83968226
#> 49 i 169.3875250 -47.34404013
#> 50 j -39.8942062 73.13350801
#> 51 a -13.9728727 57.39713713
#> 52 b -66.5129691 35.96928430
#> 53 c -117.1166782 -50.39994074
#> 54 d 11.3664747 41.03836890
#> 55 e -2.2906742 -50.92479679
#> 56 f 100.5511053 -7.87856431
#> 57 g -106.4957966 -30.09604351
#> 58 h 76.8230204 12.30348034
#> 59 i -156.5221998 -44.60296953
#> 60 j -52.4855524 -6.47755799
#> 61 a 117.0717916 75.17889124
#> 62 b -81.4254317 85.11195922
#> 63 c 25.2161824 57.43484039
#> 64 d -59.1411310 72.52628367
#> 65 e 34.6546040 14.64588792
#> 66 f -111.0535087 49.14152660
#> 67 g 161.1950176 89.12214476
#> 68 h 15.2929471 37.97482495
#> 69 i 16.0572216 -51.31033278
#> 70 j -79.7050246 -37.48362661
#> 71 a -19.1871111 39.91675128
#> 72 b -46.2559736 65.99082660
#> 73 c -169.8980492 -47.07844083
#> 74 d -12.2446113 -89.19066455
#> 75 e -39.5887006 79.83296356
#> 76 f -172.7765216 -11.13530392
#> 77 g -44.2904660 45.10859908
#> 78 h 21.5686224 30.20683760
#> 79 i 128.5500910 -16.56482373
#> 80 j -41.4685040 -26.77521331
#> 81 a 10.0501328 42.85648107
#> 82 b 36.2295085 29.57138871
#> 83 c -85.9063110 -74.65955397
#> 84 d -75.5819418 64.10378820
#> 85 e -7.1729374 -76.14300210
#> 86 f 151.2019966 63.51206461
#> 87 g -35.7407335 -70.85754704
#> 88 h -103.2578240 -2.73549177
#> 89 i 61.8360537 -45.50056013
#> 90 j -158.8989200 33.58245791
#> 91 a 178.9448887 -60.54782433
#> 92 b -126.3472318 81.50846397
#> 93 c 6.6803888 -32.06618080
#> 94 d 124.6032197 -24.92385898
#> 95 e 78.5771007 69.79021515
#> 96 f -93.1269528 59.04259520
#> 97 g 16.9356126 -71.88183761
#> 98 h 120.5286535 73.08928400
#> 99 i -169.9358308 49.09146560
#> 100 j -47.9200000 -15.78000000