Hope it's everything ok now!
library(dismo)
Dados <- data.frame(stringsAsFactors=FALSE,
Abundance_b = c(0.444444444444444, 0.5, 0.333333333333333,
0.777777777777778,
0.875),
MeanDiuRange = c(10.7916667461395, 10.7916666666667, 10.9999999205271,
10.9916664759318,
10.7666664918264),
AnnualPrec = c(881, 889, 885, 880, 882),
AnnualMeanTemp = c(22.1958333253861, 22.2041665712992, 22.2416666746139,
22.0624998410543,
22.3083331982295),
MaxTempWM = c(31.7000007629394, 31.7000007629394, 31.8999996185303,
31.6000003814697,
31.8999996185303),
LandCover = c("G", "UV", "UV", "UV", "G"),
Altitude = c(35, 31, 22, 54, 6),
BHerbaceous = c(72.0861129760742, 72.0861129760742, 64.076545715332,
73.3464584350586,
62.7008323669434),
NDVI = c(192, 194, 192, 186, 192),
TreeCover = c(39, 16, 16, 20, 16),
Soil = c("ARh", "ARh", "LVk", "ARh", "LVk"),
Grassland = c(0, 0, 0, 0, 0),
Trees = c(0, 0, 0, 0, 9),
BareSoil = c(0, 2, 87, 100, 53)
Dados$Soil <- factor(Dados$Soil, levels=c("ARa", "ARh", "LVk", "O"))
Dados$LandCover <- factor(Dados$LandCover, levels=c("CS", "DB", "G", "O","UV"))
dados.tc3.lr003 <- gbm.step(data=Dados, gbm.x = 2:14, gbm.y = 1,
family = "gaussian", tree.complexity = 3,
learning.rate = 0.003, bag.fraction = 0.5)