Efficient plot-based floristic assessment of tropical forests

Abstract

Abstract:The tropical flora remains chronically understudied and the lack of floristic understanding hampers ecological research and its application for large-scale conservation planning. Given scarce resources and the scale of the challenge there is a need to maximize the efficiency of both sampling strategies and sampling units, yet there is little information on the relative efficiency of different approaches to floristic assessment in tropical forests. This paper is the first attempt to address this gap. We repeatedly sampled forests in two regions of Amazonia using the two most widely used plotbased protocols of floristic sampling, and compared their performance in terms of the quantity of floristic knowledge and ecological insight gained scaled to the field effort required. Specifically, the methods are assessed first in terms of the number of person-days required to complete each sample ('effort'), secondly by the total gain in the quantity of floristic information that each unit of effort provides ('crude inventory efficiency'), and thirdly in terms of the floristic information gained as a proportion of the target species pool ('proportional inventory efficiency'). Finally, we compare the methods in terms of their efficiency in identifying different ecological patterns within the data ('ecological efficiency') while controlling for effort. There are large and consistent differences in the performance of the two methods. The disparity is maintained even after accounting for regional and site-level variation in forest species richness, tree density and the number of field assistants. We interpret our results in the context of selecting the appropriate method for particular research purposes.

RAPELD: a modification of the Gentry method for biodiversity surveys in long-term ecological research sites

“…Os custos de implementação são moderados, considerando a grande produção gerada pelos estudos integrados. Phillips et al (2003) explained many of the advantages of 0.1 ha plots in comparison with 1 ha plots for floristic surveys, and lamented the fact that many of the 0.1 ha plots were not marked for long-term studies. Here we describe a modification of the 0.1 ha survey method developed by Gentry (1982) that we adapted for long-term ecological sites in the Brazilian Amazon.…”

“…Caughley & Sinclair 1994, Stern 1998, Magnusson & Mourão 2004. For ecological studies of plants, square 1 ha plots have limited utility because each plot potentially contains a huge range of soil conditions and topography, making it difficult to discern ecological relationships (Phillips et al 2003). Some researchers only place plots on relatively flat areas, but this results in a biased sample of the site.…”

“…However, there is much small-scale (1 -10 km) beta diversity in tropical forest vegetation, even within vegetation "types", such as terra firme forest (Clark et al 1999, Phillips et al 2003, Tuomisto & Ruokolainen 1994, Vormisto et al 2000, Tuomisto et al 2003. Therefore, the area sampled for inter-site comparisons needs to be large.…”

“…Small plots (1 -50 ha) capture a very small part of the species diversity of the site for many taxonomic groups. This is the principal reason that many 0.1 ha plots are so much more efficient to capture the site diversity than 1 ha plots with the same total area (Phillips et al 2003). For inter-site comparisons, we consider the plot system to represent a single compound plot consisting of many subplots.…”

The Need for Large-Scale, Integrated Studies of Biodiversity - the Experience of the Program for Biodiversity Research in Brazilian Amazonia

“…Even with biased positioning, it would not be possible to locate a 10 ha or larger plot on homogeneous soil. Even within vegetation "types", such as terra firme forest, there is much small-scale (1-10 km) beta diversity in tropical forest vegetation (Clark et al 1999;Phillips et al 2003;Tuomisto and Ruokolainen 1994;Tuomisto et al 2003;Costa et al 2005). Therefore, large grid systems are essential to capture variation in environmental conditions that tend to manifest only at the landscape scale.…”