capscale图上的颜色质心-素食主义者

Question

我无法将用于数据点和图例的颜色应用于capscale图中的相应质心。由于某种原因，我得到了多个相同颜色的质心。

colvec<- c("Maroon", "blue4", "chartreuse2", "coral", "brown", "burlywood2", 
"cadetblue", "black", "azure4", "orange", "chocolate", 
"gold","purple","darkolivegreen","darkkhaki")

mclean$Estuary<-as.factor(mclean$Estuary)
mod<-capscale(dmet~Estuary, data = mclean)
df<-data.frame(mod[["CCA"]][["centroids"]])

plot(mod, type = "n")
with (mclean, points(mod, display = "sites", col = colvec[mclean$Estuary], 
bg = colvec[mclean$Estuary]))
with(mclean, points(mod, display = c('cn'), scaling = 2, pch = 3, lwd=2, 
cex=1.5, col = colvec[mclean$Estuary], bg = colvec[mclean$Estuary]))  

legend('bottomright', c("Clarence River", "Georges River", "Hawkesbury 
River", "Hastings River", "Hunter River", "Macleay River", "Manning 
River","Ocean Zone 2", "Ocean Zone 3","Ocean Zone 4", "Ocean Zone 5",  "Port 
Stephens", "Richmond River", "Shoalhaven River",  "Wallis Lake"),  
text.col=c("Maroon", "blue4", "chartreuse2", "coral", "brown", "burlywood2", 
"cadetblue", "black", "azure4", "orange", "chocolate", 
"gold","purple","darkolivegreen","darkkhaki"), cex = .70)

我的数据如下：

dput(head(mclean,15))

structure（list（Estuary = structure（c（15L，6L，6L，13L，11L，4L， 11L，15L，13L，7L，13L，7L，6L，3L，3L），. Label = c（“ CLR”，“ GGR”， “ HKR”，“ HTR”，“ HUR”，“ MLR”，“ MNR”，“ OZ3”，“ OZ4”，“ OZ5”，“ PST”， “ RMR”，“ SHR”，“ TUL”，“ WLL”），类别=“因子”），X7Li_umol_molCa = c（2.693720415， 2.812779881，1.177200469，2.455601483，2.470483917，1.701062119， 2.157952819、2.649073116、1.779779735、3.4482489377、3.104093412， 2.470483917、2.779789748、2.217482552、2.723485282），X25Mg_umol_molCa = c（99.66512342， 65.19671613、89.76236276、154.1940588、98.51759322、50.61883241， 79.56209426、189.3849851、92.77994219、46.9637362、68.34179892， 127.800864、128.7358886、99.11260888、135.0260542），X55Mn_umol_molCa = c（0.295193632， 0.165458851、0.300834275、0.08531096、0.229386134、0.154177566， 0.086489854、0.385443914、0.2555709133，-0.018802142、0.122213924， 0.355360487、0.280151918、0.150417137、0.165458851），X88Sr_umol_molCa = c（1618.688479， 1829.719242、1601.004337、1234.353123、1662.309363、1496.078427， 1597.467508，1580.962309，1121.174613，2472.243074，1911.066296， 1486.646884、1384.007886、1531.446711、1552.66672），X138Ba_umol_molCa = c（1.042565345， 2.124997907、3.647474284、1.074158234、0.774777998、1.345706639， 0.883096475、0.764999247、0.49269863、0.77553021、1.114025452， 0.822919544、0.581459604、1.117034298、0.974866297），X115In_umol_molCa = c（0.00163741， 0.004048541、0.014214877、0.004145166、0.002788995，0.009176693， 0.007827179、0.006117795、0.018893191、0.006027827、0.005038184， 0.006747568，0.004498379，0.017993515，0.015924261）），row.names = c（NA， 15L），class =“ data.frame”）

和：

 dput(head(df,15))

结构（list（CAP1 = c（-0.0529332601372674，-0.00129788917790979， -0.0159618038755354，-0.00644899011465203、0.0739661951856259， -0.0193247691971371、0.0029113150730138、0.156116046382222、0.104734865900315， 0.0732969788117582、0.0560099029273388、0.0133695637185615，-0.0913418878728444， -0.0612009210422786，-0.00693425651785134），CAP2 = c（-0.00116613160672231， -0.0603871331756709、0.075594403585706，-0.116452288246655，-0.0810967750049817， 0.0124378421599932、0.0110725363439345，-0.102064222113947、0.0048753496982861， -0.0153400247748149、0.0561685021929774、0.0231876361798966， -0.0454728606069997、0.0787904240947763、0.113355484309807）， CAP3 = c（-0.0817391532410816、0.0437660833401911、0.04009132559787， -0.0401422192388262，-0.0190094244733118、0.00417911504707151， 0.036010389926307、0.00749724900010081、0.0802116310565441， -0.0176689367575539，-0.00298220067834333，-0.172631982517045， 0.0513489284824863，-0.217196802166248、0.0430735742824018 ），CAP4 = c（0.00867314739873189，0.0167892576408617，0.0278423649968971， -0.173568704334081、0.154832695931103，-0.0824177039970023， -0.0247109368009962、0.00286418850813552，-0.0366318437737167， -0.0217294001655038，-0.022039624976774，-0.0326758822449291， 0.0184433628064148、0.117673727609336，-0.00358343081737813 ），CAP5 = c（0.0145851662085133，-0.0876574858761027，0.0318878154749647， 0.0715873684823734、0.0455892621677961、0.064903852550648， -0.0801990577548729，-0.00831860722397626，0.0150034749313496， 0.114626735611208，-0.0597519639040782，-0.119195379191939， -0.00803846048717321、0.03511200675435、0.0816982131694874 ）），row.names = c（“ EstuaryCLR”，“ EstuaryGGR”，“ EstuaryHKR”， “ EstuaryHTR”，“ EstuaryHUR”，“ EstuaryMLR”，“ EstuaryMNR”，“ EstuaryOZ3”， “ EstuaryOZ4”，“ EstuaryOZ5”，“ EstuaryPST”，“ EstuaryRMR”，“ EstuarySHR”， “ EstuaryTUL”，“ EstuaryWLL”），class =“ data.frame”）