The precedent:
California just finished
their statewide analysis.
It required painstaking
ID of core areas to
connect.
These are shown by the
colored “sticks”
connecting core areas
The precedent:
California just finished
their statewide analysis.
It required painstaking
ID of core areas to
connect.
These are shown by the
colored “sticks”
connecting core areas

Once “sticks” were
identified, California
modeled linkages oneby-one, taking months
and tens of thousands
of dollars in analyst
time.
And that was for just
one integrity-based
analysis, compared to
16 focal species plus
integrity in WA.
We need to avoid this
and automate as
much as possible!
How to accomplish something comparable but
automatable?
Need to create informative maps for 16 focal species
+ landscape integrity
Sharp-tailed Grouse
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Habitat Concentration
areas (HCAs)
6
5
8
4
3
2
1
Sharp-tailed grouse
Candidate map
#1: Cost-weighted
distances to all 11
HCAs using
resistance surface
See notes
attached to this
and following
slides
Sharp-tailed Grouse
Masked out areas
beyond 300km
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Sharp-tailed Grouse
Cost-weighted
distance from HCA #3
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Sharp-tailed Grouse
Sum of costweighted distances
from HCAs 3 & 5 =
Least-cost corridor
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Problem #1: How to get a
map like this….
Sharp-tailed Grouse
From a bunch of
maps like this?
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Sharp-tailed Grouse
Proposed method:
Minimum of all
normalized least-cost
corridors
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Sharp-tailed Grouse
Proposed method:
Minimum of all
normalized least-cost
corridors
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Sharp-tailed Grouse
Proposed method:
Minimum of all
normalized least-cost
corridors
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Sharp-tailed Grouse
Problem with
overlapping corridors
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Sharp-tailed Grouse
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Problem # 2: Which
HCAs to connect?
8
7
11
6
5
4
3
Sharp-tailed Grouse
Proposed method:
If a least-cost corridor
passes through an
intermediate HCA,
don’t map the
corridor
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Sharp-tailed Grouse
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Creates a network of
HCA’s
8
7
11
6
5
4
3
Sharp-tailed Grouse
Proposed method:
If a least-cost corridor
passes through an
intermediate HCA,
don’t map the
corridor
Assume it can be
represented by
individual corridors
Sharp-tailed grouse
Candidate map
product 2:
Minimum of all
normalized
corridor layers
using network of
HCA’s
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8
7
11
6
5
4
3
Sharp-tailed grouse
Candidate map
product 3: Some
measure of
corridor quality
Here, I’ve divided
each corridor by
the geographic
distance between
the HCAs it
connects
Sharp-tailed grouse
Candidate map
product 3: Some
measure of
corridor quality
Here, I’ve divided
each corridor by
the geographic
distance between
the HCAs it
connects
Sharp-tailed grouse
Circuitscape
results- pinch
points and
redundancy
between HCAs 3
and 5
Sharp-tailed grouse
Circuitscape resultsimportant barriers
separating HCAs 3
and 5
Candidate map
product 4:
Circuitscape results
showing pinch
points and areas
important for
network
Brighter areas are
pinch points and/or
have higher
centrality (meaning
they’re important
for multiple pairs of
HCAs).
May be more
appropriate for
ecoregional and
local analyses.
Sharp-tailed grouse
Candidate map
product 5:
Circuitscape
results showing
important barriers
in network
Sharp-tailed grouse
Problem: Some
maps display well
at larger extents…
Normalized
corridors
Sharp-tailed grouse
Problem: Some
maps display well
at larger extents…
…and some don’t
Corridor
quality 
Sharp-tailed Grouse
If needed, “sticks” can
be color coded to
indicate corridor info
(like quality) without
need to create
additional hi-res maps
(Some concern about
landowner sensitivity)
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8
7
11
6
5
4
3
NEEDS
-Funds to develop climate-smart linkage design strategies
-GIS Tools!
• Automate connectivity modeling, facilitate repeat analyses,
streamline ecoregional analyses
• Integrate into Decision Support Systems
• Get tools into hands of other states and planners
-New ways to share maps, tools, and data on the web
Opportunities & Risks
-Rare opportunity to influence connectivity conservation
throughout west (& elsewhere!)
-Highly fundable (WCS, WGA, LCCs, etc.)
-Critical planning needs (e.g. for greater sage-grouse)
-All eyes are on Washington
-Large partnerships and limited capacity = potential for
timeline slippage
-We’re on hook for Columbia Plateau analysis (Aug 2011)
-Maps take on lives of their own (So do tools!)