Codificación por color 95% de elipsis de confianza para centroides

Question

He trazado los centroides para un índice de similitud de Gower utilizando el paquete vegan{} en R y me gustaría aplicar el código de color a los rellenos de elipse en función de los factores de mi conjunto de datos original. Los centroides son para combinaciones de Mes-Sitio (y estos son los únicos centroides que quiero trazar, vea la muestra de datos a continuación), pero quiero codificar con colores las elipses por Mes y luego, en una segunda gráfica, por sitio, para mostrar las diferencias entre factores. En el momento en que el código es el siguiente:

dat.fac<-dat[,1:7] ##factors 

dat.mgower <- vegdist(decostand(dat[,8:34], "log"), "altGower") 
ord<-capscale(dat.mgower~1)  #Does the PCO 

plot(ord, display = "sites", type = "n") 

#for i in 
stats<-with(dat.fac, 
    ordiellipse(ord, Site_TP, kind="se", conf=0.95, 
    lwd=2, draw = "polygon",col="#0000ff22",border = "blue")) 

La trama MDS con los centroides se parece a esto:

Me gustaría ser capaz de código de color de los rellenos de los centroides basado en a) Sitio yb) temporada (mayo vs. septiembre). He intentado usar col=c("#0000ff22","#CAFF7022",...) pero esto no funciona porque las coordenadas para las elipses están en ord. También he intentado

with(dat.fac,ordiellipse(ord, Site_TP[1:54], kind="se", conf=0.95, 
    lwd=2, draw = "polygon",col="#0000ff22",border = "blue")) 

para obtener la primera mitad de los ceentroids a ser de un solo color (la primera mitad son todos del mismo mes), pero esto resulta en el error "Error en cov.wt (X , W): 'x' debe contener solo valores finitos. " Ayuda! Gracias.

Los datos se parece a esto:

structure(list(Core_num = structure(c(39L, 50L, 61L, 70L, 71L, 
72L, 73L, 74L, 75L, 76L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 
93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 103L, 104L, 
105L, 106L, 107L, 108L, 112L, 113L, 115L, 116L, 117L, 118L, 119L, 
120L, 121L, 122L, 123L, 124L, 125L, 126L, 127L, 128L, 129L, 130L, 
131L, 132L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 17L, 18L, 
19L, 20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 
32L, 33L, 34L, 35L, 36L, 37L, 38L, 40L, 44L, 45L, 46L, 47L, 48L, 
49L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 62L, 63L, 
64L, 65L, 66L), .Label = c("152", "153", "154", "155", "156", 
"157", "158", "159", "160", "161", "162", "163", "164", "165", 
"166", "167", "168", "169", "170", "171", "172", "173", "174", 
"175", "176", "177", "178", "179", "180", "181", "182", "183", 
"184", "185", "186", "187", "188", "189", "19", "190", "191", 
"192", "193", "194", "195", "196", "197", "198", "199", "20", 
"200", "201", "202", "203", "204", "205", "206", "207", "208", 
"209", "21", "210", "211", "212", "213", "214", "215", "216", 
"217", "22", "23", "24", "25", "26", "27", "28", "29", "30", 
"31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", 
"42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", 
"53", "54", "55", "56", "57", "58", "59", "60", "61", "62", "63", 
"64", "65", "66", "67", "68", "69", "70", "71", "72", "73", "74", 
"75", "76", "77", "78", "79", "80", "81", "82", "83", "84", "L1", 
"L10", "L11", "L12", "L13", "L14", "L15", "L16", "L17", "L18", 
"L2", "L20", "L21", "L22", "L23", "L24", "L25", "L26", "L27", 
"L28", "L3", "L4", "L5", "L6", "L7", "L9"), class = "factor"), 
    Cage_num = c(47L, 46L, 45L, 2L, 24L, 1L, 23L, 25L, 3L, 61L, 
    5L, 6L, 27L, 49L, 4L, 7L, 48L, 29L, 28L, 26L, 8L, 10L, 51L, 
    50L, 9L, 11L, 30L, 33L, 31L, 32L, 52L, 53L, 54L, 55L, 18L, 
    60L, 41L, 38L, 63L, 19L, 16L, 17L, 40L, 44L, 43L, 21L, 20L, 
    22L, 39L, 62L, 65L, 66L, 42L, 64L, 9L, 54L, 31L, 52L, 10L, 
    53L, 33L, 32L, 8L, 11L, 55L, 30L, 66L, 64L, 21L, 20L, 43L, 
    42L, 44L, 65L, 63L, 18L, 16L, 22L, 62L, 61L, 38L, 19L, 60L, 
    17L, 39L, 40L, 41L, 3L, 24L, 25L, 2L, 23L, 1L, 46L, 47L, 
    45L, 5L, 28L, 48L, 6L, 51L, 50L, 4L, 7L, 29L, 49L, 26L, 27L 
    ), Treatment = structure(c(3L, 3L, 3L, 1L, 2L, 1L, 2L, 2L, 
    1L, 3L, 1L, 1L, 2L, 3L, 1L, 1L, 3L, 2L, 2L, 2L, 1L, 1L, 3L, 
    3L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 3L, 2L, 2L, 
    3L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 3L, 3L, 3L, 2L, 
    3L, 1L, 3L, 2L, 3L, 1L, 3L, 2L, 2L, 1L, 1L, 3L, 2L, 3L, 3L, 
    1L, 1L, 2L, 2L, 2L, 3L, 3L, 1L, 1L, 1L, 3L, 3L, 2L, 1L, 3L, 
    1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 3L, 3L, 3L, 1L, 2L, 
    3L, 1L, 3L, 3L, 1L, 1L, 2L, 3L, 2L, 2L), .Label = c("C", 
    "CC", "NC"), class = "factor"), Site = structure(c(2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 7L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 8L, 8L, 1L, 1L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
    8L, 8L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 6L, 6L, 6L, 6L, 
    6L, 7L, 7L, 6L, 6L, 6L, 6L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 
    8L, 8L, 8L, 8L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 
    6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L), .Label = c("M1", "M2", "R07", "R08_Feb", "R08_Jul", 
    "R09", "R10", "R11", "R11_5m"), class = "factor"), Days_Since_Removal = c(0, 
    0, 0, 0, 0, 0, 0, 0, 0, 291, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 291, 291, 291, 
    291, 291, 291, 291, 291, 291, 669, 669, 669, 669, 669, 291, 
    291, 669, 669, 669, 669, 86, 86, 86, 86, 86, 86, 86, 86, 
    86, 86, 86, 86, 806, 806, 806, 806, 806, 806, 806, 806, 428, 
    428, 428, 806, 428, 428, 428, 428, 428, 428, 428, 428, 428, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0), Time_point = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("May", 
    "September"), class = "factor"), Site_TP = structure(c(3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 10L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 14L, 14L, 1L, 1L, 14L, 14L, 14L, 14L, 
    14L, 14L, 14L, 14L, 14L, 14L, 10L, 10L, 10L, 10L, 10L, 10L, 
    10L, 10L, 10L, 8L, 8L, 8L, 8L, 8L, 10L, 10L, 8L, 8L, 8L, 
    8L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 
    15L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 11L, 11L, 11L, 9L, 11L, 
    11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L), .Label = c("M1_May", "M1_September", "M2_May", "M2_September", 
    "R07_May", "R08_Feb_May", "R08_Jul_May", "R09_May", "R09_September", 
    "R10_May", "R10_September", "R11_5m_May", "R11_5m_September", 
    "R11_May", "R11_September"), class = "factor"), Spionidae = c(0, 
    2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 19, 7, 2, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Nereididae = c(0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 7, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Syllidae = c(0, 0, 0, 0, 
    0, 0, 0, 0, 0, 2, 8, 0, 0, 0, 3, 1, 0, 0, 0, 4, 4, 0, 0, 
    0, 1, 0, 1, 4, 1, 0, 0, 1, 1, 2, 2, 0, 1, 0, 3, 0, 0, 0, 
    3, 1, 22, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 1, 5, 3, 0, 0, 0, 0, 9, 5, 0, 0, 
    0, 0, 29, 0, 7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 1, 0, 0), Opheliidae = c(0, 2, 1, 1, 3, 
    0, 0, 1, 0, 0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 14, 0, 1, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 3, 0, 14, 1, 0, 1, 0, 0, 1, 1, 0, 2, 
    2, 3, 5, 0, 1, 0, 0, 10, 0, 4, 7, 0, 2, 1, 5, 0, 0, 3, 3, 
    0, 1, 5, 0, 8, 11, 0, 0, 13, 9, 5, 4, 6, 1, 19, 3, 2, 5, 
    1, 1, 0, 0, 3, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 
    0, 0, 0, 0, 0, 0, 0, 1, 1), Cossuridae = c(6, 29, 8, 7, 5, 
    0, 10, 31, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    4, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 4, 7, 6, 12, 0, 0, 19, 3, 4, 2, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0), Sternaspidae = c(0, 0, 0, 0, 0, 
    0, 0, 0, 6, 0, 0, 11, 5, 0, 1, 9, 1, 0, 7, 0, 0, 0, 13, 13, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 10, 0, 0, 0, 24, 1, 27, 
    5, 31, 5, 7, 4, 0, 2, 17), Sabellariidae = c(0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 10, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0), Sabellidae = c(1, 2, 1, 2, 0, 
    0, 3, 0, 2, 3, 2, 0, 0, 0, 0, 0, 2, 1, 0, 1, 0, 6, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 2, 0, 3, 0, 2, 0, 0, 0, 2, 0, 0, 0, 
    4, 16, 29, 0, 1, 0, 3, 2, 1, 7, 3, 24, 1, 1, 11, 1, 2, 1, 
    50, 0, 18, 27, 0, 0, 6, 1, 1, 43, 0, 4, 2, 1, 4, 153, 119, 
    2, 2, 2, 0, 0, 0, 0, 3, 0, 0, 4, 0, 0, 0, 0, 1, 0, 0, 0, 
    0, 4, 0, 0, 0, 2, 2, 1, 0, 0, 0), Capitellidae = c(1, 3, 
    3, 10, 7, 1, 10, 6, 17, 0, 3, 0, 0, 0, 0, 0, 0, 0, 0, 3, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 4, 0, 0, 4, 0, 0, 0, 0, 
    0, 1, 0, 0, 0, 4, 0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 3, 1, 3, 
    1, 3, 14, 1, 0, 1, 3, 1, 0, 0, 0, 0, 0, 0, 0, 0, 9, 0, 0, 
    0, 0, 6, 6, 2, 1, 0, 4, 2, 2, 1, 0, 1, 0, 0, 4, 0, 0, 1, 
    1, 1, 0, 0, 0, 0, 0, 0, 0, 4, 1, 0), Dorvillidae = c(0, 0, 
    0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 1, 0, 
    2, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 2, 0, 
    0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Cirratulidae = c(0, 0, 
    0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 8, 0, 
    0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), Oligochaeta = c(19, 35, 
    14, 41, 31, 12, 42, 38, 27, 16, 28, 2, 3, 2, 32, 0, 12, 12, 
    2, 7, 2, 4, 1, 20, 9, 14, 35, 5, 1, 0, 1, 4, 0, 6, 264, 48, 
    27, 8, 22, 0, 3, 133, 42, 5, 40, 21, 0, 2, 101, 4, 2, 0, 
    0, 11, 20, 4, 21, 22, 1, 9, 64, 5, 0, 38, 8, 20, 6, 5, 5, 
    35, 8, 7, 13, 9, 93, 20, 25, 12, 28, 63, 21, 71, 271, 4, 
    204, 8, 51, 14, 11, 10, 10, 1, 5, 4, 6, 4, 2, 3, 1, 0, 0, 
    1, 0, 1, 2, 9, 24, 1), Nemertea = c(0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0), Nematoda = c(2, 0, 0, 4, 5, 5, 0, 1, 13, 
    0, 0, 0, 1, 0, 0, 2, 0, 8, 3, 3, 2, 1, 4, 4, 0, 0, 18, 0, 
    1, 1, 1, 8, 2, 12, 1, 0, 4, 0, 1, 0, 0, 6, 0, 1, 4, 0, 0, 
    0, 1, 0, 0, 2, 6, 0, 0, 0, 1, 15, 0, 0, 20, 1, 0, 1, 2, 0, 
    0, 0, 0, 1, 16, 5, 1, 1, 0, 0, 35, 3, 1, 0, 1, 0, 0, 0, 0, 
    0, 0, 0, 1, 0, 1, 0, 1, 16, 2, 1, 0, 18, 0, 0, 0, 0, 0, 0, 
    0, 1, 0, 0), Platyhelminthes = c(0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0), Sipuncula = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 25, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 
    0, 0, 0, 0), Ostracoda = c(0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 
    0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 7, 1, 0, 0, 0, 0, 0, 0, 0, 0, 5, 
    7, 0, 2, 11, 5, 5, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0), Decapoda = c(0, 0, 0, 4, 0, 0, 2, 0, 0, 0, 0, 0, 
    1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 
    0, 0, 0, 0, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 
    0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 
    0, 1, 1, 0, 0, 4, 0, 1, 1, 0, 0, 1, 0, 2, 1, 0, 0, 1, 0, 
    0, 0, 17, 0, 0, 0, 0, 2, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 2, 
    0), Amphipoda = c(1, 1, 5, 17, 8, 75, 22, 0, 34, 4, 38, 0, 
    27, 24, 89, 2, 1, 5, 3, 42, 88, 3, 1, 21, 6, 1, 6, 60, 6, 
    11, 0, 4, 11, 17, 15, 0, 13, 5, 44, 9, 0, 0, 0, 11, 20, 28, 
    8, 45, 0, 0, 18, 2, 14, 8, 3, 0, 2, 6, 6, 0, 2, 14, 2, 2, 
    6, 3, 37, 37, 5, 20, 63, 12, 10, 49, 6, 3, 150, 83, 7, 3, 
    5, 20, 15, 4, 19, 1, 6, 0, 3, 0, 0, 0, 14, 0, 1, 2, 3, 0, 
    0, 0, 1, 16, 3, 3, 0, 3, 1, 1), Isopoda = c(0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0), Copepoda = c(0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 2, 0, 5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 7, 0, 0, 1, 0, 0, 0, 
    1, 0, 8, 1, 0, 2, 5, 1, 5, 2, 2, 0, 2, 4, 1, 0, 0, 0, 0, 
    0, 1, 1, 0, 0, 1, 0, 0, 0, 5, 3, 0, 0, 0, 1, 0, 0, 0, 0, 
    0, 0, 1, 0, 0, 0), Tanaidacea = c(0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 6, 0, 1, 0, 0, 0, 0, 3, 
    0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 3, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 
    0, 2, 0, 1, 1, 6, 2, 0, 1, 0, 2, 1, 3, 1, 0, 0, 0, 0, 2, 
    0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0), HYRDOZOA = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0), ANTHOZOA = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0), Cnidarian_larvae = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0), Tunicata = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), 
    Mollusca = c(0L, 0L, 0L, 4L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 
    0L, 0L, 2L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    1L, 14L, 2L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 0L, 0L, 
    1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 4L, 
    0L, 3L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
    0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), .Names = c("Core_num", 
"Cage_num", "Treatment", "Site", "Days_Since_Removal", "Time_point", 
"Site_TP", "Spionidae", "Nereididae", "Syllidae", "Opheliidae", 
"Cossuridae", "Sternaspidae", "Sabellariidae", "Sabellidae", 
"Capitellidae", "Dorvillidae", "Cirratulidae", "Oligochaeta", 
"Nemertea", "Nematoda", "Platyhelminthes", "Sipuncula", "Ostracoda", 
"Decapoda", "Amphipoda", "Isopoda", "Copepoda", "Tanaidacea", 
"HYRDOZOA", "ANTHOZOA", "Cnidarian_larvae", "Tunicata", "Mollusca" 
), row.names = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 19L, 
20L, 21L, 22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 
33L, 34L, 35L, 36L, 37L, 38L, 39L, 40L, 41L, 42L, 46L, 47L, 49L, 
50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 60L, 61L, 62L, 
63L, 64L, 65L, 66L, 67L, 68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 
76L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 92L, 93L, 94L, 
95L, 96L, 97L, 98L, 99L, 100L, 101L, 102L, 103L, 104L, 105L, 
109L, 110L, 111L, 112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 
120L, 121L, 122L, 123L, 124L, 125L, 126L, 127L, 128L, 129L), class = "data.frame") 

Answer 1

Idealmente, la función puede devolver la coordenadas X e Y utilizados en las elipses. He aquí una simple modificación de ordiellipse() que añade xy a cada elemento de la lista de la salida de la función:

ordiellipse2 <- 
function (ord, groups, display = "sites", kind = c("sd", "se"), 
     conf, draw = c("lines", "polygon", "none"), 
     w = weights(ord, display), col = NULL, alpha = 127, 
     show.groups, label = FALSE, ...) 
{ 
    weights.default <- function(object, ...) NULL 
    kind <- match.arg(kind) 
    draw <- match.arg(draw) 
    pts <- scores(ord, display = display, ...) 
    ## ordiellipse only works with 2D data (2 columns) 
    pts <- as.matrix(pts) 
    if (ncol(pts) > 2) 
     pts <- pts[ , 1:2, drop = FALSE] 
    if (ncol(pts) < 2) 
     stop("ordiellipse needs two dimensions") 
    w <- eval(w) 
    if (length(w) == 1) 
     w <- rep(1, nrow(pts)) 
    if (is.null(w)) 
     w <- rep(1, nrow(pts)) 
    ## make semitransparent fill 
    if (draw == "polygon" && !is.null(col)) 
     col <- rgb(t(col2rgb(col)), alpha = alpha, maxColorValue = 255) 
    if (!missing(show.groups)) { 
     take <- groups %in% show.groups 
     pts <- pts[take, , drop = FALSE] 
     groups <- groups[take] 
     w <- w[take] 
    } 
    out <- seq(along = groups) 
    inds <- names(table(groups)) 
    res <- list() 
    if (label) 
     cntrs <- names <- NULL 
    ## Remove NA scores 
    kk <- complete.cases(pts) 
    for (is in inds) { 
     gr <- out[groups == is & kk] 
     if (length(gr) > 2) { 
      X <- pts[gr, ] 
      W <- w[gr] 
      mat <- cov.wt(X, W) 
      if (kind == "se") 
       mat$cov <- mat$cov/mat$n.obs 
      if (missing(conf)) 
       t <- 1 
      else t <- sqrt(qchisq(conf, 2)) 
      xy <- vegan:::veganCovEllipse(mat$cov, mat$center, t) 
      if (draw == "lines") 
       vegan:::ordiArgAbsorber(xy, FUN = lines, 
         col = if(is.null(col)) par("fg") else col, 
         ...) 

      else if (draw == "polygon") 
       vegan:::ordiArgAbsorber(xy[, 1], xy[, 2], col = col, FUN = polygon, 
         ...) 

      if (label && draw != "none") { 
       cntrs <- rbind(cntrs, mat$center) 
       names <- c(names, is) 
      } 
      mat$scale <- t 
      mat$xy <- xy # this is the only substantive change I made 
      res[[is]] <- mat 
     } 
    } 
    if (label && draw != "none") { 
     if (draw == "lines") 
      vegan:::ordiArgAbsorber(cntrs[,1], cntrs[,2], labels=names, col = col, 
        FUN = text, ...) 
    else 
     vegan:::ordiArgAbsorber(cntrs, labels = names, col = NULL, 
       FUN = ordilabel, ...) 
    } 
    class(res) <- "ordiellipse" 
    invisible(res) 
} 

Ahora puede crear el objeto de stats, por su ejemplo, pero especifique draw = "none", because you'll want to play with stats` por su cuenta para tener un control total de el trazado de la elipse (sin necesidad de especificar argumentos gráficas):

stats<-with(dat.fac, ordiellipse2(ord, Site_TP, kind = "se", conf = 0.95, draw = "none")) 

aviso ahora que las estadísticas tiene la misma forma, pero hay un elemento xy para cada elipse:

names(stats[[1]]) 
[1] "cov" "center" "n.obs" "wt"  "scale" "xy"  

puede trazar estos en un bucle que utiliza la función polygon(), pero mejor sería colocar todo el xy coordenadas en un solo matrix o data.frame, por lo que sólo puede hacer una sola llamada a polygon(), pero con argumentos vectorizados , como col, lwd. Extraeré las matrices xy usando lapply(), luego las contraeré juntas como data.frame. Clave es el separadas las elipses individuales con NA s, por lo que el dibujo de polígonos sabe dónde uno se detiene y se inicia la siguiente:

xy.mat <- t(as.data.frame(lapply(stats, function(x){ 
      t(rbind(x$xy, NA)) 
     }))) 

trazado llega a ser fácil:

plot(ord, display = "sites", type = "n") 
polygon(xy.mat[, 1], xy.mat[, 2], col = c(rep("#0000ff20", 5), rep("#ff000030", 5)), border = c(rep("blue", 5), rep("red", 5))) 

ahora es sólo una cuestión de ordenar los argumentos gráficos al polygon() correctamente.