Spatial and Temporal Distribution Patterns of Fish in Large Deep-Water Lakes and Their Association with Environmental Factors Assessed Through Hydroacoustic Methods: A Case Study of Qiandao Lake, China

Abstract

A comprehensive understanding of the spatial and temporal distribution of fish and their relationship with aquatic environments is essential for assessing ecological impacts, advancing lake conservation, and optimizing fisheries management strategies. In this study, we investigated the distribution patterns of fish resources in Qiandao Lake, a large, deep-water lake in eastern China, using hydroacoustic methods. The results revealed pronounced spatial and temporal heterogeneity in the horizontal distribution of fish within the lake. Fish density peaked in autumn at 74.77 (±5.59) ind./1000 m2 and reached its lowest level in winter at 14.65 (±1.18) ind./1000 m2. Regionally, fish densities in the upstream (northwestern), midstream (central), and downstream (southeastern) areas were 84.80 (±4.32), 64.16 (±5.15), and 53.88 (±8.78) ind./1000 m2, respectively, showing an increasing trend with distance from the dam. The vertical distribution of fish also exhibited seasonal and regional variation. In spring, summer, and autumn, peak target strengths were recorded in the −50 to −45 dB range, with most fish measuring 10–20 cm in length. In contrast, during winter, peak target strengths shifted to the −45 to −40 dB range, with the smallest proportion of fish falling in the 1–10 cm size category, while size distributions across other ranges were relatively uniform. Generalized additive model (GAM) analysis revealed that fish density was significantly influenced by environmental factors such as dissolved oxygen (DO), pH, nitrite (NO2−), phosphate (PO43−), and chemical oxygen demand (CODMn). These findings suggest that fish distribution in lakes is shaped by regional variations in water quality, with additional impacts from human activities, including the opening of shipping lanes and fisheries management policies. This research provides valuable insights for optimizing fisheries management in large deep-water lakes.