I'm working with Fish catch in the Amazon, however there's no data available on the fishing vessels, fishing days or number of fishermen involved. I would like to know different approaches to standardize the monthly fish catch
Standardization of monthly fish catch without any data on fishing effort (vessels, days, fishermen) is tricky, but there are a few approaches that you can consider:
· Monthly average: Since months have different lengths, dividing the total catch by the number of days in the month provides a basic standardization. However, this doesn't explain the seasonal variations in fish abundance or the effort put into fishing activity.
· Comparison to the historical data: If you have historical catch data for the Amazon fishery of the location of interest, you can calculate the average catch for each month over a defined period (e.g., past 5 years). Then, visualize the trend of the current month's catch as a percentage of the historical monthly average. This approach accounts for seasonal variations but may not be ideal if fishing pressure has significantly changed with time.
· Environmental data: Fish abundance can be influenced by environmental factors like water temperature, salinity, or land runoffs. With such data, you might be able to establish correlations between these factors and historical catch data. This allows you to estimate a "baseline" catch expected for certain environmental conditions and compare the current month's catch to that expectation.
· Indigenous knowledge: Consulting with indigenous and local fishers can provide valuable insights. With their experience, they might be able to explain seasonal patterns in fish abundance or fishing activity that can be used to adjust the catch data for better comparability between months qualitatively.
The results might not be as statistically robust as those obtained with standardized Catch Per Unit Effort (CPUE), but it might give you some insight into the trend.