Daycent modeling of soil carbon and greenhouse gas emissions with pasture intensification and sugarcane production: geospatial & environmental analysis of pastureland intensification for bioenergy task II

Abstract

A research project is proposed focused on global-scale geospatial analysis relevant to bioenergy. This 3-year thematic project, conceived as a contribution to the Global Sustainable Bioenergy initiative, is structured into three tasks with objectives corresponding to targeted papers with tentative titles as follows: Task I. Potential for Pasture Intensification and Subsequent Energy Crop Production. I.1. Ground truth analysis of pasture performance gap estimation using climate binning. I.2. The impact of soil, seasonal variability of precipitation, and climate change on pasture performance gap estimation using climate binning. 1.3. Development of a global yield model for agave. 1.4. Development and preliminary application of a multi-crop global energy crop yield model on pasture land. Task II. Sustainability of Pasture Intensification and Subsequent Energy Crop Production II.1. Development of global scale biogeochemical model for pasture systems II.2. Modeling of scenarios for intensified pastureland Task III. Geospatial Analysis, Remote Sensing and Modeling. III.1. Geospatial analysis of pasture-based livestock productivity increases in Brazil III.2. Mixed crop-livestock detection/mapping using remote sensing. Work will be led by Dr. John Sheehan and carried out by an international team. A detailed project management plan is presented, including a timeline and staffing plan. In addition to six senior scholars, the research team will include 4 post docs, 3 graduate students, and 3 undergraduate students. Task I builds on an in-review paper reporting the first geospatially explicit analysis estimating the intensification potential of global pastureland, appended to the proposal, led by Dr. Sheehan with authors including several project team members. Task I is further supported by the expertise of the Steve Long group at the University of Illinois in modeling energy crop yields and their response to climate change. Findings on the intensification and energy crop potential of pastureland from Task I will be used directly in Task II, which builds on the expertise of Task leader Dr. Marcelo Galdos (CTBE) and the group led by Keith Paustian1 at Colorado State University on ecosystem modeling of agriculture. Task 3 takes advantage of the particular attributes of Brazil's well-developed, pasture-dominated livestock system and associated data, and builds on the expertise in remote sensing and mixed crop-livestock systems in the group at the University of Campinas led by Task leader Jansle Rocha. Analyses under Tasks I and III offer opportunities for validation across the tasks. In addition, Task III will lay the groundwork for new techniques critical to identifying the performance and location of mixed crop-livestock systems, which represent a large fraction of global livestock production. Successful completion of the project will meaningfully extend intellectual frontiers in the domains of geospatial analysis of pasture land, potential pasture land productivity, bioenergy crop modeling, and opportunities to increase productivity through integration, improved land management and intensification, and the sustainability of these strategies. The results will substantially advance understanding of the potential of bioenergy, establish a new team positioned to undertake further impactful analysis, and contribute to Brazilian human resource development. (AU)