CSCI
Raphael Mazor, raphaelm@sccwrp.org, Marcus W. Beck, marcusb@sccwrp.org, Mark W. Engeln
R package materials to calculate the California Stream Condition Index (CSCI) based on O/E and pMMI scores using benthic macroinvertebrates.
Citation
Please cite the package as follows:
Mazor, MD, Rehn, AC, Ode, PR, Engeln, M, Schiff, KC, Stein, ED, Gillett, DJ, Herbst, DB, Hawkins, CP. 2016. Bioassessment in complex environments: Designing an index for consistent meaning in different settings. Freshwater Science 35(1): 249-271.
Usage
The core function is CSCI which requires taxonomic and site level data.
#A list of two data frames: bugs and stations
data(bugs_stations)
# run the estimator
results <- CSCI(bugs = bugs_stations[[1]], stations = bugs_stations[[2]])
# see all the components of the report
ls(results)## [1] "core" "Suppl1_grps" "Suppl1_mmi" "Suppl1_OE" "Suppl2_mmi"
## [6] "Suppl2_OE"## $core
## StationCode SampleID Count Number_of_MMI_Iterations
## 1 Site3 BadSample1 100 1
## 2 Site3 BadSample2 600 20
## 3 Site1 Sample1 556 20
## 4 Site2 Sample2 826 20
## 5 Site3 Sample3 607 20
## 6 Site3 Sample4 513 20
## Number_of_OE_Iterations Pcnt_Ambiguous_Individuals Pcnt_Ambiguous_Taxa
## 1 1 0.0000000 0.000000
## 2 1 83.3333333 50.000000
## 3 20 0.5395683 2.631579
## 4 20 0.9685230 1.666667
## 5 20 9.7199341 6.250000
## 6 1 37.6218324 41.025641
## E Mean_O OoverE OoverE_Percentile MMI MMI_Percentile
## 1 10.248486 1.00 0.09757538 0.00 0.1638082 0.00
## 2 10.248486 1.00 0.09757538 0.00 0.3488195 0.00
## 3 7.544418 9.00 1.19293493 0.84 0.8355442 0.18
## 4 12.953853 11.30 0.87232734 0.25 0.8315653 0.17
## 5 10.248486 13.05 1.27335877 0.92 1.1933404 0.86
## 6 10.248486 9.00 0.87817846 0.26 0.9060063 0.30
## CSCI CSCI_Percentile
## 1 0.1306918 0.00
## 2 0.2231975 0.00
## 3 1.0142396 0.54
## 4 0.8519463 0.18
## 5 1.2333496 0.93
## 6 0.8920924 0.25
##
## $Suppl1_mmi
## StationCode SampleID MMI_Score Clinger_PercentTaxa
## 1 Site3 BadSample1 0.1638082 0.0000000
## 2 Site3 BadSample2 0.3488195 0.0000000
## 3 Site1 Sample1 0.8355442 0.2773399
## 4 Site2 Sample2 0.8315653 0.4699071
## 5 Site3 Sample3 1.1933404 0.6588184
## 6 Site3 Sample4 0.9060063 0.6376623
## Clinger_PercentTaxa_predicted Clinger_PercentTaxa_score
## 1 0.6422118 0.0000000
## 2 0.6422118 0.0000000
## 3 0.3929307 0.5288720
## 4 0.6216008 0.4705806
## 5 0.6422118 0.7423165
## 6 0.6422118 0.7081582
## Coleoptera_PercentTaxa Coleoptera_PercentTaxa_predicted
## 1 0.00000000 0.07977832
## 2 0.00000000 0.07977832
## 3 0.11546218 0.08284403
## 4 0.08709465 0.05155909
## 5 0.12096296 0.07977832
## 6 0.07286325 0.07977832
## Coleoptera_PercentTaxa_score Taxonomic_Richness
## 1 0.2321037 1.00
## 2 0.2321037 2.00
## 3 0.7518512 34.65
## 4 0.7653420 32.20
## 5 0.7914646 41.65
## 6 0.5690404 26.75
## Taxonomic_Richness_predicted Taxonomic_Richness_score EPT_PercentTaxa
## 1 32.27143 0.0000000 0.0000000
## 2 32.27143 0.0000000 0.5000000
## 3 26.13860 0.9005109 0.2597899
## 4 32.79767 0.6548757 0.4412853
## 5 32.27143 0.9238949 0.5190358
## 6 32.27143 0.5221013 0.5589744
## EPT_PercentTaxa_predicted EPT_PercentTaxa_score Shredder_Taxa
## 1 0.5267920 0.0000000 0.00
## 2 0.5267920 0.6971410 0.00
## 3 0.3943971 0.4958980 0.00
## 4 0.5783728 0.4912685 4.70
## 5 0.5267920 0.7326724 3.95
## 6 0.5267920 0.8072199 1.00
## Shredder_Taxa_predicted Shredder_Taxa_score Intolerant_Percent
## 1 2.033700 0.2291321 0.00000000
## 2 2.033700 0.2291321 0.00000000
## 3 1.929400 0.2457120 0.01100000
## 4 3.760033 0.7018345 0.08882825
## 5 2.033700 0.8570352 0.15390000
## 6 2.033700 0.3880949 0.13818914
## Intolerant_Percent_predicted Intolerant_Percent_score
## 1 0.1696027 0.15600955
## 2 0.1696027 0.15600955
## 3 0.1440950 0.22556901
## 4 0.3143217 0.04951897
## 5 0.1696027 0.44924085
## 6 0.1696027 0.41930636
##
## $Suppl1_grps
## StationCode pGroup1 pGroup2 pGroup3 pGroup4 pGroup5 pGroup6 pGroup7
## 1 Site1 0.0002 0.0287 0.0065 0.0361 0.0007 0.0079 0.0000
## 2 Site2 0.1077 0.2976 0.0000 0.0056 0.0253 0.0994 0.3547
## 3 Site3 0.0192 0.1103 0.1226 0.1631 0.0068 0.0002 0.0001
## pGroup8 pGroup9 pGroup10 pGroup11
## 1 0.2169 0.0843 0.4991 0.1196
## 2 0.0078 0.1012 0.0006 0.0001
## 3 0.0530 0.2653 0.0700 0.1894
##
## $Suppl1_OE
## StationCode SampleID OTU CaptureProb MeanObserved
## 1 Site1 Sample1 Acari 0.8814250 6.00
## 2 Site2 Sample2 Acari 0.9585321 10.50
## 3 Site3 BadSample1 Acari 0.8678715 0.00
## 4 Site3 BadSample2 Acari 0.8678715 0.00
## 5 Site3 Sample3 Acari 0.8678715 17.75
## 6 Site3 Sample4 Acari 0.8678715 37.00
##
## $Suppl2_OE
## StationCode SampleID OTU CaptureProb
## 1 Site1 Sample1 Acari 0.881424961134976
## 2 Site1 Sample1 Argia 0.366983484848485
## 3 Site1 Sample1 Baetis 0.880591985549809
## 4 Site1 Sample1 Callibaetis 0.101509696969697
## 5 Site1 Sample1 Ceratopsyche_Hydropsyche 0.698923583910464
## 6 Site1 Sample1 Cheumatopsyche 0.193852461500248
## Iteration1 Iteration2 Iteration3 Iteration4 Iteration5 Iteration6
## 1 7 7 6 7 7 6
## 2 8 7 6 9 7 7
## 3 22 28 26 21 25 20
## 4 1 2 2 2 2 2
## 5 4 5 4 4 2 4
## 6 2 0 0 2 2 2
## Iteration7 Iteration8 Iteration9 Iteration10 Iteration11 Iteration12
## 1 5 5 6 6 5 5
## 2 8 9 7 7 6 8
## 3 20 25 24 21 22 21
## 4 2 2 2 2 2 1
## 5 5 4 3 3 4 5
## 6 1 2 1 1 0 2
## Iteration13 Iteration14 Iteration15 Iteration16 Iteration17 Iteration18
## 1 6 4 7 6 7 7
## 2 4 9 8 8 6 8
## 3 21 25 22 24 25 30
## 4 1 2 2 1 1 1
## 5 4 3 4 5 2 4
## 6 2 0 1 1 2 2
## Iteration19 Iteration20
## 1 4 7
## 2 9 5
## 3 28 25
## 4 2 2
## 5 4 4
## 6 2 2
##
## $Suppl2_mmi
## StationCode SampleID metric Iteration value
## 1 Site3 BadSample1 Clinger_PercentTaxa 1 0
## 2 Site3 BadSample1 Clinger_PercentTaxa 2 0
## 3 Site3 BadSample1 Clinger_PercentTaxa 3 0
## 4 Site3 BadSample1 Clinger_PercentTaxa 4 0
## 5 Site3 BadSample1 Clinger_PercentTaxa 5 0
## 6 Site3 BadSample1 Clinger_PercentTaxa 6 0
## predicted_value score
## 1 0.6422118 0
## 2 0.6422118 0
## 3 0.6422118 0
## 4 0.6422118 0
## 5 0.6422118 0
## 6 0.6422118 0