Last updated: 2018-10-08

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Introduction

In this vignette, we will explore trends in the most widely used class of insecticides worldwide: neonicotinoids1. Neonicotinoids are systematic insecticides that resemble nicotine. They are commonly used in crop seed treatments.

Has usage of neonicotinoids been increasing?

We will start with creating some basic visualizations to see if there are any intriguing trends. This first graph displays how many kilograms of neonicotinoids were applied in the U.S. during each year starting in 1997 and ending in 2014.

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Next we’ll look at the intensity of neonicotinoid applications.

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In both of the above plots we see that neonicotinoid use has increased dramatically in the last 18 years, both in total amount applied and in density (use per acre). Now let’s see how neonicotinoid use has increased with respect to all other types of insecticides used.

Use Relative to Other Insecticides

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Neonicotinoids account for a lot more of the total contact toxic load now than they did in the past; and they seem to not only be replacing other insecticides, but also increasing the total amount of insecticides used. Let’s also take a look at neonicotinoids contribution to total oral toxic load:

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Neonicotinoids account for what looks like 90% of the Oral Toxic Load of all insecticides in the US! Again, we see not only replacement, but also additions in total toxic load due to neonicotinoids. This really means we should be learning more about the usage and environmental effects of neonicotinoids seeing as honeybees and other insects are almost guaranteed to be exposed to them.

So far we’ve seen a dramatic increase in neonicotinoid usage. Let’s see where these huge increases have been occurring and visualize which states use the most and which account for the highest toxic load of neonicotinoids.

Part 2:

Where has the use been increasing the most?

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Looks like Iowa and Illinois are accounting for the most kg applied (and toxic load) of neonicotinoids.

Iowa and Illinois: Neonicotinoid Hubs

As of 2014 (the most recent data), just two states, Iowa (IA) and Illinois (IL) accounted for 25% of all neonicotinoid use in the USA.

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Why might that be? Let’s take a look at what’s growing in those two states.

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Looks like corn and soybeans are the dominant crops in both Iowa and Illinois. Let’s look at national data to see how much neonicotinoids are applied to these two crop types.

Neonicotinoid use by Crop over Time

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Neonicotinoids have increasingly been applied to all crops, especially corn and soybeans. This explains why the states with the most corn and soybean crops have the highest instance of neonicotinoid use and account for such a large proportion of the national neonicotinoid use.

Why those two crops? One possible explanation is seed treatments. Neonicotinoid seed treatments are common in both corn and soybeans and both crops occupy a lot of acreage in the United States.

Session information

sessionInfo()
R version 3.5.0 (2018-04-23)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS High Sierra 10.13.6

Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

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

other attached packages:
[1] bindrcpp_0.2.2 scales_0.5.0   dplyr_0.7.5    ggplot2_2.2.1 

loaded via a namespace (and not attached):
 [1] Rcpp_0.12.17      bindr_0.1.1       knitr_1.20       
 [4] whisker_0.3-2     magrittr_1.5      workflowr_1.1.1  
 [7] tidyselect_0.2.4  munsell_0.5.0     colorspace_1.3-2 
[10] R6_2.2.2          rlang_0.2.1       stringr_1.3.1    
[13] plyr_1.8.4        tools_3.5.0       grid_3.5.0       
[16] gtable_0.2.0      R.oo_1.22.0       git2r_0.22.1     
[19] htmltools_0.3.6   assertthat_0.2.0  yaml_2.1.19      
[22] lazyeval_0.2.1    rprojroot_1.3-2   digest_0.6.15    
[25] tibble_1.4.2      purrr_0.2.5       R.utils_2.6.0    
[28] glue_1.2.0        evaluate_0.10.1   rmarkdown_1.10   
[31] labeling_0.3      stringi_1.2.3     pillar_1.2.3     
[34] compiler_3.5.0    backports_1.1.2   R.methodsS3_1.7.1
[37] pkgconfig_2.0.1

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