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Related Experiment Video

Updated: Jun 10, 2026

Measuring Carbon-based Contaminant Mineralization Using Combined CO2 Flux and Radiocarbon Analyses

Measuring Carbon-based Contaminant Mineralization Using Combined CO₂ Flux and Radiocarbon Analyses

Published on: October 21, 2016

Climate data from the Rocky Mountain Biological Laboratory (1975-2022).

Rebecca M Prather^1,2, Nora Underwood^1,2, Rebecca M Dalton^2,3

¹Department of Biological Science, Florida State University, Tallahassee, Florida, USA.

|August 23, 2023

Summary

This summary is machine-generated.

This study synthesizes climate data from five sources (1975-2022) for the Rocky Mountain Biological Laboratory (RMBL). The curated dataset simplifies climate research, offering daily observations and derived ecological variables for broader scientific use.

Keywords:

Rocky Mountain Biological Laboratory alpine growing degree days montane precipitation seasonal snow standardized precipitation evapotranspiration index stream flow temperature

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Area of Science:

Ecology
Evolutionary Biology
Hydrology
Climate Science
Environmental Science

Background:

The Rocky Mountain Biological Laboratory (RMBL) is a key research site for diverse ecological and evolutionary studies.
Climate data is crucial for understanding ecological processes at RMBL, but existing data are fragmented across multiple sources.
Previous researchers faced challenges accessing, formatting, and synthesizing climate data, leading to duplicated efforts.

Purpose of the Study:

To create a single, curated, and synthesized climate data set for the RMBL region.
To facilitate future climate-related research by providing accessible and standardized data.
To reduce duplication of effort and enhance comparability across studies using RMBL data.

Main Methods:

Integrated climate data from five distinct sources: RMBL resident billy barr, NOAA, USGS, USDA, and PRISM Climate Group.
Compiled daily observations from 1975 to 2022, including precipitation, temperature, wind speed, soil moisture, and stream flows.
Developed annotated R scripts to document data handling decisions, including missing data imputation and data summarization.

Main Results:

A comprehensive daily climate data set (1975-2022) is now available for the RMBL.
The data set includes raw observations and newly derived ecological variables (e.g., growing degree days, aridity index).
Provided R code for data cleaning and synthesis, enabling easy updates and replication.

Conclusions:

The synthesized climate data set significantly lowers barriers for researchers at RMBL and beyond.
This resource promotes more robust and comparable ecological and climate change research.
The data and code are publicly available, supporting global scientific collaboration and education.