Geology topics

Jodi L. Riegle

Publications and source records attributed to Jodi L. Riegle.

5 recordsLinked to original sources

USGS2020

Causes of land change in the U.S. Interior Highlands, 2001–2011

The causes of land change from 2001 through 2011 for the Interior Highlands region of the south-central United States were assessed using satellite imagery, historical land-use and land-cover data, and digital orthophotos. The study was designed to develop improved regional land-use and land-cover change information, including identification of the proximate causes of change. The four leading causes of land change involved various stages of forest change: harvest (376,497 hectares), reforestation (105,150 hectares), stand loss to fire (98,875 hectares), and thinning (54,029 hectares). The study provides baseline spatial data for understanding human and ecological dynamics in the region. The spatial data, including metadata, are available in the data release associated with this report at https://doi.org/10.5066/P9W4SF05.

Missouri, Arkansas, Oklahoma, Kansas↗

USGS2017

Understanding recurrent land use processes and long-term transitions in the dynamic south-central United States, c. 1800 to 2006

Forests have historically been under significant land use pressures that cause periods of degradation, clearance, and recovery. To understand these changes, studies are needed that place trends in a historical landscape context and also examine recent dynamics. Here, we use historical investigation (c. 1800) and an examination of land use and land cover change between 1973 and 2006 to establish a baseline trajectory of the forested system of the south-central United States (US) plains. The study culminates in a highly detailed accounting of the processes and causes of land change between 2001 and 2006. In the study region, the forest transitioned from early low-intensity use, to clearance for farming and timber, to widespread recovery from degradation beginning in the 1930s. By 1970, the region was transitioning from recovered woodlands to an intensive regime of recurrent timber harvest and replanting. The recurring cycle inherent in intensive silviculture has been the main cause of land change for the past several decades, accounting for more than 95% of the total extent of change between 2001 and 2006. The transition to forest recovery in the south-central US was an important historical occurrence. However, the dynamic post-transition landscape needs to be better understood.

Arkansas, Louisiana, Oklahoma, Texas↗

USGS2015

Assessing landscape change and processes of recurrence, replacement, and recovery in the Southeastern Coastal Plains, USA

The processes of landscape change are complex, exhibiting spatial variability as well as linear, cyclical, and reversible characteristics. To better understand the various processes that cause transformation, a data aggregation, validation, and attribution approach was developed and applied to an analysis of the Southeastern Coastal Plains (SECP). The approach integrates information from available national land-use, natural disturbance, and land-cover data to efficiently assess spatially-specific changes and causes. Between 2001 and 2006, the processes of change affected 7.8 % of the SECP but varied across small-scale ecoregions. Processes were placed into a simple conceptual framework to explicitly identify the type and direction of change based on three general characteristics: replacement, recurrence, and recovery. Replacement processes, whereby a land use or cover is supplanted by a new land use, including urbanization and agricultural expansion, accounted for approximately 15 % of the extent of change. Recurrent processes that contribute to cyclical changes in land cover, including forest harvest/replanting and fire, accounted for 83 %. Most forest cover changes were recurrent, while the extents of recurrent silviculture and forest replacement processes such as urbanization far exceeded forest recovery processes. The total extent of landscape recovery, from prior land use to natural or semi-natural vegetation cover, accounted for less than 3 % of change. In a region of complex change, increases in transitory grassland and shrubland covers were caused by large-scale intensive plantation silviculture and small-scale activities including mining reclamation. Explicit identification of the process types and dynamics presented here may improve the understanding of land-cover change and landscape trajectory.

Alabama, Georgia, Florida, Lousianna, Mississippi,↗

USGS2010

Social values for ecosystem services (SolVES): A GIS application for assessing, mapping, and quantifying the social values of ecosystem services-Documentation and user manual, version 1.0

In response to the need for incorporating quantified and spatially explicit measures of social values into ecosystem services assessments, the Rocky Mountain Geographic Science Center, in collaboration with Colorado State University, has developed a geographic information system application, Social Values for Ecosystem Services (SolVES). SolVES can be used to assess, map, and quantify the perceived social values of ecosystem services. SolVES derives a quantitative social values metric, the Value Index, from a combination of spatial and nonspatial responses to public attitude and preference surveys. SolVES also generates landscape metrics, such as average elevation and distance to water, calculated from spatial data layers describing the underlying physical environment. Using kernel density calculations and zonal statistics, SolVES derives and maps the 10-point Value Index and reports landscape metrics associated with each index value for social value types such as aesthetics, biodiversity, and recreation. This can be repeated for various survey subgroups as distinguished by their attitudes and preferences regarding public uses of the forests such as motorized recreation and logging for fuels reduction. The Value Index provides a basis of comparison within and among survey subgroups to consider the effect of social contexts on the valuation of ecosystem services. SolVES includes regression coefficients linking the predicted value (the Value Index) to landscape metrics. These coefficients are used to generate predicted social value maps using value transfer techniques for areas where primary survey data are not available. SolVES was developed, and will continue to be enhanced through future versions, as a public domain tool to enable decision makers and researchers to map the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding tradeoffs between different ecosystem services in a variety of physical and social contexts.

Open-File Report↗

USGS2007

Global Data Toolset (GDT)

According to the United Nations Environment Programme World Conservation Monitoring Centre (UNEP-WCMC) approximately 60 percent of the data contained in the World Database on Protected Areas (WDPA) has missing or incomplete boundary information. As a result, global analyses based on the WDPA can be inaccurate, and professionals responsible for natural resource planning and priority setting must rely on incomplete geospatial data sets. To begin to address this problem the World Data Center for Biodiversity and Ecology, in cooperation with the U. S. Geological Survey (USGS) Rocky Mountain Geographic Science Center (RMGSC), the National Biological Information Infrastructure (NBII), the Global Earth Observation System, and the Inter-American Biodiversity Information Network (IABIN) sponsored a Protected Area (PA) workshop in Asuncion, Paraguay, in November 2007. The primary goal of this workshop was to train representatives from eight South American countries on the use of the Global Data Toolset (GDT) for reviewing and editing PA data. Use of the GDT will allow PA experts to compare their national data to other data sets, including non-governmental organization (NGO) and WCMC data, in order to highlight inaccuracies or gaps in the data, and then to apply any needed edits, especially in the delineation of the PA boundaries. In addition, familiarizing the participants with the web-enabled GDT will allow them to maintain and improve their data after the workshop. Once data edits have been completed the GDT will also allow the country authorities to perform any required review and validation processing. Once validated, the data can be used to update the global WDPA and IABIN databases, which will enhance analysis on global and regional levels.

Fact Sheet↗