Realized ecological forecast through an interactive Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models

Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces (e.g., available big data, developed data assimilation (DA) techniques, and advanced cyber-infrastructure) are converging to transform ecological research into quantitative fo...

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Bibliographic Details
Published in:Geoscientific Model Development 2019-03, Vol.12 (3), p.1119-1137
Main Authors: Huang, Yuanyuan, Stacy, Mark, Jiang, Jiang, Sundi, Nilutpal, Ma, Shuang, Saruta, Volodymyr, Jung, Chang Gyo, Shi, Zheng, Xia, Jianyang, Hanson, Paul J, Ricciuto, Daniel, Luo, Yiqi
Format: Article
Language:English
Subjects:
Analysis
Automation
Big data
Biodiversity and Ecology
Biogeochemistry
Carbon dioxide
Case studies
Climate change
Computer simulation
Data assimilation
Data collection
Data management
Data processing
Data transfer (computers)
Dynamic structural analysis
Dynamics
Ecological research
Ecology
Ecology, environment
Economic forecasting
Ecosystem services
Ecosystems
Environment models
Environmental aspects
Environmental changes
ENVIRONMENTAL SCIENCES
Forecasting
Information processing
Interactive systems
Life Sciences
Mathematical models
Meteorological data
Methane
Methane production
Novels
Parameterization
Peatlands
Sensors
Temperature
Terrestrial ecosystems
Visualization (Computer)
Weather
Workflow
Workflow software
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Summary:Predicting future changes in ecosystem services is not only highly desirable but is also becoming feasible as several forces (e.g., available big data, developed data assimilation (DA) techniques, and advanced cyber-infrastructure) are converging to transform ecological research into quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD, v1.0) into models. EcoPAD (v1.0) is a web-based software system that automates data transfer and processing from sensor networks to ecological forecasting through data management, model simulation, data assimilation, forecasting, and visualization. It facilitates interactive data-model integration from which the model is recursively improved through updated data while data are systematically refined under the guidance of model. EcoPAD (v1.0) relies on data from observations, process-oriented models, DA techniques, and the web-based workflow.
ISSN:1991-9603
1991-959X
1991-962X
1991-9603
1991-962X
1991-959X
DOI:10.5194/gmd-12-1119-2019