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Forest fragmentation and bird community dynamics: Inference at regional scales

With increasing fragmentation of natural areas and a dramatic reduction of forest cover in several parts of the world, quantifying the impact of such changes on species richness and community dynamics has been a subject of much concern. Here, we tested whether in more fragmented landscapes there was a lower number of area-sensitive species and higher local extinction and turnover rates, which could explain higher temporal variability in species richness. To investigate such potential landscape effects at a regional scale, we merged two independent, large-scale monitoring efforts: the North American Breeding Bird Survey (BBS) and the Land Use and Land Cover Classification data from the U.S. Geological Survey. We used methods that accounted for heterogeneity in the probability of detecting species to estimate species richness and temporal changes in the bird communities for BBS routes in three mid-Atlantic U.S. states. Forest breeding bird species were grouped prior to the analyses into area-sensitive and non-area-sensitive species according to previous studies. We tested predictions relating measures of forest structure at one point in time (1974) to species richness at that time and to parameters of forest bird community change over the following 22-yr-period (1975–1996). We used the mean size of forest patches to characterize landscape structure, as high correlations among landscape variables did not allow us to disentangle the relative roles of habitat fragmentation per se and habitat loss. As predicted, together with lower species richness for area-sensitive species on routes surrounded by landscapes with lower mean forest-patch size, we found higher mean year-to-year rates of local extinction. Moreover, the mean year-to-year rates of local turnover (proportion of locally new species) for area-sensitive species were also higher in landscapes with lower mean forest-patch size. These associations were not observed for the non-area-sensitive species group. These results suggest that landscape structure may influence forest bird communities at regional scales through its effects on the total number of species but also on the temporal rates of change in community composition. Evidence for higher rates of local extinction and turnover in more fragmented landscapes suggests that bird communities function as metapopulations at a regional scale, and points out the importance of colonizations and recolonizations from surrounding landscapes to local community dynamics. Further, our results illustrate that the methods used to estimate the community parameters can be a powerful statistical tool in addressing questions relative to the dynamics of communities.

Ecology↗

National land-cover pattern data

Land cover and its spatial patterns are key ingredients in ecological studies that consider large regions and the impacts of human activities. Because land-cover maps show only cover types and their locations, further processing is needed to extract pattern information and to characterize its spatial variability. We are producing a nationally consistent spatial database of six land-cover pattern indices: forest area density, forest connectivity, the U index (a measure of general land-use pressure by humans), land-cover connectivity, land-cover diversity, and landscape pattern types. We use the land-cover maps produced by the Multi-resolution Land Characteristics Consortium for the conterminous United States at 30-m resolution. The goal of this paper is to encourage use of the pattern data as: contextual information and independent variables for studies involving a set of field sites; indicators of landscape conditions for ecological assessments; and dependent variables in biogeographic and socioeconomic models. The new maps will be most useful in studies that require consistent and comparable land-cover pattern measurements over large regions and can be combined with the original land-cover maps and other data.

Ecology↗

Landscape drivers and social dynamics shaping microbial contamination risk in three Maya communities in southern Belize, Central America

Land transformation can have cascading effects on hydrology, water quality, and human users of water resources, with serious implications for human health. An interdisciplinary analysis is presented, whereby remote-sensing data of changing land use and cover are related to surface hydrology and microbial contamination in domestic use areas of three indigenous Maya communities in Belize, Central America. We asked whether a departure from traditional land-use patterns toward intensified use led to consequences for hydrology and microbial contamination of drinking water, and investigated how social factors in the three study communities may act to ameliorate human health risks associated with water contamination. We showed that a departure from traditional land use to more intensive cultivation and grazing led to significantly increased surface water runoff, and intensified microbial contamination of surface water sources sometimes used for drinking. Results further suggested that groundwater contamination was widespread regardless of land cover, due to the widespread presence of pit latrines, pigs, and cows on the landscape, and that human users were consistently subject to health risks from potential pathogens as a result. Given that both surface and groundwater resources were found to be contaminated, it is important that water distribution systems (piped water from tanks; shallow and deep wells) be monitored for Escherichia coli and treated when necessary to reduce or eliminate contaminants and protect public health. Results of interviews suggested that strengthened capacity within the communities to monitor and treat centralized drinking water sources and increase water treatment at the point of use could lead to reduced risk to water consumers.

Water↗

Susceptibility index to surface contamination for the Little Cross Creek watershed, Cumberland County, North Carolina

An index of surface-water contamination potential was constructed for the Little Cross Creek Basin, a 9.7-square-mile, water-supply watershed in Cumberland County, North Carolina. The index was developed because previous water-quality investigations raised concerns regarding inputs of bacteria, suspended sediment, and phosphorus from nonpoint sources in the watershed. A geographic information system was used to build map overlays and to categorize and rate three factors that affect the transport of water and contaminants-land-surface slope, distance to water, and land use/land cover. Each factor was weighted to reflect its potential contribution to surface-water contamination; the factors then were combined to estimate susceptibility values for the entire watershed. The numerical susceptibility values were categorized to indicate lowest to highest potential for surface-water contamination, and a map was produced showing the spatial distribution of these categories within the watershed. The susceptibility index for about 17 percent of the Little Cross Creek watershed is rated in the high or highest category. These areas have high slopes, short distances to the nearest surface water, impervious land cover, and land uses that generate contaminants. About 38 percent of the watershed area is rated as having low or lowest susceptibility to contamination. These areas contain flat terrain, greater distances to water, land cover that promotes infiltration, and land uses that pose little risk for generating contaminants. Approximately 43 percent of the watershed is in the moderate category of susceptibility. Open water, which is not rated, accounts for the remaining area. The susceptibility index provides water-resource managers with a tool that can aid in prioritizing areas within the Little Cross Creek Basin for monitoring, protection, and remediation. Previous suspended sediment, total phosphorus, and fecal coliform data collected in the Little Cross Creek watershed support the results of the susceptibility analysis. Although this susceptibility index is specific to the Little Cross Creek Basin, the methods used to develop the index are transferable to other watersheds.

North Carolina↗

Land-Cover Trends of the Central Basin and Range Ecoregion

The U.S. Geological Survey (USGS) Land Cover Trends research project is focused on understanding the amounts, rates, trends, causes, and implications of contemporary land-use and land-cover (LU/LC) change in the United States. This project is supported by the USGS Geographic Analysis and Monitoring Program in collaboration with the U.S. Environmental Protection Agency (EPA) and the National Aeronautics and Space Administration (NASA). LU/LC change is a pervasive process that modifies landscape characteristics and affects a broad range of socioeconomic, biologic, and hydrologic systems. Understanding the impacts and feedbacks of LU/LC change on environmental systems requires an understanding of the rates, patterns, and driving forces of past, present, and future LU/LC change. The objectives of the Land Cover Trends project are to (1) determine and describe the amount, rates, and trends of contemporary LU/LC change by ecoregion for the period 1973-2000 for the conterminous United States, (2) document the causes, driving forces, and implications of change, and (3) synthesize individual ecoregion results into a national assessment of LU/LC change. The Land Cover Trends research team includes staff from the USGS National Center for Earth Resources Observation and Science (EROS), Rocky Mountain Geographic Science Center, Eastern Geographic Science Center, Mid-Continent Geographic Science Center, and the Western Geographic Science Center. Other partners include researchers at South Dakota State University, University of Southern Mississippi, and State University of New York College of Environmental Science and Forestry. This report presents an assessment of LU/LC change in the Central Basin and Range ecoregion for the period 1973-2000. The Central Basin and Range ecoregion is one of 84 Level-III ecoregions as defined by the Environmental Protection Agency. Ecoregions have served as a spatial framework for environmental resource management and to denote areas that contain a geographically distinct assemblage of biotic and abiotic phenomena including geology, physiography, vegetation, climate, soils, land use, wildlife, and hydrology. The established Land Cover Trends methodology generates estimates of LU/LC change using a probability sampling approach and change-detection analysis of thematic land-cover images derived from Landsat satellite imagery.

Scientific Investigations Report↗

Alaska interim land cover mapping program

In order to meet the requirements of the Alaska National Interest Lands Conservation Act (ANILCA) for comprehensive resource and management plans from all major land management agencies in Alaska, the USGS has begun a program to classify land cover for the entire State using Landsat digital data. Vegetation and land cover classifications, generated in cooperation with other agencies, currently exist for 115 million acres of Alaska. Using these as a base, the USGS has prepared a comprehensive plan for classifying the remaining areas of the State. The development of this program will lead to a complete interim vegetation and land cover classification system for Alaska and allow the dissemination of digital data for those areas classified. At completion, 153 Alaska 1:250,000-scale quadrangles will be published and will include land cover from digital Landsat classifications, statistical summaries of all land cover by township, and computer-compatible tapes. An interagency working group has established an Alaska classification system (table 1) composed of 18 classes modified from "A land use and land cover classification system for use with remote sensor data" (Anderson and others, 1976), and from "Revision of a preliminary classification system for vegetation of Alaska" (Viereck and Dyrness, 1982) for the unique ecoregions which are found in Alaska.

Alaska↗

Spatial models of Northern Bobwhite populations for conservation planning

Since 1980, northern bobwhite (Colinus virginianus) range-wide populations declined 3.9% annually. Within the West Gulf Coastal Plain Bird Conservation Region in the south-central United States, populations of this quail species have declined 6.8% annually. These declines sparked calls for land use change and prompted implementation of various conservation practices. However, to effectively reverse these declines and restore northern bobwhite to their former population levels, habitat conservation and management efforts must target establishment and maintenance of sustainable populations. To provide guidance for conservation and restoration of habitat capable of supporting sustainable northern bobwhite populations in the West Gulf Coastal Plain, we modeled their spatial distribution using landscape characteristics derived from 1992 National Land Cover Data and bird detections, from 1990 to 1994, along 10-stop Breeding Bird Survey route segments. Four landscape metrics influenced detections of northern bobwhite: detections were greater in areas with more grassland and increased aggregation of agricultural lands, but detections were reduced in areas with increased density of land cover edge and grassland edge. Using these landscape metrics, we projected the abundance and spatial distribution of northern bobwhite populations across the entire West Gulf Coastal Plain. Predicted populations closely approximated abundance estimates from a different cadre of concurrently collected data but model predictions did not accurately reflect bobwhite detections along species-specific call-count routes in Arkansas and Louisiana. Using similar methods, we also projected northern bobwhite population distribution circa 1980 based on Land Use Land Cover data and bird survey data from 1976 to 1984. We compared our 1980 spatial projections with our spatial estimate of 1992 populations to identify areas of population change. Additionally, we used our projection of the spatial distribution and abundance of bobwhite to predict areas of population sustainability. Our projections of population change and sustainability provide guidance for targeting habitat conservation and rehabilitation efforts for restoration of northern bobwhite populations in the West Gulf Coastal Plain.

Journal of Wildlife Management↗

Land cover mapping, fire regeneration, and scaling studies in the Canadian boreal forest with 1 km AVHRR and Landsat TM data

A multitemporal 1 km advanced very high resolution radiometer (AVHRR) land cover analysis approach was used as the basis for regional land cover mapping, fire disturbance-regeneration, and multiresolution land cover scaling studies in the boreal forest ecosystem of central Canada. The land cover classification was developed by using regional field observations from ground and low-level aircraft transits to analyze spectral-temporal clusters that were derived from an unsupervised cluster analysis of monthly normalized difference vegetation index (NDVI) image composites (April-September 1992). Quantitative areal proportions of the major boreal forest components were determined for a 821 km ?? 619 km region, ranging from the southern grasslands-boreal forest ecotone to the northern boreal transitional forest. The boreal wetlands (mostly lowland black spruce, tamarack, mosses, fens, and bogs) occupied approximately 33% of the region, while lakes accounted for another 13%. Upland mixed coniferous-deciduous forests represented 23% of the ecosystem. A SW-NE productivity gradient across the region is manifested by three levels of tree stand density for both the boreal wetland conifer and the mixed forest classes, which are generally aligned with isopleths of regional growing degree days. Approximately 30% of the region was directly affected by fire disturbance within the preceding 30-35 years, especially in the Canadian Shield Zone where large fire-regeneration patterns contribute to the heterogeneous boreal landscape. Intercomparisons with land cover classifications derived from 30-m Landsat Thematic Mapper (TM) data provided important insights into the relative accuracy of the 1 km AVHRR land cover classification. Primarily due to the multitemporal NDVI image compositing process, the 1 km AVHRR land cover classes have an effective spatial resolution in the 3-4 km range; therefore fens, bogs, small water bodies, and small patches of dry jack pine cannot be resolved within the wet conifer mosaic. Major differences in the 1-km AVHRR and 30-m Landsat TM-derived land cover classes are most likely due to differences in the spatial resolution of the data sets. In general, the 1 km AVHRR land cover classes are vegetation mosaics consisting of mixed combinations of the Landsat classes. Detailed mapping of the global boreal forest with this approach will benefit from algorithms for cloud screening and to atmospherically correct reflectance data for both aerosol and water vapor effects. We believe that this 1 km AVHRR land cover analysis provides new and useful information for regional water, energy, carbon, and trace gases studies in BOREAS, especially given the significant spatial variability in land cover type and associated biophysical land cover parameters (e.g., albedo, leaf area index, FPAR, and surface roughness). Multiresolution land cover comparisons (30 m, 1 km, and 100 km grid cells) also illustrated how heterogeneous landscape patterns are represented in land cover maps with differing spatial scales and provided insights on the requirements and challenges for parameterizing landscape heterogeneity as part of land surface process research.

Journal of Geophysical Research D: Atmospheres↗

Regional and climatic controls on seasonal dust deposition in the southwestern U.S.

Vertical dust deposition rates (dust flux) are a complex response to the interaction of seasonal precipitation, wind, changes in plant cover and land use, dust source type, and local vs. distant dust emission in the southwestern U.S. Seasonal dust flux in the Mojave–southern Great Basin (MSGB) deserts, measured from 1999 to 2008, is similar in summer–fall and winter–spring, and antecedent precipitation tends to suppress dust flux in winter–spring. In contrast, dust flux in the eastern Colorado Plateau (ECP) region is much larger in summer–fall than in winter–spring, and twice as large as in the MSGB. ECP dust is related to wind speed, and in the winter–spring to antecedent moisture. Higher summer dust flux in the ECP is likely due to gustier winds and runoff during monsoonal storms when temperature is also higher. Source types in the MSGB and land use in the ECP have important effects on seasonal dust flux. In the MSGB, wet playas produce salt-rich dust during wetter seasons, whereas antecedent and current moisture suppress dust emission from alluvial and dry-playa sources during winter–spring. In the ECP under drought conditions, dust flux at a grazed-and-plowed site increased greatly, and also increased at three annualized, previously grazed sites. Dust fluxes remained relatively consistent at ungrazed and currently grazed sites that have maintained perennial vegetation cover. Under predicted scenarios of future climate change, these results suggest that an increase in summer storms may increase dust flux in both areas, but resultant effects will depend on source type, land use, and vegetation cover.

Arizona, California, Nevada, Utah↗

Long-Term Stage, Stage-Residual, and Width Data for Streams in the Piedmont Physiographic Region, Georgia

This report presents the data used to assess geomorphic adjustment of streams over time and to changing land-use conditions. Thirty-seven U.S. Geological Survey streamgages were selected within the Piedmont physiographic region of Georgia. Width, depth, stage, and discharge data from these streams were analyzed to assess channel stability and determine if systematic adjustments of channel morphology could be related to time or land use and land cover. Residual analyses of stage-discharge data were used to infer channel stability, which could then be used as an indicator of habitat stability. Streamgages, representing a gradient of urbanization, were selected to test hypotheses regarding stream stability and adjustment to urban conditions. Results indicate that 14 sites exhibited long-term channel stability, 11 were degrading, 6 were aggrading, and 6 showed variability in response over the study period.

Georgia↗

Simulation of groundwater flow and analysis of the effects of water-management options in the North Platte Natural Resources District, Nebraska

The North Platte Natural Resources District (NPNRD) has been actively collecting data and studying groundwater resources because of concerns about the future availability of the highly inter-connected surface-water and groundwater resources. This report, prepared by the U.S. Geological Survey in cooperation with the North Platte Natural Resources District, describes a groundwater-flow model of the North Platte River valley from Bridgeport, Nebraska, extending west to 6 miles into Wyoming. The model was built to improve the understanding of the interaction of surface-water and groundwater resources, and as an optimization tool, the model is able to analyze the effects of water-management options on the simulated stream base flow of the North Platte River. The groundwater system and related sources and sinks of water were simulated using a newton formulation of the U.S. Geological Survey modular three-dimensional groundwater model, referred to as MODFLOW–NWT, which provided an improved ability to solve nonlinear unconfined aquifer simulations with wetting and drying of cells. Using previously published aquifer-base-altitude contours in conjunction with newer test-hole and geophysical data, a new base-of-aquifer altitude map was generated because of the strong effect of the aquifer-base topography on groundwater-flow direction and magnitude. The largest inflow to groundwater is recharge originating from water leaking from canals, which is much larger than recharge originating from infiltration of precipitation. The largest component of groundwater discharge from the study area is to the North Platte River and its tributaries, with smaller amounts of discharge to evapotranspiration and groundwater withdrawals for irrigation. Recharge from infiltration of precipitation was estimated with a daily soil-water-balance model. Annual recharge from canal seepage was estimated using available records from the Bureau of Reclamation and then modified with canal-seepage potentials estimated using geophysical data. Groundwater withdrawals were estimated using land-cover data, precipitation data, and published crop water-use data. For fields irrigated with surface water and groundwater, surface-water deliveries were subtracted from the estimated net irrigation requirement, and groundwater withdrawal was assumed to be equal to any demand unmet by surface water. The groundwater-flow model was calibrated to measured groundwater levels and stream base flows estimated using the base-flow index method. The model was calibrated through automated adjustments using statistical techniques through parameter estimation using the parameter estimation suite of software (PEST). PEST was used to adjust 273 parameters, grouped as hydraulic conductivity of the aquifer, spatial multipliers to recharge, temporal multipliers to recharge, and two specific recharge parameters. Base flow of the North Platte River at Bridgeport, Nebraska, streamgage near the eastern, downstream end of the model was one of the primary calibration targets. Simulated base flow reasonably matched estimated base flow for this streamgage during 1950–2008, with an average difference of 15 percent. Overall, 1950–2008 simulated base flow followed the trend of the estimated base flow reasonably well, in cases with generally increasing or decreasing base flow from the start of the simulation to the end. Simulated base flow also matched estimated base flow reasonably well for most of the North Platte River tributaries with estimated base flow. Average simulated groundwater budgets during 1989–2008 were nearly three times larger for irrigation seasons than for non-irrigation seasons. The calibrated groundwater-flow model was used with the Groundwater-Management Process for the 2005 version of the U.S. Geological Survey modular three-dimensional groundwater model, MODFLOW–2005, to provide a tool for the NPNRD to better understand how water-management decisions could affect stream base flows of the North Platte River at Bridgeport, Nebr., streamgage in a future period from 2008 to 2019 under varying climatic conditions. The simulation-optimization model was constructed to analyze the maximum increase in simulated stream base flow that could be obtained with the minimum amount of reductions in groundwater withdrawals for irrigation. A second analysis extended the first to analyze the simulated base-flow benefit of groundwater withdrawals along with application of intentional recharge, that is, water from canals being released into rangeland areas with sandy soils. With optimized groundwater withdrawals and intentional recharge, the maximum simulated stream base flow was 15–23 cubic feet per second (ft 3 /s) greater than with no management at all, or 10–15 ft 3 /s larger than with managed groundwater withdrawals only. These results indicate not only the amount that simulated stream base flow can be increased by these management options, but also the locations where the management options provide the most or least benefit to the simulated stream base flow. For the analyses in this report, simulated base flow was best optimized by reductions in groundwater withdrawals north of the North Platte River and in the western half of the area. Intentional recharge sites selected by the optimization had a complex distribution but were more likely to be closer to the North Platte River or its tributaries. Future users of the simulation-optimization model will be able to modify the input files as to type, location, and timing of constraints, decision variables of groundwater withdrawals by zone, and other variables to explore other feasible management scenarios that may yield different increases in simulated future base flow of the North Platte River.

Nebraska↗

Four decades of land-cover change on the Kenai Peninsula, Alaska: Detecting disturbance-influenced vegetation shifts using landsat legacy data

Across Alaska’s Kenai Peninsula, disturbance events have removed large areas of forest over the last half century. Simultaneously, succession and landscape evolution have facilitated forest regrowth and expansion. Detecting forest loss within known pulse disturbance events is often straightforward given that reduction in tree cover is a readily detectable and measurable land-cover change. Land-cover change is more difficult to quantify when disturbance events are unknown, remote, or environmental response is slow in relation to human observation. While disturbance events and related land-cover change are relatively instant, assessing patterns of post-disturbance succession requires long term monitoring. Here, we describe a method for classifying land cover and quantifying land-cover change over time, using Landsat legacy imagery for three historical eras on the western Kenai Peninsula: 1973–2002, 2002–2017, and 1973–2017. Scenes from numerous Landsat sensors, including summer and winter seasons, were acquired between 1973 and 2017 and used to classify vegetation cover using a random forest classifier. Land-cover type was summarized by era and combined to produce a dataset capturing spatially explicit land-cover change at a moderate 30-m resolution. Our results document large-scale forest loss across the study area that can be attributed to known disturbance events including beetle kill and wildfire. Despite numerous and extensive disturbances resulting in forest loss, we estimate that the study area has experienced net forest gain over the duration of our study period due to reforestation within large fire events that predate this study. Transition between forest and graminoid non-forest land cover including wetlands and herbaceous uplands is the most common land-cover change—representing recruitment of a graminoid dominated understory following forest loss and the return of forest canopy given sufficient time post-disturbance.

Alaska↗

Urban land-cover change detection through sub-pixel imperviousness mapping using remotely sensed data

We developed a Sub-pixel Imperviousness Change Detection (SICD) approach to detect urban land-cover changes using Landsat and high-resolution imagery. The sub-pixel percent imperviousness was mapped for two dates (09 March 1993 and 11 March 2001) over western Georgia using a regression tree algorithm. The accuracy of the predicted imperviousness was reasonable based on a comparison using independent reference data. The average absolute error between predicted and reference data was 16.4 percent for 1993 and 15.3 percent for 2001. The correlation coefficient (r) was 0.73 for 1993 and 0.78 for 2001, respectively. Areas with a significant increase (greater than 20 percent) in impervious surface from 1993 to 2001 were mostly related to known land-cover/land-use changes that occurred in this area, suggesting that the spatial change of an impervious surface is a useful indicator for identifying spatial extent, intensity, and, potentially, type of urban land-cover/land-use changes. Compared to other pixel-based change-detection methods (band differencing, rationing, change vector, post-classification), information on changes in sub-pixel percent imperviousness allow users to quantify and interpret urban land-cover/land-use changes based on their own definition. Such information is considered complementary to products generated using other change-detection methods. In addition, the procedure for mapping imperviousness is objective and repeatable, hence, can be used for monitoring urban land-cover/land-use change over a large geographic area. Potential applications and limitations of the products developed through this study in urban environmental studies are also discussed.

Photogrammetric Engineering and Remote Sensing↗

Monitoring changes in Landsat thermal features in urban and non-urban interfaces from 1986 to 2023 in two international urban centers: Implications for climate and global issues

Rapid urbanization is reshaping thermal environments worldwide, with the strongest impacts occurring at the interface between urban and non-urban areas. Impervious surfaces, as key indicators of urban expansion, are critical for monitoring urban growth and assessing surface urban heat island (SUHI) effects. Land use and land cover change (LULCC) provides an essential link between urban dynamics and their environmental and societal consequences. Here, we integrated the U.S. Geological Survey (USGS) Climate Global Issues (CGI) Land Cover Product with Landsat thermal time-series to investigate SUHI evolution in two contrasting metropolitan regions: Wuhan, China, and Brasília, Brazil. Using data spanning 1986–2023, we analyzed the relationships between land cover, Landsat-based land surface temperature (LST), and SUHI intensity, and identified persistent thermal hotspots. Results demonstrate that the land cover data utilized increases the accuracy of impervious surface mapping along urban–rural gradients. Average SUHI intensities were 3.4 °C in Wuhan and 3.3 °C in Brasília, with statistically significant warming trends of 0.04 °C/year and 0.01 °C/year, respectively. Maximum temperature proved to be a robust indicator of SUHI intensification, capturing long-term upward trends. Our findings highlight the important role of urban land cover dynamics in shaping temporal SUHI variability and hotspot emergence. This prototype framework demonstrates the scientific and policy value of combining long-term land cover monitoring information with satellite thermal monitoring to quantify and track SUHI at city scale, supporting sustainable urban planning and climate adaptation strategies.

Remote Sensing↗

Methodology for assessing the accuracy of long-term, annual land cover monitoring at national scale: Experiences from the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative

Annual land cover monitoring using medium-resolution satellite imagery represents a transition from periodic mapping campaigns to continuous observation systems. This transition introduces accuracy assessment challenges not encountered in one-time mapping efforts, particularly when the initial monitoring period is extended forward in time. These challenges are not addressed in existing guidance, which remains largely framed around the evaluation of maps of a single date or maps showing changes between two dates. We present a set of methodological adaptations to adjust to this evolving paradigm, using as a case study the U.S. Geological Survey (USGS) Land Change Monitoring, Assessment, and Projection (LCMAP) initiative, which generated annual land cover and land cover change products across the historical Landsat archive. Assessing the accuracy of these products was an essential component of LCMAP and resulted in an extensive reference sample dataset that may be used for accuracy estimation, area estimation, or support in the development of new algorithms or models. We review the LCMAP methodology and highlight challenges encountered and lessons learned that are transferable to other long-term, temporally dense monitoring programs. This framework demonstrates that statistically rigorous assessment can scale to operational annual land cover production, while the experiences of the project clarify where existing good practice guidance should be extended to support the needs of ongoing, continuous land cover monitoring.

Remote Sensing of Environment↗

Post-wildfire sediment fluxes and turbidity plumes in a coastal-draining watershed

Coastal watersheds impacted by wildfires experience higher erosion resulting in increased sediment delivery to the ocean that alters limiting factors (i.e., light) for marine organisms. With increasing wildfire magnitude and severity, it is critical to explore changes in riverine discharges to the ocean to assess cascading hazards associated with wildfires. In situ data, remotely sensed turbidity data, and hydrological model (Soil and Water Assessment Tool “SWAT”) simulations have been adapted to capture and investigate fire-related land use change impacts on Malibu Creek, California, USA. Modifying SWAT land cover inputs using burn severity data had minimal impact on simulations, requiring additional parameterization for acceptable model performance. Remotely sensed turbidity, in situ discharge, rating curve sediment loads, and SWAT simulated discharge and sediment loads increased following the Woolsey Fire. When compared to in situ and rating curve data in similar non-fire water years, the 2019 Woolsey Fire water year in situ discharge was 1.8 times higher, SWAT simulated discharges were 1.4–1.7 times higher, and rating curve sediment load was 1.3 times higher. However, the SWAT simulated sediment loads were slightly lower (0.8–0.9 times) than rating curve sediment loads in similar non-fire water years. Mean coastal turbidity increased to 18.2 Formazin Nephelometric Unit (FNU) during the first storm post-fire (mean background value of 4.3 FNU). Synergies between methods demonstrated rapid coastal sediment exports (remote sensing) and ongoing erosion post-fire (SWAT). These data are essential to understanding fire-related marine ecological changes and implementing effective management and conservation initiatives.

California↗

Vegetation classification and distribution mapping report: Canyon de Chelly National Monument

Executive Summary: The classification and distribution mapping of the vegetation of Canyon de Chelly National Monument (CACH) and surrounding environment was accomplished through a multi-agency effort between 2003 and 2007. The National Park Service’s Southern Colorado Plateau Network facilitated the team that conducted the work, which comprised the U.S. Geological Survey’s Southwest Biological Science Center and Fort Collins Science Center, Navajo Natural Heritage Program, Northern Arizona University, and NatureServe. The project team described 48 plant communities for CACH—35 of which were described from quantitative classification based on field-relevé data collected in 2004. Five additional plant communities were based on field relevés collected in a previous study. The team derived four additional plant communities from field observations during the photointerpretation phase of the project, and field documented them during accuracy assessment. The National Vegetation Classification Standard served as a conceptual framework for assigning these plant communities to the alliance and association level. Ten of the 48 plant communities were designated “park specials”, that is, plant communities with insufficient data to describe them as new alliances or associations. The project team also developed a spatial vegetation map database representing CACH, with three different map-class schemas: base, group, and management map classes. The base map classes represented the finest level of spatial detail. Photointerpreters delineated initial polygons through manual interpretation of 2003/2004 1:12,000-scale true color aerial photography supplemented by occasional computer screen digitizing on a mosaic of digitized aerial photos. These polygons were labeled with base map classes during photointerpretation. Field visits verified interpretation concepts. The vegetation map database includes • ? 53 base map classes, which consist of associations and park specials classified with the quantitative analysis • ? additional associations noted during photointerpretation • ? non-vegetated land cover, such as infrastructure, land use, and geological land cover. The base map classes consist of 4,718 polygons in the project area. A field-based accuracy assessment of the base map classes showed the overall accuracy to be 50.8% The group map classes represent aggregations of the base map classes, approximating the group level of the National Vegetation Classification Standard, Version 2 (Federal Geographic Data Committee 2008). Terrestrial ecological systems, as described by NatureServe (Comer et al. 2003), were used as a first approximation of the group level. The project team identified 16 group map classes in this project. The overall accuracy of the group map classes was determined using the same accuracy assessment data as for the base map classes. The overall accuracy of the group representation of vegetation was 79.9%. In consultation with park staff, the team developed management map classes that consisted of park-defined groupings of base map classes and were intended to represent a balance between maintaining required accuracy and providing a focus on vegetation of particular interest or import to park managers. The 28 management map classes have an overall accuracy of 77.1%. While the main products of this project are the vegetation classification and the vegetation map database, a number of ancillary geographic information system and digital database products were also produced that can be used independently, or to augment the main products. These products include shapefiles of the location of field-collected data and relational databases of field-collected data.

Report↗

Compilation of water-resources data and hydrogeologic setting for Brunswick County, North Carolina, 1933-2000

Water-resources data were compiled for Brunswick County, North Carolina, to describe the hydrologic conditions of the County. Hydrologic data collected by the U.S. Geological Survey as well as data collected by other governmental agencies and reviewed by the U.S. Geological Survey are presented. Data from four weather stations and two surface-water stations are summarized. Data also are presented for land use and land cover, soils, geology, hydrogeology, 12 continuously monitored ground-water wells, 73 periodically measured ground-water wells, and water-quality measurements from 39 ground-water wells. Mean monthly precipitation at the Longwood, Shallotte, Southport, and Wilmington Airport weather stations ranged from 2.19 to 7.94 inches for the periods of record, and mean monthly temperatures at the Longwood, Southport, and Wilmington Airport weather stations ranged from 43.4 to 80.1 degrees Fahrenheit for the periods of record. An evaluation of land-use and land-cover data for Brunswick County indicated that most of the County is either forested land (about 57 percent) or wetlands (about 29 percent). Cross sections are presented to illustrate the general hydrogeology beneath Brunswick County. Water-level data for Brunswick County indicate that water levels ranged from about 110 feet above mean sea level to about 22 feet below mean sea level. Chloride concentrations measured in aquifers in Brunswick County ranged from near 0 to 15,000 milligrams per liter. Chloride levels in the Black Creek and Cape Fear aquifers were measured at well above the potable limit for ground water of 250 milligrams per liter set by the U.S. Environmental Protection Agency for safe drinking water.

North Carolina↗