Last week we explored the distribution of sampling effort in the 2019 and 2020 Lock and Dam Closure datasets by visualizing how effort was balanced across sampling time periods in each Pool/Reach x Gear Type combination. There were just a few cases of imbalance in 2020, but substantially more in 2019. Brandon has already found corrections or explanations for some of these imbalances.

As we continue to track down data entry errors and other abnormalities that account for the remaining imbalances by gear type, let’s take a look at how effort is distributed if we replace gear type in the previous data visualization with strata class.

The following figures take the same form as the previous RMarkdown figures, but with HABITAT_CLASS on the x-axis instead of GEAR_CODE. I’ve also added a basic interactive table for each year to help interpret exact values where the text in the figure is too condensed to read clearly.

2020

2019