Habitat Management
The Goal:
Create a growth/development plan for a watershed that anticipates
possible development-related impacts to fish and wildlife habitats.
The Issue:
How do you identify and prioritize habitat locations and threats
over a large area?
The Answer:
A satellite-derived habitat inventory map.
The Example:
Casco Bay, Maine
Maine's Casco Bay Watershed contains fish and wildlife habitats
that are composed of wetlands, eelgrass beds, streams, forests,
and offshore islands. These habitats provide species a place to
live, feed, and reproduce. In addition, the watershed contains
15 communities that have seen population increases of 24 percent
over the past 20 years, and a doubling of housing units. The habitat
has been damaged as a result of this population growth. Many of
the older roads restrict tidal flushing, dam construction has
barred fish passageways and redirected water flow, and natural
habitat has been lost to development and road construction.
Since this scenario was not one the citizens of the Casco Bay
area wanted to see continued or repeated, the need for a comprehensive
plan that encompassed the entire watershed was apparent. Local
officials turned to remote sensing as one of the tools to accomplish
this goal. Integrating satellite-derived land cover data with
existing research enabled the planners to identify critical areas
for protection and management.
Applying Land Cover Data:
To identify critical habitat, the researchers collected and compiled
many data sources, including C-CAP land cover data, species distribution
data, and bathymetry. The relative values of habitat were analyzed
using a geographic information system (GIS) to determine the level
of importance and suitability of a given habitat. This analysis
was eventually used to create a composite habitat suitability
map for the entire watershed.
For example, the first step to determine critical habitat for
the common eider duck was to identify the spatial extent of its
feeding habitat. Two critical factors influence where an eider
duck will feed: water depth (bathymetry) and eelgrass distribution.
These data layers were analyzed in a GIS, and locations where
eelgrass was present and the water did not exceed 10 meters were
considered preferred foraging habitat (displayed in orange). The
data were displayed with existing nesting habitat (displayed in
blue).
Eider duck foraging and nesting behavior is
also influenced by proximity (closeness) to developed areas. C-CAP
land cover data were used to identify developed areas (displayed
in red) and given a 90-meter buffer (yellow stripes). Potential
eider duck habitat was given a high value if it was preferred
(far from development) or a low value for less preferred (intersected
developed or buffered areas).
All of this information was used to determine
the locations of where preferred foraging habitat intersected
with potentially preferred habitat (habitat that is far from developed
areas).
The analyses above were simplified for this
example, but illustrate an example of the types of analyses and
data used to create composite maps of habitat suitability denoted
as low, medium, or high value.
The Result:
The preliminary results pinpointed habitat at risk; approximately
one-third of the habitat rated important was at some risk. Without
the satellite imagery, it would have been nearly impossible to
develop this important planning and change detection tool. Collectively
and individually, city planners throughout the watershed are using
this information as they plan their communities' futures.
To learn more about the Casco Bay Estuary project, visit: www.cascobay.usm.maine.edu
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