Additional file 1 of Maximising the value of transmitted data from PSATs tracking marine fish: a case study on Atlantic bluefin tuna
Creators: name: Horton, Thomas W.
name: Birch, Samantha
name: Block, Barbara A.
name: Hawkes, Lucy A.
name: van der Kooij, Jeroen
name: Witt, Matthew J.
name: Righton, David
Publisher: name: figshare
Year: 2024
Subjects: subject: Neuroscience
subject: Evolutionary Biology
subject: FOS: Biological sciences
subject: Environmental Sciences not elsewhere classified
subject: Ecology
subject: Biological Sciences not elsewhere classified
subject: Information Systems not elsewhere classified
subject: Inorganic Chemistry
subject: FOS: Chemical sciences

description: Additional file 1: Figure S1. Schematic showing an example data flow for data acquisition, data processing and data analysis. Asterisk denotes a dataset not used in our analysis. Figure S2. Schematic indicating the process of serial degradation of transmitted data for 17P0786 by cropping the dataset at specific transmission durations according to the total proportion (%) of geolocation data received. Figure S3. Schematic and formula for spatial similarity (τ) calculation. Polygons 1 and 2 are the merged and dissolved 12-houly likelihood surfaces for a given dataset (i.e. tag data alias). Polygon 3 is the area of overlap between these two datasets. Figure S4. Schematic showing calculation of a) distance, b &amp; c) spatial uncertainty for 17P0786 on the 11th of March 2019. Black boxes on a) denote spatial extent of b) and c). Figure S5. Map showing the calculation of the tag vs model temperature differential. White circle represents the most probable location (latitude and longitude only without error) for one fish. Model SST is from a point estimate. Figure is for representative purposes only. Figure S6. Boxplot showing categorisation of PATs by their maximum displacement distance (straight, geodesic distance between deployment and daily locations) from their tagging location. Figure S7. Histograms of data volume distribution. All 29 transmitting PSATs are included. Figure S8. Hexbin density raster showing spatial uncertainty in relation time to nearest data observation for data transmitted via ARGOS. Spatial uncertainty is estimated from the 99th percentile of 12-hourly GPE3 error polygons. Observations are data on twilights or SST measurements. Line represents line of loess best fit for visualisation purposes. Inset map shows full extent of data. Figure S9. Relationship between the time to transmit data, programming and deployment length for transmitting tags. Data is based on means from PSATs included in this study and extended to theoretical maximum deployments. Figure S10. Time series of spatial uncertainty (area) associated with differing volumes of geolocation data received (5, 10, 20, 30, 40% and the full data archive) for 9 tags documenting long range movements. Uncertainty is defined by the area of the 99% likelihood polygon. There is one translucent point per 12-hour period for each dataset (e.g. 10% for tag i) and trend line shows weekly means with a 3-week smoothing window. Vertical dotted lines represent equinoxes. The tags that were deployed in September transmitted less than 20% of their data, so degraded datasets could not be created for 20, 30 and 40% data categories. Figure S11. Time series of geolocation data according to the overall deployment for tags depicted in Figure 2. Numbers in upper facets denote geolocation data volume. Figure S12. Boxplots showing temporal autocorrelation in spatial uncertainty and distance from archive as datasets were reduced in size by random subsampling. Random subsampling was conducted 10 times for each category. Boxplots outlined in red denote the size of the final dataset used in analyses, where median p values were more than 0.05 (i.e. the Durbin Watson test was not significant at the P = 0.05 level). Group sample size is given by labels above the x axis titles. Table S1. Summary of light-based geolocation models for fish available to researchers. Table S2. Summary of pop-up satellite archival tag products available to researchers. *SeaTagGEO uses solar power to transmit to Argos and will transmit whenever exposed to light.