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Rock structures improve seedling establishment, litter catchment, fungal richness, and soil moisture in the first year after installation.

Trace E MartynAlbert BarberánJoseph C BlankinshipMary MillerBen YangAlbert KlineElise S Gornish
Published in: Environmental management (2022)
Grasslands are essential natural and agricultural ecosystems that encompass over one-third of global lands. However, land conversion and poor management have caused losses of these systems which contributed to a 10% reduction of net primary production, a 4% increase in carbon emissions, and a potential loss of US $42 billion a year. It is, therefore, important to restore, enhance and conserve these grasslands to sustain natural plant communities and the livelihoods of those that rely on them. We installed low cost rock structures (media lunas) to assess their ability to restore grasslands by slowing water flow, reducing erosion and improving plant establishment. Our treatments included sites with small and large rock structures that were seeded with a native seed mix as well as sites with no seed or rock and sites with only seed addition. We collected summer percent cover for plants, litter, and rock and spring seedling count data. We also collected soil for nutrient, moisture, and microbial analysis. Within the first year, we found no change in plant cover between rock structures of two rock sizes. We did find, however, an increase in soil moisture, litter, fungal richness, and spring seedling germination within the rock structures, despite a historic drought. This work demonstrates that rock structures can positively impact plants and soils of grasslands even within the first year. Our results suggest that managers should seriously consider employing these low-cost structures to increase short-term plant establishment and possibly, soil health, in grasslands.
Keyphrases
  • low cost
  • high resolution
  • plant growth
  • climate change
  • healthcare
  • public health
  • risk assessment
  • cell wall
  • mass spectrometry
  • microbial community
  • machine learning
  • electronic health record