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Modeling population dynamics of scyphozoan jellyfish (Amelia spp.) in the Gulf of Mexico

机译:在墨西哥湾模拟海豚水母(Amelia spp。)的种群动态

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摘要

To gain understanding and predict how jellyfish populations will respond to anthropogenic changes, we first need to understand the factors that influence the distribution and abundance of current and historical populations. Hence, we have developed the first bioenergetics-based population model for the ubiquitous jellyfish Aurelia spp. that incorporates both benthic and pelagic life history stages. This model tracks cohorts of both life stages with temperature and/or consumption-driven relationships for growth, reproduction and mortality. We present an initial model application to test hypotheses for the environmental factors that control the initiation of strobilation and inter-annual variability in bloom timing and magnitude in Gulf of Mexico jellyfish populations between 1982 and 2007. To recreate the autumnal blooms of Aurelia spp. in the Gulf of Mexico, strobilation must commence while zooplankton biomass is increasing after the annual minimum. Under this scenario, the model simulated seasonal and inter-annual variability of Aurelia spp. biomass that corresponded well with observations. Markedly larger blooms in anomalously warm, high zooplankton years resulted from enhanced ephyrae production compounded by enhanced medusa growth under these conditions. This model confirms the importance of the polyp-to-ephyrae transition in regulating jellyfish bloom magnitude and provides a mechanistic model framework which can examine how future jellyfish populations might respond to climate change.
机译:为了了解并预测水母种群对人为变化的反应,我们首先需要了解影响当前和历史种群分布和丰富度的因素。因此,我们为无处不在的水母Aurelia spp开发了第一个基于生物能学的种群模型。包括底栖和浮游生命历史阶段。该模型通过温度和/或消耗驱动的关系追踪两个生命阶段的队列,以了解生长,繁殖和死亡率。我们提供了一个初始模型应用程序来测试关于环境因素的假设,这些环境因素控制着1982年至2007年之间墨西哥湾水母种群的爆发时间和强度控制的爆发和年际变化的启动。重建Aurelia spp的秋天绽放。在墨西哥湾,当浮游动物的生物量在年度最低值之后增加时,必须开始脱脂。在这种情况下,该模型模拟了Aurelia spp的季节和年际变化。与观测值非常吻合的生物量。在这些条件下,异常温暖,高浮游动物年的花朵明显更大,这是由于增加了e气的产生,加上水母的生长增加了。该模型证实了息肉到以弗拉伊过渡对调节水母开花程度的重要性,并提供了一个机制模型框架,可以检查未来的水母种群如何应对气候变化。

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