PEcAn Project

Ecosystem science, policy, and management informed by the best data and models

Technologies
python, postgresql, r, docker, kubernetes
Topics
data science, ecosystem models, scientific visualization, ecological forecasting, climate science
Ecosystem science, policy, and management informed by the best data and models

Why PEcAn?

Climate change science has witnessed an explosion in the amount and types of data that can be brought to bear on the potential responses of the terrestrial carbon cycle and biodiversity to global change. Many of the most pressing questions about global change are limited by our ability to synthesize existing data. Predictive Ecosystem Analyzer (PEcAn) project specifically seeks to improve this ability. Ultimately, PEcAn aims to make ecosystem modelling and data assimilation routine tools for answering scientific questions and informing policy and management.

How does PEcAn do that?

PEcAn consists of 1) state-of-the-art ecosystem models that themselves are scaffolds for integrating multiple data sources and theory, 2) a workflow management system to handle the numerous streams of data, and 3) a data assimilation statistical framework in order to synthesize the data with the model. PEcAn automates analyses aimed at understanding and forecasting ecosystem responses through these models.

Transparency, repeatability, accessibility

PEcAn's scientific workflow management fully captures the informatics of where the model inputs came from, how they were processed, how sets of model runs were completed, and how the model output was post-processed and visualized for maximizing transparency and repeatability. PEcAn's intuitive web-based interface allows non-modelers or novices to use models and techniques developed by experts.

High functionality and performance

In addition to making the PEcAn source code open source, the system is also available as a fully functional virtual machine that runs on a wide range of operating systems. The system can also interact with remote high-performance computing environments, allowing model runs to be done in parallel on remote clusters.

2020 Program

Successful Projects

Contributor
TEZAN SAHU
Mentor
infotroph, Alexey Shiklomanov, Rob Kooper, Chris Black
Organization
PEcAn Project
Extension of PEcAn API
In addition to the interactive PEcAn web interface, the PEcAn API package is built to allow users to build the PEcAn settings object via an R script...
Contributor
Prakher Prashank
Mentor
Kristina Riemer, David LeBauer-1
Organization
PEcAn Project
Metadata Upload Interface
The project aims at creating and developing a usable, self-explanatory and distinct frontend user interface for BETYdb-YABA application that will be...
Contributor
Ayush Prasad
Mentor
Shawn P. Serbin, Istem Fer, Olli Nevalainen
Organization
PEcAn Project
Extending Remote data module by connecting Google Earth Engine and other Data sources.
The existing data.remote module supports the downloading of MODIS and NLCD data. Through this project, I will extend the remote data module of PEcAn...