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22001177 SOUTHEASTERN NATURALIST 1V6o(3l.) :1364,3 N–3o6. 13
Nest-Site Selection and Success of Louisiana Bald Eagles
Nickolas R. Smith1,2,*, Thomas J. Hess Jr.3, and Alan D. Afton4
Abstract - Mating pairs of Haliaeetus leucocephalus (Bald Eagle) nest during winter in
Louisiana, and numbers of nests have increased exponentially since the mid-1970s. Active
nests have remained relatively concentrated within the south-central and southeastern
part of the state, in an area primarily consisting of inland swamps, coastal marshes,
and barrier islands, which is referred to as the Basin. However, as the number of nests
continues to grow, it is expected that nesting will continue to expand geographically into
new habitats. In order to manage an expanding population, it is imperative to first determine
parameters that influence nest-site selection. To evaluate site selection and success,
we conducted GIS-based analyses to evaluate geographic variables such as proximity to
water, landcover, human activity, and other nests. We compared 387 active nests from
the 2007–2008 winter nesting season and 1935 random sites, which represented available
habitat for site selection. Our results suggest that success of a nest within the Basin
was not greatly influenced by the physical characteristics around a site, but sites with the
highest probability of being selected for nesting generally had a higher probability of
success. Initial selection of a nest site was most influenced by distance to road, number
of houses per km2, and landcover within 3 km, but the influence of these variables varied
between sites within and outside the Basin. Our results should assist managers in making
informed decisions about effects of future developments, conservation activities, and human
use on current and future suitable nesting habitat.
Introduction
Species management frequently relies on knowledge and management of habitats
occupied by that species. Researchers often compare characteristics that make
up the area where a species is found to the areas that are available in order to better
understand factors that may influence site selection (Jones 2001). Habitat selection
occurs at hierarchical levels (Johnson 1980), wherein an animal first selects
a geographical range, then a home range within, and then selects a place to nest
within that home range. Selection may vary at these different levels (Saalfeld and
Conway 2010, Thompson and McGarigal 2002), but identifying habitat selection
at a landscape level facilitates broad management application, while still providing
direction for more-refined management on a local level. Modeling nest-site selection
to understand the disproportionate use of particular habitats, especially when
related to the success of a site, helps to achieve the ultimate goal of understanding
1School of Renewable Natural Resources, Louisiana State University, Baton Rouge, LA
70803. 2Current address - Ducks Unlimited Inc., One Waterfowl Way, Memphis TN 38120.
3Louisiana Department of Wildlife and Fisheries, Rockefeller Refuge, 5476 Grand Chenier
Hwy, Grand Chenier, LA 70743 (deceased). 4US Geological Survey, Louisiana Cooperative
Fish and Wildlife Research Unit, Louisiana State University, Baton Rouge, LA 70803. *Corresponding
author - nrsmith@ducks.org.
Manuscript Editor: Jason Davis
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the relationship that selection has to the reproductive fitness for the individuals
involved (Jones 2001).
Nest-site selection on a local level has been extensively studied, indicating that
Haliaeetus leucocephalus L. (Bald Eagle) typically select nest sites in large mature
trees (Andrew and Mosher 1982, Anthony and Isaacs 1989, Harris et al. 1987,
McEwan and Hirth 1979, Saalfeld and Conway 2010, Wood et al. 1989) in close
proximity to open water (Andrew and Mosher 1982, Anthony and Isaacs 1989,
Harris et al. 1987, McEwan and Hirth 1979, Wood et al. 1989). Other factors that
influence nest-site selection include size of water bodies (Anthony and Isaacs 1989,
Dzus and Gerrard 1993, Gerrard et al. 1975), prey availability (Gende et al. 1997,
Isaacs et al. 1983), human activity/disturbance (Andrew and Mosher 1982, Anthony
and Isaacs 1989, Buehler et al. 1991, Guinn 2013, Mundahl et al. 2013, Saalfeld and
Conway 2010), and habitat surrounding a site (Andrew and Mosher 1982, Anthony
and Isaacs 1989, Buehler 1995, McEwan and Hirth 1979, Mundahl et al. 2013,
Saalfeld and Conway 2010, Wood et al. 1989).
Harris et al. (1987) examined nest-site characteristics at a local level in southcentral
and southeastern Louisiana during 1977–1980, and reported that nests
were located primarily in Taxodium distichum (L.) Rich. (Bald Cypress)/ Nyssa
aquatica Marshall (Water Tupelo) swamps adjacent to marshes, rivers, canals,
bayous, ponds, or lakes. Since then, the number of Bald Eagles nesting in Louisiana
has grown rapidly, with no indications of slowing since at least 2008 (Smith
et al. 2016). Although Louisiana Bald Eagles still nest primarily in the southcentral
and southeastern portion of the state, they are expected to move into other
habitats as the population expands (LADWF 2007). Understanding nest-site selection
and factors contributing to nest success, especially after major expansion
in number of nests and distribution, may allow managers to make informed decisions
about potential effects of future developments, conservation activities, and
human use.
Accordingly, we used nest data collected during the most recent statewide Louisiana
nest survey to (1) describe habitats used by nesting Bald Eagles in Louisiana,
(2) examine factors influencing landscape-level nest-site selection and success, and
(3) identify areas with high potential for future nest sites.
Field-site Description
Bald Eagles establish territories and nest during winter throughout Louisiana,
but their nests are unevenly distributed; the majority of nesting occurs within the
south-central and southeastern part of the state (Smith et al. 2016). This area closely
matches the boundaries of 2 of Louisiana’s level-IV ecoregions: inland swamps,
and the deltaic coastal marshes and barrier islands (Daigle et al. 2006), henceforth
collectively referred to as “the Basin” (Fig. 1). The inland swamps are the northern
extent of the intertidal basins and comprise a large portion of the Atchafalaya
Basin. Their poorly drained soils are dominated by Bald Cypress/Water Tupelo
swamps. The deltaic coastal marshes and barrier islands are dominated by brackish
and saline marshes. The Basin encompasses 18% of Louisiana and is within the
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Mississippi Alluvial Plain, which covers 38% of the state and is one of Louisiana’s
6 level-III ecoregions.
Outside the Basin, the Mississippi Alluvial Plain is mostly a flat alluvial area
comprised of agricultural land—mainly cotton, corn, soybeans, pasture, and aquaculture—
as well as bottomland forests. The South Central Plains cover 40% of the
state and are primarily comprised of forested or woodland habitats, with less than
20% of the region in agricultural land. The Western Gulf Coastal Plain comprises
13% of the state and is a relatively flat area with fertile soils; rice and soybean
production are the primary land uses in the region. The Southeastern Plains, Mississippi
Valley Loess Plains, and Southern Coastal Plain together encompass only 9%
of the state and are similarly comprised of a mosaic of cropland, pasture, wetland,
forested, and woodland habitats.
Methods
We used GIS and remote sensing to compile variables that were previously
known or hypothesized to influence nest-site selection and succe ss (Table 1). Data
Figure 1. Map of Bald Eagle active nest sites (n = 387) from the 2007–2008 winter nesting
season in relation to level-III ecoregions and the area referred to as the Basin.
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for some variables were not available for 2007; to replace these data, we selected
data sources from 2006 and 2010 (see Table 1) because we assumed them to be most
representative of the values during the 2007–2008 winter nesting season. We compiled
information from previous studies on Bald Eagles (Buehler 1995, Harris et al.
1987, McEwan and Hirth 1979, Peterson 1986, Saalfeld and Conway 2010) to guide
the development of factors to include in our study. We gave separate consideration
to the biological basis of each included variable for both nest-site selection and nest
success, as suggested by Burnham and Anderson (2002) and Anderson (2008).
Nest-site selection
We used nest-location data collected during the 2007–2008 winter nesting season
(most recent available statewide survey) to examine landscape-level nest-site
selection. The LADWF maintains records of known nest locations as reported by
private individuals, state and federal personnel, and the media. These sites were
monitored annually, and when new nest sites were detected, they were incorporated
into the surveys (Smith et al. 2016). Multiple nests may occur within a nesting
Table 1. Summary of data used to model landscape-level nest-site selection and success.
Variable Biological indicator Data Source
Nest sites Winter 2007–2008 nest LDWFA
locations and status
Roads Human disturbance TIGER/line roads (2006) US Census Bureau
Houses per km2 Human disturbance 2010 population—census US Census Bureau
block group
2010 census block group US Census Bureau
Nearest nest Nest density Winter 2007–2008 nest LDWF
locations
Water body Foraging habitat High-resolution NHDB– US Geological Survey
linear (1:24,000)
High-resolution NHD– US Geological Survey
discrete (≥8 ha)
NLCDC 2006 (30 m)– MRLC ConsortiumD
discrete (≥8 ha)
Basin Ecoregion Level III and IV ecoregions US Geological Survey
Land cover (0.5 and 3 km) Habitat NLCD 2006 (30 m) MRLC Consortium
Open water
Woody wetland
Emergent herb wetland
Developed
Agricultural
Forest
ALouisiana Department of Wildlife and Fisheries.
BNational Hydrography Dataset.
CNational Land Cover Database.
DMulti-Resolution Land Characteristics Consortium.
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territory; thus, to reduce pseudoreplication, we excluded from analysis nests not
classified as active. Nests were classified as active by the presence of at least 1 of
the following: (1) 1 or more adults in or near a nest with signs of nest refurbishment,
i.e., presence of fresh nesting material; (2) an adult sitting low in the nest
presumably incubating; or (3) the presence of eggs or young. Our analysis of nestsite
selection is based on a total of 387 active nest locations.
To facilitate comparisons between nest sites and available habitat, we generated
5 corresponding random locations for each nest site (n = 1935). We set selection of
each random site to be within 50 km of the corresponding nest as a representation
of the relative non-nesting winter home range of Bald Eagles in Louisiana (Smith
et al., in press). After looking at the winter home ranges of non-nesting Bald Eagles
in Louisiana that were marked with satellite transmitters in a separate part of our
research, we assumed that this distance would best reflect the area from which the
nesting pair would have first selected their nest site.
Within the 50-km radius around each nest, random sites were restricted to areas
considered to be suitable habitat (Fig. 2). We based our criteria for determining
site suitability on variables associated with nest sites (Andrew and Mosher 1982,
Figure 2. Map of areas considered to be suitable habitat in relation to the area referred to
as the Basin.
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Anthony and Isaacs 1989, Dzus and Gerrard 1993, Gerrard et al. 1975, Harris et al.
1987, McEwan and Hirth 1979, Saalfeld and Conway 2010, Wood et al. 1989) and
used in the modeling of suitable habitat in other studies (Andrew and Mosher 1982,
Grier and Guinn 2003, Saalfeld and Conway 2010, Watts et al. 2008). However,
specific values were reflective of characteristics from Bald Eagle nests in Louisiana.
Specifically, we classified suitable habitat as: (1) less than 1 km (representative of
distance to nearest water body for nest sites) from a water body (discrete water body
≥8 ha or linear water body represented as polygon at 1:24,000 scale), (2) at least 3
km (representative of the observed distance between nests) from another nest, and
(3) within suitable landcover. We identified suitable landcover types as: emergent
herbaceous wetland, wooded wetland, and forest (Smith 2014) because these types
were most likely to have trees that could support a nest. We further restricted the
emergent herbaceous wetland landcover type to the area within 1 km of at least 1
other suitable landcover type. We set this condition to exclude large herbaceous
wetlands with the lowest probability of containing suitable nest trees, such as
coastal marshes. We restricted random sites to these landcover types because 95%
of documented nests were located within these landcovers.
We used distance to nearest road and number of houses per km2 to index human
disturbance around nests and random points. We assumed that sites closer to roads
and with more houses per km2 experienced more human disturbance. In Texas,
distance to human disturbance was the best predictor of landscape-level nest-site
selection (Saalfeld and Conway 2010), but absolute distance to human structures
may be misleading because tolerance to human presence may be increased by visual
buffers and habituation (Andrew and Mosher 1982, Millsap et al. 2004). We
included 2 human-disturbance indices to assess whether either had an effect on
nest-site selection by Bald Eagles in Louisiana.We used TIGER/line shapefiles created
in 2006 to identify locations of roads, then used a spatial join to calculate the
Euclidian distance from a site to the nearest road. We employed 2010 census data to
calculate density of houses, then used number of houses and total area within each
census-block group to determine number of houses per km2.
Landcover type has been included in most studies of Bald Eagle nest-site selection
(Andrew and Mosher 1982, Anthony and Isaacs 1989, Buehler 1995, Curnutt
and Robertson 1994, Dzus and Gerrard 1993, Gerrard et al. 1975, Guinn 2013,
Harris et al. 1987, McEwan and Hirth 1979, Peterson 1986, Saalfeld and Conway
2010, Wood et al. 1989). We hypothesized that the composition of habitat around a
site influences nest-site selection and that some landcover types are more influential
than others. We followed the 2006 National Land Cover Database (NLCD; Fry et al.
2011) to classify landcover, wherein we combined similar cover types to reduce the
number of variables to 6 cover types (open water, wooded wetland, emergent herbaceous
wetland, developed, agricultural, and forest; Smith 2014). We determined
the proportion of landcover types at 2 spatial scales, 500 m and 3 km, around each
site. We set the area within 500 m of a nest to correspond to USFWS (1987) primary
management zones. We selected a 3-km scale to represent the observed home-range
size of nesting Bald Eagles in Louisiana (Smith et al., in press). We calculated the
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2017 Vol. 16, No. 3
proportion of each landcover type within 500 m and 3 km of each site using the
ISECTPLYRST tool in Geospatial Modeling Environment (GME; version 7.2.0).
Nests were unevenly distributed across the state; the majority of nesting occurred
within the south-central and southeastern part of the state (Smith et al.
2016) within the Basin (Fig. 1). We defined the extent of the Basin by combining 2
level-IV ecoregions: (1) inland swamps and (2) deltaic coastal marshes and barrier
islands (Daigle et al. 2006), and we examined ecoregion-level variations in nestsite
selection within the Basin and outside the Basin. Because our random points
were set to be within 50 km of a nest, there were a similar percent of nests and
random points within the Basin (81% and 78%, respectively) and outside the Basin
(19% and 22%, respectively). Therefore, we expected that the effect of Basin alone
would not greatly influence selection, but rather the 2-way interactions of Basin
with other variables might show ecoregion-level variations in the other variables.
Roads are unevenly distributed across Louisiana, with fewer roads located
within the Basin. The area within the Basin is largely comprised of wetland habitats
(Daigle et al. 2006), and few roads cross some of the large wetland areas. Outside
the Basin, there are very few areas where roads are more than a few kilometers
apart. Thus, the observed distribution of roads in Louisiana may not allow for sites
to be more than a few kilometers from the nearest road except for within the Basin
and, therefore, the importance of distance to the nearest road may vary between
areas. For this reason, we included a 1st-order interaction of Basin x distance to road
in our analysis.
Likewise, the wetland habitat within the Basin is not ideal for human development,
and therefore, most of the Basin (81.2%) has ≤5 houses per km2. Outside the
Basin, over a third of the area (34.6%) has >5 houses per km2. Thus, we expected
that the importance of houses, as an index of human disturbance, would vary between
sites within and outside the Basin and we included Basin x houses as a 1storder
interaction.
General habitat characteristics also varied in relation to whether a site was
within or outside the Basin. Woody and emergent herbaceous wetlands are more
abundant within the Basin, whereas developed, agricultural, and forested landcover
types are more common outside the Basin. Therefore, we included a 1st-order interaction
of Basin x landcover type. Aside from these 1st-order interactions with the
Basin, we had no biological reason to presume that the influence of nest-site selection
would vary for any other interactions.
In summary, we considered the following explanatory variables in our analysis
of landscape-level nest-site selection: (1) distance to road, (2) houses per km2,
(3) land cover, (4) Basin, (5) Basin x distance to road interaction, (6) Basin x houses
per km2 interaction, and (7) Basin x landcover type interaction.
Nest success within the Basin
We used status data for nests active in the survey to classify nests as successful
or unsuccessful; we recorded nests as successful if a minimum of 1 young, 8
weeks of age or greater, was observed. We included in our nest success analysis
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only those nests for which a status could be determined. Of those nests in which
a status was determined, there were 39 nests outside the Basin, of which only 7
were unsuccessful. Due to the low sample-size of nests found outside the Basin, we
restricted our analysis to nests located within the Basin. Thus, our final analysis of
nest success is based on a total of 276 nests of which 234 (85%) were successful
and 42 (15%) were unsuccessful.
We used the same explanatory variables (distance to road, number of houses
per km2, and landcover) in our nest-success analysis as we used in the nest-site
selection analysis. We considered hypotheses from the nest-site selection analysis
to have similar effects on nest success, i.e., a variable hypothesized to have a negative
effect on the probability of a site being selected for nesting would also have a
negative effect on the probability of a nest being successful.
In addition to the 3 explanatory variables used in the analysis of nest-site selection,
we included distance to nearest water body and distance to nearest nest for
our analysis of nest success (Table 1). We used distance to nearest water body to
index distance to foraging areas. Fish and water-birds comprise the majority of a
Bald Eagle’s diet (Buehler 2000, Dugoni et al. 1986); therefore, we hypothesized
that successful nest sites would be closer to areas that provide such food sources.
Many other studies have reported that nests were close to water (Andrew and
Mosher 1982, Anthony and Isaacs 1989, Buehler 2000, Harris et al. 1987, McEwan
and Hirth 1979, Wood et al. 1989), and that eagles prefer larger water bodies over
smaller ones (Anthony and Isaacs 1989, Dzus and Gerrard 1993, Gerrard et al.
1975), but smaller water bodies may also provide suitable foraging opportunities,
especially when located near other water bodies (Peterson 1986).
We considered a water body to be any large, discrete body of water ≥8 ha in
size (e.g., lakes, ponds, and reservoirs) as well as large linear bodies of water
which were represented as polygons rather than lines at a 1:24,000 scale (e.g.,
rivers, streams, and canals). We used National Hydrography Dataset (NHD) High
Resolution Discrete and Linear Waterbody layers and removed all water bodies
that did not meet the size requirement. We also removed swamp/marsh water
types from the NHD Discrete Waterbody layer because these were represented by
landcover types and were not truly representative of unobstructed open water. The
NHD had some data gaps, e.g., large water bodies or parts of large rivers, such as
parts of the Mississippi River, were not represented; therefore, we supplemented
these files with open water from the 2006 NLCD (Fry et al. 2011). We clipped
the NLCD raster files open-water landcover class to remove coastal water, used a
region group to calculate water body size, and then eliminated areas less than 8 ha in size
from the resulting data set. We did not consider distance to nearest water body in
models of nest-site selection because random sites were restricted to areas within
1 km of a water body.
We used distance to nearest nest, as an index of nest density, to evaluate the
hypothesis that nesting density would affect nest success (Dzus and Gerrard 1993,
Elliott et al. 2011). we employed the POINTDISTANCE tool within GME to calculate
the Euclidean distance to the nearest active nest.
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In summary, we considered the following explanatory variables in our analysis
of nest success: (1) distance to road, (2) number of houses per km2, (3) landcover,
(4) distance to nearest water body, and (5) distance to nearest nest. We did not
consider interactions because we had no biological reason to presume that any interaction
would influence nest success.
Statistical analysis
We used stratified logistic regression (PROC LOGISTIC; SAS Institute Inc.
2011) to evaluate the influence of multiple explanatory variables on (1) the probability
of a nest site being selected and (2) the probability of a site being successful
or unsuccessful. We specified the identification number of the nest and associated
random sites in the strata option; the response variable was whether or not a site
was used for nesting. We included site characteristics as explanatory variables and
the classification of a site (nest/random, successful/unsuccessful) as the response
variable. We developed a set of 18 a priori candidate models for the evaluation
of landscape-level nest-site selection (Table 2) and a set of 13 a priori candidate
models for the analysis of nest success (Table 3). Model selection was based on
Akaike’s information criteria, adjusted for small sample size (AICc), where models
that best supported the data had the lowest AICc. To be consistent with an AIC
approach, we evaluated 1st-order parameters from the top model(s) using an 85%
confidence interval (CI) of the parameter estimates (Arnold 2010). Only those
parameters that did not overlap zero were considered to be influential in nest-site
selection or success.
Multicollinearity was inherent due to the nature of our landcover data (Graham
2003). For example, the percent of 1 landcover type present within a buffer influenced
the percent of all other landcover types within that same buffer as well as
the percent landcover in the smaller/larger buffer, because buffers were inclusive.
For this reason, in the nest-site selection and nest-success analyses, all landcover
types at a single spatial scale were either included or excluded together from a
model and were represented as the variable “landcover” with 6 levels. We separately
tested which spatial scale was most influential in nest-site selection and
nest success by running the full model from each analysis with landcover within
500 m and then running the full model again with landcover within 3 km. The full
model that performed best, as determined by the lowest AICc, was then considered
the most influential spatial scale. In these preliminary analyses, landcover
within a 3-km radius of sites had a greater influence in nest-site selection and
nest success than landcover within a 500-m radius and, therefore, was used for all
candidate models subsequently analyzed. To test for multicollinearity in all other
variables, we used a correlation matrix (PROC CORR; SAS Institute, Inc. 2011),
wherein variables with Pearson correlation coefficients ≥0.7 were considered
highly correlated (Dormann et al. 2013); however, none of the variables we considered
were found to be highly correlated.
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Results
General relationships
Nests within the Basin were located an average of 2.6 km from the nearest
road (range = 0.0–21.3 km); whereas, nests outside of the Basin were located an
average of 0.6 km from the nearest road (range = 0.0–2.4 km). The distribution of
distances from the nearest road and number of houses per km2 for nests and random
points were relatively similar except at the extremes. Ninety seven percent of
all nests were at least 400 m from the nearest nest, however, nest sites outside the
Basin were, on average, 13.7 km from the nearest nest (median = 7.8 km, min–max
= 0.7–52.3 km); whereas, they were 2.5 km from the nearest nest within the Basin
(median = 1.6, min–max = 0.1–19.3 km). All nests were within 3 km of a large
body of water (average distance = 466 ± 26 m). Successful nests were farther from
a large body of water, on average, than were unsuccessful nests (473 m and 372
m, respectively). Wooded wetlands made up the largest proportion of landcover
types within 3 km of nests (mean = 44.1%); emergent herbaceous wetland was the
2nd-most abundant landcover type (mean = 26.0%) at that scale. Suitable habitat,
to which random sites were restricted, encompassed 23,897 km2 in Louisiana. The
Basin contains 1/3 of that area defined as suitable and 81% of active nests, despite
the Basin only covering 18% of the state (Figs. 1, 2).
Nest-site selection
The top model accounted for 55% of the Akaike model weight and included distance
to road, number of houses per km2, landcover within 3 km, Basin, and all 1storder
interactions between Basin and the other 3 variables (Table 2). The top model
correctly classified 71.6% of sites. Interactions indicated that the importance of the
variables examined (roads, houses, and landcover) were not consistent between
sites within and outside the Basin. For example, the importance of emergent herbaceous
wetlands was more influential outside the Basin. We did not use an 85% CI
to infer the importance of individual variables because the inclusion of all 1st-order
interactions in the top model suggested that their importance was not consistent
between areas within and outside the Basin.
The influence of roads and houses varied between sites within and outside the
Basin. Outside the Basin, nest sites and random sites were usually a similar distance
from roads (0.55 km and 0.58 km, respectively) and in areas with fewer houses per
km2 (13.0 and 21.9, respectively). However, within the Basin, nest sites were usually
closer to roads (2.59 km) than random sites (3.50 km) and in areas with more
houses per km2 (8.0) than random sites (6.2). Overall, nest sites within the Basin
were farther from roads (2.59 km) and in areas with fewer houses per km2 (8.0, than
nest sites outside the Basin (0.55 km, 13.0)
The areas around nest and random sites were usually comprised of similar percentages
for developed, forested, and wooded wetland landcover types. However,
outside the Basin, areas around sites contained a larger percentage of developed and
forested landcover and less wooded-wetland landcover. The influence of open water
and agricultural landcover types was relatively consistent between sites within and
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outside the Basin; nests were in areas with more open water and less agricultural
land than random sites. However, outside the Basin, areas around sites contained a
smaller percentage of open water and a larger percentage of agricultural landcover
when compared to sites within the Basin. The influence of emergent herbaceous
wetlands had the greatest variation between sites within and outside the Basin.
Within the Basin, the percentage of emergent herbaceous wetland landcover around
a site was similar for nests and random sites, (28% and 30%, respectively), but outside
the Basin, nests were in areas with twice the amount of emergent herbaceous
wetland landcover than random sites (16% and 8%, respectively; Fig. 3).
Nest success within the Basin
The candidate models we considered indicated that nest success within the Basin
was best predicted by distance to road, number of houses per km2, and landcover
Table 2. Stratified logistic regression models predicting Louisiana Bald Eagle nest sites (n = 387)
versus random sites (n = 1935), including number of parameters (K), Akaike’s information criterion
adjusted for small sample size (AICc), difference between the AICc of the given model and the model
with the lowest AICc (ΔAICC), and Akaike’s model weight (wi).
Model K AICC ΔAICC wi
RoadA, housesB, landcoverC, basinD, basin x roadE, 15 1199.56 0.00 0.55
basin x housesF, basin x landcoverG
Road, landcover, basin, basin x road, basin x landcover 13 1202.01 2.45 0.16
Road, landcover, basin, basin x landcover 12 1202.22 2.66 0.15
Road, houses, landcover, basin, basin x road, basin x landcover 14 1203.50 3.94 0.08
Road, houses, landcover, basin, basin x land cover 13 1203.72 4.16 0.07
Road, landcover 6 1211.50 11.94 0.00
Road, houses, landcover 7 1213.15 13.59 0.00
Houses, landcover, basin, basin x houses, basin x land cover 13 1225.15 25.59 0.00
Land cover, basin, basin x land cover 11 1227.68 28.12 0.00
Houses, land cover, basin, basin x land cover 12 1229.23 29.67 0.00
Landcover 5 1237.29 37.73 0.00
Houses, landcover 6 1238.89 39.33 0.00
Road, basin, basin x road 3 1373.57 174.01 0.00
Road, houses, basin, basin x road, basin x houses 5 1373.99 174.43 0.00
Road 1 1375.93 176.37 0.00
Intercept onlyH 0 1375.93 176.37 0.00
Houses, basin, basin x houses 3 1385.62 186.06 0.00
Houses 1 1388.33 188.77 0.00
ADistance to nearest road (km).
BNumber of houses per km2.
CProportion of landcover type within 3-km at 5-km levels: open water, developed, forest, agricultural,
emergent herbaceous wetland, and reference level set as wooded wetland.
DBasin at 2 levels: within Basin and outside Basin; reference level set as outside Basin.
E1st- order interaction between outside Basin and distance to nearest road (km).
F1st-order interaction between outside Basin and houses per km2.
G1st-order interaction between outside Basin and landcover type within 3-km at 5-km levels: open water,
developed, forest, agricultural, emergent herbaceous wetland, and reference level set as wooded
wetland.
HIntercept-only model for benchmark comparison.
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within 3 km (Table 3). This top model accounted for 68.0% of the Akaike model
weight and correctly classified 70.1% of nests as either successful or unsuccessful.
Within the top model, distance to roads, number of houses per km2, developed,
agricultural, and emergent herbaceous wetlands had parameter estimates with confidence
intervals that did not overlap zero, and thus, were considered most influential.
The probability of a site being successful decreased as distance to road increased;
successful nests were generally closer to roads than unsuccessful nests
(2.6 km and 2.9 km, respectively). Number of houses per km2 was marginally influential
in predicting the success of a site; successful nests were usually in areas
with slightly more houses than unsuccessful nests (7.5 and 5.8, respectively). The
probability of a site being successful decreased as the proportion of developed and
agricultural land increased, but probability of success increased as proportion of
emergent herbaceous wetland landcover increased within 3 km of a nest site.
Discussion
Nest site selection
The interaction between other explanatory variables and the Basin suggest that
Bald Eagles use different strategies for nest-site selection depending on whether
their home ranges are within the Basin or in another part of Louisiana. However, the
Basin interactions that included roads and houses were highly influenced by sites
Figure 3. Percent of 6 landcover types within 3 km of nests and random sites within and
outside the Basin, including standard error bars.
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2017 Vol. 16, No. 3
at the extremes and not necessarily a response to human disturbance. For example,
outside the Basin, there were 4 random sites with number of houses per km2 ranging
from 147–501, but the maximum number of houses for nests was 124. These few
sites at the extreme were likely driving the variable’s inclusion in the model and
suggesting that random sites were in areas with more houses than nest sites outside
the Basin. Outside the Basin, roads appear to have little effect on nest-site selection
because there are very few areas greater than a few kilometers from a road.
Within the Basin, nest sites were located in areas closer to roads and in
areas with more houses per km2. Within this region, the characteristics that make
areas suitable for human development may also provide characteristics which enhance
a site’s suitability for nesting. For instance, there is little elevation change
within the Basin (Hupp et al. 2008), so areas farther above mean sea level provide
stable areas for human development and protection from flooding. Areas with less
flooding may be supporting larger Cypress and Tupelo trees (Keim et al. 2013),
and thus are better suited for supporting Bald Eagle nests compared to areas
that are more frequently inundated. Overall, human disturbance may not affect
nest-site selection by Bald Eagles from Louisiana as strongly as in other studies
(Andrew and Mosher 1982, Saalfeld and Conway 2010); our results are more
consistent with the idea that the influence of human disturbance on Bald Eagle
nest-site selection is minimal compared to other factors (McEwan and Hirth 1979,
Millsap et al. 2004).
Table 3. Logistic regression models predicting successful Louisiana Bald Eagle nest sites (n = 234)
versus unsuccessful sites (n = 49), including number of parameters (K), Akaike’s information criterion
adjusted for small sample size (AICc), difference between the AICc of the given model and the model
with the lowest AICc (ΔAICC), and Akaike’s model weight (wi).
Model K AICC ΔAICC wi
RoadA, housesB, landcoverC 7 226.17 0.00 0.68
Road, houses, landcover, nearest nestD, nearest waterE 9 229.03 2.86 0.16
Houses, landcover, nearest water 7 229.86 3.70 0.11
Landcover, nearest water 6 233.99 7.82 0.01
Land cover 5 234.60 8.44 0.01
Nearest nest 1 235.13 8.97 0.01
Land cover, nearest nest 6 235.16 8.99 0.01
Nearest nest, nearest water 2 235.84 9.68 0.01
Intercept onlyF 0 237.42 11.26 0.00
Nearest water 1 238.15 11.98 0.00
Houses 1 238.94 12.78 0.00
Road 1 239.14 12.98 0.00
Road, houses 2 240.82 14.66 0.00
ADistance to nearest road (km).
BNumber of houses per km2.
CProportion of landcover type within 3 km at 5 levels: open water, developed, forest, agricultural,
emergent herbaceous wetland, and reference-level set as wooded wetland.
DDistance to nearest nest (km).
EDistance to nearest water body (km).
FIntercept only model for benchmark comparison.
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The model results being driven by a few sites at the extremes may have been an
artifact of random sites being restricted to areas considered to be suitable of supporting
Bald Eagle nesting. This restricted designation of random sites may have
created relative uniformity for many aspects, whereas if the parameters we used to
locate random sites were not restricted, we may have expected greater distinction
between nest and random sites. However, our results from this greater distinction
would likely have been less informative than our more restrictive analysis
because they would likely have suggested that nest-site selection is driven by factors
already confirmed, such as that Bald Eagles nest near water and in areas with
suitable nest trees. Thus, we argue that our model should be used to determine
the probability of a site being used for nesting within areas deemed to be suitable
for nesting; i.e., within 1 km of a large body of water, and in a forested, wooded
wetland, or emergent herbaceous wetland landcover type with trees capable of supporting
a nest.
Landcover type around a site was an influential variable in our top model. Landcover
type within 500 m provided less predictive power than did landcover within
3 km for both the nestsite selection models and the nest-success models. This outcome
may be explained by the fact that Bald Eagle nest-site selection at a local level
is relatively homogenous; most nests are in large trees and the area immediately
surrounding the nest is comprised of a wooded landcover type (Andrew and Mosher
1982; Anthony and Isaacs 1989; Buehler 1995, 2000; Harris et al. 1987; Saalfeld
and Conway 2010; Wood et al. 1989).
Nest sites had more open-water than did random sites, which probably provided
more foraging habitat. Large bodies of open water are the primary foraging habitats
for Bald Eagles (Buehler 2000), and many studies have found that their presence
has been influential in nest-site selection (Andrew and Mosher 1982, Anthony and
Isaacs 1989, Buehler 2000, McEwan and Hirth 1979). However, a congregation of
smaller water bodies may also provide suitable foraging opportunities (Peterson
1986), which may be the case for the nests located farthest from a large body of
water. Our analysis accounted for Bald Eagles that selected for areas with multiple
smaller foraging areas within reasonably close proximity because we used
proportion of open water around a site. Thus, our results should better account for
differing foraging strategies in relation to water than did previous studies which
used only a linear distance to nearest large water body.
As expected, wooded and emergent herbaceous wetlands made up the greatest
proportion of the area around sites within the Basin because these 2 landcover types
were the most abundant in this region. Likewise, wooded wetlands were also the
most abundant outside the Basin; however, we found that nests were in areas with
twice as much emergent herbaceous wetland than were random sites outside the
Basin. Like open water, emergent herbaceous wetlands provide abundant foraging
opportunities for Bald Eagles in Louisiana (Harris et al. 1987). In addition to the
fish resource, emergent herbaceous wetlands also support large numbers of waterfowl
that winter in Louisiana (Baldassarre 2014, Michot 1996) and which make up
a large portion of the prey consumed during the nesting period (Dugoni et al. 1986).
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2017 Vol. 16, No. 3
Thus, emergent herbaceous wetland landcover has a discernible influence on nestsite
selection, especially when it is limited within the landscape.
Bald Eagles selected against agricultural land; however, it was still the 3rd-most
abundant landcover type around nests outside the Basin, which may be due to a
landscape-level change in habitat characteristics between the different ecoregions.
Bald Eagles may be first selecting nest sites within the Basin, where there is more
woody and emergent herbaceous wetland landcover, but as these areas become occupied
and nesting expands outside the Basin, the habitats shift to more forested
and agricultural landcover (Daigle et al. 2006). Although these habitats are more
abundant outside the Basin, their use may not be proportional with other habitat
types. Examination of resource utilization by nesting individual Bald Eagles may
provide better insight into the relationship that various habitat types play in nestsite
selection. In general, nest-site selection outside the Basin appears to be mainly
driven by habitats with more open water, less agricultural land, and more emergent
herbaceous wetlands.
The Basin may provide ideal habitat for Bald Eagle nesting, and thus, may be
driving the dissimilarity in nest numbers between the Basin and the rest of the
state. As of 2008, the number of nesting Bald Eagles in Louisiana has increased
exponentially (Smith et al. 2016). If the number continues to increase, we would
expect that more nests will be found outside the Basin because the area within the
Basin may be reaching a carrying capacity. If this is the case, our findings may be
used to prioritize conservation of areas wherein the probability of nesting would
be greatest.
Our findings highlight the importance of the Basin and its habitats for the
stability of Louisiana’s nesting Bald Eagles. A lack of sediment input, subsidence,
and sea-level rise threaten the region (Daigle et al. 2006); Louisiana loses
almost a football field-sized amount of of coastline every hour (Couvillion et al.
2011). Besides land loss, the ecosystem can be drastically altered by changes in
salinity and hydrological regimes, creating changes in the characteristics of the
wetland habitats and the species that occupy those areas (Boesch et al. 1994).
These threats may be exacerbated by projected increases in the frequency and severity
of hurricanes in the area (Knutson et al. 2010). Bald Cypress/Water Tupelo
swamps are relatively resistant to the effects of hurricanes (Shaffer et al. 2009);
however, fresh and brackish marshes can be severely affected (Barras 2006).
Past hurricanes directly destroyed a large proportion of nests in Louisiana, and
although they showed no short-term effect on the population because many of the
nests were rebuilt (Hess et al. 1994), the long-term effects are unknown. Together,
these threats should be considered in the future conservation and management of
Bald Eagles in Louisiana.
Nest success within the Basin
Nest success within the Basin followed similar patterns as observed for nestsite
selection. Thus, areas with the highest probability of being selected for
nesting generally had a higher probability of success. However, our top model
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2017 Vol. 16, No. 3
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provided relatively weak evidence that landscape-level variables could be used
to accurately predict nest success. Our top model correctly classified 70.1% of
nests; however, there was an uneven number of successful versus unsuccessful
nests. Thus, predicting that all nests were successful would have provided 84.8%
correct classification.
Bald Eagles generally have high rates of nest success (Buehler 2000, Driscoll et
al. 1999, Saalfeld et al. 2009, Watts et al. 2008), and Louisiana has one of the highest
documented rates (Smith et al. 2016). Future research looking at the long-term
trend of success for nest sites may provide a better understanding of the landscapelevel
characteristics that influence success, and then sites could be grouped by
above average, average, or below average success. Analysis of this long-term trend
of site success should also better account for nest failures from factors that cannot
be characterized through remote sensing.
We only considered landscape-level variables that could be characterized using
remote sensing, whereas nest success can be affected by other things such as
weather, prey availability, disease, and/or the age or skill level of the nesting pair
(Buehler 2000, Elliott et al. 2011, Forslund and Pärt 1995, Gende et al. 1997, Millsap
et al. 2004). However, of the variables we considered, distance to road, number
of houses per km2, and the amount of developed, agricultural, and emergent herbaceous
wetland landcover within 3 km appear to be the most influential in predicting
the success of a nest within the Basin.
Nest success may not be greatly impacted by the physical characteristics around
a site, but the initial selection of a site appears to be influenced by at least some
landscape-level factors, as shown by our models. Overall, factors associated with
habitat degradation and the ability of the Bald Eagle to adapt to a changing environment
may be the driving force behind a healthy and expanding nesting population
in Louisiana. With these results, managers may be able to focus efforts on the protection
of current and future suitable habitat, emphasizing areas with the highest
probability of nesting.
Acknowledgments
We dedicate this manuscript to the memory of Thomas Hess Jr., our co-author who devoted
much of his career to protecting the Bald Eagles of Louisiana. Financial support for
this study and its publication were provided by the Louisiana Department of Wildlife and
Fisheries and the US Fish and Wildlife Service, Division of Federal Aid, through Louisiana
State Wildlife Grant T-98, the Rockefeller Wildlife Refuge Trust, the US Geological Survey-
Louisiana Cooperative Fish and Wildlife Research Unit, and the School of Renewable
Natural Resources at Louisiana State University. We acknowledge the work of W. Dubuc,
R. Aycock, G. Melancon, J. Linscombe, and all the individuals from US Fish and Wildlife
Service and Louisiana Department of Wildlife and Fisheries who have assisted with Louisiana’s
nest-monitoring program since 1975. We also thank the landowners who contributed
information on nesting eagles. We thank W. Selman, D. Blouin, and L. Wang for providing
critical comments on this manuscript. Any use of trade, firm, or product names is for descriptive
purposes only and does not imply endorsement by the US Government.
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