Open AccessEcosystem model parameterization and adaptation for sustainable cellulosic biofuel landscape design
Author(s) -
Field John L.,
Marx Ernie,
Easter Mark,
Adler Paul R.,
Paustian Keith
Publication year - 2016
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.12316
Subject(s) - environmental science , soil carbon , cellulosic ethanol , greenhouse gas , bioenergy , biofuel , land use, land use change and forestry , land use , carbon footprint , agroforestry , ecology , soil water , soil science , engineering , cellulose , chemical engineering , biology
Abstract Renewable fuel standards in the US and elsewhere mandate the production of large quantities of cellulosic biofuels with low greenhouse gas ( GHG ) footprints, a requirement which will likely entail extensive cultivation of dedicated bioenergy feedstock crops on marginal agricultural lands. Performance data for such systems is sparse, and non‐linear interactions between the feedstock species, agronomic management intensity, and underlying soil and land characteristics complicate the development of sustainable landscape design strategies for low‐impact commercial‐scale feedstock production. Process‐based ecosystem models are valuable for extrapolating field trial results and making predictions of productivity and associated environmental impacts that integrate the effects of spatially variable environmental factors across diverse production landscapes. However, there are few examples of ecosystem model parameterization against field trials on both prime and marginal lands or of conducting landscape‐scale analyses at sufficient resolution to capture interactions between soil type, land use, and management intensity. In this work we used a data‐diverse, multi‐criteria approach to parameterize and validate the DayCent biogeochemistry model for upland and lowland switchgrass using data on yields, soil carbon changes, and soil nitrous oxide emissions from US field trials spanning a range of climates, soil types, and management conditions. We then conducted a high‐resolution case study analysis of a real‐world cellulosic biofuel landscape in Kansas in order to estimate feedstock production potential and associated direct biogenic GHG emissions footprint. Our results suggest that switchgrass yields and emissions balance can vary greatly across a landscape large enough to supply a biorefinery in response to variations in soil type and land‐use history, but that within a given land base both of these performance factors can be widely modulated by changing management intensity. This in turn implies a large sustainable cellulosic biofuel landscape design space within which a system can be optimized to meet economic or environmental objectives.