An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California

Benjamin M. Sleeter; Jinxun Liu; Colin Daniel; Leonardo Frid; Zhiliang Zhu

doi:10.3934/environsci.2015.3.577

Home/Archive/USGS

USGS · 70191918

An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California

Benjamin M. Sleeter·Jinxun Liu·Colin Daniel·Leonardo Frid·Zhiliang Zhu

View original source ↗Export metadata ↓

Abstract

Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.

Explore related subjects

AIMS Environmental Science Article

Source-reported bounding extent: 35.46961797120201° to 41.09591205639546° latitude; -122.05810546875° to -117.80639648437499° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Benjamin M. Sleeter, Jinxun Liu, Colin Daniel, Leonardo Frid, Zhiliang Zhu. 2015. An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California. https://doi.org/10.3934/environsci.2015.3.577

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2016

Use of lidar point cloud data to support estimation of residual trace metals stored in mine chat piles in the Old Lead Belt of southeastern, Missouri

Historic lead and zinc (Pb-Zn) mining in southeast Missouri’s ―Old Lead Belt‖ has left large chat piles dominating the landscape where prior to 1972 mining was the major industry of the region. As a result of variable beneficiation methods over the history of mining activity, these piles remain with large quantities of unrecovered Pb and Zn and to a lesser extent cadmium (Cd). Quantifying the residual content of trace metals in chat piles is problematic because of the extensive field effort that must go into collecting elevation points for volumetric analysis. This investigation demonstrates that publicly available lidar point data from the U.S. Geological Survey 3D Elevation Program (3DEP) can be used to effectively calculate chat pile volumes as a method of more accurately estimating the total residual trace metal content in these mining wastes. Five chat piles located in St. Francois County, Missouri, were quantified for residual trace metal content. Utilizing lidar point cloud data collected in 2011 and existing trace metal concentration data obtained during remedial investigations, residual content of these chat piles ranged from 9247 to 88,579 metric tons Pb, 1925 to 52,306 metric tons Zn, and 51 to 1107 metric tons Cd. Development of new beneficiation methods for recovering these constituents from chat piles would need to achieve current Federal soil screening standards. To achieve this for the five chat piles investigated, 42 to 72% of residual Pb would require mitigation to the 1200 mg/kg Federal non-playground standard, 88 to 98% of residual Zn would require mitigation to the Ecological Soil Screening level (ESSL) for plant life, and 70% to 98% of Cd would require mitigation to achieve the ESSL. Achieving these goals through an existing or future beneficiation method(s) would remediate chat to a trace metal concentration level that would support its use as a safe agricultural soil amendment.

Missouri↗

USGS2015

Linking state-and-transition simulation and timber supply models for forest biomass production scenarios

We linked state-and-transition simulation models (STSMs) with an economics-based timber supply model to examine landscape dynamics in North Carolina through 2050 for three scenarios of forest biomass production. Forest biomass could be an important source of renewable energy in the future, but there is currently much uncertainty about how biomass production would impact landscapes. In the southeastern US, if forests become important sources of biomass for bioenergy, we expect increased land-use change and forest management. STSMs are ideal for simulating these landscape changes, but the amounts of change will depend on drivers such as timber prices and demand for forest land, which are best captured with forest economic models. We first developed state-and-transition model pathways in the ST-Sim software platform for 49 vegetation and land-use types that incorporated each expected type of landscape change. Next, for the three biomass production scenarios, the SubRegional Timber Supply Model (SRTS) was used to determine the annual areas of thinning and harvest in five broad forest types, as well as annual areas converted among those forest types, agricultural, and urban lands. The SRTS output was used to define area targets for STSMs in ST-Sim under two scenarios of biomass production and one baseline, business-as-usual scenario. We show that ST-Sim output matched SRTS targets in most cases. Landscape dynamics results indicate that, compared with the baseline scenario, forest biomass production leads to more forest and, specifically, more intensively managed forest on the landscape by 2050. Thus, the STSMs, informed by forest economics models, provide important information about potential landscape effects of bioenergy production.

AIMS Environmental Science↗

USGS2015

Combining state-and-transition simulations and species distribution models to anticipate the effects of climate change

State-and-transition simulation models (STSMs) are known for their ability to explore the combined effects of multiple disturbances, ecological dynamics, and management actions on vegetation. However, integrating the additional impacts of climate change into STSMs remains a challenge. We address this challenge by combining an STSM with species distribution modeling (SDM). SDMs estimate the probability of occurrence of a given species based on observed presence and absence locations as well as environmental and climatic covariates. Thus, in order to account for changes in habitat suitability due to climate change, we used SDM to generate continuous surfaces of species occurrence probabilities. These data were imported into ST-Sim, an STSM platform, where they dictated the probability of each cell transitioning between alternate potential vegetation types at each time step. The STSM was parameterized to capture additional processes of vegetation growth and disturbance that are relevant to a keystone species in the Greater Yellowstone Ecosystem—whitebark pine ( Pinus albicaulis ). We compared historical model runs against historical observations of whitebark pine and a key disturbance agent (mountain pine beetle, Dendroctonus ponderosae ), and then projected the simulation into the future. Using this combination of correlative and stochastic simulation models, we were able to reproduce historical observations and identify key data gaps. Results indicated that SDMs and STSMs are complementary tools, and combining them is an effective way to account for the anticipated impacts of climate change, biotic interactions, and disturbances, while also allowing for the exploration of management options.

AIMS Environmental Science↗