Download Demographic Costs Associated with Differences in Habitat Space

RESEARCH ARTICLE
Demographic Costs Associated with
Differences in Habitat Space Occupancy
Kelly A. Williams*, Donald B. Miles
Department of Biological Sciences, Ohio University, Athens, OH 45701, United States of America
* [email protected]
Abstract
a11111
OPEN ACCESS
Citation: Williams KA, Miles DB (2016)
Demographic Costs Associated with Differences in
Habitat Space Occupancy. PLoS ONE 11(11):
e0165472. doi:10.1371/journal.pone.0165472
Editor: Petr Heneberg, Charles University, CZECH
REPUBLIC
Received: February 29, 2016
Accepted: October 12, 2016
Published: November 16, 2016
Copyright: © 2016 Williams, Miles. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: Data are uploaded on
Dryad. The DOI is: doi:10.5061/dryad.0287v.
Funding: This work was funded by an Ohio Center
for Ecology and Evolutionary Studies Research
Fellowship, the Ohio Avian Project Initiative, the
Midwest Birding Symposium Conservation Fund,
Ohio University Graduate Student Senate Original
Work Grants, the National Fire and Fire Surrogate
Project and the Scioto Valley Bird and Nature Club.
Competing Interests: The authors have declared
that no competing interests exist.
Delimiting the habitat characteristics describing the environmental conditions required by a
species has become a critical tool for predicting organismal responses to environmental
change. Grinnell emphasized the effects of environmental factors on the ability of a population to maintain a positive growth rate, yet few studies have included demographic or reproductive data in analyses of the Grinnellian niche. Identifying differences in habitat
exploitation patterns in response to structural variation in the environment presents an
incomplete description of the ability of species to adapt to changing habitats if demographic
traits are not included. We estimated the vegetation characteristics used by individuals
within a population of hooded warblers (Setophaga citrina) across a spatial transect that
includes three structurally different forest habitats. We predicted individuals should select
similar structural characteristics within each habitat and have similar reproductive success
across sample sites. In the two years post burn, adults were present but no young fledged
indicating the habitat requirements necessary for reproduction were absent in this habitat.
We found significant differences in habitat space occupied by individuals in unaltered and
harvested habitats. Nesting habitats used by female warblers differed from available habitat. Fledging success was lower in the harvested habitat 10 to 12 years post-harvest. In the
harvested habitat, fledging success was greater on mesic slopes but decreased along a
habitat gradient to xeric ridgetops, suggesting compensation in habitat use does not ameliorate fitness costs. In contrast, there was no difference in the number of fledged young
along this gradient in the unaltered habitat. Based solely on occupancy data, traditional
ecological niche models would incorrectly conclude the environmental characteristics
found across the three forested habitats are included in the Grinnellian niche of the hooded
warbler. However, examination of demographic and environmental data simultaneously
allows differentiation between occupied habitat space and niche space.
Introduction
The distribution of species across a landscape depends on the spectrum of both biotic and abiotic factors that result in a stable or positive population growth rate [1–3]. The combination of
these factors constitute a species’ niche [1,2,4,5]. The habitat requirements that restrict a species to a geographic range where there are the necessary environmental factors for survival and
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Demographic Costs and Habitat Space Occupancy
reproduction are components of the Grinnellian niche [6,7]. These environmental factors
include ambient temperature, precipitation and habitat structure that ultimately affect the
availability and distribution of resources, which in turn determines the suitability of a habitat
for a species and delimits its range [8–11]. This niche space consists of multiple habitat axes
because different environmental characteristics may be needed for different aspects of a species’
life history [2,12]. Some habitats may contain resources along critical axes, such as for foraging,
but insufficient resources for other aspects of reproductive success, such as nesting sites, and
thus be a sink habitat [13].
A common goal of niche mapping studies is to link habitat variables with estimates of abundance, density or species richness [7,14]. Ecological niche modeling is a correlational method
for determining the environmental conditions associated with a species’ distribution or abundance [9–11]. The distributional patterns are based on broad scale occupancy and estimates of
environmental factors at the macroecological level. However, these patterns can be associated
with spatially correlated landscape features and biased due to mode of sampling [10,15]. For
example, the United States Geological Survey (USGS) North American Breeding Bird Survey
(BBS) data are collected along roads yet species habitat associations along edges may differ
from core habitats [16,17]. Therefore, edge habitats may not represent the center of the environmental space required for stable or positive population growth and instead be indicative of
suboptimal habitat occupied by floaters or individuals that cannot obtain territories in higher
quality habitat [18].
A key aspect of the Grinellian niche is that a species range coincides with those environmental conditions where population growth rate is stable or positive [4]. Despite attempts to clarify
terminology when discussing the niche [4,19,20], confusion in usage still exists. Here we make
two distinctions. First, “habitat space” includes the habitat characteristics that permit the presence of a species. This habitat space represents occupancy of the species but may include space
occupied by sink, as well as, source populations. Second, we define the Grinnellian niche as the
subset of non-consumable resources that a species occupies that are tied to estimates of fitness
which suggest the species is able to maintain stable or positive population growth. Relatively
few studies integrate demographic data in the analysis of niche variation or have elucidated the
combination of structural habitat characteristics that predict successful reproduction and survival. Including demographic data enhances the understanding of how fine-scale environmental conditions affect variation in source sink dynamics across the landscape and can help to
better differentiate between habitat space that permits occupancy and habitat space that supports source populations.
Multivariate techniques can be used to identify habitat characteristics along different axes.
Variation in the habitat characteristics used by individuals, populations or species may be evaluated using the axes describing a habitat space [12,21,22]. The habitat space used by individuals within and among populations can be compared. Thus, we can determine whether the
habitat space along different axes expands, shrinks or differs in position or shape across structurally different habitats [23]. Including data on reproductive success or survival allows the
ability to establish a connection between the habitat characteristics and source sink dynamics.
Habitat space that supports a population growth of 0 would lie within a species niche space.
Less productive and sink habitats can be identified by a difference in position in habitat space
that is also associated with a reduction in reproductive success compared to either prior conditions or another habitat.
Here, we evaluate the habitat space occupied by a population of breeding hooded warblers
(Setophaga citrina) among structurally different forest habitats. Because many forests exhibit
variation in disturbance, we chose forest sites with altered structural features in different strata
(e.g., understory and subcanopy) to determine the relationship among habitat structure and
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reproductive success. Because adult hooded warblers were observed in all three (unaltered, harvested and burned) habitats during the breeding season, we predicted that individual warblers
should track components of their Grinnellian niche across the habitat gradient.
Natural history of hooded warblers
Hooded warblers are a Neotropical migrant species that inhabit mature deciduous forests
across the Eastern United States during the breeding season. These forests are typically dominated by Quercus spp. (oak), Carya spp. (hickory), Acer spp. (maple) and Fagus spp. (beech)
and have a well-developed understory and shrub layer for nesting [24]. Despite considerable
variation in plant species composition across the breeding range, there are similarities in the
habitat structure associated with the forested habitats occupied by hooded warblers. These
structural similarities include forests with a high tree species diversity in the canopy and subcanopy and high density of stems in the shrub layer compared to more even aged forests with a
high coverage of large saplings and understory trees [25].
In many species, males and females are known to require sex-specific habitat characteristics
[26–28]. For example, when there are differences between sexes in behavior contexts such as
foraging [29]; males and females may use different cues to select habitat. Male hooded warblers
that have been captive reared preferentially orient toward vertical structure while captive
reared females orient toward oblique structure [30]. Furthermore, male and female hooded
warblers use structurally different habitat during the winter [26,31]. During the breeding season, hooded warbler males sing in the midstory and favor territories with greater vertical structure (e.g., mature forest with an open midstory) to enhance territorial defense and their ability
to attract mates. In contrast, females use habitats with increased understory structure (e.g.,
complex, oblique structure like in brier thickets) for nest concealment in the shrub layer and
do not exclusively use their social partner’s territory during the breeding season [32]. Although
nest concealment was not associated with nest survival [33], high understory coverage at the
scale of the territory may increase foraging opportunities for the female and fledged young and
decrease predation because predators have more substrate to search.
Study objectives. We quantified the habitat space of males (territory centered habitat
characteristics) and females (nest site habitat characteristics) during the breeding season in
three structurally different forest habitats within an 80–100 yr old second growth forest. One
habitat was undisturbed, a second was subjected to prescribed burns, and a third forest habitat
that was subjected to a selective harvest by mechanical thinning. We used this variation to
determine whether individuals selected similar features across sites. Moreover, we investigated
whether there were differences in habitat space use between the sexes. We hypothesize that
male and female hooded warblers should exploit different environmental characteristics within
a habitat contingent on behavioral contexts (e.g., foraging, reproduction). We predicted each
sex requires a similar habitat space along the foraging axis, but require different habitat characteristics along the territorial defense (male) and nesting (female) niche axes. We also had specific predictions for each forest habitat based on the type of disturbance. Fire results in the near
complete elimination of the shrub layer, which reduces the habitat space available for foraging
and nest placement. Thus, we predicted that males would sing and defend territories in the
burned habitat but that reproductive success would be low as a consequence of unfavorable
understory structure required for nest placement. Overall, we predicted a reduction of the
Grinnelian niche space in burned habitats. Mechanical thinning entails removing a fraction of
the basal area of a forest to increase the amount of sunlight that penetrates the canopy and
reaches the forest floor. Thinned forests have increased growth in the shrub and understory
layers which results in a more heterogeneous and structurally complex understory. Hooded
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warblers are associated with canopy gaps [34,35] and often invade selectively logged forests
1–5 years post logging [35–37]. Therefore, we predicted that there would be increased reproductive success in the harvested habitat. In addition, we predicted that the habitat space would
be larger and the position in habitat space would include more complex understory vegetation
in the harvested habitat compared to undisturbed habitat. Finally, we determined if reproductive success, as estimated by the number of fledged young per nest, is related to habitat structure. We predicted that hooded warbler nest success would be positively correlated with
complex understory vegetation structure.
Materials and Methods
Study site
We monitored habitat use and reproductive success of hooded warblers at Tar Hollow State
Forest (39°33’0”N, 82°76’7”W), which is located in southern Ohio within the unglaciated Allegheny Plateau. The primary canopy species include Quercus alba (white oak), Quercus prinus
(chestnut oak), Carya spp.(hickories), and Quercus rubus and Quercus velutina (red and black
oak; [38]). Understory vegetation includes Smilax spp. (greenbrier), Viburnum acerifolium
(maple-leaf viburnum), Rubus spp., Lindera benzoin (spicebush) and many small-diameter
saplings (i.e., < 10 cm DBH [diameter at breast height]). We established study sites (20–30 ha)
at three locations within the forest. We selected sites with divergent physical structure that
mimicked different stages of disturbance, yet attempted to control for other environmental
characteristics (e.g., moisture, slope, elevation). One site had experienced no logging for the
past 80–100 years (unaltered habitat). Another site had been thinned from below in 2001 and
resulted in an approximately 25% reduction in basal area (harvested habitat). The selective harvest focused on removing midstory and subcanopy trees [39]. This manipulation created canopy gaps, but did not change overall canopy height and the density of canopy trees (>38 cm
DBH). The main effect of the disturbance was to alter the understory vegetation density and
species composition [40]. For example, there was an increase in early-successional saplings
such as Liriodenron tulipifera (tulip tree) and Sassafrass albidum (sassafras) and an increase in
Rubus spp. The third site (burned habitat) had been burned during the winter or early spring
prior to leaf-out in 2001, 2005, and 2010. This study site had reduced understory vegetation
structure and low shrub cover [40,41] in the years immediately following burning (e.g., 2010,
2011).
Ethics statement
This study and all protocols to collect data for this research were approved by the Ohio University Institutional Animal Care and Use Committee (permit H12-02). In addition, all bird banding and related methods were conducted as permitted under USGS banding permit #23434.
Capture methods
We captured hooded warblers using mist nets during late April through mid July in 2010 and
2011. Each captured bird was banded with a USGS numbered band and a unique combination
of color bands for individual identification in the field. We also individually marked and
weighed nestlings when they were between four to six days of age.
Territory mapping, nest searching and monitoring
We engaged in an exhaustive search for nests and territorial birds starting in early May through
mid-July during the 2010 and 2011 breeding seasons. We varied the direction and starting
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Demographic Costs and Habitat Space Occupancy
location on each visit to ensure that locations within the forest were sampled at different times
of day throughout the breeding season. We georeferenced all hooded warbler observations and
nest locations. When observed, we identified individuals by their unique color band combinations. Male territories were defined by the detection of an individual in a location on at least
three survey days spanning a period greater than 10 days apart. We also used behavioral interactions (e.g., territorial defense) with neighboring males following Bibby et al. [42]. We monitored nests every one to three days following the Breeding Bird Research and Monitoring
Database program (BBIRD) protocol [43] to determine nest fate.
Habitat assessment
We established and measured habitat characteristics in 104 habitat plots (11.3 m radius circle = 0.04 ha each) that portrayed different types of use by hooded warblers following the
BBIRD protocol [43]. We described the structure and composition of habitat available to warblers by selecting 10 random plots (“random plot”) in each forest habitat, 100 m apart (using a
random number generator). We also measured vegetation characteristics in habitat plots used
by hooded warblers: habitat plots were established in the center of each male's territory (“territory plot”) and centered on each nest (“nest plot”) after breeding was completed. Only nine
random plots were retained for analysis in the harvested habitat because one territory overlapped with a random plot. The smaller size (~20 ha) of the burn site prevented us from establishing more than five random habitat plots that were 100 m apart. We modified the BBIRD
protocol slightly (change in size class assignment, below) in our estimation of canopy, shrub,
and sapling cover. We recorded trees by species and size class (10–23 cm, 23–38 cm, > 38 cm
DBH) in the 11.3 m radius vegetation plots. We recorded all shrubs and saplings in a 5 m
radius plot (centered within the 11.3 m radius plot) by species. We recorded the number of vertical stems at 10 cm above the ground by species and assigned to three size classes (< 3 cm, 3–6
cm, and 6–10 cm).
Statistical analyses
Because of small sample sizes for some woody plant species and size classes, we excluded all
plant species with fewer than five occurrences in the data (combined random, nest and territory habitat plots). These included stems in the medium and large shrub size classes (3–6 and
6–9 cm). In addition, we grouped Quercus spp. as white oak (Q. alba, Quercus muehlenbergii),
and red oak (Q. rubra, Q. velutina). Although Q. prinus (chestnut oak) is a white oak, it was
recorded separately because of the high abundance of this species as well as differences in habitat characteristics (e.g., plant species composition, structure) in areas where chestnut oak
occurs (e.g., xeric ridge tops) compared to other white oaks. We grouped all Carya spp. (hickory) by genus and we grouped different species of Smilax and Rubus by genus (Smilax spp. and
Rubus spp.). We conducted all analyses in R [44].
Defining a habitat space. We used nonmetric multidimensional scaling (NMDS), an ordination technique that compares the relationships among individual objects (e.g., habitat plots)
in a multidimensional space [45]. The distance between objects in a multidimensional space
reflects their similarity or dissimilarity. In our analysis, the volume occupied by the objects is
an estimate of the habitat space used by individuals. The goal of this analysis was to compare
the similarity in habitat space occupied among individuals in the three habitats and between
males and females in relation to the availability of habitat.
We applied a square-root transformation to better normalize count data and Wisconsin
double standardization (species divided by maxima and sites standardized to equal totals) to
visually examine the habitat axes within the forest. We used three dissimilarity metrics in
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vegan [46]. 1. Bray-Curtis index,
P
xik j
i jxij
djk ¼ P
i jxij þ xik j
where xij and xik are the count of species for each site (j and k).
2. Jaccard index,
djk ¼
2B
ð1 þ BÞ
where B is Bray-Curtis dissimilarity.
3. Kulczyński index,
P
djk ¼ 1
0:5
i
minðxij ; xik Þ
P
þ
i xij
P
i
!
minðxij ; xik Þ
P
i xik
which considers the minimum count of species at each site. The Kulczyński dissimilarity coefficient is robust to situations where sites have very common or rare species [45]. We compared
the performance of the three measures using the function rankindex in package vegan [46] to
determine which dissimilarity index best separated the habitat community characteristics in
relation to a gradient in canopy cover. All three indices were found to perform similarly. We
used Jaccard dissimilarity coefficient because it is more effective in preserving the relationships
among objects (i.e., habitat plots) in the multidimensional space [46,47]. The goal of ordination
analyses is to summarize a complex multidimensional dataset in a fewer number of axes. In
order to determine the number of axes to retain for interpretation, we compared the goodness
of fit for two, three and four axes solutions. We compared the stress for each solution, which is
defined as the difference between the original distance between objects and their position in
the reduced space. We used the NMDS solution that resulted in the lowest stress.
To assist in visualization and interpretation of the relationships among the habitat characteristics associated with male and female habitat use, we plotted the 95% confidence ellipses
based on the standard deviation of the weighted averages from the centroid (function ordiellipse), as well as, the convex polygon (function ordihull) for each plot type. We interpreted the
axes describing the habitat space by calculating the correlations between the habitat characteristics and the NMDS axes. The method is similar to interpretation of Principal Components
Analysis (PCA) factor loadings. We used the vegetation variables with the highest correlation
coefficients to interpret each axis. Because individuals are plotted in this space based on the
habitat characteristics they use, we can determine the habitat characteristics that are components of the habitat space occupied by individuals.
Is there a difference in the position in habitat space?. We determined the similarity in
vegetational composition and structure among the three forest types and the overlap in habitat
space in males and females by plotting 95% confidence interval (CI) ellipses of the centroids by
forest habitat type and sex using the function ordiellipse in the package vegan. The CI ellipses
allow visual comparison of overlap in habitat space among different groups. We also tested for
differences in habitat space among habitats and by sex with function adonis in the package
vegan [46,47]. Adonis is a non-parametric permutational multivariate analysis of variance
(PERMANOVA) based on dissimilarities that tests the hypothesis of no difference in the centroids within a multivariate space [23]. We used Jaccard dissimilarity coefficient and 5,000 permutations with habitat type (unaltered, harvested, burn) and used plot type (random, female
nest, male territory) as predictor variables to test the hypotheses that there were no differences
in habitat space occupied among the male territory, female nest, and random plots or by
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habitat type. Both the visual comparison of the 95% confidence ellipses and PERMANOVA
provide tests to determine whether variation in niche space remains similar across habitats.
Alternatively, birds may alter their use of habitat characteristics depending on the environmental context due either to the availability of non-consumable resources or the interaction
between available environmental and biotic conditions. In addition, visual inspection of size
and orientation of the confidence ellipses allow us to determine if the centroids of the occupied
habitat space differs among environments and if this space expands or shrinks for different
groups. Thus, these analyses allow us to determine the habitat characteristics associated with
any observed differences in habitat space occupancy.
We only observed three males whose territories were completely within the burned habitat
(other males were present but territories encompassed areas in adjacent undisturbed habitat)
and two nests during the two years of this study so all habitat plots from the burn were
removed from further analyses and we only made comparisons of habitat space for male territory and female nest sites in the unaltered and the selective harvest habitat. We used function
adonis with 5,000 permutations to determine if there were differences in the habitat characteristics used for male territories and for female nest locations in the unaltered compared to the
harvested habitat and if there were differences in the habitat space by sex in separate analyses.
We also used function adonis to test for differences in habitat characteristics between random
and territory plots and random and nest plots.
Is there evidence of a reduction or expansion of habitat space?. We used homogeneity
of dispersions test (function betadisper in vegan), a multivariate analogue to Levene's test of
equality of variances, to compare the median distances from the centroid of the male territory
and female nest site characteristics in each habitat to determine if there were differences in the
dispersion (increase or decrease in the volume of habitat space). The homogeneity of dispersion test allows us to determine if the habitat space of different groups (e.g., individuals breeding in structurally different habitats, or by sex) remains the same, shrinks or expands. Pairwise
differences in dispersion among groups were compared using Tukey's HSD test with 999 permutations. Significant increases (or decreases) in dispersion between groups indicate an
increase (or decrease) in habitat space. We used homogeneity of dispersion with 1,000 permutations to determine if the dispersion in habitat space (all habitat plots combined) differed
between the unaltered compared to the harvested habitat. We then used separate homogeneity
of dispersion tests with 1,000 permutations to determine if there were differences in the size of
the habitat space for male territory and female nest site characteristics by forest habitat.
The Grinnellian niche: Are differences in habitat space related to reproductive success?. We tested the hypothesis that forest habitat and the structural habitat characteristics
explained variance in reproductive success using a generalized linear model with a Poisson distribution. We used the number of fledged young per nest as our estimate of reproductive success and the scores from the first two NMDS axes as our predictor variables. We used function
glmulti [48] in R to select the most supported of all possible candidate models from the full
model with all interactions (forest habitat x NMDS1 x NMDS2) using the small sample corrected AICc [49].
Results
We obtained data on the structural characteristics of the vegetation in 53 habitat plots (Fig 1)
in the unaltered habitat (n = 10 random plots, n = 14 territory centered plots, n = 29 nest centered plots), 41 plots in the selective harvest (n = 9 random plots, n = 14 territory centered
plots, n = 18 nest centered plots), and 10 plots in the burn habitat (n = 5 random plots, n = 3
territory centered plots, n = 2 nest centered plots). The best NMDS solution had four axes and
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Fig 1. Map illustrating the location of the habitat plots used to estimate vegetation composition and structure. We show the positions for the
different plot types (male territory centered, nest centered, and random) each year in (A) burn habitat, (B) harvested habitat and (C) unaltered habitat.
doi:10.1371/journal.pone.0165472.g001
a stress of 15.99%. A two axis solution had a stress value of 28.3%. The first NMDS axis
described a moisture gradient with mesic forest characterized by L. benzoin and canopy Liriodendron tulipifera at one end to xeric forests associated with canopy Q. prinus, Smilax spp., Q.
prinus saplings and midstory Acer rubrum at the other (S1 Table and S1 Fig). Canopy and subcanopy Q. prinus were positively correlated with the second axis indicating increased complexity in the canopy. In contrast, the second axis was negatively correlated with canopy Q. alba,
and Q. rubra and Q. alba saplings indicating increased understory complexity. Thus, the second axis described a structural gradient from increased complexity in the understory to
increased complexity in the canopy.
Is there a difference in the position in habitat space?
We found a significant difference in the centroids of the habitat space among the unaltered,
burn and selective harvest habitats (PERMANOVA: F2,95 = 4.5, P = 0.002); however, output
from function adonis does not indicate which centroids differ when more than two groups are
compared. Inspection of the 95% confidence ellipses from the NMDS (Fig 2) suggest that the
habitat characteristics in the burn and unaltered habitats were more similar to each other (centroids overlapped), but differed from the harvested habitat. A similar pattern was observed
when comparing only the random habitat plots in this habitat space (S2 Fig). In addition, male
territory, female nest and random habitat space differed (PERMANOVA: F2,95 = 1.5, P = 0.02).
We found no significant interaction among male, female and random habitat characteristics by
forest habitat (PERMANOVA: F4,95 = 0.85, P = 0.84).
We compared the random and territory habitat space in the unaltered and harvested habitats to determine if males were selecting components of the available (random) habitat. While
the habitat space in the two habitats overlapped (Fig 3A), we found a significant difference
between the centroids of the habitat characteristics in the unaltered compared to the harvested
habitat (PERMANOVA: F1,46 = 2.65, P < 0.001). We did not find a difference between random
habitat plots and male territory characteristics overall (PERMANOVA: F1,46 = 1.25, P = 0.18;
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Fig 2. Charcaterization of habitat space in the unaltered, burned and harvested habitat. Results of a nonmetric
multidimensional scaling analysis of similarity in the vegetational composition and structure in random habitat plots, nest
habitat plots and male territory habitat plots from the unaltered (circles), selective harvest (squares) and the burn habitat
(triangles). Convex hulls are plotted for each stand and 95% confidence ellipses based on the standard deviation of the
weighted distance from the group centroid are indicated (C = unaltered habitat, B = burned habitat, T = selective harvest
habitat).
doi:10.1371/journal.pone.0165472.g002
Fig 3A) and the interaction between habitat type and plot type was not significant (PERMANOVA: F1,46 = 0.81, P = 0.71).
We compared the random and nest habitat space in the unaltered and harvested habitats to
determine if females were selecting nest sites that differed from the available habitat (Fig 3B).
We found a significant difference between the centroids of the habitat characteristics used for
nesting in the unaltered compared to the harvested habitat (PERMANOVA: F1,65 = 4.67,
P < 0.001), and we found a significant difference between the nest and the random habitat
characteristics (PERMANOVA: F1,65 = 2.27, P = 0.007) suggesting that females were selecting
specific components of the available habitat. The interaction between habitat type and habitat
plot type was not significant (PERMANOVA: F1,65 = 0.73, P = 0.81).
The habitat characteristics of the nest and territory plots in the unaltered and harvested habitat overlapped (Fig 3C). We found no difference in the centroids of the habitat space used by
males compared to females (PERMANOVA: F1,71 = 1.51, P = 0.08) and no significant interaction between sex and forest habitat type (PERMANOVA: F1,71 = 0.88, P = 0.56). However, we
found a significant difference in the centroids of habitat space by habitat type (PERMANOVA:
F1,71 = 5.13, P = 0.002). To determine if the position of nest and territory plots occupied distinct regions in the habitat space, we used PERMANOVA to test for differences between the
centroids of the territory space and in nest space between habitats in separate analyses. The
habitat characteristics of male territories in the unaltered and harvested habitat overlapped;
however, we found a significant difference between the centroids of this habitat space
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Fig 3. Comparison of habitat space between (A) male territories and random space, (B) female nest
sites and random space, and (C) male territories and female nest sites. The position of the habitat plots in a
space defined by the first two axes from the NMDS ordination in the unaltered (circles), and selective harvest
(squares). Solid symbols represent territory plots (A) or nest plots (B) while open symbols represent random
plots. Convex hulls define habitat space in each habitat (solid line = Territory; dashed lines = Random, blue =
unaltered habitat and black = harvested habitat) and 95% confidence ellipses based on the standard deviation of
the weighted distance from the group centroid (territories or nests in unaltered habitat = blue oval, territories or
nests in harvested habitat = gray oval, random plots = red ovals). (C) Solid shapes represent nests sites and
open shapes represent male territories. Convex hulls are drawn for female and male habitat space in each
habitat (solid line = female nest; dashed lines = male territory) and 95% confidence ellipses based on the
standard deviation of the weighted distance from the group centroid are indicated (female nest sites = red ovals;
male territory = gray ovals).
doi:10.1371/journal.pone.0165472.g003
(PERMANOVA: F1,26 = 2.03, P = 0.01). There was also a significant difference between the
centroids of the habitat space used for nesting in the unaltered compared to the harvested habitat (Fig 2; PERMANOVA: F1,45 = 3.997, P < 0.001).
Is there evidence of a reduction or expansion of habitat space?
We did not find a significant difference in habitat heterogeneity, the amount of variation in habitat space, among forest habitat type (homogeneity of dispersions test, F2,101 = 2.7, P = 0.06). We
used Tukey’s HSD to test for pairwise differences between groups and found no significant difference in dispersion (volume of the habitat space, as suggested by the ellipse sizes of the three sites
in Fig 2) between the unaltered and burn habitats (P = 0.06), and between the harvested and the
burn habitat (P = 0.09), and no difference in the volume of habitat space between the unaltered
and the harvested habitats (P = 0.98). We found no difference in dispersion by habitat plot type
(nest, territory, random) when all three stands were considered (F2,101 = 0.85, P = 0.44).
We did not find a difference in the volume of habitat space (e.g., niche breadth) occupied
for nesting between the unaltered and selective harvest habitats (homogeneity of dispersion:
F1,45 = 0.08, P = 0.77), and no difference in the volume of habitat space used by males in the
two stands (homogeneity of dispersion: F1,26 = 0.34, P = 0.57). This indicates that the size of
the habitat space used by males (territory) or by females for nesting did not differ in relation to
forest habitat type.
The Grinnellian niche: Are differences in habitat space related to
reproductive success?
We determined whether habitat structure explained variance in the number of young fledged
per nest. Fewer young fledged in the selective harvest compared to the unaltered habitat (z =
-2.45, P = 0.02). The AICc selected model (AIC weight: wi = 0.13) explained 11% of the deviance in the number of fledged young and included forest type, NMDS1, the interaction
between NMDS2 and NMDS1 and the interaction between forest habitat type and NMDS1.
The number of young fledged was unrelated to the structural habitat characteristics in the unaltered habitat. However, in the harvested habitat more young fledged from nests in mesic habitat characterized by Q. alba and Rubus spp. than on xeric ridge tops (interaction of forest
habitat type and NMDS 1: z = -2.41, P = 0.016, Fig 4). The second best model (wi = 0.12) was
consistent with the selected model but did not include the interaction between NMDS axis 1
and 2. All other models had low support (wi < 0.06).
Discussion
Within a population of hooded warblers, we detected differences in the habitat space occupied
in relation to habitat characteristics in structurally different forest habitats. We found no
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Demographic Costs and Habitat Space Occupancy
Fig 4. The relationship between number of fledged young and the interaction of forest habitat type and NMDS axis 1. Unaltered habitat = solid line;
selective harvest habitat = dashed line with 95% confidence intervals.
doi:10.1371/journal.pone.0165472.g004
difference in the size (volume) of habitat space used by males (territory) or by females (nesting); however there were differences among the centroids of habitat space in the three habitats.
The centroids of the habitat space used by males and females in the unaltered and harvested
habitats compared to the available habitat also suggest differences in the habitat characteristics
selected by males and females. The habitat characteristics at nest locations in the harvested
habitat were characterized by canopy white oaks with increased complexity in the shrub layer
(increased Q. alba and Q. rubra saplings and Rubus spp.). In contrast, habitat characteristics at
nests in the unaltered habitat were characterized by complex canopy structure with Q. prinus
in the canopy and a shrub layer dominated by Smilax spp.. We also found that variation in habitat characteristics explained variation in the number of fledged young in the selective harvest
but not the unaltered habitat. Consistent with our prediction, females in the harvested habitat
occupied habitat space that was characterized by increased understory vegetation; however, the
reduced fledging success indicates a potential reduction in niche space in this habitat. The
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Demographic Costs and Habitat Space Occupancy
ability to identify differences in habitat use and any corresponding differences in fitness measures can improve our understanding of how structurally different habitats affect demographic
parameters within populations.
Habitat space
Selective harvest and burning resulted in altered habitat structure compared to the unaltered
habitat (S2 Fig) [40,41]. The burned habitat was similar to the unaltered habitat in canopy
complexity and tree species composition but had reduced complexity in the understory. The
habitat space in the harvested forest spanned a gradient from being dominated by canopy Q.
prinus and Smilax spp. to space characterized by canopy Q. alba and Rubus spp. and overall
had more complexity in the understory while the unaltered stand was characterized by a more
complex canopy with Q. prinus and a shrub layer dominated by Smilax spp. (Fig 2, S1 Fig).
We found that the habitat used by female hooded warblers differed in relation to differences
in habitat structure. In the harvested habitat, female nest sites were located in habitat space
with increased understory complexity, using a subset of the available (random) habitat space
(Fig 3B) while the habitat that the males used did not differ from the available habitat (Fig 3A).
Males and females can exhibit different preferences for habitat structure [27,28,30] and hooded
warblers exhibit habitat segregation on the wintering grounds [26,31]. For reproduction, males
and females must occupy the same habitats on the breeding grounds but they may still exhibit
different preferences in habitat structure and use different cues in selecting habitat [28].
Because of differences in morphology [50,51], foraging [29] or behavior [27,52], males and
females may require different structural components and may have different adaptive peaks in
relation to habitat use [26,27,31]. The habitat space used by females in the unaltered stand was
similar to the available habitat; however, the habitat space used by females in both stands differed from the available habitat space and female nest site characteristics in the harvested habitat differed compared to the habitat characteristics used by females in the unaltered forest (Fig
3C). In contrast, males occupied habitat space that was more similar to the available habitat.
Identification of sex differences in habitat space use and how habitat space affects reproductive
success and survival will aid in our understanding of differences in abundance, density, and
demography within or among habitats.
The Grinnellian niche space differed among forest stands
We found a similar number of male territories in both the selective harvest and unaltered habitat (e.g., 12 territories in each stand during 2011 breeding season); however, we found fewer
nests in the harvested habitat and fewer young were fledged per nest in the harvested habitat in
both years of this study. In addition, habitat space in the harvested stand characterized by
mesic slopes and more complex understory vegetation was associated with greater reproductive
success than along the ridgetops in this stand. This suggests that the Grinnellian niche space
(i.e., the habitat characteristics needed for survival and reproduction) differed and was reduced
in the selective harvest stand. While the harvested habitat provided increased complexity in the
understory, the reduced complexity in the canopy may have contributed to reduced reproductive success by providing more open perches for avian nest predators and avian nest parasites
(i.e., brown-headed cowbirds, Molothrus ater) [53,54]. The reduced canopy complexity may
have contributed to lower reproductive success in the harvested stand on the xeric ridge tops;
while the greater understory vegetation complexity on the mesic slopes may have ameliorated
the effects of avian predation and parasitism.
Burning reduced the Grinnellian niche space of hooded warblers in our burned study site.
Male hooded warblers that occupied territories in the burn habitat primarily foraged, sang and
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Demographic Costs and Habitat Space Occupancy
displayed. We detected additional males singing or foraging in the burn; however, these individuals flew to adjacent non-burned habitat so were not included in analyses. One female each
year nested in the burn habitat (the first year in a ravine characterized by L. tulipifera, Plantus
occidentalis (sycamore) and L. benzoin that was unburned), but both nests failed because of
predation during egg laying; therefore, the Grinnellian niche space for the hooded warbler was
absent in the burn two years post burn. We occasionally observed other females in the burn
habitat early in the breeding season but not by late May. In other southeastern Ohio forests,
hooded warbler and ovenbird (Seiurus aurocapilla) either declined in burned habitat, using
only portions of the habitat that were unaffected by burning for nesting, or they abandoned the
habitat all together [55]. Although burned forests may provide habitat structure for foraging
hooded warblers, there is a diminishment of the Grinnellian niche space in these stands due to
lack of sufficient nesting substrate.
Differences in habitat structure can also induce behavioral trade-offs [56]. The foraging
behavior of insectivorous birds can be affected by the thermal environment which alters insect
community composition, distribution and activity level [57] which may in turn influence avian
time and energy budgets. Indeed, biotic factors including caterpillar biomass, nest predation,
double brooding and renesting explained 87% of the variation in fecundity of black-throated
blue warblers [58]. In comparison, our best model linking the structural habitat characteristics
to the number of fledged young only explained 11% of the variation. Predators and nest parasites do not compete for the vegetation component of the Grinnellian niche, rather habitat
structure can affect a species’ ability to avoid predation and parasitism. Because predation is
associated with variation in fecundity in Passerine birds [58,59] and predators can alter the
behavior and nest placement of breeding birds [53,60], understanding what structural habitat
characteristic are associated with variation in reproductive success can help us identify habitat
space that may be associated with source and sink populations. Testing predictions about
source-sink dynamics within a habitat mosaic can be accomplished by the addition of the
above data to ecological niche models.
The Grinnellian niche and conservation biology
Understanding how variation in habitat characteristics affect reproductive success and survival
provides insight into variation in demographic data within or between populations. Because
habitats used for breeding must provide the biotic and abiotic conditions for both survival and
reproduction, it is important to consider multiple niche axes and determine if males and
females require different characteristics within the niche space. Identification of factors that
constitute niche space for populations across the landscape can be crucial for understanding
population dynamics of target species. For example, Soberón and Nakamura [5] examined the
environmental niche of the prickly pear moth (Cactoblastis cactorum), which is native to South
America but has invaded Florida. They plotted the distribution of the moth in relation to temperature and precipitation and found the niche centroid in this space shifted in relationship to
precipitation but not temperature. Similarly in the Sierra Nevada over the last 100 years, many
of the bird species examined tracked a climate niche which resulted in shifted distributions
[61]. The ability of individuals to track changes in biotic and abiotic conditions can promote
population persistence in the face of land use and climate change
Identification of the structural characteristics that are important elements of the Grinnellian
niche will aid in the identification and assessment of the factors that explain intraspecific niche
variation and is another step toward understanding of the impacts of disturbance on populations as well as the distribution of species across a landscape. The availability of data on species
presence/absence and detailed vegetation cover data allow for the assessment of broad scale
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Demographic Costs and Habitat Space Occupancy
patterns relating elements of the Grinnellian niche to species richness [4,14]. However, linking
demographic data to the non-consumable resources used by a species and identifying combinations of resources that are associated with source sink dynamics can provide data to fine tune
niche models in heterogeneous landscapes thus increasing our understanding of the impacts of
habitat heterogeneity on the population dynamics.
Supporting Information
S1 Fig. Habitat space. NMDS of the habitat space based on 104 habitat plots from random,
male territory center and female nest sites. Plant species and size classes as in S1 Table.
(PDF)
S2 Fig. Random habitat space in the burned, harvested and unaltered habitat. NMDS of the
random habitat space by habitat type.
(TIFF)
S1 Table. Acronyms for the plant species sampled in the habitat plots, scientific name, common name, size class. Stem size classes: V1 < 3 cm, T1 = 10–23 cm, T2 = 23–38 cm, T3 > 38
cm and NMDS scores.
(PDF)
Acknowledgments
We thank Cory Malone, Bob Scott Placier and many other volunteers for assistance in the
field.
Author Contributions
Conceptualization: KAW DBM.
Data curation: KAW.
Formal analysis: KAW.
Funding acquisition: KAW.
Investigation: KAW.
Methodology: KAW.
Supervision: DBM.
Writing – original draft: KAW.
Writing – review & editing: KAW DBM.
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