Promise and problems in applying quantitative complementary areas for representing the diversity of some Neotropical plants (families Dichapetalaceae, Lecythidaceae, Caryocaraceae, Chrysobalanaceae and Proteaceae)

Abstract

Priority areas for in situ conservation are an unavoidable consequence of competition with other land uses, although they are certainly not to be seen as the only areas of value for conservation. In 1990 an international workshop was convened in Manaus, Brazil, to identify priority areas within Amazonia by committee (Workshop-90). A substantial part of the data for this assessment came from five plant families recorded for the Flora Neotropica . We compare the success of the Workshop-90 method in representing these plant species with the results of using a simple quantitative method for seeking complementary areas. The promises of quantitative methods are twofold. First, they force people to make their values explicit, which is important because priorities are dependent on the values and goals of individuals and are not universal. Second, quantitative methods can achieve representation of more of what is valued. For example, within the 90 top-priority areas (an arbitrary but convenient figure taken from Workshop-90), species representation is shown to be increased when using the complementary areas method by 83%. Simple computer implementations of this method can provide the means for fast inter-active exploration of flexibility in the many alternative area choices. This permits monitoring and review with minimum effort as new data on species and threats are acquired. On the other hand, the problem for all methods is the need for very large numbers of data, whether based on species or on any other surrogates for biodiversity, if well-informed decisions are to be made. This is not a particular problem of quantitative methods, but their explicit nature does highlight the shortcomings of data. For example, patterns in the Flora Neotropica data show effects from small samples even though these data are among the best available for any large tropical wet-forest region. Furthermore, in order to assess the longer-term consequences of area choices, quantitative methods will require many explicit local data on factors affecting viability, threat and cost.