物种在很大程度上是多余的吗?测试越来越复杂的基于特征的分类在理解加拿大北极生态系统方面的可靠性

G. Y. Haage
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引用次数: 0

摘要

背景:近年来,一些生态学家提倡使用功能群来代替直接的物种来连接站点组成与环境。它们有可能揭示遥远地点之间的联系,并有助于形成广泛适用的环境政策。一些研究比较了使用功能群的效率,其中物种根据功能特征分组,如喂养方法或大小,与直接使用物种。然而,与物种数据相比,很少有人关注改变官能团复杂性的影响。这项研究比较了不同复杂性的功能群类别,复杂性定义为考虑的特征数量,与物种数据。假设更复杂的官能团类,与不太复杂的类相比,倾向于接近使用分类法时获得的结果,这是检验。方法:为了验证这一假设,本研究使用了加拿大北极地区水生(底栖)生态系统的现场组成数据。四个功能特征被认为是描述这些物种的重要特征:生物扰动(沉积物扰动)、体型、摄食习性和流动性。这些性状被用来将物种划分为不同复杂程度的功能群,复杂程度取决于所使用性状的数量(共4个)。每个站点考虑了四个环境特征:叶绿素a、色素、深度和盐度。为了测试功能群数据与物种数据的相似程度,我们试图确定相同的环境变量在解释站点组成时是否重要。这是由BIO-ENV分析和Spearman Rank相关性确定的。然后,曼特尔排列测试确定相关性是否显著。结果:从1个到4个功能性状的复杂性水平与环境变量之间存在显著的相关性(Spearman Rank≥0.5,p≤0.05),但功能群复杂性与分类数据的相似性不存在普遍趋势。对于存在/缺失数据,所有的功能结果,无论复杂性如何,都只确定了色素是重要的,而存在/缺失物种数据还包括叶绿素a和深度。无论数据类型或复杂程度如何,所有结果都具有强而显著的相关性(r≥0.5 p≤0.05),维持了食物供应(叶绿素a或色素)的测量,表明其在确定这些地点的生态系统组成中的重要性。局限性:潜在的改进包括直接测量生物体的性状,考虑更多的环境变量和增加所考虑的功能性状的数量。每个研究考虑的特征也各不相同。结论:该假设未被结果证实。在确定最复杂的功能群类(最重要的变量)而不是不太复杂的类时,不能保证所选的变量与物种数据相同。一些复杂性较低的分类与完整的物种数据显示出更大的相似性。一些结果,如存在/不存在结果,也意味着生态系统中某些物种冗余,特别是在深度方面。这些结果对生态系统中功能冗余的概念产生了影响,这是制定广泛适用的环境政策的一个关键点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Are species largely redundant? Testing the reliability of increasingly complex trait-based classifications in understanding Canadian Arctic ecosystems
Background: In recent years, some ecologists have advocated the use of functional groups instead of direct species in linking site composition to the environment. They could potentially reveal connections between distant sites and aid in the formation of widely-applicable environmental policies. Several studies have compared the efficiency of using functional groups, in which species are grouped based on functional traits, like feeding method or size, to using species directly. However, few have looked at the effect of varying the complexity of functional groups when compared to species data. This study compares functional group classes of varying complexity, with complexity defined as the number of traits considered, to species data. The hypothesis that more complex functional group classes, compared to less complex classes, tend to approach the results obtained when using taxonomy, is tested. Methods: In testing this hypothesis, this study uses site composition data from aquatic floor (benthic) ecosystems in the Canadian Arctic. Four functional traits were considered important to describe these species: Bioturbation (sediment disturbance), body size, feeding habit and mobility. These traits were used to segregate species into functional groups of varying complexity, with complexity level determined by the number of traits (out of four) being used. Four environmental characteristics were considered for each site: Chlorophyll a, phaeopigments, depth and salinity. In order to test how similar functional group data is to species data, we sought to determine whether the same environmental variables were important in explaining site composition. This was determined by BIO-ENV analyses and Spearman Rank correlations. Mantel permutation tests then determined whether the correlations were significant. Results: While all levels of complexity, from one to four functional traits, showed some significant correlations (Spearman Rank ≥0.5, p≤ 0.05) between site composition and environmental variables, there was no general trend suggesting functional group complexity correlates with greater similarity to taxonomic data. For presence/absence data, all functional results, regardless of complexity, pinpointed only phaeopigments as important, while presence/absence species data also included chlorophyll a and depth. All results with strong and significant correlations (r≥0.5 p≤ 0.05), regardless of data type or complexity, maintained a measure of food supply (Chlorophyll a or phaeopigments), demonstrating its importance in determining ecosystem composition at these sites. Limitations: Potential improvements include measuring traits directly from the organisms, considering more environmental variables and increasing the number of functional traits considered. Which traits are considered also vary with each study. Conclusions: The hypothesis was not validated by the results. When pinpointing the most complex functional group class (the most important variable), rather than a less complex class, it was not guaranteed that the chosen variables would be the same as species data. Some classes of less complexity showed greater similarity to full species data. Some outcomes, like the presence/absence results, also imply certain species redundancies in the ecosystem, particularly regarding depth. These results have implications for the concept of functional redundancies in ecosystems, an important point in developing widely applicable environmental policies.
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