Kirk Sherrill 1 , A. Pike, M. Laituri, F. Scatena, K. Hein, F. Blanco
1 Dept. of Forest, Rangeland and
Watershed Stewardship, Colorado State
University
Hydrology Days March, 20 th 2006


Roads have an undeniable presence throughout most terrestrial landscapes
– 5,000,000 mile road network in North America
– 250,000,000 vehicles in North America

Numerous Roads Effect
A. Pollution (ie. Road dust, Ambient Noise, Salt, Nitrogen, CO
2
)
B. Habitat Loss and Degradation (ie. Fragmentation, increased human access, noxious species, altered disturbance regimes etc.)
C. Water Processes

 Roads act as increased sources for water and sediment movement
 Roads act as barriers to water, sediment and aquatic species movement
 Altered stream and sediment flow are the most important road effects regarding Road and Stream network connectivity (R/S Connectivity)
(Forman and
Alexander 1998, Gibson et al. 2005, Lugo and Gucinski 2000, Montgomery 1994, Roth et al. 1996, Walker et al. 1995, and Wemple et al. 1996).


Road and Stream Network Connectivity
(R/S Connectivity)

Degree by which interactions affect ecosystem process:

Physical R/S Connectivity - Occurs from direct contact between roads and streams usually at crossing structures


Measure Physical R/S Connectivity by:
I. Performing a localized Bridge Scour Survey
II. Evaluate Steam Network Connectivity For Fish

Determine utility of using Geographic
Information System (GIS) derived data to:
– (I) Model bridge scour
– (II) Identify of road crossings which are fish barriers

Puerto Rico
Puerto Rico
Puerto Rico
 24 River Road Crossings (RRC)
Study Sites
 Rio Espiritu (~ 23,500 acres)
 Rio Mameyes (~11,000 acres)
 Northeastern Puerto Rico
 Caribbean National Forest
 Sea Level to 3,500 feet


I. Bridge Scour Survey (Johnson et al.
1999) was performed at 24 RRC
– Evaluated Scour Scores relative:

Environmental Variables (Land Cover, Geology,
Elevation, Stream Power)

Road Characteristics (Stream Size, Road Size,
Crossing Type, % Stream Constriction)
– Model Scour Scores


Amount of or potential for alteration to
Sediment and Stream
Flow in vicinity of RRC
– 11 Indicator Variables
– Rated (1-12)
– Weighted
– Summed
Final Scour Rating
Indicator Variable
1. Bank Soil Texture and Coherence
2. Average Bank Slope Angle
3. Vegetative Bank Protection
4. Bank Cutting
5. Mass Wasting or Bank Failure
6. Amount of Bar Development
7. Debris Jam Potential
8. Obstructions, Presence of Flow
Deflection
9. Channel Bed Material
10. Flow Angle of approach to road crossing structure
11. Presence of Blow hole or Scour pool
Weight
0.6
0.6
0.8
0.7
0.8
0.6
0.2
0.2
1.0
0.5
0.8

3
2
1
0
6
5
4
9
8
7
Stable Moderate Poor
Scour Rating
Stable
Moderate
Poor
Unstable
Unstable
Sites
6 Stable
8 Moderate
5 Poor
5 Unstable

Two Scales of Study:
-
Local 250 meter circular buffer
-
Broad Upstream contributing area





Average Unit Stream Power
Land Cover
Underlying Geology
Average Elevation

Characteristics of Stable Scour Site?


Stable Scour Sites:
 Average Unit Stream
Power: Not Significant
Stream Power Data Collected by
(Pike and Scatena in press)
700
600
500
400
300
200
100
0
Average Unit Stream Power
By Scour Rating
393
Stable
Moderate
Poor
Unstable
190
123
40
Scour Rating

Average Elevations Buffer Scale
By Scour Rating

Stable Scour Sites:
432 *
 Significantly Higher
Elevations
(ANOVA α=0.05,
P-Value <.01)
300
250
200
150
100
50
0
500
450
400
350
163
105
Scour Rating
Stable
Moderate
Poor
Unstable
132
700
600
500
400
300
200
100
0
Average Elevations Upstream Scale
By Scour Rating
638 *
469
Stable
Moderate
Poor
Unstable
278
337
Scour Rating


Land Cover
(Ramos Gonzalez 2001)
– (Forest, Agriculture, and Urban)

Stable Scour Sites:
 Buf Scale 6/6 Stable Sites


100% Forested Land Cover
100% Extrusive Geology
 Ups Scale 5/6 Stable Sites

100% Forested Land Cover
 Ups Scale 4/6 Stable Sites

4/6 100% Extrusive Geology




Stream Size
Road Size
Percent Stream Constriction
No Significant Trend


Significant
(ANOVA
α=0.05, P-Value <.01)
– Bridge Crossings Lower
Scour Scores
15
10
5
0
30
25
20
50
45
40
35
Bridge Scour Score By Crossing Type
Bridge
Culvert
Crossing Type

I. Modeling Bridge Scour

Best Model Stepwise Selection
– Alluvial Geology Buffer scale (+10.85)
– Crossing Type
(1=Culvert, 2= Bridge)
(-9.94)
– Stream Size
(1=Large, 2=Medium, 3=small)
(-3.96)
– R 2 = 0.65

II. Stream Network Connectivity for Adult Fish

Method
1. GIS Stream Slope Analysis (10m resolution)


3x3 Kernel and Minimum Statistic
First Stream Segments >30% Slope = First natural occurring fish barrier on stream network
2. Field Data noting potential barrier crossings

6 Crossing possible barriers

3. Verify Accuracy of Field Data and Stream Slope

Adult Fish Species Richness data (Hein et al.)
Findings
 Stream Slope correctly identified 21/24 RRC relative to
1 st natural fish barrier
 Only 2 RRC acting as Fish Barriers or Partial Fish barriers

Both Culverts



GIS can be used to:
– Model Scour
– Locate Crossing location relative to 1 st Fish
Barrier
GIS Limitations?
– Important variables require field data collection
– Extensive Biological Field Data is needed to
Identify Barrier Crossings


Low Physical R/S Connectivity Sites:
– High Proportions Forest and Extrusive Geology
– Higher Elevations
– Bridge Crossing

Lower Scour Scores and less likely to be fish barriers
– Prieta, and Bisley sites (Both 100% Forest and
100% Extrusive, at high elevation but Culvert
Crossings Poor Scour Score
– Crossing Type most important?


NSF grant DEB-0308414 NE Puerto Rico Biocomplexity project http://biocomplexity.warnercnr.colostate.edu
.

Andy Pike and Fred Scatena, Dept. of Earth and
Environmental Sciences, University of Pennsylvania,
Philadelphia, PA.

Melinda Laituri, Dept. of Forest, Rangeland and Watershed
Stewardship, Colorado State University, Fort Collins, CO.

Katie Hein and Felipe Blanco, Dept. of Aquatic, Watershed and
Earth Resources, Utah State University, Logan, UT.

Thank You
&
Questions?
Thank You
&
Questions?