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Comparison of sampling methods in low-gradient streams
Raphael Mazor1 Andy Rehn2 Ken Schiff1
1Southern California Coastal Water Research Project, Westminster, CA2Aquatic Bioassessment Laboratory, Rancho Cordova, CA
November 29, 2006
Intro
Initiation of regional biomonitoring program: Integrating data from SWAMP and NPDES programs.
Sampling methods and assessment tools (SoCal-IBI) have been proposed.
Do these tools work in low-gradient streams?
Low-gradient streams are common in southern California, and their health is of great public interest.
Questions
1. Does the So-Cal IBI function well in low-gradient streams?
2. Which sampling methods are the most precise?
3. Do different sampling methods give similar results?
Background
Sampling methods
CSBP: Targets richest habitats (riffles, margins)
San Gabriel Arroyo Seco Arroyo Seco
Background
Sampling methods
CSBP: Targets richest habitats (riffles, margins)
?
San Gabriel Arroyo Seco Arroyo Seco
? ?
Background
Sampling methods
MH: Multi-habitat (25%, 50%, and 75% of channel width)
San Gabriel Arroyo Seco Arroyo Seco
Background
Sampling methods
MH: Multi-habitat (25%, 50%, and 75% of channel width)
San Gabriel Arroyo Seco Arroyo Seco
Background
Sampling methods
MCM: Margin-Center-Margin (also gets richest habitats)
San Gabriel Arroyo Seco Arroyo Seco
Background
Sampling methods
MCM: Margin-Center-Margin (also gets richest habitats)
San Gabriel Arroyo Seco Arroyo Seco
Methods
Low-gradient streams sampled in southern California:
-Santa Clara River (4 sites)
-Rio Hondo
-Santa Margarita River (2 sites)
-Santa Ana River
-Las Virgenes Creek
-Agua Hedionda
Methods
Each method tested in each river, often sampled in triplicate.
500-count samples were sorted and identified.
Metrics and IBI scores were calculated for each sample.
Results
Number of samples:
River CSBP MCM MHSanta Clara 5 5 6Agua Hedionda 2 3 3Rio Hondo 3 3 3Santa Margarita C 2 3 3Santa Margarita D 2 3 3Santa Ana 3 3 3Las Virgenes 2 3 3TOTAL 19 23 24
Results
CSBP MCM MHRichness 18.7 19.9 16.3Individuals per sample* 453 481 377
*p < 0.05
Of 66 samples total, 16 had < 450 organisms, of which 10 were MHsamples
Sampling method does NOT affect richness, but it may result in small samples.
Results
Very good
Good
Fair
Poor
Very poor
Sant
a C
lara
Riv
er
Agu
a H
edio
nda
Cre
ek
Rio
Hon
do
Sant
a M
arga
rita
C
Sant
a M
arga
rita
D
Sant
a A
na R
iver
Las
Virg
enes
Cre
ek
SC-IB
I
0
10
20
30
40
50
60
70
80
90
100
Results
Very good
Good
Fair
Poor
Very poor
Sant
a C
lara
Riv
er
Agu
a H
edio
nda
Cre
ek
Rio
Hon
do
Sant
a M
arga
rita
C
Sant
a M
arga
rita
D
Sant
a A
na R
iver
Las
Virg
enes
Cre
ek
SC-IB
I
0
10
20
30
40
50
60
70
80
90
100CSBP MCM MH
Results
SS d.f. F p
Method 39.9 2 0.6 0.575River 2641.3 5 14.8 <0.001Interaction 380.2 10 1.1 0.408Residuals 1426.1 40
Exclude Santa Margarita C
Two-way ANOVA on IBI Score
Method does NOT affect IBI score at most sites
CSBP
0 5 10 15 20 25 30 35
MC
M
0
5
10
15
20
25
30
35
CSBP
0 5 10 15 20 25 30 35M
H0
5
10
15
20
25
30
35
SoCal-IBI
R2 = 0.52 R2 = 0.58Slope = 0.62 Slope = 0.77
Results
Good relationship between all methods.
Results
CSBP: High variability at low-scoring sites.
Other methods: High variability at all scores.
CSBP
IBI
0 5 10 15 20 25 30 35
SD
0
2
4
6
8
10
MCM
IBI
0 5 10 15 20 25 30 350
2
4
6
8
10
MH
IBI
0 5 10 15 20 25 30 350
2
4
6
8
10
CSBP
0 2 4 6 8 10
MC
M
0
2
4
6
8
10
CSBP
0 2 4 6 8 10
MH
0
2
4
6
8
10
EPT Taxa
R2 = 0.76
Slope = 0.56
R2 = 0.43
Slope = 0.38
Results
Better relationship between CSBP and MCM than CSBP and MH.
CSBP
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7
MC
M
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
CSBP
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7M
H0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
% Non-insect
R2 = 0.73
Slope = 0.60
R2 = 0.96
Slope = 0.85
Results
Better relationship between CSBP and MH than CSBP and MCM.
Results - Precision
Comparisons among streamsTypical questions:
Are streams in San Diego of fair or better condition?
Are streams draining urban areas worse than streams draining open space?
Among-stream variability (SD of site averages):
CSBP 6.6
MCM 6.1
MH 4.2
MH << MCM < CSBP
Results - Precision
Comparisons within streamsTypical questions:
Is this site in better condition following restoration?
Is this site above a biocriterion threshold?
Within-stream variability (average within-site SD):
CSBP 3.8
MCM 3.9
MH 4.1
All methods more-or-less the same.
NMDS 1 (20%)-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
NM
DS
2 (2
9%)
-1.0
-0.5
0.0
0.5
1.0
1.5
Stress = 10.2
Santa Clara
Santa Margarita D
Rio Hondo
AguaHedionda
Las Virgenes
SantaMargarita C
Santa Ana
Geography strongly influences community structure.
NMDS 1 (20%)-2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 1.5
NM
DS
2 (2
9%)
-1.0
-0.5
0.0
0.5
1.0
1.5
CSBP MCM MH
Stress = 10.2
But sampling method does not.
Conclusions
1. Does the So-Cal IBI function well in low-gradient streams?
All streams are in poor condition.
True status of low-gradient streams?
What about “reference” streams?
Conclusions
2. Which sampling methods are the most precise?
All methods similar for within-stream comparisons.
MH best for among-stream comparisons.
But: low power for most applications.
Conclusions
3. Do different sampling methods give similar results?
Geography, not sampling method, has the strongest influence on community structure and IBI scores.
Correlations between methods are good.
Conclusions
Next steps:
“Better” reference sites (Central Coast).
Test other assessment techniques (e.g., RIVPACS).
Examine physical habitat data. What drives between-site differences?
End