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| Main Authors: | , , , , , , , , , , , |
|---|---|
| Format: | Artículo científico |
| Language: | en |
| Published: |
Biology
2025
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| Online Access: | https://pubmed.ncbi.nlm.nih.gov/41463505/ |
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Table of Contents:
- Modeling Dominant Macrobenthic Species Distribution and Predicting Potential Habitats in the Yellow River Estuary, China. Yuan, Chao Huang, Juan Wang, Lan Zhang, Tao Yu, Haolin Sun, Huiying Liu, Yumeng Sun, Shuo Sun, Jingyi Shang, Yongjun Feng, Jie Xu, Jiangling Macrobenthic fauna are vital to the ecological health of the Yellow River Estuary, yet their long-term population drivers are poorly understood. This study used Boosted Regression Tree models to analyze the spatio-temporal distribution of five dominant species: , , , , and . Key environmental drivers included ammonia nitrogen, water depth, sand content of sediment, and water temperature. Specifically, and preferred deeper waters, favored habitats with moderate sand content of sediment, primarily occurred at water temperatures lower than 25 °C, and distribution was most influenced by ammonia nitrogen. All species exhibited a preference for lower ammonia nitrogen concentrations. Inorganic nitrogen and freshwater discharge from the Yellow River significantly influenced the distribution of , whereas river discharge alone was positively correlated with areas exhibiting a high occurrence probability (>0.5) for . Future studies that integrate comprehensive seasonal monitoring data, hydrodynamic conditions, and food availability could further enhance predictive accuracy, providing stronger theoretical and technical support for ecological conservation and management in the Yellow River Estuary.