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The
factors influencing variability of Great Lakes fishes occur
over large spatial and temporal scales, creating challenges
for protection and management of sensitive life stages and
habitats. Critical habitats for spawning, feeding, and growth
of many Great Lakes fishes extend from deep offshore waters
to coastal or tributary habitats. Large gyres advect larvae
of lake spawners into, or away from, critical nursery areas
that may be less productive as a result of exotic species
invasions and nutrient declines. The proximity of nearshore
and tributary regions to human habitation leaves them vulnerable
to a variety of anthropogenic threats, thus threatening spawning
and nursery habitats of potamodromous fishes. It is essential
that structure, function, and connectivity among tributary,
nearshore, and offshore habitats be identified and reference
conditions for habitat quality established to ensure the long-term
sustainability of these important lake regions.
Objectives
This
project aims to develop ecological classifications of fish
habitat for each of the 5 Great Lakes (Superior, Michigan,
Huron, Erie, and Superior), and develop indices of relative
habitat quality (growth potential, spawning and recruitment
potential), harvest and movement of selected fish species
within these ecoregions.
Justification
Integration
of large, spatially explicit databases and ecological classification
of fish habitats can provide the framework for setting reference
expectations for fish health and survival across a large region.
With a computerized ecological classification system, reference
conditions can be estimated (modeled) for all habitats in
a region based on the unique landscape position and characteristics
of each site. Spatially explicit measurements of physical
and biological habitats can facilitate prediction of fish
production (Mason et al. 1996), impacts by exotic species
(zebra mussel, ruffe) (Nalepa et al. 1995), pollution (EPA),
and coastal zone development. Analysis of spatial patterns
of fish distributions, abundances, and harvest, and the factors
that affect those patterns will facilitate management of fisheries
resources and stimulate research on the appropriate spatial
and temporal scales.
Status
Management
directed towards long-term sustainability of fisheries resources
should in part be based on a fundamental understanding of
functional relationships between fishes and their critical
habitats on the appropriate spatial and temporal scales. Regional
ecological classification has been utilized as a management
tool by managers of terrestrial landscapes, including streams
and small lakes on the landscape.
While
GIS-based ecological classifications have been developed for
many terrestrial and aquatic systems in the Great Lakes basin,
to date there has been little development of ecoregions directed
at the Great Lakes themselves, although spatially explicit
data and methods are now available. Recent advances in hydro-acoustic
and remote-sensing technology (i.e. AVHRR, which estimates
sea surface temperature) have encouraged collection of spatially
explicit estimates of fish production, primary and secondary
production, and abiotic factors (i.e. wind, currents, temperature)
in the Great Lakes. Examination of these datasets, along with
analysis of historic fisheries data, will facilitate understanding
of patterns in distribution and abundance of important sport
fishes and their prey.
Methods
Ecological
classification of Great Lakes fish habitats are being developed
using an iterative cycle of data analysis, map development,
examination, sampling, revision, and re-examination. Classifications
of ecoregions in each lake are being made using data from
a variety of sources collected independently over various
time periods. Data are being geo-referenced and assembled
in databases in a GIS. Geostatistics are used to expand discrete
point data collected during historic surveys into broader
polygons. Multiple map themes are examined for spatial correspondence
of key variables; this analysis provides tests of the initial
delineation hypotheses. Map layers representing indicator
species density and distributions will be generated.
Open-water
ecoregion classifications and databases will be merged with
other existing river and coastal wetland classifications and
their resulting GIS layers to delineate critical spawning
and nursery areas at the appropriate spatial scales. This
will include mapped spatial units and a relational database
of summarized attribute classes that describe a suite of physical
and biological attributes for each unit. Unit attributes will
include both recorded observations and predictions from models
(ours and others) of likely physical and biological characteristics.
Combinations of our classification with existing work on rivers
and coastal wetlands and developing work on offshore regions
will allow, for the first time, description of spatial relationships
that influence larger-scale ecological processes at work within
the lake ecosystems. GIS-based models will be used to estimate
indices of fish health (bioenergetic growth potential) or
spawning and recruitment potential of key species in newly
defined ecoregions to provide guidelines for managers or restoration
initiatives.
Preliminary Results
A report on preliminary cluster analysis results can be found here.
Shapefiles of preliminary clusters by lake can be downloaded by clicking on the links below:
Lake Superior (last updated: 10/05/2007)
Lake Michigan (last updated: 10/05/2007)
Lake Huron (last updated: 10/05/2007)
Lake Erie (last updated: 10/05/2007)
Lake Ontario (last updated: 10/05/2007)
Links
to Other Efforts
The
Coastal
Aquatic Gap Analysis is a means of gathering and organizing
existing information about spatial distributions of aquatic
organisms so that it may be displayed and analyzed. Gap Analysis
will enable scientists to project the occurrence of species
and biotic assemblages in areas that have not been explicitly
sampled, based on models of the relationships between those
species and enduring environmental features. This type of
analysis can be used to address many biodiversity issues,
as well as species-specific management concerns.
Mason,
D.M., and Brandt, S.B. 1996 Effects of spatial scale and foraging
efficiency on the predictions made by spatially explicit models
of fish growth rate potential. Env. Biol. Fish. 45(3):283-298.
Nalepa,
T.F., Wojcik, J.A., Fanslow, D.L., and Lang, G.A., 1995. Initial
colonization of the zebra mussel (Dreissena
polymorpha) in Saginaw Bay, Lake Huron: population recruitment,
density, and size structure. J. Great Lakes Res. 21:417-434.
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