Michael S. O'Donnell
United States Geological Survey
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Publication
Featured researches published by Michael S. O'Donnell.
Ecology and Evolution | 2015
Jeffrey R. Row; Sara J. Oyler-McCance; Jennifer A. Fike; Michael S. O'Donnell; Kevin E. Doherty; Cameron L. Aldridge; Zachary H. Bowen; Bradley C. Fedy
Given the significance of animal dispersal to population dynamics and geographic variability, understanding how dispersal is impacted by landscape patterns has major ecological and conservation importance. Speaking to the importance of dispersal, the use of linear mixed models to compare genetic differentiation with pairwise resistance derived from landscape resistance surfaces has presented new opportunities to disentangle the menagerie of factors behind effective dispersal across a given landscape. Here, we combine these approaches with novel resistance surface parameterization to determine how the distribution of high- and low-quality seasonal habitat and individual landscape components shape patterns of gene flow for the greater sage-grouse (Centrocercus urophasianus) across Wyoming. We found that pairwise resistance derived from the distribution of low-quality nesting and winter, but not summer, seasonal habitat had the strongest correlation with genetic differentiation. Although the patterns were not as strong as with habitat distribution, multivariate models with sagebrush cover and landscape ruggedness or forest cover and ruggedness similarly had a much stronger fit with genetic differentiation than an undifferentiated landscape. In most cases, landscape resistance surfaces transformed with 17.33-km-diameter moving windows were preferred, suggesting small-scale differences in habitat were unimportant at this large spatial extent. Despite the emergence of these overall patterns, there were differences in the selection of top models depending on the model selection criteria, suggesting research into the most appropriate criteria for landscape genetics is required. Overall, our results highlight the importance of differences in seasonal habitat preferences to patterns of gene flow and suggest the combination of habitat suitability modeling and linear mixed models with our resistance parameterization is a powerful approach to discerning the effects of landscape on gene flow.
Rangeland Ecology & Management | 2014
Daniel J. Manier; Cameron L. Aldridge; Michael S. O'Donnell; Spencer Schell
Abstract Although human influence across rural landscapes is often discussed, interactions between the native, natural systems and human activities are challenging to measure explicitly. We assessed the distribution of introduced, invasive species as related to anthropogenic infrastructure and environmental conditions across southwestern Wyoming. to discern direct correlations as well as covariate influences between land use, land cover, and abundance of invasive plants, and assess the supposition that these features affect surrounding rangeland conditions. Our sample units were 1 000 m long and extended outward from target features, which included roads, oil and gas well pads, pipelines, power lines, and featureless background sites. Sample sites were distributed across the region using a stratified, random design with a frame that represented features and land-use intensity. In addition to land-use gradients, we captured a representative, but limited, range of variability in climate, soils, geology, topography, and dominant vegetation. Several of these variables proved significant, in conjunction with distance from anthropogenic features, in regression models of invasive plant abundance. We used general linear models to demonstrate and compare associations between invasive plant frequency and Euclidian distance from features, natural logarithm transformed distances (log-linear), and environmental variables which were presented as potential covariates. We expected a steep curvilinear (log or exponential) decline trending towards an asymptote along the axis representing high abundance near features with rapid decrease beyond approximately 50–100 m. Some of the associations we document exhibit this pattern, but we also found some invasive plant distributions that extended beyond our expectations, suggesting a broader distribution than anticipated. Our results provide details that can inform local efforts for management and control of invasive species, and they provide evidence of the different associations between natural patterns and human land use exhibited by nonnative species in this rural setting, such as the indirect effects of humans beyond impact areas.
Journal of Map and Geography Libraries | 2014
Michael S. O'Donnell; Timothy J. Assal; Patrick J. Anderson; Zachary H. Bowen
Geospatial data play an increasingly important role in natural resources management, conservation, and science-based projects. The management and effective use of spatial data becomes significantly more complex when the efforts involve a myriad of landscape-scale projects combined with a multiorganizational collaboration. There is sparse literature to guide users on this daunting subject; therefore, we present a framework of considerations for working with geospatial data that will provide direction to data stewards, scientists, collaborators, and managers for developing geospatial management plans. The concepts we present apply to a variety of geospatial programs or projects, which we describe as a “scalable framework” of processes for integrating geospatial efforts with management, science, and conservation initiatives. Our framework includes five tenets of geospatial data management: (1) the importance of investing in data management and standardization, (2) the scalability of content/efforts addressed in geospatial management plans, (3) the lifecycle of a geospatial effort, (4) a framework for the integration of geographic information systems (GIS) in a landscape-scale conservation or management program, and (5) the major geospatial considerations prior to data acquisition. We conclude with a discussion of future considerations and challenges.
Scientific Investigations Report | 2018
Daniel J. Manier; Michael S. O'Donnell
Land-use planning has an important role in local, regional, State, and Federal land management, and planning efforts can benefit from consistent, spatially explicit information that can help guide priorities and decisions. The credibility and relevance of information used to inform planning activities depends on the availability of consistent information about the resources and values of interest or concern within the planning area. To support long-range transportation planning and other regional land-use planning efforts, the U.S. Geological Survey gathered, processed, interpreted, and compiled spatial datasets representing a wide range of information on terrestrial and aquatic ecosystem condition and importance, cultural (historical) features and places, and natural hazards. This report describes the spatial data compiled to represent natural landscape conditions (including social, cultural, and natural attributes) to estimate the potential importance of lands for wildlife, wild habitats, recreation, and conservation based on abundance of species, habitats, land and water conditions, and conservation designations. Abundance of resources, including the potential number of species, presence of important habitats and protected areas, and proximity to particular features or habitats, indicates the potential sensitivity of the natural landscape to land use, especially transportation networks. The source data, derived indices, and the methods for processing these data are described in this final report. The datasets referenced in the report are available from the U.S. Geological Survey (https://www.sciencebase.gov/catalog/ and https://doi.org/10.5066/F7MW2F8W) or the Central Federal Lands Highway Division of the Office of Federal Lands Highway (https://flh.fhwa.dot.gov).
Wildlife Monographs | 2014
Bradley C. Fedy; Kevin E. Doherty; Cameron L. Aldridge; Michael S. O'Donnell; Jeffrey L. Beck; Bryan Bedrosian; David L. Gummer; Matthew J. Holloran; Gregory D. Johnson; Nicholas W. Kaczor; Christopher P. Kirol; Cheryl A. Mandich; David Marshall; Gwyn McKee; Chad Olson; Aaron C. Pratt; Christopher C. Swanson; Brett L. Walker
Journal of Wildlife Management | 2017
Adam W. Green; Cameron L. Aldridge; Michael S. O'Donnell
Data Series | 2014
Michael S. O'Donnell; Tammy Fancher; Aaron T. Freeman; Abra E. Ziegler; Zachary H. Bowen; Cameron L. Aldridge
Studies in avian biology | 2011
Sara J. Oyler-McCance; Craig A. Stricker; Clait E. Braun; Gregory T. Wann; Michael S. O'Donnell; Cameron L. Aldridge
Natural Resources and Environmental Issues | 2011
Daniel J. Manier; Cameron L. Aldridge; Patrick J. Anderson; Geneva W. Chong; Collin G. Homer; Michael S. O'Donnell; Spencer Schell
Scientific Investigations Report | 2012
Stephen S. Germaine; Michael S. O'Donnell; Cameron L. Aldridge; Lori Baer; Tammy Fancher; Jamie L. McBeth; Robert R. McDougal; Robert G. Waltermire; Zachary H. Bowen; James Diffendorfer; Steven L. Garman