Performance assessment of two plotless sampling methods for density estimation applied to some Alpine forests of northeastern Italy
Academic Article
Publication Date:
2023
abstract:
In this study, we tested two plotless sampling methods, the ordered distance
method and point-centred quarter method, to estimate the tree density and
basal area in some managed Alpine forests in northeastern Italy. We selected
nine independent forest stands, classified according to the spatial distribution
patterns of trees (cluster, random, regular). A plotless sampling survey was
simulated within the selected stands and the tree density and basal area were
estimated by applying both the ordered distance method and point-centred
quarter method. We compared the estimates, in terms of accuracy and precision, between the two methods and against estimates obtained from a simulated survey based on a plot-based sampling method. The point-centred quarter method outperformed the ordered distance method in terms of both accuracy and precision, showing higher robustness towards the bias related to nonrandom spatial patterns. However, both the plotless methods we tested can
provide unbiased accuracy of estimates which, in addition, do not differ from
estimates of plot-based sampling. The satisfactory results are encouraging for
further tests over other Italian Alpine as well as Apennine forests. If confirmed, the plotless sampling method, especially the point-centred quarter
method, could represent an effective alternative whenever plot-based sampling is deemed redundant, or expensive.
Iris type:
01.01 Articolo in rivista
Keywords:
Distance-based Density Estimator; Ordered Distance Method; Pointcentred Quarter Method; Accuracy; Precision; Conditional Inference Trees; Forest Monitoring
List of contributors:
Torresan, Chiara
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