Share data for a Question on Cross validated

Set the offset value in lsmeans

structure(list(year = 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, 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("1900", 
"2000"), class = "factor"), Treat = structure(c(1L, 2L, 1L, 2L, 
1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 
1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 1L, 2L
), .Label = c("Yes", "No"), class = "factor"), location = structure(c(1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 
4L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 
4L, 4L, 4L), .Label = c("A", "C", "B1", "B2"), class = "factor"), 
    Habitat = structure(c(2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
    2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 2L, 2L, 2L, 2L, 2L, 
    2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("Field", 
    "city", "Forest"), class = "factor"), response = c(214, 57, 
    280, 44, 96, 167, 330, 43, 210, 86, 182, 148, 76, 175, 86, 
    234, 84, 139, 20, 7, 6, 2, 3, 2, 7, 6, 2, 16, 251, 178, 53, 
    1, 23, 12, 224, 55, 151, 28, 196, 55, 225, 63, 152, 15, 327, 
    420, 39, 383, 39, 651, 10, 211, 266, 60, 35, 13, 14, 2, 7, 
    7, 14, 192, 452, 26, 527, 0, 19, 22), leaves = c(12, 12, 
    12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
    12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
    12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
    12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
    12, 12, 12, 12, 12, 12)), .Names = c("year", "Treat", "location", 
"Habitat", "response", "leaves"), row.names = c(1L, 37L, 9L, 
43L, 15L, 49L, 21L, 57L, 29L, 65L, 35L, 7L, 47L, 19L, 53L, 25L, 
61L, 31L, 3L, 39L, 11L, 45L, 17L, 51L, 23L, 59L, 63L, 33L, 5L, 
41L, 13L, 55L, 27L, 67L, 2L, 38L, 10L, 44L, 16L, 50L, 22L, 58L, 
30L, 66L, 36L, 8L, 48L, 20L, 54L, 26L, 62L, 32L, 4L, 40L, 12L, 
46L, 18L, 52L, 24L, 60L, 64L, 34L, 6L, 42L, 14L, 56L, 28L, 68L
), class = "data.frame")

# Session Info
R version 3.3.2 (2016-10-31)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:
[1] LC_COLLATE=German_Germany.1252 
[2] LC_CTYPE=German_Germany.1252   
[3] LC_MONETARY=German_Germany.1252
[4] LC_NUMERIC=C                   
[5] LC_TIME=German_Germany.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods  
[7] base     

other attached packages:
[1] plyr_1.8.4       lsmeans_2.25     estimability_1.2
[4] optimx_2013.8.7  lme4_1.1-12      Matrix_1.2-7.1  
[7] MASS_7.3-45      ggplot2_2.2.0   

loaded via a namespace (and not attached):
 [1] zoo_1.7-13         modeltools_0.2-21  coin_1.1-2        
 [4] reshape2_1.4.2     splines_3.3.2      lattice_0.20-34   
 [7] colorspace_1.3-1   stats4_3.3.2       mgcv_1.8-15       
[10] survival_2.40-1    nloptr_1.0.4       multcomp_1.4-6    
[13] multcompView_0.1-7 stringr_1.1.0      MatrixModels_0.4-1
[16] munsell_0.4.3      dfoptim_2016.7-1   gtable_0.2.0      
[19] mvtnorm_1.0-5      coda_0.18-1        codetools_0.2-15  
[22] setRNG_2013.9-1    labeling_0.3       Rvmmin_2013-11.12 
[25] SparseM_1.74       quantreg_5.29      pbkrtest_0.4-6    
[28] parallel_3.3.2     TH.data_1.0-7      Rcpp_0.12.8       
[31] xtable_1.8-2       scales_0.4.1       BB_2014.10-1      
[34] svUnit_0.7-12      stringi_1.1.2      numDeriv_2016.8-1 
[37] grid_3.3.2         quadprog_1.5-5     tools_3.3.2       
[40] sandwich_2.3-4     magrittr_1.5       lazyeval_0.2.0    
[43] tibble_1.2         ucminf_1.1-4       optextras_2016-8.8
[46] car_2.1-3          tidyr_0.6.0        Rcgmin_2013-2.21  
[49] assertthat_0.1     minqa_1.2.4        afex_0.16-1       
[52] nnet_7.3-12        nlme_3.1-128