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These were true_survey_fleet_bio_overlap, OBS_survey_fleet_bio_overlap, yield_region_fleet_overlap, OBS_yield_region_fleet_overlap. These variable were included in point 5, below.  \r\n\r\n5.\t5d and 6d arrays\r\nReorganized all 6d arrays that aren’t temporary: \r\nrenamed variables to start with ‘ro’, and redefined so that the first two dimensions are population from and region, as opposed to population from and population to. For 6d vital arrays, dimensions were already population from and region, so did not need to reorganize. Outputted as 4d arrays indexed by the region number (region 1 = pop 1 region 1; region 2 = pop 1 region 2 (or pop 2 region 1 is single regions per pop; etc.) with naming convention of “_X” at the end where X is the region number, which required indexing over region and population (from) dimensions. \r\n\r\nOutputted all 5d arrays that aren’t temporary:\r\noutputted as 4d arrays indexed by the population number with naming convention of “_Y” at the end where Y is the population number of the first (population from) dimension, and “alt_” at the beginning. For input_T, although it’s a 5d array, I had to index over population and region because I was getting reading issues into R when indexing only over pop, thus output for it is in a 3d array, and it’s named with “alt_” in the beginning and “_X” at the end where X is the region number.\r\n\r\n6.\t7D tagging arrays\r\nOutputted as 4d arrays indexed by the region number (region 1 = pop 1 region 1; region 2 = pop 1 region 2 (or pop 2 region 1 is single regions per pop; etc.) and the year of tag releases, with naming convention of “_regX_relZ” at the end where X is the region number, which required indexing over region and population (from) dimensions, and Z is the release year\r\n\r\nHence, anything starting with “ro_” had its dimensions reorganized and reduced, whereas anything starting with “alt_” only had its dimensions 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