Geology topics

Kari E. Veblen

Publications and source records attributed to Kari E. Veblen.

13 recordsLinked to original sources

USGS2024

Season of grazing interacts with soil texture, selecting for associations of biocrust morphogroups

Livestock grazing, a widespread land use in semi-arid systems, is often placed in opposition to the perpetuation of biological soil crusts (“biocrusts”: lichens, mosses, and algal crusts including cyanobacteria) that live on the soil surface and provide ecosystem functions. The composition of biocrusts and vascular plants varies with climate, soils, and disturbance. In general, ruderal mosses and light algal crusts make up greater proportions of biocrusts in the presence of disturbance, although morphogroups of biocrusts respond differently to various disturbances. It is unknown if there are scenarios under which grazing can occur and ruderal components of biocrust could be maintained. We examine the hypothesis that soil surface texture-moisture interactions influence the ability of biocrusts to withstand trampling, reasoning that finer-textured soils are firmer (therefore serving as a better substrate for biocrusts) when dry and that coarser-textured are firmer when wet. We test these relationships within Birds of Prey, National Conservation Area (Boise, Idaho, USA). Results demonstrate two associations of biocrusts, dependent on season of grazing: one dominated by light algal crusts and lichens that frequently occurs with wet season grazing, and a second dominated by tall mosses and cup lichens that frequently occurs with dry season grazing. High cover of the invasive annual grass, Bromus tectorum (L.) was observed on sites with coarse-textured soils, and high sand content, that are grazed at relatively high intensities, creating unstable surfaces, and likely putting biocrusts at greater susceptibility to trampling. Results suggest that livestock management that accounts for soil texture and moisture could be used to maintain cover of ruderal biocrusts on fine-textured soils, that are grazed in the dry season, at low intensity. We discuss our findings in the context of managing for species of interest. Our findings are timely as varying the season of grazing is increasingly discussed as a means of favoring desirable native perennial grasses. Although ruderal morphogroups of biocrusts are not interpreted as having equivalent ecosystem functions compared to intact biocrusts, their contributions to soil stability, fertility, hydrology, and weed abatement could increase if they were more intentionally targeted by management.

Geoderma↗

USGS2023

Goldilocks forbs: Survival is highest outside—but not too far outside—of Wyoming big sagebrush canopies

In arid and semiarid systems, positive effects of nurse shrubs generally occur immediately underneath and around shrub canopies, creating microsites that can be targeted to promote plant establishment in restoration settings. Alternatively, the best microsites may occur in the interspace zone immediately surrounding nurse shrubs if positive abiotic effects extend beyond nurse shrub canopy boundaries and if competition with nurse shrubs is reduced in that zone. In the Intermountain West, U.S.A., we investigated survival of transplanted herbaceous seedlings at different distances from Wyoming big sagebrush ( Artemisia tridentata ssp. wyomingensis ) canopies. We planted two native perennial forb species, Munro's globemallow ( Sphaeralcea munroana ) and common yarrow ( Achillea millefolium ), and two native perennial grass species, bluebunch wheatgrass ( Pseudoroegneria spicata ) and bottlebrush squirreltail ( Elymus elymoides ), at four distances from sagebrush canopies at six sites across the Intermountain West, repeated across 2 years. Under above-normal precipitation, proximity to sagebrush influenced first-year survival of the forb, but not grass, species. Globemallow and yarrow survival were highest mid-way between the canopy dripline and maximum interspace distance between neighboring sagebrush plants. Ground cover characteristics and globemallow survival covaried with respect to distance from shrub, suggesting ground cover characteristics as indicators of suitable planting microsites. Under drier conditions, survival of all species was low and unaffected by distance from canopies. Our results demonstrate the value of fine-tuning the canopy-interspace paradigm to more carefully consider how plant performance may differ across zones within the interspace region between plants, especially when the goal is to maximize plant establishment in nondrought years.

Restoration Ecology↗

USGS2023

Establishing big sagebrush seedlings on the Colorado Plateau

Factors such as soil type and precipitation vary across rangeland landscapes, and these factors affect restoration outcomes and ultimately mean that “one size fits all” management strategies are not effective across large, complex landscapes. Big sagebrush (Artemisia tridentata) is a foundational rangeland species that is important to wildlife habitat across the western U.S. On the Colorado Plateau, sagebrush is important browse for ungulates, such as mule deer and pronghorn, which motivates a great deal of restoration effort. However, most scientific knowledge of big sagebrush comes from the Great Basin, and we know much less about how to restore sagebrush on the Colorado Plateau, where soils and precipitation patterns are different and conditions are warmer and drier. This fact sheet describes research about establishing and restoring sagebrush seedlings on the Colorado Plateau.

Utah↗

USGS2022

Soil depth and precipitation moderate soil textural effects on seedling survival of a foundation shrub species

In drylands, there is a need for controlled experiments over multiple planting years to examine how woody seedlings respond to soil texture and the potentially interactive effects of soil depth and precipitation. Understanding how multiple environmental factors interactively influence plant establishment is critical to restoration ecology and in this case to broad-scale restoration efforts in western US drylands dominated by big sagebrush ( Artemisia tridentata ). We planted sagebrush seedlings across a range of soil textures and depths in the southern portion of the species' range, on the Colorado Plateau. We evaluated survival of repeated plantings of caged and uncaged seedlings over two years across 20 plots in wet vs. average precipitation years at one site, and examined broader patterns of sagebrush seedling survival during an average precipitation year in 56 plots across four sites. First-year survival was >9x higher under wet than average precipitation. Under favorable (wet) conditions, early sagebrush seedling survival was highest on coarser soils, especially those that also had a shallower restrictive layer (e.g., 50-100 cm). Under average precipitation, soil texture and depth effects on survival of newly-planted seedlings were much weaker, but older (>1 yr) seedlings benefitted from growing on coarser textured soils. It may be possible to increase survival by sheltering seedlings with small mesh cages, which likely improve moisture availability. Our results provide new insights into environmental factors that limit woody seedling survival in drylands and illustrate that planting in wet years and incorporating detailed soil setting information could increase survival of sagebrush seedlings in restoration projects.

Restoration Ecology↗

USGS2022

Leveraging rangeland monitoring data for wildlife: From concept to practice

Available rangeland data, from field-measured plots to remotely sensed landscapes, provide much needed information for mapping and modeling wildlife habitats. Better integration of wildlife habitat characteristics into rangeland monitoring schemes is needed for most rangeland wildlife species at varying spatial and temporal scales. Here, we aim to stimulate use of and inspire ideas about rangeland monitoring data in the context of wildlife habitat modeling and species conservation.

Colorado, Kansas, Montana, Nebraska, New Mexico, N↗

USGS2021

Drivers of seedling establishment success in dryland restoration efforts

Restoration of degraded drylands is urgently needed to mitigate climate change, reverse desertification and secure livelihoods for the two billion people who live in these areas. Bold global targets have been set for dryland restoration to restore millions of hectares of degraded land. These targets have been questioned as overly ambitious, but without a global evaluation of successes and failures it is impossible to gauge feasibility. Here we examine restoration seeding outcomes across 174 sites on six continents, encompassing 594,065 observations of 671 plant species. Our findings suggest reasons for optimism. Seeding had a positive impact on species presence: in almost a third of all treatments, 100% of species seeded were growing at first monitoring. However, dryland restoration is risky: 17% of projects failed, with no establishment of any seeded species, and consistent declines were found in seeded species as projects matured. Across projects, higher seeding rates and larger seed sizes resulted in a greater probability of recruitment, with further influences on species success including site aridity, taxonomic identity and species life form. Our findings suggest that investigations examining these predictive factors will yield more effective and informed restoration decision-making.

Nature Ecology and Evolution↗

USGS2021

Regional ensemble modeling reduces uncertainty for digital soil mapping

Recent country and continental-scale digital soil mapping efforts have used a single model to predict soil properties across large regions. However, different ecophysiographic regions within large-extent areas are likely to have different soil-landscape relationships so models built specifically for these regions may more accurately capture these relationships relative to a ‘global’ model. We ask the question: Is a single ‘global’ model sufficient or are regionally-specific models useful for accurate digital soil mapping? We test this question by modeling soil depth classes across the 432,000 km 2 upper Colorado River Basin in the Western USA using a single global model, multiple ecophysiographic models, and ensembles of the ecophysiographic models. Effective soil depth class observations ( n = 12,194) were derived from multiple soil databases. Fifty-seven environmental covariates were derived from a 30 m digital elevation model, climate data, satellite imagery, and aeroradiometric data. Three independent land classifications were used to stratify the area. Two expert-derived land classifications, USDA Major Land Resource Areas (MLRA) and US-EPA Level III ecoregions, divided the study area into multiple ecophysiographic regions based on vegetation and broad-scale physiographic differences. The third land classification divided the study area into broad landforms. Soil depth observations were split into separate training ( n = 10,470) and validation ( n = 1,724) datasets. First, a ‘global’ random forest model was used to model soil depth classes using all training observations and covariates. ‘Global’ denotes a model built with all training data across the extent of the area, not a model at world extent. Second, the land classifications were used to subset the observations into ecophysiographic sub-datasets and random forest models were refit for each region. Models fit by ecophysiographic region are referred to as regional models. Thirdly, predictions from each regional model were fused into regional-ensemble models. Accuracy, Brier scores, and Shannon’s entropy were used to compare model accuracy and uncertainty. Regional ecophysiographic models were also compared to models built for geographic areas that were defined solely to be approximately equal in area. Training dataset density and the imbalance ratio were investigated to determine if data characteristics influenced regional accuracy/uncertainty metrics. Accuracy for the global model using the validation set was 62.8%. Regional model accuracies ranged between 56.1% and 75.0%. We found: 1) useful inter-regional differences in global model accuracy were revealed when the global model was validated by region, 2) no consistent relationship between training observation density and accuracy/uncertainty metrics, 3) no meaningful differences in accuracy and uncertainty metrics between physiographic and geographic regions, 4) ensembles of regionally-specific models were approximately as accurate as global models, and 5) both region-specific models and ensembles of regional models were less uncertain than the global model. Overall, we recommend the use of soil depth class predictions made from MLRA regional ensemble models because this prediction had higher accuracy than the ecoregion ensemble model prediction, but lower uncertainty than both the global model and the landform ensemble model predictions. We answer our question: Ensembles of regionally-specific models are approximately as accurate as global models, but result in less uncertainty.

Arizona, Colorado, Nevada, New Mexico, Utah, Wyomi↗

USGS2020

Context-dependent effects of livestock grazing in deserts of western North America

This chapter provides a general review of grazing disturbance by large mammalian grazers and the role of ecological context in moderating its effects, with emphasis on North American deserts. It discusses the ecological consequences of cessation of livestock grazing and present a case study from the Mojave Desert, United States of America. A primary effect of grazing is selective removal and ingestion of herbaceous plants, in contrast to removal of woody biomass from woody plants by browsing herbivores. The consequences of grazing–and resilience of a system to grazing disturbance–are highly context-dependent and vary across rangelands globally. Synergistic interactions between soil depth and plant structural properties, such as rooting depth and water-use efficiency, also influence plant access to water, and therefore moderate plant responses to drought and resilience to grazing. In some ecosystems, livestock grazing constitutes a novel or intensified disturbance. Application of the Intermediate Disturbance Hypothesis to grazing disturbance has been relatively infrequently tested relative to other ecological disturbances.

California, Nevada↗

USGS2018

Change in dominance determines herbivore effects on plant biodiversity

Herbivores alter plant biodiversity (species richness) in many of the world’s ecosystems, but the magnitude and the direction of herbivore effects on biodiversity vary widely within and among ecosystems. One current theory predicts that herbivores enhance plant biodiversity at high productivity but have the opposite effect at low productivity. Yet, empirical support for the importance of site productivity as a mediator of these herbivore impacts is equivocal. Here, we synthesize data from 252 large-herbivore exclusion studies, spanning a 20-fold range in site productivity, to test an alternative hypothesis—that herbivore-induced changes in the competitive environment determine the response of plant biodiversity to herbivory irrespective of productivity. Under this hypothesis, when herbivores reduce the abundance (biomass, cover) of dominant species (for example, because the dominant plant is palatable), additional resources become available to support new species, thereby increasing biodiversity. By contrast, if herbivores promote high dominance by increasing the abundance of herbivory-resistant, unpalatable species, then resource availability for other species decreases reducing biodiversity. We show that herbivore-induced change in dominance, independent of site productivity or precipitation (a proxy for productivity), is the best predictor of herbivore effects on biodiversity in grassland and savannah sites. Given that most herbaceous ecosystems are dominated by one or a few species, altering the competitive environment via herbivores or by other means may be an effective strategy for conserving biodiversity in grasslands and savannahs globally.

Nature Ecology & Evolution↗

USGS2017

Patterns in Greater Sage-grouse population dynamics correspond with public grazing records at broad scales

Human land use, such as livestock grazing, can have profound yet varied effects on wildlife interacting within common ecosystems, yet our understanding of land-use effects is often generalized from short-term, local studies that may not correspond with trends at broader scales. Here we used public land records to characterize livestock grazing across Wyoming, USA, and we used Greater Sage-grouse ( Centrocercus urophasianus ) as a model organism to evaluate responses to livestock management. With annual counts of male Sage-grouse from 743 leks (breeding display sites) during 2004–2014, we modeled population trends in response to grazing level (represented by a relative grazing index) and timing across a gradient in vegetation productivity as measured by the Normalized Vegetation Difference Index (NDVI). We found grazing can have both positive and negative effects on Sage-grouse populations depending on the timing and level of grazing. Sage-grouse populations responded positively to higher grazing levels after peak vegetation productivity, but populations declined when similar grazing levels occurred earlier, likely reflecting the sensitivity of cool-season grasses to grazing during peak growth periods. We also found support for the hypothesis that effects of grazing management vary with local vegetation productivity. These results illustrate the importance of broad-scale analyses by revealing patterns in Sage-grouse population trends that may not be inferred from studies at finer scales, and could inform sustainable grazing management in these ecosystems.

Wyoming↗

USGS2015

Long-term plant responses to climate are moderated by biophysical attributes in a North American desert

Recent elevated temperatures and prolonged droughts in many already water-limited regions throughout the world, including the southwestern U.S., are likely to intensify according to future climate-model projections. This warming and drying can negatively affect perennial vegetation and lead to the degradation of ecosystem properties. To better understand these detrimental effects, we formulate a conceptual model of dryland ecosystem vulnerability to climate change that integrates hypotheses on how plant species will respond to increases in temperature and drought, including how plant responses to climate are modified by landscape, soil, and plant attributes that are integral to water availability and use. We test the model through a synthesis of fifty years of repeat measurements of perennial plant species cover in large permanent plots across the Mojave Desert, one of the most water-limited ecosystems in North America. Plant species ranged in their sensitivity to precipitation in different seasons, capacity to increase in cover with high precipitation, and resistance to decrease in cover with low precipitation. Our model successfully explains how plant responses to climate are modified by biophysical attributes in the Mojave Desert. For example, deep-rooted plants were not as vulnerable to drought on soils that allowed for deep water percolation, whereas shallow-rooted plants were better buffered from drought on soils that promoted water retention near the surface. Synthesis. Our results emphasize the importance of understanding climate-vegetation relationships in the context of biophysical attributes that influence water availability and provide an important forecast of climate-change effects, including plant mortality and land degradation in dryland regions throughout the world.

California, Nevada↗

USGS2013

Monitoring of livestock grazing effects on Bureau of Land Management land

Public land management agencies, such as the Bureau of Land Management (BLM), are charged with managing rangelands throughout the western United States for multiple uses, such as livestock grazing and conservation of sensitive species and their habitats. Monitoring of condition and trends of these rangelands, particularly with respect to effects of livestock grazing, provides critical information for effective management of these multiuse landscapes. We therefore investigated the availability of livestock grazing-related quantitative monitoring data and qualitative region-specific Land Health Standards (LHS) data across BLM grazing allotments in the western United States. We then queried university and federal rangeland science experts about how best to prioritize rangeland monitoring activities. We found that the most commonly available monitoring data were permittee-reported livestock numbers and season-of-use data (71% of allotments) followed by repeat photo points (58%), estimates of forage utilization (52%), and, finally, quantitative vegetation measurements (37%). Of the 57% of allotments in which LHS had been evaluated as of 2007, the BLM indicated 15% had failed to meet LHS due to livestock grazing. A full complement of all types of monitoring data, however, existed for only 27% of those 15%. Our data inspections, as well as conversations with rangeland experts, indicated a need for greater emphasis on collection of grazing-related monitoring data, particularly ground cover. Prioritization of where monitoring activities should be focused, along with creation of regional monitoring teams, may help improve monitoring. Overall, increased emphasis on monitoring of BLM rangelands will require commitment at multiple institutional levels.

Society for Range Management↗

USGS2011

Range-wide assessment of livestock grazing across the sagebrush biome

Domestic livestock grazing occurs in virtually all sagebrush habitats and is a prominent disturbance factor. By affecting habitat condition and trend, grazing influences the resources required by, and thus, the distribution and abundance of sagebrush-obligate wildlife species (for example, sage-grouse Centrocercus spp.). Yet, the risks that livestock grazing may pose to these species and their habitats are not always clear. Although livestock grazing intensity and associated habitat condition may be known in many places at the local level, we have not yet been able to answer questions about use, condition, and trend at the landscape scale or at the range-wide scale for wildlife species. A great deal of information about grazing use, management regimes, and ecological condition exists at the local level (for individual livestock management units) under the oversight of organizations such as the Bureau of Land Management (BLM). However, the extent, quality, and types of existing data are unknown, which hinders the compilation, mapping, or analysis of these data. Once compiled, these data may be helpful for drawing conclusions about rangeland status, and we may be able to identify relationships between those data and wildlife habitat at the landscape scale. The overall objective of our study was to perform a range-wide assessment of livestock grazing effects (and the relevant supporting data) in sagebrush ecosystems managed by the BLM. Our assessments and analyses focused primarily on local-level management and data collected at the scale of BLM grazing allotments (that is, individual livestock management units). Specific objectives included the following: 1. Identify and refine existing range-wide datasets to be used for analyses of livestock grazing effects on sagebrush ecosystems. 2. Assess the extent, quality, and types of livestock grazing-related natural resource data collected by BLM range-wide (i.e., across allotments, districts and regions). 3. Compile and synthesize recommendations from federal and university rangeland science experts about how BLM might prioritize collection of different types of livestock grazing-related natural resource data. 4. Investigate whether range-wide datasets (Objective 1) could be used in conjunction with remotely sensed imagery to identify across broad scales (a) allotments potentially not meeting BLM Land Health Standards (LHS) and (b) allotments in which unmet standards might be attributable to livestock grazing. Objective 1: We identified four datasets that potentially could be used for analyses of livestock grazing effects on sagebrush ecosystems. First, we obtained the most current spatial data (typically up to 2007, 2008, or 2009) for all BLM allotments and compiled data into a coarse, topologically enforced dataset that delineated grazing allotment boundaries. Second, we obtained LHS evaluation data (as of 2007) for all allotments across all districts and regions; these data included date of most recent evaluation, BLM determinations of whether region-specific standards were met, and whether BLM deemed livestock to have contributed to any unmet standards. Third, we examined grazing records of three types: Actual Use (permittee-reported), Billed Use (BLM-reported), and Permitted Use (legally authorized). Finally, we explored the possibility of using existing Natural Resources Conservation Service (NRCS) Ecological Site Description (ESD) data to make up-to-date estimates of production and forage availability on BLM allotments. Objective 2: We investigated the availability of BLM livestock grazing-related monitoring data and the status of LHS across 310 randomly selected allotments in 13 BLM field offices. We found that, relative to other data types, the most commonly available monitoring data were Actual Use numbers (permittee-reported livestock numbers and season-of-use), followed by Photo Point, forage Utilization, and finally, Vegetation Trend measurement data. Data availability and frequency of data collection varied across allotments and field offices. Analysis of the BLM's LHS data indicated 67 percent of allotments analyzed were meeting standards. For those not meeting standards, livestock were considered the causal factor in 45 percent of cases (about 15 percent of all allotments). Objective 3: We sought input from 42 university and federal rangeland science experts about how best to prioritize rangeland monitoring activities associated with ascertaining livestock impacts on vegetation resources. When we presented a hypothetical scenario to these scientists and asked them to prioritize monitoring activities, the most common response was to measure ground and vegetation cover, a variable that in many cases (10 of 13 field offices sampled) BLM had already identified as a monitoring priority. Experts identified several other traditional (for example, photo points) and emerging approaches (for example, high-resolution aerial photography) to monitoring. Objective 4: We used spatial allotment data (described in Objective 1) and remotely sensed vegetation data (sagebrush cover, herbaceous vegetation cover, litter and bare soil) to assess differences in allotment LHS status ("Not met" vs. "Met"; if "Not met" - livestock-caused vs. not). We then developed logistic regression models, using vegetation variables to predict LHS status of BLM allotments in sagebrush steppe habitats in Wyoming and portions of Montana and Colorado. In general, we found that more consistent data collection at the local level might improve suitability of data for broad-scale analyses of livestock impacts. As is, data collection methodologies varied across field offices and States, and we did not find any local-level monitoring data (Actual Use, Utilization, Vegetation Trend) that had been collected consistently enough over time or space for range-wide analyses. Moreover, continued and improved emphasis on monitoring also may aid local management decisions, particularly with respect to effects of livestock grazing. Rangeland science experts identified ground cover as a high monitoring priority for assessing range condition and emphasized the importance of tracking livestock numbers and grazing dates. Ultimately, the most effective monitoring program may entail both increased data collection effort and the integration of alternative monitoring approaches (for example, remote sensing or monitoring teams). In the course of our study, we identified three additional datasets that could potentially be used for range-wide analyses: spatial allotment boundary data for all BLM allotments range-wide, LHS evaluations of BLM allotments, and livestock use data (livestock numbers and grazing dates). It may be possible to use these spatial datasets to help prioritize monitoring activities over the extensive land areas managed by BLM. We present an example of how we used spatial allotment boundary data and LHS data to test whether remotely sensed vegetation characteristics could be used to predict which allotments met or did not meet LHS. This approach may be further improved by the results of current efforts by BLM to test whether more intensive (higher resolution) LHS assessments more accurately describe land health status. Standardized data collection in more ecologically meaningful land units may improve our ability to use local-level data for broad-scale analyses.

Open-File Report↗