Published May 19, 2023 | Version v1
Dataset Open

Data and Code for Blaszczak et al. 2023, Models of underlying autotrophic biomass dynamics fit to daily river ecosystem productivity estimates improve understanding of ecosystem disturbance and resilience

Authors/Creators

  • 1. University of Nevada, Reno

Contributors

  • 1. USGS
  • 2. University of Nevada Reno
  • 3. Flathead Lake Biological Station

Description

Data and code for analyses in Blaszczak et al. 2023, Models of underlying autotrophic biomass dynamics fit to daily river ecosystem productivity estimates improve understanding of ecosystem disturbance and resilience.

See publication and ReadMe file for analysis description and further details. 

bioRxiv pre-print: Blaszczak, J.R., Yackulic, C., Shriver, R., & R.O. Hall, Jr. 2023. Models of underlying autotrophic biomass dynamics fit to daily river ecosystem productivity estimates improve understanding of ecosystem disturbance and resilience. https://doi.org/10.1101/2023.04.11.535773

Files

River Biomass Model Code and Data.zip

Files (4.7 GB)

Name Size
md5:696edc40585739e03e48ec6484103c55
4.7 GB Preview Download

Additional details

Related works

Cites
Dataset: 10.5066/F70864KX (DOI)
Dataset: 10.5066/P99X6SIR (DOI)
Dataset: 10.5066/P9LREC3P (DOI)

Funding

U.S. National Science Foundation
RII Track-2 FEC: Highly Predictive, Explanatory Models to Harness the Life Science Data Revolution 2019528
U.S. National Science Foundation
COLLABORATIVE RESEARCH: Defining Stream Biomes to Better Understand and Forecast Stream Ecosystem Change 1834679