Site Classification for Re-calibration of the
Alabama Index of Stream Macroinvertebrate Condition
Ben Jessup and Jen StampTetra Tech, Inc.
SWPBANovember 14, 2012
Lake Guntersville State Park
Why Classify?• To allow comparable judgments• Apples and oranges• Level playing field• Natural conditions
Why Classify in Alabama?
• The index of stream macroinvertebrate condition should be recalibrated
• Initial index development included samples from a limited portion of the state
• New samples have been collected from all areas of the state
• Site classification is the first step in index recalibration
Process for Site Classification
• Data compilation– Disturbance variables– Classification variables– Benthic samples and metrics
• Reference site identification– Based on the HDG– Confirmed with site data– Verified by ADEM
• Classification Analyses
Reference Site Identification
• Primary Reference Indication– HDG categories 1, 2, and 3 = Reference– HDG categories 6, 7, and 8 = Stressed
• Site data confirmationEnvironmental Variable Reference Near Ref Stressed
Specific Conductance <100.0 <200.0 >300.0Atrazine <0.06 <0.08 >0.10Chemical/Biological Oxygen Demand (CBOD5) <1.8 <2.0 >2.2Fecal Coliform (BacT) <500 <750 >1000Chlorophyll a (Chl_a) <3.0 <4.0 >5.0Total Dissolved Solids (TDS) <75 <120 >150Total Phosphorus (TP) <0.06 <0.13 >0.20Nitrate + Nitrite (NO2NO3) <0.10 <0.25 >0.40Habitat Score >67 >55 <55
Calibration dataset
• 130 reference sites• 113 stressed sites
• Benthic samples • Collected April-August from
1993-present• One sample per site used in
calibration
45
65
67
6871
75
Classification Analysis
• Find the environmental factors that affect biology
• Mapping• PCA of classification variables
– All sites • NMS Ordination of sites by taxa
– Reference only– Operational Taxonomic Units (OTU)
• Cluster analysis and DFA• Comparison of metric distributions
– Box plots and bi-plots
Level 4 Ecoregions
• Fall Line• Special considerations
– 65a & b – Blackland Prairies,
Flatwoods, & Margins– 68 c and d– Plateau Escarpment &
Southern Table Plateaus
PCA
• Classification variables only• All sites
Strongest drivers on each axis
Factor 1, 22%Temperature, Latitude
Factor 2, 16%Area, Gradient
Factor 4, 9%Precipitation, Day of year
Avg Temp -0.88% Cobb.,Bould. 0.64Elevation 0.84Latitude 0.86
Gradient -0.68SlopeNHD -0.59Discharge 0.56
Width 0.66Area 0.82
Factor 3, 13%Discharge, IonsDisch:Area -0.68Discharge -0.58Hardness 0.63Alkalinity 0.64
Precipitation -0.53Day of year 0.52
4 5 A4 5 B
4 5 D6 5 A
6 5 B6 5 D
6 5 F6 5 G
6 5 I6 5 J
6 5 P6 5 Q
6 7 F6 7 G
6 7 H6 8 B
6 8 C6 8 D
6 8 E6 8 F
7 1 F7 1 G
7 1 H7 1 J
7 5 I
-3
-2
-1
0
1
2
3
PC
AF
act
1
PCA F1 by ecoregion
45 65 67
68 71
75Fact
or 1
(Tem
pera
ture
, Lati
tude
)
PCA F2 by ecoregion
4 5 A4 5 B
4 5 D6 5 A
6 5 B6 5 D
6 5 F6 5 G
6 5 I6 5 J
6 5 P6 5 Q
6 7 F6 7 G
6 7 H6 8 B
6 8 C6 8 D
6 8 E6 8 F
7 1 F7 1 G
7 1 H7 1 J
7 5 I
E CO RE G IO N_ L 4
-3
-2
-1
0
1
2
3
4
PC
AF
act
2Fa
ctor
2 (A
rea,
Gra
dien
t)
45 65 67 6871
75
PCA F4 by ecoregion
4 5 A4 5 B
4 5 D6 5 A
6 5 B6 5 D
6 5 F6 5 G
6 5 I6 5 J
6 5 P6 5 Q
6 7 F6 7 G
6 7 H6 8 B
6 8 C6 8 D
6 8 E6 8 F
7 1 F7 1 G
7 1 H7 1 J
7 5 I
E CO RE G IO N_ L 4
-4
-3
-2
-1
0
1
2
3
4
PC
AF
act
4Fa
ctor
4 (P
reci
pita
tion,
Day
of y
ear)
45 65 67 6871
75
NMS
NMS_130PA
Axis 1
Axi
s 2
ECOREGION
45 Piedmont 65 S.E. Plains 67 Rdg + Val 68 S.W. Apps71 Int. Plat.
NMS_130PA
Axis 1
Axi
s 2
ECOREGION
45 Piedmont 65 S.E. Plains 67 Rdg + Val 68 S.W. Apps71 Int. Plat. • Standardized
taxonomy• Presence/absence
NMS_130PA
Axis 1
Axi
s 2
0
200
400
600Elev_m
Axis 1r = .378 tau = .291
Axis 2r = -.442 tau = -.346
0 200 400 600
FallLine_Code
12
NMS_130PA
Axis 1
Axi
s 2
FallLine
Above Below
NMS_130PA
Axis 1
Axi
s 2
ElevGrp
<150 >150
NMS of samples by taxaNMS_130PA
Axis 1
Axi
s 2
FallLine_Code
12
NMS_130PA
Axis 1
Axi
s 2
FallLine
Above Below
Icthyoregion FL
Tennessee Valley Above
Ridge and Valley/Piedmont Above
Plateau Above
Hills and Coastal Terraces Below
Southern Plains Below
Blackland April
O'Neil and Shepard, 2007
Cluster AnalysisNMS_130PA
Axis 1
Axi
s 2
PA-5FB3
1216
NMS_130PA
Axis 1
Axi
s 2
PA-5FB3
1216
NMS_130PA
Axis 1
Axi
s 3
PA-5FB3
1216
NMS_130PA
Axis 1
Axi
s 2
4grps
12316
Discriminant Function Analysis (DFA)
F-remove p-val
PC_CobbBould 7.72864 0.00
tmax14_C 11.79340 0.00
Elev_m 6.91748 0.00
LONGITUDE 4.70966 0.004
%Correct 1 2 3 16
1 86.8 46 2 2 3
2 11.8 9 2 0 6
3 33.3 3 0 4 5
16 79.2 9 0 1 38
Total 69.2 67 4 7 52
Four clusters
F-remove p-val
PC_CobbleBoulder 17.1 0.00
LONGITUDE 5.8 0.00
StrahlerOrder 3.9 0.02
AvgWidth_ft 2.8 0.06
Three clusters
% Correct 1 2 16
1 83.0 44 4 5
2 17.2 11 5 13
16 66.6 13 3 32
Total 62.3 68 12 50
DFA
• Can predict differences between 2 groups– Elevation, % cobble-boulder
• Does not distinguish 3-4 groups very well– May have something with stream size
Remaining Variability
Bec
ks
EP
T T
axa
(%)
HB
I
clin
ger
taxa
EP
T T
axa
Inse
ct T
axa
Into
lera
nt
Tax
a
Ple
cope
tra
Tax
a
Tric
hopt
era
Tax
a
% S
crap
er
Tol
eran
t ta
xa
(%)
% T
oler
ant
Month -0.12 -0.13 0.12 0.06 0.05 0.10 -0.09 -0.35 0.23 0.54 0.29 0.22
Alkalinity (mg/L) -0.47 -0.35 0.27 -0.53 -0.44 -0.46 -0.46 -0.49 -0.49 0.16 0.33 0.26
Hardness (mg/L) -0.59 -0.42 0.40 -0.58 -0.50 -0.50 -0.56 -0.61 -0.47 0.21 0.43 0.34
PC_CobbleBoulder 0.44 0.42 -0.54 0.27 0.30 0.11 0.42 0.32 0.35 -0.03 -0.34 -0.44
AvgPC_Riffle 0.67 0.57 -0.59 0.48 0.53 0.35 0.65 0.52 0.51 -0.18 -0.53 -0.56
Above Fall-line
Spearman rhoReference only
Metrics can be adjusted individually using residuals of the regression slope
Remaining Variability
% E
PT
HB
I
Em
phem
ero
pte
ra
Taxa
Ple
copetr
a T
axa
% P
lecopte
ra
Tole
rant
taxa (
%)
% T
ole
rant
GRADIENT_ft/mi 0.19 -0.42 -0.08 0.48 0.59 -0.41 -0.29
Hardness (mg/L) 0.01 0.25 0.53 -0.23 -0.41 0.15 0.09
PC_CobbleBoulder 0.35 -0.31 0.36 0.27 0.20 -0.35 -0.52
AvgPC_Riffle 0.62 -0.66 0.23 0.53 0.44 -0.53 -0.64
Below Fall-line
Spearman rhoReference only
Metrics can be adjusted individually using residuals of the regression slope
Conclusions
• The strongest categorical classification variable is the Fall Line, where above and below groups are defined by ecoregions
• Variability in some metrics remains after categorical classification, based on % riffles, % cobble/boulders, and hardness
• Individual metrics can be adjusted continuously or in steps
Classification Errors
• Yes• Site classes are generalizations
– We cannot assign each site to its own class– We group for convenience and statistics– We lose specificity
• If we define using ecoregional borders, some sites will be close to the edge (transitional)
• Some sites will be natural anomalies
Abstract• In 2008, the Alabama Department of Environmental Management (ADEM) developed
macroinvertebrate indices for high and low gradient streams using 205 sites from ADEM’s 1994-2005 datasets. These sites covered a limited portion of the state. An additional 285 macroinvertebrate bioassessments were conducted statewide between 2006-2011, filling in gaps in the spatial coverage of sites. ADEM sought to confirm or refine the classification of sites for biological assessments as a first step in recalibrating the indices. Using the human disturbance gradient (which includes land uses), water quality, and physical habitat, 130 reference stream sites were identified in all of the major ecoregions. Principal components analysis (PCA) showed how natural environmental variables in reference sites differed among level 4 ecoregions and were related to stressor variables and macroinvertebrate metrics. With the basic patterns apparent in reference sites, the PCA was run again with reference and non-reference sites to help classify sites in regions with low reference representation. The PCA axes related to biological variability were used to categorize sites in groups of level 4 ecoregions with similar biologically relevant characteristics. Taxa ordination was used for further exploration of biological types and to confirm final site classes. Site classes in Alabama were based on level 4 ecoregions, with stream size, slope, and water hardness as modifiers.
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