Search bioRxiv⌕ Search

Biology subjects

Cesaretti, L.

Publications and source records attributed to Cesaretti, L..

2 recordsLinked to original sources

treespat:an R package for spatial tree diversity analysis

Forest structure is a key element in understanding functionality and resilience of forest ecosystems. Analyses of forest structure and diversity have traditionally employed non-spatial measures, due to the simplicity of such approach. However, spatial structure can provide a deeper understanding of tree patterns, but widespread use of a spatially-explicit approach has been often limited by the complexity of theoretical equations and formulas, and the lack of freely distributed tools to calculate such spatial indices. To fill this gap we created the R package treespat, which allows to calculate some of the most diffuse stand-level spatial diversity indices. The document describes theory, basic definition and example application for using the treespat package. O_FIG O_LINKSMALLFIG WIDTH=174 HEIGHT=200 SRC="FIGDIR/small/541683v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@b631f7org.highwire.dtl.DTLVardef@18a85dcorg.highwire.dtl.DTLVardef@15a5f84org.highwire.dtl.DTLVardef@35146e_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

LAD: an R package to estimate leaf angle distribution from measured leaf inclination angles

Leaf angle distribution (LAD) is an important factor for characterizing the optical features of vegetation canopies. The characterization of LAD requires direct measurements of leaf inclination angles, which can be obtained from manual clinometer measurements or leveled digital photography. Package LAD allows to calculate the Leaf angle distribution (LAD) function and the G-function from measured leaf inclination angles. Using the package, the LAD distribution and G-function is derived by fitting a two parameter Beta distribution. Summary leaf angle statistics and distribution type is also calculated, by comparing the obtained LAD against theoretical distribution by de Wit (1965).

ecology↗