Geology topics

David S. Pilliod

Publications and source records attributed to David S. Pilliod.

At least 91 records · Page 5Linked to original sources

USGS2018

Regional variation in drivers of connectivity for two frog species (Rana pretiosa and R. luteiventris) from the U.S. Pacific Northwest

Comparative landscape genetics has uncovered high levels of variability in which landscape factors affect connectivity among species and regions. However, the relative importance of species traits versus environmental variation for predicting landscape patterns of connectivity is unresolved. We provide evidence from a landscape genetics study of two sister taxa of frogs, the Oregon spotted frog ( Rana pretiosa ) and the Columbia spotted frog ( Rana luteiventris ) in Oregon and Idaho, USA. Rana pretiosa is relatively more dependent on moisture for dispersal than R. luteiventris , so if species traits influence connectivity, we predicted that connectivity among R. pretiosa populations would be more positively associated with moisture than R. luteiventris . However, if environmental differences are important drivers of gene flow, we predicted that connectivity would be more positively related to moisture in arid regions. We tested these predictions using eight microsatellite loci and gravity models in two R. pretiosa regions and four R. luteiventris regions ( n = 1,168 frogs). In R. pretiosa , but not R. luteiventris , connectivity was positively related to mean annual precipitation, supporting our first prediction. In contrast, connectivity was not more positively related to moisture in more arid regions. Various temperature metrics were important predictors for both species and in all regions, but the directionality of their effects varied. Therefore, the pattern of variation in drivers of connectivity was consistent with predictions based on species traits rather than on environmental variation.

Molecular Ecology↗

USGS2018

Land treatment exploration tool

Overview Land managers make decisions regarding restoration and rehabilitation actions that influence landscapes and ecosystems. Many of these decisions involve soil and vegetation manipulations, often known as land treatments. Historically, treatments were planned on a case by case basis with decisions derived from personal experience of past successes or failures. Current adaptive management strategies require a more structured and robust approach to the planning and implementation of land treatments. The U.S. Geological Survey partnered with the Bureau of Land Management to create the Land Treatment Exploration Tool to facilitate adaptive management of land treatments . The Exploration Tool taps into a wealth of information about past treatments in the Land Treatment Digital Library (LTDL, https://www.usgs.gov/apps/ltdl ). The Exploration Tool is designed for use by resource managers during the land treatment planning stage. This tool summarizes environmental characteristics of planned treatment areas and facilitates adaptive management practices by comparing those characteristics to similar legacy treatments.

Fact Sheet↗

USGS2018

Adapting management to a changing world: Warm temperatures, dry soil, and interannual variability limit restoration success of a dominant woody shrub in temperate drylands

Restoration and rehabilitation of native vegetation in dryland ecosystems, which encompass over 40% of terrestrial ecosystems, is a common challenge that continues to grow as wildfire and biological invasions transform dryland plant communities. The difficulty in part stems from low and variable precipitation, combined with limited understanding about how weather conditions influence restoration outcomes, and increasing recognition that one‐time seeding approaches can fail if they do not occur during appropriate plant establishment conditions. The sagebrush biome, which once covered over 620,000 km 2 of western North America, is a prime example of a pressing dryland restoration challenge for which restoration success has been variable. We analyzed field data on Artemisia tridentata (big sagebrush) restoration collected at 771 plots in 177 wildfire sites across its western range, and used process‐based ecohydrological modeling to identify factors leading to its establishment. Our results indicate big sagebrush occurrence is most strongly associated with relatively cool temperatures and wet soils in the first spring after seeding. In particular, the amount of winter snowpack, but not total precipitation, helped explain the availability of spring soil moisture and restoration success. We also find considerable interannual variability in the probability of sagebrush establishment. Adaptive management strategies that target seeding during cool, wet years or mitigate effects of variability through repeated seeding may improve the likelihood of successful restoration in dryland ecosystems. Given consistent projections of increasing temperatures, declining snowpack, and increasing weather variability throughout midlatitude drylands, weather‐centric adaptive management approaches to restoration will be increasingly important for dryland restoration success.

Great Basin↗

USGS2018

Thresholds and hotspots for shrub restoration following a heterogeneous megafire

Context Reestablishing foundational plant species through aerial seeding is an essential yet challenging step for restoring the vast semiarid landscapes impacted by plant invasions and wildfire-regime shifts. A key component of the challenge stems from landscape variability and its effects on plant recovery. Objectives We assessed landscape correlates, thresholds, and tipping points for sagebrush presence from fine-scale sampling across a large, heterogeneous area burned the previous year, where we were able to quantify soil surface features that are typically occluded yet can strongly affect recovery patterns. Methods Hypothesis testing and binary-decision trees were used to evaluate factors affecting initial sagebrush establishment, using 2171 field plots (totaling ~ 2,000,000 m 2 sampled) over a 113,000-ha region. Results Sagebrush established in 50% of plots where it was seeded, a > 12-fold greater establishment frequency than in unseeded areas. Sagebrush establishment was enhanced in threshold-like ways by elevation (> 1200 m ASL), topographic features that alter heatload and soil water, and by soil-surface features such as “fertile islands” that bore the imprint of pre-fire sagebrush. Sagebrush occupancy had a negative, linear relationship with exotic-annual grass cover and parabolic relationship with perennial bunchgrasses (optimal at 40% cover). Conclusions Our approach revealed interactive, ecological relationships such as novel soil-surface effects on first year establishment of sagebrush across the burned landscape, and identified “hot spots” for recovery. The approach could be expanded across sites and years to provide the information needed to explain past seeding successes or failures, and in designing treatments at the landscape scale.

Idaho↗

USGS2018

A conservation paradox in the Great Basin—Altering sagebrush landscapes with fuel breaks to reduce habitat loss from wildfire

Interactions between fire and nonnative, annual plant species (that is, “the grass/fire cycle”) represent one of the greatest threats to sagebrush ( Artemisia spp.) ecosystems and associated wildlife, including the greater sage-grouse ( Centrocercus urophasianus ). In 2015, U.S. Department of the Interior called for a “science-based strategy to reduce the threat of large-scale rangeland fire to habitat for the greater sage-grouse and the sagebrush-steppe ecosystem.” An associated guidance document, the “Integrated Rangeland Fire Management Strategy Actionable Science Plan,” identified fuel breaks as high priority areas for scientific research. Fuel breaks are intended to reduce fire size and frequency, and potentially they can compartmentalize wildfire spatial distribution in a landscape. Fuel breaks are designed to reduce flame length, fireline intensity, and rates of fire spread in order to enhance firefighter access, improve response times, and provide safe and strategic anchor points for wildland fire-fighting activities. To accomplish these objectives, fuel breaks disrupt fuel continuity, reduce fuel accumulation, and (or) increase plants with high moisture content through the removal or modification of vegetation in strategically placed strips or blocks of land. Fuel breaks are being newly constructed, enhanced, or proposed across large areas of the Great Basin to reduce wildfire risk and to protect remaining sagebrush ecosystems (including greater sage-grouse habitat). These projects are likely to result in thousands of linear miles of fuel breaks that will have direct ecological effects across hundreds of thousands of acres through habitat loss and conversion. These projects may also affect millions of acres indirectly because of edge effects and habitat fragmentation created by networks of fuel breaks. Hence, land managers are often faced with a potentially paradoxical situation: the need to substantially alter sagebrush habitats with fuel breaks to ultimately reduce a greater threat of their destruction from wildfire. However, there is relatively little published science that directly addresses the ability of fuel breaks to influence fire behavior in dryland landscapes or that addresses the potential ecological effects of the construction and maintenance of fuel breaks on sagebrush ecosystems and associated wildlife species. This report is intended to provide an initial assessment of both the potential effectiveness of fuel breaks and their ecological costs and benefits. To provide this assessment, we examined prior studies on fuel breaks and other scientific evidence to address three crucial questions: (1) How effective are fuel breaks in reducing or slowing the spread of wildfire in arid and semi-arid shrubland ecosystems? (2) How do fuel breaks affect sagebrush plant communities? (3) What are the effects of fuel breaks on the greater sage-grouse, other sagebrush obligates, and sagebrush-associated wildlife species? We also provide an overview of recent federal policies and management directives aimed at protecting remaining sagebrush and greater sage-grouse habitat; describe the fuel conditions, fire behavior, and fire trends in the Great Basin; and suggest how scientific inquiry and management actions can improve our understanding of fuel breaks and their effects in sagebrush landscapes.

Open-File Report↗

USGS2018

An analytical framework for estimating aquatic species density from environmental DNA

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Ecology and Evolution↗

USGS2018

Assessing the effectiveness of riparian restoration projects using Landsat and precipitation data from the cloud-computing application ClimateEngine.org

Riparian vegetation along streams provides a suite of ecosystem services in rangelands and thus is the target of restoration when degraded by over-grazing, erosion, incision, or other disturbances. Assessments of restoration effectiveness depend on defensible monitoring data, which can be both expensive and difficult to collect. We present a method and case study to evaluate the effectiveness of restoration of riparian vegetation using a web-based cloud-computing and visualization tool (ClimateEngine.org) to access and process remote sensing and climate data. Restoration efforts on an Eastern Oregon ranch were assessed by analyzing the riparian areas of four creeks that had in-stream restoration structures constructed between 2008 and 2011. Within each study area, we retrieved spatially and temporally aggregated values of summer (June, July, August) normalized difference vegetation index (NDVI) and total precipitation for each water year (October-September) from 1984 to 2017. We established a pre-restoration (1984–2007) linear regression between total water year precipitation and summer NDVI for each study area, and then compared the post-restoration (2012–2017) data to this pre-restoration relationship. In each study area, the post-restoration NDVI-precipitation relationship was statistically distinct from the pre-restoration relationship, suggesting a change in the fundamental relationship between precipitation and NDVI resulting from stream restoration. We infer that the in-stream structures, which raised the water table in the adjacent riparian areas, provided additional water to the streamside vegetation that was not available before restoration and reduced the dependence of riparian vegetation on precipitation. This approach provides a cost-effective, quantitative method for assessing the effects of stream restoration projects on riparian vegetation.

Oregon↗

USGS2018

Estimating vegetation biomass and cover across large plots in shrub and grass dominated drylands using terrestrial lidar and machine learning

Terrestrial laser scanning (TLS) has been shown to enable an efficient, precise, and non-destructive inventory of vegetation structure at ranges up to hundreds of meters. We developed a method that leverages TLS collections with machine learning techniques to model and map canopy cover and biomass of several classes of short-stature vegetation across large plots. We collected high-definition TLS scans of 26 1-ha plots in desert grasslands and big sagebrush shrublands in southwest Idaho, USA. We used the Random Forests machine learning algorithm to develop decision tree models predicting the biomass and canopy cover of several vegetation classes from statistical descriptors of the aboveground heights of TLS points. Manual measurements of vegetation characteristics collected within each plot served as training and validation data. Models based on five or fewer TLS descriptors of vegetation heights were developed to predict the canopy cover fraction of shrubs (R 2 = 0.77, RMSE = 7%), annual grasses (R 2 = 0.70, RMSE = 21%), perennial grasses (R 2 = 0.36, RMSE = 12%), forbs (R 2 = 0.52, RMSE = 6%), bare earth or litter (R 2 = 0.49, RMSE = 19%), and the biomass of shrubs (R 2 = 0.71, RMSE = 175 g) and herbaceous vegetation (R 2 = 0.61, RMSE = 99 g) (all values reported are out-of-bag). Our models explained much of the variability between predictions and manual measurements, and yet we expect that future applications could produce even better results by reducing some of the methodological sources of error that we encountered. Our work demonstrates how TLS can be used efficiently to extend manual measurement of vegetation characteristics from small to large plots in grasslands and shrublands, with potential application to other similarly structured ecosystems. Our method shows that vegetation structural characteristics can be modeled without classifying and delineating individual plants, a challenging and time-consuming step common in previous methods applying TLS to vegetation inventory. Improving application of TLS to studies of shrub-steppe ecosystems will serve immediate management needs by enhancing vegetation inventories, environmental modeling studies, and the ability to train broader datasets collected from air and space.

Idaho↗

USGS2018

Weather-centric rangeland revegetation planning

Invasive annual weeds negatively impact ecosystem services and pose a major conservation threat on semiarid rangelands throughout the western United States. Rehabilitation of these rangelands is challenging due to interannual climate and subseasonal weather variability that impacts seed germination, seedling survival and establishment, annual weed dynamics, wildfire frequency, and soil stability. Rehabilitation and restoration outcomes could be improved by adopting a weather-centric approach that uses the full spectrum of available site-specific weather information from historical observations, seasonal climate forecasts, and climate-change projections. Climate data can be used retrospectively to interpret success or failure of past seedings by describing seasonal and longer-term patterns of environmental variability subsequent to planting. A more detailed evaluation of weather impacts on site conditions may yield more flexible adaptive-management strategies for rangeland restoration and rehabilitation, as well as provide estimates of transition probabilities between desirable and undesirable vegetation states. Skillful seasonal climate forecasts could greatly improve the cost efficiency of management treatments by limiting revegetation activities to time periods where forecasts suggest higher probabilities of successful seedling establishment. Climate-change projections are key to the application of current environmental models for development of mitigation and adaptation strategies and for management practices that require a multidecadal planning horizon. Adoption of new weather technology will require collaboration between land managers and revegetation specialists and modifications to the way we currently plan and conduct rangeland rehabilitation and restoration in the Intermountain West.

Rangeland Ecology and Management↗

USGS2018

An introduction and practical guide to use of the Soil-Vegetation Inventory Method (SVIM) data

Long-term vegetation dynamics across public rangelands in the western United States are not well understood because of the lack of large-scale, readily available historic datasets. The Bureau of Land Management’s Soil-Vegetation Inventory Method (SVIM) program was implemented between 1977 and 1983 across 14 western states, but the data have not been easily accessible. We introduce the SVIM vegetation cover dataset in a georeferenced, digital format; summarize how the data were collected; and discuss potential limitations and biases. We demonstrate how SVIM data can be compared with contemporary monitoring datasets to quantify changes in vegetation associated with wildfire and the abundance of exotic invasive species. Specifically, we compare SVIM vegetation cover data with cover data collected by BLM’s Assessment, Inventory, and Monitoring (AIM) program (2011–2016) in a focal area in the northern Great Basin. We address issues associated with analyzing and interpreting data from these distinct programs, including differences in survey methods and potential biases introduced by spatial and temporal variation in sampling. We compared SVIM and AIM survey methods at 44 plots and found that percent cover estimates had high correspondence for all measured functional groups. Comparisons between historic SVIM data and recent AIM data documented significant declines in the occupancy and cover of native shrubs and native perennial forbs , and a significant increase in exotic annual forbs. Wildfire was a driver of change for some functional groups, with greater change occurring in AIM plots that burned between the two time periods compared with those that did not. Our results are consistent with previous studies showing that many native shrub-dominated plant communities in the Great Basin have been replaced by exotic annuals. Our study demonstrates that SVIM data will be an important resource for researchers interested in quantifying vegetation change through time across public rangelands in the western United States.

Rangeland Ecology and Management↗

USGS2017

Heterogeneous responses of temperate-zone amphibian populations to climate change complicates conservation planning

The pervasive and unabated nature of global amphibian declines suggests common demographic responses to a given driver, and quantification of major drivers and responses could inform broad-scale conservation actions. We explored the influence of climate on demographic parameters (i.e., changes in the probabilities of survival and recruitment) using 31 datasets from temperate zone amphibian populations (North America and Europe) with more than a decade of observations each. There was evidence for an influence of climate on population demographic rates, but the direction and magnitude of responses to climate drivers was highly variable among taxa and among populations within taxa. These results reveal that climate drivers interact with variation in life-history traits and population-specific attributes resulting in a diversity of responses. This heterogeneity complicates the identification of conservation ‘rules of thumb’ for these taxa, and supports the notion of local focus as the most effective approach to overcome global-scale conservation challenges.

Scientific Reports↗

USGS2017

Survey of beaver-related restoration practices in rangeland streams of the western USA

Poor condition of many streams and concerns about future droughts in the arid and semi-arid western USA have motivated novel restoration strategies aimed at accelerating recovery and increasing water resources. Translocation of beavers into formerly occupied habitats, restoration activities encouraging beaver recolonization, and instream structures mimicking the effects of beaver dams are restoration alternatives that have recently gained popularity because of their potential socioeconomic and ecological benefits. However, beaver dams and dam-like structures also harbor a history of social conflict. Hence, we identified a need to assess the use of beaver-related restoration projects in western rangelands to increase awareness and accountability, and identify gaps in scientific knowledge. We inventoried 97 projects implemented by 32 organizations, most in the last 10 years. We found that beaver-related stream restoration projects undertaken mostly involved the relocation of nuisance beavers. The most common goal was to store water, either with beaver dams or artificial structures. Beavers were often moved without regard to genetics, disease, or potential conflicts with nearby landowners. Few projects included post-implementation monitoring or planned for longer term issues, such as what happens when beavers abandon a site or when beaver dams or structures breach. Human dimensions were rarely considered and water rights and other issues were mostly unresolved or addressed through ad-hoc agreements. We conclude that the practice and implementation of beaver-related restoration has outpaced research on its efficacy and best practices. Further scientific research is necessary, especially research that informs the establishment of clear guidelines for best practices.

Environmental Management↗

USGS2017

Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe

Terrestrial laser scanning (TLS) provides fast collection of high-definition structural information, making it a valuable field instrument to many monitoring applications. A weakness of TLS collections, especially in vegetation, is the occurrence of unsampled regions in point clouds where the sensor’s line-of-sight is blocked by intervening material. This problem, referred to as occlusion, may be mitigated by scanning target areas from several positions, increasing the chance that any given area will fall within the scanner’s line-of-sight from at least one position. Because TLS collections are often employed in remote regions where the scope of sampling is limited by logistical factors such as time and battery power, it is important to design field protocols which maximize efficiency and support increased quantity and quality of the data collected. This study informs researchers and practitioners seeking to optimize TLS sampling methods for vegetation monitoring in dryland ecosystems through three analyses. First, we quantify the 2D extent of occluded regions based on the range from single scan positions. Second, we measure the efficacy of additional scan positions on the reduction of 2D occluded regions (area) using progressive configurations of scan positions in 1 ha plots. Third, we test the reproducibility of 3D sampling yielded by a 5-scan/ha sampling methodology using redundant sets of scans. Analyses were performed using measurements at analysis scales of 5 to 50 cm across the 1-ha plots, and we considered plots in grass and shrub-dominated communities separately. In grass-dominated plots, a center-scan configuration and 5 cm pixel size sampled at least 90% of the area up to 18 m away from the scanner. In shrub-dominated plots, sampling at least 90% of the area was only achieved within a distance of 12 m. We found that 3 and 5 scans/ha are needed to sample at least ~ 70% of the total area (1 ha) in the grass and shrub-dominated plots, respectively, using 5 cm pixels to measure sampling presence-absence. The reproducibility of 3D sampling provided by a 5 position scan layout across 1-ha plots was 50% (shrub) and 70% (grass) using a 5-cm voxel size, whereas at the 50-cm voxel scale, reproducibility of sampling was nearly 100% for all plot types. Future studies applying TLS in similar dryland environments for vegetation monitoring may use our results as a guide to efficiently achieve sampling coverage and reproducibility in datasets.

Idaho↗

USGS2017

Refining the cheatgrass–fire cycle in the Great Basin: Precipitation timing and fine fuel composition predict wildfire trends

Larger, more frequent wildfires in arid and semi-arid ecosystems have been associated with invasion by non-native annual grasses, yet a complete understanding of fine fuel development and subsequent wildfire trends is lacking. We investigated the complex relationships among weather, fine fuels, and fire in the Great Basin, USA. We first modeled the annual and time-lagged effects of precipitation and temperature on herbaceous vegetation cover and litter accumulation over a 26-year period in the northern Great Basin. We then modeled how these fine fuels and weather patterns influence subsequent wildfires. We found that cheatgrass cover increased in years with higher precipitation and especially when one of the previous 3 years also was particularly wet. Cover of non-native forbs and native herbs also increased in wet years, but only after several dry years. The area burned by wildfire in a given year was mostly associated with native herb and non-native forb cover, whereas cheatgrass mainly influenced area burned in the form of litter derived from previous years’ growth. Consequently, multiyear weather patterns, including precipitation in the previous 1–3 years, was a strong predictor of wildfire in a given year because of the time needed to develop these fine fuel loads. The strong relationship between precipitation and wildfire allowed us to expand our inference to 10,162 wildfires across the entire Great Basin over a 35-year period from 1980 to 2014. Our results suggest that the region's precipitation pattern of consecutive wet years followed by consecutive dry years results in a cycle of fuel accumulation followed by weather conditions that increase the probability of wildfire events in the year when the cycle transitions from wet to dry. These patterns varied regionally but were strong enough to allow us to model annual wildfire risk across the Great Basin based on precipitation alone.

Idaho↗

USGS2017

Lidar aboveground vegetation biomass estimates in shrublands: Prediction, uncertainties and application to coarser scales

Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m subplots and 1 ha plots) to a larger landscape. A series of airborne Lidar-derived vegetation metrics were trained and linked with the field-measured biomass in Random Forests (RF) regression models. A Stepwise Multiple Regression (SMR) model was also explored as a comparison. Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the RF regression models with a pseudo R 2 of 0.76 and RMSE of 125 g/m 2 for shrub biomass and a pseudo R 2 of 0.74 and RMSE of 141 g/m 2 for total biomass, and a weak correlation with field-measured herbaceous biomass. The SMR results were similar but slightly better than RF, explaining 77–79% of the variance, with RMSE ranging from 120 to 129 g/m 2 for shrub and total biomass, respectively. We further explored the computational efficiency and relative accuracies of using point cloud and raster Lidar metrics at different resolutions (1 m to 1 ha). Metrics derived from the Lidar point cloud processing led to improved biomass estimates at nearly all resolutions in comparison to raster-derived Lidar metrics. Only at 1 m were the results from the point cloud and raster products nearly equivalent. The best Lidar prediction models of biomass at the plot-level (1 ha) were achieved when Lidar metrics were derived from an average of fine resolution (1 m) metrics to minimize boundary effects and to smooth variability. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure and statistical measures of this structure (e.g., standard deviation of height was a strong predictor of biomass). Using our model results, we developed spatially-explicit Lidar estimates of total and shrub biomass across our study site in the Great Basin, U.S.A., for monitoring and planning in this imperiled ecosystem.

Idaho↗

USGS2017

Long-term trends in restoration and associated land treatments in the southwestern United States

Restoration treatments, such as revegetation with seeding or invasive species removal, have been applied on U.S. public lands for decades. Temporal trends in these management actions have not been extensively summarized previously, particularly in the southwestern United States where invasive plant species, drought, and fire have altered dryland ecosystems. We assessed long-term (1940–2010) trends in restoration using approximately 4,000 vegetation treatments conducted on Bureau of Land Management lands across the southwestern United States. We found that since 1940, the proportions of seeding and vegetation/soil manipulation (e.g. vegetation removal or plowing) treatments have declined, while the proportions of prescribed burn and invasive species treatments have increased. Treatments in pinyon-juniper and big sagebrush communities declined in comparison to treatments in desert scrub, creosote bush, and riparian woodland communities. Restoration-focused treatment objectives increased relative to resource extraction objectives. Species richness and proportion of native species used in seeding treatments also increased. Inflation-adjusted costs per area rose 750% for vegetation/soil manipulation, 600% for seeding, and 400% for prescribed burn treatments in the decades from 1981 to 2010. Seeding treatments were implemented in warmer and drier years when compared to the climate conditions of the entire study period and warmer and wetter years relative to several years before and after the treatment. These results suggest that treatments over a 70-year period on public lands in the southwestern United States are shifting toward restoration practices that are increasingly large, expensive, and related to fire and invasive species control.

Restoration Ecology↗

USGS2017

Exploring the use of environmental DNA to determine the species of salmon redds

Annual redd counts are used to monitor the status and trends of salmonid populations, but methods to easily and reliably determine which of sympatric species made specific redds are lacking. We explored whether environmental DNA (eDNA) analysis might prove useful for determining the species of salmon redds. We collected eDNA samples from the interstitial spaces of redds of Chinook Salmon Oncorhynchus tshawytscha, redds of Coho Salmon O. kisutch, and areas of undisturbed gravel (n = 10, each), as well as from the water column adjacent to each of those sites in the Sandy River basin, Oregon, USA during the fall of 2013. The concentrations of Chinook and Coho eDNA were quantified within each sample using real-time PCR. The water in the interstitial spaces of redds contained significantly higher eDNA concentrations of the species that made the redd than (1) the other species and (2) the adjacent water column. In contrast, neither Chinook nor Coho eDNA was significantly more concentrated than the other in the water from the interstitial spaces of undisturbed gravel. The interstitial water of undisturbed gravel contained significantly higher eDNA concentrations of Coho than the adjacent water column. In contrast, Chinook eDNA concentration was similar in the interstitial water of undisturbed gravel and the adjacent water column. Both species’ redds had significantly higher concentrations of their respective species’ eDNA than did undisturbed gravel, but conclusions were confounded by differences in the timing and locations of sampling. This initial investigation highlights the potential value and some of the complexity of using eDNA analysis to indicate redd species.

Oregon↗

USGS2017

Seventy-five years of vegetation treatments on public rangelands in the Great Basin of North America

On the Ground Land treatments occurring over millions of hectares of public rangelands in the Great Basin over the last 75 years represent one of the largest vegetation manipulation and restoration efforts in the world. The ability to use legacy data from land treatments in adaptive management and ecological research has improved with the creation of the Land Treatment Digital Library (LTDL), a spatially explicit database of land treatments conducted by the U.S. Bureau of Land Management. The LTDL contains information on over 9,000 confirmed land treatments in the Great Basin, composed of seedings (58%), vegetation control treatments (24%), and other types of vegetation or soil manipulations (18%). The potential application of land treatment legacy data for adaptive management or as natural experiments for retrospective analyses of effects of land management actions on physical, hydrologic, and ecologic patterns and processes is considerable and just beginning to be realized.

California, Idaho, Nevada, Oregon, Utah↗