Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2018-76
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Development and technical paper
25 May 2018
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).
Realized ecological forecast through interactive Ecological Platform for Assimilating Data into model (EcoPAD)
Yuanyuan Huang1,2, Mark Stacy3, Jiang Jiang1,4, Nilutpal Sundi5, Shuang Ma1,6, Volodymyr Saruta1,6, Chang Gyo Jung1,6, Zheng Shi1, Jianyang Xia7,8, Paul J. Hanson9, Daniel Ricciuto9, and Yiqi Luo1,6,10 1Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA
2Laboratoire des Sciences du Climat et de l’Environnement, 91191 Gif-sur-Yvette, France
3University of Oklahoma Information Technology, Norman, Oklahoma, USA
4Key Laboratory of Soil and Water Conservation and Ecological Restoration in Jiangsu Province, Collaborative Innovation Center of Sustainable Forestry in Southern China of Jiangsu Province, Nanjing Forestry University, Nanjing, Jiangsu, China
5Department of Computer Science, University of Oklahoma, Norman, Oklahoma, USA
6Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA
7Tiantong National Forest Ecosystem Observation and Research Station, School of Ecological and Environmental Sciences, East China Normal University, Shanghai 200062, China
8Research Center for Global Change and Ecological Forecasting, East China Normal University, Shanghai 200062, China
9Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
10Department of Earth System Science, Tsinghua University, Beijing 100084 China
Abstract. Predicting future changes in ecosystem services is not only highly desirable but also becomes feasible as several forces (e.g., available big data, developed data assimilation (DA) techniques, and advanced cyberinfrastructure) are converging to transform ecological research to quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD) into models. EcoPAD is a web-based software system that automates data transfer and processes from sensor networks to ecological forecasting through data management, model simulation, data assimilation, and visualization. It facilitates interactive data-model integration from which model is recursively improved through updated data while data is systematically refined under the guidance of model. EcoPAD relies on data from observations, process-oriented models, DA techniques, and web-based workflow. We applied EcoPAD to the Spruce and Peatland Responses Under Climatic and Environmental change (SPRUCE) experiment at North Minnesota. The EcoPAD-SPRUCE realizes fully automated data transfer, feeds meteorological data to drive model simulations, assimilates both manually measured and automated sensor data into Terrestrial ECOsystem (TECO) model, and recursively forecast responses of various biophysical and biogeochemical processes to five temperature and two CO2 treatments in near real-time (weekly). The near real-time forecasting with EcoPAD-SPRUCE has revealed that uncertainties or mismatches in forecasting carbon pool dynamics are more related to model (e.g., model structure, parameter, and initial value) than forcing variables, opposite to forecasting flux variables. EcoPAD-SPRUCE quantified acclimations of methane production in response to warming treatments through shifted posterior distributions of the CH4:CO2 ratio and temperature sensitivity (Q10) of methane production towards lower values. Different case studies indicated that realistic forecasting of carbon dynamics relies on appropriate model structure, correct parameterization and accurate external forcing. Moreover, EcoPAD-SPRUCE stimulated active feedbacks between experimenters and modelers so as to identify model components to be improved and additional measurements to be made. It becomes the first interactive model-experiment (ModEx) system and opens a novel avenue for interactive dialogue between modelers and experimenters. EcoPAD also has the potential to become an interactive tool for resource management, to stimulate citizen science in ecology, and transform environmental education with its easily accessible web interface.
Citation: Huang, Y., Stacy, M., Jiang, J., Sundi, N., Ma, S., Saruta, V., Jung, C. G., Shi, Z., Xia, J., Hanson, P. J., Ricciuto, D., and Luo, Y.: Realized ecological forecast through interactive Ecological Platform for Assimilating Data into model (EcoPAD), Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-76, in review, 2018.
Yuanyuan Huang et al.
Yuanyuan Huang et al.
Yuanyuan Huang et al.

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Short summary
Predicting future changes in ecosystem services is not only highly desirable but also becomes feasible as several forces are converging to transform ecological research to quantitative forecasting. To realize ecological forecasting, we have developed an Ecological Platform for Assimilating Data (EcoPAD) into models. EcoPAD also has the potential to become an interactive tool for resource management, to stimulate citizen science in ecology, and transform environmental education.
Predicting future changes in ecosystem services is not only highly desirable but also becomes...
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