A framework for landscape indicators
for measuring aquatic responses
David Theobald,
John Norman, Erin Poston,
Silvio Ferraz
Natural Resource Ecology Lab
Dept of Recreation & Tourism
Colorado State University
Fort Collins, CO 80523 USA
11 September 2004
Context
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Challenges of STARMAP (EPA):
Addressing science needs Clean Water Act
 Integrate science with states/tribes needs
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From correlation to causation
Tenable hypotheses generated using
understanding of ecological processes
Goal: to find measures that more closely represent our
assumptions of how ecological processes are operating
Landscape processes

Spatial & temporal scales,
processes
Constraints
Poff, N.L. 1997
Landscape Context of Metrics
Co-variate(s) at spatial location, site context
1.
1.
E.g., geology, elevation, population density at a point
Co-variate(s) within some distance of a location
2.
1.
Housing density at multiple scales
Watershed-based variables
3.
1.
Amount of contributing area, flow volume, etc.
Spatial relationships between locations
4.
1.
2.
Euclidean (as the crow flies) distance between points
Euclidean (as the fish swims) hydrologic network distance between
points
Functional interaction between locations
5.
1.
2.
3.
Directed process (flow direction), anisotropic, multiple scales
How to develop spatial weights matrix?
Not symmetric, stationary  violate traditional geostatistical
assumptions!?
Challenges: conceptual & practical
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Definition of a watershed
Overland surface process vs. in-stream flow process
Scale/resolution issues
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Artifacts in data
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Attribute errors, flow direction, braided streams
Linking locations/points/events to stream network
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E.g., different answers at 1:500K vs. 1:100K vs. 1:24K
Reach-indexing gauges, dams?
Very large databases
GIS technology innovations and changes
“Watershed”-based analyses

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% agricultural, % urban (e.g., ATtILA)
Average road density (Bolstad and Swank)
Dam density (Moyle and Randall 1998)
Road length w/in riparian zone (Arya 1999)
But ~45% of HUCs are not watersheds
EPA. 1997. An ecological assessment of the
US Mid-Atlantic Region: A landscape atlas.
Southern Rockies Ecosystem Project.
2000.
Watersheds/catchments as
hierarchical, overlapping regions
River continuum concept
(Vannote et al. 1980)
Dominant downstream
process
Upper and lower Colorado Basin
Flows to downstream HUCs
Reach Contributing Areas (RCAs)
Automated delineation

Inputs:
stream network (from USGS
NHD 1:100K)
 topography (USGS NED, 30
m or 90 m)
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Process:
“Grow” contributing area
away from reach segment
until ridgeline
 Uses WATERSHED
command

“true”
“adjoint”
catchments
catchments
Reaches
(segments)
Zonal
Accumulate
Process/Functional
Up/down (net.)
Watershed – Stream
Hydrologic
distance:
-Instream
-Up vs. down?
FLOWS
Overlapping
watersheds
Accumulate
downstream
FLOWS (and
SPARROW)
Stand-alone
watershed
Watershed-based
analyses (HUCs)
Tesselation of true,
adjoint catchments
?
Watersheds
HUCs/WBD
Reach Contributing Areas (RCAs)
Grain (Resolution)
Reaches are linked to catchments
1 to 1
relationship
 Properties of
the watershed
can be linked
to network for
accumulation
operation

RCA example
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US ERF1.2 & 1 km DEM: 60,833 RCAs
Key  GeoNetworks!

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Need to represent relationships between
features
Using graph theory, networks
Retain tie to geometry of features
Implementation in ArcGIS
GeometricNetworks (ESRI – complicated, slow)
 GeoNetworks: Open, simple, fast
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Feature to Feature Relationships via Relationship Table
Up
Down
RCAs are linked together
– but spatial configuration within an RCA?
1. Ignore variability
2. Buffer streams
3. Buffer outlet
2 major hydro. processes w/in RCA
A
B
A'
B'
Legend
C'
C
#
0
outlet
nhd_rivers
catch
^_
Points
Distances
AA'
0
0.5
1
2
Miles
1. Overland (hillslope): Distance (A to A’)
2. Instream flow: Distance (A’ to O)
BB'
CC'
Flow distance: overland + instream
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Hydro-conditioned
DEM (e.g., EDNA)
FLOWDIRECTION
FLOWLENGTH
Flow distance: overland
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Hydro-conditioned DEM
(e.g., EDNA)
Burn stream into
FLOWDIRECTION
FLOWLENGTH
Flow distance: instream
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Hydro-conditioned DEM
(e.g., EDNA)
FLOWDIRECTION
FLOWLENGTH from
outline – overland
FLOWLENGTH
Why are functional metrics important?

Clearer relationship between assumption of
ecological (aquatic, terrestrial) process, potential
effects (e.g., land use change) and response

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Huge (insurmountable?) challenge is that we cannot
develop traditional experimental design (manipulated
vs. controlled) because landscapes are so large and
human activities so dominant
More direct relationship between process and
measure, biologically meaningful
FLOWS v0.1:
ArcGIS v9
tools
- Higher-level objects 
faster coding!
- Open source
- Integrated development for
documentation
Laramie Foothills Study Area and
Sample Points
Accessibility:
travel time along
roads from urban
areas
Planned future activities
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Papers
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Presentations
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Theobald GRTS Sept. 23
Poston
Products
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Completing draft manuscripts on: GIS-GRTS, RCAs,
overland/instream flow, dam fragmentation, GeoNetworks
FLOWS tools
Datasets: RCAs (ERF1.2)
Education/outreach
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Training session for FLOWS tools
Possible future activities
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Dataset development
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RCA nationwide with involvement for USGS NHD program
Reach indexing dams (for EPA, Dewald)
Discharge volume
Symposium: “At the interface of GIS and statistics for
ecological applications” (~January 2005)
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What are the strengths and weaknesses of GIS-based and statisticalbased tools?
How can/should statisticians respond, direct, and utilize GIS-based
types of tools?
How can/should statistical tools be best integrated with GIS?
What are the needs of agencies if statistical-based tools are to be used?
When should GIS-based tools be used?
How can these two approaches best complement one another?
Thanks!
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Comments? Questions?
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Funding/Disclaimer: The work reported here
was developed under the STAR Research
Assistance Agreement CR-829095 awarded
by the U.S. Environmental Protection Agency
(EPA) to Colorado State University. This
presentation has not been formally reviewed
by EPA. The views expressed here are solely
those of the presenter and STARMAP, the
Program (s)he represents. EPA does not
endorse any products or commercial services
mentioned in this presentation.

STARMAP:

RWTools: email davet@nrel.colostate.edu
www.stat.colostate.edu/~nsu/starmap
CR - 829095