首页> 外文期刊>Journal of phycology >Patterns and Controls of the Dynamics of Net Primary Production by Understory Macroalgal Assemblages in Giant Kelp Forests
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Patterns and Controls of the Dynamics of Net Primary Production by Understory Macroalgal Assemblages in Giant Kelp Forests

机译:巨型海藻林下层大型藻类组合净初级生产动态的模式和控制

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摘要

Macroalgae are important primary producers in many subtidal habitats, yet little information exists on the temporal and spatial dynamics of net primary production (NPP) by entire subtidal assemblages. This knowledge gap reflects the logistical challenges in measuring NPP of diverse macroalgal assemblages in shallow marine habitats. Here, we couple a simple primary production model with nondestructive estimates of taxon-specific biomass on subtidal reefs off Santa Barbara, California to produce a 4-year time series of net primary production by intact assemblages of understory macroalgae in giant kelp forests off Santa Barbara, California, USA. Daily bottom irradiance varied significantly throughout the year, and algal assemblages were on average exposed to saturating irradiance for only 1.34.5h per day, depending on the time of year. Despite these variable light-limiting conditions, biomass rather than irradiance explained the vast majority of variation observed in daily NPP at all times of the year. Measurements of peak biomass in spring and summer proved to be good predictors of NPP for the entire year, explaining as much as 76% of the observed variation. In contrast, bottom irradiance was a poor predictor of NPP, explaining <10% of the variation in NPP when analyzed seasonally and (similar to)2% when evaluated annually. Our finding that annual NPP by macroalgal assemblages can be predicted from a single, nondestructive measurement of biomass should prove useful for developing time series data that are necessary to evaluate natural and anthropogenic changes in NPP by one of the world's most productive ecosystems.
机译:大型藻类是许多潮下生境中重要的初级生产者,但关于整个潮下带净初级生产(NPP)的时空动态的信息很少。这种知识差距反映了在测量浅海生境中各种大型藻类组合的NPP时遇到的后勤挑战。在这里,我们将简单的初级生产模型与非破坏性的加利福尼亚州圣塔芭芭拉下潮带礁上的生物分类生物量估计相结合,以通过圣塔芭芭拉外海带巨型海藻森林中完整的林下大型藻类的完整组装,产生净初级生产的4年时间序列,美国加利福尼亚。全年的底部日照度变化很大,根据一年中的不同时间,藻类组合平均每天仅接受饱和照度1.34.5h。尽管存在这些可变的光限制条件,但是在一年中的所有时间中,每天的NPP观察到的绝大部分变化都是生物量而不是辐照度。春季和夏季峰值生物量的测量被证明是全年NPP的良好预测指标,可解释多达76%的观测到的变化。相反,底部辐照度不能很好地预测NPP,这可以解释为季节性分析时<10%的NPP变化和每年评估时(接近)2%。我们的发现表明,可以通过单一的非破坏性生物量测量来预测大型藻类组合产生的年度NPP,这对于开发时间序列数据很有用,该数据对于评估世界上生产力最高的生态系统之一的NPP的自然和人为变化是必要的。

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