PDF
Full
Outline
Traditional species distribution models rarely incorporate interspecific relationships into the modeling framework, which hinders their predictions of habitat distributions. In recent years, joint species distribution models (JSDMs) have drawn increasing attentions, but their practical applications remain rare in the marine realm. In this study, we used the HMSC (hierarchical modelling of species communities) method to study their relationships between 17 demersal fish species and environmental factors and the interspecific correlation. The model was built on the basis of bottom trawling data collected in the coastal waters of Shandong in summer, 2017, including the environmental data of water depth, bottom water temperature and bottom water salinity. Five variants of HMSC models were developed with respect to the linear or nonlinear relationships between species and the environmental variables and the exists of random effects, and WAIC and other indicators as well as cross-validation were used to evaluate the performances of fitting and prediction of these models. The results showed that the optimal model was the one incorporating nonlinear relationships and random effects (Model 5). The nonlinear models were generally superior to the linear models, and including the interspecific relationships in the model could improve model fitting performances. Temperature was the main factor influencing the distribution of demersal fishes in the coastal waters of Shandong, accounting for 51.4% of the mean explained variance, followed by water depth and random effects, which accounted for 35.7% and 12.8% explained variance, respectively. There were significant linear positive correlations between most demersal fishes and water depth, and significant nonlinear relationships with water temperature. There were significant interspecific correlations among the demersal fishes, which could be roughly divided into three groups according to the sign of the correlations, indicating that the interspecies relationships played an important role in shaping species distributions. This study suggested that the abiotic factors and biotic factors should be integrated in species distribution modeling, and our results might provide a guideline for the prediction of habitat distribution of fishery resources.
PDF
189
98
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
关闭全屏
No. 86 Xueyuan South Road, Haidian District, Beijing
010-62199257
qkjq@cast.org.cn
Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House
