The Use of GAM Modeling Techniques to Evaluate the Effects of Freshwater
Flow Into Florida Bay- Part 3- Sport Fishes
Darlene Johnson and Joan Browder
NOAA Fisheries, Miami, FL
Everglades National Park creel census data (1985-1999) was used to develop
models of nine species of sport fishes in Florida Bay to evaluate whether these
data can be useful performance measures to evaluate the impact of freshwater
flow and/or salinity on fishery resources of Florida Bay. Salinity maps were
created for each of the areas, and fishery data were linked to the average monthly
salinity of an area and indices of freshwater flow, rainfall, and wind. The fishery
data came from three major areas, the northern bay, the western bay, and the
southern bay. A review of the raw data indicated that the greatest number of fish
was taken from the western bay, followed by the northern bay. Highest catch
rates (catch/angler hour) for the combined nine selected fishes were in southern
bay, followed by the western bay.
The species caught in the highest numbers were spotted seatrout, gray snapper,
and crevalle jack. Highest catch/angler hour of spotted seatrout, gray snapper,
and pinfish were from the southern bay, although highest catches of all three
species were in the western bay. The western bay had both the highest
catch/angler hour and the highest catches of snook and black drum. Sheepshead,
crevalle jack, and red drum were taken at the highest catch/angler hour in the
northern bay, but total catches of these species were highest in the western bay.
Ladyfish were taken at the same catch/angler hour in all areas, but highest catches
were in the western bay. Spotted seatrout was the species with highest catch rate
in the western and northern bay areas. In the southern bay, gray snapper had a
slightly higher catch rate than spotted seatrout. These results do not reflect
fishery closures, although data used in model development were adjusted for
closed periods of the snook, red drum, and spotted seatrout fisheries.
General additive models were constructed for spotted seatrout, red drum, snook,
black drum, sheepshead, ladyfish, crevalle jack, and pinfish. Models were
constructed with and without “year” as a categorical variable. The inclusion of
year in the models provided an annual abundance index standardized for the effect
of other independent variables. The exclusion of year as a variable in a second set
of models allowed a clearer picture of the annually varying effects of salinity,
rainfall, freshwater flow, and other environmental variables, especially those for
which no spatial data were available. All models with year except for the one for
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snook had the higher r2, suggesting that the year variable incorporated unknown
factors that were not included in the models.
In the models without year, area, month, wind, and salinity were important to the
same number of species as in the year model, but temperature (3 species), rainfall
(7 species), and freshwater flow (7 species) were important to a greater number of
species, suggesting that the year variable was not independent from these
variables.
Snook and spotted seatrout did not show a significant relationship to monthly
average salinity within an area. There was a negative relationship between gray
snapper adjusted catch rates and salinity at the lower end of the salinity scale,
changing to a positive relationship between gray snapper catch rates and salinity
higher on the salinity scale. Predicted relationships with salinity may reflect
catchability rather than abundance. Widespread hypersaline conditions may cause
fish to concentrate in lower salinity nearshore locations where they are more
vulnerable to fishing. Furthermore, the average salinity of a fishing area does not
reflect salinity at which the fish were actually caught.
Yearly salinity patterns may be more important than the average bay salinity at
time of capture. Highest model predicted standardized catch rates of spotted
seatrout, red drum, snook, jack crevalle, ladyfish, and pinfish were in belowaverage-salinity years (average from 1985-1999 was 32.1 ppt), and highest
standardized catch rates of sheepshead, and gray snapper were in higher-thanaverage years. Gray snapper highest catch rate was in a year close to average
(32.1 ppt). Lowest model predicted standardized catch rates of red drum,
sheepshead, and snook were in higher-than-average salinity years, and lowest
standardized catch rates of black drum gray snapper, spotted seatrout, ladyfish,
crevalle jack, and pinfish were in below-average-salinity years. There was not a
large difference in annual Bay salinity between years of highest and lowest
predicted abundance for some species (ladyfish, crevalle jack, gray snapper, and
pinfish).
Catch rates of some gamefish species in any given year may be related to salinity
and freshwater inputs of previous years rather than current years. Highest
predicted catch rates of red drum, sheepshead, gray snapper, snook, pinfish, and
spotted seatrout followed multi-years of higher than average freshwater inflows,
whereas black drum, ladyfish, and crevalle jack highest catch rates followed
multi-years of lower than average freshwater flow. Previous years’ fresh water
flow may influence the growth and survival of juvenile stages, and it is the
abundance of juveniles one or more years previously that determines adult
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abundance of the current year. Four species (sheepshead, gray snapper, pinfish,
and spotted seatrout) had both their highest and their lowest predicted catch rates
following above average flow years. Spotted seatrout (an estuarine species) has
been shown to occur in higher numbers in low salinity waters in fishery
independent studies, so lower predicted catch rates during high flow years is
inconsistent with what is known about this species. For most species examined,
models suggest that salinity relationships were inconsistent with expected
conditions for highest and lowest catch rates and what has been reported
elsewhere for these species.
Individual fishing area models were developed for spotted seatrout. The models
for the northern, western, and southern areas had a better model fit than the
pooled model, which had fishing area as a categorical variable. In both spotted
seatrout models (with and without year as a categorical variable) of the western
bay, neither rainfall nor freshwater flow were significant factors. In the southern
bay model, catch rates had a parabolic relationship with rainfall, but flow was not
significant. Both rainfall and freshwater flow were significant in the northern
bay, and peak catch rates were related parabolically to both. In spotted seatrout
models without year as a categorical variable, catch rates were parabolically
related to cumulative freshwater flow in the northern bay but negatively related to
freshwater flow in the western bay. Seatrout catch rates were parabolically
related to cumulative rainfall in the northern and southern bays but positively
related to rainfall in the western bay. Area salinity was positively related to
catches in the western bay model but was insignificant in other area models. The
cumulative time period for rainfall and freshwater that correlated best with
modeled fish catch rates differed among areas. The northern bay responded to the
longest period, and the southern bay responded to the shortest.
In general, the index of area salinity was not a good predictor of creel catch rates
of estuarine species, probably because the scale of the index is too coarse an
approximation of the salinity at which fish were caught. Positive correlations
with salinity and negative relationships to rainfall or freshwater flow for estuarine
species may suggest that high salinity conditions in the Bay cause fish to
concentrate in limited favorable areas where they are heavily exploited. Higher
catch rates during these times may reflect increased catchability rather than
increased abundance. Seasonal and long-term closings of red drum, snook, and
spotted seatrout fisheries likely contributed to high predicted catch rates of the
1990's.
Johnson, Darlene, NOAA Fisheries, 75 Virginia Beach Drive, Miami, FL 33149
Phone 305 361-4490, Fax 305 361-4478, darlene.johnson@noaa.gov, Question 5
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