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Modelling habitat suitability of the Indo-Pacific humpback dolphin using artificial neural network: The influence of shipping

文献类型：期刊论文

;
作者Lin, Mingli1,2; Liu, Mingming1; Lek, Sovan2; Dong, Lijun1; Zhang, Peijun1; Gozlan, Rodolphe E.3; Li, Songhai1
刊名ECOLOGICAL INFORMATICS ; ECOLOGICAL INFORMATICS
出版日期2021-05-01 ; 2021-05-01
卷号62页码:9
关键词Linear discriminant analysis Linear discriminant analysis Estuary Top-predator Cetacean Conservation Estuary Top-predator Cetacean Conservation
ISSN号1574-9541 ; 1574-9541
DOI10.1016/j.ecoinf.2021.101274 ; 10.1016/j.ecoinf.2021.101274
通讯作者Li, Songhai
英文摘要The distribution of cetaceans is generally studied on the basis of their visual locations. However, the absence of observations does not exclude the presence of dolphins and not allow to distinguish habitats favourable to the species but where it would be currently absent due to anthropic disturbances. The modelling of ecological niches represents a powerful alternative choice and intensive computer modelling has been increasingly used to reveal the complexity of the relationships between cetaceans and their habitat. Here, we predicted the presence/ absence of the Indo-Pacific humpback dolphin (Sousa chinensis), an endangered species, using the artificial neural network model of back-propagation (BP-ANN) with eight environmental variables. The BP-ANN model had a higher success rate for correct prediction (74%) compared to linear discriminant analysis (67%), especially for the prediction of the presence of S. chinensis (63% to 31%), indicating its potential application in cetacean habitat research. In the model output map, three suitable habitats were predicted without S. chinensis sightings identified. However, only one was confirmed by subsequent field surveys, the other two being located in a strong shipping area. Therefore, we suggest that the traditional assessment of the baseline habitat based on visual sighting may miss the identification of some suitable habitats due to anthropogenic disturbance. We have also highlighted the importance of ecological modelling research for cetacean conservation. In addition, among the eight environmental variables studied, distance from shore, fish abundance and salinity proved to be the most important factors for the distribution of S. chinensis, indicating that coastal construction, sea recovery and overfishing would be key constraints for its conservation.; The distribution of cetaceans is generally studied on the basis of their visual locations. However, the absence of observations does not exclude the presence of dolphins and not allow to distinguish habitats favourable to the species but where it would be currently absent due to anthropic disturbances. The modelling of ecological niches represents a powerful alternative choice and intensive computer modelling has been increasingly used to reveal the complexity of the relationships between cetaceans and their habitat. Here, we predicted the presence/ absence of the Indo-Pacific humpback dolphin (Sousa chinensis), an endangered species, using the artificial neural network model of back-propagation (BP-ANN) with eight environmental variables. The BP-ANN model had a higher success rate for correct prediction (74%) compared to linear discriminant analysis (67%), especially for the prediction of the presence of S. chinensis (63% to 31%), indicating its potential application in cetacean habitat research. In the model output map, three suitable habitats were predicted without S. chinensis sightings identified. However, only one was confirmed by subsequent field surveys, the other two being located in a strong shipping area. Therefore, we suggest that the traditional assessment of the baseline habitat based on visual sighting may miss the identification of some suitable habitats due to anthropogenic disturbance. We have also highlighted the importance of ecological modelling research for cetacean conservation. In addition, among the eight environmental variables studied, distance from shore, fish abundance and salinity proved to be the most important factors for the distribution of S. chinensis, indicating that coastal construction, sea recovery and overfishing would be key constraints for its conservation.
WOS关键词SOUSA-CHINENSIS ; SOUSA-CHINENSIS ; CETACEAN-HABITAT ; SPATIAL-DISTRIBUTION ; AUSTRALIAN SNUBFIN ; PREDATION RISK ; ABUNDANCE ; BEHAVIOR ; SEA ; PREFERENCES ; WHALE ; CETACEAN-HABITAT ; SPATIAL-DISTRIBUTION ; AUSTRALIAN SNUBFIN ; PREDATION RISK ; ABUNDANCE ; BEHAVIOR ; SEA ; PREFERENCES ; WHALE
资助项目National Natural Science Foundation of China[41406182] ; National Natural Science Foundation of China[41406182] ; National Natural Science Foundation of China[41306169] ; National Natural Science Foundation of China[41422604] ; biodiversity investigation, observation and assessment program (2019-2023) of Ministry of Ecology and Environment of China ; development project of Institute of Deep-sea Science and Engineering Chinese Academy of Sciences[E072010101] ; Ocean Park Conservation Foundation Hong Kong[AW02-1920] ; National Natural Science Foundation of China[41306169] ; National Natural Science Foundation of China[41422604] ; biodiversity investigation, observation and assessment program (2019-2023) of Ministry of Ecology and Environment of China ; development project of Institute of Deep-sea Science and Engineering Chinese Academy of Sciences[E072010101] ; Ocean Park Conservation Foundation Hong Kong[AW02-1920]
WOS研究方向Environmental Sciences & Ecology ; Environmental Sciences & Ecology
语种英语 ; 英语
WOS记录号WOS:000639851100008 ; WOS:000639851100008
出版者ELSEVIER ; ELSEVIER
资助机构National Natural Science Foundation of China ; National Natural Science Foundation of China ; biodiversity investigation, observation and assessment program (2019-2023) of Ministry of Ecology and Environment of China ; development project of Institute of Deep-sea Science and Engineering Chinese Academy of Sciences ; Ocean Park Conservation Foundation Hong Kong ; biodiversity investigation, observation and assessment program (2019-2023) of Ministry of Ecology and Environment of China ; development project of Institute of Deep-sea Science and Engineering Chinese Academy of Sciences ; Ocean Park Conservation Foundation Hong Kong
源URL[http://ir.idsse.ac.cn/handle/183446/8648]  
专题深海科学研究部_深海生物学研究室_海洋哺乳动物与海洋生物声学研究组
通讯作者Li, Songhai
作者单位1.Chinese Acad Sci, Inst Deep Sea Sci & Engn, Marine Mammal & Marine Bioacoust Lab, Sanya 572000, Peoples R China
2.Univ Paul Sabatier, UMR EDB 5174, CNRS, F-31062 Toulouse, France
3.Univ Montpellier, EPHE, CNRS, ISEM,IRD, F-34090 Montpellier, France
推荐引用方式
GB/T 7714		 Lin, Mingli,Liu, Mingming,Lek, Sovan,et al. Modelling habitat suitability of the Indo-Pacific humpback dolphin using artificial neural network: The influence of shipping, Modelling habitat suitability of the Indo-Pacific humpback dolphin using artificial neural network: The influence of shipping[J]. ECOLOGICAL INFORMATICS, ECOLOGICAL INFORMATICS,2021, 2021,62, 62:9, 9.
APA Lin, Mingli.,Liu, Mingming.,Lek, Sovan.,Dong, Lijun.,Zhang, Peijun.,...&Li, Songhai.(2021).Modelling habitat suitability of the Indo-Pacific humpback dolphin using artificial neural network: The influence of shipping.ECOLOGICAL INFORMATICS,62,9.
MLA Lin, Mingli,et al."Modelling habitat suitability of the Indo-Pacific humpback dolphin using artificial neural network: The influence of shipping".ECOLOGICAL INFORMATICS 62(2021):9.

入库方式： OAI收割

来源：深海科学与工程研究所

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