Geology topics

Thomas P. Albright

Publications and source records attributed to Thomas P. Albright.

6 recordsLinked to original sources

USGS2016

Evaluation of downscaled, gridded climate data for the conterminous United States

Weather and climate affect many ecological processes, making spatially continuous yet fine-resolution weather data desirable for ecological research and predictions. Numerous downscaled weather data sets exist, but little attempt has been made to evaluate them systematically. Here we address this shortcoming by focusing on four major questions: (1) How accurate are downscaled, gridded climate data sets in terms of temperature and precipitation estimates?, (2) Are there significant regional differences in accuracy among data sets?, (3) How accurate are their mean values compared with extremes?, and (4) Does their accuracy depend on spatial resolution? We compared eight widely used downscaled data sets that provide gridded daily weather data for recent decades across the United States. We found considerable differences among data sets and between downscaled and weather station data. Temperature is represented more accurately than precipitation, and climate averages are more accurate than weather extremes. The data set exhibiting the best agreement with station data varies among ecoregions. Surprisingly, the accuracy of the data sets does not depend on spatial resolution. Although some inherent differences among data sets and weather station data are to be expected, our findings highlight how much different interpolation methods affect downscaled weather data, even for local comparisons with nearby weather stations located inside a grid cell. More broadly, our results highlight the need for careful consideration among different available data sets in terms of which variables they describe best, where they perform best, and their resolution, when selecting a downscaled weather data set for a given ecological application.

Ecological Applications↗

USGS2011

Natural and human dimensions of a quasi-wild species: The case of kudzu

The human dimensions of biotic invasion are generally poorly understood, even among the most familiar invasive species. Kudzu ( Pueraria montana (Lour.) Merr.) is a prominent invasive plant and an example of quasi-wild species, which has experienced repeated introduction, cultivation, and escape back to the wild. Here, we review a large body of primary scientific and historic records spanning thousands of years to characterize the complex relationships among kudzu, its natural enemies, and humans, and provide a synthesis and conceptual model relevant to the ecology and management of quasi-wild invasive species. We documented over 350, mostly insect, natural enemy species and their impacts on kudzu in its native East Asian range. These natural enemies play a minor role in limiting kudzu in its native range, rarely generating severe impacts on populations of wild kudzu. We identified a number of significant influences of humans including dispersal, diverse cultural selection, and facilitation through disturbances, which catalyzed the expansion and exuberance of kudzu. On the other hand, harvest by humans appears to be the major control mechanism in its native areas. Humans thus have a complex relationship with kudzu. They have acted as both friend and foe, affecting the distribution and abundance of kudzu in ways that vary across its range and over time. Our conceptual model of kudzu emphasizes the importance of multiple human dimensions in shaping the biogeography of a species and illustrates how kudzu and other quasi-wild species are more likely to be successful invaders.

Biological Invasions↗

USGS2010

Monitoring the dynamics of an invasive emergent macrophyte community using operational remote sensing data

Potamogeton crispus L. (curly pondweed) is a cosmopolitan aquatic macrophyte considered invasive in North America and elsewhere. Its range is expanding and, on individual water bodies, its coverage can be dynamic both within and among years. In this study, we evaluate the use of free and low-cost satellite remote sensing data to monitor a problematic emergent macrophyte community dominated by P. crispus . Between 2000 and 2006, we acquired eight satellite images of 24,000-ha Lake Sharpe, South Dakota (USA). During one of the dates for which satellite imagery was acquired, we sampled the lake for P. crispus and other emergent macrophytes using GPS and photography for documentation. We used cluster analysis to assist in classification of the satellite imagery and independently validated results using the field data. Resulting estimates of emergent macrophyte coverage ranged from less than 20 ha in 2002 to 245 ha in 2004. Accuracy assessment indicated 82% of image pixels were correctly classified, with errors being primarily due to failure to identify emergent macrophytes. These results emphasize the dynamic nature of P. crispus -dominated macrophyte communities and show how they can be effectively monitored over large areas using low-cost remote sensing imagery. While results may vary in other systems depending on water quality and local flora, such an approach could be applied elsewhere and for a variety of macrophyte communities.

Hydrobiologia↗

USGS2007

Predicting the potential distribution of invasive exotic species using GIS and information-theoretic approaches: A case of ragweed (Ambrosia artemisiifolia L.) distribution in China

Invasive exotic species pose a growing threat to the economy, public health, and ecological integrity of nations worldwide. Explaining and predicting the spatial distribution of invasive exotic species is of great importance to prevention and early warning efforts. We are investigating the potential distribution of invasive exotic species, the environmental factors that influence these distributions, and the ability to predict them using statistical and information-theoretic approaches. For some species, detailed presence/absence occurrence data are available, allowing the use of a variety of standard statistical techniques. However, for most species, absence data are not available. Presented with the challenge of developing a model based on presence-only information, we developed an improved logistic regression approach using Information Theory and Frequency Statistics to produce a relative suitability map. This paper generated a variety of distributions of ragweed (Ambrosia artemisiifolia L.) from logistic regression models applied to herbarium specimen location data and a suite of GIS layers including climatic, topographic, and land cover information. Our logistic regression model was based on Akaike's Information Criterion (AIC) from a suite of ecologically reasonable predictor variables. Based on the results we provided a new Frequency Statistical method to compartmentalize habitat-suitability in the native range. Finally, we used the model and the compartmentalized criterion developed in native ranges to "project" a potential distribution onto the exotic ranges to build habitat-suitability maps. ?? Science in China Press 2007.

Chinese Science Bulletin↗

USGS2004

The rise and fall of water hyacinth in Lake Victoria and the Kagera River basin, 1989-2001

Water hyacinth (Eichhornia crassipes (Mart.) Solms) is an invasive aquatic macrophyte associated with major negative economic and ecological impacts to the Lake Victoria region since the plant's establishment in Uganda in the 1980s. Reliable estimates of water hyacinth distribution and extent are required to gauge the severity of the problem through time, relate water hyacinth abundance to environmental factors, identify areas requiring management action, and assess the efficacy of management actions. To provide such estimates and demonstrate the utility of remote sensing for this application, we processed and analyzed remotely sensed imagery to determine the distribution and extent of water hyacinth. Maps were produced and coverage was quantified using a hybrid unsupervised image classification approach with manual editing for each of the riparian countries of Kenya, Tanzania, and Uganda, as well as for numerous gulfs and bays. A similar procedure was carried out for selected lakes in the Rwanda-Tanzania borderlands lakes region in the Kagera River basin. Results confirm the severity of the water hyacinth infestation, especially in the northern parts of the lake. A maximum lake-wide extent of at least 17,374 ha was attained in 1998. Following this, a combination of factors, including conditions associated with the 1997 to 1998 El Nin??o and biocontrol with water hyacinth weevils, appear to have contributed to a major decline in water hyacinth in the most affected parts of the lake. Some lakes in the Kagera basin, such as Lake Mihindi, Rwanda, were severely infested in the late 1990s, but the level of infestation in most of these decreased markedly by the early 2000s.

Journal of Aquatic Plant Management↗

USGS1998

Classification of surface types using SIR-C/X-SAR, Mount Everest Area, Tibet

Imaging radar is a promising tool for mapping snow and ice cover in alpine regions. It combines a high-resolution, day or night, all-weather imaging capability with sensitivity to hydrologic and climatic snow and ice parameters. We use the spaceborne imaging radar-C/X-band synthetic aperture radar (SIR-C/X-SAR) to map snow and glacial ice on the rugged north slope of Mount Everest. From interferometrically derived digital elevation data, we compute the terrain calibration factor and cosine of the local illumination angle. We then process and terrain-correct radar data sets acquired on April 16, 1994. In addition to the spectral data, we include surface slope to improve discrimination among several surface types. These data sets are then used in a decision tree to generate an image classification. This method is successful in identifying and mapping scree/talus, dry snow, dry snow-covered glacier, wet snow-covered glacier, and rock-covered glacier, as corroborated by comparison with existing surface cover maps and other ancillary information. Application of the classification scheme to data acquired on October 7 of the same year yields accurate results for most surface types but underreports the extent of dry snow cover.

Journal of Geophysical Research E: Planets↗