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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. Literature cited Aho, P.E. 1974. Decay. Pp. Q1–Q17, In O.P. Cramer (Ed.). Environmental effects of forest residues management in the Pacific Northwest. USDA Forest Service GTR PNW-24. 6394 pp. Antrobus, T.J., M.P. Guilfoyle, W.C. Barrow, Jr., P.B. Hamel, and J.S. Wakeley. 2000. Bird community composition. Pp. 34–33, In M.K. Burke and M.H. 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