Empirical estimate of the reliability of the use of the Point-Centred Quarter Method (PCQM): Solutions to ambiguous field situations and description of the PCQM+ protocol

This paper reports problems associated to the use of the Point-Centred Quarter Method (PCQM), as well as their possible solutions. Problematic settings in the application of the PCQM are amongst others due to the presence of multiple-stemmed trees (MST), to ambiguous settings for measuring the sampling point to nearest tree distance or the tree diameter, both of which may result in erroneous estimation of silvimetric variables and parameters. The analysis is based on a database of effective individual tree records including distances, diameters, and heights measured in the field in a Sri Lankan mangrove forest between 1997 and 2002, and randomly compiles a series of records that were used as PCQM sampling points. Various structural forest parameters were calculated, with particular emphasis on density and basal area.After proving that multiple- and single-stemmed trees have different silvimetric characteristics, we adopted an empirical approach to demonstrate the classical PCQM protocol applied to MST generates significantly different densities (overestimation) and basal areas (underestimation) depending on which stems are considered for measurement, and we suggest an adapted PCQM+ protocol (measurement of central stem instead of nearest stem). We test both protocols in two mangrove assemblages (one composed of Excoecaria agallocha only, and an Excoecaria agallocha/Rhizophora apiculata mixed forest) with MST proportions varying between 0% and 100%, at 5% intervals.The results indicated that the classical PCQM protocol generates density and basal area results that are strongly correlated with the MST proportion in the assemblage (p p Finally, we conclude by writing out the entire PCQM+ protocol, elaborating on the solutions to other common problems related to ambiguous settings for the consideration of stems or the measurement of their diameter (aerial roots, split trunks, dwarf growth, horizontally developing stems, boundary of an individual in MST, selectively cut trees or tree parts, very sparse assemblages, use of PCQM for remote sensing ground-truth), and by nevertheless highlighting the potential of the PCQM/PCQM+ approach. Although we used a mangrove forest data set, the PCQ-Method and our suggestions are widely applicable to other forest types. In addition, this paper is accompanied by the first interface that automatically processes standard PCQM-related data (regardless of forest type) to generate common silvimetric or forestry parameters elaborated in this paper, and it is freely available in Appendix C and from http://www.vub.ac.be/APNA/staff/FDG/pub/pub.htm