Mission Aransas Telemetry Analysis
BV Cahill, MS Kendall
2024-10-09
Tasks for Bri
### maybe incorporate day/night with suncalc
### add in satellite imagery to the position figures
# standardize the figure size (ie set coords)
# remove silly individuals that have few positions
### make tracks for each individual with color gradient, or do the kml/gif of activity
### dBBMM for each species (probably only enough data for HYAM, SCOC, ARFE, POCR)
### FIGURE OUT WHY COORD_SF ISNT PROJECTING PROPERLY
### change symbology for receiver statusData Preparation
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.0000 0.7053 1.0901 3.0173 2.2033 885.5500 
The HPEs value used here is 8.3. This reduced our dataset down to 63.2713584% of the original data.
Summary Info
# A tibble: 40 × 9
# Groups: scientific_name, indivCode, full_id, releaseDate, totalDaysL [40]
scientific_name indivCode full_id releaseDate totalDaysL length_m goodPos
<chr> <fct> <chr> <date> <dbl> <dbl> <int>
1 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.28 10571
2 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.29 27738
3 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.27 5348
4 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.24 5730
5 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.24 4872
6 Bagre marinus BAMA-155… A69-16… 2023-04-25 377 0.46 7386
7 Cynoscion nebulosus CYNE-155… A69-16… 2023-04-27 375 0.32 387
8 Cynoscion nebulosus CYNE-155… A69-16… 2023-04-27 375 0.25 1
9 Cynoscion nebulosus CYNE-155… A69-16… 2023-04-26 376 0.32 51
10 Cynoscion nebulosus CYNE-155… A69-16… 2023-04-27 375 0.29 4
# ℹ 30 more rows
# ℹ 2 more variables: uniqueDays <int>, propPresent <dbl># A tibble: 40 × 9
# Groups: scientific_name, indivCode, full_id, releaseDate, totalDaysL [40]
scientific_name indivCode full_id releaseDate totalDaysL length_m goodPos
<chr> <fct> <chr> <date> <dbl> <dbl> <int>
1 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.28 10571
2 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.29 27738
3 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.27 5348
4 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.24 5730
5 Arius felis ARFE-155… A69-16… 2023-04-25 377 0.24 4872
6 Bagre marinus BAMA-155… A69-16… 2023-04-25 377 0.46 7386
7 Cynoscion nebulosus CYNE-155… A69-16… 2023-04-27 375 0.32 387
8 Cynoscion nebulosus CYNE-155… A69-16… 2023-04-27 375 0.25 1
9 Cynoscion nebulosus CYNE-155… A69-16… 2023-04-26 376 0.32 51
10 Cynoscion nebulosus CYNE-155… A69-16… 2023-04-27 375 0.29 4
# ℹ 30 more rows
# ℹ 2 more variables: uniqueDays <int>, propPresent <dbl># A tibble: 49 × 5
# Groups: common_name_e [6]
common_name_e indivCode count medianHPEs meanHPEs
<chr> <fct> <int> <dbl> <dbl>
1 black drum POCR-1559574 10120 10.7 51.2
2 black drum POCR-1559649 12613 7.63 21.4
3 black drum POCR-1559651 6439 10.1 43.9
4 black drum POCR-1559656 8889 8.56 24.7
5 black drum POCR-1559658 2 196. 196.
6 black drum POCR-1559659 1669 26.4 75.3
7 black drum POCR-1559661 1 150. 150.
8 black drum POCR-1559664 331 31.4 179.
9 black drum POCR-1559667 18661 7.44 14.3
10 black drum POCR-1559668 4932 15.6 112.
# ℹ 39 more rows# A tibble: 49 × 16
# Groups: common_name_e [6]
common_name_e indivCode hp_es_min hp_es_median hp_es_mean hp_es_stdev
<chr> <fct> <dbl> <dbl> <dbl> <dbl>
1 black drum POCR-1559574 2.01 10.7 51.2 1847.
2 black drum POCR-1559649 1.88 7.63 21.4 526.
3 black drum POCR-1559651 1.90 10.1 43.9 868.
4 black drum POCR-1559656 1.90 8.56 24.7 358.
5 black drum POCR-1559658 113. 196. 196. 118.
6 black drum POCR-1559659 1.90 26.4 75.3 379.
7 black drum POCR-1559661 150. 150. 150. NA
8 black drum POCR-1559664 2.43 31.4 179. 1116.
9 black drum POCR-1559667 2.00 7.44 14.3 117.
10 black drum POCR-1559668 1.82 15.6 112. 4021.
# ℹ 39 more rows
# ℹ 10 more variables: hp_es_q25 <dbl>, hp_es_q75 <dbl>, hp_es_max <dbl>,
# rmse_min <dbl>, rmse_median <dbl>, rmse_mean <dbl>, rmse_stdev <dbl>,
# rmse_q25 <dbl>, rmse_q75 <dbl>, rmse_max <dbl># A tibble: 244 × 4
# Groups: common_name_e, indivCode [50]
common_name_e indivCode month count
<chr> <fct> <chr> <int>
1 black drum POCR-1559574 01 29
2 black drum POCR-1559574 04 158
3 black drum POCR-1559574 05 1586
4 black drum POCR-1559574 06 1068
5 black drum POCR-1559574 07 1844
6 black drum POCR-1559574 08 1468
7 black drum POCR-1559574 09 1053
8 black drum POCR-1559574 10 1686
9 black drum POCR-1559574 11 1228
10 black drum POCR-1559649 03 142
# ℹ 234 more rowsFigures & Things
Min. 1st Qu. Median Mean 3rd Qu. Max.
2.0e+00 4.0e+00 6.0e+00 8.3e+01 1.2e+01 1.7e+07 
Miscellaneous Notes
Vemco Definitions: HPEs/HPE -> error sensitivity of a synthesized position (relative and unitless estimate) HPEm -> horizontal distance between a synthesized position and the known location of the transmitter (eg GPS measurement); only the sync tag because no “true” location for animal whereas the sync tag obviously has the GPS coordinates
Meckley et al., 2014 suggested HPE of 6-8. Bohaboy et al., 2022 suggested 10 and then reported the % of dataset that remained. Later, they filtered HPE to 5 for the fine-scale study and similarly reported the % of dataset. They removed top 5% of HPEm for receiver error. Did something more complicated for rmse. ___ took the mean, median and 95% threshold for HPEm and had varying HPE values based on the different locations of the study
“HPE is a unitless measure of the potential precision of a position based largely on the geometry of the receivers used to estimate a position and the location of the transmitter position relative to these receivers (Smith, 2013).” -
“HPE can then be related to measured horizontal position error in meters (HPEm) for stationary synchronization and reference tags, for which the ‘true’ positions are known (Smith, 2013)” -
might need to make a scatter plot with HPE values and median, 90th and 95th percentile values for HPEm for each deployment
Ryther et al., 2024”For synctag positions, a 90th percentile of HPEm at 10 m corresponded to HPE 14, which resulted in 79.4% of fish positions being retained in our dataset for further analyses”