Reproducibility of a Geographical Study on the Effects of Wind Turbines on Bat Fatalities in the Northeast United States. Tango, M. Ph.D. Thesis, Middlebury College, Middlebury, 2021. ![Reproducibility of a Geographical Study on the Effects of Wind Turbines on Bat Fatalities in the Northeast United States [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex With the expansion of wind energy as an alternative to fossil fuel use, it is important that we have the tools necessary to analyze ecological impacts. While geographic information systems (GIS) have many tools for this analysis, the lack of reproducibility in the field will lead to both decreased accuracy of results and slow down knowledge gain during a time in which research speed could prevent extinctions. In this integrative geography and biology thesis, I study the reproducibility of a geographical analysis to better understand barriers to its reproduction. The study, conducted by consulting group DNV GL for the Wind Wildlife Research Fund, analyzes the relationship between tree-roosting bat fatalities and landscape features at onshore wind farms in the northeast United States (Peters et al. 2020). I improve its future reproducibility by analyzing the ways in which both the bat fatality studies used to provide data for the Peters et al. (2020) study and the study itself could have been reported better for clarity and transparency with regards to methods, data, and sources of uncertainty. I also improve its future reproducibility by creating models and R scripts that reproduce the methods of this study to the fullest degree reasonably possible. The models and R scripts can be applied at various spatial scales to calculate landscape metrics (i.e., connectivity, percent area of land cover type, forest core area, etc.) and determine which are most correlated with hoary bat, eastern red bat, and silver-haired bat fatalities in a particular region. Methods, models, and R scripts are publicly available and could be applied to other species and land cover type contexts. 3
@phdthesis{tango_reproducibility_2021,
address = {Middlebury},
type = {{BA} {Thesis}},
title = {Reproducibility of a {Geographical} {Study} on the {Effects} of {Wind} {Turbines} on {Bat} {Fatalities} in the {Northeast} {United} {States}},
url = {https://middlebury.figshare.com/articles/thesis/Reproducibility_of_a_Geographical_Study_on_the_Effects_of_Wind_Turbines_on_Bat_Fatalities_in_the_Northeast_United_States/21565893},
abstract = {With the expansion of wind energy as an alternative to fossil fuel use, it is important that we have the tools necessary to analyze ecological impacts. While geographic information systems (GIS) have many tools for this analysis, the lack of reproducibility in the field will lead to both decreased accuracy of results and slow down knowledge gain during a time in which research speed could prevent extinctions. In this integrative geography and biology thesis, I study the reproducibility of a geographical analysis to better understand barriers to its reproduction. The study, conducted by consulting group DNV GL for the Wind Wildlife Research Fund, analyzes the relationship between tree-roosting bat fatalities and landscape features at onshore wind farms in the northeast United States (Peters et al. 2020). I improve its future reproducibility by analyzing the ways in which both the bat fatality studies used to provide data for the Peters et al. (2020) study and the study itself could have been reported better for clarity and transparency with regards to methods, data, and sources of uncertainty. I also improve its future reproducibility by creating models and R scripts that reproduce the methods of this study to the fullest degree reasonably possible. The models and R scripts can be applied at various spatial scales to calculate landscape metrics (i.e., connectivity, percent area of land cover type, forest core area, etc.) and determine which are most correlated with hoary bat, eastern red bat, and silver-haired bat fatalities in a particular region. Methods, models, and R scripts are publicly available and could be applied to other species and land cover type contexts. 3},
school = {Middlebury College},
author = {Tango, Maddie},
year = {2021},
keywords = {NALCMS},
}
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While geographic information systems (GIS) have many tools for this analysis, the lack of reproducibility in the field will lead to both decreased accuracy of results and slow down knowledge gain during a time in which research speed could prevent extinctions. In this integrative geography and biology thesis, I study the reproducibility of a geographical analysis to better understand barriers to its reproduction. The study, conducted by consulting group DNV GL for the Wind Wildlife Research Fund, analyzes the relationship between tree-roosting bat fatalities and landscape features at onshore wind farms in the northeast United States (Peters et al. 2020). I improve its future reproducibility by analyzing the ways in which both the bat fatality studies used to provide data for the Peters et al. (2020) study and the study itself could have been reported better for clarity and transparency with regards to methods, data, and sources of uncertainty. I also improve its future reproducibility by creating models and R scripts that reproduce the methods of this study to the fullest degree reasonably possible. The models and R scripts can be applied at various spatial scales to calculate landscape metrics (i.e., connectivity, percent area of land cover type, forest core area, etc.) and determine which are most correlated with hoary bat, eastern red bat, and silver-haired bat fatalities in a particular region. 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