Urner Reusstal (IntEx)
Natural hazards such as floods, avalanches or rockfall are central issues in the Reuss Valley in Uri.
With the help of an experiment in a potential rockfall area, the forest effect against rockfall (keyword "protection forest") should be made clear to the students and thus a better understanding of the functions of a protection forest should be created.
Task
How wide must a strip of forest be to hold boulders of different cubic sizes (here: 0.25 - 2.00 m3)?
In order to be able to answer this question plausibly, the students had the task of quantitatively characterising the forest with a random sample. To do this, they had to visit a given sampling centre and record the diameter at breast height (HDB) for those trees within a radius of 9.00 m (circular area ~250 m2) that had a HDB greater than or equal to 10 cm.
The data were evaluated in two ways, by calculating the mean value for the BHD and extrapolating the number of trunks to the hectare. For the latter, the number of measured trunks was multiplied by a factor of 40 (250 m2 correspond to 1/40 of a hectare). These two values are input parameters for a simple rockfall model that allows the determination of the theoretical forest strip width.
Field Experiment
The experiment was conducted with the Collector for ArcGIS app. In addition, the students were given a string cut of nine metres and a BHD measuring tape.
Crowd Sampling Phase
18 people took part in the excursion. For the experiment, the students were divided into six groups of 3. One person acted as the sampling centre, the second person determined if a tree was in the sampling circle and measured the breast height diameter (BHD). Finally, the third person recorded the information digitally using the Collector for ArcGIS app.
The data collection took about 20 to 30 minutes. A total of 173 trees were recorded across all groups.
The number of trees recorded and their mean HDB per sampling circle could be determined automatically with the help of the app. Then it was the students' task to extrapolate the number of trees per hectare. Using a nomogram, it was then possible to determine the theoretical forest strip width for blocks of various cubic sizes depending on the input parameters.
Discussion
With the help of this experiment, it could be shown that the forest can be characterised with random sample recordings that allow an observer to make plausible statements about the forest effect in the case of natural hazards. The (small) spatial variation of this effect could be shown on the basis of the six sample points recorded, which sometimes differed greatly in forest structure.
Feedback
"It surprised me how easy the app was to use and in what a short time - despite the poor accuracy of the GPS signal - it was possible to record numerous trees within a sampling circle. Since the exact location of the trees was irrelevant for the calculation of the relevant parameters at the sampling circle level, the inaccurate GPS signal did not matter. This gave the students a good insight into the quantification of forest impacts. In the same breath, the problem of poor GPS accuracy in the forest could be pointed out and discussed." (Dr. Jochen Breschan, Institute for Terrestrial Ecosystems, ETH Zurich, 2015)
Unfortunately, there is no feedback from the students on this experiment.
Lesson Learned
The positional inaccuracy of the GPS signal of up to 30 m in the forest led to confusion among the students. Since the location of the individual tree in this example is irrelevant for the calculation of the forest effect, the recording of the individual trees as a point data set is dispensed with in a repetition of the experiment and the BHD values are added directly to the sampling centre. This avoids the misleading point pattern of the tree locations. In addition, more time must be planned for the evaluation phase so that sufficient time is available for discussion.