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Effects of edge and internal patchiness on habitat use by birds in a Florida hardwood forest

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Effects of edge and internal patchiness on habitat use by birds in a Florida hardwood forest
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Noss, Reed F
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English
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vi, 109 leaves : ill. ; 28 cm.

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Birds ( jstor )
Breeding seasons ( jstor )
Ecology ( jstor )
Edge effects ( jstor )
Forest habitats ( jstor )
Forests ( jstor )
Hammocks ( jstor )
Shrubs ( jstor )
Species ( jstor )
Wildlife ( jstor )
Birds -- Effect of habitat modification on ( lcsh )
Birds -- Habitat ( lcsh )
Habitat (Ecology) -- Florida -- San Felasco Hammock State Preserve ( lcsh )
Habitat (Ecology) -- Modification ( lcsh )
Wildlife management -- Florida ( lcsh )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Thesis:
Thesis (Ph. D.)--University of Florida, 1988.
Bibliography:
Includes bibliographical references.
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Typescript.
General Note:
Vita.
Statement of Responsibility:
by Reed F. Noss.

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AA00004820_00001 ( sobekcm )

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EFFECTS OF EDGE AND INTERNAL PATCHINESS
ON HABITAT USE BY BIRDS IN A FLORIDA HARDWOOD FOREST







By

REED F. NOSS


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY










UNIVERSITY OF FLORIDA


1988




EFFECTS OF EDGE AND INTERNAL PATCHINESS
ON HABITAT USE BY BIRDS IN A FLORIDA HARDWOOD FOREST
By
REED F. NOSS
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
1988


ACKNOWLE DGMENTS
I thank the members of my supervisory committee, Drs.
Ronald F. Labisky (Chairman), Michael W. Collopy, and John G.
Robinson in the Department of Wildlife and Range Sciences,
and Drs. Peter Feinsinger and Brian K. McNab in the
Department of Zoology, University of Florida, for guidance
and comments throughout this study. Drs. T.C. Edwards and
K.M. Portier and Mr. Tim O'Brien provided statistical advice,
and Dr. L.D. Harris provided helpful dialogue throughout the
course of this study. Ms. Candy Hollinger drew all figures.
Funding was provided by the Alachua Audubon Society, the
Frank M. Chapman Memorial Fund, the Florida Ornithological
Society, the Josselyn Van Tyne Memorial Fund, and the
Department of Wildlife and Range Sciences, University of
Florida.
I owe much gratitude to my wife, Myra, and daughter,
April, for their steadfast patience during the countless
hours I spent in the field and behind the PC. This
dissertation is dedicated to my mother, Margaret Johnson Noss
(1923-1987), who always encouraged my interest in natural
history, and to my father, James Frederick Noss, who
continues to help and encourage me today.
ii


TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS ii
ABSTRACT V
INTRODUCTION 1
STUDY AREA AND METHODS 5
Study Area 5
Bird Surveys 10
Habitat Analysis 12
Data Analysis 17
RESULTS 20
Habitat Description 20
Birds 24
Edge Effects 26
Bird Densities in Edge versus Interior Plots 43
Internal Patchiness and its Relation to Bird
Densities and Edge Effect 43
Patterns at the Between-Plot Scale 56
Responses of Individual Species to
Habitat Heterogeneity 60
DISCUSSION 64
Bird Responses to Forest Edge and Internal
Patchiness: A Matter of Scale? 64
Edge Relations 66
Patchiness Relations 71
Management Implications 75
A Final Comment on Scale and Observation 8 0
LITERATURE CITED 83
APPENDIX
I PROPORTIONAL RELATIVE ABUNDANCES OF TREE AND
SHRUB-LEVEL WOODY SPECIES 9 5
iii


Page
II BIRD SPECIES OBSERVED IN STUDY PLOTS AND THEIR
EDGES IN SAN FELASCO HAMMOCK, 1985-86 101
BIOGRAPHICAL SKETCH 108
iv


Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
EFFECTS OF EDGE AND INTERNAL PATCHINESS
ON HABITAT USE BY BIRDS IN A FLORIDA HARDWOOD FOREST
By
Reed F. Noss
August, 1988
Chairman: Dr. Ronald F. Labisky
Major Department: Wildlife and Range Sciences
(Forest Resources and Conservation)
Effects of edge and internal patchiness on habitat-use
by birds were studied in an old-growth hardwood forest in
northern Florida. Registrations of birds during the breeding
seasons of 1985 and 1986, fall 1985, and winter 1986 were
mapped in 12, 5.0-ha plots that abutted edge and in 3, 5.0-ha
interior plots >700 m from edge. Habitat-use patterns of 27
avian species were analyzed at within-plot (0.5-ha subplots)
and between-plot observation scales. Forest edges, canopy
gaps, and shrubby seepage areas ("bayheads") exhibited high
densities of birds within plots, but with seasonal and
species-specific variations. Density of birds at 0-50 m from
edge was significantly (P < .05) greater than in distance
zones farther from edge in 6 of 12 edge plots, for all
seasons combined. All 27 species used both interior and edge
habitat, but 12 species were generally attracted to edge, 11
were indifferent, and 4 avoided edge. Edge effects were
v


greatest during the breeding seasons in plots with high-
contrast edges, and in east-facing edges on sunny winter
mornings (suggesting a microclimatic influence). Attraction
to edge in the breeding seasons was stronger in subplots
lacking gaps and bayheads than in more heterogeneous
subplots. In interior plots and in all plots combined,
regression models containing indices of patchiness
(especially gap/bayhead area) explained 5-71% of the
variation in bird density, depending on season; strongest
relationships occurred during the breeding seasons.
In between-plot analyses, neither bird density nor
richness differed between edge plots and interior plots, or
between patchy plots and more homogeneous plots (except that
richness was correlated with CV of shrub density, one measure
of patchiness). Birds used gaps, bayheads, and edges
extensively within plots, but did not concentrate in areas of
the forest near edge or with more gap/bayhead area. Hence,
both edge effects and "patch effects" may be dependent on
observation scale. Allowing forests to mature to naturally
patchy old-growth may be a more prudent management strategy
than maintaining artificial openings or edges.
vi


INTRODUCTION
No natural community is homogeneous. Yet, a tradition
in community ecology has been to select the most uniform and
undisturbed areas as study sites (Forman and Godron 1981,
Noss 1987a). Although recognition of natural disturbances
and spatiotemporal mosaics is not new (e.g., Cooper 1913,
Watt 1925, 1947), selection of heterogeneous systems as units
of study only recently has become popular in North American
ecology (Forman and Godron 1981, 1986, Risser et al. 1984,
Pickett and White 1985, Urban et al. 1987). The increasing
acceptance of landscape ecology follows the recognition that
many organisms depend on environments that are frequently
disturbed and composed of multiple habitats (White 1979, den
Boer 1981, Karr and Freemark 1983, May 1986, Noss 1987a,
Merriam 1988).
Habitat heterogeneity occurs at many spatial scales, as
an expression of environmental gradients and resource
patchiness, and disturbances that are patchy in time and
space. Not only does landscape pattern affect population
distribution, but the scale at which patterns are sought will
determine what patterns are detected (Wiens 1985, 1986, Wiens
et al. 1987). Coarse-grained landscape heterogeneity
1


2
(macroheteroqeneity; Forman and Godron 1986) is generated by
large natural disturbances as well as by anthropogenic
habitat modification and fragmentation. Patches in
macroheterogeneous landscapes, e.g., interspersed woodlots,
crop fields, pastures, ponds, and housing developments, are
easily recognized as separate habitats. Boundaries between
habitats at this scale are usually called "edges." In
contrast to the mosaic of habitats at a landscape scale,
fine-grained patchiness (microheteroqeneitv; Forman and
Godron 1986) occurs within what are usually recognized as
distinct habitats or community-types.
Habitat selection, best studied for birds (Cody 1985),
involves responses to habitat cues at several spatial scales
(Hilden 1965, James 1971, Hutto 1985, Wiens 1985). Elements
of habitat heterogeneity at different scales determine the
distribution of bird populations, territories, and activity
within territories. Over a range of habitats, bird species
diversity is positively correlated with complexity of the
vertical foliage profile (MacArthur and MacArthur 1961,
Recher 1969, Karr and Roth 1971). Horizontal complexity or
patchiness of vegetation, however, may be more important than
vertical profiles in determining bird species composition and
diversity within study sites (MacArthur et al. 1962, Roth
1976, 1977, Wiens 1985, Freemark and Merriam 1986). An
important element of within-habitat patchiness is treefall
gaps. Gaps often contain high densities of resources such as


insects and fruits, and therefore attract an abundance of
birds (Blake and Hoppes 1986, Martin and Karr 1986) .
Patchiness at a coarser scale may affect bird
distribution within habitats, i.e., the well-known "edge
effect." Many bird species are attracted to edges, but a few
species are repelled and some are indifferent (Whitcomb et
al. 1981). Although maximizing edge habitat has been a
common wildlife management prescription (Thomas et al. 1979),
this policy has been criticized in recent conservation
biological literature because of documented deleterious
effects on forest interior species (Whitcomb et al. 1976,
1981, Gates and Gysel 1978, Noss 1981, 1983, Brittingham and
Temple 1983, Lovejoy et al. 1986, Wilcove et al. 1986).
Unfortunately, studies of edge effects on birds generally
have ignored habitat patchiness within forests. Gates and
Gysel (1978) hypothesized that edges attract many passerines
because they contain structural cues similar to those of the
mixed life-form habitats in which these species evolved.
Before European settlement, the eastern deciduous forest
landscape was old-growth (best understood as a mosaic of
developmental stages, rather than just the mature stage). In
contrast to the generally even-aged, close-canopied,
secondary forests in which edge effects usually have been
studied, old-growth is horizontally patchy with numerous gaps
in various stages of post-disturbance regeneration (Bormann
and Likens 1979, Runkle 1985, Whitney 1987).


Does edge effect diminish in forests with increased
internal patchiness such as that associated with treefall
gaps? Or conversely, do artificial edges disrupt the normal
distribution of bird activity with respect to internal
patchiness? This study simultaneously considered effects of
edge and internal patchiness on habitat use by birds in an
old-growth hardwood forest in north central Florida.
Specific objectives were (1) to test the null hypothesis of
uniform distribution of birds with distance from edge for
different species, seasons, and edge types; (2) to
investigate the relation between bird density and habitat
heterogeneity (as measured by several indices) in 5.0-ha
plots that abutted edge, and in 5.0-ha "control" plots
located at distances > 700 m from edge; (3) to identify bird-
habitat heterogeneity relationships at within-plot and
between-plot observation scales; and (4) to determine
interacting effects of internal habitat heterogeneity and
edge on bird habitat-use.


STUDY AREA AND METHODS
Study Area
San Felasco Hammock State Preserve (2945' N, 8230/ W)
is located 8 km northwest of Gainesville, Alachua County,
Florida. Over half of the 2500-ha preserve is mesic hammock
(a mixed-species, predominantly hardwood forest), considered
the climax community of northern Florida by many authors
(Harper 1905, Quarterman and Keever 1962, Monk 1965). In
Florida, fire, interacting with slope-moisture gradients, is
a primary determinant of plant distribution; hammocks are
naturally restricted to ravines and sinkhole slopes, islands,
peninsulas, and other sites of reduced fire freguency (Harper
1911, Clewell 1981, Platt and Schwartz in press). The high
species richness (probably the largest stand-scale number of
woody species in the continental United States) and
structural heterogeneity of north Florida hammocks derive
from a complex disturbance regime which creates numerous gaps
and maintains nonequilibrium populations of plants (Platt and
Schwartz in press).
The study site was chosen for its size (with gradients
from edge to deep interior habitat) and old-growth character.
San Felasco Hammock is probably the largest remaining mesic
5


hammock in the hammock belt that extends along the central
ridge of the Florida peninsula (Ewel and Simons 1976, Platt
and Schwartz in press). The vegetation and flora of San
Felasco Hammock were described by Ansley (1952) and Dunn
(1982), and summarized by Skeate (1987). The woody flora of
this mesic hammock is extremely rich, with as many as 20 tree
species per ha (Noss, unpublished data) and 50 "canopy
potential" tree species (Dunn 1982). Dominant canopy trees
include Ouercus hemisphaerica. Carva glabra. Magnolia
grandiflora. Ouercus nigra. Ouercus virginiana. Pinus glabra,
Liguidambar stvraciflua. Ouercus michauxii. Ouercus austrina,
Ouercus shumardii. Ouercus falcata. Acer barbatum. Fraxinus
americana, Carva tomentosa. and Tilia caroliniana. San
Felasco is near the southern range limit for many plant
species (R. Simons, personal communication), and for several
forest-interior bird species that are known elsewhere to be
sensitive to forest fragmentation and edge effects (cf.
Whitcomb et al. 1981).
The portion of San Felasco Hammock in which study plots
were selected was mature mesic hammock, as mapped by Dunn
(1982). This forest has been selectively logged (Dunn 1982),
but is essentially old-growth, with an uneven age composition
of trees, a pit-and-mound microtopography, and a horizontal
mosaic pattern enriched by treefall gaps, sinkholes, seepage
areas with dense broad-leaved evergreen trees and shrubs
(bayheads), and other patches. The mesic hammock in San


7
Felasco abruptly borders several other habitat types. Some
of these sharp edges are natural (e.g., with adjoining
sinkhole marshes and pinelands), whereas others are
artificial (e.g., with Oldfields and cleared powerline
rights-of-way).
Five major edge types were identified: hammock/
oldfield? hammock/open pine plantation; hammock/longleaf
pine-turkey oak (sandhill); hammock/herbaceous marsh; and
hammock/open powerline right-of-way. These edge types were
the strata from which 12, 5.0-ha (200 m x 250 m) plots were
selected randomly, with the restriction that the central
transects of plots be at least 300 m apart to avoid double
counting of birds. Two plots were selected to represent each
edge type, except that 4 plots (2 with southwest-facing edges
and 2 with northeast-facing edges) were selected from the
powerline right-of-way. Hence, each of 12, 5.0-ha plots
abutted an open habitat along a 200-m edge, and extended 250
m into the hammock (Fig. 1, Table 1). In addition, 3
"control" plots of 5.0 ha each were selected randomly in
interior forest >700 m from any abrupt edge (Table 1). Each
5.0-ha plot was divided into 10, 0.5-ha subplots for data
compilation and analysis (Fig. 1). A central transect line
for bird surveys extended 250 m through each plot, with
observation posts flagged every 25 m. Prominent habitat
features such as major gaps and sinks, streams, trails, and


Edge-
05L
1
-22
r
15-
05R
04L
-11
'5-
04R
03L
-1
!5-
03R
02L
-7
5-
02R
OIL
-2
5-
01 R
100 50 0 50 100
Distance (m)
Edge
FIG. 1. Schematic diagram of an individual 5.0-ha study plot. The transect
line originates at the 0-m point (edge) and extends 250 m into the interior.
Each rectangle (labled OIL, OIR, 02L, etc.) represents a 0.5-ha subplot.


TABLE 1. Individual 5.0-ha study plots and their transect
orientations, San Felasco Hammock, Florida. All edge
plots are perpendicular to edge,whereas interior plots
are perpendicular to narrow trails.
Edge Plots (N = 12)
PL1
(Powerline
1): 30
PL2
(Powerline
2): 220
PL3
(Powerline
3): 220
PL4
(Powerline
4): 40
MAI
(Marsh 1):
70
MA2
(Marsh 2):
280
SA1
(Sandhill
1) : 110
SA2
(Sandhill
2): 340
PP1
(Pine Plantation 1):
270
PP2
(Pine Plantation 2):
270
0F1
(Oldfield
1): 270
0F2
(Oldfield
2): 270
Interior Plots
(N = 3)
IF1
(Interior
Forest 1):
270
IF2
(Interior
Forest 2):
320
IF3
(Interior
Forest 3):
180


10
big trees were mapped prior to the study to facilitate
accurate location of birds.
Bird Surveys
Birds were surveyed by use of a strip-map method (Emlen
1984; similar to the "plot mapping" of Christman 1984), which
is essentially a combination of transect and spot-mapping
technigues. The method is observer-specific, with plot width
dependent on the detection abilities of an individual
observer. The 12 edge plots were sampled in spring 1985
(S85: 18 censuses each from 5 March-18 June), fall 1985 (F85:
6 censuses each from 12 September-30 November), winter 1986
(W86: 6 censuses each from 11 January-27 February) and spring
1986 (S86: 12 censuses each from 2 March-19 May). The 3
interior (control) plots were censused in W86 and S86; these
censuses were conducted during the same calendar period and
at the same frequency as for edge plots. Demarcation of
seasons was necessarily arbitrary. Breeding seasons
(indicated by singing and other territorial behavior) of
permanent resident passerines and woodpeckers begin in this
region in January and February, at the same time when
wintering species reach peak abundance. Summer residents
begin breeding in March and April, coinciding with peak
densities of migrants, often of the same species.
Daily censuses were confined to the period between
sunrise and 3 h post-sunrise. Three or 4 plots were censused


11
per census day, with plot order alternated to assure
equivalent temporal coverage. Censuses were not conducted if
weather conditions were adverse (i.e., rain or strong winds).
Auditory and visual observations of birds were mapped
during each census. A registration was defined as any
auditory/visual observation within the study plot, excluding
birds flying above the canopy. Density refers to the sum of
registrations recorded in a defined area (e.g., a subplot).
Birds using the edge (or plot boundary, for interior plots)
were mapped as each transect starting point was approached;
thereafter, registrations were recorded during 3-min periods
at each 25-m interval observation post. Registrations also
were recorded while walking slowly between observation posts.
Bird movements were recorded as separate registrations if
they were >25 m from the previous registration; however,
movements that appeared to be in response to the observer
(either attraction or avoidance) were not recorded.
Preliminary censuses indicated that most resident
(breeding, winter, and permanent) species could be detected
by ear up to 100 m from the central transect line; thus,
registrations were mapped within 100 m on each side of the
transect. The analysis assumed equivalent detectability in
all subplots of each plot, in accordance with equivalent
sampling effort. Because comparison of abundances among
species was not an objective, the analysis did not assume
that species were equally detectable, or that detectability


12
was constant from 0-100 m; thus, no coefficients of
detectability (Emlen 1971) were calculated. Resident species
with poor detectability (e.g., Blue-gray Gnatcatcher) were
excluded from analysis. Also excluded from analysis were
those species with sample sizes <30 in the 12 edge plots
(single-species analyses were performed for combined edge
plots and for all 15 plots combined), and one abundant winter
resident (Yellow-rumped Warbler) that usually occurred in
sporadic, itinerant flocks. Species with large territories
or ranges (raptors, jays, and crows) were not mapped or
analyzed. Breeding status was based on Florida Breeding Bird
Atlas criteria (Noss et al. 1985). Species richness of
probable and confirmed breeders with at least 25% of a
territory in a plot was recorded for each plot in 1985 and
1986.
Habitat Analysis
The objective of habitat analysis was to measure
parameters of forest microheterogeneity proposed in previous
studies to be important to birds, including diversity of
vertical profiles, spatial variability in tree and shrub
dispersion, variation in shrub density and canopy openness,
floristic (tree and shrub) diversity, and proportion of plot
occupied by canopy gaps and bayheads (Table 2). These
attributes of heterogeneity were measured in summer and early
fall 1986 at 2 scales: 0.5-ha subplot (for within-plot


13
TABLE 2. Habitat variables measured for each 0.5-ha subplot
(from 10 point-quarter samples/subplot) and/or each 5.0-ha
plot, San Felasco Hammock, Florida. See text for further
explanation.
Variable
Measurement definition
Plot (P) or
Subolot rsp^
DIST
median distance (m) from edge
for each subplot
SP
VT
coefficient of variation (CV) of
distances to nearest trees in
point-quarter samples
SP and P
VS
CV of distances to nearest "shrubs"
in point-quarter samples
SP and P
VTS
CV of distances to nearest trees or
shrubs in point-quarter samples
SP and P
DENS
mean number (N) of shrub stems in
quarter-circles within 2 m of each
sample point
SP and P
VSD
CV of shrub density (DENS)
measurements
SP and P
OPEN
mean canopy openness (%), or converse
of canopy density, as measured by
spherical densiometer at each
sample point
SP and P
VCO
CV of canopy openness (OPEN)
measurements
SP and P
HT
Shannon diversity (H' log10) f tree
species from point-quarter samples
SP and P
(separate)
HS
H' of shrub species from point-
quarter samples
SP and P
(separate)
HPD
H' of vertical foliage profiles at
each sample point
SP and P
(separate)
GA
proportion of area in canopy gaps
with shrub-sapling growth generally
< 2 m
SP and P
GB
proportion of area in canopy gaps
with shrub-sapling growth >2 5 m
SP and P
GAB
GA + GB
SP and P


14
TABLE 2continued
Variable
Measurement definition
Plot (P) or
Subolot (SP}
BAY
proportion of area in bayhead
vegetation
SP and P
GAPBAY
GAB + BAY (sum)
S and P
LG
largest single canopy gap in
plot (m2)
P
ST
number of tree species (S) in
from point-quarter samples
plot,
P
SS
number of "shrub" species (S) in
plot, from point-quarter samples
P


15
analysis) and 5.0-ha plot (for between-plot analysis). A
grid of 100 uniformly-distributed sampling points was
superimposed on each plot, with 10 points per subplot.
Systematic sampling is preferable to random sampling when the
objective is to distinguish pattern or variability in the
vegetation (Greig-Smith 1964, Gauch 1982).
Trees and shrubs were sampled by use of the point-
centered quarter technique (Cottam and Curtis 1956). The
nearest tree and shrub in each of 4 quarter-circles around
each sampling point was recorded by species and distance from
the point. Trees (woody stems >5 m in height) were separated
into dbh categories (<10, >10-30, >30-50, >50-70, and >70
cm). Shrubs were defined as woody stems 0.3-5m in height.
The number of shrub stems was recorded in each quarter circle
within a 2-m radius from each sampling point for determina
tion of mean shrub density. A coefficient of variation (CV)
was calculated for distances to nearest trees, shrubs, and
trees and shrubs combined in each subplot (Roth 1976), and
for shrub density. A mean CV for 10 subplots was equivalent
to the CV for a plot. The Shannon diversity index (H',
log10) was calculated for trees and shrubs for each subplot
and separately for each plot. Presence or absence ( + or -)
of vegetation within a 0.5-m diameter circle centered on each
sampling point was recorded for 4 layers: herb (<0.3 m),
shrub (>0.3-5 m), understory (>5-10 m) and overstory (>10 m),
and H' was calculated for profile types (e.g.,
+++, ++1-) in


16
each subplot and plot. Mean canopy openness (%, as
determined by a spherical densiometer over each sampling
point) and CV of canopy openness were determined for each
plot and subplot.
Canopy gaps and bayheads were mapped on each plot and
converted to proportions of area by use of a dot grid. A gap
was defined as a vertical hole in the canopy > 10 m in mean
diameter (a minimum area of 78.5 m2) and included canopy
openings caused by sinkholes as well as windthrow (treefall)
gaps. The proportionate gap area in each subplot and plot
was calculated in 3 categories: GA (gaps with shrub-sapling
growth averaging <2m in height), GB (gaps with shrub-sapling
growth >2-5 m in height) and GAB (GA + GB). The
proportionate area occupied by bayheads was calculated
separately (BAY), and added to gap area for a final patch
category (GAPBAY).
Local (edge-specific) sunshine data were collected
during censuses of east-facing edges in winter 1986 to
determine whether edges warmed by early-morning sun had
greater densities of birds. Edges were considered sunny if
sunlight was directly striking the edge face at the time of
census, and not sunny if cloudy, foggy, or before sunrise
illuminated the edge.


17
Data Analysis
Data were analyzed with SYSTAT programs (Wilkinson 1987)
on an IBM PC-XT. Major analyses included least squares
regression modelling (simple and multiple), analysis of
covariance (ANCOVA), tests for homogeneity and goodness of
fit, and tests for difference between means. Correlation of
bird densities from subplots between seasons was a measure of
consistency of site use and thus indicated which seasonal
combinations were homogeneous. Bird densities had normal
distributions in all seasons, as determined from normal
probability plots. Some habitat variables (DIST, HT, HS,
HPD, ST, SS) were distributed normally without
transformation; the other variables were normalized and their
variances stabilized by logarithmic (In) transformation.
Zero values for GA, GB, GAB, BAY, and GAPBAY were converted
to -10 on the log scale (smallest log-transformed non-zero
values were > -5). Zero values for bird registrations in
subplots were converted to .001 for single-species regression
analysis.
Edge effects in the 12 edge plots were determined by
analysis of registration densities in 5 zones 100 m wide
parallel to edge and 50 m perpendicular to edge, each
comprising 2 subplots (e.g., OIL and 01R in Fig. 1). A G-
test for goodness of fit (Sokal and Rohlf 1981) was used to
test the extrinsic null hypothesis that bird registrations
were distributed uniformly in the 5 distance zones, H0:


18
Pl = p2 = P3 = P4 ~ P5* Overall G-tests for plots (all
species, all seasons), seasons (all species, all plots), and
species (all plots, all seasons) were partitioned into
separate G-tests to determine which individual distance zones
were significantly high or low in density relative to the
mean (expected frequency). G-tests also were performed to
test for uniformity of density in distance zones in the 3
interior plots.
Regression analysis was used to model response of bird
density to distance from edge (DIST) and to habitat
heterogeneity variables. Dependent variables were
registration densities of individual bird species and all
species sums, totaled for each of the 4 seasons, for all
seasons combined, and for appropriate combinations of
seasons. Independent variables were distance from edge and
habitat heterogeneity variables (Table 2).
ANCOVA was used to test regression models for
differences in bird density among groups, e.g., between east
and non-east facing edges, between high- and moderate-
contrast edges, and between subplots with and without
gaps/bayheads, in response to the independent variable
(covariate) DIST. A preliminary ANCOVA model was first
applied to test for homogeneity of slopes among groups. If
slopes were homogeneous, ANCOVA was used to test for
homogeneity of Y-intercepts among groups (equivalent to a
test for homogeneity among group means, Sokal and Rohlf


19
1981). The null hypothesis of equal density of birds in edge
and interior plots was tested by comparing the mean number of
registrations per subplot in each group in winter and spring
1986, when all 15 plots were censused.
Simple linear regressions were performed for all
species registrations in each season and in all seasons
combined for each habitat variable. Multiple regression
models were constructed using all possible subsets
(combinations) of variables. Criteria for optimal (i.e.,
best prediction) regression models were (1) the highest r2
value; (2) the fewest number of independent variables, each
with non-significant correlations (P > .05) with all others;
(3) each variable with a significant (P < .05) t-statistic
for regression; (4) homogeneous slopes among groups (e.g.,
individual plots), as indicated by P > .05 for group by
covariate interaction; (5) normal distribution of residuals;
and (6) homogeneity of variance of residuals across different
levels of independent variables, as indicated by a
homoscedastic plot of residuals against estimates (Sokal and
Rohlf 1981, Gutzwiller and Anderson 1987, Wilkinson 1987,
K.M. Portier, personal communication). Analysis of residuals
included correlating residuals with each independent
(habitat) variable not in the optimal model. Finally,
correlations with habitat variables were determined
individually for the 12 most abundant species observed during
winter-spring 1986 in all 15 plots.


RESULTS
Habitat Description
Canopy gaps caused by treefall and sinkholes were a
prominent feature of most plots (Table 3). A mean of 3.4% of
plot area was occupied by canopy gaps (> 78.5 m2). Sinkhole
gaps were prominent in plots PP1, 0F1 (an outlier in gap
area, with one canopy opening of 3208.02 m2), and IF1.
Treefall gaps averaged 3.1% of plot area; the largest single
treefall gap (in SA1) was 864.66 m2. Bayhead vegetation
occurred in only 2 plots, PP2 and IF1, where it occupied
18.3% and 9.8% of plot area, respectively. Ninety-one (61%)
of the 150 total subplots had gaps and/or bayheads, which
covered 5.3% of the total plot area.
None of the habitat heterogeneity variables (Table 3)
was related significantly to distance from edge. The
strongest association was a positive correlation between tree
species diversity (HT) and distance from edge (r = .163, P =
.075). Plots were rich in tree species, ranging from 17 to
27 (x = 22.33) and in "shrubs" (which included tree saplings
in the shrub layer), ranging from 24 to 39 species (x =
29.73) (Appendix I).
20


21
TABLE 3. Summary of habitat measurements from 15, 5.0-ha
plots (see Table 2 for definition of variables), San
Felasco Hammock, Florida, 1986. HT, HS, HPD, LG, ST, and
SS are measured at the 5.0-ha scale; other values are means
from the 10, 0.5-ha subplots in each plot.
Plot
VT
VS
VTS
DENS
VSD
OPEN
PL1
55.8
68.9
87.1
6.8
62.9
5.6
PL2
56.8
75.2
96.3
13.8
71.6
7.9
PL3
58.1
75.2
95.9
11.2
67.9
9.2
PL4
57.8
74.0
88.5
8.7
103.9
8.6
MAI
59.0
76.3
91.1
8.7
92.7
6.3
MA2
58.0
80.6
90.4
7.8
86.9
6.1
SA1
58.2
71.5
93.5
9.4
80.4
5.6
SA2
55.6
90.4
88.2
9.0
91.2
6.2
PP1
58.3
83.1
101.8
12.0
60.5
5.9
PP2
56.8
67.3
100.3
12.6
61.7
5.3
0F1
68.5
87.9
109.0
10.2
70.2
12.4
OF2
56.0
77.4
93.4
10.9
68.1
4.9
IF1
59.9
74.0
99.0
15.2
71.3
5.3
IF2
56.1
61.0
87.4
7.8
83.5
5.9
IF3
57.3
80.9
89.3
9.1
93.3
5.6
X
58.1
76.2
94.1
10.2
77.7
6.7
SD
3.1
7.7
6.3
2.4
13.5
2.0


22
TABLE 3continued
Plot
VCO
HT
HS
HPD
GA
GB
PL1
57.2
1.15
1.15
.66
. 010
. 003
PL2
37.2
0.97
0.93
. 61
.005
.030
PL3
44.2
0.91
0.87
. 52
0.0
.060
PL4
37.8
0.99
1.17
. 39
.008
.032
MAI
57.7
1.08
1.17
.52
.004
. 048
MA2
53.8
1.07
1.15
.69
. 005
. 048
SA1
48.2
1.02
1.16
.54
. 005
.037
SA2
61.9
1.04
0.98
.59
. 010
.008
PP1
51.5
1.02
0.88
.45
. 022
.009
PP2
43.0
1.00
1.04
.47
. 005
. 002
0F1
67.3
1.10
1.14
. 62
. 068
. 010
OF2
35.8
1.05
1.08
.50
0.0
. 003
IF1
48.5
1.20
1.21
.48
.020
.004
IF2
50.4
1.00
1.17
.56
. 010
. 030
IF3
40.1
1.10
1.35
.60
0.0
. 008
X
49.0
1.05
1.10
.55
. Oil
. 022
SD
9.5
.07
. 13
.08
. 174
.020


TABLE 3continued
23
Plot
GAB
BAY
GAPBAY
LG (m^)
ST
SS
PL1
. 013
0.0
. 013
500.00
25
33
PL2
. 035
0.0
.035
319.55
19
26
PL3
. 060
0.0
.060
620.30
17
24
PL4
. 040
0.0
.040
839.60
20
30
MAI
. 052
0.0
. 052
651.63
25
26
MA2
.053
0.0
. 053
363.41
27
31
SA1
. 042
0.0
. 042
864.66
23
31
SA2
.018
0.0
.018
200.50
26
26
PP1
. 031
0.0
. 031
914.79
22
31
PP2
. 007
0.183
. 190
125.31
22
28
0F1
.078
0.0
.078
3208.02
22
32
OF2
.003
0.0
. 003
150.00
22
30
IF1
. 024
0.098
. 122
870.93
27
39
IF2
. 040
0.0
.040
651.63
17
27
X
.034
. 019
.053
701.65
22.33
29.73
SD
. 022
.052
.048
746.95
3.24
3.75


24
Birds
One hundred twenty-nine bird species were observed on
the San Felasco Hammock study plots in 1985 and 1986
(Appendix II). Quantitative analyses were conducted on 27
species; 102 species were excluded because of insufficient
sample sizes (n < 30 for 12 edge plots over all seasons) or
sampling biases. Breeding species richness (S) was
significantly higher in 1985 than in 1986 (Table 4; t = 3.89,
P = .003). In 1986, when all plots were censused, S did not
differ between edge and interior plots (t = 0.681, P = .508).
For all plots combined, S was significantly related to only
one habitat variable, variation in shrub density (VSD; r =
0.517, P = .048).
Correlations of bird densities in subplots between
seasons indicated that site use was not always consistent.
For the 12 edge plots, site use in the 1985 and 1986 breeding
seasons (S85 and S86) was consistent (r = 0.56, P < .001).
Site use for edge plots in fall 1985 (F85) was not consistent
with that in any other season (P > .05). Site use for edge
plots in winter 1986 (W86) was consistent with S86 (r =
0.272, P = .003), but not with S85 (r = 0.126, P = .17).
Site use in W86 and S86 was consistent for the 3 interior
plots (r = 0.51, P = .004) and for all 15 plots combined (r =
0.30, P < .001).


25
TABLE 4. Breeding bird species richness in 15, 5.0-ha
plots, San Felasco Hammock, Florida, 1985-86. A species
was included only if > 25% of the territory of one
breeding pair was within plot.
Plot
Number
of species
1985
1986
Mean
PL1
16
14
15.0
PL2
17
16
16.5
PL3
14
15
14.5
PL4
18
17
17.5
MAI
16
14
15.0
MA2
17
18
17.5
SA1
16
13
14.5
SA2
17
12
14.5
PP1
16
13
14.5
PP2
16
12
14.0
0F1
17
12
14.5
0F2
15
12
13.5
IF1
a
16
16.0
IF2

16
16.0
IF3

15
15.0
X
16.25
14.33
15.23
a Not censused in 1985


26
Edge Effects
G-tests of the null hypothesis that bird density was
uniform with respect to distance from edge, in the 12 edge
plots, yielded diverse results (Table 5). For all seasons
combined, 6 of the 12 edge plots had a significant
concentration of bird registrations within 50 m from edge; 4
of these 6 plots also had reduced density in the 2 zones
farthest from edge (150-200 m and 200-250 m). Of the 6 plots
that did not show a positive edge effect, 3 exhibited a low
density at 200-250 m, 1 a low density at 50-100 m, 1 a high
density at 150-200 m, and 1 a low density at 0-50 m and a
high density at 100-150 m.
For all 12 edge plots combined, a positive edge effect
was evident for all seasons combined, for the 1985 and 1986
breeding seasons, and for winter 1986but not for fall 1985
(Table 5). Although the density of registrations in the 0-50
m zone for fall 1985 was not significantly high, densities in
the 2 zones farthest from edge were low. In all other
seasons, densities in the 0-50 m zone were significantly
high, indicating an edge effect, and those in the 200-250 m
zone were low.
Bird densities in none of the 3 interior plots were
higher in the 0-50 m zone; hence, no "pseudo-edge effect" was
evident (Table 6). Although 1 interior plot had low density
in the 200-250 m zone, the other 2 had high densities in the
central zones (significant in one case). Densities in all 3


TABLE 5. Edge effect as measured by G-testsa of bird
registration densities in 5 distance zones from edge in 12,
5.0-ha plots, San Felasco Hammock, Florida, 1985-86. Plot
totals are for all seasons combined; season totals are for all
plots.
Registrations (by zones, defined in m) Positive
Edge
Plot
0-50 50-
100 100
-150 150-
200 200
-250 G
-value
P
Effect
PL1
161b
137
154
121
82
32.70
<.001
Y
PL2
196
140
221
210
185
21.65
<.001
N
PL3
206
221
197
168
133
27.85
<.001
N
PL4
211
208
201
242
123
42.97
<.001
N
MAI
229
161
170
155
138
26.73
<.001
Y
MA2
240c
205
203
158
164
22.81
<.001
Y
SA1
146
145
161
193
142
10.99
<.05
N
SA2
149d
183
216
178
183
12.86
<.02
N
PP1
245
199
150
179
143
36.22
<.001
Y
PP2
192
212
241
165
126
42.44
<.001
N
0F1
232
149
125
120
160
48.17
<.001
Y
0F2
247
119
104
145
65
129.82
<001
Y
M


TABLE 5continued
Registrations (bv
zones, defined
in m)
Positive
Edge
Plot
0-50 50
-100 100
-150 150-
-200 200-250 G-
-value
P
Effect
Seasons
S85
1176
1046
1114
1016
861
53.42
<.001
Y
F85
288
240
266
207
182
31.09
<.001
Y?
W86
286
196
156
17 5e
105
94.55
<001
Y
S86
704
579
607
636
496
39.02
<.001
Y
TOTAL 2454
2079
2143
2034
1644
164.80
<.001
Y
a
G-test of
H0: Pi =
P2 = P3
= P4 =
p5.
b Underlined values are higher or lower than predicted by H0; one
more underlined values in a row would need to be removed in order to
obtain a non-significant G-value for remaining values.
c In this plot, removal of either the 240-158 pair or the 158-164
pair resulted in a non-significant G-value*
^ Values in bold face indicate that either could be removed to
obtain a non-significant G-value for remaining values.
or
e For W86, either the 196-175 or 156-175 combinations led to
acceptance of H0 (non-significant G-value) with other values removed
fo
00


TABLE 6. Potential sampling bias (pseudo-edge effect), as
indicated by G-tests of bird registration densities in 5 distance
zones in the 3 interior plots, San Felasco Hammock, Florida, 1986.
Plots
Reaistrations
fbv zones, defined in m)
G-value
P
0-50
50-100
100-150
150-200
200-250
IF1
68
88
67
53
3 6a
24.81
<.001
IF2
50
87
85
63
60b
15.48
<.01
IF3
45
76
58
64
63
8.40
>.05
TOTAL
163
251
210
180
159
29.55
<.001
a Value 36 must be removed, plus either 88 or 53, to yield a non
significant G-value.
b One of the following combinations must be removed to yield a non
significant G-value: 50-60, 50-87, or 85-87.
VO


30
interior plots combined were highest in the 50-100 m and 100-
150 m zones.
Individual species responded differently to edge but
were classified into 3 general categories (Table 7). Twelve
species were edge-attracted (i.e., they showed a significant
concentration in the first distance zone), 11 species were
edge-indifferent (i.e., they had neither higher nor lower
than expected densities near edge), and 4 species were edge
avoiding (i.e. they showed lower than expected densities
near edge). All 4 edge-avoiding species and 10 of the 12
edge-attracted species (exceptions were the Ruby-crowned
Kinglet and Gray Catbird) bred on the study plots. In
contrast, 7 of the 11 indifferent species were wintering
birds.
The directional exposure of edge plots influenced the
distribution of birds with respect to edge, but only in
winter (Fig. 2). The relationship between bird density and
distance from edge for east-facing and non-east facing edge
plots, in the breeding seasons, did not differ in slope (Fig.
2, A and D; F = 0.242, P = .623), or in intercept (ANCOVA, F
= 1.275, P = .261). Regressions for fall (Fig. 2, B and E)
also did not differ in slope (F = 0.919, P = .340) or in
intercept (ANCOVA, F = 0.003, P = .958). In winter, however,
the slope for east-facing edges was significantly steeper
than for non-east-facing edges (Fig. 2, C and F; F = 6.723, P
= .011). Total winter registrations in subplots averaged


TABLE 7. Response of individual bird species to distance from edge,
totaled over all seasons in all edge plots, as determined by G-tests,
San Felasco Hammock, Florida, 1985-86. Birds are classified as edge-
attracted, edge-indifferent, or edge-avoiding depending on which
distance zones have values departing significantly from uniformity.
Registrations (by zones, defined in m)
Species 0-50 50-100 100-150 150-200 200-250 G-value P
EDGE-ATTRACTED SPECIES:
Northern Parula*
339
295
300
287
249
13.53
H
O

V
Carolina Wren*
279
223
201
213
179
24.67
<.001
Tufted Titmouse*
241
185
171
181
107
54.06
<.001
Northern Cardinal*
246
127
168
140a
81
142.85
<.001
White-eyed Vireo*
241
110
144
108
107
83.42
<.001
Red-bellied
Woodpecker*
162
144
139
128
108
11.89
<.02
Ruby-crowned
Kinglet
142
98
78
77
79
30.00
<001
Summer Tanager*
86
40
42
40
36
31.23
<.001
Yellow-billed
Cuckoo*
46
24
29
24
30
9.82
<.05


Table 7continued
Reaistrations
(by
zones
. defined
in m)
Species 0-
-50 50
-100
100
-150
150-200 200-250
G-value
P
Pine Warbler*
50
18
17
22
27
24.27
<.001
Carolina Chickadee*
39
16
14
21
9
24.67
<.001
Gray Catbird
24
2
2
1
6
43.39
<001
EDGE-INDIFFERENT SPECIES:
Downy Woodpecker*
69
52
56
56
29
17.75
<.001
Yellow-throated
Vireo*
42
38
56
54
48
4.81
>.30
Great Crested
Flycatcher*
53
45
41
42
40
2.42
>.50
Pileated
Woodpecker*
28
54
40
36
35
9.26
>.05
American Robin
38
39
38
34
8
29.44
<.001
Ovenbird
20
31
51
32
17
22.75
<.001
Hermit Thrush
20
28
34
35
13
14.68
<.01
Yellow-bellied
Sapsucker
29
25
18
19
8
14.3
<.01
uj
tsj


Table 7continued
Registrations
(by
zones
. defined in m)
Species
0-50
50-100
100
-150
150-200 200
-250
G-value
P
Northern Flicker
16
25
16
12
12
6.53
>.10
Eastern Phoebe
25
12
12
15
11
8.0
>.05
Black-and-white
Warbler
11
11
12
20
8
6.53
>.10
EDGE-AVOIDING SPECIES:
Red-eyed Vireo*
161
238
239
224
199
21.66
<.001
Hooded Warbler*
30
129
155
139
132
110.47
<.001
Acadian Flycatcher* 12.
65
55
67
48
51.60
<.001
Wood Thrush*
5
5
15
9
18
13.49
<.01
* Breeding in
study
area
a Either the
127-140
or the
168
-140
combination
is
uniform (non-
significant G-value) with other values removed.
U>
u>


A. Breeding Seasons, 1985 and 1986, East-Facing Edge Plots
FIG. 2. Distribution of bird registrations with distance from edge. (A) East
facing edge plots, breeding seasons; (B) East-facing edge plots, fall; (C) East
facing edge plots, winter; (D) Non-east facing edge plots, breeding seasons;
(E) Non-east facing edge plots, fall; (F) Non-east facing edge plots, winter.
CO
4^


B. Fall 1985, East-Facing Edge Plots
Distance from Edge (m)
FIG. 2 -- continued
u>
Ui
cm ro


C. Winter 1986, East-Facing Edges
FIG. 2 -- continued
U>


D. Breeding Seasons, 1985 and 1986,
Non-East-Facing Edge Plots
FIG. 2
y = 80.06 0.07 (x)
u>


Registrations
E. Fall 1985, Non-East-Facing Edge Plots
y = 11.63 0.01 (x)
r2 = .04 P = .14
Distance from Edge (m)
FIG. 2 -- continued
OJ
CD


F. Winter 1986, Non-East-Facing Edge Plots
FIG.
y = 7.07 0.02 (x)
U)
VO


40
10.15 (SD = 6.61) in east-facing plots and 5.15 (SD = 4.21)
in non-east facing plots. The difference in means was
significant (t = 4.942, P < .001), indicating that birds used
east-facing edge plots more than they used non-east facing
edge plots in winter.
Sunlight (and presumably a warmer microclimate for birds
and their insect prey) apparently attracted birds to east
facing edges in winter. Of 36 "edge-mornings" (each of the 6
east-facing edge plots was censused 6 times in winter), 16
were sunny and 20 were not. The mean number of registrations
in the first distance zone (0-50 m from edge) was 3 times
higher on sunny mornings (x = 9.94, SD = 5.20) than on
non-sunny mornings (x = 3.60, SD = 2.42), a significant
difference (t = 4.851, P c.001).
All of the edge-types sampled in this study were abrupt
edges between mesic hammock and relatively open habitat. Of
the 2 natural edge-types sampled, however, the marsh edge
(MAI and MA2) had higher structural contrast with hammock
than did the sandhill edge (SA1 and SA2). Each of these
edge-types was represented by 1 east-facing and 1 non-east
facing plot. In the breeding seasons, the slopes for high-
contrast marsh edges and moderate-contrast sandhill edges
were significantly different, the former being positive and
the latter negative (Fig. 3; F = 13.463, P = .001). Neither
slopes nor intercepts were different between these 2 edge-
types in fall or winter (P > .05).


A. Breeding Seasons, 1985 and 1986,
High-Contrast Marsh-Hammock Edges
FIG. 3. Bird responses to edge in the breeding seasons for (A) High-contrast
marsh-hammock edges; and (B) Moderate-contrast sandhill-hammock edges.


Registrations
B. Breeding Seasons, 1985 and 1986,
Moderate-Contrast Sandhill-Hammock Edges
y = 59.48 + 0.10 (x)
FIG. 3 -- continued
NJ


43
Bird Densities in Edge versus Interior Plots
Birds generally were attracted to edge within edge
plots, although seasonal trends and variation among species
and edge-types were evident. Edge effect was not apparent,
however, when bird densities were compared between edge and
interior plots (> 700 m from edge). Mean densities in
subplots of edge and interior plots were almost identical in
the seasons when all plots were censused (Table 8).
Variation in density was greater among subplots of edge plots
than among subplots of interior plots. Thus, edge affected
the distribution of bird activity within plots (and within
territories) that abutted edge; between plots, there was no
apparent attraction of birds to parts of the forest near edge
as opposed to deep in the interior.
Internal Patchiness and Its Relation to Bird
Densities and Edge Effects
Internal patchiness supplemented distance from edge as a
predictor of bird density in edge plots, but was a more
important predictor in interior plots. Correlations of bird
density with distance and with habitat variables varied among
plots and seasons in strength and, in a few cases, direction
(Table 9). Distance from edge (DIST), variation in distance
to nearest shrub (VS), shrub density (DENS), canopy openness
(OPEN), shrub species diversity (HS), and proportion of plot
area in gaps and bayheads (GAPBAY) were the variables with
the largest numbers of significant correlations with bird


44
TABLE 8. Number of bird registrations in 0.5-ha subplots of
5.0-ha edge and interior plots during the seasons when all
plots were censused, San Felasco Hammock, Florida, 1986.
N is the number of subplots in each group (edge and
interior plots).
Seasons/Reaistrations Edae
Interior
z
P
Winter 1986
N
120
30
Range
0-30
2-15
X
7.65
7.10
. 65
. 52*
SD
6.06
3.47
Spring 1986
N
120
30
Range
3-62
11 46
X
25.33
25.00
. 18
.86
SD
9.84
9.04
TOTAL
N
120
30
Range
7-69
17 61
X
32.98
32.10
. 37
.71
SD
12.88
11.20
* P-value
is for 2-tailed z
-test. Group
variances
were
homogeneous
for Spring 1986 and TOTAL, as
determined
by
Bartlett's test, but not for
Winter 1986.


45
TABLE 9. Significant correlations of bird registrations in
subplots with distance from edge and habitat variables for
15, 5.0-ha plots in each season, San Felasco Hammock,
Florida, 1985-86. Variables that produced no significant
correlations (HPD, GA, and BAY) are omitted.
PLOT
DIST
VT
VS
PL1
F85:-.949***
TOT:-.709*
F85:.686*
PL2
PL3
S86:-.859**
S86:.703*
PL4
S85:.724*
S86:.721*
TOT:.765*
MAI
S85:-.667*
S86:-.728*
TOT:-.721*
MA2
W86:-.858**
S86:-.634*
TOT:-.794**
SA1
F85:-.786**
SA2
W86:-.655*
PP1
F85:-.840**
TOT:-.716*
F85:.740*
S86:.763*
TOT:.657*
PP2
W86:-.817 **
0F1 S85:-.774**
0F2 S85:-.816**
TOT:-.734*
VTS
IF1
W86:.746*
TOT:.741*
IF2
IF3
S86:.759*
TOT:.729*


46
TABLE
9continued
PLOT
DENS VSD OPEN VCO
PL1
PL2
F85:-.695*
W86:-.695*
PL3
S85:.828** S85:-862 S86:-.636*
TOT:.828** TOT:-.715
PL4
MAI
W86:.696*
TOT:.654*
MA2
W86:.857**
SA1
F85:.644*
SA2
S85:.740*
PP1
S86:.676*
PP2
S85:.698* S85:-.709* S86:.730*
TOT:.681*
0F1
OF2
W86:.661*
IF1
W86:.765*
S86:.798**
TOT:.893***
IF2
IF3
W86:.742*
S86:.674*
TOT:.670*
IF3


47
TABLE 9continued
PLOT HT
HS
GB
PL1
PL2
PL3 S85:-.878** F85:.768*
PL4 S85:.952**
TOT:.819*
MAI
MA2
SA1
SA2 S85:.706*
S86:.880**
TOT:.751*
PP1
PP2 S85:-.861**
TOT:-.796**
OF1
OF2
IF1 S86:-.719*
TOT:-.704*
IF2 W86:.915*
W86:-.721
TOT:-.728
IF3
W86
655


48
TABLE
9continued
PLOT
GAB
GAPBAY
PL1
PL2
PL3
F85:.768*
F85:.768*
PL4
S85:.959***
S85:.959***
TOT:.819**
TOT:.819**
MAI
MA2
SA1
SA2
PP1
S86:.972***
S86:.972***
PP2
S85:.823**
OF1
OF2
IF1
S86:.850**
IF2
IF3
TOT:.947***
* P < .05
** P< .01
*** P < .001


49
registration density. Multiple regression models explained
5-71% of the variation in bird density within edge plots,
interior plots, and all plots combined (Table 10).
GAPBAY, the proportion of subplot area in gaps/bayheads,
was the single most important variable in multiple
regressions, although other variables were more important in
some seasons; DIST and HS were the most important variables
in subplots that lacked gaps or bayheads (-G). For those
subplots that contained gaps and/or bayheads (+G), GAPBAY
explained 14% of the variation in bird density in winter and
spring 1986 in all plots combined (Fig. 4). Bird density in
gap/bayhead subplots was significantly higher than in
subplots without gaps/bayheads in spring (P <.001), and in
winter and spring combined (P <.001), but did not differ in
winter (P = .26) (Table 11). Gap area alone (GAB) was nearly
as good a predictor of bird density in all cases, but does
not appear in the optimal equations (Table 10) because it was
highly correlated with GAPBAY (e.g., r = .88, P <.001 for all
plots combined); in fact, GAB is equivalent to GAPBAY in all
but the 2 plots (PP2 and IF1) that contained bayheads.
Bayheads, however, were major attractors of birds in these 2
plots.
Distance from edge (DIST) was the most important
variable in fall and winter in the 12 edge plots, and in the
breeding seasons in subplots of edge plots that lacked
gaps/bayheads (Table 10). All correlations with DIST were


TABLE 10. Optimal multiple regression models relating bird density in
0.5-ha subplots to distance and habitat variables. Results are
presented separately for the 12, 5.0-ha edge plots, the 3, 5.0-ha
interior plots, and all 15 plots combined. Variables are listed in
equations from most to least important for the breeding seasons (S85
and S86 combined), fall (F85) and winter (W86). In each season, best
models are given for all subplots, for subplots with gap/bayheads
(+G), and for subplots without gap/bayheads (-G). The 2 variables
explaining most of the resiuual variation in each case are also
listed with their Pearson correlations (r) with residuals (+ or -)
and statistical significance.
. 2
Plots/Seasons Equation R P residual
EDGE PLOTS
S85-S86
all:
114.24 + 2.38(GAPBAY)
- .09(DIST) 26.98(HS)
.29
<.001
-VT
+DENS
+G:
280.14 + 11.801(GAPBAY)
- .09(DIST) 38.96(VT)
.30
<.001
-HS
-VCO
-G:
73.56 .12(DIST)
. 18
. 006
+VSD**
+VS
F85
all:
12.41 .02(DIST)
. 07
.003
+VS
+OPEN
+G:
12.57 .02(DIST)
. 05
. 045
+VS
+0PEN
-G:
12.03 .02(DIST)
. 14
. 015
+VSD
-HS
Ln
o


Table 10continued
Plots/Seasons Equation
W86
all:
18.96 .03(DIST)
- 9.08(HS)
+G:
11.41 .03(DIST)
-G:
25.90 16.98(HS)
- .04(DIST)
INTERIOR PLOTS
TOTAL (W86-S86)
all:
+G:
-G:
72.52 + 1.51(GAPBAY)
- 32.15(HS)
219.59 + 8.43(GAPBAY)
- 38.11(VS)
60.19 34.53(HS)
W86
all:
+G:
-G:
18.09 + .38(GAPBAY)
-8.97(HS)
35.90 + 3.22(GAPBAY)
- 20.50(HT)
14.71 9.22(HS)
P residual
20
<.001
+VTS
+VT
12
. 002
+VTS
+GAPBAY
33
<.001
-VS
-DENS
49
<.001
-VS
+VT
67
. 004
+VSD
-HS
56
. 001
+VCO
-HS
35
.003
+OPEN
+VT
71
.002
-VCO
+VT
24
.048
+VS
+OPEN


Table 10continued
Plots/Seasons Equation
S86
all:
54.43 + 1.13(GAPBAY)
- 23.18(HS)
+G:
172.84 + 5.94(GAPBAY)
- 30.55(VS)
-G:
45.47 25.31(HS)
ALL PLOTS
TOTAL (W86
all:
-S86)
51.18 + 1.13(GAPBAY)
- 14.30(HS)
+G:
51.68 + 5.32(GAPBAY)
-G:
50.95 26.22(HS)
W86
all:
14.92 8.87(HS)
+G:
11.97 + 1.35(GAPBAY)
-G:
20.13 15.21(HS)
P
residual
41 .001 -VS
+VSD
55 .018 +VSD*
-VCO
41 .006 +VC0*
-VT
16
<.001
+VSD
+VCO
14
<.001
+VSD
-HT
16
.002
+VC0**
+VSD
07
.002
+VT
+VTS
05
.037
-VSD
+VTS
18
.001
+OPEN
-DENS


Table 10continued
Plots/Seasons
Equation
p2
P
residual
S86
all:
31.39
+
1.07(GAPBAY)
. 15
<001
+VSD
+VCO
+G:
39.71
+
3.97(GAPBAY)
. 14
<001
+VSD
-VTS
-G:
38.54
+
8.56(VCO)
. 18
. 003
-HS
+ 6.
56(VSD)
+DENS
* P < .05
** P < .01
*** P < .001
Ln
u>


FIG. 4. Bird response to gaps and bayheads in winter and spring 1986 in 15,
5.0-ha plots. GAPBAY is In of proportion of subplot area in gaps and bayheads
combined. These data are derived from 91 (61%) of 150 total subplots (i.e.,
those with gaps or bayheads 78.5 m^ or larger).
Ln


55
TABLE 11. Number of bird registrations in subplots with
(+G) and without (-G) area in gaps/bayheads for the 15,
5.0-ha plots, winter and spring 1986, San Felasco Hammock,
Florida. N is the number of subplots in each group. P-
value is for 2-tailed z-test.
Seasons/Reaistrations
with
caps
without
craps
z
P
Winter 1986
N
91
59
Range
0-25
0-30
X
7.96
6.90
1.12
.26
SD
5.54
5.76
Spring 1986
N
91
59
Range
6-62
3-39
X
27.88
21.24
4.52
<.001
SD
9.73
8.09
TOTAL
N
91
59
Range
11 69
7-55
X
35.84
28.14
4.01
<.001
SD
12.85
10.52


56
negative, indicating a positive edge effect. DIST was not
important when interior plots (calculated as DIST = 700 m for
all subplots) were considered with edge plots. HS was more
important than DIST or GAPBAY in winter for subplots lacking
gaps/bayheads, and was a significant variable in interior
plots and in all plots combined. HS was negatively related
to bird density, probably because the dense shrub-level
vegetation that was used heavily by birds often was dominated
by just 1 or 2 woody species.
Regression analyses revealed that subplots without gaps
or bayheads (Fig. 5A) exhibited a stronger edge effect than
those with gaps/bayheads (Fig. 5B), in the breeding seasons.
The slopes of these 2 regressions did not differ (F = 1.241,
P = .268), but their intercepts did (ANCOVA, F = 18.381, P
< .001). The same was true when subplots with and without
gaps alone were compared, but the intercepts differed less
than in the comparison with bayheads included (ANCOVA, F =
10.527, P = .002). There were no differences in slope or
intercept in either case in fall or winter (ANCOVA, P > .25).
Patterns at the Between-Plot Scale
Relationships between bird density and habitat
heterogeneity at a between-plot observation scale (Table 12)
were different from those determined at a within-plot scale
and were less often significant. For spring 1985 and both


A. Without Gaps/Bayheads (-G)
FIG. 5. Influence of habitat patchiness on edge effect as shown by regression
of bird registrations with distance from edge for (A) subplots without mappable
gaps or bayheads, and (B) subplots with mappable gaps and/or bayheads. Data
are from 12, 5.0-ha edge plots in the breeding seasons of 1985 and 1986.


B.
120
100
CO
o
cn
Cl)
cn
80
60
40
20 -
Li_
0
50
FIG. 5
continued
ro ro
With Gaps/Bayheads (+G)
y = 82.20 0.06 (x)
1 I i
100 150 200
Distance from Edge (m)
I
250
Ln
oo


TABLE 12. Optimal regression models relating bird density in 5.0-ha
plots to habitat variables (i.e., between-plot scale), San Felasco
Hammock, Florida, 1985-86. Equations shown are for the 12 edge plots;
there were no significant regressions for the 3 interior plots, for
all 15 plots combined, or for the edge plots in 1986 except in the
breeding seasons (S85 and S86 combined). The 2 variables explaining
most of the residual variation in each case are also listed with
their Pearson correlations (r) with residuals (+ or -) and
statistical significance.
Seasons
Eauation
R2
P
residual
S85
1178.20 719.79(HT)
.50
. 010
+HS*
+VS
F85
57.02 + 5.94(OPEN)
.41
. 026
-HS
-SS
S85-S86
1723.49 1002.32(HT)
.42
.022
-HS
+ST
* P < .05
Ln
KD


60
springs (breeding seasons) combined, tree species diversity
(HT) explained most of the variation in bird density among
plots, the relationship being inverse. In fall, a positive
relationship with canopy openness (OPEN) was most important.
Gap and bayhead area (GAPBAY) and other variables indicating
patchiness were not important at the between-plot scale
(except, as noted above, breeding species richness was
significantly associated with variation in shrub density,
VSD) .
Responses of Individual Species to Habitat Heterogeneity
Responses of the 12 most abundant bird species to
distance and habitat variables revealed that, for most
species, density was associated significantly with habitat
patchiness (Table 13). Edge effects observed within edge
plots (Table 7) for many species were swamped by high
abundances in interior plots >700 m from edge; distance from
edge was an important variable for only the Red-bellied
Woodpecker (which was attracted to edge) and Hooded Warbler
(which avoided edge) when all 15 plots were considered (Table
13) .
Gap and/or gap/bayhead area (GB, GAB, or GAPBAY) showed
significant correlations with density for 5 species (Northern
Parula, Carolina Wren, White-eyed Vireo, Hooded Warbler, and
Downy Woodpecker). Variations in spacing of trees and/or
shrubs (VT, VS, or VTS) correlated positively with density


61
TABLE 13. Responses of individual species to edge and
habitat heterogeneity, as indicated by significant
correlations for the 12 most abundant bird species in
the 12 edge and 3 interior 5.0-ha plots combined, San
Felasco Hammock, Florida, 1986.
Species
Variable
r
Northern Parula
GAPBAY
. 199*
Red-eyed Vireo
OPEN
-.233**
Carolina Wren
VTS
.296***
VT
.212**
GAB
.257*
OPEN
.208*
GAPBAY
. 188*
Tufted Titmouse
(none significant)
Northern Cardinal
(none significant)
White-eyed Vireo
GAPBAY
. 377***
VTS
.308***
GAB
.350**
GB
. 344**
DENS
.247**
VT
.215**
HS
-.162*
Red-bellied Woodpecker
OPEN
. 386***
VS
.255**
VT
.235**
DIST
-.247**
VTS
.184*
VCO
. 171*
HT
-.170*
Hooded Warbler
GAPBAY
.370***
GB
.321**
GAB
.284**
DENS
.265**
HS
-.232**
VTS
.217**
DIST
. 192*
Ruby-crowned Kinglet
HT
-.270**
HS
-.192*
Downy Woodpecker
GB
.359**


62
TABLE 13continued
Species
Variable r
Acadian Flycatcher
(none significant)
Summer Tanager
(none significant)
* P < .05
** P < .01
*** P < .001


63
for 4 species (Carolina Wren, White-eyed Vireo, Red-bellied
Woodpecker, and Hooded Warbler). Density of 4 species
(White-eyed Vireo, Red-bellied Woodpecker, and Ruby-crowned
Kinglet) was related negatively to diversity of trees and/or
shrubs (HT, HS). Two species (Carolina Wren and Red-bellied
Woodpecker) were positively associated with an open canopy
(OPEN), whereas the Red-eyed Vireo was negatively associated
with OPEN. Two species (White-eyed Vireo and Hooded Warbler)
were positively associated with shrub density (DENS), and 1
(Red-bellied Woodpecker) with variation in canopy openness
(VCO). Finally, 4 species (Tufted Titmouse, Northern
Cardinal, Acadian Flycatcher, and Summer Tanager) showed no
significant correlations with any of the variables.


DISCUSSION
Bird Responses to Forest Edge and Internal
Patchiness; A Matter of Scale?
A major objective of this study was to assess the
simultaneous and interacting effects of edge and internal
patchiness on bird habitat-use. Both forest edges and
internal patchiness (especially in the form of gaps and
bayheads) attracted high densities of birds within 5.0-ha
plots. Edge effect during the breeding season was
significantly stronger in 0.5-ha subplots lacking gaps or
bayheads than in patchy subplots. Forest edges, particularly
in fall and winter, appeared to "distract" birds from gaps
and bayheads; i.e., birds were attracted more strongly to
gaps and bayheads in interior plots (> 700 m from edge) than
in edge plots. In interior plots, patchiness was the best
predictor of bird density in all seasons, and was especially
important during the breeding season, when nesting, foraging,
and territorial display for many species were concentrated in
gaps and bayheads.
Attraction to edge was strongest seasonally in winter,
whereas attraction to gaps and bayheads was strongest during
the breeding season. East-facing and high-contrast edges
attracted higher densities of birds than did edges that faced
64


65
other directions or exhibited less structural contrast
between adjoining habitats. Of 27 bird species analyzed, 12
were attracted to edge, 11 were apparently indifferent, and 4
avoided edge. A common null hypothesis in edge-effect
studies is that animal densities at different distances from
edge are equivalent. In this study, bird densities across
distance zones were rarely uniform, and a clear edge effect
(concentration of registrations 0-50 m from edge) occurred in
6 of 12 edge plots, for all seasons combined.
Despite indications of attraction to edge within edge
plots, edge and interior 5.0-ha plots had equivalent
densities of birds and equivalent breeding species richness.
The lack of any difference in density between edge and
interior plots may be a consequence of habitat selection
mechanisms differing at different spatial scales (see below),
or may be related to the lower densities observed in the most
distal (200-250 m) zone of edge plots. Although sampling
problems cannot be ruled out, attraction to edge may produce
a "vacuum effect," where animal activity or density is
depressed at an intermediate distance from edge compared to
deeper forest (Bider 1968).
Similarly, although birds were attracted to gaps and
bayheads within plots, between-plot comparisons indicated
that bird density did not differ between patchy plots and
more homogeneous plots. Breeding species richness, however,
was positively associated with one indicator of habitat


patchiness at a between-plot scale, the coefficient of
variation of shrub density.
The empirical generalization that birds are abundant
near openings, discussed in the ornithological literature
since Lay (1938), was supported by this study. But this
simplistic interpretation is incomplete because it derives
from only one scale of resolution. Habitat associations of
birds differ depending on the scale at which they are
examined (Gutzwiller and Anderson 1987, Wiens et al. 1987).
The edge effect and the "patch effect" may be scale-
dependent in 2 ways: (1) birds respond to different sets of
habitat cues when selecting forests in which to settle, when
establishing territories or home ranges within forests, and
when selecting nesting, foraging, singing, and roosting sites
within territories and home ranges (Hutto 1985, Wiens 1985);
and (2) different human observation scales lead to detection
of different patterns (Allen and Starr 1982, O'Neill et al.
1986, Wiens et al. 1987).
Edge Relations
Beginning with Shelford (1913, 1927), who described an
abundance of animals at the forest margin, and Leopold
(1933), who advanced the idea that "game is a phenomenon of
edges," the attraction of wildlife to openings has been one
of the best-studied phenomena of habitat selection. Numerous
studies since Lay (1938) have documented higher bird species


67
richness near forest edge (Johnston 1947, Johnston and Odum
1956) and/or increased densities of birds near edge (Beecher
1942, Good and Dambach 1943, Johnston 1970, Gates and Gysel
1978). Although documentation of edge effects has been
ample, a lack of standardized methodologies and definitions
has produced some confusion. Sometimes the area of habitat
in various distance zones varies widely and is not specified?
hence, density-distance correlations can be spurious and edge
"effects" are really artifacts (Nelson et al. 1960, Harris
and McElveen 1981).
Much of the confusion in the edge literature reflects
the many ways in which edge, edge species, and edge effects
have been defined. Some studies of edge effects on birds
(e.g., Kendeigh 1944, Johnston 1947, Whitcomb et al. 1981)
have used qualitative criteria to classify species according
to their edge affinities. Typically, bird registrations are
mapped, territory boundaries are defined, and species are
classified as "forest-edge" if territories are concentrated
along forest margins, as "forest-interior" if territories are
located primarily inside forest, or sometimes as "interior-
edge" if territories are found both in edge and interior
habitat.
Other studies have used quantitative criteria to
determine the edge-interior affinities of birds. Galli et
al. (1976) defined edge width according to structural
characteristics of vegetation determined in a different study


68
nearby (Wales 1972). Gates and Mosher (1981) took a
"functional approach" to estimating edge width, based on
dispersion of nests of bird species associated with edge
habitat. Kroodsma (1982, 1984) mapped territories along an
edge-interior transect, and defined edge species as those
with highest densities (fractions of territories) within 60 m
of edge and/or a significant negative slope of density
against distance from edge. Strelke and Dickson (1980) and
Helle and Helle (1982) used densities of registrations within
arbitrary distance zones to determine strength of edge effect
and to classify species by edge affinities. My study was
modeled in part after those of Kroodsma (1982, 1984), Strelke
and Dickson (1980), and Helle and Helle (1982). Because edge
effects were tested among a series of replicated, well-
dispersed plots, statistical inferences could be made that
were inappropriate in previous studies.
Researchers in the eastern deciduous forest region have
often described a characteristic forest-edge avifauna (e.g.,
Kendeigh 1944, Johnston 1947, Johnston and Odum 1956, Forman
et al. 1976, Whitcomb et al. 1981). In contrast, this study
at the southern extreme of the deciduous forest biome (Braun
1950) revealed few distinct forest-edge birds. Five breeding
species, the Brown Thrasher, Common Yellowthroat, Blue
Grosbeak, Indigo Bunting, and Brown-headed Cowbird, were
confined to edges but were uncommon in the study area and
were not analyzed. The Rufous-sided Towhee, considered an


69
edge species in the northern studies mentioned above,
inhabits deciduous forest edges in Florida, but is more
abundant as a breeding species in pine flatwoods and
plantations (Repenning and Labisky 1985). Other breeding
species classified as forest-edge birds in many northern
studies, such as the Yellow-billed Cuckoo, White-eyed Vireo,
and Northern Cardinal, were found in San Felasco in all
distance zones but most abundantly near edge. In forest
interior, these latter species concentrated their activity in
gaps, bayheads, and other patches of dense shrub growth. The
Gray Catbird, a typical edge species that wintered at San
Felasco, was found at all distance zones but was strongly
associated with edge. Thus, almost all of the bird species
analyzed in this study used both forest interior and edge
habitat, although species differed in degree of attraction
to, or avoidance of, edge. Several species generally
associated with edge also inhabited the interior of San
Felasco Hammock, apparently due to its patchiness. This
observation leads to a question, as yet unanswered by any
study at what point does forest "interior" become so
patchy that it is no longer interior?
Qualitative aspects of edges may influence faunal
distribution (Harris and Smith 1978, Harris 1980, 1984,
Harris and McElveen 1981). Exposure and contrast are
potentially important qualities of edge in terms of bird
attraction. At San Felasco, a greater positive edge effect


70
was observed in high-contrast hammock-marsh edge plots than
in moderate-contrast hammock-sandhill edge plots during the
breeding seasons. This finding agrees with previous
conclusions that the magnitude of edge effect increases with
greater structural contrast between abutting communities
(Thomas et al. 1979, Harris and McElveen 1981, Harris 1984).
This study also documented a greater attraction of birds
to east-facing edges in winter, as compared to edges that
faced other directions. Densities of birds on east-facing
edges were significantly higher when morning sunlight was
striking the edge, suggesting thermoregulatory behavior, or
more likely, a response to increased insect activity. In
contrast, Helle and Helle (1982) found a peak in bird density
50-100 m from forest edge on Finnish islands and suggested
that avoidance of climatic extremes may keep many birds
(especially tropical migrants) away from edge in colder
climates. Carpenter (1935) found higher bird densities on
edges on the "lee" side of Illinois forests, sheltered from
prevailing winds; density differences between windward and
leeward edges were more pronounced in winter and early spring
than in late spring. In north-central Florida, winds are
multi-directional during the day but generally northerly at
night (Dohrenwend 1978), so wind should not produce
consistent differences in diurnal use of edges. Hence,
climatological effects of edge appear to influence bird


71
activity in many regions, but differ according to regional
and local environmental conditions.
Patchiness Relations
The edge effect, as it is usually understood, is a
response of animals to major habitat interfaces
(macroheterogeneity). Internal forest dynamics, however,
produce openings that are structurally similar to forest
edge, and might be considered forest edge at a finer scale.
In this study, the proportion of subplot area in gaps (plus
limited bayheads) was the best predictor of bird density at a
within-plot scale of analysis. The simple measure of
gap/bayhead area was more important than various
heterogeneity indices or the floristic diversity of trees and
shrubs. When data from interior plots were combined with
those from edge plots, the proportion of area in
gaps/bayheads was a far better predictor of bird density in
subplots than was distance from edge. This conclusion
applied to most individual species and to all species
combined. For the 12 edge plots, edge effect in relatively
homogeneous subplots during the breeding seasons was
significantly stronger than in subplots containing gaps
and/or bayheads. These results suggest that openings (and
other shrubby areas) of all sizes are attractive to birds,
but that the relative attractiveness of major edges and


72
smaller, internal patches depends on the range of distances
from edge and degrees of patchiness sampled.
The attraction of birds to gaps is just one indication
of the ecological significance of these patches. Gap
dynamics are an important regeneration and diversifying
phenomenon in many types of forest (Bray 1956, Williamson
1975, Hartshorn 1978, White 1979, Runkle 1981, 1982, 1985,
Brokaw 1985). In southern hardwood forests (mesic hammocks),
a number of co-dominant tree species coexist, apparently as
non-equilibrium populations, and respond independently to
disturbances that produce gaps in the canopy (Platt and
Herman 1986, Platt and Schwarz, in press). Rates of gap
formation by treefall and canopy degeneration have not been
measured in these forests, but might be expected to fall
within 0.5-2.0% per year, a rate described for mixed
mesophytic forests and many other forest types (Runkle
1985).
In San Felasco Hammock, sinkhole formation supplements
wind and tree death as a source of canopy gaps. Several
recent or enlarging sinkholes have resulted in treefalls and
shrub-level enhancement similar to that associated with
windthrows. Deep sinkholes are usually water-filled (at
least seasonally); the largest sinkholes form persistent
ponds with fringing marshes and/or shrub swamps. The largest
sinkhole in San Felasco Hammock covers 9.6 ha? the largest
gap occurring within the study plots was a 3208 m2 sinkhole


73
gap. The mean gap area (3.4%) on study plots was within the
range recorded by Runkle (1982) in 15 old-growth mesic
forests in the eastern United States. Although our gap
definitions differed (see Runkle 1982), gap area in San
Felasco Hammock appears to be typical of old-growth forests
in the eastern United States.
Unlike larger habitat discontinuities (edges), natural
gaps and other aspects of habitat patchiness were not studied
by many wildlife biologists or ornithologists until recently.
Kendeigh (1944) noted that forest interiors were sometimes
"infiltrated" by forest-edge species such as the Northern
Cardinal and Rufous-sided Towhee. These species, he wrote,
may occur "where openings or thickets have been naturally
made by trees being blown over or by other disturbance.
However, such openings are 'wounds' in the community
structure, and since they occur to such a varying extent in
different sample plots, it seems best to eliminate them
altogether" (Kendeigh 1944:96).
Recent studies have considered gaps in a more favorable
light. Birds may respond to gaps because they provide cues
indicating a concentrated food supply (cf. Hilden 1965). In
Panama, Schemske and Brokaw (1981) found more bird species in
gaps than in undisturbed forest understory, and considered
several species "treefall specialists." In Costa Rican cloud
forest, flowering and fruit production are concentrated in
treefall gaps (Linhart et al. 1987). In Illinois, Blake and


74
Hoppes (1986) and Martin and Karr (1986) captured more
migratory frugivores (in fall), granivore-omnivores, and
certain (especially foliage-gleaning) insectivores in gaps
than in non-gap areas of forest understory. Bird abundance
in gaps was correlated with greater food abundance,
particularly fruits and foliage. Many insects favor plants
growing in sunlight over those growing in shade, and
lepidopteran larvae may attack plants in gaps preferentially
(Wolda and Foster 1978, White 1984, Harrison 1987).
In this study, association of birds with gaps and
bayheads was strongest during the breeding seasons. Although
birds may concentrate in gaps because they are richer in
food, nest-site selection may be just as important (Morse
1985, Martin 1988). Dense shrub-level foliage within gaps
provides abundant nesting substrates for birds that nest in
this stratum; concealing cover around nests also offers
protection from nest predators (Chasko and Gates 1982). Ten
of 18 breeding bird species that were analyzed in this study
are primarily shrub-level (below 5 m) nesters, and all but 1
(Pileated Woodpecker) of the remaining species nest at either
shrub or tree level (Appendix II, Harrison 1975).
Van Horne (1983) cautioned that animal density may be a
misleading indicator of habitat quality. If surplus,
socially-subordinate individuals (e.g., young, inexperienced
birds, many of which may be non-breeders or "floaters")
collect in habitat sinks, lower-quality habitat may actually


75
contain a higher density of individuals. Fretwell and Lucas
(1969) predicted that individuals select patches of highest
guality first, but that as population increases, a threshold
is reached where individual fitness is maximized by selecting
lower-guality but unoccupied habitat. Without long-term,
intensive studies in gap versus non-gap sites that measure
differences in habitat occupancy and fitness over a range of
population densities, the importance of gaps to birds remains
inferential. Life history information (for most of the bird
species here), high resource levels in gaps, and attraction
of birds to gaps within plots warrant the prediction that
patchy plots will be preferred by birds until increasing
population density makes less patchy plots more advantageous
in terms of fitness.
Management Implications
Reviews of diversity concepts in wildlife management and
conservation (Samson and Knopf 1982, Noss 1983) indicate that
maximization of local habitat diversity and edge effect has
been a guiding principle. This management emphasis appears
perfectly consistent with what ecology tells us about the
dependence of organisms on disturbance, successional patches,
and habitat mosaics, and the inferred relationship between
diversity and stability (Pickett and Thompson 1978, Hansson
1979, Gilbert 1980, Karr and Freemark 1983, Pickett and White
1985, Forman and Godron 1986) But what is beneficial at a


76
local scale and for edge-adapted organisms, such as many game
species, may be deleterious at larger spatial scales and for
sensitive organisms (Faaborg 1980, Samson and Knopf 1982,
Noss 1983, Wilcove et al. 1986). Furthermore, natural
disturbances and anthropogenic disturbances may have
gualitatively different effects on wildlife, a problem that
awaits detailed study.
One common method of enhancing horizontal habitat
diversity is through the construction of "wildlife openings."
Lay (1938:256) was one of the first to advocate "the
provision of clearings with extensive margins" for songbirds.
Because the edge effect he noted was confined to the first
100 m from an opening, and because the interiors of large
clearings were depleted of wildlife, Lay recommended small
but numerous clearings. Leopold (1938:3) made similar
recommendations with regard to deer, songbirds, and
wildflowers: "The smaller and more frequent the selective
cuttings, the greater the benefit to wildlife." In practice,
wildlife openings usually have been constructed for the
benefit of game rather than nongame species. Stoddard (1936)
recommended the maintenance of existing openings and
construction of new openings in heavily forested lands for
the benefit of Wild Turkey, whose poults forage in clearings.
Provision of forest openings for turkey, quail, grouse, deer,
and other game animals quickly became a dominant feature of


77
wildlife management on public lands (Larson 1967, McCaffery
and Creed 1969, Healey and Nenno 1983).
The optimum size of maintained openings for different
species has been debated (Patrie 1966, McCaffery and Creed
1969, Segelquist and Rogers 1975). Because little research
has been conducted on optimum sizes of openings for nongame
birds, Taylor and Taylor (1979) recommended that a variety of
opening sizes be maintained. Recent research in Illinois
(Overcash and Roseberry 1987) determined that 0.1-0.2-ha
openings in mature deciduous forest were not large enough to
increase bird counts (species or individuals); edge effects
began with openings 0.3 ha in size. Brown-headed Cowbirds,
an indicator of deleterious edge effect (Brittingham and
Temple 1983), also appeared at this size, but were more
abundant in larger openings of 0.7-1.0 ha (Overcash and
Roseberry 1987). In Wisconsin, passerine nests within 35 m
of 0.01-0.2-ha openings were parasitized by cowbirds more
frequently than were nests further away, but the difference
was not significant; parasitism rates declined significantly
with distance from openings > 0.2 ha (Brittingham and Temple
1983) .
In San Felasco Hammock, most bird species were
distributed throughout plots across the full range of opening
(gap) sizes, and bird densities were generally enhanced at
all gap sizes except for the very largest (a 0.32-ha
sinkhole-marsh opening), where densities were depressed.


78
There was no evidence of deleterious edge effects (e.g.,
cowbird parasitism or increased predation on artificial
nests) in or near even the largest gaps (Noss, in
preparation). Cowbirds presently are uncommon breeders in
this region, however, and only one successful parasitism (a
Red-eyed Vireo feeding cowbird young, B. Muschlitz, personal
communication) has been documented in the study area. More
research is needed to determine the size of opening at which
edge effects begin to occur, and the qualitative differences
in edge effects associated with natural versus artificial
openings.
Construction of openings in heavily stocked conifer
plantations and other close-canopied, even-aged forests may
be beneficial to nongame birds and other wildlife. In such
cases, small openings may simulate treefall gaps, which
because of young stand age are not occurring naturally, and
provide the herbaceous and shrub growth otherwise lacking in
the forest. If, however, the landscape is already heavily
fragmented with abundant clearcuts, other open areas, and
roadsall of which increase edgeconstructing additional
openings could be counter-productive. Construction of large
openings may intensify deleterious edge effects on forest
interior species by further fragmenting the forest landscape
and favoring opportunistic, weedy species over species more
in need of protection (Robbins 1979, Noss 1983, Wilcove et
al. 1986). For guidance on management, a general rule is to


79
look to the regional landscape for context and to the needs
of the most sensitive species for specific direction (Noss
1983, 1987b, Harris 1984, Noss and Harris 1986).
The results of this study, which document attraction of
birds to edge and openings within plots, should not be
interpreted as supporting construction of artificial openings
or edge in natural forests. Artificially maintained openings
may differ from natural gaps in species composition and other
ecological properties (Denslow 1985). The structural
heterogeneity of San Felasco Hammock is due primarily to
natural processes. Natural gaps and bayheads were important
features of site heterogeneity and attracted high densities
of birds within plots. Because gaps provide concentrated
resources (food and nesting cover) for birds, management
strategies that maintain natural levels of horizontal
patchiness would be prudent.
Old-growth forests are naturally patchy, uneven-aged
systems that fractionate through natural disturbance into a
mosaic of developmental stages (Bormann and Likens 1979,
Oliver 1981, Whitney 1987); hence, they provide the
heterogeneity required by native species at no cost to
managers. Despite early impressions that old-growth forests
were wildlife-poor, contemporary wildlife ecologists
recognize the richness of this system (Meslow et al. 1981,
Schoen et al. 1981, Harris 1984). Because birds may respond
less to edge in patchy areas of forest than in more


80
homogeneous sites (this study), maturation of forests to old-
growth potentially could ameliorate deleterious edge effects
associated with fragmentation, i.e., edge could become less
of an "ecological trap" (sensu Gates and Gysel 1978).
Exceptions to the rule of maintaining unmanipulated stands of
maturing forest would occur when sites are too small to
incorporate the natural disturbance regime and maintain
habitat diversity (Pickett and Thompson 1978, White and
Bratton 1980, Shugart and West 1981, Noss 1987a, Urban et al.
1987) or if the needs of particular endangered species
dependent on successional habitat take precedence over
community-level management.
A Final Comment on Scale and Observation
Birds appear to evaluate habitat suitability at several
spatial scales (Ambuel and Temple 1983, Hutto 1985, Sherry
and Holmes 1985). Hence, there may be no fundamental scale
at which to assess bird-habitat relationships; the
appropriate scale for research depends on the specific
questions being asked. Conclusions are most meaningful when
they derive from several observational scales (Allen and
Starr 1982, Maurer 1985, Wiens 1985, 1986, O'Neill et al.
1986, Wiens et al. 1987).
Attraction of birds to edge and habitat patchiness at a
within-plot, but not at a between-plot, scale in this study
does not preclude reappearance of the relationship at a still


81
higher (e.g., between-forest) scale. In fact, a positive
association of both bird species richness and density with
habitat heterogeneity has been demonstrated repeatedly at
landscape, regional, and biogeographic scales (Williams 1964,
Wiens 1985, Boecklen 1986, Freemark and Merriam 1986).
San Felasco Hammock is larger, more mature, and more
heterogeneous than other hammocks in the region, and has a
richer avifauna (B. Muschlitz, personal communication. Harris
and Wallace 1984, personal observation). Although birds used
the entire between-plot range of habitat heterogeneity with
equal frequency, long-term research is needed to determine if
more heterogeneous sites are selected preferentially (cf.
Fretwell and Lucas 1969, Van Horne 1983). Within plots, bird
activity was concentrated in gaps and other areas of dense
shrub-level vegetation. Edges were also attractive, possibly
because they provide selection cues similar to those of gaps
(Gates and Gysel 1978). Although many species were attracted
to both edge and internal patchiness, edge birds were not
equivalent to gap birds. Some species (e.g., Indigo Bunting)
were attracted to edge but were not found in gaps, whereas
others (e.g., Hooded Warbler) were associated with gaps but
avoided edge. These results suggest that species respond
uniquely to opening size and other habitat features.
The research reported here was correlative rather than
experimental because the site is protected as a preserve.
Therefore, mechanisms that controlled habitat selection could


82
only be inferred. Observed relationships ideally should be
tested by more rigorous experimental methods, but it is
premature to conclude that "further descriptive and
correlative studies can tell us little more that is new"
(Morse 1985:153). Although manipulations that create
different levels of heterogeneity may be useful,
observational studies spanning a breadth of spatial and
temporal observation scales can answer many questions about
habitat selection without modifying the small amount of
natural area that remains.


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