Phase | Action | Description | Benefit to researcher |
---|---|---|---|
Programming | Message transmission summary | Once programmed, tag software could provide the researcher with estimated scenarios for data recovery based on latitude and longitude of estimated pop-up location. This is covered along with a method in Patterson and Hartmann [23]. Work to understand the effect of temperature on transmissions could also benefit this | It would allow researchers to make realistic assumptions on data recovery |
Transmission schedule | An option for PSATs to assign priority to geolocation data messages could be included at the programming stage. For instance, two geolocation data messages could be transmitted for every auxiliary message, enhancing the likelihood of enough geolocation data being recovered to generate plausible tracks | More geolocation data whilst also having some data on other variables (e.g., temperature and depth) | |
Modelling | Speed parameter | Recommendation for researchers to conduct a sensitivity analysis on the impact of the speed parameter on movement reconstructions | Setting speeds too low can result in erroneous track reconstructions and too high can cause overfitting |
Temperature matching threshold | For observation-driven locations do not allow progression of SSM if tag-derived SST at a location more than a specified threshold is ± remotely sensed SST | For occasions, where SST is likely to be more important for geolocating (e.g., around the equinoxes), this would prevent extreme outliers | |
Output | Including uncertainty estimates with model outputs | Semi-major and semi-minor axis of the 99th likelihood should be included as an output of the model alongside most likely locations | Researchers would be able to assess error quickly and without the need for opening separate files, which can be computationally costly. The files would still be there if researchers decided this warranted a closer look |
Data volume index | A notification or statement outlining the volume of geolocation data used to generate the track. Ultimately different species/PSATs/SSMs will require differing volumes of data but this would increase awareness of the importance of data volume | Reduce the risk of including analysis of erroneous and uncertain data, and ultimately making Type I or Type II errors when hypothesis testing | |
Gap warning | If there are gaps longer than 5% of the data set length (i.e., 15Â days for a 300Â day data set), warn that these gaps could inflate error | Reduce the risk of including analysis of erroneous and uncertain data, and ultimately making Type I or Type II errors when hypothesis testing |