Published July 8, 2021 | Version v1
Dataset Open

Data from: Recovery of silver fir (Abies alba Mill.) seedlings from ungulate browsing mirrors soil nitrogen availability

  • 1. Swiss Federal Research Institute WSL
  • 2. ETH Zurich
  • 3. INRAE

Description

Abies alba (Mill.) has a high potential for mitigating climate change in European mountain forests, yet, its natural regeneration is severely limited by ungulate browsing. Here, we simulated browsing in a common garden experiment to study growth and physiological traits, measured from bulk needles, using a randomized block design with two levels of browsing severity and seedlings originating from 19 populations across Switzerland. Genetic factors explained most variation in growth (on average, 51.5%) and physiological traits (10.2%) under control conditions, while heavy browsing considerably reduced the genetic effects on growth (to 30%), but doubled those on physiological traits related to C storage. While browsing reduced seedling height, it also lowered seedling water use efficiency (decreased δ13C) and increased their δ15N. Different populations reacted differently to browsing stress, and for seedling height, starch concentration and δ15N population differences appeared to be the result of natural selection. First, we found that populations originating from the warmest regions recovered the fastest from browsing stress, and they did so by mobilizing starch from their needles, which suggests a genetic underpinning for a growth-storage trade-off across populations. Second, we found that seedlings originating from mountain populations growing on steep slopes had a higher δ15N in the common garden than those originating from flat areas, indicating that they have been selected to grow on N poor, potentially drained, soils. This finding was corroborated by the fact that N concentration in adult needles was lower on steep slopes than on flat ground, strongly indicating that steep slopes are the most N poor environments. These results suggest that populations adapted to these N poor environments have a genetically based high N use efficiency, which could be necessary for their recover from ungulate browsing.

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Additional details

Funding

European Commission
FORGENET - A novel approach for detecting polygenic adaptation applied to FORest tree candidate GEne NETworks 705972
Swiss National Science Foundation
Using fossil records and simulations to develop spatially explicit demographic null models to detect selection from genomic data in forest trees CRSK-3_190288