95th ESA Annual Meeting (August 1 -- 6, 2010)

COS 63-1 - Quantifying size and shape of lakes – advances in, and comparisons of approaches

Wednesday, August 4, 2010: 1:30 PM
330, David L Lawrence Convention Center
Jae-Woo Kim and Donald A. Jackson, Ecology & Evolutionary Biology, University of Toronto, Toronto, ON, Canada
Background/Question/Methods

Lake morphology is an important component of lake community structure and function. It may influence various environmental variables within a lake such as primary and secondary productivity, mixing depth, and surface-water temperature which are closely associated with thermal habitat, winterkill, and hypolimnetic suitability of a lake. To quantify size and shape of a lake, traditional studies have used simple indices such as surface area, perimeter, maximum and mean depth, fetch, and shoreline development index. However, in recent years, many theoretical and technical advances have been made in the field of landscape ecology, particularly in terrestrial systems, through the use of GIS (Geographic Information System). In this study, we compared various approaches used in terrestrial landscape and aquatic ecology to quantify the size and shape of Ontario lakes. We selected a series of lakes (varying shape complexity) which we scaled to five size classes (50, 100, 500, 1000, and 5000 hectares) and compared these lakes along both the size and shape gradients by examining traditional measures, as well as incorporating methods drawn from terrestrial landscape ecology. We contrasted the different approaches through a multivariate analysis (e.g. principal component analysis) to classify the various measures into groups of metrics.

Results/Conclusions

Principal component analysis revealed that most of underlying variation was summarized by the first two axes. Principal component 1 has a strong association with indices related to size aspect of lakes such as surface area, perimeter, and fetch whereas principal component 2 has a strong association with indices related to shape aspect of lakes such as shoreline development index and fractal dimension index. When we incorporated the islands within lakes into the dataset, PCA result still showed that most of underlying variation was explained by the first two axes. However, relationships among parameters changed. While both principal component 1 and 2 still have a strong association with indices related to size and shape aspect of lakes, respectively, simply incorporating islands’ area and perimeter into lake morphology greatly influences the relationship among indices of lake morphology. This study suggests that various approaches from landscape ecology may be quite useful in addressing questions in aquatic ecology and limnology. Advances in landscape ecology may complement approaches in aquatic ecology, and vice-versa through communication and collaboration between disciplines.