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2014 SOUTHEASTERN NATURALIST 13(4):744–761
Shorebird Response to Post-Flood Drawdowns on Tennessee
National Wildlife Refuge
Kira C. Newcomb1,*, Adrian P. Monroe1, J. Brian Davis1, and Matthew J. Gray2
Abstract - Mudflats are important stopover sites for shorebirds during migration, but management
plans typically do not provide mudflat habitat in the reservoirs of the Tennessee
River Valley (TRV) during May–July. In May 2010, flooding delayed drawdowns on Tennessee
National Wildlife Refuge and created wetlands for shorebirds from May–August.
We studied wetland use and behavior of shorebirds during delayed drawdowns in 2010,
and we compared shorebird abundance between years with delayed and typical drawdowns
using International Shorebird Survey data. We found that shorebirds consistently used
wetlands for foraging throughout summer during 2010. In addition, abundance of 43% of
species tested was greater in years with delayed than typical drawdowns. Our results suggest
extending availability of mudflats throughout summer in the TRV may provide important
habitat for migrating shorebirds.
Introduction
Shorebirds (Charadriiformes) exploit diverse wetland and agricultural habitats
throughout the Western Hemisphere during their annual cycle (Rundle and Fredrickson
1981, Skagen 2006, Skagen and Knopf 1993). Most of the 53 shorebird
species that are regularly found in the US migrate thousands of kilometers between
arctic and subarctic breeding grounds and non-breeding areas (Brown et al. 2001).
For shorebirds like Pluvialis dominica (Müller) (American Golden-Plover) and
Calidris fuscicollis (White-rumped Sandpiper), migration between Canadian Arctic
breeding grounds and South American non-breeding areas may exceed 15,000 km
(Skagen 2006; taxonomy throughout follows Chesser et al. [2013]). Long-distance
migration is an energetically taxing activity for birds and can impact their survival
(Lehnen and Krementz 2007, Skagen 2006). Thus, stopover wetlands along migration
routes are critical resources for shorebirds, especially long-distance migrants,
to replenish their energy reserves (Brown et al. 2001, Lehnen and Krementz 2013,
Myers 1983, Skagen et al. 1999, Webb et al. 2010). Loss of stopover wetlands has
been extensive (Brown et al. 2001, Skagen and Knopf 1993); therefore, maintaining
remaining wetlands for migrating shorebirds is an important objective for resource
managers (Laux 2008, Smith 2006, Twedt 2013, Wirwa 2009).
The Tennessee River Valley (TRV) is the fifth largest watershed in the US
(Tennessee Valley Authority [TVA] 2004). The TVA manages water levels within
49 dam-created reservoirs throughout the TRV to facilitate navigation and
1Department of Wildlife, Fisheries, and Aquaculture, College of Forest Resources, Mississippi
State University, Mississippi State, MS 39762. 2Department of Forestry, Wildlife, and
Fisheries, College of Agricultural Sciences and Natural Resources, University of Tennessee,
Knoxville, TN 37996. *Corresponding author - knewcomb@cfr.msstate.edu.
Manuscript Editor: Roger Perry
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2014 Vol. 13, No. 4
recreation, create hydroelectric power, and control flooding (TVA 2004). Reservoirs
are drawn down annually from July–October, exposing an estimated 12,000
ha of mudflats throughout the TRV (Laux 2008). The TRV’s mudflats provide
essential resources for migratory and resident waterbirds in fall and winter (Laux
2008, Wirwa 2009). Indeed, shorebird use of these mudflat sites may be as significant
as use of similar habitats in the Mississippi Alluvial Valley (MAV; Minser et
al. 2011, Wirwa 2009). However, few mudflats exist in TVA-controlled reservoirs
from May–July because the agency maintains high water levels to support summer
recreation activities (Wirwa 2009). Wetland managers could adjust strategies
for water management on other public and private lands to provide mudflats for
migrating shorebirds during these months (Brown et al. 2001, Minser et al. 2011,
Natural Resources Conservation Service 2012, Scheiman 2007, Smith 2006, Taft
et al. 2002, Twedt 2013, Twedt et al. 1998).
The Tennessee National Wildlife Refuge (TNWR) is located in the western TRV
and encompasses a portion of the TVA-managed Kentucky Reservoir. The refuge
was established in 1945 to provide habitat for migratory birds, specifically wintering
waterfowl (TNWR 2010). Drawdowns are conducted within TNWR’s managed
impoundments from March–June to facilitate cooperative farming and enhance
growth of desirable wetland vegetation for wintering waterfowl (Low and Bellrose
1944). In early May 2010, an extensive flood inundated the Duck River Unit (DRU)
of TNWR with >3 m of water, which resulted in a second drawdown period (hereafter
referred to as delayed drawdowns). In response to the Deepwater Horizon oil
spill that affected coastal wetlands of the Gulf Coast (Corn and Copeland 2010), the
US Fish and Wildlife Service received supplemental funding to extend drawdowns
on DRU to provide mudflats for migrating shorebirds from May–August 2010.
These unanticipated events provided an opportunity, similar to a natural experiment,
for us to monitor migrating shorebirds during May–August, a period when
mudflats typically are drying at DRU but not yet exposed in surrounding reservoirs
of the TRV. Our objectives were to (1) quantify shorebird use and behavioral response
to delayed drawdowns in DRU impoundments from May–August 2010, and
(2) determine if delayed drawdowns had a positive effect on abundance and richness
of shorebirds compared to typical drawdowns using International Shorebird
Survey (ISS) data from 2000–2009 (S. Schmidt, Manomet Center for Conservation
Sciences, Manomet, MA, unpubl. data).
Field-site Description
The DRU (35°57'30''N, 87°57'00''W) of TNWR is located at the confluence of
the Tennessee and Duck Rivers in western Tennessee and consists of 10,820 ha of
seasonally flooded, moist-soil and forested wetlands; permanent open water; agricultural
fields; and upland forests (TNWR 2010). Wetland managers at DRU typically
draw down impoundments in which row crops (e.g., corn and soybeans) are
grown in early March, and then mid-April for impoundments managed primarily
for moist-soil plant production (TNWR 2010). Approximately 1564 ha of wetlands
are exposed across 15 managed impoundments on DRU during annual drawdowns
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in typical years. All impoundments are managed for production of moist-soil plants
to some extent but also contain a complex of other habitat type s (TWNR 2010).
Methods
2010 survey protocol
We monitored shorebird use in 9 managed impoundments (1753 ha total area;
63% exposed) on DRU from 24 May–28 August 2010 (Fig. 1); surveys were initiated
as soon as roads were accessible from receding floodwaters. During our study,
drawdowns began in 3 impoundments during May, 4 in June, and 1 each in July
and August. Because summer drawdowns and subsequent exposure of mudflats
occurred asynchronously among impoundments, the number of survey points
needed to view as many mudflats as possible changed throughout summer. Thus,
we established 2–6 survey points per impoundment as mudflats became available in
locations where maximum mudflat area was visible and no overlap of area surveyed
occurred with adjacent points (Fig. 1). Mudflats were associated with moist-soil
wetlands, edges of permanent open water, and agricultural fields.
Figure 1. Survey points, May–August 2010, and International Shorebird Survey (ISS) route,
2000–2009, on the Duck River Unit of Tennessee National Wildlife Refuge. Surveyed impoundments
are managed to produce moist-soil plants, but each contains a complex of
moist-soil wetlands, open water, forested and scrub-shrub wetlands, and agricultural crops.
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Previous studies have found effects of vegetation on detectability of shorebirds
in moist-soil impoundments (e.g., Farmer and Durbian 2006, Lehnen and
Krementz 2013). During drawdowns in the DRU’s moist-soil impoundments, a
mudflat zone occurs between the receding water’s edge and newly germinating
vegetation. Shorebirds concentrated in these mudflat zones and shallow open
water with sparse or no vegetation. Therefore, reduced visibility from vegetation
was not an issue, and we assumed that detectability for our surveys was near 1. In
order to maximize visibility and thus detectability, we discontinued survey points
when vegetation re-established on mudflats and most shorebirds no longer used
these areas.
Initially, we visited each survey point 6 times per week within 5 h after sunrise,
but we reduced surveys to 3 times per week once the length of time needed to
survey all points in a day exceeded 5 h. Previous shorebird research did not detect
differences in activity budgets of birds among diurnal time periods (i.e., morning,
mid-day, and afternoon; De Leon and Smith 1999, Wirwa 2009); thus, we assumed
morning surveys were representative of overall diurnal activity. We reversed the
order in which points were surveyed each day to capture potential variability associated
with birds’ habitat use among impoundments during this period (Andrei et
al. 2008). We minimized the possibility of bias from double-counting individuals
among survey points by avoiding flushing birds during surveys and altering the
order that points were surveyed each day. It is possible that some individuals were
surveyed from multiple points, but we assumed that this was random or unrelated
to our survey protocol and effect of month.
We used a spotting telescope (Swarovski® model STS-80) with 20–60X zoom to
identify and count all shorebirds at each point, excluding birds flying overhead. After
completing shorebird counts at a survey point, we used focal sampling to quantify
shorebird behavior among impoundments (Davis and Smith 1998). Following
the protocol of previous studies (Davis and Smith 1998, De Leon and Smith 1999,
Wirwa 2009), we classified and recorded activities of individuals as locomotion,
resting, foraging, alert, maintenance, or aggression. We chose individuals for focal
sampling by randomly realigning the spotting scope and observing the individual
at the center of the field of view. We followed one individual per species at each
survey point for one continuous minute and dictated a description of its activities
into a digital voice recorder (De Leon and Smith 1999, Fitzpatrick and Bouchez
1998, Laux 2008, Wirwa 2009).
2010 survey analyses
Shorebird abundance. The total number of survey points in each impoundment
and surveys per point varied because we established sampling locations as mudflats
became available. Therefore, we standardized abundance measurements of
shorebirds by averaging the number of shorebirds counted during repeated visits to
each survey point by month. This provided an overall mean number of shorebirds
per survey for each point and month. We modeled mean total abundance and richness
using linear mixed-effects models in R (v. 3.0.2; R Development Core Team
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2013) and the lme function in package nlme (v. 3.1-115; Pinheiro et al. 2013). We
included month as a fixed effect and survey point as a random effect. We also tested
for month effects on abundance of species with sufficient detections (>5% of total
individuals detected): Charadrius vociferus (Killdeer), Calidris pusilla (Semipalmated
Sandpiper), Calidris melanotos (Pectoral Sandpiper), and Calidris minutilla
(Least Sandpiper) (Table 1). We ensured that assumptions of normality were met by
log- or square root-transforming the response. We used Tukey contrasts and Holm’s
method for posthoc multiple comparisons among months. We also restricted analyses
to June–August because we only surveyed for one week in May and hence
summarized May counts with descriptive statistics (mean ± SE). In all tests, we
considered statistical significance at α = 0.05.
Behavioral observations. We followed the guidelines in Skagen and Knopf
(1993) to categorize shorebirds by average migration distance—short, intermediate,
and long—and compared monthly and overall behavioral activity data
among the 3 groups. We used multivariate ANOVA (MANOVA) in R to examine
activity budgets because our response variables (i.e., percent of one minute
observed in each behavioral activity) were correlated and should be treated as a
single multivariate response (Andrei et al. 2007, Crawley 2013, Davis and Smith
1998). We defined each focal individual as an experimental unit and included
month and shorebird migration distance as independent variables. We examined
data for outliers using Mahalanobis distance, square root- or arcsine-transformed
the response, and used Pillai’s trace as the test criterion. Following a significant
MANOVA, we used univariate ANOVA and Tukey’s HSD to determine differences
in behavior among months and migration categories of birds (Davis and
Smith 1998). We were primarily interested in foraging, maintenance, and resting,
and how these behavioral activities related to habitat use, so we restricted posthoc
analyses to these behaviors.
International Shorebird Survey analyses
Since 1974, volunteers have gathered ISS data during spring and fall migration.
These data are used to monitor shorebird populations, map staging areas, and inform
conservation planning in documents such as the US Shorebird Conservation
Plan (Bart et al. 2007). The ISS protocol recommends surveys be conducted every
10 days between 15 March and 15 June for spring migration, and 15 July and 25
October for fall migration (Schmidt 2010). When feasible, biologists at DRU conduct
1–3 ISS surveys per month each year from a vehicle along an established route
and according to the proposed schedule (Fig. 1; Schmidt 2010).
We analyzed ISS data collected at DRU to determine if shorebird use differed
between years with typical and delayed drawdowns. Typical drawdowns begin in
March and April, and delayed drawdowns, as occurred during our 2010 observations,
begin later in spring and early summer because impoundments are inundated
again after significant flooding in the adjacent Kentucky Reservoir. As a result,
delayed drawdowns begin weeks later after falling water levels allow pumping
to resume; drawdown schedule and total availability of mudflats were similar to
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2014 Vol. 13, No. 4
typical drawdowns but occurred later in the season. Thus, we assumed that detectability
was comparable between delayed and typical drawdowns, and differences
in species abundance or richness were related to habitat availability and not detectability.
We compared total monthly counts in May–August during years with
typical (n = 4) and delayed drawdowns (n = 4) from 2000–2009, but we excluded
2004 and 2006 because no ISS surveys were conducted during those years. In addition,
we excluded June surveys from our analyses because none were conducted
during 3 of the years. We could not make statistical comparisons between our
2010 survey results and ISS data because of differences in survey methodology
and extent of drawdowns. Because only limited inferences could be made with
our 2010 data about the effects of delayed drawdowns on shorebird abundance,
analysis of multi-year ISS data was important.
Delayed drawdowns and species abundance. We compared counts for 7 species
at DRU: Tringa melanoleuca (Greater Yellowlegs), T. flavipes (Lesser Yellowlegs),
Charadrius semipalmatus (Semipalmated Plover), Actitis macularius (Spotted
Sandpiper), T. solitaria (Solitary Sandpiper), Least Sandpiper, and Pectoral Sandpiper
(Table 1). We chose the aforementioned species because they were observed
at least once during each year of available ISS data. We analyzed ISS data using
zero-inflated generalized linear mixed-effects models with a negative binomial
distribution using the glmmADMB function in the R package glmmADMB (v. 0.7.7;
Fornier et al. 2012, Skaug et al. 2013). We used a zero-inflated model to address
potential issues with overdispersion and biased parameter estimates associated with
excessive zeros in the ISS data (30% of response data; Zuur et al. 2012). We created
a binary covariate (delayed year) to indicate whether delayed drawdowns occurred
between May and August of any given year. We treated delayed year and month as
fixed effects, used a random intercept for year, and designated the log-transformed
number of surveys per month as an offset to account for variation in survey effort
(Zuur et al. 2012). We ran 2 models per species, including one model with month
and delayed year as additive effects, and a second model with a delayed year ×
month interaction. Then we used a likelihood-ratio test to determine significance of
the interaction term (Bolker et al. 2013, Zuur et al. 2009). Estimated overdispersion
(ĉ) for all interpreted models was marginal (range = 0.69–1.25), except for Spotted
Sandpiper (ĉ = 1.72).
Delayed drawdowns and species richness. In addition to examining the effect of
delayed drawdowns on total monthly counts in the ISS data, we also tested for an effect
of delayed drawdowns on species richness. We analyzed species richness using
generalized linear mixed-effects models with a Poisson distribution using the glmer
function in the R package lme4 (v. 1.0-5; Bates et al. 2013). We treated delayed
year and month as fixed effects, used a random intercept for year, and designated
the log-transformed number of surveys per month as an offset. Similar to monthly
count data, we compared the additive and interaction models with likelihood-ratio
tests to determine significance of the interaction.
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Results
2010 surveys
We observed 8862 individuals of 26 shorebird species at DRU during late May–
August 2010 (Table 1). Killdeer comprised 68% of all shorebirds observed; 3 species
of sandpiper (i.e., Least, Pectoral, and Semipalmated) comprised 19% of all
individuals observed. Semipalmated Plover, Spotted Sandpiper, and White-rumped
Sandpiper also were commonly observed during surveys. Although few in number
(≤1%), we recorded several species of high conservation concern, including Charadrius
melodus (Piping Plover), Calidris subruficollis (Buff-breasted Sandpiper),
Phalaropus tricolor (Wilson’s Phalarope), and Arenaria interpres (Ruddy Turnstone).
Overall, total number of species detected was greatest in August (n = 20),
followed by July (n = 17), May (n = 11), and June (n = 8).
Table 1. Shorebirds observed at Duck River Unit, Tennessee National Wildlife Refuge, May–August
2010. Number of observed individuals unadjusted for turnover rate. Migration group is based on the
migration-distance index created by Skagen and Knopf (1993) and used by Wirwa (2009). Short = less
than 3900 km, Intermediate = 6300–12,400 km, and Long = greater than 14,800 km.
% of Migration
Species Code n total n group Scientific name
American Avocet AMAV 4 less than 1 Short Recurvirostra americana Gmelin
Baird’s SandpiperA BASA 12 less than 1 Long Calidris bairdii (Coues)
Black-bellied PloverB BBPL 16 less than 1 Intermediate Pluvialis squatarola (L.)
Buff-breasted Sandpiper BBSA 16 less than 1 Long Calidris subruficollis (Vieillot)
DunlinB DUNL 2 less than 1 Intermediate Calidris alpina (L.)
Greater YellowlegsA, B GRYE 37 less than 1 Intermediate Tringa melanoleuca (Gmelin)
KilldeerB KILL 6046 68 Short Charadrius vociferus L.
Long-billed DowitcherB LBDO 12 less than 1 Intermediate Limnodromus scolopaceus (Say)
Least SandpiperA, B LESA 565 6 Intermediate Calidris minutilla (Vieillot)
Lesser YellowlegsA, B LEYE 85 less than 1 Intermediate Tringa flavipes (Gmelin)
Marbled GodwitB MAGO 3 less than 1 Short Limosa fedoa (L.)
Pectoral SandpiperA, B PESA 607 7 Long Calidris melanotos (Vieillot)
Piping Plover PIPL 2 less than 1 Short Charadrius melodus Ord
Red-necked Phalarope RNPH 1 less than 1 Intermediate Phalaropus lobatus (L.)
Ruddy TurnstoneB RUTU 15 less than 1 Intermediate Arenaria interpres (L.)
Sanderling SAND 1 less than 1 Intermediate Calidris alba (Pallas)
Short-billed DowitcherB SBDO 10 less than 1 Intermediate Limnodromus griseus (Gmelin)
Semipalmated PloverA, B SEPL 264 3 Intermediate Charadrius semipalmatus
Bonaparte
Semipalmated SandpiperB SESA 513 6 Intermediate Calidris pusilla (L.)
Solitary SandpiperB SOSA 183 2 Intermediate Tringa solitaria Wilson
Spotted SandpiperA, B SPSA 232 3 Intermediate Actitis macularius (L.)
Stilt SandpiperB STSA 26 less than 1 Long Calidris himantopus (Bonaparte)
Western SandpiperB WESA 14 less than 1 Intermediate Calidris mauri (Cabanis)
WilletB WILL 2 less than 1 Short Tringa semipalmata (Gmelin)
Wilson’s PhalaropeB WIPH 3 less than 1 Intermediate Phalaropus tricolor (Vieillot)
White-rumped SandpiperB WRSA 191 2 Long Calidris fuscicollis (Vieillot)
ASpecies selected for analysis of International Shorebird Survey (ISS) data
BSpecies observed on ISS surveys during years with delayed drawd owns (2002, 2003, 2008, 2009).
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Shorebird abundance. We observed 428 individuals during May surveys, with a
mean ± SE = 21.7 ± 10.5 birds per survey (range = 2.5–65.0). Semipalmated Sandpiper
(57%) and Semipalmated Plover (24%) were most common, whereas Solitary
Sandpiper, Ruddy Turnstone, Killdeer, and Pluvialis squatarola (Black-bellied
Plover) each comprised less than 5% of individuals.
In general, we did not find an effect of month on shorebird abundance or species
richness during June–August 2010. We observed 8434 shorebirds with mean relative
abundance of 19.0 ± 3.9 (range = 0–201) and mean richness of 1.42 ± 0.2 (range
= 0–9.5). Total shorebird abundance (F2, 35 = 1.72, P = 0.19) and species richness
(F2, 35 = 0.28, P = 0.76) per survey did not vary by month. Mean relative abundance
of Killdeer (F2, 35 = 3.20, P = 0.053), Semipalmated Sandpiper (F2, 35 = 1.37, P = 0.27),
and Pectoral Sandpiper (F2, 35 = 2.26, P = 0.12) did not vary by month (Table 2). However,
we found an effect of month for Least Sandpiper (F2, 35 = 3.83, P = 0.031). Abundances
were similar in July and August (P = 0.75) but greater during these months
than in June (P = 0.038 for both tests). Among species comprising less than 5% of individuals
in our sample during June–August, we detected White-rumped Sandpiper—a long-
Table 2. Mean relative abundance per survey (± SE) for migrating shorebirds on the Duck River
Unit, Tennessee National Wildlife Refuge, May–August 2010. Different letter superscripts indicate
a significant difference (P < 0.05) among months when tested for 4 species, each comprising >5%
of individuals detected in June–August. Species codes are defined in Table 1. Abundance was not
formally compared in May because only the last week was surveye d.
Species May June July August
AMAV 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.02 ± 0.02
BASA 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.10 ± 0.07
BBPL 0.62 ± 0.47 0.00 ± 0.00 0.00 ± 0.00 0.02 ± 0.02
BBSA 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 0.08 ± 0.05
DUNL 0.10 ± 0.06 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00
GRYE 0.00 ± 0.00 0.01 ± 0.01 0.06 ± 0.03 0.14 ± 0.08
KILL 1.31 ± 0.52 10.53 ± 3.31A 17.46 ± 5.39A 10.26 ± 3.25A
LBDO 0.00 ± 0.00 0.00 ± 0.00 0.06 ± 0.04 0.02 ± 0.01
LESA 0.38 ± 0.33 less than 0.01 ± less than 0.01A 2.27 ± 1.36B 2.94 ± 1.88B
LEYE 0.00 ± 0.00 0.00 ± 0.00 0.81 ± 0.52 0.17 ± 0.12
MAGO 0.00 ± 0.00 0.00 ± 0.00 less than 0.01 ± less than 0.01 0.00 ± 0.00
PESA 0.10 ± 0.10 0.00 ± 0.00A 2.17 ± 1.04A 2.01 ± 0.86A
PIPL 0.00 ± 0.00 0.00 ± 0.00 0.03 ± 0.03 0.00 ± 0.00
RNPH 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 less than 0.01 ± less than 0.01
RUTU 0.71 ± 0.50 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00
SAND 0.00 ± 0.00 0.00 ± 0.00 0.00 ± 0.00 less than 0.01 ± less than 0.01
SBDO 0.00 ± 0.00 0.00 ± 0.00 0.14 ± 0.14 0.03 ± 0.02
SEPL 5.21 ± 2.47 0.11 ± 0.06 0.30 ± 0.24 0.67 ± 0.33
SESA 11.83 ± 6.72 0.31 ± 0.16A 0.26 ± 0.22A 1.16 ± 1.00A
SOSA 1.02 ± 0.70 less than 0.01 ± less than 0.01 1.02 ± 0.58 0.27 ± 0.07
SPSA 0.00 ± 0.00 less than 0.01 ± less than 0.01 0.47 ± 0.18 0.72 ± 0.20
STSA 0.00 ± 0.00 0.00 ± 0.00 0.06 ± 0.04 0.08 ± 0.06
WESA 0.14 ± 0.14 0.00 ± 0.00 0.02 ± 0.02 0.13 ± 0.12
WILL 0.00 ± 0.00 0.00 ± 0.00 0.07 ± 0.07 0.00 ± 0.00
WIPH 0.00 ± 0.00 0.00 ± 0.00 less than 0.01 ± less than 0.01 less than 0.01 ± less than 0.01
WRSA 0.29 ± 0.29 0.42 ± 0.18 0.00 ± 0.00 0.00 ± 0.00
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distance migrant—only in June, whereas Calidris bairdii (Baird’s Sandpiper), Buffbreasted
Sandpiper, and Calidris himantopus (Stilt Sandpiper) (Table 2) Baird’s
Sandpiper, Buff-breasted Sandpiper, and Calidris himantopus (Stilt Sandpiper) were
observed only in July and/or August. We detected intermediate-distance migrants—
Greater Yellowlegs, Solitary Sandpiper, Semipalmated Plover, and Spotted Sandpiper—
in all 3 months, although they tended to be more common in July and August.
In addition, Limnodromus scolopaceus (Long-billed Dowitcher), Lesser Yellowlegs,
Limnodromus griseus (Short-billed Dowitcher), and Calidris mauri (Western Sandpiper)
were only detected in July and August.
Behavioral observations. We recorded 684 focal observations of shorebirds
from June–August 2010, seven of which we excluded as outliers based on Mahalanobis
distance. Our multivariate analysis indicated that effects of month, migration
group, and month x group interaction on shorebird activities were all significant
(Table 3). Therefore, we analyzed foraging, maintenance, and resting separ ately.
We found monthly significant differences in time spent foraging for intermediate-
but not short- or long-distance migrants. Univariate analysis of foraging also
indicated a month x group interaction (F4, 668 = 5.16, P < 0.001), so we analyzed
month for each migration group separately. Percentage of time foraging did not
vary significantly by month for short- or long-distance migrants (Table 4). However,
month was significant for intermediate-distance migrants, where foraging
frequency was greatest in July, least in June, and intermediate in August (Table 5).
Table 4. Analysis of variance test statistics for differences in shorebird behavior (by migration-distance
class or pooled) among months (June–August) at Duck River Unit, Tennessee National Wildlife
Refuge, 2010. Month x group interaction was not supported for maintenance (F4, 668 = 1.30, P = 0.27).
Our sample of long-distance individuals performing resting behavior was too small to adequately test
their response to month.
Behavior Group F df P
Foraging Short 1.88 2, 323 0.15
Intermediate 13.42 2, 284 less than 0.001
Long 0.682 2, 61 0.51
Pooled 63.23 2, 674 less than 0.001
Maintenance Pooled 24.25 2, 674 less than 0.001
Resting Short 29.67 2, 323 less than 0.001
Intermediate 5.34 2, 284 0.005
Long - - -
Pooled 48.22 2, 674 less than 0.001
Table 3. Multivariate analysis of variance test statistics for shorebird behavior by month (June–August)
and migration-distance class (group) at Duck River Unit, Tennessee National Wildlife Refuge,
2010. For F values, df = 2, 668 for month and group; df = 4, 668 for month x group.
Factor Pillai’s trace F P
Month 0.175 10.63 less than 0.001
Group 0.307 20.08 less than 0.001
Month × group 0.064 1.82 0.009
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Table 5. Diurnal activity budgets (mean % of time spent during 1-minute observations, ± SE) among months for short- (n = 175), intermediate- (n = 270),
and long-distance (n = 232) migrating shorebirds on the Duck River Unit, Tennessee National Wildlife Refuge, June–August 2010 (classifications defined
in Table 1). Different letter superscripts indicate significant difference (P < 0.05) among months within distance groups (when tested) for foraging and
resting. Only foraging, maintenance, and resting behaviors were submitted to additional univariate tests. However, effects of month or month x group in -
teractions were not supported for maintenance, so posthoc tests were not performed among months within distance groups. Additionally, our small sample
of long-distance migrants resting prevented us from ef fectively testing for differences among months for this group.
Short Intermediate Long
Behavior June July August June July August June July August
Alert 9.0 ± 1.3 5.4 ± 1.3 2.7 ± 1.0 9.3 ± 3.3 1.0 ± 0.4 1.6 ± 0.6 5.0 ± 2.4 3.1 ± 0.6 1.5 ± 0.7
Antagonistic 1.3 ± 0.4 0.8 ± 0.3 0.3 ± 0.3 0.0 0.3 ± 0.3 0.5 ± 0.3 0.6 ± 0.6 0.0 0.0
Foraging 38.4 ± 3.0A 36.0 ± 3.1A 27.7 ± 3.2A 38.9 ± 7.9C 73.6 ± 2.7A 59.7 ± 3.2B 75.8 ± 8.4A 74.7 ± 7.6A 65.9 ± 7.0A
Locomotion 13.8 ± 1.7 7.7 ± 1.0 12.8 ± 2.0 15.1 ± 4.7 12.5 ± 1.6 14.0 ± 1.7 4.3 ± 1.9 4.5 ± 1.3 13.1 ± 4.0
Maintenance 26.1 ± 3.3 25.8 ± 3.5 21.3 ± 4.1 22.2 ± 7.9 5.7 ± 1.8 7.6 ± 1.9 14.2 ± 8.8 15.8 ± 7.3 17.3 ± 6.8
Resting 11.4 ± 1.7C 24.3 ± 2.3B 35.1 ± 3.0A 13.9 ± 6.1AB 6.9 ± 2.5B 16.6 ± 2.5A 0.0 1.9 ± 0.8 2.3 ± 1.2
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When we pooled observations among months, there was significant variation
among distance classes (Table 4), and we observed similar percentages of time
spent foraging among intermediate- and long-distance migrants (P = 0.59), whereas
both groups spent more time foraging than short-distance migrants (P < 0.001 for
each; Table 5).
Unlike foraging, short-distance migrants spent the most time on maintenance.
We did not find an effect of month (F2,668 = 1.07, P = 0.34) or a month x group interaction
for maintenance (F4,668 = 1.30, P = 0.27). However, pooling observations
among months indicated that time spent on maintenance varied among migrant
groups (Table 4). Intermediate- and long-distance migrants spent comparable time
on maintenance (P = 0.22), but short-distance migrants spent more time than intermediate
(P < 0.001) and long-distance migrants (P = 0.041; Table 5).
We also found a month x group interaction (F4, 668 = 4.54, P = 0.001) for resting,
and time spent resting varied significantly among months for short- and intermediate-
distance migrants (Table 4). For short-distance migrants, resting increased from
June–August (Table 5). However, for intermediate-distance migrants, time spent
resting was least in July, intermediate in June, and greatest in August. Despite an
apparent trend of increased time spent resting from June–August for long-distance
migrants, the low frequency of individuals observed resting within this group
precluded us from rigorously testing for a month effect on the frequency of this
behavior (Tables 4, 5). Resting varied among months when pooled across distance
classes (Table 4), with more time spent resting in June than July (P < 0.001) and
August (P < 0.001), and more resting in July than August (P = 0.002).
International Shorebird Surveys
Species richness. We did not detect differences in species richness between ISS
surveys conducted during typical and delayed drawdowns. The interaction model
was not supported over the additive model for explaining variation in species richness
(L = 0.31, df = 2, P = 0.86), and effect of delayed year on species richness was
equivocal (β = 0.25, SE = 0.15, P = 0.084).
Monthly abundance. We detected a positive response of abundance to delayed
drawdowns for Least Sandpiper, Greater Yellowlegs, Pectoral Sandpiper, and Spotted
Sandpiper, but not for Solitary Sandpiper, Lesser Yellowlegs, or Semipalmated
Sandpiper. The interaction model was better supported than the additive model for
explaining differences in total monthly counts only of Least Sandpiper (L = 7.37,
df = 2, P = 0.025). For this species, there was no overall effect of delayed year on
monthly counts (β = 0.26, SE = 0.89, P = 0.77), although there was a significant
positive interaction with delayed year during August (β = 2.44, SE = 1.12, P =
0.029) but not July (β = -0.28, SE = 1.11, P = 0.80). Thus, abundance of Least
Sandpiper generally decreased from May through August, except in August during
delayed years due to the positive interaction. There was a positive effect of delayed
year overall for Greater Yellowlegs (β = 1.35, SE = 0.66, P =0.039), Pectoral (β =
1.99, SE = 0.47, P < 0.001), and Spotted (β = 1.04, SE = 0.37, P = 0.005) Sandpipers.
There was no effect of delayed year on monthly counts for Solitary Sandpiper
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K.C. Newcomb, A.P. Monroe, J.B. Davis, and M.J. Gray
2014 Vol. 13, No. 4
(β = 0.58, SE = 0.45, P = 0.19), Lesser Yellowlegs (β = 0.43, SE = 0.69, P = 0.53),
or Semipalmated Plover (β = -0.94, SE = 0.75, P = 0.21).
Discussion
Mudflats associated with river systems are important sites for migratory waterbirds
(Minser et al. 2011, Smith 2006, Taylor et al. 1993). During our study, we
observed 50% of the shorebird species that breed in North America (Morrison et al.
2006). Moreover, species richness at DRU in 2010 was comparable to that of other
studies on migrating shorebirds in the TRV, the MAV, and other interior stopover
areas (Andrei et al. 2006, 2009; Davis and Smith 1998; Laux 2008; Lehnen and
Krementz 2013; Ranalli and Ritchison 2012; Short 1999; Twedt et al. 1998; Wirwa
2009). However, under typical schemes for water management, mudflat availability
in these systems may not coincide with the onset of fall migration of shorebirds (i.e.,
end of June–August). We found that shorebirds foraged in wetlands consistently
throughout summer 2010—a year with delayed drawdowns—and intermediate- and
long-distance migrants spent more time on foraging than short-distance migrants. In
addition, ISS data indicated that 4 out of 7 species’ abundances responded positively
to delayed drawdowns. Thus, we believe our results support the need for greater provisioning
of habitat for migrating shorebirds throughout summer in the TRV.
Species richness and total abundance did not differ statistically among months
in our 2010 surveys, which may reflect the consistent availability of mudflats and
thus presence of shorebirds in our study area during delayed drawdowns. Differences
in migration phenology among species and migration periods (i.e., spring vs.
fall) also could have led to these findings. For example, greater abundance of Least
Sandpiper in July and August versus June may have resulted from peak migration
earlier in spring and later in fall, while Killdeer, Semipalmated Sandpiper, and
Pectoral Sandpiper may persist in relatively high numbers at migration stopoverareas
through the end of spring migration and onset of fall migration. At DRU,
northbound shorebirds were observed into the first 2 weeks of June, followed by
approximately 2 weeks of only resident waterbirds; southbound shorebirds may
arrive as early as the last week of June (Nebel and Cooper 2008, Parmelee 1992).
Killdeer regularly nest at DRU during the summer, so their presence throughout the
summer was expected.
Results from our analyses of ISS data indicated an increase in overall monthly
counts during years with delayed drawdowns for intermediate- and long-distance
migrants such as Pectoral Sandpiper, Spotted Sandpiper, and Greater Yellowlegs, as
well as Least Sandpiper in August. Though we did not detect a difference between
species richness in years with and without delayed drawdowns, some shorebird species
were observed only during delayed years, including American Golden-Plover,
Baird’s Sandpiper, Himantopus mexicanus (Müller) (Black-necked Stilt), Limosa
fedoa (Marbled Godwit), Bartramia longicauda (Bechstein) (Upland Sandpiper),
White-rumped Sandpiper, and T. semipalmata (Willet). Conversely, no shorebird
species were observed only during typical years. These findings suggest delayed
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2014 Vol. 13, No. 4
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drawdowns may have some positive influence on species richness and abundance,
and management that mimics these flood events by implementing drawdowns
through summer may provide important stopover habitat for shorebirds when most
mudflats in the Kentucky Reservoir and elsewhere in the TRV still are inundated.
Additionally, shorebirds that initially use habitats opportunistically may develop
site fidelity pending somewhat predictable wetland availability (Skagen and Knopf
1994). In contrast to habitat along coastal migration routes, interior habitat for
shorebirds is highly variable; thus, consistent availability in managed moist-soil areas
may mitigate losses of other shorebird habitats (e.g., aquaculture ponds) within
this region (Lehnen and Krementz 2013).
Migration is an energetically taxing activity, and fat reserves are essential fuel
for survival during migration and at stopover locations (Skagen 2006). Years with
increased precipitation can create favorable environmental conditions at stopover
locations, which in turn can increase the amount of fat reserves accumulated by
shorebirds (Davis et al. 2005, Farmer and Wiens 1999, Krapu et al. 2006, Skagen
2006). This response could be attributed to increased area of mudflats and shallowly
flooded (less than 5 cm) wetlands and an increased abundance of invertebrates which
may be available during drawdowns (Lehnen and Krementz 2013, Roshier et al.
2002, Skagen and Knopf 1994). Foraging was the predominant activity observed
during delayed drawdowns on DRU in summer 2010. Furthermore, intermediateand
long-distance migrants, such as Semipalmated and Pectoral Sandpipers, spent
more time foraging than short-distance migrants, such as Killdeer, in all months.
However, intermediate-distance migrants spent the greatest amount of time foraging
in July, and short- and long-distance migrants foraged consistently during all
months. These results are likely due to differences in energetic requirements for
migration, as well as a reflection of dif ferent foraging strategies.
The practice of moist-soil management in wetland impoundments to satisfy the
needs of wetland-dependent birds and other wildlife is common on many state and
federal wetland areas (Colwell and Taft 2000, Fredrickson and Taylor 1982, Loesch
et al. 2000, Low and Bellrose 1944, Taft et al. 2002, TNWR 2010). These deliberate
management practices provide stopover habitat for migrating shorebirds in spring
and fall (Colwell and Taft 2000, Fredrickson and Taylor 1982, Loesch et al. 2000,
Taft et al. 2002). The delayed drawdowns in 2010 were made possible in large part
by supplemental funding after the Deepwater Horizon oil spill; thus, it may not
be economically feasible to conduct drawdowns to that extent under normal budget
constraints. However, we observed a positive response by shorebirds during
other years with delayed drawdowns. Because monthly abundances were generally
greater with delayed drawdowns and some species were only observed during those
years, we recommend using water management to mimic flood pulses in July and
August on sites designated as mudflats for migrating shorebirds.
Specifically, and where feasible in the TRV, resource managers might consider
draining at least one impoundment beginning in early July to benefit fall-migrating
shorebirds. Drawdowns should incrementally expose mudflats by decreasing water
Southeastern Naturalist
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2014 Vol. 13, No. 4
levels at a rate of approximately 2–3 cm per week (Fredrickson and Taylor 1982,
Hands et al. 1991, Laux 2008, Rundle and Fredrickson 1981). This management
strategy is beneficial because it 1) provides shorebirds with foraging opportunities
in impoundment mudflats; 2) benefits locally breeding rails, shorebirds, and wading
birds; and 3) provides ideal substrates for germination of moist-soil plants (Fredrickson
and Taylor 1982, Kross et al. 2008, Laux 2008, Wirwa 2009). If all contours
in an impoundment were exposed by early August, sufficient time would remain
during the growing season for some desirable moist-soil plants to mature (i.e., 60
days), which in turn would provide important habitat for migrating and wintering
waterfowl when re-flooded in fall (Fredrickson and Taylor 1982). Moreover, this
strategy could help mitigate effects of delayed exposure of mudflats in reservoirs
throughout the TRV, like Kentucky Reservoir, where mudflats are not exposed until
mid-August (Wirwa 2009).
Finally, we observed more shorebird species in 2010 (n = 26) than were observed
on ISS surveys (n = 9–21), and the 5 species unique to our observations in
2010 included 2 of conservation concern, Piping Plover and Buff-breasted Sandpiper
(Table 1). During our intensive surveys in 2010, we observed several species
(i.e., Buff-breasted Sandpiper, Marbled Godwit, Piping Plover, Calidris alba
[Sanderling], Willet, and Wilson’s Phalarope) ≤10 days before their departure from
DRU. Because we only collected data for a single year, we cannot unequivocally
conclude whether these specific observations resulted from delayed drawdowns,
inter-year variability, or survey design. However, it is possible that some of these
species were missed on traditional ISS surveys due to differences in survey sites
and frequency; thus, use of current methods may result in underestimates of the
relative importance of some areas to intermediate- and long-distance migrants.
Resource managers could consider conducting ISS surveys in this region more
frequently than the every-10 day interval prescribed by ISS protocol. However, we
advocate additional study and cost-benefit analyses to determine feasibility of increased
number of surveys relative to desired outcomes prior to implementing any
changes in protocol.
Acknowledgments
Funding for this research was provided by the US Fish and Wildlife Service and the
University of Tennessee Institute of Agriculture, Knoxville, TN. We thank TNWR staff,
especially J. Taylor, R. Wheat, and T. Littrell for supporting and facilitating this research.
D. Zabriskie, D. Gaskin, E. Gaskin, M. Hottes, and M. Heck provided critical logistic assistance.
We are especially grateful to C. Ferrell for answering questions, gathering data,
conducting ISS surveys, and sharing his enthusiasm for waterbirds. We thank R. Perry, D.
Krementz, and one anonymous reviewer for improving this manuscript. Our manuscript has
been approved for publication as FWRC-WFA manuscript WF365.
Literature Cited
Andrei, A.E., L.M. Smith, D.A. Haukos, J.G. Surles, and W.P. Johnson. 2009. Foraging
ecology of migrant shorebirds in saline lakes of the Southern Great Plains. Waterbirds
32:138–148.
Southeastern Naturalist
K.C. Newcomb, A.P. Monroe, J.B. Davis, and M.J. Gray
2014 Vol. 13, No. 4
758
Andrei, A.E., L.M. Smith, D.A. Haukos, and J.G. Surles. 2006. Community composition
and migration chronology of shorebirds using the saline lakes of the Southern Great
Plains, USA. Journal of Field Ornithology 77:372–383.
Andrei, A.E., L.M. Smith, D.A. Haukos, and W.P. Johnson. 2007. Behavior of migrant
shorebirds in saline lakes of the Southern Great Plains. Waterbirds 30:326–334.
Andrei, A.E., L.M. Smith, D.A. Haukos, and J.G. Surles. 2008. Habitat use by migrant
shorebirds in saline lakes of the Southern Great Plains. Journal of Wildlife Management
72:246–253.
Bart, J., S. Brown, B. Harrington, and R.I.G. Morrison. 2007. Survey trends of North
American shorebirds: Population declines or shifting distributions? Journal of Avian
Biology 38:73–82.
Bates, D., M. Maechler, B. Bolker, and S. Walker. 2013. Lme4: Linear mixed-effects models
using Eigen and S4. R package version 1.0-4. Available online at http://CRAN.Rproject.
org/package=lme4. Accessed 1 October 2013.
Bolker, B., H. Skaug, A. Magnusson, and A. Nielsen. 2013. Getting started with the
glmmADMB package. Available online at https://r-forge.r-project.org/scm/viewvc.
php/*checkout*/pkg/inst/doc/glmmADMB.pdf?root=glmmadmb. Accessed 1 October
2013.
Brown, S., C. Hickey, B. Harrington, and R. Gill (Eds.) 2001. US shorebird conservation
plan, 2nd Edition. Manomet Center for Conservation Sciences, Manomet, MA. Available
online at http://www.fws.gov/shorebirdplan/USShorebird/PlanDocuments.htm.
Accessed 1 September 2011.
Chesser, R.T., R.C. Banks, F.K. Barker, C. Cicero, J.L. Dunn, A.W. Kratter, I.J. Lovette,
P.C. Rasmussen, J.V. Remsen, J.D. Rising, D.F. Stotz, and K. Winker. 2013. Fifty-fourth
supplement to the American Ornithologists’ Union check-list of North American Birds.
Auk 130:558–571.
Colwell, M.A., and O.W. Taft. 2000. Waterbird communities in managed wetlands of varying
water depth. Waterbirds 23:45–55.
Corn, M.L., and C. Copeland. 2010. The Deepwater Horizon oil spill: Coastal wetland and
wildlife impacts and response. Report to the Congressional Research Service, Washington,
DC. 7-5700. 25 pp.
Crawley, M.J. 2013. The R Book, Second Edition. Wiley, West Sussex, UK. 1051 pp.
Davis, C.A., and L.M. Smith. 1998. Behavior of migrant shorebirds in playas of the Southern
High Plains, Texas. Condor 100:266–276.
Davis, C.A., L.M. Smith, and W.C. Conway. 2005. Lipid reserves of migrant shorebirds
during spring in playas of the Southern Great Plains. Condor 10 7:457–462.
De Leon, M.T., and L.M. Smith. 1999. Behavior of migrating shorebirds at North Dakota
prairie potholes. Condor 101:645–654.
Farmer, A., and F. Durbian. 2006. Estimating shorebird numbers at migration stopoversites.
Condor 108:792–807.
Farmer, A.H., and J.A. Wiens. 1999. Models and reality: Time–energy trade-offs in Pectoral
Sandpiper (Calidris melanotos) migration. Ecology 80:2566–2580.
Fitzpatrick, S., and B. Bouchez. 1998. Effects of recreational disturbance on the foraging
behavior of waders on a rocky beach. Bird Study 45:157–171.
Fornier, D.A., H.J. Skaug, J. Ancheta, J. Ianelli, A. Magnusson, M. Maunder, A. Nielsen,
and J. Sibert. 2012. AD Model-Builder: Using automatic differentiation for statistical
inference of highly parameterized complex nonlinear models. Optimization Methods
and Software 27:233–249.
Southeastern Naturalist
759
K.C. Newcomb, A.P. Monroe, J.B. Davis, and M.J. Gray
2014 Vol. 13, No. 4
Fredrickson, L.H., and T.S. Taylor. 1982. Management of seasonally flooded impoundments
for wildlife. US Fish and Wildlife Service resource publication 148, Washington, DC.
Available online at http://www.dtic.mil/cgi-bin/GetTRDoc?AD=ADA323232. Accessed
8 August 2012.
Hands, H.M., M.R. Ryan, and J.W. Smith. 1991. Migrant shorebird use of marsh, moist-soil,
and flooded agricultural habitats. Wildlife Society Bulletin 19:457–464.
Krapu, G.L., J.L. Eldridge, C.L. Gratto-Trevor, and D.A. Buhl. 2006. Fat dynamics
of Arctic-nesting sandpipers during spring in mid-continental North America. Auk
123:323–334.
Kross, J., R.M. Kaminski, K.J. Reinecke, E.J. Penny, and A.T. Pearse. 2008. Moist-soil seed
abundance in managed wetlands in the Mississippi Alluvial Valley. Journal of Wildlife
Management 72:707–714.
Laux, J.W. 2008. Waterbird responses to two east Tennessee River Valley reservoirs. M.Sc.
Thesis. University of Tennessee, Knoxville, TN. 215 pp.
Lehnen, S.E., and D.G. Krementz. 2007. The influence of body condition on the stopover
ecology of Least Sandpipers in the Lower Mississippi Alluvial Valley during fall migration.
Avian Conservation and Ecology 2:9–24.
Lehnen, S.E., and D.G. Krementz. 2013. Use of aquaculture ponds and other habitats by
autumn-migrating shorebirds along the lower Mississippi River. Environmental Management
52:417–426.
Loesch, C.R., D.J. Twedt, K. Tripp, W.C. Hunter, and M.S. Woodrey. 2000. Development
of management objectives for waterfowl and shorebirds in the Mississippi Alluvial Valley.
Lower Mississippi Valley Joint Venture, USDA Forest Service Proceedings RMRSP-
16. Available online at http://www.lmvjv.org/library/research_docs/. Accessed 14
October 2013.
Low, J.B., and F.C. Bellrose. 1944. The seed and vegetative yield of waterfowl food plants
in the Illinois River Valley. Journal of Wildlife Management 8:7–22.
Minser, W.G., M.J. Gray, J.W. Laux, and D.W. Wirwa. 2011. The value of transient
mud: How Tennessee Valley mudflats benefit migratory birds. Wildlife Professional
Spring:35–37.
Morrison, R.I.G., B.J. McCaffery, R.E. Gill, S.K. Skagen, S.L. Jones, G.W. Page, C.L.
Gratto-Trevor, and B.A. Andres. 2006. Population estimates of North American shorebirds.
Wader Study Group Bulletin 111:67–85.
Myers, J.P. 1983. Conservation of migrating shorebirds: Staging areas, geographical bottlenecks
and regional movements. American Birds 37:23–25.
Natural Resources Conservation Service (NRCS). 2012. 2012 Migratory Bird Habitat Initiative
(MBHI). Available online at http://www.la.nrcs.usda.gov/programs/MBHI/index.
html. Accessed 15 August 2012.
Nebel, S., and J.M. Cooper. 2008. Least Sandpiper (Calidris minutilla). Number 115, In A.
Poole (Ed.). The Birds of North America Online. Cornell Lab of Ornithology, Ithaca,
NY. Available online athttp://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/
115. Accessed 7 July 2014.
Parmelee, D.F. 1992. White-rumped Sandpiper (Calidris fuscicollis). Number 29, In A.
Poole (Ed.). The Birds of North America Online. Cornell Lab of Ornithology, Ithaca,
NY. Available online at http://bna.birds.cornell.edu.bnaproxy.birds.cornell.edu/bna/species/
029. Accessed 7 July 2014.
Pinheiro, J., S. Debroy, and D. Sarkar. 2013. Nlme: Linear and nonlinear mixed-effects
models. R package version 3.1-113. Available online at http://cran.r-project.org/web/
packages/nlme/index.html. Accessed 2 November 2013.
Southeastern Naturalist
K.C. Newcomb, A.P. Monroe, J.B. Davis, and M.J. Gray
2014 Vol. 13, No. 4
760
R Development Core Team. 2013. R: A language and environment for statistical computing.
R Foundation for Statistical Computing, Vienna, Austria. Version 3.0.2. Available online
at http://www.R-project.org/. Accessed 7 September 2013.
Ranalli, N., and G. Ritchison. 2012. Phenology of shorebird migration in western Kentucky.
Southeastern Naturalist 11:99–110.
Roshier, D.A., A.I. Robertson, and R.T. Kingsford. 2002. Responses of waterbirds to flooding
in an arid region of Australia and implications for conservation. Biological Conservation
106:399–411.
Rundle, W.D., and L.H. Fredrickson. 1981. Managing seasonally flooded impoundments for
migrant rails and shorebirds. Wildlife Society Bulletin 9:80–87.
Scheiman, D. 2007. Arkansas waterbirds on working-lands initiative. Audubon Arkansas
Technical Report, Little Rock, AR. 70 pp.
Schmidt, S. 2010. International Shorebird Surveys and Program for Regional and International
Shorebird Monitoring protocol. Manomet Center for Conservation Sciences,
Manomet, MA. Available online at https://www.manomet.org/issprism-protocolsforms-
and-data-submission. Accessed 21 June 2013.
Short, M.R. 1999. Shorebirds in western Tennessee: Migration ecology and evaluation
of management effectiveness. M.Sc. Thesis. University of Tennessee, Knoxville, TN.
145 pp.
Skagen, S.K. 2006. Migration stopovers and the conservation of arctic-breeding Calidridine
sandpipers. Auk 123:313–322.
Skagen, S.K., and F.L. Knopf. 1993. Toward conservation of midcontinental shorebird migrations.
Conservation Biology 7:533–541.
Skagen, S.K., and F.L. Knopf. 1994. Migrating shorebirds and habitat dynamics at a prairiewetland
complex. Wilson Bulletin 106:91–105.
Skagen, S.K., P.B. Sharpe, R.G. Waltermire, and M.B. Dillon. 1999. Biogeographical profiles
of shorebird migration in midcontinental North America. US Geological Survey
Biological Science Report 2000-0003, Denver, CO. Available online at http://www.fort.
usgs.gov/shorebirds. Accessed 31 August 2012.
Skaug, H., D. Fournier, A. Nielsen, A. Magnusson, and B. Bolker. 2013. Generalized linear
mixed models using AD Model Builder. R package version 0.7.7. Available online at
http://glmmadmb.r-forge.r-project.org. Accessed 3 October 2013.
Smith, M.D. 2006. Spatiotemporal modeling of shorebird habitat availability at Rankin
Wildlife Management Area, Tennessee. M.Sc. Thesis. University of Tennessee, Knoxville,
TN. 82 pp.
Taft, O.W., M.A. Colwell, C.R. Isola, and R.J. Safran. 2002. Waterbird response to experimental
drawdown: Implications for the multispecies management of wetland mosaics.
Journal of Applied Ecology 39:987–1001.
Taylor, D.M., C.H. Trost, and B. Jamison. 1993. Migrant shorebird habitat use and the
influence of water level at American Falls Reservoir, Idaho. Northwestern Naturalist
74:33–40.
Tennessee National Wildlife Refuge (TNWR). 2010. Comprehensive conservation plan. US
Fish and Wildlife Service, Paris, TN. Available online at http://www.fws.gov/southeast/
planning/PDFdocuments/TennesseeFinal/Tennessee%20NWR%20Final%20CCP.pdf.
Accessed 1 October 2013.
Tennessee Valley Authority (TVA). 2004. Final programmatic environmental impact statement:
Tennessee Valley Authority reservoir operations study. Federal Register 69:105.
Twedt, D.J. 2013. Foraging habitat for shorebirds in southeastern Missouri and its predicted
future availability. Wetlands 33:667–678.
Southeastern Naturalist
761
K.C. Newcomb, A.P. Monroe, J.B. Davis, and M.J. Gray
2014 Vol. 13, No. 4
Twedt, D.J., C.O. Nelms, V.E. Rettig, and S.R. Aycock. 1998. Shorebird use of managed
wetlands in the Mississippi Alluvial Valley. American Midland Naturalist 140:140–152.
Webb, E.B., L.M. Smith, M.P. Vrtiska, and T.G. Lagrange. 2010. Effects of local and landscape
variables on wetland-bird habitat-use during migration through the Rainwater
Basin. Journal of Wildlife Management 74:109–119.
Wirwa, D.W. 2009. Waterbird use of Kentucky Reservoir mudflats. M.Sc. Thesis. University
of Tennessee, Knoxville, TN. 157 pp.
Zuur, A.F., E.N. Ieno, N.J. Walker, A.A. Saveliev, and G.M. Smith. 2009. Mixed-Effects
Models and Extensions in Ecology with R. Springer , New York, NY. 574 pp.
Zuur, A.F., A.A. Saveliev, and E.N. Ieno. 2012. Zero-Inflated Models and Generalized Linear
Mixed Models with R. Highland Statistics Ltd., Newbur gh, UK. 336 pp.