Land use and land cover changes (LULCC) are both sources and consequence of climate change. For example, LULCC affect climate through alterations of carbon, energy, and moisture fluxes to the atmosphere. Conversely, agro-climatic studies suggest that cropping areas have gradually expanded to higher latitudes and altitudes over the last two decades due to improved thermal conditions and an adaptation response to climate change. Moreover, climate variability (causing droughts, heat waves, etc.) can lead to cropland losses, often resulting in famines in food insecure regions. Therefore, land management practices have become more important, as people must cope with more stressing land problems. Moreover, observations indicate that the climate impact of changes in land management is comparable to land-cover change. Modeling the feedbacks between LULCC, land management and climate change, and variability is therefore crucial for exploring the influence of alternative socio-economic development paths on future greenhouse gas emissions, climate change mitigation, impacts, and adaptation in integrated assessments.

The overall objective of this proposal is to advance the treatment of land disturbance, particularly LULCCs and land management practices, within an Integrated Assessment Model (IAM) and couple it with Earth System Model (ESM) to fully explore the potential contribution of LULCC and land management practices to future emissions and mitigation opportunities, and terrestrial carbon sources and sinks, and climate change. To achieve this objective, we will incorporate advances made by DOE in IAM and ESM modeling efforts and our research at UIUC in global land disturbance, carbon management and socio-economic research. Specifically, building upon and getting guidance from Integrated Earth System Model (iESM) and ACME projects, we will advance land disturbance and land management practices in Global Change Assessment Model (GCAM) and couple it with ACME (Accelerated Climate Modeling for Energy).

To achieve our objective, we propose to pursue the following specific tasks:

• Improving the Historical Distribution of LULCC. As a first step, here we propose to provide estimates of historical land-cover change (and underlying land use change conversions) in ACME that is consistent with satellite and ground-based observations.
• Implementation of Global-Scale Spatial Dynamic Allocation Model (SDAM) of Agricultural Land use Change in GCAM-ACME Coupled Modeling Framework. We propose to implement SDAM, specifically to downscale agricultural (cropland and pastureland) land use from large world regions to the grid cell level, into GCAM-ACME coupled modeling framework. The SDAM estimated land use changes within each grid cell are driven by nonlinear interactions between socioeconomic conditions (e.g. population, technology, and economy), biophysical characteristics of the land (e.g. soil, topography, and climate), and land use history in a fully coupled manner.
• Modeling Land Management Practices that Influence Carbon Sinks in Terrestrial Agriculture and Forest Ecosystems and Mitigate Climate Change. We propose to develop optimal management strategies for the agricultural and forestry stakeholders by understanding their impact on production systems, net returns to land, and the mitigation capabilities of these sectors to changing climate and carbon sequestration rates. This task will help to quantify the net impact of GHG sequestration efforts, and will help separate changes in carbon stocks due to changes in management from those occurring naturally or from changes in LULCC, and the impact of management practices under climate change scenarios on the capabilities of these sectors to changing climate and carbon sequestration rates.