Error in pts[gr, , drop = FALSE] : subscript out of bounds

Hi everyone :D, does anyone know how I can fix this error?

Error in pts[gr, , drop = FALSE] : subscript out of bounds

library(readxl)

Family <- data.frame (tibble::tribble(
  ~SampleID,       ~`1A`,       ~`1B`,       ~`1C`,       ~`1D`,       ~`1E`,       ~`1F`,       ~`1G`,       ~`1H`,       ~`2A`,       ~`2B`,       ~`2C`,       ~`2D`,       ~`2E`,       ~`2F`,       ~`2G`,       ~`2H`,       ~`3A`,       ~`3B`,       ~`3C`,       ~`3D`,       ~`3E`,       ~`3F`,       ~`3G`,       ~`3H`,       ~`4A`,       ~`4B`,       ~`4C`,       ~`4D`,       ~`4E`,       ~`4F`,       ~`4G`,       ~`4H`,       ~`5A`,       ~`5B`,       ~`5C`,       ~`5D`,       ~`5E`,       ~`5F`,       ~`5G`,       ~`5H`,       ~`6A`,       ~`6B`,       ~`6C`,       ~`6D`,       ~`6E`,       ~`6F`,       ~`6G`,       ~`6H`,       ~`7A`,       ~`7B`,       ~`7C`,       ~`7D`,       ~`7E`,       ~`7F`,       ~`7G`,       ~`7H`,       ~`8A`,       ~`8B`,       ~`8C`,       ~`8D`,       ~`8E`,       ~`8F`,       ~`8G`,       ~`8H`,       ~`9A`,       ~`9B`,       ~`9C`,       ~`9D`,       ~`9E`,       ~`9F`,       ~`9G`,       ~`9H`,      ~`10A`,      ~`10B`,      ~`10C`,      ~`10D`,      ~`10E`,      ~`10F`,      ~`10G`,      ~`10H`,      ~`11A`,      ~`11B`,      ~`11C`,      ~`11D`,      ~`11E`,      ~`11F`,      ~`11G`,      ~`11H`,      ~`12A`,      ~`12B`,      ~`12C`,      ~`12D`,      ~`12E`,      ~`12F`,      ~`12G`,      ~`12H`,
  "PS", 15.09523622, 15.55277853, 15.11741994,   14.554094, 15.35093463, 15.42427054, 15.95013804, 15.42427054, 15.64673681, 15.82226616, 15.89833728, 15.32111918, 15.19323748,  15.6327213, 15.42427054, 15.82409171, 15.33876286, 15.15083401, 15.66030063, 15.25702856, 15.45853597, 15.62976904, 15.42427054, 15.34240388, 15.41444138, 15.93324327, 15.97179819, 15.42427054, 15.42427054, 15.42427054, 15.14538555, 15.36670841, 14.94126609, 15.40831718,  15.0435571, 15.85328648, 15.48829559, 15.44315041, 14.91093192, 15.15380783, 15.42427054, 15.58703711, 15.60293689, 15.72780729, 15.28349865, 15.71357413, 15.42427054, 15.64458728, 14.77844862, 15.16413111, 15.42427054, 15.95385476, 15.41125872, 15.35216848, 14.77580595, 15.05406083, 15.65446864, 15.59127691,  16.0496112, 15.32687476, 15.39778217, 15.42427054, 14.80687584, 15.19724473, 15.15131767, 15.44183272, 15.07182702, 15.17657293,  15.2360694, 15.82949662, 14.86037304, 15.23637269, 15.72840703, 15.98632579,  15.3970053, 15.88057531, 15.42427054, 16.06577509, 15.20757486, 15.42427054, 14.78757775, 15.42427054, 15.03171609, 15.27112134, 15.70331648, 15.42427054, 14.85240441, 15.42861829, 16.08043349, 15.76110644, 16.12371583, 14.84752296, 15.35933445, 15.65058528, 15.18091094, 15.59099248,
  "IP", 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.38068709,  16.1299595, 16.31972059, 16.23200561, 16.29262826, 16.31972059, 16.31972059, 16.31972059, 16.40060928, 16.31972059, 16.27114993, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.43741032, 16.27004687, 16.17243104, 16.05397452, 16.31972059, 16.31972059, 16.31972059, 16.31972059,  16.1551641, 16.27912731, 16.68913472, 16.31972059, 16.31972059, 16.32830313, 16.34775976, 16.31972059, 16.31972059, 16.31972059, 16.25145003, 16.31972059, 16.36244763, 16.19753348, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.18461024, 16.32409956, 16.31972059, 16.31972059, 16.36517663, 16.37085899, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.31972059,  16.2969553, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.26498461, 16.31972059, 16.31972059, 16.31972059, 16.29075471, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.31711223, 16.16311975, 16.31972059, 16.31972059, 16.32351476, 16.34158427, 16.51249303, 16.31972059, 16.31972059, 16.31972059, 16.33774505, 16.38919092, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.31972059, 16.33387537, 16.31972059, 16.31972059, 16.31972059,
  "PU", 16.20844069, 15.64870257, 16.16151234, 16.08471445, 15.87474919, 15.98531311, 15.57029977,  15.8839279, 15.87474919, 15.86551539,    15.37963, 16.29787144, 15.87474919, 15.56819076, 15.87984026, 15.64234745, 16.18458009, 16.57731921, 15.64482559, 15.87474919, 15.87474919, 15.87474919, 15.90388237, 15.90368287, 16.40390938, 15.26156221, 15.32055595,  15.8854582, 16.08375487, 15.79791277, 15.93393468, 16.08708185, 15.87474919, 15.87474919, 16.03390029,  15.4207621, 15.78047026, 15.87474919, 16.19110155, 15.87474919, 15.88727667, 15.54155664, 15.82989846, 15.47835101, 16.19476791, 15.87474919, 15.85843405, 15.64286641,  16.1840485, 15.87474919, 15.78522972,  15.4706474, 16.01464195, 16.16397874, 16.20811279, 15.88031433, 15.87474919, 15.85762583, 15.04527395, 16.34586181, 16.45360506, 16.04628641, 16.29899651, 16.16140703, 15.90886578, 15.87474919, 15.97996124, 16.22832432, 16.14372983, 15.38089157, 15.90656313, 16.57936249, 15.45892533,  14.9354136, 16.18057749, 15.87474919, 15.95654009,  15.2916829, 16.09908404, 15.86322416, 15.87474919, 15.76604825, 16.13606026, 16.27354624, 15.74515198, 15.75320903, 15.87474919,  15.7642695, 14.77429269, 15.76687342, 14.99382061, 16.17836018, 15.87474919, 15.84613629, 16.09615514,  15.8003695
)
)

Metadata <- data.frame (tibble::tribble(
  ~SampleID, ~SamplingPoint,         ~Depth,      ~Month,
  "1A",         "CEA1",        "80 cm",      "July",
  "1B",         "CEA2",        "80 cm",      "July",
  "1C",         "CEA4", "Interstitial",      "July",
  "1D",         "CEA1",        "80 cm",    "August",
  "1E",         "CEA3",        "80 cm",    "August",
  "1F",         "CEA5",        "80 cm",    "August",
  "1G",         "CEA2",        "80 cm", "September",
  "1H",         "CEA4",        "80 cm", "September",
  "2A",         "CEA1",        "80 cm",      "July",
  "2B",         "CEA2", "Interstitial",      "July",
  "2C",         "CEA4", "Interstitial",      "July",
  "2D",         "CEA1",        "80 cm",    "August",
  "2E",         "CEA3",        "80 cm",    "August",
  "2F",         "CEA5",        "80 cm",    "August",
  "2G",         "CEA2",        "80 cm", "September",
  "2H",         "CEA4",        "80 cm", "September",
  "3A",         "CEA1", "Interstitial",      "July",
  "3B",         "CEA2", "Interstitial",      "July",
  "3C",         "CEA4",        "80 cm",      "July",
  "3D",         "CEA1", "Interstitial",    "August",
  "3E",         "CEA3", "Interstitial",    "August",
  "3F",         "CEA5", "Interstitial",    "August",
  "3G",         "CEA2", "Interstitial", "September",
  "3H",         "CEA4", "Interstitial", "September",
  "4A",         "CEA1", "Interstitial",      "July",
  "4B",         "CEA3",        "80 cm",      "July",
  "4C",         "CEA4", "Interstitial",      "July",
  "4D",         "CEA1", "Interstitial",    "August",
  "4E",         "CEA3", "Interstitial",    "August",
  "4F",         "CEA5", "Interstitial",    "August",
  "4G",         "CEA2", "Interstitial", "September",
  "4H",         "CEA4", "Interstitial", "September",
  "5A",         "CEA1",        "80 cm",      "July",
  "5B",         "CEA3",        "80 cm",      "July",
  "5C",         "CEA4", "Interstitial",      "July",
  "5D",         "CEA1",        "80 cm",    "August",
  "5E",         "CEA3",        "80 cm",    "August",
  "5F",         "CEA5",        "80 cm",    "August",
  "5G",         "CEA2",        "80 cm", "September",
  "5H",         "CEA4",        "80 cm", "September",
  "6A",         "CEA1",        "80 cm",      "July",
  "6B",         "CEA3", "Interstitial",      "July",
  "6C",         "CEA5",        "80 cm",      "July",
  "6D",         "CEA1",        "80 cm",    "August",
  "6E",         "CEA3", "Interstitial",    "August",
  "6F",         "CEA5", "Interstitial",    "August",
  "6G",         "CEA2", "Interstitial", "September",
  "6H",         "CEA4", "Interstitial", "September",
  "7A",         "CEA1", "Interstitial",      "July",
  "7B",         "CEA3", "Interstitial",      "July",
  "7C",         "CEA5",        "80 cm",      "July",
  "7D",         "CEA2",        "80 cm",    "August",
  "7E",         "CEA4",        "80 cm",    "August",
  "7F",         "CEA1",        "80 cm", "September",
  "7G",         "CEA3",        "80 cm", "September",
  "7H",         "CEA5",        "80 cm", "September",
  "8A",         "CEA1", "Interstitial",      "July",
  "8B",         "CEA3",        "80 cm",      "July",
  "8C",         "CEA5", "Interstitial",      "July",
  "8D",         "CEA2",        "80 cm",    "August",
  "8E",         "CEA4",        "80 cm",    "August",
  "8F",         "CEA1",        "80 cm", "September",
  "8G",         "CEA3",        "80 cm", "September",
  "8H",         "CEA5",        "80 cm", "September",
  "9A",         "CEA2",        "80 cm",      "July",
  "9B",         "CEA3", "Interstitial",      "July",
  "9C",         "CEA5", "Interstitial",      "July",
  "9D",         "CEA2", "Interstitial",    "August",
  "9E",         "CEA4", "Interstitial",    "August",
  "9F",         "CEA1", "Interstitial", "September",
  "9G",         "CEA3", "Interstitial", "September",
  "9H",         "CEA5", "Interstitial", "September",
  "10A",         "CEA2",        "80 cm",      "July",
  "10B",         "CEA3", "Interstitial",      "July",
  "10C",         "CEA5",        "80 cm",      "July",
  "10D",         "CEA2", "Interstitial",    "August",
  "10E",         "CEA4", "Interstitial",    "August",
  "10F",         "CEA1", "Interstitial", "September",
  "10G",         "CEA3", "Interstitial", "September",
  "10H",         "CEA5", "Interstitial", "September",
  "11A",         "CEA2", "Interstitial",      "July",
  "11B",         "CEA4",        "80 cm",      "July",
  "11C",         "CEA5", "Interstitial",      "July",
  "11D",         "CEA2",        "80 cm",    "August",
  "11E",         "CEA4",        "80 cm",    "August",
  "11F",         "CEA1",        "80 cm", "September",
  "11G",         "CEA3",        "80 cm", "September",
  "11H",         "CEA5",        "80 cm", "September",
  "12A",         "CEA2", "Interstitial",      "July",
  "12B",         "CEA4",        "80 cm",      "July",
  "12C",         "CEA1", "Interstitial",    "August",
  "12D",         "CEA2", "Interstitial",    "August",
  "12E",         "CEA4", "Interstitial",    "August",
  "12F",         "CEA1", "Interstitial", "September",
  "12G",         "CEA3", "Interstitial", "September",
  "12H",         "CEA5", "Interstitial", "September"
)
)
#Family <- t(Family)

attach(Family)
Family <- Family[,-1]
rownames(Family) <- SampleID

attach(Metadata)
#> The following object is masked from Family:
#> 
#>     SampleID
Metadata <- Metadata[,-1]
rownames(Metadata) <- SampleID


Metadata$Month <- factor(Metadata$Month,
                         levels = c("July", "August", "September"))

#remove the rare microbes. It keeps only the microbes that are present in at least 10% of the samples
dim(Family)
#> [1]  3 96

Family <- Family[,colMeans(Family) >=.1]

dim(Family)
#> [1]  3 96

library(vegan)
#> Loading required package: permute
#> Loading required package: lattice
#> This is vegan 2.5-6
#NMDS
#autotransform=F evita la transformaci?n de datos
#sratmax=0.999999 para que el an?lisis no se detenga antes de tiempo cuando se tienen muchos datos  
Family.mds <- metaMDS(Family, k=2, distance="bray", trymax=100, zerodist="add", autotransform=F)
#> Run 0 stress 0 
#> Run 1 stress 0 
#> ... Procrustes: rmse 0.1345849  max resid 0.1571215 
#> Run 2 stress 0 
#> ... Procrustes: rmse 0.1468844  max resid 0.1827923 
#> Run 3 stress 0 
#> ... Procrustes: rmse 0.1098086  max resid 0.1334504 
#> Run 4 stress 0 
#> ... Procrustes: rmse 0.1313742  max resid 0.1672068 
#> Run 5 stress 0 
#> ... Procrustes: rmse 0.09406877  max resid 0.1117154 
#> Run 6 stress 0 
#> ... Procrustes: rmse 0.1436202  max resid 0.1704672 
#> Run 7 stress 0 
#> ... Procrustes: rmse 0.1061797  max resid 0.1250528 
#> Run 8 stress 0 
#> ... Procrustes: rmse 0.065344  max resid 0.08156737 
#> Run 9 stress 0 
#> ... Procrustes: rmse 0.1522574  max resid 0.2125494 
#> Run 10 stress 0 
#> ... Procrustes: rmse 0.2055193  max resid 0.2714054 
#> Run 11 stress 0 
#> ... Procrustes: rmse 0.2100263  max resid 0.293609 
#> Run 12 stress 0 
#> ... Procrustes: rmse 0.1987479  max resid 0.2068764 
#> Run 13 stress 0 
#> ... Procrustes: rmse 0.1371842  max resid 0.1810412 
#> Run 14 stress 0 
#> ... Procrustes: rmse 0.1130561  max resid 0.1302699 
#> Run 15 stress 0 
#> ... Procrustes: rmse 0.2269855  max resid 0.2939715 
#> Run 16 stress 0 
#> ... Procrustes: rmse 0.191206  max resid 0.2006544 
#> Run 17 stress 0 
#> ... Procrustes: rmse 0.2026041  max resid 0.2111073 
#> Run 18 stress 0 
#> ... Procrustes: rmse 0.06649483  max resid 0.08095242 
#> Run 19 stress 0 
#> ... Procrustes: rmse 0.1123245  max resid 0.1296081 
#> Run 20 stress 0 
#> ... Procrustes: rmse 0.0402027  max resid 0.05011029 
#> Run 21 stress 0 
#> ... Procrustes: rmse 0.1102389  max resid 0.1280593 
#> Run 22 stress 0 
#> ... Procrustes: rmse 0.2595968  max resid 0.3187138 
#> Run 23 stress 0 
#> ... Procrustes: rmse 0.1418331  max resid 0.1635621 
#> Run 24 stress 0 
#> ... Procrustes: rmse 0.1657882  max resid 0.2194089 
#> Run 25 stress 0 
#> ... Procrustes: rmse 0.1332451  max resid 0.1496957 
#> Run 26 stress 0 
#> ... Procrustes: rmse 0.2096469  max resid 0.2599741 
#> Run 27 stress 0 
#> ... Procrustes: rmse 0.06364608  max resid 0.07761915 
#> Run 28 stress 0 
#> ... Procrustes: rmse 0.09055523  max resid 0.1112096 
#> Run 29 stress 0 
#> ... Procrustes: rmse 0.1312138  max resid 0.1494752 
#> Run 30 stress 0 
#> ... Procrustes: rmse 0.1309514  max resid 0.148171 
#> Run 31 stress 0 
#> ... Procrustes: rmse 0.05396184  max resid 0.06712616 
#> Run 32 stress 0 
#> ... Procrustes: rmse 0.02480955  max resid 0.03243993 
#> Run 33 stress 0 
#> ... Procrustes: rmse 0.1166931  max resid 0.1390499 
#> Run 34 stress 0 
#> ... Procrustes: rmse 0.09566429  max resid 0.1302332 
#> Run 35 stress 0 
#> ... Procrustes: rmse 0.1178524  max resid 0.1571025 
#> Run 36 stress 0 
#> ... Procrustes: rmse 0.08262255  max resid 0.1009439 
#> Run 37 stress 0 
#> ... Procrustes: rmse 0.1866796  max resid 0.1994117 
#> Run 38 stress 0 
#> ... Procrustes: rmse 0.1146671  max resid 0.1317499 
#> Run 39 stress 0 
#> ... Procrustes: rmse 0.244136  max resid 0.3120145 
#> Run 40 stress 0 
#> ... Procrustes: rmse 0.03765585  max resid 0.04873949 
#> Run 41 stress 0 
#> ... Procrustes: rmse 0.1375493  max resid 0.159684 
#> Run 42 stress 0 
#> ... Procrustes: rmse 0.04855299  max resid 0.06061591 
#> Run 43 stress 0 
#> ... Procrustes: rmse 0.07242498  max resid 0.09028123 
#> Run 44 stress 0 
#> ... Procrustes: rmse 0.185853  max resid 0.2395485 
#> Run 45 stress 0 
#> ... Procrustes: rmse 0.2325602  max resid 0.3048931 
#> Run 46 stress 0 
#> ... Procrustes: rmse 0.112971  max resid 0.136291 
#> Run 47 stress 0 
#> ... Procrustes: rmse 0.08997876  max resid 0.1203304 
#> Run 48 stress 0 
#> ... Procrustes: rmse 0.2047959  max resid 0.2613437 
#> Run 49 stress 0 
#> ... Procrustes: rmse 0.04408303  max resid 0.05474143 
#> Run 50 stress 0 
#> ... Procrustes: rmse 0.168473  max resid 0.1849309 
#> Run 51 stress 0 
#> ... Procrustes: rmse 0.1125476  max resid 0.1297432 
#> Run 52 stress 0 
#> ... Procrustes: rmse 0.1168605  max resid 0.1343475 
#> Run 53 stress 0 
#> ... Procrustes: rmse 0.1914945  max resid 0.2014449 
#> Run 54 stress 0 
#> ... Procrustes: rmse 0.09439259  max resid 0.1153946 
#> Run 55 stress 0 
#> ... Procrustes: rmse 0.1023114  max resid 0.1238863 
#> Run 56 stress 0 
#> ... Procrustes: rmse 0.2180059  max resid 0.3062894 
#> Run 57 stress 0 
#> ... Procrustes: rmse 0.1845164  max resid 0.1970389 
#> Run 58 stress 0 
#> ... Procrustes: rmse 0.05031243  max resid 0.06690046 
#> Run 59 stress 0 
#> ... Procrustes: rmse 0.1913063  max resid 0.2639918 
#> Run 60 stress 0 
#> ... Procrustes: rmse 0.0343796  max resid 0.04395151 
#> Run 61 stress 0 
#> ... Procrustes: rmse 0.09514829  max resid 0.1136443 
#> Run 62 stress 0 
#> ... Procrustes: rmse 0.1731753  max resid 0.1849838 
#> Run 63 stress 0 
#> ... Procrustes: rmse 0.1101407  max resid 0.1275992 
#> Run 64 stress 0 
#> ... Procrustes: rmse 0.08100763  max resid 0.1034807 
#> Run 65 stress 0 
#> ... Procrustes: rmse 0.1401588  max resid 0.1584736 
#> Run 66 stress 0 
#> ... Procrustes: rmse 0.1123464  max resid 0.1347515 
#> Run 67 stress 0 
#> ... Procrustes: rmse 0.09334535  max resid 0.1103313 
#> Run 68 stress 0 
#> ... Procrustes: rmse 0.05576913  max resid 0.06960781 
#> Run 69 stress 0 
#> ... Procrustes: rmse 0.1193046  max resid 0.1369925 
#> Run 70 stress 0 
#> ... Procrustes: rmse 0.1456745  max resid 0.1855471 
#> Run 71 stress 0 
#> ... Procrustes: rmse 0.1011683  max resid 0.1216855 
#> Run 72 stress 0 
#> ... Procrustes: rmse 0.1846276  max resid 0.2471383 
#> Run 73 stress 0 
#> ... Procrustes: rmse 0.1473411  max resid 0.1683475 
#> Run 74 stress 0 
#> ... Procrustes: rmse 0.07551493  max resid 0.09403339 
#> Run 75 stress 0 
#> ... Procrustes: rmse 0.09537604  max resid 0.1279359 
#> Run 76 stress 0 
#> ... Procrustes: rmse 0.1172307  max resid 0.1403762 
#> Run 77 stress 0 
#> ... Procrustes: rmse 0.08916962  max resid 0.1058538 
#> Run 78 stress 0 
#> ... Procrustes: rmse 0.06390933  max resid 0.07784681 
#> Run 79 stress 0 
#> ... Procrustes: rmse 0.1435814  max resid 0.1958457 
#> Run 80 stress 0 
#> ... Procrustes: rmse 0.1186567  max resid 0.163922 
#> Run 81 stress 0 
#> ... Procrustes: rmse 0.0814758  max resid 0.10752 
#> Run 82 stress 0 
#> ... Procrustes: rmse 0.1443218  max resid 0.1597057 
#> Run 83 stress 0 
#> ... Procrustes: rmse 0.1206594  max resid 0.1401694 
#> Run 84 stress 0 
#> ... Procrustes: rmse 0.1162707  max resid 0.1497814 
#> Run 85 stress 0 
#> ... Procrustes: rmse 0.1054799  max resid 0.1448007 
#> Run 86 stress 0 
#> ... Procrustes: rmse 0.126263  max resid 0.158324 
#> Run 87 stress 0 
#> ... Procrustes: rmse 0.04267561  max resid 0.05496852 
#> Run 88 stress 0 
#> ... Procrustes: rmse 0.1814412  max resid 0.2449821 
#> Run 89 stress 0 
#> ... Procrustes: rmse 0.2069519  max resid 0.2130278 
#> Run 90 stress 0 
#> ... Procrustes: rmse 0.1180169  max resid 0.1350293 
#> Run 91 stress 0 
#> ... Procrustes: rmse 0.1578048  max resid 0.1897543 
#> Run 92 stress 0 
#> ... Procrustes: rmse 0.170893  max resid 0.1850118 
#> Run 93 stress 0 
#> ... Procrustes: rmse 0.1579841  max resid 0.2099756 
#> Run 94 stress 0 
#> ... Procrustes: rmse 0.147012  max resid 0.182826 
#> Run 95 stress 0 
#> ... Procrustes: rmse 0.1566814  max resid 0.1761605 
#> Run 96 stress 0 
#> ... Procrustes: rmse 0.04060925  max resid 0.05121645 
#> Run 97 stress 0 
#> ... Procrustes: rmse 0.1164699  max resid 0.1378495 
#> Run 98 stress 0 
#> ... Procrustes: rmse 0.03551943  max resid 0.04579404 
#> Run 99 stress 0 
#> ... Procrustes: rmse 0.2135406  max resid 0.2815361 
#> Run 100 stress 0 
#> ... Procrustes: rmse 0.1365829  max resid 0.1553028 
#> *** No convergence -- monoMDS stopping criteria:
#>    100: stress < smin
#> Warning in metaMDS(Family, k = 2, distance = "bray", trymax = 100, zerodist =
#> "add", : stress is (nearly) zero: you may have insufficient data
#> Warning in postMDS(out$points, dis, plot = max(0, plot - 1), ...): skipping
#> half-change scaling: too few points below threshold
stressplot(Family.mds)

#add the metadata information
##THIS HAS TO BE IN THE SAME ORDER IN THE METADATA FILE AND IN THE COUNTS FILE
colvec<- c("yellowgreen","turquoise4", "tomato2")
plot(Family.mds, type="n", xlim=c(-.5,.5), ylim=c(-0.6,0.6))

pl <-ordiellipse(Family.mds, Metadata$Month, kind="se", conf=0.95, lwd=2, col="gray30", label=T)
#> Error in pts[gr, , drop = FALSE]: subíndice fuera de  los límites

Created on 2021-07-08 by the reprex package (v0.3.0)

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