Introduction:
The
work below represents annotations of recent journal articles which
discuss applications of Geographic Information Systems (GIS) in the
management of fisheries resources, whether commercial or recreational.
GIS has many uses in this field and the annotated sources below
are intended to provide a representative sample. The goal of this
project was to provide a learning experience for the author so that he
may better understand how GIS is used in his potential career field.
Annotated Bibliography:
Castillo,
J.,Barbieri, M.A., and Gonzalez,A. Relationships between sea surface
temperature, salinity, and pelagic fish distribution off northern
Chile. ICES J. of Mar. Sci. 53:139-146 (1996)
In
this study, the authors used GIS techniques to analyze the spatial
distribution of three pelagic fisheries (anchovy, sardine, and jack
mackerel) off the coast of Northern Chile. This information was
analyzed in relation to surface temperature and salinity profiles.
Data on the distribution of the fish was collected via
hydroaccoustic estimations. This information was obtained
simultaneously with the collection of temperature and salinity data,
during seasonal research cruises from 1993-1994. Not
surprisingly, the analysis showed that the distribution of the three
species was associated with strong thermal and haline fronts.
Perhaps more interestingly, the results also showed a stratified
distribution of the three species of fish together.
Creque,
S.M., Rutherford, E.S. and Zorn, T.G. Use of GIS-Derived
Landscape-Scale Habitat Features to Explain Spatial Patterns of Fish
Density in Michigan Rivers. N. Am. J. of Fish. Man. 25:1411-1425 (2005).
Multiple
linear regression analysis of a regional fish and habitat database was
used to determine the possibility of using GIS derived landscape-scale
habitat variables to explain the spatial variability in the density of
five sport fish in the river’s of Michigan’s Lower Peninsula.
Both small scale (site) and large scale (landscape) processes are
important to fish distributions. Understanding the relative
importance of these processes can help direct management and research
efforts to be conducted at the correct scale. Ultimately, this
study found that traditional site-scale habitat variables explained
less of the variation in fish density than landscape scale variables.
There is considerable unexplained variability associated with the
GIS derived models (associated assumptions and limitations), but they
provide insight into important habitat variables (such as temperature)
that effect fish distribution patterns on a large scale. The
authors concluded that these findings indicate that coarse measurements
obtained from GIS analysis can be useful in predicting the density of
individual fish densities and this tool would be especially helpful to
managers needing to make low-cost widespread decisions.
Franklin, E.C. et al. Benthic Habitat Mapping in the Tortugas Region, Florida. Mar. Geodesy. 26:19-24 (2003).
This study was part of a fisheries independent monitoring program in
association with the Dry Tortugas National Marine Park and the Florida
Keys National Marine Sanctuary. These MPAs were interested in
expanding their no-take zones in response to the decline of coral reefs
and reef fish stocks in Florida. To allow for a habitat-based,
stratified random sampling design of reef fish, the authors created a
digital benthic habitat map of the coral reef and hard-bottom habitats.
This was done using a GIS which allowed for the synthesis of
several different types of data, including bathymetric surveys,
side-scan sonar, in situ visual analysis and aerial photogrammetry.
Similarly to some of the work done in our Geo 565 labs, a
classification scheme was developed based on nine reef habitat types
found from 1-30 meters depth. A significant outcome was that from their
mapping the authors were able to provide estimates of area by habitat
type for the location of new no-take zones in the Tortugas region.
Keleher,
C.J. and Rahel, F.J. Thermal Limits to Salmonid Distributions in the
Rocky Mountain Region and Potential Habitat Loss Due to Global Warming:
A Geographic Information System (GIS) Approach. Trans. of the Am. Fish. Soc. 125:1-13 (1996).
In this study the authors used a GIS to combine various databases to
analyze the impact of global warming on salmonid populations in Wyoming
by comparing spatial distributions expected under various warming
regimes. Temperature is known to limit the distribution on
juvenile salmon in the region. That is, salmonids are not found
in streams where mean July air temperature exceeds 22oC and therefore salmon are highly susceptible to climate forcing. An increase in 3 oC,
as predicted by some global climate change models, in mean July air
temperature was shown to reduce the area of suitable salmonid habitat
by 38.5 % in Wyoming and by 49.8% in the Rocky Mountain Region.
In general, an increase in air temperature resulted in greater
habitat loss in the Rocky Mountain Region than in Wyoming. The
authors concluded that this was because as warming occurs, salmon are
forced into increasingly higher elevations. These populations
would then become fragmented as suitable habitat is distanced from main
river channels and limited to cold headwater streams. Thus, by
use of a GIS the authors were able to store and organize spatial data,
make predictions on the impacts of global warming to salmon
populations, and conclude that global warming will result in habitat
loss and population fragmentation.
Milner,
N.J., Wyatt, R.J. and Broad, K. HABSCORE- applications and future
developments of related habitat models. Aquatic Conserv: Mar.
Freshw. Ecosyst. 8: 633-644 (1998).
This
article consists of four main sections. In the first section, the
role of habitat evaluation methods (HEMs) were explained in regards to
fisheries management. The second section introduces HABSCORE, a
new system of salmonid stream habitat measurement and evaluation that
is based on empirical models and site features. HABSCORE and
other HEMs are compared via the ability of a particular model to
explain variance in fish population density in the third section.
Finally, in the forth section the authors consider other
contemporary HEMs, but conclude that future fisheries applications will
require the combination of GIS-based classification schemes and
site-based classification schemes, an approach that is being developed
through HABSCORE. Go HABSORE go. Note- this article ties in
well with concepts addressed by Keleher and Rahel (1996), discussed
above.
Pecquerie,
L. et al. Distribution Patterns of key fish species of the southern
benguela ecosystem: an approach combining fisher-dependent and
fishery-independent data. Afr. J. mar. Sci. 26: 115-139 (2004).
In
this paper, the authors were interested in applying ecosystem-based
fisheries management in the southern Benguela ecosystem. It was
decided that comprehensive quantitative information on the
distributions of key marine species was needed. To meet this
need, six sources of data were combined in a GIS to map the spatial and
temporal distribution of 15 key fish species in the Benguela system.
Unfortunately, biases as a result of major sampling differences
prevented detailed analysis of certain species, but maps of the density
distributions are presented along with the method used to create them.
Perez,
O.M., Telfer, T.C., and Ross, L.G. Use of GIS-Based Models for
Integrating and Developing Marine Fish Cages within the Tourism
Industry in Tenerife (Canary Islands). Coastal Mngmt.31: 255-366 (2003).
The
authors of this study used GIS and other similar technology to build a
spatial database that incorporated identified criteria (such as
distance from shore) thought to have an influence in successfully
integrating marine fish-caged aquaculture with the tourism industry in
Tenerife. The criteria were grouped into sub categories and then
combined to produce a final output that indicated the most suitable
areas for cage-based aquaculture to exist along side the tourism
industry. The results indicated that a majority of the Tenerife
coastline was suitable for such as a project. However, the
authors also noted that GIS does not provide a definitive answer to a
given problem; GIS can only generate outputs to a range of input data.
The analysis in this study indicated some if the limits to where
aquaculture can be placed.
Rowe,
D.K. et al. Use of GIS to predict effects of watr level on spawning
area for smelt, Retropinna retropinna, in Lake Taupo, New Zealand.
Fish. Man. & Ecol. 9: 205-216 (2002).
A
3D GIS model of bathymetry and substrate composition was developed and
used to calculate the total area of smelt, Retropinna retropinna,
spawning habitat for five different water levels of Lake Taupo in New
Zealand. The results showed little change in spawning area over
the first 50 cm below natural maximum lake levels, but spawning habitat
greatly decreased over the next 1.4m, indicating that a 30% reduction
would occur at the natural minimum lake level. The model was
substantiated by anecdotal evidence that high lake levels in the spring
result in high smelt recruitment. Thus, higher water levels mean
greater spawning habitat area for the smelt. The authors conclude
that their model could have applications for the effect of lake level
change on other biota such as microphyte algal cover.
Rubec,
P. J. 1999. GIS as a tool for research, management and
placement of artificial reef fisheries. Pages 112-121, In: Florida
Artificial Reef Summit ‘98, Proceedings of a conference held 5-7
March 1998 in West Palm Beach, Florida. Florida Department of
Environmental Protection, and Palm Beach Country Department of
Environmental Resources Management.
This
article details the use of GIS in planning the location of artificial
reefs, which can serve as essential fish habitat. These
artificial reefs can provide shelter from predation and associated fish
will forage over the surrounding area. Thus, the use of
artificial reefs can be an important fisheries management tool.
However, artificial reefs must be placed in a suitable habitat and may
be a part of an overall zoning structure or plan, which allows for
differing levels of human use. The application of GIS to conduct
spatial analysis can ensure the proper placement of artificial reefs,
reduced user conflicts, and the creation of a successful MPA.
Valavanis, V.D. et al. Critical regions: A GIS-based model of marine productivity hotspots. Aquat. Sci. 66: 139-148 (2004).
In
this study, a GIS model for the identification of marine productivity
hotspots (defied as areas of high chlorophyll concentration and low
temperature distribution) in the Eastern Mediterranean Sea is
developed. Spatial data from a variety of sources including
monthly satellite imagery of Advanced Very High Resolution Radiometer
(AVHRR), sea surface temperature (SST), and Sea-viewing Wide
Field-of-view Sensor (SeaWiFS) chlorophyll concentration is integrated
to map anomalous distributions of these parameters. The
geographic distribution of these anomalies is used to identify areas of
above average chlorophyll and below average SST (potential hotspots).
These locations were then compared to fishery production data
indicating both under-exploited areas and over-exploited areas of the
Mediterranean that require immediate management actions.