Last updated: 2018-10-08

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Welcome

Welcome to Insecticide Explorer!

This site was built in response to an increasing urgency to understand trends in insecticide use. Recently, many scientific studies from around the world have suggested that insect populations have decreased in abundance, diversity, and range. Declines in insect populations have in turn resulted in declines in plant and animal populations that depend on these insects to survive. Of particular concern is the decline in insect pollinator populations. Insect pollinators, especially honeybees, are essential for our current food production. Seventy percent of all crops worldwide benefit from pollination, and some crops cannot even grow without help from insect pollinators. Declining pollinator populations threaten our entire food system.

Increasing insecticide use in one of the multiple factors contributing to this decline, and this site seeks to provide visualizations of data on national insecticide use patterns from 1997 to 2014. Understanding these trends can not only help us recognize how changes in insecticide use can affect pollinator health, but it can also help us gain insight into drivers of insecticide use and identify regions that could benefit from further research into pest management and insect mitigation.

PLEASE NOTE: This project is a work in progress.

What is Toxic Load?

Learn more about the measurement we’re using to see changes in insecticide use.

Contents

This site contains a few different ways to explore insecticide data:

Shiny App

The graphs in this app are interactive, allowing users to view insecticide use by state and crop over the past 18 years. We hope you will explore different trends in insecticide use and find trends that interest you.

Shiny App Features:

  • Two different sets of plots:
    • one set for total insecticide use for each state
    • one set for per-acre insecticide use for each state.
  • A crop key for information about which crops are included in each crop category
  • A data tab where you can view and download the raw data

This reproducible R Markdown analysis was created with workflowr 1.1.1