Banner-tailed kangaroo rat burrow mounds and desert grassland habitats

Journal of Arid Environments (1999) 41: 147]160 Article No. jare.1998.0478 Available online at http:rrwww.idealibrary.com.on

Banner-tailed kangaroo rat burrow mounds and desert grassland habitats Mark C. Andersen & Fenton R. Kay w Department of Fishery and Wildlife Sciences, New Mexico State University, Las Cruces, NM 88003-0003, U.S.A. In this study, the density of banner-tailed kangaroo rat ( Dipodomys spectabilis ) mounds across a range of habitat types near Las Cruces, New Mexico was determined. Mound density varied four-fold between sites. Mound, vegetation and soil characteristics that might explain mound density variation were examined. Mounds influenced vegetation and soil characteristics by altering plant cover, and this effect varied between sites. Mound density, and soil and vegetation characteristics varied substantially between sites, but the two types of variation were not strongly related. Soil particles )2 mm diameter tended to correlate positively with mound density. Banner-tailed kangaroo rat density, measured as mound density, may be positively associated with abundance of annual grasses and forbs. q 1999 Academic Press Keywords: banner-tailed kangaroo rat; desert grassland; vegetation; soils; disturbance; Chihuahuan Desert; habitat

Introduction Our knowledge of the population and community ecology of kangaroo rats (Heteromyidae: Dipodomys ) is extensive (Best, 1972; Whitford, 1976; Jones, 1984; Schroder, 1987; Brown & Zeng, 1989; Waser & Elliott, 1991; Bowers & Brown, 1992; Amarasekare, 1994), but understanding of the habitat relations and ecosystem roles of most heteromyid species in North American deserts is limited. Kangaroo rats can have profound effects on vegetation structure and succession (Wood, 1969; Moroka et al., 1982; Mun & Whitford, 1990; Longland, 1995; Fields et al., in press). Mound-building kangaroo rats such as Dipodomys spectabilis Merriam also influence local animal community composition (Hawkins & Nicoletto, 1992) and soil fungi (Hawkins, 1996). It has been proposed that kangaroo rats act as keystone species ( sensu Paine, 1966) in the deserts of the south-western United States and northern Mexico (Brown & Heske, 1990). There are two possible mechanisms, not mutually exclusive, by which kangaroo rats may achieve keystone status. The first is through trophic effects that manifest themselves at the ecosystem level, either due to granivory (Heske et al., 1993) or to graminivory w Present address: SWCA, Inc., Environmental Consultants, 4100 Cholla Road, Las Cruces, NM 88011, U.S.A. (E-mail: [email protected]).

0140]1963r99r020147 q 14 $30.00r0

q 1999 Academic Press

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M. C. ANDERSEN & F. R. KAY

(Kerley et al., 1997). Granivores are important elements of desert ecosystems and kangaroo rats have been suggested to be keystone vertebrate granivores in desert ecosystems of North America (Brown et al., 1979). At least some species of kangaroo rats can have major ecosystem impacts as graminivores in addition to their role as granivores (Kerley et al., 1997; Kerley & Whitford, in prep.; Sipos, in prep.). The second possible mechanism is through what have been termed ‘engineering’ effects of organisms on ecosystems (Jones et al., 1994; Lawton, 1994; Brown, 1995). Engineering effects include ecosystem effects of organisms that arise as a result of activities other than feeding. Engineering effects have been extensively documented for burrowing animals in general (Mielke, 1977; Grant et al., 1980; Andersen & MacMahon, 1985; Cox & Allen, 1987; Inouye et al., 1987; Koide et al., 1987; Hobbs et al., 1988; Martinsen et al., 1990; Shachak et al., 1991; Hansell, 1993; Cortinas & Seastedt, 1996; Weltzin et al., 1997; Whitford & Kay, this volume; Kinlaw, this volume), and for kangaroo rats in particular (Moorhead et al., 1988; Mun & Whitford, 1990; Longland, 1995; Guo, 1996). The banner-tailed kangaroo rat ( Dipodomys spectabilis ) is found throughout most of the state of New Mexico, west Texas, parts of Arizona, and northern Mexico. In general, the species is found in shortgrass plains, desert grasslands, riparian areas, and some desert scrub habitats. Grasses, which constitute a major component of the species’ diet (Vorhies & Taylor, 1922; Monson, 1943; Holdenried, 1957; Best, 1988) must be present for an area to be inhabited by D. spectabilis, but areas with dense or tall grass cover are avoided. Individuals construct deep, elaborate burrow systems, centered on mounds that may rise over a meter above the surrounding terrain, and may be up to 5 m or more in diameter. There are usually several burrow openings on the mound, with well-developed runways leading to them (Vorhies & Taylor, 1922; Holdenried, 1957; Findley et al., 1975; Best, 1988). There is little information on how banner-tailed kangaroo rats influence shrub invasion of desert grasslands, or on how shrub invasion influences banner-tails. Most studies of banner-tailed kangaroo rats in rangelands have focused on the impacts of the species on range forage species (Wood, 1969; Moroka et al., 1982). There is an observable tendency for density of banner-tailed kangaroo rat mounds to decline as Chihuahuan Desert grassland is replaced by creosote ( Larrea tridentata) shrubland or mesquite ( Prosopis glandulosa) coppice dunes. In areas of creosote shrubland that appear not to represent degraded grassland and in areas of extensive coppice dune formation, banner-tail mounds are only rarely seen, and then only in areas immediately adjacent to existing grassland. This study set out to determine how the density of D. spectabilis mounds varies across a range of desert grassland habitat types with differing amounts of mesquite and proximity to creosote shrubland, to examine the effects of individual mounds on local vegetation across that range of habitat types, and to examine vegetation and soil characteristics that might explain between-site variation in mound density.

Methods Study area description Our eight field sites (Table 1) were within the northern Chihuahuan Desert, in Dona ˜ Ana and Grant Counties in southern New Mexico. The area’s climate is characterized by wide diurnal temperature variation, low relative humidity, and average annual precipitation of 230 mm, 60% of which falls during late summer monsoonal thunderstorms. Soils in the study area consist mainly of alluvial sediments derived from nearby mountain ranges, underlain by a generally impervious caliche (CaCO 3 )

Disturbance (Rank) Heavy (4) Moderate ( 2) Moderate to heavy (3) Moderate (2) Light (1 ) Heavy (4) Light (1 )

Light (1)

Site vegetation Corralitos Ranch 1: desert grassland, high forb abundance Corralitos Ranch 2: creosote scrubrgrassland edge College Ranch: Bouteloua eriopoda grassland South Well 1: Bouteloua eriopodar Aristidar Sporobolus grassland South Well 2: Aristida grassland Mayfield Well 1: Bouteloua eriopodar Aristidar Sporobolus grassland Mayfield Well 2: Bouteloua eriopoda grassland with some mesquite, grading into Ephedra upslope Light Valley: Hilaria mutica grassland

80.0 "7.08 40.7 "5.29 79.1 "5.49

38.0 "2.79

43.0 "6.55 12.3 "1.48 32.6 "3.23

22.5 "1.89

38.9 "7.54 No data

113.4 "8.47

120.7 "4.31

15.7 "4.12 19.2 "2.64 No data

118.2 "5.52

66.5 "7.59

32.6 "4.91

318.9 "19.68

58.2 "3.60

90.9 "6.74 132.0 "17.26

No data

134 "8.92

Soil depth (cm)

Total per cent cover

Penetrometer, 15-cm depth cumulative energy (J)

12.5 "0.92

0.7 "0.21

2.3 "0.50 1.4 "0.30

No data

9.4 "0.44 3.0 "0.57

3.2 "0.39

Volume per cent coarse material ()2 mm diam.)

1.2 "0.03

1.6 "0.02

1.8 "0.04 1.6 "0.03

No data

1.4 "0.03 1.8 "0.07

1.4 "0.03

Total bulk density (g cmy3 )

15

20

20

15

11

26

20

25

No. mounds measured

Table 1. Summary of characteristics for eight Chihuahuan Desert grassland study sites. Disturbance at each site is primarily the result of domestic livestock grazing. Values presented as mean "SE where appropriate. Total per cent cover measured 20 m from banner-tail mound edge. Soil depth, penetrometer energy, volume per cent coarse material, and total bulk density averaged over measurements taken 0, 5, 10, 15, and 20 m from mound

KANGAROO RAT MOUNDS AND HABITATS 149

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M. C. ANDERSEN & F. R. KAY

layer, resulting in relatively shallow soils at most sites (Table 1). Each of our sites was subject to domestic livestock grazing which provided varying levels of disturbance through vegetation removal and soil trampling.

Vegetation and mound density assessment The wandering-quarter method (Diggle, 1983; Bonham, 1989) was used to assess mound density at each site, and each mound was classified as active or inactive on the basis of signs of recent activity such as tracks and tail-drag marks. The wanderingquarter method is a transect method of density estimation. The investigator begins at a starting individual and picks a starting bearing; for each subsequent individual, the individual measured is the nearest neighbor within a 908 sector (the ‘quarter’) centered on the initial bearing. Width and length were measured (with a 30 m tape), as was height (with a meter stick) of each mound encountered on the wandering-quarter route. At every fifth mound encountered, the local vegetation was quantified using four 20-m transect lines radiating in the four cardinal directions from the mound edge. At each meter along each transect, the plant intersected (if there was one) was identified to species level. At 5-m intervals along the east and west transects, a 0.5 m 2 quadrat was placed to estimate per cent cover and vegetation species composition. Data were collected in June, July, and October 1996, and in February and June 1997, resulting in an uneven assessment of annual forb and grass species occurrence and cover.

Soil data Two or three mounds, independent of vegetation and density measurements, were chosen at each site and soil samples collected, penetrometer measurements taken, and soil depth estimated at 0, 5, 10, 15, and 20 m from each mound edge. Soil variables were also measured at two points within each site that had no evidence of kangaroo rat mounds, and at a coppice dune site without evidence of banner-tail occupancy. Soil samples were collected from 0]10 cm and 10]20 cm depth using a 4.5 cm = 10 cm soil corer. The resulting cores were placed in labeled paper sacks and returned to the laboratory. Penetrometer readings, using a penetrometer with a 308 cone, were taken at 5-cm intervals to a maximum depth of 15 cm. The penetrometer used a dropping weight and distance that provided 12 J of energy for each strike. Soil depth was estimated by measuring the depth to which a steel rod of known length could be driven into the ground. Data were collected in March 1998. Analyses of soil samples followed National Soil Survey Center (1996) guidelines. Soil samples were air-dried, run through a 2 mm sieve, and the resulting fractions weighed. A subsample of the fine material was oven-dried at 1008C for 24 h and weighed. The resulting weight was used to correct for residual moisture in the air-dried samples. Fine bulk density was calculated using the corrected values. Because the particles )2 mm diameter were of stone or caliche, no correction for moisture was made in calculating coarse bulk density. A density value of 2.65 g cmy3 was used for calculating the percentage by volume of the coarse fraction.

Statistics For our analysis, we used Model 1 and Model 4 regressions (Weisberg, 1980) using soil variables, per cent vegetative cover, per cent grass cover, and per cent forb cover as dependent variables, distance as a continuous predictor, and site as a discrete predictor.

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A Model 1 regression assumes separate regression lines for each site, while a Model 4 regression has a single regression line, pooled over all sites (Weisberg, 1980). This differs from standard analysis of covariance, which assumes different intercepts but a common slope. To amplify the results, we used a category of data-exploration plots called trellis plots (Cleveland, 1993). Soil variables were compared between non-mound and mound samples using a paired t-test on mean values by site. Because the data tended not to be normally distributed, Kruskal-Wallis analysis of variance (ANOVA) was used on ranks for analyses of mound height, mound area, and intermound distance classified by site, and soil variables at sites with and without kangaroo rats. Spearman rank correlations ( rs ) were used to relate disturbance with mound density, bare ground, and penetrometer energy. Because our data were unbalanced, Dunn’s Method was used for multiple comparisons on ranks (Zar, 1984). To look for trends in vegetative communities, a detrended correspondence analysis of the line transect vegetation data by study site was carried out (ter Braak, 1987). The 0.05 probability level was selected as our general measure of statistical significance, but results were examined at the 0.1 level in instances where it was judged that a less stringent standard of statistical significance might reveal potential biological significance. SYSTAT version 7 and Sigma Stat for Windows, version 2 were used for statistical analyses and Sq , version 4 to produce the trellis plots.

Results Mound height, mound area, and distance between mounds varied significantly between sites (respectively, H s 18.3, df.s 6, p s 0.006; H s 19.7, df.s 6, p s 0.003; H s 25.8, df.s 7, p - 0.001; Table 2). Lake Valley and Corralitos 2 tend to have the tallest mounds (Table 2) and do not differ from one another. Mayfield Well 2 tends to have mounds with the greatest area (Table 2). Lake Valley has the greatest intermound intervals, and Corralitos 1 tends to have the smallest intermound intervals (Table 2). Not all mounds at any site are active at any given time and there seems to be no pattern to occupancy within or between sites. Across sites, active mounds have greater height and volume than inactive mounds, but there is no difference in mound area ( H s 13.7, df.s 1, p - 0.001 for height; H s 4.3, df.s 1, p s 0.04 for volume). The distance to the next mound does not differ between active and inactive mounds. Mound density estimates vary from 2.5]10 mounds hay1 (Table 2). Examination of Tables 1 and 2 suggests that sites with high mound densities tend to be sites with higher levels of disturbance. To test this observation, sites were ranked for disturbance on a scale of 1 to 4 (1 s lightly disturbed to 4 s heavily disturbed) (Table 1). A correlation analysis of disturbance rank against mound density, bare ground, and

Table 2. Summary of banner-tailed kangaroo rat mound data for eight Chihuahuan Desert grassland study sites in southern New Mexico Site Corralitos 1 Corralitos 2 College Ranch South Well 1 South Well 2 Mayfield Well 1 Mayfield Well 2 Lake Valley

Density (mounds hay1 )

Mound interval (avg " SE, m)

Mound height (avg " SE, m)

Mound area (avg " SE, m 2 )

Mound volume (avg " SE, m 3 )

10.0 6.9 10.0 Insufficient data 3.6 8.0 3.5 2.5

31.6 " 2.4 31.3 " 4.4 45.5 " 4.1 41.7 " 6.0

No data 0.29 " 0.04 . 0 20 " 0.02 0.22 " 0.02

No data 4179 " 563 5504 " 900 6714 " 1136

No data 17393 " 4031 14925 " 3332 18887 " 3034

50.9 " 7.7 33.6 " 4.5 40.9 " 7.9 50.9 " 12.0

0.20 " 0.02 0.17 " 0.02 0.15 " 0.02 0.31 " 0.01

4758 " 1255 6626 " 660 5271 " 434 4397 " 382

12210 " 3318 14101 " 2262 10213 " 1709 17502 " 1965

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Table 3. Spearman rank correlations of various vegetation and soil characteristics with mound density. The critical value at the 0.05 significance level is approximately 0.75

Variable Mean per cent vegetative cover Mean grass cover Mean forb cover H9 plant species Weight of particles -2 mm, depth 0]10 cm Weight of particles -2 mm, depth 10]20 cm Weight of particles )2 mm, depth 0]10 cm Weight of particles )2 mm, depth 10]20 cm Total bulk density, depth 0]10 cm Total bulk density, depth 10]20 cm Fine bulk density, depth 0]10 cm Fine bulk density, depth 10]20 cm Soil depth Penetrometer, 0]5 cm Penetrometer, 5]10 cm Penetrometer, 10]15 cm Volume per cent coarse material, depth 0]10 cm Volume per cent coarse material, depth 10]20 cm

Correlation with mound density y0.054 y0.216 y0.270 y0.144 0.324 0.072 y0.739 y0.306 0.414 0.144 0.505 0.234 y0.036 0.126 0.036 0.126 y0.739 y0.306

cumulative penetrometer energy at 5, 10 and 15 cm depth was performed. Bare ground was used as a surrogate for disturbance since highly disturbed sites appear to have more bare ground than less disturbed sites. Cumulative penetrometer energy provides a measure of soil compaction which is expected to increase with disturbance due to trampling. Subjective evaluation of disturbance correlates highly with mound density ( rs s 0.878, p - 0.001). Neither per cent bare ground, cumulative, nor interval penetrometer energy at 5, 10 or 15 cm depth correlates significantly with density or with disturbance ranking. The correlation between per cent bare ground and cumulative penetrometer energy at 10 and 15 cm depth is just barely not significant ( rs s 0.631, p s 0.1, both intervals). The same is true of the correlation between mound density and weight of particles )2 mm diameter, and volume per cent of coarse material at 0]10 cm depth (0.1 ) p ) 0.05, Table 3). No significant differences in any soil variable were found between mean mound and non-mound samples within our study sites. When soil data from a coppice dune area and an area of heavy clay soil without evidence of mounds within our mound sites are compared, only a marginal difference is shown in weight of soil particles ( H s 11.97, df.s 6, p s 0.06) and fine bulk density ( H s 11.66, df.s 6, p s 0.07) but there is a significant difference in penetrability ( H s 12.57, df.s 6, p s 0.05). The Lake Valley sample has a greater median weight of soil particles )2 mm diameter than the heavy clay soil sample ( p - 0.1, 60.4 g vs. 0 g, respectively). The coppice dune sample has a greater median fine bulk density ( p - 0.1, 2.05 g cmy3 vs. 1.0 g cmy3 ) and greater median penetrability ( p - 0.1, 60 J vs. 319 J) than the Lake Valley soil. Although not significant, the coppice dune samples tend to have greater values of fine bulk density and higher penetrability than all other samples. Results on the influence of mounds on local vegetation are shown in the trellis plots in Figs 1]3. The figures indicate that total per cent cover, grass cover, and forb cover all tend to increase with increasing distance from a mound, but the nature of this relationship varies across sites. To confirm the visual impression conveyed by Figs 1]3,

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Figure 1. Trellis plot of per cent cover vs. distance from mound for the seven field sites for which sufficient data were available to perform the analysis. Solid circles represent data points; solid lines in each panel represent a lowess regression line through the data. Text labels on plot panels represent sites as follows: CR1 s Corralitos Ranch 1; CR2 s Corralitos Ranch 2; CR s College Ranch; SW2 s South Well 2; MW1 s Mayfield Well 1; MW2 s Mayfield Well 2; LV s Lake Valley.

a Model 1 regression was compared with a Model 4 regression (Weisberg, 1980) for each of the cover variables. The Model 1 regression (with a separate regression line for each site) fits the data significantly better than the Model 4 (pooled) regression for total per cent cover, grass cover, and forb cover (Table 4). Although many of the regressions of per cent cover, grass cover, and forb cover on distance from mound for individual sites are not statistically significant, the pooled regressions of total per cent cover, grass cover, and forb cover on distance from mound are all highly significant (Table 5). These results confirm that per cent cover, grass cover, and forb cover tend to increase with distance from the mound, and that the relationship varies between sites. The relationship of soil characteristics to distance from mound, by site, are similar to those of vegetative cover. Significant results using Model 1 and 4 regression comparisons for the soil data are shown in Table 4. Weight of the )2 mm soil fraction and the resulting volume per cent of coarse material tend to be greatest on the mound edge and to be lower at greater distances from the mound at all sites. The Lake Valley site tends to have much greater values at all distances from the mound than any other site (Table 1). Bulk density did not vary significantly by site (Table 1) or distance from mound edge within any site. Figure 4 shows plot scores for the first two axes of a detrended correspondence analysis of the step-point transect vegetation data. This plot shows substantial variation among the sites with respect to vegetation characteristics. The plot also shows the

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Figure 2. Trellis plot of grass cover vs. distance from mound for the seven field sites for which sufficient data were available to perform the analysis. Solid circles represent the data points; solid lines in each panel represent a lowess regression line through the data. Text labels on plot panels as in Fig. 1.

location of the site data centroids. Some separation of the sites is evident in the centroids. Corralitos 2 tends to be separated from most of the other sites in the plot and is at the margin of a creosote shrubland. Lake Valley also tends to separate rather widely on the plot, and is at a slightly higher elevation, in a tobosa grass ( Hilaria mutica)rblue grama ( Bouteloua gracilis ) grassland. There is no mesquite on the Lake Valley site. South Well 2 (SW), the site with the overall densest stands of grass, is less well separated on the plot. There is less mesquite at South Well than at Mayfield Well 2, the other high-density grassland site.

Discussion and conclusions Several authors (Vorhies & Taylor, 1922; Holdenried, 1957; Schroder & Geluso, 1975; Reichman et al., 1985; Best et al., 1988) report data on banner-tailed kangaroo rat mound size and spacing. The data are summarized in Best (1988). Our measurements of mound height and intermound distance fit within those previous data. Only one study (Best et al., 1988) compares burrow mound characteristics between geographic localities. Best et al. (1988) report significant differences in mound height and intermound distance between widely separated populations of two Mexican subspecies of D. spectabilis. One of their subspecies, D. s. zygomaticus, is found in Chihuahuan Desert grassland, the other, D. s. cratodon, is found in cactus shrub forest. Mounds of

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Figure 3. Trellis plot of forb cover vs. distance from mound for the seven field sites for which sufficient data were available to perform the analysis. Solid circles represent the data points; solid lines in each panel represent a lowess regression line through the data. Text labels on plot panels as in Fig. 1.

D. s. zygomaticus are higher (41.6 cm) and closer together (10.5 m) than at any of our sites (Table 2), while mounds of D. s. cratodon reported by Best et al. (1988) are about in the middle of our range of mound height (18.4 cm) and closer together (19.6 m) than our mounds (Table 2). Best et al. (1988) conjecture that soil or other environmental factors may influence mound characteristics at their study sites. Green & Murphy (1932) report that burrow-mound surface soils contain more fine material than off-mound soils, but that larger particles increase with depth in the mound compared to off-mound soils. Our data suggest that large soil particles ()2 mm diam.) tend to be most abundant at the edge of the mound and in the top 10 cm of soil. Kangaroo rats move pieces of caliche and stone to the surface during burrowing activity, where the particles tend to accumulate on the mound surface and get turned into the soil. The weight and volume per cent of )2 mm particles vary between sites (Table 1), a reflection of local soil conditions. These variables are closely related (volume per cent is computed from weight of particles )2 mm), and highly correlated. Thus they can both be viewed as surrogates for a single quantity, namely near-surface coarse material. The only soil factors that approach a statistically significant correlation with banner-tail mound density (0.1 ) p ) 0.05) are weight of particles )2 mm diameter and volume per cent of coarse material in the top 10 cm of soil (Table 3). Our data suggest that sites with larger amounts of coarse material are more favorable to banner-tailed kangaroo rats, but do not suggest what mechanism may be operating. The fact that mound height varies between sites, along with our observation regarding

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Table 4. Significant results of analyses of covariance using dependent variable listed, distance from mound as continuous predictor, and site as categorical predictor. Dependent variables were subjected to natural log q 1 transform where indicated. Residual standard errors are for Model 1regressions, F-statistics and p-values pertain to a likelihood ratio test of Model 1 vs. Model 4 Residual standard Multiple R 2 Multiple R 2 (Model 4) (Model 1) error

Dependent variable Vegetation Per cent cover Grass cover Forb cover Soil Weight of particles ) 2 mm, depth 0]10 cm (transformed) Weight of particles ) 2 mm, depth 10]20 cm (transformed) Volume per cent coarse material, depth 0]10 cm Volume per cent coarse material, depth 10]20 cm

F

P

df.s 276 14.65 5.08 6.15 df.s 158

0.016 0.041 0.016

0.731 0.662 0.550

df.s 12, 276 2.40 2.91 2.64 df.s 6, 158

0.583

0.051

0.698

25.44

-0.001

0.534

0.028

0.764

18.06

-0.001

0.001

0.019

0.682

9.17

0.003

0.001

0.028

0.614

11.01

0.001

0.006 0.001 0.002

coarse material, provides a strong suggestion that some soil mechanical property plays an important role in site suitability. Our data on soil bulk density and soil penetrability (Table 1) suggest that ease of burrowing is not the operant factor. The coppice dune area, which tends to have higher penetrability and fine bulk density values than other sites, has no banner-tails. Lake Valley, which has the lowest penetrability (Table 1) and relatively low fine bulk density (1.14 g cmy3 ), has a moderate density of mounds (Table 2). Further analysis of soil structure from our study sites may shed light on this aspect of the habitat requirements of banner-tailed kangaroo rats. Schroder & Geluso’s (1975) study of distribution and density of banner-tail mounds reports that the mounds are regularly distributed over a 47 ha study site, but that at a smaller-scale they tend to be clumped. They suggest intraspecific competition as the driving force for the observed distribution. Amarasekare (1994) and Jones et al. (1988) have also studied variation in mound density. Amarasekare (1994) described banner-tail mound density in relation to habitat characteristics. She found strong habitat differences between areas occupied by Dipodomys spectabilis and unoccupied areas, but, as in our

Table 5. Results from regressions of various dependent variables on distance from mound for each study site. For the overall (Model 4) regressions, the coefficients were: per cent cover: 0.588 (p - 0.001); grass cover: 0.162 (p - 0.001); forb cover: 0.120 (p s 0.032)

Site Corralitos Ranch 1 Corralitos Ranch 2 College Ranch Mayfield Well 1 Mayfield Well 2 South Well 2 Lake Valley

Per cent cover Coefficient p 0.968 0.260 0.514 0.140 0.964 0.753 0.327

0.105 0.541 0.018 0.569 -0.001 0.080 0.224

Grass cover Coefficient p 0.042 0.183 0.280 0.032 0.208 0.090 0.140

0.782 0.138 0.062 0.558 0.002 0.488 0.329

Forb cover Coefficient p 0.124 0.298 y0.240 0.122 0.118 0.223 0.510

0.321 0.043 0.048 0.404 0.296 0.120 0.017

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Figure 4. Site scores (v) vs. the first two ordination axes for the transect vegetation data. Text markers represent site centroids as follows: CR1 s Corralitos Ranch 1; CR2 s Corralitos Ranch 2; CR s College Ranch; SW1 s South Well 1; SW2 s South Well 2; MW1 s Mayfield Well 1; MW2 s Mayfield Well 2; LV s Lake Valley.

study, no statistically significant habitat differences between occupied areas. Jones et al. (1988) documented a range of temporal variability in population density (unsaturated density s 3.6 hay1 , saturated density s 9.1 hay1 ) almost as great at one of their sites as the range of spatial variability in population density we observed (Table 2). Individual D. spectabilis can profoundly influence local vegetation through the influence of their mounds on per cent cover, and grass and forb abundances (Figs 1]3; Tables 4 and 5). The strength and shape of this effect varies between sites (Figs 1]3; Table 4). Several other workers have also found that mounds of D. spectabilis have profound effects on local vegetation (Moorhead et al., 1988; Mun & Whitford, 1990; Bowers & Brown, 1992). Guo (1996) finds that patterns of plant species diversity associated with banner-tail mounds conform to the predictions of the ‘intermediate disturbance hypothesis’ (Paine & Vadas, 1969; Connell, 1975; Huston, 1979; Miller, 1982). Schroder (1979) provides evidence for possible behavioral mechanisms for the effects of banner-tailed kangaroo rats on vegetation. None of these authors has addressed the influence of vegetation on density of banner-tails. The detrended correspondence analysis (Fig. 4) suggests that vegetation is an important differentiating factor between at least some of the sites. Two sites stand out. Lake Valley is a tobosarblue grama grassland and Corralitos 2 is on the margin of a creosote shrubland in which we found no banner-tails. South Well 2 is well separated and has somewhat less mesquite than either Mayfield Well site or the College Ranch site. Why Mayfield Well 1 and Corralitos 1 do not separate more clearly is not apparent, since they were both highly disturbed and had little perennial grass. In any event, it seems reasonable to assume that some of the four-fold variation in mound density we find between sites should be related to variation in vegetation characteristics. This does not appear to be the case (Table 5) in our data. None of the substantial

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variation in vegetation that we measured (Fig. 4) can be correlated with the observed variation in mound density. Our observations on a variety of habitats occupied by banner-tails suggests that vegetation factors (i.e. overall spatial variability in food abundance) may play an important role in success of banner-tails in a habitat. We have noted that annual forbs and grasses tend to be seasonally abundant in habitats occupied by D. spectabilis, and appear to be more abundant in habitats with greater apparent density of mounds. We recorded (Table 1) an apparent high abundance of forbs at Corralitos 1, a site with a high density of mounds. For logistical reasons, our measurements of vegetation were not always made when forbs and annual grasses were at their peak of abundance. Measurement of annual forbs and grasses during the spring and summer peaks of productivity may provide data to clarify the role of vegetation in affecting banner-tailed kangaroo rat abundance. The often reported high abundance of annual plants on banner-tail mounds (Vorhies & Taylor, 1922; Holdenried, 1957; Moorhead et al., 1988; Mun & Whitford, 1990; Guo, 1996) may prove to be the result of the animals’ selecting areas of high forb and annual grass abundance, areas which are often highly disturbed and relatively open. We still have no insight into why banner-tailed kangaroo rats tend not to be found in creosote shrubland (except where shrub invasion is relatively recent) or in mesquite coppice dunes. We wish to thank G. Kerley and W. Whitford for their comments on an earlier draft of this manuscript. K. Havstad and the Jornada Experimental Range extended many courtesies and allowed us to carry out much of the study on that facility. W. Whitford provided logistical support. Much of this material was presented at the 7th International Theriological Congress in Acapulco, Mexico.

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