Using a new framework of two-phase generalized additive models to incorporate prey abundance in spatial distribution models of juvenile slender lizardfish in Haizhou Bay, China

ABSTRACT

The predictive skill of species distribution models depends on the quality and quantity of input information. In addition to the physical environmental variables, prey availability is also one of the main drivers regulating spatial distribution of marine species. However, prey distribution data have rarely been considered in habitat models due to the lack of information on non-commercial prey species. This may lead to an incomplete view of species distributions and biased model predictions. In this study, we developed a new framework of two-phase generalized additive models (GAMs) based on the Tweedie distribution to incorporate the predicted prey abundance as covariates in habitat models, and applied this framework to juvenile slender lizardfish Saurida elongata in Haizhou Bay, China. This study demonstrated that the predictive skill of habitat models could be greatly improved through incorporating prey abundance as explanatory variables. The importance of prey distribution data in the habitat model confirms the essentiality of including prey data while modelling species distribution. Spatial overlap and GAM analysis demonstrated that not all dominant prey can be selected as potential explanatory variables and only those prey species showing high spatiotemporal occurrences with predators should be incorporated. The framework derived in this study could be extended to other marine organisms to improve the predictive skill of habitat models and enhance our understanding of the ecological mechanisms underlying the distribution of marine species.

SUBJECT EDITOR:

• Alf Josefson

KEYWORDS:

• Haizhou Bay
• Saurida elongate
• generalized additive model
• prey
• biotic variables
• habitat

Acknowledgements

We are grateful to many colleagues and students for their assistance in field sampling and sample analyses. The study of the first author (Dr Ying Xue) as a visiting scholar in Dr Yong Chen's lab at the University of Maine was financially supported by the China Scholarship Council (CSC). We also appreciate the support from the Ocean University of China and the University of Maine.

Disclosure statement

No potential conflict of interest was reported by the authors.

ORCID

Ying Xue http://orcid.org/0000-0002-5813-5683

Kisei Tanaka http://orcid.org/0000-0002-1901-6972

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (31772852); the State's Key Project of Research and Development Plan (2017YFE0104400); the Fundamental Research Funds for the Central Universities (201562030, 201612004); and the Scientific and Technological Innovation Project Financially Supported by Qingdao National Laboratory for Marine Science and Technology (2015ASKJ02).