Scale and Landscape Features Matter for Understanding Waterbird Habitat Selection

doi:10.3390/rs13214397

	Scale and Landscape Features Matter for Understanding Waterbird Habitat Selection
	Li, Jinya ; Zhang, Yang 1; Zhao, Lina 1,2; Deng, Wanquan 3; Qian, Fawen 4; Ma, Keming 1
	2021
发表期刊	REMOTE SENSING
卷号	13 期号:21
摘要	Clarifying species-environment relationships is crucial for the development of efficient conservation and restoration strategies. However, this work is often complicated by a lack of detailed information on species distribution and habitat features and tends to ignore the impact of scale and landscape features. Here, we tracked 11 Oriental White Storks (Ciconia boyciana) with GPS loggers during their wintering period at Poyang Lake and divided the tracking data into two parts (foraging and roosting states) according to the distribution of activity over the course of a day. Then, a three-step multiscale and multistate approach was employed to model habitat selection characteristics: (1) first, we minimized the search range of the scale for these two states based on daily movement characteristics; (2) second, we identified the optimized scale of each candidate variable; and (3) third, we fit a multiscale, multivariable habitat selection model in relation to natural features, human disturbance and especially landscape composition and configuration. Our findings reveal that habitat selection of the storks varied with spatial scale and that these scaling relationships were not consistent across different habitat requirements (foraging or roosting) and environmental features. Landscape configuration was a more powerful predictor for storks' foraging habitat selection, while roosting was more sensitive to landscape composition. Incorporating high-precision spatiotemporal satellite tracking data and landscape features derived from satellite images from the same periods into a multiscale habitat selection model can greatly improve the understanding of species-environmental relationships and guide efficient recovery planning and legislation.
关键词	species distribution models satellite tracking multiscale model landscape composition and configuration variance partitioning analysis
学科领域	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
DOI	10.3390/rs13214397
收录类别	SCI
语种	英语
WOS关键词	CONFIGURATION ; DISTRIBUTIONS ; CONSERVATION ; MULTISCALE ; MODELS
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000718475100001
出版者	MDPI
文献子类	Article
出版地	BASEL
EISSN	2072-4292
资助机构	National Key R&D Program of China ; National Natural Science Foundation of China [NSFC 41601439]
作者邮箱	jyli@rcees.ac.cn ; zhangyang182@mails.ucas.ac.cn ; zhaoln@ibcas.ac.cn ; dengwanquan@gxhky.org ; cranenw@caf.ac.cn ; mkm@rcees.ac.cn
作品OA属性	gold
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/26697
专题	系统与进化植物学国家重点实验室
作者单位	1.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China 2.Univ Chinese Acad Sciences, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Bot, State Key Lab Systemat & Evolutionary Bot, Beijing 100093, Peoples R China 4.Beijing Forestry Univ, Coll Forestry, Beijing 100083, Peoples R China 5.Chinese Acad Forestry, Res Inst Forest Ecol Environm & Protect, Key Lab Biodivers Conservat Natl Forestry & Grass, Beijing 100091, Peoples R China
推荐引用方式 GB/T 7714	Li, Jinya,Zhang, Yang,Zhao, Lina,et al. Scale and Landscape Features Matter for Understanding Waterbird Habitat Selection[J]. REMOTE SENSING,2021,13(21).
APA	Li, Jinya,Zhang, Yang,Zhao, Lina,Deng, Wanquan,Qian, Fawen,&Ma, Keming.(2021).Scale and Landscape Features Matter for Understanding Waterbird Habitat Selection.REMOTE SENSING,13(21).
MLA	Li, Jinya,et al."Scale and Landscape Features Matter for Understanding Waterbird Habitat Selection".REMOTE SENSING 13.21(2021).

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