Scale and Landscape Features Matter for Understanding Waterbird Habitat Selection
文献类型：期刊论文
| 作者 | Li, Jinya; Zhang, Yang5; Zhao, Lina2,5; Deng, Wanquan3; Qian, Fawen1; Ma, Keming5 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2021 |
| 卷号 | 13期号:21 |
| 关键词 | species distribution models satellite tracking multiscale model landscape composition and configuration variance partitioning analysis |
| DOI | 10.3390/rs13214397 |
| 文献子类 | Article |
| 英文摘要 | 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. |
| 学科主题 | Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology |
| 电子版国际标准刊号 | 2072-4292 |
| 出版地 | BASEL |
| WOS关键词 | CONFIGURATION ; DISTRIBUTIONS ; CONSERVATION ; MULTISCALE ; MODELS |
| WOS研究方向 | Science Citation Index Expanded (SCI-EXPANDED) |
| 语种 | 英语 |
| 出版者 | MDPI |
| WOS记录号 | WOS:000718475100001 |
| 资助机构 | National Key R&D Program of China ; National Natural Science Foundation of China [NSFC 41601439] |
| 源URL | [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.Beijing Forestry Univ, Coll Forestry, Beijing 100083, 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.Chinese Acad Forestry, Res Inst Forest Ecol Environm & Protect, Key Lab Biodivers Conservat Natl Forestry & Grass, Beijing 100091, Peoples R China 5.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, 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). |
入库方式： OAI收割
来源：植物研究所
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