I have a dataset of marine debris items (number of items standardized per effort: Items/(number of volunteersHoursLenght)) taken from 2 main locations (WA and Queensland) in Australia (8 Sub Sites in total: 4 in WA and 4 in Queensland) at irregular sampling intervals over a period 15 years.

I want to test if there is a change over the years on the amount of debris in these locations and more specifically a change after the implementation of a mitigation strategy (in 2013).

Here’s the head of the data:

Description of each one of the varables in the dataframe:

eventid = each sampling (clean-up) event Location = Queensland and New South Wales Sites = all the 9 sampling beaches

Date = specific dates for the clean-up events (day-month-year) Date1 = specific dates for the clean-up events (day-month-year) on the POSICXT format Year= Year of sampling event (2004 to 2018) Month= Month of the sampling event (jan to dec) nMonth= a number was determined to the respective month of the sampling event (1 to 12) Day= Day of sampling (1 to 31) Days = Days since the first date of clean up = just another way of using the dates

MARPOL = before and after implementation (factor with 2 levels) DaysC = days between sampling events for the same sites = number of days since the previous clean-up event DaysI = Days since intervention, all the dates before implementation are zero, and after we count the number of days since the implementation date (1 jan 2013) DaysIa= same as DayI but instead of zero for before the intervention we have negative values (days)

Items = number of fishing and shipping items counted in each clean-up event Hours = hours spent by all volunteers together at each clean up event Lenght = Lenght of beach sampled by all volunteers together at each clean up event volunteers = all volunteers at each clean up event HoursVolunteer = hours spent bt each volunteer at each clean up event (Hours/volunteers) Ieffort = the items standarized by the effort (hours, volunteers and lenght)

GrossWeight = total weight of the all the items found (not just fishing and shipping debris) GrossTotal = total amount of the all the items found (not just fishing and shipping debris)

Problems:

My data has a few problems: (1) I think I will need to fix the effects of seasonal variation (Monthly) and (2) of possible spatial correlation (probability of finding an item is higher after finding one since they can come from the same ship). (3) How do I handle the fact that the measurements were not taken at a regular interval?

I was trying to use GAMs to analyse the data and see the trends over time. The model I came across is the following:

m4<- gamm(Ieffort ~ s(DaysIa)+MARPOL+ s(nMonth, bs = "ps", k = 12), random=list(Site=~1,Location=~1),data = d)