PubMed Health⌕ Search

PubMed · 16958875

Conventional functional classification schemes underestimate the relationship with ecosystem functioning.

Abstract

Studies linking the functional diversity of a biota to ecosystem functioning typically employ a priori classifications of species into hypothetically complementary groups. However, multiple alternate classifications exist in which the number of functional groups, the number of species per functional group, and the grouping of species differ from the a priori scheme. Without assessing the relative precision, or ability of an a priori scheme to accurately predict ecosystem functioning relative to its many alternatives, the validity and utility of analyses based on a single a priori classification scheme remains unclear. We examine the precision of a priori classifications used in 10 experimental grassland systems in Europe and the United States that have found evidence for a significant role of functional plant diversity in governing ecosystem function. The predictive precision of the a priori classifications employed in these studies was seldom significantly higher than the precision of random classifications. Post-hoc classification schemes that performed well in predicting ecosystem function resembled each other more with regard to species composition than average classifications, but there was still considerable variability in the manner in which these classification schemes grouped species. These results suggest that we need a more nuanced understanding of how the diversity of functional traits of species in an assemblage affects ecosystem functioning.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Justin P Wright, Shahid Naeem, Andy Hector, Clarence Lehman, Peter B Reich, Bernhard Schmid, David Tilman. 2006. Conventional functional classification schemes underestimate the relationship with ecosystem functioning.. https://doi.org/10.1111/j.1461-0248.2005.00850.x

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Development of an ecologic marine classification in the new zealand region.

We describe here the development of an ecosystem classification designed to underpin the conservation management of marine environments in the New Zealand region. The classification was defined using multivariate classification using explicit environmental layers chosen for their role in driving spatial variation in biologic patterns: depth, mean annual solar radiation, winter sea surface temperature, annual amplitude of sea surface temperature, spatial gradient of sea surface temperature, summer sea surface temperature anomaly, mean wave-induced orbital velocity at the seabed, tidal current velocity, and seabed slope. All variables were derived as gridded data layers at a resolution of 1 km. Variables were selected by assessing their degree of correlation with biologic distributions using separate data sets for demersal fish, benthic invertebrates, and chlorophyll-a. We developed a tuning procedure based on the Mantel test to refine the classification's discrimination of variation in biologic character. This was achieved by increasing the weighting of variables that play a dominant role and/or by transforming variables where this increased their correlation with biologic differences. We assessed the classification's ability to discriminate biologic variation using analysis of similarity. This indicated that the discrimination of biologic differences generally increased with increasing classification detail and varied for different taxonomic groups. Advantages of using a numeric approach compared with geographic-based (regionalisation) approaches include better representation of spatial patterns of variation and the ability to apply the classification at widely varying levels of detail. We expect this classification to provide a useful framework for a range of management applications, including providing frameworks for environmental monitoring and reporting and identifying representative areas for conservation.

Classification↗

SINEs of progress: Mobile element applications to molecular ecology.

Mobile elements represent a unique and under-utilized set of tools for molecular ecologists. They are essentially homoplasy-free characters with the ability to be genotyped in a simple and efficient manner. Interpretation of the data generated using mobile elements can be simple compared to other genetic markers. They exist in a wide variety of taxa and are useful over a wide selection of temporal ranges within those taxa. Furthermore, their mode of evolution instills them with another advantage over other types of multilocus genotype data: the ability to determine loci applicable to a range of time spans in the history of a taxon. In this review, I discuss the application of mobile element markers, especially short interspersed elements (SINEs), to phylogenetic and population data, with an emphasis on potential applications to molecular ecology.

Classification↗