Vegetation and climate characteristics of arid and ... - Sevilleta LTER

Journal of Arid Environments (2002) 51: 55–78 

doi:10.1006/jare.2001.0929, available online at http://www.idealibrary.com on 

Vegetation and climate characteristics of arid and 

semi-arid grasslands in North America and their 

biome transition zone 

T. Hochstrasser*, Gy. Kröel-Dulayw, D.P.C. Petersz,*, J.R. Gosz} 

% Graduate Degree Program in Ecology, Natural Resource Ecology 

Laboratory, and Department of Rangeland Ecosystem Sciences, Colorado 

State University, Fort Collins, CO 80523-1499, U.S.A. 

wInstitute of Ecology and Botany, Hungarian Academy of Sciences, 

Vácrátot H-2163, Hungary 

zUnited States Department of Agriculture-Agricultural Research Service, 

Jornada Experimental Range, Box 30003, MSC 3JER, NMSU, 

Las Cruces, NM, U.S.A. 

}Department of Biology, University of New Mexico, Albuquerque, 

NM 87131, U.S.A. 

(Received 7 March 2001, accepted 28 September 2001) 

The objective of this study was to investigate the relationship among species 

richness, functional group composition, and climate for three sites 

representing the shortgrass steppe, the Chihuahuan desert grasslands and 

their biome transition zone. We found that perennial species richness 

increased as the climate became more favorable for plant growth. The biome 

transition zone was more similar to the Chihuahuan desert grassland site in 

most climate and vegetation characteristics, partly because of the shorter 

biogeographic distance between the two sites. This study clarified the 

ecological position of the biome transition zone site with respect to the 

adjacent biomes. 

# 2002 Elsevier Science Ltd. 

Keywords: annuals; Chihuahuan desert grasslands; ecotone; perennials; 

regional analysis; shortgrass steppe; species area curve 

Nomenclature: USDA NRCS (1999) 

Introduction 

Regional or geographic patterns in species richness are often related to climate 

( Wright, 1983; Currie & Paquin, 1987; Wright et al., 1993; Gross et al., 2000). In 

semi-arid and arid environments, plant species richness increases with higher water 

*Corresponding author. Fax: +1-505-646-5889. e-mail: debpeter@nmsu.edu 

0140-1963/02/010055 + 24 $35.00/0 # 2002 Elsevier Science Ltd.

56 T. HOCHSTRASSER ET AL. 

availability (Shmida, 1985; Ward & Olsvig-Whittaker, 1993; Kutiel et al., 2000). This 

relationship is often interpreted as the increasing branch of a hump-shaped 

relationship between the energy captured by vegetation in photosynthesis (a process 

dependent on water availability) and species richness (Wright et al., 1993). Climatic 

variables that affect water availability include total precipitation and temperature as 

well as their temporal distributions. The correlation between species richness and climate 

within a region is typically based on observations at the local scale at different sites within 

biomes (alpha diversity, sensu Whittaker, 1972) (Shmida, 1985; Gross 

et al., 2000). There have been few studies of species diversity patterns across biome 

transitions (Risser, 1995). Thus, it is unknown how this regional relationship between 

climate and species richness is affected by these transition zones. Because biome 

transition zones are expected to be among the most sensitive areas to directional changes 

in climate and they can have important effects on plant and animal composition 

(Solomon, 1986; di Castri et al., 1988; Bestelmeyer & Wiens, 2001), it is critical to 

understand the relationship between climate and species diversity at broad scales. 

For biome transition zones, it has been proposed that landscape-scale species 

richness (gamma diversity, sensu Whittaker, 1972) is higher than in adjacent biomes 

(Neilson, 1993). Many species reach the edge of their physiological tolerance at the 

edge of biomes (Shmida & Wilson, 1985; Gosz, 1992). Therefore, minor changes in 

soils, topography or disturbance at biome transition zones can result in thresholds in 

response of the vegetation. The predicted result is high spatial heterogeneity in species 

composition (beta diversity, sensu Whittaker, 1972) and therefore high landscapescale 

species richness (gamma diversity) for the biome transition zone compared with 

adjacent biomes (Neilson, 1993). Our goal was to investigate the relationship between 

species richness and climate for two dry grassland biomes and their transition zone 

located along a north–south gradient in North America. Following the above 

hypotheses, we expected that local-scale species richness (alpha diversity) would 

follow patterns in climate. Spatial heterogeneity (beta diversity) was expected to peak 

at the biome transition zone and, as a consequence, landscape-scale species richness 

(gamma diversity) would be highest at the biome transition zone. 

Two grassland biomes of particular importance in North America are the shortgrass 

steppe located along the eastern slope of the Rocky Mountains and the Chihuahuan 

desert grasslands located in the central Rio Grande valley and extending into 

Northern Mexico (Lauenroth & Milchunas, 1992; Schmutz et al., 1992). These 

biomes meet to form a transition zone in central New Mexico (McLaughlin, 1986). 

Plant communities at this transition zone are dominated or codominated by the 

perennial C 4 grasses, Bouteloua gracilis ( Willd. ex Kunth) Lag. ex Griffiths, the 

dominant species of the shortgrass steppe, and Bouteloua eriopoda (Torr.) Torr., the 

dominant species of Chihuahuan desert grasslands (Gosz, 1993). Several species have 

been found to reach the edge of their distribution at this biome transition zone (Gosz, 

1992). However, it has not been investigated how species richness and climate of this 

biome transition zone compare with core areas of the adjacent biomes. 

In arid ecosystems dominated by perennial grasses, highly variable presence and 

abundance of annual species makes cross-site comparisons of richness difficult (Ward 

& Olsvig-Whittaker, 1993). Therefore, it may be important to distinguish responses of 

annual and perennial species. Long-term data are more useful than short-term data 

for examining relationships between annual species richness and climate (Bowers, 

1987). However, few, if any, long-term datasets exist for biomes and their transition 

zones, and in many cases these data have been collected using different methods. 

Thus, a combination of short-term studies using standard methods across sites and 

long-term data often collected with different methods may provide the most 

information about regional patterns in species richness. We had three specific 

objectives: (1) to characterize climate across multiple temporal scales for three sites 

selected to represent two grassland biomes and their transition zone, (2) to evaluate

ARID AND SEMI-ARID GRASSLANDS IN NORTH AMERICA 57 

the above hypotheses by contrasting species richness of annuals and perennials at 

multiple scales between these sites, and (3) to compare the year of sampling with 

multi-year patterns in species richness and long-term climate. 

Method 

Study site descriptions 

We selected three sites to represent the core areas of the shortgrass steppe and 

Chihuahuan desert biomes as well as their transition zone. These sites were selected 

because long-term vegetation and climate data were available for them. 

Shortgrass steppe site (SGS) 

The site selected to represent the shortgrass steppe biome was the Central Plains 

Experimental Range located in northcentral Colorado (40?81N, 104?81W, 1650 m, 

a.s.l.). The topography is gently rolling with level uplands separated by swales. Soils 

range from a clay loam to loamy sand. Moderate grazing by cattle occurs throughout 

the site at intensities maintained since 1939 (Klipple & Costello, 1960). The pasture 

selected for sampling is exposed to moderate grazing. Total basal cover ranges from 

25% to 40%. Plant communities are dominated by B. gracilis; other grasses, 

succulents, shrubs, and forbs account for the remainder of cover (Lauenroth & 

Milchunas, 1992). The average (7S.D.) above-ground net primary production is 172 

(741) g m 2 (ungrazed) and 103 (723) g m 2 (grazed) (Sims & Singh, 1978). A 

complete site description is available at http://sgs.cnr.colostate.edu. 

Chihuahuan desert grassland site (CD) 

The Jornada Experimental Range (32?51N, 106?81W, 1350 m a.s.l) in southern New 

Mexico was selected to represent Chihuahuan desert grasslands. These grasslands 

occur on soils varying in texture from sandy loams to loamy sands with an indurated 

calcium carbonate layer at 15 to 450 cm depths. Grazing by cattle occurs throughout 

the site at varying intensities. Our sampling was conducted in a pasture that has been 

lightly grazed since 1967 (R. Beck, pers. comm.). Grassland communities are 

dominated by B. eriopoda; other grasses, succulents, shrubs, and forbs account for the 

remainder of cover (Paulsen & Ares, 1962). Total basal cover ranges from 5% to 20% 

(Gibbens & Beck, 1988). Average (7S.D.) above-ground net primary production is 

148 (733) g m 2 (ungrazed) and 109 (765) g m 2 (grazed) (Sims & Singh, 1978). A 

complete site description is available at http://jornada.nmsu.edu. 

Chihuahuan desert grassland/shortgrass steppe transition site (SGS/CD) 

The Sevilleta National Wildlife Refuge (34?51N, 106?91W, 1650 m a.s.l.) in central 

New Mexico was selected to represent the biome transition zone between the 

shortgrass steppe and the Chihuahuan desert (Gosz, 1992). Grazing by cattle has 

been excluded from the site since 1973, although grazing by native herbivores, such as 

pronghorn antelope and rabbits, occurs at low-to-moderate intensities. Soils range 

from sandy loam to loamy sand with a calcium carbonate layer at varying depths and 

stages of development from15 to 450 cm. Additional information is available at http:// 

sevilleta.unm.edu.


The area within the SGS/CD selected for study was the McKenzie Flats where 

patches of variable size (o10 to 41000 m 2 ) and shape are clearly distinguished based 

upon their dominance or co-dominance by B. gracilis or B. eriopoda (Gosz, 1993). The 

area selected for sampling consists of patches where both species co-dominate to 

represent the transition zone between community types. Other species of annual and 

perennial grasses and forbs, cactus, and shrubs can be found in all patch types (Kröel- 

Dulay et al., submitted). Cover of all species ranges from 30% to 50% (Peters, 2000a). 

Net primary productivity is estimated at 193 g m 2 (750 S.D.) (D. Moore, pers. 

comm.). 

Climatic analyses 

Monthly weather data from 1916 to 1995 and daily data from 1940 to 1995 were used 

to characterize the climatic regime of each site for a range of temporal scales selected 

to represent different aspects of climate found to be important in dry grasslands. We 

calculated long-term (80 years) mean annual, seasonal, and monthly precipitation and 

temperature (average, minimum, and maximum) for each site. A ‘season’ was defined 

as a three-month time period: winter ( January–March), spring (April–June), summer 

(July–September), and fall (October–December). We also characterized climatic 

variability because of its importance to local and regional patterns in vegetation 

(Conley et al., 1992). The coefficient of variation is often used to describe variability in 

precipitation since it standardizes for the amount received (Conley et al., 1992; 

Cowling et al., 1994). Daily precipitation data were used to characterize the 

distribution of rainfall and drought events within each year because small rainfall 

events and drought are important to vegetation responses in arid and semi-arid 

ecosystems (Albertson & Weaver, 1944; Herbel et al., 1972; Sala et al., 1992). Rain 

events were separated into one of seven size classes based on amount of precipitation 

(p5, 6–10, 11–15, 16–20, 21–25, 26–30, 430 mm event 1 ) (Sala et al., 1992). The 

distribution of droughts was determined by counting the number of sequences of 

consecutive days without rain for each year. Drought events were separated into one of 

eight size classes (1–5, 6–10, 11–15, 16–20, 20–25, 26–30, 31–40, 440 days without 

rain). The impacts of these drought events can vary with the season they are occurring 

in, but this was not addressed in this study. 

We also used the long-term monthly data to compare the amount of precipitation 

received in different types of years based on the ENSO phenomenon. Patterns in 

precipitation are known to differ significantly in the winter and spring during El Niño 

conditions and in the summer during La Niña conditions for central New Mexico 

(Molles & Dahm, 1990), with important effects on the vegetation, such as seedling 

establishment of the dominant species at the SGS/CD site (Peters, 2000b). Similar 

analyses and comparisons have not been conducted for the other two sites. Because 

the southern oscillation index (SOI) is a key indicator of the state of this phenomenon, 

years with a larger negative SOI (p 1?0 5-month running mean) were classified as El 

Niño (Molles & Dahm, 1990). Years with a large positive SOI (X1?0) were defined as 

La Niña; remaining years were considered ‘other’. 

Vegetation sampling 

At each site, we selected a homogeneous 50 ha area representative of the undisturbed 

vegetation under the current grazing management regime. We randomly located 

30–40 pairs of quadrats (4 m 4 m) within each area at points not affected by local 

disturbance regime (e.g. burrowing activity of kangaroo rats) and topographic 

differences. The two quadrats in each pair were separated by 8 m; a nested design was 

used where four 1 m 1 m quadrats were located within each of the 4 m 4m


quadrats (Fig. 1). In each quadrat, we visually estimated the canopy cover (%) 

for each species. This sampling design was shown to be effective at describing 

multiple scales of pattern in vegetation for sand grasslands in Hungary (Kertész & 

Bartha, 1997; Kovács-Láng et al., 2000; Gosz et al., 2000). Sampling was conducted 

during the period of peak growth in vegetation for each site: August 1996 (SGS/CD, 

CD) and mid-June to mid-July 1997 (SGS). 

Year of sampling vs. long-term data 

In order to compare short-term and multi-year vegetation data with climate, we made 

two analyses. First, we compared the weather of the year of sampling to long-term 

climate. For this analysis, we used Bailey’s moisture index developed for semi-arid 

climates to combine monthly precipitation and temperature into one expression of 

moisture availability (Bailey, 1979). This index is based on the premise that 

evaporation is exponentially related to temperature: 

018 PPTðiÞ 

siðiÞ ¼ 

1045 TEMPðiÞ 

where si(i ) is the moisture index of month (i ), PPT(i ) is the amount of precipitation 

(cm) received in month (i ), and TEMP(i ) is the average temperature (1C) in month (i ). 

Figure 1. Sampling design for vegetation sampling where canopy cover of each species in each 

1m 1 m quadrat and 4 m 4 m plot was estimated.


Values of this index decrease with increasing aridity. Yearly estimates of this index were 

calculated by summing monthly values. 

Second, we compared our plant species richness data (cf. below) to multi-year 

vegetation data and growing season (April–September) precipitation from each site. 

The time period and method of sampling differed among sites. For the SGS, 4 years of 

richness data were available (1983–1986) that were collected in 025 m 2 circular plots 

located 7–10 m apart on randomly located transects (Milchunas & Lauenroth, 1995). 

For the SGS/CD, 6 years of data (1994–1999) were obtained from 400 m long 

transects using a line-intercept method (http://sevilleta.unm.edu). For the CD, 9 years 

of data (1989–1997) were available that were collected in 1 m 2 quadrats located 10 m 

apart (L. F. Huenneke, unpubl. data). Because these samples were collected on a 

small scale, our 1 m 1 m quadrats were the most appropriate for comparison. The 

long-term data from the SGS and SGS/CD sites were compared with our data by 

adding species presence in adjacent sampling units until the total area was 1 m 2 (sensu 

Palmer, 1990; Gross et al., 2000). At the SGS, the closest four plots along each 

transect were summed. At the SGS/CD, we assumed the line-intercept was 10-cm 

wide; thus, we summed all species that occurred within each 10 m line segment to 

obtain 1 m 2 ‘quadrats’. We averaged the species richness of each functional group in 

each year for each site. 

Climate 

Statistical analyses 

We tested for differences in monthly and seasonal precipitation, temperature, and 

moisture using a mixed model analysis of variance with year as a random effect since 

these variables may not be independent between sites in any given year (Mixed Model 

Procedure, SAS Institute Inc., 1988). Precipitation was square root transformed. 

Post hoc comparisons of means were conducted using Fisher’s least significant 

difference test with a significance level of 005. Differences in the coefficient of 

variation were determined using p a 90% confidence interval (CI) defined by 

Chebyshev’s rule (CI = mean7 

ffiffiffiffiffiffiffiffi 

10 standard deviation) (Sokal & Rohlf, 1969). 

The amount of rainfall received during October–May and June–September in El 

Niño, La Niña, and other years, as well as the number of droughts and rainfall events 

per year in each category were compared using a one-way analysis of variance 

(ANOVA Procedure, SAS Institute Inc., 1988). Tukey’s studentized range test was 

used to test for differences among sites (a=005). 

Vegetation 

Using our different quadrat sizes and information about the distance between 

quadrats, we constructed a species–area curve for perennial and annual species in the 

following way. We determined the average cumulative species richness of four 

1m 1 m quadrat nested within a 4 m 4 m quadrat (4 m 2 ) and of two 4 m 4m 

quadrats in a quadrat pair (32 m 2 )(sensu Palmer, 1990; Gross et al., 2000). We also 

calculated the average cumulative species richness for three quadrat pairs within 

100 m from each other (96 m 2 ), for seven pairs within 400 m (224 m 2 ), for 14 pairs 

within 600 m (448 m 2 ), and for the whole 50 ha area (1000 m 2 ). Thus, we estimated 

species richness for eight spatial scales (1, 14, 16, 32, 96, 224, 448, 1000 m 2 ), where 

the largest scale (1000 m 2 ) was considered to be an estimate of the species richness in 

the 50 ha area corresponding to the landscape-scale species richness (gamma 

diversity). The species richness within quadrat pairs (1, 14, 16, 32 m 2 ) was considered 

to be the local-scale species richness (alpha diversity).


Spatial heterogeneity of the vegetation composition was described based on species 

composition at the local scale (1, 4, 16, and 32 m 2 ). We used the distance measure 

corresponding to Jaccard’s coefficient (1FJaccard’s coefficient). The mean of this 

distance measure between all possible quadrat pairs was termed habitat heterogeneity 

index (h) by Qian et al. (1997): 

h ¼ 

2 

nðn 

1Þ 

X 

nðn 1Þ=2 

jok 

 

1 

C jk 

A j þ B k 

where A j and B k are the numbers of species in the jth and kth plot under the ith 

pairwise comparison (i =1ton(n 1)/2, n = number of plots in the dataset, and jok), 

respectively, C jk is the number of species common to both the jth and the kth plot. 

Only species that occurred in X10% of the quadrats were used. Means were 

compared between sites using a one-way analysis of variance (General Linear Models 

Procedure, SAS Institute Inc., 1988). Post hoc comparisons of means were conducted 

using Fisher’s least-significant difference test with a significance level of 001. 

C jk 

 

Multi-year data 

Relationships between local-scale species richness for annuals and perennials and 

growing season precipitation were obtained using regression analysis (Regression 

Procedure, SAS Institute Inc., 1988). Differences between the multi-year data 

between sites and our 1 m 1 m quadrats from each site were not assessed statistically 

since sampling methods differed among datasets and sample sizes were small (4–9 

points). Thus, only qualitative comparisons were made. 

Results 

Climate 

Mean annual precipitation (MAP) over the past 80 years was highest at the shortgrass 

steppe site (310 mm; S.D. = 86) and similar for the Chihuahuan desert (248 mm; S.D. 

= 87) and transition zone sites (232 mm; S.D. = 79). The two southern sites also had 

similarly high inter-annual variability of precipitation (CV = 35) compared to the SGS 

site (CV = 28). The SGS site is characterized by a continental climate with peak 

amounts of precipitation in May, June, and July, whereas the CD and SGS/CD are 

characterized by a monsoonal pattern in precipitation with large amounts in July, 

August, and September (Fig. 2). 

Mean annual temperature (MAT) increased from north to south. At the SGS site, 

monthly temperatures ranged from 281C (in January) to 2171C (in July), at the 

SGS/CD site from 261C to2461C, and at the CD site from 381C to2611C. 

Average monthly minimum and maximum temperature showed the same trend as the 

average temperature (results not shown). Maximum temperature was on average 61C 

higher at the SGS/CD than at the SGS and 151C lower at the SGS/CD than at the 

CD. Minimum temperature was on average 351C higher at the SGS/CD than at the 

SGS and 051C lower at the SGS/CD than at the CD. 

When monthly precipitation was summarized according to season, summer ( July– 

September) precipitation was largest at the CD, intermediate at the SGS and lowest at 

the SGS/CD (Fig. 3(a)). The transition site (SGS/CD) had spring moisture (April– 

June) statistically intermediate between the CD and the SGS. The difference in spring 

moisture between these sites is of strong biological importance, too (Gosz, 1992). The 

coefficient of variation in seasonal precipitation was largest in the spring for the CD


Figure 2. Long-term (1916–1995) monthly temperature (1C) ( ) and precipitation (mm) 

( ) for three sites representing two biomes and their transition: (a) shortgrass steppe [SGS], (b) 

shortgrass steppe/Chihuahuan desert grassland [SGS/CD], (c) Chihuahuan desert grassland 

[CD]. Average and standard errors shown. Mean annual precipitation (MAP) and mean annual 

temperature (MAT) also shown. 

site, whereas at the SGS/CD it was largest in the fall (Fig. 3(b)). On a monthly basis, 

July and August were least variable for all three sites (Fig. 3(c)). The SGS was less 

variable in the spring (March–June) compared to the two southern sites that had their 

highest variability during this time period. 

On a daily basis, variability in precipitation at these sites implies that plants have to 

sometimes withstand long periods without rainfall. Drought during the spring may be


Figure 3. Seasonal precipitation for each site (abbreviations same as Fig. 2): (a) average 

seasonal precipitation summed over three-month periods, (b) coefficient of variation of seasonal 

precipitation, and (c) coefficient of variation of monthly precipitation. Average and standard 

errors shown. Stars indicate statistically significant differences ((a) a =0?05, (b) and (c) a = 

0?1). ( ) SGS; ( ) SGS/CD; ( )CD. 

particularly important in explaining differences in the vegetation of these sites. 

Although the distribution of the number of consecutive days without rain was similar 

among sites, important differences were found between the SGS and the two southern 

sites (Fig. 4(a)). A significantly larger number of extended droughts (e.g. 440 days 

without rain) occurred at the SGS/CD and CD sites compared with the SGS site. 

Plants at these sites also have to be capable of utilizing small rainfall events since the 

majority of events are p5 mm at all three sites (Fig. 4(b)). Even though we expected the 

number of large rainfall events to be highest at the most mesic site (SGS), high rainfall 

at this site resulted from a larger number of small- and medium-sized rainfall events. 

Variability in total precipitation between October and May was related to the 

ENSO phenomenon at the two southern sites (Fig. 5). At these sites, precipitation was


Figure 4. Frequency distributions of droughts and rainfall events based on daily weather data 

(1940–1995) for three sites: (a) average number/year of periods without rain in size class and (b) 

average number/year of rainfall events in one of seven size classes. Stars indicate statistically 

significant difference (a=0?05). ( ) SGS; ( ) SGS/CD; ( )CD. 

highest in El Niño years and lowest in La Niña years during this period. June– 

September precipitation was not affected by El Niño or La Niña. By contrast, 

precipitation at the SGS site was similar for all types of years in both seasons. 

Vegetation 

Total cover of the vegetation decreased from north to south. Bouteloua gracilis had a 

higher total cover at the SGS site compared to the other sites, and B. eriopoda had 

similar cover at the SGS/CD and CD site (Fig. 6(a)). The contribution of other 

species to total cover decreased from the north (SGS) to south (CD). Functional 

group composition of subdominant species differed among sites (Fig. 6(b)). At the 

SGS, subdominant cover was evenly divided among C 4 perennials, mainly the grass 

Buchloe dactyloides, succulent species, mainly Opuntia polyacantha, and a group of C 3 

perennials, mainly forbs and subshrubs. At the SGS/CD, the cover of subdominants 

was mainly attributed to C 4 annuals. C 3 perennial forbs and shrubs were the most 

important subdominant species group at the CD site. 

The total number of identified species (gamma diversity) at the biome transition 

zone (52) was more similar to the CD (50) than to the SGS site (67). Three species 

were unidentified at these sites. The two southern, more arid sites also had the most 

species in common (22) that included three species of perennial grasses, seven


Figure 5. Precipitation received at each site during one of three types of years (El Niño (n = 

15), La Niña (n = 9) and ‘other’ (n = 56)) for two time periods. Average and standard error 

shown. Stars indicate statistically significant differences (a =0?05). ( ) EI Niño; ( ) La Niña; 

( ) Other. 

Figure 6. Average cover (%) at each site in 4 m 4 m quadrats: (a) two dominant grasses 

(Bouteloua gracilis, Bouteloua eriopoda) and other/subdominant species combined: ( ) Others; 

( ) B. gracilis; ( ) B. eriopoda; and (b) cover of subdominant species divided into five functional 

groups (C 3 and C 4 annuals include grasses and forbs, C 3 and C 4 perennials include grasses, 

forbs and subshrubs/shrubs): ( )C 3 Annuals; ( )C 4 Annuals; ( )C 3 Perennials; ( )C 4 

Perennials; ( ) Succulents. 

perennial forbs, 10 annuals, and two succulents (Appendix). Few species were found 

at both the transition site and the shortgrass steppe site (6) that included three 

perennial grasses, one perennial forb, one annual, and one subshrub. Only three 

species were common to both the SGS and CD sites; these species were also found at 

the SGS/CD site, and included a perennial C 4 grass (Aristida purpurea), perennial C 4 

forb (Evolvulus nuttalianus), and a C 3 subshrub (Gutierrezia sarothrae). Most species at


Table 1. Number of species by group found within a 50 ha area within each of 

three sites 

Site 

Species group SGS SGS/CD CD 

C 3 annual grasses and forbs 8 4 1 

C 4 annual grasses and forbs 4 16 17 

C 3 perennial grasses and forbs 32 12 13 

C 4 perennial grasses and forbs 15 12 12 

Shrubs and subshrubs 5 5 4 

Succulents 3 3 3 

Total 67 52 50 

the SGS were C 3 perennial grasses and forbs (48%), whereas the other sites 

had a similar number of C 4 annuals, C 3 and C 4 perennial grasses, and forbs (23–34%) 

(Table 1). Numbers of shrub (4–5) and succulent species (3) were similar for all three 

sites. Number of C 3 annual species was low in all cases and decreased from the SGS 

(8) to the CD site (1). 

Figure 7. Number of species within a 50 ha area (1000 m 2 ) at eight spatial scales for three sites: 

(a) perennials (b) annuals. ( ) SGS; ( ) SGS/CD; ( )CD.


Perennial species richness was similar between the SGS/CD and the CD whereas 

annual species richness was highest at the transition zone from the local to the 

landscape scale (Fig. 7). The species–area curve of the perennial species was similar at 

the CD and the SGS/CD, and less steep at the SGS. Spatial heterogeneity varied both 

for the functional group sampled and the size of the sampling quadrat (Fig. 8). The 

spatial heterogeneity of perennial and annual species composition was generally higher 

at the SGS and the SGS/CD compared with the CD. At small spatial scales perennial 

species composition was most heterogeneous at the SGS, whereas at bigger spatial 

scales it was similar at the SGS and the SGS/CD. Quadrat size had a larger influence 

on spatial heterogeneity of annuals than perennials. These patterns may be partially 

explained by differences in numbers of species used to perform these calculations 

since spatial heterogeneity of species composition may increase as species number 

increases. 

Year of sampling vs. long-term data 

The value of Bailey’s annual moisture index decreased from the SGS (3?3) to the two 

southern sites (SGS/CD = 2?1, CD = 2?2) indicating similar aridity for the two 

southern sites and a more mesic climate for the northern site (Fig. 9). For the year of 

sampling, moisture in the spring preceding sampling was below average for most 

months at the two southern sites and near the long-term average the SGS (Fig. 9). 

During the summer of the sampling ( June–August), moisture levels were average or 

above average for all three sites. 

Figure 8. Spatial heterogeneity of species composition for four spatial scales within a 50 ha 

area at three sites: (a) perennial species (b) annual species. Different letters indicate significantly 

different results (a =0?01) for a given quadrat size. ( ) SGS; ( ) SGS/CD; ( )CD.


Figure 9. Long-term average and standard error of monthly moisture index ( ) and for the 

year of sampling (——) for three sites. (a) shortgrass steppe [SGS], (b) transition zone [SGS/ 

CD], (c) Chihuahuan desert grassland [CD]. Months are arranged in the sequence of the water 

year starting with October and ending with September. The arrow indicates the time of 

sampling for each site. 

Based on long-term data, perennial species richness was found insensitive of 

growing season precipitation for all the three sites (Fig. 10(a)). This suggests that our 

short-term data collected in a single year is a reliable measure for perennial species, 

and due to the standardized methodology can be used to compare the sites. However, 

the perennial species values collected in our short-term sampling are very different 

from long-term values for the SGS and the SGS/CD, where 1 m 2 long-term data were 

derived from different sampling designs. This implies that these long-term data cannot 

be used for cross-site comparisons due to differences in sampling designs between 

sites. 

Contrary to perennials, annual species richness showed a statistically significant 

correspondence with growing season precipitation (April–September) at each site 

(Fig. 10(b)).


Figure 10. Species richness at the 1 m 2 scale from our sampling (open symbols) and multi-year 

data for each site (solid symbols) as a function of growing season (April–September) 

precipitation (PPT) (mm) in the year of sampling: (a) perennials, slopes of regression lines 

were not significantly different from zero (average is depicted as regression line) (b) annuals 

(equations for best-fitting regression line on graph). ( ) SGS; ( ) SGS/CD; ( )CD. 

Discussion 

Patterns in climate 

The climate of these sites is typical for arid lands in that their mean annual 

precipitation (MAP) is low and highly variable (Huenneke & Nobel, 1996). MAP 

ranges from 160 to 1700 mm for grasslands all over the world (Ripley, 1992), which 

indicates that our sites are situated at the arid end of this range. The precipitation at 

these sites occurs primarily as small rainfall events, and prolonged periods without 

rain are common (Albertson & Weaver, 1944; Herbel et al., 1972; Sala et al., 1992).


The amount and seasonal of precipitation at these sites is influenced by continental 

scale climate phenomena, such as the strength of westerly winds and high-pressure 

systems (Neilson, 1987). These generating forces are strongly influenced by the Rocky 

Mountains, which form a biogeographic barrier between the SGS site and the two 

southern sites. The SGS site, which is located to the East of the Rocky Mountains, 

had a significantly higher amount and lower variability of MAP, as well as a different 

seasonality of precipitation in comparison with the two southern sites. The winter 

precipitation of the two southern sites was affected by the ENSO phenomenon, 

whereas it was unrelated to the Southern Oscillation at the SGS. The similarity in 

climate between the two southern sites corresponds to a previous study showing that 

they fall within the same general climatic region characterized by monsoon rains 

during the summer and fall (Comrie & Glenn, 1998). 

However, there were also important differences between the climate of the two 

southern sites that may affect species composition. Higher minimum and maximum 

temperatures at the CD compared to the SGS/CD can have important effects on 

species distributions (Paruelo et al., 1998; Alward et al., 1999). Higher and less 

variable spring moisture at the SGS/CD compared to sites further south was also 

found in previous studies using a regional approach to climate analysis (Gosz, 1992; 

Comrie & Glenn, 1998). These seasonal differences may influence the dominance 

patterns and phenology of species at this transition site (Peters, in press). In a regional 

analysis of a biome transition zone in Europe, it was found that strong correlations 

exist between vegetation and certain climate characteristics but different vegetation 

types were related to different characteristics in climate (Moreno et al., 1990). 

Patterns of species richness and functional group abundance 

Our results are similar to other studies (e.g. Cowling et al., 1994; Kadmon & Danin, 

1999; Kutiel et al., 2000) showing that patterns in species diversity depend on 

functional group. Perennial species richness at the local scales (alpha diversity) were 

related to a long-term aridity gradient where richness was higher at the semi-arid SGS 

compared to the more arid CD and SGS/CD sites. Total species richness (gamma 

diversity) followed similar patterns as perennial species. An increase in perennial 

species richness with increasing precipitation has been found in other arid 

environments (Ward & Olsvig-Whittaker, 1993; Leiva et al., 1997; Kutiel et al., 

2000; Kovács-Láng et al., 2000; Gross et al., 2000). These patterns are independent of 

the year of sampling since perennial species richness was not related to growing season 

precipitation. 

Highest local-scale perennial species richness at the SGS site may correspond to the 

more mesic conditions, particularly in the spring when temperatures are cool, that 

allow more C 3 perennial grasses and forbs to coexist with the C 4 dominant, B. gracilis. 

These results are supported by the high cover attributed to perennials at the SGS site 

compared to the other two sites. The lack of a relationship between perennial species 

richness and growing season precipitation for all three sites is not surprising given the 

longevity and drought-tolerance of grasses and forbs in these grasslands (Dittberner, 

1971; Fair et al., 1999). Furthermore, many of these perennials have little ability to 

rapidly respond to short-term favorable conditions since seed storage in the soil is 

highly variable in time and space (Coffin & Lauenroth, 1989; Kemp, 1989). 

By contrast, annual species richness was related to growing season precipitation in 

the year of sampling. Kutiel et al. (2000) also found that the proportion of annual 

species (out of total species found) was more closely related to rainfall in the year of 

sampling than the proportion of perennial species over 4 years. The increase in annual 

species richness with an increase in growing season precipitation within a site is 

common in dry grasslands and reflects the ability of these species to respond


opportunistically to favorable conditions (Bowers, 1987). High seed production, 

effective storage of seeds in the soil, and few requirements for germination allow 

annuals to respond rapidly when conditions are favorable, yet maintain seed sources 

through periods of drought (Danin & Orshan, 1990). Nutrients may accumulate in 

desert soils during drought that lead to an above average response upon drought relief 

(Charley & Cowling, 1968). This may explain the above-average annual species 

richness at the biome transition zone site in the year of sampling. 

We found that the scale of the sampling quadrat can have an important influence on 

the level of spatial heterogeneity (beta diversity) detected. The spatial heterogeneity of 

perennial species composition was high at the SGS and the SGS/CD and lowest at the 

CD. Because the SGS/CD was similar to the CD in other vegetation characteristics, 

our results indicate that spatial heterogeneity of perennial species composition is 

particularly high at the transition zone site. In another study (Kröel-Dulay et al., 

submitted), we found that species composition differs between patches of the two 

dominant species at the SGS/CD site. Our cover data show that dominance increases 

from the SGS to the CD. The CD site is characterized by many rare species, which 

corresponds to the common perception that dominance increases as aridity increases 

(Ward & Olsvig-Whittaker, 1993). 

Evaluation of hypotheses 

Perennial species richness (alpha diversity) of the three sites followed an aridity 

gradient. Therefore, the first hypothesis that species richness (alpha diversity) 

increases with more favorable climatic condition was supported by our data, after we 

distinguished between functional groups of plant species. In general, the two southern 

sites were more similar to each other in most vegetation characteristics than to the 

SGS site. The similarities of these two sites can be explained by their position in 

relation to the Rocky Mountains, which form a major biogeographic barrier. The 

biogeographic proximity of the two southern sites results from both the similarity in 

climate as well as their short geographic distance (257 km vs. SGS/CD to SGS 

955 km). Similarity in climate can explain similarities in functional group composition 

(Cowling et al., 1994), and geographic proximity can increase dispersal between sites 

and therefore increase the floristic similarity of the sites (Leiva et al., 1997). It remains 

to be understood if climate or geographic proximity was more important in 

determining the strong similarity of vegetation characteristics in these two sites. 

Although high spatial heterogeneity of perennial species composition (beta 

diversity) was found at the transition zone, this did not result in higher landscapelevel 

species richness (gamma diversity) as predicted due to the mixing of different 

regional floras and high spatial heterogeneity in the environment at biome transition 

zones (Shmida & Wilson, 1985; Neilson, 1993). However, our results are limited since 

we only sampled a small part of the landscape at each site (50 ha) that was dominated 

by grasses. All three sites contain additional grassland and shrubland types that 

contribute to species richness. Furthermore, differences in landuse (grazing), 

topography, soils, and animal-generated soil disturbances can have important effects 

on species richness at each site (Cornelius et al., 1991; Singh et al., 1996; Fields et al., 

1999; Ryerson & Parmenter, 2001). Variation in these factors could not be accounted 

for in our sampling. So this hypothesis may be more appropriately tested at a larger 

spatial scale than the extent of our sampling. However, rigorous hypothesis testing at 

larger scales may prove difficult (Rice & Westoby, 1983). 

Similar to our study, it was found that ant species composition was more similar at 

the SGS/CD and the CD, than at the southern sites and the SGS (Bestelmeyer & 

Wiens, 2001). However, ant species richness was similar among all three sites. Ant 

species richness is also expected to peak at biome transition zones. Based on patterns


in species composition, highest ant species richness was suggested to occur north of 

the SGS/CD site near the Colorado/New Mexico border where seasonal precipitation 

changes from monsoonal (summer–fall peak) to continental (spring–summer) 

(Comrie & Glenn, 1998). In another study, the probabilities of establishment of the 

two dominant grasses (Bouteloua gracilis and B. eriopoda) were shown by simulation 

modelling to be equal for both species south of the SGS/CD site in southcentral New 

Mexico (Minnick & Coffin, 1999). Additional plant diversity studies at more sites 

along the gradient are needed to determine if peaks in species diversity occur at 

transition zones based on different vegetation and climate characteristics than 

examined in this study. 

Long-vs. short-term vegetation sampling in arid environments 

Our single year–single season sample of the vegetation with standardized methods 

could reveal important differences and similarities between these sites in perennial 

species richness. The long-term data that were available from these sites were not 

gathered with standard methods, thus they could not be used for cross-site 

comparisons. Different sampling methods can have a strong effect on the number 

of species detected at any given site (Stohlgren et al., 1998). Nevertheless, within each 

site, the long-term data were able to reveal the dynamics of species richness over time. 

In the absence of standardized long-term data from each site, a combination of longand 

short-term standardized data can be used. However, in order to compare these 

grassland sites, long-term sampling with standardized methods would be best. 

Summary 

Using long-term data, we found that annual, but not perennial, species richness (local 

or alpha diversity) was related to the weather in the year of sampling at all three of 

these arid and semi-arid grassland sites. Long-term data could not be used for crosssite 

comparison because they were gathered with different methodology at the 

different sites. Using short-term data collected with standardized methodology, we 

found that perennial species richness decreased as the climate became less favorable 

for plant growth along the north–south gradient. Spatial heterogeneity in perennial 

species composition (beta diversity) was high at the shortgrass steppe and the 

transition zone site. However, this did not translate into higher perennial species 

richness at the landscape-level (gamma diversity) at the transition zone site. Instead, 

landscape-level species richness was similar between the biome transition zone and the 

Chihuahuan desert grassland site. The biome transition zone site was more similar to 

the Chihuahuan desert grassland site in most climate and vegetation characteristics, 

which may have been partly due to the shorter biogeographic distance between the 

two sites. Using both long- and short-term climate and vegetation data helped to 

clarify the ecological position of the biome transition zone site with respect to the 

adjacent biomes, but also highlighted the need for long-term studies with standardized 

methodology. 

This study was supported by grants from the National Science Foundation to Colorado State 

University and New Mexico State University (INT-9896168) and to the University of New 

Mexico (DEB-9411976). G. Kröel-Dulay was also supported by a grant from the Hungarian 

National Science Foundation (OTKA 21166). T. Hochstrasser received a scholarship for 

research and further education (bourse de recherche et de perfectionnement) from the 

University of Lausanne, Switzerland and the Francis C. Clark Award for Excellence in Soil 

Biology through Colorado State University. Miklos Kertész developed the sampling design, and 

Sandor Bartha, Miklos Kertész and Edit Kovács-Láng gave valuable advice during field


sampling. Esteban Muldavin, John Anderson, Cindy Villa and Kelly Rimar helped with species 

identification. We thank Jim Zumbrunnen, Robin Reich and Sarah Goslee for statistical advice. 

We thank Brandon Bestelmeyer, Laura Huenneke, Ron Neilson, and an anonymous reviewer 

for helpful comments on the manuscript. Special thanks to Daniel Milchunas, Laura Huenneke 

and the Sevilleta LTER for availability and use of multi-year species richness data. All three sites 

are National Science Foundation supported Long Term Ecological Research sites. The SGS 

LTER is administered by the USDA-ARS and the US Forest service, the Sevilleta LTER by the 

US Fishery and Wildlife Service and the Jornada LTER by the USDA-ARS and New Mexico 

State University. This is Sevilleta Long-Term Ecological Research Program publication 

number 255. 

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Appendix Genus, species and family name of plants found within a 50 ha area at 

each of three sites (SGS = Shortgrass Steppe, SGS/CD = transition zone, CD = 

Chihuahuan Desert Grassland). Three species at the SGS/CD and three at the CD 

were unidentified 

Species name Family SGS SGS/CD CD 

C 3 annual forbs 

Chenopodium leptophyllum Chenopodiaceae 

Ipomoea costellata Convolvulaceae 

Ipomopsis laxiflora Polemoniaceae 

Lappula occidentalis var. Boraginaceae 

 

occidentalis 

Lepidium densiflorum Brassicaceae 

Lupinus pusillus Fabaceae 

Nama hispidus Hydrophyllaceae 

Oenothera spp. Onagraceae 

Plantago patagonica Plantaginaceae 

Proboscidea parviflora Martyniaceae 

C 4 annual forbs 

Amaranthus fimbriatus Amaranthaceae 

Boerhavia spicata Nyctaginaceae 

Chamaesyce glyptosperma Euphorbiaceae 

Chamaesyce revoluta Euphorbiaceae 

Chamaesyce serpyllifolia Euphorbiaceae 

Chamaesyce serrula Euphorbiaceae 

Euphorbia dentata Euphorbiaceae 

Kallstroemia parviflora Zygophyllaceae 

Kallstroemia spp. Zygophyllaceae 

Machaeranthera 

Asteraceae 

 

tanacetifolia 

Mollugo cerviana Aizoaceae 

Pectis angustifolia Asteraceae 

Pectis papposa Asteraceae 

Portulaca halimoides Portulacaceae 

Portulaca oleracea Portulacaceae 

Portulaca parvula Portulacaceae 

Portulaca sp. Portulacaceae 

Salsola kali Chenopodiaceae 

Tidestromia lanuginosa Amaranthaceae 

Tribulus terrestris Zygophyllaceae 

C 3 perennial forbs 

Acourtia nana Asteraceae 

Allium textile Liliaceae 

Astragalus adsurgens Fabaceae 

Astragalus flexuosus Fabaceae 

Astragalus lotiflorus Fabaceae 

Astragalus mollissimus Fabaceae 

Astragalus spp. Fabaceae 

Bahia absinthifolia Asteraceae 

Caesalpinia drepanocarpa Fabaceae 

Caesalpinia jamesii Fabaceae 

Chaetopappa ericoides Asteraceae 

Cirsium sp. Asteraceae 

Convolvulus sp. Convolvulaceace 

Croton pottsii Euphorbiaceae


Appendix (Continued). 


Cryptantha cinerea 

Boraginaceae 

 

var. jamesii 

Cymopterus acaulis Apiaceae 

Dalea candida Fabaceae 

Erigeron sp. Asteraceae 

Evolvulus nuttallianus Convolvulaceae 

Gaura coccinea Onagraceae 

Glandularia wrightii Verbenaceae 

Hybanthus verticillatus Violaceae 

Lesquerella ludoviciana Brassicaceae 

Leucocrinum montanum Liliaceae 

Lithospermum incisum Boraginaceae 

Machaeranthera pinnafitida Asteraceae 

Orobanche fasciculata* Orobranchaceae 

Oxytropis sp. Fabaceae 

Penstemon albidus Scrophulariaceae 

Picradeniopsis oppositifolia Asteraceae 

Potentilla sp. Rosaceae 

Psilostrophe tagetina Asteraceae 

Sarcostemma cynanchoides Asclepiadaceae 

Scutellaria brittonii Lamiaceae 

Senecio tridenticulatus Asteraceae 

Solanum elaeagnifolium Solanaceae 

Sphaeralcea coccinea Malvaceae 

Sphaeralcea hastulata Malvaceae 

Sphaeralcea wrightii Malvaceae 

Talinum aurantiacum Portulacaceae 

Talinum parviflorum Portulacaceae 

Tetraclea coulteri Verbenaceae 

Thelosperma filifolium Asteraceae 

Tragopogon dubius Asteraceae 

Viola nuttallii Violaceae 

Zinnia grandiflora Asteraceae 

C 4 perennial forbs 

Allionia incarnata Nyctaginaceae 

Ammocodon chenopodioides Nyctaginaceae 

Chamaesyce albomarginata Euphorbiaceae 

Chamaesyce micromera Euphorbiaceae 

Gaillardia pinnatifitida Asteraceae 

Heterotheca villosa Asteraceae 

Hymenopappus filifolius Asteraceae 

Liatris punctata Asteraceae 

Lygodesmia juncea Asteraceae 

Mirabilis nyctaginea Nictaginaceae 

Oenothera coronopifolia Onagraceae 

Psoralidium tenuiflorum Fabaceae 

Sophora nuttalliana Fabaceae 

Verbena bracteata Verbenaceae 

C 3 annual grass 

Vulpia octoflora Poaceae 

C 4 annual grasses 

Aristida adscensionis Poaceae 

Bouteloua aristidoides Poaceae


Appendix (Continued). 


Bouteloua barbata Poaceae 

Brachiaria arizonica Poaceae 

Monroa squarrosa Poaceae 

Panicum hirticaule Poaceae 

Tragus berteronianus Poaceae 

C 3 perennial grasses/graminoids 

Carex eleocharis Cyperaceae 

Carex sp. Cyperaceae 

Elymus elymoides Poaceae 

Pascopyrum smithii Poaceae 

C 4 perennial grasses/graminoids 

Aristida purpurea Poaceae 

Bouteloua eriopoda Poaceae 

Bouteloua gracilis Poaceae 

Buchloe dactyloides Poaceae 

Enneapogon desvauxii Poaceae 

Erioneuron pulchellum Poaceae 

Muhlenbergia porteri Poaceae 

Muhlenbergia torreyi Poaceae 

Pleuraphis jamesii Poaceae 

Pleuraphis mutica Poaceae 

Schedonnardus paniculatus Poaceae 

Sporobolus cryptandrus Poaceae 

Sporobolus flexuosus Poaceae 

Sporobolus contractus Poaceae 

C 3 shrubs/subshrubs 

Artemisia frigida Asteraceae 

Ephedra torreyana Ephedraceae 

Ephedra trifurca Ephedraceae 

Gutierrezia sarothrea Asteraceae 

Prosopis glandulosa Mimosaceae 

Senecio sp. Asteraceae 

Yucca elata Agavaceae 

Yucca glauca Agavaceae 

C 4 shrubs/subshrubs 

Atriplex canescens Chenopodiacaeae 

Ericameria nauseosa Asteraceae 

Eriogonum effusum Polygonaceae 

CAM succulents 

Echinocereus viridiflorus Cactaceae 

Escobaria vivipara Cactaceae 

Mammillaria sp. Cactaceae 

Opuntia clavata Cactaceae 

Opuntia imbricata Cactaceae 

Opuntia phaeacantha Cactaceae 

Opuntia polyacantha Cactaceae 

*This species is a non-photosynthetic plant associated with Artemisia frigida.

Vegetation and climate characteristics of arid and ... - Sevilleta LTER

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