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Comparative efficiency and accuracy of variable area transects versus square plots for sampling tree diversity and density
Authors:Cheryl D. Nath  Raphaël Pélissier  Claude Garcia
Affiliation:(1) French Institute of Pondicherry, 11 St Louis Street, PB 33, Pondicherry, 605001, India;(2) UMR AMAP, TA-A51/PS2, Boulevard de la Lironde, 34398 Montpellier Cedex 5, France;(3) CIRAD—UPR 36, TA 10/D, Campus de Baillarguet, 34398 Montpellier Cedex 5, France
Abstract:Agroforestry systems have been recognized as areas with high conservation potential, and there is a need to quickly assess the biodiversity and tree stocking density available in these systems. However, it is not clear if the commonly used fixed area plot is most efficient for sampling such landscapes, or if a different method could provide equivalent data with less effort. Thus, a field and simulation-based study was carried out to compare the efficiency and accuracy of a variable area transect versus the fixed area square plot. Field efficiency tests were carried out in three habitat types, robusta coffee plantations, arabica coffee plantations and a privately owned forest fragment, in Kodagu, southern India. A simulation study of bias, precision and accuracy of the two methods for tree density estimation also was carried out using various spatial distribution patterns and densities. The variable area transect was significantly more efficient per unit effort in the field than the fixed area square plot. In the simulation tests both methods performed equally well under random spatial distribution. However, under simulated aggregated distribution both methods were positively biased (square plot up to 12% at low density, variable area transect 9–12% at all densities), and under simulated regular distribution the variable area transect was slightly negatively biased (−5 to −7% at medium to high density). The variable area transect thus can be recommended over the square plot for rapid assessment of tree diversity and density, when the vegetation is expected to be randomly dispersed.
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