CPUE with Temperature
Libraries
library(ggplot2)Data
Import data
Set the working directory and read in the data set. This is a csv copy of the excel file that was sent, for the sheet with all sites included.
setwd("C:\\Users\\Jack\\Documents\\AB\\PVA MS Sturgeon 2019")The working directory was changed to C:/Users/Jack/Documents/AB/PVA MS Sturgeon 2019 inside a notebook chunk. The working directory will be reset when the chunk is finished running. Use the knitr root.dir option in the setup chunk to change the working directory for notebook chunks.dat <- read.csv("All Sturgeon Data Feb 2019.csv")View data
head(dat)Get a summary of each column.
sapply(X = dat, FUN = summary)$Sample.ID
CHAIN_OF_ROCKS_040815_1508_TL60_5 CHAIN_OF_ROCKS_040815_1511_TL60_6
84 82
CHAIN_OF_ROCKS_040715_1339_TL60_2 ROBINSON_BAYOU_032802_1530_TL60_3
58 50
OHIO_RIVER_REACH_121014_1504_TL60_3 OHIO_RIVER_REACH_121014_1453_TL60_1
49 46
BELOW_LWD_27_052405_1600_TL60_2 BELOW_LWD_27_110413_1423_TL_3
43 43
BELOW_LWD_27_113004_1537_TL60_5 OHIO_RIVER_REACH_121014_1458_TL60_2
43 43
BELOW_LWD_27_042403_1830_TL60_1 MS_RIVER_CHAIN_OF_ROCKS_041916_1521_TL_3
42 42
BELOW_LWD_27_041414_1442_TL_4 BELOW_LWD_27_050205_1724_TL60_8
41 41
BELOW_LWD_27_050305_1617_TL60_8 BELOW_LWD_27_110513_1453_TL_3
41 41
BELOW_LWD_27_042203_1701_TL60_8 BELOW_LWD_27_042303_2000_TL60_3
40 40
BELOW_LWD_27_042303_2000_TL60_6 CHAIN_OF_ROCKS_040815_1444_TL60_2
40 40
CHAIN_OF_ROCKS_040815_1502_TL60_4 OHIO_RIVER_REACH_120914_1519_TL60_2
40 40
BELOW_LWD_27_041414_1455_TL_6 BELOW_LWD_27_050205_1724_TL60_3
39 39
BELOW_LWD_27_050205_1724_TL60_5 CHAIN_OF_ROCKS_040715_1335_TL60_1
39 39
CHAIN_OF_ROCKS_040715_1349_TL60_4 CHAIN_OF_ROCKS_040815_1450_TL60_3
39 39
BELOW_LWD_27_041514_1555_TL_5 ISL63_OLDTWN_BEND_030707_1630_TL60_1
38 38
ROBINSON_BAYOU_040302_1616_TL60_8 BELOW_LWD_27_041414_1439_TL_3
38 36
BELOW_LWD_27_041414_1450_TL_5 BELOW_LWD_27_050205_1724_TL60_1
36 36
BELOW_LWD_27_052305_1806_TL60_6 BELOW_LWD_27_052305_1806_TL60_8
36 36
BELOW_LWD_27_113004_1537_TL60_6 MS_RIVER_CHAIN_OF_ROCKS_041816_1541_TL_5
36 36
BELOW_LWD_27_041414_1436_TL_2 BELOW_LWD_27_042303_2000_TL60_2
35 35
BELOW_LWD_27_050205_1724_TL60_2 BELOW_LWD_27_050305_1617_TL60_2
35 35
BELOW_LWD_27_110513_1445_TL_1 CHAIN_OF_ROCKS_040715_1345_TL60_3
35 35
BELOW_LWD_27_051904_1644_TL60_2 BELOW_LWD_27_052004_1740_TL60_1
34 34
BELOW_LWD_27_110413_1415_TL_1 BELOW_LWD_27_113004_1537_TL60_4
34 34
BELOW_LWD_27_050205_1724_TL60_7 BELOW_LWD_27_050305_1617_TL60_3
33 33
BELOW_LWD_27_052004_1740_TL60_4 BELOW_LWD_27_052305_1806_TL60_1
33 33
BELOW_LWD_27_110413_1427_TL_4 BELOW_LWD_27_052405_1600_TL60_4
33 32
CHEROKEE_LNDG_031804_1602_TL60_1 MAYERSVILLE_DIKES_121905_1653_GN90_11
32 32
BELOW_LWD_27_051904_1644_TL60_4 ROBINSON_BAYOU_040302_1616_TL60_3
31 31
BELOW_LWD_27_041414_1431_TL_1 BELOW_LWD_27_050305_1617_TL60_7
30 30
FARMER_LNDG_031704_1530_TL60_7 ISLAND63_CHUTE_LOWER_051215_1353_TL60_2
30 30
OHIO_RIVER_REACH_121014_1442_TL40_7 SAWYER_BEND_111803_1000_TL60_5
30 30
BELOW_LWD_27_041414_1514_TL40_7 BELOW_LWD_27_042203_1701_TL60_7
29 29
BELOW_LWD_27_050205_1724_TL60_6 BELOW_LWD_27_050305_1617_TL60_1
29 29
BELOW_LWD_27_050305_1617_TL60_6 BELOW_LWD_27_051904_1644_TL60_5
29 29
BELOW_LWD_27_113004_1537_TL60_2 OHIO_RIVER_REACH_120914_1510_TL60_1
29 29
OHIO_RIVER_REACH_121014_1510_TL60_4 ROBINSON_BAYOU_040302_1616_TL60_5
29 29
ROBINSON_BAYOU_040402_1827_TL60_5 BALESHED_STACK_120100_1000_TL60_1
29 28
BELOW_LWD_27_050305_1617_TL60_5 BELOW_LWD_27_052405_1600_TL60_3
28 28
CHAIN_OF_ROCKS_040815_1442_TL60_1 ISLAND63_CHUTE_LOWER_081815_1407_TRAWL10_2
28 28
ROBINSON_BAYOU_040302_1616_TL60_6 SAWYER_BEND_111803_1000_TL60_7
28 28
BELOW_LWD_27_042303_2000_TL60_1 BELOW_LWD_27_051904_1644_TL60_3
27 27
ROBINSON_BAYOU_032802_1530_TL60_1 ROBINSON_BAYOU_040302_1616_TL60_7
27 27
CHAIN_OF_ROCKS_040715_1355_TL60_5 MAYERSVILLE_DIKES_121905_1653_GN90_9
26 26
MHOON_BEND_LOW_032206_1600_TL60_5 RACETRACK_ISL_011304_1451_TL60_2
26 26
ROBINSON_BAYOU_032802_1530_TL60_5 BELOW_LWD_27_050205_1724_TL60_4
26 25
BELOW_LWD_27_050305_1617_TL60_4 BELOW_LWD_27_051804_1517_TL60_1
25 25
BELOW_LWD_27_120104_1705_TL60_5 CHAIN_OF_ROCKS_040715_1359_TL60_6
25 25
MS_RIVER_CHAIN_OF_ROCKS_041816_1523_TL_1 BELOW_LWD_27_051804_1517_TL60_6
25 24
BELOW_LWD_27_052405_1600_TL60_5 (Other)
24 6959
$STATE
AR IL LA MO MS TN
757 596 1323 5296 2157 259
$COUNTY
Adams Alexander Ascension Avoyelles Bolivar
72 320 42 3 420
Cape Girardeau Catahoula Chicot Claiborne Coahoma
57 50 27 485 334
Concordia Crittenden Desha Dyer E. Baton Rouge
111 59 161 4 5
E. Carroll E. Feliciana East Carroll Iberville Issaquena
14 3 343 54 2
Jefferson Lake Lauderdale Lee Madison
119 12 79 141 225
Mississippi Monroe New Madrid Pemiscot Perry
791 23 56 419 149
Phillips Plaquemines Point Coupee Randolph Red River
351 2 4 151 6
Scott Shelby St. Charles St. Genevieve St. James
137 154 176 226 62
St. John St. John the Baptist St. Louis Tensas Tipton
2 2 3440 30 10
Tunica Union Warren Washington Wilkerson
386 102 231 203 133
$STATION
Below LWD 27 Ohio River Reach Chain of Rocks
2435 549 539
Robinson Bayou MS River Chain of Rocks Togo Bend
419 247 224
Big Island Mhoon Bend At I-57 Near Cairo
163 151 150
Baleshed Stack Cottonwood Reach Hard Scrabble
150 149 144
Fort Adams Racetrack Mayersville Dikes
133 121 108
Mhoon Bend Lower Island 63 Chute Lower Sawyer Bend
108 106 103
Lakeport Towhead Walnut Bend Cherokee Landing
97 90 89
Prentiss Revetment Delta Point Friars Point
86 85 80
Plum Point At Cairo Victoria Bend
79 75 74
Below Ohio Confluence Island 63 Chute Middle Fort Adams Reach
72 68 67
Stilling Basin Barbars Canal Hwy 60 Bridge
66 64 63
Loosahatchie Bar Island 63 Secondary Channel Mhoon Bend Up
63 61 60
NR Chester Prison St. Genevieve Weirs Racetrack Island
60 60 59
Walnut Point Thebes Gap At I57 Bridge
58 57 54
Farmer Landing Midground Island Island 63 Mth Secondary Channel
53 53 50
RED DS LD1 Driver Bar Bushberg
50 49 46
Meramec R Confluence Island 70 Secondary Channel Loosahatchie
46 45 45
Marigold Point Mhoon Bend Middle Mosenthien Island
45 44 43
Beaver Island Cottonwood Reach 4 Cates Landing
41 41 40
Palmetto Bend Cottonwood Bar Kate Aubrey
40 39 39
Cottonwood Reach 2 Island 63 Old Town Bend Bayou Goula TWHD
38 38 37
Corona Bar Montezuma TWHD Gramercy Bridge
37 37 35
Powers Island Island 63 Chute Upper Kentucky Bend
35 34 34
Reid Bedford Bend Below Natchez Sergeant Point
34 32 32
Prentiss Bar Grand Gulf S Sunflower Cutoff
30 28 28
Schmidts Island Smith Point Duck Island
27 27 26
American Chute Belle Island Island 69 Secondary Channel
25 25 25
MTH Bayou Pierre Point Houmas Montezuma Bend
25 25 24
Above Ohio Confluence Burnham Island Island 63 Secondary Channel Above
23 23 23
Michaels TWHD Swiftsure Towhead Donaldsonville DS
23 23 21
MS River at Vicksburg Concordia Bar MS River RM 168-Below I-255
21 20 20
St. Genevieve Island Terrene Dike Buck Ridge
20 20 19
Fitler Bend At Hwy 60 62 Cannon Point
19 18 18
(Other)
844
$River.Mile.Start
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
33.3 581.5 900.0 808.6 1143.2 1153.5 36
$River.Mile.End
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
180.0 180.0 180.0 212.4 180.0 439.0 10380
$TIME
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
630 1423 1524 1477 1630 2000 29
$PROJECT
ACM Hoopnet Birds Point New Madrid Breach Bonnet Carre Dikenotch
3 5 168 481
LMR LMR Diversion LMR Secondary Channels Maurepas
3995 3 178 37
Mhoon Bend Pallid Study MMR MMR Random MMR Targeted
270 2952 149 1780
MRG&P Ecohydrology MS River Below New Orleans Nelson Electric Sand and Gravel Dredge
238 2 56 71
$YEAR
Min. 1st Qu. Median Mean 3rd Qu. Max.
1997 2003 2005 2006 2011 2018
$Waypoint.1
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
277 317 364 1242 370 10099 9865
$Waypoint.2
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
511.0 583.2 590.0 875.4 1287.0 1291.0 10374
$GPS.Unit
1k 2k 4k CP GIS GPS
9865 2 84 277 113 14 33
$LAT
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
29.94 34.01 36.98 36.01 38.75 38.76 305
$LON
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
-93.26 -90.76 -90.18 -90.29 -90.06 -89.11 305
$CREW
AWK, JAC, SGG, WEL, WTS, KJK, SD, Mitch
9830 2
ERDC JAC, SGG, WTS, BRL, WEL, KJK
238 247
JAC, WTS, SGG, BRL, WEL, KJK, Bruce Reid-video KJK
20 1
KJK, SGG, WTS, JAC, BRL, WEL, JPK KJK, SGG, WTS, JAC, JJH, JPK, BRL, WEL
7 6
KJK, WTS, JJH, JAC, SGG, BRL, AWK KJK, WTS, SGG, LDWF
1 8
NMF, WTS, BRL, JAC, SGG, KJK SGG, WEL, KJK
6 2
WTS, JAC, JJH, SGG, BRL, WEL, JPK, KJK
20
$LOCATION
Bonnet Carre CHAIN_OF_ROCKS
9813 8 247
Coffee Point Dikes ISL63 ISL64
6 208 21
Island82_2°Channel MS River MS River at Chain of Rocks RM 190.5
2 20 6
MS River at Racetrack MS River at St. Louis RM 175.5-180 MS River at Vicksburg
1 7 1
MS River Empire to Ft. Jackson MS River RM 168-Below I-255 Rosedale
2 20 17
SUNFLO
9
$STN
Between 4R&3R Between 5R&4R Chain of Rocks
10077 2 2 6
GIANTSB Island 82 2° Channel LOWER Lower Transitional
8 2 108 2
MIDDLE MS River MS River Below I255 St. Louis
78 4 20 7
Stilling Basin Bay 1-95 Stilling Basin Bay 307-282 Stilling Basin Bay 310 Stilling Basin Bay 348
1 1 1 1
Stilling Basin Bay 96-350 TINYISL UPPER Vicksburg
4 1 43 20
$SAMPLE
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.000 2.000 3.000 3.679 5.000 14.000
$General.Comments
3 Containers: fish, detritus, inverts, etc.
10380 2
Bay 276-305 Bay 306-335
2 2
Bay 76-95 Outside baffle
1 1
$Lat.Begin
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
29.45 34.22 34.30 35.93 38.75 38.76 9726
$Lon.Begin
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
-91.18 -90.76 -90.72 -90.57 -90.18 -89.60 9726
$Lat.End
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
29.44 30.00 30.00 30.77 31.99 31.99 10374
$Lon.End
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
-91.14 -91.13 -90.44 -90.61 -90.43 -89.60 10374
$Water.Temp.S
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
1.66 7.48 11.86 12.25 14.43 35.66 57
$GEAR
Angel_Net Backpack_Shocker Cast_Net Dip_Net Electroshock_18 Electroshock_LDWF
1 1 24 3 14 32
Floating_Gillnet Foot Gar_Net Gillnet_140 Gillnet_180 Gillnet_90
2 3 7 7 15 296
GN LDWF GN300 Hand_Grab HN Hoopnet_3 Hoopnet_4
7 4 5 1 2 1
Large_Gillnet_Seine Missouri_Trawl_10 MONO_GN_LDWF Observed Seine_10 Seine_20
16 373 1 2 2 1
Small_Gillnet_Seine Sturgeon_Gillnet TRAM TRAM100 TRAM150 TRAM300
2 5 6 7 1 30
Trawl_16 TRAWL25 TRML Trotline_10 Trotline_20 Trotline_30
91 8 1 1 129 4
Trotline_40 Trotline_50 Trotline_60
292 8 8983
$Gear.Code
ANG_GN CAST DIP ES_LDWF ES18 FLOAT_GN FOOT GAR GN GN140 GN180 GN90 HAND
1 24 3 32 14 2 3 7 57 7 15 296 5
HN HN3 HN4 LG_GN_SN MO_TR_10 OBS SHKR SM_GN_SN SN10 SN20 STU_GN TL10 TL20
1 2 1 16 373 2 1 2 2 1 5 1 129
TL30 TL40 TL50 TL60 TR TR16
4 292 8 8983 8 91
$G_S
Scaphirhynchus_albus Scaphirhynchus_platorynchus Scaphirhynchus_sp
310 9841 237
$Common
Pallid sturgeon Scaphirhynchus sp. Shovelnose sturgeon
310 237 9841
$NO
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.000 1.000 1.000 1.022 1.000 53.000
$Total.Length
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
15.3 591.0 666.0 636.4 736.0 1087.0 7293
$Standard.Length
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
54.1 508.0 561.0 561.3 618.0 940.0 7545
$Fork.Length
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
17 540 600 588 647 1000 363
$LBS
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.000 1.000 2.000 1.762 2.000 9.020 8054
$OZS
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.000 3.000 7.000 9.716 11.000 5803.000 8051
$Floy.Tag.No
PARSONS 943 RELEASE 11274 262 320 915 971 979 986 987
892 15 5 5 4 4 4 4 4 4 4 4
988 WES_11772 WES_11773 1000 11576 2439 253 254 268 270 272 274
4 4 4 3 3 3 3 3 3 3 3 3
276 277 282 291 294 295 300 301 303 304 305 306
3 3 3 3 3 3 3 3 3 3 3 3
307 308 309 310 311 314 315 317 318 319 322 327
3 3 3 3 3 3 3 3 3 3 3 3
328 329 333 338 339 342 343 346 347 348 350 49
3 3 3 3 3 3 3 3 3 3 3 3
50 571 585 65 729 730 731 733 734 736 737 740
3 3 3 3 3 3 3 3 3 3 3 3
744 745 746 748 749 76 762 763 917 918 921 923
3 3 3 3 3 3 3 3 3 3 3 3
937 940 941 942 944 945 946 947 948 949 950 953
3 3 3 3 3 3 3 3 3 3 3 3
955 957 959 (Other)
3 3 3 9175
$Pit.Tag.No
014785280 152278204A 152304205A NONE 014780104 014783039 014787804 014788618 014788893 014789119
9968 2 2 2 2 1 1 1 1 1 1
014790838 014791112 014797772 014802345 014806124 014806818 014809361 014810800 014811305 014816310 014817061
1 1 1 1 1 1 1 1 1 1 1
014820558 014821518 014821633 014825567 014825884 014832044 014834823 014835538 014837307 014838355 014842085
1 1 1 1 1 1 1 1 1 1 1
019797344 020326262 021632351 023343796 024100326 024352105 114569540A 114633183A 114933531A 114934533A 114935524A
1 1 1 1 1 1 1 1 1 1 1
114936671A 114936796A 114939124A 114939260A 114939383A 114939467A 114944362A 114944494A 114945496A 114946277A 114947331A
1 1 1 1 1 1 1 1 1 1 1
114951654A 114951677A 114954113A 114954610A 114954733A 114955112A 114957467A 114959363A 114959396A 114961296A 114961297A
1 1 1 1 1 1 1 1 1 1 1
114961351A 114961591A 114962213A 114962232A 114962267A 114962565A 114966511A 114966565A 114966571A 11496657A 114969377A
1 1 1 1 1 1 1 1 1 1 1
114969574A 114969696A 114973572A 114975383A 115128220A 115221256A 115221483A 115221622A 115222212A 115222290A 115222320A
1 1 1 1 1 1 1 1 1 1 1
115222364A 115222393A 115222513A 115222520A 115222590A 115222591A 115222751A 115223161A 115223166A 115223255A 115223335A
1 1 1 1 1 1 1 1 1 1 1
(Other)
318
$COMMENTS
8087
YELLOW
383
GRAVID
239
FEMALE
122
RELEASED
81
ETOH
59
INCOMPL
59
PHOTO
51
NAKED
48
RECAPTURE
43
FORMALIN
40
GIVEN_TO_HATCHERY
31
WORM
27
TOO_SMALL_TO_TAG
25
USFWS
25
NO_TAG
20
RECAP
18
RECAP_ORANGE
18
ORANGE
17
OLD_TAG
16
Yellow tag
16
GRAVID_FEMALE
15
GRAVID_YELLOW
14
TAKEN_FOR_PARASITES
12
DOA
11
FECAL_SAMPLE
11
Female-Gravid
10
ETOH100
9
LINE_BROKE_CAUGHT_NEXT_DAY
9
DEAD
8
PRESERVED_LARVAE
8
LAB
7
MALE_GIVEN_TO_HATCHERY
7
PEC_RAY_CLIP_TAKEN
7
RETAINED
7
TRANSMITTER_NO_CWT
7
NO_PEC_RAY_CLIP_TAKEN
6
OLD_TAGS
6
Preserved in Ethanol
6
TELEMETRY
6
ETOH70
5
LARVAE
5
MATURE_MALE
5
Morphometric measurements taken
5
PITTAG_NOTREAD
5
SNAGGED
5
END_OR_SAVED
4
ENDO_SACRIFICED
4
ETOH?
4
FEMALE_LAP_DONE_GENETICS
4
GENETICS
4
IMMAT_FEMALE
4
MATURE_FEMALE
4
RECAP_WHITE
4
RECAP_YELLOW
4
RETAINED_MSU
4
STOMACH_SAMPLE
4
TWRA_CAPTURE
4
WORM_LAPROSCOPE
4
YELLOW_TAG
4
COLONIC_FLUSH
3
DECOMPOSED
3
ERDC-2015-00294
3
ERDC-2015-00296
3
FEMALE_GIVEN_TO_HATCHERY
3
MALE
3
MALE_LAP_DONE_GENETICS
3
No Genetics
3
Orange, Both spines present
3
PHOTO_BAND_SAVED
3
POINTBAR
3
RETAINED_ENDO
3
Rostrum Notch
3
SPINE_TAKEN
3
TRANSMITTER_CWT_DETECTED
3
WALLUS_LAB_16
3
WALLUS_LAB_41
3
WALLUS_LAB_42
3
WALLUS_LAB_45
3
WALLUS_LAB_46
3
CERT_RECAP
2
CRAYFISH
2
CWT_DETECTED
2
CWT_NEG_PIT_NEG_YELLOW
2
CWT_NEG_SPINE_18589
2
CWT_NEG_SPINE_18614
2
DOA- iced down
2
DRY_GEN_CLIP_INCOMPL
2
DRY_GEN_SAMPLE
2
DUPLICATE_TAG
2
FEMALE; Recap info: 4/24/18 MS River at Chain of Rocks; POC: Alex, 660-281-7967, AK11161986@mail.ru
2
GRAINY_SCALES
2
GRAV_SAMPLE
2
IMMAT_MALE
2
INCOMPLETE_BELLY_SCALES
2
KEPT_4_AGE_GRTH
2
LOST
2
MALE_IMMATURE_GIVEN_TO_HATCHER
2
Missing Tail
2
(Other)
613
$ANOMALIES
NO_TAIL MISSING_TAIL ROSTRUM_TIP_BLOODY EGG_CHECK_WOUND
9945 37 34 14 13
BAND_SCAR NOTCH_ROSTRUM RED_PEC_FINS TAIL_MISSING BAND
10 6 6 6 5
NOTCHED_ROSTRUM RUBBER_BAND DAMAGED_ROSTRUM DEF_ROSTRUM GRAVID
5 5 4 4 4
NO_EYES O_RING_SCAR RING_SCAR ROSTRUM_TIP_BLOODY_L BROKEN_TAIL
4 4 4 4 3
EGG_CHECK_WOUND_BELL MONOFILAMENT NO_ROSTRUM O_RING R_BAND
3 3 3 3 3
RED_L_PEC RED_PECS ROSTRUM_NOTCH ???? BANDED
3 3 3 2 2
BRUISED_NOSE CAUDAL_CURLED DEF_BARB DEF_PEDUNCLE DEF_TAIL
2 2 2 2 2
EGG_CHECK_SCAR FEMALE HEALED_BROKEN_TAIL L_PECT LEFT_ROSTRUM_NOTCH
2 2 2 2 2
MISSING_DOR_FIN MISSING_DORSAL_SCUTE MISSING_L_OB MISSING_R_EYE MISSING_R_PEC_FIN
2 2 2 2 2
NOTCHED_ROST OIL_RING RED_EYES RED_L_EYE RED_PEC_FIN
2 2 2 2 2
ROST_ABRASIONS ROSTRUM_TIP_BLOODY_B SCAR TAIL 6TH_DORSAL_SCUTE_MIS
2 2 2 2 1
ABRASION ANG_CONSTRICT_ACROSS ANOMALY? ASYMETRICAL_ROSTRUM BAND_CUTTING_PECS
1 1 1 1 1
BAND_INJ_MIDBODY BAND_INJ_ROSTRUM BAND_SCAR_MISSING_R_ BANDED_HEAD BANDED_HEALED
1 1 1 1 1
BANDED_PLATES_DAMAGE BANDED_RED_EYES BANDED_ROST_NOT_REMO BANDED_SWIMMING_IMPA BARBLES_HIGHLY_BRANC
1 1 1 1 1
BENT_FOLDED_ROSTRUM BIG_EYES_SGG BLACK_BAND BOTH_PECS_RED BRANCH_L_O_BRBL
1 1 1 1 1
BROKEN_PEC_RAY BROKEN_PEDUNCLE BRUISED_ROSTRUM_TIP BUTTERSCOTCH_PIC_TAK CAUDAL_FIN_MISSING
1 1 1 1 1
CUT_ROSTRUM DAM_BARBELS_ROST_SCA DAMAGE_L_ROST DAMAGE_TAIL DAMAGED_DORSAL_FIN
1 1 1 1 1
DAMAGED_L_INNER_R_OU DAMAGED_L_OUTER_BARB DAMAGED_R_INNER_BARB DAMAGED_ROST DAMAGED_TAIL
1 1 1 1 1
DEF DEF_CAUDAL_FIN DEF_DOR_FIN DEF_L_ROSTRUM DEF_PEC_FIN_RIGHT
1 1 1 1 1
DEF_ROST DEFORMED_OPERCULUM DEFORMED_PEC_FIN DEFORMED_TAIL (Other)
1 1 1 1 150
$Weight.kgs
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.000 0.610 0.907 0.981 1.230 6.400 7317
$Life.Stage
0.88 L PYSL YOY YSL
10302 1 23 39 9 14
$KGS
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.000 0.520 0.815 0.924 1.130 6.400 9638
$Envelope.No
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
7633 13143 13488 14438 15323 19988 10276
$Genus
Scaphirhynchus
10388
$DATE
4/8/2015 0:00 5/2/2005 0:00 5/3/2005 0:00 4/14/2014 0:00 4/7/2015 0:00 12/10/2014 0:00 11/30/2004 0:00
313 277 250 246 226 213 211
4/3/2002 0:00 4/23/2003 0:00 5/24/2005 0:00 5/23/2005 0:00 5/19/2004 0:00 3/28/2002 0:00 11/4/2013 0:00
200 166 157 150 148 147 144
4/18/2016 0:00 11/5/2013 0:00 1/16/2002 0:00 4/22/2003 0:00 12/19/2005 0:00 4/19/2016 0:00 12/9/2014 0:00
139 131 129 126 117 108 106
4/2/2003 0:00 11/29/2000 0:00 5/18/2004 0:00 5/20/2004 0:00 11/18/2003 0:00 5/12/2015 0:00 4/15/2014 0:00
105 102 100 99 97 93 92
12/2/2004 0:00 3/18/2004 0:00 12/1/2004 0:00 3/4/2008 0:00 3/7/2007 0:00 3/22/2006 0:00 3/25/2003 0:00
91 89 88 86 83 80 80
11/16/2014 0:00 4/10/2002 0:00 3/24/2005 0:00 2/14/2002 0:00 4/1/2003 0:00 4/23/2014 0:00 8/18/2015 0:00
79 79 77 73 71 70 68
11/7/2013 0:00 4/9/2003 0:00 1/15/2008 0:00 12/1/2000 0:00 2/2/2004 0:00 4/4/2002 0:00 11/17/2014 0:00
65 64 62 62 62 62 60
4/14/2004 0:00 4/15/2004 0:00 1/13/2004 0:00 11/21/2002 0:00 4/22/2014 0:00 3/22/2005 0:00 5/17/2001 0:00
60 60 58 57 57 55 55
3/17/2004 0:00 5/30/2007 0:00 1/30/2008 0:00 3/16/2004 0:00 1/29/2008 0:00 11/7/2006 0:00 12/13/2011 0:00
53 53 52 52 51 50 50
2/4/2004 0:00 1/28/2003 0:00 11/18/2014 0:00 11/23/2008 0:00 2/20/2002 0:00 3/27/2007 0:00 4/11/2002 0:00
50 49 49 49 49 49 49
10/29/2014 0:00 10/26/2004 0:00 10/27/2004 0:00 3/19/2002 0:00 6/27/2011 0:00 3/12/2012 0:00 1/25/2002 0:00
47 46 46 46 46 45 43
11/16/2011 0:00 3/6/2008 0:00 3/21/2006 0:00 4/24/2003 0:00 11/19/2014 0:00 4/9/2002 0:00 12/19/2001 0:00
43 43 42 42 40 40 39
4/15/2003 0:00 10/16/2001 0:00 11/19/2002 0:00 11/3/2004 0:00 2/25/1997 0:00 3/26/2003 0:00 5/14/2003 0:00
39 37 37 37 37 37 37
1/25/2001 0:00 2/21/2002 0:00 3/23/2005 0:00 4/3/2003 0:00 1/23/1997 0:00 12/14/2004 0:00 3/24/2004 0:00
36 36 36 36 35 35 35
11/13/2003 0:00 (Other)
34 2186
$MM
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.000 3.000 4.000 5.923 11.000 12.000
$DD
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.00 8.00 16.00 15.21 23.00 31.00
$YYYY
Min. 1st Qu. Median Mean 3rd Qu. Max.
1997 2003 2005 2006 2011 2018 Convert variables
Convert the DATE variable from factor to Date class
dat$DATE <- as.Date(as.character(dat$DATE), format = "%m/%d/%Y")
head(dat$DATE)[1] "1997-01-09" "1997-01-09" "1997-01-09" "1997-01-09" "1997-01-09" "1997-01-09"Compute the value of the effort variable
The effort is the number of trotlines, etc., put out per day. This is found from the maximum value of the variable SAMPLE per day.
effort <- aggregate(dat$SAMPLE, by = list(dat$DATE), FUN = max)
effortNow make this a column of the data frame we are using.
for(i in 1:nrow(dat)){
dat$effort[i] <- max(dat$SAMPLE[dat$DATE == dat$DATE[i]], na.rm = TRUE)
}
dat[1:50, c("DATE", "effort")]Aggregate data
For the imported data, each row is a fish. We need to convert this to counts of numbers of fish.
dat2 <- aggregate(Sample.ID ~ River.Mile.Start + Water.Temp.S + effort + G_S, FUN = length, data = dat)Calculate the catch per unit effort as the number of fish caught divided by the number gears used at that location.
dat2$cpue <- dat2$Sample.ID / dat2$effortVisualize relationship
Plot the cpue vs river mile relationship by species.
levels(dat2$G_S) <- c("S. albus", "S. platorynchus", "S. sp.")
ggplot(dat2, aes(x = River.Mile.Start, y = cpue)) +
xlab("River mile start") +
ylab("Catch per unit effort") +
geom_point(shape = 1) +
facet_wrap( ~ G_S, ncol = 1, scales = "free_y") +
theme(panel.background = element_rect(fill = "white", colour = "black"),
panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
strip.background = element_rect(fill = "white", colour = "black"),
legend.key = element_blank(),
legend.title = element_blank())
Model
Across all species
Linear model across all species.
fit <- lm(cpue ~ River.Mile.Start + Water.Temp.S, data = dat2)
summary(fit)
Call:
lm(formula = cpue ~ River.Mile.Start + Water.Temp.S, data = dat2)
Residuals:
Min 1Q Median 3Q Max
-4.673 -2.543 -1.411 0.634 36.817
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.2377053 0.6847118 1.808 0.0712 .
River.Mile.Start 0.0037501 0.0006956 5.391 1.04e-07 ***
Water.Temp.S -0.0238504 0.0251577 -0.948 0.3435
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4.831 on 544 degrees of freedom
Multiple R-squared: 0.05991, Adjusted R-squared: 0.05646
F-statistic: 17.33 on 2 and 544 DF, p-value: 5.033e-08By species
Make subsets of the data by species.
datA <- subset(dat2, subset = G_S == "Scaphirhynchus_albus")
datP <- subset(dat2, subset = G_S == "Scaphirhynchus_platorynchus")
datSp <- subset(dat2, subset = G_S == "Scaphirhynchus_sp")Linear model with temperature effect.
fitA <- lm(cpue ~ River.Mile.Start + Water.Temp.S, data = datA)
fitP <- lm(cpue ~ River.Mile.Start + Water.Temp.S, data = datP)
fitSp <- lm(cpue ~ River.Mile.Start + Water.Temp.S, data = datSp)
summary(fitA)
Call:
lm(formula = cpue ~ River.Mile.Start + Water.Temp.S, data = datA)
Residuals:
Min 1Q Median 3Q Max
-0.6791 -0.2211 -0.0786 0.1275 3.1705
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.2049353 0.1259570 1.627 0.1060
River.Mile.Start -0.0002416 0.0001260 -1.918 0.0571 .
Water.Temp.S 0.0282042 0.0062006 4.549 1.17e-05 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.4969 on 139 degrees of freedom
Multiple R-squared: 0.1701, Adjusted R-squared: 0.1582
F-statistic: 14.24 on 2 and 139 DF, p-value: 2.358e-06summary(fitP)
Call:
lm(formula = cpue ~ River.Mile.Start + Water.Temp.S, data = datP)
Residuals:
Min 1Q Median 3Q Max
-4.655 -2.543 -1.299 0.603 36.900
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.1013139 0.6879058 1.601 0.110
River.Mile.Start 0.0038928 0.0006982 5.576 3.95e-08 ***
Water.Temp.S -0.0314742 0.0251862 -1.250 0.212
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4.718 on 525 degrees of freedom
Multiple R-squared: 0.06874, Adjusted R-squared: 0.06519
F-statistic: 19.38 on 2 and 525 DF, p-value: 7.603e-09summary(fitSp)
Call:
lm(formula = cpue ~ River.Mile.Start + Water.Temp.S, data = datSp)
Residuals:
Min 1Q Median 3Q Max
-2.0012 -1.0244 -0.3563 0.2242 15.7512
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -8.616e-01 1.111e+00 -0.776 0.44092
River.Mile.Start -4.779e-05 1.253e-03 -0.038 0.96971
Water.Temp.S 1.094e-01 3.925e-02 2.787 0.00703 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 2.516 on 63 degrees of freedom
Multiple R-squared: 0.1111, Adjusted R-squared: 0.08284
F-statistic: 3.936 on 2 and 63 DF, p-value: 0.02452Linear model with no temperature effect.
fitA <- lm(cpue ~ River.Mile.Start, data = datA)
fitP <- lm(cpue ~ River.Mile.Start, data = datP)
fitSp <- lm(cpue ~ River.Mile.Start, data = datSp)
summary(fitA)
Call:
lm(formula = cpue ~ River.Mile.Start, data = datA)
Residuals:
Min 1Q Median 3Q Max
-0.4792 -0.2462 -0.1028 0.0725 3.4080
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.6363051 0.0885310 7.187 3.6e-11 ***
River.Mile.Start -0.0003459 0.0001323 -2.615 0.0099 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.5307 on 140 degrees of freedom
Multiple R-squared: 0.04657, Adjusted R-squared: 0.03976
F-statistic: 6.838 on 1 and 140 DF, p-value: 0.009904summary(fitP)
Call:
lm(formula = cpue ~ River.Mile.Start, data = datP)
Residuals:
Min 1Q Median 3Q Max
-4.634 -2.587 -1.276 0.657 36.788
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.5037104 0.4947615 1.018 0.309
River.Mile.Start 0.0041161 0.0006753 6.095 2.12e-09 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4.721 on 526 degrees of freedom
Multiple R-squared: 0.06597, Adjusted R-squared: 0.0642
F-statistic: 37.15 on 1 and 526 DF, p-value: 2.115e-09summary(fitSp)
Call:
lm(formula = cpue ~ River.Mile.Start, data = datSp)
Residuals:
Min 1Q Median 3Q Max
-0.9191 -0.7688 -0.6097 -0.3846 17.0818
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 1.1778431 0.8789471 1.340 0.185
River.Mile.Start -0.0004054 0.0013111 -0.309 0.758
Residual standard error: 2.645 on 64 degrees of freedom
Multiple R-squared: 0.001491, Adjusted R-squared: -0.01411
F-statistic: 0.09559 on 1 and 64 DF, p-value: 0.7582Removing the non-significant temperature effect results in a significant river mile effect with a non-significant intercept. The intercept would have to be significantly negative to justify a cutoff for the presence of shovel-nose sturgeon in the lower reaches of the river. Also, although the regression is significant, the value of R^2 is extremely small, so the relationship very little explanatory power and could probably be safely ignored.
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