USGS Science⌕ Search

SEARCH · USGS Science

Results for “Land Use and Land Cover”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,783 records · Page 99Linked to original sources
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↗
USGS2003

Channel response to tectonic forcing: field analysis of stream morphology and hydrology in the Mendocino triple junction region, northern California

An empirical calibration of the shear stress model for bedrock incision is presented, using field and hydrologic data from a series of small, coastal drainage basins near the Mendocino triple junction in northern California. Previous work comparing basins from the high uplift zone (HUZ, uplift rates around 4 mm/year) to ones in the low uplift zone (LUZ, ∼0.5 mm/year) indicates that the HUZ channels are about twice as steep for a given drainage area. This observation suggests that incision processes are more effective in the HUZ. It motivates a detailed field study of channel morphology in the differing tectonic settings to test whether various factors that are hypothesized to influence incision rates (discharge, channel width, lithology, sediment load) change in response to uplift or otherwise differ between the HUZ and LUZ. Analysis of regional stream gaging data for mean annual discharge and individual floods yields a linear relationship between discharge and drainage area. Increased orographic precipitation in the HUZ accounts for about a twofold increase in discharge in this area, corresponding to an assumed increase in the erosional efficiency of the streams. Field measurements of channel width indicate a power-law relationship between width and drainage area with an exponent of ∼0.4 and no significant change in width between the uplift rate zones, although interpretation is hampered by a difference in land use between the zones. The HUZ channel width dataset reveals a scaling break interpreted to be the transition between colluvial- and fluvial-dominated incision processes. Assessments of lithologic resistance using a Schmidt hammer and joint surveys show that the rocks of the study area should be fairly similar in their susceptibility to erosion. The HUZ channels generally have more exposed bedrock than those in the LUZ, which is consistent with protection by sediment cover inhibiting incision in the LUZ. However, this difference is likely the result of a recent pulse of sediment due to land use in the LUZ. Therefore, the role of sediment flux in setting incision rates cannot be constrained with any certainty. To summarize, of the four response mechanisms analyzed, the only factor that demonstrably varies between uplift rate zones is discharge, although this change is likely insufficient to explain the relationship between channel slope and uplift rate. The calibrated model allows us to make a prediction of channel concavity that is consistent with a previous estimate from slope–drainage area data. We show that the inclusion of nonzero values of critical shear stress in the model has important implications for the theoretical relationship between steady-state slope and uplift rate and might provide an explanation for the observations. This analysis underscores the importance of further work to constrain quantitatively threshold shear stress for bedrock incision.

California↗
USGS2014

Integrated conceptual ecological model and habitat indices for the southwest Florida coastal wetlands

The coastal wetlands of southwest Florida that extend from Charlotte Harbor south to Cape Sable, contain more than 60,000 ha of mangroves and 22,177 ha of salt marsh. These coastal wetlands form a transition zone between the freshwater and marine environments of the South Florida Coastal Marine Ecosystem (SFCME). The coastal wetlands provide diverse ecosystem services that are valued by society and thus are important to the economy of the state. Species from throughout the region spend part of their life cycle in the coastal wetlands, including many marine and coastal-dependent species, making this zone critical to the ecosystem health of the Everglades and the SFCME. However, the coastal wetlands are increasingly vulnerable due to rising sea level, changes in storm intensity and frequency, land use, and water management practices. They are at the boundary of the region covered by the Comprehensive Everglades Restoration Plan (CERP), and thus are impacted by both CERP and marine resource management decisions. An integrated conceptual ecological model (ICEM) for the southwest coastal wetlands of Florida was developed that illustrates the linkages between drivers, pressures, ecological process, and ecosystem services. Five ecological indicators are presented: (1) mangrove community structure and spatial extent; (2) waterbirds; (3) prey-base fish and macroinvertebrates; (4) crocodilians; and (5) periphyton. Most of these indicators are already used in other areas of south Florida and the SFCME, and therefore will allow metrics from the coastal wetlands to be used in system-wide assessments that incorporate the entire Greater Everglades Ecosystem.

Ecological Indicators↗
USGS2021

Post-white-nose syndrome passive acoustic sampling effort for determining bat species occupancy within the mid-Atlantic region

We assessed the sampling effort requirements for detecting the presence of extant bat species following the impact of white-nose syndrome in the mid-Atlantic region of the United States. We acoustically sampled 27,796 nights across 846 sites between 15 May and 15 August 2016–2018 within the District of Columbia, Maryland, Pennsylvania, Virginia, and West Virginia. We developed simulations to determine the number of sites required to document bat species when each site was sampled different numbers of nights. We examined these simulations with respect to land cover, physiographic region, and time period. We generally found that sampling a greater number of sample sites within a survey area increased detection more than increasing the number of nights at individual sampling sites. The sampling effort required to detect a given bat species varied by species, as well as land-cover type and physiographic region. Our results suggest that land managers and researchers should use caution in using protocols developed with other objectives, e.g., the U.S. Fish and Wildlife Service endangered and threatened bat species and the North American Bat monitoring programs’ methods are designed relative to their specific needs. Unfortunately, neither protocol may be adequate for accurately detecting bat communities within all mid-Atlantic areas.

Maryland, Pennsylvania, Virginia, West Virginia↗
USGS2016

Thermokarst rates intensify due to climate change and forest fragmentation in an Alaskan boreal forest lowland

Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depend on forest type.

Alaska↗
USGS1990

Construction and performance of a long-term earthen liner experiment

In land burial schemes, compacted soil barriers with low hydraulic conductivity are commonly used in cover and liner systems to control the movement of liquids and prevent groundwater contamination. An experimental liner measuring 8 x 15 x 0.9 m was constructed with design criteria and equipment to simulate construction of soil liners built at waste disposal facilities. The surface of the liner was flooded with a 29.5 cm deep pond on April 12, 1988. Infiltration of water into the liner has been monitored for two years using 4 large-ring (1.5 m OD) and 32 small-ring (0.28 m OD) infiltrometers, and a water-balance that accounts for total infiltration and evaporation. Average long-term infiltration fluxes based on two years of monitoring are 5.8 x 10-9 cm/s, 6.0 x 10-8 cm/s and 5.6 x 10-8 for the large-ring, small-ring, and water-balance data, respectively. The saturated hydraulic conductivity of the liner based on small-ring data, estimated using Darcy's Law and the Green-Ampt Approximation, is 3 x 10-8 and 4 x 10-8 cm/s, respectively. All sets of data indicate that the liner's performance exceed that which is required by the U.S. EPA.

Conference Paper↗
USGS2017

Importance of scale, land cover, and weather on the abundance of bird species in a managed forest

Climate change and habitat loss are projected to be the two greatest drivers of biodiversity loss over the coming century. While public lands have the potential to increase regional resilience of bird populations to these threats, long-term data are necessary to document species responses to changes in climate and habitat to better understand population vulnerabilities. We used generalized linear mixed models to determine the importance of stand-level characteristics, multi-scale land cover, and annual weather factors to the abundance of 61 bird species over a 20-year time frame in Chippewa National Forest, Minnesota, USA. Of the 61 species modeled, we were able to build final models with R-squared values that ranged from 26% to 69% for 37 species; the remaining 24 species models had issues with convergence or low explanatory power (R-squared < 20%). Models for the 37 species show that stand-level characteristics, land cover factors, and annual weather effects on species abundance were species-specific and varied within guilds. Forty-one percent of the final species models included stand-level characteristics, 92% included land cover variables at the 200 m scale, 51% included land cover variables at the 500 m scale, 46% included land cover variables at the 1000 m scale, and 38% included weather variables in best models. Three species models (8%) included significant weather and land cover interaction terms. Overall, models indicated that aboveground tree biomass and land cover variables drove changes in the majority of species. Of those species models including weather variables, more included annual variation in precipitation or drought than temperature. Annual weather variability was significantly more likely to impact abundance of species associated with deciduous forests and bird species that are considered climate sensitive. The long-term data and models we developed are particularly suited to informing science-based adaptive forest management plans that incorporate climate sensitivity, aim to conserve large areas of forest habitat, and maintain an historical mosaic of cover types for conserving a diverse and abundant avian assemblage.

Minnesota↗
USGS2003

Comparative alteration mineral mapping using visible to shortwave infrared (0.4-2.4 μm) Hyperion, ALI, and ASTER imagery

Advanced Land Imager (ALI), Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and Hyperion imaging spectrometer data covering an area in the Central Andes between Volcan Socompa and Salar de Llullaillaco were used to map hydrothermally altered rocks associated with several young volcanic systems. Six ALI channels in the visible and near-infrared wavelength range (0.4-1.0 ??m) were useful for discriminating between ferric-iron alteration minerals based on the spectral shapes of electronic absorption features seen in continuum-removed spectra. Six ASTER channels in the short wavelength infrared (1.0-2.5 ??m) enabled distinctions between clay and sulfate mineral types based on the positions of band minima related to Al-OH vibrational absorption features. Hyperion imagery embedded in the broader image coverage of ALI and ASTER provided essential leverage for calibrating and improving the mapping accuracy of the multispectral data. This capability is especially valuable in remote areas of the earth where available geologic and other ground truth information is limited.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2019

Controls of the spatial variability of denitrification potential in nontidal floodplains of the Chesapeake Bay watershed, USA

Identifying floodplains with high rates of denitrification will help prioritize restoration projects for the removal of nitrogen. Currently, relationships of denitrification with hydrogeomorphic, physiographic, and climate ( i.e. , largescale) characteristics of floodplains are relatively unknown, even though these characteristics have datasets ( e.g. , geographic mapping tools) that are publicly available (or soon-to-become) that could be used to understand denitrification variability. Thus, we investigated control of denitrification by these largescale characteristics in eighteen nontidal floodplains of the Chesapeake Bay watershed ( i.e. , at regional scale, >100 km, scale), using measurements or compiled data at the scales of the stream reach and respective catchment; floodplain soil and herbaceous vegetation ( i.e. , local) characteristics were additionally investigated. Soil denitrification potentials were measured in May, July, and August using complementary acetylene-based techniques under an anoxic environment. Linear largescale predictors of denitrification potential measurements included stream nitrogen and phosphorus concentrations (+), channel width-to-depth ratio (+), floodplain sedimentation (+), forested (−) and urban (+) catchment land cover, and seasonal air temperature (−). Three predictors, catchment forested land cover (strongly related to agricultural land cover), catchment urban land cover, and floodplain sedimentation were related to the most number of denitrification potential measurements. Soil structure, soil nutrient concentrations, and herbaceous vegetation characteristics that were seasonally measured (with a few exceptions) were linear predictors of denitrification potentials in May and August, with nitrogen and carbon characteristics the most consistent (positive) predictors across measurements. Nutrient amendment assays further supported the importance of nitrogen and carbon controls. Using the local characteristics as statistical mediators in path analysis, greater non-forested catchment land cover indirectly increased denitrification through greater floodplain soil nitrate, total phosphorus, and herbaceous aboveground biomass. Additionally, greater floodplain sedimentation indirectly increased denitrification through greater soil pH, total phosphorus, and potential carbon mineralization. Due to the consistency of relationships across denitrification potential measurements along with path modeling results, hotspots of floodplain denitrification should be found in urban and agricultural catchments where river-floodplain hydrologic connectivity promotes sedimentation. Largescale predictors explained 43–57% of the variation in denitrification potentials and should be useful for prediction in floodplains. Siting restoration projects in watersheds for maximum nitrate removal using publicly available largescale datasets is both feasible and effective.

Chesapeake Bay watershed↗
USGS2007

Riparian Land Use/Land Cover Data for Five Study Units in the Nutrient Enrichment Effects Topical Study of the National Water-Quality Assessment Program

This dataset was developed as part of the National Water-Quality Assessment (NAWQA) Program, Nutrient Enrichment Effects Topical (NEET) study for five study units distributed across the United States: Apalachicola-Chattahoochee-Flint River Basin, Central Columbia Plateau-Yakima River Basin, Central Nebraska Basins, Potomac River Basin and Delmarva Peninsula, and White, Great and Little Miami River Basins. One hundred forty-three stream reaches were examined as part of the NEET study conducted 2003-04. Stream segments, with lengths equal to the logarithm of the basin area, were delineated upstream from the downstream ends of the stream reaches with the use of digital orthophoto quarter quadrangles (DOQQ) or selected from the high-resolution National Hydrography Dataset (NHD). Use of the NHD was necessary when the stream was not distinguishable in the DOQQ because of dense tree canopy. The analysis area for each stream segment was defined by a buffer beginning at the segment extending to 250 meters lateral to the stream segment. Delineation of land use/land cover (LULC) map units within stream segment buffers was conducted using on-screen digitizing of riparian LULC classes interpreted from the DOQQ. LULC units were mapped using a classification strategy consisting of nine classes. National Wetlands Inventory (NWI) data were used to aid in wetland classification. Longitudinal transect sampling lines offset from the stream segments were generated and partitioned into the underlying LULC types. These longitudinal samples yielded the relative linear extent and sequence of each LULC type within the riparian zone at the segment scale. The resulting areal and linear LULC data filled in the spatial-scale gap between the 30-meter resolution of the National Land Cover Dataset and the reach-level habitat assessment data collected onsite routinely for NAWQA ecological sampling. The final data consisted of 12 geospatial datasets: LULC within 25 meters of the stream reach (polygon); LULC within 50 meters of the stream reach (polygon); LULC within 50 meters of the stream segment (polygon); LULC within 100 meters of the stream segment (polygon); LULC within 150 meters of the stream segment (polygon); LULC within 250 meters of the stream segment (polygon); frequency of gaps in woody vegetation LULC at the reach scale (arc); stream reaches (arc); longitudinal LULC at the reach scale (arc); frequency of gaps in woody vegetation LULC at the segment scale (arc); stream segments (arc); and longitudinal LULC at the segment scale (arc).

Data Series↗
USGS2017

Using multi-date satellite imagery to monitor invasive grass species distribution in post-wildfire landscapes: An iterative, adaptable approach that employs open-source data and software

Among the most pressing concerns of land managers in post-wildfire landscapes are the establishment and spread of invasive species. Land managers need accurate maps of invasive species cover for targeted management post-disturbance that are easily transferable across space and time. In this study, we sought to develop an iterative, replicable methodology based on limited invasive species occurrence data, freely available remotely sensed data, and open source software to predict the distribution of Bromus tectorum (cheatgrass) in a post-wildfire landscape. We developed four species distribution models using eight spectral indices derived from five months of Landsat 8 Operational Land Imager (OLI) data in 2014. These months corresponded to both cheatgrass growing period and time of field data collection in the study area. The four models were improved using an iterative approach in which a threshold for cover was established, and all models had high sensitivity values when tested on an independent dataset. We also quantified the area at highest risk for invasion in future seasons given 2014 distribution, topographic covariates, and seed dispersal limitations. These models demonstrate the effectiveness of using derived multi-date spectral indices as proxies for species occurrence on the landscape, the importance of selecting thresholds for invasive species cover to evaluate ecological risk in species distribution models, and the applicability of Landsat 8 OLI and the Software for Assisted Habitat Modeling for targeted invasive species management.

International Journal of Applied Earth Observation↗
USGS2025

An enhanced national-scale urban tree canopy cover dataset for the United States

Moderate-resolution (30-m) national map products have limited capacity to represent fine-scale, heterogeneous urban forms and processes, yet improvements from incorporating higher resolution predictor data remain rare. In this study, we applied random forest models to high-resolution land cover data for 71 U.S. urban areas, moderate-resolution National Land Cover Database (NLCD) Tree Canopy Cover (TCC), and additional explanatory climatic and structural data to develop an enhanced urban TCC dataset for U.S. urban areas. With a coefficient of determination (R 2 ) of 0.747, our model estimated TCC within 3% for 62 urban areas and added 13.4% more city-level TCC on average, compared to the native NLCD TCC product. Cross validations indicated model stability suitable for building a national-scale TCC dataset (median R 2 of 0.752, 0.675, and 0.743 for 1,000-fold cross validation, urban area leave-one-out cross validation, and cross validation by Census block group median year built, respectively). Additionally, our model code can be used to improve moderate-resolution TCC in other parts of the world where high-resolution land cover data have limited spatiotemporal availability.

conterminous United States↗
USGS1999

A GIS modeling method applied to predicting forest songbird habitat

We have developed an approach for using “presence” data to construct habitat models. Presence data are those that indicate locations where the target organism is observed to occur, but that cannot be used to define locations where the organism does not occur. Surveys of highly mobile vertebrates often yield these kinds of data. Models developed through our approach yield predictions of the amount and the spatial distribution of good-quality habitat for the target species. This approach was developed primarily for use in a GIS context; thus, the models are spatially explicit and have the potential to be applied over large areas. Our method consists of two primary steps. In the first step, we identify an optimal range of values for each habitat variable to be used as a predictor in the model. To find these ranges, we employ the concept of maximizing the difference between cumulative distribution functions of (1) the values of a habitat variable at the observed presence locations of the target organism, and (2) the values of that habitat variable for all locations across a study area. In the second step, multivariate models of good habitat are constructed by combining these ranges of values, using the Boolean operators “and” and “or.” We use an approach similar to forward stepwise regression to select the best overall model. We demonstrate the use of this method by developing species-specific habitat models for nine forest-breeding songbirds (e.g., Cerulean Warbler, Scarlet Tanager, Wood Thrush) studied in southern Ohio. These models are based on species’ microhabitat preferences for moisture and vegetation characteristics that can be predicted primarily through the use of abiotic variables. We use slope, land surface morphology, land surface curvature, water flow accumulation downhill, and an integrated moisture index, in conjunction with a land-cover classification that identifies forest/nonforest, to develop these models. The performance of these models was evaluated with an independent data set. Our tests showed that the models performed better than random at identifying where the birds occurred and provided useful information for predicting the amount and spatial distribution of good habitat for the birds we studied. In addition, we generally found positive correlations between the amount of habitat, as predicted by the models, and the number of territories within a given area. This added component provides the possibility, ultimately, of being able to estimate population sizes. Our models represent useful tools for resource managers who are interested in assessing the impacts of alternative management plans that could alter or remove habitat for these birds.

Ecological Applications↗
USGS2015

Projection of corn production and stover-harvesting impacts on soil organic carbon dynamics in the U.S. Temperate Prairies

Terrestrial carbon sequestration potential is widely considered as a realistic option for mitigating greenhouse gas emissions. However, this potential may be threatened by global changes including climate, land use, and management changes such as increased corn stover harvesting for rising production of cellulosic biofuel. Therefore, it is critical to investigate the dynamics of soil organic carbon (SOC) at regional or global scale. This study simulated the corn production and spatiotemporal changes of SOC in the U.S. Temperate Prairies, which covers over one-third of the U.S. corn acreage, using a biogeochemical model with multiple climate and land-use change projections. The corn production (either grain yield or stover biomass) could reach 88.7–104.7 TgC as of 2050, 70–101% increase when compared to the base year of 2010. A removal of 50% stover at the regional scale could be a reasonable cap in view of maintaining SOC content and soil fertility especially in the beginning years. The projected SOC dynamics indicated that the average carbon sequestration potential across the entire region may vary from 12.7 to 19.6 g C/m 2 /yr (i.e., 6.6–10.2 g TgC/yr). This study not only helps understand SOC dynamics but also provides decision support for sustainable biofuel development.

Iowa, Kansas, Minnesota, Missouri, Nebraska, North↗
USGS2012

A data-based conservation planning tool for Florida panthers

Habitat loss and fragmentation are the greatest threats to the endangered Florida panther ( Puma concolor coryi ). We developed a data-based habitat model and user-friendly interface so that land managers can objectively evaluate Florida panther habitat. We used a geographic information system (GIS) and the Mahalanobis distance statistic ( D 2 ) to develop a model based on broad-scale landscape characteristics associated with panther home ranges. Variables in our model were Euclidean distance to natural land cover, road density, distance to major roads, human density, amount of natural land cover, amount of semi-natural land cover, amount of permanent or semi-permanent flooded area–open water, and a cost–distance variable. We then developed a Florida Panther Habitat Estimator tool, which automates and replicates the GIS processes used to apply the statistical habitat model. The estimator can be used by persons with moderate GIS skills to quantify effects of land-use changes on panther habitat at local and landscape scales. Example applications of the tool are presented.

Florida↗
USGS2008

Retrospective Review of Watershed Characteristics and a Framework for Future Research in the Sarasota Bay Watershed, Florida

The U.S. Geological Survey, in cooperation with the Sarasota Bay Estuary Program conducted a retrospective review of characteristics of the Sarasota Bay watershed in west-central Florida. This report describes watershed characteristics, surface- and ground-water processes, and the environmental setting of the Sarasota Bay watershed. Population growth during the last 50 years is transforming the Sarasota Bay watershed from rural and agriculture to urban and suburban. The transition has resulted in land-use changes that influence surface- and ground-water processes in the watershed. Increased impervious cover decreases recharge to ground water and increases overland runoff and the pollutants carried in the runoff. Soil compaction resulting from agriculture, construction, and recreation activities also decreases recharge to ground water. Conventional approaches to stormwater runoff have involved conveyances and large storage areas. Low-impact development approaches, designed to provide recharge near the precipitation point-of-contact, are being used increasingly in the watershed. Simple pollutant loading models applied to the Sarasota Bay watershed have focused on large-scale processes and pollutant loads determined from empirical values and mean event concentrations. Complex watershed models and more intensive data-collection programs can provide the level of information needed to quantify (1) the effects of lot-scale land practices on runoff, storage, and ground-water recharge, (2) dry and wet season flux of nutrients through atmospheric deposition, (3) changes in partitioning of water and contaminants as urbanization alters predevelopment rainfall-runoff relations, and (4) linkages between watershed models and lot-scale models to evaluate the effect of small-scale changes over the entire Sarasota Bay watershed. As urbanization in the Sarasota Bay watershed continues, focused research on water-resources issues can provide information needed by water-resources managers to ensure the future health of the watershed.

Open-File Report↗
USGS2003

Habitat use by Swainson's Hawks on their austral winter grounds in Argentina

We examined the use of agricultural habitats by Swainson's Hawks (Buteo swainsoni)in La Pampa and Santa Fe provinces, Argentina. We found an association of foraging Swainson's Hawks with permanent pastures such as fallow, natural, and alfalfa fields. The hawks also used plowed fields for sunning, resting, and preening. Fields planted with annual crops and pastures were used very little, except when they were cut for hay, plowed, and harvested, or when low crop height and cover allowed the hawks to land in fields. The availability of abundant, yet widely-spaced and transient food-sources, such as insect outbreaks, appeared to be the principal factor influencing habitat use by the hawks. Their reliance on agricultural habitats makes Swainson's Hawks highly vulnerable to pesticide contamination and has contributed to the occurrence of significant mortality events on their wintering grounds.

Journal of Raptor Research↗
USGS2010

Targeting land-use change for nitratenitrogen load reductions in an agricultural watershed

The research was conducted as part of the USDA's Conservation Effects Assessment Project. The objective of the project was to evaluate the environmental effects of land-use changes, with a focus on understanding how the spatial distribution throughout a watershed influences their effectiveness.The Soil and Water AssessmentTool (SWAT) water quality model was applied to the Squaw Creek watershed, which covers 4,730 ha (11,683 ac) of prime agriculture land in southern Iowa. The model was calibrated (2000 to 2004) and validated (1996 to 1999) for overall watershed hydrology and for streamflow and nitrate loadings at the watershed outlet on an annual and monthly basis. Four scenarios for land-use change were evaluated including one scenario consistent with recent land-use changes and three scenarios focused on land-use change on highly erodible land areas, upper basin areas, and floodplain areas. Results for the Squaw Creek watershed suggested that nitrate losses were sensitive to land-use change. If land-use patterns were restored to 1990 conditions, nitrate loads may be reduced 7% to 47% in the watershed and subbasins, whereas converting row crops to grass in highly erodible land, upper basin, and floodplain areas would reduce nitrate loads by 47%, 16%, and 8%, respectively. These SWAT model simulations can provide guidance on how to begin targeting land-use change for nitrate load reductions in agricultural watersheds.

Journal of Soil and Water Conservation↗