Geology topics

Benjamin M. Sleeter

Publications and source records attributed to Benjamin M. Sleeter.

At least 37 records · Page 2Linked to original sources

USGS2017

Climate 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-economic scenarios. Estimation results show that crop net returns are more sensitive to thermal and less sensitive to moisture variability than livestock net returns; other agricultural land uses substitute cropland use when 30-year averaged degree-days or precipitation are not beneficial for crop production. Under future climate and socio-economic scenarios, we project that crop and livestock net returns are both increasing, but with crop net returns increasing at a higher rate; cropland increases with declines of marginal and pastureland by the end of the twenty-first century. Projections also show that impacts of future climate on agricultural land uses are substantially different and a larger variation of land-use change is evident when socio-economic scenarios are incorporated into the climate impact analysis.

Climatic Change↗

USGS2017

Community for Data Integration 2016 annual report

The Community for Data Integration (CDI) represents a dynamic community of practice focused on advancing science data and information management and integration capabilities across the U.S. Geological Survey and the CDI community. This annual report describes the various presentations, activities, and outcomes of the CDI monthly forums, working groups, virtual training series, and other CDI-sponsored events in fiscal year 2016. The report also describes the objectives and accomplishments of the 13 CDI-funded projects in fiscal year 2016.

Open-File Report↗

USGS2017

A carbon balance model for the great dismal swamp ecosystem

Background Carbon 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-scale land management at the Great Dismal Swamp National Wildlife Refuge. We estimate the net ecosystem carbon balance by considering past ecosystem disturbances resulting from storm damage, fire, and land management actions including hydrologic inundation, vegetation clearing, and replanting. Results We modeled the annual ecosystem carbon stock and flow rates for the 30-year historic time period of 1985–2015, using age-structured forest growth curves and known data for disturbance events and management activities. The 30-year total net ecosystem production was estimated to be a net sink of 0.97 Tg C. When a hurricane and six historic fire events were considered in the simulation, the Great Dismal Swamp became a net source of 0.89 Tg C. The cumulative above and below-ground carbon loss estimated from the South One and Lateral West fire events totaled 1.70 Tg C, while management activities removed an additional 0.01 Tg C. The carbon loss in below-ground biomass alone totaled 1.38 Tg C, with the balance (0.31 Tg C) coming from above-ground biomass and detritus. Conclusions Natural disturbances substantially impact net ecosystem carbon balance in the Great Dismal Swamp. Through alternative management actions such as re-wetting, below-ground biomass loss may have been avoided, resulting in the added carbon storage capacity of 1.38 Tg. Based on two model assumptions used to simulate the peat system, (a burn scar totaling 70 cm in depth, and the soil carbon accumulation rate of 0.36 t C/ha −1 /year −1 for Atlantic white cedar), the total soil carbon loss from the South One and Lateral West fires would take approximately 1740 years to re-amass. Due to the impractical time horizon this presents for land managers, this particular loss is considered permanent. Going forward, the baseline carbon stock and flow parameters presented here will be used as reference conditions to model future scenarios of land management and disturbance.

North Carolina, Virginia↗

USGS2017

Future 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 use histories and demographic trends. We developed a set of stochastic, empirical-based projections of LULC change for the state of California, for the period 2001–2100. Land use histories and demographic trends were used to project a “business-as-usual” (BAU) scenario and three population growth scenarios. For the BAU scenario, we projected developed lands would more than double by 2100. When combined with cultivated areas, we projected a 28% increase in anthropogenic land use by 2100. As a result, natural lands were projected to decline at a rate of 139 km 2 yr −1 ; grasslands experienced the largest net decline, followed by shrublands and forests. The amount of cultivated land was projected to decline by approximately 10%; however, the relatively modest change masked large shifts between annual and perennial crop types. Under the three population scenarios, developed lands were projected to increase 40–90% by 2100. Our results suggest that when compared to the BAU projection, scenarios based on demographic trends may underestimate future changes in LULC. Furthermore, regardless of scenario, the spatial pattern of LULC change was likely to have the greatest negative impacts on rangeland ecosystems.

California↗

USGS2017

Human footprint affects US carbon balance more than climate change

The MC2 model projects an overall increase in carbon capture in conterminous United States during the 21st century while also simulating a rise in fire causing much carbon loss. Carbon sequestration in soils is critical to prevent carbon losses from future disturbances, and we show that natural ecosystems store more carbon belowground than managed systems do. Natural and human-caused disturbances affect soil processes that shape ecosystem recovery and competitive interactions between native, exotics, and climate refugees. Tomorrow's carbon budgets will depend on how land use, natural disturbances, and climate variability will interact and affect the balance between carbon capture and release.

Book chapter↗

USGS2017

Projecting 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 residents over a 50-year period (2011–2061) along the Washington, Oregon, and northern California coasts. We created a spatially explicit, land use/land cover, state-and-transition simulation model to project future developed land use based on historical development trends. We then compared our development projection results to tsunami-hazard zones associated with a Cascadia subduction zone (CSZ) earthquake. Changes in tsunami-hazard exposure by 2061 were estimated for 50 incorporated cities, 7 tribal reservations, and 17 counties relative to current (2011) estimates. Across the region, 2061 population exposure in tsunami-hazard zones was projected to increase by 3880 households and 6940 residents. The top ten communities with highest population exposure to CSZ-related tsunamis in 2011 are projected to remain the areas with the highest population exposure by 2061. The largest net population increases in tsunami-hazard zones were projected in the unincorporated portions of several counties, including Skagit, Coos, and Humboldt. Land-change simulation modeling of projected future development serves as an exploratory tool aimed at helping local governments understand the hazard-exposure implications of community growth and to include this knowledge in risk-reduction planning.

International Journal of Disaster Risk Reduction↗

USGS2016

State-and-transition simulation models: a framework for forecasting landscape change

Summary A 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 simulation model (STSM), which captures a number of these common features, accompanied by a software product, called ST-Sim, to build and run such models. The STSM method divides a landscape into a set of discrete spatial units and simulates the discrete state of each cell forward as a discrete-time-inhomogeneous stochastic process. The method differs from a spatially interacting Markov chain in several important ways, including the ability to add discrete counters such as age and time-since-transition as state variables, to specify one-step transition rates as either probabilities or target areas, and to represent multiple types of transitions between pairs of states. We demonstrate the STSM method using a model of land-use/land-cover (LULC) change for the state of Hawai'i, USA. Processes represented in this example include expansion/contraction of agricultural lands, urbanization, wildfire, shrub encroachment into grassland and harvest of tree plantations; the model also projects shifts in moisture zones due to climate change. Key model output includes projections of the future spatial and temporal distribution of LULC classes and moisture zones across the landscape over the next 50 years. State-and-transition simulation models can be applied to a wide range of landscapes, including questions of both land-use change and vegetation dynamics. Because the method is inherently stochastic, it is well suited for characterizing uncertainty in model projections. When combined with the ST-Sim software, STSMs offer a simple yet powerful means for developing a wide range of models of landscape dynamics.

Methods in Ecology and Evolution↗

USGS2016

Estimating 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 (60-m spatial resolution) derived from sequential remotely sensed Landsat imagery were used to generate 960-m resolution land cover change maps for the Piedmont ecoregion. These maps were used in the Integrated Biosphere Simulator (IBIS) to simulate ecosystem carbon stock and flux changes from 1971 to 2010. Results: Results show that land use change, especially urbanization and forest harvest had significant impacts on carbon sources and sinks. From 1971 to 2010, forest ecosystems sequestered 0.25 Mg C ha−1 yr−1, while agricultural ecosystems sequestered 0.03 Mg C ha−1 yr−1. The total ecosystem C stock increased from 2271 Tg C in 1971 to 2402 Tg C in 2010, with an annual average increase of 3.3 Tg C yr−1. Conclusions: Terrestrial lands in the Piedmont ecoregion were estimated to be weak net carbon sink during the study period. The major factors contributing to the carbon sink were forest growth and afforestation; the major factors contributing to terrestrial emissions were human induced land cover change, especially urbanization and forest harvest. An additional amount of carbon continues to be stored in harvested wood products. If this pool were included the carbon sink would be stronger. Keywords: Land-use change, Carbon change, Piedmont ecoregion, IBIS model

Carbon Balance and Management↗

USGS2016

Future land-use related water demand in California

Water shortages in California are a growing concern amidst ongoing drought, earlier spring snowmelt, projected future climate warming, and currently mandated water use restrictions. Increases in population and land use in coming decades will place additional pressure on already limited available water supplies. We used a state-and-transition simulation model to project future changes in developed (municipal and industrial) and agricultural land use to estimate associated water use demand from 2012 to 2062. Under current efficiency rates, total water use was projected to increase 1.8 billion cubic meters(+4.1%) driven primarily by urbanization and shifts to more water intensive crops. Only if currently mandated 25% reductions in municipal water use are continuously implemented would water demand in 2062 balance to water use levels in 2012. This is the first modeling effort of its kind to examine regional land-use related water demand incorporating historical trends of both developed and agricultural land uses.

California↗

USGS2016

Divergent 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 from six LULC modeling applications for the United States and assessed quantitative, spatial, and conceptual inconsistencies. Each set of projections provided multiple scenarios covering a period from roughly 2000 to 2050. Given the unique spatial, thematic, and temporal characteristics of each set of projections, individual projections were aggregated to a common set of basic, generalized LULC classes (i.e., cropland, pasture, forest, range, and urban) and summarized at the county level across the conterminous United States. We found very little agreement in projected future LULC trends and patterns among the different models. Variability among scenarios for a given model was generally lower than variability among different models, in terms of both trends in the amounts of basic LULC classes and their projected spatial patterns. Even when different models assessed the same purported scenario, model projections varied substantially. Projections of agricultural trends were often far above the maximum historical amounts, raising concerns about the realism of the projections. Comparisons among models were hindered by major discrepancies in categorical definitions, and suggest a need for standardization of historical LULC data sources. To capture a broader range of uncertainties, ensemble modeling approaches are also recommended. However, the vast inconsistencies among LULC models raise questions about the theoretical and conceptual underpinnings of current modeling approaches. Given the substantial effects that land-use change can have on ecological and societal processes, there is a need for improvement in LULC theory and modeling capabilities to improve acceptance and use of regional- to national-scale LULC projections for the United States and elsewhere.

Ecological Modelling↗

USGS2016

The potential carbon benefit of reforesting Hawai‘i Island non-native grasslands with endemic Acacia koa trees

Large areas of forest in the tropics have been cleared and converted to pastureland. Hawai‘i Island is no exception, with over 100,000 ha of historically forested land now dominated by non-native grasses. Passive forest restoration has been unsuccessful because these grasslands tend to persist even after grazers have been removed, yet active outplanting of native tree species can be cost-prohibitive at the landscape scale. It is therefore essential to seek co-benefits of forest restoration to defray costs, such as accredited carbon offsets from increased carbon sequestration. We developed a reforestation scenario for non-native grasslands on Hawai‘i Island by outplanting endemic koa ( Acacia koa ) trees paid for with carbon offsets via the California Cap and Trade Program. This scenario entails reforesting 53,531 ha of non-native grassland at 2500 ha y-1 over 22 years. We estimated planting costs at \$6,178 ha-1, a total cost of approximately \$331,000,000. We used the Land Use and Carbon Simulator (LUCAS) model to estimate island-wide ecosystem carbon sequestration with and without koa reforestation using 100 Monte Carlo simulations per year over a 60-year period. Income from carbon offsets was set at \$13.57 per ton of CO 2 equivalent, the current California Cap and Trade Program carbon market price.

Hawai'i↗

USGS2015

Projected carbon stocks in the conterminous USA with land use and variable fire regimes

The dynamic global vegetation model (DGVM) MC2 was run over the conterminous USA at 30 arc sec (~800 m) to simulate the impacts of nine climate futures generated by 3GCMs (CSIRO, MIROC and CGCM3) using 3 emission scenarios (A2, A1B and B1) in the context of the LandCarbon national carbon sequestration assessment. It first simulated potential vegetation dynamics from coast to coast assuming no human impacts and naturally occurring wildfires. A moderate effect of increased atmospheric CO 2 on water use efficiency and growth enhanced carbon sequestration but did not greatly influence woody encroachment. The wildfires maintained prairie‐forest ecotones in the Great Plains. With simulated fire suppression, the number and impacts of wildfires was reduced as only catastrophic fires were allowed to escape. This greatly increased the expansion of forests and woodlands across the western USA and some of the ecotones disappeared. However, when fires did occur, their impacts (both extent and biomass consumed) were very large. We also evaluated the relative influence of human land use including forest and crop harvest by running the DGVM with land use (and fire suppression) and simple land management rules. From 2041 through 2060, carbon stocks (live biomass, soil and dead biomass) of US terrestrial ecosystems varied between 155 and 162 Pg C across the three emission scenarios when potential natural vegetation was simulated. With land use, periodic harvest of croplands and timberlands as well as the prevention of woody expansion across the West reduced carbon stocks to a range of 122–126 Pg C, while effective fire suppression reduced fire emissions by about 50%. Despite the simplicity of our approach, the differences between the size of the carbon stocks confirm other reports of the importance of land use on the carbon cycle over climate change.

Global Change Biology↗

USGS2015

Projecting the spatiotemporal carbon dynamics of the Greater Yellowstone Ecosystem from 2006 to 2050

Background Climate change and the concurrent change in wildfire events and land use comprehensively affect carbon dynamics in both spatial and temporal dimensions. The purpose of this study was to project the spatial and temporal aspects of carbon storage in the Greater Yellowstone Ecosystem (GYE) under these changes from 2006 to 2050. We selected three emission scenarios and produced simulations with the CENTURY model using three General Circulation Models (GCMs) for each scenario. We also incorporated projected land use change and fire occurrence into the carbon accounting. Results The three GCMs showed increases in maximum and minimum temperature, but precipitation projections varied among GCMs. Total ecosystem carbon increased steadily from 7,942 gC/m 2 in 2006 to 10,234 gC/m 2 in 2050 with an annual rate increase of 53 gC/m 2 /year. About 56.6% and 27% of the increasing rate was attributed to total live carbon and total soil carbon, respectively. Net Primary Production (NPP) increased slightly from 260 gC/m 2 /year in 2006 to 310 gC/m 2 /year in 2050 with an annual rate increase of 1.22 gC/m 2 /year. Forest clear-cutting and fires resulted in direct carbon removal; however, the rate was low at 2.44 gC/m 2 /year during 2006–2050. The area of clear-cutting and wildfires in the GYE would account for 10.87% of total forested area during 2006–2050, but the predictive simulations demonstrated different spatial distributions in national forests and national parks. Conclusions The GYE is a carbon sink during 2006–2050. The capability of vegetation is almost double that of soil in terms of sequestering extra carbon. Clear-cutting and wildfires in GYE will affect 10.87% of total forested area, but direct carbon removal from clear-cutting and fires is 109.6 gC/m 2 , which accounts for only 1.2% of the mean ecosystem carbon level of 9,056 gC/m 2 , and thus is not significant.

Greater Yellowstone Ecosystem↗

USGS2015

Integrated climate and land use change scenarios for California rangeland ecosystem services: wildlife habitat, soil carbon, and water supply

Context In addition to biodiversity conservation, California rangelands generate multiple ecosystem services including livestock production, drinking and irrigation water, and carbon sequestration. California rangeland ecosystems have experienced substantial conversion to residential land use and more intensive agriculture. Objectives To understand the potential impacts to rangeland ecosystem services, we developed six spatially explicit (250 m) climate/land use change scenarios for the Central Valley of California and surrounding foothills consistent with three Intergovernmental Panel on Climate Change emission scenario narratives. Methods We quantified baseline and projected change in wildlife habitat, soil organic carbon (SOC), and water supply (recharge and runoff). For six case study watersheds we quantified the interactions of future development and changing climate on recharge, runoff and streamflow, and precipitation thresholds where dominant watershed hydrological processes shift through analysis of covariance. Results The scenarios show that across the region, habitat loss is expected to occur predominantly in grasslands, primarily due to future development (up to a 37 % decline by 2100), however habitat loss in priority conservation errors will likely be due to cropland and hay/pasture expansion (up to 40 % by 2100). Grasslands in the region contain approximately 100 teragrams SOC in the top 20 cm, and up to 39 % of this SOC is subject to conversion by 2100. In dryer periods recharge processes typically dominate runoff. Future development lowers the precipitation value at which recharge processes dominate runoff, and combined with periods of drought, reduces the opportunity for recharge, especially on deep soils. Conclusion Results support the need for climate-smart land use planning that takes recharge areas into account, which will provide opportunities for water storage in dry years. Given projections for agriculture, more modeling is needed on feedbacks between agricultural expansion on rangelands and water supply.

California↗

USGS2015

Land-use impacts on water resources and protected areas: applications of state-and-transition simulation modeling of future scenarios

Human land use will increasingly contribute to habitat loss and water shortages in California, given future population projections and associated land-use demand. Understanding how land-use change may impact future water use and where existing protected areas may be threatened by land-use conversion will be important if effective, sustainable management approaches are to be implemented. We used a state-and-transition simulation modeling (STSM) framework to simulate spatially-explicit (1 km 2 ) historical (1992-2010) and future (2011-2060) land-use change for 52 California counties within Mediterranean California ecoregions. Historical land use and land cover (LULC) change estimates were derived from the Farmland Mapping and Monitoring Program dataset and attributed with county-level agricultural water-use data from the California Department of Water Resources. Five future alternative land-use scenarios were developed and modeled using the historical land-use change estimates and land-use projections based on the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios A2 and B1 scenarios. Spatial land-use transition outputs across scenarios were combined to reveal scenario agreement and a land conversion threat index was developed to evaluate vulnerability of existing protected areas to proximal land conversion. By 2060, highest LULC conversion threats were projected to impact nearly 10,500 km 2 of land area within 10 km of a protected area boundary and over 18,000 km 2 of land area within essential habitat connectivity areas. Agricultural water use declined across all scenarios perpetuating historical drought-related land use from 2008-2010 and trends of annual cropland conversion into perennial woody crops. STSM is useful in analyzing land-use related impacts on water resource use as well as potential threats to existing protected land. Exploring a range of alternative, yet plausible, LULC change impacts will help to better inform resource management and mitigation strategies.

California↗

USGS2015

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

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.

California↗

USGS2015

Downscaling global land-use/land-cover projections for use in region-level state-and-transition simulation modeling

Global land-use/land-cover (LULC) change projections and historical datasets are typically available at coarse grid resolutions and are often incompatible with modeling applications at local to regional scales. The difficulty of downscaling and reapportioning global gridded LULC change projections to regional boundaries is a barrier to the use of these datasets in a state-and-transition simulation model (STSM) framework. Here we compare three downscaling techniques to transform gridded LULC transitions into spatial scales and thematic LULC classes appropriate for use in a regional STSM. For each downscaling approach, Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) LULC projections, at the 0.5 × 0.5 cell resolution, were downscaled to seven Level III ecoregions in the Pacific Northwest, United States. RCP transition values at each cell were downscaled based on the proportional distribution between ecoregions of (1) cell area, (2) land-cover composition derived from remotely-sensed imagery, and (3) historic LULC transition values from a LULC history database. Resulting downscaled LULC transition values were aggregated according to their bounding ecoregion and “cross-walked” to relevant LULC classes. Ecoregion-level LULC transition values were applied in a STSM projecting LULC change between 2005 and 2100. While each downscaling methods had advantages and disadvantages, downscaling using the historical land-use history dataset consistently apportioned RCP LULC transitions in agreement with historical observations. Regardless of the downscaling method, some LULC projections remain improbable and require further investigation.

AIMS Environmental Science↗

USGS2015

Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

AIMS Environmental Science↗