For silver fir (Abies alba), a species expected to play an important role in climate-change adaptation of Central European forests, seed viability in Austria appears to be declining. Therefore, it is crucial to examine the constraints on seed viability and to identify ways to counteract the observed trend. In this study, we investigated factors associated with silver fir seed viability in seed stands and seed orchards in Austria. We hypothesized that seedling emergence is affected by endogenous (tree age, species abundance) and exogenous (climatic) conditions of seed stands, and that differences in emergence occur among seed production unit types, with higher success expected in seed orchards. We conducted a common garden experiment using seed lots from 63 seed stands and six seed orchards across Austria to investigate the likelihood of seedling emergence as a function of the proportion of silver fir-associated forest cover in seed stands, tree age, climate parameters, and seed weight. Our results show a positive relationship between seedling emergence and the proportion of silver fir-associated forest cover, as well as between seedling emergence and the maximum age of the silver trees in stands. The effect of mean annual temperature on seedling emergence depended on annual precipitation levels: seeds from stands in warmer conditions had a higher probability of emergence, but only under sufficient precipitation. As climate change, habitat loss, and fragmentation intensify, seed-sourcing strategies should explicitly incorporate ecological filters when selecting stands for seed harvest to safeguard seed viability and genetic diversity for nursery production. Seed stand management should be refocused on promoting structural conditions that enhance reproductive success, while seed orchards should continue to serve as essential sources of quality and genetically diverse reproductive material.

We counted the final number of vital emerged seedlings 11 weeks after sowing and used the proportion of vital emerged seedlings as an estimate of seed viability. Seedlings were considered vital when a healthy shoot system was developed.

Daily minimum and maximum temperatures and precipitation at seed source populations were obtained from datasets with a 1 km × 1 km spatial resolution (Hiebl & Frei, 2016, 2018). The daily climate data time series are based on gridded values (Lehner et al., 2024) and have been further processed to a final resolution of 250 m × 250 m. We averaged the daily temperature and precipitation values over the 10 years from November 2012 to October 2022.

The same expert at each seed stand conducted field measurements and site evaluation during the stands’ certification, in accordance with the relevant legal guidelines (BMLUK, 2023). These assessments provided data on stand characteristics, including tree age, elevation, stand size, and tree species composition.

Since data on silver fir abundance alone were unavailable, we used remote sensing data on mixed Norway spruce and silver fir forest cover (hereafter: spruce-fir cover) as a proxy. The examined seed stands indeed consisted predominantly of mixed spruce-fir forests, reinforcing the suitability of the dataset for our analysis. Using the central coordinates of each stand, we estimated the proportion of spruce-fir forest within concentric circles with radii ranging from 100 to 2,000 m. The forest cover data were extracted from an existing dataset with a 10 m x 10 m spatial resolution (Schadauer et al., 2024). The dataset is based on a supervised classification of Sentinel-2 time series and validated using data from the Austrian forest inventory, with a user’s accuracy of 0.72 for the spruce-fir class.

References

• Hiebl, J., & Frei, C. (2016). Daily temperature grids for Austria since 1961—Concept, creation and applicability. Theoretical and Applied Climatology, 124(1), 161–178. https://doi.org/10.1007/s00704-015-1411-4
• Hiebl, J., & Frei, C. (2018). Daily precipitation grids for Austria since 1961—Development and evaluation of a spatial dataset for hydroclimatic monitoring and modelling. Theoretical and Applied Climatology, 132(1), 327–345. https://doi.org/10.1007/s00704-017-2093-x
• Lehner, F., Klisho, T., & Formayer, H. (2024). BioClim Austria: Gridded climate indicators for 1961-1990 and 1991-2020 at 250m resolution [Dataset]. Zenodo. https://doi.org/10.5281/zenodo.10887293
• BMLUK. (2023). Gesamte Rechtsvorschrift für Forstliche Vermehrungsgutverordnung 2002, Fassung vom 20.02.2023. https://www.bundesamt-wald.at/dam/jcr:8e88f249-0fb1-42fa-808f-865b3710d624/Forstliche_Vermehrungsgutverordnung_2002_Fassung_Feb2023_konsolidiert.pdf
• Schadauer, T., Karel, S., Loew, M., Knieling, U., Kopecky, K., Bauerhansl, C., Berger, A., Graeber, S., & Winiwarter, L. (2024). Evaluating tree species mapping: probability sampling validation of pure and mixed species classes using convolutional neural networks and Sentinel-2 time series. Remote Sensing, 16(16), Article 16. https://doi.org/10.3390/rs16162887

Key Information Sources

Climate and species distribution data for climate-space plot were derived from the following sources:

• Caudullo, G., Welk, E., & San-Miguel-Ayanz, J. (2017). Chorological maps for the main European woody species. Data in Brief, 12, 662–666. https://doi.org/10.1016/j.dib.2017.05.007
• Brun, P., Zimmermann, N.E., Hari, C., Pellissier, L., & Karger, D. (2022). Data from: CHELSA-BIOCLIM+ A novel set of global climate-related predictors at kilometre-resolution [Dataset]. EnviDat. https://doi.org/10.16904/envidat.332
• Karger, D. N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R. W., Zimmermann, N. E., Linder, H. P., & Kessler, M. (2017). Climatologies at high resolution for the earth’s land surface areas. Scientific Data, 4(1), 170122. https://doi.org/10.1038/sdata.2017.122
• Mauri A., de Rigo D., & Caudullo G. (2016). Abies alba in Europe: distribution, habitat, usage and threats. European Atlas of Forest Tree Species, 48-49. https://forest.jrc.ec.europa.eu/media/atlas/Abies_alba.pdf