Landscape Controls over Major Nutrients and Primary Productivity of Arctic Lakes

Abstract

Increasing surface temperatures in the Arctic are affecting the dynamics between lakes and their landscapes. In this paper, we use landscape metrics for land cover and statistical analysis to explore the interactions between such measures as shape and patch density indices for land cover and lake primary productivity. The objective was to identify metrics that could be used to predict lake primary productivity, as measured by chlorophyll a, total nitrogen and total phosphorus estimates. Land cover and landscape metrics for the Toolik region of Alaska were derived using satellite imagery and Fragstats software. The metrics, treated as independent variables in a stepwise regression, were derived for two levels of land cover. The first comprised the entire watershed studied; the second was derived using buffers created around water channels within each watershed. A statistically significant model for each dependent variable was obtained. Results suggest that, of the metrics tested; those related to broad leaf vegetation complexes were most useful in predicting lake primary productivity. The Landscape Shape Index for riparian patches and the Patch Density for heath complex were the two most important metrics for predicting variation in chlorophyll a (p<0.001, r2 = 0.52). For total nitrogen estimates, the most significant metrics were Percentage of riparian complex and Patch Density for fen complex (p<0.001, r2 = 0.48). Total phosphorus estimates were most influenced by the Patch Density for shrub complex, the Mean Shape Index for moist acidic tundra complex, and the Patch Density for aquatic vegetation (p<0.001, r2 = 0.52).