J. D. Sauerländer's Verlag, Bad Orb

The member states of the European network of protected areas, Natura 2000, are committed to report to the European Commission regularly about the situation of habitats and species. The reports are based on the monitoring of a type of compartment-based inventory scheme carried out in the forests which comply with the Flora-Fauna-Habitat guidelines. The monitoring aims to quantify habitat trees and coarse woody debris, which both are rare in most forests which are cultivated for wood production. By analysing three different inventories of forest enterprises the traditional forest inventories proved to be inefficient to record the quantity of habitat trees and dead wood. This is attributable to the subjective assessment of experts as well as the inventory based on fixed radius sample plots (fig. 2). Therefore, a line based sampling method is proposed where straight lines are regularly arranged. In this Line Transect Sampling (LTS) all habitat trees and coarse woody debris pieces which are visible from the centre line are included. The LTS was tested in one Natura 2000 area and the estimations of the number of habitat trees and the volume of standing coarse woody debris were compared with the estimations of the traditional forest inventories (fig. 3). A time study showed that in the traditional inventory sampling scheme, much effort is required for navigation and moving between sample plots (tab. 2). In a simulation study representing the conditions of the field survey different sample amplitudes for LTS and fixed radius sample plots were tested. Combining the results of these two studies, the relation of sampling error and sampling effort was specified (fig. 4). To enhance the efficiency of a sample plot-based forest inventory, the LTS can be integrated in the sampling scheme while moving from plot to plot. Complementing the traditional forest inventory with LTS provides precise estimations on rare objects such as habitat trees and coarse woody debris without considerable extra costs (fig. 5). Unlike in sampling theory, Adaptive Cluster Sampling (ACS), which is commonly regarded as effective sampling method for sparse and clustered objects, was not an efficient monitoring tool for sampling habitat trees and coarse woody debris. Based on this problem the suitability of ACS and fixed radius sample plots was further analysed. Therefore, a dataset where every tree was mapped with its coordinates was used to calculate the spherical contact distribution function and the nearest-neighbour distribution function (fig. 6–8).

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