WHFF Project: 2018.07
Authors: Lorenzo Manghi and Urs Rutishauser
The most important facts in brief
The methods the Random Encounter Model (REM) and Distance Sampling with Phototraps (FDS) for ram management were tested in the Swiss Plateau and the Jura Mountains
No statistically significant differences in density estimates were found between the methods.
For roe deer, densities were found between 10.7 and 28.5 animals/km2, while for wild boar densities varied between 0.2 and 11.9 animals/km2
No positive relationship was found between deer densities and browsing intensity, suggesting that other factors play a more important role.
It is hypothesized that alternative food sources and other non-nutritional factors such as anthropogenic disturbance may lead to differences in browsing rates.
Adaptive management of the forest continues to be an important tool for setting management objectives, evaluating interventions, and monitoring the effects
Project description
Adaptive management is one of the most appropriate tools in the management of forest resources. This approach requires the collaboration of different stakeholders (foresters, hunters, forest owners, public administrations, etc.). In this process, the objectives to be achieved, control measures and monitoring methods are identified and, if necessary, corrected with new interventions. One of the most important parameters to be considered in this type of forest management is the density and composition of wild ungulate populations.
Compared to simpler methods, such as the collection of relative abundance indices, which without calibration can only show the relative trend of the population, methods are available that offer the possibility to estimate absolute numbers of wildlife populations and the variability of the results. Among these methods, the Random Encounter Model (SEM) and Distance Sampling with Phototraps (FDS) have recently become established.
In the present project, these new methods were tested in a representative ecological context of the Swiss Plateau and the Jura in order to assess the results with a view to future inclusion and implementation in wildlife management programs.
Conclusions
Overall, homogeneous estimates were obtained between SEM and FDS for all species surveyed simultaneously by the two methods, so no statistically significant differences were found between density estimates.
For roe deer, densities ranged from 10.7 to 28.5 animals/km2, while for wild boar densities ranged from 0.2 to 11.9 animals/km2. The determined roe deer densities are comparable to hunting statistics and quite high compared to estimated densities in other European areas with similar ecological characteristics. For fox and badger, densities were estimated between 1.8 and 10.9 individuals/km2 and between 1.4 and 1.9 individuals/km2, respectively.
Overall, the SEM and FDS were found to be very good methods. These two methods have provided remarkably consistent results in terms of density, precision of results, and amount of work. Therefore, the decision to use one method instead of the other can be made depending on specific research needs or economic-logistical opportunities. If somewhat more precise results are desired, SEM may be the best choice. On the other hand, if less monitoring effort or greater ease of use are particularly important, the choice may be the FDS. An important feature of both SEM and FDS is the ability to monitor all species simultaneously.
Further, a project objective was to make a simple comparison between local deer densities and browsing rates of the major tree species. No positive relationship was found between deer densities and browsing intensity, suggesting that other factors play a more important role. It is hypothesized that alternative food sources and other non-nutritional factors such as anthropogenic disturbance may lead to differences in browsing rates. It is hypothesized that forest management closer to the natural dynamics of the forest may be useful in limiting damage. The limited number of study sites and the complexity of the relationship between ungulate density and forest damage emphasize the need to conduct further studies.
In summary, the authors believe that adaptive management of forests remains an important tool for setting management objectives, evaluating interventions, and monitoring impacts. In this context, it is essential that all stakeholders actively participate in problem solving, aware that there is no conflict between wildlife and forest, but between the interests of different categories.
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