Open AccessGlobal simulation of bioenergy crop productivity: analytical framework and case study for switchgrass
Author(s) -
Kang Shujiang,
Nair Sujithkumar Surendran,
Kline Keith L.,
Nichols Jeffrey A.,
Wang Dali,
Post Wilfred M.,
Brandt Craig C.,
Wullschleger Stan D.,
Singh Nagendra,
Wei Yaxing
Publication year - 2014
Publication title -
gcb bioenergy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.378
H-Index - 63
eISSN - 1757-1707
pISSN - 1757-1693
DOI - 10.1111/gcbb.12047
Subject(s) - bioenergy , environmental science , miscanthus , biomass (ecology) , panicum virgatum , energy crop , biofuel , greenhouse gas , sustainability , agricultural engineering , agroforestry , agronomy , engineering , waste management , ecology , biology
A global energy crop productivity model that provides geospatially explicit quantitative details on biomass potential and factors affecting sustainability would be useful, but does not exist now. This study describes a modeling platform capable of meeting many challenges associated with global‐scale agro‐ecosystem modeling. We designed an analytical framework for bioenergy crops consisting of six major components: (i) standardized natural resources datasets, (ii) global field‐trial data and crop management practices, (iii) simulation units and management scenarios, (iv) model calibration and validation, (v) high‐performance computing ( HPC ) simulation, and (vi) simulation output processing and analysis. The HPC ‐Environmental Policy Integrated Climate ( HPC ‐ EPIC ) model simulated a perennial bioenergy crop, switchgrass ( Panicum virgatum L.), estimating feedstock production potentials and effects across the globe. This modeling platform can assess soil C sequestration, net greenhouse gas ( GHG ) emissions, nonpoint source pollution (e.g., nutrient and pesticide loss), and energy exchange with the atmosphere. It can be expanded to include additional bioenergy crops (e.g., miscanthus, energy cane, and agave) and food crops under different management scenarios. The platform and switchgrass field‐trial dataset are available to support global analysis of biomass feedstock production potential and corresponding metrics of sustainability.