2010 SOUTHEASTERN NATURALIST 9(4):649–672
Fish Assemblage Variability in a Florida Spring
Kirsten Work1,*, Melissa Gibbs1, Brenda Peters1, and Laura French1
Abstract - Florida springs are generally characterized as static ecosystems with
unique faunal and floral assemblages that persist under relatively stable physical
and chemical conditions. We sampled the fish fauna of Volusia Blue Spring to
determine whether this presumption would withstand scrutiny at a higher temporal
resolution and over time. We sampled by seining or snorkeling at five stations
along the 320-m run weekly or bimonthly from October 2000 to September 2004.
This four-year study consisted of 1152 samples that produced approximately
164,000 observations of 30 species of fish on 72 sampling trips. Concurrent water
quality samples were collected at 14 sites along the center of the run and at each
of the seine sites. Virtually anoxic water discharged from the spring head, but this
water accumulated oxygen as it traveled the run. Fish density and species composition
also changed dramatically along the length of the run. Species that tolerate low
oxygen concentrations, such as poeciliids, dominated the assemblage at the spring
head. Species that use patches of algae or small backwater areas, such as fundulids,
were prominent in the middle reach of the run. Larger species, such as centrarchids
and Lepisosteus spp., were abundant in the lower reach of the run. Within these
broad patterns, most species exhibited great variability in density, probably due to
the influence of variable emigration of potential predators, and also perhaps smaller
species, from the St. Johns River.
Introduction
In most streams, fish species are patchily distributed and segregate with
respect to an array of abiotic and biotic factors, such as water depth and velocity,
substrate type, dissolved oxygen concentrations, temperature, aquatic
plants and other structure, and competitors or predators (Dibble and Harrel
2000, Gorman and Karr 1978, Kessler et al. 1995, McKinsey and Chapman
1998). These patches may shift with changes in season or with periodic disturbances,
such as floods or droughts. Variation in water inputs often causes
major changes in the morphometry and water chemistry of streams, which in
turn affect stream fish assemblages. Seasonal and periodic changes in water
input and associated physical and chemical parameters that are typical of
streams are not present in most natural springs. Springs are comparatively
stable environments, with little variation in temperature and water chemistry,
primarily because spring water originates from large underground
aquifers (Hubbs 1995, Whitford 1956).
In contrast to the diversity of abiotic and biotic factors that influence
stream fishes, low dissolved oxygen concentration has been
considered one of the most important factors that control longitudinal
1Stetson University Biology Department, DeLand, fl32724. *Corresponding author
- kwork@stetson.edu.
650 Southeastern Naturalist Vol. 9, No. 4
fish distribution patterns in springs (McKinsey and Chapman 1998). In
many springs, water issuing from the spring head is anoxic or hypoxic.
Dissolved oxygen concentrations in Florida springs often range from zero
to 2.6 mg/L and average under 1 mg/L during the day throughout the year
(McKinsey and Chapman 1998), whereas the dissolved oxygen concentrations
of unpolluted temperate lakes and rivers average from 7 to10 mg
O2 L-1 during daylight hours (Matthews 1998). Oxygen concentrations as
low as those recorded in Florida springs have been associated with large
fish kills in eutrophic lakes that experience a rapid depletion of oxygen to
3–4 mg L-1 (Bennett 1971). In springs, upstream fish assemblages exhibit
more specialization to the oxygen-poor waters (e.g., upturned mouth,
small body size, aquatic surface respiration) than the downstream assemblages,
which experience a relatively oxygen-rich habitat (Hubbs 1995).
Many of the habitats found in streams also are present in springs (highflow center-channel areas, low-flow backwater areas, snags, submerged
vegetation); however, the constant flow and low dissolved oxygen of springs
affect the suitability of these areas as fish habitat. In streams, center-channel,
high-flow areas usually are more oxygenated than backwater areas that
receive loads of detritus, as decomposition of this detritus may deoxygenate
the water. During low water, streams may be reduced to center-channel
pools and riffles that are only marginally or seasonally connected, restricting
fish movement along the stream (Matthews 1998). During high water, fish
may inhabit backwater areas to escape high, scouring flows. In contrast to
streams, the center-channel high-flow areas of springs may possess the lowest
dissolved oxygen; low-flow backwater areas may support greater algal
growth and therefore higher oxygen concentrations. These low-flow areas
also may allow fish to avoid the constant high flow of the center channel
of springs. The constant flow and water chemistry of a spring provides a
consistent habitat with little seasonal variability. This consistent habitat also
can serve as a refuge for species or populations that typically inhabit more
variable rivers.
The goal of this study was to survey the fish assemblage of Volusia
Blue Spring, flspatially and over time to identify factors that influence
fish density and distribution in this well-delineated and stable habitat. Few
ecological studies of cool-water springs have been published (e.g., Herald
and Strickland 1949, Hubbs 1995, Hubbs and Allen 1943, McKinsey and
Chapman 1998, Munch et al. 2006, Odum and Caldwell 1955, Walsh et al.
2009), and most studies have not investigated both inter-annual and seasonal
variation in a cool-water spring. For Volusia Blue Spring, we hypothesized
that fish would be segregated longitudinally on the basis of dissolved oxygen
concentration and horizontally into oxygen-rich microhabitats along the
shoreline. Finally, although springs are generally stable with consistent flow
throughout the year, we expected seasonal variation in fish assemblages due
to the influx of large species from the St. Johns River that use the run as a
warm-water refuge during the winter.
2010 K. Work, M. Gibbs, B. Peters, and L. French 651
Study Area
Volusia Blue Spring in central Florida (28°56'51.0"N, 81°20'22.5"W) is
a first magnitude spring that has discharged water historically at an average
of 4.6 m3 s-1 or 162 cubic feet per second (cfs) (range = 1.8–6.1 m3 s-1) daily
from the Floridan aquifer into the St. Johns River (Scott et al. 2004). The
run is 320 m long and approximately 20–30 m wide. Quercus virginiana
Miller (Live Oak) and Sabal palmetto Walter (Sabal Palm) line the banks,
and little submerged vegetation occurs in the run. The run possesses gently
sloping banks with scattered woody debris at low water. During high flows,
water reaches steep muddy banks, allowing organisms access to holes in the
mud. The run possesses no physical longitudinal delineation (i.e., no riffle/
pool structure) other than a deep hole at the spring head and a slight slope to
the river. The run provides habitat for more than 40 species of fish (Florida
Division of Recreation and Parks 2005), including several nonindigenous
species, such as Oreochromis aureus (Blue Tilapia) and two South American
armored catfish species, Pterygoplichthys disjunctivus (Vermiculated
Sailfin Catfish) and Hoplosternum littorale (Brown Hoplo). During summer,
public recreation heavily affects the upper portion of the run; large numbers
of people swimming, tubing, and wading in the run completely denudes the
center channel of algae. Megalops atlanticus (Tarpon) and the threatened
Trichechus manatus latirostris (Harlan) (Florida Manatee) use the run as
winter habitat (Florida Division of Recreation and Parks 2005).
Methods
Sampling
We sampled five stations for fish, weekly or semi-monthly, from October
2000 to September 2004 (Fig. 1). The stations were relatively evenly distributed
along Volusia Blue Spring run. Each sampling effort began at the
headspring (station 1) and continued downstream to station 5. Over the four
years of this study, we conducted 72 surveys of the run, although on several
occasions we were unable to sample the stations near the St. Johns River.
We sampled stations 1–4 during every month of the year, whereas station 5
was under-sampled in fall due to backflow of tannin-stained river water and
danger of alligators. Inclement weather also precluded complete surveys on
some dates.
The area of each station was approximately 500 m2, with the exception of
station 1, which encompassed the entire headspring and so was much larger
(2500 m2). At each of the five stations, we used a 6-m x 2.4-m seine with 3-mm
mesh to sample three subsampling sites (each approximately 6 m long x 3 m
wide, and 30 cm–1 m deep) for small fish. We identified these fish in the field
and released them. The subsampling sites were located along the bank on both
sides of the spring run, and we sampled these sites throughout the course of
the study. We used the following criteria for initial selection of subsampling
652 Southeastern Naturalist Vol. 9, No. 4
sites: presence of fish, nearby cover (bushes, submerged limbs, algal beds),
and relative freedom from obstacles within the site. We recognize that avoiding
structure for logistical reasons biased our samples against species that
were associated with structure (Angermeier and Karr 1984). We sampled the
same sites with the same methods throughout the four-year study, so we consider
our composite data to be a representative assessment of fish assemblage
variability in Volusia Blue Spring. All sites had sandy bottoms and varying
amounts of algae, with the exception of two sub-sampling sites at Station 1.
Station 1 was rocky with little available cover, as it experienced the most human
disturbance from swimmers frequently sitting along the banks. Stations
2 and 3 were exposed to moderate human disturbance from swimmers in the
center of the run; these two stations had available cover in the form of algae
and woody debris, particularly along the banks. Stations 4 and 5 experienced
little or no human disturbance, as the public was not allowed to access these
areas, and these stations contained moderate cover. Station 5 had more leaf
litter than the other stations and was seasonally inundated by the St. Johns
River during late summer and fall. Finally, after seining was completed, we
surveyed the area encompassing all three sub-sampling sites at each station
via snorkeling to identify and enumerate larger (>8 cm) fish species that easily
evaded the seine. This snorkel survey represented a fourth sample of each
station. We identified all fish to species, except Lepisosteus osseus (Longnose
Gar) and L. platyrhincus (Florida Gar). Highly spotted L. osseus were common
in the run, making the discernment of retreating Lepisosteus species
difficult. Similarly, very small Lepomis macrochirus (Bluegill) and L. gulosus
Figure 1. Sampling stations within Volusia Blue Spring, fl. Large dots along the
periphery of stations represent subsampling sites, and small dots in the mid channel
represent water quality sampling sites.
2010 K. Work, M. Gibbs, B. Peters, and L. French 653
(Warmouth) were difficult to differentiate while moving, so we also combined
data for these two species. We recognize the possibility that we counted fish
twice, but we consider the seine sites within a station far enough apart to have
limited this problem for the density estimates of small fish. While snorkeling,
we attempted to keep track of fish movements to reduce the problem of double
counting larger species during snorkel counts.
We collected concurrent water quality data at each of the subsampling
sites and at 14 mid-channel stations along the length of the run (Fig. 1). At
each of the subsampling sites, we measured surface water velocity and dissolved
oxygen concentration after each fish collection. We anticipated that
the subsampling sites near the bank would provide refuges of lower flow and
higher dissolved oxygen from the center channel of the run. We estimated
surface water velocity with the rate of travel of a float. We measured dissolved
oxygen concentration with a handheld YSI 85 multiparameter meter
(Yellow Springs, OH). At each of the 14 mid-channel stations, we measured
water velocity as above; we measured temperature, dissolved oxygen, and
specific conductance (± 1% accuracy for all measurements) with the handheld
YSI meter; and we collected pH data with an Oakton pH test handheld
meter (Vernon Hills, IL). In Volusia Blue Spring, surface water velocity,
discharge, and gage height vary somewhat independently of each other due
to the influence of the St. Johns River’s large hydraulic head on the spring’s
flow. When the St. Johns River gage height is high, river water can backflow
into the spring, causing high gage height in the spring and sluggish flow,
regardless of the discharge from the springhead. However, water quality can
vary with discharge (K. Work, unpubl. data), so we considered discharge as
a potentially important parameter in addition to flow rate and gage height.
We acquired discharge and gage height data for the spring from the US
Geological Survey online database of streamflow (station 02235500: http://
waterdata.usgs.gov/fl/nwis/rt). In our analyses, we only used data that had
been collected within two days of our sample dates.
Data analyses
We evaluated annual, seasonal, and spatial variation in water velocity,
dissolved oxygen concentration, total fish density, and densities of
individual species with separate Kruskal-Wallis nonparametric multisample
tests. The coefficient of variation (CV) was used to quantify the magnitude
of variability in discharge, water velocity, specific conductance, and total
fish density across all dates. Fish assemblage variability was evaluated with
a principal components analysis (PCA). Principal components analysis creates
new composite variables that are linear combinations of variables in
the original dataset, thereby reducing the complexity of large data sets of
many species or parameters. These new composite variables can be analyzed
for large-scale shifts in assemblages, such as seasonal or annual changes.
Natural log-transformed densities of all fish species in all samples (all dates
654 Southeastern Naturalist Vol. 9, No. 4
and stations) were used in the PCA, but we eliminated any species that occurred
in fewer than 25% of the samples. We plotted the first two axes of the
PCA; each data point represented the fish assemblage on a particular date
at a particular station. We overlaid three sets of polygons on the same PCA
data points in three separate graphs to represent samples grouped either by
years, seasons, or stations to determine whether annual, seasonal, or spatial
patterns were present in the fish assemblage data. For example, if polygons
among years exhibited no overlap, then the fish assemblage differed in
composition between years. If polygons were approximately the same size
and had the same position in PCA space, then either the fish assemblage
was similar between years or the variability was too great to discriminate
between years.
To examine whether variation in fish densities was related to physical or
chemical characteristics of the run, we calculated Spearman rank correlations
between water velocity, dissolved oxygen, and measures of fish species
density. Where large numbers of correlations were calculated, the alpha level
for significance was adjusted with a Bonferroni correction (Miller 1991).
All statistical calculations were made using SPSS 13.0 (SPSS 2004). When
correlations between water velocity and fish density appeared nonlinear, we
determined whether each species typically minimized or maximized their
exposure to high water velocities. For each station, we divided the water
velocity of the subsampling site in which each species was observed (or the
average of multiple subsampling sites if the species was present at more than
one subsampling site) by the maximum water velocity available at a station.
For example, for species i at station 1:
% maximum water velocity available = water velocity in subsample used by
species i / maximum water velocity in station 1.
We repeated this process to assess fish associations with dissolved oxygen.
Results
Physical and chemical characteristics
Discharge from the headspring was high (2.7–5.2 m3 s-1 or 63–214 cfs)
and fairly consistent (CV = 12%), even though the study period included
recovery from a drought. High discharge, however, did not correspond with
high gage heights or with high water velocities, both of which correlate
more with changes in water volume of the St. Johns River than with the
discharge from the spring. The influence of the large and variable hydraulic
head of the St. Johns River causes an increase in gage heights regardless of
discharge after long periods of high rainfall. Seasonal changes in the hydraulic
head of the St. Johns River produced significant variation in water
velocity (χ2 = 7.9, df = 3, P = 0.05), with highest average velocities for the
run in spring (0.31 m s-1 ± 0.10 SD) and lowest in fall (0.19 m s-1 ± 0.10
SD). Water velocity was predictable at large spatial scales, with the high2010
K. Work, M. Gibbs, B. Peters, and L. French 655
est velocities at station 2, due to the narrowing of the channel beyond the
headspring, and lowest at station 5, due to the wider channel at that station
(χ2 = 37.0, df = 4, P < 0.001; Fig. 2A). Velocity was consistently higher in
the center of the channel than on the banks (center channel average velocity
was ≥0.2–0.5 m s-1, while the velocity was often 0 m s-1 on the bank; χ2 =
58.8, df = 1, P < 0.0001). Despite these clear spatial patterns, water velocity
was highly variable among stations (CV = 146%) and at a station over
time (CV = 93% for one subsampling site at station 1 across all dates).
Dissolved oxygen concentration varied seasonally (χ2 = 11.5, df = 3, P =
0.009), with highest averages of samples from the entire run in summer (1.6
mg L-1 ± 1.0 SD) and lowest in fall (1.1 mg L-1 ± 0.56 SD). Dissolved oxygen
concentration also varied spatially (χ2 = 178.1, df = 4, P < 0.001), with lowest
concentrations at the springhead and highest concentrations at the two
stations near the confluence with the St. Johns River (Fig. 2B). Near the
banks, dissolved oxygen concentration occasionally reached 4–6 mg L-1, but
it was typically much lower (bank average = 1.26 mg L-1 ± 0.74 SD). Within
a given site, the dissolved oxygen concentration measurements near the bank
always exceeded measurements in the center of the channel (center channel
average = 0.76 mg L-1 ± 0.80 SD; χ2 = 239.6, df = 1, P < 0.0001). Variability
in dissolved oxygen among all samples was high (CV = 128%), although
variability among dates for one station was much lower (CV = 44% for one
subsampling site at station 1).
Specific conductance was high compared to many freshwater streams
(all sample average = 1450 μS cm-1 ± 370 SD). It was variable seasonally
(χ2 = 45.8, df = 3, P < 0.0001), with highest values in summer (average of all
center channel stations = 1650 μS cm-1 ± 400 SD) and lowest in winter (average
of all center channel stations = 1230 μS cm-1 ± 180 SD), but not variable
spatially (χ2 = 0.15, df = 4, P = 0.99). Variability was relatively low across
all stations (CV = 26%) and within one station (CV = 26% for station 1).
Variability in temperature and pH were negligible (all sample averages =
23.2 °C ± 0.71 SD and 7.67 ± 0.26 SD, respectively).
Fish assemblage patterns
Thirty-four fish species were observed during the course of this study
(Table 1). Total fish density (all individuals of all species) declined
down the length of the spring run (χ2 = 29.3, df = 4, P < 0.001; Fig. 3),
primarily due to high densities of Gambusia holbrooki (Eastern Mosquitofish)
at the headspring. Across all dates, 82.8% ± 18.6 SD of all fish
collected at the headspring were G. holbrooki. Total fish density also varied
seasonally (χ2 = 13.1, df = 3, P = 0.004; Fig. 3), again primarily due to
high G. holbrooki densities in winter. Gambusia holbrooki was the most
abundant fish species in the run on most sampling dates (58.6 ± 21.4%
SD of total fish density across all dates and stations). The total density of
fish was quite variable (CV = 133%).
656 Southeastern Naturalist Vol. 9, No. 4
Figure 2. Spatial variation
in Volusia Blue
Spring water velocity
(A), dissolved oxygen
concentration (B), and
specific conductance
(C) over the period of
2000–2004. Bars represent
averages for each
station across all dates
with standard deviations.
2010 K. Work, M. Gibbs, B. Peters, and L. French 657
Most species exhibited high inter-annual variation in occurrence, and
31.4% of species were not observed every year (Table 2). Densities of all
species, with the exception of Lepisosteus spp., Notemigonus crysoleucas
(Golden Shiner), Notropis chalybaeus (Ironcolor Shiner), Piaractus
brachypomus (Pirapatinga), and Ictalurus punctatus (Channel Catfish),
varied significantly among years (P < 0.05). Much of this variation was
sporadic; however, most centrarchids increased during the study period,
and most fundulids declined (Fig. 4). The nonindigenous loricariid, Pterygoplichthys
disjunctivus, also increased during the study period; at times,
we observed hundreds of fish in groups scattered along the spring run. We
observed large schools of the nonindigenous O. aureus in 2000, which had
virtually disappeared by 2001, and a small school of the nonindigenous
Table 1. Fish species observed in Blue Spring during 2000–2006 (* indicates nonindigenous
species).
Family Scientific Name Common Name Authority
Lepisosteidae Lepisosteus osseus Longnose Gar (Linnaeus, 1758)
Lepisosteus platyrhincus Florida Gar DeKay, 1842
Amiidae Amia calva Bowfin Linnaeus, 1766
Megalopidae Megalops atlanticus Tarpon Valenciennes, 1847
Cyprinidae Ctenopharyngodon idella Grass Carp* (Valenciennes, 1844)
Notemigonus crysoleucas Golden Shiner (Mitchill, 1814)
Notropis chalybaeus Ironcolor Shiner (Cope, 1867)
Notropis petersoni Coastal Shiner Fowler, 1942
Catostomidae Erimyzon sucetta Lake Chubsucker (Lacepède, 1803)
Characidae Piaractus brachypomus Pirapatinga* (Cuvier, 1818)
Ictaluridae Ictalurus punctatus Channel Catfish (Rafinesque, 1818)
Callichthyidae Hoplosternum littorale Brown Hoplo* (Hancock, 1828)
Loricariidae Pterygoplichthys Vermiculated Sailfin (Weber, 1991)
disjunctivus Catfish*
Mugilidae Mugil cephalus Striped Mullet Linnaeus, 1758
Atherinopsidae Menidia beryllina Inland Silverside (Cope, 1867)
Fundulidae Fundulus chrysotus Golden Topminnow (Günther, 1866)
Fundulus seminolis Seminole Killifish Girard, 1859
Lucania goodei Bluefin Killifish Jordan, 1880
Lucania parva Rainwater Killifish (Baird & Girard, 1855)
Poeciliidae Gambusia holbrooki Eastern Mosquitofish Girard, 1859
Heterandria formosa Least Killifish Girard, 1859
Poecilia latipinna Sailfin Molly (Lesueur, 1821)
Cyprinodontidae Jordanella floridae Flagfish Goode & Bean, 1879
Centrarchidae Enneacanthus gloriosus Bluespotted Sunfish (Holbrook, 1855)
Lepomis auritus Redbreast Sunfish (Linnaeus, 1758)
Lepomis gulosus Warmouth (Cuvier, 1829)
Lepomis macrochirus Bluegill Rafinesque, 1819
Lepomis microlophus Redear Sunfish (Günther, 1859)
Lepomis punctatus Spotted Sunfish (Valenciennes, 1831)
Micropterus salmoides Largemouth Bass (Lacepède, 1802)
Pomoxis nigromaculatus Black Crappie (Lesueur, 1829)
Percidae Percina nigrofasciata Blackbanded Darter (Agassiz, 1854)
Cichlidae Oreochromis aureus Blue Tilapia* (Steindachner, 1864)
Achiridae Trinectes maculatus Hogchoker (Bloch & Schneider, 1801)
658 Southeastern Naturalist Vol. 9, No. 4
Table 2. Occurrences of rare species in Blue Spring, fl. Many of these species were not collected
during routine sampling, but were observed at other times.
Species 2000 2001 2002 2003 2004 2005 2006
Amia calva X
Ctenopharyngodon idella X
Notropis petersoni X
Hoplosternum littorale X X
Menidia beryllina X X X
Jordanella floridae X
Enneacanthus gloriosus X
Percina nigrofasciata X
Oreochromis aureus X X X X X X
Trinectes maculatus X
Figure 3. Spatial and seasonal variation in density of the fish fauna of Volusia Blue
Spring over the period of 2000–2004. Bars represent averages for each station across
all dates with standard deviations.
P. brachypomus sporadically. However, due to high variation in counts
within a season, fewer than half of the species (8 out of 21) exhibited statistically
significant seasonal variation, and in most cases, inter-annual
2010 K. Work, M. Gibbs, B. Peters, and L. French 659
Figure 4. Temporal variation
in large predators (A),
centrarchids (B), and small
fundulids and poeciliids (C)
over the period of 2000–
2004. Values represent averages
for each date across all
stations, and error bars are
standard deviations.
660 Southeastern Naturalist Vol. 9, No. 4
variation was as great as or greater than seasonal variation (Fig. 4). Only
G. holbrooki, which produced large numbers of juveniles in winter, and
M. atlanticus, which used Volusia Blue Spring as a warm-water refuge
from cool river or ocean temperatures, exhibited a strong and predictable
seasonal pattern of high densities in winter.
All fish species varied spatially in density (number of individuals per
square meter, P < 0.001; Fig. 5). With the exception of poeciliids, the majority
of small species (fundulids, cyprinids, small centrarchids) were most abundant
midway down the run (stations 2 and 3), although Lucania parva (Rainwater
Killifish) densities also were high at the lower end of the run (stations 4–5).
Lepomis microlophus (Redear Sunfish) were most abundant at station 4. However,
most individuals of L. microlophus that occurred at sites 4 and 5 were
large (estimated total length > 20 cm versus ≈5–15 cm upstream). Larger species,
such as Micropterus salmoides (Largemouth Bass), Lepisosteus spp., and
M. atlanticus, generally were most abundant at the lower end of the run (stations
4 and 5), although M. salmoides also occurred at stations 2 and 3.
As a result of the large variation and differing patterns of density
among species, the first three axes of the PCA only explained 39.7% of the
variation in fish density. The first two axes explained the majority of this
variation (16% and 14%, respectively). Fundulids and poeciliids correlated
most with the first axis, and centrarchids correlated most with the second axis
(Table 3). Clusters of samples from different years and seasons overlapped
greatly (Fig. 6A, B). The polygons circumscribing PCA points for stations
also overlapped, although stations 1 and 5 were nested within a smaller
portion of the PC space than any of the other stations (Fig. 6C). Despite the
prevalence of large predatory species at station 5 that were virtually absent
at station 1, these two stations overlapped in the PC space because fundulids
and centrarchids were relatively scarce at both stations.
Table 3. Loadings of the fish variables on the first two principle components.
Species Axis 1 Axis 2
Lepisosteus osseus/platyrhincus -0.165 -0.115
Notemigonus crysoleucas -0.016 0.161
Pterygoplichthys disjunctivus -0.231 0.143
Mugil cephalus 0.208 0.355
Fundulus chrysotus 0.461 0.142
Fundulus seminolis 0.281 0.335
Lucania goodei 0.740 0.160
Lucania parva 0.525 0.079
Gambusia holbrooki 0.652 -0.284
Heterandria formosa 0.751 -0.075
Poecilia latipinna 0.697 -0.191
Lepomis auritus -0.067 0.482
Lepomis macrochirus/gulosus 0.065 0.778
Lepomis microlophus -0.095 0.351
Lepomis punctatus 0.053 0.648
Micropterus salmoides -0.092 0.357
2010 K. Work, M. Gibbs, B. Peters, and L. French 661
Figure 5. Spatial variation
in large predators
(A), centrarchids (B), and
small fundulids and poeciliids
(C) over the period
of 2000–2004. Values represent
averages for each
date across all stations,
and error bars are standard
deviations.
662 Southeastern Naturalist Vol. 9, No. 4
Figure 6. Plots of the first
two axes of principle components
analyses of the
Volusia Blue Spring fish
fauna showing annual variation
(A), seasonal variation
(B), and spatial variation
(C). The first two axes accounted
for only 30% of the
variation in the fish fauna.
2010 K. Work, M. Gibbs, B. Peters, and L. French 663
Relationships with water velocity and dissolved oxygen
Most species were affected by water volume in the run (gage height),
discharge, or water velocity; only seven species were unaffected by one
of these measures of water volume or flow rate (Table 4). However,
none of these relationships were linear; species’ densities typically were
high at low velocities and low to zero at moderate and high velocities
(Fig. 7). Even large species that were commonly found in the center
channel exhibited this type of distribution. Fish typically selected much
lower water velocities than the maximum available (average = 29% of
maximum available; Table 5). Only the largest species (Lepisosteus spp.
and M. atlanticus) and benthic species (I. punctatus and P. disjunctivus)
selected greater water velocities (average = 57% of maximum available).
Although we observed a shift in the assemblage from low-oxygen tolerant
poeciliids at the headspring to a much more diverse assemblage at the lower
end of the run, correlations with dissolved oxygen were weak (Table 4).
Plots of the distributions of most species relative to oxygen concentration
yielded unimodal or bimodal curves rather than positive linear relationships
(Fig. 8). However, all species controlled their oxygen exposure by selecting
areas with 70–80% of the maximum oxygen concentration available at a station
(Table 5).
Discussion
The stable and dramatic gradients in dissolved oxygen and water velocity
for Volusia Blue Spring supported the fish distribution patterns
predicted by previous studies of Florida springs (McKinsey and Chapman
1998, Odum and Caldwell 1955). The ability of poeciliids to use the airwater
interface for respiration in hypoxic water (McKinsey and Chapman
1998, McLane 1955, Odum and Caldwell 1955) allowed G. holbrooki
and Poecilia latipinna (Sailfin Molly) to occur at the headspring. Most
other small species, such as the fundulids, require higher dissolved oxygen
concentrations and are usually associated with algal beds and woody
structure (McLane 1955). These species’ densities typically were highest
downstream of the spring head, but upstream of the highest densities of
the larger potential predators, such as M. salmoides and Lepisosteus spp.
Lucania parva provided an exception to this pattern; the distribution of this
species greatly overlapped with potential predators, perhaps due to its ability
to change color for camouflage (Cox et al. 2009). The smaller species
(poeciliids, fundulids, cyprinids, small centrarchids) typically occurred
along the banks, areas that possessed significantly higher oxygen concentrations
and lower water velocities than the center of the channel. Finally,
low dissolved oxygen concentrations likely contributed to the virtual exclusion
of larger species from the spring head. Although Lepisosteus spp., M.
atlanticus, and P. disjunctivus gulp air at the surface (Graham 1997; Wootton
1990; K. Work, pers. observ.), areas with higher oxygen concentrations
664 Southeastern Naturalist Vol. 9, No. 4
Table 4. Spearman rank correlations (rs) of fish species with dissolved oxygen and flow in Blue Spring, Volusia County, fl. Fish density data were collected by
seine (small fishes) or by snorkel survey (large fishes) from October 2000 to September 2004. Significant (P < 0.05) correlations shown in bold.
Species Discharge Gage height Water velocity Dissolved oxygen
Lepisosteus osseus/platyrhincus rs = 0.17, P = 0.23 rs = -0.07, P = 0.65 rs = 0.03, P = 0.68 rs = 0.21, P = 0.0005
Megalops atlanticus rs = 0.20, P = 0.15 rs = 0.07, P = 0.64 rs = 0.21, P = 0.002 rs = 0.05, P = 0.39
Notemigonus crysoleucas rs = 0.35, P = 0.01 rs = 0.24, P = 0.09 rs = -0.07, P = 0.30 rs = -0.02, P = 0.69
Notropis chalybaeus rs = -0.05, P = 0.74 rs = 0.15, P = 0.30 rs = 0.04, P = 0.58 rs = -0.03, P = 0.63
Piaractus brachypomus rs = -0.08, P = 0.68 rs = 0.49, P < 0.0001 rs = 0.09, P = 0.18 rs = 0.07, P = 0.27
Ictalurus punctatus rs = 0.50, P < 0.0001 rs = 0.22, P = 0.13 rs = 0.01, P = 0.86 rs = -0.002, P = 0.98
Pterygoplichthys disjunctivus rs = 0.57, P < 0.0001 rs = 0.56, P < 0.0001 rs = 0.16, P = 0.019 rs = -0.15, P = 0.014
Mugil cephalus rs = -0.18, P = 0.21 rs = -0.40, P < 0.0001 rs = -0.02, P = 0.79 rs = 0.43, P < 0.001
Menidia beryllina rs = -0.04, P = 0.75 rs = 0.49, P < 0.0001 rs = 0.01, P = 0.88 rs = 0.02, P = 0.79
Fundulus chrysotus rs = -0.21, P = 0.13 rs = -0.36, P = 0.01 rs = 0.12, P = 0.046 rs = 0.12, P = 0.046
Fundulus seminolis rs = -0.06, P = 0.69 rs = 0.02, P = 0.90 rs = -0.10, P = 0.14 rs = 0.07, P = 0.26
Lucania goodei rs = -0.17, P = 0.23 rs = -0.59, P < 0.0001 rs = -0.07, P = 0.28 rs = 0.57, P < 0.001
Lucania parva rs = -0.16, P = 0.26 rs = -0.65, P < 0.0001 rs = -0.12, P = 0.063 rs = 0.41, P < 0.001
Gambusia holbrooki rs = 0.16, P = 0.27 rs = -0.24, P = 0.10 rs = -0.09, P = 0.16 rs = -0.17, P = 0.005
Heterandria formosa rs = -0.27, P = 0.05 rs = -0.60, P < 0.0001 rs = -0.18, P = 0.008 rs = 0.31, P < 0.001
Poecilia latipinna rs = 0.14, P = 0.33 rs = -0.08, P = 0.57 rs = -0.11, P = 0.11 rs = 0.008, P = 0.90
Lepomis auritus rs = 0.30, P = 0.03 rs = -0.23, P = 0.11 rs = 0.02, P = 0.74 rs = 0.37, P < 0.001
Lepomis macrochirus/gulosus rs = 0.52, P < 0.0001 rs = -0.32, P = 0.02 rs = 0.18, P = 0.006 rs = 0.29, P < 0.001
Lepomis microlophus rs = 0.004, P = 0.98 rs = -0.24, P = 0.09 rs = -0.07, P = 0.32 rs = 0.24, P < 0.001
Lepomis punctatus rs = 0.46, P < 0.0001 rs = -0.12, P = 0.39 rs = 0.03, P = 0.69 rs = 0.24, P < 0.001
Micropterus salmoides rs = 0.18, P = 0.21 rs = -0.18, P = 0.21 rs = -0.004, P = 0.95 rs = 0.41, P < 0.001
Pomoxis nigromaculatus rs = 0.03, P = 0.82 rs = 0.02, P = 0.91 rs = -0.03, P = 0.68 rs = 0.08, P = 0.17
Oreochromis aureus rs = -0.35, P = 0.01 rs = 0.30, P = 0.04 rs = -0.01, P = 0.87 rs = -0.001, P = 0.98
2010 K. Work, M. Gibbs, B. Peters, and L. French 665
Figure 7. The relationship
between fish density and
water velocity in Volusia
Blue Spring from 2000–
2004.
666 Southeastern Naturalist Vol. 9, No. 4
are less stressful to large fish (Wootton 1990). Even at the lower end of the
run, all three species were commonly observed gulping at the surface. Interestingly,
during periods of extremely high gage height during floods, we
observed a shift in these larger species toward the spring head, possibly in
response to the backflow of tannic-stained water from the river. Although
we could not seine at high gage heights, during these periods we also observed
a paucity of small fish, particularly Lucania spp. and Heterandria
formosa (Least Killifish), perhaps due to the proximity of large predators.
Despite the support for the predictable trends of species’ distributions
observed in other studies (McKinsey and Chapman 1998, Odum and
Caldwell 1955), the more extensive dataset of our study highlighted the
high degree of variation that underlies these predictable patterns, as indicated
by high coefficients of variation for fish densities relative to stream
fish populations and the low explanatory power of the PCA. Clearly, the
fish fauna did not fall into neat groupings based exclusively on water
velocity or oxygen tolerance, despite the high flow rates, extremely low
oxygen concentrations, and the strong and consistent oxygen gradient.
Most of the smaller (poeciliids, fundulids, small centrarchids) or benthic
(P. disjunctivus) species typically selected lower water velocities than the
maximum available at a station, but their nonlinear distributions relative
Table 5. Water velocity and dissolved oxygen preferences as a percentage of the maximum
available at a station (with standard deviation) in Volusia Blue Spring, flduring 2000–2004.
% max = percent maximum available (± SD).
Water velocity (m s-1) Dissolved oxygen (mg L-1)
Species Range % max Range % max
Lepisosteus osseus/platyrhincus 0-1.00 48.5 ± 39.7 0.12–4.86 74.7 ± 20.7
Megalops atlanticus 0–0.42 61.1 ± 39.8 0.51–2.19 71.4 ± 17.6
Notemigonus crysoleucas 0–0.56 24.4 ± 27.1 0.17–3.08 76.4 ± 21.3
Notropis chalybaeus 0–0.20 20.2 ± 30.4 0.18–2.48 72.5 ± 28.2
Ictalurus punctatus 0–0.36 79.1 ± 39.6 0.22–2.58 64.6 ± 23.3
Pterygoplichthys disjunctivus 0–0.57 41.0 ± 38.4 0.09–4.86 76.9 ± 20.3
Mugil cephalus 0–1.00 35.0 ± 34.8 0.18–6.04 71.5 ± 23.4
Menidia beryllina 0–0.17 23.2 ± 26.9 0.39–1.80 86.4 ± 13.9
Fundulus chrysotus 0–0.50 33.4 ± 29.4 0.19–6.04 72.6 ± 19.6
Fundulus seminolis 0–0.56 27.3 ± 28.5 0.18–5.23 75.4 ± 21.6
Lucania goodei 0–0.59 37.0 ± 26.9 0.09–6.04 69.6 ± 19.3
Lucania parva 0–0.72 38.3 ± 27.6 0.20–6.04 70.3 ± 16.5
Gambusia holbrooki 0–0.72 35.0 ± 19.4 0.06–6.04 70.1 ± 15.7
Heterandria formosa 0–0.59 32.3 ± 24.7 0.09–6.04 73.4 ± 21.2
Poecilia latipinna 0–0.56 33.4 ± 27.6 0.07–6.04 71.5 ± 19.0
Lepomis auritus 0–0.57 25.2 ± 26.7 0.22–4.57 79.6 ± 19.4
Lepomis macrochirus/gulosus 0–0.95 27.1 ± 23.6 0.14–6.04 76.1 ± 18.5
Lepomis microlophus 0–0.57 25.5 ± 27.6 0.16–5.23 79.4 ± 15.0
Lepomis punctatus 0–0.57 28.1 ± 28.5 0.22–4.97 77.6 ± 18.1
Micropterus salmoides 0–0.57 28.6 ± 25.8 0.16–4.97 74.6 ± 19.8
Pomoxis nigromaculatus 0–0.19 30.4 ± 40.4 0.55–4.51 81.6 ± 17.9
Oreochromis aureus 0–0.15 13.7 ± 14.0 1.31–1.58 98.4 ± 3.3
2010 K. Work, M. Gibbs, B. Peters, and L. French 667
Figure 8. The relationship
between fish density and
dissolved oxygen concentration
in Volusia Blue
Spring from 2000–2004.
668 Southeastern Naturalist Vol. 9, No. 4
to water velocity indicated that individuals selected higher velocities under
some conditions. Most species selected 70–80% of the maximum oxygen
concentration available at a station. For many species, the unimodal
relationships of fish density against dissolved oxygen concentration were
skewed toward lower oxygen concentrations, further suggesting that
fish were not selecting the maximum available oxygen concentrations as
might be expected in this system with extremely low dissolved oxygen
concentrations. These relationships suggest that although relatively constant
flow and oxygen gradients affect fish distributions in Volusia Blue
Spring, other factors, some of which may be biotic, modify the responses
of fish to these parameters.
Why is the Volusia Blue Spring fish fauna variable?
Several factors likely contribute to the variability of the fish fauna.
First, although Volusia Blue Spring differs from the St. Johns River in hydrology
and chemistry, the run is short and wide with a broad connection
to this large river. The St. Johns River contains a high diversity of organisms,
many of which use the run as a periodic resource rather than as a
permanent habitat, such as Trichechus manatus latirostris, M. atlanticus,
Mugil cephalus (Striped Mullet), and Callinectes sapidus (Blue Crab),
which are each present in the river on a seasonal basis (McLane 1955).
Several studies of stream fish assemblages have indicated that the location
of a site and the connectivity among sites within a landscape have
significant effects on site-level fish diversity (Erős and Grossman 2005,
Magalhães et al. 2002, Taylor 1997, Taylor and Warren 2001). Therefore,
it is likely that “stream level variability” (Dunham and Vinyard 1997),
or the variability of the St. Johns River, affected the variability of the
fish fauna in Volusia Blue Spring. The magnitude of the influx of species,
either as numbers of species or as numbers of individuals, has not
been quantified, but assemblage composition is likely to be influenced
at the very least by species that use the run as a thermal refuge in winter.
Large piscivorous species, like M. atlanticus, are predaceous on smaller
species, whereas others may alter the availability and distribution of resources.
For example, manatee movements and the feeding activity of
P. disjunctivus can strip attached algae off the bottom of the run, thereby
removing habitat for smaller fish species (K. Work, unpubl. data). We did
not quantify these activities, so we can only speculate as to their effects
on fish variability. However, the influx of more than thirty M. atlanticus
(>2 m long), for example, to a 620-m run likely would affect the densities
and distributions of other fish species in the run. Furthermore, less visible
species that move into and out of the run from the St. Johns River may
have more subtle effects on the fish fauna. Large species like M. atlanticus
may have home ranges larger than the spring run, but smaller species
with smaller home ranges still may make forays out of the run (Hill and
2010 K. Work, M. Gibbs, B. Peters, and L. French 669
Grossman 1987). As a result, some of the variability that we observed
likely was not true population variation, but rather a snapshot of a subset
of the population in the run at any given time.
A second potential factor in the high variability of the Volusia Blue
Spring fish fauna is that, although the run provides a harsh oxygen
environment, species can move easily throughout the run due to its morphology.
The run is comparatively wide and deep with no riffles, so even
large predators occasionally reach the spring head. Small headwater
streams often have riffles that preclude movement of larger predators
between pools during low-water periods. Pools with few or no large predators
may serve as refugia for smaller prey species. Matthews et al. (1994)
observed significant differences among pools in a small, variable Oklahoma
stream, and some of the differences were attributed to the presence
or absence of M. salmoides and large L. macrochirus. Although we did
not observe M. atlanticus at the spring head during this study, individuals
of 60% of all species were observed at the spring head on at least one
occasion during the four years of our study, including predators such as
M. salmoides and Lepisosteus spp. Occasional forays of predators into lowoxygen,
but prey-rich habitat near the spring head may increase variability
in the distribution and densities of smaller species.
Finally, the fish fauna of Volusia Blue Spring may be inherently stochastic.
Environmental instability can cause variability in fish populations (e.g.,
Humpl and Pivnička 2006, Marchetti and Moyle 2001, Matthews et al. 1994,
Oberdorff et al. 2001, Pearsons et al. 1992, Pusey et al. 2000), and such environmental
instability varies in magnitude. Highly controlled experimental
streams should be comparatively stable and, therefore, a good indicator of
the potential for inherent variability in a stream fish assemblage. Matthews
and Marsh-Matthews (2006) followed seven assemblages of stream fishes
in experimental streams over the course of a year. These assemblages were
stocked with the same species at the same densities and life stages and yet,
at the end of the year, the assemblages differed substantially. Some of this
variability may have been due to differences in resources between pools that
developed over the course of the year, but much of the variation appeared to
be unpredictable change. It is likely that the variability of the Volusia Blue
Spring fish fauna is a combination of this type of inherent variability overlain
with St. Johns River-induced variability.
This study indicated that the Volusia Blue Spring fish fauna was more
variable than expected from the results of previous studies on Florida springs
(McKinsey and Chapman 1998, Odum and Caldwell 1955), particularly
given the consistency of the physical and chemical parameters of the spring.
This consistency provides a predictable physical and chemical habitat, but
the close connection with the St. Johns River undoubtedly magnifies inherent
fish assemblage variation. Volusia Blue Spring is likely more variable than
most springs in Florida due to this river connection. However, all springs
670 Southeastern Naturalist Vol. 9, No. 4
may be more variable than indicated by studies of short duration or low
temporal resolution (i.e., infrequently sampled). Most Florida springs are
threatened by reductions in flow, increases in nutrient inputs, and invasions
of nonindigenous species (Scott et al. 2004). Therefore, a better understanding
of variability in the ecology of these springs is crucial for developing
effective strategies to protect them.
Acknowledgments
We thank personnel of Blue Spring State Park in Volusia County for granting access
to the spring and for logistical aid. We also acknowledge the people who made
substantial contributions as field assistants: Corey Green, Sabrina Krisberg, Kara
Moore, Aaron Odegard, Kevin Palmer, Tessa Payne, Alicia Schultheis, Kira Smedley,
and Trevor Tyner. Finally, we thank Terry Farrell for consultation and Cindy Bennington,
Stephen Walsh, and two anonymous reviewers for editing the manuscript.
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