Most Recent Levels (2014)

Note the different y-axis scales.

Here we see that orchards and grape insecticides are some of the most intense within the contact toxicity, while both corn and orchards and grapes are the most intense within oral toxicity.

Let’s take a look at intense insecticides were previous to 2014.

Change over last 18 years

Below we can view the same graph as above, just as line graphs to see differences in crops a bit better.

Conclusions

The crops with decreasing insecticide intensity appear to be Other Crops, Orchards and Grapes, Pasture and Hay, and Rice, with Orchards and grapes accounting for the most significant decrease. The insecticides used in the rest of the crops have either increased in intensity or have oscillated with no significant change (at least visible from the above graphs).

These are interesting trends to see because at the start of this vignette, we saw that insecticides used on Orchards and Grapes were the most intense (in terms of contact toxic load per acre) out of all the crops; yet, we also see that these insecticides have also decreased dramatically in intensity since the late 1990s. One possible explanation would be that the Food Quality Protection Act was passed in 1996 and encouraged a decrease in the use of organophosphate insecticides.

Continue investigating insecticide use by reading about changes in the world’s most widely used class of insecticides: neonicotinoids

Session information

sessionInfo()

R version 3.5.0 (2018-04-23)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 16299)

Matrix products: default

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

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

other attached packages:
 [1] bindrcpp_0.2.2  scales_0.5.0    forcats_0.3.0   stringr_1.3.1  
 [5] purrr_0.2.5     readr_1.1.1     tidyr_0.8.1     tibble_1.4.2   
 [9] ggplot2_2.2.1   tidyverse_1.2.1 dplyr_0.7.5    

loaded via a namespace (and not attached):
 [1] tidyselect_0.2.4  reshape2_1.4.3    haven_1.1.2      
 [4] lattice_0.20-35   colorspace_1.3-2  htmltools_0.3.6  
 [7] yaml_2.1.19       rlang_0.2.1       R.oo_1.22.0      
[10] pillar_1.2.3      foreign_0.8-70    glue_1.2.0       
[13] R.utils_2.6.0     modelr_0.1.2      readxl_1.1.0     
[16] bindr_0.1.1       plyr_1.8.4        munsell_0.5.0    
[19] gtable_0.2.0      workflowr_1.1.1   cellranger_1.1.0 
[22] rvest_0.3.2       R.methodsS3_1.7.1 psych_1.8.4      
[25] evaluate_0.10.1   labeling_0.3      knitr_1.20       
[28] parallel_3.5.0    broom_0.4.4       Rcpp_0.12.17     
[31] backports_1.1.2   jsonlite_1.5      mnormt_1.5-5     
[34] hms_0.4.2         digest_0.6.15     stringi_1.1.7    
[37] grid_3.5.0        rprojroot_1.3-2   cli_1.0.0        
[40] tools_3.5.0       magrittr_1.5      lazyeval_0.2.1   
[43] crayon_1.3.4      whisker_0.3-2     pkgconfig_2.0.1  
[46] xml2_1.2.0        lubridate_1.7.4   rstudioapi_0.7   
[49] assertthat_0.2.0  rmarkdown_1.10    httr_1.3.1       
[52] R6_2.2.2          nlme_3.1-137      git2r_0.22.1     
[55] compiler_3.5.0