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BookmarkScienceDaily (Feb. 9, 2001) — Feb. 1, 2001 -- A new study has found that the traditional method used to study ecological relationships between species numbers and land area is flawed. These findings will have a significant impact in the developing world where diversity is higher, but the flora and fauna less well known.
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Widely used in conservation studies and one of the best-documented patterns in ecology, a power law is used to determine the relationship between the number of plant species and land area - without actually surveying all of the land being studied.
It was believed that the relationship between species richness and land area was scale-invariant; the logarithm of the number of species was supposed to increase as a constant multiple of the increase in log area. However, a new study by Imperial College scientists, published in the journal Science today, shows that this is not the case.
Professor Mick Crawley and Josie Harral of the Department of Biology surveyed plots of land in Berkshire, UK, ranging in size from one-hundredth of a metre squared to 100 kilometres squared (km2). They found that the power value changed systematically with area. At small scales, where individual plants interact with one another, species accumulated relatively slowly. Likewise at large scales (more than 100 km2) species accumulated with area relatively slowly. It was at intermediate scales (from hectares to 10 km2) that species richness accumulated most rapidly as the size of the area sampled was increased.
Professor Mick Crawley comments: “What our work shows is that you can not predict species richness at a large scale from survey work carried out (cheaply) at a small scale. Since the flora and fauna of Britain is so well known this is of less practical importance, but in the third world it is a big deal.
“We have shown that the relationship between plant species-richness and land area surveyed is not constant as formerly believed. The problem is we don't yet know how the relationship changes with scale in other parts of the world. So prediction remains very difficult,” he said.
