Bats’ Roost Selection and Population Count using Light Detection and Ranging (LiDAR) System in Wind Cave Nature Reserve

Limestone karst ecosystems in Sarawak are critical to the survival of bats since they offer protection and permanent shelter for most bat species. Increasing growth of limestone quarry and cave tourism industries in Malaysia impose threat to the cave-dwelling bats. Roost sites are identified as t...

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Main Author:	Nursyafiqah, Shazali
Format:	Thesis
Language:	English
Published:	2017
Subjects:	QL Zoology
Online Access:	http://ir.unimas.my/id/eprint/23843/1/Nursyafiqah%20ft.pdf
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id	my-unimas-ir.23843
record_format	uketd_dc
spelling	my-unimas-ir.238432023-12-12T09:55:18Z Bats’ Roost Selection and Population Count using Light Detection and Ranging (LiDAR) System in Wind Cave Nature Reserve 2017 Nursyafiqah, Shazali QL Zoology Limestone karst ecosystems in Sarawak are critical to the survival of bats since they offer protection and permanent shelter for most bat species. Increasing growth of limestone quarry and cave tourism industries in Malaysia impose threat to the cave-dwelling bats. Roost sites are identified as the key habitat requirement for bats and may be the limiting resources in highly disturb environment. Given the importance of cave to the bats, this thesis aims to understand the cave used by bats by understanding their roost requirements and the population number of bats roost in Wind Cave Nature Reserve (NR). Factors involved in roost selection were investigated and number of bats roost in the cave were determined using new approach. Their light intensity, roost temperature, ambient temperature, roost height, and distance of roost to nearest entrance were identified as factor that influence roost selection of bats in Wind Cave NR for dry and wet seasons. Eight species of bats that roost in Wind Cave NR were specific in selecting their roost site. The roosts temperature are significantly different between species but not by seasons. Further, using advanced remote sensing technology, the LiDAR system, bat population in Wind Cave NR were measured through 3D image. There were 2,886 bats that roosts in Wind Cave NR. Penthetor lucasi (megabat; n = 979) followed by Rhinolophus affinis (microbat; n = 947) was found to be the highest number of species that inhabit the cave. In addition, Wind Cave NR has been modeled into three-dimensional cave where its shows the bat’s roost site accurately. Use of conventional species identification method along with the new scanning technology allow to better understand bat fauna and better estimate their population size. Universiti Malaysia Sarawak, (UNIMAS) 2017 Thesis http://ir.unimas.my/id/eprint/23843/ http://ir.unimas.my/id/eprint/23843/1/Nursyafiqah%20ft.pdf text en validuser masters Universiti Malaysia Sarawak Faculty of Resource Science & Technology
institution	Universiti Malaysia Sarawak
collection	UNIMAS Institutional Repository
language	English
topic	QL Zoology
spellingShingle	QL Zoology Nursyafiqah, Shazali Bats’ Roost Selection and Population Count using Light Detection and Ranging (LiDAR) System in Wind Cave Nature Reserve
description	Limestone karst ecosystems in Sarawak are critical to the survival of bats since they offer protection and permanent shelter for most bat species. Increasing growth of limestone quarry and cave tourism industries in Malaysia impose threat to the cave-dwelling bats. Roost sites are identified as the key habitat requirement for bats and may be the limiting resources in highly disturb environment. Given the importance of cave to the bats, this thesis aims to understand the cave used by bats by understanding their roost requirements and the population number of bats roost in Wind Cave Nature Reserve (NR). Factors involved in roost selection were investigated and number of bats roost in the cave were determined using new approach. Their light intensity, roost temperature, ambient temperature, roost height, and distance of roost to nearest entrance were identified as factor that influence roost selection of bats in Wind Cave NR for dry and wet seasons. Eight species of bats that roost in Wind Cave NR were specific in selecting their roost site. The roosts temperature are significantly different between species but not by seasons. Further, using advanced remote sensing technology, the LiDAR system, bat population in Wind Cave NR were measured through 3D image. There were 2,886 bats that roosts in Wind Cave NR. Penthetor lucasi (megabat; n = 979) followed by Rhinolophus affinis (microbat; n = 947) was found to be the highest number of species that inhabit the cave. In addition, Wind Cave NR has been modeled into three-dimensional cave where its shows the bat’s roost site accurately. Use of conventional species identification method along with the new scanning technology allow to better understand bat fauna and better estimate their population size.
format	Thesis
qualification_level	Master's degree
author	Nursyafiqah, Shazali
author_facet	Nursyafiqah, Shazali
author_sort	Nursyafiqah, Shazali
title	Bats’ Roost Selection and Population Count using Light Detection and Ranging (LiDAR) System in Wind Cave Nature Reserve
title_short	Bats’ Roost Selection and Population Count using Light Detection and Ranging (LiDAR) System in Wind Cave Nature Reserve
title_full	Bats’ Roost Selection and Population Count using Light Detection and Ranging (LiDAR) System in Wind Cave Nature Reserve
title_fullStr	Bats’ Roost Selection and Population Count using Light Detection and Ranging (LiDAR) System in Wind Cave Nature Reserve
title_full_unstemmed	Bats’ Roost Selection and Population Count using Light Detection and Ranging (LiDAR) System in Wind Cave Nature Reserve
title_sort	bats’ roost selection and population count using light detection and ranging (lidar) system in wind cave nature reserve
granting_institution	Universiti Malaysia Sarawak
granting_department	Faculty of Resource Science & Technology
publishDate	2017
url	http://ir.unimas.my/id/eprint/23843/1/Nursyafiqah%20ft.pdf
_version_	1794022997495906304

Bats’ Roost Selection and Population Count using Light Detection and Ranging (LiDAR) System in Wind Cave Nature Reserve

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