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Common patterns of functional and biotic indices in response to multiple stressors in marine harbours ecosystems.
Environmental Pollution ( IF 8.9 ) Pub Date : 2020-01-09 , DOI: 10.1016/j.envpol.2020.113959
Michela D'Alessandro 1 , Erika M D Porporato 2 , Valentina Esposito 3 , Salvatore Giacobbe 4 , Alain Deidun 5 , Federica Nasi 3 , Larissa Ferrante 3 , Rocco Auriemma 3 , Daniela Berto 6 , Monia Renzi 7 , Gianfranco Scotti 1 , Pierpaolo Consoli 8 , Paola Del Negro 3 , Franco Andaloro 8 , Teresa Romeo 9
Affiliation  

Evaluating the effects of anthropogenic pressure on the marine environment is one of the focal objectives in identifying strategies for its use, conservation and restoration. In this paper, we assessed the effects of chemical pollutants, grain size and plastic litter on functional traits, biodiversity and biotic indices. The study was conducted on the benthic communities of three harbours in the central Mediterranean Sea: Malta, Augusta and Syracuse, subjected to different levels of anthropogenic stress (high, medium and low, respectively). Six traits were considered, subdivided into 22 categories: reproductive frequency, environmental position, mobility, life habit, feeding habit and bioturbation. Functional diversity indices analysed were: Functional Divergence, Quadratic Entropy, Functional Evenness and Functional Richness. To assess the trait responses to environmental gradients, we applied RLQ analysis, which considers simultaneously the relationship between three components: environmental data (R), species abundances (L) and species traits (Q). From our analyses, significant relationships (P-value = 0.0018 for permutation of samples and P-value = 0.00027 for permutation of species) between functional traits and environmental data were highlighted. The trait categories significantly influenced by environmental variables were those representing feeding habits and mobility. In particular, the first category was influenced by chemical pollutants (organotin compounds and polycyclic aromatic hydrocarbons) and grain size (silt and sand), while the latter category was influenced only by chemical pollutants.

Pearson correlations performed for functional vs biotic and diversity indices confirmed the validity of the chosen conceptual framework for harbour environments. Finally, linear models assessing the influence of stressors on functional parameters underlined the link between environmental data vs benthic and functional indices. Our results highlight the fact that functional trait analysis provides a useful and fast method for detecting in greater depth the effects of multiple stressors on functional diversity in marine ecosystems.



中文翻译:

海洋港口生态系统中应对多种压力的功能和生物指标的常见模式。

评估人为压力对海洋环境的影响是确定其使用,保护和恢复策略的重点目标之一。在本文中,我们评估了化学污染物,粒度和塑料垃圾对功能性状,生物多样性和生物指标的影响。该研究是在地中海中部三个港口的底栖生物群落上进行的:马耳他,奥古斯塔和锡拉库扎,它们受到不同程度的人为压力(分别为高,中和低)。考虑了六个特征,分为22个类别:生殖频率,环境位置,活动性,生活习惯,进食习惯和生物扰动。分析的功能多样性指数为:功能散度,二次熵,功能均匀度和功能丰富度。为了评估性状对环境梯度的响应,我们应用了RLQ分析,该分析同时考虑了三个组成部分之间的关​​系:环境数据(R),物种丰富度(L)和物种特征(Q)。根据我们的分析,突出了功能性状与环境数据之间的显着关系(样本排列的P值= 0.0018,物种排列的P值= 0.00027)。受环境变量影响显着的特征类别是代表进食习惯和活动能力的特征类别。特别是,第一类受化学污染物(有机锡化合物和多环芳烃)和粒度(粉砂和沙粒)的影响,而后一类仅受化学污染物的影响。同时考虑了三个组成部分之间的关​​系:环境数据(R),物种丰富度(L)和物种特征(Q)。根据我们的分析,突出了功能性状与环境数据之间的显着关系(样本排列的P值= 0.0018,物种排列的P值= 0.00027)。受环境变量影响显着的特征类别是代表进食习惯和活动能力的特征类别。特别是,第一类受化学污染物(有机锡化合物和多环芳烃)和粒度(粉砂和沙粒)的影响,而后一类仅受化学污染物的影响。同时考虑了三个组成部分之间的关​​系:环境数据(R),物种丰富度(L)和物种特征(Q)。根据我们的分析,突出了功能性状与环境数据之间的显着关系(样本排列的P值= 0.0018,物种排列的P值= 0.00027)。受环境变量影响显着的特征类别是代表进食习惯和活动能力的特征类别。特别是,第一类受化学污染物(有机锡化合物和多环芳烃)和粒度(粉砂和沙粒)的影响,而后一类仅受化学污染物的影响。根据我们的分析,突出了功能性状与环境数据之间的显着关系(样本排列的P值= 0.0018,物种排列的P值= 0.00027)。受环境变量影响显着的特征类别是代表进食习惯和活动能力的特征类别。特别是,第一类受化学污染物(有机锡化合物和多环芳烃)和粒度(粉砂和沙粒)的影响,而后一类仅受化学污染物的影响。根据我们的分析,突出了功能性状与环境数据之间的显着关系(样本排列的P值= 0.0018,物种排列的P值= 0.00027)。受环境变量影响显着的特征类别是代表进食习惯和活动能力的特征类别。特别是,第一类受化学污染物(有机锡化合物和多环芳烃)和粒度(粉砂和沙粒)的影响,而后一类仅受化学污染物的影响。受环境变量影响显着的特征类别是代表进食习惯和活动能力的特征类别。特别是,第一类受化学污染物(有机锡化合物和多环芳烃)和粒度(粉砂和沙粒)的影响,而后一类仅受化学污染物的影响。受环境变量影响显着的特征类别是代表进食习惯和活动能力的特征类别。特别是,第一类受化学污染物(有机锡化合物和多环芳烃)和粒度(粉砂和沙粒)的影响,而后一类仅受化学污染物的影响。

用于功能进行皮尔森相关性VS生物和多样性指数证实港口环境所选择的概念框架的有效性。最后,评估应激源对功能参数影响的线性模型强调了环境数据底栖生物和功能指数之间的联系。我们的结果强调了一个事实,即功能性状分析提供了一种有用且快速的方法,可以更深入地检测多种压力源对海洋生态系统功能多样性的影响。

更新日期:2020-01-09
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