The Efficacy of Fisheries Management: A Length-Based Stock Assessment of Eight Fish Species in Xingkai Lake, China

TL;DR

A study in Xingkai Lake, China, evaluates how a large-mesh fishing gear policy impacted eight fish species, finding mixed results with small species recovering but larger ones still overfished.

Contribution

The first application of the Length-Based Bayesian Biomass method to assess the stock status of eight fish species in a Chinese freshwater lake.

Findings

Four small, fast-growing fish species recovered to healthy population levels after the mesh size policy.

Three large, slow-growing species remained overfished despite the policy, indicating limited effectiveness.

Fisheries in Xingkai Lake remain overexploited, highlighting the need for ecosystem-based management.

Abstract

Overfishing has led to a continuous decline in fishery resources in Xingkai Lake, the largest transboundary freshwater lake in Asia, though the specific status of fish populations has lacked scientific assessment. To promote resource recovery, local authorities implemented a large-mesh fishing gear policy in 2019, yet its effectiveness remained unclear. This study provides the first systematic evaluation of the impact of this five-year policy on the recovery of eight major commercial fish species in the lake. The results show that while increasing mesh size effectively promoted the rapid recovery of small fish species, medium and large species will require more time to rebuild their populations. Overall, the lake’s fisheries remain in an overexploited state. This indicates that a single management measure is unlikely to achieve optimal outcomes for all fish species and may even pose potential risks of unbalancing fish community structure. This research offers key scientific evidence for developing more targeted, multi-species collaborative management strategies, providing important guidance for achieving sustainable fisheries and ecological balance in Xingkai Lake.

Standardized fishing gear represents a common fisheries management intervention, yet its effectiveness in multi-species freshwater ecosystems remains insufficiently assessed. This study presents the first application of the Length-Based Bayesian Biomass (LBB) method to systematically evaluate the stock status of eight major commercial fish species in Xingkai Lake (located within China). Length-frequency data collected in 2019 (marking the policy initiation) and 2024 (after five years of implementation) were used to estimate key population parameters and exploitation indicators. The results revealed that the four species (Carassius gibelio, Acheilognathus macropterus, Hemiculter lucidus, and Hemiculter leucisculus) recovered to healthy status (B/BMSY ≥ 1.0), demonstrating the policy’s effectiveness for small-bodied, fast-growing species. In contrast, three species (Chanodichthys abramoides, Chanodichthys mongolicus, and Chanodichthys erythropterus) remained grossly overfished (B/BMSY < 0.5), while Culter alburnus experienced increased fishing pressure, indicating limited efficacy for larger, slow-growing species with collapsed initial stocks. Although the mesh size increase facilitated recovery of specific populations, fisheries resources in Xingkai Lake continue to face overfishing pressure. Management strategies lacking an ecosystem perspective may not only fail to achieve conservation objectives but could also trigger ecological risks. This study underscores that ecosystem-based management is essential for sustainable management of multi-species fisheries.

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