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Ecosystem ecology: size-based constraints on the pyramids of life
pmid: 23623003
Biomass distribution and energy flow in ecosystems are traditionally described with trophic pyramids, and increasingly with size spectra, particularly in aquatic ecosystems. Here, we show that these methods are equivalent and interchangeable representations of the same information. Although pyramids are visually intuitive, explicitly linking them to size spectra connects pyramids to metabolic and size-based theory, and illuminates size-based constraints on pyramid shape. We show that bottom-heavy pyramids should predominate in the real world, whereas top-heavy pyramids indicate overestimation of predator abundance or energy subsidies. Making the link to ecological pyramids establishes size spectra as a central concept in ecosystem ecology, and provides a powerful framework both for understanding baseline expectations of community structure and for evaluating future scenarios under climate change and exploitation.
- Simon Fraser University Canada
- University of Victoria Canada
- University of Victoria Canada
Conservation of Natural Resources, Food Chain, Ecology, Climate Change, Models, Biological, Body Size, Humans, Biomass, Ecosystem
Conservation of Natural Resources, Food Chain, Ecology, Climate Change, Models, Biological, Body Size, Humans, Biomass, Ecosystem
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).309 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
