SEARCH

SEARCH BY CITATION

Keywords:

  • aboveground annual net primary productivity (ANPP);
  • Chihuahuan desert;
  • desert grasslands;
  • global climate change;
  • precipitation

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • • 
    Plant productivity in deserts may be more directly responsive to soil water availability than to precipitation. However, measurement of soil moisture alone may not be enough to elucidate plant responses to precipitation pulses, as edaphic factors may influence productivity when soil moisture is adequate.
  • • 
    The first objective of the study was to determine the responses of the aboveground annual net primary productivity (ANPP) of three perennial species (from different functional groups) in a Chihuahuan Desert grassland to variation in natural precipitation (annual and seasonal) and a 25% increase in seasonal precipitation (supplemental watering in summer and winter). Secondly, ANPP responses to other key environmental and soil parameters were explored during dry, average, and wet years over a 5-yr period.
  • • 
    ANPP predictors for each species were dynamic. High ANPP in Dasylirion leiophyllum was positively associated with higher soil NH4-N and frequent larger precipitation events, while that in Bouteloua curtipendula was positively correlated with frequent small summer precipitation events with short inter-pulse periods and supplemental winter water. Opuntia phaeacantha was responsive to small precipitation events with short inter-pulse periods.
  • • 
    Although several studies have shown ANPP increases with increases in precipitation and soil moisture in desert systems, this was not observed here as a universal predictor of ANPP, particularly in dry years.

Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Climate change scenarios predict significant alterations in the timing and magnitude of precipitation in arid and semiarid ecosystems, which may result in alterations of plant productivity (Knapp & Smith, 2001; Weltzin & Tissue, 2003; Schwinning et al., 2004; Snyder & Tartowski, 2006). According to the pulse-reserve paradigm, biomass production following a precipitation event is dependent on the intervals between precipitation events and the duration necessary to obtain sufficient water to initiate biomass production (Noy-Meir, 1973). When a precipitation event is large, rapid biomass production is initiated and continues until the available water is consumed (Noy-Meir, 1973; Sala & Lauenroth, 1982). If precipitation events are small but tightly clustered, soil water may accumulate and generate a single large period of biomass production (Noy-Meir, 1973; Reynolds et al., 2004). In contrast, intermediate intervals between precipitation events may trigger a series of shorter periods of biomass production as the soil begins to dry between these events; however, the available soil moisture will not become fully depleted unless the interval between precipitation events exceeds the soil moisture recharge interval. When the available soil water supply becomes fully depleted, biomass production ceases (Noy-Meir, 1973; Reynolds et al., 2004).

Recently, Ogle & Reynolds (2004) developed a threshold-delay model that incorporates precipitation thresholds, lag times in response variables, resource partitioning, and plant functional type strategies to predict plant responses to variable precipitation regimes. This model suggests that productivity in deserts is a direct response not to precipitation (as suggested by the pulse-reserve model) but rather to soil water availability (Reynolds et al., 2004). However, measurement of soil moisture alone may not be sufficient to determine plant responses to precipitation pulses, as nitrogen (N) availability (e.g. Whitford, 1986) and soil temperatures may also control primary production even during periods when soil moisture is adequate. Coexistence of different plant functional types in arid environments may reflect niche partitioning of soil water through plant physiological responses to seasonal temperatures and utilization of soil water in different soil layers (Guo & Brown, 1997; Reynolds et al., 2004; Muldavin et al., 2008).

Although many variables often affect plant aboveground annual net primary productivity (ANPP) in desert ecosystems, ANPP typically correlates strongly with annual precipitation (Knapp & Smith, 2001; Weltzin & Tissue, 2003; Huxman et al., 2004b). Similarly, mesic grasslands are strongly influenced by the amount and distribution of annual precipitation, but ANPP in any given year can fluctuate depending on precipitation frequency and magnitude, as well as plant production occurring in the previous year (Sala et al., 1988; Knapp et al., 2001; Oesterheld et al., 2001). ANPP may also be strongly influenced by the mixture of plant functional types within a community. For example, shrub ANPP was associated with annual precipitation, but ANPP in grasses was not; however, when grass and shrub ANPPs were pooled, the different functional responses to precipitation were masked (Jobbagy & Sala, 2000). Therefore, when studying community ANPP responses to precipitation, individual plant functional group responses should be considered in order to understand their unique contribution to the overall community (Jobbagy & Sala, 2000; Huenneke et al., 2002; Havstad et al., 2006).

In the Chihuahuan Desert, a 25% increase in winter and summer precipitation has been predicted, with most of the additional precipitation occurring in fewer, more intense precipitation events (Johns et al., 1997; Flato et al., 2000). Our first objective was to determine the responses of ANPP of three dominant perennial species (Dasylirion leiophyllum, a shrub; Opuntia phaeacantha, a succulent; and Bouteloua curtipendula, a grass) to variation in the timing and magnitude of natural precipitation (annual and seasonal) and a 25% increase in seasonal precipitation (e.g. supplemental watering in summer and winter). Secondly, we explored ANPP responses to other key environmental and soil parameters to determine the potential impact of these variables on ANPP for these three different functional plant types.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Study site

The study was conducted in a sotol grassland ecosystem (1526 m elevation) within the Pine Canyon Watershed, Big Bend National Park (BBNP), TX, USA (29°5′N, 103°10′W, 1526 m above sea level), in the Chihuahuan Desert. The dominant plant genera include Dasylirion, Condalia, Opuntia, Bouteloua, Agave, Nolina, and Muhlenbergia, with Dasylirion, Opuntia, and Bouteloua composing 30–50% of the community plant cover. This soil overlays a fractured igneous bedrock formation, also known as the Lajitas-rock outcrop complex; the soil texture is a sandy-loam within a rocky A-horizon and has little to no litter layer (Aide et al., 2003). BBNP has a bimodal and highly variable seasonal rainfall regime, with the majority of annual precipitation occurring as monsoonal rain in the late summer. The average annual precipitation is c. 365 mm (range 170–570 mm) at Panther Junction (c. 6 km from the field site). Most of the seasonal precipitation (45%) occurs in the summer months (June, July, and August). The fall (September, October, and November) receives c. 27% of the annual rainfall, while 17% occurs in the spring (March, April, and May) and only 11% occurs in the winter (December, January, and February). Average daily air temperatures at the site in the summer range from a minimum of 18–22°C to a maximum of 32–36°C, while winter daily air temperature averages can range from a minimum of 1–6°C to a maximum of 14–20°C. Spring and fall experience similar temperatures, ranging from 9 to 30°C.

Research plots and study plants

The study focused on three dominant perennial species representing three different functional types: Dasylirion leiophyllum (Engelm.) (sotol; a C3 shrub), Opuntia phaeacantha (Engelm.) (brownspine prickly pear; a crassulacean acid metabolism (CAM) succulent), and Bouteloua curtipendula ((Michx.) Torr.) (sideoats grama; a C4 grass). In January 2002, water treatments were applied to smaller individual plots (three 1 × 0.5 m plots per treatment; one plant per plot; 12 plots per species; 36 plots in total) and larger community plots (three 3 × 3 m plots per treatment; many plants per plot; 12 plots in total) to simulate a Hadley Climate Model 2 scenario (Gordon et al., 2000), as described in Patrick et al. (in press). Plots were distributed randomly throughout the sotol grassland site and watering was contained within each plot (Patrick et al., in press). The smaller individual plots were used for ANPP measurements and the larger community plots were used for soil sampling, in order to avoid long-term damage to the ANPP plants, as previously described for this site (Bell et al., 2008; Patrick et al., in press). All plots had similar soil conditions, which are characteristic of this region of BBNP (Bell et al., 2008; Patrick et al., in press).

Dasylirion leiophyllum is a polycarpic, dioecious perennial (C3) with drought-resistant fibrous leaves that arise from and wrap around a woody caudex. The roots of this species are fibrous and typically spread densely through the upper 10–30 cm of soil. Older plants have roots that can extend even deeper and to further distances from the plant. Flowering usually occurs in the spring or early summer (Powell, 1998). Opuntia phaeacantha is a succulent CAM plant that produces green pads with 3–7-cm-long dark-brown spines and has shallow roots that are usually found in the first 5–10 cm of the soil. Most roots are in close proximity to the plant, although they can extend up to a meter away in the upper soil layers as well as downward to 30 cm in older and larger plants. Flowering generally occurs from May to June, producing either new pads or red to purple fleshy fruit in the spring (Powell & Weedin, 2004). Bouteloua curtipendula is a perennial bunch grass (C4) with fibrous roots extending into the upper 10 cm of soil; flowering primarily occurs in June–November (Powell, 2000).

Precipitation manipulation and soil moisture

Seasonal precipitation treatments were applied to the research plots as follows: natural precipitation only (control (C)); natural precipitation plus supplemental summer precipitation (S); natural precipitation plus supplemental winter precipitation (W); and natural precipitation plus supplemental summer and winter precipitation (SW). Water was added as a single storm event during the winter (water application in February) and as three distinct storm events in the summer (June, July, and August). For winter and summer watering in 2002, supplemental precipitation amounts were determined as 25% of average seasonal rainfall amounts based on 30-yr rainfall data from National Park Service records. In subsequent years, supplemental water treatment amounts were determined as 25% of ambient precipitation received preceding a watering event (e.g. 3 months before the winter supplemental event, and 1 month before each summer supplemental event). Plots were slowly watered using watering cans to limit any possible surface runoff, and watering occurred on approximately the same dates in each year. Water for the tanks was provided by a local water source and transported to the site annually by the BBNP fire department.

Soil maximum and minimum temperatures were measured (15 cm depth) using HOBO ProTemp/Temp External data loggers (Onset Computer Corporation, Pocasset, MA, USA). The volumetric soil moisture content was measured from 2003 to 2006 using ECH2O-10 dielectric aquameter probes (Decagon Devices, Pullman, WA, USA). One probe was placed in each plot at a soil depth of 15 cm. Measurements were logged every 2 h on Em5 data loggers (Decagon Devices) and averaged for the 24-h period. Daily high and low air temperatures and precipitation were obtained from a meteorological weather station located at Panther Junction park headquarters. Daily precipitation was used to calculate annual precipitation magnitude and inter-pulse periods (e.g. dry day events).

Soil nutrient and chemical measurements

Soil collections consisted of two composite soil samples collected from 0–15-cm depths from each community plot (12 treatment plots; 24 composite samples collected during each sample period across the study). One composite soil sample consisted of at least four subsamples within the plot to provide the best possible representation of the soil nutrient and chemical properties of the plot as a whole (Bell et al., 2008). In every composite sample, soils were collected from under each dominant plant (D. leiophyllum, O. phaeacantha, and B. curtipendula) as well as from interplant spaces. Exchangeable soil ammonium (inline image-N) was determined via colorimetric assay and was extracted 1 d after the sample collection date using a 50-ml 2M KCl solution from 5 g per dry weight equivalent soil per sample (Robertson et al., 1999). Concentrations of extractable NO3-N were determined 1 d after the sample collection date by A&L Soil Laboratories (Lubbock, TX, USA) using ion-specific probes. Soil pH was measured using a 2 : 1 paste extract, and soil organic matter (SOM) was estimated using a loss-on-ignition method (Robertson et al., 1999). All soil samples were collected in March and September for each year (end of winter and summer seasons in BBNP) for each plot and analyzed within 2 wk of collection; more details on the sampling and laboratory methods are given in Bell et al. (2008).

Plant measurements

Total leaf area per plant (m2) was estimated by multiplying the total number of leaves per plant with the average leaf area of each plant for 2002–2004 and 2006 (Smith & Knapp, 2001). The frequency of measurements varied depending on the species, but measurements were taken at least four times a year (once each season). Aboveground biomass (vegetative and reproductive) was determined nondestructively for each measurement period by taking off-plot destructive samples of each species to develop allometric regressions between field growth measurements (leaf area) and biomass (Retta et al., 2000; Smith & Knapp, 2001). Because of the unique morphology of these plants, this provided more accurate biomass estimates than using plant volume alone (Huenneke et al., 2001). Aboveground net primary production (NPP) was estimated on a plot ground area (m2) basis for each measurement month by subtracting the total plant biomass (vegetative and reproductive) for the month from that of the previous month (Huenneke et al., 2001; Muldavin et al., 2008). These values were obtained for each measurement month and then totalled at the end of each year to obtain aboveground ANPP for that year. Only positive increments were used as it was generally difficult to determine whether any negative increment values (e.g. declines in biomass) were a result of herbivory, senescence or human error (Huenneke et al., 2001). The aboveground ANPP values were still an underestimate of total plant NPP because belowground productivity was not determined.

Statistical analysis

All growth and soil parameters were analyzed using repeated measures ANOVA to compare the main effects and interactive effects of water treatment and year (spss 11.5; SPSS Inc., Chicago, IL, USA). Parameters were considered significantly different when P ≤ 0.05; significant effects were further analyzed using least significant difference (LSD) post hoc tests. Linear regression analyses were used to relate aboveground ANPP to natural precipitation events and supplemental precipitation treatments. Because of the nature of the data and small sample size, a Kendall's tau correlation matrix was used to detect potential correlations between species ANPP and environmental parameters (Field, 2000). These parameters included precipitation variables (annual precipitation, annual events, magnitude of precipitation event, and inter-pulse period), maximum and minimum air and soil temperatures, and soil variables (soil moisture, soil nitrate, soil ammonium, soil organic matter, and soil pH). The magnitude of the precipitation event was divided into four classes (< 5, 5–10, 10–20, and > 20 mm) and the inter-pulse period was divided into five classes (0–5, 6–10, 11–20, > 20, and > 50 d). R values in this matrix can range from −1.0 to 1.0 (1.0 indicates perfectly positively correlated variables and −1.0 indicates perfectly negatively correlated variables) and were considered significantly different when P ≤ 0.05.

Redundancy analysis (RDA) was used to explore the environmental influence of precipitation (annual precipitation, annual events, magnitude of precipitation event, and inter-pulse period), temperature (maximum and minimum air and soil temperatures), and soil (moisture, nitrate, ammonium, organic matter, and pH) factors on above-ground ANPP (canoco 4.5; University of South Bohemia, Ceske Budejovice, Czech Republic). This constrained ordination technique is analogous to a multivariate multiple regression and was chosen because it performs well with nonorthogonal and collinear gradient data (McGarigal et al., 2000). Each year was analyzed separately to determine the possible effects of specific environmental factors on ANPP over time. Almost all RDA graphs had a high species–environment correlation value, suggesting that most of the measured environmental variables were important, although there may be other unaccounted factors of equal importance (McGarigal et al., 2000). Only the first and second axes were shown in the graphs, with the first axis explaining most of the variation for RDA graphs.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Environmental variables

Mean high and low monthly air temperatures were similar in each year during the 5-yr study period (Fig. 1a) and within the average range of air temperatures that have been measured over a 30-yr period for BBNP (1976–2006). Annual precipitation varied among years (see Supporting Information Table S1), but, relative to the mean annual precipitation for 1976–2006 (365 mm), measurement years were designated as follows: 2001 (191 mm, dry); 2002 (357 mm, average); 2003 (410 mm, average); 2004 (567 mm, wet); 2005 (329 mm, average); and 2006 (274 mm, dry). Seasonal precipitation varied for each year (Fig. 1b; see Table S2). In general, summer received the largest amount of precipitation and exhibited the shortest inter-pulse periods, while winter (December through February) was the driest period with the longest inter-pulse periods (> 20 or 50 d). During the experimental period, winters were exceedingly dry in 2002 (89% below average) and 2006 (63% below average). Summer precipitation was average for all years except 2004, when summer precipitation was 47% above average. In the driest year (2001), precipitation was below average for all seasons (Table S2). Volumetric soil water content was higher after supplemental or natural precipitation events, particularly large events, and generally ranged from 3 to 10% (Fig. 1c). Measured soil moisture was higher in wet years than in dry years, and soil moisture differed by season, with greater soil moisture in the summer and fall compared with the winter and spring. In addition, at the same site during this period it was observed that maximum soil moisture was highest in the SW plots, lower in the S and W plots, and lowest in the C plots during the summer (Patrick et al., in press).

image

Figure 1. Monthly environmental variables for the sotol grassland in Pine Canyon at Big Bend National Park for 2002–2006: (a) average maximum and minimum air temperatures, (b) monthly precipitation, and (c) soil moisture for each supplemental water treatment. Arrows indicate watering additions (the longer the arrow, the larger the event) and occur in this order (in mm): 2002: 11, 11, 11; 2003: 7, 7, 17, 21; 2004: 7, 3, 18, 27; 2005: 20, 7, 12, 16; and 2006: 4, 7, 0.7, and 5. C, control; SW, summer/winter; W, winter; S, summer.

Download figure to PowerPoint

Soil responses to natural and supplemental precipitation

Annual shifts in extractable soil NO3-N were observed during the study period, as NO3-N concentrations were significantly higher in 2002 and 2003 compared with 2004 and 2006 (P ≤ 0.001; Fig. 2a). In 2002, soil NO3-N concentrations were significantly higher in the W plots (P = 0.05) compared with all other treatment plots, while the S treatment had significantly higher values than the control (P = 0.044; Fig. 2a). In 2004, soil NO3-N concentrations in the W treatment were significantly higher than in the control plots (P ≤ 0.05; Fig. 2a). Extractable soil NH4-N concentrations (Fig. 2b) and soil organic matter (Fig. 2c) showed no response to supplemental water treatments. Annually, soil NH4-N concentrations in 2006 were significantly higher (P ≤ 0.001) than in previous years (Fig. 2b). Soil pH was generally acidic (pH 5.6–6.0) throughout 2002–2003 for all plots (Fig. 2d). In 2004, significant differences in overall soil pH values were observed as soil in plots receiving supplemental water became more basic (Fig. 2d).

image

Figure 2. Annual averages for (a) extractable soil NO3-N, (b) extractable soil NH4-N, (c) soil organic matter, and (d) soil pH for the sotol grassland in Pine Canyon at Big Bend National Park for 2002–2006. Values are plotted as means ± SEM (2002, n = 15; 2003, n = 12; 2004, n = 30, 2006, n = 12) for each supplemental water treatment (C, control; SW, summer/winter; W, winter; and S, summer). Values designated with letters exhibit a statistical difference at P ≤ 0.05 for each year.

Download figure to PowerPoint

Aboveground ANPP responses to natural and supplemental precipitation

Dasylirion leiophyllum did not exhibit an overall response in ANPP to increasing annual precipitation (R2 = 0.013; P = 0.211), although there was a significant difference in ANPP among years (Fig. 3a; Table 1). Bouteloua curtipendula exhibited a significant (R2 = 0.058; P ≤ 0.05) decline in aboveground ANPP with increasing annual precipitation, but only 6% of the variation in ANPP could be explained by annual precipitation (Fig. 3b; Table 1). No relationship between ANPP and annual precipitation was observed in O. phaeacantha during this study (R2 = 0.000; P ≤ 0.1; Fig. 3c; Table 1). However, O. phaeacantha did exhibit a significant increase in ANPP as a result of increasing precipitation in an average year (2003) (R2 = 0.381, P ≤ 0.05). Seasonally, D. leiophyllum produced higher biomass during the summer, B. curtipendula in mid and late summer, and O. phaeacantha during the spring and early summer (data not shown).

image

Figure 3. Aboveground annual net primary productivity (ANPP) for (a) Dasylirion leiophyllum, (b) Opuntia phaeacantha, and (c) Bouteloua curtipendula for 2002–2004 and 2006 from the sotol grassland in Big Bend National Park. Values are plotted as means ± SEM (n = 3) for each supplemental water treatment (C, control; SW, summer/winter; W, winter; and S, summer). Statistical difference: *, P ≤ 0.1; **, P ≤ 0.05.

Download figure to PowerPoint

Table 1. F-values for repeated measures and one-way ANOVAs used to test supplemental water treatment, year, and their interactions for annual net primary productivity (ANPP) for each species
StatisticsDasylirion leiophyllumBouteloua curtipendulaOpuntia phaeacantha
  1. Statistical difference: *, P ≤ 0.1; **, P≤ 0.05; ***, P≤ 0.001.

  2. C, control; SW, summer/winter; W, winter; S, summer.

Repeated measures
Year4.683**3.958*17.597***
Treatment0.5720.8321.751 (SW > C*)
Year × treatment1.5611.1232.186
One-way
20020.6084.054** (W > C,SW,S)0.474
20030.2012.049 (W > S**)2.293 (SW > C*,W**)
20040.8350.2211.152
20061.644 (S > SW*)0.0780.586

Dasylirion leiophyllum showed no significant response of ANPP to seasonal supplemental precipitation during the 5-yr period (Fig. 3a; Table 1). Supplemental water additions increased ANPP in W plants of B. curtipendula compared with all treatments in an average year (2002; P ≤ 0.05; Fig. 3b). ANPP of W plants was only significantly greater than that of S plants in 2003 (P ≤ 0.05), with no treatment differences in other years. Opuntia phaeacantha did not exhibit a significant ANPP response to supplemental precipitation (Fig. 3c), except in 2003, where SW plants had significantly higher ANPP than W plants (P ≤ 0.05).

Redundancy and Kendall tau analyses

When each year was analyzed separately using RDA, a different tri-plot arrangement emerged (Fig. 4a–d); only significant environmental and soil variables are shown for each year. One consistent pattern was that concentrations of NH4-N, NO3-N, and soil organic matter, followed by inter-pulse duration and magnitude of precipitation event, were typically of high importance in predicting ANPP for D. leiophyllum and B. curtipendula. In the first 3 yr (2002–2004), when annual precipitation amounts were average or above average, 70–90% of the variability in ANPP of the different species could be explained by these soil and environmental variables. In a dry year (2006), only 32% of the variability in ANPP could be explained by these same factors.

image

Figure 4. Redundancy analysis (RDA) comparing aboveground annual net primary productivity (ANPP) of Dasylirion leiophyllum (Dasy), Opuntia phaeacantha (Opu), and Bouteloua curtipendula (Bout) with measured environmental variables for the sotol grassland in Big Bend National Park for each year: (a) 2002, (b) 2003, (c) 2004, and (d) 2006. ANPP values are means ± SEM (n = 3) and soil values (extractable soil NO3-N, extractable soil NH4-N, soil organic matter, and soil pH) are means ± SEM (2002, n = 15; 2003, n = 12; 2004, n = 30; 2006, n = 12) for each treatment. Treatments: closed circles, control (C); open circles, summer and winter (SW); triangles, winter (W); squares, summer (S). Environmental variables: IP, inter-pulse period (d); M, precipitation magnitude (mm); Prec, annual precipitation; Eve, annual events; SOM, soil organic matter; SM%, soil moisture; MaxAT, maximum air temperature; MinAT, minimum air temperature; MaxST, maximum soil temperature; MinST, minimum soil temperature.

Download figure to PowerPoint

For D. leiophyllum, ANPP was highly correlated with concentrations of NH4-N, NO3-N, and soil organic matter during average to wet years (Fig. 4a–c), but not during a dry year (2006), when ANPP was more highly correlated with climatic variables, specifically small precipitation events and short inter-pulse periods (Fig. 4d). However, D. leiophyllum ANPP also exhibited a negative correlation with soil moisture and NO3-N during a wet year (2004) (Fig. 4c). ANPP in D. leiophyllum showed a positive correlation with S treatment during average (2002) and dry (2006) precipitation periods. In the Kendall tau correlation analysis, D. leiophyllum showed a significant positive correlation with NH4-N (R = 0.595) but only in 2004 (Table 2); there was no significant correlation with any precipitation variable (data not shown).

Table 2.  Kendall tau correlation matrix among species annual net primary productivity (ANPP) and environmental parameters measured in the sotol grasslands in Big Bend National Park (BBNP) for each year
2002BoutDasyOpuNO3-NNH4-NSOMpHPrecSM%
Bout1.000        
Dasy0.0911.000       
Opu−0.182−0.0611.000      
NO3-N0.7880.061−0.0301.000     
NH4-N0.2600.1370.4730.3511.000    
SOM0.1820.121−0.1520.3330.1071.000   
pH0.0610.0000.5150.2120.595−0.0911.000  
Prec−0.0670.1680.235−0.0340.1860.000−0.0671.000 
SM%−0.2680.2350.034−0.168−0.017−0.067−0.2680.3331.000
2003BoutDasyOpuNO3-NNH4-NSOMpHPrecSM%
Bout1.000        
Dasy−0.1211.000       
Opu−0.4240.2731.000      
NO3-N0.2420.030−0.1521.000     
NH4-N0.107−0.198−0.3210.2601.000    
SOM−0.0610.2730.0910.333−0.0151.000   
pH0.455−0.1210.121−0.0610.0760.3031.000  
Prec−0.0670.0340.570−0.034−0.084−0.134−0.1681.000 
SM%−0.4360.2680.2680.134−0.1520.1680.1340.0001.000
2004BoutDasyOpuNO3-NNH4-NSOMpHPrecSM%
Bout1.000        
Dasy−0.3821.000       
Opu−0.0300.1071.000      
NO3-N0.046−0.092−0.0761.000     
NH4-N−0.3330.5950.030−0.0461.000    
SOM0.0300.229−0.091−0.2900.0301.000   
pH−0.2420.046−0.1210.0460.121−0.2421.000  
Prec−0.0340.0510.5030.338−0.101−0.1010.4691.000 
SM%0.101−0.321−0.235−0.068−0.168−0.3020.268−0.3331.000
2006BoutDasyOpuNO3-NNH4-NSOMpHPrecSM%
  1. Bout, Bouteloua curtipendula; Dasy, Dasylirion leiophyllum; Opu, Opuntia phaeacantha; SOM, soil organic matter; Prec, annual precipitation; SM%, volumetric soil moisture.

  2. R values in bold indicate a statistical difference of P ≤ 0.05.

Bout1.000        
Dasy0.3031.000       
Opu−0.2120.0611.000      
NO3-N−0.061−0.3330.0611.000     
NH4-N0.242−0.0300.0610.5761.000    
SOM−0.0300.1820.4550.1820.1211.000   
pH0.3330.1820.0300.0610.000−0.0911.000  
Prec−0.2010.0670.101−0.335−0.268−0.201−0.4361.000 
SM%−0.1010.101−0.0670.570−0.369−0.168−0.2680.6671.000

During wet years, ANPP in B. curtipendula was correlated with soil variables and long inter-pulse periods, while in a dry year greater control of ANPP was exerted by climatic variables and soil NH4-N concentrations. In an average year (2002), ANPP was positively correlated with soil organic matter and negatively correlated with the occurrence of an inter-pulse period of 6–10 d and precipitation magnitudes of 10–20 mm (Fig. 4a). As precipitation increased, B. curtipendula ANPP was positively correlated with NH4-N and NO3-N concentrations, soil moisture, and inter-pulse periods > 20 d (Fig. 4b,c). However, ANPP was negatively correlated with small precipitation magnitudes of 5–10 mm in a wet year (2004). In a dry year (2006), which had an extensive drought period at the beginning of the year followed by large moisture pulses in the summer, variation in ANPP of B. curtipendula was not strongly correlated with the measured environmental variables (Fig. 4d). Bouteloua curtipendula ANPP did show significant correlations in the Kendall tau correlation matrix for 2002 and 2003 (Table 2). Bouteloua curtipendula was positively correlated with NO3-N (R = 0.788) in 2002 and negatively correlated with soil pH (R = −0.455) in 2003. There was no significant correlation with any precipitation variables (data not shown).

Variability in O. phaeacantha ANPP was more highly correlated with climatic variables (magnitude of precipitation event and inter-pulse period) than soil variables, although the response varied depending on moisture inputs during the specific year. During average and wet years, ANPP was correlated with annual precipitation, number of precipitation events, small and medium precipitation magnitude events, and shorter inter-pulse periods (Fig. 4a–c). During a dry year, variation in O. phaeacantha ANPP was correlated with soil pH, small precipitation magnitude events, and medium inter-pulse periods (Fig. 4d). In O. phaeacantha, ANPP was negatively correlated with inter-pulse periods > 50 d during average years (2002 and 2003), soil NO3-N in a wet year (2004), and soil organic matter in a dry year (2006). ANPP in O. phaeacantha was correlated with the W treatment in average (2002) and dry (2006) years. Opuntia phaeacantha ANPP also showed correlations for each year in the Kendall tau correlation analysis (Table 2). Opuntia phaeacantha ANPP was positively correlated with NH4-N (R = 0.473) and soil pH (R = 0.515) in 2002 and annual precipitation in 2003 (R = 0.570) and 2004 (R = 0.503). It was negatively correlated with soil organic matter (R = −0.455) in 2004. Opuntia phaeacantha was the only species that also showed correlations of ANPP with inter-pulse period and magnitude intervals, but only for 2003 and 2004. In 2003, ANPP was positively correlated with precipitation magnitude classes 5–10 mm (R = 0.532), 10–20 mm (R = 0.698), and > 20 mm (R = 0.698), as well as inter-pulse period class 11–20 d (R = 0.698). It was negatively correlated with inter-pulse period class > 20 d (R = −0.698). For 2004, O. phaeacantha ANPP was positively correlated with precipitation magnitude classes < 5 mm (R = 0.533), 10–20 mm (R = 0.533), and > 20 mm (R = 0.533), as well as the inter-pulse period class 0–5 d (R = 0.503).

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Aboveground ANPP responses to natural precipitation

The responses of ANPP of our three dominant perennial species (D. leiophyllum, a shrub; O. phaeacantha, a succulent; and B. curtipendula, a grass) to variation in the timing and magnitude of natural precipitation (annual and seasonal) during the 5-yr study period varied for each species. Dasylirion leiophyllum exhibited its highest ANPP during the wettest year (2004) when precipitation was 55% above average, precipitation events were 44% above average, and large precipitation events (> 20 mm) were 140% more frequent than average. These frequent large precipitation events, combined with frequent smaller events, wet the upper and lower soil layers for long periods of time, allowing roots in both zones to utilize soil moisture for most of the growing season, thereby promoting plant growth (Gibbens & Lenz, 2001). Apparently, frequent large precipitation events in the wet year, in which these events were twice as frequent as in any other year, were key determinants of productivity in this deeper rooted shrub. Fravolini et al. (2005) found similar results with another deep-rooted shrub, mesquite (Prosopis velutina), where large rain events during wet summers resulted in increased water uptake and photosynthesis, especially in course-textured soils, leading to increased biomass.

In B. curtipendula, ANPP was highest in an average precipitation year following a dry year, which suggests that total annual precipitation was not a major determinant of productivity in this species. The winter precipitation was below average, but summer precipitation was average, with most of the precipitation occurring in small (< 5 mm) events during this period of high physiological activity. During the summer, there were also very few inter-pulse periods > 10 d, indicating that the soil was rarely dry for extended periods of time. These data suggest that frequent, small precipitation events with relatively few extended dry inter-pulse periods promote productivity in this shallow-rooted bunchgrass. Similarly, Jobbagy & Sala (2000) observed a weak correlation of ANPP with annual precipitation in several grass species in the Patagonian steppe, as ANPP was more strongly correlated with seasonal precipitation amounts and temperature. This suggests that grass ANPP was primarily responsive to the seasonal timing and magnitude of precipitation and subsequent soil moisture, rather than to the amount of precipitation received annually. In our study, ANPP in B. curtipendula may be more influenced by seasonal precipitation patterns, mainly summer precipitation with frequent precipitation events and few long inter-pulse periods, rather than total summer precipitation amounts. In addition, adequate winter and spring precipitation may maintain root development, allowing these plants to fully exploit water availability when physiologically active during the late spring and summer months (Bates et al., 2006; Muldavin et al., 2008). Furthermore, the decline of ANPP during wetter years (2003–2004) may be attributable to other limiting factors (e.g. NH4-N and NO3-N) or increased competition as a result of greater plant density (Yahdjian & Sala, 2006; Muldavin et al., 2008).

In O. phaeacantha, ANPP was highest in an average precipitation year (2003), when plants received average winter precipitation, as well as average fall precipitation in the previous year. This precipitation pattern differed from that in other study years, when plants were exposed to either dry winters, or both a dry winter and a dry fall in the previous year. In the spring of 2003, precipitation magnitude was below average, but most precipitation events were small (< 5 mm) with most inter-pulse periods < 20 d, indicating that soil moisture was probably adequate at shallow rooting depths (5–10 cm), where O. phaeacantha roots are most abundant and can readily utilize water (Dougherty et al., 1996). Pad production occurs in mid/late spring (Powell, 1998) and is largely dependent on prior fall and winter precipitation, when water is stored in the soil and in the succulent pads of O. phaeacantha, rather than only current spring precipitation events (Muldavin et al., 2008).

Aboveground ANPP response to supplemental precipitation

ANPP responses to increased supplemental seasonal precipitation also varied depending on the species. Supplemental seasonal precipitation did not influence ANPP in D. leiophyllum, but greater ANPP was observed for B. curtipendula. In B. curtipendula, supplemental winter precipitation in an average year (2002), following a very dry year, generated a large positive ANPP response in our winter watering treatment. The large pulse of supplemental water (e.g. 25 mm, which constituted more than half of the natural winter precipitation) plus the very dry conditions preceding the supplemental winter precipitation event was sufficient to initiate plant growth when temperatures increased in the spring. The significant impact of this large single rainfall event indicates the critical importance of winter precipitation in this grass species. In subsequent years, winter precipitation was generally average and the impact of the W treatment was no longer observed. The SW treatments in 2002 did not generate the same response as the W treatment, suggesting that summer additions altered the impact of the winter precipitation treatment. Bates et al. (2006) observed a similar response during a 7-yr study in the northern Great Basin where shallow-rooted grasses produced greater biomass when the majority of the precipitation was shifted from spring to winter. Furthermore, it is possible that the upper soils may have approached water-holding capacity during the summers of 2003 and 2004, resulting in the treatments being less effective in triggering individual growth responses (Muldavin et al., 2008).

In O. phaeacantha, SW treatments increased ANPP following two consecutive years of average precipitation. Pad production in O. phaeacantha depends largely on water that is available before mid-spring, when new pads are produced. Therefore, supplemental water in 2002 for the SW treatment in the summer during an average summer and fall rainfall period and in the winter during an average winter followed by a dry spring may have delivered sufficient additional water for increased pad production in 2003. However, because O. phaeacantha pads store water, it is unclear if increased winter precipitation could also significantly contribute to increased pad production the following summer.

Best predictors of ANPP

Past studies have shown that annual precipitation may only partially explain differences in ANPP (Knapp & Smith, 2001; Huenneke et al., 2002). Storm frequency and intensity may also be important regulators of plant productivity (Knapp et al., 2002; Schwinning et al., 2004; Fravolini et al., 2005). In slow-growing species, such as commonly occur in desert environments, growth responses to precipitation events may be delayed or not affected to a significant degree (Huxman et al., 2004a; Sher et al., 2004).

When we further explored ANPP responses to other key environmental and soil parameters to determine the potential impact of these variables on the ANPP of each species, we found that the responses varied for each species and between sampling years. For D. leiophyllum, soil organic matter (RDA analysis) and soil NH4-N (Kendall tau correlation) may have strong impacts on aboveground ANPP during wet years. However, during drier years, ANPP was mainly affected by climatic variables (e.g. small precipitation events and shorter inter-pulse periods) rather than soil variables (e.g. NH4-N and NO3-N). The importance of the woody caudex of this species to plant growth dynamics has never been fully investigated, but it may allow the plant to store sufficient quantities of water and nutrients in wetter years. The ability to store water in some shrubs allows survival through long drought periods (Barker et al., 2006). Dasylirion leiophyllum is a very long-lived and slow-growing plant, potentially establishing an ‘island of fertility’ which may provide the plant with a localized nutrient supply when soil moisture is not limiting (Schlesinger & Pilmanis, 1998; Reynolds et al., 1999). Dasylirion leiophyllum also had roots within the upper soil horizons, allowing it to compete with grasses for soil moisture, as well as having deeper roots giving it access to water in lower soil horizons (Scott et al., 2000; Gibbens & Lenz, 2001). Because of this extensive root system, it is difficult to clearly distinguish which climatic variables have a greater impact on ANPP as indicated by the Kendall tau correlation.

For B. curtipendula, soil organic matter (RDA analysis) and NO3-N (Kendall tau correlation) had strong impacts on ANPP in an average precipitation year, suggesting that nitrogen mineralization rates may be a significant regulator of ANPP when soil moisture is sufficient for growth. In above-average precipitation years, soil NH4-N and NO3-N concentrations had stronger impacts on ANPP than in average rainfall years (RDA analysis), perhaps as a result of changes in available nitrogen. During a dry year, climatic variables and soil NH4-N had a greater impact on ANPP because soil moisture was apparently scarcer in the upper soil horizons. It is possible that seasonal precipitation, in particular winter precipitation, and longer inter-pulse duration may have a greater impact on ANPP in B. curtipendula, especially during a dry season when soil moisture is less available (Bates et al., 2006; Yahdjian & Sala, 2006; Muldavin et al., 2008).

ANPP in O. phaecantha appears to be primarily regulated by climatic variables rather than soil variables, particularly precipitation magnitude and length of inter-pulse periods (RDA analysis and Kendall tau correlation). Following an average precipitation year, ANPP may be affected more strongly by shorter inter-pulse period duration (11–20 d) than by annual precipitation; however, when annual precipitation was above-average, both precipitation magnitude and the frequency of shorter inter-pulse periods had a greater impact on ANPP. An exception to this may occur with winter precipitation (e.g. when there was greater winter precipitation in 2003 and 2004, but ANPP in O. phaeacantha still declined in 2004). This may be a result of changes in soil NO3-N, because ANPP in O. phaeacantha was negatively correlated with NO3-N concentrations, suggesting that increased nitrogen availability may limit ANPP (Whitford, 1986; Austin et al., 2004; Havstad et al., 2006).

It is possible that there may be a memory or lag effect caused by past precipitation events as a result of pad water storage in O. phaeacantha (Dougherty et al., 1996; Schwinning et al., 2004). During a dry year, soil pH, small precipitation magnitude events, and inter-pulse periods of 11–20 d had significant impacts on ANPP in O. phaeacantha. There was almost no new pad production during the dry spring of a dry year (2006). During dry winters and springs, O. phaeacantha may maintain current pads rather than promote vegetative and sexual reproduction, resulting in very little detectable change in ANPP (Powell & Weedin, 2004). In the RDA analysis, O. phaeacantha ANPP was positively correlated with inter-pulse periods of 11–20 d and negatively related to inter-pulse periods > 20 d for all years except 2004, which experienced more frequent shorter inter-pulse periods. Therefore, medium inter-pulse periods are apparently greater regulators of ANPP in O. phaeacantha than precipitation magnitude and amount.

In this Chihuahuan Desert grassland ecosystem in Big Bend National Park, ANPP is limited not only by soil moisture and temperature constraints, but also by soil NO3-N and NH4-N concentrations. During consecutive years of average and above-average precipitation, extractable nitrogen pools were negatively correlated with annual precipitation, intermediate magnitude events, and shorter inter-pulse periods (RDA analysis). This may suggest that soil N is assimilated as soil moisture becomes available via precipitation events (Bell et al., 2008). However, during an average rainfall year following a dry year (2002) or a dry year following an average rainfall year (2006), extractable nitrogen pools were positively correlated with annual precipitation, intermediate magnitude events, and shorter inter-pulse periods (Muldavin et al., 2008). This may indicate a seasonal soil N build-up during seasons with sporadic precipitation. Furthermore, as soil moisture becomes available via successive precipitation events, soil nitrogen becomes soluble and readily available for plant and microbial uptake.

Soil nitrogen is commonly limiting in desert grasslands, especially in wet years as a result of declines in nitrogen availability and immobilization from previous year ANPP (Whitford, 1986; Austin et al., 2004; Havstad et al., 2006). Wind and water erosion, especially in sites of low plant cover, may also cause shifts in available nitrogen in wetter years (Schlesinger & Pilmanis, 1998; Havstad et al., 2006). Plant cover in the sotol grassland site is c. 50%, resulting in a patchy landscape. Consequently, the bare soil-patches could experience soil nitrogen loss through runoff during wetter years, which may cause vegetation shifts in arid ecosystems as a result of limited N availability (Schlesinger et al., 2000; Muldavin et al., 2008).

Conclusions

Many studies have shown that ANPP increases with greater annual precipitation. In this sotol grassland site in the Chihuahuan Desert, there was no universal predictor of ANPP, as the response of each species to precipitation and other environmental factors (e.g. soil NH4-N and NO3-N concentrations) was highly variable over the 5-yr study period. In the more deeply rooted shrub D. leiophyllum, annual precipitation was important in predicting ANPP, which was highest in the wettest year as a result of frequent large precipitation events. In the more shallow-rooted grass B. curtipendula, the magnitude of annual precipitation was not a key determinant of ANPP as frequent small precipitation events in the summer with relatively few long dry inter-pulse periods seemed to regulate periods of active growth. Supplemental winter water during a very dry winter also stimulated ANPP in B. curtipendula, suggesting the critical importance of winter precipitation in this grass, especially during a dry year. In the succulent O. phaeacantha, there was no relationship between ANPP and annual precipitation, but small precipitation events with short inter-pulse periods during the winter and fall may have generated the greatest productivity.

ANPP was regulated by soil NO3-N and NH4-N concentrations, particularly in wet years. In D. leiophyllum, soil NH4-N was positively correlated with ANPP in wet years but not in average or dry years. In B. curtipendula, soil NO3-N and NH4-N were positively correlated with ANPP in wet years compared with dry years. In O. phaecantha, precipitation magnitude and inter-pulse duration were positively correlated with ANPP. In average and wet years, c. 70–90% of the variability of ANPP could be explained by climatic and soil factors. In dry years, only 32% of the variability in ANPP could be explained by these same factors. Therefore, in dry years, other factors (e.g. herbivory, aboveground and belowground competition, and the pattern of plant recovery from drought stress) apparently have important impacts on plant productivity. Consequently, because of the diversity of environmental factors regulating ANPP in these three representative species, and their interactive effects, it may be difficult to accurately predict plant response in this desert ecosystem to variable timing and magnitude of precipitation, especially in dry years.

Acknowledgements

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

The project was supported by a USGS small watershed grant to JCZ and an NPS grant to DTT and JCZ. Assistance from Dr Joe Sirotnak, John Forsythe, the BBNP Fire Crew, and the rest of the staff at BBNP was greatly appreciated. We would also like to thank the following people for their assistance in the field: Natasja van Gestel, Elizabeth Gordon, Heath Grizzle, Erin Hurt, Michael Loik, Kari Malen, Amber Nagy, Lisa Patrick, and Jen Resinger.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • Aide M, Aide C, Dolde J, Guffey C. 2003. Geochemical indicators of external additions to soils in Big Bend National Park, Texas. Soil Science 168: 200208.
  • Austin AT, Yahdjian L, Stark JM, Belnap J, Porporato A, Norton U, Ravetta D, Schaeffer SM. 2004. Water pulses and biogeochemical cycles in arid and semiarid ecosystems. Oecologia 141: 221235.
  • Barker DH, Vanier C, Naumburg E, Charlet TN, Nielsen KM, Newingham BA, Smith SD. 2006. Enhanced monsoon precipitation and nitrogen deposition affect leaf traits and photosynthesis differently in spring and summer in the desert shrub Larrea tridentata. New Phytologist 169: 799808.
  • Bates JD, Svejcar T, Miller RF, Angell RA. 2006. The effects of precipitation timing on sagebrush steppe vegetation. Journal of Arid Environments 64: 670697.
  • Bell C, McIntyre N, Cox S, Tissue D, Zak J. 2008. Soil microbial responses to temporal variations of moisture and temperature in a Chihuahuan Desert grassland. Microbial Ecology 56: 153167.
  • Dougherty RL, Lauenroth WK, Singh JS. 1996. Response of a grassland cactus to frequency and size of rainfall events in a North American shortgrass steppe. Journal of Ecology 84: 177183.
  • Field A. 2000. Discovering statistics using SPSS for windows. Trowbridge, UK: The Cromwell Press Ltd.
  • Flato GM, Boer GJ, Lee WG, McFarlane NA, Ramsden D, Reader MC, Weaver AJ. 2000. The Canadian Centre for climate modeling and analysis global coupled model and its climate. Climate Dynamics 16: 451467.
  • Fravolini A, Hultine KR, Brugnoli E, Gazal R, English NB, Williams DG. 2005. Precipitation pulse use by an invasive woody legume: the role of soil texture and pulse size. Oecologia 144: 618627.
  • Gibbens RP, Lenz JM. 2001. Root systems of some Chihuahuan desert plants. Journal of Arid Environments 49: 221263.
  • Gordon C, Cooper C, Senior CA, Banks H, Gregory JM, Johns TC, Mitchell JFB, Wood RA. 2000. The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Climate Dynamics 16: 147168.
  • Guo Q, Brown JH. 1997. Interactions between winter and summer annuals in the Chihuahuan Desert. Oecologia 111: 123128.
  • Havstad KM, Huenneke LF, Schlesinger WH. 2006. Structure and function of a chihuahuan desert ecosystem. Oxford, UK: Oxford University Press.
  • Huenneke LF, Anderson JP, Remmenga M, Schlesinger WH. 2002. Desertification alters patterns of aboveground net primary production in Chihuahuan ecosystems. Global Change Biology 8: 247264.
  • Huenneke LF, Clason D, Muldavin E. 2001. Spatial heterogeneity in Chihuahuan Desert vegetation: implications for sampling methods in semi-arid ecosystems. Journal of Arid Environments 47: 257270.
  • Huxman TE, Smith MD, Fay PA, Knapp AK, Shaw MR, Loik ME, Smith SD, Tissue DT, Zak JC, Weltzin JF et al . 2004a. Convergence across biomes to a common rain-use efficiency. Nature 429: 651654.
  • Huxman TE, Synder KA, Tissue D, Leffler AJ, Ogle K, Pockman WT, Sandquist DR, Potts DL, Schwinning S. 2004b. Precipitation pulses and carbon fluxes in semiarid and arid ecosystems. Oecologia 141: 254268.
  • Jobbagy EG, Sala OE. 2000. Controls of grass and shrub aboveground production in the Patagonian steppe. Ecological Applications 10: 541549.
  • Johns TC, Carnell RE, Crossley JF, Gregory JM, Mitchell JFB, Senior CA, Tett SFB, Wood RA. 1997. The second Hadley Centre coupled ocean atmosphere GCM: model description, spinup and validation. Climate Dynamics 13: 103134.
  • Knapp AK, Briggs JM, Koelliker JK. 2001. Frequency and extent of water limitation to primary production in a mesic temperate grassland. Ecosystems 4: 1928.
  • Knapp AK, Fay PA, Blair JM, Collins SL, Smith MD, Carlisle JD, Harper CW, Danner BT, Lett MS, McCarron JK. 2002. Rainfall variability, carbon cycling, and plant species diversity in a mesic grassland. Science 298: 22022205.
  • Knapp AK, Smith MD. 2001. Variation among biomes in temporal dynamics of aboveground primary production. Science 291: 481484.
  • McGarigal K, Cushman S, Stafford S. 2000. Multivariate statistics for wildlife and ecology research. New York, NY, USA: Springer Science+Business Media.
  • Muldavin EH, Moore DI, Collins SL, Wetherill KR, Lightfoot DC. 2008. Aboveground net primary production dynamics in a northern Chihuahuan Desert ecosystem. Oecologia 155: 123132.
  • Noy-Meir I. 1973. Desert ecosystems: environment and producers. Annual Review of Ecology and Systematics 4: 2551.
  • Oesterheld M, Loreti J, Semmartin M, Sala OE. 2001. Inter-annual variation in primary production of a semi-arid grassland related to previous-year production. Journal of Vegetation Science 12: 137142.
  • Ogle K, Reynolds JF. 2004. Plant responses to precipitation in desert ecosystems: integrating functional types, pulses, thresholds, and delays. Oecologia 141: 282294.
  • Patrick LD, Ogle K, Bell CW, Zak JC, Tissue DT. (in press. Physiological responses of two contrasting desert plant species to precipitation variability are differentially regulated by soil moisture and nitrogen dynamics. Global Change Biology.
  • Powell AM. 1998. Trees and shrubs of the trans-pecos and adjacent areas. Austin, TX, USA: University of Texas Press.
  • Powell AM. 2000. Grasses of the trans-pecos and adjacent areas. Marathon, TX, USA: Iron Mountain Press.
  • Powell AM, Weedin JF. 2004. Cacti of the trans-pecos and adjacent areas. Lubbock, TX, USA: Texas Tech University Press.
  • Retta A, Armbrust DV, Hagen LJ, Skidmore EL. 2000. Leaf and stem area relationships to masses and their height distributions in native grasses. Agronomy Journal 92: 225230.
  • Reynolds JF, Kemp PR, Ogle K, Fernandez RJ. 2004. Modifying the ‘pulse reserve’ paradigm for deserts of North America: precipitation pulses, soil water, and plant responses. Oecologia 141: 194210.
  • Reynolds JF, Virginia RA, Kemp PR, De Soyza AG, Tremmel DC. 1999. Impact of drought on desert shrubs: effects of seasonality and degree of resource island development. Ecological Monographs 69: 69106.
  • Robertson GP, Coleman DC, Bledsoe CS, Sollins P. 1999. Standard soil methods for long-term ecological research. New York, NY, USA: Oxford University Press.
  • Sala OE, Lauenroth WK. 1982. Small rainfall events: an ecological role in semiarid regions. Oecologia 53: 301304.
  • Sala OE, Parton WJ, Joyce LA, Lauenroth WK. 1988. Primary production of the central grassland region of the United States. Ecology 69: 4045.
  • Schlesinger WH, Pilmanis AM. 1998. Plant-soil interactions in deserts. Biogeochemistry 42: 169187.
  • Schlesinger WH, Ward TJ, Anderson J. 2000. Nutrient losses in runoff from grassland and shrubland habitats in southern New Mexico: II. Field plots. Biogeochemistry 49: 6986.
  • Schwinning S, Sala OE, Loik ME, Ehleringer JR. 2004. Thresholds, memory, and seasonality; understanding pulse dynamics in arid/semi-arid ecosystems. Oecologia 141: 191193.
  • Scott RL, Shuttleworth WJ, Keefer TO, Warrick AW. 2000. Modeling multiyear observations of soil moisture recharge in the semiarid American Southwest. Water Resources Research 36: 22332246.
  • Sher AA, Goldberg DE, Novoplansky A. 2004. The effect of mean and variance in resource supply on survival of annuals from Mediterranean and desert environments. Oecologia 141: 353362.
  • Smith MD, Knapp AK. 2001. Physiological and morphological traits of exotic, invasive exotic, and native plant species in tallgrass prairie. International Journal of Plant Science 162: 785792.
  • Snyder KA, Tartowski SL. 2006. Multi-scale temporal variation in water availability: implications for vegetation dynamics in arid and semi-arid ecosystems. Journal of Arid Environments 65: 219234.
  • Weltzin JF, Tissue DT. 2003. Resource pulses in arid environments – patterns of rain, patterns of life. New Phytologist 157: 167173.
  • Whitford WG. 1986. Pattern and process in desert ecosystems. Albuquerque, NM, USA: University of New Mexico Press.
  • Yahdjian L, Sala OE. 2006. Vegetation structure constrains primary production response to water availability in the Patagonian steppe. Ecology 87: 952962.

Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information

Table S1 Annual precipitation, number of precipitation events, precipitation magnitude class, and inter-pulse period class for 2001–2006 at the Panther Junction Visitor’s Center in Big Bend National Park.

Table S2 Seasonal precipitation, number of precipitation events, precipitation magnitude class, and inter-pulse period class for 2001–2006 at the Panther Junction Visitor’s Center in Big Bend National Park.

Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

FilenameFormatSizeDescription
NPH_2643_sm_Suppmat.doc93KSupporting info item