Steinwandter, Michael; Schlick-Steiner, Birgit C; Steiner, Florian M; Seeber, Julia (2020): Litter decomposition and total carbon and nitrogen content data from a 24 month litterbag experiment with single-species and mixtures of four Alpine litter types [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.919093
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Abstract:
In this study, litter decomposition patterns, non-additive effects, and spectral data of abundant alpine leaf litters were assessed in litterbag experiments containing single species and mixtures. We tested if low-quality shrub litter decomposes faster in mixtures with high-quality litter and if predictions on decomposed litter using spectral data are feasible. Therefore, we measured chemical and physical traits and near-infrared reflectance (NIR) spectra of six alpine freshly fallen litter types. A litterbag experiments (0.1 mm mesh size) with single and 2- and 3-species mixtures was conducted with three species from three functional groups (shrub, grass, forb). Decomposition rates, litter mass loss, non-additive effects, total carbon and nitrogen content, and NIR spectra were recorded after 6, 12 and 24 months (the latter are not shown). The six freshly fallen litter types showed significantly differences in leaf litter traits and NIR spectra. Decomposition rates steadily slowed during the 24 months, with shrub litter having the lowest on all sampling dates. In litter mixtures, shrub and grass litter showed higher decomposition rates after 12 and 24 months compared with the single-species treatments.
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Related to:
Steinwandter, Michael; Schlick-Steiner, Birgit C; Steiner, Florian M; Seeber, Julia (2019): One plus one is greater than two: mixing litter types accelerates decomposition of low-quality alpine dwarf shrub litter. Plant and Soil, 438(1-2), 405-419, https://doi.org/10.1007/s11104-019-03991-5
Coverage:
Latitude: 47.126000 * Longitude: 11.290900
Minimum Elevation: 2000.0 m * Maximum Elevation: 2000.0 m
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License:
Creative Commons Attribution-NonCommercial 4.0 International (CC-BY-NC-4.0)
Size:
1760 data points