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Relationships between lake macrophyte cover and lake and landscape features

机译:湖泊植物区系覆盖度与湖泊景观特征的关系

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We examined the ability of lake and landscape features to predict a variety of macrophyte cover metrics using 54 north temperate lakes. We quantified submersed cover, emergent cover, floating leaf cover, Eurasian watermilfoil cover and total macrophyte cover. Measured lake features included lake physio-chemical and morphometric variables and landscape features included hydrologic, catchment and land use/cover variables. Univariate regression analyses demonstrated that these macrophyte cover metrics are predicted by a wide range of predictor variables, most commonly by: Secchi disk depth, maximum or mean depth, catchment morphometry, road density and the proportion of urban or agricultural land use/cover in the riparian zone or catchment (r(2) = 0.06-0.46). Using a combination of lake and landscape features in multiple regressions, we were able to explain 29-55% of the variation in macrophyte cover metrics. Total macrophyte cover and submersed cover were related to Secchi disk depth and mean depth, whereas the remaining metrics were best predicted by including at least one land use/cover variable (road density, proportion local catchment agriculture land use/cover, proportion cumulative catchment urban land use/cover, or proportion riparian agriculture land use/cover). The two main conclusions from our research are: (1) that different macrophyte growth forms and species are predicted by a different suite of variables and thus should be examined separately, and (2) that anthropogenic landscape features may override patterns in natural landscape or local features and are important in predicting present-day macrophytes in lakes. (c) 2007 Elsevier B.V. All rights reserved.
机译:我们检查了湖泊和景观特征使用54个北部温带湖泊预测各种大型植物覆盖率的能力。我们量化了潜水覆盖物,紧急覆盖物,浮叶覆盖物,欧亚水草覆盖物和大型植物覆盖物。所测量的湖泊特征包括湖泊的理化和形态计量变量,景观特征包括水文,集水区和土地利用/覆盖变量。单变量回归分析表明,这些大型植物的覆盖度指标可通过多种预测变量进行预测,最常见的预测方法包括:底盘深度,最大或平均深度,流域形态,道路密度以及城市或农业土地利用/覆盖面积的比例。河岸带或流域(r(2)= 0.06-0.46)。在多个回归中使用湖泊和景观特征的组合,我们能够解释大型植物覆盖率指标的29-55%的变化。大型植物的总覆盖度和潜水覆盖度与Secchi盘深度和平均深度有关,而其余指标最好通过包括至少一个土地利用/覆盖变量(道路密度,当地集水区农业土地利用/覆盖比例,城市累计集水比例)来预测土地利用/覆盖或河岸农业土地利用/覆盖的比例)。我们研究的两个主要结论是:(1)不同的大型植物的生长形式和物种是由不同的变量集预测的,因此应分别进行研究;(2)人为的景观特征可能会覆盖自然景观或局部地区的格局。特征和对预测当今湖泊中的大型植物很重要。 (c)2007 Elsevier B.V.保留所有权利。

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