Using large benthic macrofauna to refine and improve ecological indicators of bottom trawling disturbance
Using large benthic macrofauna to refine and improve ecological indicators of bottom trawling disturbance
复制标题
利用大型底栖动物细化和改善底拖网捕捞扰动的生态指标
DOI：
10.1016/j.ecolind.2019.105811
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发表时间：
2020
影响因子：
6.9
通讯作者：
G. Dinesen
中科院分区：
文献类型：
--
作者：
Ciarán McLaverty;O. R. Eigaard;H. Gislason;Francois Bastardie;Mollie E. Brooks;P. Jonsson;A. Lehmann;G. Dinesen
底拖网捕捞改变了底栖生物群落的丰度、多样性、大小组成和功能。然而，在大的空间尺度上检测这些影响的能力可能会被各种复杂的因素所掩盖，例如社区对干扰和共同变化的环境条件的适应。因此，基于生态系统的渔业管理方法需要生态指标，这些指标可以将拖网捕捞的影响与其他自然和人类驱动因素“分开”，并有效应对生态质量的变化。我们在卡特加特海峡的挪威龙虾Nephropsnorvegicus渔场的21个地点采集了大型底栖动物样品，并将底栖动物群落分为小（1-4 mm）和大（>4 mm）尺寸组。四个分类指标（总密度，物种密度，香农多样性，生物量）和四个功能指标（功能多样性，功能丰富度，功能均匀度，功能分散度）计算的基础上，每个大小部分，和两个馏分相结合（汇集社区）。在这里，我们比较这些指标的能力，以检测拖网捕捞影响的大小类别。我们表明，来自大型大型底栖动物的指标在这方面是非常有效的，并受其他环境驱动因素，如深度，沉积物粒度，底流速度，盐度和温度的影响较小。这表明，底栖生物群落的分类和功能特征显示出对拖网干扰的大小依赖性敏感性，因此，基于大型底栖动物的群落指标可能提供有用的指标。相比之下，来自小部分的指标表现不佳，而那些基于汇集的社区表现出不同的能力来检测拖网捕捞。小型大型底栖动物的典型特征是密度高、多样性大和种群增长率高，它们对拖网捕捞的相对适应能力可能掩盖了较敏感的大型底栖动物的反应。这突出说明了根据整个底栖生物群落计算指标的一个根本问题。这里概述的方法易于应用，提高了指标性能，并且由于分析所需的分类群和个体较少，有可能减少实验室工作量。
Bottom trawling alters the abundance, diversity, size-composition, and function of benthic communities. However, the ability to detect these impacts over large spatial scales can be obscured by various complicating factors, such as community adaptation to disturbance and co-varying environmental conditions. An ecosystem-based approach to fisheries management therefore requires ecological indicators which can ‘disentangle’ trawling effects from other natural and human drivers, and respond effectively to shifts in ecological quality. We collected benthic macrofaunal samples at 21 sites across a Norway lobsterNephrops norvegicusfishing ground in the Kattegat, and separated the benthic community into small (1–4 mm) and large (>4 mm) size fractions. Four taxonomic indicators (total density, species density, Shannon diversity, and biomass) and four functional indicators (functional diversity, functional richness, functional evenness, and functional dispersion) were calculated based on each size fraction, and the two fractions combined (pooled community). Here, we compare the ability of these indicators to detect trawling impacts across size categories. We show that indicators derived from large macrofauna were highly effective in this regard, and were less influenced by other environmental drivers, such as depth, sediment grain size, bottom current velocity, salinity, and temperature. This suggests that the taxonomic and functional characteristics of benthic communities display a size-dependent sensitivity to trawling disturbance, and therefore community metrics based on large benthic macrofauna may provide useful indicators. By contrast, indicators derived from the small fraction performed poorly, and those based on the pooled community demonstrated a varied ability to detect trawling. Small macrofauna are typically characterised by high density, diversity, and population growth rates, and their relative resilience to trawling may mask the response of the more sensitive macrofauna. This highlights an underlying issue with calculating indicators based on the whole benthic community. The approach outline here is easily applied, improves indicator performance, and has the potential to reduce laboratory workloads due to the fewer taxa and individuals required for analyses.