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USGS2010

The need for simultaneous evaluation of ecosystem services and land use change

We are living in a period of massive global change. This rate of change may be almost without precedent in geologic history ( 1 ). Even the most remote areas of the planet are influenced by human activities. Modern landscapes have been highly modified to accommodate a growing human population that the United Nations has forecast to peak at 9.1 billion by 2050. Over this past century, reliance on services from ecosystems has increased significantly and, over past decades, sustainability of our modern, intensively managed ecosystems has been a topic of serious international concern ( 1 ). Numerous papers addressing a particular land-use change effect on specific ecosystem services have recently been published. For example, there is currently great interest in increasing biofuel production to achieve energy inde- pendence goals and recent papers have independently focused attention on impacts of land-use change on single ecosystem services such as carbon sequestration ( 2 ) and many others (e.g., water availability, biodiversity, pollination). However, land-use change clearly affects myriad ecosystem services simultaneously. Hence, a broader perspective and context is needed to evaluate and understand interrelated affects on multiple ecosystem services, especially as we strive for the goal of sustainably managing global ecosystems. Similarly, land uses affect ecosystem services synergistically; single land-use evaluations may be misleading because the overall impact on an ecosystem is not evaluated. A more holistic approach would provide a means and framework to characterize how land-use change affects provisioning of goods and services of complete ecosystems.

Environmental Science & Technology↗

USGS2010

Federal land management, carbon sequestration, and climate change in the Southeastern U.S.: a case study with fort benning

Land use activities can have a major impact on the temporal trendsandspatialpatternsofregionalland-atmosphereexchange of carbon. Federal lands generally have substantially different land management strategies from surrounding areas, and the carbon consequences have rarely been quantified and assessed. Using the Fort Benning Installation as a case study, we used the General Ensemble biogeochemical Modeling System (GEMS) to simulate and compare ecosystem carbon sequestration between the U.S. Army's Fort Benning and surrounding areas from 1992 to 2050. Our results indicate that the military installation sequestered more carbon than surrounding areas from 1992 to 2007 (76.7 vs 18.5 g C m -2 yr -1 ), and is projected to continue sequestering more carbon from 2008 to 2050 (75.7 vs 25.6 g C m -2 yr -1 ), mostly because of the proactive management approaches adopted on military training lands. Our results suggest that federal lands might play a positive and important role in sequestering and conserving atmospheric carbon because some anthropogenic disturbances (e.g., urbanization, forest harvesting, and agriculture) can be minimized or prevented on federal lands

Georgia↗

USGS2025

Land application of biosolid, livestock, and drilling wastes to US farmland: A potential pathway for the redistribution of contaminants in the environment

In the United States (U.S.), waste byproducts generated from the treatment of municipal waste (biosolids), production of livestock (livestock waste), and drilling of oil and gas wells (drilling waste) are commonly applied to agricultural lands. Although this can be a cost-effective reuse/disposal practice, there is limited research on the potential for contaminant exposures and effects on ecosystems, wildlife, and human health from such land applications. In this study, we conducted extensive chemical, microbial, and toxicity analyses of biosolid, livestock, and drilling wastes just prior to land application on agricultural lands at 34 sites across the U.S. Twenty-two analytical methods were used to determine potential contaminant exposures profiles for 452 organic and 114 inorganic chemicals, nine microbial groups, estrogenicity, and cytotoxicity. Analytical results document unique and substantial chemical, microbial, and toxicity profiles for these land-applied wastes. Of the three waste byproducts, biosolids contained the greatest concentrations of household chemicals, pesticides, pharmaceuticals, per-/polyfluoroalkyl substances, calcium, and phosphorus. Livestock waste contained the greatest concentrations of total and leachable dissolved organic carbon, biogenic hormones, mycotoxins, plant estrogens, total inorganic nitrogen, and potassium. Drilling waste contained the greatest concentrations of BTEX compounds (benzene, toluene, ethylbenzene, and xylenes), polycyclic aromatic hydrocarbons, rare-earth elements, barium, strontium, and uranium–thorium series radioisotopes. Biosolid and livestock wastes had greater culturable heterotrophic bacteria, halophilic bacteria, Escherichia coli ( E. coli ), enterococci, and staphylococci concentrations, and greater microbial diversity than drilling waste. Bioassay analyses indicated that exposure to contaminants in livestock wastes and biosolids could result in estrogenic effects, whereas exposure to contaminants in drilling waste could result in cytotoxic effects. Our study documents that current reuse/disposal practices for biosolid, livestock, and drilling wastes on agricultural lands could provide a potential pathway for the redistribution of unique and complex contaminant mixtures into the environment that have bioactive, endocrine disrupting, and carcinogenic characteristics. Results of this study provide a snapshot of chemical compositions and concentrations that can be used to inform the development of best-management practices to help maximize beneficial reuse of these wastes and minimize risk to the environment and human health.

Environmental Science: Processes & Impacts↗

USGS2016

Land-use change reduces habitat suitability for supporting managed honey bee colonies in the Northern Great Plains

Human reliance on insect pollination services continues to increase even as pollinator populations exhibit global declines. Increased commodity crop prices and federal subsidies for biofuel crops, such as corn and soybeans, have contributed to rapid land-use change in the US Northern Great Plains (NGP), changes that may jeopardize habitat for honey bees in a part of the country that supports >40% of the US colony stock. We investigated changes in biofuel crop production and grassland land covers surrounding ∼18,000 registered commercial apiaries in North and South Dakota from 2006 to 2014. We then developed habitat selection models to identify remotely sensed land-cover and land-use features that influence apiary site selection by Dakota beekeepers. Our study demonstrates a continual increase in biofuel crops, totaling 1.2 Mha, around registered apiary locations in North and South Dakota. Such crops were avoided by commercial beekeepers when selecting apiary sites in this region. Furthermore, our analysis reveals how grasslands that beekeepers target when selecting commercial apiary locations are becoming less common in eastern North and South Dakota, changes that may have lasting impact on pollinator conservation efforts. Our study highlights how land-use change in the NGP is altering the landscape in ways that are seemingly less conducive to beekeeping. Our models can be used to guide future conservation efforts highlighted in the US national pollinator health strategy by identifying areas that support high densities of commercial apiaries and that have exhibited significant land-use changes.

North Dakota, South Dakota↗

USGS2008

Deer hunting on Pennsylvania's public and private lands: A two-tiered system of hunters?

Recreational hunting is crucial for controlling white-tailed deer populations. Public land is increasingly important as access to private lands declines. However, differences between public and private land hunters remain unknown. Our study of Pennsylvania hunters revealed differences between private and public land hunters that may pose problems for management. Hunters who only hunted public land had lower harvest rates, especially of antlerless deer, spent less time hunting, were less committed to hunting, were more likely to hunt alone, less likely to belong to a hunting camp, and more likely to live in urban areas. They were less likely to believe that high deer populations could damage forest ecosystems, and less willing to harvest antlerless deer. The implications of these findings, in the context of already-declining hunter capacity to keep deer populations in check, and concomitant declining access to private land, are discussed. Copyright ?? Taylor & Francis Group, LLC.

Human Dimensions of Wildlife↗

USGS2021

The effects of urban land cover dynamics on urban heat Island intensity and temporal trends

Assessments of surface urban heat island (UHI) have focused on using remote sensing and land cover data to quantify UHI intensity and spatial distribution within a certain time period by including land cover information. In this study, we implemented a prototype approach to characterize the spatiotemporal variations of UHI using time series of Landsat land surface temperature products and annual land change information. We analyzed UHI distribution and change in Sioux Falls, South Dakota, in the north-central United States and found that the mean UHI intensity in the region was as large as 2.2°C during the period 1986–2017 with an increasing trend of 0.02°C per year within the area with a 5-km non-urban extent. The UHI intensity associated with high intensity urban land cover usually is stronger than with low intensity urban land cover. We evaluated the impact of different non-urban reference extents on UHI variation using different non-urban buffers. The result also suggests that the overall temporal trends of UHI intensity are almost the same when using a 5-km or 10-km non-urban buffer surrounding the urban core. The prototype approach provides a framework to consistently quantify UHI and monitor its change to a large geographic extent.

South Dakota↗

USGS2021

The contribution of land cover change to the decline of honey yields in the Northern Great Plains

Decreased availability of forage, as well as increased pesticide exposure, are important factors in the decline of honey bee health. Here, we isolate land cover transitions and their effect on honey production at 160 commercial apiaries in the Northern Great Plains. We found that land cover changes from 2008 to 2012 caused an annual decline in honey yields of 0.9% in the study area. Transitions from grassland to soybean (but not corn) were particularly detrimental to honey yields, potentially due to bee contact with pesticides within and around agricultural fields. When our results are applied to known apiary locations across all of North Dakota (U.S.A.), we estimate a 2.5% (1.6 million USD) decline in 2012 honey yields due to land cover changes occurring between 2008 and 2012. Even when controlling for changes in land cover, we found that on average colonies in the study area experienced a 14% annual decline in honey yields. We discuss possible explanations for these non-land-cover-related honey yield declines, including changing economic conditions (e.g. pollination services), changes in land management (e.g. pesticides), and increases in pests or diseases.

South Dakota↗

USGS2022

Grassy–herbaceous land moderates regional climate effects on honey bee colonies in the Northcentral US

The lack of seasonally sustained floral resources (i.e. pollen and nectar) is considered a primary global threat to pollinator health. However, the ability to predict the abundance of flowering resources for pollinators based upon climate, weather, and land cover is difficult due to insufficient monitoring over adequate spatial and temporal scales. Here we use spatiotemporally distributed honey bee hive scales that continuously measure hive weights as a standardized method to assess nectar intake. We analyze late summer colony weight gain as the response variable in a random forest regression model to determine the importance of climate, weather, and land cover on honey bee colony productivity. Our random forest model predicted resource acquisition by honey bee colonies with 71% accuracy, highlighting the detrimental effects of warm, wet regions in the Northcentral United States on nectar intake, as well as the detrimental effect of years with high growing degree day accumulation. Our model also predicted that grassy–herbaceous natural land had a positive effect on the summer nectar flow and that large areas of natural grassy–herbaceous land around apiaries can moderate the detrimental effects of warm, wet climates. These patterns characterize multi-scale ecological processes that constrain the quantity and quality of pollinator nutritional resources. That is, broad climate conditions constrain regional floral communities, while land use and weather act to further modify the quantity and quality of pollinator nutritional resources. Observing such broad-scale trends demonstrates the potential for utilizing hive scales to monitor the effects of climate change on landscape-level floral resources for pollinators. The interaction of climate and land use also present an opportunity to manage for climate-resilient landscapes that support pollinators through abundant floral resources under climate change.

Michigan, Minnesota, North Dakota, Ohio, Pennsylva↗

USGS2008

United states national land cover data base development 1992-2001 and beyond

An accurate, up-to-date and spatially-explicate national land cover database is required for monitoring the status and trends of the nation's terrestrial ecosystem, and for managing and conserving land resources at the national scale. With all the challenges and resources required to develop such a database, an innovative and scientifically sound planning must be in place and a partnership be formed among users from government agencies, research institutes and private sectors. In this paper, we summarize major scientific and technical issues regarding the development of the NLCD 1992 and 2001. Experiences and lessons learned from the project are documented with regard to project design, technical approaches, accuracy assessment strategy, and projecti imiplementation.Future improvements in developing next generation NLCD beyond 2001 are suggested, including: 1) enhanced satellite data preprocessing in correction of atmospheric and adjacency effect and the topographic normalization; 2) improved classification accuracy through comprehensive and consistent training data and new algorithm development; 3) multi-resolution and multi-temporal database targeting major land cover changes and land cover database updates; 4) enriched database contents by including additional biophysical parameters and/or more detailed land cover classes through synergizing multi-sensor, multi-temporal, and multi-spectral satellite data and ancillary data, and 5) transform the NLCD project into a national land cover monitoring program. ?? 2008 IEEE.

Conference Paper↗

USGS2001

A Landsat 7 scene selection strategy for a national land cover database

A strategy for selecting Landsat 7 ETM+ imagery for development of a new generation national land cover database of the United States has been developed. This strategy is formulated to target Landsat 7 ETM+ scenes based on land cover and land use, vegetation phenology and image quality (cloudiness, haze). Criteria based on phenology and scene quality provide a national baseline for acquiring Landsat 7 data. Optimal time periods for discriminating land cover types were identified for each Landsat 7 path-row footprint and each proposed land cover mapping zone (mosaic of several path-rows based on landscape and ecoregion), from which three Landsat scenes were selected. This database of selected scenes is used to guide Landsat 7 data purchasing. This methodology provides a consistent framework for populating Landsat 7 imagery to be used for a new national land cover characterization initiative.

Conference Paper↗

USGS2020

Using value of information to prioritize research needs for migratory bird management under climate change: A case study using federal land acquisition in the United States

In response to global habitat loss, many governmental and non‐governmental organizations have implemented land acquisition programs to protect critical habitats permanently for priority species. The ability of these protected areas to meet future management objectives may be compromised if the effects of climate change are not considered in acquisition decisions. Unfortunately, the effects of climate change on ecological systems are complex and plagued by uncertainty, making it difficult for organizations to prioritize research needs to improve decision‐making. Herein, we demonstrate the use of qualitative value of information analysis to identify and prioritize which sources of uncertainty should be reduced to improve land acquisition decisions to protect migratory birds in the face of climate change. The qualitative value of information analysis process involves four steps: ( i ) articulating alternative hypotheses; ( ii ) determining the magnitude of uncertainty regarding each hypothesis; ( iii ) evaluating the relevance of each hypothesis to acquisition decision‐making; and ( iv ) assessing the feasibility of reducing the uncertainty surrounding each hypothesis through research and monitoring. We demonstrate this approach using the objectives of 3 U.S. federal land acquisition programs that focus on migratory bird management. We used a comprehensive literature review, expert elicitation, and professional judgement to evaluate 11 hypotheses about the effect of climate change on migratory birds. Based on our results, we provide a list of priorities for future research and monitoring to reduce uncertainty and improve land acquisition decisions for the programs considered in our case study. Reducing uncertainty about how climate change will influence the spatial distribution of priority species and biotic homogenization were identified as the highest priorities for future research due to both the value of this information for improving land acquisition decisions and the feasibility of reducing uncertainty through research and monitoring. Research on how changes in precipitation patterns and winter severity will influence migratory bird abundance is also expected to benefit land acquisition decisions. By contrast, hypotheses about phenology and migration distance were identified as low priorities for research. By providing a rigorous and transparent approach to prioritizing research, we demonstrate that qualitative value of information is a valuable tool for prioritizing research and improving management decisions in other complex, high‐uncertainty cases where traditional quantitative value of information analysis is not possible. Given the inherent complexity of ecological systems under climate change, and the difficulty of identifying management‐relevant research priorities, we expect this approach to have wide applications within the field of natural resource management.

Biological Reviews↗

USGS2008

Buruli ulcer disease prevalence in Benin, West Africa: Associations with land use/cover and the identification of disease clusters

Background: Buruli ulcer (BU) disease, caused by infection with the environmental mycobacterium M. ulcerans, is an emerging infectious disease in many tropical and sub-tropical countries. Although vectors and modes of transmission remain unknown, it is hypothesized that the transmission of BU disease is associated with human activities in or around aquatic environments, and that characteristics of the landscape (e.g., land use/cover) play a role in mediating BU disease. Several studies performed at relatively small spatial scales (e.g., within a single village or region of a country) support these hypotheses; however, if BU disease is associated with land use/cover characteristics, either through spatial constraints on vector-host dynamics or by mediating human activities, then large-scale (i.e., country-wide) associations should also emerge. The objectives of this study were to (1) investigate associations between BU disease prevalence in villages in Benin, West Africa and surrounding land use/cover patterns and other map-based characteristics, and (2) identify areas with greater and lower than expected prevalence rates (i.e., disease clusters) to assist with the development of prevention and control programs. Results: Our landscape-based models identified low elevation, rural villages surrounded by forest land cover, and located in drainage basins with variable wetness patterns as being associated with higher BU disease prevalence rates. We also identified five spatial disease clusters. Three of the five clusters contained villages with greater than expected prevalence rates and two clusters contained villages with lower than expected prevalence rates. Those villages with greater than expected BU disease prevalence rates spanned a fairly narrow region of south-central Benin. Conclusion: Our analyses suggest that interactions between natural land cover and human alterations to the landscape likely play a role in the dynamics of BU disease. For example, urbanization, potentially by providing access to protected water sources, may reduce the likelihood of becoming infected with BU disease. Villages located at low elevations may have higher BU disease prevalence rates due to their close spatial proximity to high risk environments. In addition, forest land cover and drainage basins with variable wetness patterns may be important for providing suitable growth conditions for M. ulcerans, influencing the distribution and abundance of vectors, or mediating vector-human interactions. The identification of disease clusters in this study provides direction for future research aimed at better understanding these and other environmental and social determinants involved in BU disease outbreaks. ?? 2008 Wagner et al; licensee BioMed Central Ltd.

International Journal of Health Geographics↗

USGS1994

Designing global land cover databases to maximize utility—the US prototype

One of the most pressing problems in global climate and ecosystem studies is a lack of adequate land cover data. Staff from the United States Geological Survey's EROS Data Center and the University of Nebraska have developed a United States prototype for a proposed global land cover characteristics database derived from 1-km Advanced Very High Resolution Radiometer satellite data. A total of 159 seasonally distinct spectral I temporal land cover classes were labelled according to their constituent vegetation types rather than forcing the vegetation complexes into a predefined classification scheme. The database contains attributes that characterize each land cover class, including elevation, climate attributes and biophysical parameters derived from the normalized difference vegetation index (ND VI). The database design permits convenient translation to a variety of land cover classification schemes commonly used in global scale models. This approach allows scientists to continue using classification schemes with which they are comfortable, eliminates duplicating land cover database development, and provides a degree of uniformity in the development of parallel but distinct databases.

Book chapter↗

USGS2012

History of land cover mapping

The historical roots of land-cover mapping reside in the early history of aerial photography and applications spanning forestry, agriculture, urban planning, and water-resources management. Considering this long span of mapping, any attempt to provide an exhaustive treatment of the full history of land-cover mapping will necessarily be incomplete. For that reason, this chapter on the history of land-cover mapping emphasizes the “modern” era of land-cover mapping, which has been arbitrarily defined to begin in the early 1970s. This was when civil space-based remote sensing came of age, and intellectual efforts focused on strategies for using new observations in understanding the characteristics of, and the changes in, land use and land cover.

Book chapter↗

USGS2017

Mediterranean 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 future land use scenarios and their associated county-level water use demand out to 2062. We examined a range of potential water demand futures sampled from a 20-year record of historical (1992–2012) data to develop a suite of potential future land change scenarios, including low/high change scenarios for urbanization and agriculture as well as “lowest of the low” and “highest of the high” anthropogenic use. Future water demand decreased 8.3 billion cubic meters (Bm 3 ) in the lowest of the low scenario and decreased 0.8 Bm 3 in the low agriculture scenario. The greatest increased water demand was projected for the highest of the high land use scenario (+9.4 Bm 3 ), high agricultural expansion (+4.6 Bm 3 ), and high urbanization (+2.1 Bm 3 ) scenarios. Overall, these scenarios show agricultural land use decisions will likely drive future demand more than increasing municipal and industrial uses, yet improved efficiencies across all sectors could lead to potential water use savings. Results provide water managers with information on diverging land use and water use futures, based on historical, observed land change trends and water use histories.

California↗

USGS2025

Land-use and socioeconomic time-series reveal legacy of redlining on present-day gentrification within a growing United States city

Home Owners’ Loan Corporation (HOLC) maps illustrated patterns of segregation in United States cites in the 1930s. As the causes and drivers of demographic and land-use segregation vary over years, these maps provide an important spatial lens in determining how patterns of segregation spatially and temporally developed during the past century. Using a high-resolution land-use time series (1937-2018) of Denver, Colorado, USA, in conjunction with 80 years of U.S. Census data, we found divergent land-use and demographics patterns across HOLC categories were both pre-existent to the establishment of HOLC mapping and continued to develop over time. Over this period, areas deemed “declining” or “hazardous” had more diverse land use compared to “desirable” areas. “Desirable” areas were dominated by one land-use type (single-family residential), while single-family residential diminished in prominence in the “declining/hazardous” areas. This divergence became more established decades after HOLC mapping, with impact to racial metrics and low-income households. We found changes in these demographic patterns also occurred between 2000 and 2019, highlighting how processes like gentrification can develop from both rapid demographic and land-use changes. This study demonstrates how the legacy of urban segregation develops over decades and can simultaneously persist in some neighborhoods while providing openings for fast-paced gentrification in others.

Colorado↗

USGS2004

The characteristics and interpretability of land surface change and implications for project design

The need for comprehensive, accurate information on land-cover change has never been greater. While remotely sensed imagery affords the opportunity to provide information on land-cover change over large geographic expanses at a relatively low cost, the characteristics of land-surface change bring into question the suitability of many commonly used methodologies. Algorithm-based methodologies to detect change generally cannot provide the same level of accuracy as the analyses done by human interpreters. Results from the Land Cover Trends project, a cooperative venture that includes the U.S. Geological Survey, Environmental Protection Agency, and National Aeronautics and Space Administration, have shown that land-cover conversion is a relatively rare event, occurs locally in small patches, varies geographically and temporally, and is spectrally ambiguous. Based on these characteristics of change and the type of information required, manual interpretation was selected as the primary means of detecting change in the Land Cover Trends project. Mixtures of algorithm-based detection and manual interpretation may often prove to be the most feasible and appropriate design for change-detection applications. Serious examination of the expected characteristics and measurability of change must be considered during the design and implementation phase of any change analysis project.

Photogrammetric Engineering and Remote Sensing↗

USGS2004

Development of a 2001 National Land Cover Database for the United States

Multi-Resolution Land Characterization 2001 (MRLC 2001) is a second-generation Federal consortium designed to create an updated pool of nation-wide Landsat 5 and 7 imagery and derive a second-generation National Land Cover Database (NLCD 2001). The objectives of this multi-layer, multi-source database are two fold: first, to provide consistent land cover for all 50 States, and second, to provide a data framework which allows flexibility in developing and applying each independent data component to a wide variety of other applications. Components in the database include the following: (1) normalized imagery for three time periods per path/row, (2) ancillary data, including a 30 m Digital Elevation Model (DEM) derived into slope, aspect and slope position, (3) perpixel estimates of percent imperviousness and percent tree canopy, (4) 29 classes of land cover data derived from the imagery, ancillary data, and derivatives, (5) classification rules, confidence estimates, and metadata from the land cover classification. This database is now being developed using a Mapping Zone approach, with 66 Zones in the continental United States and 23 Zones in Alaska. Results from three initial mapping Zones show single-pixel land cover accuracies ranging from 73 to 77 percent, imperviousness accuracies ranging from 83 to 91 percent, tree canopy accuracies ranging from 78 to 93 percent, and an estimated 50 percent increase in mapping efficiency over previous methods. The database has now entered the production phase and is being created using extensive partnering in the Federal government with planned completion by 2006.

Photogrammetric Engineering and Remote Sensing↗