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Spatial Relationships between Polychaete Assemblages and Environmental Variables over Broad Geographical Scales

机译:广泛地理尺度上多面体组合与环境变量之间的空间关系

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摘要

This study examined spatial relationships between rocky shore polychaete assemblages and environmental variables over broad geographical scales, using a database compiled within the Census of Marine Life NaGISA (Natural Geography In Shore Areas) research program. The database consisted of abundance measures of polychaetes classified at the genus and family levels for 74 and 93 sites, respectively, from nine geographic regions. We tested the general hypothesis that the set of environmental variables emerging as potentially important drivers of variation in polychaete assemblages depend on the spatial scale considered. Through Moran's eigenvector maps we indentified three submodels reflecting spatial relationships among sampling sites at intercontinental (>10000 km), continental (1000–5000 km) and regional (20–500 km) scales. Using redundancy analysis we found that most environmental variables contributed to explain a large and significant proportion of variation of the intercontinental submodel both for genera and families (54% and 53%, respectively). A subset of these variables, organic pollution, inorganic pollution, primary productivity and nutrient contamination was also significantly related to spatial variation at the continental scale, explaining 25% and 32% of the variance at the genus and family levels, respectively. These variables should therefore be preferably considered when forecasting large-scale spatial patterns of polychaete assemblages in relation to ongoing or predicted changes in environmental conditions. None of the variables considered in this study were significantly related to the regional submodel.
机译:这项研究使用海洋生物人口普查NaGISA(海岸自然地理)研究计划中汇编的数据库,在广泛的地理范围内研究了岩岸多毛小动物组合与环境变量之间的空间关系。该数据库由来自9个地理区域的74个和93个站点的多类多足动物按属和家庭级别分类的丰度度量组成。我们测试了一般的假设,即环境变量的集合作为多毛动物组合变化的潜在重要驱动因素而出现,取决于所考虑的空间尺度。通过Moran的特征向量图,我们确定了三个子模型,这些子模型反映了洲际(> 10000 km),大陆(1000-5000 km)和区域(20-500 km)尺度的采样点之间的空间关系。使用冗余分析,我们发现大多数环境变量都有助于解释属和家族的洲际子模型的很大一部分变化(分别为54%和53%)。这些变量的一部分,有机污染,无机污染,初级生产力和营养污染也与大陆尺度的空间变化显着相关,分别解释了属和家庭水平的25%和32%的变化。因此,在预测与环境状况的持续或预测变化有关的多毛动物组合的大规模空间格局时,应优先考虑这些变量。在这项研究中考虑的变量都没有与区域子模型显着相关。

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