Kristi L. Sayler

Exploring subtle land use and land cover changes: a framework for future landscape studies

Land cover and land use changes can have a wide variety of ecological effects, including significant impacts on soils and water quality. In rural areas, even subtle changes in farming practices can affect landscape features and functions, and consequently the environment. Fine-scale analyses have to be performed to better understand the land cover change processes. At the same time, models of land cover change have to be developed in order to anticipate where changes are more likely to occur next. Such predictive information is essential to propose and implement sustainable and efficient environmental policies. Future landscape studies can provide a framework to forecast how land use and land cover changes is likely to react differently to subtle changes. This paper proposes a four step framework to forecast landscape futures at fine scales by coupling scenarios and landscape modelling approaches. This methodology has been tested on two contrasting agricultural landscapes located in the United States and France, to identify possible landscape changes based on forecasting and backcasting agriculture intensification scenarios. Both examples demonstrate that relatively subtle land cover and land use changes can have a large impact on future landscapes. Results highlight how such subtle changes have to be considered in term of quantity, location, and frequency of land use and land cover to appropriately assess environmental impacts on water pollution (France) and soil erosion (US). The results highlight opportunities for improvements in landscape modelling.

Addressing foundational elements of regional land-use change forecasting

Regional land-use models must address several foundational elements, including understanding geographic setting, establishing regional land-use histories, modeling process and representing drivers of change, representing local land-use patterns, managing issues of scale and complexity, and development of scenarios. Key difficulties include managing an array of biophysical and socioeconomic processes across multiple spatial and temporal scales, and acquiring and utilizing empirical data to support the analysis of those processes. The Southeastern and Pacific Northwest regions of the United States, two heavily forested regions with significant forest industries, are examined in the context of these foundational elements. Geographic setting fundamentally affects both the primary land cover (forest) in the two regions, and the structure and form of land use (forestry). Land-use histories of the regions can be used to parameterize land-use models, validate model performance, and explore land-use scenarios. Drivers of change in the two regions are many and varied, with issues of scale and complexity posing significant challenges. Careful scenario development can be used to simplify process-based land-use models, and can improve our ability to address specific research questions. The successful modeling of land-use change in these two areas requires integration of both top-down and bottom-up drivers of change, using scenario frameworks to both guide and simplify the modeling process. Modular approaches, with utilization and integration of existing process models, allow regional land-use modelers the opportunity to better represent primary drivers of land-use change. However, availability of data to represent driving forces remains a primary obstacle.

Spatially explicit modeling of 1992–2100 land cover and forest stand age for the conterminous United States

Information on future land-use and land-cover (LULC) change is needed to analyze the impact of LULC change on ecological processes. The U.S. Geological Survey has produced spatially explicit, thematically detailed LULC projections for the conterminous United States. Four qualitative and quantitative scenarios of LULC change were developed, with characteristics consistent with the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES). The four quantified scenarios (A1B, A2, B1, and B2) served as input to the forecasting scenarios of land-use change (FORE-SCE) model. Four spatially explicit data sets consistent with scenario storylines were produced for the conterminous United States, with annual LULC maps from 1992 through 2100. The future projections are characterized by a loss of natural land covers in most scenarios, with corresponding expansion of anthropogenic land uses. Along with the loss of natural land covers, remaining natural land covers experience increased fragmentation under most scenarios, with only the B2 scenario remaining relatively stable in both the proportion of remaining natural land covers and basic fragmentation measures. Forest stand age was also modeled. By 2100, scenarios and ecoregions with heavy forest cutting had relatively lower mean stand ages compared to those with less forest cutting. Stand ages differed substantially between unprotected and protected forest lands, as well as between different forest classes. The modeled data were compared to the National Land Cover Database (NLCD) and other data sources to assess model characteristics. The consistent, spatially explicit, and thematically detailed LULC projections and the associated forest stand-age data layers have been used to analyze LULC impacts on carbon and greenhouse gas fluxes, biodiversity, climate and weather variability, hydrologic change, and other ecological processes.

THE DRIVING FORCES OF LAND CHANGE IN THE NORTHERN PIEDMONT OF THE UNITED STATES

Abstract. Driving forces facilitate or inhibit land‐use / land‐cover change. Human driving forces include political, economic, cultural, and social attributes that often change across time and space. Remotely sensed imagery provides regional land‐change data for the Northern Piedmont, an ecoregion of the United States that continued to urbanize after 1970 through conversion of agricultural and forest land covers to developed uses. Eight major driving forces facilitated most of the land conversion; other drivers inhibited or slowed change. A synergistic web of drivers may be more important in understanding land change than individual drivers by themselves.

Modelling regional land change scenarios to assess land abandonment and reforestation dynamics in the Pyrenees (France)

Over the last decades and centuries, European mountain landscapes have experienced substantial transformations. Natural and anthropogenic LULC changes (land use and land cover changes), especially agro-pastoral activities, have directly influenced the spatial organization and composition of European mountain landscapes. For the past sixty years, natural reforestation has been occurring due to a decline in both agricultural production activities and rural population. Stakeholders, to better anticipate future changes, need spatially and temporally explicit models to identify areas at risk of land change and possible abandonment. This paper presents an integrated approach combining forecasting scenarios and a LULC changes simulation model to assess where LULC changes may occur in the Pyrenees Mountains, based on historical LULC trends and a range of future socio-economic drivers. The proposed methodology considers local specificities of the Pyrenean valleys, sub-regional climate and topographical properties, and regional economic policies. Results indicate that some regions are projected to face strong abandonment, regardless of the scenario conditions. Overall, high rates of change are associated with administrative regions where land productivity is highly dependent on socio-economic drivers and climatic and environmental conditions limit intensive (agricultural and/or pastoral) production and profitability. The combination of the results for the four scenarios allows assessments of where encroachment (e.g. colonization by shrublands) and reforestation are the most probable. This assessment intends to provide insight into the potential future development of the Pyrenees to help identify areas that are the most sensitive to change and to guide decision makers to help their management decisions.

Modeled historical land use and land cover for the conterminous United States

ABSTRACT The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.

The Southern Piedmont's Continued Land-Use Evolution, 1973–2011

The southern Piedmont in the U.S. was an important farming region during the 19th century, but by the end of the 20th century, agricultural land use had decreased substantially with forest becoming the majority land cover by the 1970s. Geographical literature has documented this change but has not concentrated on the region’s contemporary land uses. The Piedmont currently has three main types of land use and land cover changes: cyclic forestry, changes between forest and agriculture, and urbanization. The first and second groupings are reversible and land uses and land covers can change among them, but urbanization is normally a permanent change that increases in area through time. U.S. Geological Survey findings indicate that cyclic forestry of cutting (clearing) and regrowth dominated recent land change in the Piedmont. This paper explores the Piedmont’s current land uses and some of their driving forces.

Parcels versus pixels: modeling agricultural land use across broad geographic regions using parcel-based field boundaries

ABSTRACT Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land use change model to project parcel-based agricultural change across a large region in the United States Great Plains. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using real parcel boundaries based on contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. The conceptual approach is practical and scalable, with potential use for national-scale projections.

Modeled 2030 land cover for the Northern Glaciated Plains ecoregion

Land use and land cover (LULC) change occurs at a local level within contiguous ownership and management units (parcels), yet LULC models primarily use pixel-based spatial frameworks. The few parcel-based models being used overwhelmingly focus on small geographic areas, limiting the ability to assess LULC change impacts at regional to national scales. We developed a modified version of the Forecasting Scenarios of land-use change (FORE-SCE) model to project parcel-based agricultural change across the Northern Great Plains ecoregion of the Great Plains of the United States. A scenario representing an agricultural biofuel scenario was modeled from 2012 to 2030, using parcel data to represent real, contiguous ownership and land management units. The resulting LULC projection provides a vastly improved representation of landscape pattern over existing pixel-based models, while simultaneously providing an unprecedented combination of thematic detail and broad geographic extent. These data represent 50 individual Monte Carlo runs for the 2012 to 2030 biofuel scenario in the Northern Glaciated Plains ecoregion. Each of the 50 individual runs represents one model realization of the scenario, with uncertainty parameters factored in. Each individual run is thus unique. A combination of the 50 individual runs can be used to assess relative probability of land-use class membership for each pixel in the modeled ecoregion.

Human drivers, biophysical changes, and climatic variation affecting contemporary cropping proportions in the northern prairie of the U.S

ABSTRACT Grassland to cropland conversion in the northern prairie of the United States has been a topic of recent land use change studies. Within this region more corn and soybeans are grown now (2017) than in the past, but most studies to date have not examined multi-decadal trends and the synergistic web of socio-ecological driving forces involved, opting instead for short-term analyses and easily targeted agents of change. This paper examines the coalescing of biophysical and socioeconomic driving forces that have brought change to the agricultural landscape of this region between 1980 and 2013. While land conversion has occurred, most of the region’s cropland in 2013 had been previously cropped by the early 1980s. Furthermore, the agricultural conditions in which crops were grown during those three decades have changed considerably because of non-biophysical alterations to production practices and changing agricultural markets. Findings revealed that human drivers played more of a role in crop change than biophysical changes, that blending quantitative and qualitative methods to tell a more complete story of crop change in this region was difficult because of the synergistic characteristics of the drivers involved, and that more research is needed to understand how farmers make crop choice decisions.