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Predominant use of windthrows by nesting eastern woodrats (Neotoma floridana) in the South Carolina coastal plain.


Use of small mammal sign (e.g., nests, burrows, runways, feces) as an indicator of animal presence or to estimate population density is often cost--and time-effective, but may also be unreliable, resulting in biased estimates (Powell et al., 1994; Van Horne et al., 1997). Woodrats of the genus Neotoma are widely known for their construction of conspicuous houses, made of sticks or other available materials (Wiley, 1980; Hall, 1981). Houses are so widely accepted as an indicator of woodrat presence that house counts have been used to estimate population densities of Neotoma species in the western US (Vogl, 1967; Hammer and Maser, 1973; Sakai and Noon, 1993) and population trends in the endangered Key Largo woodrat (N. floridana smalli; McCleery et al., 2006). However, a few authors caution that house density and other sign may be unreliable for estimating woodrat density (Humphrey, 1988; Fargo and Laudenslayer, 1999). We present evidence for a major revision in our understanding of eastern woodrat (N. floridana) nesting behavior in the US southeastern coastal plain, and show that house counts may be completely unreliable. Eastern woodrats occur throughout the southeastern and south central US (Hall, 1981; Whitaker and Hamilton, 1998). They are habitat generalists, inhabiting rocky bluffs and outcrops, upland woods, swamps and hammocks, dry scrub pine, dense riparian vegetation, marshes, grasslands and abandoned buildings and refuse piles (Goertz, 1970; Wiley, 1980; Webster et al., 1985; Whitaker and Hamilton, 1998). Neotoma floridana is listed as endangered, threatened or species of concern in five states (IL, NC, SC, TN, FL), although recent surveys have not been conducted in states where populations are presumably stable (Monty and Feldhamer, 2002). Edwards and Bradley (2001) recognize two distinct clades of N. floridana: southern (subspecies from MS and SC) and western (subspecies from MO, OK and TX).

Studies of the habitat of the southern clade of Neotoma floridana in the southeastern US coastal plain are sparse. North Carolina populations in Pender County, at the northeastern limit of the species' range, occur in mesic hardwood forests dominated by ground cover (up to 52%) of dwarf palmetto (Sabal minor) (Webster et al., 1987; Wilson, 1999). Webster et al. (1987) suggest that Sabal cover may be an important indicator of N. floridana habitat. In Florida, HaySmith (1995) studied woodrats in three habitats: bottomland hardwood swamps, mesic hammocks with saw palmetto (Serenoa repens), and open understory hammocks. The majority of nests were closely associated with fetterbush (Lyonia lucida). The endangered N. f smalli occurs in tropical hammock forest on Key Largo (Humphrey, 1992; McCleery et al., 2006). Little information exists from the South Carolina coastal plain where woodrats are reported from "wooded swamps" (Chamberlain, 1928).

Literature and field guide descriptions routinely include stick houses as a standard feature of eastern woodrat (Neotoma floridana) nesting behavior (Svihla and Svihla, 1933; Ivey, 1959; Webster et al., 1985; Wilson, 1999; Reid, 2006). Communal latrines nearby with characteristic oval-shaped scat may indicate house occupancy (Webster et al., 1985; Brown, 1997; Whitaker and Hamilton, 1998). Stick houses in Pender County North Carolina occur near the base of oaks (Quercus) or within the multiple trunks of Carolina basswood (Tilia caroliniana) (Wilson, 1999).

A few studies have documented alternative locations for Neotoma floridana nests. Greater than 90% of den sites were underground in north-central Florida (HaySmith, 1995), and there are anecdotal references to underground nest chambers elsewhere (Pearson, 1952; Finley, 1958). Wilson (1999) found a few woodrat nests in the exposed roots of overturned trees in North Carolina; these were regarded as alternative, "non-preferential" sites in an area where stick houses were common. Another anecdotal reference notes occasional N. floridana use of rootmasses in the absence of appropriate materials for building stick houses in east Texas (Schmidly, 1983). Early studies of the Key Largo woodrat (N. f. smalli) suggested near exclusive use of stick houses, although there were reports of some nests in rock piles or crevices, trash piles, underground or in downed trees (Brown, 1978; Hersh, 1981; Barbour and Humphrey, 1982). McCleery et al. (2006) found that N. f smalli currently use garbage and rock piles for most nest sites with smaller numbers located in standing or fallen tree roots, logs or stumps. Yet the implied consensus remains that stick houses predominate and are the "preferred" nest site for eastern woodrats.

Nests appear to be the center of Neotoma floridana activity (HaySmith, 1995), and Fitch and Rainey (1956) found foraging to occur within a short distance (21 m) of the nest using live-trapping techniques. Therefore, characterization of nests sites is crucial to understanding N. floridana ecology. Our objectives were to characterize N. floridana nest sites in the South Carolina coastal plain. In addition to noting nest type by frequency and description, we conducted a microhabitat analysis of N. floridana nest sites in three different habitats, in order to identify microhabitat variables important in nest site selection across habitats. We tested two null hypotheses: no habitat differences among the three study sites, and no differences between N. floridana nest sites and random paired sites within the same habitats. Our design also allowed us to test the hypothesis that Sabal minor is an important woodrat habitat indicator in South Carolina.


In 2001, we began a study of the distribution of Neotoma floridana in the South Carolina Coastal Plain; this species was chosen by the Francis Marion National Forest (FMNF) as a Management Indicator Species of fire-maintained ecotonal habitat between bottomland hardwood and upland pine forest. Only three prior records existed of N. floridana from the FMNF in the South Carolina Heritage database (Francis Marion and Sumter National Forests, 2002). Field procedures followed guidelines established by the American Society of Mammalogists Animal Care and Use Committee (Gannon et al., 2007), and were conducted under Francis Marion University IACUC protocol number 007.

We surveyed three study sites, each a different forest type, in the South Carolina coastal plain intermittently from Mar. 2001 to Jun. 2006: (1) A mature southern mixed hardwood forest on the Francis Marion University campus (Florence County; 34[degrees] 11'N, 79[degrees] 38'W), characterized by mixed oak (Quercus spp.), sweet gum (Liquidambar styraciflua), red maple (Acer rubrum), American holly (Ilex opaca), and occasional loblolly pine (Pinus taeda). (2) A bottomland hardwood-upland pine ecotone along Wambaw Creek in FMNF (Charleston County; 33[degrees] 10'N, 79[degrees] 29'W) where bottomland cypress (Taxodium distichum)-tupelo (Nyssa aquatica) forest gives way abruptly to upland pine flatwoods (P. taeda with occasional P. palustris) that undergo prescribed burns. (3) A disturbed maritime forest along Forest Road 5146, also in FMNF (Charleston County; 33[degrees] 1'N, 79[degrees] 35'W) characterized by laurel, water and live oaks (Q. laurifolia, Q. nigra, Q. virginiana), with scattered loblolly pines. The understory and midstory are dominated by yaupon holly (Ilex vomitoria) and oak saplings. Hurricane Hugo heavily impacted habitats (1) and (3) in 1989 and habitat (2) features a high concentration of windthrown trees along the ecotone.

We conducted trapping surveys with Tomahawk No. 201 live traps (Tomahawk Live Trap Co., Tomahawk, Wisconsin) baited with commercial rabbit food and sliced apples. Traps were checked daily starting at sunrise; sex, age class and reproductive condition were noted for each capture. Animals were not marked since we were simply confirming active nests. We placed traps on or near coarse woody debris (CWD). Captured animals were released and observed until they reached an obvious nest. Nest sites were easily identified by watching animals disappear inside or under windthrows, CWD or other habitat features. If other potential nest locations existed nearby, they were also trapped. We confirmed nest sites through multiple recaptures at the original sites, and failure to capture woodrats at alternate sites or at paired random sites.

We collected microhabitat data from Aug. 2005-May 2006 from spring through late summer to minimize variation in vegetation cover, using a protocol modified from James and Shugart (1970), Balcom and Yahner (1996), and Castleberry et al. (2002). By this time, some of the earliest documented nests had been abandoned, or the original locations lost; therefore, we focused exclusively on active nests for microhabitat analysis. We identified nests through selective trapping at all habitat features (CWD, rootmasses) known to support nests from our earlier surveys. We collected microhabitat data from each nest site as it was confirmed active, and from paired non-nest sites. Circular plots of 10 m radii were centered on nest sites, and on paired non-nest plots sited in a randomly chosen cardinal direction, 23 m from nest plot centers to avoid overlap (Balcom and Yahner, 1996; Castleberry et al., 2002). For 27 active nests and 27 paired random sites, we measured or calculated 21 microhabitat variables within the circular plots, or within two 20 m x 1 m belt transects aligned with the cardinal directions within each plot (Appendix 1). We collected data from 10 nests each in the southern mixed hardwood forest and the maritime forest, and from 7 nests in the bottomland-upland ecotone. Analyzing nests in each of the three different habitats allowed us to test for microhabitat features that describe nest sites across all habitats. Our protocol allowed an omnibus comparison of multiple microhabitat variables at known nest sites to a random sample of sites available to woodrats within the same environments.


We reduced the number of variables from 22 to 12 (Table 1) using PROC VARCLUST (SAS version 9.1) before running a multivariate test. We tested normality assumptions using Shapiro-Wilks test. NUMHRD, VOLROT, and MEANBA were transformed logarithmically, and DENUND exponentially to meet normality requirements. Assumptions of multivariate analysis (sphericity tests and multivariate normality) were also confirmed. We eliminated NUMSAB (number of Sabal minor plants) from multivariate analysis because it was represented in <20% of all plots (Castleberry et al., 2002). We used multivariate analysis of variance (MANOVA) to test microhabitat differences among habitats, and nest sites vs. random sites. MANOVA tested the fixed effects of habitat, the random effects of nests and random (non-nest) sites and interactions between nest sites and habitats. We considered nest sites to be nested within habitats. We assumed significant differences at P [less than or equal to] 0.05.


We documented a total of 40 active Neotoma floridana nests between 2001 and 2006. The majority of nests (n = 26; 65%) were underneath or inside rootmasses of windthrown hardwood trees (Fig. 1). Adding pine rootmasses accounted for 77.5% (n = 31) of all nests. Nests associated with windthrown resources in any form (rootmasses or downed woody debris; n = 35) accounted for 87.5% of the total. Eight of these showed significant quantities of ejected material, including soil, rotting wood or acorn shells. A minority (12.5%; n = 5) of active nests was associated with readily visible latrines. Only 25% of nests (n = 10) had any sticks or stick piles at or near the nest entrance; of these, 90% (n = 9) had inconspicuous groupings of a few sticks that could easily be overlooked during visual surveys. We observed only two woodrat stick houses during the entire study, both in the maritime forest; of these, only one was occupied. We never observed stick houses anywhere else, despite extensive ground surveys throughout FMNF. Sabal minorwas absent from two of the three habitats surveyed (southern mixed hardwoods and maritime forest).

MANOVA revealed significant differences among the three habitats in ground cover, midstory density, basal area, hardwood CWD and rootmass volume (Table 2). Woodrat nest plots showed significantly lower basal area, and significantly higher volumes of hardwood CWD and rootmasses than non-nest plots (Table 3). There were no significant habitat--nest site interactions.


We reject the null hypotheses. The three habitats studied differ significantly in a number of variables (Table 2). This result merely confirms the fact that Neotama floridana is a habitat generalist in the southeastern coastal plain. Most importantly, we conclude that N. floridana selected nest sites that contained high hardwood CWD and rootmass volume, and that these microhabitat variables characterized woodrat nest sites across all three habitats (Table 3). Lower basal area within nest plots correlated with higher windthrow loading. Dwarf palmetto (Sabal minor), although associated with N. floridana nest sites in southeastern North Carolina (Webster et al., 1987; Wilson, 1999), was not a general predictor of N. floridana habitat in the South Carolina coastal plain. S. minorwas absent from two of the three habitats.

In contrast to the vast majority of the literature, we found that Neotoma floridana predominantly use windthrows for nesting at our study sites in the South Carolina coastal plain--in particular the rootmasses (a.k.a. tipup mounds, root boles, root wads, mound-and-pit/pit-and-mound topography) of downed hardwoods. Use of stick houses as a proxy for population density estimates, as done for some western Neotoma species, would introduce severe bias in the South Carolina coastal plain. In fact, stick structures of any kind were completely absent from two of our three field sites (bottomland-upland ecotone and southern mixed hardwoods), and thus woodrat populations would be entirely missed using house surveys. Our study, along with those of Humphrey (1988) and Fargo and Laudenslayer (1999), further reinforces the idea that caution is needed when using physical structures or sign to estimate population densities--or even presence--of woodrats. Our results support the predominant use of nest sites by eastern woodrats heretofore considered infrequent alternatives. Although Key Largo woodrats may have shifted from building stick houses in mature hammock habitat to nesting in rock and trash piles since the 1970s as a result of habitat loss, McCleery et al. (2006) suspect that woodrats may always have been abundant, but overlooked in young hammock. An important conclusion of our study is that eastern woodrats may regularly inhabit rootmasses, entirely unnoticed in many locations. Perhaps other Neotoma species (and subspecies) use alternative nest sites more frequently than has been assumed.

We observed abundant fine woody debris appropriate for building stick houses at all three of our study sites. The question naturally arises as to why woodrats do not build stick houses in these areas. It may be that above a certain density threshold, rootmasses become preferred nest sites. On the other hand, rootmass distribution is far from uniform in our field sites, and considering the abundance of construction materials, one might still expect to find stick houses where rootmasses occur at low density; yet this was not the case. It is clear that more studies are needed at the landscape level, comparing sites where stick houses are present and absent, to distinguish the factors that determine the balance between stick house construction and use of alternative nest sites.

The fact that only 12.5% of nests were associated with obvious latrines, a commonly noted woodrat indicator, further cautions against the use of fecal sign as an indicator of woodrat presence. Many nests were not associated with visible latrines.

A potential bias in our study involves our determination of nest sites. We analyzed active nests, but the possibility remains that woodrats were also using other sites for nesting, resulting in a bias toward rootmasses and CWD. However, subsequent to our analysis, we conducted extensive grid trapping (640 trap nights among three grids) in the same sites where we analyzed nest microhabitat, and we captured woodrats only at points within 5 m of a rootmass or other CWD feature. In every case, we observed the animals moving into or under these features upon release. These results, in conjunction with the near total absence of stick houses and any microhabitat features that could provide cover for nesting, increase our confidence that woodrats are using rootmasses or CWD for nesting at our sites, and in the appropriateness of our microhabitat analysis protocol. There simply were no other possible locations for woodrat nests other than those we identified through live-trapping and release.

Although the importance of CWD to small mammals is widely recognized, few studies have documented small mammal use of rootmasses. McCay (2000) found that 14% of cotton mice (Peromyscus gossypinus) day refuges occurred under upturned root boles; the majority (69%) occurred in rotting stumps. Greenberg (2002) found white-footed mice (P. leucopus) to use pit and rootmass microsites. Our study strongly suggests that while stick houses remain an important component of eastern woodrat nesting ecology, rootmasses may also be important throughout Neotoma floridana's range (and perhaps for other Neotoma species). We suggest that when present, rootmasses should be surveyed in Neotoma field studies, especially where populations have declined (Monty and Feldhamer, 2002), and even where stick houses are common.


The ecology of windthrow has been studied from a botanical perspective, from large-scale spatial effects (Greenberg and McNab, 1998; Ulanova, 2000), to the effects of correlated microscale pit and mound topography of rootmasses on forest soils, plant diversity and succession (Bormann et al., 1995; Cooper-Ellis et al., 1999; Clinton and Baker, 2000). In addition to implications for Neotoma floridana, our study suggests the need for a closer look at rootmasses, separate from CWD, as an important landscape resource providing habitat heterogeneity and microhabitat resources for animals. In contrast with Pearson (1952) who did not observe any signs of rootmass excavation by woodrats, we found eight nests with ejected soil and other material, from rotting wood to acorn fragments (likely remnants of food caches). Although most rootmasses in our study did not appear to be excavated, woodrats are clearly capable of excavating soil and organic material, which may further modify rootmass structure, benefiting other species. Many other animals, including small mammals, reptiles and amphibians and invertebrates occupy N. magister nests (Merritt, 1987). It seems likely that N. floridana nests receive similar use.

Coarse woody debris is a well-documented forest resource important to many small mammals (Carey and Johnson, 1995; Bowman et al., 2000; Loeb, 1996, 1999). The physical structure of rootmasses is certainly distinct from that of CWD. Their network of roots and soil may provide distinctive tunnels and crevices, with different physical and chemical parameters from CWD and the surrounding soil and litter. Rootmasses may act as thermal, hydric and predation refuges, buffering a distinct community of animals from environmental extremes such as drought and fire. A potentially fruitful hypothesis for future investigation is that rootmasses function as keystone structure (Tews et al., 2004) in forested landscapes. The significance of rootmasses, in addition to standing and downed dead wood, merits a closer look in forest ecosystem structure, function and composition.

Acknowledgments.--R. Mackie of the USDA Sumter and Francis Marion National Forests provided essential coordination and logistical support. We thank M. S. Bunch, M. T. Mengak and W. D. Webster for recommendations on woodrat field research. We received statistical advice from J. E. Baltzell, J. Battacharjee and R. A. Browne; any errors of fact or interpretation remain ours alone. D. Carlson and L. F. Swails assisted with plant identification and other field advice. P. D. Weigl provided insightful comments on the manuscript. Our field assistants included J. Fowler, S. Haertel, J. Krebs, J. Liston, F. Oliver, J. Rhoderick and J. Ulmer. Partial financial support was provided by the Professional Development Committee of Francis Marion University; challenge cost-share agreement 00-CS-11081209029 between the USDA Forest Service and Francis Marion University; and the Visiting Scholar Program at the Baruch Institute.
APPENDIX 1.--Microhabitat variables measured or calculated in 0.0314
ha circular plots centered on Neotoma floridana nest sites, and in
paired random plots

        Variable                               Methods

Canopy cover                     Mean percent canopy cover of all
                                   trees [greater than or equal to] 8
                                   cm dbh and > 2 m high, from 21
                                   sightings through a GRS densiometer
                                   at 2-m intervals along two 20 x 1 m
                                   perpendicular belt transects,
                                   aligned with cardinal directions
Ground cover                     Mean percent cover (same method as
                                   canopy) of all vegetation < 1 m
                                   high and < 8 cm dbh high along belt
Litter cover                     Mean percent cover (same method as
                                   canopy) of dry leaf and twig litter
                                   along belt transects
Midstory density                 Mean density (number/m) of woody
                                   stems > 2 m high and < 8 cm dbh
                                   along belt transects
Understory density               Mean density (number/ M2) of woody
                                   stems 1-2 m high along belt
Total trees                      Mean number of woody stems ? 8 cm dbh
                                   in circular plots
Tree basal area                  Mean basal area ([m.sup.2]/ha) of all
                                   trees in circular plots, calculated
                                   from dbh measurements
Plot mean basal area             Mean basal area/total number of trees
                                   in circular plots
Volume of coarse woody debris    Mean volume ([m.sup.3]) * in circular
  (CWD)                            plots of all CWD pieces [greater
                                   than or equal to] 10 cm diameter at
                                   small end and [greater than or
                                   equal to] 1 m long, up to circular
                                   plot boundary
Volume of hardwood CWD; volume   Mean value in circular plots
  of conifer CWD, number of
  CWD pieces; number of
  hardwood CWD pieces; number
  of conifer CWD pieces;
  number of standing dead
  trees; number of rootmasses;
  number of Sabal minor plants
Standing dead wood basal area    Mean basal area ([m.sup.2]/ha) of all
                                   standing dead snags > 1 m high and
                                   [greater than or equal to] 8 cm dbh
                                   in circular plots
Root mass volume ([m.sup.3])     Mean volume estimated from length,
                                   width and height measurements of
                                   all rootmasses in circular plots
Number of mast producing trees   Mean of Carya, Quercus, Juglans spp.
                                   trees [greater than or equal to] 8
                                   cm dbh in circular plots
Number of hollow logs            Mean number of C"D pieces [greater
                                   than or equal to] 10 cm small end
                                   diameter containing a cavity
                                   [greater than or equal to] 0.5 m
                                   long in circular plots

* CWD cubic volume calculated as [V.sub.m] = [[pi]/8([D.sup.2.sub.s] +
[D.sup.2.sub.L)l/10,000 where [V.sub.m] is volume in cubic meters,
[D.sub.s] the small-end diameter in centimeters, [D.sub.L] the
large-end diameter in centimeters, and l the log length in meters
(Smalian's volume formula; Husch et al., 1972)



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Department of Biology, Francis Marion University, Florence, South Carolina 29501



Department of Biology, The University of Louisiana at Monroe, 71209

(1) Corresponding author: e-mail:; Telephone: 843-661-1408; FAX: 843-6614660
TABLE 1.--Variables derived from cluster analysis (PROC VARCLUST,
SAS v. 9.1; MAXEIGEN = 0.7) for multivariate tests

Code                       Variable

BOLBAS    Standing dead snag basal area ([m.sup.2]/ha)
COVGRD    Ground cover (%)
COVLIT    Litter cover (%)
DENMID    Midstory density (number stems/[m.sup.2])
DENUND    Understory density (number stems/[m.sup.2])
MEANBA    Stand mean basal area (STANBA/no. trees in plot)
NUMHRD    Number hardwood CAT) pieces
NUMSAB    Number Sabal minor plants
STANBA    Stand basal area ([m.sup.2]/ha)
VOLCON    Conifer CWD volume ([m.sup.3]/0.0314 ha)
VOLHRD    Hardwood CWD volume ([m.sup.3]/0.0314 ha)
VOLROT    Rootmass volume ([m.sup.3]/0.0314 ha)

TABLE 2.--Mean values ([+ or -] SE) and MANOVA results for
microhabitat variables showing significant differences between

                            Southern mixed     Bottomland-upland
                          hardwoods (n = 20)   ecotone (n = 14)

Source                       [bar.X] (SE)        [bar.X] (SE)

Ground cover (%)              34.5 (4.24)         69.7 (2.62)
Midstory density (no.         0.62 (0.06)         0.28 (0.06)
Stand basal area             28.05 (3.30)        24.69 (4.25)
Stand mean basal area         1.35 (0.13)         0.75 (0.23)
  (STANBA/no. trees)
Volume hardwood CWT)          2.20 (0.46)         1.26 (0.41)
  ([m.sup.3]/0.0314 ha)
Number hardwood               6.60 (1.03)         4.43 (0.94)
  logs/0.0314 ha
Rootmass volume               9.44 (2.83)         4.09 (1.62)
  ([m.sup.3]/0.0314 ha)

                          Maritime forest
                             (n = 20)

                           [bar.X] (SE)        F        p
                            39.5 (3.11)       9.85   <0.0001
Ground cover (%)            1.51 (0.17)      10.37   <0.0001
Midstory density (no.
  stems/[m.sup.2])         21.50 (1.99)       2.62    0.0355
Stand basal area
  ([m.sup.2]/ha)            0.39 (0.13)       3.49    0.0091
Stand mean basal area
  (STANBA/no. trees)        1.16 (0.33)      10.92   <0.0001
Volume hardwood CWT)
  ([m.sup.3]/0.0314 ha)     2.25 (0.64)       7.44   <0.0001
Number hardwood
  logs/0.0314 ha            5.36 (1.35)      10.38   <0.0001
Rootmass volume
  ([m.sup.3]/0.0314 ha)

TABLE 3.--Mean values ([+ or -] SE) and MANOVA results for microhabitat
variables showing significant differences between nest and random
(non-nest) sites; n = 54

        Source            Nest [bar.X]    Random [bar.X]
                          (SE) (n = 27)   (se) (n = 27)

Stand Basal Area          19.63 (1.66)    29.76 (2.95)
Number hardwood logs/      5.59 (0.64)     3.26 (0.88)
  0.0314 ha
Rootmass volume           11.78 (2.02)     1.30 (0.48)
  ([m.sup.3]/0.0314 ha)
Stand mean basal area      0.85 (0.37)     1.29 (0.67)
  (STANBA/no. trees)
Volume hardwood CWD        2.74 (0.34)     0.40 (0.13)
  ([m.sup.2]/0.0314 ha)

        Source                       F                P

Stand Basal Area                   8.77           0.0046
Number hardwood logs/             12.19            0.001
  0.0314 ha
Rootmass volume                   46.93         <0.0001
  ([m.sup.3]/0.0314 ha)
Stand mean basal area              6.73           0.0123
  (STANBA/no. trees)
Volume hardwood CWD               41.83         <0.0001
  ([m.sup.2]/0.0314 ha)

FIG. 1.--Percentages of 40 South Carolina coastal plain N. floridana
nest locations, by category (n)

Hardwood rootmass (26)         65.0%
Pine rootmass (5)              12.5%
Under rotting log (3)           7.5%
Standing dead tree (2)          5.0%
Hollow base of live tree (1)    2.5%
Hollow hardwood log (1)         2.5%
Underground (1)                 2.5%
Stick house (1)                 2.5%

Note: Table made from pie chart.
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Article Details
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Author:Knowles, Travis W.; Burger, Joseph Robert
Publication:The American Midland Naturalist
Article Type:Report
Geographic Code:1USA
Date:Jul 1, 2008
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