Academic journal article Cartography and Geographic Information Science

Landscape Controls over Major Nutrients and Primary Productivity of Arctic Lakes

Academic journal article Cartography and Geographic Information Science

Landscape Controls over Major Nutrients and Primary Productivity of Arctic Lakes

Article excerpt

Introduction

Changing climatic factors are altering Arctic landscapes, affecting the dynamics between the landscapes and the lakes located within them (Schindler and Smol 2006). One of the major climatic factors researchers have documented over the last three decades is an increase of 3.5[degrees]C in surface temperature (IPCC, AR4, Synthesis report: 32), a trend expected to continue in the near future. Warming temperatures are causing permafrost to melt, which induces more frequent thermokarst activities (Serreze et al. 2000). Scientists expect the cumulative effect of these activities will be the release of nutrients, including compounds of nitrogen, phosphorus and various ions, into streams and lakes (Keller et al. 2007). With changes in the nature of the influx, oligotrophic Arctic lakes may increase their primary productivity.

Recent research, particularly in the disciplines of biology and ecology, has provided a foundation for studying nutrient modeling as it relates to ecosystems in the Arctic. What is largely missing, however, is a spatial perspective, which we argue could be provided by employing satellite imagery and landscape metrics. Marion et al. (1989), for example, conducted a study of the tundra ecosystem and observed variations within major nutrients (nitrogen and phosphorus), along with potassium, calcium and magnesium in soils supporting different vegetation communities. In a similar study, Chapin and Shaver (1988) inferred that water in the soil played a significant role in cycling nutrients within vegetation communities. Moreover, water tracks within the watershed aided nutrient transfer. Besides the water content of soil, they also found temperature and active soil depth to be important factors in the mineralization process of nutrients within forbs and graminiods.

Focusing on biogeochemical diversity in the Arctic, Giblin et al. (1991) demonstrated that the uptake rate for nutrients by vegetation species partially controlled extractable nutrient levels in the surrounding soil. These researchers also studied vegetation land cover to understand how the characteristic root structures of different vegetation species interacted with soil horizons. They found that certain dominant species, such as Eriophorum vaginatum, could intercept more nutrients due to deep root structure; other species, however, such as Ledum decumbuns, relied on the upper organic layer of the soil for their nitrogen and phosphorus supply. Recently, a more comprehensive study by Keller et al. (2007) examined geochemical weathering and its effects on soils and streams in the Arctic. They found that the weathering rate of parent material caused a higher concentration of nutrients to reach surface waters. The rate of weathering was related to both glacial age and active soil depth. Nutrient modeling studies of the Arctic may largely fail to address spatial context issues, but there are studies outside the region that have used spatial techniques to analyze the contribution of land surface processes towards surface water chemistry (King et al. 2005; Allan and Johnson 1997; Griffith et al. 2002). Percentages (Gergel et al. 2002), proportion metrics, and fragmentation metrics of prominent land cover types, such as agriculture or riparian vegetation (Jones, et al. 2001) were all found useful in predicting water quality in this body of work. These studies also highlighted that the structural arrangement of land cover in the immediate vicinity of water channels played a significant role in allowing nutrients to, or restraining nutrients from, entering surface waters.

The purpose of this study was to incorporate a spatial perspective, via landscape metrics, to the study of nutrient modeling in the Arctic. Using landscape metrics as a means of describing the spatial and structural properties of land cover, we assessed how well the metrics predicted lake primary productivity and major nutrient concentrations in Arctic lakes. …

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