The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Gordon B. Stenhouse - One of the best experts on this subject based on the ideXlab platform.
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grizzly bear response to fine spatial and Temporal Scale spring snow cover in western alberta
PLOS ONE, 2019Co-Authors: Ethan E Berman, Nicholas C Coops, Sean P Kearney, Gordon B. StenhouseAbstract:Snow dynamics influence seasonal behaviors of wildlife, such as denning patterns and habitat selection related to the availability of food resources. Under a changing climate, characteristics of the Temporal and spatial patterns of snow are predicted to change, and as a result, there is a need to better understand how species interact with snow dynamics. This study examines grizzly bear (Ursus arctos) spring habitat selection and use across western Alberta, Canada. Made possible by newly available fine-Scale snow cover data, this research tests a hypothesis that grizzly bears select for locations with less snow cover and areas where snow melts sooner during spring (den emergence to May 31st). Using Integrated Step Selection Analysis, a series of models were built to examine whether snow cover information such as fractional snow covered area and date of snow melt improved models constructed based on previous knowledge of grizzly bear selection during the spring. Comparing four different models fit to 62 individual bear-years, we found that the inclusion of fractional snow covered area improved model fit 60% of the time based on Akaike Information Criterion tallies. Probability of use was then used to evaluate grizzly bear habitat use in response to snow and environmental attributes, including fractional snow covered area, date since snow melt, elevation, and distance to road. Results indicate grizzly bears select for lower elevation, snow-free locations during spring, which has important implications for management of threatened grizzly bear populations in consideration of changing climatic conditions. This study is an example of how fine spatial and Temporal Scale remote sensing data can be used to improve our understanding of wildlife habitat selection and use in relation to key environmental attributes.
Casey J Wichman - One of the best experts on this subject based on the ideXlab platform.
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bicycle infrastructure and traffic congestion evidence from dc s capital bikeshare
Journal of Environmental Economics and Management, 2018Co-Authors: Timothy L Hamilton, Casey J WichmanAbstract:Abstract This study explores the impact of bicycle-sharing infrastructure on urban transportation. We estimate a causal effect of the Capital Bikeshare on traffic congestion in the metropolitan Washington, D.C., area. We exploit a unique traffic dataset that is finely defined on a spatial and Temporal Scale. Our approach examines within-city commuting decisions as opposed to traffic patterns on major thruways. Empirical results suggest that the availability of a bikeshare reduces traffic congestion upwards of 4% within a neighborhood. In addition, we estimate heterogeneous treatment effects using panel quantile regression. Results indicate that the congestion-reducing impact of bikeshares is concentrated in highly congested areas.
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bicycle infrastructure and traffic congestion evidence from dc s capital bikeshare
2015Co-Authors: Timothy L Hamilton, Casey J WichmanAbstract:We explore the impact of bicycle-sharing infrastructure on urban transportation. Accounting for selection bias in a matching framework, we estimate a causal effect of the Capital Bikeshare on traffic congestion in the metropolitan Washington, DC, area. We exploit a unique traffic dataset that is finely defined on a spatial and Temporal Scale. Our approach examines within-city commuting decisions as opposed to traffic patterns on major thruways. Empirical results suggest that the availability of a bikeshare reduces traffic congestion by 2 to 3% within a neighborhood. We also identify geographic spillovers that may counteract benefits from reductions in local pollution.
Ethan E Berman - One of the best experts on this subject based on the ideXlab platform.
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grizzly bear response to fine spatial and Temporal Scale spring snow cover in western alberta
PLOS ONE, 2019Co-Authors: Ethan E Berman, Nicholas C Coops, Sean P Kearney, Gordon B. StenhouseAbstract:Snow dynamics influence seasonal behaviors of wildlife, such as denning patterns and habitat selection related to the availability of food resources. Under a changing climate, characteristics of the Temporal and spatial patterns of snow are predicted to change, and as a result, there is a need to better understand how species interact with snow dynamics. This study examines grizzly bear (Ursus arctos) spring habitat selection and use across western Alberta, Canada. Made possible by newly available fine-Scale snow cover data, this research tests a hypothesis that grizzly bears select for locations with less snow cover and areas where snow melts sooner during spring (den emergence to May 31st). Using Integrated Step Selection Analysis, a series of models were built to examine whether snow cover information such as fractional snow covered area and date of snow melt improved models constructed based on previous knowledge of grizzly bear selection during the spring. Comparing four different models fit to 62 individual bear-years, we found that the inclusion of fractional snow covered area improved model fit 60% of the time based on Akaike Information Criterion tallies. Probability of use was then used to evaluate grizzly bear habitat use in response to snow and environmental attributes, including fractional snow covered area, date since snow melt, elevation, and distance to road. Results indicate grizzly bears select for lower elevation, snow-free locations during spring, which has important implications for management of threatened grizzly bear populations in consideration of changing climatic conditions. This study is an example of how fine spatial and Temporal Scale remote sensing data can be used to improve our understanding of wildlife habitat selection and use in relation to key environmental attributes.
Eugene Mccann - One of the best experts on this subject based on the ideXlab platform.
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framing space and time in the city urban policy and the politics of spatial and Temporal Scale
Journal of Urban Affairs, 2003Co-Authors: Eugene MccannAbstract:This article seeks to analyze urban politics through the lens of the social constructionist approach to Scale. This approach views Scale not as a set of pre-given, natural, and immutable levels upo...
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framing space and time in the city urban policy and the politics of spatial and Temporal Scale
Journal of Urban Affairs, 2003Co-Authors: Eugene MccannAbstract:ABSTRACT:This article seeks to analyze urban politics through the lens of the social constructionist approach to Scale. This approach views Scale not as a set of pre-given, natural, and immutable l...
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Framing Space and Time in the City: Urban Policy and the Politics of Spatial and Temporal Scale
Journal of Urban Affairs, 2003Co-Authors: Eugene MccannAbstract:Abstract: This article seeks to analyze urban politics through the lens of the social constructionist approach to Scale. This approach views Scale not as a set of pre-given, natural, and immutable levels upon which social life occurs. Rather, it regards Scale as a fluid context for and product of power relations in society. The article argues that urban politics is frequently characterized by political strategies that frame reality in terms of Scale. Agents of the state, capital, and civil society all engage in the politics around competing scalar framings. As a result, the politics of Scale has important but contingent material consequences. The article illustrates these points through a case study of the politics that surrounded the development of a new neighborhood planning initiative in Austin, Texas in the late 1990s. Based on this case study, the article also argues that while geographers studying the politics of Scale tend to explain it solely in terms of spatial Scale, scalar politics in the urban context frequently combines framings of spatial and Temporal Scale. This simultaneous framing of space and time in the city has important, if sometimes unpredictable, implications for policy and politics.
Sean P Kearney - One of the best experts on this subject based on the ideXlab platform.
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grizzly bear response to fine spatial and Temporal Scale spring snow cover in western alberta
PLOS ONE, 2019Co-Authors: Ethan E Berman, Nicholas C Coops, Sean P Kearney, Gordon B. StenhouseAbstract:Snow dynamics influence seasonal behaviors of wildlife, such as denning patterns and habitat selection related to the availability of food resources. Under a changing climate, characteristics of the Temporal and spatial patterns of snow are predicted to change, and as a result, there is a need to better understand how species interact with snow dynamics. This study examines grizzly bear (Ursus arctos) spring habitat selection and use across western Alberta, Canada. Made possible by newly available fine-Scale snow cover data, this research tests a hypothesis that grizzly bears select for locations with less snow cover and areas where snow melts sooner during spring (den emergence to May 31st). Using Integrated Step Selection Analysis, a series of models were built to examine whether snow cover information such as fractional snow covered area and date of snow melt improved models constructed based on previous knowledge of grizzly bear selection during the spring. Comparing four different models fit to 62 individual bear-years, we found that the inclusion of fractional snow covered area improved model fit 60% of the time based on Akaike Information Criterion tallies. Probability of use was then used to evaluate grizzly bear habitat use in response to snow and environmental attributes, including fractional snow covered area, date since snow melt, elevation, and distance to road. Results indicate grizzly bears select for lower elevation, snow-free locations during spring, which has important implications for management of threatened grizzly bear populations in consideration of changing climatic conditions. This study is an example of how fine spatial and Temporal Scale remote sensing data can be used to improve our understanding of wildlife habitat selection and use in relation to key environmental attributes.
