• TABLE OF CONTENTS
HIDE
 Abstract
 Introduction
 Methodology
 Results and discussion
 Conclusions
 Acknowledgements
 Reference






Group Title: Hyrdrobiologia, 297/280 : 107-119, 1994.
Title: Bird abundance and species richness on Florida lakes: influence of trophic status, lake morphology, and aquatic macrophytes
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Title: Bird abundance and species richness on Florida lakes: influence of trophic status, lake morphology, and aquatic macrophytes
Series Title: Hyrdrobiologia, 297/280 : 107-119, 1994.
Physical Description: Book
Language: English
Creator: Hoyer, Mark V.
Canfield, Daniel E. Jr.
Publisher: Hyrdrobiologia
Publication Date: 1994
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Volume ID: VID00001
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Table of Contents
    Abstract
        Page 107
    Introduction
        Page 107
    Methodology
        Page 108
    Results and discussion
        Page 109
        Page 110
        Page 111
        Page 112
        Page 113
        Page 114
        Page 115
        Page 116
    Conclusions
        Page 117
    Acknowledgements
        Page 118
    Reference
        Page 118
        Page 119
Full Text

Hydrobiologia 297/280: 107-119, 1994.
J. J. Kerekes (ed.), Aquatic Birds in the Trophic Web of Lakes. 107
1994 Kluwer Academic Publishers. Printed in Belgium.


Bird abundance and species richness on Florida lakes: influence of
trophic status, lake morphology, and aquatic macrophytes


Mark V. Hoyer & Daniel E. Canfield, Jr.
Department of Fisheries and Aquaculture, University of Florida, Gainesville, Florida 32611, USA


Key words: Florida, bird populations, trophic status, lakes, water quality, aquatic macrophytes


Abstract

Data from 46 Florida lakes were used to examine relationships between bird abundance (numbers and
biomass) and species richness, and lake trophic status, lake morphology and aquatic macrophyte abun-
dance. Average annual bird numbers ranged from 7 to 800 birds km-2 and bird biomass ranged from
1 to 465 kg km-2. Total species richness ranged from 1 to 30 species per lake. Annual average bird
numbers and biomass were positively correlated to lake trophic status as assessed by total phosphorus
(r= 0.61), total nitrogen (r=0.60) and chlorophyll a (r=0.56) concentrations. Species richness was
positively correlated to lake area (r = 0.86) and trophic status (r = 0.64 for total phosphorus concentra-
tions). The percentage of the total annual phosphorus load contributed to 14 Florida lakes by bird
populations was low averaging 2.4%. Bird populations using Florida lakes, therefore, do not significantly
impact the trophic status of the lakes under natural situations, but lake trophic status is a major fac-
tor influencing bird abundance and species richness on lakes. Bird abundance and species richness were
not significantly correlated to other lake morphology or aquatic macrophyte parameters after the effects
of lake area and trophic status were accounted for using stepwise multiple regression. The lack of sig-
nificant relations between annual average bird abundance and species richness and macrophyte abun-
dance seems to be related to changes in bird species composition. Bird abundance and species richness
remain relatively stable as macrophyte abundance increases, but birds that use open-water habitats (e.g.,
double-crested cormorant, Phalacrocorax auritus) are replaced by species that use macrophyte commu-
nities (e.g., ring-necked duck, Aythya collaris).


Introduction

Florida has more than 7700 lakes that range in
size from 0.4 ha to over 180000 ha (Shafer et al.,
1986). The majority of the research and lake man-
agement conducted on these lakes involves inves-
tigations of eutrophication related problems and
aquatic macrophyte management (Shireman et al.
1983; Joyce 1985; Canfield & Hoyer 1988a; Di-
erberg et al. 1988). This work is done primarily
for the purposes of providing potable water, flood


control, navigation, recreational boating, swim-
ming, and fishing. Consequently, consideration is
seldom given to the bird populations that utilize
these lakes and very little information is available
to determine how different lake management ac-
tions may affect bird populations.
Hoyer & Canfield (1990) provided a prelimi-
nary examination of the relations among bird
abundance and species richness and lake trophic
status, morphology, aquatic macrophytes for 33
Florida lakes. In this paper, data from 13 addi-





Hydrobiologia 297/280: 107-119, 1994.
J. J. Kerekes (ed.), Aquatic Birds in the Trophic Web of Lakes. 107
1994 Kluwer Academic Publishers. Printed in Belgium.


Bird abundance and species richness on Florida lakes: influence of
trophic status, lake morphology, and aquatic macrophytes


Mark V. Hoyer & Daniel E. Canfield, Jr.
Department of Fisheries and Aquaculture, University of Florida, Gainesville, Florida 32611, USA


Key words: Florida, bird populations, trophic status, lakes, water quality, aquatic macrophytes


Abstract

Data from 46 Florida lakes were used to examine relationships between bird abundance (numbers and
biomass) and species richness, and lake trophic status, lake morphology and aquatic macrophyte abun-
dance. Average annual bird numbers ranged from 7 to 800 birds km-2 and bird biomass ranged from
1 to 465 kg km-2. Total species richness ranged from 1 to 30 species per lake. Annual average bird
numbers and biomass were positively correlated to lake trophic status as assessed by total phosphorus
(r= 0.61), total nitrogen (r=0.60) and chlorophyll a (r=0.56) concentrations. Species richness was
positively correlated to lake area (r = 0.86) and trophic status (r = 0.64 for total phosphorus concentra-
tions). The percentage of the total annual phosphorus load contributed to 14 Florida lakes by bird
populations was low averaging 2.4%. Bird populations using Florida lakes, therefore, do not significantly
impact the trophic status of the lakes under natural situations, but lake trophic status is a major fac-
tor influencing bird abundance and species richness on lakes. Bird abundance and species richness were
not significantly correlated to other lake morphology or aquatic macrophyte parameters after the effects
of lake area and trophic status were accounted for using stepwise multiple regression. The lack of sig-
nificant relations between annual average bird abundance and species richness and macrophyte abun-
dance seems to be related to changes in bird species composition. Bird abundance and species richness
remain relatively stable as macrophyte abundance increases, but birds that use open-water habitats (e.g.,
double-crested cormorant, Phalacrocorax auritus) are replaced by species that use macrophyte commu-
nities (e.g., ring-necked duck, Aythya collaris).


Introduction

Florida has more than 7700 lakes that range in
size from 0.4 ha to over 180000 ha (Shafer et al.,
1986). The majority of the research and lake man-
agement conducted on these lakes involves inves-
tigations of eutrophication related problems and
aquatic macrophyte management (Shireman et al.
1983; Joyce 1985; Canfield & Hoyer 1988a; Di-
erberg et al. 1988). This work is done primarily
for the purposes of providing potable water, flood


control, navigation, recreational boating, swim-
ming, and fishing. Consequently, consideration is
seldom given to the bird populations that utilize
these lakes and very little information is available
to determine how different lake management ac-
tions may affect bird populations.
Hoyer & Canfield (1990) provided a prelimi-
nary examination of the relations among bird
abundance and species richness and lake trophic
status, morphology, aquatic macrophytes for 33
Florida lakes. In this paper, data from 13 addi-






tional Florida lakes have been added to the ear-
lier 'data. Our purpose, here, is to further exam-
ine relationships between limnological factors and
bird numbers, biomass and species richness.
Many factors have been shown to influence
aquatic bird populations including geographic lo-
cation, habitat condition in nesting and wintering
areas, and climatic factors (Weller & Spatcher,
1965). We, however, focused our study on three
major habitat characteristics that have previously
been shown to be important to bird populations:
lake trophic status (Nilsson & Nilsson 1978;
Murphy etal. 1984;), lake morphology (Mac-
Arthur & Wilson, 1967; Brown & Dinsmore,
1986) and aquatic macrophyte abundance
(Johnson & Montalbano, 1984; Montalbano
et al., 1979). Because there are also concerns that
birds can contribute to eutrophication problems
in lakes (Manny et al., 1975; Nordlie, 1976), we
examined the potential of the bird populations to
contribute to the nutrient load of Florida lakes.


Methods

Birds counts for this study were obtained by
counting birds that were observed on or feeding
from aquatic habitats during a survey of 46
Florida lakes. The counts were conducted be-
tween November 1988 and September 1990.
Birds were counted on each lake once in the win-
ter (November to February), once in the spring
(March to May) and once in the summer (July to
September). Birds were counted by observers
who motored once around the perimeter of each
lake in a small boat. Birds were identified to spe-
cies except gulls, terns, and crows, and care was
taken not to count birds twice that flushed ahead
of the boat.
Species richness was defined as the total num-
ber of bird species observed throughout the entire
sampling period. Average annual bird abun-
dances (birds km-2) were calculated by averag-
ing all three counts for each lake. Average annual
bird biomass (kg km-2) was calculated by mul-
tiplying the average live weight of a given species,
taken from Terres (1980), by annual average bird


abundance values for that species and summing
by lake. The annual total phosphorus load ex-
creted by bird populations was calculated by mul-
tiplying the average annual bird biomass by the
total phosphorus defecation rates calculated by
Manny et al. (1975) for canada geese (Branta ca-
nadensis).
Aquatic macrophytes were sampled at each
lake once during the summer. The percent lake
volume infested with aquatic macrophytes (PVI)
and the percent lake area covered by macrophytes
(PAC) were determined according to the methods
of Maceina & Shireman (1980). The above-
ground standing crop of emergent, floating-
leaved, and submerged vegetation (Canfield et al.,
1990) was measured along ten uniformly-placed
transects around the lake. At each transect, divers
cut the above ground portions of aquatic macro-
phytes that were inside a 0.25 m2 plastic square
randomly thrown once in each plant zone. The
vegetation was placed in nylon mesh bags, spun
to remove excess water, and weighed to the near-
est 0.10 kg. Average standing crop (kg m-2) for
each vegetation zone was calculated by averaging
10 samples from each zone. The combined width
(m) of the floating-leaved and emergent zones
was also measured at each transect and then av-
eraged for each lake.
Composite samples of all plant types present in
a lake were collected for phosphorus content
analysis. Plant material was dried at 70 C to a
constant weight and ground in a Wiley Mill until
fragments were <0.85 mm. Dried plant material
was then given a persulfate digestion, diluted and
analyzed for total phosphorus (see below).
Lake area (km2) was obtained from Shafer
et al. (1986) and shoreline length (km) was mea-
sured from aerial photographs with a 1:20000 or
1:40000 reduction. Mean depth (m) was calcu-
lated from the fathometer transects used for PVI
and PAC calculations. Shoreline development
was calculated according to the methods of Wet-
zel (1975).
Summer water samples were collected from six
stations (three littoral and three open-water) and
three open-water samples were collected from
each lake on two additional dates during the year.






Water samples were collected 0.5 m below the
surface in acid-cleaned Nalgene bottles, placed
on ice, returned to the laboratory, and analyzed.
Secchi depth (m) was measured at each station
where water was collected.
Total phosphorus was analyzed (Murphy &
Riley, 1962) after a persulfate oxidation (Menzel
& Corwin, 1965). Total nitrogen was determined
by a modified Kjeldahl technique (Nelson &
Sommers, 1975). Water was filtered through Gel-
man type A-E glass fiber filters for chlorophyll a
determinations. Chlorophyll a was determined by
using the method of Yentsch & Menzel (1963)
and the equations of Parson & Strickland (1963).
Measured planktonic chlorophyll a values are
often not good indicators of lake trophic status
when large amounts of aquatic macrophytes are
present because aquatic macrophytes and asso-
ciated epiphytic algae can compete for nutrients
that would otherwise be used by planktonic algal
cells (Canfield etal., 1983). Thus, we also as-
sessed the trophic status of each lake by calcu-
lating a total water column phosphorus concen-
tration (WCP) value for each lake (see Canfield
et al., 1983). WCP values were obtained by add-
ing the measured total phosphorus in the water to
the phosphorus incorporated in plant tissue.
Statistical analyses were conducted using
SYSTAT (Wilkinson, 1987). Because the data
values spanned orders of magnitude and vari-
ances were proportional to the means, all data
were transformed to their logarithms (base 10),
except PVI and PAC which are percent values.
For the logarithmic transformation, a value of
0.001 kg was added to the plant biomass values
that were measured as 0 values. Unless stated
otherwise, statements of statistical significance
imply P 0.05.


Results and discussion

--.. lakes included in this study encompassed a
wide range of limnological conditions (Table 1).
The size of the lakes ranged from 0.02 to 2.71 km2
and lake trophic status, based on the classifica-
tion system of Forsberg & Ryding (1980), ranged


from oligotrophic to hypereutrophic. The lakes,
however, are representative of Florida lakes
(Canfield & Hoyer, 1988b) and therefore provide
the range of conditions needed to examine the
effects of lake trophic status, aquatic macrophyte
abundance and lake morphology on Florida bird
populations.
Fifty bird species were observed during the
study period, but some species occurred on only
one lake (Table 2). These rare species included
the american white pelican (Pelecanus erythrorhyn-
chos), canada goose, and fulvous whistling duck
(Dendrocygna bicolor). Some species, however,
occurred on as many as 38 of the 46 study lakes.
The most common species observed were counted
on more than 65 % of the lakes sampled, and
included the great blue heron (Ardea herodias),
great egret (Casmerodius albus), and anhinga (An-
hinga anhinga). The species occurring with the
highest densities (birds km- 2) were mallard (Anas
platyrhynchos), american coot (Fulica americana),
and red-winged blackbird (Agelaius phoeniceus).
Least numerous birds included american white
pelican, sora (Porzana carolina), and limpkin
(Aramus guarauna).
All trophic state variables in our study were
significantly correlated to bird abundance (num-
bers and biomass), and species richness (Table 3).
The strongest correlations were with total phos-
phorus concentrations (r=0.61, r=0.61, and
r = 0.64, respectively). Similar correlations were
reported between bird abundance, species rich-
ness and lake trophic state variables for 33
Florida lakes (Hoyer & Canfield, 1990). Hoyer &
Canfield (1990), however, suggested that chloro-
phyll a rather than total phosphorus should be
used as the major trophic state variable for pre-
dicting bird abundance and species richness in
lakes because chlorophyll a is a convenient esti-
mator of the organic base upon which aquatic
bird populations depend. Because chlorophyll a
values can greatly underestimate the trophic sta-
tus of lakes with large biomasses of aquatic veg-
etation, we choose to use WCP concentrations to
assess lake trophic status in this study (see Can-
field et al., 1983). Regression analyses yielded the
following statistically significant regression equa-







Table 1. Summary statistics for trophic state, aquatic macrophyte (plant biomasses are live weight estimates), lake morphology,
and bird population parameters estimated in 46 Florida lakes. The annual average (Mean) is listed with the minimum (Min), and
maximum (Max) values, and the standard error of the mean (SE).

Parameters Mean Min Max SE

Trophic state:
Total phosphorus (y gl ') 57 1.0 1043 24
Water column phosphors (pgl 1) 196 1 4538 99
Total nitrogen (ig 1-1) 882 82 3256 110
Chlorophyll a (pg 1) 27 1 241 7
Secchi depth (m) 2.0 0.3 5.8 0.2

Aquatic macrophytes:
Percent volume infested with macrophytes (%) 25 0 98 5
Percent area covered with macrophytes (%) 43 1 100 6
Emergent biomass (kg m-2) 3.9 0.3 26.8 0.7
Floating leaf biomass (kg m 2) 1.3 0.0 11.2 0.4
Submergent biomass (kg m-2) 1.8 0.0 16.6 0.5
Emergent and floating leaf width (m) 29.3 0.4 162.8 4.7

Lake morphology:
Lake surface area (km2) 0.74 0.02 2.71 0.10
Shoreline length (km) 3.49 0.60 8.40 0.30
Shoreline development 1.34 1.00 2.45 0.06
Mean depth (m) 2.8 0.6 5.9 0.2

Bird population:
Bird numbers (bird km-2) 174 7 803 28
Bird biomass (kg km2) 114 1 465 17
Species richness (total species) 17 1 30 1


tions for predicting bird abundance (numbers and
biomass) and species richness from WCP con-
centrations:

Log (bird numbers)
= 1.14 + 0.48 Log (WCP) R2 = 0.30 (1)
Log (Birds biomass)
= 0.91 + 0.53 Log (WCP) R2 = 0.38 (2)
Log (Species richness)
= 0.57 + 0.31 Log (WCP) R2 = 0.22. (3)

There is a large amount of variance in bird num-
bers and biomass at any given level of WCP
(Figs 1A and 1B) and the total variance in bird
numbers (Equation 1) and biomass (Equation 2)
accounted for by WCP concentrations alone was


low 30 and 38 %, respectively. We, therefore, used
the WCP values and all aquatic macrophyte and
lake morphology parameters as independent var-
iables in stepwise multiple regressions to try to
account for more variance in bird numbers and
biomass. An alpha-to-enter and an alpha-to-
remove of 0.05 was used for the analyses (Wilkin-
son, 1987) and we used only WCP as a trophic
state parameter because all trophic state param-
eters were intercorrelated. No aquatic macro-
phyte or lake morphology parameters, however,
accounted for significantly more variance after
WCP values were entered into the multiple re-
gression models.
Although there was a significant correlation be-
tween species richness and WCP values, species
richness was most strongly correlated to lake area






111

Table 2. List of bird species identified and counted on 46 Florida lakes between November 1988 and September 1990. N is the
number of lakes on which a bird was observed. Annual average bird numbers (Mean, birds km-2) for each species is listed with
the minimum (Min) and maximum (Max) values, and the standard error of the mean (SE).

Common name Scientific name N Mean Min Max SE


Pied-billed Grebe
American White Pelican
Double-crested Cormorant
Anhinga
Least Bittern
Great Blue Heron
Great Egret
Snowy Egret
Little Blue Heron
Tricolored Heron
Cattle Egret
Green-backed Heron
Black-crowned Night-heron
White Ibis
Glossy Ibis
Wood Stork
Canada Goose
Fulvous Whistling Duck
Wood Duck
Mottled Duck
Mallard
Blue-winged Teal
Ring-necked Duck
Turkey Vulture
Black Vulture
Bald Eagle
Osprey
Northern Harrier
Red-tailed Hawk
Red-shouldered Hawk
American Kestrel
Sora
Purple Gallinule
Common Moorhen
American Coot
Limpkin
Sandhill Crane
Semipalmated Plover
Killdeer
Lesser Yellowlegs
Common Snipe
Gulls
Terns
Belted Kingfisher
Purple Martin
Tree Swallow
Bank Swallow
Crows
Red-winged Blackbird
Boat-tailed Grackle


Podilymbus podiceps
Pelecanus erythrorhynchos
Phalacrocorax auritus
Anhinga anhinga
Ixobrychus exilis
Ardea herodias
Casmerodius albus
Egretta thula
Egretta caerulea
Egretta tricolor
Bubulcus ibis
Butorides striatus
Nycticorax nycticorax
Eudocimus albus
Plegadis falcinellus
Mycteria americana
Branta canadensis
Dendrocygna bicolor
Aix sponsa
Anus fulvigula
Anas platyrhynchos
Anas discors
Aythya collaris
Cathartes aura
coragyps atratus
Haliaeetus leucocephalus
Pandion haliaetus
Circus cyaneus
Buteo jamaicensis
Buteo lineatus
Falco sparverius
Porzana carolina
Porphyrula martinica
Gallinula chloropus
Fulica americana
Aramus guarauna
Grus canadensis
Charadrius semipalmatus
Charadrius vociferus
Tringa solitaria
Gallinago gallinago
Laridae Larinae(')
Laridae Sterninae")
Ceryle alcyon
Progne subis
Tachycineta bicolor
Riparia riparia
Corvidae(2)
Agelaius phoeniceus
Quiscalus major


(1) Listed as subfamily.
(2) Listed as family.


2.6
0.9
66.7
71.9
1.2
20.6
43.7
8.7
8.3
8.3
129.2
16.7
12.3
78.0
0.7
3.2
0.6
0.1
33.3
5.2
183.9
9.2
220.8
41.7
34.5
7.4
6.7
0.8
4.2
3.7
0.6
0.7
10.3
146.4
292.9
1.5
1.7
3.3
11.1
3.7
51.9
98.3
39.6
22.2
138.9
15.2
1.3
304.3
92.3
156.4


0.2

2.8
2.6
0.1
0.8
1.7
0.5
0.5
0.5
6.7
0.8
2.0
3.4
0.0
0.6


2.1
0.7
18.9
2.2
19.7
3.9
2.4
0.5
0.3
0.10
0.5
0.3
0.10

0.9
6.7
18.4
0.2
0.3
0.4
1.0
1.1
5.0
6.7
2.2
0.8
9.8
3.3

8.2
4.1
7.4














Table 3. Correlation matrix for all parameters sampled on 46 Florida lakes. All absolute r values equal to or greater then 0.30 are significant at a p50.05 level.


Variables


XI X2 X3 X4 X5 X6 X7 X8 X9 X10 X11 X12 X13 X14 X15 Y1 Y2 Y3


Trophic state:
X1. Total phosphorus (pg 1-1) 1.00
X2. Water column phosphorus (pg 1-') 0.54 1.00
X3. Total nitrogen (g gl-') 0.81 0.59 1.00
X4. Chlorophyll a (pg 1-') 0.87 0.41 0.82 1.00
X5. Secchi depth (m) -0.86 -0.47 -0.88 -0.87 1.00


Aquatic macrophytes:
X6. PVI (%)
X7. PAC (%)
X8. Emergent (kg m2)
X9. Floating-leaved (kg m-2)
X10. Submerged (kg m-2)
Xll. Width (m)

Lake morphology:
X12. Surface area (km2)
X13. Shore line length (km)
X14. Mean depth (m)
X15. Shoreline development

Bird population:
Y1. Bird numbers (birds km-2)
Y2. Bird biomass (kgkm-2)
Y3. Species richness (total species)


-0.21 0.48 0.06 -0.25 0.13 1.00
-0.40 0.35 -0.17 -0.47 0.34 0.85 1.00
0.06 0.35 0.08 0.19 -0.07 -0.04 -0.13 1.00
0.08 0.47 0.25 0.03 -0.12 0.46 0.44 0.24 1.00
-0.49 0.16 -0.30 -0.49 0.50 0.51 0.61 0.28 0.26 1.00
-0.12 0.26 0.05 -0.26 0.12 0.46 0.52 0.05 0.38 0.60 1.00


0.50 0.37 0.46 0.45 -0.41 -0.03 -0.16 -0.01 -0.06 -0.16 0.04 1.00
0.43 0.35 0.39 0.38 -0.35 -0.02 -0.11 0.06 0.02 -0.09 0.04 0.90 1.00
0.15 -0.03 -0.16 -0.13 0.11 0.02 0.11 0.16 0.18 0.14 0.00 -0.20 0.24 1.00
-0.20 -0.46 -0.40 -0.18 0.41 -0.47 -0.39 0.01 -0.36 -0.01 -0.37 0.10 0.06 -0.09 1.00



0.61 0.55 0.59 0.56 -0.51 0.10 -0.11 0.05 0.08 -0.09 -0.07 0.40 0.45 0.12 -0.19 1.00
0.61 0.61 0.60 0.56 -0.52 0.13 -0.01 0.07 0.24 -0.06 -0.04 0.31 0.40 0.22 -0.30 0.92 1.00
0.64 0.47 0.59 0.56 -0.53 -0.01 -0.16 -0.06 0.02 -0.18 0.01 0.86 0.82 -0.07 -0.08 0.70 0.62 1.00

























10 100 1000


1000





0)
0
E

.2O


m
0o


Water Column Phosphorus (pg I"1)



B

*
*


*
0


-
S


1 10 100 1000 10000

Water Column Phosphorus (Lg 1-1)
Fig. 1. Relation between annual average bird numbers (A,
birds km-2) and biomass (B, kg km-2) and water column
phosphorus concentration (WCP, jig 1 ') for 46 Florida lakes.
WCP values are calculated by adding the phosphorus incor-
porated in aquatic macrophyte and epiphytic algae tissue to
the measured total phosphorus concentration according to the
methods of Canfield et al. (1983).




(r = 0.86; Table 3; Fig. 2). Similar species-area re-
lations have been reported for many flora and
fauna (Flessa & Sepkoski, 1978; Connor &
McCoy, 1979). The best-fit multiple linear regres-
sion, however, indicated that lake area and WCP


Lake Surface Area (km2)
Fig. 2. Relation between lake species richness (total species)
and surface area (km2).



could account for 77 % of the variance in species
richness:

Log (Species richness)
= 1.12 + 0.56 Log (Lake area)
+ 0.12 Log (WCP) R2 = 0.77. (4)
No other lake morphology or aquatic macrophyte
variables significantly accounted for additional
variance.
We anticipated significant correlations between
the lake morphology variables other than lake
area and bird abundance and species richness
because previous studies had linked shoreline de-
velopment and mean depth with bird abundance
and species richness (Nilsson & Nilsson, 1978;
Murphy et al., 1984). Shoreline development for
our lakes, however, averaged only 1.34 and the
values only ranged from 1.00 to 2.45 (Table 1).
This makes it very difficult to detect a significant
effect when other variables are strongly corre-
lated. Lake mean depth values in our study ranged
0.6 to 5.9 m (Table 1), but many of the aquatic
birds counted in our study were limited to shal-
low shoreline areas where they could forage for
food. Because these birds can not wade in lim-
netic portions of a lake system, it is not surpris-
ing that mean depth values were not significantly


1000


1^
4E
100

I-



z
E 10
m
1


A 0

** *
0
*t *
*

g


I I


*
..

Ot




* *** *


10000








related to bird abundance, and species richness
(Table 3). The width of the immediate shoreline
that can used by many wading birds, however, is
potentially important. This width would be re-
lated to the slope of a lake system, out from the
shoreline, which would determine the maximum
depth at which many bird species could wade and
forage for food. The slope of a lake has also been
related to patterns in aquatic macrophyte biom-
ass and coverage (Canfield & Duarte, 1988), thus
slope rather than shoreline development or mean
depth may be the most important factor influenc-
ing bird abundance and species richness after the
effects of lake trophic status are accounted for.
Birds use aquatic macrophytes for nesting,
resting and refuge sites. Macrophytes are also
used as food by birds and the plants provide sub-
strate for invertebrate food items (Odum et al.,
1984; Engel, 1990). Bird abundance, biomass and
species richness, however, were not significantly
correlated with any aquatic macrophyte param-
eters that were measured in this study (Table 3;
Figs 3A, 3B, and 3C). This is surprising consid-
ering the reported association between aquatic
birds and aquatic macrophytes. Individual bird
species, however, may require different types and
quantities of aquatic macrophytes (Weller &


Spatcher, 1965; Weller & Fredrickson, 1974). For
example, ring-neck ducks (Aythya collaris) were
observed on 11 lakes. These were the only lakes
in which Hydrilla verticillata, a major food source
for ring-neck ducks, was found. This relation has
also been observed by other researchers in Florida
(Gassaway et al., 1977; Johnson & Montalbano,
1984). Of the 12 lakes on which least bitterns
(Ixobrychus exilis) were observed, 11 had exten-
sive stands of cattails (Typha sp.), which is re-
ported to be a primary habitat for the species
(Palmer, 1962).
To examine the relation between individual bird
species and percent area covered with aquatic
macrophytes, we calculated the frequency of de-
tection for each species in lakes with low (< 26 %,
n= 20), moderate (26 to 75%, n= 11), and high
(> 75%, n = 15) areal coverages of aquatic mac-
rophytes (Table 5). We divided the individual bird
species into three different groups using the fre-
quency of detection values: (1) species with a de-
creasing frequency of detection as aquatic mac-
rophyte coverage increases, (2) species with an
increase in the frequency of detection with an
increase in aquatic macrophyte coverage, and
(3) species that show a random frequency of de-
tection with an increase in aquatic macrophytes.


Table 4. Annual total phosphorus load (mg m- 2 yr- ') for 14 Florida lakes, from Huber et al. (1982) and corresponding annual
total phosphorus load (mg m- 2 yr ) contributed from bird populations utilizing these lakes. The annual total phosphorus load
was calculated by multiplying the annual average bird biomass by the total phosphorus defecation rate for waterfowl calculated
by Manny et al. (1985).

Lake County Annual load Bird load Bird load
(% of total)

Okahumpka Putnam 1790 16.5 0.9
Bivens Arm Alachua 800 19.4 2.4
Wales Polk 370 2.9 0.8
Clear Pasco 270 2.0 0.7
Susannah Orange 250 22.6 9.1
Hollingsworth Polk 150 8.8 5.9
Hartridge Polk 130 4.8 3.7
Bell Pasco 2150 9.2 0.4
Bonny Polk 420 9.8 2.3
Lindsey Hernando 730 7.4 1.0
Koon Lafayette 1310 7.4 0.6
Orienta Seminole 690 19.1 2.8
Rowell Bradford 8030 9.6 0.1
Marianna Polk 290 7.1 2.5









1000


o 800


I. 600


, 400


*O 200
m
0


10 30 50 70 90
Percent Area Covered With Macrophytes


500


N, 400
E

"d 300
0

E 200
0
m
E
i-
100


10 30 50 70 90
Percent Area Covered With Macrophytes


40

u>
r 30
0

0
.2 20
0
0)
1)
10
a


10 30 50 70 90
Percent Area Covered With Macrophytes


A






* 5


* t
gi .
n O 8o I*
>. *.**. 4 *. *


The double-crested cormorant (Phalacrocorax au-
ritus) and anhinga showed a much higher fre-
quency of detection in lakes with low aquatic
macrophyte coverage (Table 5). These bird spe-
cies are fish eaters and they can have difficulty
capturing prey in lakes full of aquatic vegetation;
thus cormorants and anhingas are less likely to
inhabit lakes with large coverages of aquatic mac-
rophytes. In a similar situation, largemouth bass
populations have difficulty capturing prey in lakes
with large coverages of aquatic vegetation (Colle
& Shireman, 1980; Savino & Stein, 1982). Ring-
necked duck and american coot use aquatic veg-
etation as a direct food source and show a high
frequency of detection in lakes with high aquatic
macrophyte coverages (Table 5). These birds
probably are attracted to matted vegetation as a
food source (Johnson & Montalbano, 1984) and
have a higher probability of occurring on a lake
with large populations of aquatic macrophytes.
Least bittern is an example of a bird species that
shows a random frequency of detection at all lev-
els of aquatic macrophyte coverages. The least
bittern, however, shows a strong relation with
Typha sp. (Palmer, 1962). This suggests that this
species may show little or no relation to the total
aquatic macrophyte population but requires
Typha sp. or plant species with a similar structure
to be present on a lake system.
Part of the variance in the bird abundance and
species richness relations and the lack of signifi-
cance by other variables that we assumed a priori
would influence bird abundance and species rich-
ness could be the result of our survey sampling
strategy. Constraints imposed on our study al-
lowed only three bird counts during a year-long
period. Changes in bird abundance over an an-
nual cycle are quite prevalent in lake systems
(Johnson & Montalbano, 1989), especially those
in Florida (Hoyer & Canfield, 1990). Our study,
however, supports other published studies that
have indicated lake trophic status is a major fac-


Fig. 3. The relation between bird numbers (A, birds km- 2),
biomass (B, kg km-2), and species richness (C, total species)
and percent area covered with aquatic macrophytes for 46
Florida lakes.


C


SS .

* *
0 %



0 0
** 0

3

0* 0 *
I I i I






116

Table 5. Frequency of detection (%) of bird species using Florida lakes with low (<26%), moderate (26 to 75%), and high
(>75%) percent area coverage of aquatic macrophytes. The number of lakes in each group is listed in parentheses. Bird species
are grouped by those increasing, decreasing and having no relation to aquatic macrophytes.

Species relation to increasing aquatic macrophyte coverage Percent area covered with aquatic macrophytes

Low (n = 20) Moderate (n = 11) High (n = 15)

Decreasing frequency of detection:
Double-crested Cormorant 85 54 46
Anhinga 80 73 53
Great Egret 85 73 60
Snowy Egret 85 73 60
Little Blue Heron 65 55 40
Tricolored Heron 55 55 20
Green-backed Heron 75 55 47
Black-crowned Night-heron 20 18 7
White Ibis 60 55 .33
Wood Stork 20 18 0
Wood Duck 20 18 0
Mallard 45 18 0
Osprey 70 73 40
Northern Harrier 20 18 13
Common Moorhen 70 64 47
Semipalmated Plover 25 18 0
SGulls 65 55 13
Terns 55 36 20
Belted Kingfisher 80 64 53
Purple Martin 55 18 7
Crows 90 82 67
Red-winged Blackbird 80 73 60
Boat-tailed Grackle 80 55 53

Increasing frequency of detection:
Pied-billed Grebe 40 55 60
Ring-necked Duck 5 36 40
Turkey Vulture 10 18 47
Red-shouldered Hawk 15 27 33
American Coot 35 45 47

Random frequency of detection:
Least Bittern 35 36 7
Great Blue Heron 80 73 93
Cattle Egret 45 55 33
Black Vulture 45 45 33
Bald Eagle 35 45 20
Red-tailed Hawk 10 18 20
Purple Gallinule 25 27 13
Limpkin 10 18 13
Killdeer 20 18 33
Common Snipe 15 36 20







tor determining bird abundance and species rich-
ness on lake systems (Nilsson & Nilsson, 1978;
Murphy et al., 1984; Hoyer & Canfield, 1990).
Nutrient imports from bird populations can
contribute significantly to the annual nutrient load
of some lake systems (Manny et al., 1975; Nor-
dlie, 1976). We, therefore, estimated the annual
phosphorus load of the bird populations to de-
termine if the bird populations on our study lakes
could be significantly influencing the trophic sta-
tus of the lakes. Because detailed nutrient budgets
were not available for most of the study lakes, we
first expressed the estimated phosphorus load
from the birds as a percentage of the lake's WCP
value. The percentage of the total phosphorus in
each lake's water column that could be attributed
to the annual bird phosphorus load averaged 6 %,
but values ranged from <1% to 25 %. Four lakes
had values exceeding 20%. To examine bird
phosphorus loading rates in more detail, we used
annual total phosphorus loading data (Huber
et al., 1982) for 14 lakes that were included in our
study. The percentage of the annual phosphorous
load that could have been contributed by the bird
populations utilizing these lakes ranged from
<1% to 9% and averaged 2.4% (Table 4). Our
calculated phosphorus contributions by bird
populations to the annual phosphorus imports,
however, are probably overestimates because the
majority of the birds are getting their nutrients
from the lake by feeding on organisms that live in
the lake. Thus, the annual contribution of nutri-
ents by bird populations to Florida lakes is gen-
erally low and the trophic status of these lakes is
probably not significantly affected by bird popu-
lations. There, however, remains the potential for
birds to contribute significantly to the nutrient
loading rates of lakes, especially if large popula-
tions of birds feed outside the lake and roost on
the lake (Manny et al., 1975; Nordlie, 1976).


Conclusions

Aquatic bird populations are influenced by many
limnological factors. Our study and others, how-
ever, have suggested that a water body's trophic


status is a major factor influencing species abun-
dance (numbers and biomass) and richness (Nils-
son & Nilsson, 1978; Murphy et al., 1984; Brown
& Dinsmore, 1986). Productive aquatic ecosys-
tems are able to support a greater number and
biomass of organisms and more specialized spe-
cies (Hutchinson, 1959; MacArthur, 1970;
Wright, 1983). For many lakes, eutrophication
control is a major management objective and cur-
rent lake management strategies generally include
attempts to reduce nutrient concentrations
through lake drawdowns, alum treatments, and
nutrient diversions (Canfield & Hoyer, 1988a; Di-
erberg etal., 1988). Successful eutrophication
control programs, however, have resulted in re-
ductions in fish (Yurk & Ney, 1989) and similar
reductions in bird abundance and species rich-
ness could be expected based on the results of
this study. Eutrophication abatement programs
should therefore be planned with full consider-
ation of the potential trade-off between cleaner
water and reduced fish and bird populations.
Bird populations have the potential to signifi-
cantly contribute to the nutrient load of lake sys-
tems if large numbers of birds feed outside the
lake and then roost on the lake. The percentage
of the total phosphorus load contributed to 14
Florida lakes by bird populations, however, was
low averaging 2.4%. These values are also in-
flated because the majority of the nutrient load
contributed by these bird populations comes from
the lake through feeding activities of the birds.
Thus, bird populations using Florida lakes, under
normal situations, do not significantly impact the
trophic status of the lakes and this is probably
true of most other lakes. Bird abundance and
species richness is increased on eutrophic lakes
because productive lakes have greater food re-
sources.
Aquatic macrophytes are important to bird
populations that use lakes and the management
of aquatic macrophytes has the potential to affect
bird populations. Our study, however, strongly
suggests that the removal of aquatic macrophytes
from lakes may have no effect on annual average
bird abundance (numbers or biomass) or total
species richness. The bird species composition,









however, will change as aquatic macrophytes are
removed from the lake system. Birds that use
aquatic macrophytes (e.g., ring-necked duck) will
be replaced by species that use open-water habi-
tats (e.g., double-crested cormorant). Some bird
species may also require specific type of aquatic
vegetation and the removal of that type may ex-
clude an individual bird species from a lake sys-
tem. Our analyses therefore suggest the impor-
tance of examining bird species as functional
groups in more detailed studies.
The majority of the birds counted during this
study were observed using near-shore areas.
These areas were where the water depth was shal-
low enough to allow wading birds to forage for
food and where terrestrial vegetation provides
cover and roosting areas. Future studies of bird
populations using lakes systems should carefully
examine near-shore areas, and determine the im-
portance of terrestrial vegetation to bird popula-
tions. As shorelines are developed for homes or
parks, much of the terrestrial vegetation is often
removed so people can see the lake. This could
have a major effect on not only how many birds
are present on the lake, but the species compo-
sition and distribution. We, therefore, suggest that
whole-lake bird counts be conducted with a de-
scription of individual bird habitat use, nesting
locations, and feeding activities. Studies should
include a minimum of monthly counts because of
the seasonal changes that can occur in bird popu-
lations.



Acknowledgements

We thank S. F. Mitchell and an anonymous re-
viewer for their many constructive comments on
this manuscript. Christy Horsburgh, Phillip Law-
son, and Mark Jennings were instrumental in col-
lection of data and conducting bird counts. We
thank Mary Stonecipher for conducting chemical
analyses. This research was funded in part by the
Bureau of Aquatic Plant Management (Contract
number C 3748), Florida Department of Natural
Resources.


References

Brown, M. & J. J. Dinsmore, 1986. Implications of marsh
size and isolation for marsh bird management. J. Wildl.
Mgmt. 50: 392-397.
Canfield, D. E. Jr., K. A. Langeland, M. J. Maceina,
W. Haller, J. V. Shireman & J. R. Jones, 1983. Trophic
state classification of lakes with aquatic macrophytes. Can.
J. Fish. aquat. Sci. 40: 1713-1718.
Canfield, D. E. Jr. & C. M. Duarte, 1988. Patterns in biom-
ass and cover of aquatic macrophytes in lakes: a test with
Florida lakes. Can. J. Fish. aquat. Sci. 45: 1976- 1982.
Canfield, D. E. Jr. & M. V. Hoyer, 1988a. The eutrophication
of Lake Okeechobee. Lake Reservoir Mgmt 4: 91-99.
Canfield, D. E. Jr. & M. V. Hoyer, 1988b. Regional geology
and the chemical and trophic state characteristics of Florida
lakes. Lake Reservoir Mgmt. 4: 21-31.
Canfield, D. E. Jr., M. V. Hoyer & C. M. Duarte, 1990. An
empirical method for characterizing standing crops of
aquatic vegetation. J. Aquat. Plant Mgmt. 28: 64-69.
Colle, D. E. & J. V. Shireman, 1980. Coefficients of condition
for largemouth bass, bluegill, and redear sunfish in hydrilla-
infested lakes. Trans. am. Fish. Soc. 109: 521-531.
Connor, E. F. & E. D. McCoy, 1979. The statistics of the
species-area relationships. Am. Nat. 113: 791-833.
Dierberg, F. E., V. P. Williams & W. H. Schneider, 1988.
Evaluating water quality effects of lake management in
Florida. Lake Reservoir Mgmt. 4: 101-112.
Engel, S., 1990. Ecosystem responses to growth and control
of submerged macrophytes: A literature review. Depart-
ment of Natural Resources. Technical Bulletin No. 170.
Madison, W1.
Flessa, K. W. & J. J. Sepkoski Jr., 1978. On the relationship
between phanerozoic diversity and changes in habitat area.
Paleobiology 4: 359-356.
Forsberg, C. & S. K. Ryding, 1980. Eutrophication variables
and trophic state indices in 30 Swedish waste-receiving
lakes. Arch. Hydrobiol. 89: 189-207.
Gasaway, R. D., S. Hardin & J. Howard, 1977. Factors in-
fluencing wintering waterfowl abundance in Lake Wales,
Florida. Proc. Annual Conf. S. E. Assoc. Fish and Wild-
life Agencies. 31: 77-83.
Hoyer, M. V. & D. E. Canfield, Jr., 1990. Limnological fac-
tors influencing bird abundance and species richness on
Florida lakes. Lake Reservoir Mgmt. 6: 132-141.
Huber, W. C., P. L. Brezonik, J. P. Heaney, R. E. Dickinson
& S. D. Preston, 1982. A classification of Florida lakes.
Final Report, Florida Department of Environmental Regu-
lation. Tallahassee, FL.
Hutchinson, G. E., 1959. Homage to Santa Rosalia, or 'Why
are there so many kinds of animals?' Am. Nat. 93: 137-145.
Johnson, F. A. & F. Montalbano, 1984. Selection of plant
communities by wintering waterfowl on Lake Okeechobee,
Florida. J. Wildl. Mgmt. 48: 174-178.
Johnson, F. A. & F. Montalbano, 1989. Southern reservoirs
and lakes. In M. Smith, R. L. Pederson and R. M. Kamin-









however, will change as aquatic macrophytes are
removed from the lake system. Birds that use
aquatic macrophytes (e.g., ring-necked duck) will
be replaced by species that use open-water habi-
tats (e.g., double-crested cormorant). Some bird
species may also require specific type of aquatic
vegetation and the removal of that type may ex-
clude an individual bird species from a lake sys-
tem. Our analyses therefore suggest the impor-
tance of examining bird species as functional
groups in more detailed studies.
The majority of the birds counted during this
study were observed using near-shore areas.
These areas were where the water depth was shal-
low enough to allow wading birds to forage for
food and where terrestrial vegetation provides
cover and roosting areas. Future studies of bird
populations using lakes systems should carefully
examine near-shore areas, and determine the im-
portance of terrestrial vegetation to bird popula-
tions. As shorelines are developed for homes or
parks, much of the terrestrial vegetation is often
removed so people can see the lake. This could
have a major effect on not only how many birds
are present on the lake, but the species compo-
sition and distribution. We, therefore, suggest that
whole-lake bird counts be conducted with a de-
scription of individual bird habitat use, nesting
locations, and feeding activities. Studies should
include a minimum of monthly counts because of
the seasonal changes that can occur in bird popu-
lations.



Acknowledgements

We thank S. F. Mitchell and an anonymous re-
viewer for their many constructive comments on
this manuscript. Christy Horsburgh, Phillip Law-
son, and Mark Jennings were instrumental in col-
lection of data and conducting bird counts. We
thank Mary Stonecipher for conducting chemical
analyses. This research was funded in part by the
Bureau of Aquatic Plant Management (Contract
number C 3748), Florida Department of Natural
Resources.


References

Brown, M. & J. J. Dinsmore, 1986. Implications of marsh
size and isolation for marsh bird management. J. Wildl.
Mgmt. 50: 392-397.
Canfield, D. E. Jr., K. A. Langeland, M. J. Maceina,
W. Haller, J. V. Shireman & J. R. Jones, 1983. Trophic
state classification of lakes with aquatic macrophytes. Can.
J. Fish. aquat. Sci. 40: 1713-1718.
Canfield, D. E. Jr. & C. M. Duarte, 1988. Patterns in biom-
ass and cover of aquatic macrophytes in lakes: a test with
Florida lakes. Can. J. Fish. aquat. Sci. 45: 1976- 1982.
Canfield, D. E. Jr. & M. V. Hoyer, 1988a. The eutrophication
of Lake Okeechobee. Lake Reservoir Mgmt 4: 91-99.
Canfield, D. E. Jr. & M. V. Hoyer, 1988b. Regional geology
and the chemical and trophic state characteristics of Florida
lakes. Lake Reservoir Mgmt. 4: 21-31.
Canfield, D. E. Jr., M. V. Hoyer & C. M. Duarte, 1990. An
empirical method for characterizing standing crops of
aquatic vegetation. J. Aquat. Plant Mgmt. 28: 64-69.
Colle, D. E. & J. V. Shireman, 1980. Coefficients of condition
for largemouth bass, bluegill, and redear sunfish in hydrilla-
infested lakes. Trans. am. Fish. Soc. 109: 521-531.
Connor, E. F. & E. D. McCoy, 1979. The statistics of the
species-area relationships. Am. Nat. 113: 791-833.
Dierberg, F. E., V. P. Williams & W. H. Schneider, 1988.
Evaluating water quality effects of lake management in
Florida. Lake Reservoir Mgmt. 4: 101-112.
Engel, S., 1990. Ecosystem responses to growth and control
of submerged macrophytes: A literature review. Depart-
ment of Natural Resources. Technical Bulletin No. 170.
Madison, W1.
Flessa, K. W. & J. J. Sepkoski Jr., 1978. On the relationship
between phanerozoic diversity and changes in habitat area.
Paleobiology 4: 359-356.
Forsberg, C. & S. K. Ryding, 1980. Eutrophication variables
and trophic state indices in 30 Swedish waste-receiving
lakes. Arch. Hydrobiol. 89: 189-207.
Gasaway, R. D., S. Hardin & J. Howard, 1977. Factors in-
fluencing wintering waterfowl abundance in Lake Wales,
Florida. Proc. Annual Conf. S. E. Assoc. Fish and Wild-
life Agencies. 31: 77-83.
Hoyer, M. V. & D. E. Canfield, Jr., 1990. Limnological fac-
tors influencing bird abundance and species richness on
Florida lakes. Lake Reservoir Mgmt. 6: 132-141.
Huber, W. C., P. L. Brezonik, J. P. Heaney, R. E. Dickinson
& S. D. Preston, 1982. A classification of Florida lakes.
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lation. Tallahassee, FL.
Hutchinson, G. E., 1959. Homage to Santa Rosalia, or 'Why
are there so many kinds of animals?' Am. Nat. 93: 137-145.
Johnson, F. A. & F. Montalbano, 1984. Selection of plant
communities by wintering waterfowl on Lake Okeechobee,
Florida. J. Wildl. Mgmt. 48: 174-178.
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and lakes. In M. Smith, R. L. Pederson and R. M. Kamin-










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