Intraspecies variability in plant and soil chemical properties in a common garden plantation of the energy crop Populus
Craig, M. E.; Harman-Ware, A. E.; Cope, K. R.; Kalluri, U.
Show abstract
Optimizing crops for synergistic soil carbon (C) sequestration represents a frontier approach toward CO2 removal in food and bioenergy production systems. While the central roles of plants in biological C capture and storage belowground in soils is well known, we lack an understanding of how intraspecies variation in bioenergy plants affects soil biogeochemistry. This knowledge gap is exacerbated by spatial heterogeneity in soil and plant systems, and by the difficulty of characterizing belowground plant traits. Here, we sought to obtain first insights on the spatial variation of C and nutrients in soil and plant tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes--grown and characterized previously for aboveground biomass-to-biofuels research. Such field sites represent a potential resource for evaluating genotype-specific effects on soil C, but this usage may be complicated due to dense plantings of intermixed genotypes. Thus, we sampled soils at the scale of individual trees to determine whether it is feasible to detect soil property variation with different plant genotypes in this system. We additionally sampled stem and root tissues to evaluate the potential for inferring important belowground traits based on aboveground-belowground correlations. We found that substantial variation in soil properties could be explained at the scale of individual trees, suggesting that genetically diverse plantations can be used to assess plant-soil correlations. Though we did not observe genotype-specific patterns in soil C, other properties such as soil acid-base chemistry (soil pH and base cations) and bulk density showed genotype-specific correlations. Stem and root nutrient levels were generally not correlated, suggesting that belowground traits should be measured directly. In conclusion, our pilot study suggests that long-term common gardens of genome-wide association study populations represent useful resources for understanding plant genotypic relationships with soil properties in Populus field study test plots. These resources could be used to develop verified plant species, geographic region-specific standardized sampling methods, and baseline data. Such context-specific, empirically verified data and models will be necessary for informing applied research strategies in selecting high aboveground productivity genotypes for enhanced soil C storage in managed, commercial scale, woody bioenergy crop plantation systems.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Microbial extracellular polysaccharide production and aggregate stability controlled by Switchgrass (Panicum virgatum) root biomass and soil water potential 97%
- Belowground allocation and dynamics of recently fixed plant carbon in a California annual grassland soil 96%
- Tillage homogenizes soil bacterial communities in microaggregate fractions by facilitating dispersal 96%
Similar papers in this journal
Similar papers in this journal
- Non-destructive, whole-plant phenotyping reveals dynamic changes in water use efficiency, photosynthesis efficiency, and rhizosphere acidification of sorghum accessions under osmotic stress 93%
- Inoculation with the mycorrhizal fungus Rhizophagus irregularis modulates the relationship between root growth and nutrient content in maize (Zea mays L.) 92%
- Nodal root diameter and node number in maize (Zea mays L.) interact to influence plant growth under nitrogen stress 92%
Similar papers in this journal
- Recovery of silver fir (Abies alba Mill.) seedlings from ungulate browsing mirrors soil nitrogen availability 92%
- Adaptive plasticity in plant traits increases time to hydraulic failure under drought in a foundation tree 91%
- Water levels primarily drive variation in photosynthesis and nutrient use of scrub Red Mangroves in the southeastern Florida Everglades 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.