4.1 Article

Environmental influences on the spatio-temporal distribution of Coilia nasus in the Yangtze River estuary

Journal

JOURNAL OF APPLIED ICHTHYOLOGY
Volume 36, Issue 3, Pages 317-327

Publisher

HINDAWI LTD
DOI: 10.1111/jai.14028

Keywords

Coilia nasus; GAM; spatio-temporal distribution; the Yangtze River estuary; zero-inflated model

Funding

  1. National Natural Science Founding of China [41606146]
  2. Shanghai Municipal Science and Technology Commission Local Capacity Construction Project [18050502000]

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The Yangtze River estuary (YRE) is an important migration channel and foraging habitat for Coilia nasus. Due to its ecological significance and a prioritization of this species' protection, the need to investigate and analyze environmental relationships of the abundance of Coilia nasus in the YRE as well as develop an understanding of their temporal and spatial distributions is becoming exceedingly important. Using fishery data and environmental survey data from 2009 to 2016, three models including generalized additive mixed models (GAMM), generalized additive models with zero-inflated Poisson distribution (ZIP-GAM) and two-step GAM were used to analyze relationships between environmental factors and the distribution of Coilia nasus in the YRE. The results showed that model fitting of GAMM was more consistent with observations and revealed influences of water temperature, salinity, chlorophyll, and pH on distribution. GAMM demonstrated that higher Coilia nasus abundances were located in waters with water temperature values at 15 degrees C and 30 degrees C, and lower Coilia nasus abundances were located in areas with water temperature values at 10 degrees C and 20 degrees C. All models indicated that the effect of salinity on abundance of Coilia nasus present a multimodal pattern including three peaks at 5, 15, and 25 ppt respectively. Additionally, abundance of Coilia nasus increased with the increase of chlorophyll A in its range of 0-4 mg/L. In a range of 8.0-9.5, higher PH value was more suitable for the aggregation of Coilia nasus. Cross validation was used to evaluate the predictive performance of models and GAMM was found to be the best. The predicted abundance distribution of Coilia nasus in the summer and autumn of 2016 was relatively higher overall than that in winter and spring. The predicted zero abundance distribution pattern was consistent with the sampling presence distribution which was obtained using fishery independent survey data of the year 2009-2015. Facing the urgency protection of Coilia nasus in YRE, results of this study could be used for Coilia nasus conservation and reserve planning.

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