Dear all, For my current research topic I am analyzing the horizontal movement tracks of humpback whales in response to different disturbances. To quantify movement I am using several methods including FPT analysis included in the adehabitatLT package. I am currently trying to find an appropriate radius that allows me to identify changes at small scales because exposure times of disturbances are often less than 30 minutes. To do this I first have to compute the FPT for each relocation at different radii so that I may use the varlogfpt function. This is where I get an output that have a lot of NA values and I do not understand why.
Track of animal loaded into R: ------------------------------------------------------------------------------------------------ Name Date Lat Lon mn12_161ab_Base 9-6-2012 19:09:28 77,55643335690100 11,27667241604030 mn12_161ab_Base 9-6-2012 19:12:45 77,55696075632120 11,27084375824340 mn12_161ab_Base 9-6-2012 19:15:28 77,55699816456820 11,27702308557660 mn12_161ab_Base 9-6-2012 19:18:06 77,55598805558040 11,28580614377480 mn12_161ab_Base 9-6-2012 19:21:09 77,55591859473830 11,28338931414880 mn12_161ab_Base 9-6-2012 19:24:00 77,55549373669390 11,28408170335610 mn12_161ab_Base 9-6-2012 19:26:28 77,55324309888590 11,28398869516110 mn12_161ab_Base 9-6-2012 19:28:55 77,55139062949150 11,27833972589440 mn12_161ab_Base 9-6-2012 19:32:06 77,55475135943500 11,27173342072610 mn12_161ab_Base 9-6-2012 19:35:12 77,55611753940680 11,26495443169710 mn12_161ab_Base 9-6-2012 19:38:36 77,55860892997800 11,25700440709650 mn12_161ab_Base 9-6-2012 19:41:33 77,56089170155290 11,25495483479950 mn12_161ab_Base 9-6-2012 19:44:24 77,56222432364140 11,25873209612050 mn12_161ab_Base 9-6-2012 19:47:14 77,56434154308270 11,26363348896560 mn12_161ab_Base 9-6-2012 19:50:07 77,56646024135830 11,26660137473080 mn12_161ab_Base 9-6-2012 19:52:41 77,56839120918160 11,27226333803470 mn12_161ab_Base 9-6-2012 19:55:17 77,57057993643930 11,27136493626320 mn12_161ab_Base 9-6-2012 19:58:07 77,57214283776610 11,27233383879820 mn12_161ab_Base 9-6-2012 20:01:46 77,57500953017100 11,26666329382660 mn12_161ab_Base 9-6-2012 20:05:03 77,57767923609360 11,26380969360000 mn12_161ab_Base 9-6-2012 20:08:16 77,58012176578860 11,26323326856280 mn12_161ab_Base 9-6-2012 20:10:50 77,58187998271110 11,25941145266200 mn12_161ab_Base 9-6-2012 20:15:10 77,58474230359560 11,25209963783920 mn12_161ab_Base 9-6-2012 20:17:45 77,58645775778830 11,24338930348240 mn12_161ab_Base 9-6-2012 20:22:01 77,58856954384490 11,23638816507940 mn12_161ab_Base 9-6-2012 20:25:35 77,59112792527880 11,22931664515410 mn12_161ab_Base 9-6-2012 20:28:33 77,59242584084420 11,21224684125400 mn12_161ab_Base 9-6-2012 20:32:33 77,59249206431210 11,19452015830120 mn12_161ab_Base 9-6-2012 20:35:17 77,59633456212130 11,20196047802890 mn12_161ab_Base 9-6-2012 20:37:57 77,59679722529070 11,19449197951810 mn12_161ab_Base 9-6-2012 20:41:56 77,59852082259090 11,18645961656580 mn12_161ab_Base 9-6-2012 20:45:25 77,59969926846610 11,17264464402770 mn12_161ab_Base 9-6-2012 20:48:18 77,60022752599820 11,16985355832960 mn12_161ab_Base 9-6-2012 20:53:02 77,59909823003750 11,16205375327660 mn12_161ab_Base 9-6-2012 20:56:56 77,59722096161280 11,15916057027840 mn12_161ab_Base 9-6-2012 21:00:37 77,59533239422310 11,16281457328250 mn12_161ab_Base 9-6-2012 21:03:23 77,59329022766340 11,17116763774670 mn12_161ab_Base 9-6-2012 21:07:20 77,59114261080940 11,16946709571400 mn12_161ab_Base 9-6-2012 21:09:55 77,58989120696670 11,17493721261540 mn12_161ab_Base 9-6-2012 21:13:12 77,58793385734110 11,17878092157690 mn12_161ab_Base 9-6-2012 21:16:25 77,58522912212770 11,18033497915500 mn12_161ab_Base 9-6-2012 21:20:03 77,58336514505540 11,18515516867340 mn12_161ab_Base 9-6-2012 21:23:17 77,58200107158110 11,18616970800400 mn12_161ab_Base 9-6-2012 21:26:41 77,58042091845630 11,18911668020680 mn12_161ab_Base 9-6-2012 21:30:02 77,57846059499860 11,19511603166340 mn12_161ab_Base 9-6-2012 21:34:06 77,57651004097650 11,19619598150720 mn12_161ab_Base 9-6-2012 21:37:58 77,57456184147340 11,19587058275390 mn12_161ab_Base 9-6-2012 21:41:26 77,57347863238240 11,20194901181800 mn12_161ab_Base 9-6-2012 21:44:34 77,57219536268080 11,20738548393350 mn12_161ab_Base 9-6-2012 21:46:59 77,57132649274410 11,21131172345690 mn12_161ab_Base 9-6-2012 21:50:48 77,57118138905010 11,21986934010630 mn12_161ab_Base 9-6-2012 21:53:59 77,57038958699530 11,22805999078830 mn12_161ab_Base 9-6-2012 21:56:27 77,57009674153950 11,23402810606740 mn12_161ab_Base 9-6-2012 22:01:36 77,56844936775150 11,24399900071270 mn12_161ab_Base 9-6-2012 22:04:41 77,56843904903480 11,25186272077050 mn12_161ab_Base 9-6-2012 22:08:56 77,56790521875880 11,26010099033360 mn12_161ab_Base 9-6-2012 22:12:04 77,56669715185240 11,27139578849330 mn12_161ab_Base 9-6-2012 22:15:36 77,56649731454960 11,27975667115040 mn12_161ab_Base 9-6-2012 22:20:17 77,56562818131410 11,29716578688230 mn12_161ab_Base 9-6-2012 22:25:17 77,56598909594260 11,31559241509630 mn12_161ab_Base 9-6-2012 22:28:18 77,56419294888910 11,31338913732350 mn12_161ab_Base 9-6-2012 22:31:51 77,56264733580530 11,31256648894900 ---------------------------------------------------------------------------------------------- Script: Trial <-read.table("mn12_161_Base.txt", sep="\t", dec=",", header=T) # Store date in POSIXct object da <- as.character(Trial$Date) da <- as.POSIXct(strptime(as.character(Trial$Date),"%d-%m-%Y %H:%M:%S")) #Creat an object of class ltraj, ltraj automatically computes some descriptive parameters including angles etc. Trial_ltraj <- as.ltraj(xy = Trial[,c("Lon","Lat")], date = da, id = Trial$Name) #FPT calculations i<-fpt(Trial_ltraj, seq(0.,0.14, length=100)) i ------------------------------------------------------------------------------------------- > i [[1]] r1 r2 r3 r4 r5 r6 r7 r8 r9 r10 r11 r12 r13 r14 r15 1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 2 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 3 0 344.6375 NA NA NA NA NA NA NA NA NA NA NA NA NA 4 0 258.1202 NA NA NA NA NA NA NA NA NA NA NA NA NA 5 0 674.4649 985.1631 NA NA NA NA NA NA NA NA NA NA NA NA 6 0 748.0733 1134.6472 NA NA NA NA NA NA NA NA NA NA NA NA 7 0 729.2368 1091.5573 NA NA NA NA NA NA NA NA NA NA NA NA 8 0 733.1255 1084.1339 NA NA NA NA NA NA NA NA NA NA NA NA 9 0 294.5591 NA NA NA NA NA NA NA NA NA NA NA NA NA 10 0 307.2180 620.3491 NA NA NA NA NA NA NA NA NA NA NA NA 11 0 299.7344 1253.8778 1834.7958 NA NA NA NA NA NA NA NA NA NA NA 12 0 556.1033 950.1141 1277.7050 2529.3255 NA NA NA NA NA NA NA NA NA NA 13 0 476.6646 850.8415 1189.6811 2655.8799 3104.398 NA NA NA NA NA NA NA NA NA 14 0 620.8436 1053.2058 2150.3288 2796.4636 NA NA NA NA NA NA NA NA NA NA 15 0 421.3395 1520.1129 2421.3037 3389.3135 NA NA NA NA NA NA NA NA NA NA 16 0 393.4383 1364.6252 2486.5748 NA NA NA NA NA NA NA NA NA NA NA 17 0 568.8497 1091.7618 1653.1042 NA NA NA NA NA NA NA NA NA NA NA 18 0 651.1217 1241.0961 1725.5470 NA NA NA NA NA NA NA NA NA NA NA 19 0 601.2497 1217.6464 1660.2531 NA NA NA NA NA NA NA NA NA NA NA 20 0 563.3341 1498.7189 1972.7839 2776.7161 NA NA NA NA NA NA NA NA NA NA 21 0 600.6826 1216.7037 1993.0220 2713.3706 3145.339 NA NA NA NA NA NA NA NA NA 22 0 580.4407 994.0854 1881.3701 2551.0977 3104.858 NA NA NA NA NA NA NA NA NA 23 0 514.5602 930.4308 1452.4218 2576.8718 3108.979 3409.341 NA NA NA NA NA NA NA NA 24 0 295.0017 652.6900 1252.1293 1621.2101 2986.674 3293.020 3534.912 NA NA NA NA NA NA NA 25 0 306.0586 628.1298 944.0977 1380.4156 1691.505 3173.182 3452.472 3704.978 NA NA NA NA NA NA 26 0 370.2110 589.7890 774.2219 1029.8940 1426.411 1813.891 2347.478 3992.852 4309.935 4597.379 NA NA NA NA 27 0 226.6533 480.5771 700.0599 881.4927 1149.310 1750.642 2338.048 2664.809 4220.055 4525.838 4959.074 NA NA NA 28 0 139.6300 279.2600 426.0528 1070.3791 1401.887 1637.533 1857.919 2326.503 2857.790 7751.681 8310.697 9735.137 10009.282 10302.132 29 0 193.2195 746.7581 919.7588 1088.8537 1433.440 1824.170 5500.718 5870.687 6207.190 6479.671 6841.504 7272.666 7785.197 9494.052 30 0 238.9733 693.3732 899.4945 1049.1422 1222.770 1667.134 2124.660 6172.640 6477.207 6839.951 7345.563 7787.369 9452.568 9776.581 31 0 294.4359 741.5590 929.8951 1143.7828 1458.367 1850.267 5410.325 5774.742 6124.558 6411.090 6754.681 7156.565 7717.067 8235.309 32 0 257.6360 489.0948 1083.2537 1383.0705 4385.307 4711.977 5000.641 5299.355 5638.852 6019.302 6310.700 6617.125 6994.920 7554.321 33 0 370.3541 712.7265 2233.2269 2817.7925 3214.330 4123.309 4435.882 4721.449 4977.971 5222.833 5542.386 5911.153 6232.976 6509.439 34 0 428.3577 1611.0865 2042.9567 2545.4944 3070.002 3768.394 4303.758 4591.564 4865.635 5106.471 5388.780 5728.222 6095.917 6375.997 35 0 712.6666 1355.7869 1651.0522 2069.5007 2573.601 3046.903 3785.599 4291.029 4572.840 4839.566 5074.790 5321.443 5646.307 6026.280 36 0 576.9311 923.3175 1532.9022 1934.1300 2329.497 2935.214 3278.819 4201.258 4486.279 4761.453 4992.680 5204.165 5512.152 5869.831 37 0 687.1306 1438.2095 1770.1222 2192.9917 2781.356 3148.951 4111.652 4398.554 4676.951 4920.897 5140.822 5407.222 5744.229 6122.140 38 0 539.8671 1080.0077 2371.7589 2957.0739 3370.371 4230.967 4519.292 4790.948 5024.581 5235.346 5555.643 5924.042 6253.966 6512.305 39 0 502.5727 1098.8807 2263.7699 2876.7800 3275.157 4196.464 4480.357 4757.002 4986.748 5196.228 5485.442 5839.941 6197.878 6456.624 40 0 708.3758 1113.2496 2816.6642 3201.9093 4171.379 4459.573 4741.820 4973.468 5185.521 5468.282 5820.922 6185.233 6445.831 6777.702 41 0 557.8089 1376.5757 1717.5131 3789.6367 4374.924 4661.983 4906.295 5126.328 5366.099 5700.954 6093.895 6373.318 6662.277 7052.016 42 0 630.2661 1193.3800 1873.1848 2570.3404 4480.458 4760.433 4989.828 5196.567 5467.604 5825.079 6199.229 6455.391 6788.114 7185.957 43 0 693.2642 1258.6225 1972.1365 2542.3680 2998.083 4954.106 5165.311 5409.632 5760.718 6158.485 6419.620 6730.438 7126.538 7698.261 44 0 659.0779 1424.3069 1985.2594 2562.8746 2956.804 5000.693 5205.326 5468.793 5833.932 6215.386 6468.055 6805.847 7199.270 7768.425 45 0 622.3183 1508.8291 2004.5159 2617.4568 2906.259 5105.491 5310.809 5640.120 6037.259 6350.617 6617.429 7010.112 7567.029 7935.106 46 0 748.1320 1420.2905 1918.0444 2387.3146 2944.222 3200.280 5638.642 6042.090 6359.177 6630.009 7026.052 7589.457 7953.123 9750.808 47 0 776.8924 1295.0113 1850.4047 2345.2464 2684.623 3198.436 3560.258 6111.756 6406.718 6704.037 7106.426 7688.063 8020.653 9826.634 48 0 747.8301 1239.3244 1821.7368 2307.3685 2662.949 3181.705 3520.586 6077.367 6392.165 6678.445 7082.122 7663.593 8009.702 9829.559 49 0 393.4405 1177.9598 1609.1929 2131.2111 2603.489 2973.969 3531.979 3860.269 6685.946 7094.584 7684.306 8027.297 9845.986 10121.594 50 0 390.1414 743.8896 1481.0651 1903.5644 2440.425 2956.124 3306.767 3835.756 4209.547 7645.069 8005.137 9831.567 10109.160 NA 51 0 362.0675 703.6954 1426.9361 1783.0602 2396.771 2841.141 3291.330 3881.757 4126.403 7898.816 9736.808 10025.405 10748.965 NA 52 0 291.4742 618.8264 982.8837 1358.4474 2116.623 2548.785 3111.380 3553.447 3855.896 4383.907 4684.176 NA NA NA 53 0 279.8816 605.5687 937.5612 1281.5761 1655.178 2415.930 2717.749 3279.507 3763.386 4094.186 4587.000 4800.000 NA NA 54 0 322.8420 626.1536 911.6326 1250.8055 1594.668 1888.862 2639.129 2984.677 3518.672 3957.830 4287.510 4781.669 4999.944 NA 55 0 315.5918 650.3962 953.5294 1185.6491 1450.562 1775.865 2079.556 2370.648 3086.402 3435.790 3939.198 4388.004 NA NA 56 0 317.4154 613.4286 889.4016 1165.8956 1439.092 1678.931 1931.073 2232.853 2525.786 3248.952 NA NA NA NA 57 0 276.7260 531.1405 826.6545 1120.4563 1375.921 1610.042 1841.894 2093.399 2379.462 NA NA NA NA NA 58 0 244.4130 462.7608 737.0829 984.1782 1228.584 1502.651 1757.180 NA NA NA NA NA NA NA 59 0 241.9073 454.8290 645.5639 889.2351 1155.662 1388.209 NA NA NA NA NA NA NA NA 60 0 188.9915 377.9831 567.6136 NA NA NA NA NA NA NA NA NA NA NA 61 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 62 0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA 63 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA ----------------------------------------------------------------------------------------- What I do not understand is why the output is triangle shaped with NA values as can be seen above. I do understand why there are NA values for relocations and the end of the track, probably because the animal doesn'tleave the circle with radius r. What I do not understand is why there are so many NA values for relocations in the beginning of the track because I am sure they pass the circle with radius r. When I run the varlogfpt function I get an output but I am wondering whether this is a valid output because of the output (NA values) I get from the fpt function. Hopefully my question is clear, Thanks in advance, Onno Keller
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