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Harvard Forest Data Archive

HF342

Gene Expression and Tree Growth in the CTFS-ForestGEO Plot at Harvard Forest 2017-2019

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Data

Overview

  • Lead: Nate Swenson, Sean McMahon, Stuart Davies
  • Investigators: Alex Koure, Cara Scalpone, Uzay Sezen, Jessica Shue, Samantha Worthy
  • Contact: Sean McMahon
  • Start date: 2017
  • End date: 2019
  • Status: completed
  • Location: Prospect Hill Tract (Harvard Forest)
  • Latitude: -72.1755
  • Longitude: 42.5388
  • Elevation: 350 meter
  • Taxa: Acer rubrum (red maple), Fagus grandifolia (American beech), Fraxinus americana (white ash), Prunus serotina (black cherry), Quercus rubra (northern red oak)
  • Release date: 2020
  • Revisions:
  • EML file: knb-lter-hfr.342.1
  • DOI: digital object identifier
  • EDI: data package
  • DataONE: data package
  • Related links:
  • Study type: short-term measurement, modeling
  • Research topic: ecological informatics and modelling; forest-atmosphere exchange; physiological ecology, population dynamics and species interactions; regional studies
  • LTER core area: primary production, populations
  • Keywords: demography, dendrometers, genomics, population dynamics, species diversity
  • Abstract:

    Major goals in ecosystem ecology have been to scale from leaves to canopies and to determine whether individual-level, intra-species and inter-specific variation is critical for models projecting ecosystem processes now and in the future. The project is important in that it examines these issues in detail considering genotypes and levels of gene expression all the way up to canopy level CO2 flux. Ecological genomics and transcriptomics are nascent fields that have been primarily restricted to model species in natural and (mostly) controlled environments. To date, we have very few studies of non-model organisms in nature and/or studies of functional genomics through space and time. The research is producing extraordinarily rich datasets regarding the gene expression of trees across populations, through space in each population, across the growing season and across years and linking this information to growth and gas exchange. It will, therefore, provide tremendous insights into how much variation exists in nature thereby guiding sampling designs in future ecological 'omics projects. More importantly, it will provide unusually detailed phenotypic information for important non-model species that have large impacts on the CO2 flux of eastern US forests.

  • Methods:

    We installed dendrometer bands on 250 trees in Harvard Forest and measured them every week over 2017 and 2018, and twice in 2019. We sampled leaf material from these same trees for RNAseq sequencing in the early summer of 2017. Additional leaf samples were taken from 20 trees five further times over 2017 and 2018. Libraries have been prepared. Sequencing is completed for Fagus in 2017 and 2018, but other species are still being processed.

  • Use:

    This dataset is released to the public under Creative Commons license CC BY (Attribution). Please keep the designated contact person informed of any plans to use the dataset. Consultation or collaboration with the original investigators is strongly encouraged. Publications and data products that make use of the dataset must include proper acknowledgement.

  • Citation:

    Swenson N, McMahon S, Davies S. 2020. Gene Expression and Tree Growth in the CTFS-ForestGEO Plot at Harvard Forest 2017-2019. Harvard Forest Data Archive: HF342.

Detailed Metadata

hf342-01: dendrometer data

  1. site: Harvard Forest LTER/ForestGEO plot
  2. tree.id: physical tag number of the tree
  3. band.number: number of the dendrometer band; greater than 1 if more than one band was installed/used during the study
  4. species: USDA code for the species of each tree (plants.usda.gov)
  5. orig.dbh: diameter at breast height of each tree from the first census data of the plot (unit: centimeter / missing value: NA)
  6. gap.width: dendrometer band gap width measured in mm using calipers (unit: millimeter / missing value: NA)
  7. doy: numerical day of the year the measurement was taken; starting at 1 on January 1st of each year (unit: nominalDay / missing value: NA)
  8. year: year in which the measurement was taken
  9. date: date on which the measurement was taken