Physico-chemical factors alone cannot simulate phytoplankton behaviour in a lowland river
Physico-chemical factors alone cannot simulate phytoplankton behaviour in a lowland river
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仅物理化学因素无法模拟低地河流中的浮游植物行为
DOI：
10.1016/j.jhydrol.2013.05.027
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发表时间：
2013
影响因子：
6.4
通讯作者：
M. Loewenthal
中科院分区：
文献类型：
--
作者：
A. J. Waylett;M. Hutchins;A. Johnson;M. Bowes;M. Loewenthal
我们对河流中浮游植物行为的理解仍有许多空白。考虑到预测的未来气候变化，至少表面上看来，有利于更大规模的浮游植物繁殖，这项研究是为了评估我们目前能用河流水质模型模拟这种行为的程度。2009-2011年（英国），河流质量模型（QUESTOR）在泰晤士河上游45公里的范围内运行。为了确定最合适的模型表示，模拟了浮游植物，并在三种不同的假设下与实际观测数据进行了比较。其中第一种是混合浮游植物种群，另外两种是由已知在河流中丰富的两种群体（绿藻或冷水硅藻，如stephanodiscus hantzschii）中的任何一种占主导地位。浮游植物种群的控制因素主要有流量、温度和辐射。在这些控制因素中，基于停留时间，河流流量对浮游植物的消耗或积累的影响更大。营养物浓度（磷酸盐和硝酸盐）似乎过高，并没有限制或控制浮游植物的行为。数据强调了晚春和夏季的两次主要繁殖，成功地模拟了混合浮游植物种群（这解释了2009-10年间16-35%的每周变化）。从年与年的时间框架来看，放牧损失率在年与年之间存在明显的差异。这可以通过底栖滤食性动物和浮游动物的结合来解释，这两种动物在泰晤士河中都有足够的数量。
There are still a number of gaps in our understanding regarding phytoplankton behaviour in rivers. Given predicted future changes in climate, which appear superficially at least, to favour larger phytoplankton blooms, this study was initiated to assess how well we can currently simulate this behaviour with a river water quality model. The river quality model (QUESTOR) was run for a 45 km stretch of the upper Thames for 2009–2011 (UK). To identify the most suitable model representation, phytoplankton was simulated and compared to actual observed data under three alternative assumptions. The first of these was of a Mixed Phytoplankton population and the other two being that there was domination by either of two groups (Green Algae, or cool water diatoms such asStephanodiscus hantzschii) known to be abundant in the river. The factors for controlling the phytoplankton populations were found to be flow, temperature and radiation. Of these controlling factors, river flow has the larger effect on depletion or build-up of phytoplankton, based on residence time. The nutrient concentrations (phosphate and nitrate) seem to be in excess and not limiting or controlling of the phytoplankton behaviour. The data highlighted two main blooms in late spring and summer, which were successfully modelled with a Mixed Phytoplankton population (which explained 16–35% of the weekly variability throughout 2009–10). On a year-to-year time frame there is clear evidence of between-year differences in grazing loss rates. This can be accounted for by a combination of benthic filter feeders and zooplankton, both having been observed in sufficient numbers in the Thames.