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At least 1,747 records · Page 97Linked to original sources

USGS1997

Drainage-return, surface-water withdrawal, and land-use data for the Sacramento-San Joaquin Delta, with emphasis on Twitchell Island, California

Partial data on drainage returns and surface-water withdrawals are presented for areas of the Sacramento-San Joaquin Delta, California, for March 1994 through February 1996. These areas cover most of the delta. Data are also presented for all drainage returns and some surface-water withdrawals for Twitchell Island, which is in the western part of the delta. Changes in land use between 1968 and 1991 are also presented for the delta. Measurements of monthly drainage returns and surface-water withdrawals were made using flowmeters installed in siphons and drain pipes on Twitchell Island. Estimates of monthly returns throughout the delta were made using electric power-consumption data with pump-efficiency-test data. For Twitchell Island, monthly measured drainage returns for the 1995 calendar year totaled about 11,200 acre-feet, whereas drainage returns estimated from power-consumption data totaled 5 percent less at about 10,600 acre-feet. Monthly surface-water withdrawals onto Twitchell Island through 12 of the 21 siphons totaled about 2,400 acre-feet for 1995. For most of the delta, the monthly estimated drainage returns for 1995 totaled about 430,000 acre-feet. The area consisting of Bouldin, Brannan, Staten, Tyler, and Venice Islands had the largest estimated drainage returns for calendar year 1995. Between 1968 and 1991, native vegetation in the delta decreased by 25 percent (about 40,000 acres), and grain and hay crops increased by 340 percent (about 71,000 acres). For Twitchell Island, native vegetation decreased about 77 percent (about 850 acres), while field crop acreage increased by about 44 percent (about 780 acres).

Open-File Report↗

USGS2005

Mapping impervious surface type and sub-pixel abundance using Hyperion hyperspectral imagery

Impervious surfaces have been identified as an important and quantifiable indicator of environmental degradation in urban settings. A number of research efforts have been directed at mapping impervious surface type using multispectral imagery. To date, however, no studies have compared equivalent techniques using multispectral and hyperspectral imagery to that end. In this study, data from NASA's 220‐channel Hyperion instrument were used to: a) delineate three types of impervious surface, and b) map sub‐pixel percent abundance for a study site near Washington, D.C., USA. The results were compared with the results of similar methods using same‐spatial‐resolution Landsat ETM+ data for mapping impervious surface type, and with the results of the U.S. Geological Survey's National Land Cover Data (NLCD) 2001 impervious surface data layer, which is derived from Landsat and high‐resolution Ikonos data. The accuracy of discriminating impervious surface type using Hyperion data was assessed at 88% versus Landsat at 59%. The sub‐pixel percent impervious map corresponded well with the NLCD 2001; impervious surface in the study area was calculated at 29.3% for NLCD 2001 and 28.4% for the Hyperion‐derived layer. The results suggest that fairly simple techniques using hyperspectral data are effective for quantifying impervious surface type, and that high‐spectral‐resolution imagery may be a good alternative to high‐spatial‐resolution data.

Geocarto International↗

USGS2025

Identifying preferential flow from soil moisture time series: Review of methodologies

Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially-distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods, to highlight important information for readers who want to identify PF from soil moisture data, and to inform those who aim to develop new methods or improve existing ones.

Vadose Zone Journal↗

USGS2015

Land use structures fish assemblages in reservoirs of the Tennessee River

Inputs of nutrients, sediments and detritus from catchments can promote selected components of reservoir fish assemblages, while hindering others. However, investigations linking these catchment subsidies to fish assemblages have generally focussed on one or a handful of species. Considering this paucity of community-level awareness, we sought to explore the association between land use and fish assemblage composition in reservoirs. To this end, we compared fish assemblages in reservoirs of two sub-basins of the Tennessee River representing differing intensities of agricultural development, and hypothesised that fish assemblage structure indicated by species percentage composition would differ among reservoirs in the two sub-basins. Using multivariate statistical analysis, we documented inter-basin differences in land use, reservoir productivity and fish assemblages, but no differences in reservoir morphometry or water regime. Basins were separated along a gradient of forested and non-forested catchment land cover, which was directly related to total nitrogen, total phosphorous and chlorophyll- a concentrations. Considering the extensive body of knowledge linking land use to aquatic systems, it is reasonable to postulate a hierarchical model in which productivity has direct links to terrestrial inputs, and fish assemblages have direct links to both land use and productivity. We observed a shift from an invertivore-based fish assemblage in forested catchments to a detritivore-based fish assemblage in agricultural catchments that may be a widespread pattern among reservoirs and other aquatic ecosystems.

Tennessee River↗

USGS2005

Distribution and abundance of nonnative fishes in streams of the western United States

This report presents data from one of the largest standardized stream surveys conducted in he western United States, which shows that one of every four individual fish in streams of 12 western states are nonnative. The states surveyed included Arizona, California, Colorado, Idaho, Montana, Nevada, North Dakota, Oregon, South Dakota, Utah, Washington, and Wyoming. The most widely distributed and abundant nonnative fishes in the western USA were brook trout Salvelinus fontinalis, brown trout Salmo trutta, rainbow trout Oncorhynchus mykiss, common carp Cyprinus carpio, smallmouth bass Micropterus dolomieu, largemouth bass M. salmoides, green sunfish Lepomis cyanellus, fathead minnow Pimephales promelas, yellow perch Percaflavescens, yellow bullhead Ameiurus natalis, cutthroat trout O. clarkii, western mosquitofish Gambusia affinis, golden shiner Notemigonus crysoleucas, channel catfish Ictalurus punctatus, and red shiner Cyprinella lutrensis. The greatest abundance and distribution of nonnative fishes was in interior states, and the most common nonnatives were introduced for angling. Nonnative fishes were widespread in pristine to highly disturbed streams influenced by all types of land use practices. We present ranges in water temperature, flow, stream order, riparian cover, human disturbance, and other environmental conditions where the 10 most common introduced species were found. Of the total western U.S. stream length bearing fish, 50.1% contained nonnative fishes while 17.9% contained physical environment that was ranked highly or moderately disturbed by humans. Introduced fishes can adversely affect stream communities, and they are much more widespread in western U.S. streams than habitat destruction. The widespread distribution and high relative abundance of nonnative fishes and their documented negative effects suggest their management and control should elicit at least as much attention as habitat preservation in the protection of native western U.S. stream biota. ?? Copyright by the American Fisheries Society 2005.

North American Journal of Fisheries Management↗

USGS2014

Land cover trends dataset, 1973-2000

The U.S. Geological Survey Land Cover Trends Project is releasing a 1973–2000 time-series land-use/land-cover dataset for the conterminous United States. The dataset contains 5 dates of land-use/land-cover data for 2,688 sample blocks randomly selected within 84 ecological regions. The nominal dates of the land-use/land-cover maps are 1973, 1980, 1986, 1992, and 2000. The land-use/land-cover maps were classified manually from Landsat Multispectral Scanner, Thematic Mapper, and Enhanced Thematic Mapper Plus imagery using a modified Anderson Level I classification scheme. The resulting land-use/land-cover data has a 60-meter resolution and the projection is set to Albers Equal-Area Conic, North American Datum of 1983. The files are labeled using a standard file naming convention that contains the number of the ecoregion, sample block, and Landsat year. The downloadable files are organized by ecoregion, and are available in the ERDAS IMAGINE TM (.img) raster file format.

Data Series↗

USGS2026

Magnitude and frequency of urban floods in Alabama and Mississippi using data through the 2024 water year

To improve flood-frequency estimates for urban streams in Alabama and Mississippi, the U.S Geological Survey, in cooperation with the Alabama and Mississippi Departments of Transportation, estimated streamflows corresponding to selected annual exceedance probabilities (AEPs) for 64 streamgages on urban streams in the two States—48 in Alabama and 16 in Mississippi. Using estimates from 42 of the 64 streamgages, regression equations were developed that can be used to predict streamflows corresponding to the selected AEPs at ungaged locations on urban streams. Annual peak-flow data through September 2024 were used in the at-site flood-frequency analyses. Drainage area and the percentage of developed land use in the drainage basins of the streamgages (from the 2011 National Land Cover Database) were identified as statistically significant explanatory variables. Pseudo coefficient of determination (pseudo-R2) values ranged from 81 percent for the 0.2-percent AEP (500-year flood) to 91 percent for the 4- and 2-percent AEPs (25- and 50-year floods, respectively). Standard errors of prediction ranged from 23.1 percent for the 4-percent AEP (25-year flood) to 36.1 percent for the 2-percent AEP (500-year flood).

Alabama, Mississippi↗

USGS2009

Use of multi-temporal Landsat images to monitor forest disturbance (1987-2007) in the Black Hills of South Dakota

Monitoring forest disturbance is important for studying carbon pools and fluxes. The goal of this study is to observe forest disturbance of different burn severity levels using multi-temporal Landsat images. The Jasper Fire occurred in the Black Hills National Forest, South Dakota, during August and September of 2000. The fire disturbance to ecosystem characteristics has a widespread and long-term impact. We used 18 Landsat images acquired from 1987 to 2007 to monitor the land cover changes due to the fire disturbance. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Burn Ratio (NBR), and Integrated Forest Index (IFI) were calculated from the Landsat at-sensor-reflectance data. Based on IFI in 2000 and Composite Burn Index data collected in May 2002, nine field plots were selected and monitored. The results showed that all four spectral indices were capable of detecting and monitoring the forest disturbance caused by thinning and fire. IFI and NBR are more suitable for long-term monitoring while NDVI and EVI are more sensitive to rapid changes within a one-year period.

South Dakota↗

USGS1999

A weighted least-squares approach to temporal NDVI smoothing

Satellite imagery provides a unique vantage point for observing seasonal dynamics of the landscape that have implications for global change issues. An objective evaluation of surface conditions may be performed using the normalized difference vegetation index (NDVI) derived from National Oceanic and Atmospheric Administration advanced very high resolution radiometer data. NDVI data are typically very noisy, affected by a number of phenomena including cloud contamination, atmospheric perturbations, and variable illumination and viewing geometry, each of which usually reduces the NDVI. This work describes a weighted least-squares linear regression approach to temporal NDVI smoothing to more efficiently reduce contamination in the NDVI signal. This approach uses a moving window operating on temporal NDVI to calculate a regression line. The window is moved one period at a time, resulting in a family of regression lines associated with each point; this family of lines is then averaged at each point and interpolated between points to provide a continuous temporal NDVI signal. Also, since the factors that cause contamination usually serve to reduce NDVI values, the system applies a weighting factor that favors peak points over sloping or valley points. A final operation assures that all peak NDVI values are retained. The resulting relationship between the smoothed curve and the original data is statistically based. The smoothed data may be used to improve applications involving time-series NDVI data, such as land cover classification, seasonal vegetation characterization, and vegetation monitoring

Conference Paper↗

USGS2019

Spatial and Temporal Patterns of Best Management Practice Implementation in the Chesapeake Bay Watershed, 1985–2014

Efforts to restore water quality in Chesapeake Bay and its tributaries often include extensive Best Management Practice (BMP) implementation on agricultural and developed lands. These BMPs include a variety of methods to reduce nutrient and sediment loads, such as cover crops, conservation tillage, urban filtering systems, and other practices. Estimates of BMP implementation throughout the Chesapeake Bay watershed were provided for each year from 1985 through 2014 by the Chesapeake Bay Program (CBP). This dataset of BMP implementation is a compilation of actions reported by New York, Maryland, Pennsylvania, Delaware, West Virginia, Virginia, and the District of Columbia, and includes a wide array of management activities. Management actions vary among the jurisdictions and generally reflect the typical land use in each region. The amount of implementation also varies according to different priorities, reporting practices, and special programs within each jurisdiction. For example, extensive cover crop implementation was reported in Maryland whereas Pennsylvania, in general, has lower levels of BMP implementation reported on cropland. Pennsylvania and Maryland have higher levels of infiltration BMPs on developed land compared to those in Virginia. Conservation tillage BMPs accounted for the majority of reported agricultural BMP implementation in 1985. By 2014, however, a more diverse collection of agricultural BMPs was reported and conservation tillage BMPs accounted for a smaller proportion of overall reported agricultural BMP implementation. After the year 2000, land-use change BMPs, such as land retirement, pasture fencing, and forest buffers, were more commonly reported across the Chesapeake Bay watershed. Expected changes in nutrient and sediment loads in the Chesapeake Bay watershed due to BMP implementation were estimated by use of specially designed annual scenarios of the CBP Partnership Phase 5.3.2 Watershed Model. Nitrogen loads to streams were estimated to be reduced by 11 percent from 1985 to 2014 due to the implementation of BMPs. Compared with 1985, phosphorus loads were estimated to be 19 percent lower and sediment loads were estimated to be 23 percent lower by 2014 due to the effects of BMPs. Reductions in total nitrogen from 1985 to 2014 due to BMPs varied spatially across the watershed and were estimated to be as high as 42 percent in areas of the Eastern Shore of the Chesapeake Bay. Reductions in phosphorus and sediment also varied spatially, with the largest reductions occurring in the Potomac watershed upstream of Washington, D.C. and the Eastern Shore of Maryland, according to the CBP model results. Additional model scenarios were developed to estimate the effect of individual BMP types. The largest estimated reductions in total nitrogen loads on agricultural lands in 2014 were attributed to land retirement, animal waste management systems, and conservation tillage. The largest estimated reductions in total phosphorus loads on agricultural lands were attributed to animal waste management systems, pasture fencing, and phytase feed additives in 2014. The largest estimated reduction in total sediment loads on agricultural lands was attributed to conservation tillage, pasture fencing, and conservation plans. Dry ponds, wet ponds, and constructed wetlands were reported extensively throughout the watershed. These BMPs accounted for about half of the reduction in nitrogen loads from developed land to streams, half of the phosphorus reduction, and about a third of the sediment reduction.

Chesapeake Bay Watershed↗

USGS2020

Changes in physiology and microbial diversity in larval ornate chorus frogs are associated with habitat quality

Environmental change associated with anthropogenic disturbance can lower habitat quality, especially for sensitive species such as many amphibians. Variation in environmental quality may affect an organism’s physiological health and, ultimately, survival and fitness. Using multiple health measures can aid in identifying populations at increased risk of declines. Our objective was to measure environmental variables at multiple spatial scales and their effect on three indicators of health in ornate chorus frog ( Pseudacris ornata ) tadpoles to identify potential correlates of population declines. To accomplish this, we measured a glucocorticoid hormone (corticosterone; CORT) profile associated with the stress response, as well as the skin mucosal immune function (combined function of skin secretions and skin bacterial community) and bacterial communities of tadpoles from multiple ponds. We found that water quality characteristics associated with environmental variation, including higher water temperature, conductivity and total dissolved solids, as well as percent developed land nearby, were associated with elevated CORT release rates. However, mucosal immune function, although highly variable, was not significantly associated with water quality or environmental factors. Finally, we examined skin bacterial diversity as it aids in immunity and is affected by environmental variation. We found that skin bacterial diversity differed between ponds and was affected by land cover type, canopy cover and pond proximity. Our results indicate that both local water quality and land cover characteristics are important determinants of population health for ornate chorus frogs. Moreover, using these proactive measures of health over time may aid in early identification of at-risk populations that could prevent further declines and aid in management decisions.

Conservation Physiology↗

USGS2021

Hotter drought escalates tree cover declines in blue oak woodlands of California

California has, in recent years, become a hotspot of interannual climatic variability, recording devastating climate-related disturbances with severe effects on tree resources. Understanding the patterns of tree cover change associated with these events is vital for developing strategies to sustain critical habitats of endemic and threatened vegetation communities. We assessed patterns of tree cover change, especially the effects of the 2012–2016 drought within the distribution range of blue oak ( Quercus douglasii ), an endemic tree species to California with a narrow geographic extent. We utilized multiple, annual land-cover and land-surface change products from the U.S. Geological Survey (USGS) Land Change Monitoring, Assessment and Projection (LCMAP) project along with climate and wildfire datasets to monitor changes in tree cover state and condition and examine their relationships with interannual climate variability between 1985 and 2016. Here, we refer to a change in tree cover class without a land-cover change to another class as “conditional change.” The unusual drought of 2012–2016, accompanied by anomalously high temperatures and vapor pressure deficit, was associated with exceptional spikes in the amount of both fire and non-fire induced tree cover loss and tree cover conditional change, especially in 2015 and 2016. Approximately 1,266 km 2 of tree cover loss and 617 km 2 of tree cover conditional change were recorded during that drought. Tree cover loss through medium to high severity fires was especially large in exceptionally dry and hot years. Our study demonstrates the usefulness of the LCMAP products for monitoring the effects of climatic extremes and disturbance events on both thematic and conditional land-cover change over a multi-decadal period. Our results signify that blue oak woodlands may be vulnerable to extreme climate events and changing wildfire regimes. Here, we present early evidence that frequent droughts associated with climate warming may continue to affect tree cover in this region, while drought interaction with wildfires and the resulting feedbacks may have substantial influence as well. Consequently, efforts to conserve the blue oak woodlands, and potentially other vegetation communities in the Western United States, may benefit from consideration of climate risks as well as the potential for climate-fire and vegetation feedbacks.

California↗

USGS2002

Simulation of flow and effects of best-management practices in the upper Seco Creek basin, south-central Texas, 1991-98

The Hydrological Simulation Program— FORTRAN model was used to assess the effects of two best-management practices—brush management (removal of woody species locally known as cedar) and weather modification (rainfall enhancement)—on selected hydrologic processes in six subbasins that compose the upper Seco Creek Basin in south-central Texas. A parameter set for use with the model was developed to simulate surface-water-budget components for the six gaged subbasins. Simulation of brush management, represented by decreases in simulated evapotranspiration of 5 to 6 percent, resulted in increases of 1 to 47 percent in annual runoff and increases of 14 to 48 percent in surface runoff for the six subbasins. Simulation of weather modification, represented by a 10-percent increase in rainfall totals and intensities, resulted in increases of 5 to 6 percent in evapotranspiration, increases of 2 to 92 percent in annual runoff, and increases of 36 to 101 percent in surface runoff. Rainfall and runoff data for the study were collected during January 1, 1991–September 30, 1998. Data from 60 storms were used for the simulations. The model was calibrated with data from 33 storms (in two subbasins) and tested with data from 27 storms (in four subbasins). Twenty-one pervious land segments were defined for the study on the basis of geology and land cover. An error analysis and a sensitivity analysis were done on each subbasin, and the results were used to develop the final parameter set.

Texas↗

USGS2010

Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model

This paper presents a fine-scale (30 meter resolution) regional land cover modeling system, based on the SLEUTH cellular automata model, that was developed for a 257000 km 2 area comprising the Chesapeake Bay drainage basin in the eastern United States. As part of this effort, we developed a new version of the SLEUTH model (SLEUTH-3r), which introduces new functionality and fit metrics that substantially increase the performance and applicability of the model. In addition, we developed methods that expand the capability of SLEUTH to incorporate economic, cultural and policy information, opening up new avenues for the integration of SLEUTH with other land-change models. SLEUTH-3r is also more computationally efficient (by a factor of 5) and uses less memory (reduced 65%) than the original software. With the new version of SLEUTH, we were able to achieve high accuracies at both the aggregate level of 15 sub-regional modeling units and at finer scales. We present forecasts to 2030 of urban development under a current trends scenario across the entire Chesapeake Bay drainage basin, and three alternative scenarios for a sub-region within the Chesapeake Bay watershed to illustrate the new ability of SLEUTH-3r to generate forecasts across a broad range of conditions.

Computers, Environment and Urban Systems↗

USGS2015

Quantifying soil carbon loss and uncertainty from a peatland wildfire using multi-temporal LiDAR

Peatlands are a major reservoir of global soil carbon, yet account for just 3% of global land cover. Human impacts like draining can hinder the ability of peatlands to sequester carbon and expose their soils to fire under dry conditions. Estimating soil carbon loss from peat fires can be challenging due to uncertainty about pre-fire surface elevations. This study uses multi-temporal LiDAR to obtain pre- and post-fire elevations and estimate soil carbon loss caused by the 2011 Lateral West fire in the Great Dismal Swamp National Wildlife Refuge, VA, USA. We also determine how LiDAR elevation error affects uncertainty in our carbon loss estimate by randomly perturbing the LiDAR point elevations and recalculating elevation change and carbon loss, iterating this process 1000 times. We calculated a total loss using LiDAR of 1.10 Tg C across the 25 km 2 burned area. The fire burned an average of 47 cm deep, equivalent to 44 kg C/m 2 , a value larger than the 1997 Indonesian peat fires (29 kg C/m 2 ). Carbon loss via the First-Order Fire Effects Model (FOFEM) was estimated to be 0.06 Tg C. Propagating the LiDAR elevation error to the carbon loss estimates, we calculated a standard deviation of 0.00009 Tg C, equivalent to 0.008% of total carbon loss. We conclude that LiDAR elevation error is not a significant contributor to uncertainty in soil carbon loss under severe fire conditions with substantial peat consumption. However, uncertainties may be more substantial when soil elevation loss is of a similar or smaller magnitude than the reported LiDAR error.

Virginia↗

USGS2016

Exposure of native bees foraging in an agricultural landscape to current-use pesticides

The awareness of insects as pollinators and indicators of environmental quality has grown in recent years, partially in response to declines in honey bee (Apis mellifera) populations. While most pesticide research has focused on honey bees, there has been less work on native bee populations. To determine the exposure of native bees to pesticides, bees were collected from an existing research area in northeastern Colorado from two land cover types: grasslands (2013-2014) and wheat fields (2014). Traps were deployed bi-monthly during the summer at each land cover type and all bees, regardless of species, were composited as whole samples and analyzed for 136 current-use pesticides and degradates. This reconnaissance approach provides a sampling of all species and represents overall pesticide exposure (internal and external). Nineteen pesticides and degradates were detected in 54 composite samples collected. Compounds detected in >10% of the samples included the insecticides thiamethoxam (46%), bifenthrin (28%), clothianidin (24%), chlorpyrifos (17%), and imidacloprid (13%), the fungicides azoxystrobin (17%), and pyraclostrobin (11%), and the herbicide atrazine (19%). Concentrations ranged from 1.1 to 312 ng/g for individual pesticides. Pesticides were detected in samples collected from both grasslands and wheat fields; the location of the sample and the surrounding land cover at the 1000 m buffer influenced the pesticides detected but because of a small number of temporally comparable samples, correlations between pesticide concentration and land cover were not significant. The results show native bees collected in both grasslands and wheat fields are exposed to multiple pesticides, these results can direct future research on routes/timing of pesticide exposure and the design of future conservation efforts for pollinators.

Colorado↗

USGS2014

Modelling landscape-scale erosion potential related to vehicle disturbances along the U.S.-Mexico border

Decades of intensive off-road vehicle use for border security, immigration, smuggling, recreation, and military training along the USA–Mexico border have prompted concerns about long-term human impacts on sensitive desert ecosystems. To help managers identify areas susceptible to soil erosion from anthropogenic activities, we developed a series of erosion potential models based on factors from the Universal Soil Loss Equation (USLE). To better express the vulnerability of soils to human disturbances, we refined two factors whose categorical and spatial representations limit the application of the USLE for non-agricultural landscapes: the C -factor (vegetation cover) and the P -factor (support practice/management). A soil compaction index ( P -factor) was calculated as the difference in saturated hydrologic conductivity ( K s ) between disturbed and undisturbed soils, which was then scaled up to maps of vehicle disturbances digitized from aerial photography. The C -factor was improved using a satellite-based vegetation index, which was better correlated with estimated ground cover ( r 2  = 0·77) than data derived from land cover ( r 2  = 0·06). We identified 9,780 km of unauthorized off-road tracks in the 2,800-km 2 study area. Maps of these disturbances, when integrated with soil compaction data using the USLE, provided landscape-scale information on areas vulnerable to erosion from both natural processes and human activities and are detailed enough for adaptive management and restoration planning. The models revealed erosion potential hotspots adjacent to the border and within areas managed as critical habitat for the threatened flat-tailed horned lizard and endangered Sonoran pronghorn.

Land Degradation and Development↗

USGS2020

Estimating the drivers of species distributions with opportunistic data using mediation analysis

Ecological occupancy modeling has historically relied on high-quality, low-quantity designed-survey data for estimation and prediction. In recent years, there has been a large increase in the amount of high-quantity, unknown-quality opportunistic data. This has motivated research on how best to combine these two data sources in order to optimize inference. Existing methods can be infeasible for large datasets or require opportunistic data to be located where designed-survey data exist. These methods map species occupancies, motivating a need to properly evaluate covariate effects (e.g., land cover proportion) on their distributions. We describe a spatial estimation method for supplementarily including additional opportunistic data using mediation analysis concepts. The opportunistic data mediate the effect of the covariate on the designed-survey data response, decomposing it into a direct and indirect effect. A component of the indirect effect can then be quickly estimated via regressing the mediator on the covariate, while the other components are estimated through a spatial occupancy model. The regression step allows for use of large quantities of opportunistic data that can be collected in locations with no designed-survey data available. Simulation results suggest that the mediated method produces an improvement in relative MSE when the data are of reasonable quality. However, when the simulated opportunistic data are poorly correlated with the true spatial process, the standard, unmediated method is still preferable. A spatiotemporal extension of the method is also developed for analyzing the effect of deciduous forest land cover on red-eyed vireo distribution in the southeastern United States and find that including the opportunistic data do not lead to a substantial improvement. Opportunistic data quality remains an important consideration when employing this method, as with other data integration methods.

eastern United States↗