Greenhouse gas and forest productivity of Amazon peatlands: data mining internship

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Sponsoring College, Department, School or Center: 
Faculty Name: 
Hinsby Cadillo-Quiroz
Preferred Skills or Majors: 

-Capacity for numerical analysis is basic
-Experience in R, Excel, or databases (Access, SQL, or others) is helpful. Experience in matlab is very helpful too.
- Interest for incorporation of environmental sciences into tools for decision making
- Be comfortable with remote based supervision/training
- Experience or interest on forest ecology, or mathematical ecosystem modeling will be a plus

Closing Date: 
May 1, 2021
Location or Campus: 
Life Sciences Building E room 722, Tempe Campus
Hours Per Week: 

Desired Academic Year: 
Project Description: 

Environmental trace gas fluxes monitoring and integration with forest productivity

Atmospheric trace gases are both major controls of global warming and important indicators of ecosystem functions. Methane fluxes in natural ecosystems are responsible for the primary terrestrial sink of atmospheric methane (soil methane consumption) and approximately half of global methane emissions (e.g., wetland methane emission). We are studying methane and carbon cycling in the under-studied peatlands of the Amazon basin. Forest productivity can be a major driver for GHG still to be accounted and this element is a component in evaluation on an NSF sponsored study. A resulting estimates of peatland greenhouse gas budgets and their controls will help fill a gap in global estimates of atmospheric greenhouse gas exchange and management strategies.

Process and aims:
At the Cadillo lab at Arizona State University, we are compiling 7+ years of data from multiple study sites for analysis and publication. Internship position will aid this effort by calculating gas fluxes, water or vegetation change from raw instrument data, organizing the results in a database with additional field data, and extracting combined data for each plot.
REU intern (s) will learn/advance their skill on programing and data management with the software R, and then build scripts to analyze data with guidance from faculty and postdoctoral mentors.

Application Instructions and Contact Info: 

-Send a brief letter of interest or motivation, and if any past experience or class can be relevant
- Indicate time availability and capacity for remote work. Ideally, we are looking for at least a 20 hours per week commitment
-Latinx minorities are highly encourage, although spots are open for any applicant.
- Submit he above info plus updated CV and transcript to Starting date is as as soon as possible for the fall term.