Nuisance foam events and Phaeocystis globosa blooms in Dutch coastal waters analyzed with fuzzy logic

被引:80
作者
Blauw, A. N. [1 ,2 ]
Los, F. J. [1 ]
Huisman, J. [2 ]
Peperzak, L. [3 ]
机构
[1] Deltares, NL-2600 MH Delft, Netherlands
[2] Univ Amsterdam, Aquat Microbiol Inst Biodivers & Ecosyst Dynam, NL-1018 WS Amsterdam, Netherlands
[3] Natl Inst Coastal & Marine Management RIKZ, NL-4330 EA Middelburg, Netherlands
关键词
Phaeocystis; Phytoplankton; Modelling; Fuzzy logic; Eutrophication; Algal blooms; Netherlands; North Sea; Latitude; 52; 5; Longitude; 4; HARMFUL ALGAL BLOOMS; SOUTHERN NORTH-SEA; SPRING BLOOM; POUCHETII HAPTOPHYCEAE; PHYTOPLANKTON BLOOMS; ECOLOGICAL MODEL; GROWTH-RATE; LIFE-CYCLE; CHAOS; PRYMNESIOPHYCEAE;
D O I
10.1016/j.jmarsys.2010.05.003
中图分类号
P [天文学、地球科学];
学科分类号
070403 [天体物理学];
摘要
Phaeocystis globosa is a nuisance algal species because It can cause foam on beaches which are associated with coastal blooms Models of Phaeocystis have considered its bloom dynamics but not the foam formation The process of foam formation is poorly understood which limits the suitability of traditional deterministic model approaches We therefore applied fuzzy logic to simulate observed Phaeocystis bloom dynamics in coastal waters of the North Sea and foam formation on adjacent beaches Phaeocystts bloom initiation is estimated to occur when the mean mixed-layer daily irradiance exceeds circa 25 to 35 mu mol photons m(-2) s(-1) Peak bloom intensity was higher at monitoring stations with higher nutrient availability although bloom termination did not coincide with nutrient depletion Foam events occurred on Dutch beaches during and following Phaeocystis blooms when the wind direction was landward Over the period 2003-2007 90% of observed foam events were correctly predicted by the model however there were many false positives The fuzzy logic approach proved helpful in screening and adjusting hypotheses on the dynamics of Phaeocystis and associated foam events The resulting model communicates current understanding of foam formation enhances the predictability of these events and provides a basis for more detailed modelling efforts (C) 2010 Elsevier BV All rights reserved
引用
收藏
页码:115 / 126
页数:12
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