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 preci-sion, 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 non-random 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 con-firmed, the plotless sampling method, especially the point-centred quarter method, could represent an effective alternative whenever plot-based sampling is deemed redundant, or expensive. © SISEF.

Old-growth forests are characterized by the presence of large and very large trees. The estimation of their wood volume and biomass is essential in order to monitor the ecological processes in these stands and their contribution to carbon cycle. However, conventional wood volume estimation techniques based on mensuration of stem diameter at breast height and tree height is most often unfeasible for large and very large trees in old-growth forests because volume models or tables are usually elaborated from trees of smaller size grown up in regularly managed forest stands. Random Branch Sampling (RBS) is often proposed as a possible estimation alternative under such conditions. Starting from the ground level some of the parts of the main trunk and of the branches are sampled and measured to estimate the overall wood volume (or other biophysical variables). The application of RBS in old-growth forests, where tree cutting is usually forbidden or very difficult, requires that the crown of the tree can physically be reached to measure the sampled parts. We argue that under such conditions it is usually preferable to fully measure all the components of the tree crown because RBS estimates are not precise if based on only one sampling path and that, on the other hand, measuring the main trunk and all the branches by tree-climbing consumes the same time as replicating several RBS paths on the same tree. To demonstrate our hypothesis we selected 16 large beech trees located in the old-growth forest of Mount Cimini in Central Italy. Using a modern tree-climbing approach the main trunk and all the branches were measured and recorded in the field. The database was used to simulate RBS paths. Real values from volume census were contrasted with estimates based on RBS. On the whole, RBS estimates based on one single path prove to be highly imprecise. Even for trees characterized by a rather regular form, at least three RBS paths should be repeated on the same tree to maintain the relative standard error under or near 15%. This paper introduces the problem and describes the experimental test. The results are discussed under the perspective of standardized application of the proposed methodology. © 2013 Elsevier B.V.