Modelling the effect of tourism disturbance on hatching rate of the Chinese giant salamander (Andrias davidianus) by using artificial neural network

Abstract

The endangered Chinese giant salamander (Andrias davidianus) is an endangered species among the conserved Chinese amphibians. Tourism-related pressures have increased for this species recently. The effect of tourism on the hatching rate of the target species was determined by experimentally observing the influences of different intensities of tourism disturbance on salamander in the Zhangjiajie Chinese Giant Salamander National Nature Reserve. Water quality factors (e.g. total nitrogen, total phosphorus, dissolved oxygen and Escherichia coli abundance) were analysed, and hatching rate was estimated. Results showed that high levels of tourism disturbance (500,000–1,200,000 visitors per year) had active effects on the hatching time and negative effects on the hatching rate. The prediction performance of artificial neural network models was validated by the low root mean square error values of 2.2539 and 3.2612 for the training and testing data and high determination coefficient values of 0.9732 and 0.9508 for the training and testing data, respectively. The potential for positive or negative feedback mechanisms in such relationships between tourists and wildlife highlights the importance of considering both sides of the complex interaction to find a balance between the development of tourism and wild animal protection.

Keywords

• Chinese giant salamander (Andrias davidianus)
• wildlife tourism
• water quality factors
• hatching rate
• artificial neural network model