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At least 883 records · Page 49Linked to original sources

USGS2015

Developing a 30-m grassland productivity estimation map for central Nebraska using 250-m MODIS and 30-m Landsat-8 observations

Accurately estimating aboveground vegetation biomass productivity is essential for local ecosystem assessment and best land management practice. Satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. A 250-m grassland biomass productivity map for the Greater Platte River Basin had been developed based on the relationship between Moderate Resolution Imaging Spectroradiometer (MODIS) GSN and Soil Survey Geographic (SSURGO) annual grassland productivity. However, the 250-m MODIS grassland biomass productivity map does not capture detailed ecological features (or patterns) and may result in only generalized estimation of the regional total productivity. Developing a high or moderate spatial resolution (e.g., 30-m) productivity map to better understand the regional detailed vegetation condition and ecosystem services is preferred. The 30-m Landsat data provide spatial detail for characterizing human-scale processes and have been successfully used for land cover and land change studies. The main goal of this study is to develop a 30-m grassland biomass productivity estimation map for central Nebraska, leveraging 250-m MODIS GSN and 30-m Landsat data. A rule-based piecewise regression GSN model based on MODIS and Landsat (r = 0.91) was developed, and a 30-m MODIS equivalent GSN map was generated. Finally, a 30-m grassland biomass productivity estimation map, which provides spatially detailed ecological features and conditions for central Nebraska, was produced. The resulting 30-m grassland productivity map was generally supported by the SSURGO biomass production map and will be useful for regional ecosystem study and local land management practices.

Nebraska↗

USGS2024

Enhancing assessments of coastal wetland migration potential with sea-level rise: Accounting for uncertainty in elevation data, tidal data, and future water levels

Sea-level rise rates are predicted to surpass rates of wetland vertical adjustment in the coming decades in many areas, increasing the potential for wetland submergence. Information on where wetland migration is possible can help natural resource managers for planning land acquisition or enhancing habitat connectivity to bolster adaptation of coastal wetlands to rising seas. Elevation-based models of wetland migration are often hampered with uncertainty associated with ground surface elevation, current water levels (i.e., tides and extreme water levels), and future water levels from sea-level rise. Here, we developed an approach that involved digital elevation model error reduction and the use of Monte Carlo simulations that utilize uncertainty assumptions regarding elevation error, contemporary water levels, and future sea levels to identify potential wetland migration areas. Our analyses were developed for Duvall and Nassau Counties in northeastern Florida (USA). We focus on the migration of regularly oceanic-flooded wetlands (i.e., flooded by oceanic water daily) and irregularly oceanic-flooded wetlands (i.e., flooded by oceanic water less frequently than daily). For two relative sea-level rise scenarios based on the 0.5 m and the 1.5 m global mean sea-level rise scenarios, we quantified migration by wetland flooding frequency class and identified land cover and land use types that are vulnerable to future exposure to oceanic waters. The variability in total coverage and relative coverage of wetland migration from our results highlights how topography and accelerated sea-level rise interact. Our wetland migration results communicate uncertainty by showing flooding frequency class as probabilistic outputs.

Florida↗

USGS2023

Trade-offs in adapting to changes in climate, land use, and water availability in California

Changes in land use and land cover, water systems, and climate are inextricably linked, and their combined stresses have had severe impacts in many regions worldwide. Integrated adaptation planning can support adaptive capacity by helping institutions manage land and water resources at regional to local scales. Linkages between these stressors mean that planners are often faced with potential trade-offs, and how to couple social and environmental sustainability remains a key question. We explore these questions in California’s Central Coast, a region that is already experiencing serious water shortages, housing shortages, rapid expansion of perennial agriculture, and severe droughts that are projected to become worse with climate change. Linked models of land use change (the Land Use and Carbon + Water Simulator [LUCAS-W]), water resources (LUCAS-W), and climate (the Basin Characterization Model [BCM]) produced forecasts of exposure to regional changes at 270-m resolution. We worked with regional stakeholders to develop a matrix of nine vulnerability measures that assessed key sensitivities to these changes. Each vulnerability measure combined one of the three exposure projections with spatial datasets representing one of three sensitivity communities (agricultural, domestic, or ecological). We assessed how five scenarios of land-use and water management strategies under consideration by regional planners could provide institutional, top-down adaptive capacity, and whether there were trade-offs in sustainable development goals for these communities. We found that specific land and water management strategies could greatly reduce regional vulnerability, particularly programs to cap water extractions to sustainable levels. The most dramatic trade-off was between the strategy of water demand caps that increased risk of habitat loss and ecosystem preservation that increased water vulnerability. However, trade-offs were usually limited and spatially localized, suggesting local tailoring of the strategies we assessed could reduce them. Trade-offs were more frequent across exposure classes (land use vs. water vs. climate changes) rather than sensitivity classes (agricultural vs. domestic vs. ecological communities), suggesting win-win opportunities for natural resource management. Our vulnerability maps can inform prioritization efforts for local adaptation planning.

California↗

USGS2008

Quality of Shallow Ground Water in Three Areas of Unsewered Low-Density Development in Wyoming and Montana, 2001

The quality of shallow ground water underlying unsewered low-density development outside of Sheridan and Lander, Wyo., and Red Lodge, Mont., was evaluated. In 2001, 29 wells (10 each in Sheridan and Lander and 9 in Red Lodge) were installed at or near the water table and sampled for a wide variety of constituents to identify potential effects of human activities on shallow ground-water quality resulting from development on the land surface. All wells were completed in unconfined aquifers in unconsolidated deposits of Quaternary age with shallow water tables (less than 50 feet below land surface). Land use and land cover was mapped in detail within a 500-meter radius surrounding each well, and potential contaminant sources were inventoried within the radii to identify human activities that may affect shallow ground-water quality. This U.S. Geological Survey National Water-Quality Assessment ground-water study was conducted to examine the effects of unsewered low-density development that often surrounds cities and towns of many different sizes in the western United States?a type of development that often is informally referred to as ?exurban? or ?rural ranchette? development. This type of development has both urban and rural characteristics. Residents in these developments typically rely on a private ground-water well for domestic water supply and a private septic system for sanitary waste disposal. Although the quality of shallow ground water generally was suitable for domestic or other uses without treatment, some inorganic constituents were detected infrequently in ground water in the three study areas at concentrations larger than U.S. Environmental Protection Agency drinking-water standards or proposed standards. Natural factors such as geology, aquifer properties, and ground-water recharge rates likely influence most concentrations of these constituents. These inorganic constituents generally occur naturally in the study areas and were more likely to limit suitability of water for drinking or other intended uses rather than any constituents suspected of being introduced as a result of human activities. Effects of human activities associated with low-density development, such as septic systems; fertilizer and pesticide use on pastures, lawns and gardens; manure from horses, cattle, and pets; and increases in road construction and vehicular traffic, were minimal at the time of sampling (2001) but were apparent in the presence of a few types of constituents in shallow ground water. Concentrations of nitrate generally were less than a national background level (1.1 milligrams per liter) assumed to indicate effects from human activities. Total coliform bacteria were detected infrequently (in samples from three wells), and Escherichia coli were not detected in samples from a subset of wells. Trace concentrations of methylene blue active substances (ingredients in laundry detergents) were detected at concentrations slightly greater than laboratory reporting levels in samples from 11 wells, but it is unclear if the detections are indicative of natural sources or possible aquifer contamination from septic-tank effluent. Pesticides were detected in both the Sheridan and Lander, Wyo., study areas. Volatile organic compounds were detected very infrequently in all three study areas. Most pesticides and volatile organic compounds were found in water from a few wells in each study area, and commonly as mixtures. The primary exception to this generalization was the relatively widespread detection of the pesticide prometon at trace levels in the Sheridan and Lander study areas. Concentrations of pesticides and volatile organic compounds generally were small and always were smaller than applicable drinking-water standards. Detections of all constituents indicating possible human effects on shallow ground-water quality were consistent with overlying land use mapped during the study, and potential sources of contamination inventoried du

Scientific Investigations Report↗

USGS2016

How will predicted land-use change affect waterfowl spring stopover ecology? Inferences from an individual-based model

Habitat loss, habitat fragmentation, overexploitation and climate change pose familiar and new challenges to conserving natural populations throughout the world. One approach conservation planners may use to evaluate the effects of these challenges on wildlife populations is scenario planning. We developed an individual-based model to evaluate the effects of future land use and land cover changes on spring-migrating dabbling ducks in North America. We assessed the effects of three Intergovernmental Panel on Climate Change emission scenarios (A1B, A2 and B1) on dabbling duck stopover duration, movement distances and mortality. We specifically focused on migration stopover duration because previous research has demonstrated that individuals arriving earlier on the nesting grounds exhibit increased reproductive fitness. Compared to present conditions, all three scenarios increased stopover duration and movement distances of agent ducks. Although all three scenarios presented migrating ducks with increased amounts of wetland habitat, scenarios also contained substantially less cropland, which decreased overall carrying capacity of the study area. Synthesis and applications . Land-use change may increase waterfowl spring migration stopover duration in the midcontinent region of North America due to reduced landscape energetic carrying capacity. Climate change will alter spatial patterns of crop distributions with corn and rice production areas shifting to different regions. Thus, conservation planners will have to address population-level energetic implications of shifting agricultural food resources and increased uncertainty in yearly precipitation patterns within the next 50 years.

Journal of Applied Ecology↗

USGS2015

Simulating forest landscape disturbances as coupled human and natural systems

Anthropogenic disturbances resulting from human land use affect forest landscapes over a range of spatial and temporal scales, with diverse influences on vegetation patterns and dynamics. These processes fall within the scope of the coupled human and natural systems (CHANS) concept, which has emerged as an important framework for understanding the reciprocal interactions and feedbacks that connect human activities and ecosystem responses. Spatial simulation modeling of forest landscape change is an important technique for exploring the dynamics of CHANS over large areas and long time periods. Landscape models for simulating interactions between human activities and forest landscape dynamics can be grouped into two main categories. Forest landscape models (FLMs) focus on landscapes where forests are the dominant land cover and simulate succession and natural disturbances along with forest management activities. In contrast, land change models (LCMs) simulate mosaics of different land cover and land use classes that include forests in addition to other land uses such as developed areas and agricultural lands. There are also several examples of coupled models that combine elements of FLMs and LCMs. These integrated models are particularly useful for simulating human–natural interactions in landscapes where human settlement and agriculture are expanding into forested areas. Despite important differences in spatial scale and disciplinary scope, FLMs and LCMs have many commonalities in conceptual design and technical implementation that can facilitate continued integration. The ultimate goal will be to implement forest landscape disturbance modeling in a CHANS framework that recognizes the contextual effects of regional land use and other human activities on the forest ecosystem while capturing the reciprocal influences of forests and their disturbances on the broader land use mosaic.

Book chapter↗

USGS2004

Digital data used to relate nutrient inputs to water quality in the Chesapeake Bay watershed, version 3.0

Chesapeake Bay restoration efforts are focused on improving water quality, living resources, and ecological habitats by 2010. One aspect of the water-quality restoration is the refinement of strategies designed to implement nutrient-reduction practices within the Bay watershed. These strategies are being refined and implemented by resource managers of the Chesapeake Bay Program (CBP), a partnership comprised of various Federal, State, and local agencies that includes jurisdictions within Delaware, Maryland, New York, Pennsylvania, Virginia, West Virginia, and the District of Columbia. The U.S. Geological Survey (USGS), an active member of the CBP, provides necessary water-quality information for these Chesapeake Bay nutrient-reduction strategy revisions and evaluations. The formulation and revision of effective nutrient-reduction strategies requires detailed scientific information and an analytical understanding of the sources, transport, and delivery of nutrients to the Chesapeake Bay. The USGS is supporting these strategies by providing scientific information to resource managers that can help them evaluate and understand these processes. One statistical model available to resource managers is a collection of SPAtially Referenced Regressions On Watershed (SPARROW) attributes, which uses a nonlinear regression approach to spatially relate nutrient sources and watershed characteristics to nutrient loads of streams throughout the Chesapeake Bay watershed. Developed by the USGS, information generated by SPARROW can help resource managers determine the geographical distribution and relative contribution of nutrient sources and the factors that affect their transport to the Bay. Nutrient source information representing the late 1990s time period was obtained from several agencies and used to create and compile digital spatial datasets of total nitrogen and total phosphorus contributions that served as input sources to the SPARROW models. These data represent atmospheric deposition, point-source locations, land-use, land-cover, and agricultural sources such as commercial fertilizer and manure applications. Watershed-characteristics datasets representing factors that affect the transport of nutrients also were compiled from previous applications of the SPARROW models in the Chesapeake Bay watershed. Datasets include average-annual precipitation and temperature, slope, soil permeability, and hydrogeomorphic regions. Nutrient-input and watershed-characteristics datasets representing conditions during the late 1990s were merged with a connected network of stream reaches and watersheds to provide the spatial detail required by SPARROW. Stream-nutrient load estimates for 125 sampling sites (87 for total nitrogen and 103 for total phosphorus) served as the dependent variables for the regressions, and were used to calibrate models of total nitrogen and total phosphorus depicting late 1990s conditions in the Chesapeake Bay watershed. Spatial data generated for the models can be used to identify the location of nutrient sources, while the models' nutrient estimates can be used to evaluate stream-nutrient load contributed locally by each source evaluated, the amount of local load generated that is transported to the Bay, and the factors that affect the nutrient transport. Applying the SPARROW methodology to late 1990s information completes three time periods (late 1980s, early 1990s, and late 1990s) of viable data that resource managers can use to evaluate the water-quality conditions within the Bay watershed in order to refine restoration goals and nutrient-reduction strategies.

Chesapeake Bay watershed↗

USGS2018

Modeling intrinsic potential for beaver (Castor canadensis) habitat to inform restoration and climate change adaptation

Through their dam-building activities and subsequent water storage, beaver have the potential to restore riparian ecosystems and offset some of the predicted effects of climate change by modulating streamflow. Thus, it is not surprising that reintroducing beaver to watersheds from which they have been extirpated is an often-used restoration and climate-adaptation strategy. Identifying sites for reintroduction, however, requires detailed information about habitat factors—information that is not often available at broad spatial scales. Here we explore the potential for beaver relocation throughout the Snohomish River Basin in Washington, USA with a model that identifies some of the basic building blocks of beaver habitat suitability and does so by relying solely on remotely sensed data. More specifically, we developed a generalized intrinsic potential model that draws on remotely sensed measures of stream gradient, stream width, and valley width to identify where beaver could become established if suitable vegetation were to be present. Thus, the model serves as a preliminary screening tool that can be applied over relatively large extents. We applied the model to 5,019 stream km and assessed the ability of the model to correctly predict beaver habitat by surveying for beavers in 352 stream reaches. To further assess the potential for relocation, we assessed land ownership, use, and land cover in the landscape surrounding stream reaches with varying levels of intrinsic potential. Model results showed that 33% of streams had moderate or high intrinsic potential for beaver habitat. We found that no site that was classified as having low intrinsic potential had any sign of beavers and that beaver were absent from nearly three quarters of potentially suitable sites, indicating that there are factors preventing the local population from occupying these areas. Of the riparian areas around streams with high intrinsic potential for beaver, 38% are on public lands and 17% are on large tracts of privately-owned timber land. Thus, although there are a large number of areas that could be suitable for relocation and restoration using beavers, current land use patterns may substantially limit feasibility in these areas.

Washington↗

USGS2024

Federal lands greenhouse gas emissions and sequestration in the United States: Estimates for 2005–22

In 2016, the Secretary of the U.S. Department of the Interior requested that the U.S. Geological Survey (USGS) produce a publicly available and annually updated database of estimated greenhouse gas emissions associated with the extraction and use of fossil fuels from Federal lands. The first report in this series included emissions estimates from 2005 to 2014 and were reported for 29 States and two offshore areas. Native American and Tribal lands were not included in that analysis. This report recalculates those previous years (2005–14) with updated data and methods and extends the estimates to 2022. Nationwide emissions from fossil fuels produced on Federal lands in 2022 were 1,081.2 million metric tons of carbon dioxide equivalent (MMT CO 2 Eq.) for CO 2 , 33.4 MMT CO 2 Eq. for methane (CH 4 ), and 4.3 MMT CO 2 Eq. for nitrous oxide (N 2 O). Compared to 2005, the 2022 totals represent decreases in emissions for all three greenhouse gases (by 17 percent for CO 2 , 37 percent for CH 4 , and 30 percent for N 2 O). Emissions from fossil fuels produced on Federal lands represent, on average, 21.8 percent of U.S. emissions for CO 2 , 6.1 percent for CH 4 , and 1.3 percent for N 2 O over the 18 years included in this estimate. The trends and relative magnitudes of the greenhouse gas emissions estimated are roughly parallel to the Federal lands fossil fuel production volumes. In 2021, Federal lands of the conterminous United States stored 70,424 MMT CO 2 Eq. in terrestrial ecosystems. Soils stored most of the terrestrial ecosystem carbon (66 percent), followed by live vegetation (25 percent), deadwood (5 percent), and litter (4 percent). Carbon sequestration on Federal lands was highly variable over time, owing primarily to interannual variability in climate and weather, and variability in land use and land cover (LULC) change and disturbances, among these are wildfires and logging. Between 2005 and 2021, Federal lands sequestered an average of 83 MMT CO 2 Eq./yr. By subtracting the cumulative effects of LULC and disturbance-related CO 2 losses to the atmosphere from the total, we estimate that ecosystems at the national level sequestered CO 2 at an annual mean rate of 17 MMT CO 2 Eq./yr in a term called the net ecosystem exchange (NEE). This annual NEE sequestration value represents about 1.4 percent of average fossil fuel emissions over the same period. The USGS estimates presented in this report represent an accounting for the emissions resulting from fossil fuel extraction on Federal lands and the end-use combustion of those fuels, as well as for the sequestration of carbon in terrestrial ecosystems on Federal lands. A combined net CO 2 emissions estimate, which is the difference between the emitted and sequestered CO 2 from both the fossil fuel and ecosystems estimates, provides context for evaluating the greenhouse gas contributions of activities on these lands. The estimates included in this report can provide context for future energy decisions, as well as a basis to track change in the future.

Scientific Investigations Report↗

USGS2015

Downscaling 250-m MODIS growing season NDVI based on multiple-date landsat images and data mining approaches

The satellite-derived growing season time-integrated Normalized Difference Vegetation Index (GSN) has been used as a proxy for vegetation biomass productivity. The 250-m GSN data estimated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have been used for terrestrial ecosystem modeling and monitoring. High temporal resolution with a wide range of wavelengths make the MODIS land surface products robust and reliable. The long-term 30-m Landsat data provide spatial detailed information for characterizing human-scale processes and have been used for land cover and land change studies. The main goal of this study is to combine 250-m MODIS GSN and 30-m Landsat observations to generate a quality-improved high spatial resolution (30-m) GSN database. A rule-based piecewise regression GSN model based on MODIS and Landsat data was developed. Results show a strong correlation between predicted GSN and actual GSN (r = 0.97, average error = 0.026). The most important Landsat variables in the GSN model are Normalized Difference Vegetation Indices (NDVIs) in May and August. The derived MODIS-Landsat-based 30-m GSN map provides biophysical information for moderate-scale ecological features. This multiple sensor study retains the detailed seasonal dynamic information captured by MODIS and leverages the high-resolution information from Landsat, which will be useful for regional ecosystem studies.

Remote Sensing↗

USGS2020

Changing suspended sediment in United States rivers and streams: Linking sediment trends to changes in land use/cover, hydrology and climate

Sediment is one of the leading pollutants in rivers and streams across the United States (US) and the world. Between 1992 and 2012, concentrations of annual mean suspended sediment decreased at over half of the 137 stream sites assessed across the contiguous US. Increases occurred at less than 25 % of the sites, and the direction of change was uncertain at the remaining 25 %. Sediment trends were characterized using the Weighted Regressions on Time, Discharge, and Season (WRTDS) model, and decreases in sediment ranged from −95 % to −8.5 % of the 1992 concentration. To explore potential drivers of these changes, the sediment trends were (1) parsed into two broad contributors of change, changes in land management versus changes in the streamflow regime, and (2) grouped by land use of the watershed and correlated to concurrent changes in land use or land cover (land use/cover), hydrology and climate variables and static/long-term watershed characteristics. At 83 % of the sites, changes in land management (captured by changes in the concentration–streamflow relationship over time; C–Q relationship) contributed more to the change in the sediment trend than changes in the streamflow regime alone (i.e., any systematic change in the magnitude, frequency or timing of flows). However, at >50 % of the sites, changes in the streamflow regime contributed at least a 5 % change in sediment, and at 11 sites changes in the streamflow regime contributed over half the change in sediment, indicating that at many sites changes in streamflow were not the main driver of changes in sediment but were often an important supporting factor. Correlations between sediment trends and concurrent changes in land use/cover, hydrology and climate were often stronger at sites draining watersheds with more homogenous, human-related land uses (i.e., agricultural and urban lands) compared to mixed-use or undeveloped lands. At many sites, decreases in sediment occurred despite small-to-moderate increases in the amount of urban or agricultural land in the watershed, suggesting conservation efforts and best-management practices (BMPs) used to reduce sediment runoff to streams may be successful, up to a point, as lands are converted to urban and agricultural uses.

Hydrology and Earth System Sciences↗

USGS2000

Sensitivity of species habitat-relationship model performance to factors of scale

Researchers have come to different conclusions about the usefulness of habitat-relationship models for predicting species presence or absence. This difference frequently stems from a failure to recognize the effects of spatial scales at which the models are applied. We examined the effects of model complexity, spatial data resolution, and scale of application on the performance of bird habitat relationship (BHR) models on the Craig Mountain Wildlife Management Area and on the Idaho portion of the U.S. Forest Service's Northern Region. We constructed and tested BHR models for 60 bird species detected on the study areas. The models varied by three levels of complexity (amount of habitat information) and three spatial data resolutions (0.09 ha, 4 ha, 10 ha). We tested these models at two levels of analysis: the site level (a homogeneous area <0.5 ha) and cover-type level (an aggregation of many similar sites of a similar land-cover type), using correspondence between model predictions and species detections to calculate kappa coefficients of agreement. Model performance initially increased as models became more complex until a point was reached where omission errors increased at a rate greater than the rate at which commission errors were decreasing. Heterogeneity of the study areas appeared to influence the effect of model complexity. Changes in model complexity resulted in a greater decrease in commission error than increase in omission error. The effect of Spatial data resolution on the performance of BHR models was influenced by the variability of the study area. BHR models performed better at cover-type levels of analysis than at the site level for both study areas. Correct-presence estimates (1 - minus percentage omission error) decreased slightly as number of species detections increased on each study area. Correct-absence estimates (1 - percentage commission error) increased as number of species detections increased on each study area. This suggests that a large number of detections may be necessary to achieve reliable estimates of model accuracy.

Idaho↗

USGS2020

Mangrove blue carbon in the face of deforestation, climate change, and restoration

Coastal wetlands have disproportionately high carbon densities, known as blue carbon, compared to most terrestrial ecosystems. Mangroves and their blue carbon stocks are at risk globally from land‐use and land‐cover change (LULCC) activities such as aquaculture, alongside biophysical disturbances such as sea‐level rise and cyclones. Global estimates of carbon emissions from mangrove loss have been previously unable to differentiate between the variable impacts of different drivers of loss. This article discusses the impacts that different LULCC activities and biophysical disturbances have on carbon stocks (biomass and soil) and greenhouse gas fluxes (CO 2 and CH 4 ). The dynamics of carbon stocks and fluxes depends on the type of LULCC; aquaculture often results in biomass and soil carbon removal, and some forms of agriculture can substantially increase methane emissions. Natural disturbances have mixed impacts on mangrove carbon; sea‐level rise will drown some mangroves and their carbon stocks but provide opportunities for new carbon accumulation, while cyclones can have immediate negative impacts on stocks but positive impacts on sequestration during recovery. Mangrove rehabilitation practices can actively restore carbon stocks and reduce greenhouse gas emissions from previous land uses. It is critical to consider the type of LULCC when estimating carbon emissions due to mangrove loss or rehabilitation. Mangrove blue carbon is now high on the international conservation policy agenda, and a better understanding of how carbon stocks and fluxes respond to anthropogenic and biophysical disturbance may provide better incentives for mangrove conservation and sustainable management.

Annual Plant Reviews↗

USGS2016

The National Wind Erosion Research Network: Building a standardized long-term data resource for aeolian research, modeling and land management

The National Wind Erosion Research Network was established in 2014 as a collaborative effort led by the United States Department of Agriculture’s Agricultural Research Service and Natural Resources Conservation Service, and the United States Department of the Interior’s Bureau of Land Management, to address the need for a long-term research program to meet critical challenges in wind erosion research and management in the United States. The Network has three aims: (1) provide data to support understanding of basic aeolian processes across land use types, land cover types, and management practices, (2) support development and application of models to assess wind erosion and dust emission and their impacts on human and environmental systems, and (3) encourage collaboration among the aeolian research community and resource managers for the transfer of wind erosion technologies. The Network currently consists of thirteen intensively instrumented sites providing measurements of aeolian sediment transport rates, meteorological conditions, and soil and vegetation properties that influence wind erosion. Network sites are located across rangelands, croplands, and deserts of the western US. In support of Network activities, http://winderosionnetwork.org was developed as a portal for information about the Network, providing site descriptions, measurement protocols, and data visualization tools to facilitate collaboration with scientists and managers interested in the Network and accessing Network products. The Network provides a mechanism for engaging national and international partners in a wind erosion research program that addresses the need for improved understanding and prediction of aeolian processes across complex and diverse land use types and management practices.

Arizona, California, Colorado, Idaho, North Dakota↗

USGS1970

Sediment transport by streams in the Palouse River basin, Washington and Idaho, July 1961-June 1965

The Palouse River basin covers about 3,300 square miles in southeastern Washington and northwestern Idaho. The eastern part of the basin is composed of steptoes and foothills which are generally above an altitude of 2,600 feet; the central part is of moderate local relief and is mantled chiefly by thick loess deposits; and the western part is characterized by low relief and scabland topography and is underlain mostly by basalt. Precipitation increases eastward across the study area. It ranges annually from 12 to 18 inches in the western part and from 14 to 23 inches in the central part, and it exceeds 40 inches in the eastern part. Surface runoff from the basin for the 4-year period of study (July 1961-June 1965) averaged 408,000 acre-feet per year, compared with 445,200 acre-feet per year for the 27-year period of record. The eastern part of the basin contributed about 55 percent of the total, whereas the central and western parts contributed 37 percent and 8 percent, respectively. Most sediment transport from the Palouse River basin and the highest sediment concentrations in streams occurred in the winter. Of the several storms during the study period, those of February 3-9, 1963, December 22-27, 1964, and January 27-February 4, 1965, accounted for 81 percent of the total 4-year suspended-sediment load; the storm of February 3-9, 1963, accounted for nearly one-half the total load. The discharge-weighted mean concentration of suspended sediment carried in the Palouse River past Hooper during the study period was 2,970 milligrams per liter. The average annual sediment discharge of the Palouse River at its mouth was about 1,580,000 tons per year, and the estimated average annual sediment yield was 480 tons per square mile. The yield ranged from 5 tons per square mile from the western part of the basin to 2,100 tons per square mile from the central part. The high yield from the central part is attributed to a scarcity of vegetal cover, to the fine-grained loess soils, and to rapid runoff during winter storms. Sediment yield from the eastern part of the basin ranged from 460 to more than 1,000 tons per square mile. During high flow, silt particles make up the largest part of the suspended-sediment load, whereas during low flow, clay particles represent the greatest part. On the average, the suspended sediment transported by the Palouse River past Hooper contained 3 percent sand, 68 percent silt, and 29 percent clay. Unmeasured sediment discharge was estimated to have been 5 percent of the total sediment discharge. Data collected during the 4-year period of study show that sediment loads were higher than those recorded by V. G. Kaiser during the longer period 1939-65. Whereas Kaiser's study showed an average annual soil loss of 9.6 million tons, the average annual loss during the recent study was 14.2 million tons. The factor that has had the greatest effect on the increase of sediment yields is land use. Lands once covered and protected by natural vegetation have been extensively, cultivated, and much of the soil has become susceptible to erosion, particularly in areas mantled by loessal soils.

Idaho, Washington↗

USGS2025

Spatial regimes provide ample early warning of tipping points

Accelerating global change is a hallmark of the Anthropocene, and the interaction of rapid change in climate, land use and land cover makes understanding the response of social-ecological systems to global change difficult to predict. Global change directly and indirectly affects both social-ecological systems and the landscapes in which they are embedded. Spatial heterogeneity in the location, manifestation of, and responses to global change makes spatially explicit approaches to management and conservation necessary. Spatial regimes, a concept derived from resilience theory, are at the forefront of attempts to operationalize and quantify resilience of dynamic landscapes. Spatial regimes are defined as dynamic landscape units that are shaped by a self-organizing set of processes and structures. They have identifiable spatial extents with discrete boundaries at a given scale that exhibit relative homogeneity in process, structure and composition maintained by feedback mechanisms. Here, we describe the concept of, evidence for, and applications of spatial regimes and how spatial regimes relate to scale and telecoupling of change across social-ecological systems. We emphasize the utility of the concept as an early warning of regime change, one that can provide ample early warning. We discuss methods that can be used to detect spatial regimes and uses of the concept for understanding and managing the spatio-temporal response of social-ecological systems to global change.

Advances in Ecological Research↗

USGS2013

Quantifying climate change mitigation potential in Great Plains wetlands for three greenhouse gas emission scenarios

We examined opportunities for avoided loss of wetland carbon stocks in the Great Plains of the United States in the context of future agricultural expansion through analysis of land-use land-cover (LULC) change scenarios, baseline carbon datasets and biogeochemical model outputs. A wetland map that classifies wetlands according to carbon pools was created to describe future patterns of carbon loss and potential carbon savings. Wetland avoided loss scenarios, superimposed upon LULC change scenarios, quantified carbon stocks preserved under criteria of carbon densities or land value plus cropland suitability. Up to 3420 km 2 of wetlands may be lost in the region by 2050, mainly due to conversion of herbaceous wetlands in the Temperate Prairies where soil organic carbon (SOC) is highest. SOC loss would be approximately 0.20 ± 0.15 megagrams of carbon per hectare per year (MgC ha −1 yr −1 ), depending upon tillage practices on converted wetlands, and total ecosystem carbon loss in woody wetlands would be approximately 0.81 ± 0.41 MgC ha −1 yr −1 , based on biogeochemical model results. Among wetlands vulnerable to conversion, wetlands in the Northern Glaciated Plains and Lake Agassiz Plains ecoregions exhibit very high mean SOC and on average, relatively low land values, potentially creating economically competitive opportunities for avoided carbon loss. This mitigation scenarios approach may be adapted by managers using their own preferred criteria to select sites that best meet their objectives. Results can help prioritize field-based assessments, where site-level investigations of carbon stocks, land value, and consideration of local priorities for climate change mitigation programs are needed.

Great Plains↗

USGS2010

Effect of land cover change on runoff curve number estimation in Iowa, 1832-2001

Within the first few decades of European-descended settlers arriving in Iowa, much of the land cover across the state was transformed from prairie and forest to farmland, patches of forest, and urbanized areas. Land cover change over the subsequent 126 years was minor in comparison. Between 1832 and 1859, the General Land Office conducted a survey of the State of Iowa to aid in the disbursement of land. In 1875, an illustrated atlas of the State of Iowa was published, and in 2001, the US Geological Survey National Land Cover Dataset was compiled. Using these three data resources for classifying land cover, the hydrologic impact of the land cover change at three points in time over a period of 132+ years is presented in terms of the effect on the area-weighted average curve number, a term commonly used to predict peak runoff from rainstorms. In the four watersheds studied, the area-weighted average curve number associated with the first 30 years of settlement increased from 61·4 to 77·8. State-wide mapped forest area over this same period decreased 19%. Over the next 126 years, the area-weighted average curve number decreased to 76·7, despite an additional forest area reduction of 60%. This suggests that degradation of aquatic resources (plants, fish, invertebrates, and habitat) arising from hydrologic alteration was likely to have been much higher during the 30 years of initial settlement than in the subsequent period of 126 years in which land cover changes resulted primarily from deforestation and urbanization.

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