Modeling Soil Processes: Review, Key Challenges, and New Perspectives
Моделирование почвенных процессов: обзор, ключевые проблемы и новые перспективы
2016-05-01
SCID: 54.1/7ejh6th3
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data-model integrationecosystem servicessoil heterogeneity and uncertaintysoil modelssoil process modeling
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Abstract (AI)
Core Ideas A community effort is needed to move soil modeling forward. Establishing an international soil modeling consortium is key in this respect. There is a need to better integrate existing knowledge in soil models. Integration of data and models is a key challenge in soil modeling. The remarkable complexity of soil and its importance to a wide range of ecosystem services presents major challenges to the modeling of soil processes. Although major progress in soil models has occurred in the last decades, models of soil processes remain disjointed between disciplines or ecosystem services, with considerable uncertainty remaining in the quality of predictions and several challenges that remain yet to be addressed. First, there is a need to improve exchange of knowledge and experience among the different disciplines in soil science and to reach out to other Earth science communities. Second, the community needs to develop a new generation of soil models based on a systemic approach comprising relevant physical, chemical, and biological processes to address critical knowledge gaps in our understanding of soil processes and their interactions. Overcoming these challenges will facilitate exchanges between soil modeling and climate, plant, and social science modeling communities. It will allow us to contribute to preserve and improve our assessment of ecosystem services and advance our understanding of climate‐change feedback mechanisms, among others, thereby facilitating and strengthening communication among scientific disciplines and society. We review the role of modeling soil processes in quantifying key soil processes that shape ecosystem services, with a focus on provisioning and regulating services. We then identify key challenges in modeling soil processes, including the systematic incorporation of heterogeneity and uncertainty, the integration of data and models, and strategies for effective integration of knowledge on physical, chemical, and biological soil processes. We discuss how the soil modeling community could best interface with modern modeling activities in other disciplines, such as climate, ecology, and plant research, and how to weave novel observation and measurement techniques into soil models. We propose the establishment of an international soil modeling consortium to coherently advance soil modeling activities and foster communication with other Earth science disciplines. Such a consortium should promote soil modeling platforms and data repository for model development, calibration and intercomparison essential for addressing contemporary challenges.
Key Findings
1
An international soil modeling consortium and stronger knowledge exchange are needed to coordinate advances across soil science and Earth-system communities.
2
Improved soil modeling could strengthen assessment of ecosystem services and understanding of climate-change feedbacks while enhancing communication across science and society.
3
Next-generation models should adopt a systemic approach integrating relevant physical, chemical, and biological processes and their interactions.
4
Soil-process models remain fragmented across disciplines and ecosystem services, with substantial uncertainty in prediction quality despite major progress.
5
Systematically representing soil heterogeneity and uncertainty, together with integrating data and models, remains a central modeling challenge.
Research Object
soil processes in terrestrial ecosystems
Research Subject
their modeling, integration of physical, chemical, and biological knowledge, and quantification of ecosystem-service functions under heterogeneity and uncertainty
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2016-05-01
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