I am analyzing data using a factorial three-way ANOVA with a-priori contrasts and type III sums of squares.  (Please don't speak about type I SS vs. type III SS.  That's not the point of my question.)  I get the contrasts like I need using `summary.aov()`, however that uses type I SS.  When I use the `Anova()` function from `library(car)` to get type III SS, I don't get the contrasts.  Why don't I get contrasts?

I have also tried using `drop1()` with the `lm()` model, but I get the same results as `Anova()` (without the contrasts).  I have also tried the following, all without a resolution to my issue: `ezANOVA()` from `library(ez)`, `glht()` from `library(multcomp)` which returned the error *Error in glht.matrix(EpiLM, linfct = con) :   ‘ncol(linfct)’ is not equal to ‘length(coef(model))’*, and `C()`.   I have searched extensively online for answers to this error messages as well as this issue generally, but without finding a solution.  

Please advise on a statistical method or function in R to analyze data using factorial ANOVA with a-priori contrasts and type III SS as shown in my example below.  

Sample data:

    DF <- structure(list(Code = structure(c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L,  
    3L, 4L, 4L, 4L, 5L, 5L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 
    9L, 10L, 10L, 10L, 11L, 11L, 11L, 12L, 12L, 12L), .Label = c("A", 
    "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L"), class = 
    "factor"), GzrTreat = structure(c(3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,  2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), contrasts = structure(c(1, 
    -2, 1, 1, 0, -1), .Dim = c(3L, 2L), .Dimnames = list(c("I", 
    "N", "R"), NULL)), .Label = c("I", "N", "R"), class = "factor"), 
    BugTreat = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = 
    c("Immigration", "Initial", "None"), class = "factor"), TempTreat =   
    structure(c(2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 
    2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 
    1L, 1L, 1L, 1L, 1L), .Label = c("Not Warm", "Warmed"), class = 
    "factor"), ShadeTreat = structure(c(2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 
    2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 
    1L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L), .Label = c("Light", 
    "Shaded"), class = "factor"), EpiChla = c(0.268482353, 0.423119608, 
    0.579507843, 0.738839216, 0.727856863, 0.523960784, 0.405801961, 
    0.335964706, 0.584441176, 0.557543137, 0.436456863, 0.563909804, 
    0.432398039, 0.344956863, 0.340309804, 0.992884314, 0.938390196, 
    0.663270588, 0.239833333, 0.62875098, 0.466011765, 0.536182353, 
    0.340309804, 0.721172549, 0.752082353, 0.269372549, 0.198180392, 
    1.298882353, 0.298354902, 0.913139216, 0.846129412, 0.922317647, 
    0.727033333, 1.187662745, 0.35622549, 0.073547059), log_EpiChla = 
    c(0.10328443, 0.153241402, 0.198521787, 0.240259426, 0.237507762, 
    0.182973791, 0.147924145, 0.125794985, 0.19987612, 0.192440084, 
    0.157292589, 0.194211702, 0.156063718, 0.128708355, 0.127205194, 
    0.299482089, 0.287441205, 0.220962908, 0.093363308, 0.21185469, 
    0.166137456, 0.186442772, 0.127205194, 0.235824411, 0.243554515, 
    0.103589102, 0.078522208, 0.361516746, 0.113393422, 0.281746574, 
    0.266262141, 0.283825153, 0.23730072, 0.339980371, 0.132331903, 
    0.030821087), MeanZGrowthAFDM_g = c(0.00665, 0.003966667, 0.004466667, 
    0.01705, 0.0139, 0.0129, 0.0081, 0.003833333, 0.00575, 0.011266667, 
    0.0103, 0.009, 0.0052, 0.00595, 0.0105, 0.0091, 0.00905, 0.0045, 0.0031, 
    0.006466667, 0.0053, 0.009766667, 0.0181, 0.00725, 0, 0.0012, 5e-04, 
    0.0076, 0.00615, 0.0814, NA, 0.0038, 0.00165, 0.0046, 0, 0.0015)), 
    .Names = c("Code", "GzrTreat", "BugTreat", "TempTreat", "ShadeTreat", 
    "EpiChla", "log_EpiChla", "MeanZGrowthAFDM_g"), class = "data.frame", 
    row.names = c(NA, -36L))


Code:

    ## a-priori contrasts
    library(stats)
    contrasts(DF$GzrTreat) <- cbind(c(1,-2,1), c(1,0,-1))
    round(crossprod(contrasts(DF$GzrTreat)))
    c_labels <- list(GzrTreat=list('presence'=1, 'immigration'=2))

    ## model  
    library(car)
    EpiLM <- lm(log_EpiChla~TempTreat*GzrTreat*ShadeTreat, DF)
    summary.aov(EpiLM, split=c_labels) ### MUST USE summary.aov(), to get 
    #contrast results, but sadly this uses Type I SS
    Anova(EpiLM, split=c_labels, type="III") # Uses Type III SS, but NO     
    #CONTRASTS!!!!!

    # I need contrast results like from summary.aov(), AND Type III SS 
    # like from Anova()