Associations Between Two Bottomland Hardwood Forest Shrew Species and Hurricane-Generated Woody Debris
R. Brandon Cromer, Charles A. Gresham, Megan Goddard, J. Drew Landham, and Hugh G. Hanlin
Southeastern Naturalist, Volume 6, Number 2 (2007): 235–246
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2007 SOUTHEASTERN NATURALIST 6(2):235–246
Associations Between Two Bottomland Hardwood Forest
Shrew Species and Hurricane-Generated Woody Debris
R. Brandon Cromer1,*, Charles A. Gresham2, Megan Goddard3,
J. Drew Landham4, and Hugh G. Hanlin5
Abstract - We investigated associations between soricids and coarse woody debris
(CWD) in bottomland hardwood forests impacted by Hurricane Hugo. The objectives
were to evaluate CWD loadings at three forests disturbed by Hurricane Hugo,
monitor soricid captures at these forests, and identify habitat associates of soricids.
Pitfall traps were used to sample soricids from January 2002–December 2003, and
habitat parameters (CWD, vegetation, soils, and microsite) surrounding pitfalls were
sampled. We found CWD volume was significantly higher at study sites that experienced
highest hurricane wind speeds. Captures of soricids were highest in forests
with high CWD loadings, and regression models associated soricids with log cover
and CWD volume. Sorex longirostris (southeastern shrew) was associated with logs
in an advanced state of decay and woody litter. Blarina carolinensis (southern shorttailed
shrew)was associated with log cover and leaf-litter cover. Soricid captures also
increased with close proximity of CWD. We found that major disturbances have a
lasting influence on bottomland hardwood communities, and forests with high loadings
of deteriorating CWD provide habitat for S. longirostris and B. carolinensis.
Introduction
Bottomland hardwood forests (BHF) occur along stream and river floodplains
on the coastal plain of the southern Atlantic and Gulf Coast states. The
state of South Carolina contains an estimated 2.9 million hectares of BHF
(Brown 1997). The flat topography makes these areas subject to seasonal
flooding (Hupp 2000). Bottomland forests serve to filter sediments and
nutrients from floodwater and provide habitat for invertebrates, fish,
herpetofauna, mammals, and birds (Antrobus et al. 2000, Burdick et al. 1989,
Howard and Allen 1988, Lockaby and Walbridge 1998, Madison 1997).
Because of their proximity to the Atlantic Ocean and Gulf of Mexico,
coastal plain forests of the southeast are threatened by hurricanes. In September,
1989, the category-four storm named Hurricane Hugo made landfall
near Charleston, SC, with maximum sustained wind speeds of 217 km/h
1Department of Mathematics and Science, 634 Henderson Street, Mount Olive College,
Mount Olive, NC 28365. 2Department of Forestry and Natural Resources,
Clemson University, Baruch Institute of Coastal Ecology and Forest Science, PO
Box 596, Georgetown, SC 29442-0596. 3Department of Forestry and Natural Resources,
261 Lehotsky Hall, Clemson University, Clemson, SC 29634. 4Department
of Forestry and Natural Resources, 234 Lehotsky Hall, Clemson University,
Clemson, SC 29634. 5Department of Biology and Geology, 171 University Parkway,
University of South Carolina Aiken, Aiken, SC 29801. *Corresponding author -
rcromer@moc.edu.
236 Southeastern Naturalist Vol. 6, No. 2
(Brennan 1991, Purvis 1996). Approximately 50,000 ha of floodplain forests
were impacted (Hook et al. 1996, Sheffield and Thompson 1992). In the
months after the storm, public and private land managers salvaged an estimated
15% of downed woody debris, but much of the remaining debris was
left to decay on the forest floor (Lupold 1996).
Coarse woody debris (CWD) is any standing or fallen dead woody
material greater than 7.5 cm in diameter (Harmon et al. 1986). Decomposition
of CWD can vary with size and environmental conditions (Van Lear
1993) and therefore has the potential to persist for long periods of time
(Harmon and Hua 1991). Standard CWD loadings for BLH forests range
from 11.5 to 18.75 m3/ha (Brinson and Rheinhardt 1998, McMinn and Hardt
1993); however, these levels can greatly increase following a major storm.
Coarse woody debris in ecosystems is important to nutrient cycling, moisture
retention, erosion reduction, and wildlife cover (Hagan and Grove
1999). Woody cover can provide habitat for many species of invertebrates
and vertebrates (Caldwell 1993, Hendrix 1993, McCay 2000). Small mammals
have strong associations with CWD (Barnum et al. 1992, Loeb 1999).
Soricids are subject to predation; therefore, they are typically secretive and
rely on forest floor substrate (i.e., CWD) and underground tunnels for
security (Hartman et al. 2001, Loeb 1999, McCay and Komoroski 2003,
McCay et al. 1998).
We investigated the association between soricids and CWD generated by
Hurricane Hugo by evaluating bottomland forests of different disturbance
levels. We chose to work with two common southeastern soricid species,
Sorex longigrostris Bachman (southeastern shrew) and Blarina carolinensis
Bachman (southern short-tailed shrew), because some studies have linked
these species to woody debris (Loeb 1999, McCay and Komoroski 2003,
Whittaker and Feldhamer 2005). However, other studies have found no clear
relationship (Mengak and Guynn 2003).
The objectives of our study were: to determine differences in CWD
volume and size distribution among forests with different levels (high intensity,
moderate intensity, and low intensity) of hurricane damage; to monitor
shrew communities (species composition and capture patterns) in relation to
CWD characteristics in hurricane impacted sites; and to develop statistical
models predicting shrew occurrence in relation to CWD occurrence.
Methods
Study areas
Research was conducted at three study areas located within the Lower
and Upper Coastal Plain physiographical provinces of South Carolina: the
Santee Experimental Forest (SEF), Francis Beidler Forest, and Congaree
National Park (CNP). These sites were chosen for three primary reasons: all
sites were impacted by Hurricane Hugo, all sites contained substantial acreage
of BLH, and none of the downed timber was salvaged. In addition, all
sites had similar vegetative composition and hydrology.
2007 R.B. Cromer, C.A. Gresham, M. Goddard, J.D. Landham, and H.G. Hanlin 237
The SEF (2468 ha) is part of the Francis Marion National Forest (FMNF)
within Berkeley County, SC. Plots (n = 4) were established within a BLH
forest adjacent to Nicholson Creek. Soils of this site (Typic Paleaquults)
were poorly drained and subject to seasonal flooding (USDA 1980). The
SEF sustained maximum sustained winds of 217 km/h from Hurricane Hugo,
and nearly 80% of the trees were destroyed (Brennan 1991, Hook et al.
1996). The SEF served as our most heavily impacted site.
Beidler Forest, a National Audubon Society sanctuary, consists of 2400
ha of old-growth floodplain forests (Brunswig and Winton 1978). The forest
lies in Four Holes Swamp, approximately 80 km from the Atlantic Ocean.
Plots (n = 4) were established in BLH communities with poorly drained soils
(Typic Albaqualfs) subject to flooding (USDA 1980, 1990). Sustained hurricane
winds at Beidler Forest were measured at 160 km/h, damaging an
estimated 64% of BLH trees (Brown 1996, Duever and McCollum 1992,
Duever and McCollum 1996, Purvis et al. 1990). Beidler Forest served as
our site of intermediate disturbance.
Congaree National Park is an old-growth floodplain forest maintained by
the United States National Park Service. The 8988-ha park lies in the upper
coastal plain of South Carolina on the floodplain of the Congaree River,
approximately 160 km from the South Carolina coast. Plots (n = 3) were
established in bottomland sites with well-to moderately well-drained, alluvial
soils (Oxyaquic Udifluvents; USDA 1979). Sustained wind speeds
reached 116 km/h, and damage was estimated at 37% (Putz and Sharitz
1996). Congaree National Park served as our site of low disturbance.
Data were collected at eleven 20-m x 100-m (0.20-ha) research plots. A
100-m transect was placed down the center of each plot. Circular subplots
(n = 21, radius = 3.0 m) were established along the central transect at 5-m
intervals. Pitfall trapping, CWD, vegetation, environmental, and microsite
data were collected within each subplot (Table 1).
Soricids were sampled by use of pitfall traps installed at the center of each
subplot (Corn and Bury 1990). Plastic buckets with lids (diameter = 25 cm,
depth = 45 cm) were placed within 1 m of each subplot. Traps were opened in
the spring, summer, and fall of the years 2002–2003 and were closed when not
in use. Traps were checked for captures on a daily basis, and sponges were
placed in each trap for moisture retention during dry periods or flotation
“rafts” for shrews during wet periods. Shrews captured alive were released onsite,
and dead specimens were collected. All research was conducted within
the guidelines of the Clemson University Animal Use Permit # 00-087.
Coarse woody debris (m3/ha) was measured using the planar intersect
method (Van Wagner 1968; Table 1). Two 2-m transects extending outward
from each pitfall trap were randomly selected from the four cardinal points.
Diameter of CWD (> 7.5 cm) were taken along each transect. Decay class
was determined according to a five-class system, where class-I logs were
solid and bark was intact and class-V logs lack bark and the wood has
become soft and powdery (Spetich et al. 1999). The distance from each
pitfall trap to the nearest log was measured.
238 Southeastern Naturalist Vol. 6, No. 2
Diameter at breast height (dbh) of saplings (2.5–10 cm dbh) and trees
(> 10 cm dbh) was collected to determine basal area (m2/ha) within the 0.20-
ha plot (Table 1). Percent cover of ground vegetation (< 30 cm tall) was
estimated in two 1-m2 plots adjacent to pitfalls (Daubenmire 1959; Table 1).
Seedlings and shrubs (> 30 cm tall and < 2.5 cm dbh) were sampled within
two plots (radius = 1.5 m) adjacent to pitfalls (Table 1). These were identified
to species and placed in three height classes (Table 1). Within each 1.5-
m radius plot, percent cover of the microsite was estimated (Daubenmire
1959; Table 1).
Soil series were determined from the soil survey maps of Berkeley,
Dorchester, and Richland counties (USDA 1979, 1980, 1990). A soil corer
was used to collect samples from the upper and lower depths of the A
horizon. Soil-texture analysis was conducted according to Gee and Bauder
(1986). Soil-carbon analysis was conducted according to Nelson and
Sommers (1996) using a Leco C-144 Carbon Analyzer.
Statistical analysis
All statistical analyses were done by use of SAS Version 9.0 (SAS 2002).
All data sets first were tested for normality using the Shapiro-Wilk test
(Shapiro and Wilk 1965). Data found to not fit the requirements of a normal
distribution were either transformed or analyzed through non-parametric
statistics (Wilcoxon sum rank tests). Non-normal data expressed in
Table 1. Variables collected to quantify habitats at study sites in the Congaree National Park
(CNP) in Richland County, Beidler Forest in Dorchester County, and the Santee Experimental
Forest (SEF) in Berkeley County, SC. CWD decay classes described by Spetich et al. (1999).
Data type Name Description
CWD volume (m3/ha) Class I Bark present, twigs present, wood intact
Class II Bark present, twigs absent, wood intact
Class III Bark absent, twigs absent, wood partially decayed
Class IV Bark absent, twigs absent, wood soft/blocky
Class V Bark absent, twigs absent, wood soft/powdery
All Sum of all CWD volume (m3/ha)
Microsite Bare soil % cover of soil lacking any cover
FWD % cover of woody material < 7.5 cm
Leaf litter % cover of leaf material
Log % cover of woody material > 7.5 cm
Stump % cover of tree stumps
Roots % cover of tree/plant roots
Basal area (m2/ha) Sapling Diameter (dbh.) < 2.5 cm
Canopy Diameter (dbh.) 2.5 to 10.0 cm
Shrub layer 30–100 cm Tally of woody vegetation (30–100 cm tall)
100–150 cm Tally of woody vegetation (100–150 cm tall)
> 150 cm Tally of woody vegetation (> 150 cm tall)
Ground layer Grass % cover of grasses (< 30 cm tall)
Herb % cover of herbs (< 30 cm tall)
Vine % cover of vines (< 30 cm tall)
Woody % cover of woody seedlings (< 30 cm tall)
Shrew captures Soricid species captures
2007 R.B. Cromer, C.A. Gresham, M. Goddard, J.D. Landham, and H.G. Hanlin 239
percentages (plant cover, microsite cover, and soil texture) required arcsine
transformation (Fowler et al. 1998). Multiple comparisons of normalized
data were conducted with analysis of variance (ANOVA). Tukey’s mean
separation test was used to determine differences in treatment levels.
Multiple regression models were created to evaluate the response of
captures to habitat variables at the plot level. Initial tests for collinearity and
explanatory variables were conducted through Pearson’s product-moment
correlation analysis. Forward stepwise regression was conducted with selected
variables admitted to the model at the significance level of P < 0.05. Residual
plots were examined for linearity and outliers. Transformation of variables and
removal of outliers was done on occasion to increase model fitness.
Logistic regression models were used to evaluate shrew captures at
individual traps in relation to habitat variables. The presence or absence of a
capture was used for this procedure. One hundred pitfalls were randomly
chosen for analysis to avoid any trap selection bias. Forward stepwise
regression was conducted with selected variables admitted to the model at
the significance level of P < 0.05. Transformation of variables and removal
of outliers was done on occasion to increase model fitness.
Results
The total volume (m3/ha) of downed coarse woody debris (inclusive of
all decay classes) was significantly highest at the SEF (F = 49.56, P <
0.0001; Table 2). However, CWD volume did not differ between Beidler and
the CNP. Only decay class III differed among study areas (F = 25.11, P =
0.0004; Table 2).
Tree and sapling basal area were significantly different among forests
(F = 54.39, P < 0.0001, F = 4.88; P = 0.0411; Table 2). Wilcoxon sum rank
tests revealed a statistical difference in seedling density (stems/ha) between
forests for the 30–100 cm category (2 = 4.06, P = 0.0238; Table 2). Grass
and woody vegetation cover (< 30 cm in height) both differed significantly
among forests (F = 5.89, P = 0.0036; F = 11.60, P < 0.0001; Table 2).
Only two of six microsite variables differed among forests: leaf-litter
cover and log cover (Table 2). Leaf-litter coverage did not differ between
Beidler Forest and the SEF, but was significantly lower at the CNP (F =
40.45, P < 0.0001). Log coverage was highest at SEF, with no difference
between Beidler Forest and the CNP (F = 34.54, P = 0.0001).
Based on soil texture, CNP and SEF soils were classified as loam soils,
and Beidler Forest soils were classified as sandy loam soils. Analysis of
variance revealed significant differences between several particle size distributions
among forests. Soils at Beidler Forest were significantly higher in
sand content in both upper and lower depths (F = 40.90, P < 0.0001; F =
47.43, P < 0.0001) and carbon in upper and lower depths (F = 5.18, P <
0.0001; F = 2.26, P < 0.0001) than other sites. Soils at the CNP were
significantly higher in silt content than other sites at both upper and lower
depths (F = 49.38, P < 0.0001; F = 32.62, P < 0.0001; respectively).
240 Southeastern Naturalist Vol. 6, No. 2
There were a total of 265 soricids captured and captures were significantly
highest at the SEF (2 = 9.96, P = 0. 0011; Table 2). Southern short-tailed
shrews (n = 199) were more frequently captured at the SEF than in other forests
(2 =7.23, P = 0.0046), but no statistical difference was found in captures of
southeastern shrews (n = 66) (2 = 0.42, P = 0. 6652) (Table 2).
Captures of soricids were significantly highest at category 1 traps (CWD
within 0.5 m) (mean = 53.25, SE = 4.16) but category 2 (0.5–1m: mean = 28.25,
SE = 11.52), category 3 (1–2 m: mean = 34.80, SE = 5.81), and category 4
Table 2. Summary of variables examined at study sites in the Congaree National Park (CNP) in
Richland County, Beidler Forest in Dorchester County, and the Santee Experimental Forest
(SEF) in Berkeley County, SC. Means are presented with S.E., F or 2 statistics, and P-values
from ANOVA and Wilcoxon tests. Values in the same row with different superscripts (x, y, z)
are different at P < 0.05.
Study area
CNP Beidler Forest SEF
Variable Mean S.E. Mean S.E. Mean S.E. F / 2 P-value
CWD Class I 30.96 27.04X 0.00 0.00X 0.37 0.37X 1.88 0.2135
(m3/ha)A Class II 3.96 2.70X 14.36 7.26X 4.95 3.41X 1.21 0.3465
Class III 11.81 4.25X 71.17 25.54X 188.03 10.15Y 25.11 0.0004
Class IV 69.04 37.73X 73.22 19.75X 146.28 25.81X 2.69 0.1275
Class V 35.30 17.74X 34.49 18.79X 36.93 10.86X 0.01 0.9936
All 151.07 4.41X 193.25 7.84X 376.55 25.37Y 49.56 < 0.0001
Microsite Bare soil 10.44 3.67X 3.89 2.20X 6.90 1.85X 1.61 0.2583
(%)A,C FWD 2.59 0.75X 6.63 2.61X 3.29 0.37X 1.31 0.3209
Leaf litter 19.68 3.67X 78.69 3.94Y 68.36 2.71Y 40.45 < 0.0001
Log 2.25 0.75X 8.39 1.29Y 12.83 1.04Z 34.54 0.0001
Stump 0.06 0.00X 0.34 0.11X 0.76 0.35X 1.00 0.4316
Roots 0.57 0.08X 0.06 0.00X 0.38 0.21X 3.20 0.0952
Basal area Sapling 1.38 0.08X 2.15 0.54X 6.48 0.23Y 54.39 < 0.0001
(m2/ha)A Canopy 47.94 4.14X 32.35 9.16XY 19.67 1.11Y 4.88 0.0411
Shrub layerC 30–100 cm 14.85 4.27X 29.73 3.16Y 25.28 2.73Y 4.06 0.0238
100–150 cm 15.25 5.44X 18.88 1.91X 11.07 1.75X 3.25 0.0563
> 150 cm 19.50 4.94X 18.00 2.92X 14.63 2.17X 0.68 0.5150
Ground Grass 11.94 2.92XY 5.27 0.84X 18.39 18.39Y 5.89 0.0036
layerA,C Herb 4.89 1.23X 6.66 1.94X 5.99 0.77X 0.37 0.6905
Vine 4.51 1.03X 4.31 0.41X 8.40 1.53X 2.92 0.0575
Woody 2.62 0.12X 6.66 0.71Y 9.15 0.70Y 11.60 < 0.0001
Shrew Soricids 8.33 2.16X 7.88 1.78X 17.50 1.43Y 9.96 0.0011
capturesB,D B. carolinensis 8.83 2.17X 8.00 2.06X 17.00± 1.49Y 7.23 0.0046
S. longirostris 7.67 4.18X 7.20 2.87X 9.63± 0.94X 0.42 0.6653
AStatistical analysis with ANOVA.
BStatistical analysis with Wilcoxon rank sum test.
CData transformed with arcsine transformation.
DCaptures adjusted compensate for inequalities in trap night and replication number.
2007 R.B. Cromer, C.A. Gresham, M. Goddard, J.D. Landham, and H.G. Hanlin 241
(> 2 m: mean = 37.58, SE = 2.96) traps did not differ (2 = 3.52, P = 0.0412).
Captures of southern short-tailed shrews also followed this trend (2 = 3.69, P =
0.0360). Captures were significantly highest at category 1 traps (mean = 74.08,
SE = 4.25), but category 2 (mean = 41.50, SE = 17.86), 3 (mean = 51.30, SE =
7.08), and category 4 (mean = 50.30, SE = 4.54) traps did not differ.
Habitat relationships
Multiple regression models were created for soricids and for each soricid
species using the mean number of captures per plot. Soricids were positively
associated with log cover (R2 = 0.7276, F = 130.87, P < 0.0001; Table 3). The
southeastern shrew was positively associated with decay class IV CWD (R2 =
0.5491, F = 69.42, P < 0.0001) and woody litter cover (R2 = 0.2934,
F = 104.29, P < 0.0001) (Table 3). The southern short-tailed shrew was
positively associated with log cover (R2 = 0.6101, F = 76.68, P < 0.0001;
Table 3).
Logistic regression models were created for these same taxa at the trap
level to test trap success relative to local features (Table 4). Total CWD
volume was positively associated with soricids ( 2 = 4.66, P = 0.0309). The
southeastern shrew was negatively associated with bare soil (F = 4.45, P =
0.0309), but the southern short-tailed shrew was positively associated with
spatial cover of leaf litter (F = 6.56, P = 0.0104).
Table 3. Multiple regression model fitting taxonomic groupings and species at the plot level for
study sites in the Congaree National Park (CNP) in Richland County, Beidler Forest in
Dorchester County, and the Santee Experimental Forest (SEF) in Berkeley County, SC. Parameter
estimates (Par Est.), standard errors (SE), variable (Partial) R2, model R2, F statistics, and
P-values are provided.
Multiple regression model
Partial Model
Taxa VariableA Par est. SE R2 R2 F P-value
SoricidaeB Log cover 15.05 1.08 0.73 0.96 130.87 < 0.0001
Snag volume 0.07 0.01 0.10 25.92 < 0.0001
Stump cover -43.83 3.89 0.10 54.37 < 0.0001
Sapling BA -2.79 0.53 0.04 37.75 < 0.0001
SQ CWD decay IIC 0.02 0.01 0.01 6.21 0.0165
Sorex longirostris LN CWD decay IVD 1.36 0.08 0.54 0.89 69.42 < 0.0001
Woody litter cover 0.47 0.04 0.29 104.29 < 0.0001
CWD decay VE 0.02 0.00 0.03 22.97 < 0.0001
CWD decay IIC -0.01 0.01 0.01 10.23 0.0023
Blarina carolinensisB LN log cover 1.59 0.28 0.61 0.80 76.68 < 0.0001
LN CWD decay VE 0.15 0.07 0.09 14.29 0.0004
Snag volume 0.01 0.00 0.05 8.79 0.0047
Stump cover -1.52 0.44 0.04 7.75 0.0078
Sapling BA -0.14 0.07 0.02 4.53 0.0387
AVariable entered model at significance level of = 0.05.
BLog of abundance used for better fitting model.
CVolume of decay class-II coarse woody debris.
DVolume of decay class-IV coarse woody debris.
EVolume of decay class-V coarse woody debris.
242 Southeastern Naturalist Vol. 6, No. 2
Discussion
Habitat for soricids in southern BHL forests can be influenced by major
disturbances. Our evaluation of long-term impacts of a major hurricane found
that CWD loadings were highest at the SEF, the bulk of which were class-III
logs—those with little to no bark, a solid interior, and exterior decay. Decomposition
of CWD is dependent on species, stem diameter, moisture, and
climate (Aho 1974, MacMillan 1988, Van Lear 1993). Decomposition tends
to be faster in mesic, warm climates such as the southeastern US (Van Lear
1993). The bulk of CWD generated by Hurricane Hugo still possessed a solid
center; however, the external portions of the logs are in decay.
As logs begin to reach advanced levels of decay, they can provide habitat
for many species of invertebrates and vertebrates (Caldwell 1993, Hendrix
1993, McCay 2000). We consistently found associations between soricids and
CWD. Moreover, there was a strong affinity between soricids and CWD of
advanced decay—probably dating back to Hurricane Hugo. Where CWD
loadings were highest, soricid captures also were greatest. Soricids are insectivorous
and use ground-cover substrate and subsurface refugia to forage for
insects (Ford and Rodrigue 2001, Wilson and Ruff 1999). Soricids are voracious
predators and strongly benefit from the source of insects provided in
areas with high levels of CWD (Carraway et al. 2000).
Noticeable associations were found between habitat parameters and species
of shrews. The association between southeastern shrews and CWD was
expected (Blackburn and Andrews 1992, Loeb 1999), but we also found
southeastern shrews to be strongly associated with decay class-IV logs. Logs
of advanced decay host a wealth of insect species (McCay et al. 1998), a
factor that may have influenced our captures of southeastern shrews. Like
the southeastern shrew, the southern short-tailed shrew has similar lifehistory
connections with CWD, relying on logs for nesting, insect prey, and
protection from predators (Wilson and Ruff 1999). Our model reflects a
strong association between southern short-tailed shrews and CWD, especially
influenced by the spatial coverage of logs.
Captures of soricids were greatest at pitfalls within 0.5 m of CWD,
whereas captures at pitfalls with CWD outside of this range decreased
Table 4. Logistic regression for trap level captures for study sites in the Congaree National Park
(CNP) in Richland County, Beidler Forest in Dorchester County, and the Santee Experimental
Forest (SEF) in Berkeley County, SC. Parameter estimates (Par est.), standard errors (SE),
2statistics, and P-values are provided.
Logistic regression model
Index VariableA Par est. SE 2 P-value
SoricidsB SQRT CWD TotalC 0.93 0.44 4.66 0.0309
S. longirostrisD Bare soil -8.87 4.20 4.45 0.0349
B. carolinensisB Leaf litter cover 14.09 6.08 6.56 0.0104
AVariable entered model at significance level of = 0.05.
BLog of abundance used for better fitting model.
CSquare root of volume of all coarse woody debris.
DSquare root of abundance used for better fitting model.
2007 R.B. Cromer, C.A. Gresham, M. Goddard, J.D. Landham, and H.G. Hanlin 243
significantly. This may indicate that much of the soricid’s activities were
within close proximity to cover items such as logs. Whittaker and Feldhamer
(2005) had more captures of southern short-tailed shrews at traps within
close proximity to log cover. Similar results were recorded by McCay et al.
(1998) with the Sorex fumeus Miller (smoky shrew) in the southern Appalachian
Mountains.
Besides CWD variables, we found other habitat variables to be associated
with the capture of shrews. We found a positive association between southeastern
shrews and leaf litter and a negative association between southern
short-tailed shrews and bare soil. Other research has shown correlations
between litter cover and shrew abundance (Hartman et al. 2001). Whittaker
and Feldhamer (2005) noted that soricids used forest-floor substrates in order
to reduce the risk of predation. Our associations may support those results.
Long-term impacts from Hurricane Hugo are prevalent in the high
loading of CWD, particularly in forests that sustained greater wind damage.
Areas with the greatest CWD loadings contained a substantial amount
of decay class-III and -IV logs. Woody debris of advanced decomposition
was consistently associated with soricid captures. Both the southeastern
and the southern short-tailed shrew appear to be species that have benefited
from the lasting effects of Hurricane Hugo.
Acknowledgments
We thank the Andrew Mellon Foundation for funding this research. We also
thank the US Forest Service, the National Audubon Society, and the US National
Park Service. Carl Trettin, Kep Lagasca, Norm Brunswig, Mike Dawson, Martha
Bogle, and Theresa Yeadnock cooperated with the research and use of facilities. We
also thank E. Harrison, S. Worley, J. Franchini, and J. Clary for conducting field
work. G. Askew, W. Conner, B. Song, T. Williams, L.Roth, C. Lucas, J. Vernon, W.
Inabinette, and S. Knoche at the Baruch Institute of Coastal Ecology provided
support and facilities. We also thank W. Bridges for statistical support.
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