Relationships between lake macrophyte cover and lake and landscape features

被引:52
作者
Cheruvelil, Kendra Spence [1 ,2 ]
Soranno, Patricia A. [2 ]
机构
[1] Michigan State Univ, Lyman Briggs Sch Sci, E Lansing, MI 48825 USA
[2] Michigan State Univ, Dept Fisheries & Wildlife, E Lansing, MI 48824 USA
关键词
lake morphometry; physio-chemistry; land use/cover; catchment; hydrology; Eurasian watermilfoil;
D O I
10.1016/j.aquabot.2007.10.005
中图分类号
Q94 [植物学];
学科分类号
071001 [植物学];
摘要
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.
引用
收藏
页码:219 / 227
页数:9
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