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Dryad

Abundance and richness of biota and soil properties across successive soil ages since glacial recession

Cite this dataset

Pothula, Satyendra; Adams, Byron (2022). Abundance and richness of biota and soil properties across successive soil ages since glacial recession [Dataset]. Dryad. https://doi.org/10.5061/dryad.stqjq2c6d

Abstract

Ecosystems shaped by retreating glaciers provide a unique opportunity to study the order and timing of biotic colonization, and how this influences the structure of successive ecological communities. In the last century glaciers across most of the cryosphere have receded at an unprecedented pace. Many studies have been published from different parts of the world testing hypotheses about how soil ecosystems are responding to rapid, contemporary deglaciation events. To better understand and draw general conclusions about how soil ecosystems respond to deglaciation, we conducted a global meta-analysis of 95 published articles focused on the succession of various organisms and soil physicochemical properties in glacier forefields along the chronosequence. Our global synthesis reveals that key soil properties and the abundance and richness of biota follow two conspicuous patterns: 1) Some taxa demonstrate a persistent increase in abundance and richness over the entire chronosequence, 2) other taxa increase in abundance and richness during the first 50 years of succession, then gradually decline 50 years onward. The soil properties and soil organisms that are intimately tied to vegetation follow the first pattern, consistent with the idea that aboveground patterns of vegetation can drive patterns of belowground biodiversity. The second pattern may be due to an initial increase and subsequent decline in available nutrients and habitat suitability caused by increased biotic interactions, including resource competition among soil biota. A consensus view of the patterns of historical and contemporary soil ecosystem responses to deglaciation provides a better understanding of the processes that generate these patterns and informs predictions of ongoing and future responses to environmental changes. 

Funding

National Science Foundation of Sri Lanka, Award: OPP-1637708