Wednesday, September 1, 2010

The accuracy needed

The literature on biodiversity conservation is replete with papers examining how effective individual taxa are at predicting overall patterns of biodiversity. There is a temptation to conclude from these studies that they represent only a subset of possible outcomes ... a cynic would say its highly likely that if an author's favorite taxon turns out to not be an efficient indicator the paper doesn't get submitted. But I digress.

Yael Mandelik and colleagues published a paper recently estimating the cost-efficiency of different indicator taxa for predicting patterns of biodiversity in Mediterranean ecosystems (Journal of Applied Ecology doi: 10.1111/j.1365-2664.2010.01864.x). Their primary data came from a large survey in Israel that included plants, ground dwelling beetles, moths, spiders and small mammals. (wait a second - no birds?!! what gives ...) They did a really nice job of explaining their methods, and one figure in particular is really useful - a "cost frontier" that plots the ecological efficiency of an indicator or set of indicators vs the cost of sampling that indicator. A cost frontier is a line joining all of the points with highest ecological efficiency for a given cost. Combinations of indicators that are below the frontier are inefficient in that they are not generating adequate ecological efficiency for their cost.
They go on to say:
In our study, plants were the cheapest cost-efficient indicator for richness and composition patterns. However, the marginal costs of representing the additional c. 30%of diversity variation are high, requiring c. 9 times the initial budget. Thus, the accuracy needed is a main factor in determining the budget requirements of biodiversity surveys. [emphasis added]
This is the key point - how accurate the prediction has to be depends on the decision being made and the objectives of the decision makers. It might be perfectly adequate to have an R^2 of 0.7 for species composition predictions. This is why it is essential to ask who is making the decisions, and what decisions is a given scientific analysis supposed to support?

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