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Discussion papers | Copyright
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

Development and technical paper | 25 May 2018

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This discussion paper is a preprint. A revision of the manuscript is 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 Yuanyuan Huang et al.
  • 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.

Yuanyuan Huang et al.
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Status: final response (author comments only)
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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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