Crustacean Zooplankton Species Richness in 66 North American Lakes

Data from 66 North American lakes were collected to construct a model for predicting the number of crustacean zooplankton species expected in a lake. The chosen lakes have a range from 4 sq m to 80 x 10**9 sq m surface area, range from ultra-oligotrophic to hypereutrophic, and have zooplankton species lists based of several years of observation The number of crustacean zooplankton species in a lake is significantly correlated with lake size, average rate of photosynthesis (parabolic function) and the number of lakes within 20 km. A multiple linear regression model, using these three independent variables, explains approximately 75% of the variation in log species richness. Prediction of species richness is not enhanced by the knowledge of lake depth, salinity, elevation, latitude, longitude, or distance to nearest lake. The North American species area curve is statistically different from and steeper than the corresponding European curve. Number of sites: 69

本研究采集了北美66个湖泊的相关数据，以构建用于预测湖泊中甲壳类浮游动物（crustacean zooplankton）物种数的模型。所选湖泊的表面积范围为4平方米至80×10^9平方米，营养状态覆盖从超贫营养（ultra-oligotrophic）到超富营养（hypereutrophic）的梯度，其浮游动物物种名录基于多年观测建立。湖泊内甲壳类浮游动物的物种数与湖泊面积、平均光合速率（呈抛物线函数关系）以及20公里范围内的湖泊数量均存在显著相关性。采用上述三个自变量构建的多元线性回归模型，可解释约75%的物种丰富度对数的变异量。即便加入湖泊深度、盐度、海拔、纬度、经度或到最近湖泊的距离等变量，也无法提升该物种丰富度的预测精度。北美物种-面积曲线在统计学上与欧洲对应曲线存在显著差异，且斜率更陡峭。本数据集共包含69个采样位点。