Effects of Hydrologic and Environmental Factors on Ecological Conditions of Upland Streams in the Northeast, USA. National Monitoring Conference National Monitoring Conference May 7-11, 2006 May 7-11, 2006 Jonathan G. Kennen, NJWSC, West Jonathan G. Kennen, NJWSC, West Trenton, NJ Trenton, NJ Karen R. Murray NYWSC, Troy, NY Karen R. Murray NYWSC, Troy, NY Karen M. Beaulieu, CTWSC, East Karen M. Beaulieu, CTWSC, East Hartford, CT Hartford, CT
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Effects of Hydrologic and Environmental Factors on Ecological Conditions of Upland Streams in the Northeast, USA. National Monitoring Conference May 7-11,
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Effects of Hydrologic and Environmental Factors on Ecological Conditions of Upland
Streams in the Northeast, USA.
National Monitoring ConferenceNational Monitoring Conference
May 7-11, 2006May 7-11, 2006
Jonathan G. Kennen, NJWSC, West Trenton, NJJonathan G. Kennen, NJWSC, West Trenton, NJKaren R. Murray NYWSC, Troy, NYKaren R. Murray NYWSC, Troy, NY
Karen M. Beaulieu, CTWSC, East Hartford, CTKaren M. Beaulieu, CTWSC, East Hartford, CT
There are many mechanisms by which hydrology impacts biota.
J. Kennen, NJWSC, West Trenton, NJJ. Kennen, NJWSC, West Trenton, NJ
HealthyWater
StressorsRequirements Sources
Excess Predators
High Turbidity
Sedimentation
Excess Nutrients
Altered Flows
Chemical Pollutants
High WaterTemperature
Physica
l H
abita
t
Excess Competitors
Few Competitors & Predators
Poor RiparianBuffers
Impervious Surfaces/
Stormwater
Point Sources
Use of Pesticides& Fertilizers
Historic Sediment
Reservoirs
Channel Erosion
Construction
Invasive SpeciesIntroductions
Food (Algae, Meiofauna)
InterstitialHabitat
Altered Food Webs
SubstrateSuitability
Refugia
(algal bloom)
RoadCrossings
(low
DO
)
Movement Barriers
Connections to Other Populations
Insuf. Woody Debris
Livestock & Poultry
Poor RiparianBuffers
Multiple stressors can have Multiple stressors can have additiveadditive and/or and/or synergisticsynergistic effects effects
+x–
?
Stream hydrology differs – can have Stream hydrology differs – can have linearlinear, , thresholdthreshold, or , or even a even a delayed delayed response to disturbanceresponse to disturbance
disturbancebio
tic in
teg
rity
?
disturbancebio
tic in
teg
rity
?
“I asked you a question buddy, what’s the minimum flow we need to protect aquatic
species in this here Basin?”
Project ObjectivesProject Objectives
Describe relations with observed ecological patterns Describe relations with observed ecological patterns
Identify important environmental and hydrological Identify important environmental and hydrological
parameters parameters
Discern disturbance gradient from biotaDiscern disturbance gradient from biota
Use sound science to identify key variables water Use sound science to identify key variables water
managers can use to improve stream qualitymanagers can use to improve stream quality
Scope
-77 upland watersheds
-Range of urban intensity
-7 NAWQA study units
- 1993-2002
Quantitative invertebrate riffle samples
Gaging station co-located at or near
aquatic invertebrate sampling site
Hydrologic data needed for a minimum of
3 or more years
Quantitative invertebrate riffle samples
Gaging station co-located at or near
aquatic invertebrate sampling site
Hydrologic data needed for a minimum of
3 or more years
Quantitative invertebrate riffle samples
Gaging station co-located at or near
aquatic invertebrate sampling site
Hydrologic data needed for a minimum of
3 or more years
Data RequirementsData Requirements
Data CompilationData Compilation
GIS Data –“Roads Corrected” Land use /
cover, etc.
Hydrologic descriptors (Hydrological
Integrity Assessment Process –171 Variables)
Quantitative invertebrate (density –
numbers/m2)
Assemblage metrics and indices
General Analytical ApproachGeneral Analytical Approach
Invertebrate Data
Ordination (NMDS)
Extract Axis Scores
Environmental Variables
PCA/Corr. [=data reduction]
Final Set of Variables
(Standardize, Transform, Assess Colliniarity)
(>527 vars.)
(76 vars.)
Multiple Linear Regression (MLR)(Axis Score = disturbance gradient)
(+/- 37 vars.)
Why use Ordination?Why use Ordination?
Reduces complexity of community data Reduces complexity of community data
while retaining structurewhile retaining structure
Derives environmental gradients based Derives environmental gradients based
on biotaon biota
Places sites with similar communities Places sites with similar communities
close together, those with dissimilar close together, those with dissimilar
Distribution of Sites Coded by Relative Distribution of Sites Coded by Relative Position Along the Disturbance GradientPosition Along the Disturbance Gradient
Level of Disturbance
High
Moderate
Minimum
Very High
NE Ecoregions
Ordination Color Coded (high to low) by Ordination Color Coded (high to low) by Percent Riparian ForestPercent Riparian Forest
Disturbance Gradient
LowMediumHigh
% Rip. Forest
Relations with assemblage structure Relations with assemblage structure and functionand function
Strong relations with metrics further support
interpretation as a disturbance gradient.
0 10 20
EPTR
- 1
0
1
M
D
S
7
6
_
1
Richness of Sensitive EPT Taxa
Dis
t. G
rad
.
3 4 5 6
Ri chTOL
- 1
0
1
M
D
S
7
6
_
1
Dis
t. G
rad
.
Richness of Tolerant Taxa
Relations with Land Use & ConfigurationRelations with Land Use & Configuration
Relations show the extent of anthropogenic effects and help target attributes that may be useful from a LU planning perspective.- 1 0 1
MDS76_1
0
20
40
c
9
2
_
c
f
_
a
r
Decline in Core Forest
Dis
t. G
rad
.
- 1 0 1
MDS76_1
20
40
60
80
R
I
P
S
U
M
_
F
O
R
E
Decline in % Riparian Forest
Dis
t. G
rad
.
Relations with assemblage structureRelations with assemblage structure
Tolerant Tolerant species species increaseincrease
Sensitive Sensitive species species
decreasedecrease
Regression Model using Disturbance Regression Model using Disturbance Gradient as Response VariableGradient as Response Variable
Results of significant (p<0.05) MLR model –Results of significant (p<0.05) MLR model –disturbance gradient is response variabledisturbance gradient is response variable
Model r2 Partial r2 P-value Variable name
0.7875 0.4918 <0.0001 – Percent riparian forest 0.1093 <0.0001 – April low flows 0.0420 0.0048 + Road density 0.0315 0.0061 – Percent of forest in stream segment 0.0281 0.0162 + Percent of forest patches < 50 acres 0.0263 0.0162 + Distance to nearest road 0.0236 0.0131 – April maximum flows 0.0202 0.0161 + Annual 30d maximum flows 0.0144 0.0385 – Annual runoff
0
5
10
15
20
25
30
0 50 100 150 200 250
R = 0.445
Example –Percent Riparian ForestExample –Percent Riparian Forest
Significant linear Significant linear relations observed –no relations observed –no defined inflection point.defined inflection point.
R = 0.575
0
2
4
6
8
10
12
14
16
0 20 40 60 80 100Percent Riparian Forest
EP
T R
ichn
ess
Percent Riparian Forest
EP
T R
ich
nes
s
% o
f O
mn
ivo
res
Variability of January Flow
Summary of FindingsSummary of Findings
1.1. Patterns in biota are highly related to stream Patterns in biota are highly related to stream degradation. degradation.
2.2. Environmental alterations are related to Environmental alterations are related to changes in the biotic integrity across a changes in the biotic integrity across a disturbance gradient. disturbance gradient.
3.3. Riparian forest areas lessen the effects of Riparian forest areas lessen the effects of human-induced landscape and hydrologic human-induced landscape and hydrologic alterations. alterations.
4.4. Intolerant taxa become less prevalent as Intolerant taxa become less prevalent as streams become more degraded.streams become more degraded.
Management ImplicationsManagement Implications
Relations between invertebrate Relations between invertebrate assemblage metrics and environmental assemblage metrics and environmental and flow attributes can be used to: and flow attributes can be used to: target levels of riparian coverage that are target levels of riparian coverage that are
protective of structural complexity and/or protective of structural complexity and/or meet designated aquatic life usemeet designated aquatic life use
or. . target portions of the flow regime or. . target portions of the flow regime that are protective of biological integritythat are protective of biological integrity