Many demersal marine fish species depend on a dispersive larval stage that connects geographically discrete sub‐populations. Understanding connectivity between these sub‐populations is necessary to determine stock structure, which identifies the appropriate spatial scale for fishery management. Such connectivity is poorly understood for King George whiting (Sillaginodes punctatus; Perciformes) in South Australia's gulf system, even though spawning grounds and nursery areas are adequately defined. In response to declines in commercial catches and estimated biomass, this study aimed to determine the most important spawning grounds and nursery areas to recruitment, and the connectivity between them. A biophysical model was seeded with particles according to the distribution and density of eggs throughout the spawning area in 2017 and 2018. Despite inter‐annual differences in the origins of particles, dispersal pathways and predicted settlement areas remained consistent between years. Predicted settlement was generally highest to nursery areas only short distances from regional spawning grounds, consistent with previous hydrodynamic models. However, the model also predicted that spawning in one region could contribute to recruitment in an adjacent region later in the spawning season, which aligned with the breakdown of thermohaline fronts at the entrance of each gulf. The connectivity between spawning grounds and nursery areas predicted by the model is supported by spatio‐temporal patterns in the otolith chemistry of pre‐flexion larvae and settled juveniles. Consequently, the most parsimonious explanation is that the populations of King George whiting in South Australia's gulf system constitute a single, panmictic stock, which has implications for fishery management.

中文翻译：

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使用生物物理模型调查南澳大利亚州海湾的乔治·白鳕鱼的产卵场与育苗区之间的连通性（Sillaginodes punctatus：Perciformes）

许多深海海鱼种类依赖于分散的幼体阶段，该阶段连接地理上分散的亚群。必须了解这些亚种群之间的连通性，才能确定种群结构，从而确定适合渔业管理的空间规模。对于乔治·王白鳕鱼（Sillaginodes punctatus; 即使在产卵场和育苗场已充分定义的情况下，也可以在南澳大利亚的海湾系统中找到。为了应对商业捕捞量和估计生物量的下降，本研究旨在确定最重要的产卵场和育苗场以及它们之间的联系。根据2017年和2018年整个产卵区域卵的分布和密度，用颗粒植入了生物物理模型。尽管颗粒起源之间存在年际差异，但各年之间的扩散途径和预计的沉降面积仍保持一致。通常，与区域产卵场只有很短距离的苗圃地区，预计的沉降最高，这与以前的水动力模型一致。然而，该模型还预测，在产卵季节的一个区域产卵可能会促进邻近区域的募集，这与每个海湾入口处的热盐卤锋的分解一致。该模型所预测的产卵场与育苗场之间的连通性由屈曲前幼虫和定居的幼虫的耳石化学时空模式支持。因此，最简约的解释是南澳大利亚州海湾系统中乔治国王白鳕的种群构成单一的恐慌种群，对渔业管理产生影响。该模型所预测的产卵场与育苗场之间的连通性由屈曲前幼虫和定居的幼虫的耳石化学时空模式支持。因此，最简约的解释是南澳大利亚州海湾系统中乔治国王白鳕的种群构成单一的恐慌种群，对渔业管理产生影响。该模型所预测的产卵场与育苗场之间的连通性由屈曲前幼虫和定居的幼虫的耳石化学时空模式支持。因此，最简约的解释是南澳大利亚州海湾系统中乔治国王白鳕的种群构成单一的恐慌种群，对渔业管理产生影响。