Geology topics

T.J. Stohlgren

Publications and source records attributed to T.J. Stohlgren.

At least 19 recordsLinked to original sources

USGS2017

Distributional changes and range predictions of downy brome (Bromus tectorum) in Rocky Mountain National Park

Downy brome (Bromus tectorum L.), an invasive winter annual grass, may be increasing in extent and abundance at high elevations in the western United States. This would pose a great threat to high-elevation plant communities and resources. However, data to track this species in high-elevation environments are limited. To address changes in the distribution and abundance of downy brome and the factors most associated with its occurrence, we used field sampling and statistical methods, and niche modeling. In 2007, we resampled plots from two vegetation surveys in Rocky Mountain National Park for presence and cover of downy brome. One survey was established in 1993 and had been resampled in 1999. The other survey was established in 1996 and had not been resampled until our study. Although not all comparisons between years demonstrated significant changes in downy brome abundance, its mean cover increased nearly fivefold from 1993 (0.7%) to 2007 (3.6%) in one of the two vegetation surveys (P = 0.06). Although the average cover of downy brome within the second survey appeared to be increasing from 1996 to 2007, this slight change from 0.5% to 1.2% was not statistically significant (P = 0.24). Downy brome was present in 50% more plots in 1999 than in 1993 (P = 0.02) in the first survey. In the second survey, downy brome was present in 30% more plots in 2007 than in 1996 (P = 0.08). Maxent, a species-environmental matching model, was generally able to predict occurrences of downy brome, as new locations were in the ranges predicted by earlier generated models. The model found that distance to roads, elevation, and vegetation community influenced the predictions most. The strong response of downy brome to interannual environmental variability makes detecting change challenging, especially with small sample sizes. However, our results suggest that the area in which downy brome occurs is likely increasing in Rocky Mountain National Park through increased frequency and cover. Field surveys along with predictive modeling will be vital in directing efforts to manage this highly invasive species. ?? Weed Science Society of America 2011.

Invasive Plant Science and Management↗

USGS2013

Multi-scale and nested-intensity sampling techniques for archaeological survey

This paper discusses sampling techniques for archaeological survey that are directed toward evaluating the properties of surface artifact distributions. The sampling techniques we experimented with consist of a multi-scale sampling plot developed in plant ecology and the use of a nested-intensity survey design. We present results from the initial application of these methods. The sampling technique we borrowed from plant ecology is the Modified-Whittaker multiscale sampling plot, which gathers observations at the spatial scales of 1 sq m, 10 sq m, 100 sq m, and 1000 sq m. Nested-intensity surveys gather observations on the same sample units at multiple resolutions. We compare the results of a closely-spaced walking survey, a crawling survey, and a test excavation to a depth of 10 cm. These techniques were applied to ten 20 × 50 m survey plots distributed over an area of 418 ha near the Hudson-Meng Bison Bonebed in NW Nebraska. These approaches can significantly improve the accuracy of survey data. Our results show that high-resolution coverage techniques overlook more material than archaeologists have suspected. The combined approaches of multi-scale and nested-intensity sampling provide new tools to improve our ability to investigate the properties of surface records.

Journal of Field Archaeology↗

USGS2011

Widespread plant species: natives vs. aliens in our changing world

Estimates of the level of invasion for a region are traditionally based on relative numbers of native and alien species. However, alien species differ dramatically in the size of their invasive ranges. Here we present the first study to quantify the level of invasion for several regions of the world in terms of the most widely distributed plant species (natives vs. aliens). Aliens accounted for 51.3% of the 120 most widely distributed plant species in North America, 43.3% in New South Wales (Australia), 34.2% in Chile, 29.7% in Argentina, and 22.5% in the Republic of South Africa. However, Europe had only 1% of alien species among the most widespread species of the flora. Across regions, alien species relative to native species were either as well-distributed (10 comparisons) or more widely distributed (5 comparisons). These striking patterns highlight the profound contribution that widespread invasive alien plants make to floristic dominance patterns across different regions. Many of the most widespread species are alien plants, and, in particular, Europe and Asia appear as major contributors to the homogenization of the floras in the Americas. We recommend that spatial extent of invasion should be explicitly incorporated in assessments of invasibility, globalization, and risk assessments.

Biological Invasions↗

USGS2010

Technical note assessing the accuracy of Landsat Thematic Mapper classification using double sampling

Double sampling was used to provide a cost efficient estimate of the accuracy of a Landsat Thematic Mapper (TM) classification map of a scene located in the Rocky Mountain National Park, Colorado. In the first phase, 200 sample points were randomly selected to assess the accuracy between Landsat TM data and aerial photography. The overall accuracy and Kappa statistic were 49.5 per cent and 32.5 per cent, respectively. In the second phase, 25 sample points identified in the first phase were selected using stratified random sampling and located in the field. This information was used to correct for misclassification errors associated with the first phase samples. The overall accuracy and Kappa statistic increased to 59.6 per cent and 45.6 per cent, respectively.

International Journal of Remote Sensing↗

USGS2010

Ensemble habitat mapping of invasive plant species

Ensemble species distribution models combine the strengths of several species environmental matching models, while minimizing the weakness of any one model. Ensemble models may be particularly useful in risk analysis of recently arrived, harmful invasive species because species may not yet have spread to all suitable habitats, leaving species-environment relationships difficult to determine. We tested five individual models (logistic regression, boosted regression trees, random forest, multivariate adaptive regression splines (MARS), and maximum entropy model or Maxent) and ensemble modeling for selected nonnative plant species in Yellowstone and Grand Teton National Parks, Wyoming; Sequoia and Kings Canyon National Parks, California, and areas of interior Alaska. The models are based on field data provided by the park staffs, combined with topographic, climatic, and vegetation predictors derived from satellite data. For the four invasive plant species tested, ensemble models were the only models that ranked in the top three models for both field validation and test data. Ensemble models may be more robust than individual species-environment matching models for risk analysis. ?? 2010 Society for Risk Analysis.

Risk Analysis↗

USGS2008

Effects of spatial heterogeneity on butterfly species richness in Rocky Mountain National Park, CO, USA

We investigated butterfly responses to plot-level characteristics (plant species richness, vegetation height, and range in NDVI [normalized difference vegetation index]) and spatial heterogeneity in topography and landscape patterns (composition and configuration) at multiple spatial scales. Stratified random sampling was used to collect data on butterfly species richness from seventy-six 20 ?? 50 m plots. The plant species richness and average vegetation height data were collected from 76 modified-Whittaker plots overlaid on 76 butterfly plots. Spatial heterogeneity around sample plots was quantified by measuring topographic variables and landscape metrics at eight spatial extents (radii of 300, 600 to 2,400 m). The number of butterfly species recorded was strongly positively correlated with plant species richness, proportion of shrubland and mean patch size of shrubland. Patterns in butterfly species richness were negatively correlated with other variables including mean patch size, average vegetation height, elevation, and range in NDVI. The best predictive model selected using Akaike's Information Criterion corrected for small sample size (AICc), explained 62% of the variation in butterfly species richness at the 2,100 m spatial extent. Average vegetation height and mean patch size were among the best predictors of butterfly species richness. The models that included plot-level information and topographic variables explained relatively less variation in butterfly species richness, and were improved significantly after including landscape metrics. Our results suggest that spatial heterogeneity greatly influences patterns in butterfly species richness, and that it should be explicitly considered in conservation and management actions. ?? 2008 Springer Science+Business Media B.V.

Biodiversity and Conservation↗

USGS2008

Potential habitat distribution for the freshwater diatom Didymosphenia geminata in the continental US

The diatom Didymosphenia geminata is a single-celled alga found in lakes, streams, and rivers. Nuisance blooms of D geminata affect the diversity, abundance, and productivity of other aquatic organisms. Because D geminata can be transported by humans on waders and other gear, accurate spatial prediction of habitat suitability is urgently needed for early detection and rapid response, as well as for evaluation of monitoring and control programs. We compared four modeling methods to predict D geminata's habitat distribution; two methods use presence-absence data (logistic regression and classification and regression tree [CART]), and two involve presence data (maximum entropy model [Maxent] and genetic algorithm for rule-set production [GARP]). Using these methods, we evaluated spatially explicit, bioclimatic and environmental variables as predictors of diatom distribution. The Maxent model provided the most accurate predictions, followed by logistic regression, CART, and GARP. The most suitable habitats were predicted to occur in the western US, in relatively cool sites, and at high elevations with a high base-flow index. The results provide insights into the factors that affect the distribution of D geminata and a spatial basis for the prediction of nuisance blooms. ?? The Ecological Society of America.

Frontiers in Ecology and the Environment↗

USGS2008

Non-native plant invasions of United States National parks

The United States National Park Service was created to protect and make accessible to the public the nation's most precious natural resources and cultural features for present and future generations. However, this heritage is threatened by the invasion of non-native plants, animals, and pathogens. To evaluate the scope of invasions, the USNPS has inventoried non-native plant species in the 216 parks that have significant natural resources, documenting the identity of non-native species. We investigated relationships among non-native plant species richness, the number of threatened and endangered plant species, native species richness, latitude, elevation, park area and park corridors and vectors. Parks with many threatened and endangered plants and high native plant species richness also had high non-native plant species richness. Non-native plant species richness was correlated with number of visitors and kilometers of backcountry trails and rivers. In addition, this work reveals patterns that can be further explored empirically to understand the underlying mechanisms. ?? Springer Science+Business Media B.V. 2008.

Biological Invasions↗

USGS2008

Effects of past logging and grazing on understory plant communities in a montane Colorado forest

Throughout Pinus ponderosa-Pseudotsuga menziesii forests of the southern Colorado Front Range, USA, intense logging and domestic grazing began at the time of Euro-American settlement in the late 1800s and continued until the early 1900s. We investigated the long-term impacts of these settlement-era activities on understory plant communities by comparing understory composition at a historically logged and grazed site to that of an environmentally similar site which was protected from past use. We found that species richness and cover within functional groups rarely differed between sites in either upland or riparian areas. Multivariate analyses revealed little difference in species composition between sites on uplands, though compositional differences were apparent in riparian zones. Our findings suggest that settlement-era logging and grazing have had only minor long-term impacts on understories of upland Front Range P. ponderosa-P. menziesii forests, though they have had a greater long-term influence on riparian understories, where these activities were likely the most intense. ?? 2008 Springer Science+Business Media B.V.

Plant Ecology↗

USGS2008

Near term climate projections for invasive species distributions

Climate change and invasive species pose important conservation issues separately, and should be examined together. We used existing long term climate datasets for the US to project potential climate change into the future at a finer spatial and temporal resolution than the climate change scenarios generally available. These fine scale projections, along with new species distribution modeling techniques to forecast the potential extent of invasive species, can provide useful information to aide conservation and invasive species management efforts. We created habitat suitability maps for Pueraria montana (kudzu) under current climatic conditions and potential average conditions up to 30 years in the future. We examined how the potential distribution of this species will be affected by changing climate, and the management implications associated with these changes. Our models indicated that P. montana may increase its distribution particularly in the Northeast with climate change and may decrease in other areas. ?? 2008 Springer Science+Business Media B.V.

Biological Invasions↗

USGS2008

Modelling invasion for a habitat generalist and a specialist plant species

Predicting suitable habitat and the potential distribution of invasive species is a high priority for resource managers and systems ecologists. Most models are designed to identify habitat characteristics that define the ecological niche of a species with little consideration to individual species' traits. We tested five commonly used modelling methods on two invasive plant species, the habitat generalist Bromus tectorum and habitat specialist Tamarix chinensis, to compare model performances, evaluate predictability, and relate results to distribution traits associated with each species. Most of the tested models performed similarly for each species; however, the generalist species proved to be more difficult to predict than the specialist species. The highest area under the receiver-operating characteristic curve values with independent validation data sets of B. tectorum and T. chinensis was 0.503 and 0.885, respectively. Similarly, a confusion matrix for B. tectorum had the highest overall accuracy of 55%, while the overall accuracy for T. chinensis was 85%. Models for the generalist species had varying performances, poor evaluations, and inconsistent results. This may be a result of a generalist's capability to persist in a wide range of environmental conditions that are not easily defined by the data, independent variables or model design. Models for the specialist species had consistently strong performances, high evaluations, and similar results among different model applications. This is likely a consequence of the specialist's requirement for explicit environmental resources and ecological barriers that are easily defined by predictive models. Although defining new invaders as generalist or specialist species can be challenging, model performances and evaluations may provide valuable information on a species' potential invasiveness.

Diversity and Distributions↗

USGS2007

Rapid plant diversity assessment using a pixel nested plot design: A case study in Beaver Meadows, Rocky Mountain National Park, Colorado, USA

Geospatial statistical modelling and thematic maps have recently emerged as effective tools for the management of natural areas at the landscape scale. Traditional methods for the collection of field data pertaining to questions of landscape were developed without consideration for the parameters of these applications. We introduce an alternative field sampling design based on smaller unbiased random plot and subplot locations called the pixel nested plot (PNP). We demonstrate the applicability of the PNP design of 15 m x 15 m to assess patterns of plant diversity and species richness across the landscape at Rocky Mountain National Park (RMNP), Colorado, USA in a time (cost)-efficient manner for field data collection. Our results produced comparable results to a previous study in the Beaver Meadow study (BMS) area within RMNP, where there was a demonstrated focus of plant diversity. Our study used the smaller PNP sampling design for field data collection which could be linked to geospatial information data and could be used for landscape-scale analyses and assessment applications. In 2003, we established 61 PNP in the eastern region of RMNP. We present a comparison between this approach using a sub-sample of 19 PNP from this data set and 20 of Modified Whittaker nested plots (MWNP) of 20 m x 50 m that were collected in the BMS area. The PNP captured 266 unique plant species while the MWNP captured 275 unique species. Based on a comparison of PNP and MWNP in the Beaver Meadows area, RMNP, the PNP required less time and area sampled to achieve a similar number of species sampled. Using the PNP approach for data collection can facilitate the ecological monitoring of these vulnerable areas at the landscape scale in a time- and therefore cost-effective manner. ?? 2007 The Authors.

Diversity and Distributions↗

USGS2007

Predicting yellow toadflax infestations in the Flat Tops Wilderness of Colorado

Understanding species-environment relationships is important to predict the spread of non-native species. Yellow toadflax (Linaria vulgaris Mill.) is an invasive perennial recently found in the Flat Tops Wilderness of the White River National Forest on the western slope of the Colorado Rocky Mountains. We hypothesized yellow toadflax occurrence could be predicted from easily measured site characteristics. We used logistic regression with stepwise selection to generate a model to predict yellow toadflax occurrence on a particular plot based on that site's physical characteristics. The experimental design was a paired-plot study in two locations using circular 1,018-m2 plots. Sixty-eight plots that did not contain yellow toadflax and 65 plots that contained yellow toadflax were sampled at the Ripple Creek site in 1999. In 2000, 54 non-toadflax plots and 55 toadflax-containing plots were sampled in the Marvine Creek site. Site characteristics sampled included: vegetation type; under-canopy light level; slope; aspect; soil properties; presence of disturbance, trails, and/or water; and total species richness. A model that correctly classified >90% of the 242 plots sampled included two vegetation type parameters, the presence of trails, and total species richness. Yellow toadflax is most often found in areas that were open-canopy sites, along trails, and with higher species diversity plots (>23 species). This approach can be used for other species in other areas to rapidly identify areas vulnerable to invasion. ?? 2007 Springer Science+Business Media, Inc.

Biological Invasions↗

USGS2007

Assessing exotic plant species invasions and associated soil characteristics: A case study in eastern Rocky Mountain National Park, Colorado, USA, using the pixel nested plot design

Rocky Mountain National Park (RMNP), Colorado, USA, contains a diversity of plant species. However, many exotic plant species have become established, potentially impacting the structure and function of native plant communities. Our goal was to quantify patterns of exotic plant species in relation to native plant species, soil characteristics, and other abiotic factors that may indicate or predict their establishment and success. Our research approach for field data collection was based on a field plot design called the pixel nested plot. The pixel nested plot provides a link to multi-phase and multi-scale spatial modeling-mapping techniques that can be used to estimate total species richness and patterns of plant diversity at finer landscape scales. Within the eastern region of RMNP, in an area of approximately 35,000 ha, we established a total of 60 pixel nested plots in 9 vegetation types. We used canonical correspondence analysis (CCA) and multiple linear regressions to quantify relationships between soil characteristics and native and exotic plant species richness and cover. We also used linear correlation, spatial autocorrelation and cross correlation statistics to test for the spatial patterns of variables of interest. CCA showed that exotic species were significantly (P < 0.05) associated with photosynthetically active radiation (r = 0.55), soil nitrogen (r = 0.58) and bare ground (r = -0.66). Pearson's correlation statistic showed significant linear relationships between exotic species, organic carbon, soil nitrogen, and bare ground. While spatial autocorrelations indicated that our 60 pixel nested plots were spatially independent, the cross correlation statistics indicated that exotic plant species were spatially associated with bare ground, in general, exotic plant species were most abundant in areas of high native species richness. This indicates that resource managers should focus on the protection of relatively rare native rich sites with little canopy cover, and fertile soils. Using the pixel nested plot approach for data collection can facilitate the ecological monitoring of these vulnerable areas at the landscape scale in a time- and cost-effective manner. ?? 2006 Elsevier B.V. All rights reserved.

Applied Soil Ecology↗

USGS2007

A global organism detection and monitoring system for non-native species

Harmful invasive non-native species are a significant threat to native species and ecosystems, and the costs associated with non-native species in the United States is estimated at over $120 Billion/year. While some local or regional databases exist for some taxonomic groups, there are no effective geographic databases designed to detect and monitor all species of non-native plants, animals, and pathogens. We developed a web-based solution called the Global Organism Detection and Monitoring (GODM) system to provide real-time data from a broad spectrum of users on the distribution and abundance of non-native species, including attributes of their habitats for predictive spatial modeling of current and potential distributions. The four major subsystems of GODM provide dynamic links between the organism data, web pages, spatial data, and modeling capabilities. The core survey database tables for recording invasive species survey data are organized into three categories: "Where, Who & When, and What." Organisms are identified with Taxonomic Serial Numbers from the Integrated Taxonomic Information System. To allow users to immediately see a map of their data combined with other user's data, a custom geographic information system (GIS) Internet solution was required. The GIS solution provides an unprecedented level of flexibility in database access, allowing users to display maps of invasive species distributions or abundances based on various criteria including taxonomic classification (i.e., phylum or division, order, class, family, genus, species, subspecies, and variety), a specific project, a range of dates, and a range of attributes (percent cover, age, height, sex, weight). This is a significant paradigm shift from "map servers" to true Internet-based GIS solutions. The remainder of the system was created with a mix of commercial products, open source software, and custom software. Custom GIS libraries were created where required for processing large datasets, accessing the operating system, and to use existing libraries in C++, R, and other languages to develop the tools to track harmful species in space and time. The GODM database and system are crucial for early detection and rapid containment of invasive species. ?? 2007 Elsevier B.V. All rights reserved.

Ecological Informatics↗

USGS2007

Species-area curves indicate the importance of habitats' contributions to regional biodiversity

We examined species-area curves, species composition and similarity (Jaccard's coefficients), and species richness in 17 vegetation types to develop a composite index of a vegetation type's contribution to regional species richness. We collected data from 1 to 1000 m2 scales in 147 nested plots in Rocky Mountain National Park, Colorado, USA to compare three species-area curve models' abilities to estimate the number of species observed in each vegetation type. The log(species)-log(area) curve had the largest adjusted coefficients of determination (r2 values) in 12 of the 17 types, followed by the species-log(area) curve with five of the highest values. When the slopes of the curves were corrected for species overlap among plots with Jaccard's coefficients, the species-log(area) curves estimated values closest to those observed. We combined information from species-area curves and measures of heterogeneity with information on the area covered by each vegetation type and found that the types making the greatest contributions to regional biodiversity covered the smallest areas. This approach may provide an accurate and relatively rapid way to rank hotspots of plant diversity within regions of interest.

Colorado↗

USGS2007

Rapid assessment of postfire plant invasions in coniferous forests of the western United States

Fire is a natural part of most forest ecosystems in the western United States, but its effects on nonnative plant invasion have only recently been studied. Also, forest managers are engaging in fuel reduction projects to lessen fire severity, often without considering potential negative ecological consequences such as nonnative plant species introductions. Increased availability of light, nutrients, and bare ground have all been associated with high-severity fires and fuel treatments and are known to aid in the establishment of nonnative plant species. We use vegetation and environmental data collected after wildfires at seven sites in coniferous forests in the western United States to study responses of nonnative plants to wildfire. We compared burned vs. unburned plots and plots treated with mechanical thinning and/or prescribed burning vs. untreated plots for nonnative plant species richness and cover and used correlation analyses to infer the effect of abiotic site conditions on invasibility. Wildfire was responsible for significant increases in nonnative species richness and cover, and a significant decrease in native cover. Mechanical thinning and prescribed fire fuel treatments were associated with significant changes in plant species composition at some sites. Treatment effects across sites were minimal and inconclusive due to significant site and site x treatment interaction effects caused by variation between sites including differences in treatment and fire severities and initial conditions (e.g., nonnative species sources). We used canonical correspondence analysis (CCA) to determine what combinations of environmental variables best explained patterns of nonnative plant species richness and cover. Variables related to fire severity, soil nutrients, and elevation explained most of the variation in species composition. Nonnative species were generally associated with sites with higher fire severity, elevation, percentage of bare ground, and lower soil nutrient levels and lower canopy cover. Early assessments of postfire stand conditions can guide rapid responses to nonnative plant invasions. ?? 2007 by the Ecological Society of America.

Western United States↗

USGS2007

Modeling aboveground biomass of Tamarix ramosissima in the Arkansas River Basin of Southeastern Colorado, USA

Predictive models of aboveground biomass of nonnative Tamarix ramosissima of various sizes were developed using destructive sampling techniques on 50 individuals and four 100-m2 plots. Each sample was measured for average height (m) of stems and canopy area (m2) prior to cutting, drying, and weighing. Five competing regression models (P < 0.05) were developed to estimate aboveground biomass of T. ramosissima using average height and/or canopy area measurements and were evaluated using Akaike's Information Criterion corrected for small sample size (AICc). Our best model (AICc = -148.69, ??AICc = 0) successfully predicted T. ramosissima aboveground biomass (R2 = 0.97) and used average height and canopy area as predictors. Our 2nd-best model, using the same predictors, was also successful in predicting aboveground biomass (R2 = 0.97, AICc = -131.71, ??AICc = 16.98). A 3rd model demonstrated high correlation between only aboveground biomass and canopy area (R2 = 0.95), while 2 additional models found high correlations between aboveground biomass and average height measurements only (R2 = 0.90 and 0.70, respectively). These models illustrate how simple field measurements, such as height and canopy area, can be used in allometric relationships to accurately predict aboveground biomass of T. ramosissima. Although a correction factor may be necessary for predictions at larger scales, the models presented will prove useful for many research and management initiatives.

Western North American Naturalist↗