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Multi-Scale and Multi-
Dimensional Controls on Biota
and Physical Habitat
Phil Kaufmann, Ken Bazata, Lyle Cowles,
and Dave Peck
Lawrence, KS
April 2001
EMAP-Surface Waters Objectives
• Estimate Extent of Lake and Stream Resource
– number/area of lakes, stream miles
• Estimate Current Status of Ecological Condition
– at regional scale with known confidence
• Estimate Changes and Trends in Condition
• Describe Associations between Status/Trends in
Conditions and Differences/Changes in Human
Activity
• Diagnose Probable Causes of Impairment
Biological Condition
(e.g., species richness)
Land Use
Human Disturbance Natural controls
(stream size, elevation, slope)
Chemical Habitat
Land use and many natural controls affect biota
indirectly through their effect on habitat.
Physical Habitat
HABITAT
... the set of conditions that support
and control the distribution and
abundance of aquatic organisms:
Physical
Chemical
Biological
Consider Landscape and Historical
Contexts
PHYSICAL HABITAT INDICATOR
DEVELOPMENT
Determine Aspects of Interest
Define Metrics to Quantify Aspects
Develop Field Monitoring Protocol
Quantify Variability, Precision
Demonstrate Ecological Relevance
-- biological associations
-- sensitivity to human disturbance
8/97
• Water Chemistry
• Nutrients, Temperature
• Biotic Interactions
Natural Controls & Human Influences
BENTHOS SUBSTRATE SIZE
Land and Water
Management
Sediment Supply:
* Geology, Relief
* Climate, Vegetation
* Disturbance
Stream Competence:
* Flow, Slope, Morphol.
Substrate Erosivity:
* Armoring
* Channel Complexity
Elements of Stream Physical Habitat
Channel Dimensions
Gradient
Substrate Size and Type
Hab. Complexity & Cover
Riparian Vegetation Cover and Structure
Channel-Riparian Interaction
Anthropogenic Alterations
Note: Chemistry, Nutrients, Temperature
11
Adequate Habitat Indicator?
• Accurate & Responsive -- Does it
measure what we intend ?
• Precise -- Can we separate changes or
differences from measurement error?
• Relevant -- To Biological needs?
Ecological processes? Societal values?
• Practical -- Can we do it? ...afford it?
12
Associations with Habitat Data
• Raw Measurements
• Habitat Characterization Metrics
• Measures of “Alteration” of Particular Habitat
Features
• Measures of “Quality” of Particular Features
• Integrated Habitat Disturbance Assessment
• Integrated Habitat Quality Assessment
• Multi-Dimensional Associations
• Multi-Scale Associations
13
Associations with Habitat Data
• Raw Measurements
• Habitat Characterization Metrics
• Measures of “Alteration” of Particular Habitat
Features
• Measures of “Quality” of Particular Features
• Integrated Habitat Disturbance Assessment
• Integrated Habitat Quality Assessment
• Multi-Dimensional Associations
• Multi-Scale Associations
R7 IBI vs Substrate fines, sand+fines, mean diameter, and
bed stability (R=Upland,B=E.Lowland, G=W.Plains)
Streambed Stability vs Riparian Agriculture: Varies by Stream Size (R=Uplnd, B=E.Lowland, G=W.Plains)
W<5m W >5-<12 m
W > 12- <32 m W >32 m
16
Associations with Habitat Data
• Raw Measurements
• Habitat Characterization Metrics
• Measures of “Alteration” of Particular Habitat
Features
• Measures of “Quality” of Particular Features
• Integrated Habitat Disturbance Assessment
• Integrated Habitat Quality Assessment
• Multi-Dimensional Associations
• Multi-Scale Associations
Habitat Quality
18
Associations with Habitat Data
• Raw Measurements
• Habitat Characterization Metrics
• Measures of “Alteration” of Particular Habitat
Features
• Measures of “Quality” of Particular Features
• Integrated Habitat Disturbance Assessment
• Integrated Habitat Quality Assessment
• Multi-Dimensional Associations
• Multi-Scale Associations
Habitat “Response Curves” “Q
UA
LIT
Y”
1
MODELLED
RESPONSES :
* Monotonic Increase
* Monotonic Decrease
* Threshold Response
-- Hi, Low, Both
* Hyperbolic
1
0
0
HABITAT MEASUREMENT
20
Associations with Habitat Data
• Raw Measurements
• Habitat Characterization Metrics
• Measures of “Alteration” of Particular Habitat
Features
• Measures of “Quality” of Particular Features
• Integrated Habitat Disturbance Assessment
• Integrated Habitat Quality Assessment
• Multi-Dimensional Associations
• Multi-Scale Associations
Physical Habitat Quality
Index (Sub-components)
1. Riparian Vegetation
2. Rip. Human Disturbance
3. Substrate
4. Channel Alterations
5. Habitat Volume
6. Structural Complexity
7. Fish Concealment
8. Water Velocity
Habitat Quality Index Components
• Rip. Veg. ----- Complexity, Cover
• Rip. Disturb-- Proximity-Weighted Tally
• Substrate --- Fines, Embeddedness, Bedrock, Macrophytes Algae
• Channel Alts-- Pipes, Revetment, Rel. Bed Stability,
Deviation in Resid. Pool Vol
• Volume ------ Width, X-Sect. Area, Resid. Pool, %Dry
• Complexity --- CV Depth, Sinuosity
• Cover --------- Separate and Sum of 6 Cover Types
• Velocity ----- Slope, Shear Stress
Habitat
Qualit
y
Most Hab Volume Var’s Disturb, % Dry,
Shear Stress, Fines
Ripar Veg Complexity Canopy Cover Most Fish Cover Var’s
Habitat Quality Index Calculation
(1/8)
Component 1 = Mean of Subcomponents
Component 2 = Mean of Subcomponents
--- etc for 8 Components
Quality Index = (1 x 2 x 3 x 4 x 5 x 6 x 7 x 8)
Reg7 IBI vs Habitat Quality Index (Red=Uplands, Blue=E.Lowlands, Green=W.Plains)
Width Classes for Reg 7
Streams
• Class 1 : < 5 m
• Class 2 : 5 - 13 m
• Class 3 : 13 - 32 m
• Class 4 : > 32 m
Reg7 IBI vs Habitat Quality Index by stream width
classes (Red=Uplands, Blue=E.Lowlands, Green=W.Plains)
W<5m W >5-<12 m
W > 12- <32 m W >32 m
Reg7 IBI vs Habitat Quality Index and Sub-Components (Red=Uplands, Blue=E.Lowlands, Green=W.Plains)
IBI vs Phab Correlations (Signif p<.05)
(Spearman r * >.10, ** >.20, *** >.30 etc.) Rveg Rdist Sub ChAlt Vol Comp Cov Velo QTPH1
====================================================================
Whole Reg . * *** *** . * * * ****
----------------------------------------------------------------------------------------------------
E. Lowland * . *** **** . ** . ** ****
Uplands . . . . . ** . **** **
W. Plains. . *** *** . . . . **** -------------------------------------------------------------------------------------------------------------------
Width <5m . . *** ** . . . . ***
Width 5-32 . * **** ***** . **** * *** *****
Width >32 (**) **** (**) (***) (**) (**) (**) . (**)
Reg7 IBI MLR by Width Class
<5m 5-32m >32m All+SbQual -ChDist +Cover -ChDist
+RipVeg +SbQual +SbQual +SbQual
-NPAI -SedMet +RipVeg
+Complx -NPAI
______ +Cover _______ ________
19% 38% 73% 22%
% Variance in Reg 7 IBI (6) Explained By
Indexes of Habitat and Chemistry
0
5
10
15
20
25
30
35
<5m 5-13m 13-32m >32m All
Habitat
SedMet
NPAgInd
Stream Width Classes
% Variance in Reg 7 IBI Explained By
Habitat Index and its Components
0
5
10
15
20
25
30
35
40
45
50
1 2 3 4 All
Index
Separates
Stream Width Classess
% Variance in Reg 7 IBI Explained By Hab Index
Components + Chemistry (NPAI + MTLINDX)
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 All
8 QP H's
8 QPH + 2 Chm
Stream Width Classess
34
Associations with Habitat Data
• Raw Measurements
• Habitat Characterization Metrics
• Measures of “Alteration” of Particular Habitat
Features
• Measures of “Quality” of Particular Features
• Integrated Habitat Disturbance Assessment
• Integrated Habitat Quality Assessment
• Multi-Dimensional Associations
• Multi-Scale Associations
The Mid-Atlantic Highlands
Indicators of Condition: Fish Community Structure (IBI)
Macroinvertebrate Community Structure (EPT)
(Periphyton Community Structure)
Indicators of Stress: Physical Habitat (in-stream and near-stream)
Ambient Chemistry (nutrients, major ions)
Fish Tissue Contamination (mercury, organic contaminants)
Watershed Characteristics
MAHA Study Design: Indicators
MAHA Study Design: Probability Survey
MAHA Study Design: Sampling Design
Watershed
Riparian
Reach
Landscape
Fish IBI Results
17%
17%
36%
31%
Proportion of Stream Length
(Insufficient Data)
Good
Fair
Poor
10%
23%
37%31%
Valleys
10%15%
32%
43%
North-Central Appalachians
15%
28%
44%14%
Ridge and Blue Ridge
Fish IBI Results Geographic Distribution
35%
3%
32%
30%
Western Appalachians
(Insufficient Data)
Ranking of Potential Stressors
0% 10% 20% 30% 40%
Introduced Fish 34%
% of Stream Length
0% 10% 20% 30% 40%
Riparian Habitat
Sedimentation
Mine Drainage
Acidic Deposition
Tissue Contamination
Phosphorus
Acid Mine Drainage
24%
25%
14%
11%
10%
5%
1%
Nitrogen
5%
Linkages Among Indicators - MAHA streams
MLR Models for Native Fish Spp Richness (n=122)
• Drainage area 0.44 0.44
• Stream order 0.15 0.52
• Sinuosity 0.15 0.59
• SO4 0.14 0.64
• Fish Cover--Rocks 0.16 0.70
• Riparian Disturbance 0.12 0.73
• DOC 0.04 0.75
• Bed Stability 0.06 0.77
• Ripar. Canopy Cover 0.13 0.79
Variable Partial R2 Model R2
Native Fish Species Richness MLR All MAHA Streams
Natural
Controls
58%
Physical
Habitat
14%
Chemical
Habitat
7%
Unexplained
21%
MAHA Native Fish Species Richness MLR High Gradient Ecoregions
Natural
Controls
66%
Physical
Habitat
15%
Chemical
Habitat
2%
Unexplained
17%
Low Gradient Ecoregions
Physical
Habitat
12%
Chemical
Habitat
19%
Unexplained
5%
Natural
Controls
64%
Linkages Among Indicators - MAHA streams MLR Models predicting Chemical and Physical
Habitat (n=122)
Model R2: .59 .35 .23 .49 .47 .25
Predictor Variables:
Drainage Area X X X X X
Elevation X X
Slope X X
Runoff X
Pop. Density X
Road Density X
% Urban X X X
% Forest X X X X
% Agriculture X X X X
% Barren X X X X
TN TP SO4 %SaFn RP %Pool
% Variance Explained Using Different
Habitat Assessment Approaches in MLR
0
10
20
30
40
50
60
70
80
90
Fish Spp IBI EPT_taxa HBI
RBP
QPH
PHab
Mid-Atlantic Region Streams (7/97)
Watershed Quality vs:
1) Riparian Quality
2) Channel Phab
3) Chan-Ripar P-Hab
4) Chloride Conc.
Condition of watershed, riparian, channel, and water do not always agree !
Controls on Fish IBI -- Mid-Atlantic Region:
Single Watershed Var:
* Landcover Disturbed (-19)
* Road Density (-20)
* Human Pop. Density (-30)
Multi-Dimension/Single Scale:
* Watershed Condit. (+24)
* Riparian Condition (+08)
* Channel Phab Qual (+29)
Multi-Dimension/Multi-Scale:
* Chan.-Riparian Condit (+27)
* Wtrshed-Ripar Condit (+35)
* Chan-Ripar-Wtrshed (+45)
Red ------ pH<5.0
Scarlet -- SO4 >5,000 ueq/L
Multi-Scale and Multi-Dimensional Controls
on Biota and Physical Habitat Conclusions (1)
• Direct linkages between human land use and biotic condition are often difficult to draw.
• Geomorphology (watershed size, slope, elevation) causes substantial natural variability in habitat and biota.
Multi-Scale and Multi-Dimensional
Controls on Biota and Physical Habitat Conclusions (2)
• After accounting for geomorphic controls, Spp Richness (fish, benthos) and many other metrics are usually best predicted by a combination of channel (physical & chemical), riparian, and watershed variables.
• Scoring of ecological condition indices like IBI aims to minimize the influence of natural controls.
Multi-Scale and Multi-Dimensional
Controls on Biota and Physical Habitat Conclusions (3)
• The aspects of physical and chemical habitat most important to biota differ by ecoregion and taxonomic group.
• The primary mechanism of human land use impact on aquatic biota appears to be its influence on chemical and physical habitat.
Multi-Scale and Multi-Dimensional
Controls on Biota and Physical Habitat Conclusions (4)
• Best Assessments make use of combined single and integrated (multi-dimensional) variables derived from data at collected and summarized at multiple scales.
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