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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