NEON Science

LINKING MICROBIAL COMMUNITY STRUCTURE AND FUNCTION FOR IMPROVED UNDERSTANDING OF ECOSYSTEM PROCESSES

August 1, 2020 – July 31, 2022. National Science Foundation, Division of Environmental Biology (Ecosystem Science) 

Award Number: 2026815

PI: Kusum Naithani

Students: Ayanna St. Rose (Ph.D. Student, 2019 - Present), Alexis O'Callahan (Ph.D. Student, 2020 - Present)

Abstract: 

A fundamental challenge of microbial ecology is to discover unifying links between microbial communities and ecosystem processes that hold across biomes. This EAGER project will develop a procedure to analyze soil microbial data collected by the National Ecological Observatory Network (NEON), which has the advantage of generating high-quality, comparable data through standardized and quality-controlled collection and processing methods at field sites across the continent. The high-risk, high-payoff aspect of this project will involve development and testing of a 'DNA barcoding' technique for characterizing soil microbiomes in the field. Improved understanding of the links between microbial community structure and ecosystem processes will enable scientists to better predict how environmental changes impact biogeochemical cycles and stewardship of natural resources. This project will include training opportunities at the undergraduate and graduate levels.

This EAGER project integrates soil microbiology with ecosystem ecology to improve understanding of ecosystem processes, and will chart new ground using a new method, based on a MinION genomics platform, for characterizing soil microbes in the field. Specific research objectives are to (1) develop a data analysis pipeline for the NEON soil microbiota data; (2) identify unifying links between microbial structure (species richness, abundance, diversity, composition) and ecosystem processes (soil respiration and nitrogen mineralization) through analyses of publicly available NEON data products; and (3) collect and analyze soil microbial data in the field using MinION based DNA barcoding technique at NEON domain sites (D10 ? CPER, D10 ? RMNP, D10 ? STER, D13 ? NIWO) near Boulder, CO to develop and benchmark [using next generation sequencing and Phospholipid Fatty Acid (PLFA) profiling] soil analysis methods by coordinating sampling with NEON scientists. The results will reveal consistencies across biomes in microbial community structure and ecosystem processes. The methods and pipeline developed for these studies will facilitate improvements in ecosystem models that are key to reducing uncertainty in predictions of carbon fluxes and stocks, nitrification/denitrification, carbon decomposition, and overall land management. The studies will include training of graduate students, development of a course on using large data sets, and use of tutorials to engage undergraduates in using and analyzing NEON data.. The data collected at the NEON sites will be shared through GitHub and repositories like DRYAD & PANGAEA. Results from this work will be shared with scientific community via presentations and workshops at scientific meetings, an "R" library, and peer-reviewed publications.

A network of networks approach to macrosystems biology research. 

SanClements M., Record S., Rose K., Donnelly A., Chong S., Duffy K., Hallmark A., Heffernan J., Mitchell J., Moore D., Naithani K., O’Reilly C., Sokol E., Weintraub S., Stack Whitney K., and Yang D. (2022) People, infrastructure, and data: A pathway to an inclusive and diverse ecological Network of Networks. Ecosphere, e4262. doi: 10.1002/ecs2.4262


Successes, pitfalls, and opportunities for developing open education resources through community-driven collaborations.  

 Naithani K., Jones M., and Grayson K. (2022) Building Communities of Teaching Practice and Data-Driven Open Education Resources with NEON Faculty Mentoring Networks. Ecosphere, 13(8): e4210.

doi:10.1002/ecs2.4210

neonMicrobe: R package for analyzing NEON marker gene sequence data.  

Qin C., Bartelme R., Chung A., Fairbanks D., Lin Y., Liptzin D., Muscarella C., Naithani K., Peay K., Pellitier P., St. Rose A., Stanish L., Werbin Z., and Zhu K. (2021) From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package. Ecosphere, 12 (11): e03842. doi: 10.1002/ecs2.3842.

GitHub Repo

NEON data for next generation ecology research and education. 

Nagy R. C. et al. (90 authors including Naithani K.) (2021) Harnessing the NEON data revolution to advance open environmental science with a diverse and data-capable community. Ecosphere, 12 (12): e03833. doi:10.1002/ecs2.3833

Alexis presented her work at the joint meeting of the ESA & the CSIEE in Montreal, Canada. 

Ayanna presented her work at the Black Geoscientists Conference in Houston, TX. 

Ayanna presented a poster on remote sensing tools for multi-trophic biodiversity estimation at the IALE-World Conference in Nairobi, Kenya.

Alexis and Ayanna are learning how to use NEON data at NEON Unconference  in Boulder this summer! 

Congratulations to Ayanna for successfully defending her thesis in Biological Analytics!