This research project aims to develop a portfolio approach to development of land change scenarios for the United States based on empirical data and global integrated assessment modeling.This research will continue the development and capabilities of the Land Use and Carbon Scenario Simulator (LUCAS), which has been developed by USGS scientists for the purposes of projecting land change and its impact on ecosystem carbon dynamics.
Statement of Problem: Climate change and the potential adoption and implementation of mitigation and/or adaptation strategies are important aspects to projecting future land change. Climate change impacts land-use through alteration of biophysical characteristics that control suitability for a given land use, while land change impacts climate through alteration of surface and atmospheric boundaries and resultant energy and water fluxes. This research examines important interactions between land use and climate under a range of future conditions in order to identify regions which are most at risk to negative impacts and where climate-land interactions provide new potential opportunities. Additionally, the biosphere offers opportunities for climate mitigation through the offset of greenhouse-gas emissions. Research should further our understanding of how climate mitigation and adaptation strategies might evolve and impact the composition and trajectories of important land sectors.
Research is needed to develop geostatistical approaches to projecting land change based on empirical data. Additionally, future projections should incorporate causal mechanisms where possible, such as abrupt policy interventions (e.g. Conservation Reserve Program, Endangered Species Act), economic drivers (e.g. Great Recession), and environmental drivers (e.g. episodic and prolonged drought, climate change, wildfire). This research should aim to develop a portfolio approach to land change projection and work to robustly characterize, and reduce where possible, the large uncertainties associated with land-change prediction, forecasting, and projection.
Why this Research is Important: The recognition of the need for improving the understanding and management of climate and land change is longstanding. The National Research Council identified this issue as one of the 21st century grand challenges, it is a formal element of the US Global Change Research Program and relates to the central goals of the Climate Action Plan. The USGS Climate and Land Use Change science strategy also identifies the need to improve the understanding of the combined effects of climate and land use change. Because resource managers are keenly aware of the threats that climate and land use change have on their management goals, and are asking for information on land use, cover, and condition for their activities, research on climate and land change questions should be an important element of the USGS Land Change Science Program.
Objective(s):
- Develop geostatistical methods for developing a portfolio of empirical-based projections of land-use and land-cover change for the United States over short (10-20 years), medium (20-50 years), and long-time horizons (50-100 years). Scenarios will explore changes in major land use conversions, including urbanization, expansion and contraction of agriculture, and forestry, as well as changes in land cover due to natural disturbances (e.g. wildfire, insect/disease) and climate change.
- Develop a coupled modeling capability which can be used to explore the impacts of potential climate-based mitigation and adaptation strategies on changes in land use and land cover from local to global scales.
- Work with local, regional, and national stakeholders to develop alternative scenarios of land change (e.g. “what-if” scenarios) based on local, regional, and national driving forces analysis and policy-based assumptions.
Methods: This project will develop an entirely new set of statistical tools, methods, and models to project land change over short, medium, and long-time horizons across a range of spatial scales. Additionally, this research will develop new modeling approaches to link coarse-scale global integrated assessment models (IAM’s) with empirically-based land change forecasting methods. Lastly, this research will need to develop cutting-edge computational capabilities, including parallelization of models for deployment on high performance computing facilities. Currently, work has been done utilizing USGS compute facilities in Denver, CO as well as on the NASA Earth Exchange.
Below are other science projects associated with this project.
The LUCAS Model
LandCarbon
Below are publications associated with this project.
Adaptation with climate uncertainty: An examination of agricultural land use in the United States
Effects of contemporary land-use and land-cover change on the carbon balance of terrestrial ecosystems in the United States
Integrating continuous stocks and flows into state-and-transition simulation models of landscape change
Future scenarios of land change based on empirical data and demographic trends
Mediterranean California’s water use future under multiple scenarios of developed and agricultural land use change
Climate impacts on agricultural land use in the USA: the role of socio-economic scenarios
Projecting community changes in hazard exposure to support long-term risk reduction: A case study of tsunami hazards in the U.S. Pacific Northwest
Baseline and projected future carbon storage and carbon fluxes in ecosystems of Hawai‘i
A carbon balance model for the great dismal swamp ecosystem
Divergent projections of future land use in the United States arising from different models and scenarios
Estimating carbon sequestration in the piedmont ecoregion of the United States from 1971 to 2010
State-and-transition simulation models: a framework for forecasting landscape change
- Overview
This research project aims to develop a portfolio approach to development of land change scenarios for the United States based on empirical data and global integrated assessment modeling.This research will continue the development and capabilities of the Land Use and Carbon Scenario Simulator (LUCAS), which has been developed by USGS scientists for the purposes of projecting land change and its impact on ecosystem carbon dynamics.
Statement of Problem: Climate change and the potential adoption and implementation of mitigation and/or adaptation strategies are important aspects to projecting future land change. Climate change impacts land-use through alteration of biophysical characteristics that control suitability for a given land use, while land change impacts climate through alteration of surface and atmospheric boundaries and resultant energy and water fluxes. This research examines important interactions between land use and climate under a range of future conditions in order to identify regions which are most at risk to negative impacts and where climate-land interactions provide new potential opportunities. Additionally, the biosphere offers opportunities for climate mitigation through the offset of greenhouse-gas emissions. Research should further our understanding of how climate mitigation and adaptation strategies might evolve and impact the composition and trajectories of important land sectors.
Research is needed to develop geostatistical approaches to projecting land change based on empirical data. Additionally, future projections should incorporate causal mechanisms where possible, such as abrupt policy interventions (e.g. Conservation Reserve Program, Endangered Species Act), economic drivers (e.g. Great Recession), and environmental drivers (e.g. episodic and prolonged drought, climate change, wildfire). This research should aim to develop a portfolio approach to land change projection and work to robustly characterize, and reduce where possible, the large uncertainties associated with land-change prediction, forecasting, and projection.
Why this Research is Important: The recognition of the need for improving the understanding and management of climate and land change is longstanding. The National Research Council identified this issue as one of the 21st century grand challenges, it is a formal element of the US Global Change Research Program and relates to the central goals of the Climate Action Plan. The USGS Climate and Land Use Change science strategy also identifies the need to improve the understanding of the combined effects of climate and land use change. Because resource managers are keenly aware of the threats that climate and land use change have on their management goals, and are asking for information on land use, cover, and condition for their activities, research on climate and land change questions should be an important element of the USGS Land Change Science Program.
Objective(s):
- Develop geostatistical methods for developing a portfolio of empirical-based projections of land-use and land-cover change for the United States over short (10-20 years), medium (20-50 years), and long-time horizons (50-100 years). Scenarios will explore changes in major land use conversions, including urbanization, expansion and contraction of agriculture, and forestry, as well as changes in land cover due to natural disturbances (e.g. wildfire, insect/disease) and climate change.
- Develop a coupled modeling capability which can be used to explore the impacts of potential climate-based mitigation and adaptation strategies on changes in land use and land cover from local to global scales.
- Work with local, regional, and national stakeholders to develop alternative scenarios of land change (e.g. “what-if” scenarios) based on local, regional, and national driving forces analysis and policy-based assumptions.
Methods: This project will develop an entirely new set of statistical tools, methods, and models to project land change over short, medium, and long-time horizons across a range of spatial scales. Additionally, this research will develop new modeling approaches to link coarse-scale global integrated assessment models (IAM’s) with empirically-based land change forecasting methods. Lastly, this research will need to develop cutting-edge computational capabilities, including parallelization of models for deployment on high performance computing facilities. Currently, work has been done utilizing USGS compute facilities in Denver, CO as well as on the NASA Earth Exchange.
- Science
Below are other science projects associated with this project.
The LUCAS Model
Our team is developing the Land Use and Carbon Scenario Simulator (LUCAS) model. LUCAS is a state-and-transition simulation model designed to track changes in land use, land cover, land management, and disturbance, and their impacts on ecosystem carbon storage and flux.LandCarbon
The biologic carbon sequestration assessment program (LandCarbon) investigates ecosystem carbon cycle problems and develops carbon management science and monitoring methods. - Publications
Below are publications associated with this project.
Filter Total Items: 23Adaptation with climate uncertainty: An examination of agricultural land use in the United States
This paper examines adaptation responses to climate change through adjustment of agricultural land use. The climate drivers we examine are changes in long-term climate normals (e.g., 10-year moving averages) and changes in inter-annual climate variability. Using US county level data over 1982 to 2012 from Census of Agriculture, we find that impacts of long-term climate normals are as important asAuthorsJianhong E. Mu, Bruce A. McCarl, Benjamin M. Sleeter, John T. Abatzoglou, Hongliang ZhangEffects of contemporary land-use and land-cover change on the carbon balance of terrestrial ecosystems in the United States
Changes in land use and land cover (LULC) can have profound effects on terrestrial carbon dynamics, yet their effects on the global carbon budget remain uncertain. While land change impacts on ecosystem carbon dynamics have been the focus of numerous studies, few efforts have been based on observational data incorporating multiple ecosystem types spanning large geographic areas over long time horiAuthorsBenjamin M. Sleeter, Jinxun Liu, Colin Daniel, Bronwyn Rayfield, Jason T. Sherba, Todd Hawbaker, Zhiliang Zhu, Paul Selmants, Thomas R. LovelandIntegrating continuous stocks and flows into state-and-transition simulation models of landscape change
State-and-transition simulation models (STSMs) provide a general framework for forecasting landscape dynamics, including projections of both vegetation and land-use/land-cover (LULC) change. The STSM method divides a landscape into spatially-referenced cells and then simulates the state of each cell forward in time, as a discrete-time stochastic process using a Monte Carlo approach, in response toAuthorsColin J. Daniel, Benjamin M. Sleeter, Leonardo Frid, Marie-Josée FortinFuture scenarios of land change based on empirical data and demographic trends
Changes in land use and land cover (LULC) have important and fundamental interactions with the global climate system. Top-down global scale projections of land use change have been an important component of climate change research; however, their utility at local to regional scales is often limited. The goal of this study was to develop an approach for projecting changes in LULC based on land useAuthorsBenjamin M. Sleeter, Tamara S. Wilson, Ethan Sharygin, Jason T. SherbaMediterranean California’s water use future under multiple scenarios of developed and agricultural land use change
With growing demand and highly variable inter-annual water supplies, California’s water use future is fraught with uncertainty. Climate change projections, anticipated population growth, and continued agricultural intensification, will likely stress existing water supplies in coming decades. Using a state-and-transition simulation modeling approach, we examine a broad suite of spatially explicit fAuthorsTamara S. Wilson, Benjamin M. Sleeter, D. Richard CameronClimate impacts on agricultural land use in the USA: the role of socio-economic scenarios
We examine the impacts of climate on net returns from crop and livestock production and the resulting impact on land-use change across the contiguous USA. We first estimate an econometric model to project effects of weather fluctuations on crop and livestock net returns and then use a semi-reduced form land-use share model to study agricultural land-use changes under future climate and socio-econoAuthorsJianhong E. Mu, Benjamin M. Sleeter, John T. Abatzoglou, John M. AntleProjecting community changes in hazard exposure to support long-term risk reduction: A case study of tsunami hazards in the U.S. Pacific Northwest
Tsunamis have the potential to cause considerable damage to communities along the U.S. Pacific Northwest coastline. As coastal communities expand over time, the potential societal impact of tsunami inundation changes. To understand how community exposure to tsunami hazards may change in coming decades, we projected future development (i.e. urban, residential, and rural), households, and residentsAuthorsBenjamin M. Sleeter, Nathan J. Wood, Christopher E. Soulard, Tamara S. WilsonBaseline and projected future carbon storage and carbon fluxes in ecosystems of Hawai‘i
This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act of 2007 and to improve understanding of factors influencing carbon balance in ecosystems of Hawai‘i. Ecosystem carbon storage, carbon fluxes, and carbon balance were examined for major terrestrial ecosystems on the seven main Hawaiian islands in two time periods: baseline (from 2007A carbon balance model for the great dismal swamp ecosystem
BackgroundCarbon storage potential has become an important consideration for land management and planning in the United States. The ability to assess ecosystem carbon balance can help land managers understand the benefits and tradeoffs between different management strategies. This paper demonstrates an application of the Land Use and Carbon Scenario Simulator (LUCAS) model developed for local-scalAuthorsRachel Sleeter, Benjamin M. Sleeter, Brianna Williams, Dianna M. Hogan, Todd Hawbaker, Zhiliang ZhuDivergent projections of future land use in the United States arising from different models and scenarios
A variety of land-use and land-cover (LULC) models operating at scales from local to global have been developed in recent years, including a number of models that provide spatially explicit, multi-class LULC projections for the conterminous United States. This diversity of modeling approaches raises the question: how consistent are their projections of future land use? We compared projections fromAuthorsTerry L. Sohl, Michael Wimberly, Volker C. Radeloff, David M. Theobald, Benjamin M. SleeterEstimating carbon sequestration in the piedmont ecoregion of the United States from 1971 to 2010
Background: Human activities have diverse and profound impacts on ecosystem carbon cycles. The Piedmont ecoregion in the eastern United States has undergone significant land use and land cover change in the past few decades. The purpose of this study was to use newly available land use and land cover change data to quantify carbon changes within the ecoregion. Land use and land cover change data (AuthorsJinxun Liu, Benjamin M. Sleeter, Zhiliang Zhu, Linda S. Heath, Zhengxi Tan, Tamara S. Wilson, Jason T. Sherba, Decheng ZhouState-and-transition simulation models: a framework for forecasting landscape change
SummaryA wide range of spatially explicit simulation models have been developed to forecast landscape dynamics, including models for projecting changes in both vegetation and land use. While these models have generally been developed as separate applications, each with a separate purpose and audience, they share many common features.We present a general framework, called a state-and-transition simAuthorsColin Daniel, Leonardo Frid, Benjamin M. Sleeter, Marie-Josée Fortin