Assessing the Influence of Landscape Characteristics on Bat Fatalities at South Texas Wind Energy Facilities. Kimes, H. Ph.D. Thesis, December, 2022. ![Assessing the Influence of Landscape Characteristics on Bat Fatalities at South Texas Wind Energy Facilities [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper abstract bibtex Although wind energy is a viable renewable energy source, strikes by wind turbine blades unintentionally cause bat fatalities. Previous research has suggested siting of wind energy facilities, and turbine placement within facilities, influence the number of bat fatalities; however, there is a knowledge gap regarding the reasons for the variability. This study occurred in Texas, the leading producer of wind energy and home to the greatest diversity and largest colonies of bats in the United States. The objective of my thesis was to assess the influence of landscape characteristics surrounding wind energy facilities and around specific turbines on the number of bat fatalities. I systematically searched 200 wind turbines and collected 1,067 bat carcasses at Hidalgo and Los Vientos Wind Energy Facilities from 2017–2018; I found Tadarida brasiliensis (n = 577), Lasiurus intermedius (n = 203), L. ega (n = 69), Nycticeius humeralis (n = 51), L. xanthinus (n = 30), L. cinereus (n = 18), L. blossevilli (n = 2) Myotis velifer (n = 2), Nyctinomops macrotis (n = 1), Perimyotis subflavus (n = 1), and unknown spp. (n = 113). I used Fragstats and ArcGIS Pro to acquire landscape metrics at the two facilities and among the 100 wind turbines at each facility at multiple scales (100 m, 500 m, 1 km, 5 km, and 25 km). Landscape characteristics included landcover types such as barren, crops, herbaceous, developed, shrub/scrub, hay/pasture, forest, wetlands, and open water, proximity to water sources, elevation and degree of slope. Using generalized linear models, zero-inflated and negative binomial models, and AIC model selection, results indicate that landscape characteristics at the broadest scale (5 km and 25 km) examined were most strongly associated with estimated bat fatality rates. I suggest wind farms should be constructed in areas that consist of uniform and connected habitat throughout the facility, without the presence of fragmented water sources. Managers should also implement mitigation efforts and pre/post-construction assessments to potentially reduce bat fatalities.
@phdthesis{kimes_assessing_2022,
title = {Assessing the {Influence} of {Landscape} {Characteristics} on {Bat} {Fatalities} at {South} {Texas} {Wind} {Energy} {Facilities}},
url = {https://digital.library.txstate.edu/handle/10877/16360},
abstract = {Although wind energy is a viable renewable energy source, strikes by wind
turbine blades unintentionally cause bat fatalities. Previous research has suggested siting
of wind energy facilities, and turbine placement within facilities, influence the number of
bat fatalities; however, there is a knowledge gap regarding the reasons for the variability.
This study occurred in Texas, the leading producer of wind energy and home to the
greatest diversity and largest colonies of bats in the United States. The objective of my
thesis was to assess the influence of landscape characteristics surrounding wind energy
facilities and around specific turbines on the number of bat fatalities. I systematically
searched 200 wind turbines and collected 1,067 bat carcasses at Hidalgo and Los Vientos
Wind Energy Facilities from 2017–2018; I found Tadarida brasiliensis (n = 577),
Lasiurus intermedius (n = 203), L. ega (n = 69), Nycticeius humeralis (n = 51), L.
xanthinus (n = 30), L. cinereus (n = 18), L. blossevilli (n = 2) Myotis velifer (n = 2),
Nyctinomops macrotis (n = 1), Perimyotis subflavus (n = 1), and unknown spp. (n = 113).
I used Fragstats and ArcGIS Pro to acquire landscape metrics at the two facilities and
among the 100 wind turbines at each facility at multiple scales (100 m, 500 m, 1 km, 5
km, and 25 km). Landscape characteristics included landcover types such as barren,
crops, herbaceous, developed, shrub/scrub, hay/pasture, forest, wetlands, and open water,
proximity to water sources, elevation and degree of slope. Using generalized linear
models, zero-inflated and negative binomial models, and AIC model selection, results
indicate that landscape characteristics at the broadest scale (5 km and 25 km) examined were most strongly associated with estimated bat fatality rates. I suggest wind farms
should be constructed in areas that consist of uniform and connected habitat throughout
the facility, without the presence of fragmented water sources. Managers should also
implement mitigation efforts and pre/post-construction assessments to potentially reduce
bat fatalities.},
language = {en},
urldate = {2023-06-01},
author = {Kimes, Houston},
month = dec,
year = {2022},
keywords = {NALCMS},
}
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The objective of my thesis was to assess the influence of landscape characteristics surrounding wind energy facilities and around specific turbines on the number of bat fatalities. I systematically searched 200 wind turbines and collected 1,067 bat carcasses at Hidalgo and Los Vientos Wind Energy Facilities from 2017–2018; I found Tadarida brasiliensis (n = 577), Lasiurus intermedius (n = 203), L. ega (n = 69), Nycticeius humeralis (n = 51), L. xanthinus (n = 30), L. cinereus (n = 18), L. blossevilli (n = 2) Myotis velifer (n = 2), Nyctinomops macrotis (n = 1), Perimyotis subflavus (n = 1), and unknown spp. (n = 113). I used Fragstats and ArcGIS Pro to acquire landscape metrics at the two facilities and among the 100 wind turbines at each facility at multiple scales (100 m, 500 m, 1 km, 5 km, and 25 km). Landscape characteristics included landcover types such as barren, crops, herbaceous, developed, shrub/scrub, hay/pasture, forest, wetlands, and open water, proximity to water sources, elevation and degree of slope. Using generalized linear models, zero-inflated and negative binomial models, and AIC model selection, results indicate that landscape characteristics at the broadest scale (5 km and 25 km) examined were most strongly associated with estimated bat fatality rates. I suggest wind farms should be constructed in areas that consist of uniform and connected habitat throughout the facility, without the presence of fragmented water sources. Managers should also implement mitigation efforts and pre/post-construction assessments to potentially reduce bat fatalities.","language":"en","urldate":"2023-06-01","author":[{"propositions":[],"lastnames":["Kimes"],"firstnames":["Houston"],"suffixes":[]}],"month":"December","year":"2022","keywords":"NALCMS","bibtex":"@phdthesis{kimes_assessing_2022,\n\ttitle = {Assessing the {Influence} of {Landscape} {Characteristics} on {Bat} {Fatalities} at {South} {Texas} {Wind} {Energy} {Facilities}},\n\turl = {https://digital.library.txstate.edu/handle/10877/16360},\n\tabstract = {Although wind energy is a viable renewable energy source, strikes by wind \nturbine blades unintentionally cause bat fatalities. Previous research has suggested siting \nof wind energy facilities, and turbine placement within facilities, influence the number of \nbat fatalities; however, there is a knowledge gap regarding the reasons for the variability. \nThis study occurred in Texas, the leading producer of wind energy and home to the \ngreatest diversity and largest colonies of bats in the United States. The objective of my \nthesis was to assess the influence of landscape characteristics surrounding wind energy \nfacilities and around specific turbines on the number of bat fatalities. I systematically \nsearched 200 wind turbines and collected 1,067 bat carcasses at Hidalgo and Los Vientos \nWind Energy Facilities from 2017–2018; I found Tadarida brasiliensis (n = 577), \nLasiurus intermedius (n = 203), L. ega (n = 69), Nycticeius humeralis (n = 51), L. \nxanthinus (n = 30), L. cinereus (n = 18), L. blossevilli (n = 2) Myotis velifer (n = 2), \nNyctinomops macrotis (n = 1), Perimyotis subflavus (n = 1), and unknown spp. (n = 113). \nI used Fragstats and ArcGIS Pro to acquire landscape metrics at the two facilities and \namong the 100 wind turbines at each facility at multiple scales (100 m, 500 m, 1 km, 5 \nkm, and 25 km). Landscape characteristics included landcover types such as barren, \ncrops, herbaceous, developed, shrub/scrub, hay/pasture, forest, wetlands, and open water, \nproximity to water sources, elevation and degree of slope. Using generalized linear \nmodels, zero-inflated and negative binomial models, and AIC model selection, results \nindicate that landscape characteristics at the broadest scale (5 km and 25 km) examined were most strongly associated with estimated bat fatality rates. I suggest wind farms \nshould be constructed in areas that consist of uniform and connected habitat throughout \nthe facility, without the presence of fragmented water sources. Managers should also \nimplement mitigation efforts and pre/post-construction assessments to potentially reduce \nbat fatalities.},\n\tlanguage = {en},\n\turldate = {2023-06-01},\n\tauthor = {Kimes, Houston},\n\tmonth = dec,\n\tyear = {2022},\n\tkeywords = {NALCMS},\n}\n\n","author_short":["Kimes, H."],"key":"kimes_assessing_2022","id":"kimes_assessing_2022","bibbaseid":"kimes-assessingtheinfluenceoflandscapecharacteristicsonbatfatalitiesatsouthtexaswindenergyfacilities-2022","role":"author","urls":{"Paper":"https://digital.library.txstate.edu/handle/10877/16360"},"keyword":["NALCMS"],"metadata":{"authorlinks":{}}},"bibtype":"phdthesis","biburl":"https://bibbase.org/zotero/NAAtlas","dataSources":["b2hK7W3gKFFH29MkC","wszmZbW485BrvbZff","3fS6y29xitMxSyCmw","SmeabbQSEFozkXJuC","3cx6m8LrzQx6SsjF2","PseKevEbLcNJBrbk4"],"keywords":["nalcms"],"search_terms":["assessing","influence","landscape","characteristics","bat","fatalities","south","texas","wind","energy","facilities","kimes"],"title":"Assessing the Influence of Landscape Characteristics on Bat Fatalities at South Texas Wind Energy Facilities","year":2022}