Data for Ecosystem Synthesis - Groundfish Update Review December 4-5 2017
December 2017
This script compiles data from different sources summarized below, and creates the following output that is then used in RunIndiAnalysis.Rmd: C:/RProjects/R_Working_Group/Guru/Guru_indicators/inst/output/Indi_used_in_analysis.csv
Source this code if you need to re-do Indi_used_in_analysis.csv and select what idnicators will be included in analysis
Data provided by the Atlantic Zone Monitoring Program (AZMP)
Biological, chemical, and physical data in Maritimes region were provided by C. Johnson and D. Hebert. We used metrics from the standard AZMP scorecards in the AZMP Research Document (Figs. 17 & 31). D. Hebert provided metrics used in the AZMP Research Document, including the 2017 multi-species (groundfish) survey.
Optical, Chemical, and Biological Oceanographic conditions
Data below is in: Johnson, C., Devred, E., Casault, B., Head, E., and Spry, J. 2017. Optical, Chemical, and Biological Oceanographic Conditions on the Scotian Shelf and in the Eastern Gulf of Maine in 2016. DFO Can. Sci. Advis. Sec. Res. Doc. 2017/xxx. v + 54 p. http://www.dfo-mpo.gc.ca/csas-sccs/Publications/ResDocs-DocRech/2017/2017_012-eng.html
Remote-sensing data (annual anomalies)
- Bloom initiation [Day of Year]
- Bloom duration [Days]
- Bloom amplitude [mg chl/m3]
- Bloom magnitude [mg chl·d/m3]
Fig_20 <- read.csv("data/azmp/JohnsonC/RES2017_Final/data_products/bloom_parameters/csv/CSAS_2017_xxx_Fig_20_Annual_Anomalies_CG.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
Fig_20$ID <- "4X"Annual means of phytoplankton (Chlorophyll), zooplankton abundance and biomass (annual means)
Data for the WSS is represented by Browns Bank line
- Chlorophyll 0-100m [mg m-2]
- C. finmarchicus [log10(Individuals/Individus m-2 + 1)]
- Pseudocalanus [log10(Individuals/Individus m-2 + 1)]
- Copepods [log10(Individuals/Individus m-2 + 1)]
- Non-copepods [log10(Individuals/Individus m-2 + 1)]
- Zooplankton biomass [g m-2]
Fig_17 <- read.csv("data/azmp/JohnsonC/RES2017_Final/data_products/csv/CSAS_2017_xxx_Fig_17_Annual_Means_CG.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
Fig_17$ID <- "4X"Time-series of copepod indicator species (group abundance annual means)
- Arctic Calanus [log10(Individuals/Individus m-2 + 1)]
- Warm Offshore copepod species [log10(Individuals/Individus m-2 + 1)]
- Warm Shelf copepod species [log10(Individuals/Individus m-2 + 1)]
Fig_31 <- read.csv("data/azmp/JohnsonC/RES2017_Final/data_products/csv/CSAS_2017_xxx_Fig_31_Annual_Means_CG.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
Fig_31$ID <- "4X"Time-series of Physical Oceanographic Data
Data below is in: Hebert, D., Pettipas, R., Brickman, D., and Dever, M. 2015. Meteorological, Sea Ice and Physical Oceanographic Conditions on the Scotian Shelf and in the Gulf of Maine during. 2014. DFO Can. Sci. Advis. Sec. Res. Doc. 2015/040. v + 49 p. http://publications.gc.ca/collections/collection_2016/mpo-dfo/Fs70-5-2015-040-eng.pdf
- NAO_winter: North Atlantic Oscillation Index used here is the difference in winter (December, January and February) sea level atmospheric pressures between the Azores and Iceland.
- NAO_5Yr_mean: 5 year rolling mean of NAO Index
- GulfStreamDisplacement_5YrMean
- ShelfSlopeFrontDisplacement_5YrMean
- AnnualAvgIceVol: Annual Average Ice Volume (km3)
- BottomT_July: July bottom temperature for NAFO Division 4X
- BottomT_July_anomaly: July bottom temperature anomalies for NAFO Division 4X
- SST_anomalies: annual sea surface temperature anomalies derived from satellite imagery compared to their long-term monthly means
- TemperatureMeanSurface: Figure 30. The mean annual surface temperature for the Scotian Shelf
- StratificationIndex: Figure 29. Stratification index (0-50m density gradient) mean annual anomaly. Under increased stratification, there is a tendency for more primary production to be recycled within the upper mixed layer and hence less available for the deeper layers
- Salinity: Figure 30. The mean annual salinity for the Scotian Shelf
Physical <- read.csv("data/azmp/HebertD/extraction_by_CG.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
Physical$ID <- "4X"Merge and standardize AZMP data
Merge the data sets by year and ID; note that here we selected variable that may be relevant for NAFO Division 4X although some are relevant at larger scales (e.g. NAO).
azmp1 <- left_join(Physical,Fig_17, by=c('YEAR', 'ID'))
azmp2 <- left_join(azmp1, Fig_20, by=c('YEAR', 'ID'))
azmp <- left_join(azmp2, Fig_31, by=c('YEAR', 'ID'))
summary(azmp)## YEAR ID BottomT_July BottomT_July_anomaly
## Min. :1970 Length:47 Min. :5.514 Min. :-1.7287
## 1st Qu.:1982 Class :character 1st Qu.:7.028 1st Qu.:-0.2144
## Median :1993 Mode :character Median :7.420 Median : 0.1771
## Mean :1993 Mean :7.451 Mean : 0.2080
## 3rd Qu.:2004 3rd Qu.:7.995 3rd Qu.: 0.7519
## Max. :2016 Max. :9.359 Max. : 2.1157
##
## NAO NAO_5YrMean GulfStreamDisplacement_5YrMean
## Min. :-4.60 Min. :12.06 Min. :-47.0200
## 1st Qu.:15.20 1st Qu.:16.78 1st Qu.: -6.2500
## Median :22.50 Median :19.54 Median : -0.6300
## Mean :20.50 Mean :19.59 Mean : -0.7138
## 3rd Qu.:27.35 3rd Qu.:22.04 3rd Qu.: 7.8500
## Max. :38.30 Max. :27.82 Max. : 32.6200
## NA's :4 NA's :18
## ShelfSlopeFrontDisplacement_5YrMean SST_anomalies AnnualAvgIceVol
## Min. :-45.11 Min. :-1.8823 Min. :0.0024
## 1st Qu.:-12.60 1st Qu.:-0.7133 1st Qu.:0.4721
## Median : -1.77 Median : 0.2793 Median :1.7973
## Mean : -0.89 Mean : 0.3185 Mean :2.1686
## 3rd Qu.: 16.44 3rd Qu.: 1.3358 3rd Qu.:3.6447
## Max. : 32.08 Max. : 3.9438 Max. :7.5260
## NA's :18 NA's :11
## StratificationIndex TemperatureMeanSurface Salinity
## Min. :-0.015290 Min. :-1.795300 Min. :-0.44450
## 1st Qu.:-0.004820 1st Qu.:-0.562300 1st Qu.:-0.08755
## Median :-0.001300 Median : 0.004000 Median : 0.05750
## Mean :-0.001463 Mean :-0.006328 Mean : 0.03852
## 3rd Qu.: 0.001250 3rd Qu.: 0.381150 3rd Qu.: 0.17650
## Max. : 0.010150 Max. : 2.295500 Max. : 0.38670
##
## Chlorophyll C_finmarchicus Pseudocalanus Copepods
## Min. : 48.74 Min. :3.381 Min. :1.891 Min. :4.843
## 1st Qu.: 83.31 1st Qu.:3.676 1st Qu.:2.762 1st Qu.:5.046
## Median :103.98 Median :3.871 Median :3.223 Median :5.226
## Mean :126.89 Mean :3.887 Mean :3.056 Mean :5.205
## 3rd Qu.:136.74 3rd Qu.:4.153 3rd Qu.:3.445 3rd Qu.:5.365
## Max. :348.29 Max. :4.333 Max. :3.814 Max. :5.474
## NA's :29 NA's :29 NA's :29 NA's :29
## NonCopepods ZooplanktonBiomass BloomInitiation_doy BloomDuration_days
## Min. :3.659 Min. :20.75 Min. :-3.2151 Min. :-1.5887
## 1st Qu.:3.855 1st Qu.:29.53 1st Qu.:-1.0814 1st Qu.:-0.5151
## Median :4.070 Median :32.73 Median : 0.1771 Median :-0.2237
## Mean :4.087 Mean :34.43 Mean :-0.2094 Mean : 0.4261
## 3rd Qu.:4.385 3rd Qu.:39.97 3rd Qu.: 0.6855 3rd Qu.: 0.5969
## Max. :4.507 Max. :50.72 Max. : 1.3606 Max. : 7.4909
## NA's :29 NA's :29 NA's :28 NA's :28
## BloomAmplitude BloomMagnitude ArcticCalanus CopepodsWarmOffshore
## Min. :-1.5801 Min. :-1.2628 Min. :1.337 Min. :1.871
## 1st Qu.:-0.8999 1st Qu.:-0.8796 1st Qu.:1.909 1st Qu.:2.479
## Median :-0.4827 Median :-0.4077 Median :2.128 Median :2.789
## Mean :-0.2383 Mean :-0.2665 Mean :2.095 Mean :2.768
## 3rd Qu.: 0.2374 3rd Qu.: 0.1855 3rd Qu.:2.421 3rd Qu.:2.972
## Max. : 2.6288 Max. : 2.3073 Max. :2.816 Max. :3.567
## NA's :28 NA's :28 NA's :29 NA's :29
## CopepodsWarmSppShelf
## Min. :1.162
## 1st Qu.:1.936
## Median :2.234
## Mean :2.440
## 3rd Qu.:2.951
## Max. :4.119
## NA's :29Source functions to stdize indicators (z-scores: distribution with a mean of 0 and a standard deviation of 1)
source('R/stdize.R')
source('R/stdizeFrame.R')Standardize function and select indicators taht will be used in the MV analysis.
azmp_s <- stdizeFrame(azmp)
colnames(azmp_s)## [1] "YEAR"
## [2] "ID"
## [3] "BottomT_July"
## [4] "BottomT_July_anomaly"
## [5] "NAO"
## [6] "NAO_5YrMean"
## [7] "GulfStreamDisplacement_5YrMean"
## [8] "ShelfSlopeFrontDisplacement_5YrMean"
## [9] "SST_anomalies"
## [10] "AnnualAvgIceVol"
## [11] "StratificationIndex"
## [12] "TemperatureMeanSurface"
## [13] "Salinity"
## [14] "Chlorophyll"
## [15] "C_finmarchicus"
## [16] "Pseudocalanus"
## [17] "Copepods"
## [18] "NonCopepods"
## [19] "ZooplanktonBiomass"
## [20] "BloomInitiation_doy"
## [21] "BloomDuration_days"
## [22] "BloomAmplitude"
## [23] "BloomMagnitude"
## [24] "ArcticCalanus"
## [25] "CopepodsWarmOffshore"
## [26] "CopepodsWarmSppShelf"
## [27] "BottomT_July_s"
## [28] "BottomT_July_anomaly_s"
## [29] "NAO_s"
## [30] "NAO_5YrMean_s"
## [31] "GulfStreamDisplacement_5YrMean_s"
## [32] "ShelfSlopeFrontDisplacement_5YrMean_s"
## [33] "SST_anomalies_s"
## [34] "AnnualAvgIceVol_s"
## [35] "StratificationIndex_s"
## [36] "TemperatureMeanSurface_s"
## [37] "Salinity_s"
## [38] "Chlorophyll_s"
## [39] "C_finmarchicus_s"
## [40] "Pseudocalanus_s"
## [41] "Copepods_s"
## [42] "NonCopepods_s"
## [43] "ZooplanktonBiomass_s"
## [44] "BloomInitiation_doy_s"
## [45] "BloomDuration_days_s"
## [46] "BloomAmplitude_s"
## [47] "BloomMagnitude_s"
## [48] "ArcticCalanus_s"
## [49] "CopepodsWarmOffshore_s"
## [50] "CopepodsWarmSppShelf_s"azmp_suite <- azmp_s[,c("YEAR", "ID","BottomT_July_s", "NAO_s", "NAO_5YrMean_s","SST_anomalies_s", "AnnualAvgIceVol_s", "StratificationIndex_s","TemperatureMeanSurface_s", "Salinity_s", "Chlorophyll_s", "C_finmarchicus_s", 'GulfStreamDisplacement_5YrMean_s','ShelfSlopeFrontDisplacement_5YrMean_s',
"Pseudocalanus_s", "Copepods_s", "NonCopepods_s", "ZooplanktonBiomass_s", "BloomInitiation_doy_s", "BloomDuration_days_s","BloomAmplitude_s", "BloomMagnitude_s", "ArcticCalanus_s", "CopepodsWarmOffshore_s", "CopepodsWarmSppShelf_s")]
summary(azmp_suite)## YEAR ID BottomT_July_s NAO_s
## Min. :1970 Length:47 Min. :-2.37780 Min. :-2.7771
## 1st Qu.:1982 Class :character 1st Qu.:-0.51871 1st Qu.:-0.5868
## Median :1993 Mode :character Median :-0.03799 Median : 0.2208
## Mean :1993 Mean : 0.00000 Mean : 0.0000
## 3rd Qu.:2004 3rd Qu.: 0.66771 3rd Qu.: 0.7573
## Max. :2016 Max. : 2.34216 Max. : 1.9686
##
## NAO_5YrMean_s SST_anomalies_s AnnualAvgIceVol_s
## Min. :-1.9343 Min. :-1.7926 Min. :-1.1780
## 1st Qu.:-0.7219 1st Qu.:-0.8404 1st Qu.:-0.9226
## Median :-0.0129 Median :-0.0319 Median :-0.2019
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.6280 3rd Qu.: 0.8287 3rd Qu.: 0.8027
## Max. : 2.1140 Max. : 2.9530 Max. : 2.9135
## NA's :4 NA's :11
## StratificationIndex_s TemperatureMeanSurface_s Salinity_s
## Min. :-2.79796 Min. :-2.24518 Min. :-2.5743
## 1st Qu.:-0.67937 1st Qu.:-0.69775 1st Qu.:-0.6719
## Median : 0.03289 Median : 0.01296 Median : 0.1011
## Mean : 0.00000 Mean : 0.00000 Mean : 0.0000
## 3rd Qu.: 0.54888 3rd Qu.: 0.48629 3rd Qu.: 0.7354
## Max. : 2.34978 Max. : 2.88881 Max. : 1.8556
##
## Chlorophyll_s C_finmarchicus_s GulfStreamDisplacement_5YrMean_s
## Min. :-1.0828 Min. :-1.74995 Min. :-2.555018
## 1st Qu.:-0.6039 1st Qu.:-0.72803 1st Qu.:-0.305469
## Median :-0.3175 Median :-0.05428 Median : 0.004623
## Mean : 0.0000 Mean : 0.00000 Mean : 0.000000
## 3rd Qu.: 0.1364 3rd Qu.: 0.92255 3rd Qu.: 0.472521
## Max. : 3.0677 Max. : 1.54505 Max. : 1.839244
## NA's :29 NA's :29 NA's :18
## ShelfSlopeFrontDisplacement_5YrMean_s Pseudocalanus_s Copepods_s
## Min. :-2.37146 Min. :-2.0399 Min. :-1.8329
## 1st Qu.:-0.62799 1st Qu.:-0.5145 1st Qu.:-0.8034
## Median :-0.04719 Median : 0.2924 Median : 0.1090
## Mean : 0.00000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.92939 3rd Qu.: 0.6818 3rd Qu.: 0.8143
## Max. : 1.76814 Max. : 1.3275 Max. : 1.3634
## NA's :18 NA's :29 NA's :29
## NonCopepods_s ZooplanktonBiomass_s BloomInitiation_doy_s
## Min. :-1.43312 Min. :-1.6417 Min. :-2.2705
## 1st Qu.:-0.77755 1st Qu.:-0.5885 1st Qu.:-0.6587
## Median :-0.05686 Median :-0.2043 Median : 0.2919
## Mean : 0.00000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.99571 3rd Qu.: 0.6645 3rd Qu.: 0.6760
## Max. : 1.40352 Max. : 1.9535 Max. : 1.1859
## NA's :29 NA's :29 NA's :28
## BloomDuration_days_s BloomAmplitude_s BloomMagnitude_s
## Min. :-0.97561 Min. :-1.4079 Min. :-1.1259
## 1st Qu.:-0.45575 1st Qu.:-0.6942 1st Qu.:-0.6928
## Median :-0.31465 Median :-0.2564 Median :-0.1596
## Mean : 0.00000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.08267 3rd Qu.: 0.4990 3rd Qu.: 0.5108
## Max. : 3.42089 Max. : 3.0080 Max. : 2.9087
## NA's :28 NA's :28 NA's :28
## ArcticCalanus_s CopepodsWarmOffshore_s CopepodsWarmSppShelf_s
## Min. :-1.78513 Min. :-1.87256 Min. :-1.6183
## 1st Qu.:-0.43742 1st Qu.:-0.60352 1st Qu.:-0.6382
## Median : 0.07805 Median : 0.04414 Median :-0.2613
## Mean : 0.00000 Mean : 0.00000 Mean : 0.0000
## 3rd Qu.: 0.76751 3rd Qu.: 0.42636 3rd Qu.: 0.6464
## Max. : 1.69719 Max. : 1.66898 Max. : 2.1259
## NA's :29 NA's :29 NA's :29Explore correlations between azmp indicators
azmp_suite_corr <- azmp_suite[, -c(1:2)]
chart.Correlation(azmp_suite_corr, histogram=FALSE, pch=16,
method = "pearson",
main = "azmp")
This Table matches the results from the previous figure but provides the full set of results
a <- rcorr(as.matrix(azmp_suite_corr,type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | BottomT_July_s | NAO_s | NAO_5YrMean_s | SST_anomalies_s | AnnualAvgIceVol_s | StratificationIndex_s | TemperatureMeanSurface_s | Salinity_s | Chlorophyll_s | C_finmarchicus_s | GulfStreamDisplacement_5YrMean_s | ShelfSlopeFrontDisplacement_5YrMean_s | Pseudocalanus_s | Copepods_s | NonCopepods_s | ZooplanktonBiomass_s | BloomInitiation_doy_s | BloomDuration_days_s | BloomAmplitude_s | BloomMagnitude_s | ArcticCalanus_s | CopepodsWarmOffshore_s | CopepodsWarmSppShelf_s | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| BottomT_July_s | 1.00 | 0.24 | -0.06 | 0.59 | -0.01 | -0.04 | 0.33 | 0.09 | -0.31 | -0.39 | 0.00 | 0.17 | -0.46 | 0.37 | 0.54 | -0.39 | -0.32 | 0.11 | -0.23 | -0.33 | -0.80 | 0.85 | 0.24 |
| NAO_s | 0.24 | 1.00 | 0.57 | 0.28 | 0.13 | 0.09 | 0.18 | 0.01 | 0.08 | -0.22 | 0.23 | 0.05 | 0.22 | 0.46 | 0.54 | -0.23 | -0.10 | -0.01 | -0.06 | -0.17 | -0.38 | 0.51 | 0.27 |
| NAO_5YrMean_s | -0.06 | 0.57 | 1.00 | -0.30 | 0.25 | 0.03 | -0.15 | -0.02 | 0.03 | 0.04 | 0.66 | 0.41 | 0.45 | 0.35 | 0.29 | 0.21 | -0.04 | 0.18 | 0.24 | 0.40 | 0.04 | -0.09 | 0.50 |
| SST_anomalies_s | 0.59 | 0.28 | -0.30 | 1.00 | -0.44 | 0.45 | 0.78 | -0.18 | -0.41 | -0.49 | -0.14 | -0.30 | -0.60 | 0.31 | 0.49 | -0.30 | -0.45 | 0.09 | -0.31 | -0.43 | -0.71 | 0.76 | 0.22 |
| AnnualAvgIceVol_s | -0.01 | 0.13 | 0.25 | -0.44 | 1.00 | -0.41 | -0.45 | 0.43 | 0.39 | 0.29 | 0.34 | 0.33 | 0.31 | 0.09 | 0.09 | 0.21 | 0.39 | -0.24 | 0.14 | 0.04 | 0.34 | -0.23 | -0.15 |
| StratificationIndex_s | -0.04 | 0.09 | 0.03 | 0.45 | -0.41 | 1.00 | 0.72 | -0.61 | -0.10 | -0.16 | 0.20 | -0.14 | -0.25 | 0.19 | 0.47 | -0.11 | -0.43 | 0.28 | -0.02 | 0.06 | -0.40 | 0.31 | 0.01 |
| TemperatureMeanSurface_s | 0.33 | 0.18 | -0.15 | 0.78 | -0.45 | 0.72 | 1.00 | -0.20 | -0.24 | -0.43 | -0.17 | -0.25 | -0.49 | 0.28 | 0.61 | -0.20 | -0.44 | 0.13 | -0.20 | -0.31 | -0.76 | 0.57 | 0.15 |
| Salinity_s | 0.09 | 0.01 | -0.02 | -0.18 | 0.43 | -0.61 | -0.20 | 1.00 | 0.27 | 0.19 | -0.28 | -0.23 | 0.39 | 0.19 | 0.12 | 0.28 | 0.37 | -0.25 | 0.08 | -0.01 | 0.12 | -0.20 | 0.18 |
| Chlorophyll_s | -0.31 | 0.08 | 0.03 | -0.41 | 0.39 | -0.10 | -0.24 | 0.27 | 1.00 | 0.05 | -0.20 | -0.26 | 0.13 | -0.27 | -0.19 | 0.12 | 0.08 | -0.30 | 0.74 | 0.55 | 0.41 | -0.26 | -0.34 |
| C_finmarchicus_s | -0.39 | -0.22 | 0.04 | -0.49 | 0.29 | -0.16 | -0.43 | 0.19 | 0.05 | 1.00 | 0.08 | -0.10 | 0.68 | 0.31 | -0.32 | 0.59 | 0.41 | -0.20 | 0.14 | 0.24 | 0.56 | -0.34 | 0.12 |
| GulfStreamDisplacement_5YrMean_s | 0.00 | 0.23 | 0.66 | -0.14 | 0.34 | 0.20 | -0.17 | -0.28 | -0.20 | 0.08 | 1.00 | 0.63 | 0.61 | 0.69 | 0.62 | 0.60 | 0.11 | -0.10 | -0.25 | -0.30 | -0.43 | 0.04 | 0.90 |
| ShelfSlopeFrontDisplacement_5YrMean_s | 0.17 | 0.05 | 0.41 | -0.30 | 0.33 | -0.14 | -0.25 | -0.23 | -0.26 | -0.10 | 0.63 | 1.00 | 0.43 | 0.46 | 0.45 | 0.27 | -0.10 | 0.11 | -0.41 | -0.42 | -0.40 | -0.11 | 0.72 |
| Pseudocalanus_s | -0.46 | 0.22 | 0.45 | -0.60 | 0.31 | -0.25 | -0.49 | 0.39 | 0.13 | 0.68 | 0.61 | 0.43 | 1.00 | 0.39 | -0.05 | 0.57 | 0.63 | -0.40 | 0.14 | 0.16 | 0.36 | -0.40 | 0.27 |
| Copepods_s | 0.37 | 0.46 | 0.35 | 0.31 | 0.09 | 0.19 | 0.28 | 0.19 | -0.27 | 0.31 | 0.69 | 0.46 | 0.39 | 1.00 | 0.70 | 0.50 | -0.17 | 0.09 | -0.15 | -0.05 | -0.23 | 0.43 | 0.81 |
| NonCopepods_s | 0.54 | 0.54 | 0.29 | 0.49 | 0.09 | 0.47 | 0.61 | 0.12 | -0.19 | -0.32 | 0.62 | 0.45 | -0.05 | 0.70 | 1.00 | 0.18 | -0.32 | 0.24 | -0.15 | -0.15 | -0.52 | 0.46 | 0.60 |
| ZooplanktonBiomass_s | -0.39 | -0.23 | 0.21 | -0.30 | 0.21 | -0.11 | -0.20 | 0.28 | 0.12 | 0.59 | 0.60 | 0.27 | 0.57 | 0.50 | 0.18 | 1.00 | 0.35 | -0.22 | 0.19 | 0.23 | 0.39 | -0.38 | 0.49 |
| BloomInitiation_doy_s | -0.32 | -0.10 | -0.04 | -0.45 | 0.39 | -0.43 | -0.44 | 0.37 | 0.08 | 0.41 | 0.11 | -0.10 | 0.63 | -0.17 | -0.32 | 0.35 | 1.00 | -0.64 | 0.09 | -0.09 | 0.41 | -0.65 | -0.18 |
| BloomDuration_days_s | 0.11 | -0.01 | 0.18 | 0.09 | -0.24 | 0.28 | 0.13 | -0.25 | -0.30 | -0.20 | -0.10 | 0.11 | -0.40 | 0.09 | 0.24 | -0.22 | -0.64 | 1.00 | -0.46 | -0.11 | -0.30 | 0.42 | 0.25 |
| BloomAmplitude_s | -0.23 | -0.06 | 0.24 | -0.31 | 0.14 | -0.02 | -0.20 | 0.08 | 0.74 | 0.14 | -0.25 | -0.41 | 0.14 | -0.15 | -0.15 | 0.19 | 0.09 | -0.46 | 1.00 | 0.86 | 0.59 | -0.38 | -0.26 |
| BloomMagnitude_s | -0.33 | -0.17 | 0.40 | -0.43 | 0.04 | 0.06 | -0.31 | -0.01 | 0.55 | 0.24 | -0.30 | -0.42 | 0.16 | -0.05 | -0.15 | 0.23 | -0.09 | -0.11 | 0.86 | 1.00 | 0.63 | -0.29 | -0.17 |
| ArcticCalanus_s | -0.80 | -0.38 | 0.04 | -0.71 | 0.34 | -0.40 | -0.76 | 0.12 | 0.41 | 0.56 | -0.43 | -0.40 | 0.36 | -0.23 | -0.52 | 0.39 | 0.41 | -0.30 | 0.59 | 0.63 | 1.00 | -0.67 | -0.28 |
| CopepodsWarmOffshore_s | 0.85 | 0.51 | -0.09 | 0.76 | -0.23 | 0.31 | 0.57 | -0.20 | -0.26 | -0.34 | 0.04 | -0.11 | -0.40 | 0.43 | 0.46 | -0.38 | -0.65 | 0.42 | -0.38 | -0.29 | -0.67 | 1.00 | 0.28 |
| CopepodsWarmSppShelf_s | 0.24 | 0.27 | 0.50 | 0.22 | -0.15 | 0.01 | 0.15 | 0.18 | -0.34 | 0.12 | 0.90 | 0.72 | 0.27 | 0.81 | 0.60 | 0.49 | -0.18 | 0.25 | -0.26 | -0.17 | -0.28 | 0.28 | 1.00 |
Data from multi-species indicators
Data below is in: Bundy A, Gomez C, Cook A. In preparation. Indicator Selection Guidance Framework. Can. Tech. Rep. Fish. Aquat. Sci.
Note that indicators derived from commercial fisheries landings are labelled as “.L”.
MultiSppIndi <- read.csv("data/fish&inverts/nafo4Xsetq_filtered&interpolated_Patch_s.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
MultiSppIndi_Suite <- MultiSppIndi[,c('YEAR', "ID", "MargalefRichness_s","Heips_s","LargeFishIndicator_s","BTGZoopiscivore_s","BTGPiscivore_s","Biomass_s","BiomassSkates_s","BiomassFlatfish_s",'MeanLengthAbundance_s',"MeanTrophicLevel_s","BiomassGadoids_s","CommunityCondition_s","CCMediumBenthivore_s", "CCPiscivore_s","CCZoopiscivore_s","CCLargeBenthivore_s","MeanLifespan_s", "Intrinsicvulnerabilityindex.L_s", "InverseCVBiomass_s", 'MeanTrophicLevel.L_s', "MarineTrophicIndex.L_s",'DiversityTargetSpp.L_s', 'FishingPressure.L_s', 'FPClupeids.L_s', 'Landings.L_s', 'LSkates.L_s', 'LFlatfish.L_s','LLargePelagic.L_s')]
nafosetq <- read.csv("data/fish&inverts/nafosetq.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
inverts <- nafosetq[,c('YEAR', 'ID', 'BiomassInvertebrates_s', 'BiomassTL2_s')]
inverts_4X <- inverts[inverts$YEAR %in% c(1999:2016) & inverts$ID %in% c("4X"),]Merge the indicators patched and interpolated with invertebrate-based indicators that have a shorter-time series
MultiSpp <- left_join(MultiSppIndi_Suite,inverts_4X, by=c('YEAR', 'ID'))
summary(MultiSpp)## YEAR ID MargalefRichness_s Heips_s
## Min. :1970 Length:46 Min. :-1.0115 Min. :-1.3875
## 1st Qu.:1981 Class :character 1st Qu.:-0.6943 1st Qu.:-0.8165
## Median :1992 Mode :character Median :-0.4522 Median :-0.2379
## Mean :1992 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.:2004 3rd Qu.: 0.2763 3rd Qu.: 0.6800
## Max. :2015 Max. : 2.2516 Max. : 2.2938
##
## LargeFishIndicator_s BTGZoopiscivore_s BTGPiscivore_s
## Min. :-1.3459 Min. :-1.0896 Min. :-1.4663
## 1st Qu.:-0.7490 1st Qu.:-0.6937 1st Qu.:-0.7904
## Median :-0.2225 Median :-0.2020 Median :-0.1566
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.6491 3rd Qu.: 0.3882 3rd Qu.: 0.4519
## Max. : 2.7368 Max. : 3.6182 Max. : 2.8846
##
## Biomass_s BiomassSkates_s BiomassFlatfish_s
## Min. :-1.5753 Min. :-1.1525 Min. :-1.79712
## 1st Qu.:-0.7375 1st Qu.:-0.7058 1st Qu.:-0.56020
## Median :-0.3192 Median :-0.3391 Median :-0.06608
## Mean : 0.0000 Mean : 0.0000 Mean : 0.00000
## 3rd Qu.: 0.4919 3rd Qu.: 0.2529 3rd Qu.: 0.48134
## Max. : 2.4398 Max. : 3.0811 Max. : 4.34715
##
## MeanLengthAbundance_s MeanTrophicLevel_s BiomassGadoids_s
## Min. :-1.6550 Min. :-2.53000 Min. :-1.1283
## 1st Qu.:-0.8949 1st Qu.:-0.42807 1st Qu.:-0.5877
## Median :-0.1570 Median :-0.07689 Median :-0.2530
## Mean : 0.0000 Mean : 0.00000 Mean : 0.0000
## 3rd Qu.: 0.5831 3rd Qu.: 0.61217 3rd Qu.: 0.3881
## Max. : 2.7343 Max. : 2.22196 Max. : 4.3559
##
## CommunityCondition_s CCMediumBenthivore_s CCPiscivore_s
## Min. :-2.2765 Min. :-2.66356 Min. :-1.85112
## 1st Qu.:-0.5490 1st Qu.:-0.50280 1st Qu.:-0.66749
## Median : 0.1562 Median : 0.08642 Median :-0.06179
## Mean : 0.0000 Mean : 0.00000 Mean : 0.00000
## 3rd Qu.: 0.5209 3rd Qu.: 0.58311 3rd Qu.: 0.74109
## Max. : 2.7943 Max. : 2.50117 Max. : 2.01837
##
## CCZoopiscivore_s CCLargeBenthivore_s MeanLifespan_s
## Min. :-2.0268 Min. :-2.1480 Min. :-1.68778
## 1st Qu.:-0.7831 1st Qu.:-0.7917 1st Qu.:-0.88525
## Median : 0.1004 Median : 0.1518 Median : 0.09522
## Mean : 0.0000 Mean : 0.0000 Mean : 0.00000
## 3rd Qu.: 0.7426 3rd Qu.: 0.6990 3rd Qu.: 0.62016
## Max. : 1.5256 Max. : 1.9741 Max. : 2.62630
##
## Intrinsicvulnerabilityindex.L_s InverseCVBiomass_s MeanTrophicLevel.L_s
## Min. :-2.6609 Min. :-1.3515 Min. :-1.8699
## 1st Qu.:-0.6899 1st Qu.:-0.7150 1st Qu.:-0.9063
## Median : 0.3178 Median :-0.1656 Median : 0.2547
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.8138 3rd Qu.: 0.4526 3rd Qu.: 0.8983
## Max. : 1.5512 Max. : 2.9640 Max. : 1.5923
##
## MarineTrophicIndex.L_s DiversityTargetSpp.L_s FishingPressure.L_s
## Min. :-1.65225 Min. :-1.7510 Min. :-2.03104
## 1st Qu.:-0.76349 1st Qu.:-0.9061 1st Qu.:-0.74969
## Median :-0.03629 Median : 0.2908 Median :-0.04239
## Mean : 0.00000 Mean : 0.0000 Mean : 0.00000
## 3rd Qu.: 0.59628 3rd Qu.: 0.9245 3rd Qu.: 0.65648
## Max. : 2.64684 Max. : 1.3470 Max. : 2.56651
##
## FPClupeids.L_s Landings.L_s LSkates.L_s LFlatfish.L_s
## Min. :-1.5738 Min. :-1.6614 Min. :-0.3648 Min. :-1.2128
## 1st Qu.:-0.7833 1st Qu.:-0.8609 1st Qu.:-0.3158 1st Qu.:-0.9529
## Median :-0.2502 Median : 0.1368 Median :-0.2808 Median :-0.2824
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.6221 3rd Qu.: 0.7181 3rd Qu.:-0.1584 3rd Qu.: 0.8546
## Max. : 2.4614 Max. : 1.8037 Max. : 5.9392 Max. : 2.1518
##
## LLargePelagic.L_s BiomassInvertebrates_s BiomassTL2_s
## Min. :-1.3529 Min. :-1.44958 Min. :-0.42033
## 1st Qu.:-0.4427 1st Qu.:-0.85103 1st Qu.:-0.04473
## Median :-0.1275 Median :-0.08607 Median : 0.12532
## Mean : 0.0000 Mean : 0.00000 Mean : 0.30703
## 3rd Qu.: 0.2203 3rd Qu.: 0.67432 3rd Qu.: 0.61302
## Max. : 5.6395 Max. : 2.09293 Max. : 1.38104
## NA's :29 NA's :29Explore correlations between multi-species indicators
MultiSpp_corr <- MultiSpp[, -c(1:2)]
chart.Correlation(MultiSpp_corr, histogram=FALSE, pch=16,
method = "pearson",
main = "multi-species indicators")
This Table matches the results from the previous figure but provides the full set of results
a <- rcorr(as.matrix(MultiSpp_corr,type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | MargalefRichness_s | Heips_s | LargeFishIndicator_s | BTGZoopiscivore_s | BTGPiscivore_s | Biomass_s | BiomassSkates_s | BiomassFlatfish_s | MeanLengthAbundance_s | MeanTrophicLevel_s | BiomassGadoids_s | CommunityCondition_s | CCMediumBenthivore_s | CCPiscivore_s | CCZoopiscivore_s | CCLargeBenthivore_s | MeanLifespan_s | Intrinsicvulnerabilityindex.L_s | InverseCVBiomass_s | MeanTrophicLevel.L_s | MarineTrophicIndex.L_s | DiversityTargetSpp.L_s | FishingPressure.L_s | FPClupeids.L_s | Landings.L_s | LSkates.L_s | LFlatfish.L_s | LLargePelagic.L_s | BiomassInvertebrates_s | BiomassTL2_s | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| MargalefRichness_s | 1.00 | 0.18 | 0.23 | 0.73 | -0.08 | -0.15 | 0.30 | 0.61 | -0.58 | 0.05 | 0.27 | -0.17 | 0.25 | -0.23 | -0.03 | -0.64 | 0.59 | 0.64 | -0.56 | -0.83 | -0.67 | 0.61 | -0.42 | 0.02 | -0.83 | -0.19 | -0.58 | 0.00 | 0.58 | 0.58 |
| Heips_s | 0.18 | 1.00 | 0.52 | 0.02 | 0.31 | -0.53 | -0.28 | 0.30 | -0.19 | 0.25 | -0.14 | -0.50 | -0.10 | -0.20 | -0.40 | -0.40 | 0.40 | 0.41 | 0.06 | -0.41 | -0.06 | 0.68 | 0.26 | 0.73 | -0.32 | -0.26 | -0.30 | 0.26 | -0.58 | -0.25 |
| LargeFishIndicator_s | 0.23 | 0.52 | 1.00 | -0.14 | 0.56 | -0.33 | -0.03 | 0.48 | 0.01 | 0.38 | 0.07 | -0.48 | -0.06 | -0.36 | -0.33 | -0.07 | 0.23 | 0.26 | 0.07 | -0.34 | -0.15 | 0.54 | 0.16 | 0.55 | -0.29 | -0.21 | -0.23 | -0.01 | -0.54 | -0.34 |
| BTGZoopiscivore_s | 0.73 | 0.02 | -0.14 | 1.00 | -0.19 | 0.17 | 0.34 | 0.44 | -0.53 | 0.01 | 0.32 | 0.00 | 0.24 | -0.13 | 0.16 | -0.54 | 0.59 | 0.37 | -0.56 | -0.49 | -0.36 | 0.37 | -0.58 | -0.23 | -0.63 | -0.11 | -0.40 | -0.11 | 0.49 | 0.64 |
| BTGPiscivore_s | -0.08 | 0.31 | 0.56 | -0.19 | 1.00 | -0.03 | -0.28 | 0.03 | 0.10 | 0.71 | 0.02 | -0.12 | -0.25 | -0.19 | -0.12 | 0.12 | 0.11 | 0.25 | -0.02 | -0.07 | 0.21 | 0.28 | -0.03 | 0.24 | 0.00 | -0.20 | 0.07 | -0.01 | -0.51 | -0.30 |
| Biomass_s | -0.15 | -0.53 | -0.33 | 0.17 | -0.03 | 1.00 | 0.17 | 0.02 | 0.19 | -0.30 | 0.32 | 0.18 | -0.14 | 0.27 | 0.04 | 0.23 | -0.15 | -0.24 | -0.07 | 0.45 | 0.31 | -0.49 | -0.68 | -0.65 | 0.24 | 0.13 | 0.38 | -0.10 | 0.12 | 0.49 |
| BiomassSkates_s | 0.30 | -0.28 | -0.03 | 0.34 | -0.28 | 0.17 | 1.00 | 0.15 | 0.05 | -0.16 | 0.27 | 0.15 | 0.26 | -0.14 | 0.23 | -0.25 | 0.12 | -0.18 | -0.12 | -0.02 | -0.42 | -0.10 | -0.28 | -0.14 | -0.16 | 0.44 | -0.31 | -0.01 | 0.28 | 0.16 |
| BiomassFlatfish_s | 0.61 | 0.30 | 0.48 | 0.44 | 0.03 | 0.02 | 0.15 | 1.00 | -0.26 | -0.07 | 0.18 | -0.35 | 0.13 | -0.07 | -0.21 | -0.39 | 0.50 | 0.42 | -0.37 | -0.53 | -0.33 | 0.51 | -0.26 | 0.16 | -0.46 | -0.28 | -0.25 | 0.02 | -0.02 | 0.34 |
| MeanLengthAbundance_s | -0.58 | -0.19 | 0.01 | -0.53 | 0.10 | 0.19 | 0.05 | -0.26 | 1.00 | -0.07 | 0.07 | 0.01 | -0.20 | 0.31 | 0.03 | 0.55 | -0.55 | -0.45 | 0.46 | 0.58 | 0.38 | -0.50 | 0.18 | -0.12 | 0.56 | 0.32 | 0.38 | -0.11 | -0.33 | -0.41 |
| MeanTrophicLevel_s | 0.05 | 0.25 | 0.38 | 0.01 | 0.71 | -0.30 | -0.16 | -0.07 | -0.07 | 1.00 | -0.01 | -0.21 | -0.20 | -0.35 | -0.13 | 0.02 | -0.02 | 0.28 | -0.23 | -0.20 | 0.09 | 0.30 | 0.21 | 0.25 | -0.03 | -0.04 | -0.11 | -0.24 | -0.26 | -0.47 |
| BiomassGadoids_s | 0.27 | -0.14 | 0.07 | 0.32 | 0.02 | 0.32 | 0.27 | 0.18 | 0.07 | -0.01 | 1.00 | -0.11 | 0.19 | -0.05 | -0.25 | 0.05 | -0.28 | 0.14 | 0.01 | -0.17 | -0.14 | 0.00 | -0.42 | -0.31 | -0.19 | -0.12 | 0.14 | -0.14 | 0.41 | 0.02 |
| CommunityCondition_s | -0.17 | -0.50 | -0.48 | 0.00 | -0.12 | 0.18 | 0.15 | -0.35 | 0.01 | -0.21 | -0.11 | 1.00 | 0.37 | 0.04 | 0.73 | 0.06 | 0.02 | -0.32 | 0.06 | 0.30 | -0.09 | -0.42 | -0.19 | -0.44 | 0.10 | 0.02 | 0.07 | 0.12 | 0.25 | 0.35 |
| CCMediumBenthivore_s | 0.25 | -0.10 | -0.06 | 0.24 | -0.25 | -0.14 | 0.26 | 0.13 | -0.20 | -0.20 | 0.19 | 0.37 | 1.00 | -0.31 | 0.38 | -0.14 | 0.14 | 0.02 | 0.07 | -0.21 | -0.39 | 0.17 | -0.05 | -0.15 | -0.31 | -0.07 | -0.23 | -0.09 | 0.07 | 0.09 |
| CCPiscivore_s | -0.23 | -0.20 | -0.36 | -0.13 | -0.19 | 0.27 | -0.14 | -0.07 | 0.31 | -0.35 | -0.05 | 0.04 | -0.31 | 1.00 | -0.08 | 0.23 | -0.26 | -0.02 | 0.17 | 0.31 | 0.44 | -0.37 | 0.01 | -0.23 | 0.40 | 0.01 | 0.57 | 0.14 | 0.49 | 0.63 |
| CCZoopiscivore_s | -0.03 | -0.40 | -0.33 | 0.16 | -0.12 | 0.04 | 0.23 | -0.21 | 0.03 | -0.13 | -0.25 | 0.73 | 0.38 | -0.08 | 1.00 | 0.02 | 0.25 | -0.31 | -0.13 | 0.18 | -0.19 | -0.26 | -0.16 | -0.34 | -0.04 | 0.15 | -0.22 | -0.07 | 0.13 | 0.34 |
| CCLargeBenthivore_s | -0.64 | -0.40 | -0.07 | -0.54 | 0.12 | 0.23 | -0.25 | -0.39 | 0.55 | 0.02 | 0.05 | 0.06 | -0.14 | 0.23 | 0.02 | 1.00 | -0.60 | -0.37 | 0.35 | 0.54 | 0.59 | -0.57 | 0.22 | -0.25 | 0.60 | 0.12 | 0.59 | -0.40 | 0.00 | -0.30 |
| MeanLifespan_s | 0.59 | 0.40 | 0.23 | 0.59 | 0.11 | -0.15 | 0.12 | 0.50 | -0.55 | -0.02 | -0.28 | 0.02 | 0.14 | -0.26 | 0.25 | -0.60 | 1.00 | 0.37 | -0.40 | -0.52 | -0.37 | 0.60 | -0.31 | 0.29 | -0.64 | -0.22 | -0.56 | 0.24 | -0.01 | 0.58 |
| Intrinsicvulnerabilityindex.L_s | 0.64 | 0.41 | 0.26 | 0.37 | 0.25 | -0.24 | -0.18 | 0.42 | -0.45 | 0.28 | 0.14 | -0.32 | 0.02 | -0.02 | -0.31 | -0.37 | 0.37 | 1.00 | -0.37 | -0.77 | -0.29 | 0.74 | -0.08 | 0.28 | -0.52 | -0.40 | -0.33 | 0.08 | 0.57 | 0.20 |
| InverseCVBiomass_s | -0.56 | 0.06 | 0.07 | -0.56 | -0.02 | -0.07 | -0.12 | -0.37 | 0.46 | -0.23 | 0.01 | 0.06 | 0.07 | 0.17 | -0.13 | 0.35 | -0.40 | -0.37 | 1.00 | 0.41 | 0.27 | -0.29 | 0.29 | 0.10 | 0.35 | -0.13 | 0.40 | 0.21 | -0.40 | -0.78 |
| MeanTrophicLevel.L_s | -0.83 | -0.41 | -0.34 | -0.49 | -0.07 | 0.45 | -0.02 | -0.53 | 0.58 | -0.20 | -0.17 | 0.30 | -0.21 | 0.31 | 0.18 | 0.54 | -0.52 | -0.77 | 0.41 | 1.00 | 0.61 | -0.82 | 0.07 | -0.34 | 0.73 | 0.35 | 0.56 | -0.04 | -0.76 | 0.10 |
| MarineTrophicIndex.L_s | -0.67 | -0.06 | -0.15 | -0.36 | 0.21 | 0.31 | -0.42 | -0.33 | 0.38 | 0.09 | -0.14 | -0.09 | -0.39 | 0.44 | -0.19 | 0.59 | -0.37 | -0.29 | 0.27 | 0.61 | 1.00 | -0.40 | 0.14 | -0.15 | 0.64 | 0.15 | 0.70 | 0.00 | -0.52 | 0.13 |
| DiversityTargetSpp.L_s | 0.61 | 0.68 | 0.54 | 0.37 | 0.28 | -0.49 | -0.10 | 0.51 | -0.50 | 0.30 | 0.00 | -0.42 | 0.17 | -0.37 | -0.26 | -0.57 | 0.60 | 0.74 | -0.29 | -0.82 | -0.40 | 1.00 | 0.08 | 0.61 | -0.64 | -0.32 | -0.60 | 0.19 | -0.40 | -0.39 |
| FishingPressure.L_s | -0.42 | 0.26 | 0.16 | -0.58 | -0.03 | -0.68 | -0.28 | -0.26 | 0.18 | 0.21 | -0.42 | -0.19 | -0.05 | 0.01 | -0.16 | 0.22 | -0.31 | -0.08 | 0.29 | 0.07 | 0.14 | 0.08 | 1.00 | 0.64 | 0.48 | 0.08 | 0.06 | 0.07 | -0.35 | -0.61 |
| FPClupeids.L_s | 0.02 | 0.73 | 0.55 | -0.23 | 0.24 | -0.65 | -0.14 | 0.16 | -0.12 | 0.25 | -0.31 | -0.44 | -0.15 | -0.23 | -0.34 | -0.25 | 0.29 | 0.28 | 0.10 | -0.34 | -0.15 | 0.61 | 0.64 | 1.00 | -0.04 | -0.12 | -0.35 | 0.34 | -0.54 | -0.60 |
| Landings.L_s | -0.83 | -0.32 | -0.29 | -0.63 | 0.00 | 0.24 | -0.16 | -0.46 | 0.56 | -0.03 | -0.19 | 0.10 | -0.31 | 0.40 | -0.04 | 0.60 | -0.64 | -0.52 | 0.35 | 0.73 | 0.64 | -0.64 | 0.48 | -0.04 | 1.00 | 0.32 | 0.62 | 0.00 | -0.59 | -0.58 |
| LSkates.L_s | -0.19 | -0.26 | -0.21 | -0.11 | -0.20 | 0.13 | 0.44 | -0.28 | 0.32 | -0.04 | -0.12 | 0.02 | -0.07 | 0.01 | 0.15 | 0.12 | -0.22 | -0.40 | -0.13 | 0.35 | 0.15 | -0.32 | 0.08 | -0.12 | 0.32 | 1.00 | -0.10 | -0.06 | 0.21 | 0.28 |
| LFlatfish.L_s | -0.58 | -0.30 | -0.23 | -0.40 | 0.07 | 0.38 | -0.31 | -0.25 | 0.38 | -0.11 | 0.14 | 0.07 | -0.23 | 0.57 | -0.22 | 0.59 | -0.56 | -0.33 | 0.40 | 0.56 | 0.70 | -0.60 | 0.06 | -0.35 | 0.62 | -0.10 | 1.00 | -0.07 | 0.60 | -0.10 |
| LLargePelagic.L_s | 0.00 | 0.26 | -0.01 | -0.11 | -0.01 | -0.10 | -0.01 | 0.02 | -0.11 | -0.24 | -0.14 | 0.12 | -0.09 | 0.14 | -0.07 | -0.40 | 0.24 | 0.08 | 0.21 | -0.04 | 0.00 | 0.19 | 0.07 | 0.34 | 0.00 | -0.06 | -0.07 | 1.00 | 0.19 | 0.26 |
| BiomassInvertebrates_s | 0.58 | -0.58 | -0.54 | 0.49 | -0.51 | 0.12 | 0.28 | -0.02 | -0.33 | -0.26 | 0.41 | 0.25 | 0.07 | 0.49 | 0.13 | 0.00 | -0.01 | 0.57 | -0.40 | -0.76 | -0.52 | -0.40 | -0.35 | -0.54 | -0.59 | 0.21 | 0.60 | 0.19 | 1.00 | 0.08 |
| BiomassTL2_s | 0.58 | -0.25 | -0.34 | 0.64 | -0.30 | 0.49 | 0.16 | 0.34 | -0.41 | -0.47 | 0.02 | 0.35 | 0.09 | 0.63 | 0.34 | -0.30 | 0.58 | 0.20 | -0.78 | 0.10 | 0.13 | -0.39 | -0.61 | -0.60 | -0.58 | 0.28 | -0.10 | 0.26 | 0.08 | 1.00 |
Sable grey seal population numbers
Do we want to include this? if so, we should contact Nell. Below a message from her:
“The assessment is complete but the SAR not yet approved by minister, so this is for internal use for the moment. The yellow highlighted estimate for total pop is adjusted for the a sex ratio of 0.69:1, as the assessment model assumes 1:1 and we know that is not true, based of survival estimates for males and females. Sable accounts for 95% of grey seals on Scotian Shelf. Total pup production on Sable in 2016 was estimated to be 83,600. There is small and rapidly expanding breeding colony on some small islands in southwest Nova Scotia (NAFO 4X). Total pup production in 2016 on SW NS was estimated to be 2,100 pups. The breeding colonies in Gulf of St. Lawrence and Hay Island (just off Cape Breton) are almost stable. In 2016, the US also surveyed all its breeding colonies in Gulf of Maine, and estimate about 6,000 pups born”. Nell.denHeyer@dfo-mpo.gc.ca
seals <- read.csv("data/seals/seals.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
seals$NumberGreySealPups <- as.numeric(seals$NumberGreySealPups)
seals$NumberGreySealPups_Model <- as.numeric(seals$NumberGreySealPups_Model)
seals$ID <- "4X" # added this just so it matches the other data frames but this estimate is for the Scotian Shelf
seals <- seals[,c("YEAR", "ID","NumberGreySealPups", "NumberGreySealPups_Model","GreySealPopulation_Model")]
seals_s <- stdizeFrame(seals)
seals_indi <- seals_s[,c("YEAR", "ID", "GreySealPopulation_Model_s")]
head(seals_indi)## YEAR ID GreySealPopulation_Model_s
## 1 1960 4X -0.8330146
## 2 1961 4X -0.8313029
## 3 1962 4X -0.8295445
## 4 1963 4X -0.8275312
## 5 1964 4X -0.8251392
## 6 1965 4X -0.8223345Explore correlations between seal indicators; given high correlations we only selected one seal index for further analysis:
seals_s_corr <- seals_s[, -c(1:2)]
chart.Correlation(seals_s_corr, histogram=FALSE, pch=16,
method = "pearson",
main = "seals")
Table below matches the results from the previous figure but provides the full set of results:
a <- rcorr(as.matrix(seals_s_corr,type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | NumberGreySealPups | NumberGreySealPups_Model | GreySealPopulation_Model | NumberGreySealPups_s | NumberGreySealPups_Model_s | GreySealPopulation_Model_s | |
|---|---|---|---|---|---|---|
| NumberGreySealPups | 1 | 1 | 1 | 1 | 1 | 1 |
| NumberGreySealPups_Model | 1 | 1 | 1 | 1 | 1 | 1 |
| GreySealPopulation_Model | 1 | 1 | 1 | 1 | 1 | 1 |
| NumberGreySealPups_s | 1 | 1 | 1 | 1 | 1 | 1 |
| NumberGreySealPups_Model_s | 1 | 1 | 1 | 1 | 1 | 1 |
| GreySealPopulation_Model_s | 1 | 1 | 1 | 1 | 1 | 1 |
Stock Indices from Maritimes Region
Below we provide a synthesis of different indices derived from the following stock assessments as reccommneded by Kirsten Clark:
- 4X5Yb Cod: Irene Andrushchenko
- 4X5Yb Haddock: Monica Finley
- 4Xopqrs5 Pollock: Ryan Martin
- 4VWX5Z Cusk: Don Clark
- RV Survey: Don Clark
- 3NOPS4VWX5ZC Halibut: Nell den Heyer and Brendan Wringe
- 4VWX Silver Hake: Mark Showell until January, then Irene Andrushchenko
Indices are derived from different sources: - Commercial fisheries landings “.L” - Halibut survey are labelled as “.HS” - DFO’s Summer RV survey “.RV” - Model VPA “.VPA” - US survey data “.NMFS”: Note taht Ryan Martin adviced that we could use US survey data for this exercise and for discussion at the update meetings, however, beyond that we would require permission from the US to utilize their data.
Summer Research Vessel survey biomass obtained from D. Clark
For SOTO, Don Clark provided biomass indices for several species from the summer Research Vessel survey (10/18/2017). Note that species biomass indices derived from this are labelled as “.RV”.
BiomassSummerRV <- read.csv("data/stocks/RVSurvey/4X summer species.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
BiomassSummerRV_s <- stdizeFrame(BiomassSummerRV)Select species that will be included in analysis (here CG did a preliminary selection based on Table 1 in http://publications.gc.ca/collections/collection_2017/mpo-dfo/Fs70-7-2017-004-eng.pdf
BiomassSummerRV_indi <- BiomassSummerRV_s[,c("YEAR", "ID", "AtlanticCod.RV_s", "Haddock.RV_s", "WhiteHake.RV_s", "SilverHake.RV_s", "Cusk.RV_s", "Pollock.RV_s", "Redfish.RV_s", "Halibut.RV_s", "AmericanPlaice.RV_s", "WitchFlounder.RV_s", "YellowTailFlounder.RV_s", "WinterFlounder.RV_s", "AtlanticWolfish.RV_s", "Monkfish.RV_s", "SmoothSkate.RV_s", "ThornySkate.RV_s", "SpinyDogfish.RV_s")]Explore correlations
BiomassSummerRV_indi_corr <- BiomassSummerRV_indi[, -c(1:2)]
chart.Correlation(BiomassSummerRV_indi_corr, histogram=FALSE, pch=20,
method = "pearson",
main = "Biomass RV Survey Indices")
Table below matches the results from the previous figure but provides the full set of results:
a <- rcorr(as.matrix(BiomassSummerRV_indi_corr, type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | AtlanticCod.RV_s | Haddock.RV_s | WhiteHake.RV_s | SilverHake.RV_s | Cusk.RV_s | Pollock.RV_s | Redfish.RV_s | Halibut.RV_s | AmericanPlaice.RV_s | WitchFlounder.RV_s | YellowTailFlounder.RV_s | WinterFlounder.RV_s | AtlanticWolfish.RV_s | Monkfish.RV_s | SmoothSkate.RV_s | ThornySkate.RV_s | SpinyDogfish.RV_s | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AtlanticCod.RV_s | 1.00 | 0.17 | 0.45 | -0.30 | 0.56 | 0.19 | -0.50 | -0.39 | 0.55 | 0.33 | 0.15 | -0.38 | 0.63 | 0.51 | 0.30 | 0.53 | -0.05 |
| Haddock.RV_s | 0.17 | 1.00 | -0.05 | 0.03 | 0.10 | 0.09 | -0.05 | 0.22 | -0.07 | 0.52 | 0.23 | 0.00 | 0.33 | 0.31 | 0.18 | 0.20 | 0.03 |
| WhiteHake.RV_s | 0.45 | -0.05 | 1.00 | -0.06 | 0.26 | 0.09 | -0.10 | -0.23 | 0.41 | 0.15 | -0.20 | -0.14 | 0.27 | 0.34 | 0.03 | 0.33 | -0.05 |
| SilverHake.RV_s | -0.30 | 0.03 | -0.06 | 1.00 | -0.14 | -0.18 | 0.05 | 0.34 | -0.14 | 0.02 | -0.25 | 0.29 | -0.18 | -0.18 | -0.12 | -0.12 | -0.06 |
| Cusk.RV_s | 0.56 | 0.10 | 0.26 | -0.14 | 1.00 | -0.04 | -0.38 | -0.25 | 0.53 | 0.55 | -0.24 | -0.57 | 0.62 | 0.58 | 0.58 | 0.80 | -0.40 |
| Pollock.RV_s | 0.19 | 0.09 | 0.09 | -0.18 | -0.04 | 1.00 | 0.07 | -0.01 | -0.23 | -0.14 | 0.00 | 0.12 | -0.03 | -0.11 | -0.08 | -0.10 | 0.01 |
| Redfish.RV_s | -0.50 | -0.05 | -0.10 | 0.05 | -0.38 | 0.07 | 1.00 | 0.47 | -0.35 | -0.08 | -0.22 | 0.29 | -0.40 | -0.31 | -0.13 | -0.33 | -0.08 |
| Halibut.RV_s | -0.39 | 0.22 | -0.23 | 0.34 | -0.25 | -0.01 | 0.47 | 1.00 | -0.34 | 0.06 | -0.05 | 0.45 | -0.28 | -0.21 | -0.06 | -0.24 | -0.12 |
| AmericanPlaice.RV_s | 0.55 | -0.07 | 0.41 | -0.14 | 0.53 | -0.23 | -0.35 | -0.34 | 1.00 | 0.32 | 0.01 | -0.44 | 0.40 | 0.36 | 0.21 | 0.43 | -0.12 |
| WitchFlounder.RV_s | 0.33 | 0.52 | 0.15 | 0.02 | 0.55 | -0.14 | -0.08 | 0.06 | 0.32 | 1.00 | -0.08 | -0.33 | 0.58 | 0.56 | 0.44 | 0.66 | -0.20 |
| YellowTailFlounder.RV_s | 0.15 | 0.23 | -0.20 | -0.25 | -0.24 | 0.00 | -0.22 | -0.05 | 0.01 | -0.08 | 1.00 | 0.12 | 0.02 | -0.14 | -0.22 | -0.21 | 0.34 |
| WinterFlounder.RV_s | -0.38 | 0.00 | -0.14 | 0.29 | -0.57 | 0.12 | 0.29 | 0.45 | -0.44 | -0.33 | 0.12 | 1.00 | -0.47 | -0.54 | -0.43 | -0.59 | 0.20 |
| AtlanticWolfish.RV_s | 0.63 | 0.33 | 0.27 | -0.18 | 0.62 | -0.03 | -0.40 | -0.28 | 0.40 | 0.58 | 0.02 | -0.47 | 1.00 | 0.74 | 0.50 | 0.80 | -0.18 |
| Monkfish.RV_s | 0.51 | 0.31 | 0.34 | -0.18 | 0.58 | -0.11 | -0.31 | -0.21 | 0.36 | 0.56 | -0.14 | -0.54 | 0.74 | 1.00 | 0.62 | 0.75 | -0.32 |
| SmoothSkate.RV_s | 0.30 | 0.18 | 0.03 | -0.12 | 0.58 | -0.08 | -0.13 | -0.06 | 0.21 | 0.44 | -0.22 | -0.43 | 0.50 | 0.62 | 1.00 | 0.70 | -0.49 |
| ThornySkate.RV_s | 0.53 | 0.20 | 0.33 | -0.12 | 0.80 | -0.10 | -0.33 | -0.24 | 0.43 | 0.66 | -0.21 | -0.59 | 0.80 | 0.75 | 0.70 | 1.00 | -0.44 |
| SpinyDogfish.RV_s | -0.05 | 0.03 | -0.05 | -0.06 | -0.40 | 0.01 | -0.08 | -0.12 | -0.12 | -0.20 | 0.34 | 0.20 | -0.18 | -0.32 | -0.49 | -0.44 | 1.00 |
Plot the defined subset of indices; upper panel is raw data and lower panels is with loess smoothing:
BiomassSummerRV_indi_melt <- melt(BiomassSummerRV_indi, id=c('YEAR', "ID"))
#grid.arrange(Plot_color(BiomassSummerRV_indi_melt), Plot_color_smooth(BiomassSummerRV_indi_melt), ncol = 1)
Plot_color(BiomassSummerRV_indi_melt)
Plot_color_smooth(BiomassSummerRV_indi_melt)
4X5Yb Haddock: Monica Finley
A full assessment for 4X5Yb Haddock was conducted last year. This year there will be an update. The link to the Haddock SAR document from last year is http://waves-vagues.dfo-mpo.gc.ca/Library/40599954.pdf
We gathered data from the following tables/figures provided by K. Clark (word document) and M. Finley:
- Fig 19 (HaddockConditionWSS.RV, HaddockConditionBoF.RV) Fulton’s condition factor (weight/length3) for 28-55 cm Haddock from the Bay of Fundy and the western Scotian Shelf sampled during the summer survey, 1970-2016.
- Figure 22 4X5Y Haddock 4+ biomass from the ADAPT VPA model formulation (HaddockBiomassAge4+.vpa)
- Tab 1 (HaddocKLandings.L):Reported annual catch (t) of Haddock from NAFO Division 4X5Y
- Tab 7:Summer survey total biomass index (t) for 4X5Y Haddock calculated separately for Bay of Fundy strata (482-495) (HaddockBiomassBoF), western Scotian Shelf strata (470-481) (HaddockBiomassWestern.RV) and both areas combined, 1970-2016 (HaddockBiomassWSS.RV). The average includes data from 1970-2016. A conversion factor of 1.2 has been applied to indices from 1970-1981 to account for vessel and gear changes.
- Tab 8 (HaddockAbund.RV):Summer survey total abundance index at age (000’s) for 4X5Y Haddock calculated separately for Scotian Shelf strata (470-481) and Bay of Fundy strata (482-495) then combined, 1970-2015. A conversion factor of 1.2 has been applied to indices from 1970-1981 to account for vessel and gear changes. Abundance at age data from 1985-2015 was used for assessment modelling.
- Table 13 (HaddockAbund.VPAs):Estimated population abundance at age and ages 4+ biomass from the VPA model formulation of M fixed at 0.2, except 0.3, 0.6, and 0.9 for ages 10-11+ for the three time blocks (2000-2004, 2005-2009, and 2010-2015, respectively) for 4X5Y Haddock. *The abundance at age 1 for 2016 was an assigned value, as the most recent 10 years of geometric mean of recruitment at age 1 (excluding the exceptional strong 2013 year class)
Haddock <- read.csv("data/stocks/4X5Yb Haddock/Assessment of 4X5Y Haddock in 2016.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
Haddock$ID <- "4X"
Haddock_s <- stdizeFrame(Haddock)
Haddock_indi <- Haddock_s[,c("YEAR", "ID", "HaddockBiomassAge4plus.vpa_s", "HaddockConditionWSS.RV_s", "HaddockConditionBoF.RV_s", 'HaddockLandings.L_s','HaddockBiomassBoF.RV_s','HaddockBiomassWestern.RV_s','HaddockBiomassWSS.RV_s','Age1HaddockAbund.RV_s','Age2HaddockAbund.RV_s','Age3HaddockAbund.RV_s','Age4HaddockAbund.RV_s','Age5HaddockAbund.RV_s','Age6HaddockAbund.RV_s','Age7HaddockAbund.RV_s','Age8HaddockAbund.RV_s','Age9HaddockAbund.RV_s','Age10HaddockAbund.RV_s','Age11HaddockAbund.RV_s','Age12HaddockAbund.RV_s','Age13HaddockAbund.RV_s','Age1HaddockAbund.VPA_s','Age2HaddockAbund.VPA_s','Age3HaddockAbund.VPA_s','Age4HaddockAbund.VPA_s','Age5HaddockAbund.VPA_s','Age6HaddockAbund.VPA_s','Age7HaddockAbund.VPA_s','Age8HaddockAbund.VPA_s','Age9HaddockAbund.VPA_s','Age10HaddockAbund.VPA_s','Age11HaddockAbund.VPA_s')]Explore correlations
Haddock_indi_corr <- Haddock_indi[, -c(1:2)]
chart.Correlation(Haddock_indi_corr, histogram=FALSE, pch=20,
method = "pearson",
main = "Haddock Indices")
Table below matches the results from the previous figure but provides the full set of results:
a <- rcorr(as.matrix(Haddock_indi_corr, type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | HaddockBiomassAge4plus.vpa_s | HaddockConditionWSS.RV_s | HaddockConditionBoF.RV_s | HaddockLandings.L_s | HaddockBiomassBoF.RV_s | HaddockBiomassWestern.RV_s | HaddockBiomassWSS.RV_s | Age1HaddockAbund.RV_s | Age2HaddockAbund.RV_s | Age3HaddockAbund.RV_s | Age4HaddockAbund.RV_s | Age5HaddockAbund.RV_s | Age6HaddockAbund.RV_s | Age7HaddockAbund.RV_s | Age8HaddockAbund.RV_s | Age9HaddockAbund.RV_s | Age10HaddockAbund.RV_s | Age11HaddockAbund.RV_s | Age12HaddockAbund.RV_s | Age13HaddockAbund.RV_s | Age1HaddockAbund.VPA_s | Age2HaddockAbund.VPA_s | Age3HaddockAbund.VPA_s | Age4HaddockAbund.VPA_s | Age5HaddockAbund.VPA_s | Age6HaddockAbund.VPA_s | Age7HaddockAbund.VPA_s | Age8HaddockAbund.VPA_s | Age9HaddockAbund.VPA_s | Age10HaddockAbund.VPA_s | Age11HaddockAbund.VPA_s | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| HaddockBiomassAge4plus.vpa_s | 1.00 | -0.02 | -0.15 | 0.36 | 0.05 | 0.50 | 0.39 | -0.34 | -0.19 | 0.10 | 0.55 | 0.58 | 0.54 | 0.49 | 0.42 | 0.42 | 0.28 | 0.27 | 0.01 | -0.10 | -0.31 | -0.22 | 0.07 | 0.61 | 0.74 | 0.69 | 0.62 | 0.52 | 0.44 | 0.37 | 0.28 |
| HaddockConditionWSS.RV_s | -0.02 | 1.00 | 0.84 | 0.60 | -0.02 | 0.18 | 0.14 | -0.24 | -0.17 | 0.00 | -0.23 | -0.08 | -0.05 | -0.18 | -0.37 | -0.28 | -0.22 | -0.35 | -0.26 | -0.32 | -0.26 | -0.36 | -0.45 | -0.31 | -0.15 | -0.11 | -0.11 | -0.11 | -0.14 | -0.21 | -0.29 |
| HaddockConditionBoF.RV_s | -0.15 | 0.84 | 1.00 | 0.78 | 0.12 | 0.13 | 0.16 | -0.20 | -0.20 | 0.04 | -0.14 | -0.13 | -0.11 | -0.28 | -0.41 | -0.42 | -0.39 | -0.52 | -0.34 | -0.37 | -0.27 | -0.36 | -0.36 | -0.28 | -0.32 | -0.24 | -0.23 | -0.25 | -0.27 | -0.43 | -0.52 |
| HaddockLandings.L_s | 0.36 | 0.60 | 0.78 | 1.00 | 0.40 | 0.26 | 0.38 | -0.16 | -0.04 | 0.11 | 0.05 | 0.12 | 0.04 | -0.12 | -0.28 | -0.38 | -0.35 | -0.38 | -0.24 | -0.23 | -0.39 | -0.34 | -0.06 | 0.15 | 0.22 | 0.11 | -0.04 | -0.18 | -0.26 | -0.29 | -0.42 |
| HaddockBiomassBoF.RV_s | 0.05 | -0.02 | 0.12 | 0.40 | 1.00 | 0.17 | 0.55 | 0.09 | 0.45 | 0.34 | 0.39 | 0.31 | 0.00 | 0.05 | -0.15 | -0.15 | -0.17 | -0.20 | -0.31 | -0.11 | -0.02 | 0.31 | 0.42 | 0.35 | 0.09 | -0.14 | -0.29 | -0.21 | -0.16 | -0.18 | -0.32 |
| HaddockBiomassWestern.RV_s | 0.50 | 0.18 | 0.13 | 0.26 | 0.17 | 1.00 | 0.92 | -0.01 | 0.33 | 0.80 | 0.42 | 0.59 | 0.53 | 0.05 | 0.13 | 0.03 | 0.04 | 0.01 | 0.14 | 0.07 | -0.01 | 0.14 | 0.10 | 0.44 | 0.36 | 0.36 | 0.31 | 0.34 | 0.32 | 0.19 | 0.21 |
| HaddockBiomassWSS.RV_s | 0.39 | 0.14 | 0.16 | 0.38 | 0.55 | 0.92 | 1.00 | 0.02 | 0.46 | 0.82 | 0.51 | 0.63 | 0.45 | 0.06 | 0.05 | -0.03 | -0.03 | -0.08 | -0.01 | 0.02 | -0.02 | 0.29 | 0.33 | 0.53 | 0.31 | 0.17 | 0.04 | 0.11 | 0.13 | 0.03 | -0.05 |
| Age1HaddockAbund.RV_s | -0.34 | -0.24 | -0.20 | -0.16 | 0.09 | -0.01 | 0.02 | 1.00 | 0.27 | 0.07 | 0.01 | -0.09 | -0.13 | -0.13 | -0.19 | -0.11 | -0.21 | -0.13 | -0.13 | -0.08 | 0.94 | 0.24 | 0.20 | 0.12 | -0.19 | -0.25 | -0.22 | -0.10 | -0.23 | -0.23 | -0.15 |
| Age2HaddockAbund.RV_s | -0.19 | -0.17 | -0.20 | -0.04 | 0.45 | 0.33 | 0.46 | 0.27 | 1.00 | 0.45 | 0.24 | 0.25 | 0.03 | -0.05 | -0.14 | -0.16 | -0.19 | -0.14 | -0.19 | -0.08 | 0.22 | 0.91 | 0.45 | 0.11 | 0.11 | -0.10 | -0.11 | -0.11 | -0.05 | -0.19 | -0.20 |
| Age3HaddockAbund.RV_s | 0.10 | 0.00 | 0.04 | 0.11 | 0.34 | 0.80 | 0.82 | 0.07 | 0.45 | 1.00 | 0.45 | 0.43 | 0.25 | -0.05 | 0.01 | -0.01 | 0.03 | -0.06 | -0.11 | -0.07 | 0.04 | 0.28 | 0.85 | 0.38 | 0.07 | -0.04 | -0.09 | -0.01 | 0.03 | -0.15 | -0.20 |
| Age4HaddockAbund.RV_s | 0.55 | -0.23 | -0.14 | 0.05 | 0.39 | 0.42 | 0.51 | 0.01 | 0.24 | 0.45 | 1.00 | 0.40 | 0.24 | 0.13 | 0.09 | 0.20 | 0.09 | 0.06 | -0.06 | -0.06 | 0.02 | 0.15 | 0.47 | 0.92 | 0.39 | 0.11 | 0.10 | 0.07 | 0.17 | 0.07 | -0.08 |
| Age5HaddockAbund.RV_s | 0.58 | -0.08 | -0.13 | 0.12 | 0.31 | 0.59 | 0.63 | -0.09 | 0.25 | 0.43 | 0.40 | 1.00 | 0.45 | 0.10 | 0.14 | 0.20 | 0.08 | 0.22 | 0.06 | 0.25 | -0.11 | 0.14 | 0.15 | 0.31 | 0.87 | 0.37 | 0.07 | 0.23 | 0.12 | 0.15 | 0.18 |
| Age6HaddockAbund.RV_s | 0.54 | -0.05 | -0.11 | 0.04 | 0.00 | 0.53 | 0.45 | -0.13 | 0.03 | 0.25 | 0.24 | 0.45 | 1.00 | 0.38 | 0.30 | 0.30 | 0.43 | 0.28 | 0.43 | 0.05 | -0.21 | -0.14 | -0.03 | 0.06 | 0.33 | 0.87 | 0.64 | 0.39 | 0.39 | 0.31 | 0.52 |
| Age7HaddockAbund.RV_s | 0.49 | -0.18 | -0.28 | -0.12 | 0.05 | 0.05 | 0.06 | -0.13 | -0.05 | -0.05 | 0.13 | 0.10 | 0.38 | 1.00 | 0.56 | 0.37 | 0.27 | 0.36 | 0.28 | 0.24 | -0.22 | -0.14 | 0.06 | 0.22 | 0.12 | 0.41 | 0.83 | 0.67 | 0.48 | 0.52 | 0.55 |
| Age8HaddockAbund.RV_s | 0.42 | -0.37 | -0.41 | -0.28 | -0.15 | 0.13 | 0.05 | -0.19 | -0.14 | 0.01 | 0.09 | 0.14 | 0.30 | 0.56 | 1.00 | 0.57 | 0.40 | 0.63 | 0.40 | 0.38 | -0.19 | -0.19 | 0.12 | 0.11 | 0.14 | 0.33 | 0.63 | 0.85 | 0.69 | 0.55 | 0.68 |
| Age9HaddockAbund.RV_s | 0.42 | -0.28 | -0.42 | -0.38 | -0.15 | 0.03 | -0.03 | -0.11 | -0.16 | -0.01 | 0.20 | 0.20 | 0.30 | 0.37 | 0.57 | 1.00 | 0.83 | 0.74 | 0.43 | 0.29 | -0.13 | -0.12 | 0.06 | 0.18 | 0.23 | 0.34 | 0.29 | 0.63 | 0.85 | 0.75 | 0.71 |
| Age10HaddockAbund.RV_s | 0.28 | -0.22 | -0.39 | -0.35 | -0.17 | 0.04 | -0.03 | -0.21 | -0.19 | 0.03 | 0.09 | 0.08 | 0.43 | 0.27 | 0.40 | 0.83 | 1.00 | 0.66 | 0.53 | 0.17 | -0.24 | -0.18 | -0.01 | -0.05 | 0.05 | 0.39 | 0.24 | 0.41 | 0.74 | 0.69 | 0.73 |
| Age11HaddockAbund.RV_s | 0.27 | -0.35 | -0.52 | -0.38 | -0.20 | 0.01 | -0.08 | -0.13 | -0.14 | -0.06 | 0.06 | 0.22 | 0.28 | 0.36 | 0.63 | 0.74 | 0.66 | 1.00 | 0.62 | 0.63 | -0.13 | -0.11 | -0.13 | -0.03 | 0.20 | 0.20 | 0.32 | 0.65 | 0.66 | 0.70 | 0.81 |
| Age12HaddockAbund.RV_s | 0.01 | -0.26 | -0.34 | -0.24 | -0.31 | 0.14 | -0.01 | -0.13 | -0.19 | -0.11 | -0.06 | 0.06 | 0.43 | 0.28 | 0.40 | 0.43 | 0.53 | 0.62 | 1.00 | 0.58 | -0.09 | -0.14 | -0.41 | -0.28 | -0.17 | 0.21 | 0.27 | 0.28 | 0.47 | 0.60 | 0.82 |
| Age13HaddockAbund.RV_s | -0.10 | -0.32 | -0.37 | -0.23 | -0.11 | 0.07 | 0.02 | -0.08 | -0.08 | -0.07 | -0.06 | 0.25 | 0.05 | 0.24 | 0.38 | 0.29 | 0.17 | 0.63 | 0.58 | 1.00 | -0.06 | -0.12 | -0.33 | -0.24 | -0.08 | -0.18 | 0.00 | 0.27 | 0.17 | 0.34 | 0.47 |
| Age1HaddockAbund.VPA_s | -0.31 | -0.26 | -0.27 | -0.39 | -0.02 | -0.01 | -0.02 | 0.94 | 0.22 | 0.04 | 0.02 | -0.11 | -0.21 | -0.22 | -0.19 | -0.13 | -0.24 | -0.13 | -0.09 | -0.06 | 1.00 | 0.27 | 0.00 | 0.15 | -0.11 | -0.22 | -0.22 | -0.09 | -0.17 | -0.15 | -0.05 |
| Age2HaddockAbund.VPA_s | -0.22 | -0.36 | -0.36 | -0.34 | 0.31 | 0.14 | 0.29 | 0.24 | 0.91 | 0.28 | 0.15 | 0.14 | -0.14 | -0.14 | -0.19 | -0.12 | -0.18 | -0.11 | -0.14 | -0.12 | 0.27 | 1.00 | 0.28 | 0.16 | 0.17 | -0.07 | -0.18 | -0.19 | -0.06 | -0.15 | -0.12 |
| Age3HaddockAbund.VPA_s | 0.07 | -0.45 | -0.36 | -0.06 | 0.42 | 0.10 | 0.33 | 0.20 | 0.45 | 0.85 | 0.47 | 0.15 | -0.03 | 0.06 | 0.12 | 0.06 | -0.01 | -0.13 | -0.41 | -0.33 | 0.00 | 0.28 | 1.00 | 0.39 | 0.15 | 0.20 | -0.06 | -0.14 | -0.15 | -0.01 | -0.15 |
| Age4HaddockAbund.VPA_s | 0.61 | -0.31 | -0.28 | 0.15 | 0.35 | 0.44 | 0.53 | 0.12 | 0.11 | 0.38 | 0.92 | 0.31 | 0.06 | 0.22 | 0.11 | 0.18 | -0.05 | -0.03 | -0.28 | -0.24 | 0.15 | 0.16 | 0.39 | 1.00 | 0.49 | 0.26 | 0.18 | 0.08 | 0.10 | 0.07 | -0.12 |
| Age5HaddockAbund.VPA_s | 0.74 | -0.15 | -0.32 | 0.22 | 0.09 | 0.36 | 0.31 | -0.19 | 0.11 | 0.07 | 0.39 | 0.87 | 0.33 | 0.12 | 0.14 | 0.23 | 0.05 | 0.20 | -0.17 | -0.08 | -0.11 | 0.17 | 0.15 | 0.49 | 1.00 | 0.54 | 0.26 | 0.26 | 0.13 | 0.13 | 0.10 |
| Age6HaddockAbund.VPA_s | 0.69 | -0.11 | -0.24 | 0.11 | -0.14 | 0.36 | 0.17 | -0.25 | -0.10 | -0.04 | 0.11 | 0.37 | 0.87 | 0.41 | 0.33 | 0.34 | 0.39 | 0.20 | 0.21 | -0.18 | -0.22 | -0.07 | 0.20 | 0.26 | 0.54 | 1.00 | 0.61 | 0.36 | 0.36 | 0.23 | 0.34 |
| Age7HaddockAbund.VPA_s | 0.62 | -0.11 | -0.23 | -0.04 | -0.29 | 0.31 | 0.04 | -0.22 | -0.11 | -0.09 | 0.10 | 0.07 | 0.64 | 0.83 | 0.63 | 0.29 | 0.24 | 0.32 | 0.27 | 0.00 | -0.22 | -0.18 | -0.06 | 0.18 | 0.26 | 0.61 | 1.00 | 0.70 | 0.50 | 0.48 | 0.51 |
| Age8HaddockAbund.VPA_s | 0.52 | -0.11 | -0.25 | -0.18 | -0.21 | 0.34 | 0.11 | -0.10 | -0.11 | -0.01 | 0.07 | 0.23 | 0.39 | 0.67 | 0.85 | 0.63 | 0.41 | 0.65 | 0.28 | 0.27 | -0.09 | -0.19 | -0.14 | 0.08 | 0.26 | 0.36 | 0.70 | 1.00 | 0.74 | 0.57 | 0.62 |
| Age9HaddockAbund.VPA_s | 0.44 | -0.14 | -0.27 | -0.26 | -0.16 | 0.32 | 0.13 | -0.23 | -0.05 | 0.03 | 0.17 | 0.12 | 0.39 | 0.48 | 0.69 | 0.85 | 0.74 | 0.66 | 0.47 | 0.17 | -0.17 | -0.06 | -0.15 | 0.10 | 0.13 | 0.36 | 0.50 | 0.74 | 1.00 | 0.76 | 0.71 |
| Age10HaddockAbund.VPA_s | 0.37 | -0.21 | -0.43 | -0.29 | -0.18 | 0.19 | 0.03 | -0.23 | -0.19 | -0.15 | 0.07 | 0.15 | 0.31 | 0.52 | 0.55 | 0.75 | 0.69 | 0.70 | 0.60 | 0.34 | -0.15 | -0.15 | -0.01 | 0.07 | 0.13 | 0.23 | 0.48 | 0.57 | 0.76 | 1.00 | 0.85 |
| Age11HaddockAbund.VPA_s | 0.28 | -0.29 | -0.52 | -0.42 | -0.32 | 0.21 | -0.05 | -0.15 | -0.20 | -0.20 | -0.08 | 0.18 | 0.52 | 0.55 | 0.68 | 0.71 | 0.73 | 0.81 | 0.82 | 0.47 | -0.05 | -0.12 | -0.15 | -0.12 | 0.10 | 0.34 | 0.51 | 0.62 | 0.71 | 0.85 | 1.00 |
Plot the defined subset of indices; upper panel is raw data and lower panels is with loess smoothing:
Haddock_indi_melt <- melt(Haddock_indi, id=c('YEAR', "ID"))
Plot_color(Haddock_indi_melt)
Plot_color_smooth(Haddock_indi_melt)
4VWX5Z Cusk: Don Clark
We gathered data from the following tables/figures in http://waves-vagues.dfo-mpo.gc.ca/Library/365968.pdf:
- Tab 1: Cusk Landings in 4X5YZ
- Fig 1: Cusk Biomass Index in 4VWX5Z derived from the Halibut Survey
Cusk <- read.csv("data/stocks/4VWX5Z Cusk/4VWX5Z Cusk.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
Cusk_s <- stdizeFrame(Cusk)
Cusk_indi <- Cusk_s[,c("YEAR", "ID", "CuskLandings4X5YZ.L_s", "CuskLandings4VW.L_s", "CuskBiomass4VWX5Z.HS_s")]Explore correlations
Cusk_indi_corr <- Cusk_indi[, -c(1:2)]
chart.Correlation(Cusk_indi_corr, histogram=FALSE, pch=20,
method = "pearson",
main = "Cusk Indices")
Table below matches the results from the previous figure but provides the full set of results:
a <- rcorr(as.matrix(Cusk_indi_corr,type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | CuskLandings4X5YZ.L_s | CuskLandings4VW.L_s | CuskBiomass4VWX5Z.HS_s | |
|---|---|---|---|
| CuskLandings4X5YZ.L_s | 1.00 | 0.77 | 0.16 |
| CuskLandings4VW.L_s | 0.77 | 1.00 | 0.38 |
| CuskBiomass4VWX5Z.HS_s | 0.16 | 0.38 | 1.00 |
Plot the defined subset of indices; upper panel is raw data and lower panels is with loess smoothing:
Cusk_indi_melt <- melt(Cusk_indi, id=c('YEAR', "ID"))
Plot_color(Cusk_indi_melt)
Plot_color_smooth(Cusk_indi_melt)
4Xopqrs5 Pollock: Ryan Martin
Data obtained from the 2017 Science Response http://waves-vagues.dfo-mpo.gc.ca/Library/365968.pdf:
- Fig 1 (PollockBiomassSummer.RV, PollockBiomassFall.NMFS, PollockBiomassSpring.NMFS): Western Component Pollock biomass indices, scaled to the DFO Summer Research Vessel (RV) survey mean (1984-1994) for the DFO Summer RV, NMFS Spring (red line), and NMFS Fall surveys from 1984-2016.
- Fig 7 (PollockFemaleCondition.RV): Fish condition (Fulton’s K) of Western Component Pollock from the DFO Summer Research Vessel survey based on strata representing unit areas 4Xopqrs+5Yb, 1984-2016
Pollock <- read.csv("data/stocks/4Xopqrs5 Pollock/2016 WC Pollock update data.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
Pollock$ID <- "4X"
Pollock_s <- stdizeFrame(Pollock)
Pollock_indi <- Pollock_s[,c("YEAR", "ID", "PollockBiomasSummer.RV_s", "PollockBiomasSpring.NMFS_s", "PollockBiomasFall.NMFS_s",
"PollockFemaleCondition.RV_s", "PollockMaleCondition.RV_s")]Explore correlations
Pollock_indi_corr <- Pollock_indi[, -c(1:2)]
chart.Correlation(Pollock_indi_corr, histogram=FALSE, pch=20,
method = "pearson",
main = "Pollock Indices")
Table below matches the results from the previous figure but provides the full set of results:
a <- rcorr(as.matrix(Pollock_indi_corr,type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | PollockBiomasSummer.RV_s | PollockBiomasSpring.NMFS_s | PollockBiomasFall.NMFS_s | PollockFemaleCondition.RV_s | PollockMaleCondition.RV_s | |
|---|---|---|---|---|---|
| PollockBiomasSummer.RV_s | 1.00 | 0.00 | 0.22 | 0.47 | 0.45 |
| PollockBiomasSpring.NMFS_s | 0.00 | 1.00 | -0.18 | 0.19 | 0.30 |
| PollockBiomasFall.NMFS_s | 0.22 | -0.18 | 1.00 | 0.31 | 0.28 |
| PollockFemaleCondition.RV_s | 0.47 | 0.19 | 0.31 | 1.00 | 0.88 |
| PollockMaleCondition.RV_s | 0.45 | 0.30 | 0.28 | 0.88 | 1.00 |
Plot the defined subset of indices; upper panel is raw data and lower panels is with loess smoothing:
Pollock_indi_melt <- melt(Pollock_indi, id=c('YEAR', "ID"))
Plot_color(Pollock_indi_melt)
Plot_color_smooth(Pollock_indi_melt)
4X5Yb Cod: Irene Andrushchenko
Data obtained from the 2017 Science Response http://publications.gc.ca/collections/collection_2017/mpo-dfo/Fs70-7-2017-024-eng.pdf:
- Fig 2: Landings (CodLandings.L) and Total Allowable Catch (CodTAC) for 4X5Yb Atlantic Cod by quota year
- Fig 4: Scaled biomass index of Atlantic Cod in 4X5Yb from the DFO Summer Research Vessel survey from 1970 to 2017 (CodSBiomass.RV). Age 1+ and Age 3+ Virtual Population Analysis scaled biomass estimates from 1980-2008 are also shown (DFO 2011a): CodBiomassAge3.vpa and CodBiomassAge1.vpa
- Fig 7: Age 1 recruitment index from DFO Summer Research Vessel survey CodAge1Recruitment.RV
Cod <- read.csv("data/stocks/4X5Yb Cod/4X5YbCod.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
Cod$ID <- "4X"
Cod_s <- stdizeFrame(Cod)
Cod_indi <- Cod_s[,c("YEAR", "ID", "CodLandings.L_s", "CodTAC_s", "CodBiomassAge1.vpa_s",
"CodSBiomass.RV_s", "CodAge1Recruitment.RV_s")]Explore correlations
Cod_indi_corr <- Cod_indi[, -c(1:2)]
chart.Correlation(Cod_indi_corr, histogram=FALSE, pch=20,
method = "pearson",
main = "Atlantic cod Indices")
Table below matches the results from the previous figure but provides the full set of results:
a <- rcorr(as.matrix(Cod_indi_corr,type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | CodLandings.L_s | CodTAC_s | CodBiomassAge1.vpa_s | CodSBiomass.RV_s | CodAge1Recruitment.RV_s | |
|---|---|---|---|---|---|
| CodLandings.L_s | 1.00 | 0.99 | 0.93 | 0.66 | 0.23 |
| CodTAC_s | 0.99 | 1.00 | 0.91 | 0.71 | 0.33 |
| CodBiomassAge1.vpa_s | 0.93 | 0.91 | 1.00 | 0.62 | 0.11 |
| CodSBiomass.RV_s | 0.66 | 0.71 | 0.62 | 1.00 | 0.38 |
| CodAge1Recruitment.RV_s | 0.23 | 0.33 | 0.11 | 0.38 | 1.00 |
Plot the defined subset of indices; upper panel is raw data and lower panels is with loess smoothing:
Cod_indi_melt <- melt(Cod_indi, id=c('YEAR', "ID"))
Plot_color(Cod_indi_melt)
Plot_color_smooth(Cod_indi_melt)
3NOPs4VWX5Zc Atlantic Halibut: Nell den Heyer
Data obtained from the 2017 Science Response http://waves-vagues.dfo-mpo.gc.ca/Library/40625175.pdf:
- Fig 2: Landings in canadian waters (HalibutCanadianLandings.L), Total Allowable Catch (HalibutTAC), Landings in foreign waters (HalibutForeignLandings.L), and reported Canadian and foreign landings (metric tonnes) for 3NOPs4VWX5Zc Atlantic Halibut (HalibutLandings.L)
- Fig 3: mean number of halibut per tow for DFO Summer Research Vessel survey sets in 4VWX from 1970 to 2016 (HalibutNumberPerTow4VWX.RV)
- Fig 5: Halibut biomass estimated between 1970 and 2013 from the stock assessment model (HalibutModelBiomass.m), and biomass of Halibut obtained in the Halibut Survey (HalibutBiomass.HS)
Halibut <- read.csv("data/stocks/3NOPS4VWX5ZC Halibut/HalibutIndices.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
Halibut$ID <- "4X" # this si just to simplify data merging
Halibut_s <- stdizeFrame(Halibut)
Halibut_indi <- Halibut_s[,c("YEAR", "ID", "HalibutCanadianLandings.L_s", "HalibutTAC_s", "HalibutForeignLandings.L_s",
"HalibutLandings.L_s", "HalibutModelBiomass.m_s", "HalibutBiomass.HS_s", "HalibutNumberPerTow4VWX.RV_s")]Explore correlations
Halibut_indi_corr <- Halibut_indi[, -c(1:2)]
chart.Correlation(Halibut_indi_corr, histogram=FALSE, pch=20,
method = "pearson",
main = "Halibut Indices")
Table below matches the results from the previous figure but provides the full set of results:
a <- rcorr(as.matrix(Halibut_indi_corr,type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | HalibutCanadianLandings.L_s | HalibutTAC_s | HalibutForeignLandings.L_s | HalibutLandings.L_s | HalibutModelBiomass.m_s | HalibutBiomass.HS_s | HalibutNumberPerTow4VWX.RV_s | |
|---|---|---|---|---|---|---|---|
| HalibutCanadianLandings.L_s | 1.00 | 0.68 | 0.50 | 0.97 | 0.61 | 0.89 | 0.34 |
| HalibutTAC_s | 0.68 | 1.00 | 0.46 | 0.69 | 0.13 | 0.92 | 0.39 |
| HalibutForeignLandings.L_s | 0.50 | 0.46 | 1.00 | 0.70 | 0.07 | 0.36 | -0.03 |
| HalibutLandings.L_s | 0.97 | 0.69 | 0.70 | 1.00 | 0.55 | 0.87 | 0.26 |
| HalibutModelBiomass.m_s | 0.61 | 0.13 | 0.07 | 0.55 | 1.00 | 0.94 | 0.63 |
| HalibutBiomass.HS_s | 0.89 | 0.92 | 0.36 | 0.87 | 0.94 | 1.00 | 0.81 |
| HalibutNumberPerTow4VWX.RV_s | 0.34 | 0.39 | -0.03 | 0.26 | 0.63 | 0.81 | 1.00 |
Plot the defined subset of indices; upper panel is raw data and lower panels is with loess smoothing:
Halibut_indi_melt <- melt(Halibut_indi, id=c('YEAR', "ID"))
Plot_color(Halibut_indi_melt)
Plot_color_smooth(Halibut_indi_melt)
Silver Hake 4VWX: Mark Showell
Data obtained from the 2017 Science Response http://publications.gc.ca/collections/collection_2017/mpo-dfo/Fs70-7-2017-010-eng.pdf:
- Fig 2: Silver Hake Total Allowable Catch (line) and landings (bars) (x 1000 mt) by fishing area, 1977-2016. Basin: landings from Emerald and LaHave basins. Slope: landings from the shelf edge outside the basins SilverHakeLandings4VWX.L
- Fig 3: Stratified total biomass estimates from the DFO Summer Research Vessel survey (excludes Bay of Fundy strata), 1970-2016. 1970-1981 estimates are adjusted for vessel/ear effect (Fanning 1985) SilverHakeBiomass4VWX.RV
- Fig 5: Age 1 abundance estimates for Scotian Shelf Silver Hake from the DFO Summer Research Vessel (RV) survey. The 2014 and 2015 year classes are estimated from the DFO Summer RV survey length frequency data SilverHakeAge1Abund4VWX.RV
SilverHake <- read.csv("data/stocks/4VWX Silver Hake/silverhake.csv", header=TRUE, na.strings = "NA", sep=",", as.is=T, strip.white=T)
SilverHake$ID <- "4X" # this si just to simplify data merging
SilverHake_s <- stdizeFrame(SilverHake)
SilverHake_indi <- SilverHake_s[,c("YEAR", "ID", "SilverHakeAge1Abund4VWX.RV_s", "SilverHakeLandings4VWX.L_s", "SilverHakeBiomass4VWX.RV_s")]Explore correlations
SilverHake_indi_corr <- SilverHake_indi[, -c(1:2)]
chart.Correlation(SilverHake_indi_corr, histogram=FALSE, pch=20,
method = "pearson",
main = "Silver Hake Indices")
Table below matches the results from the previous figure but provides the full set of results:
a <- rcorr(as.matrix(SilverHake_indi_corr,type="spearman"))
kable(a$r, digits=2, full_width = F, position = "float_right") | SilverHakeAge1Abund4VWX.RV_s | SilverHakeLandings4VWX.L_s | SilverHakeBiomass4VWX.RV_s | |
|---|---|---|---|
| SilverHakeAge1Abund4VWX.RV_s | 1.00 | -0.28 | 0.04 |
| SilverHakeLandings4VWX.L_s | -0.28 | 1.00 | 0.35 |
| SilverHakeBiomass4VWX.RV_s | 0.04 | 0.35 | 1.00 |
Plot the defined subset of indices; upper panel is raw data and lower panels is with loess smoothing:
SilverHake_indi_melt <- melt(SilverHake_indi, id=c('YEAR', "ID"))
Plot_color(SilverHake_indi_melt)
Plot_color_smooth(SilverHake_indi_melt)
Merge and save data-frames of all indicators that will be used in multi-variate analysis
Merge all data standardized - azmp_suite - MultiSpp - seals_indi - BiomassSummerRV_indi - Haddock_indi - Pollock_indi - Cusk_indi - Cod_indi - Halibut_indi - SilverHake_indi
IndiSuite0 <- left_join(MultiSpp, seals_indi, by=c('YEAR', 'ID'))
IndiSuite1 <- left_join(IndiSuite0, azmp_suite, by=c('YEAR', 'ID'))
IndiSuite2 <- left_join(IndiSuite1, BiomassSummerRV_indi, by=c('YEAR', 'ID'))
IndiSuite3 <- left_join(IndiSuite2, Haddock_indi, by=c('YEAR', 'ID'))
IndiSuite4 <- left_join(IndiSuite3, Pollock_indi, by=c('YEAR', 'ID'))
IndiSuite5 <- left_join(IndiSuite4, Cusk_indi, by=c('YEAR', 'ID'))
IndiSuite6 <- left_join(IndiSuite5, Cod_indi, by=c('YEAR', 'ID'))
IndiSuite7 <- left_join(IndiSuite6, Halibut_indi, by=c('YEAR', 'ID'))
IndiSuite <- left_join(IndiSuite7, SilverHake_indi, by=c('YEAR', 'ID'))
summary(IndiSuite)## YEAR ID MargalefRichness_s Heips_s
## Min. :1970 Length:46 Min. :-1.0115 Min. :-1.3875
## 1st Qu.:1981 Class :character 1st Qu.:-0.6943 1st Qu.:-0.8165
## Median :1992 Mode :character Median :-0.4522 Median :-0.2379
## Mean :1992 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.:2004 3rd Qu.: 0.2763 3rd Qu.: 0.6800
## Max. :2015 Max. : 2.2516 Max. : 2.2938
##
## LargeFishIndicator_s BTGZoopiscivore_s BTGPiscivore_s
## Min. :-1.3459 Min. :-1.0896 Min. :-1.4663
## 1st Qu.:-0.7490 1st Qu.:-0.6937 1st Qu.:-0.7904
## Median :-0.2225 Median :-0.2020 Median :-0.1566
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.6491 3rd Qu.: 0.3882 3rd Qu.: 0.4519
## Max. : 2.7368 Max. : 3.6182 Max. : 2.8846
##
## Biomass_s BiomassSkates_s BiomassFlatfish_s
## Min. :-1.5753 Min. :-1.1525 Min. :-1.79712
## 1st Qu.:-0.7375 1st Qu.:-0.7058 1st Qu.:-0.56020
## Median :-0.3192 Median :-0.3391 Median :-0.06608
## Mean : 0.0000 Mean : 0.0000 Mean : 0.00000
## 3rd Qu.: 0.4919 3rd Qu.: 0.2529 3rd Qu.: 0.48134
## Max. : 2.4398 Max. : 3.0811 Max. : 4.34715
##
## MeanLengthAbundance_s MeanTrophicLevel_s BiomassGadoids_s
## Min. :-1.6550 Min. :-2.53000 Min. :-1.1283
## 1st Qu.:-0.8949 1st Qu.:-0.42807 1st Qu.:-0.5877
## Median :-0.1570 Median :-0.07689 Median :-0.2530
## Mean : 0.0000 Mean : 0.00000 Mean : 0.0000
## 3rd Qu.: 0.5831 3rd Qu.: 0.61217 3rd Qu.: 0.3881
## Max. : 2.7343 Max. : 2.22196 Max. : 4.3559
##
## CommunityCondition_s CCMediumBenthivore_s CCPiscivore_s
## Min. :-2.2765 Min. :-2.66356 Min. :-1.85112
## 1st Qu.:-0.5490 1st Qu.:-0.50280 1st Qu.:-0.66749
## Median : 0.1562 Median : 0.08642 Median :-0.06179
## Mean : 0.0000 Mean : 0.00000 Mean : 0.00000
## 3rd Qu.: 0.5209 3rd Qu.: 0.58311 3rd Qu.: 0.74109
## Max. : 2.7943 Max. : 2.50117 Max. : 2.01837
##
## CCZoopiscivore_s CCLargeBenthivore_s MeanLifespan_s
## Min. :-2.0268 Min. :-2.1480 Min. :-1.68778
## 1st Qu.:-0.7831 1st Qu.:-0.7917 1st Qu.:-0.88525
## Median : 0.1004 Median : 0.1518 Median : 0.09522
## Mean : 0.0000 Mean : 0.0000 Mean : 0.00000
## 3rd Qu.: 0.7426 3rd Qu.: 0.6990 3rd Qu.: 0.62016
## Max. : 1.5256 Max. : 1.9741 Max. : 2.62630
##
## Intrinsicvulnerabilityindex.L_s InverseCVBiomass_s MeanTrophicLevel.L_s
## Min. :-2.6609 Min. :-1.3515 Min. :-1.8699
## 1st Qu.:-0.6899 1st Qu.:-0.7150 1st Qu.:-0.9063
## Median : 0.3178 Median :-0.1656 Median : 0.2547
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.8138 3rd Qu.: 0.4526 3rd Qu.: 0.8983
## Max. : 1.5512 Max. : 2.9640 Max. : 1.5923
##
## MarineTrophicIndex.L_s DiversityTargetSpp.L_s FishingPressure.L_s
## Min. :-1.65225 Min. :-1.7510 Min. :-2.03104
## 1st Qu.:-0.76349 1st Qu.:-0.9061 1st Qu.:-0.74969
## Median :-0.03629 Median : 0.2908 Median :-0.04239
## Mean : 0.00000 Mean : 0.0000 Mean : 0.00000
## 3rd Qu.: 0.59628 3rd Qu.: 0.9245 3rd Qu.: 0.65648
## Max. : 2.64684 Max. : 1.3470 Max. : 2.56651
##
## FPClupeids.L_s Landings.L_s LSkates.L_s LFlatfish.L_s
## Min. :-1.5738 Min. :-1.6614 Min. :-0.3648 Min. :-1.2128
## 1st Qu.:-0.7833 1st Qu.:-0.8609 1st Qu.:-0.3158 1st Qu.:-0.9529
## Median :-0.2502 Median : 0.1368 Median :-0.2808 Median :-0.2824
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.6221 3rd Qu.: 0.7181 3rd Qu.:-0.1584 3rd Qu.: 0.8546
## Max. : 2.4614 Max. : 1.8037 Max. : 5.9392 Max. : 2.1518
##
## LLargePelagic.L_s BiomassInvertebrates_s BiomassTL2_s
## Min. :-1.3529 Min. :-1.44958 Min. :-0.42033
## 1st Qu.:-0.4427 1st Qu.:-0.85103 1st Qu.:-0.04473
## Median :-0.1275 Median :-0.08607 Median : 0.12532
## Mean : 0.0000 Mean : 0.00000 Mean : 0.30703
## 3rd Qu.: 0.2203 3rd Qu.: 0.67432 3rd Qu.: 0.61302
## Max. : 5.6395 Max. : 2.09293 Max. : 1.38104
## NA's :29 NA's :29
## GreySealPopulation_Model_s BottomT_July_s NAO_s
## Min. :-0.8023 Min. :-2.37780 Min. :-2.77712
## 1st Qu.:-0.6855 1st Qu.:-0.53841 1st Qu.:-0.59231
## Median :-0.2995 Median :-0.05553 Median : 0.18759
## Mean : 0.1262 Mean :-0.04389 Mean :-0.01105
## 3rd Qu.: 0.7973 3rd Qu.: 0.56453 3rd Qu.: 0.77113
## Max. : 2.2963 Max. : 2.34216 Max. : 1.96863
##
## NAO_5YrMean_s SST_anomalies_s AnnualAvgIceVol_s
## Min. :-1.9343 Min. :-1.79265 Min. :-1.17804
## 1st Qu.:-0.7219 1st Qu.:-0.86238 1st Qu.:-0.85659
## Median :-0.0129 Median :-0.05813 Median :-0.09262
## Mean : 0.0000 Mean :-0.04323 Mean : 0.02558
## 3rd Qu.: 0.6280 3rd Qu.: 0.78290 3rd Qu.: 0.84589
## Max. : 2.1140 Max. : 2.95304 Max. : 2.91350
## NA's :3 NA's :11
## StratificationIndex_s TemperatureMeanSurface_s Salinity_s
## Min. :-2.79796 Min. :-2.24518 Min. :-2.574302
## 1st Qu.:-0.68342 1st Qu.:-0.72731 1st Qu.:-0.699754
## Median : 0.02278 Median :-0.01032 Median : 0.110742
## Mean :-0.02363 Mean :-0.03829 Mean : 0.006201
## 3rd Qu.: 0.50386 3rd Qu.: 0.43706 3rd Qu.: 0.736968
## Max. : 2.34978 Max. : 2.88881 Max. : 1.855648
##
## Chlorophyll_s C_finmarchicus_s GulfStreamDisplacement_5YrMean_s
## Min. :-1.08279 Min. :-1.749955 Min. :-2.555018
## 1st Qu.:-0.55240 1st Qu.:-0.685437 1st Qu.:-0.305469
## Median :-0.25855 Median :-0.000539 Median : 0.004623
## Mean : 0.04566 Mean : 0.080677 Mean : 0.000000
## 3rd Qu.: 0.16903 3rd Qu.: 0.931818 3rd Qu.: 0.472521
## Max. : 3.06769 Max. : 1.545054 Max. : 1.839244
## NA's :29 NA's :29 NA's :17
## ShelfSlopeFrontDisplacement_5YrMean_s Pseudocalanus_s
## Min. :-2.37146 Min. :-1.7346
## 1st Qu.:-0.62799 1st Qu.:-0.4150
## Median :-0.04719 Median : 0.3141
## Mean : 0.00000 Mean : 0.1200
## 3rd Qu.: 0.92939 3rd Qu.: 0.7189
## Max. : 1.76814 Max. : 1.3275
## NA's :17 NA's :29
## Copepods_s NonCopepods_s ZooplanktonBiomass_s
## Min. :-1.832882 Min. :-1.43312 Min. :-1.64167
## 1st Qu.:-0.825465 1st Qu.:-0.79624 1st Qu.:-0.57357
## Median : 0.272115 Median :-0.13298 Median :-0.15458
## Mean : 0.003181 Mean :-0.06828 Mean : 0.07602
## 3rd Qu.: 0.861537 3rd Qu.: 0.74486 3rd Qu.: 0.72220
## Max. : 1.363392 Max. : 1.40352 Max. : 1.95353
## NA's :29 NA's :29 NA's :29
## BloomInitiation_doy_s BloomDuration_days_s BloomAmplitude_s
## Min. :-1.6409 Min. :-0.97561 Min. :-0.93091
## 1st Qu.:-0.3062 1st Qu.:-0.47432 1st Qu.:-0.63979
## Median : 0.3486 Median :-0.32579 Median :-0.16210
## Mean : 0.1261 Mean :-0.19005 Mean : 0.07821
## 3rd Qu.: 0.6854 3rd Qu.: 0.05296 3rd Qu.: 0.50304
## Max. : 1.1859 Max. : 1.25234 Max. : 3.00803
## NA's :28 NA's :28 NA's :28
## BloomMagnitude_s ArcticCalanus_s CopepodsWarmOffshore_s
## Min. :-1.12588 Min. :-1.78513 Min. :-1.87256
## 1st Qu.:-0.58873 1st Qu.:-0.43285 1st Qu.:-0.60363
## Median :-0.14424 Median : 0.12495 Median :-0.14216
## Mean : 0.05501 Mean : 0.08803 Mean :-0.08569
## 3rd Qu.: 0.53351 3rd Qu.: 0.77336 3rd Qu.: 0.37098
## Max. : 2.90866 Max. : 1.69719 Max. : 1.66898
## NA's :28 NA's :29 NA's :29
## CopepodsWarmSppShelf_s AtlanticCod.RV_s Haddock.RV_s
## Min. :-1.61833 Min. :-1.418797 Min. :-1.43019
## 1st Qu.:-0.64781 1st Qu.:-0.733421 1st Qu.:-0.63285
## Median :-0.31387 Median : 0.006068 Median :-0.21382
## Mean :-0.05441 Mean : 0.025163 Mean :-0.00763
## 3rd Qu.: 0.59965 3rd Qu.: 0.649310 3rd Qu.: 0.42123
## Max. : 2.12586 Max. : 2.879079 Max. : 5.01579
## NA's :29
## WhiteHake.RV_s SilverHake.RV_s Cusk.RV_s
## Min. :-1.2858 Min. :-0.740970 Min. :-0.99188
## 1st Qu.:-0.7225 1st Qu.:-0.495989 1st Qu.:-0.83805
## Median :-0.2756 Median :-0.278745 Median :-0.57576
## Mean : 0.0123 Mean :-0.009898 Mean : 0.02015
## 3rd Qu.: 0.5570 3rd Qu.:-0.047113 3rd Qu.: 1.04464
## Max. : 2.8974 Max. : 4.731097 Max. : 1.97534
##
## Pollock.RV_s Redfish.RV_s Halibut.RV_s
## Min. :-1.052963 Min. :-0.99278 Min. :-1.15535
## 1st Qu.:-0.607451 1st Qu.:-0.64741 1st Qu.:-0.85422
## Median :-0.370907 Median :-0.31200 Median :-0.40914
## Mean :-0.002049 Mean :-0.07336 Mean :-0.05184
## 3rd Qu.: 0.248288 3rd Qu.: 0.36473 3rd Qu.: 0.65107
## Max. : 2.658467 Max. : 3.22772 Max. : 3.09170
##
## AmericanPlaice.RV_s WitchFlounder.RV_s YellowTailFlounder.RV_s
## Min. :-1.39195 Min. :-1.072649 Min. :-1.26763
## 1st Qu.:-0.67087 1st Qu.:-0.678947 1st Qu.:-0.81136
## Median :-0.07329 Median :-0.313487 Median : 0.02052
## Mean : 0.02982 Mean : 0.009531 Mean : 0.02698
## 3rd Qu.: 0.45389 3rd Qu.: 0.535217 3rd Qu.: 0.38991
## Max. : 2.95903 Max. : 4.093787 Max. : 2.88105
##
## WinterFlounder.RV_s AtlanticWolfish.RV_s Monkfish.RV_s
## Min. :-1.492791 Min. :-1.1374 Min. :-0.94469
## 1st Qu.:-0.620804 1st Qu.:-0.7116 1st Qu.:-0.62104
## Median : 0.014139 Median :-0.2181 Median :-0.29584
## Mean :-0.009436 Mean : 0.0234 Mean : 0.01382
## 3rd Qu.: 0.418946 3rd Qu.: 0.5881 3rd Qu.: 0.26794
## Max. : 3.886342 Max. : 3.7860 Max. : 3.52963
##
## SmoothSkate.RV_s ThornySkate.RV_s SpinyDogfish.RV_s
## Min. :-1.2111844 Min. :-0.94074 Min. :-1.177725
## 1st Qu.:-0.7825441 1st Qu.:-0.70587 1st Qu.:-0.777172
## Median :-0.3540179 Median :-0.33962 Median :-0.292754
## Mean :-0.0003087 Mean : 0.02102 Mean : 0.003795
## 3rd Qu.: 0.3638615 3rd Qu.: 0.61038 3rd Qu.: 0.617474
## Max. : 2.7230255 Max. : 3.57301 Max. : 2.949183
##
## HaddockBiomassAge4plus.vpa_s HaddockConditionWSS.RV_s
## Min. :-1.726733 Min. :-1.93500
## 1st Qu.:-0.973857 1st Qu.:-0.73320
## Median :-0.041242 Median :-0.11656
## Mean :-0.004853 Mean : 0.04776
## 3rd Qu.: 0.838406 3rd Qu.: 0.94413
## Max. : 1.876806 Max. : 1.74368
## NA's :15
## HaddockConditionBoF.RV_s HaddockLandings.L_s HaddockBiomassBoF.RV_s
## Min. :-1.76376 Min. :-1.1467 Min. :-1.27840
## 1st Qu.:-0.77556 1st Qu.:-0.7582 1st Qu.:-0.68588
## Median : 0.07928 Median :-0.4546 Median :-0.35842
## Mean : 0.04113 Mean : 0.0000 Mean :-0.02598
## 3rd Qu.: 0.81453 3rd Qu.: 0.6657 3rd Qu.: 0.41484
## Max. : 2.13239 Max. : 2.4630 Max. : 3.25180
##
## HaddockBiomassWestern.RV_s HaddockBiomassWSS.RV_s Age1HaddockAbund.RV_s
## Min. :-0.924908 Min. :-1.302387 Min. :-0.65897
## 1st Qu.:-0.436095 1st Qu.:-0.493481 1st Qu.:-0.44610
## Median :-0.179265 Median :-0.243571 Median :-0.32305
## Mean : 0.006786 Mean :-0.004825 Mean : 0.00000
## 3rd Qu.: 0.095126 3rd Qu.: 0.336692 3rd Qu.:-0.02823
## Max. : 6.054770 Max. : 5.395671 Max. : 5.50896
##
## Age2HaddockAbund.RV_s Age3HaddockAbund.RV_s Age4HaddockAbund.RV_s
## Min. :-0.8943 Min. :-0.9081 Min. :-1.2452
## 1st Qu.:-0.6159 1st Qu.:-0.6580 1st Qu.:-0.7980
## Median :-0.2797 Median :-0.3037 Median :-0.2441
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.3617 3rd Qu.: 0.2795 3rd Qu.: 0.6338
## Max. : 4.7875 Max. : 4.3752 Max. : 3.0900
##
## Age5HaddockAbund.RV_s Age6HaddockAbund.RV_s Age7HaddockAbund.RV_s
## Min. :-1.1961 Min. :-1.0974 Min. :-1.1882
## 1st Qu.:-0.8013 1st Qu.:-0.7081 1st Qu.:-0.6159
## Median :-0.2885 Median :-0.3196 Median :-0.3357
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.5228 3rd Qu.: 0.2462 3rd Qu.: 0.1558
## Max. : 2.9330 Max. : 2.7341 Max. : 2.6749
##
## Age8HaddockAbund.RV_s Age9HaddockAbund.RV_s Age10HaddockAbund.RV_s
## Min. :-0.9360 Min. :-0.96400 Min. :-0.7645
## 1st Qu.:-0.6085 1st Qu.:-0.59862 1st Qu.:-0.5504
## Median :-0.2759 Median :-0.35530 Median :-0.3733
## Mean : 0.0000 Mean : 0.00000 Mean : 0.0000
## 3rd Qu.: 0.1030 3rd Qu.: 0.02327 3rd Qu.: 0.2921
## Max. : 3.3094 Max. : 3.76854 Max. : 5.2636
##
## Age11HaddockAbund.RV_s Age12HaddockAbund.RV_s Age13HaddockAbund.RV_s
## Min. :-0.7512 Min. :-0.7923 Min. :-0.5333
## 1st Qu.:-0.6172 1st Qu.:-0.6427 1st Qu.:-0.5333
## Median :-0.4033 Median :-0.4150 Median :-0.3166
## Mean : 0.0000 Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.2301 3rd Qu.: 0.2801 3rd Qu.: 0.0739
## Max. : 4.0521 Max. : 3.1576 Max. : 5.5164
##
## Age1HaddockAbund.VPA_s Age2HaddockAbund.VPA_s Age3HaddockAbund.VPA_s
## Min. :-0.59307 Min. :-0.58937 Min. :-0.5699
## 1st Qu.:-0.43104 1st Qu.:-0.42753 1st Qu.:-0.4105
## Median :-0.25774 Median :-0.26246 Median :-0.2397
## Mean : 0.00910 Mean :-0.03071 Mean :-0.1687
## 3rd Qu.: 0.04012 3rd Qu.: 0.01046 3rd Qu.: 0.0390
## Max. : 5.13225 Max. : 5.13005 Max. : 0.5276
## NA's :15 NA's :15 NA's :15
## Age4HaddockAbund.VPA_s Age5HaddockAbund.VPA_s Age6HaddockAbund.VPA_s
## Min. :-1.31300 Min. :-1.28979 Min. :-1.25888
## 1st Qu.:-0.80939 1st Qu.:-0.81800 1st Qu.:-0.77496
## Median :-0.18571 Median :-0.19927 Median :-0.09466
## Mean :-0.04829 Mean :-0.01674 Mean :-0.03143
## 3rd Qu.: 0.68604 3rd Qu.: 0.70742 3rd Qu.: 0.36314
## Max. : 2.31098 Max. : 2.31139 Max. : 2.24871
## NA's :15 NA's :15 NA's :15
## Age7HaddockAbund.VPA_s Age8HaddockAbund.VPA_s Age9HaddockAbund.VPA_s
## Min. :-1.22334 Min. :-1.19328 Min. :-1.09588
## 1st Qu.:-0.70543 1st Qu.:-0.62876 1st Qu.:-0.58767
## Median :-0.21208 Median :-0.30890 Median :-0.38720
## Mean : 0.01289 Mean : 0.02927 Mean : 0.02932
## 3rd Qu.: 0.48348 3rd Qu.: 0.36064 3rd Qu.: 0.42776
## Max. : 2.29558 Max. : 2.41970 Max. : 2.49985
## NA's :15 NA's :15 NA's :15
## Age10HaddockAbund.VPA_s Age11HaddockAbund.VPA_s PollockBiomasSummer.RV_s
## Min. :-0.98243 Min. :-0.91790 Min. :-0.885568
## 1st Qu.:-0.64515 1st Qu.:-0.71082 1st Qu.:-0.752064
## Median :-0.41855 Median :-0.53045 Median :-0.338289
## Mean :-0.01031 Mean : 0.01532 Mean : 0.000889
## 3rd Qu.: 0.46910 3rd Qu.: 0.53219 3rd Qu.: 0.299621
## Max. : 2.54726 Max. : 2.59889 Max. : 3.344088
## NA's :15 NA's :15 NA's :14
## PollockBiomasSpring.NMFS_s PollockBiomasFall.NMFS_s
## Min. :-0.87774 Min. :-0.56905
## 1st Qu.:-0.61907 1st Qu.:-0.41741
## Median :-0.37960 Median :-0.31646
## Mean :-0.02759 Mean : 0.01578
## 3rd Qu.: 0.02412 3rd Qu.:-0.03656
## Max. : 3.12697 Max. : 4.76302
## NA's :14 NA's :14
## PollockFemaleCondition.RV_s PollockMaleCondition.RV_s
## Min. :-1.52179 Min. :-2.06158
## 1st Qu.:-0.83939 1st Qu.:-0.65456
## Median :-0.21012 Median :-0.08107
## Mean :-0.01028 Mean :-0.01098
## 3rd Qu.: 0.64994 3rd Qu.: 0.67395
## Max. : 2.65480 Max. : 2.14689
## NA's :14 NA's :14
## CuskLandings4X5YZ.L_s CuskLandings4VW.L_s CuskBiomass4VWX5Z.HS_s
## Min. :-1.10175 Min. :-1.26114 Min. :-1.89552
## 1st Qu.:-0.33925 1st Qu.:-0.33836 1st Qu.:-0.70910
## Median : 0.09297 Median : 0.07177 Median :-0.12382
## Mean : 0.12468 Mean : 0.14013 Mean :-0.02221
## 3rd Qu.: 0.46402 3rd Qu.: 0.68696 3rd Qu.: 0.65187
## Max. : 2.20920 Max. : 1.81481 Max. : 1.85820
## NA's :37 NA's :37 NA's :29
## CodLandings.L_s CodTAC_s CodBiomassAge1.vpa_s
## Min. :-1.48898 Min. :-1.35436 Min. :-1.37451
## 1st Qu.:-1.03475 1st Qu.:-0.99546 1st Qu.:-0.84023
## Median : 0.07393 Median : 0.16903 Median :-0.01974
## Mean :-0.08583 Mean : 0.07795 Mean : 0.00000
## 3rd Qu.: 0.59987 3rd Qu.: 0.91224 3rd Qu.: 0.47637
## Max. : 1.80677 Max. : 1.83875 Max. : 2.00288
## NA's :29 NA's :17
## CodSBiomass.RV_s CodAge1Recruitment.RV_s HalibutCanadianLandings.L_s
## Min. :-1.38006 Min. :-0.706311 Min. :-1.4609
## 1st Qu.:-0.70006 1st Qu.:-0.492676 1st Qu.:-0.7097
## Median : 0.03359 Median :-0.315542 Median :-0.3947
## Mean : 0.05255 Mean : 0.009516 Mean :-0.1323
## 3rd Qu.: 0.67186 3rd Qu.:-0.012148 3rd Qu.: 0.2971
## Max. : 2.88414 Max. : 4.568782 Max. : 2.8551
##
## HalibutTAC_s HalibutForeignLandings.L_s HalibutLandings.L_s
## Min. :-1.17342 Min. :-0.9924 Min. :-1.3842
## 1st Qu.:-0.83788 1st Qu.:-0.7638 1st Qu.:-0.7602
## Median :-0.46040 Median :-0.5310 Median :-0.4328
## Mean :-0.04993 Mean :-0.3006 Mean :-0.1821
## 3rd Qu.: 0.79143 3rd Qu.:-0.1321 3rd Qu.: 0.3860
## Max. : 1.45496 Max. : 2.4273 Max. : 2.6964
## NA's :18
## HalibutModelBiomass.m_s HalibutBiomass.HS_s HalibutNumberPerTow4VWX.RV_s
## Min. :-1.2463 Min. :-1.00508 Min. :-1.2248
## 1st Qu.:-0.7289 1st Qu.:-0.81383 1st Qu.:-0.7777
## Median :-0.1542 Median :-0.43601 Median :-0.3585
## Mean : 0.0000 Mean :-0.09217 Mean :-0.0402
## 3rd Qu.: 0.4245 3rd Qu.: 0.53253 3rd Qu.: 0.3541
## Max. : 3.3666 Max. : 2.54850 Max. : 2.8550
## NA's :2 NA's :28
## SilverHakeAge1Abund4VWX.RV_s SilverHakeLandings4VWX.L_s
## Min. :-1.2340 Min. :-0.9931
## 1st Qu.:-0.8112 1st Qu.:-0.7823
## Median :-0.2278 Median :-0.5831
## Mean : 0.0000 Mean : 0.0000
## 3rd Qu.: 0.5055 3rd Qu.: 0.6932
## Max. : 3.0292 Max. : 2.1591
## NA's :7
## SilverHakeBiomass4VWX.RV_s
## Min. :-1.28627
## 1st Qu.:-0.83270
## Median :-0.26941
## Mean :-0.01193
## 3rd Qu.: 0.62467
## Max. : 2.32555
## write.csv(IndiSuite, file = "output/Indi_used_in_analysis.csv",row.names=FALSE)
IndiSuite_melt <- melt(IndiSuite, id=c('YEAR', "ID"))
write.csv(IndiSuite_melt, file = "output/Indi_used_in_analysis_melt.csv",row.names=FALSE)For more information about this document please contact: Catalina.Gomez@dfo-mpo.gc.ca