Magazine article Natural History

Circles in the Sand

Magazine article Natural History

Circles in the Sand

Article excerpt

In the interior of the Namib Desert, millions of barren sand patches look like abandoned dohyO, or sumo wrestling rings. They range in diameter from 12 feet in the southern part of the desert-which runs 1,200 miles on Africa's Atlantic coast-to 114 feet in the north. The gaps, which are defined by a rim of grass, are known as fairy circles, because the cause of their formation has been undetermined, despite considerable study and speculation.

One theory-the self-organization hypothesis-posits that, based on competition for water resources, belts of vegetation optimize water usage and create bare areas inside their circles. Once formed, these patches act as catch basins that plants along the edges can access during dry seasons. Eroded sediment from the bare patches collects at the outer vegetated ridges. The root systems of these plants absorb the diffused water, thereby inhibiting plant growth beyond the rings, where moisture is limited. This interplay between plants and available water creates a closed loop that perpetuates the average life of these circles for more than forty years. Then, the circles die off for equally unknown reasons.

Another popular hypothesis suggests that social insects-specifically, the sand termite, Psammotermes allocerus-are the cause. Sand termites are known to create homes in arid locations and may be involved here in ecological engineering. They build where soil moisture is most reliable based on soil properties. They then clear and maintain bare patches by herbivory and chemical inhibitors and store water under the bare patches, thus creating a closed loop, not dissimilar to the one described in the self-organization hypothesis.

Proponents of each theory are passionate in their defense. Subscribers to the social insect theory have spent nearly a decade collecting data in the field. The self-organization theorists have created several mathematical models that predict large-scale patterns, based on data from small-scale plant-soil-water interactions. …

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