Instituto Mediterráneo de Estudios Avanzados (IMEDEA), CSIC-UIB. Miquel Marquès 21, 07190, Esporles, Balearic Islands, Spain; Centro Oceanográfico de Illes Balears (COB-IEO), CSIC. Moll de Ponent S/n, 07015, Palma, Balearic Islands, Spain.
Instituto Mediterráneo de Estudios Avanzados (IMEDEA), CSIC-UIB. Miquel Marquès 21, 07190, Esporles, Balearic Islands, Spain.
Mar Environ Res. 2024 Nov;202:106713. doi: 10.1016/j.marenvres.2024.106713. Epub 2024 Aug 27.
Climate warming is causing shifts in reproductive phenology, a crucial life history trait determining offspring survival and population productivity. Evaluating these impacts on exploited marine resources is essential for implementing adaptive measures from an ecosystemic approach. This study introduces a statistical model designed to predict fish spawning phenology from sea surface temperature profiles, integrating mortality-corrected hatch-date distributions inferred from fishery-dependent samplings, along with the gonadosomatic index of adult individuals. When applied to different dolphinfish (Coryphaena hippurus) populations across a broad latitudinal range, the model reasonably predicts the spawning phenology across its extensive thermal ranges, elucidating a direct relationship between mean annual temperature and the breadth of the spawning season. Despite the varying thermal profiles, results show a consistent timing of spawning peaks approximately 49 days before the peak in temperature. Importantly, these findings account for the impact of fishery constraints, such as seasonal closures or different sampling schedules, offering a robust tool for adjusting management practices in response to inter-annual temperature variations. These insights are critical for both short-term fishery management, including the strategic planning of seasonal closures, and long-term projections of spawning phenology shifts under changing thermal regimes. By enhancing our ability to predict spawning times, this research contributes significantly to the sustainable management of fish populations and the adaptive response to environmental changes.
气候变暖正在导致生殖物候学发生变化，这是一个决定后代生存和种群生产力的关键生活史特征。评估这些对受捕捞海洋资源的影响，对于从生态系统方法实施适应性措施至关重要。本研究引入了一种统计模型，旨在根据海表温度剖面预测鱼类的产卵物候学，整合了从渔业依赖的抽样中推断出的经过死亡率校正的孵化日期分布，以及成年个体的性腺指数。当应用于不同纬度范围内的不同鲯鳅（Coryphaena hippurus）种群时，该模型合理地预测了其广泛的温度范围内的产卵物候学，阐明了平均年度温度与产卵季节宽度之间的直接关系。尽管温度剖面存在差异，但结果显示，在温度峰值前大约 49 天左右，产卵高峰期的时间大致相同。重要的是，这些发现考虑了渔业限制的影响，如季节性关闭或不同的抽样时间表，为根据年度间的温度变化调整管理实践提供了一个稳健的工具。这些见解对于短期渔业管理至关重要，包括季节性关闭的战略规划，以及在不断变化的热环境下预测产卵物候学变化的长期预测。通过提高预测产卵时间的能力，本研究为鱼类种群的可持续管理和对环境变化的适应性反应做出了重要贡献。
