Semi-arid Grass Research Articles

A systematic strategy to analyse individual‐based models reveals pathways of degradation and recovery in Patagonian rangelands

One of the central problems in ecology is how to scale from small‐scale observations and experiments to large‐scale patterns and processes. One approach to such upscaling is to use dynamic simulation models, but their application to large scales relevant for management is limited by computational costs, and their outputs are difficult to analyse without a systematic strategy. Our general objective is to propose such a strategy. The idea is to approximate the dynamics of detailed simulation models through a set of states, external drivers, and transition matrices, and then use Markov chain and network analysis of the resulting transition matrices to gain insights into the dynamics of the underlying detailed model. We used the individual‐based model COIRON, which simulates the dynamics of semiarid grass steppes in Patagonia (Argentina) under alternative grazing management, as example. Our specific objectives are to identify pathways of degradation and rehabilitation, as well as critical grazing thresholds and early‐warning vegetation states to guide sustainable grazing management in these steppes. Our results indicate nonlinear effects of stocking rate and grazing season on steppe dynamics. Markov chain analysis suggests benefits of seasonal over continuous grazing at intermediate stocking rates, and network analysis of recovery and degradation trajectories shows that intermediate stocking rates maximize differences between grazing seasons. Finally, our analysis identified specific vegetation states as early warning signals that indicate a high risk of irreversible vegetation changes. Patagonian grass steppes should ideally be managed with multi‐paddock grazing at moderate stocking rates around 0.5 sheep ha−1. The transition matrices summarize the relevant key features of the detailed model for larger scales, and applying Markov and network theory provides a systematic strategy to analyse its dynamics to respond to biological questions, both are often difficult to obtain by direct analysis of the detailed model.

Modeling seasonal vegetation phenology from hydroclimatic drivers for contrasting plant functional groups within drylands of the Southwestern USA

In dryland ecosystems, vegetation within different plant functional groups exhibits distinct seasonal phenologies that are affected by the prevailing hydroclimatic forcing. The seasonal variability of precipitation, atmospheric evaporative demand, and streamflow influences root-zone water availability to plants in water-limited environments. Increasing interannual variations in climate forcing of the local water balance and uncertainty regarding climate change projections have raised the potential for phenological shifts and changes to vegetation dynamics. This poses significant risks to plant functional types across large areas, especially in drylands and within riparian ecosystems. Due to the complex interactions between climate, water availability, and seasonal plant water use, the timing and amplitude of phenological responses to specific hydroclimate forcing cannot be determined a priori, thus limiting efforts to dynamically predict vegetation greenness under future climate change. Here, we analyze two decades (1994–2021) of remote sensing data (soil adjusted vegetation index (SAVI)) as well as contemporaneous hydroclimate data (precipitation, potential evapotranspiration, depth to groundwater, and air temperature), to identify and quantify the key hydroclimatic controls on the timing and amplitude of seasonal greenness. We focus on key phenological events across four different plant functional groups occupying distinct locations and rooting depths in dryland SE Arizona: semi-arid grasses and shrubs, xeric riparian terrace and hydric riparian floodplain trees. We find that key phenological events such as spring and summer greenness peaks in grass and shrubs are strongly driven by contributions from antecedent spring and monsoonal precipitation, respectively. Meanwhile seasonal canopy greenness in floodplain and terrace vegetation showed strong response to groundwater depth as well as antecedent available precipitation (aaP = P − PET) throughout reaches of perennial and intermediate streamflow permanence. The timings of spring green-up and autumn senescence were driven by seasonal changes in air temperature for all plant functional groups. Based on these findings, we develop and test a simple, empirical phenology model, that predicts the timing and amplitude of greenness based on hydroclimate forcing. We demonstrate the feasibility of the model by exploring simple, plausible climate change scenarios, which may inform our understanding of phenological shifts in dryland plant communities and may ultimately improve our predictive capability of investigating and predicting climate-phenology interactions in the future.

Effects of soil moisture, net radiation, and atmospheric vapor pressure deficit on surface evaporation fraction at a semi-arid grass site

Surface energy partitioning is one of the most important aspects of the land-atmosphere coupling. The objective of this study is to examine how soil moisture (SM) and atmospheric conditions (net radiation, Rn and vapor pressure deficit, VPD) affect surface evaporation fraction (EF, determined by LE/(LE + H), where LE and H are latent and sensible heat flux, respectively) with measurements at a semi-arid grass site in China during the mid-growing season, 2020. The three factors (SM, Rn, and VPD) were divided into different levels, and then their effects on EF were investigated qualitatively using a combinatorial stratification method and quantificationally using a path analysis. Generally, the results indicated that the effect of one factor of SM, Rn and VPD on EF was influenced by the other two factors. EF tended to increase with increasing SM. Increased VPD (Rn) enhanced (weakened) the SM-EF relationship. When soil was dry, EF tended to decrease with increasing VPD; when soil was wet, EF initially levelled off and then decreased with increasing VPD. Increased Rn enhanced (weakened) the positive (negative) effect of VPD on EF when soil was wet (dry). In terms of Rn effect, EF tended to decrease as Rn increases. Further, path analysis suggested that SM, Rn, and VPD not only directly affected EF, but also indirectly affected EF, mainly through canopy conductance (Gs) and temperature difference between land surface and air (∆T). The direct effect of SM accounted for >50 % of its total effect on EF, while the total effects of Rn and VPD on EF were dominated by their indirect effects. These observational evidences may have implications for improving representation of land-atmosphere coupling in atmospheric general circulation models over the semi-arid regions covered by grass.

Effects of Soil Moisture, Net Radiation, and Atmospheric Vapor Pressure Deficit on Surface Evaporation Fraction at a Semi-Arid Grass Site

Effects of Soil Moisture, Net Radiation, and Atmospheric Vapor Pressure Deficit on Surface Evaporation Fraction at a Semi-Arid Grass Site

UAV‐derived imagery for vegetation structure estimation in rangelands: validation and application

AbstractThe purpose of this study is to develop an unmanned aerial vehicle (UAV)‐based remote sensing method that can estimate vegetation indicators in arid and semiarid rangelands. This method was used to quantify six rangeland indicators (canopy size, bare soil gap size, plant height, scaled height, vegetation cover, and bare soil cover) in a semiarid grass–shrub ecosystem. The drone‐based estimates were validated with field measurements by using the standard transect methods (gap intercept, drop disk, and line‐point intercept methods) in the spring and summer of 2017. The drone‐based estimates showed strong agreements with in situ measurements in cases where deciduous vegetation (mesquite) had leaves with R2 for bare soil gap size and vegetation height of 0.97 and 0.89 in the summer, respectively. The RMSE of bare soil gap size and vegetation height are 0.2 m and 6.72 cm in the summer, respectively. Based on these results, we found that drone‐based remote sensing proved to be an efficient and highly accurate method that serves as a complement to field measurements for rangeland indicator estimation. We discussed the possible applications of drone‐based products on arid and semiarid rangelands: the spatially explicit input of an ecological model, to detect and characterize non‐stationarity, and to detect landscape anisotropy.

Assessing Drought Vegetation Dynamics in Semiarid Grass- and Shrubland Using MESMA

Drought intensity and duration are expected to increase over the coming century in the semiarid western United States due to anthropogenic climate change. Historic data indicate that megadroughts in this region have resulted in widespread ecosystem transitions. Landscape-scale monitoring with remote sensing can help land managers to track these changes. However, special considerations are required: traditional vegetation indices such as NDVI often underestimate vegetation cover in semiarid systems due to short and multimodal green pulses, extremely variable rainfall, and high soil fractions. Multi-endmember spectral mixture analysis (MESMA) may be more suitable, as it accounts for both green and non-photosynthetic soil fractions. To determine the suitability of MESMA for assessing drought vegetation dynamics in the western US, we test multiple endmember selection and model parameters for optimizing the classification of fractional cover of green vegetation (GV), non-photosynthetic vegetation (NPV), and soil (S) in semiarid grass- and shrubland in central New Mexico. Field spectra of dominant vegetation species were collected at the Sevilleta National Wildlife Refuge over six field sessions from May–September 2019. Landsat Thematic Mapper imagery from 2009 (two years pre-drought), and Landsat Operational Land Imager imagery from 2014 (final year of drought), and 2019 (five years post-drought) was unmixed. The best fit model had high levels of agreement with reference plots for all three classes, with R2 values of 0.85 (NPV), 0.67 (GV), and 0.74 (S) respectively. Reductions in NPV and increases in GV and S were observed on the landscape after the drought event, that persisted five years after a return to normal rainfall. Results indicate that MESMA can be successfully applied for monitoring changes in relative vegetation fractions in semiarid grass and shrubland systems in New Mexico.

Artificial forest conversion into grassland alleviates deep-soil desiccation in typical grass zone on China’s Loess Plateau: Regional modeling

Afforestation has significantly increased vegetation cover and has slowed soil erosion on China’s Loess Plateau (CLP). However, intensive afforestation activities in semi-arid regions that are in excess of local water availability can cause imbalances in the soil water budget. This can cause soil desiccation, which in turn builds up dry soil layers (DSL) in the soil profile. The occurrence of DSL can threaten the sustainable development of restored ecosystems in water-scarce regions. Knowledge of the spatial characteristics of DSL in artificial forests and their response to land-use change is critical for optimal soil water management and ecological sustainability in the CLP. Therefore, the spatial characteristics of DSL under artificial forest in a typical grassland area on the CLP were investigated. The temporal (2015–2040) dynamics of soil water content (SWC) in the 0–5 m soil profile after the land-use change were simulated and analysed using the Hydrus-1D software. Based on the investigation, DSL existed at some 81% of the sampling sites in the typical grassland area on the CLP. The occurrence of DSL was graded as severe, with a mean thickness of 297 cm and mean SWC of only 9%. The model simulation showed that two phases of SWC dynamics developed after land-use change. One of the phases is the gradual recovery of SWC after the conversion of artificial forests into grassland. The other is that of SWC fluctuations with rainfall under grassland conditions. It requires some 2–13 years (mean of ~7 years) for the soil water to recover in the 0–5 m soil profile after artificial forest is converted to grassland across the semi-arid grass zone of the CLP. Structural equation modelling showed that the duration of DSL recovery was driven directly or indirectly by the degree of dryness of the DSL, soil hydraulic properties, and slope. It is therefore concluded that DSL in the 5-m soil profile can fully recover if there is a vegetation shift in the semi-arid grassland area of the CLP. This is critical for prediction studies of DSL dynamics and sustainable soil water management in water-scarce plateau regions.

GEA Group, Germany

Afforestation has significantly increased vegetation cover and has slowed soil erosion on China’s Loess Plateau (CLP). However, intensive afforestation activities in semi-arid regions that are in excess of local water availability can cause imbalances in the soil water budget. This can cause soil desiccation, which in turn builds up dry soil layers (DSL) in the soil profile. The occurrence of DSL can threaten the sustainable development of restored ecosystems in water-scarce regions. Knowledge of the spatial characteristics of DSL in artificial forests and their response to land-use change is critical for optimal soil water management and ecological sustainability in the CLP. Therefore, the spatial characteristics of DSL under artificial forest in a typical grassland area on the CLP were investigated. The temporal (2015–2040) dynamics of soil water content (SWC) in the 0–5 m soil profile after the land-use change were simulated and analysed using the Hydrus-1D software. Based on the investigation, DSL existed at some 81% of the sampling sites in the typical grassland area on the CLP. The occurrence of DSL was graded as severe, with a mean thickness of 297 cm and mean SWC of only 9%. The model simulation showed that two phases of SWC dynamics developed after land-use change. One of the phases is the gradual recovery of SWC after the conversion of artificial forests into grassland. The other is that of SWC fluctuations with rainfall under grassland conditions. It requires some 2–13 years (mean of ~7 years) for the soil water to recover in the 0–5 m soil profile after artificial forest is converted to grassland across the semi-arid grass zone of the CLP. Structural equation modelling showed that the duration of DSL recovery was driven directly or indirectly by the degree of dryness of the DSL, soil hydraulic properties, and slope. It is therefore concluded that DSL in the 5-m soil profile can fully recover if there is a vegetation shift in the semi-arid grassland area of the CLP. This is critical for prediction studies of DSL dynamics and sustainable soil water management in water-scarce plateau regions.

Testing water fluxes and storage from two hydrology configurations within the ORCHIDEE land surface model across US semi-arid sites

Abstract. Plant activity in semi-arid ecosystems is largely controlled by pulses of precipitation, making them particularly vulnerable to increased aridity that is expected with climate change. Simple bucket-model hydrology schemes in land surface models (LSMs) have had limited ability in accurately capturing semi-arid water stores and fluxes. Recent, more complex, LSM hydrology models have not been widely evaluated against semi-arid ecosystem in situ data. We hypothesize that the failure of older LSM versions to represent evapotranspiration, ET, in arid lands is because simple bucket models do not capture realistic fluctuations in upper-layer soil moisture. We therefore predict that including a discretized soil hydrology scheme based on a mechanistic description of moisture diffusion will result in an improvement in model ET when compared to data because the temporal variability of upper-layer soil moisture content better corresponds to that of precipitation inputs. To test this prediction, we compared ORCHIDEE LSM simulations from (1) a simple conceptual 2-layer bucket scheme with fixed hydraulic parameters and (2) an 11-layer discretized mechanistic scheme of moisture diffusion in unsaturated soil based on Richards equations, against daily and monthly soil moisture and ET observations, together with data-derived estimates of transpiration / evapotranspiration, T∕ET, ratios, from six semi-arid grass, shrub, and forest sites in the south-western USA. The 11-layer scheme also has modified calculations of surface runoff, water limitation, and resistance to bare soil evaporation, E, to be compatible with the more complex hydrology configuration. To diagnose remaining discrepancies in the 11-layer model, we tested two further configurations: (i) the addition of a term that captures bare soil evaporation resistance to dry soil; and (ii) reduced bare soil fractional vegetation cover. We found that the more mechanistic 11-layer model results in a better representation of the daily and monthly ET observations. We show that, as predicted, this is because of improved simulation of soil moisture in the upper layers of soil (top ∼ 10 cm). Some discrepancies between observed and modelled soil moisture and ET may allow us to prioritize future model development and the collection of additional data. Biases in winter and spring soil moisture at the forest sites could be explained by inaccurate soil moisture data during periods of soil freezing and/or underestimated snow forcing data. Although ET is generally well captured by the 11-layer model, modelled T∕ET ratios were generally lower than estimated values across all sites, particularly during the monsoon season. Adding a soil resistance term generally decreased simulated bare soil evaporation, E, and increased soil moisture content, thus increasing transpiration, T, and reducing the negative bias between modelled and estimated monsoon T∕ET ratios. This negative bias could also be accounted for at the low-elevation sites by decreasing the model bare soil fraction, thus increasing the amount of transpiring leaf area. However, adding the bare soil resistance term and decreasing the bare soil fraction both degraded the model fit to ET observations. Furthermore, remaining discrepancies in the timing of the transition from minimum T∕ET ratios during the hot, dry May–June period to high values at the start of the monsoon in July–August may also point towards incorrect modelling of leaf phenology and vegetation growth in response to monsoon rains. We conclude that a discretized soil hydrology scheme and associated developments improve estimates of ET by allowing the modelled upper-layer soil moisture to more closely match the pulse precipitation dynamics of these semi-arid ecosystems; however, the partitioning of T from E is not solved by this modification alone.

Prior rainfall pattern determines response of net ecosystem carbon exchange to a large rainfall event in a semi-arid woodland

Abstract Semi-arid climate is characterized by long dry periods which are interrupted by rainfall events differing in magnitude. The effect of these rainfall events on ecosystem carbon fluxes has been studied in semi-arid grass and shrublands, but data for woodlands is lacking. In this study net ecosystem productivity (NEP), partitioned ecosystem respiration (Reco) and gross primary productivity (GPP) in a semi-arid eucalyptus woodland were measured using eddy covariance data. Four natural large rainfall events with similar magnitude (35–60 mm), but contrasting previous rainfall patterns (several moderate rainfall events vs. limited or no rainfall) were chosen. NEP, Reco and GPP rates 28 days prior to and 35 days after the three central rainfall events were used. Prior rainfall patterns influenced ecosystem carbon fluxes after the central rainfall event. GPP rates were not affected by the four rainfall events. After four weeks with several medium to large rainfall events, the central rainfall event had little effect on Reco. In contrast, a large rainfall event following four weeks with very little rainfall induced an increase in Reco for about three weeks and thus a decrease in NEP. The strong increase in Reco after the central rainfall event can, at least partly, be explained by an increase in soil respiration upon rewetting. A water addition experiment (30 mm rainfall simulation) conducted in the field following a long dry period (only 4.8 mm rainfall input in 45 days) showed that heterotrophic soil respiration usually decreases rapidly after rewetting. In the sandy soil of the study area, the top 0–5 cm dry within a few days after rainfall, but at 10 cm depth the soil remained moist for several weeks after the large rainfall event that followed a long dry period. Therefore, sustained higher Reco following the large rainfall event could be due to respiration of roots in the moist deeper soil layers. We conclude that the previous rainfall should be considered when interpreting the response of ecosystem C fluxes to rainfall events which could alter ecosystem carbon balance and may potentially affect seasonal or inter-annual variability of ecosystem carbon uptake.

Genotyping-by-Sequencing in a Species Complex of Australian Hummock Grasses (Triodia): Methodological Insights and Phylogenetic Resolution.

Next-generation sequencing is becoming increasingly accessible to researchers asking biosystematic questions, but current best practice in both choosing a specific approach and effectively analysing the resulting data set is still being explored. We present a case study for the use of genotyping-by-sequencing (GBS) to resolve relationships in a species complex of Australian arid and semi-arid grasses (Triodia R.Br.), highlighting our solutions to methodological challenges in the use of GBS data. We merged overlapping paired-end reads then optimised locus assembly in the program PyRAD to generate GBS data sets for phylogenetic and distance-based analyses. In addition to traditional concatenation analyses in RAxML, we also demonstrate the novel use of summary species tree analyses (taking gene trees as input) with GBS loci. We found that while species tree analyses were relatively robust to variation in PyRAD assembly parameters, our RAxML analyses resulted in well-supported but conflicting topologies under different assembly settings. Despite this conflict, multiple clades in the complex were consistently supported as distinct across analyses. Our GBS data assembly and analyses improve the resolution of taxa and phylogenetic relationships in the Triodia basedowii complex compared to our previous study based on Sanger sequencing of nuclear (ITS/ETS) and chloroplast (rps16-trnK spacer) markers. The genomic results also partly support previous evidence for hybridization between species in the complex. Our methodological insights for analysing GBS data will assist researchers using similar data to resolve phylogenetic relationships within species complexes.

Exploiting Differential Vegetation Phenology for Satellite-Based Mapping of Semiarid Grass Vegetation in the Southwestern United States and Northern Mexico

We developed and evaluated a methodology for subpixel discrimination and large-area mapping of the perennial warm-season (C4) grass component of vegetation cover in mixed-composition landscapes of the southwestern United States and northern Mexico. We describe the methodology within a general, conceptual framework that we identify as the differential vegetation phenology (DVP) paradigm. We introduce a DVP index, the Normalized Difference Phenometric Index (NDPI) that provides vegetation type-specific information at the subpixel scale by exploiting differential patterns of vegetation phenology detectable in time-series spectral vegetation index (VI) data from multispectral land imagers. We used modified soil-adjusted vegetation index (MSAVI2) data from Landsat to develop the NDPI, and MSAVI2 data from MODIS to compare its performance relative to one alternate DVP metric (difference of spring average MSAVI2 and summer maximum MSAVI2), and two simple, conventional VI metrics (summer average MSAVI2, summer maximum MSAVI2). The NDPI in a scaled form (NDPIs) performed best in predicting variation in perennial C4 grass cover as estimated from landscape photographs at 92 sites (R2 = 0.76, p < 0.001), indicating improvement over the alternate DVP metric (R2 = 0.73, p < 0.001) and substantial improvement over the two conventional VI metrics (R2 = 0.62 and 0.56, p < 0.001). The results suggest DVP-based methods, and the NDPI in particular, can be effective for subpixel discrimination and mapping of exposed perennial C4 grass cover within mixed-composition landscapes of the Southwest, and potentially for monitoring of its response to drought, climate change, grazing and other factors, including land management. With appropriate adjustments, the method could potentially be used for subpixel discrimination and mapping of grass or other vegetation types in other regions where the vegetation components of the landscape exhibit contrasting seasonal patterns of phenology.

Effects of litter, seed position, and water availability on establishment of seedlings for two semiarid grass species

We conducted a field investigation and controlled experiments in a glasshouse to determine how litter, seed position, and/or water supply affect seedling emergence and the establishment of two native grass species (Leymus chinensis (Trin.) Tzvel. and Bromus inermis Leyss) in northern China. Both water supply and seed position dramatically influenced seedling emergence and growth, as well as the accumulation of biomass for these two species. For L. chinensis, the quantity of litter had a significant impact on seedling survival, height increment, and biomass production when grown in either the glasshouse or the field while that component had little influence on B. inermis seedling emergence or survival. The effects of litter were physical but not biological or chemical, suggesting that this component is important only in the first year of seedling establishment. Therefore, longer-term experiments are probably necessary to examine the biological and chemical impacts that litter has on seedling performance.

Shrubs increase soil resources heterogeneity along semiarid grass slopes in the Loess Plateau

The response of soil resources to the introduction of shrubs in semiarid grasslands is essential to the distribution of vegetation and revegetation. To determine how soil resources respond to the introduction of shrubs in semiarid grassland slopes, we investigated in the Loess Plateau of China the spatial patterns of soil organic matter (OM), total and extractable nitrogen (N) and phosphorous (P) in grass slopes with shrubs introduced (SS) and in adjacent native grass slopes without shrub introduction (GS). Three soil types, Loessial, Castanozems and Skeletal, were examined to test the influences of soil type on the effects of shrubs on soil resources. Shrub introduction in grass slopes induced significant increases in soil resources, especially in clay rich soils. The best fit models of spatial structure for soil variables differed with soil types in both GS and SS. A Gaussian model described most of the soil resources in GS, but Spherical and Gaussian models were useful for describing spatial structure in SS. Shrub introduction increased the magnitude of spatial heterogeneity, but reduced the effective range of spatial correlation for most variables (OM, NO3−, total P and extractable P) along grass slopes. The increase of spatial heterogeneity was greater in sandy soil than in clay rich soil. The relationships among OM, N and P were not influenced by shrub introduction. Taken together, the results of this study indicated that shrubs increased soil resources heterogeneity, and these increases varied with soil types in semiarid grass slopes of the Loess Plateau. These changes might cause degradation of the ecosystem in the area, suggesting that shrubs should be avoided in favor of implementing natural rehabilitation with native grasses for the semiarid grass slopes of the Loess Plateau.

Economical and financial analysis of lamb finishing fed with diets formulated according to the NRC (1985) and the NRC (2007)

This study compares both versions of the nutritional requirement system determined by the National Research Council (NRC) version 1985 (NRC85) and NRC version 2007 (NRC07), for finishing lambs in feedlots. Nineteen crossbred lambs were divided in four groups representing four experimental treatments: one diet according to NRC85 and three diets according to NRC07. The diets recommended by NRC07 considers crude protein intake relative to ruminal undegradable protein at 20, 40, and 60 % levels (NRC07/20, NRC07/40, and NRC07/60). Diets were composed of Brazilian semi-arid native grass silage, soybean meal, corn, annatto byproduct, and limestone. Purchases and sales of lambs were done according to average market prices in Brazil. The economic indicators considered pointed that all treatments were viable but NRC07/20 and NRC07/60 were more profitable with similar net present values (NPVs) and internal return rates (IRRs). NRC07/20 was the best option showing an IRR of 17.20 % and a payback period (PP) of 5.07 considering a fixed annual interest rate of 6 %. Sensitivity analysis considering a 10 % raise in variable costs showed negative NPVs, IRRs inferior to the opportunity cost rates adopted and PPs that exceeded the planning horizon of 7 years for both NRC85 and NRC07/40.

Long‐term experimental loss of foundation species: consequences for dynamics at ecotones across heterogeneous landscapes

Biome transition zones where species co‐exist near their geographic limits are expected to be among the most responsive to changes in climate that result in mortality of foundation species. Long‐term (>13 years) patterns in dominance and cover of functional types were examined following the annual experimental removal of one of three foundation species at an arid‐semiarid biome transition zone. Objectives were to identify key processes influencing these patterns, and to predict future landscape‐scale dynamics following mortality of different foundation species. Aboveground biomass of dominant species was removed from 3 × 4 m plots. Cover by species on control and removal plots was estimated annually in communities with a single dominant species, and in ecotonal communities with two dominant species across two types of ecotones (semiarid grassland‐arid grassland, arid grassland‐arid shrubland).For most species and functional types, trends in cover through time were related to the remaining species assemblages rather than to variable climatic conditions. In ecotonal communities, resident co‐dominant species increased to dominance following the loss of a foundation species with little change in community composition. In mono‐dominated communities, dominant species loss resulted in a shift to species that are currently sub‐dominants of the same functional type as the species that was removed. Subdominant perennial grass and shrub species increased rapidly following removals in most grassland locations. Annuals and perennial forbs had variable cover values through time that were not clearly related to pulses in precipitation and were not synchronized across locations. The most common response regardless of the identity of the foundation species removed or the community type was an increase in cover by sub‐dominant grasses and by the arid grass species (Bouteloua eriopoda). The rate of increase by B. eriopoda depended on initial cover, and resulted from both vegetative growth and seedling recruitment from other locations. Seed dispersal and seedling recruitment from other locations were not found for the semiarid grass, Bouteloua gracilis or the arid shrub, Larrea tridentata. Because B. eriopoda is more susceptible to shrub invasion, drought, and livestock grazing than the other two foundation species, widespread loss of either of the other species and subsequent increase in B. eriopoda is expected to result in an increase in landscape‐scale vulnerability to these environmental drivers. The extent and magnitude of this change in vulnerability will depend on the ability of B. eriopoda to respond based on the micro‐environmental conditions of the site regardless of which species (B. gracilis, L. tridentata) is lost.

Competitive interactions between grass and succulent shrubs at the ecotone between an arid grassland and succulent shrubland in the Karoo

Nearest-neighbour analysis was used to examine the competitive interactions between Stipa- grostis brevifolia ,aC 4 perennial grass, and two leaf succulent shrubs, Ruschia robusta and Leipoldtia pauciflora, at the ecotone between semi-arid grass- land and succulent shrubland in the Karoo. The root distribution in the soil was also compared to assess the degree of overlap in the potential use of soil resources. Regressions between the combined sizes of interspecific, nearest-neighbour species and the dis- tance between them showed significant positive correlations for S. brevifolia and R. robusta, which suggest the presence of competition. We infer from individual species regressions that the grass exerted a stronger competitive force on the shrub R. robusta than R. robusta on the grass. There was also evidence for strong intraspecific competitive relationships within S. brevifolia and R. robusta. There was no evidence of competition between S. brevifolia and L. pauciflora or among L. pauciflora individuals. S. brevifolia had the deepest root system, and was recorded at depths of 70 cm. Most of this root mass occurred between 10 and 40 cm. Ruschia robusta roots were recorded as deep as 55 cm, but more than 90% was found in the top 20 cm of the soil, creating a degree of overlap with the vertical root distribution of S. brevifolia. A clear separation in rooting depths occurred between S. brevifolia, and L. pauciflora which had only 3% of the total root mass below 10 cm. The partial overlap in the vertical root distribution between S. brevifolia and R. robusta may account for the observed competitive relation- ship, but each species dominates in a different layer, potentially minimising the net competition between S. brevifolia and R. robusta. Our findings demonstrate the possibility of a two-layer water-obtaining strategy in a semi-desert ecosystem, where the succulent shrubs seem to be playing the typical ''grass'' role described in most models of water partitioning between grass and woody plants. The stronger competitive effect of S. brevifolia on R. robusta at all the sites is of significance to species dynamics, and might be related to winter/summer rainfall dynamics at the climatic transition.

Root-associated fungal communities colonizing two dominant semiarid grasses: Hilaria sp. and Stipa sp.

AbstractWe conducted a preliminary survey of the fungal communities associated with roots of Stipa hymenoides and Hilaria jamesii, two grasses native to the southwestern United States. Root samples from 10 different plants were collected at a semiarid grassland in Utah. Fungal communities were assessed using microscopic and molecular methods. Roots were cleared with KOH and stained using blue ink to visualize mycorrhizal and endophytic fungi. A total of 100 root segments were surface sterilized and plated on malt extract agar with antibiotics. Fungal endophytes were identified using nrITS primers. Results/Conclusions Microscopic analyses showed that all root samples from both Hillaria and Stipa were colonized by dark septate and arbuscular mycorrhizal fungi. Vesicles and hyaline hyphae also were observed in all the roots. Sclerotia, a characteristic structure of some dark septate fungi were also found. Approximately 75 fungi were isolated representing at least 45 morphotypes. Molecular identification showed that both grasses are colonized by endophytes in the orders Pleosporales, Hypocreales, and Sordariales commonly found in semiarid grasses, liverworts, and mosses.

Root-associated fungal communities colonizing two dominant semiarid grasses: Hilaria sp. and Stipa sp.

Root-associated fungal communities colonizing two dominant semiarid grasses: Hilaria sp. and Stipa sp.

Long-term dynamics of a semiarid grass steppe under stochastic climate and different grazing regimes: A simulation analysis

We built a grid-based spatial explicit stochastic model that simulates grazing events and basic processes like seedling establishment, growth or mortality of the dominant species in the grass steppes of Patagonia. After evaluating the model with field data, we performed simulation experiments aimed to explore the interaction of precipitation and grazing regimes on vegetation dynamics. Grazing generated a reduction in tussock density which results in a decline in aboveground net primary production (ANPP). Both response variables presented a non-linear behavior including high temporal variability and delay effects, which may prolong for decades. There was a clear threshold in the response of the variables to stock density, though changes become evident only when a highly selective grazing scenario was used. Under high stock density conditions, precipitation use efficiency (PUE) was 82% lower than the values for non-grazed runs. The inter-annual variability of precipitation was more important than the grazing regime in explaining differences in tussock density. Simulation results highlight important issues regarding rangeland management: grazing regime might be as important as stocking density as a degradation agent, temporal lags might obscure degradation processes for decades, the definition of monitoring variables need to consider their response time constants.