In the Dinaric Mountains, the future of silver fir and Norway spruce appears to be uncertain, especially given the threat of climate change to both species and browsing pressure on fir. Stand development of mixed Dinaric mountain forest in Slovenia was simulated for the period 2010–2110 using the ForClim model to explore the prospects of both target species under five management scenarios (business-as-usual, no management, single-tree selection, fir conservation and exclusion of browsing) and three climate scenarios (current climate and two climate change scenarios). Simulations under the current climate revealed a decrease in fir proportion from 53% in 2010 to 14–37% in 2110, while the proportion of spruce remained relatively constant (13% in 2010 and 9–13% in 2110). Climate change may intensify the decline of both species along an elevation gradient. An upward shift was projected for fir in the observed period; in low-elevation stands (600–800 m a.s.l.), fir could almost disappear, while at high elevations (1050–1400 m a.s.l.), our simulations projected an increase in the proportion of both fir and spruce. No single management strategy proved to be significantly beneficial for either species. The most promising strategies were the fir conservation-oriented scenario and the exclusion of browsing; large ungulates strongly impacted the development of fir, but not that of spruce. Forest management affords different options for maintaining both species, but its capacity to prevent fir decline under climate change and high browsing pressure is limited. Concurrent measures of wildlife management and silviculture should be applied to maintain conifers in the studied forests.
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This research was financially supported by the ARANGE project within the European Commission’s 7th Framework Program (Grant agreement no. 289437). The first author was additionally funded by the Pahernik Foundation. We are grateful to Janez Škerbec and Igor Pridigar, local foresters in the Snežnik area, who made the data available and provided us with important and useful information.
This article originates from the conference “Mountain Forest Management in a Changing World,” held 7–9 July 2015 in Smokovec, High Tatra Mountains, Slovakia.
Communicated by Manfred J. Lexer.
Determination of stand types and acquisition of input data for model initialization
Stand types were defined via several stand characteristics: (1) species mixture, (2) stand development stage, (3) site type (considering elevation, slope and aspect, and soil type and depth) and (4) stand structure (i.e., even-aged or uneven-aged) (for details, see Lexer 2013). Each stand in the study area (comprised in the GIS stand map and database, n = 1438, mean area = 3.5 ha) was categorized into one of the 47 defined stand types, but only 31 of them were included in our study (for details, see the study area description and Table 4). Afterward, stand types were attributed to three main elevation strata based on their elevation range: (1) low- (the prevailing elevation range 600–800 m), (2) mid- (750–1100 m) and (3) high-elevation stands (1050–1400 m). Since the elevation ranges of stands and consequently stand types were broadly defined, stand types cannot be unambiguously categorized to a certain elevation stratum and some overlap in elevation range occurred.
Two basic data sources to determine the initial diameter distribution of each stand types were used (SFS 2012): (1) permanent sampling plots (PSP) on a fixed grid (200 × 250 m, n = 823, 500 m2 each), comprising data on individual trees with registered location within the plot (i.e., azimuth and distance to the plot center), tree species, 5-cm-diameter class, social and health status, quality and some other individual tree characteristics, and (2) forest stand map and database, comprising polygons delineating individual stands and data on the main stand characteristics (i.e., area, stand volume, volume of each tree species, volume increment, allowable cut) for each polygon/stand. The procedure to acquire the initial diameter distribution was conducted in two steps. First, when stand type was defined for all stands, we overlapped the GIS layers of (1) forest stands and (2) PSP in order to identify PSP located in particular stand type. Second, we extracted PSP per stand type and calculated the average diameter distribution in 5-cm-diameter classes, starting at the measurement threshold of 10 cm in dbh. The number of PSP per stand type varied between 4 and 109, but only in 7 stand types out of 31 was the number of plots less than 10. The calculated average diameter distribution was a direct input for initializing the ForClim model.
Another input for the ForClim model was the regeneration data. The detailed data on the density of seedlings and saplings per height classes (i.e., 0–15 cm, 15–30 cm, 30–60 cm, 60–130 cm, 0–10 cm in dbh) per each tree species were acquired from 33 regeneration inventory plots located in the study area. For initializing AM3, the data acquired in the regeneration survey in the fenced areas were used (for details, see Klopčič et al. 2010).
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Klopčič, M., Mina, M., Bugmann, H. et al. The prospects of silver fir (Abies alba Mill.) and Norway spruce (Picea abies (L.) Karst) in mixed mountain forests under various management strategies, climate change and high browsing pressure. Eur J Forest Res 136, 1071–1090 (2017). https://doi.org/10.1007/s10342-017-1052-5
- Stand dynamics
- Tree species composition
- Dinaric Mountains