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首页> 外文期刊>Limnologica >How many seasons are there in a sub-tropical lake? A multivariate statistical approach to determine seasonality and its application to phytoplankton dynamics
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How many seasons are there in a sub-tropical lake? A multivariate statistical approach to determine seasonality and its application to phytoplankton dynamics

机译：亚热带湖泊有多少个季节？确定季节变化的多元统计方法及其在浮游植物动力学中的应用

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摘要

Seasonal patterns in factors that affect primary producers are an important part of defining the structure and function of aquatic ecosystems. However, defining seasonality is often more difficult in aquatic than in terrestrial ecosystems, particularly in subtropical and tropical environments. In this study, a long-term data set for a shallow subtropical lake (Lake George, Florida, USA) was used to investigate seasonality using a range of physical, chemical and hydrological parameters. K-means cluster analysis of monthly averages among 11 selected environmental factors across 18 years suggested the overall annual pattern consists of three different seasonal clusters: a cold season (January-April), a warm season (May-August) and a flushing season (September-December). High dissolved oxygen and increased Secchi depth are key features of the cold season, while the warm season is characterized by high mean light irradiances, temperature, rainfalls, total nitrogen and phytoplankton biomass (as chlorophyll a level). The flushing season is characterized by high river discharge rates and high levels of dissolved nutrients and colored organic matter. Multiple response permutation procedures indicated that these seasonal cluster arrangements were significantly different than randomly permuted clusters (A-statistics=0.3314, significance of delta = 0.0160, based on 1000 permutations). Results from principal component analyses supported the presence of the three seasons in the lake. Linear models explaining chlorophyll a levels using the 3-season system generally indicated better ratios of explained variance compared to the models without seasonal alignments, further indicating that even for sub-tropical systems defining seasons provides a better understanding of phytoplankton dynamics. The approaches used in this study provide statistically based multivariate tools for the definition of seasonality in aquatic ecosystems. The ability to accurately define seasons is a key step in modeling the structure and dynamics of aquatic ecosystem, which is essential to the development of effective management strategies in a rapidly changing world. (C) 2016 Elsevier GmbH. All rights reserved.
机译：影响初级生产者的因素中的季节性模式是确定水生生态系统结构和功能的重要组成部分。但是，在水生环境中确定季节性通常比在陆地生态系统中更为困难，特别是在亚热带和热带环境中。在这项研究中，使用了一个浅亚热带湖泊（美国佛罗里达州乔治湖）的长期数据集，使用一系列物理，化学和水文参数来调查季节性。用K均值聚类分析18年中11个选定环境因子的月平均值，表明总体年度模式由三个不同的季节聚类组成：寒冷季节（1月至4月），温暖季节（5月至8月）和潮红季节（ 9月-12月）。高溶解氧和增加的Secchi深度是寒冷季节的关键特征，而温暖季节的特征是平均光照强度，温度，降雨量，总氮和浮游植物生物量（以叶绿素a水平）较高。冲洗季节的特点是河流排泄率高，溶解的营养物和有色有机物含量高。多重响应排列程序表明，这些季节性群集排列与随机排列的群集明显不同（A统计量= 0.3314，显着性= 0.0160，基于1000个排列）。主成分分析的结果支持了湖中三个季节的存在。使用三季系统解释叶绿素a水平的线性模型通常表明，与没有季节性调整的模型相比，所解释方差的比率更好，进一步表明，即使对于定义季节的亚热带系统，也可以更好地理解浮游植物的动态。本研究中使用的方法为定义水生生态系统的季节性提供了基于统计的多元工具。准确定义季节的能力是对水生生态系统的结构和动力学进行建模的关键步骤，这对于在瞬息万变的世界中制定有效的管理策略至关重要。 （C）2016 Elsevier GmbH。版权所有。

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