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At least 721 records · Page 40Linked to original sources
USGS2011

Methods of InSAR atmosphere correction for volcano activity monitoring

When a Synthetic Aperture Radar (SAR) signal propagates through the atmosphere on its path to and from the sensor, it is inevitably affected by atmospheric effects. In particular, the applicability and accuracy of Interferometric SAR (InSAR) techniques for volcano monitoring is limited by atmospheric path delays. Therefore, atmospheric correction of interferograms is required to improve the performance of InSAR for detecting volcanic activity, especially in order to advance its ability to detect subtle pre-eruptive changes in deformation dynamics. In this paper, we focus on InSAR tropospheric mitigation methods and their performance in volcano deformation monitoring. Our study areas include Okmok volcano and Unimak Island located in the eastern Aleutians, AK. We explore two methods to mitigate atmospheric artifacts, namely the numerical weather model simulation and the atmospheric filtering using Persistent Scatterer processing. We investigate the capability of the proposed methods, and investigate their limitations and advantages when applied to determine volcanic processes. ?? 2011 IEEE.

Conference Paper↗
USGS2007

Estimation of forest fuel load from radar remote sensing

Understanding fire behavior characteristics and planning for fire management require maps showing the distribution of wildfire fuel loads at medium to fine spatial resolution across large landscapes. Radar sensors from airborne or spaceborne platforms have the potential of providing quantitative information about the forest structure and biomass components that can be readily translated to meaningful fuel load estimates for fire management. In this paper, we used multifrequency polarimetric synthetic aperture radar (SAR) imagery acquired over a large area of the Yellowstone National Park by the Airborne SAR sensor to estimate the distribution of forest biomass and canopy fuel loads. Semiempirical algorithms were developed to estimate crown and stem biomass and three major fuel load parameters, namely: 1) canopy fuel weight; 2) canopy bulk density; and 3) foliage moisture content. These estimates, when compared directly to measurements made at plot and stand levels, provided more than 70% accuracy and, when partitioned into fuel load classes, provided more than 85% accuracy. Specifically, the radar-generated fuel parameters were in good agreement with the field-based fuel measurements, resulting in coefficients of determination of R2 = 85 for the canopy fuel weight, R 2 = 0.84 for canopy bulk density, and R2 =0.78 for the foliage biomass. ?? 2007 IEEE.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2013

Assessment of spectral band impact on intercalibration over desert sites using simulation based on EO-1 Hyperion data

Since the beginning of the 1990s, stable desert sites have been used for the calibration monitoring of many different sensors. Many attempts at sensor intercalibration have been also conducted using these stable desert sites. As a result, site characterization techniques and the quality of intercalibration techniques have gradually improved over the years. More recently, the Committee on Earth Observation Satellites has recommended a list of reference pseudo-invariant calibration sites for frequent image acquisition by multiple agencies. In general, intercalibration should use well-known or spectrally flat reference. The reflectance profile of desert sites, however, might not be flat or well characterized (from a fine spectral point of view). The aim of this paper is to assess the expected accuracy that can be reached when using desert sites for intercalibration. In order to have a well-mastered estimation of different errors or error sources, this study is performed with simulated data from a hyperspectral sensor. Earth Observing-1 Hyperion images are chosen to provide the simulation input data. Two different cases of intercalibration are considered, namely, Landsat 7 Enhanced Thematic Mapper Plus with Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and Environmental Satellite MEdium Resolution Imaging Spectrometer (MERIS) with Aqua MODIS. The simulation results have confirmed that intercalibration accuracy of 1% to 2% can be achieved between sensors, provided there are a sufficient number of available measurements. The simulated intercalibrations allow explaining results obtained during real intercalibration exercises and to establish some recommendations for the use of desert sites for intercalibration.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2016

Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS2013

Location-only and use-availability data: analysis methods converge

This Special Feature arose from a session on a topic of the same name that took place during The Wildlife Society meeting in Kona, Hawaii, from 5 to 10 November, 2011. The purpose of that session and this Special Feature is to compare methods for predictive modelling of species geographical distributions and the modelling of habitat (resource) selection by animals. The predictive modelling of species geographical distributions and the modelling of habitat selection based on the environmental conditions at sites where animals are known to occur are essentially the same problem. Presence-only and used-available data both consist of a sample of locations with known presence of a species or an individual. A separate sample of locations from a study area, with unknown presence (pseudo-absence), is also assumed to exist. The probability or relative probability of presence of a species or individual is modelled and estimated across a certain time implicitly defined by the sampling mechanism, for example, by the time period during which museum specimens or radiotelemetry data were collected. A number of modelling methods have appeared in the literature over the last couple of decades. Many of these methods were made feasible by the availability of geographical information systems (GIS), global positioning system (GPS) radiotelemetry and public online data access initiatives (e.g. global biodiversity information facility). The papers in this Special Feature are intended to present the state of the methodological art in their subject area, with particular attention paid to contrasting the advantages and disadvantages of alternative methods of analysis for data.

Journal of Animal Ecology↗
USGS2024

Integrating presence-only and detection/non-detection data to estimate distributions and expected abundance of difficult-to-monitor species on a landscape-scale

Estimating species distribution and abundance is foundational to effective management and conservation. Using an integrated species distribution model that combines presence-only data from various sources with detection/non-detection data from structured surveys, we estimated the distribution and expected abundance of three difficult-to-monitor mammals of management concern across New York State, namely, coyotes ( Canis latrans ), bobcats ( Lynx rufus ) and black bears ( Ursus americanus ). Three distinct landscape-scale camera trap surveys provided detection/non-detection data over 9 years between 2013 and 2021, and we augmented those data with incidental records of our focal species from public repositories. We used an inhomogeneous Poisson point process to construct an integrated model that fit both data types simultaneously. We demonstrate a simple application of spatial point density of all species records in the accessed public databases to inform the thinning process to account for unknown spatial sampling in the presence-only data, often referred to as the ‘magic covariate’. Using this approach, we examine habitat associations and provide spatially explicit estimates in expected abundance across the entirety of New York State for all three focal species. As expected, coyotes were the most widely distributed and abundant species, with a strong positive association with agricultural land uses. Bobcats exhibited low expected abundance throughout the state and showed positive associations with deciduous forest and forest edge, and a negative association with road density. Finally, we observed considerable spatial variation in abundance of black bears with expected abundance increasing in association with various forest cover and composition covariates and decreasing with crop cover. We present insights into habitat associations and spatial variation in abundance, and provide management implications for each of the species of interest. Synthesis and applications . Our integrated modelling method allows for managers to use citizen sightings combined with detection/non-detection surveys to estimate robust indices of abundance for both high- and low-density, and wide-spread versus patchily distributed species. Through comparison with previous studies, we highlight how broad-scale programmes, such as the statewide efforts to estimate species distributions undertaken here, can benefit substantively from integrated models that leverage additional data (here, incidental records) from a larger region of space, and thus capture more landscape heterogeneity than is plausible within formalized surveys alone.

New York↗
USGS2024

Evaluating water-quality trends in agricultural watersheds prioritized for management-practice implementation

Many agricultural watersheds rely on the voluntary use of management practices (MPs) to reduce nonpoint source nutrient and sediment loads; however, the water-quality effects of MPs are uncertain. We interpreted water-quality responses from as early as 1985 through 2020 in three agricultural Chesapeake Bay watersheds that were prioritized for MP implementation, namely, the Smith Creek (Virginia), Upper Chester River (Maryland), and Conewago Creek (Pennsylvania) watersheds. We synthesized patterns in MPs, climate, land use, and nutrient inputs to better understand factors affecting nutrient and sediment loads. Relations between MPs and expected water-quality improvements were not consistently identifiable. The number of MPs increased in all watersheds since the early 2010s, but most monitored nutrient and sediment loads did not decrease. Nutrient and sediment loads increased or remained stable in Smith Creek and the Upper Chester River. Sediment loads and some nutrient loads decreased in Conewago Creek. In Smith Creek, a 36-year time-series model suggests that changes in manure affected flow-normalized total nitrogen loads. We hypothesize that increases in nutrient applications may overshadow some expected MP effects. MPs might have stemmed further water-quality degradation, but improvements in nutrient loads may rely on reducing manure and fertilizer applications. Our results highlight the importance of assessing MP performance with long-term monitoring-based studies.

Journal of the American Water Resources Assocation↗
USGS2024

Integration of Indigenous Research Methodologies, Traditional Ecological Knowledge and molecular scatology in an assessment of mesocarnivore presence, diet and habitat use on Yurok Ancestral Lands.

Partnerships between Tribes and researchers in wildlife monitoring and application of Traditional Ecological Knowledge (TEK) have taken a variety of forms, and some scholars have noted a need for culturally sensitive approaches. Guided by Indigenous Research Methodologies, this research is coupled with Yurok TEK, or hlkelonah 'ue-megetohl ('to take care of the earth'), enabling an applied, culturally sensitive approach in partnership with the Yurok Tribe. We present results from a molecular scatology study of wildlife within the ancestral territory of the Yurok Tribe. Scats were collected opportunistically on road transects. All samples ( N = 132) were analysed via DNA barcoding and results matched to documented 'Oohl 'we-toh (Yurok language) names to determine the depositor species ( N = 8). Though there were four focal mesocarnivore species in our study, only bobcat ( Chmuuek; Lynx rufus ) and gray fox ( Wergers; Urocyon cinereoargenteus ) were detected as depositor species. Post hoc analyses were conducted to explore distribution, habitat use and selection in a use-availability context, and food habits of these two species. We found almost complete separation of bobcat and gray fox use of transects, as well as indication of partitioning of vegetation cover types and food. We demonstrate an integrated framework of Western and Indigenous sciences that allows the Indigenous researcher to transcend structured academic disciplinary boundaries. Our approach can be modified for partnerships between Tribes, agencies, academics and students for wildlife monitoring in broader geographic regions in various research applications.

California↗
USGS2020

The effects of swimming exercise and dissolved oxygen on growth performance, fin condition and survival of rainbow trout Oncorhynchus mykiss

Swimming exercise and dissolved oxygen (DO) are important parameters to consider when operating intensive salmonid aquaculture facilities. While previous research has focused on each of these two variables in rainbow trout Oncorhynchus mykiss , studies examining both variables in combination, and their potential interaction, are absent from the scientific literature. Both swimming exercise (usually measured in body lengths per second, or BL/s) and DO can be readily controlled in modern aquaculture systems; therefore, we sought to evaluate the effects of these variables, separately and combined, on several outcomes in rainbow trout including growth performance, fin health and survival. Rainbow trout fry (18 g) were stocked into 12 circular 0.5 m 3 tanks, provided with either high (1.5–2 BL/s) or low (approximately 0.5 BL/s) swimming exercise and high (100% saturation) or low (70% saturation) DO, and grown to approximately 1 kg. By the conclusion of the study, higher DO was independently associated with significantly ( p < .05) increased growth performance. Significant differences were not noted in other outcomes, namely feed conversion, condition factor and mortality, although caudal and right pectoral fin damage was associated with low oxygen and low swimming exercise treatments respectively. Cardiosomatic index was significantly higher among exercised fish. These results suggest that swimming exercise and DO at saturation during the culture of rainbow trout can be beneficial to producers through improved growth performance and cardiac health.

Aquaculture Research↗
USGS2025

Biodiversity on public lands: How community science can help

Species inventories are crucial for conservation but are difficult to assemble and maintain. Bioblitzes, which encourage the public to document biodiversity in a particular area and timeframe, may offer useful information but their integration with other datasets poses challenges. We investigated the potential contribution of bioblitzes to natural resource management using observations from the United States National Park Service (NPS) 2016 Centennial Bioblitz. Through automated cross-referencing over 19,000 iNaturalist “research-grade” observations from 107 national parks with existing park inventory lists, we matched 86% of species documented in the Bioblitz to NPS species lists, based on current taxonomy, and matched another 6% of species using alternative scientific names using our matching process in R. Of the remaining 13.5% that did not match the NPS species lists, we manually found that 84% of the unmatched species were found within the lists or were outside the boundaries of the park, identifying 141 native species that were unrecorded in NPS species lists. Many introduced species were recorded; they were more likely to be documented in parks closer to cities. Parks near cities also drew more participants. Our study shows how public participation, through iNaturalist and bioblitzes, can facilitate biodiversity monitoring across large spatial scales.

Conservation Science and Practice↗
USGS2019

Examining progress toward achieving the Ten Steps of the Rome Declaration on Responsible Inland Fisheries

Inland capture fisheries provide food for nearly a billion people and are important in the livelihoods of millions of households worldwide. Although there are limitations to evaluating many of the contributions made by inland capture fisheries, there is growing recognition by the international community that these services make critical contributions, most notably to food security and livelihoods in rural populations in those low-income countries with extensive freshwater resources. With the increasing appreciation of the key role of inland fisheries to the health and well-being of human populations globally, the Food and Agriculture Organization of the United Nations and Michigan State University convened the 2015 global conference, Freshwater, fish, and the future – cross-sectoral approaches to sustain livelihoods, food security, and aquatic ecosystems. What emerged from the interactions between inland fisheries scientists, resource managers, policy makers, and community representatives from across the world, was a forward-looking call-to-action culminating with the 2015 Rome Declaration “Ten Steps to Responsible Inland Fisheries” (FAO and MSU 2016). Four years after this landmark conference and Declaration, we seek to advance discussion on the “Ten Steps,” namely, what successful implementation looks like, assess current examples of implementation, suggest potential signals of progress, and provide some specific, indicative examples of progress for each step. While there are promising signs of progress, we conclude that there remains a strong need to galvanize momentum for sustained action to ensure that inland fish and fisheries are accounted for and incorporated into broader water resource management discussions and frameworks.

Fish and Fisheries↗
USGS2023

Wherever I may roam—Human activity alters movements of red deer (Cervus elaphus) and elk (Cervus canadensis) across two continents

Human activity and associated landscape modifications alter the movements of animals with consequences for populations and ecosystems worldwide. Species performing long-distance movements are thought to be particularly sensitive to human impact. Despite the increasing anthropogenic pressure, it remains challenging to understand and predict animals' responses to human activity. Here we address this knowledge gap using 1206 Global Positioning System movement trajectories of 815 individuals from 14 red deer ( Cervus elaphus ) and 14 elk ( Cervus canadensis ) populations spanning wide environmental gradients, namely the latitudinal range from the Alps to Scandinavia in Europe, and the Greater Yellowstone Ecosystem in North America. We measured individual-level movements relative to the environmental context, or movement expression, using the standardized metric Intensity of Use, reflecting both the directionality and extent of movements. We expected movement expression to be affected by resource (Normalized Difference Vegetation Index, NDVI) predictability and topography, but those factors to be superseded by human impact. Red deer and elk movement expression varied along a continuum, from highly segmented trajectories over relatively small areas (high intensity of use), to directed transitions through restricted corridors (low intensity of use). Human activity (Human Footprint Index, HFI) was the strongest driver of movement expression, with a steep increase in Intensity of Use as HFI increased, but only until a threshold was reached. After exceeding this level of impact, the Intensity of Use remained unchanged. These results indicate the overall sensitivity of Cervus movement expression to human activity and suggest a limitation of plastic responses under high human pressure, despite the species also occurring in human-dominated landscapes. Our work represents the first comparison of metric-based movement expression across widely distributed populations of a deer genus, contributing to the understanding and prediction of animals' responses to human activity.

Idaho, Montana, Wyoming↗
USGS2021

Beware of spatial autocorrelation when applying machine learning algorithms to borehole geophysical logs

Although many of the algorithms now considered to be machine learning algorithms (MLAs) have existed for nearly a century (e.g., Rosenblatt 1958 ), interest in MLAs has recently increased exponentially for solving data-driven problems across a variety of fields due to the expanded availability of large, complex datasets that may be difficult to interrogate using other methods, increases in computing power, and a growing library of easily implemented machine learning tools. While MLAs are often similar to statistical methods, there are key differences in the approach to problem solving. Namely, statistical methods are more concerned with generating informative models from “long” data (i.e., many more observations than explanatory variables), whereas MLAs are typically concerned with generating accurate predictions from “wide” data (i.e., a large number of variables with relatively fewer observations, Bzdok et al. 2018 ). In hydrogeologic studies, such wide datasets may be available from boreholes, where various types of geophysical, geochemical, and lithological information may exist. Borehole datasets are therefore a tempting target for MLAs to reveal hidden relations among gathered data and parameters of interest (e.g., contaminant concentration), and as a method of parameter reduction (e.g., reduce costs by collecting fewer datasets).

Groundwater↗
USGS2008

A bioenergetic model for zebrafish Danio rerio (Hamilton)

A bioenergetics model was developed from observed consumption, respiration and growth rates for zebrafish Danio rerio across a range (18-32?? C) of water temperatures, and evaluated with a 50 day laboratory trial at 28?? C. No significant bias in variable estimates was found during the validation trial; namely, predicted zebrafish mass generally agreed with observed mass. ?? 2008 The Authors.

Journal of Fish Biology↗
USGS2009

Phylogeny and phylogenetic classification of the antbirds, ovenbirds, woodcreepers, and allies (Aves: Passeriformes: Infraorder Furnariides)

The infraorder Furnariides is a diverse group of suboscine passerine birds comprising a substantial component of the Neotropical avifauna. The included species encompass a broad array of morphologies and behaviours, making them appealing for evolutionary studies, but the size of the group (ca. 600 species) has limited well-sampled higher-level phylogenetic studies. Using DNA sequence data from the nuclear RAG-1 and RAG-2 exons, we undertook a phylogenetic analysis of the Furnariides sampling 124 (more than 88%) of the genera. Basal relationships among family-level taxa differed depending on phylogenetic method, but all topologies had little nodal support, mirroring the results from earlier studies in which discerning relationships at the base of the radiation was also difficult. In contrast, branch support for family-rank taxa and for many relationships within those clades was generally high. Our results support the Melanopareidae and Grallariidae as distinct from the Rhinocryptidae and Formicariidae, respectively. Within the Furnariides our data contradict some recent phylogenetic hypotheses and suggest that further study is needed to resolve these discrepancies. Of the few genera represented by multiple species, several were not monophyletic, indicating that additional systematic work remains within furnariine families and must include dense taxon sampling. We use this study as a basis for proposing a new phylogenetic classification for the group and in the process erect new family-group names for clades having high branch support across methods. ?? 2009 The Willi Hennig Society.

Cladistics↗
USGS2012

Extension of the spatial autocorrelation (SPAC) method to mixed-component correlations of surface waves

Using ambient seismic noise for imaging subsurface structure dates back to the development of the spatial autocorrelation (SPAC) method in the 1950s. We present a theoretical analysis of the SPAC method for multicomponent recordings of surface waves to determine the complete 3 × 3 matrix of correlations between all pairs of three-component motions, called the correlation matrix. In the case of isotropic incidence, when either Rayleigh or Love waves arrive from all directions with equal power, the only non-zero off-diagonal terms in the matrix are the vertical–radial (ZR) and radial–vertical (RZ) correlations in the presence of Rayleigh waves. Such combinations were not considered in the development of the SPAC method. The method originally addressed the vertical–vertical (ZZ), RR and TT correlations, hence the name spatial autocorrelation. The theoretical expressions we derive for the ZR and RZ correlations offer additional ways to measure Rayleigh wave dispersion within the SPAC framework. Expanding on the results for isotropic incidence, we derive the complete correlation matrix in the case of generally anisotropic incidence. We show that the ZR and RZ correlations have advantageous properties in the presence of an out-of-plane directional wavefield compared to ZZ and RR correlations. We apply the results for mixed-component correlations to a data set from Akutan Volcano, Alaska and find consistent estimates of Rayleigh wave phase velocity from ZR compared to ZZ correlations. This work together with the recently discovered connections between the SPAC method and time-domain correlations of ambient noise provide further insights into the retrieval of surface wave Green’s functions from seismic noise.

Geophysical Journal International↗
USGS2006

Improved phase-ellipse method for in-situ geophone calibration

For amplitude and phase response calibration of moving-coil electromagnetic geophones two parameters are needed, namely, the geophone natural frequency, f 0 , and the geophone upper resonance frequency f u . The phase-ellipse method is commonly used for the in situ determination of these parameters. For a given signal-to-noise ratio, the precision of the measurement of f 0 and f u depends on the phase sensitivity, f(δφ/δf) For some commercial geophones f(δφ/δf) at f u can be an order of magnitude less than the sensitivity at f 0 . In this paper we present an improved phase-ellipse method with increased precision. Compared to measurements made with the existing phase-ellipse methods, our method shows a 6- and 3-fold improvement in the precision, respectively, on measurements of f 0 and f u on a commercial geophone.

Geophysical Prospecting↗
USGS2008

Estimation of the bottleneck size in Florida panthers

We have estimated the extent of genetic variation in museum (1890s) and contemporary (1980s) samples of Florida panthers Puma concolor coryi for both nuclear loci and mtDNA. The microsatellite heterozygosity in the contemporary sample was only 0.325 that in the museum samples although our sample size and number of loci are limited. Support for this estimate is provided by a sample of 84 microsatellite loci in contemporary Florida panthers and Idaho pumas Puma concolor hippolestes in which the contemporary Florida panther sample had only 0.442 the heterozygosity of Idaho pumas. The estimated diversities in mtDNA in the museum and contemporary samples were 0.600 and 0.000, respectively. Using a population genetics approach, we have estimated that to reduce either the microsatellite heterozygosity or the mtDNA diversity this much (in a period of c. 80years during the 20th century when the numbers were thought to be low) that a very small bottleneck size of c. 2 for several generations and a small effective population size in other generations is necessary. Using demographic data from Yellowstone pumas, we estimated the ratio of effective to census population size to be 0.315. Using this ratio, the census population size in the Florida panthers necessary to explain the loss of microsatellite variation was c .41 for the non-bottleneck generations and 6.2 for the two bottleneck generations. These low bottleneck population sizes and the concomitant reduced effectiveness of selection are probably responsible for the high frequency of several detrimental traits in Florida panthers, namely undescended testicles and poor sperm quality. The recent intensive monitoring both before and after the introduction of Texas pumas in 1995 will make the recovery and genetic restoration of Florida panthers a classic study of an endangered species. Our estimates of the bottleneck size responsible for the loss of genetic variation in the Florida panther completes an unknown aspect of this account. ?? 2008 The Authors. Journal compilation ?? 2008 The Zoological Society of London.

Animal Conservation↗