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|Title:||Optimal strategies for sampling functional traits in species-rich forests||Contributor(s):||Paine, C E Timothy (author) ; Baraloto, Christopher (author); Diaz, Sandra (author)||Publication Date:||2015-10||Early Online Version:||2015-03-06||Open Access:||Yes||DOI:||10.1111/1365-2435.12433||Handle Link:||https://hdl.handle.net/1959.11/26721||Abstract:||1.Functional traits provide insight into a variety of ecological questions, yet the optimal sampling method to estimate the community-level distribution of plant functional trait values remains a subject of debate, especially in species-rich forests.2.We present a simulation analysis of the trait distribution of a set of nine completely sampled permanent plots in the lowland rain forests of French Guiana.3.Increased sampling intensity consistently improved accuracy in estimating community-weighted means and variances of functional trait values, whereas there was substantial variation among functional traits and minor differences among sampling strategies.4.Thus, investment in intensified sampling yields a greater improvement in the accuracy of estimation than does an equivalent investment in sampling design complication.5.Notably, 'taxon-free' strategies frequently had greater accuracy than did abundance-based strategies, which had the additional cost of requiring botanical surveys.6.We conclude that there is no substitute for extensive field sampling to accurately characterize the distribution of functional trait values in species-rich forests.||Publication Type:||Journal Article||Source of Publication:||Functional Ecology, 29(10), p. 1325-1331||Publisher:||Wiley-Blackwell Publishing Ltd||Place of Publication:||United Kingdom||ISSN:||1365-2435||Field of Research (FOR):||060202 Community Ecology (excl. Invasive Species Ecology)||Socio-Economic Objective (SEO):||960806 Forest and Woodlands Flora, Fauna and Biodiversity||Peer Reviewed:||Yes||HERDC Category Description:||C1 Refereed Article in a Scholarly Journal|
|Appears in Collections:||Journal Article|
School of Environmental and Rural Science
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