Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Algorithms”

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 1,513 records · Page 84Linked to original sources

Inventory and mapping of flood inundation using interactive digital image analysis techniques

LANDSAT digital data and color infra-red photographs were used in a multiphase sampling scheme to estimate the area of agricultural land affected by a flood. The LANDSAT data were classified with a maximum likelihood algorithm. Stratification of the LANDSAT data, prior to classification, greatly reduced misclassification errors. The classification results were used to prepare a map overlay showing the areal extent of flooding. These data also provided statistics required to estimate sample size in a two phase sampling scheme, and provided quick, accurate estimates of areas flooded for the first phase. The measurements made in the second phase, based on ground data and photo-interpretation, were used with two phase sampling statistics to estimate the area of agricultural land affected by flooding These results show that LANDSAT digital data can be used to prepare map overlays showing the extent of flooding on agricultural land and, with two phase sampling procedures, can provide acreage estimates with sampling errors of about 5 percent. This procedure provides a technique for rapidly assessing the areal extent of flood conditions on agricultural land and would provide a basis for designing a sampling framework to estimate the impact of flooding on crop production.

Canadian Journal of Remote Sensing↗

Data integration using color space transforms

The demand for increased spatial resolution without sacrificing spectral discrimination can be fulfilled by integration of data from different sensor systems and satellite programs. Data of high spatial resolution are frequently available in panchromatic (black-and-white) form rather than multispectral. Techniques gave been developed to combine the higher resolution panchromatic data with a multispectral data set of lower spatial resolution. The standard method of integration modulates the intensity of the mutispectral with the panchromatic data. A less subjective approach uses an algorithm that describes color in terms of intensity (I), hue (H), and saturation (S). Combinations of high resolution panchromatic data (SPOT panchromatic) and lower resolution multispectral data [Landsat thematic mapper (TM), SPOT XS] have been developed. The SPOT data were acquired on April 3, 1986, and the Landsat TM data were acquired on April 5, 1986. The data sets were registered to each other and the multi-spectral data sets were contrast enhanced. The enhanced multispectral data sets were then transformed from red/green/blue (RGB) color space into IHS space. In each case (TM/SPOT panchromatic and SPOT XS/SPOT panchromatic), the SPOT panchromatic data were remapped on a cumulative histogram percentage basis to match the multispectral "I" data. These remapped SPOT panchromatic data were substituted for the original multispectral "I" and the hybrid IHS data transformed back into RGB space for display. While this technique is experimental and still being refined, the results, to date, indicate that the IHS method will be valuable for generating improved images that effectively present both high resolution spatial digital data and multispectral data.

Pecora XI Symposium↗

Landsat-faciliated vegetation classification of the Kenai National Wildlife Refuge and adjacent areas, Alaska

A Landsat-based vegetation map was prepared for Kenai National Wildlife Refuge and adjacent lands, 2 million and 2.5 million acres respectively. The refuge lies within the middle boreal sub zone of south central Alaska. Seven major classes and sixteen subclasses were recognized: forest (closed needleleaf, needleleaf woodland, mixed); deciduous scrub (lowland and montane, subalpine); dwarf scrub (dwarf shrub tundra, lichen tundra, dwarf shrub and lichen tundra, dwarf shrub peatland, string bog/wetlands); herbaceous (graminoid meadows and marshes); scarcely vegetated areas ; water (clear, moderately turbid, highly turbid); and glaciers. The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo interpretation, and digital Landsat data. Major steps in the Landsat analysis involved: preprocessing (geometric connection), spectral class labeling of sample areas, derivation of statistical parameters for spectral classes, preliminary classification of the entree study area using a maximum-likelihood algorithm, and final classification through ancillary information such as digital elevation data. The vegetation map (scale 1:250,000) was a pioneering effort since there were no intermediate-sclae maps of the area. Representative of distinctive regional patterns, the map was suitable for use in comprehensive conservation planning and wildlife management.

Alaska↗

Monitoring the earth: too many players?

A number of organizations are currently engaged in, or proposing to embark on, worldwide measurement/monitoring programs. Program objectives vary in type and complexity, including a form of technical library (the Global Environment Monitoring System of the United Nations Environment Program), and an ambitious experiment to validate algorithms to derive land surface climatological parameters (International Satellite Land Surface Climatology Project). Modeling and understanding the Earth as an integrated system is an immense undertaking and will require at least as many measurements as are currently acquired. Improved coordination is required among the diverse national and international measurement/monitoring programs to ensure that sensors, launch dates, orbits, and supporting research are complementary to the maximum extent possible. Development of a long-term program of Earth system monitoring/modeling, such as the International Global Change Program proposed by the International Council of Scientific Unions, could provide the necessary focus and structure for effective international coordination and cooperation.

Pecora 10 Symposium↗

Processing techniques for global land 1-km AVHRR data

The U.S. Geological Survey's (USGS) Earth Resources Observation Systems (EROS) Data Center (EDC) in cooperation with several international science organizations has developed techniques for processing daily Advanced Very High Resolution Radiometer (AVHRR) 1-km data of the entire global land surface. These techniques include orbital stitching, geometric rectification, radiometric calibration, and atmospheric correction. An orbital stitching algorithm was developed to combine consecutive observations acquired along an orbit by ground receiving stations into contiguous half-orbital segments. The geometric rectification process uses an AVHRR satellite model that contains modules for forward mapping, forward terrain correction, and inverse mapping with terrain correction. The correction is accomplished by using the hydrologic features coastlines and lakes from the Digital Chart of the World. These features are rasterized into the satellite projection and are matched to the AVHRR imagery using binary edge correlation techniques. The resulting coefficients are related to six attitude correction parameters: roll, roll rate, pitch, pitch rate, yaw, and altitude. The image can then be precision corrected to a variety of map projections and user-selected image frames. Because the AVHRR lacks onboard calibration for the optical wavelengths, a series of time-variant calibration coefficients derived from vicarious calibration methods and are used to model the degradation profile of the instruments. Reducing atmospheric effects on AVHRR data is important. A method has been develop that will remove the effects of molecular scattering and absorption from clear sky observations, using climatological measurements of ozone. Other methods to remove the effects of water vapor and aerosols are being investigated.

Pecora 12 Symposium↗

Integration of environmental simulation models with satellite remote sensing and geographic information systems technologies: case studies

Environmental modelers are testing and evaluating a prototype land cover characteristics database for the conterminous United States developed by the EROS Data Center of the U.S. Geological Survey and the University of Nebraska Center for Advanced Land Management Information Technologies. This database was developed from multi temporal, 1-kilometer advanced very high resolution radiometer (AVHRR) data for 1990 and various ancillary data sets such as elevation, ecological regions, and selected climatic normals. Several case studies using this database were analyzed to illustrate the integration of satellite remote sensing and geographic information systems technologies with land-atmosphere interactions models at a variety of spatial and temporal scales. The case studies are representative of contemporary environmental simulation modeling at local to regional levels in global change research, land and water resource management, and environmental simulation modeling at local to regional levels in global change research, land and water resource management and environmental risk assessment. The case studies feature land surface parameterizations for atmospheric mesoscale and global climate models; biogenic-hydrocarbons emissions models; distributed parameter watershed and other hydrological models; and various ecological models such as ecosystem, dynamics, biogeochemical cycles, ecotone variability, and equilibrium vegetation models. The case studies demonstrate the important of multi temporal AVHRR data to develop to develop and maintain a flexible, near-realtime land cover characteristics database. Moreover, such a flexible database is needed to derive various vegetation classification schemes, to aggregate data for nested models, to develop remote sensing algorithms, and to provide data on dynamic landscape characteristics. The case studies illustrate how such a database supports research on spatial heterogeneity, land use, sensitivity analysis, and scaling issues involving regional extrapolations and parameterizations of dynamic land processes within simulation models.

Pecora 12 Symposium↗

A workshop model simulating fate and effect of drilling muds and cuttings on benthic communities

Oil and gas exploration and production at marine sites has generated concern over potential environmental impacts resulting from the discharge of spent drilling muds and cuttings. This concern has led to a broad array of publicly and privately sponsored research. This report described a cooperative modeling effort designed to focus information resulting from this research through construction of explicit equations that simulate the potential impacts of discharge drilling fluids (muds) and cuttings on marine communities. The model is the result of collaboration among more than 30 scientists. The principal cooperating organizations were the E.S. Environmental Protection Agency, the U.S. Minerals Management Service, the Offshore Operators Committee, and the Alaska Oil and Gas Association. The overall simulation model can be conceptualized as three connected submodels: Discharge and Plume Fate, Sediment Redistribution, and Benthic Community Effects. On each day of simulation, these submodels are executed in sequence, with flows of information between submodels. The Benthic Community Effects submodel can be further divided into sections that calculate mortality due to burial, mortality due to toxicity, mortality due to resuspension disturbance, and growth of the community. The model represents a series of seven discrete 1-m 2 plots at specified distances along a transect in one direction away from a discharge point. It consists of coupled difference equations for which parameter values can easily be set to evaluate different conditions or to examine the sensitivity of output to various assumptions. Sets of parameter values were developed to represent four general cases or scenarios: (1) a shallow (5 m), cold environment with ice cover during a substantial fraction of the year, such as might be encountered in the Beaufort Sea, Alaska; (2) a shallow (20 m), temperate environment, such as might be encountered in the Gulf of Mexico; (3) a deeper (80 m), temperate environment, such as might be encountered in the Gulf of Mexico; and (4) a very deep (1,000 m) environment, such as might be encountered on the Atlantic slope. The focus of the modeling effort was on the connection of a reasonable representation of physical fate to the biological responses of populations, rather than on highly detailed representations of individual processes. For example, the calculations of physical fate are not as detailed as those in the recently published model of Brandsma et al. (1983). The value of the model described herein is in the broad scope of processes that are explicitly represented and linked together. The model cannot be considered to produce reliable predictions of the quantitative impacts of discharged drilling fluids and cuttings on biological populations at a particular site. Limitations of the model in predicting integrated fate and effects can be traced to three general areas: level of refinement of the algorithms used in the model; lack of understanding of the processes determining fate and effects; and parameter and data values. Despite the limitations, several qualitative conclusions concerning both potential impacts and the importance of various remaining data gaps can be drawn from the modeling effort. These include: (1) Simple, unequivocal conclusions about fate and effects across geographical regions and drilling operations are difficult, if not misleading, due to the large amount of variability in characteristics of discharged materials (e.g., oil content and toxicity), discharge conditions (e.g., duration of drilling operations), physical environments (e.g., water depth, current direction, and sediment disturbance regimes), and biological communities (e.g., intrinsic growth rates). Different combinations of these characteristics can result in substantial differences in simulated environmental fate and biological effects. For examples, simulated recovery in some high-energy environments occurs within months after the cessation of discharge operations, even at heavily impacted sites, whereas simulated recover in some low-energy environments takes years at heavily impacted sites. <2) Considerable difficulties remain in the reliable extrapolation of results from laboratory toxicity experiments to predictions of population effects in the field. (3) The volume of material discharged and duration of operations in the production drilling operations simulated by the model are sufficient to produce substantial simulated biological impacts at some plots, both in terms of differences from a control plot during the period of discharge operations, and in terms of the recovery period following the perturbations. Evaluation of the significance of potential effects involves the following factors: • Definition of a specific spatial and temporal reference frame (e.g., What is the natural variation? Is 1 year to be considered a "long" or "short" time? Is 50 m to be considered a "large" or "trivial" distance? • Consideration of rare or unique resources and particularly sensitive biotic assemblages. • Consideration of the potential for long term, cumulative effects. Some of these aspects are clearly beyond the scope of this modeling efforts (e.g., the model does not simulate the long term fate of resuspended material). The model does, however, contain an internal "reference frame" by comparison to simulated behavior at a control plot. The model, in general, simulates substantial "natural" variation at the reference or control plots, both over time, due to sediment disturbance events in medium to high energy environments, and over space, due to geographically varying conditions, such as water depth and current regime.

Report↗

Vegetation mapping of Nowitna National Wildlife Refuge, Alaska using Landsat MSS digital data

A Landsat-derived vegetation map was prepared for Nowitna National Wildlife Refuge. The refuge lies within the middle boreal subzone of north central Alaska. Seven major vegetation classes and sixteen subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, alluvial, subalpine); dwarf scrub (prostrate dwarf shrub tundra, dwarf shrub-graminoid tussock peatland); herbaceous (graminoid bog, marsh and meadow); scarcely vegetated areas (scarcely vegetated scree and floodplain); water (clear, turbid); and other areas (mountain shadow). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photointerpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is a 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

Alaska↗

Intermediate-scale vegetation mapping of Innoko National Wildlife Refuge, Alaska using Landsat MSS digital data

A Landsat-derived vegetation map was prepared for lnnoko National Wildlife Refuge. The refuge lies within the northern boreal subzone of northwestern central Alaska. Six major vegetation classes and 21 subclasses were recognized: forest (closed needleleaf, open needleleaf, needleleaf woodland, mixed, and broadleaf); broadleaf scrub (lowland, upland burn regeneration, subalpine); dwarf scrub (prostrate dwarf shrub tundra, erect dwarf shrub heath, dwarf shrub-graminoid peatland, dwarf shrub-graminoid tussock peatland, dwarf shrub raised bog with scattered trees, dwarf shrub-graminoid marsh); herbaceous (graminoid bog, graminoid marsh, graminoid tussock-dwarf shrub peatland); scarcely vegetated areas (scarcely vegetated scree and floodplain); and water (clear, sedimented). The methodology employed a cluster-block technique. Sample areas were described based on a combination of helicopter-ground survey, aerial photo-interpretation, and digital Landsat data. Major steps in the Landsat analysis involved preprocessing (geometric correction), derivation of statistical parameters for spectral classes, spectral class labeling of sample areas, preliminary classification of the entire study area using a maximum-likelihood algorithm, and final classification utilizing ancillary information such as digital elevation data. The final product is 1:250,000-scale vegetation map representative of distinctive regional patterns and suitable for use in comprehensive conservation planning.

Alaska↗

Using hydrophones as a surrogate monitoring technique to detect temporal and spatial variability in bedload transport

Collecting physical bedload measurements is an expensive and time-consuming endeavor that rarely captures the spatial and temporal variability of sediment transport. Technological advances can improve monitoring of sediment transport by filling in temporal gaps between physical sampling periods. We have developed a low-cost hydrophone recording system designed to record the sediment-generated noise (SGN) resulting from collisions of coarse particles (generally larger than 4 mm) in gravel-bedded rivers. The sound level of the signal recorded by the hydrophone is assumed to be proportional to the magnitude of bedload transport as long as the acoustic frequency of the SGN is known, the grain-size distribution of the bedload is assumed constant, and the frequency band of the ambient noise is known and can be excluded from the analysis. Each system has two hydrophone heads and samples at half-hour intervals. Ten systems were deployed on the San Joaquin River, California, and its tributaries for ten months during water year 2014, and two systems were deployed during a flood event on the Gunnison River, Colorado in 2014. A mobile hydrophone system was also tested at both locations to collect longitudinal profiles of SGN. Physical samples of bedload were not collected in this study. In lieu of physical measurements, several audio recordings from each site were aurally reviewed to confirm the presence or absence of SGN, and hydraulic data were compared to historical measurements of bedload transport or transport capacity estimates to verify if hydraulic conditions during the study would likely produce bedload transport. At one site on the San Joaquin River, the threshold of movement was estimated to have occurred around 30 m 3 /s based on SGN data. During the Gunnison River flood event, continuous data showed clockwise hysteresis, indicating that bedload transport was generally less at any given streamflow discharge during the recession limb of the hydrograph. Spatial variability in transport was also detected in the longitudinal profiles audibly and using signal processing algorithms. These experiments demonstrate the ability of hydrophone technology to capture the temporal and spatial variability of sediment transport, which may be missed when samples are collected using conventional methods.

California, Colorado↗

Developing climate data records and essential climate variables from landsat data

The series of Landsat missions has compiled the longest record of satellite observation of the Earth&rsquo;s land surface, extending for more than 38 years for most areas of the globe. Landsat data are particularly important as long term climate data records because the scale of observation is sufficient to differentiate between natural and human drivers of land cover change. The USGS has established consistent radiometric calibration across the Landsat TM and ETM+ sensors, and have extended the calibration back to the earlier MSS sensors. The USGS is developing capabilities to create fundamental climate data records (FCDRs), thematic climate data records (TCDRs), and essential climate variables (ECVs) from the Landsat data archive. Two high priority TCDRs were identified: surface reflectance and land surface temperature because they have direct application or are required as input to the generation of ECVs. We will focus development on a few of the terrestrial ECVs that have a high potential for being derived from Landsat data, that include land cover, albedo, fire disturbance, surface water, snow and ice, and leaf area index (LAI). We are collaborating with scientists who have demonstrated successful algorithm development and application of these science products to develop a framework of processing capabilities to support research projects and land management applications, along with an independent strategy for product validation. Our goal is to scale the creation and validation of these products from specific sites in the conterminous U.S. and Alaska, for extension to continental and global scales.

Conference Paper↗

Modelling ecosystem service flows under uncertainty with stochiastic SPAN

Ecosystem service models are increasingly in demand for decision making. However, the data required to run these models are often patchy, missing, outdated, or untrustworthy. Further, communication of data and model uncertainty to decision makers is often either absent or unintuitive. In this work, we introduce a systematic approach to addressing both the data gap and the difficulty in communicating uncertainty through a stochastic adaptation of the Service Path Attribution Networks (SPAN) framework. The SPAN formalism assesses ecosystem services through a set of up to 16 maps, which characterize the services in a study area in terms of flow pathways between ecosystems and human beneficiaries. Although the SPAN algorithms were originally defined deterministically, we present them here in a stochastic framework which combines probabilistic input data with a stochastic transport model in order to generate probabilistic spatial outputs. This enables a novel feature among ecosystem service models: the ability to spatially visualize uncertainty in the model results. The stochastic SPAN model can analyze areas where data limitations are prohibitive for deterministic models. Greater uncertainty in the model inputs (including missing data) should lead to greater uncertainty expressed in the model&rsquo;s output distributions. By using Bayesian belief networks to fill data gaps and expert-provided trust assignments to augment untrustworthy or outdated information, we can account for uncertainty in input data, producing a model that is still able to run and provide information where strictly deterministic models could not. Taken together, these attributes enable more robust and intuitive modelling of ecosystem services under uncertainty.

Conference Paper↗

Using maximum topology matching to explore differences in species distribution models

Species distribution models (SDM) are used to help understand what drives the distribution of various plant and animal species. These models are typically high dimensional scalar functions, where the dimensions of the domain correspond to predictor variables of the model algorithm. Understanding and exploring the differences between models help ecologists understand areas where their data or understanding of the system is incomplete and will help guide further investigation in these regions. These differences can also indicate an important source of model to model uncertainty. However, it is cumbersome and often impractical to perform this analysis using existing tools, which allows for manual exploration of the models usually as 1-dimensional curves. In this paper, we propose a topology-based framework to help ecologists explore the differences in various SDMs directly in the high dimensional domain. In order to accomplish this, we introduce the concept of maximum topology matching that computes a locality-aware correspondence between similar extrema of two scalar functions. The matching is then used to compute the similarity between two functions. We also design a visualization interface that allows ecologists to explore SDMs using their topological features and to study the differences between pairs of models found using maximum topological matching. We demonstrate the utility of the proposed framework through several use cases using different data sets and report the feedback obtained from ecologists.

Conference Paper↗

Spatially explicit shallow landslide susceptibility mapping over large areas

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

California↗

Laboratory simulation of the effects of overburden stress on the specific storage of shallow artesian aquifers

A laboratory experiment to measure the specific storage of an aquifer material was conducted. A known dead load, simulating an overburden load, was applied to a sample of completely saturated aquifer material contained inside a cylinder. After the dead load was applied, water was withdrawn from the sample, causing the hydrostatic pressure to decrease and the effective stress to increase. The resulting compression of the sample and the amount of water withdrawn were measured after equilibrium was reached. The procedure was repeated by increasing the dead load and the hydrostatic pressure followed by withdrawing water to determine new values of effective stress and compaction. The simulated dead loads are typical of those experienced by shallow artesian aquifers. The void ratio and the effective stress of the aquifer sample, as simulated by different dead loads, determine the pore volume compressibility which, in turn, determines the values of specific storage. An analytical algorithm was used to independently determine the stress dependent profile of specific storage. These values are found to be in close agreement with laboratory results. Implications for shallow artesian aquifers, with relatively small overburden stress, are also addressed.

Conference Paper↗

A nowcast model for tides and tidal currents in San Francisco Bay, California

National Oceanographic and Atmospheric Administration (NOAA) installed Physical Oceanographic Real-Time System (PORTS) in San Francisco Bay, California to provide observations of tides, tidal currents, and meteorological conditions. PORTS data are used for optimizing vessel operations, increasing margin of safety for navigation, and guiding hazardous material spill prevention and response. Because tides and tidal currents in San Francisco Bay are extremely complex, limited real-time observations are insufficient to provide spatial resolution for variations of tides and tidal currents. To fill the information gaps, a highresolution, robust, semi-implicit, finite-difference nowcast numerical model has been implemented for San Francisco Bay. The model grid and water depths are defined on coordinates based on Mercator projection so the model outputs can be directly superimposed on navigation charts. A data assimilation algorithm has been established to derive the boundary conditions for model simulations. The nowcast model is executed every hour continuously for tides and tidal currents starting from 24 hours before the present time (now) covering a total of 48 hours simulation. Forty-eight hours of nowcast model results are available to the public at all times through the World Wide Web (WWW). Users can view and download the nowcast model results for tides and tidal current distributions in San Francisco Bay for their specific applications and for further analysis.

California↗

Climate matching as a tool for predicting potential North American spread of Brown Treesnakes

Climate matching identifies extralimital destinations that could be colonized by a potential invasive species on the basis of similarity to climates found in the species&rsquo; native range. Climate is a proxy for the factors that determine whether a population will reproduce enough to offset mortality. Previous climate matching models (e.g., Genetic Algorithm for Rule-set Prediction [GARP]) for brown treesnakes ( Boiga irregularis ) were unsatisfactory, perhaps because the models failed to allow different combinations of climate attributes to influence a species&rsquo; range limits in different parts of the range. Therefore, we explored the climate space described by bivariate parameters of native range temperature and rainfall, allowing up to two months of aestivation in the warmer portions of the range, or four months of hibernation in temperate climes. We found colonization area to be minimally sensitive to assumptions regarding hibernation temperature thresholds. Although brown treesnakes appear to be limited by dry weather in the interior of Australia, aridity rarely limits potential distribution in most of the world. Potential colonization area in North America is limited primarily by cold. Climatically suitable portions of the United States (US) mainland include the Central Valley of California, mesic patches in the Southwest, and the southeastern coastal plain from Texas to Virginia.

Conference Paper↗

Non-invasive genetic sampling of Southern Mule Deer ( Odocoileus hemionus fuliginatus ) reveals limited movement across California State Route 67 in San Diego County

&mdash;The Southern Mule Deer is a mobile but non-migratory large mammal found throughout southern California and is a covered species in the San Diego Multi-Species Conservation Plan. We assessed deer movement and population connectivity across California State Route 67 and two smaller roads in eastern San Diego County using non-invasive genetic sampling. We collected deer scat pellets between April and November 2015, and genotyped pellets at 15 microsatellites and a sex determination marker. We successfully genotyped 71 unique individuals from throughout the study area and detected nine recapture events. Recaptures were generally found close to original capture locations (within 1.5 km). We did not detect recaptures across roads; however, pedigree analysis detected 21 first order relative pairs, of which approximately 20% were found across State Route 67. Exact tests comparing allele frequencies between groups of individuals in pre-defined geographic clusters detected significant genetic differentiation across State Route 67. In contrast, the assignment-based algorithm of STRUCTURE supported a single genetic cluster across the study area. Our data suggest that State Route 67 may reduce, but does not preclude, movement and gene flow of Southern Mule Deer.

California↗