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评估沿河口梯度的浮游食物网动态的自上而下、自下而上和环境驱动因素。

Evaluating top-down, bottom-up, and environmental drivers of pelagic food web dynamics along an estuarine gradient.

机构信息

Southwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, Santa Cruz, California, USA.

Delta Science Program, Delta Stewardship Council, Sacramento, California, USA.

出版信息

Ecology. 2024 Apr;105(4):e4274. doi: 10.1002/ecy.4274. Epub 2024 Feb 28.

Abstract

Identification of the key biotic and abiotic drivers within food webs is important for understanding species abundance changes in ecosystems, particularly across ecotones where there may be strong variation in interaction strengths. Using structural equation models (SEMs) and four decades of integrated data from the San Francisco Estuary, we investigated the relative effects of top-down, bottom-up, and environmental drivers on multiple trophic levels of the pelagic food web along an estuarine salinity gradient and at both annual and monthly temporal resolutions. We found that interactions varied across the estuarine gradient and that the detectability of different interactions depended on timescale. For example, for zooplankton and estuarine fishes, bottom-up effects appeared to be stronger in the freshwater upstream regions, while top-down effects were stronger in the brackish downstream regions. Some relationships (e.g., bottom-up effects of phytoplankton on zooplankton) were seen primarily at annual timescales, whereas others (e.g., temperature effects) were only observed at monthly timescales. We also found that the net effect of environmental drivers was similar to or greater than bottom-up and top-down effects for all food web components. These findings can help identify which trophic levels or environmental factors could be targeted by management actions to have the greatest impact on estuarine forage fishes and the spatial and temporal scale at which responses might be observed. More broadly, this study highlights how environmental gradients can structure community interactions and how long-term data sets can be leveraged to generate insights across multiple scales.

摘要

确定食物网中的关键生物和非生物驱动因素对于理解生态系统中物种丰度的变化非常重要,特别是在生态交错区,那里的相互作用强度可能会有很大的变化。本研究使用结构方程模型(SEMs)和旧金山湾长达四十年的综合数据,调查了在沿河口盐度梯度以及在年度和月度时间分辨率上,对浮游食物网多个营养级的顶级、底层和环境驱动因素的相对影响。我们发现,相互作用在河口梯度上存在差异,并且不同相互作用的可检测性取决于时间尺度。例如,对于浮游动物和河口鱼类,底层效应在上游淡水区似乎更强,而顶层效应在下游咸水区更强。一些关系(例如浮游植物对浮游动物的底层效应)主要在年度时间尺度上可见,而其他关系(例如温度效应)仅在月度时间尺度上观察到。我们还发现,对于所有食物网组成部分,环境驱动因素的净效应与底层和顶层效应相似或更大。这些发现可以帮助确定哪些营养级或环境因素可以通过管理措施来针对,以对河口饲料鱼类产生最大影响,以及可能观察到响应的空间和时间尺度。更广泛地说,这项研究强调了环境梯度如何构建群落相互作用,以及长期数据集如何能够在多个尺度上产生见解。

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