Abstract
Glacier and ice sheet surfaces are important microbe-dominated ecosystems that are changing rapidly due to climate change, with potentially significant impacts. A theoretical framework of the supraglacial (glacier surface) ecosystem is needed to enable its mathematical modelling, a necessary tool for understanding, quantifying and predicting present day and future ecosystem dynamics. Here we review key biological processes occurring on glacier and ice sheet surfaces and present three frameworks for constructing process-based models of the surface ecosystem, using the largest supraglacial ecosystem on Earth – the Greenland ice sheet surface – as an important example. The models are based on organic carbon transformations, but vary in numerical complexity and in the level of detail of biological processes. This perspective is intended to guide future supraglacial ecosystem model development, field data collection for parameterisation and validation purposes, and encourage inter-disciplinary collaboration between modellers and experimentalists.
Highlights
Glaciers and ice sheets currently cover ∼10% of the surface of continents and contain >30 million km3 of ice
Estimates of microbial activity and associated carbon and nutrient transformations on a large scale are highly uncertain, and predictions of future ecosystem change are virtually impossible. The aim of this perspective paper is to provide a theoretical framework of the supraglacial ecosystem in order to facilitate ecological modeling as a tool for understanding present day and future ecosystem dynamics
We focus on the largest supraglacial ecosystem on Earth—the Greenland ice sheet (GrIS) surface—as an important example and present three conceptual models of the GrIS microbial ecosystem
Summary
Glaciers and ice sheets currently cover ∼10% of the surface of continents and contain >30 million km of ice. Estimates of microbial activity and associated carbon and nutrient transformations on a large scale are highly uncertain, and predictions of future ecosystem change are virtually impossible. The aim of this perspective paper is to provide a theoretical framework of the supraglacial ecosystem in order to facilitate ecological modeling as a tool for understanding present day and future ecosystem dynamics. We discuss the strengths and weaknesses of each modeling approach, their role in improving the understanding of carbon cycling and ecosystem dynamics, and the necessary integration of these modeling approaches with field data to parameterize and validate numerical output This perspective is intended to guide future supraglacial ecosystem model development and field data collection, and encourage cross-disciplinary collaboration between modelers and experimentalists
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