Adding value to a proposed biodiversity “Barometer of Life”
How can we come up with a global report card for overall biodiversity when so many species are still unknown to science?
A proposed global biodiversity “Barometer” or “Barometer of Life”” (Brummitt et al 2008; Baillie et al 2008; Stuart et al. 2010) will assess extinction risk values for a subset of species designed to be broadly representative of biodiversity as a whole. The assessment is based on Red List criteria, including assessments of change in geographic range. This extension to a representative set of species (forming a sampled red list index or ”SRLI”) can provide a much-needed, ongoing, report card about the status of overall biodiversity.
This representative sample of species, and the accompanying information on geographic range extent from SRLI assessments, could have other important benefits as well. The GEO Biodiversity Observation Network (GEO BON) will explore some ways to constructively build on this strategy. One of the biggest challenges for GEO BON is to facilitate monitoring of genetic diversity for many different species. One proposed broad-brush approach will attempt to assess the general loss of genetic diversity, using models that link loss of geographic range extent for a given species to its loss of genetic diversity. The ongoing monitoring of range extent for the representative species in a Barometer of Life therefore also could provide a basis for this proposed genetic diversity report card.
Information for a representative set of species also would serve GEO BON’s needs for effective surrogates for overall biodiversity. One GEO BON strategy (see Andrefouet et al. 2008) is to promote biodiversity surrogates models using available species data, integrated with environmental layers. The link to environmental descriptors allows biodiversity predictions to be made for any locality in a given region (Ferrier et al. 2007). Calculations based on the models then may provide useful outputs for monitoring and decision-making – estimating gains or losses in biodiversity when the condition or intactness of a given locality changes. GEO BON will use ongoing observations of changes in land/water condition (for example, through remote sensing), and interpret these through the “lens” provided by such spatial models of biodiversity. The Biodiversity Barometer could help with this strategy, because reliable information about the gains and losses for overall biodiversity depends on using a representative sample of species to help build the models.
Effective surrogates for overall biodiversity would provide an attractive alternative to the limited measures of biodiversity gains and losses often used in conservation planning studies (Faith et al. 2010). The Millennium Ecosystem Assessment (2005), in arguing for “surrogate information for general biodiversity patterns”, called for “a ‘calculus’ of biodiversity, so that gains and losses at the level of biodiversity option values can be quantified”. The set of representative species making up a Biodiversity Barometer could help to produce the calculus, or “Biodiversity Calculator”, that is needed to inform decisions in biodiversity conservation planning and to monitor biodiversity losses resulting from changes in condition of land/water localities.
see also published version of this essay: Faith, DP (2010) More Benefits from a Barometer of Life. Science Online, 24 Jun 2010
The recent Letters in Science, noting the huge effort required to collect data and build up trend information, in effect provide support for using the Barometer of Life to help implement the Lens approach.
Andrefouet S. et al. (2008) The GEO Biodiversity Observation Network: Concept Document. GEO – Group on Earth Observations, Geneva, Switzerland.
Baillie J. et al. (2008) Conservation Letters 1: 18–26.
Brummitt N. et al. (2008) Endang Species Res 6: 127–135.
Faith D.P. et al. (2010) Curr Opin Environ Sustain 2: 66-74.
Ferrier S. et al. (2007) Div Distrib 13: 252–264.
Millennium Ecosystem Assessment. (2005) Washington, DC: Island Press.
Stuart et al. (2010) Science 328:177.
Dr Dan Faith , Principal Research Scientist