Project title
Characterizing the climate sensitivity of tropical tree woody growth
Mentor's name(s)
Helene Muller-Landau, Senior Scientist
Contact information: mullerh@si.eduCo-mentor's name(s)
Kristina Anderson-Teixeira, Smithsonian scientist, and Krishna Anujan, postdoctoral fellow
Contact information: teixeirak@si.edu, anujank@si.eduLocation of internship. Will mentor be at this location?
Barro Colorado Island and/or Gamboa, Panama. The mentor(s) will be at these locations.
Project summary
Woody growth of tropical trees represents a globally important CO2 sink that will shape the future trajectory of climate change, yet we understand remarkably little about how tropical tree growth is shaped by interannual climate variation. The challenge is that long-term records of annual growth are rare for tropical trees. Our current understanding derives primarily from annual tree rings, which are formed by only a small minority of tropical tree species in seasonal forests. We do not know how tropical tree woody growth responds to climatic drivers across the range of tropical climates or for the large diversity of species characteristic of tropical forests.
The Smithsonian-led Forest Global Earth Observatory (ForestGEO) has collected a unique data set on the annual growth of tropical trees (measured using dendrometer bands) starting in 2008 that is perfectly suited to provide the first such analysis. In this project, we will analyze data from five tropical ForestGEO sites across Asia and the Americas and 18 1-ha plots spanning a precipitation gradient in Panama – a total of 320 site-years of data including 13,176 trees of 1,505 species (>15 times more than the total number of tropical species with tree-ring records). We will provide the first analysis of how tropical tree growth responds to interannual variation in temperature and precipitation across a range of climates and a diversity of species, yielding novel and important understanding of how tropical tree growth responds to climatic variation and – by extension – how tropical forest CO2 sequestration is likely to respond to climate change.
Since 2008, we have been monitoring tree growth annually using dendrometers on a subset of trees on the Barro Colorado Island (BCI) 50-ha plot, and on other smaller ForestGEO plots. High-quality local meteorological data collected at BCI and nearby sites provide complementary data on climate variation at these sites. Further, extensive plant functional traits data available for Panama tree species enable linkages of performance to species traits.
Objectives:
- Quantify interannual variation in individual tree growth and stand-level forest woody productivity in tropical forests of central Panama, and its relationship to interannual climate variation.
- Investigate interspecific and size-related variation in tree growth responses to temporal climate variation, and its relationship to species functional traits.
Mentorship goals
The intern will have the opportunity to gain experience in tropical forest field data collection, data management and data cleaning using R and GitHub, statistical analyses and figure preparation using the R programming language, reviewing scientific literature, scientific discussions in English, working in a team with lab members and collaborators from diverse backgrounds, preparation of scientific presentations, preparation of data publications, and the scholarly publishing process. The intern will have the opportunity to contribute to (and potentially lead) a data publication and a scholarly manuscript, with support from the mentors.
This opportunity is particularly well suited for candidates seeking more research experience prior to graduate school.
Intern’s role, time commitment and expected products
The position is full-time and extends for 12 months. The start date is flexible, but should be no later than June 2024. (Full stipend of US$1250/month will be provided for entire the duration of the internship, as will support for round-trip travel to Panama.)
The intern will be awarded a stipend of US$1250/month, as well as support for round-trip travel to Panama in the case of non-Panamanian candidates.
The ideal candidate has a bachelor’s degree in a relevant field, strong quantitative skills including experience programming in R, strong organizational skills, strong English oral and written communication skills, and some Spanish communication skills. For full consideration, please email a (1) CV, (2) an unofficial undergraduate transcript (with an explanation of the grading scheme if from a non-US university), (3) a scientific writing sample, preferably in English but can be in Spanish (e.g., undergraduate thesis, lab report, research paper), (4) a sample of code you have written with commenting (preferably in R or Python, but can be another language), and (5) a cover letter describing your qualifications, interest in the position, potential start dates, and contact information for 3 references to mullerh@si.edu.
Expected products: The intern is expected to contribute importantly to and therefore be an author on one or more data publications, and will also have the opportunity to contribute as a coauthor (or potentially lead author) on a scholarly manuscript for publication in a scientific journal.
Regularly held occasions for group discussions, attendance at lectures, career counseling, and other educational and experiential opportunities for interns
The intern will participate in weekly lab meetings of the Muller-Landau and Anderson-Teixeira labs, and will have the opportunity to attend weekly seminars on BCI (Thursdays) and at Tupper (Tuesdays), as well as STRI training opportunities (e.g., periodic offerings in GIS, R programming). The intern will meet weekly with the STRI advisor (Helene Muller-Landau) and will also meet regularly via videoconference with the coadvisors (Kristina Anderson-Teixeira and Krishna Anujan). The intern will also have the opportunity to informally interact with other STRI staff scientists, employees, visiting scientists, fellows, and interns, including over shared meals on BCI.
List of suggested readings
ForestGEO dendrometer band protocol: https://forestgeo.si.edu/protocols/dendrometer-bands
Muller-Landau, H. C., K. C. Cushman, E. E. Arroyo, I. Martinez Cano, K. J. Anderson-Teixeira, and B. Backiel. 2021. Patterns and mechanisms of spatial variation in tropical forest productivity, woody residence time, and biomass. New Phytologist, 229: 3065-3087. https://doi.org/10.1111/nph.17084
Anderson-Teixeira, Kristina J., Herrmann, Valentine, Rollinson, Christine R., Gonzalez, Bianca, Gonzalez-Akre, Erika B., Pederson, Neil, Alexander, M. Ross, Allen, Craig D., Alfaro-Sanchez, Raquel, Awada, Tala, Baltzer, Jennifer L., Baker, Patrick J., Birch, Joseph D., Bunyavejchewin, Sarayudh, Cherubini, Paolo, Davies, Stuart J., Dow, Cameron, Helcoski, Ryan, Kaspar, Jakub, Lutz, James A., Margolis, Ellis Q., Maxwell, Justin T., McMahon, Sean M., Piponiot, Camille, Russo, Sabrina E., et al. 2022. Joint effects of climate, tree size, and year on annual tree growth derived from tree-ring records of ten globally distributed forests. Global Change Biology, 28(1): 245-266. https://doi.org/10.1111/gcb.15934
Alfaro-Sanchez, R., H. C. Muller-Landau, S. J. Wright, and J. J. Camarero. 2017. Growth and reproduction respond differently to climate in three Neotropical tree species. Oecologia, 184: 531-541. https://doi.org/10.1007/s00442-017-3879-3
Araujo, R. F., S. Grubinger, C. H. S. Celes, R. I. Negrón-Juárez, M. Garcia, J. P. Dandois, and H. C. Muller-Landau. 2021. Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50-ha plot. Biogeosciences, 18: 6517-6531. https://doi.org/10.5194/bg-18-6517-2021
