Christoph Hahn

This study investigates the use of adaptive cluster sampling (ACS) for estimating bark stripping damage in forests, employing the Hansen–Hurwitz (HH) and Horvitz–Thompson (HT) estimators. Through simulations, we analysed the total, summer, and new bark stripping damage with varying grid sizes and sample sizes in eight full-censused stands in Northern Styria/Austria. The results showed that the HT estimator consistently had lower standard errors (SEs) (variability of the sample mean from the true population mean) than the HH estimator. SEs decreased with increasing grid space for new and summer damages, but increased for total damage up to 35 m, then remained stable. Inclusion probabilities (IP) were highest for total damage. ACS showed precision gains, particularly for rare and clustered damages like new damage, but did not achieve the target SE of 10%. Adaptive sampling is most beneficial for monitoring rare and clustered events, though precision remains limited, especially for new damage. The study suggests ACS is suitable for rare damage types (e.g., summer and new bark stripping wounds) but requires further refinement to meet operational precision targets. Future work should focus on integrating adaptive designs with practical field methods, such as fixed-radius plots and refined damage criteria.

Precise assessment of bark stripping damage is of high economic importance, since bark stripping makes wood unusable for saw timber and it is important for compensation payments for game damage. Bark stripping is clustered and decreases with increasing tree diameter, so that common forest inventories, optimized for assessing timber production variables such as standing timber volume, do not provide adequately precise estimates of bark stripping damage. In this study we analysed different sampling designs (random sampling, systematic sampling), tree selection methods (fixed radius plot, angle count sampling) and number of plots and plot sizes (plot radius: 2–20 m; basal area factor: 1–6m²/ha) for bark stripping assessment. The analysis is based on simulation studies in 9 fully censused stands (9026 trees). Simulations were done for actually assessed damage and randomly distributed damage and each scenario was repeated 100 times with different random points or different random grid locations. Systematic sampling was considerably more precise than random sampling in both scenarios. Sampling intensities to attain a standard error of 10% ranged between 12 and 18% dependent on the plot size. For a given sampling intensity, precision increased with decreasing plot size or increasing basal area factor. This implies, however, a large number of plots to be measured, which is expensive, when travel costs are high. Differences between tree selection by fixed radius plots or angle count sampling were minor. For bark stripping damage, we recommend sampling with fixed radius plots with a radius of 4–6 m and the measurement of approximately 230 or 150 plots, respectively.

Key message: Bark stripping wounds by red deer (Cervus elavus L.) were assessed on 9026 Norway spruce trees. Wound variables (length, width, area, relative width, height above ground, and angle) were analysed using generalized additive models with spatial soap film smoothers. Wounds located at the uphill side of trees were larger in summer than winter, and wound size depended on the diameter at breast height (DBH) and was spatially clustered. Context: In Austria, red deer (Cervus elaphus L.) is the main species causing bark stripping wounds. In winter, they often gnaw at the bark because of food scarcity; in summer, large pieces of bark are detached to help digestion, water, and nutrient uptake or as social behaviour. Aims: The aim of this study was to analyse wound size (length, width, area, relative width (i.e., width divided by stem circumference)) and wound position (height above ground, angle (i.e., deviation between wound azimuth from slope line)) for winter and summer bark stripping wounds by red deer depending on stand attributes and to describe the spatial patterns of wound size within stands. Methods: A total of 3832 wounds on 9026 trees in nine experimental stands of Norway spruce (Picea abies (L.) Karst.) located at 47° 19’ N and 14° 46’ E at an elevation of 1009–1622 m were analysed. A linear regression model was fit for wound length over wound width for each season. For all wound variables (wound length, width, area, relative width, position, height above ground, and angle) generalized additive models (GAM) with soap film smoothers, which predict spatial patterns, were fitted. Results: Of all wounds, 79.5 % were inflicted in winter and 20.5 % in summer. Wound length (31.9 cm ± 31.2 SD), width (11.7 cm ± 6.0 SD), area (446.5 cm²± 558.1 SD), and relative wound width (0.177 cm ± 0.098 SD) were modelled depending on summer or winter bark peeling, DBH, and tree coordinates. For wound height above ground (119.4 cm± 26.8 SD) and angle (− 1.9 ± 97.3 SD), no meaningful GAM could be calculated. Seasonal differences between wound length and area were more pronounced than for wound width; differences in height above ground were minimal, but significant. Analyses further showed that wounds were mainly located at the uphill side of the trees. Conclusion: The spatial clustering of wound sizes might reduce the efficiency of thinning to remove heavily damaged trees in bark-peeled stands and might increase the number of sample points required to assess deer impact in forest inventories. Also, the uphill location of damages is an important information in inventories.