Decomposition of plant litter is a key process for the transfer of carbon and nutrients in ecosystems. Carbon contained in the decaying biomass is released to the atmosphere as respired CO₂, and may contribute to global warming. Litterbag studies have been used to improve our knowledge of the drivers of litter decomposition, but they lack comparability because litter quality is plant species-specific. The use of commercial tea bags as a standard substrate was suggested in order to harmonize studies, where green tea and rooibos represent more labile and more recalcitrant C compounds as surrogates of local litter. Here we examine the potential of the use of standardized material for improving our understanding of litter decomposition across climate regions, and to further develop pertinent models. We measured the decomposition of incubated local and standard litters over two years along an elevation gradient in the Austrian Limestone Alps. The similar response to changes in temperature and precipitation of the pairs of local and standard litter—i.e., Fagus sylvatica and green tea, and Pinus nigra and rooibos tea, respectively—suggests the suitability of the standard litters for further examining the role of environmental drivers of decomposition. Harmonized data obtained from standardized litter experiments would provide a key prerequisite for further developing simulation models for the estimation of the C balance of ecosystem litter pools.

Background: Forests are an important component of the global carbon (C) cycle and can be net sources or sinks of CO₂, thus mitigating or exacerbating the effects of anthropogenic greenhouse gas emissions. While forest productivity is often inferred from national-scale yield tables or from satellite products, forest C emissions resulting from dead organic matter decay are usually simulated, therefore it is important to ensure the accuracy and reliability of a model used to simulate organic matter decay at an appropriate scale. National Forest Inventories (NFIs) provide a record of carbon pools in ecosystem components, and these measurements are essential for evaluating rates and controls of C dynamics in forest ecosystems. In this study we combine the observations from the Swiss NFIs and machine learning techniques to quantify the decay rates of the standing snags and downed logs and identify the main controls of dead wood decay. Results: We found that wood decay rate was affected by tree species, temperature, and precipitation. Dead wood originating from Fagus sylvatica decayed the fastest, with the residence times ranging from 27 to 54 years at the warmest and coldest Swiss sites, respectively. Hardwoods at wetter sites tended to decompose faster compared to hardwoods at drier sites, with residence times 45–92 and 62–95 years for the wetter and drier sites, respectively. Dead wood originating from softwood species had the longest residence times ranging from 58 to 191 years at wetter sites and from 78 to 286 years at drier sites. Conclusions: This study illustrates how long-term dead wood observations collected and remeasured during several NFI campaigns can be used to estimate dead wood decay parameters, as well as gain understanding about controls of dead wood dynamics. The wood decay parameters quantified in this study can be used in carbon budget models to simulate the decay dynamics of dead wood, however more measurements (e.g. of soil C dynamics at the same plots) are needed to estimate what fraction of dead wood is converted to CO₂, and what fraction is incorporated into soil.

Recent temperature observations suggest a general warming trend that may be causing the range of tree species to shift to higher latitudes and altitudes. Since biotic interactions such as herbivory can change tree species composition, it is important to understand their contribution to vegetation changes triggered by climate change. To investigate the response of forests to climate change and herbivory by wild ungulates, we used the forest gap model ForClim v2.9.6 and simulated forest development in three climatically different valleys in the Swiss Alps. We used altitudinal transects on contrasting slopes covering a wide range of forest types from the cold (upper) to the dry (lower) treeline. This allowed us to investigate (1) altitudinal range shifts in response to climate change, (2) the consequences for tree species composition, and (3) the combined effect of climate change and ungulate herbivory. We found that ungulate herbivory changed species composition and that both basal area and stem numbers decreased with increasing herbivory intensity. Tree species responded differently to the change in climate, and their ranges did not change concurrently, thus causing a succession to new stand types. While climate change partially compensated for the reductions in basal area caused by ungulate herbivory, the combined effect of these two agents on the mix of the dominant species and forest type was non-compensatory, as browsing selectively excluded species from establishing or reaching dominance and altered competition patterns, particularly for light. We conclude that there is an urgent need for adaptive forest management strategies that address the joint effects of climate change and ungulate herbivory.

Forest management to a large extent determines the possible services that the forest can provide. Different objectives in forest management determine the rotation length and valuation of different stages in forest succession. We present a method of mapping potential forest management at 1-km resolution to inform policy, land use modeling, and forest resource projections. The presented method calculates the suitability of a location to different forest management alternatives based on biotic, abiotic, socioeconomic, and political factors. A sensitivity analysis of the resulting map to the data sources used was performed. This showed that the results are very sensitive to some data sources. The potential use of the map and the sensitivity to the availability of data sources are discussed. An extension to the method, including regional scaling, is suggested. Data availability is the main restriction on refinement of the proposed methodology