Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters

doi:10.1007/s13131-020-1546-8

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	Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters
	Zhang, Yunlei 1; Yu, Huaming 3; Yu, Haiqing 1; Xu, Binduo 1; Zhang, Chongliang 1; Ren, Yiping 1,2; Xue, Ying 1; Xu, Lili4
	2020-05-02
发表期刊	ACTA OCEANOLOGICA SINICA
ISSN	0253-505X
页码	12
通讯作者	Xue, Ying([email protected])
摘要	Habitat suitability index (HSI) models have been widely used to analyze the relationship between species abundance and environmental factors, and ultimately inform management of marine species. The response of species abundance to each environmental variable is different and habitat requirements may change over life history stages and seasons. Therefore, it is necessary to determine the optimal combination of environmental variables in HSI modelling. In this study, generalized additive models (GAMs) were used to determine which environmental variables to be included in the HSI models. Significant variables were retained and weighted in the HSI model according to their relative contribution (%) to the total deviation explained by the boosted regression tree (BRT). The HSI models were applied to evaluate the habitat suitability of mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent areas in 2011 and 2013-2017. Ontogenetic and seasonal variations in HSI models of mantis shrimp were also examined. Among the four models (non-optimized model, BRT informed HSI model, GAM informed HSI model, and both BRT and GAM informed HSI model), both BRT and GAM informed HSI model showed the best performance. Four environmental variables (bottom temperature, depth, distance offshore and sediment type) were selected in the HSI models for four groups (spring-juvenile, spring-adult, falljuvenile and fall-adult) of mantis shrimp. The distribution of habitat suitability showed similar patterns between juveniles and adults, but obvious seasonal variations were observed. This study suggests that the process of optimizing environmental variables in HSI models improves the performance of HSI models, and this optimization strategy could be extended to other marine organisms to enhance the understanding of the habitat suitability of target species.
关键词	habitat suitability index mantis shrimp generalized additive model boosted regression tree Haizhou Bay
DOI	10.1007/s13131-020-1546-8
收录类别	SCI
语种	英语
资助项目	National Key R&D Program of China[2017YFE0104400]; National Natural Science Foundation of China[31772852]; Marine S& T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology (Qingdao)[2018SDKJ0501-2]
WOS研究方向	Oceanography
WOS类目	Oceanography
WOS记录号	WOS:000530192700001
出版者	SPRINGER
引用统计	被引频次：13[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.qdio.ac.cn/handle/337002/167317
专题	中国科学院海洋研究所
通讯作者	Xue, Ying
作者单位	1.Ocean Univ China, Coll Fisheries, Qingdao 266003, Peoples R China 2.Pilot Natl Lab Marine Sci & Technol Qingdao, Lab Marine Fisheries Sci & Food Prod Proc, Qingdao 266237, Peoples R China 3.Ocean Univ China, Coll Ocean & Atmospher Sci, Qingdao 266100, Peoples R China 4.Chinese Acad Sci, Inst Oceanol, Qingdao 266071, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Yunlei,Yu, Huaming,Yu, Haiqing,et al. Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters[J]. ACTA OCEANOLOGICA SINICA,2020:12.
APA	Zhang, Yunlei.,Yu, Huaming.,Yu, Haiqing.,Xu, Binduo.,Zhang, Chongliang.,...&Xu, Lili.(2020).Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters.ACTA OCEANOLOGICA SINICA,12.
MLA	Zhang, Yunlei,et al."Optimization of environmental variables in habitat suitability modeling for mantis shrimp Oratosquilla oratoria in the Haizhou Bay and adjacent waters".ACTA OCEANOLOGICA SINICA (2020):12.

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