Ecosystems 2*5 - CiteSeerX

ECOSYSTEMS

Ecosystems (1999) 2: 422–438

r 1999 Springer-Verlag

Spatial Variability of Soil Properties in the Shortgrass Steppe: The Relative Importance of Topography, Grazing, Microsite, and Plant Species in Controlling Spatial Patterns Ingrid C. Burke,1,2,3,* William K. Lauenroth,2,3,4 Rebecca Riggle,1 Peter Brannen,1 Brian Madigan,1 and Scott Beard4 Department of Forest Sciences; 2Graduate Degree Program in Ecology; 3Natural Resource Ecology Lab; and 4Department of Rangeland Ecosystem Science, Colorado State University, Fort Collins, Colorado 80523, USA

ABSTRACT tion of litter beneath individual plants. Over 50 y of heavy grazing by cattle did not have a significant effect on most of the soil organic matter pools we studied. This result was consistent with our hypothesis that this system, with its strong dominance of belowground organic matter, is minimally influenced by aboveground herbivory. In addition, soils beneath two of the important plant species of the shortgrass steppe, B. gracilis and O. polyacantha, differed little from one another. The processes that create spatial variability in shortgrass steppe ecosystems do not affect all soil organic matter pools equally. Topographic variability, developing over pedogenic time scales (centuries to thousands of years), has the largest effect on the most stable pools of soil organic matter. The influence of microsite is most evident in the pools of organic matter that turn over at time scales that approximate the life span of individual plants (years to decades and centuries).

We conducted a study to evaluate the relative importance of topography, grazing, the location of individual plants (microsite), and plant species in controlling the spatial variability of soil organic matter in shortgrass steppe ecosystems. We found that the largest spatial variation occurs in concert with topography and with microsite-scale heterogeneity, with relatively little spatial variability due to grazing or to plant species. Total soil C and N, coarse and fine particulate organic matter C and N, and potentially mineralizable C were significantly affected by topography, with higher levels in toeslope positions than in midslopes or summits. Soils beneath individual plants (Bouteloua gracilis and Opuntia polyacantha) were elevated by 2–3 cm relative to surrounding soils. All pools of soil organic matter were significantly higher in the raised hummocks directly beneath plants than in the soil surface of interspaces or this layer under plants. High levels of mineral material in the hummocks suggest that erosion is an important process in their formation, perhaps in addition to biotic accumula-

Key words: spatial variability; shortgrass steppe; soil organic matter; topography; microsite; grazing.

INTRODUCTION Grasslands worldwide have been shown to have a high degree of spatial variability that is controlled by both abiotic and biotic factors. Studies of regional-

Received 21 January 1999; accepted 28 May 1999. *Corresponding author. e-mail: [email protected]

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Spatial Variability of Soil Properties scale patterns have indicated that grassland vegetation, primary production, soil organic matter, litter quality, and nutrient availability are significantly related to regional patterns in precipitation, temperature, soil texture, and land-use history (Sala and others 1988; Burke and others 1989, 1991, 1997; Epstein and others 1996, 1997a, 1997b, 1998; Murphy and others submitted). At local scales (less than 1 km), a separate set of literature exists that focuses on controls over spatial variability in soil properties and processes. Literature from the 1980s on grassland biogeochemistry shows strong spatial variability at landscape scales, induced by topographic variation likely associated with both geomorphic and fluvial processes (Schimel and others 1985a, 1985b; Aguilar and Heil 1988; Yonker and others 1988). More recent work has indicated that total soil organic matter pools and nutrient turnover also are strongly influenced by spatial patterns in plant species composition (for example, Wedin and Tilman 1990, 1996; Vinton and Burke 1995, 1997). Further work has indicated that in semiarid grasslands the presence or absence of individual plants has a strong influence on the spatial patterning of soil properties (Hook and others 1991; Burke and others 1995; Vinton and Burke 1995, 1997), with bunchgrasses concentrating C and N beneath their canopies in so-called ‘‘resource islands.’’ Finally, in some parts of the world, grazing by cattle or other herbivores in grasslands has been shown to cause significant changes in soil organic matter and nutrient availability (Reuss and McNaughton 1987; Holland and Detling 1990; Milchunas and Lauenroth 1993; Manley and others 1995; Biondini and Manske 1996). Whereas some of the interactions among these causes of spatial variability in grasslands have been identified (Hobbs and others 1991; Wedin 1995; Vinton and Burke 1997; Burke and others 1998), there are few data for evaluating the relative importance of individual factors, since many have been studied in different locations. Understanding the sources of spatial variability in soils is important because most of the organic matter and energy flow in shortgrass steppe systems is belowground (Lauenroth and Milchunas 1992; Burke and others 1996); spatial variability in soil organic matter represents variation in most of the organisms and energy flow in these ecosystems. The general objective of the study presented here was to assess the relative importance of topography, grazing, microsite, and plant species in controlling the spatial variability of soil organic matter pools and processes in a shortgrass steppe ecosystem. Below, we provide a brief review of the previous literature on the effects of each separate factor to

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provide context and then present the specific objectives that organized our study.

Topography At a landscape scale, there is strong spatial variation in soil organic matter and nutrient supply in central North American grassland ecosystems (Aguilar and Heil 1988; Aguilar and others 1988; Schimel and others 1985a, 1985b; Yonker and others 1988). In all of this work, the catena concept (Gerrard 1981) was used as a model to explain the pattern of variability along toposequences. The catena concept suggests that the downhill movement of material as a result of gravity and water movement results in a predictable sequence of soil characteristics from summits to toeslopes. Aguilar and Heil (1988) and Aguilar and others (1988) working in the northern mixed prairie found that the catena model only partially explained their observed variability in soil properties. Schimel and others (1985a, 1985b) sampled a single shortgrass steppe toposequence at the Central Plains Experimental Range (CPER) and found excellent correspondence with the catena model. However, Yonker and others (1988) sampled 24 toposequences along an 8-km transect at the CPER and found that the catena model was insufficient to explain landscape-scale variability in soil carbon. They suggested that ‘‘the role of water as the agent of differentiation is minimized in the presentday landscape’’ indicating that the catena is not a useful general model to explain landscape-scale variability in soil properties. Whereas the catena model may be useful in wet areas, in the semiarid shortgrass steppe its use is limited because of the important role of other influences, such as wind, in redistributing organic and mineral material over landscapes.

Grazing The response of grassland soils to grazing is extremely variable (Milchunas and Lauenroth 1993; Burke and others 1997). In a literature review of the effects of grazing worldwide, Milchunas and Lauenroth (1993) found that studies in some areas have shown significant losses of soil organic matter in response to grazing, some have shown significant increases, and some have shown no changes. In the shortgrass steppe, there are only slight changes in plant species composition in response to long-term grazing or exclosure from grazing (Milchunas and others 1988, 1989, 1992; Milchunas and Lauenroth 1993). These responses have been interpreted as being the result of a long evolutionary history of grazing by large, generalist herbivores (Milchunas

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I. C. Burke and others

and others 1988, 1989). Similar effects recently have been documented in tallgrass prairie (Collins and others 1998) and northern mixed grass prairie (Biondini and Manske 1996). However, litter cover in shortgrass steppe is reduced significantly by grazing and bare ground cover increases (Milchunas and others 1989); effects are generally greatest in toeslope landscape positions. How do these changes in organic matter inputs influence total organic matter and nutrient availability in the shortgrass steppe? Are the effects of grazing on soil organic matter also greatest in toeslope positions? We recently have hypothesized that cattle grazing will have minimal effects on soil organic matter and biogeochemistry of grassland ecosystems (Burke and others 1996). Because most of the organic matter in grassland ecosystems is located in roots and soil organic matter, removal of aboveground biomass during grazing would represent a relatively small change in carbon and nutrient cycling.

Plant Species Grasslands have provided critical information demonstrating a significant impact of plant species on soil organic matter and nutrients (for example, Knapp and Seastedt 1986; Tilman 1986, 1987; Seastedt 1988; Gleeson and Tilman 1990, 1994; Huenneke and others 1990; Wedin and Tilman 1990, 1993, 1996; Seastedt and others 1991; Tilman and Wedin 1991a, 1991b; Aerts and Caluwe 1994; Berendse 1994). Vinton and Burke (1997) showed that whereas distinctions among plant species with respect to litter quality can have significance for grassland organic matter, they are less important in the semiarid shortgrass steppe than in the subhumid tallgrass prairie and suggested that this corresponds with increasing nutrient limitation across the precipitation gradient. In the shortgrass steppe, which is strongly water limited and shows relatively small effects of plant species and litter quality on soil organic matter and nutrient turnover, we anticipate that processes associated with differential capabilities of species to form resource islands may be the most important influence of plant species on spatial patterns of soils. In this study, we focus our assessment of the role of plant species on soil organic matter patterns in shortgrass steppe on the differences between Bouteloua gracilis, the dominant C4 bunchgrass, and Opuntia polyacantha, a subdominant succulent. We focus on B. gracilis because of its very significant importance to the shortgrass steppe; the shortgrass steppe is unusual in that it is overwhelmingly dominated by this one species (60–80% of the cover and biomass). O. polyacantha covers only approxi-

mately 2% of the shortgrass steppe (Hook and others 1991); however, we have observed that patches (a group of cladodes) dominated by O. polyacantha have several important effects on the shortgrass steppe. First, plant diversity is higher inside of the patches than outside, likely due to protection from cattle grazing by the spines (Bayless 1996). Second, field observations indicate that there is considerable microtopographic relief associated with O. polyacantha.

Microsite Arid and semiarid environments are characterized by a patchy plant cover and by a heterogeneous distribution of C and N. Numerous studies have shown that soil C and N are concentrated beneath shrubs in semiarid and arid shrublands (Charley and West 1975, 1977; Burke 1989; Burke and others 1989; Bolton and others 1990, 1993; Schlesinger and others 1990, 1996; Jackson and Caldwell 1993; Halvorson and others 1995, 1997; Schlesinger and Pilmanis 1998). Hook and others (1991) found that in the shortgrass steppe resource islands form beneath individuals of the dominant bunchgrass, B. gracilis, and compared their results to separate studies on the shortgrass steppe to suggest that this level of spatial variability in C and N was highly significant relative to other sources of variability. Soils beneath individual B. gracilis plants are raised relative to surrounding soils by an average of 3 cm, have higher soil organic matter, and greater potential for nitrogen mineralization than do soils located between individuals. Average basal cover of B. gracilis is approximately 30% in the shortgrass steppe, and interspaces account for 48–62%. Subsequent work (reviewed in Burke and others 1998) has indicated that these resource islands develop over periods of several decades after major disturbance, such as cultivation, in association with the recovery of B. gracilis (Burke and others 1995). In a comparative study with desert grasslands of New Mexico, Lauenroth and others (1997) found that resource islands associated with B. gracilis in the shortgrass steppe are more concentrated with organic matter than are those in the desert grassland associated with Bouteloua eriopoda. Their interpretation was that the shorter life span associated with B. eriopoda (0.5% surviving 30 y relative to 400 y for B. gracilis) resulted in less time for a resource island to develop. Work by Schlesinger and others (1990, 1996) and Schlesinger and Pilmanis (1998) has suggested that life form shifts in the desert southwest from grasses to shrubs induced by livestock grazing lead to increased small-scale heterogeneity, and that this heterogeneity thus can be used as an indicator of ecosystem

Spatial Variability of Soil Properties degradation. Alternatively, in the shortgrass steppe, with higher heterogeneity associated with the dominant native species than in the desert southwest, we hypothesize that cattle grazing will reduce smallscale heterogeneity associated with B. gracilis. Although considerable work has illustrated the importance of small-scale heterogeneity in semiarid and arid grasslands, no work has been conducted to assess the processes through which these resource islands form (Burke and others 1998). Two sets of processes, biotic and abiotic, could be responsible. First, since semiarid and arid systems are characterized by discontinuous aboveground plant cover, resource islands could form due to concentrated aboveground biomass inputs to organic matter. However, it frequently has been suggested that the major source of organic matter in grassland soils is belowground biomass (Dormaar 1992; Burke and others 1997). Belowground biomass also may be concentrated below individual plants in surface layers (0–10 cm), with roots of adjacent plants not converging to cover all space until slightly deeper layers. Hook and others (1994) and Kelly and others (1996) showed that particulate organic matter derived from fine roots is concentrated close to individual plants at the surface, relative to interspaces. Second, organic matter accumulation and associated microtopography may occur due to physical soil redistribution from interspaces to beneath individual plants. There is considerable anecdotal support for such mechanisms; there are high average wind speeds associated with many semiarid and arid systems, and little litter is observed on the surface of soils, suggesting that it is redistributed by wind. In a study in shrub steppe in Wyoming, Coppinger and others (1991) used 137Cs to demonstrate significant mineral redistribution from interspaces to locations beneath shrubs in a similarly windy environment. In shortgrass steppe, Martinez-Turanzas and others (1997) found that significant microtopography formed in the first decade after disturbances, and that more relief occurs on fine-textured than on coarse-textured soils, suggesting that the movement of fine soil material is important over short time scales. Previously, all of the literature focusing on plantinduced soil heterogeneity has described sampling procedures that confound concentration differences between and under individual plants with the volume of organic matter accumulation under individual plants. Investigators have tended to sample a given depth increment from the surface down, ignoring the microtopographic relief associated with individual plants, so that different soil layers are compared. One of our key questions regarding the

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formation and importance of resource islands in grasslands is whether resource islands develop by increasing the concentration of organic matter within a given soil layer, or by increasing the volume of organic matter by raising the soil level.

Specific Objectives The specific objectives of our study were as follows. First, we wished to determine the importance of grazing, topography, plant species, and microenvironment in explaining the spatial variability of soils in the shortgrass steppe. Within this objective, we hoped to evaluate the relative importance of each factor against the others. Second, we intended to focus in on microenvironmental heterogeneity associated with individual plants, to determine if this plant-scale heterogeneity is influenced by the other factors (grazing, plant species type, and topography), and to provide more information on the composition of resource islands and the relative importance of biotic (in situ organic matter accumulation) and abiotic processes (physical redistribution of soil) in the formation of resource islands. Finally, we wished to assess whether the temporal dynamics of soil organic matter pools (for example, long- vs short-turnover dynamics) influence their patterning at small and larger spatial scales.

METHODS We conducted our study on the Shortgrass Steppe Long-Term Ecological Research Site (SGS-LTER), and within the SGS-LTER, on the Central Plains Experimental Range (CPER). This site (40° 49’ N, 107° 47’W) is located approximately 56 km northeast of Fort Collins, Colorado, USA. The CPER is owned and managed by the USDA Agricultural Research Service, which initiated grazing experiments on the site in 1938. Mean annual air temperature is 8.6°C, and mean annual precipitation is 321 mm (Lauenroth and Sala 1992), with the high degree of interannual variability characteristic of semiarid climates of the Great Plains (Lauenroth and Burke 1995). The topography is gently rolling. Soils are generally sandy loams of late Pleistocene to mid-Holocene alluvial origin, modified by more recent Holocene eolian deposition (Yonker and others 1988). The vegetation is dominated by shortgrass steppe vegetation, with B. gracilis and Buchloe¨ dactyloides as the dominant grasses, and subdominant vegetation including O. polyacantha, Aristida longiseta, and Agropyron smithii and other grasses and subshrubs (nomenclature for plants follows Great Plains Flora Association 1986). Our study used a grazing experiment set up by the Agricultural Research Service in 1938. At that time,

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Figure 1. Diagram of plant-interplant mosaic in the shortgrass steppe indicating the location from which under, between, and hummock samples were taken.

two replicate, 130-ha pastures were set up for treatments of light, heavy, and moderate grazing intensity. Exclosures, representing no grazing, were set up within each pasture, with one long exclosure located between two adjacent heavy and moderately grazed pastures, running the full length of the 1.6-km boundary, 12 m wide (Milchunas and others 1989). Several decades ago, the experiment was reduced to one replicate of each pasture; however, the remaining 130-ha pastures are relatively large and incorporate a very high degree of landscape variability within their bounds. For this study, we focused only on the heavily grazed pasture and the exclosure, to capture the maximum influence of grazing. We chose this design because all of our former work has indicated only slight effects of grazing on vegetation, and we wished to find the maximum effect of grazing on soils. This sampling design allows for side-by-side comparison of heavily grazed and ungrazed pastures, on the same landscape positions. The strip crosses three full catenary sequences, in a north-south direction, and has the advantage of being the site of several long-term studies (Milchunas and others 1989). The slopes are gently rolling, not exceeding 30 degrees, with approximately 50 m from summit to toeslope. From 1939 to 1962, the heavily grazed pasture was managed at a stocking rate necessary to sustain an annual removal of 60% of the aboveground standing biomass averaged across the pasture (Milchunas and others 1989). Since 1962, the heavily grazed treatment has been managed to maintain 22.5 g m⫺2 of aboveground biomass (Milchunas and others 1989). We acknowledge that the design is limited because the fencelines define only one formal replicate; however, we consider that (a) the existing pastures are extraordinarily valuable because of the long-term (60 y), consistent management of the experiment; and (b) the size and landscape variation within the pasture and exclosure adequately represent the topographic, soil, vegetation, and grazing

variability present within the CPER (Burke and Lauenroth 1993). The exclosure/heavily grazed pasture border runs across three toposequences or catenary sequences. We designated each toposequence as a block, each containing three positions, summit, a midslope position facing north, and the toeslope. Within each block ⫻ grazing ⫻ landscape position combination, we located five individual plants representing each of two species (B. gracilis and O. polyacantha).

Field Sampling We used this overall design to conduct three closely related studies. In a first, we evaluated the variance in soil organic matter pools. We sampled soils in each block (3) ⫻ grazing treatment (2) ⫻ topographic location (3) ⫻ plant species (2) combination in each of three microsites (Figure 1). A 5.5-cm in diameter soil core was taken from a 0–5 cm depth in each interspace according to the sampling design above, located in the surface position that we used to estimate the baseline for microtopographic relief. Two additional soil cores were taken from beneath the center of individual plants. The first was taken from the surface down to a depth corresponding to the surface level of the interspace; we termed this microsite the ‘‘hummock.’’ Finally, a soil core was taken 0–5 cm immediately below the hummock soil sample (termed ‘‘under-plant’’ soil sample) in the same soil layer as the 0–5 cm sample from interspaces. Soil samples were stored in coolers, returned to the laboratory, and stored at 4°C for several days until processing for physical and chemical analysis. In a related but separate design for the second study, we characterized soil respiration rates and soil moisture for the large-scale treatments of grazing and topography, across all blocks. We consider field rates of CO2 flux to be a sensitive indicator of in situ soil processes. To avoid the confounding factor of aboveground plant respiration, we only sampled in

Spatial Variability of Soil Properties the interspaces associated with the design described above [block (3) ⫻ grazing treatments (2) ⫻ topographic locations (3)], with three replicates at each of the 18 locations above. We measured soil respiration by using a Environmental Gas Monitor (version 1; PP Systems, Haverhill, MA, USA), a continuous flow, infrared gas analyzer. Each measurement takes approximately 2 min, depending upon the rate of respiration. We measured soil respiration on 10 dates, at approximately weekly intervals, during the 1997 growing season (3 July to 13 September). Soil moisture was measured at each location by using time domain reflectometry (TDR; Topp and others 1980; Topp and Davis 1985). We installed TDR to a depth of 10 cm in the soil at three locations adjacent to the locations at which the soil respiration measurements were taken. TDR was measured with a Tektronix 1506b metallic cable tester. The instrument was calibrated for our soils, and conversions were made using data from Wythers (1996). In our third study, we used a simple microsurveying technique to estimate the microtopography associated with each plant sampled. We stretched a string between two bars forming a double right angle with legs of known and equal length. Keeping the string parallel with the slope of the ground and the legs perpendicular to the ground, we placed the legs in the interspaces on either side of a hummock (the raised soil under an individual plant). A small ruler was used to measure the distance down from the string to the top, center of the hummock, and the height of the hummock above the interspace soil surface was determined by subtraction. We defined this height of the hummock as microtopographic relief (sensu Hook and others 1991; Martinez-Turanzas 1997). We recorded the microtopographic relief associated with each plant.

Laboratory Analysis Soil samples were passed through a 2-mm sieve and subsampled for four different types of soil characterization, estimation of total C and N pools, particle size fractionation, estimation of particulate organic matter C and N, and estimation of potentially mineralizable C and N by using laboratory incubations. Potentially mineralizable C and N provide a good index of the most active pools of organic matter and potential N availability. To determine potentially mineralizable C and N, we used a standard laboratory incubation technique (Burke and others 1995a). An initial 10-g subsample of the fresh sieved soil was taken to determine moisture content. Second, a 1.5-g subsample was taken to determine initial nitrate and ammonium content of soils. This sample was extracted in 2 N KCl and shaken for 0.5 h,

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filtered, and analyzed for nitrate and ammonium concentration on an Alpkem Flow Solution 3000 (Ol Analytical, College Station, TX, USA), an automatic flow injection analyzer. We placed a third soil subsample of 15 g into a cup, brought it up to field capacity, and incubated it in a 1000-mL mason jar at a constant 25°C temperature in the dark for 28 d. The jar also contained a vial of 1.5 N NaOH to serve as a CO2 trap for the estimation of CO2 respired during the incubation period (potential C mineralization) and approximately 10 mL of distilled water in the bottom for maintenance of a saturated atmosphere (Schimel and others 1985b; Burke and others 1989). After 30 d, the CO2 trap was titrated with 1.0 N HCl to determine potential C mineralization. The soil sample was extracted in KCl and analyzed as described above for determination of nitrate and ammonium. Potential net N mineralization was estimated as the difference between final and initial nitrate plus ammonium. After the above subsamples were taken, we dried the remaining soils at 55°C until constant weight. An 0.1-g subsample was taken from each of the dried samples for total C and N determination on a LECO CHN-1000, an automated combustion element analyzer (LECO, St. Joseph, MI, USA). We estimated soil particle fractionation and particulate organic matter C and N in a combined procedure. Particulate organic matter (POM; Cambardella and Elliott 1992) provides an indication of the so-called ‘‘intermediate’’ pools of organic matter that turn over on scales of years to decades (‘‘coarse’’ POM) and decades to centuries (‘‘fine’’ POM; Kelly and others 1996). These pools represent relatively recent litter inputs as they are stabilized into humic material, with fine fractions representing the older material, with lower C:N ratios than coarse material or litter (Cambardella and Elliott 1992). We modified the original procedure described by Cambardella and Elliott (1992) slightly. We analyzed 50 g of dried soil, suspended in 100 mL of 5% sodium hexametaphosphate solution. The solution was shaken for 18 h at room temperature, transferred quantitatively to a 1-L cylinder, and brought up to volume with room temperature water. The solution was plunged to suspend all solids, and the density was measured using a standard hydrometer with a Bouyoucos scale (g L⫺1) at 2 h (measures fine and heavy clays) and at 2.4 h (measures fine clay only). We then passed the dispersed sample through a 0.5-mm sieve to collect the coarse particulate organic matter fraction, and then through a 53micron sieve to collect the fine POM fraction. Coarse and fine fractions were rinsed well, then collected in aluminum pans and dried at 55°C to remove all

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water; fractions were weighed, ground in a ball mill, and analyzed for percentage of C and N on the LECO, as described above. Because of the small size of the coarse fraction, materials from the field replicates within each experimental unit were composited before grinding and C and N analysis; the fine fractions were not composited since there was a larger volume of material (the sandy loam soils characteristic of our site had a great deal of material in this size class).

Statistical Analyses Soil data were expressed on a mass per unit volume (cm3) basis, rather than per unit area (ha), because the design included the ‘‘hummock’’ position, of variable areal dimensions and depth. We conducted three separate sets of statistical analyses, for each of the three designs used in this study. For the first design, we tested the significance of grazing, topography, plant species, microsite, and their interactions as they influence the suite of variables that we estimated with this design: total C and N, fine and particulate soil organic matter C and N, potentially mineralizable C and N, and percentage of sand, silt, and clay. The experimental design was a randomized block split three ways, with the factors (three blocks, three landscape positions, two grazing treatments, two species, and three microenvironmental positions) arranged for analysis in order of decreasing physical distance between sampling locations (Table 1). Data were analyzed using the general linear models procedure in SAS (1996) with error terms for each group of factors specified as the appropriate block interaction term for that level in the hierarchy (Table 1). Means for each factor were calculated using LSMEANS (SAS). Least significant differences were calculated from the standard errors according the standard formula LSD ⫽ t(df) ⫻ SQRT(2) ⫻ SE. To evaluate the results of this large analysis, we focused our attention on two key metrics for each main factor and interaction, the probability that the factor or interaction was significant, and the proportion of the variance explained by that factor or interaction (calculated as the partial r2). For main effects and interactions that were both statistically significant (P ⱕ 0.05), we plotted the LSMEANS to evaluate the result and used this information in our interpretation. If main effects were significant and interactions did not confound the trends, we present graphs of main effects but not if the interactions alter the main trends. We did not spend a great deal of time assessing main effects or interactions that were statistically significant but that contributed a very small proportion of the variance (less than approxi-

mately 3%). In analyzing interactions, we assessed the variation of the factor lower in the hierarchy within the factor higher in the hierarchy (Chapman, personal communication). For the second design that focused on field respiration rates, we tested the significance of grazing and topography and their interactions on in situ soil respiration rates and soil moisture. Rather than conduct an analysis by individual date, we averaged fluxes across all dates for each location within the experimental design and conducted a split plot analysis of variance to assess the influence of grazing treatment (2), topographic location (3), block (3), and their interactions on soil respiration and soil moisture. The significance level for this analysis was P ⬍ 0.05. For the third design that focused on microtopography, we used a split plot analysis of variance to test the hypothesis that grazing, topography, plant species, and their interactions influence microtopographic relief, expressed as height in centimeters of the soil surface above the adjacent interspace. The error term was simply the block interaction term, and a significance level of P ⬍ 0.05 was used.

RESULTS

AND

DISCUSSION

Our analysis showed that topography and microsite explained more variance in soil organic matter pools and processes than did plant species type and grazing treatment, for most of the variables we studied. Between 70% and 90% of the variance in soil organic matter pools and processes could be explained by topography, grazing, microenvironment, plant species, and their interactions. Below, we take each main source of variation in turn and describe its role in influencing soil organic matter pools and processes. We first organize our discussion around the main effects and their interactions and then address the question of the relative importance of those effects.

Topography Our results showed significant effects of topographic position on most soil organic matter pools, including total soil C and N, potentially mineralizable C, and coarse and fine POM C and N (Figures 2–4). There was consistently more of these fractions of organic matter in the toeslope position than in the midslope or summit landscape positions. Potentially mineralizable N was not significantly different among landscape positions. In situ soil respiration rates and soil moisture were not significantly different among landscape positions (Figure 5), although there was a trend of higher levels of respiration in toeslope positions on six of the ten sample dates.

Table 1. Effects of Topography, a Grazing, b Plant Species c and Microsite d on Soil Properties in a Shortgrass Steppe Ecosystem

Source

Coarse POM N (var.)

Coarse POM N (P)

Fine POM C (var.)

Fine POM C (P)

Fine POM N (var.)

Fine POM N (P)

0.3256 0.0174

1.87 3.61

0.1221 0.0473

12.76 1.85

0.0164 0.2525

2.01 18.03

0.0070 0.0001

1.45 16.95

0.0529 0.0006

5.30 35.89

0.1886 0.0104

4.57 31.08

0.1433 0.0068

6.58 1.89 4.40

0.1510 0.1161

1.00 0.03 1.63

0.7226 0.0696

1.87 1.53 1.00

0.0575 0.2445

0.18 1.45 2.78

0.0042 0.0025

4.17 1.17 3.35

0.0392 0.0127

4.06 5.30 5.02

0.0579 0.1540

2.78 4.84 5.62

0.0854 0.1665

0.0682 0.5470 0.7765

4.18 3.13 0.44 0.02

0.0598 0.7426 0.8752

1.14 0.26 0.52 2.78

0.5509 0.6958 0.0700

1.67 2.23 0.01 0.22

0.0142 0.9864 0.3817

0.44 0.01 0.14 0.32

0.8837 0.7713 0.2944

1.01 0.11 0.39 0.29

0.5605 0.5444 0.3450

5.80 0.02 0.06 0.12

0.8541 0.9579 0.6799

6.87 0.82 0.02 0.53

0.3639 0.9893 0.4641

0.70

0.5879

0.97

0.5282

1.66

0.3392

0.27

0.6229

0.63

0.3413

0.54

0.4374

0.20

0.8633

0.07

0.9645

0.0001 0.0365 0.3807

7.50 11.94 2.52 0.96

0.0001 0.0148 0.0824

8.72 6.90 3.11 0.95

0.0001 0.0012 0.0480

8.44 51.53 1.27 0.08

0.0001 0.1843 0.8146

3.26 45.03 0.76 1.40

0.0001 0.7011 0.1454

3.24 35.76 10.57 3.17

0.0001 0.0001 0.0059

3.63 30.94 9.47 2.06

0.0001 0.0001 0.0506

8.40 8.29 1.97 0.91

0.0001 0.1113 0.1692

11.07 8.33 2.47 1.14

0.0001 0.0815 0.1403

0.40 1.11

0.6652 0.0430

0.90 0.88

0.3119 0.1001

0.73 0.36

0.3000 0.3048

0.82 3.75

0.3945 0.0003

0.32 1.51

0.9205 0.1251

6.36 0.63

0.0007 0.3253

7.24 0.77

0.0009 0.3144

0.75 1.53

0.5617 0.0540

1.11 1.61

0.4164 0.0653

0.3015

4.75

0.0001

0.62

0.5007

0.24

0.7713

0.56

0.5861

1.74

0.3043

0.10

0.9850

0.17

0.9704

1.82

0.1369

1.38

0.3072

0.33

0.6643

0.30

0.4046

0.95

0.0847

1.29

0.0169

6.60

0.0001

3.83

0.0071

0.54

0.3829

0.49

0.4735

1.05

0.1295

0.70

0.2944

0.36

0.9116

1.21

0.1305

1.18

0.1852

0.97

0.1674

3.02

0.0001

1.99

0.2379

0.40

0.8358

0.25

0.9395

1.65

0.1726

1.63

0.2301

Total C (var.)

Total C (P)

Total N (var.)

Total N (P)

Sand (P)

Silt (var.)

Silt (P)

2 2

12.3 41.0

0.4471 0.1421

10.19 37.99

0.4499 0.1248

4.36 38.91

0.6081 0.0811

10.53 22.36

0.4206 0.2164

5.83 40.36

0.1790 0.0092

4.95 43.38

4 1 2

24.8 0.0 1.9

0.8564 0.2822

20.74 0.00 1.55

0.9736 0.3963

15.64 0.18 0.36

0.3535 0.4062

19.45 0.03 4.57

0.8665 0.1787

4.28 2.12 4.25

0.0804 0.0659

6 1 2 1

3.6 6.6 0.9 0.0

0.0001 0.0631 0.7885

4.29 9.36 2.41 0.38

0.0001 0.0039 0.1177

1.09 0.04 3.18 0.01

0.8143 0.1177 0.9163

5.89 3.87 0.13 0.25

0.0192 0.8794 0.5013

2.88 2.51 0.79 0.05

2

0.5

0.2022

0.88

0.0698

0.53

0.6662

0.10

0.9081

12 2 4 2

1.6 2.4 0.3 0.1

0.0001 0.2126 0.2717

1.59 0.43 0.45 0.10

0.1774 0.4523 0.6588

7.42 4.31 0.35 0.13

0.0071 0.9250 0.8505

6.37 8.64 1.82 0.33

4 2

0.2 0.3

0.3746 0.0838

1.31 1.69

0.0425 0.0022

0.91 1.16

0.6767 0.2351

4

0.5

0.0660

0.37

0.5360

1.96

2

0.0

0.7005

0.12

0.6041

4

0.2

0.4955

0.29

0.6455

48

2.6

5.88

Coarse POM C (P)

C min. (P)

Fine Clay (P)

18.77

7.88

aSummit,

8.77

6.78

9.43

16.74

13.23

15.55

11.85

13.36

midslope, and toeslope. grazed vs ungrazed. gracilis vs O. polyacantha. dBetween plants, hummucks, and under plants. The variance (var.) columns represent the proportion of variance explained by the factor, calculated as the partial R 2 ⫻ 100; P is the probability from the analysis that the factor has a significant effect on the response variable. Factors are organized from the greatest physical separation (most expected variability) to the least. Factors are tested against the block (3) interaction term located in italics immediately below them in column 1. Values in boldface are significant at an alpha level of P ⫽ 0.05. See text for more details on the experimental design. bHeavily cB.

POM, particulate organic matter; C min, carbon mineralization; N min, nitrogen mineralization.

Spatial Variability of Soil Properties

Block Topography Block ⫻ topography (error) Grazing Topography ⫻ grazing Block ⫻ topography ⫻ grazing (error) Species Topography ⫻ species Grazing ⫻ species Topography ⫻ grazing ⫻ species Block ⫻ topography ⫻ grazing ⫻ species (error) Microsite Topography ⫻ microsite Grazing ⫻ microsite Topography ⫻ grazing ⫻ microsite Species ⫻ microsite Topography ⫻ species ⫻ microsite Grazing ⫻ microsite ⫻ species Topography ⫻ grazing ⫻ species ⫻ microsite Block ⫻ topography ⫻ grazing ⫻ species ⫻ microsite (error)

Coarse POM C (var.)

C min (var.)

Fine Clay (var.)

Sand (var.)

df

N min. (P)

N min. (var.)

Heavy Clay (P)

Heavy Clay (var.)

429

430

I. C. Burke and others Figure 2. Total soil carbon and nitrogen along topographic sequences (Sum, summit; Mid, midslope; Toe, toeslope), from grazing treatments (grazed, ungrazed), associated with individual plants (Btw, between; Und, under; Hum, hummock), and from resource islands associated with either B. gracilis (Bogr) or O. polyacantha (Oppo). Vertical bars represent standard errors.

Figure 3. Potential carbon and nitrogen mineralization rates along topographic sequences (Sum, summit; Mid, midslope; Toe, toeslope), from grazing treatments (grazed, ungrazed), associated with individual plants (Btw, between; Und, under; Hum, hummock), and from resource islands associated with either B. gracilis (Bogr) or O. polyacantha (Oppo). Vertical bars represent standard errors.

Many studies in semiarid and arid regions have shown a significant topographic influence on soil organic matter accumulation, with toeslope positions frequently having largest pools and rates of N mineralization (for example, Schimel and others 1985a, 1985b; Aguilar and Heil 1988; Burke 1989; Burke and others 1989). These patterns have been

interpreted as being the result of two simultaneous processes. First, it is suggested that downslope movement of fine soil materials, such as clay, acts to stabilize soil organic matter. For instance, Schimel (1985b) showed that although toeslopes had greater N mineralization rates than higher landscape positions, there was a slower rate of N turnover on a


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Figure 4. Carbon and nitrogen contained in coarse and fine POM from topographic sequences (Sum, summit; Mid, midslope; Toe, toeslope), from grazing treatments (G, grazed; NG, ungrazed), associated with individual plants (Btw, between; Und, under; Hum, hummock), and from resource islands associated with either B. gracilis (Bogr) or O. polyacantha (Oppo). Vertical bars represent standard errors.

Figure 5. Field-measured soil respiration rates and soil water (v/v) along topographic sequences from 3 July to 13 September. Vertical bars represent standard errors.

proportional basis in toeslope positions. In this explanation, erosion leads to a change in soil texture, which is the proximal control over organic matter accumulation and mineralization. In concert with the movement of mineral materials, organic matter may be redistributed downslope through erosion (Aguilar and Heil 1988). However, our data

did not show a significant main effect of landscape position on sand, silt, or clay content (Figure 6). Nor has other work in the shortgrass steppe (Yonker and others 1988; Singh and others 1998) shown a consistent pattern of soil texture along toposequences. A second explanation is that net primary production is higher in toeslope positions because of greater water availability due to subsurface water flow, leading to higher organic matter accumulation rates. Knapp and others (1993) reported that soil water was significantly lower in uplands than in lowland positions for a tallgrass prairie, corresponding with patterns of primary production. However, neither long-term soil water data (Singh and others 1998) nor the weekly soil moisture data collected for this article showed a significant effect of landscape position on soil water content. In addition, long-term soil water data (Sala and others 1992) show that small precipitation events account for the largest fraction of events; such small events would be very unlikely to result in topographic patterns in soil moisture. Finally, the variation could be due to occasional surface water flow during hard rain events. No such rain events were measured during an intensive study during the 1970s at this site; however, we have observed such surface flow once within the past 25 y. Thus, we are unable to clearly identify such surface flow as the mechanism responsible for the landscape scale patterns we have found. In summary, our data showed a consistent and significant effect of landscape position on soil or-

432

I. C. Burke and others Figure 6. Percentage sand, silt, and clay from soils along topographic sequences (Sum, summit; Mid, midslope; Toe, toeslope), from grazing treatments (grazed, ungrazed), associated with individual plants (Btw, between; Und, under; Hum, hummock), and from resource islands associated with either B. gracilis (Bogr) or O. polyacantha (Oppo). Vertical bars represent standard errors.

ganic matter. The pattern is not, at this time, explicable on the basis of downslope movement of sediments or water. Topography influenced the response of soil organic matter to grazing, microsite, and species, which we will discuss in the relevant sections below.

Grazing The main effects of grazing were significant only for coarse POM C and N, which were higher in ungrazed pastures than in grazed pastures (Table 1 and Figure 4). Although grazing was significant, it did not explain a very large proportion of the variance for coarse POM (less than 2% for both C and N). Coarse POM represents relatively recent (years to decade) litter inputs, and these patterns agree with results by Milchunas and others (1989) that show reduced aboveground litter as a result of grazing. In addition, there was an interesting interaction of grazing with topography. For both coarse POM C and N, the largest differences between grazed and ungrazed treatments occurred on toeslope positions. This result also agrees with data from Milchunas and others (1989) that showed highest grazing effects on plant cover in toeslope positions; this interaction explained 3% of the variance in coarse POM C and N.

In situ soil respiration was significantly higher in ungrazed than in grazed pastures throughout the growing season (Figure 7). Potentially mineralizable C and N did not differ between grazing treatments (Figure 3); this result may have occurred because these soils were sieved and much of the fine plant litter that was present on the surfaces of ungrazed pastures was removed. These results represent the first test of our hypothesis that grazing would not significantly alter biogeochemical processes in the shortgrass steppe. The higher litter cover of ungrazed pastures (Milchunas and others 1989) had only a minor effect on soil organic matter, one that we see in the response of in situ respiration rates and the coarse POM C and N.

Microsite The composition of soil material in the hummock beneath plants was 98% (by mass) mineral and only 2% organic, suggesting that an important element in the formation of hummocks is physical redistribution of soil materials. We found that material in the hummock had slightly but significantly more coarse material (sand and silt) than soils beneath them and beside them (the ‘‘between’’ and ‘‘under’’ microsite locations; Figure 6). Either eolian or fluvial erosion could account for this small-scale soil redistribution;


433

Figure 7. Field-measured soil respiration rates and soil water (v/v) from grazing treatments (G, grazed; NG, ungrazed) from 3 July to 13 September. Vertical bars represent standard errors.

our field observations and the very high average windspeeds (5–7 m s⫺1; Lauenroth and Milchunas 1992) of the site suggest that small-scale wind redistribution is a common occurrence. Accumulation of larger particles, such as sand, may occur because these particles are readily transported short distances, through saltation. In addition, we have observed small-scale fluvial transport of organic material associated with rare, large storm events. There was microtopographic relief associated with both species (hummock development), in all landscape positions, and in both grazed and ungrazed treatments (Figure 8). Landscape position, plant species, and an interaction between plant species and grazing all significantly affected the degree of microtopographic relief. For both species and both grazing treatments, microtopographic relief was lowest in toeslope landscape positions, compared with ridge and midslope positions. This strong landscape effect suggests that small-scale soil movement is most prevalent in the summit and midslope positions, with greater net losses between plants and net gains under plants than in toeslope positions. Hummocks were higher under O. polyacantha than under B. gracilis for all landscape positions in the grazed treatment, suggesting that this species is more effective at capturing soil particles. The cladodes are likely to provide a better physical barrier to erosion than the leaves of B. gracilis, since they have a large

Figure 8. Height of hummocks associated with individuals of B. gracilis and O. polyacantha located along topographic sequences.

surface area and tend to be oriented perpendicular to the soil surface. O. polyacantha showed a consistent significant response to grazing in its microtopographic relief; grazed treatments had higher hummocks beneath O. polyacantha than ungrazed treatments, whereas hummocks beneath B. gracilis did not show a consistent response to grazing. Our interpretation of this result is that grazing increases the amount of small-scale soil redistribution. Since cattle avoid walking on or grazing within O. polyacantha clones, soil may accumulate in these areas much more than under B. gracilis, which they both graze and trample. All soil factors were significantly influenced by microsite, including total pools of C and N (Figure 2), mineralizable C and N (Figure 3), and coarse and fine particulate organic matter C and N (Figure 4). Interestingly, we found no differences in soil resources of any type between the two microsites located in the same horizontal layer, that is, the ‘‘between’’ and ‘‘under’’ locations (Figure 1). All of the additional resources attributed to the ‘‘resource islands’’ in our system were located in the raised hummock beneath individual plants. Organic mate-

434


rial may accumulate in hummocks by one or more of three processes (Hook and others 1991), by the accumulation of litter beneath individual plants, by the accumulation of N by roots from adjacent areas in tissues that are deposited as litter beneath the plants, or by physical redistribution of litter and soil organic matter. Our data do not provide the necessary information for distinguishing which of these processes may be most important, but the 98% mineral composition of the hummocks suggests that physical transport is important. Most of the variables we studied had significant two or three-way interactions of microsite with topography (Table 1, fine clay, total C and N, coarse POM C and N). In each case, the accumulation of material in the hummock was most pronounced in the toeslope position. Our hypothesis that grazing would decrease heterogeneity (decrease the effect of microsite for our response variables) could be tested by evaluating the grazing by microsite interaction. This interaction was only significant for total N and coarse POM C and N, and in these cases the data do show that grazing decreased the differences among microsites overall. The microrelief data described above suggest that this effect is species dependent, with microrelief increasing under grazing for O. polyacantha, and remaining the same for B. gracilis.

Plant Species There were few significant differences in soil properties between O. polyacantha and B. gracilis, despite their very considerable differences in life history, photosynthetic pathway, morphology, and susceptibility to grazing. Other than the effects on microtopographic relief discussed above, only potentially mineralizable N (Figure 3) and soil particle distribution (Figure 6) differed between the two species with greater potential N mineralization and greater sand content (and lower clay and silt) under O. polyacantha than B. gracilis. These species effects represented a small proportion of the variance for N mineralization (2%). Recall, however, that our statistical analyses were based upon the concentration of organic matter per cubic centimeter, and not the entire volumetric content. The greater microrelief of O. polyacantha under grazed conditions and the larger circumference of individuals suggests that there is a greater volume of soil in the hummock beneath O. polyacantha and that this species has higher total organic matter content beneath each individual than does B. gracilis. We did not conduct this analysis for several reasons. First, the horizontal dimensions of the two species are very different, with the average diameter of O. polyacantha individu-

als (groups of cladodes) exceeding that of B. gracilis by 5–10 times. Second, the shape of hummocks varies considerably among individuals, and a calculation would have to assume a particular threedimensional shape. We were very surprised by the relative lack of difference in the concentration of organic matter and mineralizable C and N between species, given the very different characteristics in aboveground fine litter production and the vertical distribution of roots (Dougherty and others 1996). One possible interpretation is that the biological differences between the species are not important to the accumulation of organic matter, suggesting that physical redistribution of soils is the key process resulting in the development of resource islands. MartinezTuranzas and others (1997) showed that microtopography associated with perennial bunchgrasses on the shortgrass steppe can form in as little as 8 y after plant establishment, suggesting that soil movement is, indeed, the primary factor forming hummocks in this system.

Major Controls over Spatial Variability in Shortgrass Steppe How do landscape position, grazing, microsite, and plant species compare in their effects on the spatial variability of soil properties in the shortgrass steppe? Partial r2s calculated from our analysis of variance indicate that these four factors and their interactions account for 70%–90% of the variance that we measured (Table 1). There were two particularly interesting trends in the partial r2s. The first insight from the analysis of variance is that landscape position and microsite as single factors explained the largest amount of variance compared with the other single factors, plant species and grazing. This result is significant for management because the small contribution of grazing to the spatial variability of soil organic matter supports our plant community data that show that grazing has relatively small effects on the structure and functioning of this particular ecosystem (Milchunas and others 1988, 1989). Since organic matter in this system is dominated by the very large pools that exist belowground, removal of aboveground biomass does not have a large influence on biogeochemical cycling (Burke and others 1996). In addition, despite the considerable differences between two of the dominant plants of the shortgrass steppe, O. polyacantha and B. gracilis, these species differences do not contribute very much to the overall spatial variability of the system. Rather, as suggested by Vinton and Burke (1997), the microenvironmental conditions created by the presence and absence of individual


435

scales (centuries to millennia), for instance, that create topographic-scale spatial variance, have the largest influence on the soil pools that turn over slowly. Active fractions of organic matter are influenced both by underlying patterns in total organic matter, and by annual, seasonal, and even weekly influences, such as recent plant production, litter quality, and microclimate. The sizes and duration of existence of resource islands in shortgrass steppe ecosystems appear to be controlled by the morphology and life span of the constituent plant species. Because the average life span of the plant species is short relative to the dynamics of the largest organic matter pools, resource islands have their largest impact on the intermediate to rapid turnover pools, such as particulate and mineralizable organic matter. Interestingly, this trend in our results suggests that although resource islands represent an important source of spatial variation in shortgrass steppe, the influence of individual islands is relatively short term.

Realm of Inference

Figure 9. Proportion of the variance explained by topography and microsite for soil carbon and nitrogen in four soil organic matter pools that differ in turnover time. Numbers in parentheses under x axis labels are ranges of turnover times for each variable.

plants is a more important source of variation in this system than is the identity of individual species. Second, we found that the relative importance of microsite and landscape position varied among the key soil organic matter pools, with clear patterns based upon the temporal dynamics of the pools (Figure 9). Topography was most important for the pools of soil organic matter that turn over slowly (total C and N and fine particulate organic matter C and N) and least important for the pools of organic matter that turn over rapidly (coarse POM C and N, mineralizable C and N). Conversely, the effects of microsite were largest for the rapid turnover pools and smallest for the slow turnover pools. We suggest that this result indicates that single factors that create spatial variability in ecosystems differ from one another in their temporal scaling and so differ in their influences on aspects of ecosystem structure and functioning. Processes that occur over long time

How generalizable are our results? In previous work, we have demonstrated that field results from the CPER site are directly applicable to approximately 19% of the shortgrass steppe region of the US, or approximately 6% of the central Great Plains (Burke and Lauenroth 1993). This realm of inference was identified on the basis of similarities in soils, precipitation, temperature, vegetation, and land-use management practices. In addition, however, we think that our results have broad implications for many semiarid regions of the world where plant cover is discontinuous, most of which have been shown to have important topographic scale variation and resource islands associated with individual plants (Burke and others 1998). Prior work has shown that in the much higher precipitation region of the tallgrass prairie, outside our realm of inference where plant cover is continuous, plant species identity has a considerably more important effect on soil organic matter dynamics than occurs in the shortgrass steppe (Vinton and Burke 1997). Specific limitations of our work within semiarid regions of the world with discontinuous plant cover include areas where life form attributes of individual plant species differ a great deal, for instance, in life span and susceptibility to grazing (Schlesinger and others 1990; Lauenroth and others 1997), causing significant effects of plant species and of grazing management on soil organic matter dynamics.

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CONCLUSIONS

northeastern Colorado [senior honors thesis]. Fort Collins, CO: Colorado State University.

Spatial variability in soil organic matter of the shortgrass steppe is most strongly related to topography and plant-induced heterogeneity, or microsite, with relatively small effects of plant species or of grazing. Topography has a strong influence on total pools of organic matter, and neither this study nor previous studies at this site provide adequate explanations for why this variation occurs in this semiarid landscape. Individual plants also create significant variation in soil organic matter, with all of the additional resources accumulating in the hummocks, or raised areas directly beneath plants. Our study provides some evidence that physical redistribution of material by wind or water is at least one important process that leads to this pattern. We also found that two sources of variation that have been shown to be important in other grasslands represent only minor influences on soil organic matter at our site: the effects of grazing and distinctions between individual plant species. Whereas other work has shown that shortgrass steppe vegetation is tolerant to grazing, this study suggests that soil organic matter pools also do not respond substantially to grazing. Finally, the processes that create resource islands and are therefore an important component of spatial variability in shortgrass steppe ecosystems do not affect all soil organic matter pools equally. Topographic variability, developing over pedogenic time scales (centuries to thousands of years), has the largest effect on the most stable pools of soil organic matter. The influence of microsite (resource islands) is most evident in the pools of organic matter that turn over at time scales that approximate the life span of individual plants (years to decades and centuries).

Berendse F. 1994. Litter decomposability—a neglected component of plant fitness. J Ecol 82:187–90.

ACKNOWLEDGEMENTS

Cambardella CA, Elliott ET. 1992. Particulate soil organic-matter changes across a grassland cultivation sequence. Soil Sci Soc Am J 56:777–83.

We acknowledge support from the National Science Foundation Long-Term Ecological Research Program (DEB-9632852).

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