Model-Based Analysis of the Potential of Macroinvertebrates as Indicators for Microbial Pathogens in Rivers
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Collection
2.3. Ecuadorian Water Regulation in Relation to Water Use
2.4. Model Development
2.5. Model Optimization
2.6. Modeling and Analysis
3. Results
3.1. Current Water Quality Status
3.2. Model Development
3.3. Model Optimization
4. Discussion
4.1. Model Relevance and Optimization from a Statistical Point of View
4.2. Model Relevance and Optimization from an Ecological Point of View
4.3. A Possible Screening Tool for Microbial Pollution
5. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
Abbreviations
BMWP | Biological Monitoring Working Party |
BMWP-Col | Biological Monitoring Working Party adapted to Colombia |
BOD5 | Biochemical Oxygen Demand 5 d |
BWQ | Biological Water Quality |
CCI | correctly classified instances |
CEN | confusion entropy of a confusion matrix |
CMW | cost matrix weights |
COD | chemical oxygen demand |
CSC | cost-sensitive classifier |
CSO | combined sewer overflow |
CTs | classification trees |
DO | Dissolved Oxygen |
DTM | Decision tree model |
FC | Fecal coliforms |
fcv | folds cross validation |
FCR | Fecal coliform regulation |
FN | false negative |
FP | false positive |
ISO | International Organization for Standardization |
k-fold | three, five or ten-fold |
m a.s.l. | meters above sea level |
MPN.100 mL−1 | most probable number per 100 mL |
PCF | Pruning confidence factor |
TN | true negative |
TP | true positive |
TS | tolerant score |
SWO | surface water outfalls |
Weka | Waikato Environment for Knowledge Analysis |
Appendix A
Parameter | Analysis Method | Units | Mean Value ± Standard Deviation | Min Value | Max Value | Median Value |
---|---|---|---|---|---|---|
Mean depth | m | 0.33 ± 0.30 | 0.04 | 1.63 | 0.26 | |
Flow velocity | m·s−1 | 0.59 ± 0.44 | 0.07 | 1.84 | 0.47 | |
Temperature | °C | 11.50 ± 1.10 | 9.10 | 13.40 | 11.90 | |
pH | SM 4500 H B | 7.58 ± 0.45 | 6.33 | 8.36 | 7.70 | |
Dissolved oxygen (DO) | SM 4500 0-G | mg·L−1 | 9.08 ± 1.47 | 6.65 | 12.60 | 9.54 |
Total solids | SM 2540 B | mg·L−1 | 89.09 ± 51.65 | 19.00 | 190.00 | 74.00 |
Turbidity | SM2130B | NTU | 7.68 ± 11.11 | 0.51 | 48.20 | 3.66 |
True color | SM2120 C | HU | 14.39 ± 8.52 | 0.00 | 40.00 | 14.00 |
Specific conductivity | SM 2510 B | μS·cm−1 | 91.64 ± 44.12 | 13.20 | 238.00 | 82.30 |
Phosphates | SM 4500-P-E | mg P·L−1 | 0.07 ± 0.12 | 0.03 | 0.55 | 0.03 |
Nitrate + Nitrite | SM 4500 N03 E | mg N·L−1 | 0.05 ± 0.12 | BDL | 0.70 | 0.02 |
Ammonia nitrate | SM 4500 NH3 C | mg·L−1 | 0.02 ± 0.07 | 0.00 | 0.40 | 0.00 |
Organic nitrogen | SM 4500 Norg B | mg N·L−1 | 0.55 ± 1.21 | 0.00 | 6.55 | 0.14 |
Biochemical oxygen demand 5 day (BOD5) | SM 5210-B | mg·L−1 | 1.06 ± 2.35 | BDL | 13.00 | 0.40 |
Chemical oxygen demand (COD) | SM 5220-C | mg·L−1 | 9.94 ± 8.39 | 2.00 | 46.00 | 8.00 |
Fecal coliforms | SM 9221 E | MPN.100 mL−1 | 3.60 × 104 ± 1.02 × 105 | 4.5 × 100 | 5.4 × 105 | 7.9 × 101 |
Total coliforms | SM 9221 E | MPN.100 mL−1 | 4.1 × 104 ± 1.1 × 105 | 7.8 × 100 | 5.4 × 105 | 3.3x102 |
Model No. | FCR a | Dataset Macroinvertebrates | Model Settings | |||||
---|---|---|---|---|---|---|---|---|
J4.8 | PCF b | CMW c | ||||||
TP d | FN e | FP f | TN g | |||||
* 1hapi1j | Recreational | Presence/absence | 3, 5 and 10 fcv k | 0.25 | ||||
* 1ap2 | Recreational | Presence/absence | 3, 5 and 10 fcv | 0.10 | ||||
1ap3 | Recreational | Presence/absence | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 2 | 0 |
1ap4 | Recreational | Presence/absence | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 3 | 0 |
1ap5 | Recreational | Presence/absence | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 5 | 0 |
1ap6 | Recreational | Presence/absence | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 6 | 0 |
1ap7 | Recreational | Presence/absence | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 7 | 0 |
1ap8 | Recreational | Presence/absence | 3, 5 and 10 fcv | 0.10 | 0 | 1 | 10 | 0 |
* 1a1 | Recreational | Abundance | 3, 5, 10 fcv and 66%tr | 0.25 | ||||
* 1a2 | Recreational | Abundance | 3, 5, 10 fcv and 66%tr | 0.10 | ||||
1a3 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 1 | 0 |
1a4 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 2 | 0 |
1a5 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 3 | 0 |
1a6 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 4 | 0 |
1a7 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 5 | 0 |
1a8 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 7 | 0 |
1a9 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 8 | 0 |
1a10 | Recreational | Abundance | 3, 5 and 10 fcv | 0.1 | 0 | 1 | 8 | 0 |
1a11 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 9 | 0 |
1a12 | Recreational | Abundance | 3, 5 and 10 fcv | 0.1 | 0 | 1 | 9 | 0 |
1a13 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 10 | 0 |
1a14 | Recreational | Abundance | 3, 5 and 10 fcv | 0.1 | 0 | 1 | 10 | 0 |
1a15 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 11 | 0 |
1a16 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 12 | 0 |
1a17 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 15 | 0 |
1a18 | Recreational | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 18 | 0 |
* 2ap1 | Agriculture l | Presence/absence | 3, 5 and 10 fcv | 0.25 | ||||
* 2ap2 | Agriculture | Presence/absence | 3, 5 and 10 fcv | 0.10 | ||||
2ap3 | Agriculture | Presence/absence | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 2 | 0 |
2ap4 | Agriculture | Presence/absence | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 3 | 0 |
2ap5 | Agriculture | Presence/absence | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 5 | 0 |
* 2a1 | Agriculture | Abundance | 3, 5, 10 fcv and 66%tr | 0.25 | ||||
* 2a2 | Agriculture | Abundance | 3, 5, 10 fcv and 66%tr | 0.10 | ||||
2a3 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 1 | 0 |
2a4 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 2 | 0 |
2a5 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 3 | 0 |
2a6 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 4 | 0 |
2a7 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 5 | 0 |
2a8 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 8 | 0 |
2a9 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 10 | 0 |
2a10 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 12 | 0 |
2a11 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 15 | 0 |
2a12 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 17 | 0 |
2a13 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 18 | 0 |
2a14 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 20 | 0 |
2a15 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 21 | 0 |
2a16 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 22 | 0 |
2a17 | Agriculture | Abundance | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 25 | 0 |
Model No. | FCR a | Model Outcomes | |||
---|---|---|---|---|---|
CCI b (%) | Kappa Statistics | Number of Leaves | CEN c | ||
Mean ± sd | Mean ± sd | Mean ± sd | |||
* 1eapf1g | Recreational d | 40.40 ± 3.50 | −0.21 ± 0.09 | 6 | 1.03 ± 0.01 |
* 1ap2 | Recreational | 48.48 ± 3.03 | −0.09 ± 0.07 | 2 | 1.01 ± 0.02 |
1apf3g | Recreational | 42.42 ± 6.06 | −0.12 ± 0.13 | 3 | 0.99 ± 0.04 |
1ap4 | Recreational | 41.41 ± 7.63 | −0.11 ± 0.17 | 4 | 0.95 ± 0.11 |
1ap5 | Recreational | 43.43 ± 1.75 | −0.01 ± 0.02 | 4 | 0.80 ± 0.05 |
1ap6 | Recreational | 42.42 ± 3.03 | −0.03 ± 0.05 | 4 | 0.80 ± 0.06 |
1ap7 | Recreational | 42.42 ± 3.03 | −0.02 ± 0.05 | 1 | 0.77 ± 0.06 |
1ap8 | Recreational | 42.42 ± 0.00 | −0.01 ± 0.01 | 1 | 0.60 ± 0.12 |
* 1a1 | Recreational | 70.45 ± 1.50 | 0.39 ± 0.05 | 5 | 0.81 ± 0.03 |
* 1a2 | Recreational | 70.45 ± 1.50 | 0.39 ± 0.05 | 4 | 0.81 ± 0.03 |
1a3 | Recreational | 69.70 ± 0.00 | 0.37 ± 0.00 | 5 | 0.83 ± 0.00 |
1a4 | Recreational | 72.73 ± 6.05 | 0.44 ± 0.13 | 4 | 0.78 ± 0.09 |
1a5 | Recreational | 77.77 ± 4.64 | 0.56 ± 0.09 | 3 | 0.65 ± 0.08 |
1a6 | Recreational | 76.78 ± 9.24 | 0.55 ± 0.17 | 3 | 0.65 ± 0.12 |
1a7 | Recreational | 77.73 ± 12.24 | 0.56 ± 0.23 | 3 | 0.63 ± 0.17 |
1a8 | Recreational | 78.77 ± 8.00 | 0.58 ± 0.15 | 3 | 0.61 ± 0.11 |
1a9 | Recreational | 79.80 ± 1.73 | 0.60 ± 0.04 | 3 | 0.63 ± 0.05 |
1a10 | Recreational | 79.81 ± 1.74 | 0.60 ± 0.04 | 3 | 0.63 ± 0.05 |
1a11 | Recreational | 70.69 ± 7.64 | 0.44 ± 0.14 | 3 | 0.70 ± 0.09 |
1a12 | Recreational | 70.69 ± 7.64 | 0.44 ± 0.14 | 3 | 0.70 ± 0.09 |
1a13 | Recreational | 66.68 ± 10.92 | 0.36 ± 0.21 | 3 | 0.73 ± 0.15 |
1a14 | Recreational | 63.63 ± 12.13 | 0.32 ± 0.20 | 3 | 0.68 ± 0.05 |
1a15 | Recreational | 62.62 ± 10.65 | 0.30 ± 0.17 | 3 | 0.71 ± 0.02 |
1a16 | Recreational | 58.57 ± 6.30 | 0.24 ± 0.10 | 3 | 0.70 ± 0.02 |
1a17 | Recreational | 47.47 ± 8.78 | −0.01 ± 0.01 | 3 | 0.60 ± 0.12 |
1a18 | Recreational | 42.42 ± 0.00 | 0.00 ± 0.00 | 1 | 0.53 ± 0.00 |
* 2ap1 | Agriculture | 66.67 ± 0.00 | 0.17 ± 0.03 | 4 | 0.88 ± 0.01 |
* 2ap2 | Agriculture | 69.70 ± 3.03 | 0.24 ± 0.00 | 3 | 0.84 ± 0.01 |
2ap3 | Agriculture | 75.76 ± 5.25 | 0.47 ± 0.13 | 4 | 0.67 ± 0.15 |
2ap4 | Agriculture | 73.74 ± 6.31 | 0.44 ± 0.11 | 3 | 0.70 ± 0.06 |
2ap5 | Agriculture | 71.72 ± 9.26 | 0.42 ± 0.18 | 3 | 0.66 ± 0.14 |
* 2a1 | Agriculture | 86.35 ± 7.99 | 0.68 ± 0.19 | 3 | 0.52 ± 0.20 |
* 2a2 | Agriculture | 77.25 ± 16.87 | 0.43 ± 0.44 | 3 | 0.67 ± 0.26 |
2a3 | Agriculture | 84.86 ± 9.07 | 0.64 ± 0.21 | 3 | 0.57 ± 0.21 |
2a4 | Agriculture | 89.88 ± 4.61 | 0.74 ± 0.13 | 3 | 0.47 ± 0.13 |
2a5 | Agriculture | 86.86 ± 7.61 | 0.68 ± 0.18 | 3 | 0.54 ± 0.19 |
2a6 | Agriculture | 86.86 ± 7.61 | 0.68 ± 0.18 | 3 | 0.54 ± 0.19 |
2a7 | Agriculture | 85.86 ± 6.31 | 0.66 ± 0.16 | 3 | 0.57 ± 0.14 |
2a8 | Agriculture | 80.83 ± 9.76 | 0.57 ± 0.21 | 3 | 0.63 ± 0.14 |
2a9 | Agriculture | 80.81 ± 9.74 | 0.57 ± 0.21 | 3 | 0.63 ± 0.14 |
2a10 | Agriculture | 80.81 ± 14.95 | 0.58 ± 0.29 | 3 | 0.60 ± 0.18 |
2a11 | Agriculture | 72.74 ± 6.05 | 0.42 ± 0.13 | 3 | 0.70 ± 0.09 |
2a12 | Agriculture | 60.60 ± 9.09 | 0.26 ± 0.12 | 3 | 0.71 ± 0.08 |
2a13 | Agriculture | 63.63 ± 10.51 | 0.33 ± 0.13 | 3 | 0.66 ± 0.00 |
2a14 | Agriculture | 57.56 ± 5.26 | 0.25 ± 0.06 | 2 | 0.67 ± 0.00 |
2a15 | Agriculture | 58.57 ± 7.01 | 0.26 ± 0.09 | 2 | 0.67 ± 0.00 |
2a16 | Agriculture | 47.48 ± 19.70 | 0.17 ± 0.18 | 2 | 0.60 ± 0.12 |
2a17 | Agriculture | 40.39 ± 13.64 | 0.09 ± 0.11 | 2 | 0.59 ± 0.11 |
(a) Recreational Fecal Coliform Regulation | |
Model: 1a4 | Models: 1a5, 1a6, 1a7 |
Baetidae <= 3: A Baetidae > 3 | Perlidae = 0: B | Perlidae > 0 | | Chironomidae <= 3: B | | Chironomidae > 3: A | Baetidae <= 3 | Scirtidae = 1: A | Scirtidae > 1: B Baetidae > 3: B |
Model: 1a8 | Models: 1a9, 1a10, 1a11, 1a12 |
Baetidae <= 3 | Elminthidae <= 2: A | Elminthidae > 2: B Baetidae > 3: B | Baetidae <= 3 | Scirtidae <= 4: A | Scirtidae > 4: B Baetidae > 3: B |
(b) Agriculture fecal coliform regulation | |
Model: 2ap3 | Models: 2ap4, 2ap5 |
Perlidae = presence: A Perlidae = absence | Baetidae = presence | | Leptophlebiidae = presence: A | | Leptophlebiidae = absence: B | Baetidae = absence: A | Perlidae = presence: A Perlidae = absence | Baetidae = presence: B | Baetidae = absence: A |
Models: 2a1, 2a2, 2a3, 2a4, 2a5, 2a6 | Models: 2a7, 2a8, 2a9, 2a10, 2a11 |
Baetidae <= 4: A Baetidae > 4 | Perlidae = 0: B | Perlidae > 0: A | Perlidae = 0 | Baetidae <= 4: A | Baetidae > 4: B Perlidae > 0: A |
A: fulfillment; B: non-fulfillment |
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Regulations | Water Used for | Fecal Coliforms Limited Value MPN.100 mL−1 |
---|---|---|
Recreational | Recreational with primary contact | ≤200 |
Agriculture | Agriculture and livestock | ≤1000 |
Raw water | Raw water previous to non-conventional treatment a | ≤2000 |
Sampled Points in the Machangara River | Points with the Same Taxa | |||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Site | Sensitivity Score ↓ | 3 | 4 | 13 | 15 | 19 | 20 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 | 37 | 38 | 39 | 40 | 41 | 42 | 43 | 44 | 45 | 46 | 47 | 49 | 50 | 51 | ||
Taxa | ||||||||||||||||||||||||||||||||||||
Biological Water Quality BMWP-Col → | 69 | 57 | 71 | 59 | 35 | 48 | 58 | 82 | 55 | 74 | 63 | 46 | 40 | 29 | 19 | 64 | 55 | 39 | 49 | 33 | 59 | 38 | 34 | 11 | 8 | 67 | 37 | 57 | 82 | 56 | 93 | 29 | 11 | |||
Land use category → | 5 | 5 | 5 | 3 | 5 | 4 | 3 | 5 | 6 | 3 | 6 | 6 | 3 | 6 | 3 | 6 | 2 | 2 | 2 | 2 | 2 | 1 | 1 | 1 | 1 | 5 | 5 | 5 | 3 | 6 | 5 | 3 | 5 | |||
Tubificidae | 1 | 38 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 28 | ||||||
Chironomidae | 2 | 38 | 4 | 1 | 56 | 9 | 4 | 6 | 2 | 4 | 4 | 2 | 1 | 15 | 2 | 40 | 2 | 6 | 9 | 43 | 15 | 8 | 2 | 3 | 2 | 23 | 10 | 4 | 27 | |||||||
Dytiscidae | 3 | 1 | 1 | |||||||||||||||||||||||||||||||||
Physidae | 3 | 14 | 1 | 1 | 3 | |||||||||||||||||||||||||||||||
Glossiphoniidae | 3 | 1 | 1 | 1 | 1 | 3 | 1 | 6 | ||||||||||||||||||||||||||||
Empididae | 4 | 1 | 1 | |||||||||||||||||||||||||||||||||
Psychodidae | 4 | 1 | 1 | |||||||||||||||||||||||||||||||||
Hydrophilidae | 4 | 1 | 1 | |||||||||||||||||||||||||||||||||
Planorbidae | 4 | 1 | 2 | 2 | ||||||||||||||||||||||||||||||||
Dixidae | 4 | 1 | 1 | 2 | ||||||||||||||||||||||||||||||||
Limoniidae | 4 | 3 | 5 | 3 | 3 | |||||||||||||||||||||||||||||||
Tabanidae | 4 | 1 | 1 | 1 | 3 | |||||||||||||||||||||||||||||||
Limnaeidae | 4 | 1 | 1 | 2 | 2 | 4 | ||||||||||||||||||||||||||||||
Ceratopogonidae | 4 | 1 | 1 | 1 | 2 | 1 | 1 | 6 | ||||||||||||||||||||||||||||
Planariidae | 4 | 6 | 1 | 14 | 2 | 1 | 6 | 1 | 1 | 8 | ||||||||||||||||||||||||||
Staphylinidae | 5 | 2 | 1 | |||||||||||||||||||||||||||||||||
Hydropsychidae | 5 | 1 | 1 | 1 | 3 | |||||||||||||||||||||||||||||||
Muscidae | 5 | 1 | 2 | 1 | 5 | 5 | 2 | 3 | 2 | 3 | 1 | 10 | ||||||||||||||||||||||||
Tipulidae | 5 | 1 | 6 | 4 | 5 | 2 | 1 | 3 | 1 | 1 | 1 | 3 | 1 | 1 | 1 | 14 | ||||||||||||||||||||
Baetidae | 5 | 3 | 13 | 37 | 2 | 43 | 16 | 2 | 38 | 3 | 2 | 1 | 1 | 3 | 53 | 7 | 189 | 45 | 108 | 151 | 31 | 17 | 19 | 1 | 3 | 4 | 30 | 140 | 27 | |||||||
Scirtidae | 6 | 132 | 1 | 1 | 2 | 3 | 1 | 1 | 1 | 1 | 4 | 4 | 2 | 12 | ||||||||||||||||||||||
Elminthidae | 6 | 2 | 2 | 3 | 16 | 2 | 3 | 1 | 1 | 5 | 1 | 2 | 4 | 1 | 1 | 4 | 1 | 1 | 17 | |||||||||||||||||
Simuliidae | 6 | 18 | 3 | 3 | 13 | 1 | 21 | 2 | 31 | 26 | 19 | 45 | 8 | 18 | 5 | 14 | 51 | 22 | 10 | 1 | 14 | 2 | 1 | 18 | 1 | 5 | 3 | 15 | 27 | |||||||
Aeshnidae | 7 | 1 | 1 | 2 | ||||||||||||||||||||||||||||||||
Tricorythidae | 7 | 25 | 7 | 6 | 2 | 3 | 2 | 8 | 1 | 1 | 14 | 9 | 1 | 2 | 13 | |||||||||||||||||||||
Hyalellidae | 7 | 88 | 4 | 6 | 30 | 7 | 10 | 1 | 16 | 3 | 2 | 3 | 2 | 1 | 1 | 6 | 2 | 2 | 2 | 116 | 61 | 38 | 5 | 22 | ||||||||||||
Leptoceridae | 8 | 1 | 1 | 1 | 1 | 1 | 2 | 6 | ||||||||||||||||||||||||||||
Leptophlebiidae | 8 | 10 | 4 | 1 | 2 | 6 | 5 | 1 | 2 | 56 | 9 | |||||||||||||||||||||||||
Hydrobiosidae | 8 | 2 | 3 | 6 | 4 | 2 | 1 | 9 | 1 | 1 | 14 | 2 | 2 | 1 | 1 | 1 | 1 | 6 | 17 | |||||||||||||||||
Helicopsychidae | 9 | 1 | 1 | |||||||||||||||||||||||||||||||||
Ptilodactylidae | 9 | 1 | 1 | 2 | ||||||||||||||||||||||||||||||||
Odontoceridae | 9 | 1 | 1 | 2 | ||||||||||||||||||||||||||||||||
Hydracarina | 10 | 1 | 1 | 2 | ||||||||||||||||||||||||||||||||
Blepharoceridae | 10 | 1 | 1 | 2 | ||||||||||||||||||||||||||||||||
Gripopterygidae | 10 | 1 | 1 | 2 | ||||||||||||||||||||||||||||||||
Calamoceratidae | 10 | 2 | 1 | 1 | 1 | 4 | ||||||||||||||||||||||||||||||
Perlidae | 10 | 1 | 7 | 6 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 1 | 9 | 12 | ||||||||||||||||||||||
Taxa richness → | 12 | 10 | 11 | 10 | 8 | 10 | 9 | 14 | 10 | 13 | 10 | 8 | 7 | 6 | 4 | 12 | 12 | 7 | 11 | 8 | 11 | 7 | 7 | 4 | 3 | 12 | 7 | 11 | 14 | 11 | 14 | 7 | 3 | |||
Land use category → | 1 | Urban area | 2 | Suburban area, pastures and crops | 3 | Pastures | 4 | Bare soil | 5 | Native vegetation | 6 | Forest vegetation | ||||||||||||||||||||||||
Biological water quality classification → | Very good | Good | Moderate | Deficient | Bad | |||||||||||||||||||||||||||||||
Taxa analyzed to construct the models → | Included | Not included | p = Taxa present |
Model No. | FCR a | Model Settings | Model Outcomes | ||||
---|---|---|---|---|---|---|---|
CCI c (%) | Kappa Statistics | Number of Leaves | CEN d | ||||
J4.8 | PCF b | Mean ± sd | Mean ± sd | Mean ± sd | |||
1eapf1g | Recreational h | 3, 5 and 10 fcv i | 0.25 | 40.40 ± 3.50 | −0.21 ± 0.09 | 6 | 1.03 ± 0.01 |
1ap2 | Recreational | 3, 5 and 10 fcv | 0.10 | 48.48 ± 3.03 | −0.09 ± 0.07 | 2 | 1.01 ± 0.02 |
1a1 | Recreational | 3, 5, 10 fcv and 66%tr | 0.25 | 70.45 ± 1.50 | 0.39 ± 0.05 | 5 | 0.81 ± 0.03 |
1a2 | Recreational | 3, 5, 10 fcv and 66%tr | 0.10 | 70.45 ± 1.50 | 0.39 ± 0.05 | 4 | 0.81 ± 0.03 |
2ap1 | Agriculture | 3, 5 and 10 fcv | 0.25 | 66.67 ± 0.00 | 0.17 ± 0.03 | 4 | 0.88 ± 0.01 |
2ap2 | Agriculture j | 3, 5 and 10 fcv | 0.10 | 69.70 ± 3.03 | 0.24 ± 0.00 | 3 | 0.84 ± 0.01 |
2a1 | Agriculture | 3, 5, 10 fcv and 66%tr | 0.25 | 86.35 ± 7.99 | 0.68 ± 0.19 | 3 | 0.52 ± 0.20 |
2a2 | Agriculture | 3, 5, 10 fcv and 66%tr | 0.10 | 77.25 ± 16.87 | 0.43 ± 0.44 | 3 | 0.67 ± 0.26 |
Model No. | Model Settings | Model Outcomes | |||||||
---|---|---|---|---|---|---|---|---|---|
J4.8 | PCF a | CMW b | CCI g (%) | Kappa Statistics | CEN h | ||||
TP c | FN d | FP e | TN f | Mean ± sd | Mean ± sd | Mean ± sd | |||
1iaj-4k | 3, 5 and 10 fcv l | 0.25 | 0 | 1 | 2 | 0 | 72.73 ± 6.05 | 0.44 ± 0.13 | 0.78 ± 0.09 |
1a5 to 1a7 | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 3 to 5 | 0 | 77.43 ± 8.03 | 0.56 ± 0.15 | 0.64 ± 0.11 |
1a8 | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 7 | 0 | 78.77 ± 8.00 | 0.58 ± 0.15 | 0.61 ± 0.11 |
1a9 to 1a12 | 3, 5 and 10 fcv | 0.1 and 0.25 | 0 | 1 | 8 and 9 | 0 | 74.93 ± 6.93 | 0.51 ± 0.13 | 0.67 ± 0.07 |
2ap3 | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 2 | 0 | 75.76 ± 5.25 | 0.47 ± 0.13 | 0.67 ± 0.15 |
2ap4 and 2ap5 | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 3 and 5 | 0 | 72.73 ± 7.17 | 0.43 ± 0.13 | 0.68 ± 0.10 |
2a3 to 2a6 | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 1 to 4 | 0 | 87.12 ± 6.59 | 0.69 ± 0.16 | 0.53 ± 0.16 |
2a7 to 2a11 | 3, 5 and 10 fcv | 0.25 | 0 | 1 | 5 to 15 | 0 | 80.21 ± 9.44 | 0.56 ± 0.19 | 0.63 ± 0.13 |
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Jerves-Cobo, R.; Córdova-Vela, G.; Iñiguez-Vela, X.; Díaz-Granda, C.; Van Echelpoel, W.; Cisneros, F.; Nopens, I.; Goethals, P.L.M. Model-Based Analysis of the Potential of Macroinvertebrates as Indicators for Microbial Pathogens in Rivers. Water 2018, 10, 375. https://doi.org/10.3390/w10040375
Jerves-Cobo R, Córdova-Vela G, Iñiguez-Vela X, Díaz-Granda C, Van Echelpoel W, Cisneros F, Nopens I, Goethals PLM. Model-Based Analysis of the Potential of Macroinvertebrates as Indicators for Microbial Pathogens in Rivers. Water. 2018; 10(4):375. https://doi.org/10.3390/w10040375
Chicago/Turabian StyleJerves-Cobo, Rubén, Gonzalo Córdova-Vela, Xavier Iñiguez-Vela, Catalina Díaz-Granda, Wout Van Echelpoel, Felipe Cisneros, Ingmar Nopens, and Peter L. M. Goethals. 2018. "Model-Based Analysis of the Potential of Macroinvertebrates as Indicators for Microbial Pathogens in Rivers" Water 10, no. 4: 375. https://doi.org/10.3390/w10040375