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Ranchers and other land managers of central and northern Great Plains rangelands face recurrent droughts that negatively influence economic returns and environmental resources for ranching enterprises. Accurately estimating annual forage production and initiating drought decision-making actions proactively early in the growing season are both critical to minimize financial losses and degradation to rangeland soil and plant resources. Long-term forage production data sets from Alberta, Kansas, Montana, Nebraska, North Dakota, South Dakota, and Wyoming demonstrated that precipitation in April, May, and June (or some combination of these months) robustly predict annual forage production. Growth curves from clipping experiments and ecological site descriptions (ESDs) indicate that maximum monthly forage growth rates occur 1 mo after the best spring month (April to June) precipitation prediction variable. Key for rangeland managers is that the probability of receiving sufficient precipitation after 1 July to compensate for earlier spring precipitation deficits is extremely low. The complexity of human dimensions of drought decision-making necessitates that forage prediction tools account for uncertainty in matching animal demand to forage availability, and that continued advancements in remote sensing applications address both spatial and temporal relationships in forage production to inform critical decision dates for drought management in these rangeland ecosystems.

Dryland (arid and semi-arid) ecosystems globally provide more than half of livestock production and store roughly one-third of soil organic carbon (SOC). Biogeochemical pools are changing due to sh...

Potential carbon mineralization (Cmin) is a commonly used indicator of soil health, with greater Cmin values interpreted as healthier soil. While Cmin values are typically greater in agricultural soils managed with minimal physical disturbance, the mechanisms driving the increases remain poorly understood. This study assessed bacterial and archaeal community structure and potential microbial drivers of Cmin in soils maintained under various degrees of physical disturbance. Potential carbon mineralization, 16S rRNA sequences, and soil characterization data were collected as part of the North American Project to Evaluate Soil Health Measurements (NAPESHM). Results showed that type of cropping system, intensity of physical disturbance, and soil pH influenced microbial sensitivity to physical disturbance. Furthermore, 28% of amplicon sequence variants (ASVs), which were important in modeling Cmin, were enriched under soils managed with minimal physical disturbance. Sequences identified as enriched under minimal disturbance and important for modeling Cmin, were linked to organisms which could produce extracellular polymeric substances and contained metabolic strategies suited for tolerating environmental stressors. Understanding how physical disturbance shapes microbial communities across climates and inherent soil properties and drives changes in Cmin provides the context necessary to evaluate management impacts on standardized measures of soil microbial activity. Foundation for Food and Agricultural Research [523926]; Samuel Roberts Noble Foundation; General Mills Published version Foundation for Food and Agricultural Research (grant ID 523926), General Mills, and The Samuel Roberts Noble Foundation.

In adaptive management of rangelands, monitoring is the vital link that connects management actions with on-the-ground changes. Traditional field monitoring methods can provide detailed information for assessing the health of rangelands, but cost often limits monitoring locations to a few key areas or random plots. Remotely sensed imagery, and drone-based imagery in particular, can observe larger areas than field methods while retaining high enough spatial resolution to estimate many rangeland indicators of interest. However, the geographic extent of drone imagery products is often limited to a few hectares (for resolution ≤ 1 cm) due to image collection and processing constraints. Overcoming these limitations would allow for more extensive observations and more frequent monitoring. We developed a workflow to increase the extent and speed of acquiring, processing, and analyzing drone imagery for repeated monitoring of two common indicators of interest to rangeland managers: vegetation cover and vegetation heights. By incorporating a suite of existing technologies in drones (real-time kinematic GPS), data processing (automation with Python scripts, high performance computing), and cloud-based analysis (Google Earth Engine), we greatly increased the efficiency of collecting, analyzing, and interpreting high volumes of drone imagery for rangeland monitoring. End-to-end, our workflow took 30 days, while a workflow without these innovations was estimated to require 141 days to complete. The technology around drones and image analysis is rapidly advancing which is making high volume workflows easier to implement. Larger quantities of monitoring data will significantly improve our understanding of the impact management actions have on land processes and ecosystem traits.

Monitoring of forage utilization typically occurs at sample locations, or key areas, selected for their presumed potential to represent utilization across pastures. However, utilization can vary greatly across landscapes and may not be well represented by traditional ground-based sampling without great effort. Remote sensing from satellite and manned airborne platforms offers spatial coverage at landscape scale, but their poor spatial resolution (satellite) and cost (manned airborne) may limit their use in monitoring forage utilization. High-resolution photogrammetric point clouds obtained from small unmanned aerial systems (sUAS) represent an appealing alternative. We developed a method to estimate utilization by observing the height reduction of herbaceous plants represented by 3-dimensional point clouds. We tested our method in a semiarid savanna in southern Arizona by comparing utilization estimates with ground-based methods after a month-long grazing duration. In six plots, we found strong correlation between imagery and ground-based estimates (r2 = 0.78) and similar average estimate of utilization of across all plots (ground-based = 18%, imagery = 20%). With a few workflow and technological improvements, we think it is feasible to estimate point cloud utilization over the entire pasture (150 ha) and potentially even larger areas. These improvements include optimizing the number of images collected and used, equipping drones with more accurate global navigation satellite systems (e.g., Global Positioning System), and processing images with cloud-based parallel processing. We show proof of concept to provide confident estimates of forage utilization patterns over large pastures and landscapes, at levels of spatial precision that are consistent with ground-based methods. The adoption of drone-based monitoring of utilization of forage on rangelands could follow the paradigm shift already demonstrated by Global Positioning Systems and Geographic information systems technologies, where the initial high computing costs were reduced, use became the norm, and the availability of more precise spatial patterns was applied to prescribe and evaluate management practices.

Livestock grazing is an extensive and long-standing natural resource use on U.S. public lands that has become extremely controversial in recent decades. In this article, we approach the controversy...

In the Desert Grassland, second and subsequent defoliations on perennial grasses during the active growing season can have substantial impacts on grass recovery and reproduction following herbivory. Land managers implement tactics to avoid multiple defoliations on plants by way of rotational grazing, reduced stocking rates, and/or reduced time spent within a given pasture. We explored frequency and rate of defoliation by cattle on perennial bunchgrasses within an 11-day grazing period in three pastures including distance to water (300 and 600 m) and plant height to determine their influence on animal diet selection. Results indicate that 32% of all marked plants were defoliated by cattle and only 5% of defoliated plants were defoliated a second time by day 10 of the grazing period. Defoliation patterns in the studied pastures did not differ between two distances from water, or in relation to plant height. However, at the second defoliation cattle grazed plants that were shorter than at the first defoliation suggesting a selection for high quality re-growth over larger forage on offer. The results of this study show that a 10-day grazing period during the growing season of the Desert Grassland is an effective strategy to avoid second defoliations on individual perennial grass plants while maintaining sufficient forage for use during the dormant winter grazing season.

Quantification of rates and patterns of community dynamics is central for understanding the organization and function of ecosystems. These insights may support a greater empirical understanding of ecological resilience, and the application of resilience concepts toward ecosystem management. Distinct types of dynamics in natural communities can be used to interpret and apply resilience concepts, but quantitative methods that can systematically distinguish among them are needed. We develop a quantitative method to analyze long-term records of plant community dynamics using principles of movement ecology. We analyzed dissimilarity of species composition through time with linear and nonlinear statistical models to assign community change to four classes of movement trajectories. Compositional change in each sampled plot through time was classified into four classes, stability, abrupt nonlinear change, transient reversible change, and gradual linear drift, each representing a different aspect of ecological resilience. These competing models were evaluated based on estimated coefficients, goodness of fit, and parsimony. We tested our method's accuracy and robustness through simulations, or the ability to distinguish among trajectories and classify them correctly. We simulated 16,000 trajectories of four types, of which 94-100% were correctly classified. Next, we analyzed 13 long-term vegetation records from North American grasslands (annual grasslands with warm-season and cool-season communities, shortgrass, mixedgrass, and tallgrass prairies, and sagebrush steppe), and a record of primary succession at Mt. St. Helens volcano. Collectively, we analyzed 14,647 observations from 775 plots, between 1915 and 2012. Dynamics could be reliably assigned for 705 plots (91%), and overall statistical fit was high (goodness of fit, 0.77 ± 0.15 SD). Among the perennial grasslands, stability was most common (44% of all plots), followed by gradual linear (22%), abrupt nonlinear (17%), and reversible (6%) change. Among annual grasslands, abrupt nonlinear shifts (33%) were more common in the warm-season community than in the cool-season (20%). As expected, abrupt nonlinear change was common during primary succession (51%) while reversible change was rare (3%). Generally, reversible dynamics often required 2-3 decades. Analysis of long-term community change, or trajectories, with principles of movement ecology provides a quantitative basis to compare and interpret ecological resilience within and among ecosystems.

Unmanned aerial vehicles (UAVs) provide a new research tool to obtain high spatial and temporal resolution imagery at a reduced cost. Rapid advances in miniature sensor technology are leading to greater potentials for ecological research. We demonstrate one of the first applications of UAV lidar and hyperspectral imagery and a fusion method for individual plant species identification and 3D characterization at submeter scales in south-eastern Arizona, USA. The UAV lidar scanner characterized the individual vegetation canopy structure and bare ground elevation, whereas the hyperspectral sensor provided species-specific spectral signatures for the dominant and target species at our study area in leaf-on condition. We hypothesized that the fusion of the two different data sources would perform better than either data type alone in the arid and semi-arid ecosystems with sparse vegetation. The fusion approach provides 84–89% overall accuracy (kappa values of 0.80–0.86) in target species classification at the canopy scale, leveraging a wide range of target spectral responses in the hyperspectral data and a high point density (50 points/m2) in the lidar data. In comparison, the hyperspectral image classification alone produced 72–76% overall accuracies (kappa values of 0.70 and 0.71). The UAV lidar-derived digital elevation model (DEM) is also strongly correlated with manned airborne lidar-derived DEM (R2 = 0.98 and 0.96), but was obtained at a lower cost. The lidar and hyperspectral data as well as the fusion method demonstrated here can be widely applied across a gradient of vegetation and topography to monitor and detect ecological changes at a local scale.

Dryland ecosystems occur worldwide and play a prominent, but potentially shifting, role in global biogeochemical cycling. Widespread woody plant proliferation, often associated with declines in palatable grasses, has jeopardized livestock production in drylands and prompted attempts to reduce woody cover by chemical or mechanical means. Woody encroachment also has the potential to significantly alter terrestrial carbon storage. However, little is known of the long-term biogeochemical consequences of woody encroachment in the broader context of its interaction with common dryland land uses, including "brush management" (woody plant clearing) and livestock grazing. Present assessments exhibit considerable variation in the consequences of these land use/land cover changes, with evidence that brush management may counteract sizeable impacts of shrub encroachment on soil biogeochemical pools. A challenge to assessing the net effects of brush management in shrub-encroached grasslands on soil organic carbon (SOC) and total nitrogen (N) pools is that land management practices are typically considered in isolation, when they are co-occurring phenomena. Furthermore, few studies have assessed spatial patterns in brush management and how these are affected in decades following treatment on sites with contrasting grazing histories. To address these uncertainties and interactions, we quantified the impacts of shrub encroachment and their subsequent mortality resulting from brush management (herbicide application) on SOC and N pools in a Sonoran Desert grassland where long-term grazing manipulations (>100 yr) co-occur with shrub encroachment and brush management. Pools of SOC and N associated with herbicided shrubs declined markedly over ~40 yr, offsetting 66% of the increases from shrub encroachment. However, spatial patterns in SOC induced by shrubs persisted over the decades following brush management. Century-long protection from grazing did little to change SOC and N pools. Accordingly, shrub encroachment and shrub mortality from brush management each far outweighed livestock grazing impacts. Consideration of the patterns of SOC and N through space (e.g., bole-to-dripline gradients), time (e.g., shrub age/size), land use (e.g., livestock grazing and brush management), and their interactions will position us to improve predictions of SOC and N responses to land use/land cover change, inform C-based management decisions, and objectively evaluate trade-offs with other ecosystem services.

Vegetation dynamics in rangelands and other ecosystems are known to be mediated by topoedaphic properties. Vegetation monitoring programs, however, often do not consider the impact of soils and other sources of landscape heterogeneity on the temporal patterns observed. Ecological sites (ES) comprise a land classification system based on soil, topographic, and climate variations that can be readily applied by land managers to classify topoedaphic properties at monitoring locations. We used a long-term (>40 y) vegetation record from southeastern Arizona, USA to test the utility of an ES classification for refining interpretations of monitoring data in an area of relatively subtle soil differences. We focused on two phenomena important to rangeland management in the southeastern Arizona region: expansion of the native tree velvet mesquite (Prosopis velutina Woot.) and spread of the introduced perennial grass Lehmann lovegrass (Eragrostis lehmanniana Nees). Specifically, we sought to determine if a quantitative, ES-specific analysis of the long-term record would (1) improve detection of changes in plant species having heightened ecological or management importance and (2) further clarify topoedaphic effects on vegetation trajectories. We found that ES class membership was a significant factor explaining spatiotemporal variation in velvet mesquite canopy cover, Lehmann lovegrass basal cover, and Lehmann lovegrass density measurements. In addition, we observed that the potential magnitude of velvet mesquite and Lehmann lovegrass increases varied substantially among ES classes. Our study brings attention to a practical land management tool that might be called upon to increase the effectiveness of vegetation-based indicators of ecosystem change.

On the Ground•Seasonal climate predictions, based largely on the status of the El Niño-Southern Oscillation, are one such tool but need to be used with prudence, understanding when and where they perform the best.•Advance planning and preparation for drought includes finding the right place for uncertain climate predictions in management decision making, as well as working to reduce overall exposure to drought risks.

Buffelgrass (Pennisetum ciliare (L.) Link), a non-native perennial bunchgrass, invades ecologically intact areas of the Sonoran Desert. It competitively excludes native plants and increases fire frequency and intensity. Since the 1990s, whole buffelgrass plants have been manually uprooted and removed to control the invasion in southern Arizona. Uprooting plants results in bare, disturbed soil which promotes buffelgrass seed germination. This study examined whether leaving entire uprooted buffelgrass plants (thatch) on a field site reduces future buffelgrass establishment compared to removing uprooted plants from the site. A secondary goal was to determine whether light reduction and autoallelopathy were major factors in the negative effect of thatch on buffelgrass seedling density. Field plots with an average of 8,095 kg/ha thatch had 1.9 buffelgrass seedlings/m2 which was significantly fewer than the 2.9 seedlings/m2 in plots without thatch. Thatched portions of thatch plots (50% of their total a...

Recreational camping has been shown to suppress plant cover and expand bare ground area. These shifts have important implications for soil health. We used campsites in a semiarid savanna at the Santa Rita Experimental Range (SRER) in Arizona to test the hypotheses that 1) recreational camping is a disturbance that limits plant cover and soil microbial activity, and 2) the presence of Prosopis, which is known to encourage a fertility island effect, increases soil microbial activity within campsites. Camping disturbance did not influence any sampled measures of edaphic properties, plant cover, or soil microbial biomass and exoenzyme activities. However, the presence of Prosopis resulted in elevated litter, total dissolved nitrogen (TDN), and dissolved organic carbon (DOC). Multiple linear regression models suggest that observed resistance of soil microbial activities to camping disturbance may be due to both increased availability of organic C and N substrates beneath Prosopis and heightened seasonal water availability.

Shifts in the abundance of grasses and woody plants in drylands have occurred several times during the Holocene. However, our understanding of the rates and dynamics of this state-change in recent decades is limited to scattered studies conducted at disparate spatial and temporal scales; the potential misperceptions of shrub cover change could be remedied using cross spatiotemporal scale analyses that link field observations, repeat ground-level photography and remote sensing perspectives. The study was conducted across a semi-arid landscape in southern Arizona. Local data from long-term transects revealed three distinct chronological phases of shrub cover change: expansion (1961–1991, 0.7% y−1), decline (1992–1997, −2.3% y−1) and stabilization (1998–2012, 22–25% with no net cover change). Twenty-eight years (1984–2011) of broad-scale Landsat Thematic Mapper assessments confirm that shrub cover has been relatively stable in recent decades regardless of grazing regimes and landforms with the exception of the proliferation of succulents at lower elevations (verified by repeat photography acquired in 1987 and 2015) where the physical environment is the harshest, reflecting elevated temperature and winter precipitation deficit. Warmer, drier future climates are predicted to reduce woody plant carrying capacity and promote a shift to xerophytic succulents.

Increased preparation for drought among livestock producers reliant on rain-fed forage should reduce the economic losses and environmental degradation when the eventual drought occurs. We surveyed livestock ranchers in southeastern Arizona, USA, to determine their level of increased preparation for drought following 10 very dry years, as well as their level of threat from drought, importance of coping strategies, ranching experience, herd size, and satisfaction with drought management information. We used the protection motivation theory (PMT) model to structure our analysis because it provides a cognitive process approach to understand what motivates people to increase preparation for looming problems and how the likelihood of that behavior is a function of threat and coping strategy assessments. Thirty-seven percent of ranchers reported a high increase in preparedness, and another 31 % reported some increased preparation. Increased preparation was positively associated with three coping practices: reserve pastures, rotate grazing, and drought planning. However, increased preparation was negatively associated with drought threat severity, suggesting that the more prepared ranchers have implemented coping strategies that buffer them from the looming threat of drought. We found no relationship between increased preparation and levels of ranching experience, herd size, or satisfaction with drought information. Structure and content of education and assistance programs for improving rancher preparation for drought should benefit from the PMT-based analysis because it identifies drivers leading to increased preparedness and how those drivers differ among members of the ranching community.

Livestock producers on rangelands are interested in drought at spatial scales of pastures ( 3 fold to 40–65% of years but frequencies did not differ between SPI and SPEI; and the frequency of summer drought did not change after 1996. At the small-scale, the extent of drought increased in winter and water years and decreased in summer since 1996 when using SPEI, but did not change when using SPI. Since 1996, the chances of a management unit-sized drought patch (1–10 contiguous cells) increased in winter, water year, and summer when using SPEI; but not in summer when using SPI. Scaling relationships show extensive drought patches (>20% of large area) when the large-scale is near average conditions, and those patches are larger in summer than winter. Increased drought frequency and patchy spatial distribution of drought have implications for herd structure and herd movements among pastures to avoid economic losses and overgrazing in drought patches. We propose increased efforts to detect drought patches with on-site gauge networks and temperature monitoring as well as remote sensing of precipitation patterns and vegetation indices.

Erosion dynamics in semiarid environments is defined by high magnitude, low frequency rainfalls that produce runoff with high sediment concentration. Check dams are widely used in this environment as a sedimentation mitigation technique, however their impact on overall watershed sediment balance is not well known. In 2008 a total of 37 loose rock semipermeable check dams were installed on two small (4 and 3.1 ha [9.8 and 7.6 ac]) watersheds located on the alluvial fan of the Santa Rita Mountains in southern Arizona. Each watershed was equipped with a rain gauge, supercritical flow flume, and sediment sampler. The runoff and sediment yield characteristics following the check dam installation were compared with 35 years of historical records. Impacts of the check dams on runoff from major rainstorms were not detectable; however the number of runoff events generated by small (less than one year recurrence interval) rainstorms decreased by 60%. During four years check dams retained 75 t (82.6 tn) of sediment (50% of sediment yield) and were filled to more than 80% of their capacity. Depositional areas upstream of the dams have potential to support watershed restoration.

State-and-transition models (STMs) are used in natural resource management to describe ecological site scale response to natural and anthropogenic disturbances. STMs are primarily based for expert opinion and literature reviews, lacking analytical testing to support vegetation community dynamics, thresholds, and state changes. We developed a unique approach, combining ordination and permutation MANOVA (perMANOVA) with raw data interpretation, to examine vegetation data structure and identify thresholds for a STM. We used a long-term monitoring dataset for an ecological site on the Santa Rita Experimental Range, Arizona. Basal cover of perennial grasses and canopy cover of shrubs and cacti were measured on permanent transects beginning in 1957. Data were grouped by drivers identified by the STM including species invasion, grazing, drought, and mesquite treatment. Ordination by nonmetric multidimensional scaling described the structure of the data. PerMANOVA was used to test for differences between groups of sample units. Analyses of combined key species (Lehmann's lovegrass and mesquite [Prosopis velutina Woot.]) and nonkey species patterns demonstrated an irreversible transition and occurrence of a structural threshold due to Lehmann's lovegrass invasion, as well as a short-term reversible transition (restoration pathway) following mesquite treatment. Sensitivity analysis, in which key species were removed from the dataset, showed that the relative composition of nonkey species did not differ between states previously defined by the key species. This apparent disconnect between dynamics of key and nonkey species may be related to changes in the functional attributes that were not monitored during this time series. Our analyses suggest that, for this ecological site, transition to a Lehmann's lovegrass state occurs when basal cover of this species exceeds 1–2%, which often occurs within 6 yr of its arrival. Evaluation of the restoration pathway showed a recrossing of the threshold within 6 yr of treatment and when mesquite canopy cover exceeded 10%.

Subalpine meadows are some of the most ecologically important components of mountain landscapes, and primary productivity is important to the maintenance of meadow functions. Understanding how changes in primary productivity are associated with variability in moisture and temperature will become increasingly important with current and anticipated changes in climate. Our objective was to describe patterns and variability in aboveground live vascular plant biomass in relation to climatic factors. We harvested aboveground biomass at peak growth from four 64-m2 plots each in xeric, mesic, and hydric meadows annually from 1994 to 2000. Data from nearby weather stations provided independent variables of spring snow water content, snow-free date, and thawing degree days for a cumulative index of available energy. We assembled these climatic variables into a set of mixed effects analysis of covariance models to evaluate their relationships with annual aboveground net primary productivity (ANPP), and we ...

Questions What factors explain the variation in plant survival parameters across species and ecosystems? Location Western North America. Methods We compiled six long-term data sets from western North America to test for ecosystem-dependent demographic responses for forbs and grasses. Based on these data, we characterized 123 survivorship curves for 109 species. Three demographic parameters were extracted from these survivorship curves: survival rate at age 1, life expectancy at age 1, and a parameter describing the shape of the survivorship curve. We used a mixed effects model to compare the differences in demographic parameters between life forms (forbs or grasses) and among ecosystems, incorporating ‘ecosystem’ as a random factor, with life form treated as a categorical factor, and mean annual precipitation and mean annual temperature treated as continuous variables. Results Grasses had higher survival and longer life expectancy than forbs at 1 yr of age. Both forbs and grasses followed Type III survivorship curves, although forbs were closer to Type II compared to the grasses. Averaging across species, hazard ratios for whole survivorship curves differed among most ecosystems. While mean annual precipitation had no effect on any demographic parameter, mean annual temperature had a significantly negative effect on both first year survival rates and life expectancy for forbs. Conclusions Our results demonstrate that life form exerts a strong influence on demographic parameters and their response to temperature variation among ecosystems. This unprecedented information on the age-specific demography of herbaceous plants has implications for population modelling and research on life-history evolution and senescence.

[1] Precipitation regimes are predicted to shift to more extreme patterns that are characterized by more heavy rainfall events and longer dry intervals, yet their ecological impacts on vegetation production remain uncertain across biomes in natural climatic conditions. This in situ study investigated the effects of these climatic conditions on aboveground net primary production (ANPP) by combining a greenness index from satellite measurements and climatic records during 2000–2009 from 11 long-term experimental sites in multiple biomes and climates. Results showed that extreme precipitation patterns decreased the sensitivity of ANPP to total annual precipitation (PT) at the regional and decadal scales, leading to decreased rain use efficiency (RUE; by 20% on average) across biomes. Relative decreases in ANPP were greatest for arid grassland (16%) and Mediterranean forest (20%) and less for mesic grassland and temperate forest (3%). The cooccurrence of heavy rainfall events and longer dry intervals caused greater water stress conditions that resulted in reduced vegetation production. A new generalized model was developed using a function of both PT and an index of precipitation extremes and improved predictions of the sensitivity of ANPP to changes in precipitation patterns. Our results suggest that extreme precipitation patterns have substantially negative effects on vegetation production across biomes and are as important as PT. With predictions of more extreme weather events, forecasts of ecosystem production should consider these nonlinear responses to altered extreme precipitation patterns associated with climate change.

The resilience of a global sample of ecosystems to an increase in drought conditions is assessed, comparing data from the early twenty-first with the late twentieth century; results indicate a cross-ecosystem capacity for tolerating low precipitation and responding to high precipitation during recent warm drought and yet suggest a threshold to resilience with prolonged warm drought. The early twenty-first century has seen a global increase in drought conditions. These authors describe the response of plant communities in a global sample of ecosystems to drought stress as a measure of ecosystem resilience, comparing data from the early twenty-first century with the late twentieth century. They find a common range of water-use efficiency values across timescales and locations, with the increases in dry years this century not yet compromising the ability to lower water-use efficiency in response to wetter years. This work will help provide an understanding of how vegetation production will respond to the altered hydroclimatic conditions predicted with climate change, important when making decisions about food production and resource management. Climate change is predicted to increase both drought frequency and duration, and when coupled with substantial warming, will establish a new hydroclimatological model for many regions1. Large-scale, warm droughts have recently occurred in North America, Africa, Europe, Amazonia and Australia, resulting in major effects on terrestrial ecosystems, carbon balance and food security2,3. Here we compare the functional response of above-ground net primary production to contrasting hydroclimatic periods in the late twentieth century (1975–1998), and drier, warmer conditions in the early twenty-first century (2000–2009) in the Northern and Southern Hemispheres. We find a common ecosystem water-use efficiency (WUEe: above-ground net primary production/evapotranspiration) across biomes ranging from grassland to forest that indicates an intrinsic system sensitivity to water availability across rainfall regimes, regardless of hydroclimatic conditions. We found higher WUEe in drier years that increased significantly with drought to a maximum WUEe across all biomes; and a minimum native state in wetter years that was common across hydroclimatic periods. This indicates biome-scale resilience to the interannual variability associated with the early twenty-first century drought—that is, the capacity to tolerate low, annual precipitation and to respond to subsequent periods of favourable water balance. These findings provide a conceptual model of ecosystem properties at the decadal scale applicable to the widespread altered hydroclimatic conditions that are predicted for later this century. Understanding the hydroclimatic threshold that will break down ecosystem resilience and alter maximum WUEe may allow us to predict land-surface consequences as large regions become more arid, starting with water-limited, low-productivity grasslands.

Regression equations were developed to estimate above ground biomass and carbon and nitrogen mass of foliage and stem size fractions from plant size dimensions (basal diameter, canopy area, height, canopy volume) for a tall shrub species (Prosopis velutina) that has increased in abundance in arid and semi-arid grasslands in the southwestern United States and northwestern Mexico. Regression equations were also developed to describe relationships among the dimensions of plant size. All equations were significant (p 0.72. In addition to species-specific information, we found support for the global patterns of foliar biomass increasing to the ¾ power of stem biomass and height increasing to the ½ power of stem diameter. We provide a comprehensive report of all equations, which can support a variety of in situ (ground-based), modeling, and remote-sensing objectives related to quantifying changes in ecosystem function and carbon sequestration accompanying changes in woody plant abundance. We advocate that comprehensive reporting should become more common for arid and semi-arid woody species in order to support a broad spectrum of users while laying the foundation for the development of global generalizations similar to those available for forest trees.

Theory predicts that strong indirect effects of environmental change will impact communities when niche differences between competitors are small and variation in the direct effects experienced by competitors is large, but empirical tests are lacking. Here we estimate negative frequency dependence, a proxy for niche differences, and quantify the direct and indirect effects of climate change on each species. Consistent with theory, in four of five communities indirect effects are strongest for species showing weak negative frequency dependence. Indirect effects are also stronger in communities where there is greater variation in direct effects. Overall responses to climate perturbations are driven primarily by direct effects, suggesting that single species models may be adequate for forecasting the impacts of climate change in these communities., Environmental change can have indirect effects on populations by altering the outcome of competitive interactions. Here, Chu et al. show that although direct effects dominate the responses of grassland species to climate perturbations, indirect effects could be greater among species with smaller niche differences.

AGWA: The Automated Geospatial Watershed Assessment Tool to Inform Rangeland Management DOI:10.2458/azu_rangelands_v33i4_goodrich

Repeat remote sensing field campaigns at experimental sites result in a valuable set of remote sensing data resources, geographic information system data sets, digitized maps, and tabular data that are tied to specific locations. Archiving and distributing these geospatial data generally become the responsibility of local universities and federal research centers with few resources dedicated to the task. The developments in archiving and distributing geospatial data are presented through the description and discussion of three interconnected case studies of data preservation at government and academic units in southeastern Arizona. The main challenges were associated with data archiving, developing online data distribution systems, interconnecting the data distribution systems, and sustaining the archiving and distribution systems. The case studies present multiple approaches to meeting these challenges within the constraints of government and academic units. Results should guide other local efforts to archive and preserve long-term geospatial data and distribute them online.

Multispecies allometric models to predict grass biomass may increase field study efficiency by eliminating the need for speciesspecific data. We used field measurements during two growing seasons to develop single-species and multispecies regression models predicting the current year’s aboveground biomass for eight common cespitose grass species. Simple and stepwise regression analyses were based on natural log expressions of biomass, basal diameter, and height, and a dummy variable expression of grazing history. Basal diameter had the strongest relationship with biomass among single-species (adjusted R 2 5 0.80 to 0.91) and multispecies (adjusted R 2 5 0.85) models. Regression slopes (b) for diameter among single-species (b 5 1.01 to 1.49) and the multispecies (b 5 1.25) models suggests that biomass will double when diameter increases ,75%. Height and grazing history added little predictive value when diameter was already in the model. When applied to actual populations, biomass estimates from multispecies models were within 3–29% of estimates from the single-species models. Although the multispecies biomass–size relationship was robust across the cespitose life-form, users should be cautious about applying our equations to different locations, plant sizes, and population size-structures.

The science of ecohydrology is characterized by feedbacks, gradual trends and extreme events that are best revealed with long-term experimental studies of hydrological processes and biological communities. In this review, we identified 81 US Department of Agriculture (USDA) experimental watersheds, forests and ranges with data records of more than 20 years measuring important ecosystem dynamics such as variations in vegetation, precipitation, climate, runoff, water quality and soil moisture. Through a series of examples, we showed how USDA long-term data have been used to understand key ecohydrological issues, including (1) time lag between cause and effects, (2) critical thresholds and cyclic trends, (3) context of rare and extreme events and (4) mechanistic feedbacks for simulation modelling. New analyses of network-wide, long-term data from USDA experimental sites were used to illustrate the potential for multi-year, multi-site ecohydrological research. Three areas of investigation were identified to best exploit the unique spatial distribution and long-term data of USDA experimental sites: convergence, cumulative synthesis and autocorrelation. This review underscored the need for continuous, interdisciplinary data records spanning more than 20 years across a wide range of ecosystems within and outside the conterminous USA to address major crosscutting problems facing ecohydrology. Conversely, the heightened interest in ecohydrology has impacted USDA experimental sites by encouraging new long-term data collection efforts and adapting existing long-term data collection networks to address new science issues. Copyright © 2008 John Wiley & Sons, Ltd.

Over the last century, proliferation of velvet mesquite ( Prosopis velutina ) in Southwestern grasslands has led to mesquite removal to increase livestock forage, but the effects of mesquite on the fluxes of C- and N-based gases are not well understood. We report soil surface fluxes and porespace concentrations of carbon dioxide (CO 2 ), nitrous oxide (N 2 O), and methane (CH 4 ) over two monsoon seasons beneath mesquite canopy (LIVE), in open grassland (OPEN), and under a mesquite skeleton (DEAD) in Southeastern Arizona. In 2003, CO 2 production was not different among sites, but on three 2004 measurement dates, CO 2 production was greatest from LIVE. In both years, N 2 O production was highest in LIVE in early monsoon, while CH 4 production dominated in OPEN and DEAD sites. CH 4 consumption increased in all sites as the summer progressed, resulting in net monsoon CH 4 fluxes near zero. Over both years, temperature and precipitation accounted for significant variability in CO 2 flux and precipitation correlated with N 2 O production. Soil moisture accounted for significant variability in CH 4 flux in 2003. Observed variations in trace gas dynamics suggest that several years of measurements would be required to accurately predict mesquite management effects on trace gas flux in Southwestern rangelands.

Upper-elevation villagers in Nepal harvest large numbers of 5–10 cm diameter trees to construct itinerant herders' shelters. The harvest of these poles, as well as fuelwood and tree-leaf livestock fodder, may be altering upper-elevation forest structure and resource availability in Nepal. Near a village in west-central Nepal, we evaluated the sustainability of Symplocos ramosissima poles harvested for herders' shelter construction by comparing estimates of harvest and replenishment rates under 4 scenarios of spatial distribution of harvest within 3 equal-area forest types: 1) harvest evenly distributed, 2) harvest only in forest type closest to area of hut construction, 3) harvest in two closest forest types, 4) harvest in each forest type proportional to recent use patterns, as deduced from the density of stumps of pole-sized S. ramosissima. Mean density ± SE of pole-size S. ramosissima was 375 ± 32 stems ha−1. Tree-ring analysis of 24 pole-size S. ramosissima indicated a mean age of 35 years an...