Fine-Scale Cartography of Human Impacts along French Mediterranean Coasts: A Relevant Map for the Management of Marine Ecosystems.

PubMed

Holon, Florian; Mouquet, Nicolas; Boissery, Pierre; Bouchoucha, Marc; Delaruelle, Gwenaelle; Tribot, Anne-Sophie; Deter, Julie

2015-01-01

Ecosystem services provided by oceans and seas support most human needs but are threatened by human activities. Despite existing maps illustrating human impacts on marine ecosystems, information remains either large-scale but rough and insufficient for stakeholders (1 km² grid, lack of data along the coast) or fine-scale but fragmentary and heterogeneous in methodology. The objectives of this study are to map and quantify the main pressures exerted on near-coast marine ecosystems, at a large spatial scale though in fine and relevant resolution for managers (one pixel = 20 x 20 m). It focuses on the French Mediterranean coast (1,700 km of coastline including Corsica) at a depth of 0 to 80 m. After completing and homogenizing data presently available under GIS on the bathymetry and anthropogenic pressures but also on the seabed nature and ecosystem vulnerability, we provide a fine modeling of the extent and impacts of 10 anthropogenic pressures on marine habitats. The considered pressures are man-made coastline, boat anchoring, aquaculture, urban effluents, industrial effluents, urbanization, agriculture, coastline erosion, coastal population and fishing. A 1:10 000 continuous habitat map is provided considering 11 habitat classes. The marine bottom is mostly covered by three habitats: infralittoral soft bottom, Posidonia oceanica meadows and circalittoral soft bottom. Around two thirds of the bottoms are found within medium and medium high cumulative impact categories. Seagrass meadows are the most impacted habitats. The most important pressures (in area and intensity) are urbanization, coastal population, coastal erosion and man-made coastline. We also identified areas in need of a special management interest. This work should contribute to prioritize environmental needs, as well as enhance the development of indicators for the assessment of the ecological status of coastal systems. It could also help better apply and coordinate management measures at a relevant scale for biodiversity conservation.

Toward an operational framework for fine-scale urban land-cover mapping in Wallonia using submeter remote sensing and ancillary vector data

NASA Astrophysics Data System (ADS)

Beaumont, Benjamin; Grippa, Tais; Lennert, Moritz; Vanhuysse, Sabine; Stephenne, Nathalie; Wolff, Eléonore

2017-07-01

Encouraged by the EU INSPIRE directive requirements and recommendations, the Walloon authorities, similar to other EU regional or national authorities, want to develop operational land-cover (LC) and land-use (LU) mapping methods using existing geodata. Urban planners and environmental monitoring stakeholders of Wallonia have to rely on outdated, mixed, and incomplete LC and LU information. The current reference map is 10-years old. The two object-based classification methods, i.e., a rule- and a classifier-based method, for detailed regional urban LC mapping are compared. The added value of using the different existing geospatial datasets in the process is assessed. This includes the comparison between satellite and aerial optical data in terms of mapping accuracies, visual quality of the map, costs, processing, data availability, and property rights. The combination of spectral, tridimensional, and vector data provides accuracy values close to 0.90 for mapping the LC into nine categories with a minimum mapping unit of 15 m2. Such a detailed LC map offers opportunities for fine-scale environmental and spatial planning activities. Still, the regional application poses challenges regarding automation, big data handling, and processing time, which are discussed.

Patterns of resting state connectivity in human primary visual cortical areas: a 7T fMRI study.

PubMed

Raemaekers, Mathijs; Schellekens, Wouter; van Wezel, Richard J A; Petridou, Natalia; Kristo, Gert; Ramsey, Nick F

2014-01-01

The nature and origin of fMRI resting state fluctuations and connectivity are still not fully known. More detailed knowledge on the relationship between resting state patterns and brain function may help to elucidate this matter. We therefore performed an in depth study of how resting state fluctuations map to the well known architecture of the visual system. We investigated resting state connectivity at both a fine and large scale within and across visual areas V1, V2 and V3 in ten human subjects using a 7Tesla scanner. We found evidence for several coexisting and overlapping connectivity structures at different spatial scales. At the fine-scale level we found enhanced connectivity between the same topographic locations in the fieldmaps of V1, V2 and V3, enhanced connectivity to the contralateral functional homologue, and to a lesser extent enhanced connectivity between iso-eccentric locations within the same visual area. However, by far the largest proportion of the resting state fluctuations occurred within large-scale bilateral networks. These large-scale networks mapped to some extent onto the architecture of the visual system and could thereby obscure fine-scale connectivity. In fact, most of the fine-scale connectivity only became apparent after the large-scale network fluctuations were filtered from the timeseries. We conclude that fMRI resting state fluctuations in the visual cortex may in fact be a composite signal of different overlapping sources. Isolating the different sources could enhance correlations between BOLD and electrophysiological correlates of resting state activity. © 2013 Elsevier Inc. All rights reserved.

Modeling dynamics of western juniper under climate change in a semiarid ecosystem

NASA Astrophysics Data System (ADS)

Shrestha, R.; Glenn, N. F.; Flores, A. N.

2013-12-01

Modeling future vegetation dynamics in response to climate change and disturbances such as fire relies heavily on model parameterization. Fine-scale field-based measurements can provide the necessary parameters for constraining models at a larger scale. But the time- and labor-intensive nature of field-based data collection leads to sparse sampling and significant spatial uncertainties in retrieved parameters. In this study we quantify the fine-scale carbon dynamics and uncertainty of juniper woodland in the Reynolds Creek Experimental Watershed (RCEW) in southern Idaho, which is a proposed critical zone observatory (CZO) site for soil carbon processes. We leverage field-measured vegetation data along with airborne lidar and timeseries Landsat imagery to initialize a state-and-transition model (VDDT) and a process-based fire-model (FlamMap) to examine the vegetation dynamics in response to stochastic fire events and climate change. We utilize recently developed and novel techniques to measure biomass and canopy characteristics of western juniper at the individual tree scale using terrestrial and airborne laser scanning techniques in RCEW. These fine-scale data are upscaled across the watershed for the VDDT and FlamMap models. The results will immediately improve our understanding of fine-scale dynamics and carbon stocks and fluxes of woody vegetation in a semi-arid ecosystem. Moreover, quantification of uncertainty will also provide a basis for generating ensembles of spatially-explicit alternative scenarios to guide future land management decisions in the region.

Developing and Delivering National-Scale Gridded Phenology Data Products

NASA Astrophysics Data System (ADS)

Marsh, L.; Crimmins, M.; Crimmins, T. M.; Gerst, K.; Rosemartin, A.; Switzer, J.; Weltzin, J. F.

2016-12-01

The USA National Phenology Network (USA-NPN; www.usanpn.org) is now producing and freely delivering daily maps and short-term forecasts of accumulated growing degree days and spring onset dates (based on the Extended Spring Indices) at fine spatial scale for the conterminous United States. These data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. Accumulated growing degree day (AGDD) maps were selected because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening and migration. The Extended Spring Indices (SI-x) are based on predictive climate models for lilac and honeysuckle leaf and bloom; they have been widely used to summarize changes in the timing of spring onset. The SI-x is used as a national indicator of climate change impacts by the US Global Change Research Program and the Environmental Protection Agency. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. To best serve various audiences, the AGDD and SI-x gridded maps are available in various formats through a range of access tools, including the USA-NPN online visualization tool as well as industry standards compliant web services. We plan to expand the suite of gridded map products offered by the USA-NPN to include predictive maps of phenological transitions for additional plant and animal species at fine spatial and temporal resolution in the near future. USA-NPN invites you to use freely available daily and short-term forecast maps of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States.

Satellite-Scale Snow Water Equivalent Assimilation into a High-Resolution Land Surface Model

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J.M.; Reichle, Rolf H.; Houser, Paul R.; Arsenault, Kristi R.; Verhoest, Niko E.C.; Paulwels, Valentijn R.N.

2009-01-01

An ensemble Kalman filter (EnKF) is used in a suite of synthetic experiments to assimilate coarse-scale (25 km) snow water equivalent (SWE) observations (typical of satellite retrievals) into fine-scale (1 km) model simulations. Coarse-scale observations are assimilated directly using an observation operator for mapping between the coarse and fine scales or, alternatively, after disaggregation (re-gridding) to the fine-scale model resolution prior to data assimilation. In either case observations are assimilated either simultaneously or independently for each location. Results indicate that assimilating disaggregated fine-scale observations independently (method 1D-F1) is less efficient than assimilating a collection of neighboring disaggregated observations (method 3D-Fm). Direct assimilation of coarse-scale observations is superior to a priori disaggregation. Independent assimilation of individual coarse-scale observations (method 3D-C1) can bring the overall mean analyzed field close to the truth, but does not necessarily improve estimates of the fine-scale structure. There is a clear benefit to simultaneously assimilating multiple coarse-scale observations (method 3D-Cm) even as the entire domain is observed, indicating that underlying spatial error correlations can be exploited to improve SWE estimates. Method 3D-Cm avoids artificial transitions at the coarse observation pixel boundaries and can reduce the RMSE by 60% when compared to the open loop in this study.

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

NASA Technical Reports Server (NTRS)

Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

2017-01-01

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meng, Ran; Wu, Jin; Schwager, Kathy L.

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE PAGES

Meng, Ran; Wu, Jin; Schwager, Kathy L.; ...

2017-01-21

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Fine-Scale Population Estimation by 3D Reconstruction of Urban Residential Buildings

PubMed Central

Wang, Shixin; Tian, Ye; Zhou, Yi; Liu, Wenliang; Lin, Chenxi

2016-01-01

Fine-scale population estimation is essential in emergency response and epidemiological applications as well as urban planning and management. However, representing populations in heterogeneous urban regions with a finer resolution is a challenge. This study aims to obtain fine-scale population distribution based on 3D reconstruction of urban residential buildings with morphological operations using optical high-resolution (HR) images from the Chinese No. 3 Resources Satellite (ZY-3). Specifically, the research area was first divided into three categories when dasymetric mapping was taken into consideration. The results demonstrate that the morphological building index (MBI) yielded better results than built-up presence index (PanTex) in building detection, and the morphological shadow index (MSI) outperformed color invariant indices (CIIT) in shadow extraction and height retrieval. Building extraction and height retrieval were then combined to reconstruct 3D models and to estimate population. Final results show that this approach is effective in fine-scale population estimation, with a mean relative error of 16.46% and an overall Relative Total Absolute Error (RATE) of 0.158. This study gives significant insights into fine-scale population estimation in complicated urban landscapes, when detailed 3D information of buildings is unavailable. PMID:27775670

Challenges of predicting the potential distribution of a slow-spreading invader: a habitat suitability map for an invasive riparian tree

USGS Publications Warehouse

Jarnevich, Catherine S.; Reynolds, Lindsay V.

2011-01-01

Understanding the potential spread of invasive species is essential for land managers to prevent their establishment and restore impacted habitat. Habitat suitability modeling provides a tool for researchers and managers to understand the potential extent of invasive species spread. Our goal was to use habitat suitability modeling to map potential habitat of the riparian plant invader, Russian olive (Elaeagnus angustifolia). Russian olive has invaded riparian habitat across North America and is continuing to expand its range. We compiled 11 disparate datasets for Russian olive presence locations (n = 1,051 points and 139 polygons) in the western US and used Maximum entropy (Maxent) modeling to develop two habitat suitability maps for Russian olive in the western United States: one with coarse-scale water data and one with fine-scale water data. Our models were able to accurately predict current suitable Russian olive habitat (Coarse model: training AUC = 0.938, test AUC = 0.907; Fine model: training AUC = 0.923, test AUC = 0.885). Distance to water was the most important predictor for Russian olive presence in our coarse-scale water model, but it was only the fifth most important variable in the fine-scale model, suggesting that when water bodies are considered on a fine scale, Russian olive does not necessarily rely on water. Our model predicted that Russian olive has suitable habitat further west from its current distribution, expanding into the west coast and central North America. Our methodology proves useful for identifying potential future areas of invasion. Model results may be influenced by locations of cultivated individuals and sampling bias. Further study is needed to examine the potential for Russian olive to invade beyond its current range. Habitat suitability modeling provides an essential tool for enhancing our understanding of invasive species spread.

A three-dimensional spatial mapping approach to quantify fine-scale heterogeneity among leaves within canopies1

PubMed Central

Wingfield, Jenna L.; Ruane, Lauren G.; Patterson, Joshua D.

2017-01-01

Premise of the study: The three-dimensional structure of tree canopies creates environmental heterogeneity, which can differentially influence the chemistry, morphology, physiology, and/or phenology of leaves. Previous studies that subdivide canopy leaves into broad categories (i.e., “upper/lower”) fail to capture the differences in microenvironments experienced by leaves throughout the three-dimensional space of a canopy. Methods: We use a three-dimensional spatial mapping approach based on spherical polar coordinates to examine the fine-scale spatial distributions of photosynthetically active radiation (PAR) and the concentration of ultraviolet (UV)-absorbing compounds (A300) among leaves within the canopies of black mangroves (Avicennia germinans). Results: Linear regressions revealed that interior leaves received less PAR and produced fewer UV-absorbing compounds than leaves on the exterior of the canopy. By allocating more UV-absorbing compounds to the leaves on the exterior of the canopy, black mangroves may be maximizing UV-protection while minimizing biosynthesis of UV-absorbing compounds. Discussion: Three-dimensional spatial mapping provides an inexpensive and portable method to detect fine-scale differences in environmental and biological traits within canopies. We used it to understand the relationship between PAR and A300, but the same approach can also be used to identify traits associated with the spatial distribution of herbivores, pollinators, and pathogens. PMID:29188145

Refined genetic maps reveal sexual dimorphism in human meiotic recombination at multiple scales

NASA Astrophysics Data System (ADS)

Bhérer, Claude; Campbell, Christopher L.; Auton, Adam

2017-04-01

In humans, males have lower recombination rates than females over the majority of the genome, but the opposite is usually true near the telomeres. These broad-scale differences have been known for decades, yet little is known about differences at the fine scale. By combining data sets, we have collected recombination events from over 100,000 meioses and have constructed sex-specific genetic maps at a previously unachievable resolution. Here we show that, although a substantial fraction of the genome shows some degree of sexually dimorphic recombination, the vast majority of hotspots are shared between the sexes, with only a small number of putative sex-specific hotspots. Wavelet analysis indicates that most of the differences can be attributed to the fine scale, and that variation in rate between the sexes can mostly be explained by differences in hotspot magnitude, rather than location. Nonetheless, known recombination-associated genomic features, such as THE1B repeat elements, show systematic differences between the sexes.

Postfire soil burn severity mapping with hyperspectral image unmixing

Treesearch

Peter R. Robichaud; Sarah A. Lewis; Denise Y. M. Laes; Andrew T. Hudak; Raymond F. Kokaly; Joseph A. Zamudio

2007-01-01

Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after...

MODELING SCALE-DEPENDENT LANDSCAPE PATTERN, DISPERSAL, AND CONNECTIVITY FROM THE PERSPECTIVE OF THE ORGANISM

EPA Science Inventory

Effects of fine- to broad-scale patterns of landscape heterogeneity on dispersal success were examined for organisms varying in life history traits. To systematically control spatial pattern, a landscape model was created by merging physiographically-based maps of simulated land...

Fine-scale mapping of a locus for severe bipolar mood disorder on chromosome 18p11.3 in the Costa Rican population

PubMed Central

McInnes, L. Alison; Service, Susan K.; Reus, Victor I.; Barnes, Glenn; Charlat, Olga; Jawahar, Satya; Lewitzky, Steve; Yang, Qing; Duong, Quyen; Spesny, Mitzi; Araya, Carmen; Araya, Xinia; Gallegos, Alvaro; Meza, Luis; Molina, Julio; Ramirez, Rolando; Mendez, Roxana; Silva, Sandra; Fournier, Eduardo; Batki, Steven L.; Mathews, Carol A.; Neylan, Thomas; Glatt, Charles E.; Escamilla, Michael A.; Luo, David; Gajiwala, Paresh; Song, Terry; Crook, Stephen; Nguyen, Jasmine B.; Roche, Erin; Meyer, Joanne M.; Leon, Pedro; Sandkuijl, Lodewijk A.; Freimer, Nelson B.; Chen, Hong

2001-01-01

We have searched for genes predisposing to bipolar disorder (BP) by studying individuals with the most extreme form of the affected phenotype, BP-I, ascertained from the genetically isolated population of the Central Valley of Costa Rica (CVCR). The results of a previous linkage analysis on two extended CVCR BP-I pedigrees, CR001 and CR004, and of linkage disequilibrium (LD) analyses of a CVCR population sample of BP-I patients implicated a candidate region on 18p11.3. We further investigated this region by creating a physical map and developing 4 new microsatellite and 26 single-nucleotide polymorphism markers for typing in the pedigree and population samples. We report the results of fine-scale association analyses in the population sample, as well as evaluation of haplotypes in pedigree CR001. Our results suggest a candidate region containing six genes but also highlight the complexities of LD mapping of common disorders. PMID:11572994

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India

PubMed Central

Sarkar, Mriganka Shekhar; Johnson, Jeyaraj A.; Sen, Subharanjan

2017-01-01

Background Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals’ ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger (Panthera tigris), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. Methods We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly’s selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D2 method and the Boyce index. Results There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Discussion Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve. PMID:29114438

Assessment of fine-scale resource selection and spatially explicit habitat suitability modelling for a re-introduced tiger (Panthera tigris) population in central India.

PubMed

Sarkar, Mriganka Shekhar; Krishnamurthy, Ramesh; Johnson, Jeyaraj A; Sen, Subharanjan; Saha, Goutam Kumar

2017-01-01

Large carnivores influence ecosystem functions at various scales. Thus, their local extinction is not only a species-specific conservation concern, but also reflects on the overall habitat quality and ecosystem value. Species-habitat relationships at fine scale reflect the individuals' ability to procure resources and negotiate intraspecific competition. Such fine scale habitat choices are more pronounced in large carnivores such as tiger ( Panthera tigris ), which exhibits competitive exclusion in habitat and mate selection strategies. Although landscape level policies and conservation strategies are increasingly promoted for tiger conservation, specific management interventions require knowledge of the habitat correlates at fine scale. We studied nine radio-collared individuals of a successfully reintroduced tiger population in Panna Tiger Reserve, central India, focussing on the species-habitat relationship at fine scales. With 16 eco-geographical variables, we performed Manly's selection ratio and K-select analyses to define population-level and individual-level variation in resource selection, respectively. We analysed the data obtained during the exploratory period of six tigers and during the settled period of eight tigers separately, and compared the consequent results. We further used the settled period characteristics to model and map habitat suitability based on the Mahalanobis D 2 method and the Boyce index. There was a clear difference in habitat selection by tigers between the exploratory and the settled period. During the exploratory period, tigers selected dense canopy and bamboo forests, but also spent time near villages and relocated village sites. However, settled tigers predominantly selected bamboo forests in complex terrain, riverine forests and teak-mixed forest, and totally avoided human settlements and agriculture areas. There were individual variations in habitat selection between exploratory and settled periods. Based on threshold limits of habitat selection by the Boyce Index, we established that 83% of core and 47% of buffer areas are now suitable habitats for tiger in this reserve. Tiger management often focuses on large-scale measures, but this study for the first time highlights the behaviour and fine-scale individual-specific habitat selection strategies. Such knowledge is vital for management of critical tiger habitats and specifically for the success of reintroduction programs. Our spatially explicit habitat suitability map provides a baseline for conservation planning and optimizing carrying capacity of the tiger population in this reserve.

Algebraic dynamic multilevel method for compositional flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Cusini, Matteo; Fryer, Barnaby; van Kruijsdijk, Cor; Hajibeygi, Hadi

2018-02-01

This paper presents the algebraic dynamic multilevel method (ADM) for compositional flow in three dimensional heterogeneous porous media in presence of capillary and gravitational effects. As a significant advancement compared to the ADM for immiscible flows (Cusini et al., 2016) [33], here, mass conservation equations are solved along with k-value based thermodynamic equilibrium equations using a fully-implicit (FIM) coupling strategy. Two different fine-scale compositional formulations are considered: (1) the natural variables and (2) the overall-compositions formulation. At each Newton's iteration the fine-scale FIM Jacobian system is mapped to a dynamically defined (in space and time) multilevel nested grid. The appropriate grid resolution is chosen based on the contrast of user-defined fluid properties and on the presence of specific features (e.g., well source terms). Consistent mapping between different resolutions is performed by the means of sequences of restriction and prolongation operators. While finite-volume restriction operators are employed to ensure mass conservation at all resolutions, various prolongation operators are considered. In particular, different interpolation strategies can be used for the different primary variables, and multiscale basis functions are chosen as pressure interpolators so that fine scale heterogeneities are accurately accounted for across different resolutions. Several numerical experiments are conducted to analyse the accuracy, efficiency and robustness of the method for both 2D and 3D domains. Results show that ADM provides accurate solutions by employing only a fraction of the number of grid-cells employed in fine-scale simulations. As such, it presents a promising approach for large-scale simulations of multiphase flow in heterogeneous reservoirs with complex non-linear fluid physics.

Monitoring forest dynamics with multi-scale and time series imagery.

PubMed

Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong

2016-05-01

To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.

Fine scale mapping of the structure and composition of the Elkhorn Slough (California, USA) tidal plume

NASA Astrophysics Data System (ADS)

Fischer, Andrew M.; Ryan, John P.; Rienecker, Erich V.

2017-01-01

Fine scale mapping of the structure and composition of a tidal ebb plume from a highly modified coastal lagoon (Elkhorn Slough, California, USA) was conducted by combining in situ, observational data sets from surface underway mapping, autonomous underwater vehicle (AUV) profiles, drifter tracking and the analysis of plume structure indices. The results reveal a 6-m-deep, jet-like, sediment laden plume extending one km offshore at low tide, which becomes entrained in the prevailing nearshore circulation. The plume that exits the slough is significantly different from the water that enters the slough. The rapidly evolving discharge plume is associated with elevated and highly correlated (r = 0.93) concentrations of dissolved organic matter and nitrate. While dissolved constituents remain in the shallow plume and are transported northward with the prevailing current, sediment may settle quickly through the water column and can be transported southwestward with the littoral currents. This study illustrates the applications of AUVs, when coupled with additional datasets, for generating higher resolution observational snapshots of dynamic and ephemeral tidal plumes. The results provide unique perspective on small-scale dynamics of an estuarine plume and its influence on coastal ecology.

Uncertainty Analysis in the Creation of a Fine-Resolution Leaf Area Index (LAI) Reference Map for Validation of Moderate Resolution LAI Products

EPA Science Inventory

The validation process for a moderate resolution leaf area index (LAI) product (i.e., MODIS) involves the creation of a high spatial resolution LAI reference map (Lai-RM), which when scaled to the moderate LAI resolution (i.e., >1 km) allows for comparison and analysis with this ...

Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data.

PubMed

Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R

2015-09-11

Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite's Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds.

Evaluating Sentinel-2 for Lakeshore Habitat Mapping Based on Airborne Hyperspectral Data

PubMed Central

Stratoulias, Dimitris; Balzter, Heiko; Sykioti, Olga; Zlinszky, András; Tóth, Viktor R.

2015-01-01

Monitoring of lakeshore ecosystems requires fine-scale information to account for the high biodiversity typically encountered in the land-water ecotone. Sentinel-2 is a satellite with high spatial and spectral resolution and improved revisiting frequency and is expected to have significant potential for habitat mapping and classification of complex lakeshore ecosystems. In this context, investigations of the capabilities of Sentinel-2 in regard to the spatial and spectral dimensions are needed to assess its potential and the quality of the expected output. This study presents the first simulation of the high spatial resolution (i.e., 10 m and 20 m) bands of Sentinel-2 for lakeshore mapping, based on the satellite’s Spectral Response Function and hyperspectral airborne data collected over Lake Balaton, Hungary in August 2010. A comparison of supervised classifications of the simulated products is presented and the information loss from spectral aggregation and spatial upscaling in the context of lakeshore vegetation classification is discussed. We conclude that Sentinel-2 imagery has a strong potential for monitoring fine-scale habitats, such as reed beds. PMID:26378538

Understanding Peripheral Bat Populations Using Maximum-Entropy Suitability Modeling

PubMed Central

Barnhart, Paul R.; Gillam, Erin H.

2016-01-01

Individuals along the periphery of a species distribution regularly encounter more challenging environmental and climatic conditions than conspecifics near the center of the distribution. Due to these potential constraints, individuals in peripheral margins are expected to change their habitat and behavioral characteristics. Managers typically rely on species distribution maps when developing adequate management practices. However, these range maps are often too simplistic and do not provide adequate information as to what fine-scale biotic and abiotic factors are driving a species occurrence. In the last decade, habitat suitability modelling has become widely used as a substitute for simplistic distribution mapping which allows regional managers the ability to fine-tune management resources. The objectives of this study were to use maximum-entropy modeling to produce habitat suitability models for seven species that have a peripheral margin intersecting the state of North Dakota, according to current IUCN distributions, and determine the vegetative and climatic characteristics driving these models. Mistnetting resulted in the documentation of five species outside the IUCN distribution in North Dakota, indicating that current range maps for North Dakota, and potentially the northern Great Plains, are in need of update. Maximum-entropy modeling showed that temperature and not precipitation were the variables most important for model production. This fine-scale result highlights the importance of habitat suitability modelling as this information cannot be extracted from distribution maps. Our results provide baseline information needed for future research about how and why individuals residing in the peripheral margins of a species’ distribution may show marked differences in habitat use as a result of urban expansion, habitat loss, and climate change compared to more centralized populations. PMID:27935936

Mapping Urban Tree Canopy Coverage and Structure using Data Fusion of High Resolution Satellite Imagery and Aerial Lidar

NASA Astrophysics Data System (ADS)

Elmes, A.; Rogan, J.; Williams, C. A.; Martin, D. G.; Ratick, S.; Nowak, D.

2015-12-01

Urban tree canopy (UTC) coverage is a critical component of sustainable urban areas. Trees provide a number of important ecosystem services, including air pollution mitigation, water runoff control, and aesthetic and cultural values. Critically, urban trees also act to mitigate the urban heat island (UHI) effect by shading impervious surfaces and via evaporative cooling. The cooling effect of urban trees can be seen locally, with individual trees reducing home HVAC costs, and at a citywide scale, reducing the extent and magnitude of an urban areas UHI. In order to accurately model the ecosystem services of a given urban forest, it is essential to map in detail the condition and composition of these trees at a fine scale, capturing individual tree crowns and their vertical structure. This paper presents methods for delineating UTC and measuring canopy structure at fine spatial resolution (<1m). These metrics are essential for modeling the HVAC benefits from UTC for individual homes, and for assessing the ecosystem services for entire urban areas. Such maps have previously been made using a variety of methods, typically relying on high resolution aerial or satellite imagery. This paper seeks to contribute to this growing body of methods, relying on a data fusion method to combine the information contained in high resolution WorldView-3 satellite imagery and aerial lidar data using an object-based image classification approach. The study area, Worcester, MA, has recently undergone a large-scale tree removal and reforestation program, following a pest eradication effort. Therefore, the urban canopy in this location provides a wide mix of tree age class and functional type, ideal for illustrating the effectiveness of the proposed methods. Early results show that the object-based classifier is indeed capable of identifying individual tree crowns, while continued research will focus on extracting crown structural characteristics using lidar-derived metrics. Ultimately, the resulting fine resolution UTC map will be compared with previously created UTC maps of the same area but for earlier dates, producing a canopy change map corresponding to the Worcester area tree removal and replanting effort.

The Recombination Landscape in Wild House Mice Inferred Using Population Genomic Data.

PubMed

Booker, Tom R; Ness, Rob W; Keightley, Peter D

2017-09-01

Characterizing variation in the rate of recombination across the genome is important for understanding several evolutionary processes. Previous analysis of the recombination landscape in laboratory mice has revealed that the different subspecies have different suites of recombination hotspots. It is unknown, however, whether hotspots identified in laboratory strains reflect the hotspot diversity of natural populations or whether broad-scale variation in the rate of recombination is conserved between subspecies. In this study, we constructed fine-scale recombination rate maps for a natural population of the Eastern house mouse, Mus musculus castaneus We performed simulations to assess the accuracy of recombination rate inference in the presence of phase errors, and we used a novel approach to quantify phase error. The spatial distribution of recombination events is strongly positively correlated between our castaneus map, and a map constructed using inbred lines derived predominantly from M. m. domesticus Recombination hotspots in wild castaneus show little overlap, however, with the locations of double-strand breaks in wild-derived house mouse strains. Finally, we also find that genetic diversity in M. m. castaneus is positively correlated with the rate of recombination, consistent with pervasive natural selection operating in the genome. Our study suggests that recombination rate variation is conserved at broad scales between house mouse subspecies, but it is not strongly conserved at fine scales. Copyright © 2017 by the Genetics Society of America.

Sea-Ice Feature Mapping using JERS-1 Imagery

NASA Technical Reports Server (NTRS)

Maslanik, James; Heinrichs, John

1994-01-01

JERS-1 SAR and OPS imagery are examined in combination with other data sets to investigate the utility of the JERS-1 sensors for mapping fine-scale sea ice conditions. Combining ERS-1 C band and JERS-1 L band SAR aids in discriminating multiyear and first-year ice. Analysis of OPS imagery for a field site in the Canadian Archipelago highlights the advantages of OPS's high spatial and spectral resolution for mapping ice structure, melt pond distribution, and surface albedo.

Large-Scale, High-Resolution Neurophysiological Maps Underlying fMRI of Macaque Temporal Lobe

PubMed Central

Papanastassiou, Alex M.; DiCarlo, James J.

2013-01-01

Maps obtained by functional magnetic resonance imaging (fMRI) are thought to reflect the underlying spatial layout of neural activity. However, previous studies have not been able to directly compare fMRI maps to high-resolution neurophysiological maps, particularly in higher level visual areas. Here, we used a novel stereo microfocal x-ray system to localize thousands of neural recordings across monkey inferior temporal cortex (IT), construct large-scale maps of neuronal object selectivity at subvoxel resolution, and compare those neurophysiology maps with fMRI maps from the same subjects. While neurophysiology maps contained reliable structure at the sub-millimeter scale, fMRI maps of object selectivity contained information at larger scales (>2.5 mm) and were only partly correlated with raw neurophysiology maps collected in the same subjects. However, spatial smoothing of neurophysiology maps more than doubled that correlation, while a variety of alternative transforms led to no significant improvement. Furthermore, raw spiking signals, once spatially smoothed, were as predictive of fMRI maps as local field potential signals. Thus, fMRI of the inferior temporal lobe reflects a spatially low-passed version of neurophysiology signals. These findings strongly validate the widespread use of fMRI for detecting large (>2.5 mm) neuronal domains of object selectivity but show that a complete understanding of even the most pure domains (e.g., faces vs nonface objects) requires investigation at fine scales that can currently only be obtained with invasive neurophysiological methods. PMID:24048850

Mapping the geographic distribution of canopy species communities in lowland Amazon rainforest with CAO-AToMS (Invited)

NASA Astrophysics Data System (ADS)

Feret, J.; Asner, G. P.

2013-12-01

Mapping regional canopy diversity will greatly advance our understanding as well as the conservation of tropical rainforests. Changes in species composition across space and time are particularly important to understand the influence of climate, human activity and environmental factors on these ecosystems, but to date such monitoring is extremely challenging and is facing a scale gap between small-scale, highly detailed field studies and large-scale, low-resolution satellite observations. Advances were recently made in the field of spectroscopic imagery for the estimation of canopy alpha-diversity, and an original approach based on the segmentation of the spectral space proved its ability to estimate Shannon diversity index with unprecedented accuracy. We adapted this method in order to estimate spectral dissimilarity across landscape as a proxy for changes in species composition. We applied this approach and mapped species composition over four sites located in lowland rainforest of Peruvian Amazon. This study was based on spectroscopic imagery acquired using the Carnegie Airborne Observatory (CAO) Airborne Taxonomic Mapping System (AToMS), operating a unique sensor combining the fine spectral and spatial resolution required for such task. We obtained accurate estimation of Bray-Curtis distance between pairs of plots, which is the most commonly used metric to estimate dissimilarity in species composition (n=497 pairs, r=0.63). The maps of species composition were then compared to topo-hydrographic properties. Our results indicated a strong shift in species composition and community diversity between floodplain and terra firme terrain conditions as well as a significantly higher diversity of species communities within Amazonian floodplains. These results pave the way for global mapping of tropical canopy diversity at fine geographic resolution.

Identification of fine scale and landscape scale drivers of urban aboveground carbon stocks using high-resolution modeling and mapping.

PubMed

Mitchell, Matthew G E; Johansen, Kasper; Maron, Martine; McAlpine, Clive A; Wu, Dan; Rhodes, Jonathan R

2018-05-01

Urban areas are sources of land use change and CO 2 emissions that contribute to global climate change. Despite this, assessments of urban vegetation carbon stocks often fail to identify important landscape-scale drivers of variation in urban carbon, especially the potential effects of landscape structure variables at different spatial scales. We combined field measurements with Light Detection And Ranging (LiDAR) data to build high-resolution models of woody plant aboveground carbon across the urban portion of Brisbane, Australia, and then identified landscape scale drivers of these carbon stocks. First, we used LiDAR data to quantify the extent and vertical structure of vegetation across the city at high resolution (5×5m). Next, we paired this data with aboveground carbon measurements at 219 sites to create boosted regression tree models and map aboveground carbon across the city. We then used these maps to determine how spatial variation in land cover/land use and landscape structure affects these carbon stocks. Foliage densities above 5m height, tree canopy height, and the presence of ground openings had the strongest relationships with aboveground carbon. Using these fine-scale relationships, we estimate that 2.2±0.4 TgC are stored aboveground in the urban portion of Brisbane, with mean densities of 32.6±5.8MgCha -1 calculated across the entire urban land area, and 110.9±19.7MgCha -1 calculated within treed areas. Predicted carbon densities within treed areas showed strong positive relationships with the proportion of surrounding tree cover and how clumped that tree cover was at both 1km 2 and 1ha resolutions. Our models predict that even dense urban areas with low tree cover can have high carbon densities at fine scales. We conclude that actions and policies aimed at increasing urban carbon should focus on those areas where urban tree cover is most fragmented. Copyright © 2017 Elsevier B.V. All rights reserved.

Surficial geologic map of the Heath-Northfield-Southwick-Hampden 24-quadrangle area in the Connecticut Valley region, west-central Massachusetts

USGS Publications Warehouse

Stone, Janet R.; DiGiacomo-Cohen, Mary L.

2010-01-01

The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in west-central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text, quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Norton-Manomet-Westport-Sconticut Neck 23-quadrangle area in southeast Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.; DiGiacomo-Cohen, Mary L.; Kincare, Kevin A.

2012-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 23 7.5-minute quadrangles (919 mi2 total) in southeastern Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

Surficial geologic map of the Mount Grace-Ashburnham-Monson-Webster 24-quadrangle area in central Massachusetts

USGS Publications Warehouse

Stone, Janet R.

2013-01-01

The surficial geologic map shows the distribution of nonlithified earth materials at land surface in an area of 24 7.5-minute quadrangles (1,238 mi2 total) in central Massachusetts. Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and as resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, and organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for assessing water resources, construction-aggregate resources, and earth-surface hazards, and for making land-use decisions. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This report includes explanatory text (PDF), quadrangle maps at 1:24,000 scale (PDF files), GIS data layers (ArcGIS shapefiles), metadata for the GIS layers, scanned topographic base maps (TIF), and a readme.txt file.

On the effects of scale for ecosystem services mapping

USGS Publications Warehouse

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

On the Effects of Scale for Ecosystem Services Mapping

PubMed Central

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability. PMID:25549256

On the effects of scale for ecosystem services mapping.

PubMed

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete.

PubMed

Karydas, Christos G; Sekuloska, Tijana; Silleos, Georgios N

2009-02-01

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.

Generation and emplacement of fine-grained ejecta in planetary impacts

USGS Publications Warehouse

Ghent, R.R.; Gupta, V.; Campbell, B.A.; Ferguson, S.A.; Brown, J.C.W.; Fergason, R.L.; Carter, L.M.

2010-01-01

We report here on a survey of distal fine-grained ejecta deposits on the Moon, Mars, and Venus. On all three planets, fine-grained ejecta form circular haloes that extend beyond the continuous ejecta and other types of distal deposits such as run-out lobes or ramparts. Using Earth-based radar images, we find that lunar fine-grained ejecta haloes represent meters-thick deposits with abrupt margins, and are depleted in rocks 1cm in diameter. Martian haloes show low nighttime thermal IR temperatures and thermal inertia, indicating the presence of fine particles estimated to range from ???10??m to 10mm. Using the large sample sizes afforded by global datasets for Venus and Mars, and a complete nearside radar map for the Moon, we establish statistically robust scaling relationships between crater radius R and fine-grained ejecta run-out r for all three planets. On the Moon, ???R-0.18 for craters 5-640km in diameter. For Venus, radar-dark haloes are larger than those on the Moon, but scale as ???R-0.49, consistent with ejecta entrainment in Venus' dense atmosphere. On Mars, fine-ejecta haloes are larger than lunar haloes for a given crater size, indicating entrainment of ejecta by the atmosphere or vaporized subsurface volatiles, but scale as R-0.13, similar to the ballistic lunar scaling. Ejecta suspension in vortices generated by passage of the ejecta curtain is predicted to result in ejecta run-out that scales with crater size as R1/2, and the wind speeds so generated may be insufficient to transport particles at the larger end of the calculated range. The observed scaling and morphology of the low-temperature haloes leads us rather to favor winds generated by early-stage vapor plume expansion as the emplacement mechanism for low-temperature halo materials. ?? 2010 Elsevier Inc.

Generating high temporal and spatial resolution thermal band imagery using robust sharpening approach

USDA-ARS?s Scientific Manuscript database

Thermal infrared band imagery provides key information for detecting wild fires, mapping land surface energy fluxes and evapotranspiration, monitoring urban heat fluxes and drought monitoring. Thermal infrared (TIR) imagery at fine resolution is required for field scale applications. However, therma...

AIR QUALITY MODELING AT COARSE-TO-FINE SCALES IN URBAN AREAS

EPA Science Inventory

Urban air toxics control strategies are moving towards a community based modeling approach, with an emphasis on assessing those areas that experience high air toxic concentration levels, the so-called "hot spots". This approach will require information that accurately maps and...

Multiplexed and scalable super-resolution imaging of three-dimensional protein localization in size-adjustable tissues.

PubMed

Ku, Taeyun; Swaney, Justin; Park, Jeong-Yoon; Albanese, Alexandre; Murray, Evan; Cho, Jae Hun; Park, Young-Gyun; Mangena, Vamsi; Chen, Jiapei; Chung, Kwanghun

2016-09-01

The biology of multicellular organisms is coordinated across multiple size scales, from the subnanoscale of molecules to the macroscale, tissue-wide interconnectivity of cell populations. Here we introduce a method for super-resolution imaging of the multiscale organization of intact tissues. The method, called magnified analysis of the proteome (MAP), linearly expands entire organs fourfold while preserving their overall architecture and three-dimensional proteome organization. MAP is based on the observation that preventing crosslinking within and between endogenous proteins during hydrogel-tissue hybridization allows for natural expansion upon protein denaturation and dissociation. The expanded tissue preserves its protein content, its fine subcellular details, and its organ-scale intercellular connectivity. We use off-the-shelf antibodies for multiple rounds of immunolabeling and imaging of a tissue's magnified proteome, and our experiments demonstrate a success rate of 82% (100/122 antibodies tested). We show that specimen size can be reversibly modulated to image both inter-regional connections and fine synaptic architectures in the mouse brain.

The roles of competition and habitat in the dynamics of populations and species distributions Ecology

Treesearch

Charles B. Yackulic; Janice Reid; James D. Nichols; James E. Hines; Raymond Davis; Eric Forsman

2014-01-01

The role of competition in structuring biotic communities at fine spatial scales is well known from detailed process-based studies. Our understanding of competition’s importance at broader scales is less resolved and mainly based on static species distribution maps. Here, we bridge this gap by examining the joint occupancy dynamics of an invading species (Barred Owl,...

Mobile laser scanning applied to the earth sciences

USGS Publications Warehouse

Brooks, Benjamin A.; Glennie, Craig; Hudnut, Kenneth W.; Ericksen, Todd; Hauser, Darren

2013-01-01

Lidar (light detection and ranging), a method by which the precise time of flight of emitted pulses of laser energy is measured and converted to distance for reflective targets, has helped scientists make topographic maps of Earth's surface at scales as fine as centimeters. These maps have allowed the discovery and analysis of myriad otherwise unstudied features, such as fault scarps, river channels, and even ancient ruins [Glennie et al., 2013b].

Fine-Scale Environmental Indicators of Public Health and Well-Being for Urban Communities

EPA Science Inventory

Urban ecosystem services contribute to public health and well-being by buffering natural and man-made hazards, and by promoting healthful lifestyles that include physical activity, social interaction, and engagement with nature. As part of the EnviroAtlas online mapping tool, EP...

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management.

PubMed

Malmstrom, Carolyn M; Butterfield, H Scott; Planck, Laura; Long, Christopher W; Eviner, Valerie T

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management

PubMed Central

Butterfield, H. Scott; Planck, Laura; Long, Christopher W.; Eviner, Valerie T.

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics. PMID:29016604

Predictive coarse-graining

NASA Astrophysics Data System (ADS)

Schöberl, Markus; Zabaras, Nicholas; Koutsourelakis, Phaedon-Stelios

2017-03-01

We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a probabilistic coarse-to-fine map. This corresponds to a directed probabilistic model where the coarse variables play the role of latent generators of the fine scale (all-atom) data. From an information-theoretic perspective, the framework proposed provides an improvement upon the relative entropy method [1] and is capable of quantifying the uncertainty due to the information loss that unavoidably takes place during the coarse-graining process. Furthermore, it can be readily extended to a fully Bayesian model where various sources of uncertainties are reflected in the posterior of the model parameters. The latter can be used to produce not only point estimates of fine-scale reconstructions or macroscopic observables, but more importantly, predictive posterior distributions on these quantities. Predictive posterior distributions reflect the confidence of the model as a function of the amount of data and the level of coarse-graining. The issues of model complexity and model selection are seamlessly addressed by employing a hierarchical prior that favors the discovery of sparse solutions, revealing the most prominent features in the coarse-grained model. A flexible and parallelizable Monte Carlo - Expectation-Maximization (MC-EM) scheme is proposed for carrying out inference and learning tasks. A comparative assessment of the proposed methodology is presented for a lattice spin system and the SPC/E water model.

Predictive coarse-graining

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schöberl, Markus, E-mail: m.schoeberl@tum.de; Zabaras, Nicholas; Department of Aerospace and Mechanical Engineering, University of Notre Dame, 365 Fitzpatrick Hall, Notre Dame, IN 46556

We propose a data-driven, coarse-graining formulation in the context of equilibrium statistical mechanics. In contrast to existing techniques which are based on a fine-to-coarse map, we adopt the opposite strategy by prescribing a probabilistic coarse-to-fine map. This corresponds to a directed probabilistic model where the coarse variables play the role of latent generators of the fine scale (all-atom) data. From an information-theoretic perspective, the framework proposed provides an improvement upon the relative entropy method and is capable of quantifying the uncertainty due to the information loss that unavoidably takes place during the coarse-graining process. Furthermore, it can be readily extendedmore » to a fully Bayesian model where various sources of uncertainties are reflected in the posterior of the model parameters. The latter can be used to produce not only point estimates of fine-scale reconstructions or macroscopic observables, but more importantly, predictive posterior distributions on these quantities. Predictive posterior distributions reflect the confidence of the model as a function of the amount of data and the level of coarse-graining. The issues of model complexity and model selection are seamlessly addressed by employing a hierarchical prior that favors the discovery of sparse solutions, revealing the most prominent features in the coarse-grained model. A flexible and parallelizable Monte Carlo – Expectation–Maximization (MC-EM) scheme is proposed for carrying out inference and learning tasks. A comparative assessment of the proposed methodology is presented for a lattice spin system and the SPC/E water model.« less

Identifying Where REDD+ Financially Out-Competes Oil Palm in Floodplain Landscapes Using a Fine-Scale Approach

PubMed Central

MacMillan, Douglas C.; Xofis, Panteleimon; Ancrenaz, Marc; Tzanopoulos, Joseph; Ong, Robert; Goossens, Benoit; Koh, Lian Pin; Del Valle, Christian; Peter, Lucy; Morel, Alexandra C.; Lackman, Isabelle; Chung, Robin; Kler, Harjinder; Ambu, Laurentius; Baya, William; Knight, Andrew T.

2016-01-01

Reducing Emissions from Deforestation and forest Degradation (REDD+) aims to avoid forest conversion to alternative land-uses through financial incentives. Oil-palm has high opportunity costs, which according to current literature questions the financial competitiveness of REDD+ in tropical lowlands. To understand this more, we undertook regional fine-scale and coarse-scale analyses (through carbon mapping and economic modelling) to assess the financial viability of REDD+ in safeguarding unprotected forest (30,173 ha) in the Lower Kinabatangan floodplain in Malaysian Borneo. Results estimate 4.7 million metric tons of carbon (MgC) in unprotected forest, with 64% allocated for oil-palm cultivations. Through fine-scale mapping and carbon accounting, we demonstrated that REDD+ can outcompete oil-palm in regions with low suitability, with low carbon prices and low carbon stock. In areas with medium oil-palm suitability, REDD+ could outcompete oil palm in areas with: very high carbon and lower carbon price; medium carbon price and average carbon stock; or, low carbon stock and high carbon price. Areas with high oil palm suitability, REDD+ could only outcompete with higher carbon price and higher carbon stock. In the coarse-scale model, oil-palm outcompeted REDD+ in all cases. For the fine-scale models at the landscape level, low carbon offset prices (US $3 MgCO2e) would enable REDD+ to outcompete oil-palm in 55% of the unprotected forests requiring US $27 million to secure these areas for 25 years. Higher carbon offset price (US $30 MgCO2e) would increase the competitiveness of REDD+ within the landscape but would still only capture between 69%-74% of the unprotected forest, requiring US $380–416 million in carbon financing. REDD+ has been identified as a strategy to mitigate climate change by many countries (including Malaysia). Although REDD+ in certain scenarios cannot outcompete oil palm, this research contributes to the global REDD+ debate by: highlighting REDD+ competitiveness in tropical floodplain landscapes; and, providing a robust approach for identifying and targeting limited REDD+ funds. PMID:27276218

Identifying Where REDD+ Financially Out-Competes Oil Palm in Floodplain Landscapes Using a Fine-Scale Approach.

PubMed

Abram, Nicola K; MacMillan, Douglas C; Xofis, Panteleimon; Ancrenaz, Marc; Tzanopoulos, Joseph; Ong, Robert; Goossens, Benoit; Koh, Lian Pin; Del Valle, Christian; Peter, Lucy; Morel, Alexandra C; Lackman, Isabelle; Chung, Robin; Kler, Harjinder; Ambu, Laurentius; Baya, William; Knight, Andrew T

2016-01-01

Reducing Emissions from Deforestation and forest Degradation (REDD+) aims to avoid forest conversion to alternative land-uses through financial incentives. Oil-palm has high opportunity costs, which according to current literature questions the financial competitiveness of REDD+ in tropical lowlands. To understand this more, we undertook regional fine-scale and coarse-scale analyses (through carbon mapping and economic modelling) to assess the financial viability of REDD+ in safeguarding unprotected forest (30,173 ha) in the Lower Kinabatangan floodplain in Malaysian Borneo. Results estimate 4.7 million metric tons of carbon (MgC) in unprotected forest, with 64% allocated for oil-palm cultivations. Through fine-scale mapping and carbon accounting, we demonstrated that REDD+ can outcompete oil-palm in regions with low suitability, with low carbon prices and low carbon stock. In areas with medium oil-palm suitability, REDD+ could outcompete oil palm in areas with: very high carbon and lower carbon price; medium carbon price and average carbon stock; or, low carbon stock and high carbon price. Areas with high oil palm suitability, REDD+ could only outcompete with higher carbon price and higher carbon stock. In the coarse-scale model, oil-palm outcompeted REDD+ in all cases. For the fine-scale models at the landscape level, low carbon offset prices (US $3 MgCO2e) would enable REDD+ to outcompete oil-palm in 55% of the unprotected forests requiring US $27 million to secure these areas for 25 years. Higher carbon offset price (US $30 MgCO2e) would increase the competitiveness of REDD+ within the landscape but would still only capture between 69%-74% of the unprotected forest, requiring US $380-416 million in carbon financing. REDD+ has been identified as a strategy to mitigate climate change by many countries (including Malaysia). Although REDD+ in certain scenarios cannot outcompete oil palm, this research contributes to the global REDD+ debate by: highlighting REDD+ competitiveness in tropical floodplain landscapes; and, providing a robust approach for identifying and targeting limited REDD+ funds.

Large-Scale SNP Discovery and Genotyping for Constructing a High-Density Genetic Map of Tea Plant Using Specific-Locus Amplified Fragment Sequencing (SLAF-seq)

PubMed Central

Ma, Chun-Lei; Jin, Ji-Qiang; Li, Chun-Fang; Wang, Rong-Kai; Zheng, Hong-Kun; Yao, Ming-Zhe; Chen, Liang

2015-01-01

Genetic maps are important tools in plant genomics and breeding. The present study reports the large-scale discovery of single nucleotide polymorphisms (SNPs) for genetic map construction in tea plant. We developed a total of 6,042 valid SNP markers using specific-locus amplified fragment sequencing (SLAF-seq), and subsequently mapped them into the previous framework map. The final map contained 6,448 molecular markers, distributing on fifteen linkage groups corresponding to the number of tea plant chromosomes. The total map length was 3,965 cM, with an average inter-locus distance of 1.0 cM. This map is the first SNP-based reference map of tea plant, as well as the most saturated one developed to date. The SNP markers and map resources generated in this study provide a wealth of genetic information that can serve as a foundation for downstream genetic analyses, such as the fine mapping of quantitative trait loci (QTL), map-based cloning, marker-assisted selection, and anchoring of scaffolds to facilitate the process of whole genome sequencing projects for tea plant. PMID:26035838

Modulation of habitat-based conservation plans by fishery opportunity costs: a New Caledonia case study using fine-scale catch data.

PubMed

Deas, Marilyn; Andréfouët, Serge; Léopold, Marc; Guillemot, Nicolas

2014-01-01

Numerous threats impact coral reefs and conservation actions are urgently needed. Fast production of marine habitat maps promotes the use of habitat-only conservation plans, where a given percentage of the area of each habitat is set as conservation objectives. However, marine reserves can impact access to fishing grounds and generate opportunity costs for fishers that need to be minimized. In New Caledonia (Southwest Pacific), we used fine-scale fishery catch maps to define nineteen opportunity costs layers (expressed as biomass catch loss) considering i) total catches, ii) target fish families, iii) local marine tenure, and iv) gear type. The expected lower impacts on fishery catch when using the different cost constraints were ranked according to effectiveness in decreasing the costs generated by the habitat-only scenarios. The exercise was done for two habitat maps with different thematic richness. In most cases, habitat conservation objectives remained achievable, but effectiveness varied widely between scenarios and between habitat maps. The results provide practical guidelines for coral reef conservation and management. Habitat-only scenarios can be used to initiate conservation projects with stakeholders but the costs induced by such scenarios can be lowered by up to 50-60% when detailed exhaustive fishery data are used. When using partial data, the gain would be only in the 15-25% range. The best compromises are achieved when using local data.

Rooting strategies in a subtropical savanna: a landscape-scale three-dimensional assessment.

PubMed

Zhou, Yong; Boutton, Thomas W; Wu, X Ben; Wright, Cynthia L; Dion, Anais L

2018-04-01

In resource-limited savannas, the distribution and abundance of fine roots play an important role in acquiring essential resources and structuring vegetation patterns and dynamics. However, little is known regarding the three-dimensional distribution of fine roots in savanna ecosystems at the landscape scale. We quantified spatial patterns of fine root density to a depth of 1.2 m in a subtropical savanna landscape using spatially specific sampling. Kriged maps revealed that fine root density was highest at the centers of woody patches, decreased towards the canopy edges, and reached lowest values within the grassland matrix throughout the entire soil profile. Lacunarity analyses indicated that spatial heterogeneities of fine root density decreased continuously to a depth of 50 cm and then increased in deeper portions of the soil profile across this landscape. This vertical pattern might be related to inherent differences in root distribution between trees/shrubs and herbaceous species, and the presence/absence of an argillic horizon across this landscape. The greater density of fine roots beneath woody patches in both upper and lower portions of the soil profile suggests an ability to acquire disproportionately more resources than herbaceous species, which may facilitate the development and persistence of woody patches across this landscape.

A Modeling Approach to Global Land Surface Monitoring with Low Resolution Satellite Imaging

NASA Technical Reports Server (NTRS)

Hlavka, Christine A.; Dungan, Jennifer; Livingston, Gerry P.; Gore, Warren J. (Technical Monitor)

1998-01-01

The effects of changing land use/land cover on global climate and ecosystems due to greenhouse gas emissions and changing energy and nutrient exchange rates are being addressed by federal programs such as NASA's Mission to Planet Earth (MTPE) and by international efforts such as the International Geosphere-Biosphere Program (IGBP). The quantification of these effects depends on accurate estimates of the global extent of critical land cover types such as fire scars in tropical savannas and ponds in Arctic tundra. To address the requirement for accurate areal estimates, methods for producing regional to global maps with satellite imagery are being developed. The only practical way to produce maps over large regions of the globe is with data of coarse spatial resolution, such as Advanced Very High Resolution Radiometer (AVHRR) weather satellite imagery at 1.1 km resolution or European Remote-Sensing Satellite (ERS) radar imagery at 100 m resolution. The accuracy of pixel counts as areal estimates is in doubt, especially for highly fragmented cover types such as fire scars and ponds. Efforts to improve areal estimates from coarse resolution maps have involved regression of apparent area from coarse data versus that from fine resolution in sample areas, but it has proven difficult to acquire sufficient fine scale data to develop the regression. A method for computing accurate estimates from coarse resolution maps using little or no fine data is therefore needed.

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

PubMed

Mahajan, Anubha; Wessel, Jennifer; Willems, Sara M; Zhao, Wei; Robertson, Neil R; Chu, Audrey Y; Gan, Wei; Kitajima, Hidetoshi; Taliun, Daniel; Rayner, N William; Guo, Xiuqing; Lu, Yingchang; Li, Man; Jensen, Richard A; Hu, Yao; Huo, Shaofeng; Lohman, Kurt K; Zhang, Weihua; Cook, James P; Prins, Bram Peter; Flannick, Jason; Grarup, Niels; Trubetskoy, Vassily Vladimirovich; Kravic, Jasmina; Kim, Young Jin; Rybin, Denis V; Yaghootkar, Hanieh; Müller-Nurasyid, Martina; Meidtner, Karina; Li-Gao, Ruifang; Varga, Tibor V; Marten, Jonathan; Li, Jin; Smith, Albert Vernon; An, Ping; Ligthart, Symen; Gustafsson, Stefan; Malerba, Giovanni; Demirkan, Ayse; Tajes, Juan Fernandez; Steinthorsdottir, Valgerdur; Wuttke, Matthias; Lecoeur, Cécile; Preuss, Michael; Bielak, Lawrence F; Graff, Marielisa; Highland, Heather M; Justice, Anne E; Liu, Dajiang J; Marouli, Eirini; Peloso, Gina Marie; Warren, Helen R; Afaq, Saima; Afzal, Shoaib; Ahlqvist, Emma; Almgren, Peter; Amin, Najaf; Bang, Lia B; Bertoni, Alain G; Bombieri, Cristina; Bork-Jensen, Jette; Brandslund, Ivan; Brody, Jennifer A; Burtt, Noël P; Canouil, Mickaël; Chen, Yii-Der Ida; Cho, Yoon Shin; Christensen, Cramer; Eastwood, Sophie V; Eckardt, Kai-Uwe; Fischer, Krista; Gambaro, Giovanni; Giedraitis, Vilmantas; Grove, Megan L; de Haan, Hugoline G; Hackinger, Sophie; Hai, Yang; Han, Sohee; Tybjærg-Hansen, Anne; Hivert, Marie-France; Isomaa, Bo; Jäger, Susanne; Jørgensen, Marit E; Jørgensen, Torben; Käräjämäki, Annemari; Kim, Bong-Jo; Kim, Sung Soo; Koistinen, Heikki A; Kovacs, Peter; Kriebel, Jennifer; Kronenberg, Florian; Läll, Kristi; Lange, Leslie A; Lee, Jung-Jin; Lehne, Benjamin; Li, Huaixing; Lin, Keng-Hung; Linneberg, Allan; Liu, Ching-Ti; Liu, Jun; Loh, Marie; Mägi, Reedik; Mamakou, Vasiliki; McKean-Cowdin, Roberta; Nadkarni, Girish; Neville, Matt; Nielsen, Sune F; Ntalla, Ioanna; Peyser, Patricia A; Rathmann, Wolfgang; Rice, Kenneth; Rich, Stephen S; Rode, Line; Rolandsson, Olov; Schönherr, Sebastian; Selvin, Elizabeth; Small, Kerrin S; Stančáková, Alena; Surendran, Praveen; Taylor, Kent D; Teslovich, Tanya M; Thorand, Barbara; Thorleifsson, Gudmar; Tin, Adrienne; Tönjes, Anke; Varbo, Anette; Witte, Daniel R; Wood, Andrew R; Yajnik, Pranav; Yao, Jie; Yengo, Loïc; Young, Robin; Amouyel, Philippe; Boeing, Heiner; Boerwinkle, Eric; Bottinger, Erwin P; Chowdhury, Rajiv; Collins, Francis S; Dedoussis, George; Dehghan, Abbas; Deloukas, Panos; Ferrario, Marco M; Ferrières, Jean; Florez, Jose C; Frossard, Philippe; Gudnason, Vilmundur; Harris, Tamara B; Heckbert, Susan R; Howson, Joanna M M; Ingelsson, Martin; Kathiresan, Sekar; Kee, Frank; Kuusisto, Johanna; Langenberg, Claudia; Launer, Lenore J; Lindgren, Cecilia M; Männistö, Satu; Meitinger, Thomas; Melander, Olle; Mohlke, Karen L; Moitry, Marie; Morris, Andrew D; Murray, Alison D; de Mutsert, Renée; Orho-Melander, Marju; Owen, Katharine R; Perola, Markus; Peters, Annette; Province, Michael A; Rasheed, Asif; Ridker, Paul M; Rivadineira, Fernando; Rosendaal, Frits R; Rosengren, Anders H; Salomaa, Veikko; Sheu, Wayne H-H; Sladek, Rob; Smith, Blair H; Strauch, Konstantin; Uitterlinden, André G; Varma, Rohit; Willer, Cristen J; Blüher, Matthias; Butterworth, Adam S; Chambers, John Campbell; Chasman, Daniel I; Danesh, John; van Duijn, Cornelia; Dupuis, Josée; Franco, Oscar H; Franks, Paul W; Froguel, Philippe; Grallert, Harald; Groop, Leif; Han, Bok-Ghee; Hansen, Torben; Hattersley, Andrew T; Hayward, Caroline; Ingelsson, Erik; Kardia, Sharon L R; Karpe, Fredrik; Kooner, Jaspal Singh; Köttgen, Anna; Kuulasmaa, Kari; Laakso, Markku; Lin, Xu; Lind, Lars; Liu, Yongmei; Loos, Ruth J F; Marchini, Jonathan; Metspalu, Andres; Mook-Kanamori, Dennis; Nordestgaard, Børge G; Palmer, Colin N A; Pankow, James S; Pedersen, Oluf; Psaty, Bruce M; Rauramaa, Rainer; Sattar, Naveed; Schulze, Matthias B; Soranzo, Nicole; Spector, Timothy D; Stefansson, Kari; Stumvoll, Michael; Thorsteinsdottir, Unnur; Tuomi, Tiinamaija; Tuomilehto, Jaakko; Wareham, Nicholas J; Wilson, James G; Zeggini, Eleftheria; Scott, Robert A; Barroso, Inês; Frayling, Timothy M; Goodarzi, Mark O; Meigs, James B; Boehnke, Michael; Saleheen, Danish; Morris, Andrew P; Rotter, Jerome I; McCarthy, Mark I

2018-04-01

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10 -7 ); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.

Mediterranean maquis fuel model development and mapping to support fire modeling

NASA Astrophysics Data System (ADS)

Bacciu, V.; Arca, B.; Pellizzaro, G.; Salis, M.; Ventura, A.; Spano, D.; Duce, P.

2009-04-01

Fuel load data and fuel model maps represent a critical issue for fire spread and behaviour modeling. The availability of accurate input data at different spatial and temporal scales can allow detailed analysis and predictions of fire hazard and fire effects across a landscape. Fuel model data are used in spatially explicit fire growth models to attain fire behaviour information for fuel management in prescribed fires, fire management applications, firefighters training, smoke emissions, etc. However, fuel type characteristics are difficult to be parameterized due to their complexity and variability: live and dead materials with different size contribute in different ways to the fire spread and behaviour. In the last decades, a strong help was provided by the use of remote sensing imagery at high spatial and spectral resolution. Such techniques are able to capture fine scale fuel distributions for accurate fire growth projections. Several attempts carried out in Europe were devoted to fuel classification and map characterization. In Italy, fuel load estimation and fuel model definition are still critical issues to be addressed due to the lack of detailed information. In this perspective, the aim of the present work was to propose an integrated approach based on field data collection, fuel model development and fuel model mapping to provide fuel models for the Mediterranean maquis associations. Field data needed for the development of fuel models were collected using destructive and non destructive measurements in experimental plots located in Northern Sardinia (Italy). Statistical tests were used to identify the main fuel types that were classified into four custom fuel models. Subsequently, a supervised classification by the Maximum Likelihood algorithm was applied on IKONOS images to identify and map the different types of maquis vegetation. The correspondent fuel model was then associated to each vegetation type to obtain the fuel model map. The results show the potential of this approach in achieving a reasonable accuracy in fuel model development and mapping; fine scale fuel model maps can be potentially helpful to obtain realistic predictions of fire behaviour and fire effects.

Association genetics in Pinus taeda L. I. wood property traits

Treesearch

Santiago C. Gonzalez-Martinez; Nicholas C. Wheeler; Elhan Ersoz; C. Dana Nelson; David B. Neale

2007-01-01

Genetic association is a powerful method for dissecting complex adaptive traits due to (i) fine-scale mapping resulting from historical recombination, (ii) wide coverage of phenotypic and genotypic variation within a single experiment, and (iii) the simultaneous discovery of loci and alleles. In this article, genetic association among single nucleotide polymorphisms (...

Multi-scale interactions between local hydrography, seabed topography, and community assembly on cold-water coral reefs

NASA Astrophysics Data System (ADS)

Henry, L.-A.; Moreno Navas, J.; Roberts, J. M.

2013-04-01

We investigated how interactions between hydrography, topography and species ecology influence the assembly of species and functional traits across multiple spatial scales of a cold-water coral reef seascape. In a novel approach for these ecosystems, we used a spatially resolved complex three-dimensional flow model of hydrography to help explain assembly patterns. Forward-selection of distance-based Moran's eigenvector mapping (dbMEM) variables identified two submodels of spatial scales at which communities change: broad-scale (across reef) and fine-scale (within reef). Variance partitioning identified bathymetric and hydrographic gradients important in creating broad-scale assembly of species and traits. In contrast, fine-scale assembly was related more to processes that created spatially autocorrelated patches of fauna, such as philopatric recruitment in sessile fauna, and social interactions and food supply in scavenging detritivores and mobile predators. Our study shows how habitat modification of reef connectivity and hydrography by bottom fishing and renewable energy installations could alter the structure and function of an entire cold-water coral reef seascape.

A Spatial Framework to Map Heat Health Risks at Multiple Scales.

PubMed

Ho, Hung Chak; Knudby, Anders; Huang, Wei

2015-12-18

In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G(i) index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G(i) index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level.

Mapping of the Resistance of a Superconducting Transition Edge Sensor as a Function of Temperature, Current, and Applied Magnetic Field

NASA Technical Reports Server (NTRS)

Zhang, Shou; Eckart, Megan E.; Jaeckel, Felix; Kripps, Kari L.; McCammon, Dan; Zhou, Yu; Morgan, Kelsey M.

2017-01-01

We have measured the resistance R (T, I, B(sub ext) of a superconducting transition edge sensor over the entire transition region on a fine scale, producing a four-dimensional map of the resistance surface. The dimensionless temperature and current sensitivities (alpha equivalence partial derivative log R/partial derivative log T|(sub I) and beta equivalence partial derivative log R/partial derivative log I|(sub T) of the TES resistance have been determined at each point. alpha and beta are closely related to the sensor performance, but show a great deal of complex, large amplitude fine structure over large portions of the surface that is sensitive to the applied magnetic field. We discuss the relation of this structure to the presence of Josephson weak link fringes.

Documenting Uncertainty and Error in Gridded Growing Degree Day and Spring Onset Maps Generated by the USA National Phenology Network

NASA Astrophysics Data System (ADS)

Crimmins, T. M.; Switzer, J.; Rosemartin, A.; Marsh, L.; Gerst, K.; Crimmins, M.; Weltzin, J. F.

2016-12-01

Since 2016 the USA National Phenology Network (USA-NPN; www.usanpn.org) has produced and delivered daily maps and short-term forecasts of accumulated growing degree days and spring onset dates at fine spatial scale for the conterminous United States. Because accumulated temperature is a strong driver of phenological transitions in plants and animals, including leaf-out, flowering, fruit ripening, and migration, these data products have utility for a wide range of natural resource planning and management applications, including scheduling invasive species and pest detection and control activities, determining planting dates, anticipating allergy outbreaks and planning agricultural harvest dates. The USA-NPN is a national-scale program that supports scientific advancement and decision-making by collecting, storing, and sharing phenology data and information. We will be expanding the suite of gridded map products offered by the USA-NPN to include predictive species-specific maps of phenological transitions in plants and animals at fine spatial and temporal resolution in the future. Data products, such as the gridded maps currently produced by the USA-NPN, inherently contain uncertainty and error arising from multiple sources, including error propagated forward from underlying climate data and from the models implemented. As providing high-quality, vetted data in a transparent way is central to the USA-NPN, we aim to identify and report the sources and magnitude of uncertainty and error in gridded maps and forecast products. At present, we compare our real-time gridded products to independent, trustworthy data sources, such as the Climate Reference Network, on a daily basis and report Mean Absolute Error and bias through an interactive online dashboard.

The recombination landscape around forensic STRs: Accurate measurement of genetic distances between syntenic STR pairs using HapMap high density SNP data.

PubMed

Phillips, C; Ballard, D; Gill, P; Court, D Syndercombe; Carracedo, A; Lareu, M V

2012-05-01

Family studies can be used to measure the genetic distance between same-chromosome (syntenic) STRs in order to detect physical linkage or linkage disequilibrium. However, family studies are expensive and time consuming, in many cases uninformative, and lack a reliable means to infer the phase of the diplotypes obtained. HapMap provides a more comprehensive and fine-scale estimation of recombination rates using high density multi-point SNP data (average inter-SNP distance: 900 nucleotides). Data at this fine scale detects sub-kilobase genetic distances across the whole recombining human genome. We have used the most recent HapMap SNP data release 22 to measure and compare genetic distances, and by inference fine-scale recombination rates, between 29 syntenic STR pairs identified from 39 validated STRs currently available for forensic use. The 39 STRs comprise 23 core loci: SE33, Penta D & E, 13 CODIS and 7 non-CODIS European Standard Set STRs, plus supplementary STRs in the recently released Promega CS-7™ and Qiagen Investigator HDplex™ kits. Also included were D9S1120, a marker we developed for forensic use unique to chromosome 9, and the novel D6S1043 component STR of SinoFiler™ (Applied Biosystems). The data collated provides reliable estimates of recombination rates between each STR pair, that can then be placed into haplotype frequency calculators for short pedigrees with multiple meiotic inputs and which just requires the addition of allele frequencies. This allows all current STR sets or their combinations to be used in supplemented paternity analyses without the need for further adjustment for physical linkage. The detailed analysis of recombination rates made for autosomal forensic STRs was extended to the more than 50 X chromosome STRs established or in development for complex kinship analyses. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Modulation of Habitat-Based Conservation Plans by Fishery Opportunity Costs: A New Caledonia Case Study Using Fine-Scale Catch Data

PubMed Central

Deas, Marilyn; Andréfouët, Serge; Léopold, Marc; Guillemot, Nicolas

2014-01-01

Numerous threats impact coral reefs and conservation actions are urgently needed. Fast production of marine habitat maps promotes the use of habitat-only conservation plans, where a given percentage of the area of each habitat is set as conservation objectives. However, marine reserves can impact access to fishing grounds and generate opportunity costs for fishers that need to be minimized. In New Caledonia (Southwest Pacific), we used fine-scale fishery catch maps to define nineteen opportunity costs layers (expressed as biomass catch loss) considering i) total catches, ii) target fish families, iii) local marine tenure, and iv) gear type. The expected lower impacts on fishery catch when using the different cost constraints were ranked according to effectiveness in decreasing the costs generated by the habitat-only scenarios. The exercise was done for two habitat maps with different thematic richness. In most cases, habitat conservation objectives remained achievable, but effectiveness varied widely between scenarios and between habitat maps. The results provide practical guidelines for coral reef conservation and management. Habitat-only scenarios can be used to initiate conservation projects with stakeholders but the costs induced by such scenarios can be lowered by up to 50–60% when detailed exhaustive fishery data are used. When using partial data, the gain would be only in the 15–25% range. The best compromises are achieved when using local data. PMID:24835216

Postfire soil burn severity mapping with hyperspectral image unmixing

USGS Publications Warehouse

Robichaud, P.R.; Lewis, S.A.; Laes, D.Y.M.; Hudak, A.T.; Kokaly, R.F.; Zamudio, J.A.

2007-01-01

Burn severity is mapped after wildfires to evaluate immediate and long-term fire effects on the landscape. Remotely sensed hyperspectral imagery has the potential to provide important information about fine-scale ground cover components that are indicative of burn severity after large wildland fires. Airborne hyperspectral imagery and ground data were collected after the 2002 Hayman Fire in Colorado to assess the application of high resolution imagery for burn severity mapping and to compare it to standard burn severity mapping methods. Mixture Tuned Matched Filtering (MTMF), a partial spectral unmixing algorithm, was used to identify the spectral abundance of ash, soil, and scorched and green vegetation in the burned area. The overall performance of the MTMF for predicting the ground cover components was satisfactory (r2 = 0.21 to 0.48) based on a comparison to fractional ash, soil, and vegetation cover measured on ground validation plots. The relationship between Landsat-derived differenced Normalized Burn Ratio (dNBR) values and the ground data was also evaluated (r2 = 0.20 to 0.58) and found to be comparable to the MTMF. However, the quantitative information provided by the fine-scale hyperspectral imagery makes it possible to more accurately assess the effects of the fire on the soil surface by identifying discrete ground cover characteristics. These surface effects, especially soil and ash cover and the lack of any remaining vegetative cover, directly relate to potential postfire watershed response processes. ?? 2006 Elsevier Inc. All rights reserved.

Demonstrating the Uneven Importance of Fine-Scale Forest Structure on Snow Distributions using High Resolution Modeling

NASA Astrophysics Data System (ADS)

Broxton, P. D.; Harpold, A. A.; van Leeuwen, W.; Biederman, J. A.

2016-12-01

Quantifying the amount of snow in forested mountainous environments, as well as how it may change due to warming and forest disturbance, is critical given its importance for water supply and ecosystem health. Forest canopies affect snow accumulation and ablation in ways that are difficult to observe and model. Furthermore, fine-scale forest structure can accentuate or diminish the effects of forest-snow interactions. Despite decades of research demonstrating the importance of fine-scale forest structure (e.g. canopy edges and gaps) on snow, we still lack a comprehensive understanding of where and when forest structure has the largest impact on snowpack mass and energy budgets. Here, we use a hyper-resolution (1 meter spatial resolution) mass and energy balance snow model called the Snow Physics and Laser Mapping (SnowPALM) model along with LIDAR-derived forest structure to determine where spatial variability of fine-scale forest structure has the largest influence on large scale mass and energy budgets. SnowPALM was set up and calibrated at sites representing diverse climates in New Mexico, Arizona, and California. Then, we compared simulations at different model resolutions (i.e. 1, 10, and 100 m) to elucidate the effects of including versus not including information about fine scale canopy structure. These experiments were repeated for different prescribed topographies (i.e. flat, 30% slope north, and south-facing) at each site. Higher resolution simulations had more snow at lower canopy cover, with the opposite being true at high canopy cover. Furthermore, there is considerable scatter, indicating that different canopy arrangements can lead to different amounts of snow, even when the overall canopy coverage is the same. This modeling is contributing to the development of a high resolution machine learning algorithm called the Snow Water Artificial Network (SWANN) model to generate predictions of snow distributions over much larger domains, which has implications for improving land surface models that do not currently resolve or parameterize fine-scale canopy structure. In addition, these findings have implications for understanding the potential of different forest management strategies (i.e. thinning) based on local topography and climate to maximize the amount and retention of snow.

Hope for the Forests? Habitat Resiliency Illustrated in the Face of Climate Change Using Fine-Scale Modeling

NASA Astrophysics Data System (ADS)

Flint, L. E.; Flint, A. L.; Weiss, S. B.; Micheli, E. R.

2010-12-01

In the face of rapid climate change, fine-scale predictions of landscape change are of extreme interest to land managers that endeavor to develop long term adaptive strategies for maintaining biodiversity and ecosystem services. Global climate model (GCM) outputs, which generally focus on estimated increases in air temperature, are increasingly applied to species habitat distribution models. For sensitive species subject to climate change, habitat models predict significant migration (either northward or towards higher elevations), or complete extinction. Current studies typically rely on large spatial scale GCM projections (> 10 km) of changes in precipitation and air temperature: at this scale, these models necessarily neglect subtleties of topographic shading, geomorphic expression of the landscape, and fine-scale differences in soil properties - data that is readily available at meaningful local scales. Recent advances in modeling take advantage of available soils, geology, and topographic data to construct watershed-scale scenarios using GCM inputs and result in improved correlations of vegetation distribution with temperature. For this study, future climate projections were downscaled to 270-m and applied to a physically-based hydrologic model to calculate future changes in recharge, runoff, and climatic water deficit (CWD) for basins draining into the northern San Francisco Bay. CWD was analyzed for mapped vegetation types to evaluate the range of CWD for historic time periods in comparison to future time periods. For several forest communities (including blue oak woodlands, montane hardwoods, douglas-fir, and coast redwood) existing landscape area exhibiting suitable CWD diminishes by up 80 percent in the next century, with a trend towards increased CWD throughout the region. However, no forest community loses all suitable habitat, with islands of potential habitat primarily remaining on north facing slopes and deeper soils. Creation of new suitable habitat is also predicted throughout the region. Results have direct application to management issues of habitat connectivity, forest land protection and acquisition, and active management solutions such as transplanting or assisted migration. Although this analysis considers only one driver of forest habitat distribution, consideration of hydrologic derivatives at a fine scale explains current forest community distributions and provides a far more informed perspective on potential future forest distributions. Results demonstrate the utility of fine-scale modeling and provide landscape managers and conservation agencies valuable management tools in fine-scale future forest scenarios and a framework for evaluating forest resiliency in a changing climate.

Fine-scale mapping of the FGFR2 breast cancer risk locus: putative functional variants differentially bind FOXA1 and E2F1.

PubMed

Meyer, Kerstin B; O'Reilly, Martin; Michailidou, Kyriaki; Carlebur, Saskia; Edwards, Stacey L; French, Juliet D; Prathalingham, Radhika; Dennis, Joe; Bolla, Manjeet K; Wang, Qin; de Santiago, Ines; Hopper, John L; Tsimiklis, Helen; Apicella, Carmel; Southey, Melissa C; Schmidt, Marjanka K; Broeks, Annegien; Van 't Veer, Laura J; Hogervorst, Frans B; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Fasching, Peter A; Lux, Michael P; Ekici, Arif B; Beckmann, Matthias W; Peto, Julian; Dos Santos Silva, Isabel; Fletcher, Olivia; Johnson, Nichola; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Marme, Federick; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Guénel, Pascal; Truong, Thérèse; Laurent-Puig, Pierre; Menegaux, Florence; Bojesen, Stig E; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Milne, Roger L; Zamora, M Pilar; Arias, Jose I; Benitez, Javier; Neuhausen, Susan; Anton-Culver, Hoda; Ziogas, Argyrios; Dur, Christina C; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Meindl, Alfons; Schmutzler, Rita K; Engel, Christoph; Ditsch, Nina; Brauch, Hiltrud; Brüning, Thomas; Ko, Yon-Dschun; Nevanlinna, Heli; Muranen, Taru A; Aittomäki, Kristiina; Blomqvist, Carl; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Yatabe, Yasushi; Dörk, Thilo; Helbig, Sonja; Bogdanova, Natalia V; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Chenevix-Trench, Georgia; Wu, Anna H; Tseng, Chiu-Chen; Van Den Berg, David; Stram, Daniel O; Lambrechts, Diether; Thienpont, Bernard; Christiaens, Marie-Rose; Smeets, Ann; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Radice, Paolo; Peterlongo, Paolo; Bonanni, Bernardo; Bernard, Loris; Couch, Fergus J; Olson, Janet E; Wang, Xianshu; Purrington, Kristen; Giles, Graham G; Severi, Gianluca; Baglietto, Laura; McLean, Catriona; Haiman, Christopher A; Henderson, Brian E; Schumacher, Fredrick; Le Marchand, Loic; Simard, Jacques; Goldberg, Mark S; Labrèche, France; Dumont, Martine; Teo, Soo-Hwang; Yip, Cheng-Har; Phuah, Sze-Yee; Kristensen, Vessela; Grenaker Alnæs, Grethe; Børresen-Dale, Anne-Lise; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; Andrulis, Irene L; Knight, Julia A; Glendon, Gord; Tchatchou, Sandrine; Devilee, Peter; Tollenaar, Robert A E M; Seynaeve, Caroline M; García-Closas, Montserrat; Figueroa, Jonine; Chanock, Stephen J; Lissowska, Jolanta; Czene, Kamila; Darabi, Hartef; Eriksson, Kimael; Hooning, Maartje J; Martens, John W M; van den Ouweland, Ans M W; van Deurzen, Carolien H M; Hall, Per; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Reed, Malcolm W R; Blot, William; Signorello, Lisa B; Cai, Qiuyin; Pharoah, Paul D P; Ghoussaini, Maya; Harrington, Patricia; Tyrer, Jonathan; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K; Noh, Dong-Young; Hartman, Mikael; Hui, Miao; Lim, Wei-Yen; Buhari, Shaik A; Hamann, Ute; Försti, Asta; Rüdiger, Thomas; Ulmer, Hans-Ulrich; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Vachon, Celine; Slager, Susan; Fostira, Florentia; Pilarski, Robert; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Hou, Ming-Feng; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J; Ponder, Bruce A J; Dunning, Alison M; Easton, Douglas F

2013-12-05

The 10q26 locus in the second intron of FGFR2 is the locus most strongly associated with estrogen-receptor-positive breast cancer in genome-wide association studies. We conducted fine-scale mapping in case-control studies genotyped with a custom chip (iCOGS), comprising 41 studies (n = 89,050) of European ancestry, 9 Asian ancestry studies (n = 13,983), and 2 African ancestry studies (n = 2,028) from the Breast Cancer Association Consortium. We identified three statistically independent risk signals within the locus. Within risk signals 1 and 3, genetic analysis identified five and two variants, respectively, highly correlated with the most strongly associated SNPs. By using a combination of genetic fine mapping, data on DNase hypersensitivity, and electrophoretic mobility shift assays to study protein-DNA binding, we identified rs35054928, rs2981578, and rs45631563 as putative functional SNPs. Chromatin immunoprecipitation showed that FOXA1 preferentially bound to the risk-associated allele (C) of rs2981578 and was able to recruit ERα to this site in an allele-specific manner, whereas E2F1 preferentially bound the risk variant of rs35054928. The risk alleles were preferentially found in open chromatin and bound by Ser5 phosphorylated RNA polymerase II, suggesting that the risk alleles are associated with changes in transcription. Chromatin conformation capture demonstrated that the risk region was able to interact with the promoter of FGFR2, the likely target gene of this risk region. A role for FOXA1 in mediating breast cancer susceptibility at this locus is consistent with the finding that the FGFR2 risk locus primarily predisposes to estrogen-receptor-positive disease. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Fine-Scale Mapping of the FGFR2 Breast Cancer Risk Locus: Putative Functional Variants Differentially Bind FOXA1 and E2F1

PubMed Central

Meyer, Kerstin B.; O’Reilly, Martin; Michailidou, Kyriaki; Carlebur, Saskia; Edwards, Stacey L.; French, Juliet D.; Prathalingham, Radhika; Dennis, Joe; Bolla, Manjeet K.; Wang, Qin; de Santiago, Ines; Hopper, John L.; Tsimiklis, Helen; Apicella, Carmel; Southey, Melissa C.; Schmidt, Marjanka K.; Broeks, Annegien; Van ’t Veer, Laura J.; Hogervorst, Frans B.; Muir, Kenneth; Lophatananon, Artitaya; Stewart-Brown, Sarah; Siriwanarangsan, Pornthep; Fasching, Peter A.; Lux, Michael P.; Ekici, Arif B.; Beckmann, Matthias W.; Peto, Julian; dos Santos Silva, Isabel; Fletcher, Olivia; Johnson, Nichola; Sawyer, Elinor J.; Tomlinson, Ian; Kerin, Michael J.; Miller, Nicola; Marme, Federick; Schneeweiss, Andreas; Sohn, Christof; Burwinkel, Barbara; Guénel, Pascal; Truong, Thérèse; Laurent-Puig, Pierre; Menegaux, Florence; Bojesen, Stig E.; Nordestgaard, Børge G.; Nielsen, Sune F.; Flyger, Henrik; Milne, Roger L.; Zamora, M. Pilar; Arias, Jose I.; Benitez, Javier; Neuhausen, Susan; Anton-Culver, Hoda; Ziogas, Argyrios; Dur, Christina C.; Brenner, Hermann; Müller, Heiko; Arndt, Volker; Stegmaier, Christa; Meindl, Alfons; Schmutzler, Rita K.; Engel, Christoph; Ditsch, Nina; Brauch, Hiltrud; Brüning, Thomas; Ko, Yon-Dschun; Nevanlinna, Heli; Muranen, Taru A.; Aittomäki, Kristiina; Blomqvist, Carl; Matsuo, Keitaro; Ito, Hidemi; Iwata, Hiroji; Yatabe, Yasushi; Dörk, Thilo; Helbig, Sonja; Bogdanova, Natalia V.; Lindblom, Annika; Margolin, Sara; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M.; Chenevix-Trench, Georgia; Wu, Anna H.; Tseng, Chiu-chen; Van Den Berg, David; Stram, Daniel O.; Lambrechts, Diether; Thienpont, Bernard; Christiaens, Marie-Rose; Smeets, Ann; Chang-Claude, Jenny; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Radice, Paolo; Peterlongo, Paolo; Bonanni, Bernardo; Bernard, Loris; Couch, Fergus J.; Olson, Janet E.; Wang, Xianshu; Purrington, Kristen; Giles, Graham G.; Severi, Gianluca; Baglietto, Laura; McLean, Catriona; Haiman, Christopher A.; Henderson, Brian E.; Schumacher, Fredrick; Le Marchand, Loic; Simard, Jacques; Goldberg, Mark S.; Labrèche, France; Dumont, Martine; Teo, Soo-Hwang; Yip, Cheng-Har; Phuah, Sze-Yee; Kristensen, Vessela; Grenaker Alnæs, Grethe; Børresen-Dale, Anne-Lise; Zheng, Wei; Deming-Halverson, Sandra; Shrubsole, Martha; Long, Jirong; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Kauppila, Saila; Andrulis, Irene L.; Knight, Julia A.; Glendon, Gord; Tchatchou, Sandrine; Devilee, Peter; Tollenaar, Robert A.E.M.; Seynaeve, Caroline M.; García-Closas, Montserrat; Figueroa, Jonine; Chanock, Stephen J.; Lissowska, Jolanta; Czene, Kamila; Darabi, Hartef; Eriksson, Kimael; Hooning, Maartje J.; Martens, John W.M.; van den Ouweland, Ans M.W.; van Deurzen, Carolien H.M.; Hall, Per; Li, Jingmei; Liu, Jianjun; Humphreys, Keith; Shu, Xiao-Ou; Lu, Wei; Gao, Yu-Tang; Cai, Hui; Cox, Angela; Reed, Malcolm W.R.; Blot, William; Signorello, Lisa B.; Cai, Qiuyin; Pharoah, Paul D.P.; Ghoussaini, Maya; Harrington, Patricia; Tyrer, Jonathan; Kang, Daehee; Choi, Ji-Yeob; Park, Sue K.; Noh, Dong-Young; Hartman, Mikael; Hui, Miao; Lim, Wei-Yen; Buhari, Shaik A.; Hamann, Ute; Försti, Asta; Rüdiger, Thomas; Ulmer, Hans-Ulrich; Jakubowska, Anna; Lubinski, Jan; Jaworska, Katarzyna; Durda, Katarzyna; Sangrajrang, Suleeporn; Gaborieau, Valerie; Brennan, Paul; McKay, James; Vachon, Celine; Slager, Susan; Fostira, Florentia; Pilarski, Robert; Shen, Chen-Yang; Hsiung, Chia-Ni; Wu, Pei-Ei; Hou, Ming-Feng; Swerdlow, Anthony; Ashworth, Alan; Orr, Nick; Schoemaker, Minouk J.; Ponder, Bruce A.J.; Dunning, Alison M.; Easton, Douglas F.

2013-01-01

The 10q26 locus in the second intron of FGFR2 is the locus most strongly associated with estrogen-receptor-positive breast cancer in genome-wide association studies. We conducted fine-scale mapping in case-control studies genotyped with a custom chip (iCOGS), comprising 41 studies (n = 89,050) of European ancestry, 9 Asian ancestry studies (n = 13,983), and 2 African ancestry studies (n = 2,028) from the Breast Cancer Association Consortium. We identified three statistically independent risk signals within the locus. Within risk signals 1 and 3, genetic analysis identified five and two variants, respectively, highly correlated with the most strongly associated SNPs. By using a combination of genetic fine mapping, data on DNase hypersensitivity, and electrophoretic mobility shift assays to study protein-DNA binding, we identified rs35054928, rs2981578, and rs45631563 as putative functional SNPs. Chromatin immunoprecipitation showed that FOXA1 preferentially bound to the risk-associated allele (C) of rs2981578 and was able to recruit ERα to this site in an allele-specific manner, whereas E2F1 preferentially bound the risk variant of rs35054928. The risk alleles were preferentially found in open chromatin and bound by Ser5 phosphorylated RNA polymerase II, suggesting that the risk alleles are associated with changes in transcription. Chromatin conformation capture demonstrated that the risk region was able to interact with the promoter of FGFR2, the likely target gene of this risk region. A role for FOXA1 in mediating breast cancer susceptibility at this locus is consistent with the finding that the FGFR2 risk locus primarily predisposes to estrogen-receptor-positive disease. PMID:24290378

Mapping epibenthic assemblages and their relations to sedimentary features in shallow-water, high-energy environments

NASA Astrophysics Data System (ADS)

Sisson, John D.; Shimeta, Jeff; Zimmer, Cheryl Ann; Traykovski, Peter

2002-03-01

Knowledge of spatial relationships among benthic biota and sedimentary features in shallow-water (<30 m) high-energy environments has been severely limited by sampling technology. We describe and report tests of a SCUBA-diving mapping method specifically for this region. Underwater acoustic location is used to achieve meter-scale resolution over kilometer-scale regions of the sea floor. A triad of acoustic transponders is bottom-mounted at known positions, 300-500 m apart. Transported by underwater personal vehicles, SCUBA-divers map the bed using hand-held acoustic receivers that record ranges to the transponders. The mean error of acoustic fixes was 2.4±1.2 m in a 0.5 km×1.0 km test area. Dense assemblages of epibenthic animals were mapped relative to sediment texture and bedforms off the exposed south coast of Martha's Vineyard Island, Massachusetts, USA. Surveys one month apart within a 0.6 km×0.6 km area (8-12 m depth) revealed 100-m-scale patches of the tube worm Spiophanes bombyx (⩽30,000 m -2) in fine sand and of the sand dollar Echinarachnius parma (⩽55 m -2) in coarse sand. Raised mud patches that, together with fine sand, occurred in two shore-perpendicular belts are likely exposed, ancient marsh deposits. Depth gradients of sand-ripple geometry indicated that ripples in deeper areas were not in equilibrium with wave conditions monitored during surveys; i.e., they were relict ripples. Thus, sand dollars in some areas may have had >1 month to rework surficial sands since their transformation by physical processes. Linear regressions of ripple characteristics against sand dollar or tube worm densities were not significant, although such relationships would be highly dependent on temporal scale. The survey method described here can be used at more frequent intervals to explore such interactions between epibenthic animals and sediment-transport dynamics.

Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.

Mapping paddy rice distribution using multi-temporal Landsat imagery in the Sanjiang Plain, northeast China

PubMed Central

XIAO, Xiangming; DONG, Jinwei; QIN, Yuanwei; WANG, Zongming

2016-01-01

Information of paddy rice distribution is essential for food production and methane emission calculation. Phenology-based algorithms have been utilized in the mapping of paddy rice fields by identifying the unique flooding and seedling transplanting phases using multi-temporal moderate resolution (500 m to 1 km) images. In this study, we developed simple algorithms to identify paddy rice at a fine resolution at the regional scale using multi-temporal Landsat imagery. Sixteen Landsat images from 2010–2012 were used to generate the 30 m paddy rice map in the Sanjiang Plain, northeast China—one of the major paddy rice cultivation regions in China. Three vegetation indices, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Land Surface Water Index (LSWI), were used to identify rice fields during the flooding/transplanting and ripening phases. The user and producer accuracies of paddy rice on the resultant Landsat-based paddy rice map were 90% and 94%, respectively. The Landsat-based paddy rice map was an improvement over the paddy rice layer on the National Land Cover Dataset, which was generated through visual interpretation and digitalization on the fine-resolution images. The agricultural census data substantially underreported paddy rice area, raising serious concern about its use for studies on food security. PMID:27695637

Rare variation facilitates inferences of fine-scale population structure in humans.

PubMed

O'Connor, Timothy D; Fu, Wenqing; Mychaleckyj, Josyf C; Logsdon, Benjamin; Auer, Paul; Carlson, Christopher S; Leal, Suzanne M; Smith, Joshua D; Rieder, Mark J; Bamshad, Michael J; Nickerson, Deborah A; Akey, Joshua M

2015-03-01

Understanding the genetic structure of human populations has important implications for the design and interpretation of disease mapping studies and reconstructing human evolutionary history. To date, inferences of human population structure have primarily been made with common variants. However, recent large-scale resequencing studies have shown an abundance of rare variation in humans, which may be particularly useful for making inferences of fine-scale population structure. To this end, we used an information theory framework and extensive coalescent simulations to rigorously quantify the informativeness of rare and common variation to detect signatures of fine-scale population structure. We show that rare variation affords unique insights into patterns of recent population structure. Furthermore, to empirically assess our theoretical findings, we analyzed high-coverage exome sequences in 6,515 European and African American individuals. As predicted, rare variants are more informative than common polymorphisms in revealing a distinct cluster of European-American individuals, and subsequent analyses demonstrate that these individuals are likely of Ashkenazi Jewish ancestry. Our results provide new insights into the population structure using rare variation, which will be an important factor to account for in rare variant association studies. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mehrez, Loujaine; Ghanem, Roger; Aitharaju, Venkat

Design of non-crimp fabric (NCF) composites entails major challenges pertaining to (1) the complex fine-scale morphology of the constituents, (2) the manufacturing-produced inconsistency of this morphology spatially, and thus (3) the ability to build reliable, robust, and efficient computational surrogate models to account for this complex nature. Traditional approaches to construct computational surrogate models have been to average over the fluctuations of the material properties at different scale lengths. This fails to account for the fine-scale features and fluctuations in morphology, material properties of the constituents, as well as fine-scale phenomena such as damage and cracks. In addition, it failsmore » to accurately predict the scatter in macroscopic properties, which is vital to the design process and behavior prediction. In this work, funded in part by the Department of Energy, we present an approach for addressing these challenges by relying on polynomial chaos representations of both input parameters and material properties at different scales. Moreover, we emphasize the efficiency and robustness of integrating the polynomial chaos expansion with multiscale tools to perform multiscale assimilation, characterization, propagation, and prediction, all of which are necessary to construct the data-driven surrogate models required to design under the uncertainty of composites. These data-driven constructions provide an accurate map from parameters (and their uncertainties) at all scales and the system-level behavior relevant for design. While this perspective is quite general and applicable to all multiscale systems, NCF composites present a particular hierarchy of scales that permits the efficient implementation of these concepts.« less

Infrared-Bright Interacting Galaxies

NASA Astrophysics Data System (ADS)

Rojas Ruiz, Sofia; Murphy, Eric Joseph; Armus, Lee; Smith, John-David; Bradford, Charles Matt; Stierwalt, Sabrina

2018-01-01

We present the mid-infrared spectral mapping of eight LIRG-class interacting galaxies: NGC 6670, NGC 7592, IIZw 96, IIIZw 35, Arp 302, Arp 236, Arp 238, Arp 299. The properties of galaxy mergers, which are bright and can be studied at high resolutions at low-z, provide local analogs for sources that may be important contributors to the Far Infrared Background (FIRB.) In order to study star formation and the physical conditions in the gas and dust in our sample galaxies, we used the Spitzer InfraRed Spectrograph (IRS) to map the galaxies over the 5-35 μm window to trace the PAH, molecular hydrogen, and atomic fine structure line emission on scales of 1.4 – 5.3 kpc. Here we present the reduction for low and high-resolution data, and preliminary results in the analysis of fine structure line ratios and dust features in the two nuclei and interacting regions from one of our sample galaxies, NGC 6670.

What can the occult do for you?

NASA Astrophysics Data System (ADS)

Holwerda, B. W.; Keel, W. C.

2017-03-01

Interstellar dust is still a dominant uncertainty in Astronomy, limiting precision in e.g., cosmological distance estimates and models of how light is re-processed within a galaxy. When a foreground galaxy serendipitously overlaps a more distant one, the latter backlights the dusty structures in the nearer foreground galaxy. Such an overlapping or occulting galaxy pair can be used to measure the distribution of dust in the closest galaxy with great accuracy. The STARSMOG program uses Hubble to map the distribution of dust in foreground galaxies in fine (<100 pc) detail. Integral Field Unit (IFU) observations will map the effective extinction curve, disentangling the role of fine-scale geometry and grain composition on the path of light through a galaxy. The overlapping galaxy technique promises to deliver a clear understanding of the dust in galaxies: geometry, a probability function of dimming as a function of galaxy mass and radius, and its dependence on wavelength.

Seafloor Tectonic Fabric from Satellite Altimetry

NASA Astrophysics Data System (ADS)

Smith, Walter H. F.

Ocean floor structures with horizontal scales of 10 to a few hundred kilometers and vertical scales of 100 m or more generate sea surface gravity anomalies observable with satellite altimetry. Prior to 1990, altimeter data resolved only tectonic lineaments, some seamounts, and some aspects of mid-ocean ridge structure. New altimeter data available since mid-1995 resolve 10-km--scale structures over nearly all the world's oceans. These data are the basis of new global bathymetric maps and have been interpreted as exhibiting complexities in the sea floor spreading process including ridge jumps, propagating rifts, and variations in magma supply. This chapter reviews the satellite altimetry technique and its resolution of tectonic structures, gives examples of intriguing tectonic phenomena, and shows that structures as small as abyssal hills are partially resolved. A new result obtained here is that the amplitude of the fine-scale (10--80 km) roughness of old ocean floor is spreading-rate dependent in the same that it is at mid-ocean ridges, suggesting that fine-scale tectonic fabric is generated nearly exclusively by ridge-axis processes.

Multimap formation in visual cortex

PubMed Central

Jain, Rishabh; Millin, Rachel; Mel, Bartlett W.

2015-01-01

An extrastriate visual area such as V2 or V4 contains neurons selective for a multitude of complex shapes, all sharing a common topographic organization. Simultaneously developing multiple interdigitated maps—hereafter a “multimap”—is challenging in that neurons must compete to generate a diversity of response types locally, while cooperating with their dispersed same-type neighbors to achieve uniform visual field coverage for their response type at all orientations, scales, etc. Previously proposed map development schemes have relied on smooth spatial interaction functions to establish both topography and columnar organization, but by locally homogenizing cells' response properties, local smoothing mechanisms effectively rule out multimap formation. We found in computer simulations that the key requirements for multimap development are that neurons are enabled for plasticity only within highly active regions of cortex designated “learning eligibility regions” (LERs), but within an LER, each cell's learning rate is determined only by its activity level with no dependence on location. We show that a hybrid developmental rule that combines spatial and activity-dependent learning criteria in this way successfully produces multimaps when the input stream contains multiple distinct feature types, or in the degenerate case of a single feature type, produces a V1-like map with “salt-and-pepper” structure. Our results support the hypothesis that cortical maps containing a fine mixture of different response types, whether in monkey extrastriate cortex, mouse V1 or elsewhere in the cortex, rather than signaling a breakdown of map formation mechanisms at the fine scale, are a product of a generic cortical developmental scheme designed to map cells with a diversity of response properties across a shared topographic space. PMID:26641946

Generation, Validation, and Application of Abundance Map Reference Data for Spectral Unmixing

NASA Astrophysics Data System (ADS)

Williams, McKay D.

Reference data ("ground truth") maps traditionally have been used to assess the accuracy of imaging spectrometer classification algorithms. However, these reference data can be prohibitively expensive to produce, often do not include sub-pixel abundance estimates necessary to assess spectral unmixing algorithms, and lack published validation reports. Our research proposes methodologies to efficiently generate, validate, and apply abundance map reference data (AMRD) to airborne remote sensing scenes. We generated scene-wide AMRD for three different remote sensing scenes using our remotely sensed reference data (RSRD) technique, which spatially aggregates unmixing results from fine scale imagery (e.g., 1-m Ground Sample Distance (GSD)) to co-located coarse scale imagery (e.g., 10-m GSD or larger). We validated the accuracy of this methodology by estimating AMRD in 51 randomly-selected 10 m x 10 m plots, using seven independent methods and observers, including field surveys by two observers, imagery analysis by two observers, and RSRD using three algorithms. Results indicated statistically-significant differences between all versions of AMRD, suggesting that all forms of reference data need to be validated. Given these significant differences between the independent versions of AMRD, we proposed that the mean of all (MOA) versions of reference data for each plot and class were most likely to represent true abundances. We then compared each version of AMRD to MOA. Best case accuracy was achieved by a version of imagery analysis, which had a mean coverage area error of 2.0%, with a standard deviation of 5.6%. One of the RSRD algorithms was nearly as accurate, achieving a mean error of 3.0%, with a standard deviation of 6.3%, showing the potential of RSRD-based AMRD generation. Application of validated AMRD to specific coarse scale imagery involved three main parts: 1) spatial alignment of coarse and fine scale imagery, 2) aggregation of fine scale abundances to produce coarse scale imagery-specific AMRD, and 3) demonstration of comparisons between coarse scale unmixing abundances and AMRD. Spatial alignment was performed using our scene-wide spectral comparison (SWSC) algorithm, which aligned imagery with accuracy approaching the distance of a single fine scale pixel. We compared simple rectangular aggregation to coarse sensor point spread function (PSF) aggregation, and found that the PSF approach returned lower error, but that rectangular aggregation more accurately estimated true abundances at ground level. We demonstrated various metrics for comparing unmixing results to AMRD, including mean absolute error (MAE) and linear regression (LR). We additionally introduced reference data mean adjusted MAE (MA-MAE), and reference data confidence interval adjusted MAE (CIA-MAE), which account for known error in the reference data itself. MA-MAE analysis indicated that fully constrained linear unmixing of coarse scale imagery across all three scenes returned an error of 10.83% per class and pixel, with regression analysis yielding a slope = 0.85, intercept = 0.04, and R2 = 0.81. Our reference data research has demonstrated a viable methodology to efficiently generate, validate, and apply AMRD to specific examples of airborne remote sensing imagery, thereby enabling direct quantitative assessment of spectral unmixing performance.

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

PubMed

Horikoshi, Momoko; Mӓgi, Reedik; van de Bunt, Martijn; Surakka, Ida; Sarin, Antti-Pekka; Mahajan, Anubha; Marullo, Letizia; Thorleifsson, Gudmar; Hӓgg, Sara; Hottenga, Jouke-Jan; Ladenvall, Claes; Ried, Janina S; Winkler, Thomas W; Willems, Sara M; Pervjakova, Natalia; Esko, Tõnu; Beekman, Marian; Nelson, Christopher P; Willenborg, Christina; Wiltshire, Steven; Ferreira, Teresa; Fernandez, Juan; Gaulton, Kyle J; Steinthorsdottir, Valgerdur; Hamsten, Anders; Magnusson, Patrik K E; Willemsen, Gonneke; Milaneschi, Yuri; Robertson, Neil R; Groves, Christopher J; Bennett, Amanda J; Lehtimӓki, Terho; Viikari, Jorma S; Rung, Johan; Lyssenko, Valeriya; Perola, Markus; Heid, Iris M; Herder, Christian; Grallert, Harald; Müller-Nurasyid, Martina; Roden, Michael; Hypponen, Elina; Isaacs, Aaron; van Leeuwen, Elisabeth M; Karssen, Lennart C; Mihailov, Evelin; Houwing-Duistermaat, Jeanine J; de Craen, Anton J M; Deelen, Joris; Havulinna, Aki S; Blades, Matthew; Hengstenberg, Christian; Erdmann, Jeanette; Schunkert, Heribert; Kaprio, Jaakko; Tobin, Martin D; Samani, Nilesh J; Lind, Lars; Salomaa, Veikko; Lindgren, Cecilia M; Slagboom, P Eline; Metspalu, Andres; van Duijn, Cornelia M; Eriksson, Johan G; Peters, Annette; Gieger, Christian; Jula, Antti; Groop, Leif; Raitakari, Olli T; Power, Chris; Penninx, Brenda W J H; de Geus, Eco; Smit, Johannes H; Boomsma, Dorret I; Pedersen, Nancy L; Ingelsson, Erik; Thorsteinsdottir, Unnur; Stefansson, Kari; Ripatti, Samuli; Prokopenko, Inga; McCarthy, Mark I; Morris, Andrew P

2015-07-01

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation

PubMed Central

van de Bunt, Martijn; Surakka, Ida; Sarin, Antti-Pekka; Mahajan, Anubha; Marullo, Letizia; Thorleifsson, Gudmar; Hӓgg, Sara; Hottenga, Jouke-Jan; Ladenvall, Claes; Ried, Janina S.; Winkler, Thomas W.; Willems, Sara M.; Pervjakova, Natalia; Esko, Tõnu; Beekman, Marian; Nelson, Christopher P.; Willenborg, Christina; Ferreira, Teresa; Fernandez, Juan; Gaulton, Kyle J.; Steinthorsdottir, Valgerdur; Hamsten, Anders; Magnusson, Patrik K. E.; Willemsen, Gonneke; Milaneschi, Yuri; Robertson, Neil R.; Groves, Christopher J.; Bennett, Amanda J.; Lehtimӓki, Terho; Viikari, Jorma S.; Rung, Johan; Lyssenko, Valeriya; Perola, Markus; Heid, Iris M.; Herder, Christian; Grallert, Harald; Müller-Nurasyid, Martina; Roden, Michael; Hypponen, Elina; Isaacs, Aaron; van Leeuwen, Elisabeth M.; Karssen, Lennart C.; Mihailov, Evelin; Houwing-Duistermaat, Jeanine J.; de Craen, Anton J. M.; Deelen, Joris; Havulinna, Aki S.; Blades, Matthew; Hengstenberg, Christian; Erdmann, Jeanette; Schunkert, Heribert; Kaprio, Jaakko; Tobin, Martin D.; Samani, Nilesh J.; Lind, Lars; Salomaa, Veikko; Lindgren, Cecilia M.; Slagboom, P. Eline; Metspalu, Andres; van Duijn, Cornelia M.; Eriksson, Johan G.; Peters, Annette; Gieger, Christian; Jula, Antti; Groop, Leif; Raitakari, Olli T.; Power, Chris; Penninx, Brenda W. J. H.; de Geus, Eco; Smit, Johannes H.; Boomsma, Dorret I.; Pedersen, Nancy L.; Ingelsson, Erik; Thorsteinsdottir, Unnur; Stefansson, Kari; Ripatti, Samuli; Prokopenko, Inga; McCarthy, Mark I.; Morris, Andrew P.

2015-01-01

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated. PMID:26132169

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data

PubMed Central

Abdoun, Oussama; Joucla, Sébastien; Mazzocco, Claire; Yvert, Blaise

2010-01-01

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware. PMID:21344013

NeuroMap: A Spline-Based Interactive Open-Source Software for Spatiotemporal Mapping of 2D and 3D MEA Data.

PubMed

Abdoun, Oussama; Joucla, Sébastien; Mazzocco, Claire; Yvert, Blaise

2011-01-01

A major characteristic of neural networks is the complexity of their organization at various spatial scales, from microscopic local circuits to macroscopic brain-scale areas. Understanding how neural information is processed thus entails the ability to study them at multiple scales simultaneously. This is made possible using microelectrodes array (MEA) technology. Indeed, high-density MEAs provide large-scale coverage (several square millimeters) of whole neural structures combined with microscopic resolution (about 50 μm) of unit activity. Yet, current options for spatiotemporal representation of MEA-collected data remain limited. Here we present NeuroMap, a new interactive Matlab-based software for spatiotemporal mapping of MEA data. NeuroMap uses thin plate spline interpolation, which provides several assets with respect to conventional mapping methods used currently. First, any MEA design can be considered, including 2D or 3D, regular or irregular, arrangements of electrodes. Second, spline interpolation allows the estimation of activity across the tissue with local extrema not necessarily at recording sites. Finally, this interpolation approach provides a straightforward analytical estimation of the spatial Laplacian for better current sources localization. In this software, coregistration of 2D MEA data on the anatomy of the neural tissue is made possible by fine matching of anatomical data with electrode positions using rigid-deformation-based correction of anatomical pictures. Overall, NeuroMap provides substantial material for detailed spatiotemporal analysis of MEA data. The package is distributed under GNU General Public License and available at http://sites.google.com/site/neuromapsoftware.

A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti

PubMed Central

2013-01-01

Background Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Methods Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Results Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these “hotspots”. Conclusions Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations. PMID:23587358

A ubiquitous method for street scale spatial data collection and analysis in challenging urban environments: mapping health risks using spatial video in Haiti.

PubMed

Curtis, Andrew; Blackburn, Jason K; Widmer, Jocelyn M; Morris, J Glenn

2013-04-15

Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these "hotspots". Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations.

The Spatial Scale and Spatial Configuration of Residential Settlement: Measuring Segregation in the Postbellum South

PubMed Central

Logan, John R.; Martinez, Matthew

2018-01-01

Studies of residential segregation typically focus on its degree without questioning its scale and configuration. We study Southern cities in 1880 to emphasize the salience of these spatial dimensions. Distance-based and sequence indices can reflect spatial patterns but with some limitations, while geocoded 100% population data make possible more informative measures. One improvement is flexibility in spatial scale, ranging from adjacent buildings to whole districts of the city. Another is the ability to map patterns in fine detail. In Southern cities we find qualitatively distinct configurations that include not only black “neighborhoods” as usually imagined, but also backyard housing, alley housing, and side streets that were predominantly black. These configurations represent the sort of symbolic boundaries recognized by urban ethnographers. By mapping residential configurations and interpreting them in light of historical accounts, our intention is to capture meanings that are too often missed by quantitative studies of segregation. PMID:29479108

Geohydrology of the Valley-Fill Aquifer in the Norwich-Oxford-Brisben Area, Chenango County, New York

USGS Publications Warehouse

Hetcher, Kari K.; Miller, Todd S.; Garry, James D.; Reynolds, Richard J.

2003-01-01

This set of maps and geohydrologic sections depicts the geology and hydrology of aquifers in the 21.9-square-mile reach of the Chenango River valley between Brisben and North Norwich, N.Y. This report depicts the principal geographic features of the study area; locations of domestic, commercial, and municipal wells from which data were obtained to construct water-table and saturated-thickness maps and five geohydrologic sections; surficial geology; water-table altitude; generalized saturated thickness of the unconfined (water-table) aquifer; generalized thickness of the discontinuous series of confined aquifers; and five geohydrologic sections, all of which are in the northern part of the study area.The unconsolidated material in the Chenango River valley consists primarily of three types of deposits: (1) glaciofluvial material consisting of stratified coarse-grained sediment (sand and gravel) that was deposited by meltwater streams flowing above, below, or next to a glacier; (2) glaciolacustrine material consisting of stratified fine-grained sediment (very fine sand, silt, and clay) that was deposited in lakes that formed at the front of a glacier; and (3) recent alluvial material consisting of stratified fine-to-medium grained sediment (fine-to-medium sand and silt) that was deposited on flood plains.The water-table map was compiled from water-level data obtained from wells completed in the unconfined aquifer, and from altitudes of stream and river surfaces indicated on 1:24,000-scale topographic maps. Depth to the water table ranged from less than 5 feet below land surface near major streams to more than 75 feet on some of the kame terraces along the valley walls. Saturated thickness of the unconfined aquifer ranged from less than 1 foot near Norwich to more than 200 feet at a kame delta north of Oxford.A discontinuous series of confined aquifers is present throughout much of the Chenango River valley north of Oxford. These aquifers consist of kame deposits, eskers, and subglacial outwash sand and gravel deposits that are overlain and confined by lacustrine fine sand, silt, and clay. The saturated thickness of these aquifers is as much as 150 feet near North Norwich.

Integrating High-Resolution Datasets to Target Mitigation Efforts for Improving Air Quality and Public Health in Urban Neighborhoods

PubMed Central

Shandas, Vivek; Voelkel, Jackson; Rao, Meenakshi; George, Linda

2016-01-01

Reducing exposure to degraded air quality is essential for building healthy cities. Although air quality and population vary at fine spatial scales, current regulatory and public health frameworks assess human exposures using county- or city-scales. We build on a spatial analysis technique, dasymetric mapping, for allocating urban populations that, together with emerging fine-scale measurements of air pollution, addresses three objectives: (1) evaluate the role of spatial scale in estimating exposure; (2) identify urban communities that are disproportionately burdened by poor air quality; and (3) estimate reduction in mobile sources of pollutants due to local tree-planting efforts using nitrogen dioxide. Our results show a maximum value of 197% difference between cadastrally-informed dasymetric system (CIDS) and standard estimations of population exposure to degraded air quality for small spatial extent analyses, and a lack of substantial difference for large spatial extent analyses. These results provide the foundation for improving policies for managing air quality, and targeting mitigation efforts to address challenges of environmental justice. PMID:27527205

Fine mapping of the NRC-1 tumor suppressor locus within chromosome 3p12.

PubMed

Zhang, Kun; Lott, Steven T; Jin, Li; Killary, Ann McNeill

2007-08-31

Identification of tumor suppressor genes based on physical mapping exercises has proven to be a challenging endeavor, due to the difficulty of narrowing regions of loss of heterozygosity (LOH), infrequency of homozygous deletions, and the labor-intensive characterization process for screening candidates in a given genomic interval. We previously defined a chromosome 3p12 tumor suppressor locus NRC-1 (Nonpapillary Renal Carcinoma-1) by functional complementation experiments in which renal cell carcinoma microcell hybrids containing introduced normal chromosome 3p fragments were either suppressed or unsuppressed for tumorigenicity following injection into athymic nude mice. We now present the fine-scale physical mapping of NRC-1 using a QPCR-based approach for measuring copy number at sequence tagged sites (STS) which allowed a sub-exon mapping resolution. Using STS-QPCR and a novel statistical algorithm, the NRC-1 locus was narrowed to 4.615-Mb with the distal boundary mapping within a 38-Kb interval between exon 3 and exon 4 of the DUTT1/Robo1 gene, currently the only candidate tumor suppressor gene in the interval. Further mutational screening and gene expression analyses indicate that DUTT1/ROBO1 is not involved in the tumor suppressor activity of NRC-1, suggesting that there are at least two important tumor suppressor genes within the chromosome 3p12 interval.

Fine scale vegetation classification and fuel load mapping for prescribed burning

Treesearch

Andrew D. Bailey; Robert Mickler

2007-01-01

Fire managers in the Coastal Plain of the Southeastern United States use prescribed burning as a tool to reduce fuel loads in a variety of vegetation types, many of which have elevated fuel loads due to a history of fire suppression. While standardized fuel models are useful in prescribed burn planning, those models do not quantify site-specific fuel loads that reflect...

Tree regeneration spatial patterns in ponderosa pine forests following stand-replacing fire: Influence of topography and neighbors

Treesearch

Justin P. Ziegler; Chad M. Hoffman; Paula J. Fornwalt; Carolyn H. Sieg; Michael A. Battaglia; Marin E. Chambers; Jose M. Iniguez

2017-01-01

Shifting fire regimes alter forest structure assembly in ponderosa pine forests and may produce structural heterogeneity following stand-replacing fire due, in part, to fine-scale variability in growing environments. We mapped tree regeneration in eighteen plots 11 to 15 years after stand-replacing fire in Colorado and South Dakota, USA. We used point pattern analyses...

Quantitative modeling of soil genesis processes

NASA Technical Reports Server (NTRS)

Levine, E. R.; Knox, R. G.; Kerber, A. G.

1992-01-01

For fine spatial scale simulation, a model is being developed to predict changes in properties over short-, meso-, and long-term time scales within horizons of a given soil profile. Processes that control these changes can be grouped into five major process clusters: (1) abiotic chemical reactions; (2) activities of organisms; (3) energy balance and water phase transitions; (4) hydrologic flows; and (5) particle redistribution. Landscape modeling of soil development is possible using digitized soil maps associated with quantitative soil attribute data in a geographic information system (GIS) framework to which simulation models are applied.

EPA's EnviroAtlas: Identifying Nature's benefits, deficits, and ...

EPA Pesticide Factsheets

Cities, towns, and Tribes rely on clean air, water and other natural resources for public health and well-being. Yet natural infrastructure and its benefits are not always fully understood or considered in local decisions. EnviroAtlas is a free, online, easy-to-use mapping toolkit designed for citizens, analysts, and decision-makers to assess the status of local and regional “green” assets, their relevance to society, current threats, and future opportunities. Research-based maps, analysis tools, and descriptive information address seven environmental benefit categories: - Clean air - Clean and plentiful water - Natural hazard mitigation - Climate stabilization - Recreation, culture, and aesthetics - Food, fuel, and materials - Biodiversity conservation More than 300 datasets for the coterminous U.S. summarize ecosystem processes, stressors, and end users at the spatial scale of sub-watersheds (n = ~90,000). A fine-scale component for selected communities features one-meter resolution landcover data and ~100 “green infrastructure” maps summarized by census block-group. Demographic data and built environment metrics are integrated into some of these maps, and are also provided by block group for overlays and other analyses. Numerous pixel-level maps are available as well. Map layers are consistent across EnviroAtlas communities; 18 of these are currently online, with six communities added annually. EnviroAtlas community maps and information addr

QUIESCENT PROMINENCES IN THE ERA OF ALMA: SIMULATED OBSERVATIONS USING THE 3D WHOLE-PROMINENCE FINE STRUCTURE MODEL

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gunár, Stanislav; Heinzel, Petr; Mackay, Duncan H.

2016-12-20

We use the detailed 3D whole-prominence fine structure model to produce the first simulated high-resolution ALMA observations of a modeled quiescent solar prominence. The maps of synthetic brightness temperature and optical thickness shown in the present paper are produced using a visualization method for synthesis of the submillimeter/millimeter radio continua. We have obtained the simulated observations of both the prominence at the limb and the filament on the disk at wavelengths covering a broad range that encompasses the full potential of ALMA. We demonstrate here extent to which the small-scale and large-scale prominence and filament structures will be visible inmore » the ALMA observations spanning both the optically thin and thick regimes. We analyze the relationship between the brightness and kinetic temperature of the prominence plasma. We also illustrate the opportunities ALMA will provide for studying the thermal structure of the prominence plasma from the cores of the cool prominence fine structure to the prominence–corona transition region. In addition, we show that detailed 3D modeling of entire prominences with their numerous fine structures will be important for the correct interpretation of future ALMA observations of prominences.« less

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics

PubMed Central

Chen, Wenan; Larrabee, Beth R.; Ovsyannikova, Inna G.; Kennedy, Richard B.; Haralambieva, Iana H.; Poland, Gregory A.; Schaid, Daniel J.

2015-01-01

Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other fine-mapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to one-fifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf. PMID:25948564

High resolution mapping of development in the wildland-urban interface using object based image extraction.

PubMed

Caggiano, Michael D; Tinkham, Wade T; Hoffman, Chad; Cheng, Antony S; Hawbaker, Todd J

2016-10-01

The wildland-urban interface (WUI), the area where human development encroaches on undeveloped land, is expanding throughout the western United States resulting in increased wildfire risk to homes and communities. Although census based mapping efforts have provided insights into the pattern of development and expansion of the WUI at regional and national scales, these approaches do not provide sufficient detail for fine-scale fire and emergency management planning, which requires maps of individual building locations. Although fine-scale maps of the WUI have been developed, they are often limited in their spatial extent, have unknown accuracies and biases, and are costly to update over time. In this paper we assess a semi-automated Object Based Image Analysis (OBIA) approach that utilizes 4-band multispectral National Aerial Image Program (NAIP) imagery for the detection of individual buildings within the WUI. We evaluate this approach by comparing the accuracy and overall quality of extracted buildings to a building footprint control dataset. In addition, we assessed the effects of buffer distance, topographic conditions, and building characteristics on the accuracy and quality of building extraction. The overall accuracy and quality of our approach was positively related to buffer distance, with accuracies ranging from 50 to 95% for buffer distances from 0 to 100 m. Our results also indicate that building detection was sensitive to building size, with smaller outbuildings (footprints less than 75 m 2 ) having detection rates below 80% and larger residential buildings having detection rates above 90%. These findings demonstrate that this approach can successfully identify buildings in the WUI in diverse landscapes while achieving high accuracies at buffer distances appropriate for most fire management applications while overcoming cost and time constraints associated with traditional approaches. This study is unique in that it evaluates the ability of an OBIA approach to extract highly detailed data on building locations in a WUI setting.

High resolution mapping of development in the wildland-urban interface using object based image extraction

USGS Publications Warehouse

Caggiano, Michael D.; Tinkham, Wade T.; Hoffman, Chad; Cheng, Antony S.; Hawbaker, Todd J.

2016-01-01

The wildland-urban interface (WUI), the area where human development encroaches on undeveloped land, is expanding throughout the western United States resulting in increased wildfire risk to homes and communities. Although census based mapping efforts have provided insights into the pattern of development and expansion of the WUI at regional and national scales, these approaches do not provide sufficient detail for fine-scale fire and emergency management planning, which requires maps of individual building locations. Although fine-scale maps of the WUI have been developed, they are often limited in their spatial extent, have unknown accuracies and biases, and are costly to update over time. In this paper we assess a semi-automated Object Based Image Analysis (OBIA) approach that utilizes 4-band multispectral National Aerial Image Program (NAIP) imagery for the detection of individual buildings within the WUI. We evaluate this approach by comparing the accuracy and overall quality of extracted buildings to a building footprint control dataset. In addition, we assessed the effects of buffer distance, topographic conditions, and building characteristics on the accuracy and quality of building extraction. The overall accuracy and quality of our approach was positively related to buffer distance, with accuracies ranging from 50 to 95% for buffer distances from 0 to 100 m. Our results also indicate that building detection was sensitive to building size, with smaller outbuildings (footprints less than 75 m2) having detection rates below 80% and larger residential buildings having detection rates above 90%. These findings demonstrate that this approach can successfully identify buildings in the WUI in diverse landscapes while achieving high accuracies at buffer distances appropriate for most fire management applications while overcoming cost and time constraints associated with traditional approaches. This study is unique in that it evaluates the ability of an OBIA approach to extract highly detailed data on building locations in a WUI setting.

Partial Least Square Discriminant Analysis Based on Normalized Two-Stage Vegetation Indices for Mapping Damage from Rice Diseases Using PlanetScope Datasets.

PubMed

Shi, Yue; Huang, Wenjiang; Ye, Huichun; Ruan, Chao; Xing, Naichen; Geng, Yun; Dong, Yingying; Peng, Dailiang

2018-06-11

In recent decades, rice disease co-epidemics have caused tremendous damage to crop production in both China and Southeast Asia. A variety of remote sensing based approaches have been developed and applied to map diseases distribution using coarse- to moderate-resolution imagery. However, the detection and discrimination of various disease species infecting rice were seldom assessed using high spatial resolution data. The aims of this study were (1) to develop a set of normalized two-stage vegetation indices (VIs) for characterizing the progressive development of different diseases with rice; (2) to explore the performance of combined normalized two-stage VIs in partial least square discriminant analysis (PLS-DA); and (3) to map and evaluate the damage caused by rice diseases at fine spatial scales, for the first time using bi-temporal, high spatial resolution imagery from PlanetScope datasets at a 3 m spatial resolution. Our findings suggest that the primary biophysical parameters caused by different disease (e.g., changes in leaf area, pigment contents, or canopy morphology) can be captured using combined normalized two-stage VIs. PLS-DA was able to classify rice diseases at a sub-field scale, with an overall accuracy of 75.62% and a Kappa value of 0.47. The approach was successfully applied during a typical co-epidemic outbreak of rice dwarf (Rice dwarf virus, RDV), rice blast ( Magnaporthe oryzae ), and glume blight ( Phyllosticta glumarum ) in Guangxi Province, China. Furthermore, our approach highlighted the feasibility of the method in capturing heterogeneous disease patterns at fine spatial scales over the large spatial extents.

Constructing fine-granularity functional brain network atlases via deep convolutional autoencoder.

PubMed

Zhao, Yu; Dong, Qinglin; Chen, Hanbo; Iraji, Armin; Li, Yujie; Makkie, Milad; Kou, Zhifeng; Liu, Tianming

2017-12-01

State-of-the-art functional brain network reconstruction methods such as independent component analysis (ICA) or sparse coding of whole-brain fMRI data can effectively infer many thousands of volumetric brain network maps from a large number of human brains. However, due to the variability of individual brain networks and the large scale of such networks needed for statistically meaningful group-level analysis, it is still a challenging and open problem to derive group-wise common networks as network atlases. Inspired by the superior spatial pattern description ability of the deep convolutional neural networks (CNNs), a novel deep 3D convolutional autoencoder (CAE) network is designed here to extract spatial brain network features effectively, based on which an Apache Spark enabled computational framework is developed for fast clustering of larger number of network maps into fine-granularity atlases. To evaluate this framework, 10 resting state networks (RSNs) were manually labeled from the sparsely decomposed networks of Human Connectome Project (HCP) fMRI data and 5275 network training samples were obtained, in total. Then the deep CAE models are trained by these functional networks' spatial maps, and the learned features are used to refine the original 10 RSNs into 17 network atlases that possess fine-granularity functional network patterns. Interestingly, it turned out that some manually mislabeled outliers in training networks can be corrected by the deep CAE derived features. More importantly, fine granularities of networks can be identified and they reveal unique network patterns specific to different brain task states. By further applying this method to a dataset of mild traumatic brain injury study, it shows that the technique can effectively identify abnormal small networks in brain injury patients in comparison with controls. In general, our work presents a promising deep learning and big data analysis solution for modeling functional connectomes, with fine granularities, based on fMRI data. Copyright © 2017 Elsevier B.V. All rights reserved.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir.

PubMed

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-09-23

The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies.

Mapping lava morphology of the Galapagos Spreading Center at 92°W: fuzzy logic provides a classification of high-resolution bathymetry and backscatter

NASA Astrophysics Data System (ADS)

McClinton, J. T.; White, S. M.; Sinton, J. M.; Rubin, K. H.; Bowles, J. A.

2010-12-01

Differences in axial lava morphology along the Galapagos Spreading Center (GSC) can indicate variations in magma supply and emplacement dynamics due to the influence of the adjacent Galapagos hot spot. Unfortunately, the ability to discriminate fine-scale lava morphology has historically been limited to observations of the small coverage areas of towed camera surveys and submersible operations. This research presents a neuro-fuzzy approach to automated seafloor classification using spatially coincident, high-resolution bathymetry and backscatter data. The classification method implements a Sugeno-type fuzzy inference system trained by a multi-layered adaptive neural network and is capable of rapidly classifying seafloor morphology based on attributes of surface geometry and texture. The system has been applied to the 92°W segment of the western GSC in order to quantify coverage areas and distributions of pillow, lobate, and sheet lava morphology. An accuracy assessment has been performed on the classification results. The resulting classified maps provide a high-resolution view of GSC axial morphology and indicate the study area terrain is approximately 40% pillow flows, 40% lobate and sheet flows, and 10% fissured or faulted area, with about 10% of the study area unclassifiable. Fine-scale features such as eruptive fissures, tumuli, and individual pillowed lava flow fronts are also visible. Although this system has been applied to lava morphology, its design and implementation are applicable to other undersea mapping applications.

Physical mapping of a pollen modifier locus controlling self-incompatibility in apricot and synteny analysis within the Rosaceae.

PubMed

Zuriaga, Elena; Molina, Laura; Badenes, María Luisa; Romero, Carlos

2012-06-01

S-locus products (S-RNase and F-box proteins) are essential for the gametophytic self-incompatibility (GSI) specific recognition in Prunus. However, accumulated genetic evidence suggests that other S-locus unlinked factors are also required for GSI. For instance, GSI breakdown was associated with a pollen-part mutation unlinked to the S-locus in the apricot (Prunus armeniaca L.) cv. 'Canino'. Fine-mapping of this mutated modifier gene (M-locus) and the synteny analysis of the M-locus within the Rosaceae are here reported. A segregation distortion loci mapping strategy, based on a selectively genotyped population, was used to map the M-locus. In addition, a bacterial artificial chromosome (BAC) contig was constructed for this region using overlapping oligonucleotides probes, and BAC-end sequences (BES) were blasted against Rosaceae genomes to perform micro-synteny analysis. The M-locus was mapped to the distal part of chr.3 flanked by two SSR markers within an interval of 1.8 cM corresponding to ~364 Kb in the peach (Prunus persica L. Batsch) genome. In the integrated genetic-physical map of this region, BES were mapped against the peach scaffold_3 and BACs were anchored to the apricot map. Micro-syntenic blocks were detected in apple (Malus × domestica Borkh.) LG17/9 and strawberry (Fragaria vesca L.) FG6 chromosomes. The M-locus fine-scale mapping provides a solid basis for self-compatibility marker-assisted selection and for positional cloning of the underlying gene, a necessary goal to elucidate the pollen rejection mechanism in Prunus. In a wider context, the syntenic regions identified in peach, apple and strawberry might be useful to interpret GSI evolution in Rosaceae.

High-density genetic map using whole-genome re-sequencing for fine mapping and candidate gene discovery for disease resistance in peanut

USDA-ARS?s Scientific Manuscript database

High-density genetic linkage maps are essential for fine mapping QTLs controlling disease resistance traits, such as early leaf spot (ELS), late leaf spot (LLS), and Tomato spotted wilt virus (TSWV). With completion of the genome sequences of two diploid ancestors of cultivated peanut, we could use ...

The underlying processes of a soil mite metacommunity on a small scale.

PubMed

Dong, Chengxu; Gao, Meixiang; Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran's eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale.

The underlying processes of a soil mite metacommunity on a small scale

PubMed Central

Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran’s eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale. PMID:28481906

Mapping Fearscapes of a Mammalian Herbivore using Terrestrial LiDAR and UAV Imagery

NASA Astrophysics Data System (ADS)

Olsoy, P.; Nobler, J. D.; Forbey, J.; Rachlow, J. L.; Burgess, M. A.; Glenn, N. F.; Shipley, L. A.

2013-12-01

Concealment allows prey animals to remain hidden from a predator and can influence both real and perceived risks of predation. The heterogeneous nature of vegetative structure can create a variable landscape of concealment - a 'fearscape' - that may influence habitat quality and use by prey. Traditional measurements of concealment rely on a limited number of distances, heights, and vantage points, resulting in small snapshots of concealment available to a prey animal. Our objective was to demonstrate the benefits of emerging remote sensing techniques to map fearscapes for pygmy rabbits (Brachylagus idahoensis) in sagebrush steppe habitat across a continuous range of scales. Specifically, we used vegetation height rasters derived from terrestrial laser scanning (TLS) to create viewsheds from multiple vantage points, representing predator visibility. The sum of all the viewsheds modeled horizontal concealment of prey at both the shrub and patch scales. We also used a small, unmanned aerial vehicle (UAV) to determine vertical concealment at a habitat scale. Terrestrial laser scanning provided similar estimates of horizontal concealment at the shrub scale when compared to photographic methods (R2 = 0.85). Both TLS and UAV provide the potential to quantify concealment of prey from multiple distances, heights, or vantage points, allowing the creation of a manipulable fearscape map that can be correlated with habitat use by prey animals. The predictive power of such a map also could identify shrubs or patches for fine scale nutritional and concealment analysis for future investigation and conservation efforts. Fearscape map at the mound-scale. Viewsheds were calculated from 100 equally spaced observer points located 4 m from the closest on-mound sagebrush of interest. Red areas offer low concealment, while green areas provide high concealment.

Fine-Scale Relief in the Amazon Drives Large Scale Ecohydrological Processes

NASA Astrophysics Data System (ADS)

Nobre, A. D.; Cuartas, A.; Hodnett, M.; Saleska, S. R.

2014-12-01

Access to soil water by roots is a key ecophysiological factor for plant productivity in natural systems. Periodically during dry seasons or critically during episodic climate droughts, shortage of water supply can reduce or severely impair plant life. At the other extreme persistent soil waterlogging will limit root respiration and restrict local establishment to adapted species, usually leading to stunted and less productive communities. Soil-water availability is therefore a very important climate variable controlling plant physiology and ecosystem dynamics. Terra-firme, the non-seasonally floodable terrain that covers 82% of the landscape in Amazonia,[1] supports the most massive part of the rainforest ecosystem. The availability of soil water data for terra-firme is scant and very coarse. This lack of data has hampered observational and modeling studies aiming to develop a large-scale integrative ecohydrological picture of Amazonia and its vulnerability to climate change. We have mapped the Amazon basin with a new terrain model developed in our group (HAND, Height Above the Nearest drainage[2]), delineating soil water environments using topographical data from the SRTM digital elevation model (250 m horizontal interpolated resolution). The preliminary results show that more than 50% of Terra-firme has the water table very close to the surface (up to 2 m deep), while the remainder of the upland landscape has variable degree of dependence on non-saturated soil (vadose layer). The mapping also shows extremely heterogeneous patterns of fine-scale relief across the basin, which implies complex ecohydrological regional forcing on the forest physiology. Ecoclimate studies should therefore take into account fine-scale relief and its implications for soil-water availability to plant processes. [1] Melack, J. M., & Hess, L. L. (2011). Remote sensing of the distribution and extent of wetlands in the Amazon basin. In W. J. Junk & M. Piedade (Eds.), Amazonian floodplain forests: Ecophysiology, ecology, biodiversity and sustainable management (pp. 1-28). Ecological Studies-Springer. [2] Nobre, A. D., Cuartas, L. A., Hodnett, M., … Saleska, S. (2011). Height Above the Nearest Drainage - a hydrologically relevant new terrain model. Journal of Hydrology, 404(1-2), 13-29

Cell-accurate optical mapping across the entire developing heart.

PubMed

Weber, Michael; Scherf, Nico; Meyer, Alexander M; Panáková, Daniela; Kohl, Peter; Huisken, Jan

2017-12-29

Organogenesis depends on orchestrated interactions between individual cells and morphogenetically relevant cues at the tissue level. This is true for the heart, whose function critically relies on well-ordered communication between neighboring cells, which is established and fine-tuned during embryonic development. For an integrated understanding of the development of structure and function, we need to move from isolated snap-shot observations of either microscopic or macroscopic parameters to simultaneous and, ideally continuous, cell-to-organ scale imaging. We introduce cell-accurate three-dimensional Ca 2+ -mapping of all cells in the entire electro-mechanically uncoupled heart during the looping stage of live embryonic zebrafish, using high-speed light sheet microscopy and tailored image processing and analysis. We show how myocardial region-specific heterogeneity in cell function emerges during early development and how structural patterning goes hand-in-hand with functional maturation of the entire heart. Our method opens the way to systematic, scale-bridging, in vivo studies of vertebrate organogenesis by cell-accurate structure-function mapping across entire organs.

Cell-accurate optical mapping across the entire developing heart

PubMed Central

Meyer, Alexander M; Panáková, Daniela; Kohl, Peter

2017-01-01

Organogenesis depends on orchestrated interactions between individual cells and morphogenetically relevant cues at the tissue level. This is true for the heart, whose function critically relies on well-ordered communication between neighboring cells, which is established and fine-tuned during embryonic development. For an integrated understanding of the development of structure and function, we need to move from isolated snap-shot observations of either microscopic or macroscopic parameters to simultaneous and, ideally continuous, cell-to-organ scale imaging. We introduce cell-accurate three-dimensional Ca2+-mapping of all cells in the entire electro-mechanically uncoupled heart during the looping stage of live embryonic zebrafish, using high-speed light sheet microscopy and tailored image processing and analysis. We show how myocardial region-specific heterogeneity in cell function emerges during early development and how structural patterning goes hand-in-hand with functional maturation of the entire heart. Our method opens the way to systematic, scale-bridging, in vivo studies of vertebrate organogenesis by cell-accurate structure-function mapping across entire organs. PMID:29286002

Hyperspectral image visualization based on a human visual model

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Peng, Honghong; Fairchild, Mark D.; Montag, Ethan D.

2008-02-01

Hyperspectral image data can provide very fine spectral resolution with more than 200 bands, yet presents challenges for visualization techniques for displaying such rich information on a tristimulus monitor. This study developed a visualization technique by taking advantage of both the consistent natural appearance of a true color image and the feature separation of a PCA image based on a biologically inspired visual attention model. The key part is to extract the informative regions in the scene. The model takes into account human contrast sensitivity functions and generates a topographic saliency map for both images. This is accomplished using a set of linear "center-surround" operations simulating visual receptive fields as the difference between fine and coarse scales. A difference map between the saliency map of the true color image and that of the PCA image is derived and used as a mask on the true color image to select a small number of interesting locations where the PCA image has more salient features than available in the visible bands. The resulting representations preserve hue for vegetation, water, road etc., while the selected attentional locations may be analyzed by more advanced algorithms.

Improved regional-scale Brazilian cropping systems' mapping based on a semi-automatic object-based clustering approach

NASA Astrophysics Data System (ADS)

Bellón, Beatriz; Bégué, Agnès; Lo Seen, Danny; Lebourgeois, Valentine; Evangelista, Balbino Antônio; Simões, Margareth; Demonte Ferraz, Rodrigo Peçanha

2018-06-01

Cropping systems' maps at fine scale over large areas provide key information for further agricultural production and environmental impact assessments, and thus represent a valuable tool for effective land-use planning. There is, therefore, a growing interest in mapping cropping systems in an operational manner over large areas, and remote sensing approaches based on vegetation index time series analysis have proven to be an efficient tool. However, supervised pixel-based approaches are commonly adopted, requiring resource consuming field campaigns to gather training data. In this paper, we present a new object-based unsupervised classification approach tested on an annual MODIS 16-day composite Normalized Difference Vegetation Index time series and a Landsat 8 mosaic of the State of Tocantins, Brazil, for the 2014-2015 growing season. Two variants of the approach are compared: an hyperclustering approach, and a landscape-clustering approach involving a previous stratification of the study area into landscape units on which the clustering is then performed. The main cropping systems of Tocantins, characterized by the crop types and cropping patterns, were efficiently mapped with the landscape-clustering approach. Results show that stratification prior to clustering significantly improves the classification accuracies for underrepresented and sparsely distributed cropping systems. This study illustrates the potential of unsupervised classification for large area cropping systems' mapping and contributes to the development of generic tools for supporting large-scale agricultural monitoring across regions.

Structural Variation Shapes the Landscape of Recombination in Mouse

PubMed Central

Morgan, Andrew P.; Gatti, Daniel M.; Najarian, Maya L.; Keane, Thomas M.; Galante, Raymond J.; Pack, Allan I.; Mott, Richard; Churchill, Gary A.; de Villena, Fernando Pardo-Manuel

2017-01-01

Meiotic recombination is an essential feature of sexual reproduction that ensures faithful segregation of chromosomes and redistributes genetic variants in populations. Multiparent populations such as the Diversity Outbred (DO) mouse stock accumulate large numbers of crossover (CO) events between founder haplotypes, and thus present a unique opportunity to study the role of genetic variation in shaping the recombination landscape. We obtained high-density genotype data from 6886 DO mice, and localized 2.2 million CO events to intervals with a median size of 28 kb. The resulting sex-averaged genetic map of the DO population is highly concordant with large-scale (order 10 Mb) features of previously reported genetic maps for mouse. To examine fine-scale (order 10 kb) patterns of recombination in the DO, we overlaid putative recombination hotspots onto our CO intervals. We found that CO intervals are enriched in hotspots compared to the genomic background. However, as many as 26% of CO intervals do not overlap any putative hotspots, suggesting that our understanding of hotspots is incomplete. We also identified coldspots encompassing 329 Mb, or 12% of observable genome, in which there is little or no recombination. In contrast to hotspots, which are a few kilobases in size, and widely scattered throughout the genome, coldspots have a median size of 2.1 Mb and are spatially clustered. Coldspots are strongly associated with copy-number variant (CNV) regions, especially multi-allelic clusters, identified from whole-genome sequencing of 228 DO mice. Genes in these regions have reduced expression, and epigenetic features of closed chromatin in male germ cells, which suggests that CNVs may repress recombination by altering chromatin structure in meiosis. Our findings demonstrate how multiparent populations, by bridging the gap between large-scale and fine-scale genetic mapping, can reveal new features of the recombination landscape. PMID:28592499

Structural Variation Shapes the Landscape of Recombination in Mouse.

PubMed

Morgan, Andrew P; Gatti, Daniel M; Najarian, Maya L; Keane, Thomas M; Galante, Raymond J; Pack, Allan I; Mott, Richard; Churchill, Gary A; de Villena, Fernando Pardo-Manuel

2017-06-01

Meiotic recombination is an essential feature of sexual reproduction that ensures faithful segregation of chromosomes and redistributes genetic variants in populations. Multiparent populations such as the Diversity Outbred (DO) mouse stock accumulate large numbers of crossover (CO) events between founder haplotypes, and thus present a unique opportunity to study the role of genetic variation in shaping the recombination landscape. We obtained high-density genotype data from [Formula: see text] DO mice, and localized 2.2 million CO events to intervals with a median size of 28 kb. The resulting sex-averaged genetic map of the DO population is highly concordant with large-scale (order 10 Mb) features of previously reported genetic maps for mouse. To examine fine-scale (order 10 kb) patterns of recombination in the DO, we overlaid putative recombination hotspots onto our CO intervals. We found that CO intervals are enriched in hotspots compared to the genomic background. However, as many as [Formula: see text] of CO intervals do not overlap any putative hotspots, suggesting that our understanding of hotspots is incomplete. We also identified coldspots encompassing 329 Mb, or [Formula: see text] of observable genome, in which there is little or no recombination. In contrast to hotspots, which are a few kilobases in size, and widely scattered throughout the genome, coldspots have a median size of 2.1 Mb and are spatially clustered. Coldspots are strongly associated with copy-number variant (CNV) regions, especially multi-allelic clusters, identified from whole-genome sequencing of 228 DO mice. Genes in these regions have reduced expression, and epigenetic features of closed chromatin in male germ cells, which suggests that CNVs may repress recombination by altering chromatin structure in meiosis. Our findings demonstrate how multiparent populations, by bridging the gap between large-scale and fine-scale genetic mapping, can reveal new features of the recombination landscape. Copyright © 2017 by the Genetics Society of America.

Contrasting patterns of fine-scale herb layer species composition in temperate forests

NASA Astrophysics Data System (ADS)

Chudomelová, Markéta; Zelený, David; Li, Ching-Feng

2017-04-01

Although being well described at the landscape level, patterns in species composition of forest herb layer are rarely studied at smaller scales. Here, we examined fine-scale environmental determinants and spatial structures of herb layer communities in thermophilous oak- and hornbeam dominated forests of the south-eastern part of the Czech Republic. Species composition of herb layer vegetation and environmental variables were recorded within a fixed grid of 2 × 2 m subplots regularly distributed within 1-ha quadrate plots in three forest stands. For each site, environmental models best explaining species composition were constructed using constrained ordination analysis. Spatial eigenvector mapping was used to model and account for spatial structures in community variation. Mean Ellenberg indicator values calculated for each subplot were used for ecological interpretation of spatially structured residual variation. The amount of variation explained by environmental and spatial models as well as the selection of variables with the best explanatory power differed among sites. As an important environmental factor, relative elevation was common to all three sites, while pH and canopy openness were shared by two sites. Both environmental and community variation was mostly coarse-scaled, as was the spatially structured portion of residual variation. When corrected for bias due to spatial autocorrelation, those environmental factors with already weak explanatory power lost their significance. Only a weak evidence of possibly omitted environmental predictor was found for autocorrelated residuals of site models using mean Ellenberg indicator values. Community structure was determined by different factors at different sites. The relative importance of environmental filtering vs. spatial processes was also site specific, implying that results of fine-scale studies tend to be shaped by local conditions. Contrary to expectations based on other studies, overall dominance of spatial processes at fine scale has not been detected. Ecologists should keep this in mind when making generalizations about community dynamics.

Fine Mapping and Evolution of a QTL Region on Cattle Chromosome 3

ERIC Educational Resources Information Center

Donthu, Ravikiran

2009-01-01

The goal of my dissertation was to fine map the milk yield and composition quantitative trait loci (QTL) mapped to cattle chromosome 3 (BTA3) by Heyen et al. (1999) and to identify candidate genes affecting these traits. To accomplish this, the region between "BL41" and "TGLA263" was mapped to the cattle genome sequence assembly Btau 3.1 and a…

Fine Mapping Causal Variants with an Approximate Bayesian Method Using Marginal Test Statistics.

PubMed

Chen, Wenan; Larrabee, Beth R; Ovsyannikova, Inna G; Kennedy, Richard B; Haralambieva, Iana H; Poland, Gregory A; Schaid, Daniel J

2015-07-01

Two recently developed fine-mapping methods, CAVIAR and PAINTOR, demonstrate better performance over other fine-mapping methods. They also have the advantage of using only the marginal test statistics and the correlation among SNPs. Both methods leverage the fact that the marginal test statistics asymptotically follow a multivariate normal distribution and are likelihood based. However, their relationship with Bayesian fine mapping, such as BIMBAM, is not clear. In this study, we first show that CAVIAR and BIMBAM are actually approximately equivalent to each other. This leads to a fine-mapping method using marginal test statistics in the Bayesian framework, which we call CAVIAR Bayes factor (CAVIARBF). Another advantage of the Bayesian framework is that it can answer both association and fine-mapping questions. We also used simulations to compare CAVIARBF with other methods under different numbers of causal variants. The results showed that both CAVIARBF and BIMBAM have better performance than PAINTOR and other methods. Compared to BIMBAM, CAVIARBF has the advantage of using only marginal test statistics and takes about one-quarter to one-fifth of the running time. We applied different methods on two independent cohorts of the same phenotype. Results showed that CAVIARBF, BIMBAM, and PAINTOR selected the same top 3 SNPs; however, CAVIARBF and BIMBAM had better consistency in selecting the top 10 ranked SNPs between the two cohorts. Software is available at https://bitbucket.org/Wenan/caviarbf. Copyright © 2015 by the Genetics Society of America.

Improving FIA trend analysis through model-based estimation using landsat disturbance maps and the forest vegetation simulator

Treesearch

Sean P. Healey; Gretchen G. Moisen; Paul L. Patterson

2012-01-01

The Forest Inventory and Analysis (FIA) Program's panel system, in which 10-20 percent of the sample is measured in any given year, is designed to increase the currency of FIA reporting and its sensitivity to factors operating at relatively fine temporal scales. Now that much of the country has completed at least one measurement cycle over all panels, there is an...

Using an epiphytic moss to identify previously unknown sources of atmospheric cadmium pollution

Treesearch

Geoffrey H. Donovan; Sarah E. Jovan; Demetrios Gatziolis; Igor Burstyn; Yvonne L. Michael; Michael C. Amacher; Vicente J. Monleon

2016-01-01

Urban networks of air-quality monitors are often too widely spaced to identify sources of air pollutants, especially if they do not disperse far from emission sources. The objectives of this study were to test the use of moss bio-indicators to develop a fine-scale map of atmospherically-derived cadmium and to identify the sources of cadmium in a complex urban setting....

Occupancy mapping and surface reconstruction using local Gaussian processes with Kinect sensors.

PubMed

Kim, Soohwan; Kim, Jonghyuk

2013-10-01

Although RGB-D sensors have been successfully applied to visual SLAM and surface reconstruction, most of the applications aim at visualization. In this paper, we propose a noble method of building continuous occupancy maps and reconstructing surfaces in a single framework for both navigation and visualization. Particularly, we apply a Bayesian nonparametric approach, Gaussian process classification, to occupancy mapping. However, it suffers from high-computational complexity of O(n(3))+O(n(2)m), where n and m are the numbers of training and test data, respectively, limiting its use for large-scale mapping with huge training data, which is common with high-resolution RGB-D sensors. Therefore, we partition both training and test data with a coarse-to-fine clustering method and apply Gaussian processes to each local clusters. In addition, we consider Gaussian processes as implicit functions, and thus extract iso-surfaces from the scalar fields, continuous occupancy maps, using marching cubes. By doing that, we are able to build two types of map representations within a single framework of Gaussian processes. Experimental results with 2-D simulated data show that the accuracy of our approximated method is comparable to previous work, while the computational time is dramatically reduced. We also demonstrate our method with 3-D real data to show its feasibility in large-scale environments.

Real-Time Large-Scale Dense Mapping with Surfels

PubMed Central

Fu, Xingyin; Zhu, Feng; Wu, Qingxiao; Sun, Yunlei; Lu, Rongrong; Yang, Ruigang

2018-01-01

Real-time dense mapping systems have been developed since the birth of consumer RGB-D cameras. Currently, there are two commonly used models in dense mapping systems: truncated signed distance function (TSDF) and surfel. The state-of-the-art dense mapping systems usually work fine with small-sized regions. The generated dense surface may be unsatisfactory around the loop closures when the system tracking drift grows large. In addition, the efficiency of the system with surfel model slows down when the number of the model points in the map becomes large. In this paper, we propose to use two maps in the dense mapping system. The RGB-D images are integrated into a local surfel map. The old surfels that reconstructed in former times and far away from the camera frustum are moved from the local map to the global map. The updated surfels in the local map when every frame arrives are kept bounded. Therefore, in our system, the scene that can be reconstructed is very large, and the frame rate of our system remains high. We detect loop closures and optimize the pose graph to distribute system tracking drift. The positions and normals of the surfels in the map are also corrected using an embedded deformation graph so that they are consistent with the updated poses. In order to deal with large surface deformations, we propose a new method for constructing constraints with system trajectories and loop closure keyframes. The proposed new method stabilizes large-scale surface deformation. Experimental results show that our novel system behaves better than the prior state-of-the-art dense mapping systems. PMID:29747450

Stream piracy in the Black Hills: A geomorphology lab exercise

USGS Publications Warehouse

Zaprowski, B.J.; Evenson, E.B.; Epstein, J.B.

2002-01-01

The Black Hills of South Dakota exhibits many fine examples of stream piracy that are very suitable for teaching geomorphology lab exercises. This lab goes beyond standard topographic map interpretation by using geologic maps, well logs, gravel provenance and other types of data to teach students about stream piracy. Using a step-by-step method in which the lab exercises ramp up in difficulty, students hone their skills in deductive reasoning and data assimilation. The first exercises deal with the identification of stream piracy at a variety of spatial scales and the lab culminates with an exercise on landscape evolution and drainage rearrangement.

Wild boar mapping using population-density statistics: From polygons to high resolution raster maps.

PubMed

Pittiglio, Claudia; Khomenko, Sergei; Beltran-Alcrudo, Daniel

2018-01-01

The wild boar is an important crop raider as well as a reservoir and agent of spread of swine diseases. Due to increasing densities and expanding ranges worldwide, the related economic losses in livestock and agricultural sectors are significant and on the rise. Its management and control would strongly benefit from accurate and detailed spatial information on species distribution and abundance, which are often available only for small areas. Data are commonly available at aggregated administrative units with little or no information about the distribution of the species within the unit. In this paper, a four-step geostatistical downscaling approach is presented and used to disaggregate wild boar population density statistics from administrative units of different shape and size (polygons) to 5 km resolution raster maps by incorporating auxiliary fine scale environmental variables. 1) First a stratification method was used to define homogeneous bioclimatic regions for the analysis; 2) Under a geostatistical framework, the wild boar densities at administrative units, i.e. subnational areas, were decomposed into trend and residual components for each bioclimatic region. Quantitative relationships between wild boar data and environmental variables were estimated through multiple regression and used to derive trend components at 5 km spatial resolution. Next, the residual components (i.e., the differences between the trend components and the original wild boar data at administrative units) were downscaled at 5 km resolution using area-to-point kriging. The trend and residual components obtained at 5 km resolution were finally added to generate fine scale wild boar estimates for each bioclimatic region. 3) These maps were then mosaicked to produce a final output map of predicted wild boar densities across most of Eurasia. 4) Model accuracy was assessed at each different step using input as well as independent data. We discuss advantages and limits of the method and its potential application in animal health.

Wild boar mapping using population-density statistics: From polygons to high resolution raster maps

PubMed Central

Pittiglio, Claudia; Khomenko, Sergei

2018-01-01

The wild boar is an important crop raider as well as a reservoir and agent of spread of swine diseases. Due to increasing densities and expanding ranges worldwide, the related economic losses in livestock and agricultural sectors are significant and on the rise. Its management and control would strongly benefit from accurate and detailed spatial information on species distribution and abundance, which are often available only for small areas. Data are commonly available at aggregated administrative units with little or no information about the distribution of the species within the unit. In this paper, a four-step geostatistical downscaling approach is presented and used to disaggregate wild boar population density statistics from administrative units of different shape and size (polygons) to 5 km resolution raster maps by incorporating auxiliary fine scale environmental variables. 1) First a stratification method was used to define homogeneous bioclimatic regions for the analysis; 2) Under a geostatistical framework, the wild boar densities at administrative units, i.e. subnational areas, were decomposed into trend and residual components for each bioclimatic region. Quantitative relationships between wild boar data and environmental variables were estimated through multiple regression and used to derive trend components at 5 km spatial resolution. Next, the residual components (i.e., the differences between the trend components and the original wild boar data at administrative units) were downscaled at 5 km resolution using area-to-point kriging. The trend and residual components obtained at 5 km resolution were finally added to generate fine scale wild boar estimates for each bioclimatic region. 3) These maps were then mosaicked to produce a final output map of predicted wild boar densities across most of Eurasia. 4) Model accuracy was assessed at each different step using input as well as independent data. We discuss advantages and limits of the method and its potential application in animal health. PMID:29768413

Topography- and nightlight-based national flood risk assessment in Canada

NASA Astrophysics Data System (ADS)

Elshorbagy, Amin; Bharath, Raja; Lakhanpal, Anchit; Ceola, Serena; Montanari, Alberto; Lindenschmidt, Karl-Erich

2017-04-01

In Canada, flood analysis and water resource management, in general, are tasks conducted at the provincial level; therefore, unified national-scale approaches to water-related problems are uncommon. In this study, a national-scale flood risk assessment approach is proposed and developed. The study focuses on using global and national datasets available with various resolutions to create flood risk maps. First, a flood hazard map of Canada is developed using topography-based parameters derived from digital elevation models, namely, elevation above nearest drainage (EAND) and distance from nearest drainage (DFND). This flood hazard mapping method is tested on a smaller area around the city of Calgary, Alberta, against a flood inundation map produced by the city using hydraulic modelling. Second, a flood exposure map of Canada is developed using a land-use map and the satellite-based nightlight luminosity data as two exposure parameters. Third, an economic flood risk map is produced, and subsequently overlaid with population density information to produce a socioeconomic flood risk map for Canada. All three maps of hazard, exposure, and risk are classified into five classes, ranging from very low to severe. A simple way to include flood protection measures in hazard estimation is also demonstrated using the example of the city of Winnipeg, Manitoba. This could be done for the entire country if information on flood protection across Canada were available. The evaluation of the flood hazard map shows that the topography-based method adopted in this study is both practical and reliable for large-scale analysis. Sensitivity analysis regarding the resolution of the digital elevation model is needed to identify the resolution that is fine enough for reliable hazard mapping, but coarse enough for computational tractability. The nightlight data are found to be useful for exposure and risk mapping in Canada; however, uncertainty analysis should be conducted to investigate the effect of the overglow phenomenon on flood risk mapping.

Mapping Henry: Synchrotron-sourced X-ray fluorescence mapping and ultra-high-definition scanning of an early Tudor portrait of Henry VIII

NASA Astrophysics Data System (ADS)

Dredge, Paula; Ives, Simon; Howard, Daryl L.; Spiers, Kathryn M.; Yip, Andrew; Kenderdine, Sarah

2015-11-01

A portrait of Henry VIII on oak panel c. 1535 has recently undergone technical examination to inform questions regarding authorship and the painting's relationship to a group of similar works in the collections of the National Portrait Gallery, London, and the Society of Antiquaries. Due to previous conservation treatments of the painting, the conventional transmission X-radiograph image was difficult to interpret. As a result, the painting underwent high-definition X-ray fluorescence (XRF) elemental mapping on the X-ray fluorescence microscopy beamline of the Australian Synchrotron. Scans were conducted at 12.6 and 18.5 keV, below and above the lead (Pb) L edges, respectively. Typical scan parameters were 120 μm pixel size at 7 ms dwell time, with the largest scan covering an area 545 × 287 mm2 collected in 23 h (10.8 MP). XRF mapping of the panel has guided the conservation treatment of the painting and the revelation of previously obscured features. It has also provided insight into the process of making of the painting. The informative and detailed elemental maps, alongside ultra-high-definition scans of the painting undertaken before and after varnish and over-paint removal, have assisted in comparison of the finely painted details with the London paintings. The resolution offered by the combination of imaging techniques identifies pigment distribution at an extremely fine scale, enabling a new understanding of the artist's paint application.

Communicating Flood Risk with Street-Level Data

NASA Astrophysics Data System (ADS)

Sanders, B. F.; Matthew, R.; Houston, D.; Cheung, W. H.; Karlin, B.; Schubert, J.; Gallien, T.; Luke, A.; Contreras, S.; Goodrich, K.; Feldman, D.; Basolo, V.; Serrano, K.; Reyes, A.

2015-12-01

Coastal communities around the world face significant and growing flood risks that require an accelerating adaptation response, and fine-resolution urban flood models could serve a pivotal role in enabling communities to meet this need. Such models depict impacts at the level of individual buildings and land parcels or "street level" - the same spatial scale at which individuals are best able to process flood risk information - constituting a powerful tool to help communities build better understandings of flood vulnerabilities and identify cost-effective interventions. To measure understanding of flood risk within a community and the potential impact of street-level models, we carried out a household survey of flood risk awareness in Newport Beach, California, a highly urbanized coastal lowland that presently experiences nuisance flooding from high tides, waves and rainfall and is expected to experience a significant increase in flood frequency and intensity with climate change. Interviews were completed with the aid of a wireless-enabled tablet device that respondents could use to identify areas they understood to be at risk of flooding and to view either a Federal Emergency Management Agency (FEMA) flood map or a more detailed map prepared with a hydrodynamic urban coastal flood model (UCI map) built with grid cells as fine as 3 m resolution and validated with historical flood data. Results indicate differences in the effectiveness of the UCI and FEMA maps at communicating the spatial distribution of flood risk, gender differences in how the maps affect flood understanding, and spatial biases in the perception of flood vulnerabilities.

Climate change: evaluating your local and regional water resources

USGS Publications Warehouse

Flint, Lorraine E.; Flint, Alan L.; Thorne, James H.

2015-01-01

The BCM is a fine-scale hydrologic model that uses detailed maps of soils, geology, topography, and transient monthly or daily maps of potential evapotranspiration, air temperature, and precipitation to generate maps of recharge, runoff, snow pack, actual evapotranspiration, and climatic water deficit. With these comprehensive environmental inputs and experienced scientific analysis, the BCM provides resource managers with important hydrologic and ecologic understanding of a landscape or basin at hillslope to regional scales. The model is calibrated using historical climate and streamflow data over the range of geologic materials specific to an area. Once calibrated, the model is used to translate climate-change data into hydrologic responses for a defined landscape, to provide managers an understanding of potential ecological risks and threats to water supplies and managed hydrologic systems. Although limited to estimates of unimpaired hydrologic conditions, estimates of impaired conditions, such as agricultural demand, diversions, or reservoir outflows can be incorporated into the calibration of the model to expand its utility. Additionally, the model can be linked to other models, such as groundwater-flow models (that is, MODFLOW) or the integrated hydrologic model (MF-FMP), to provide information about subsurface hydrologic processes. The model can be applied at a relatively small scale, but also can be applied to large-scale national and international river basins.

Biodiversity Mapping via Natura 2000 Conservation Status and Ebv Assessment Using Airborne Laser Scanning in Alkali Grasslands

NASA Astrophysics Data System (ADS)

Zlinszky, A.; Deák, B.; Kania, A.; Schroiff, A.; Pfeifer, N.

2016-06-01

Biodiversity is an ecological concept, which essentially involves a complex sum of several indicators. One widely accepted such set of indicators is prescribed for habitat conservation status assessment within Natura 2000, a continental-scale conservation programme of the European Union. Essential Biodiversity Variables are a set of indicators designed to be relevant for biodiversity and suitable for global-scale operational monitoring. Here we revisit a study of Natura 2000 conservation status mapping via airbone LIDAR that develops individual remote sensing-derived proxies for every parameter required by the Natura 2000 manual, from the perspective of developing regional-scale Essential Biodiversity Variables. Based on leaf-on and leaf-off point clouds (10 pt/m2) collected in an alkali grassland area, a set of data products were calculated at 0.5 ×0.5 m resolution. These represent various aspects of radiometric and geometric texture. A Random Forest machine learning classifier was developed to create fuzzy vegetation maps of classes of interest based on these data products. In the next step, either classification results or LIDAR data products were selected as proxies for individual Natura 2000 conservation status variables, and fine-tuned based on field references. These proxies showed adequate performance and were summarized to deliver Natura 2000 conservation status with 80% overall accuracy compared to field references. This study draws attention to the potential of LIDAR for regional-scale Essential Biodiversity variables, and also holds implications for global-scale mapping. These are (i) the use of sensor data products together with habitat-level classification, (ii) the utility of seasonal data, including for non-seasonal variables such as grassland canopy structure, and (iii) the potential of fuzzy mapping-derived class probabilities as proxies for species presence and absence.

Fine-Scale Map of Encyclopedia of DNA Elements Regions in the Korean Population

PubMed Central

Yoo, Yeon-Kyeong; Ke, Xiayi; Hong, Sungwoo; Jang, Hye-Yoon; Park, Kyunghee; Kim, Sook; Ahn, TaeJin; Lee, Yeun-Du; Song, Okryeol; Rho, Na-Young; Lee, Moon Sue; Lee, Yeon-Su; Kim, Jaeheup; Kim, Young J.; Yang, Jun-Mo; Song, Kyuyoung; Kimm, Kyuchan; Weir, Bruce; Cardon, Lon R.; Lee, Jong-Eun; Hwang, Jung-Joo

2006-01-01

The International HapMap Project aims to generate detailed human genome variation maps by densely genotyping single-nucleotide polymorphisms (SNPs) in CEPH, Chinese, Japanese, and Yoruba samples. This will undoubtedly become an important facility for genetic studies of diseases and complex traits in the four populations. To address how the genetic information contained in such variation maps is transferable to other populations, the Korean government, industries, and academics have launched the Korean HapMap project to genotype high-density Encyclopedia of DNA Elements (ENCODE) regions in 90 Korean individuals. Here we show that the LD pattern, block structure, haplotype diversity, and recombination rate are highly concordant between Korean and the two HapMap Asian samples, particularly Japanese. The availability of information from both Chinese and Japanese samples helps to predict more accurately the possible performance of HapMap markers in Korean disease-gene studies. Tagging SNPs selected from the two HapMap Asian maps, especially the Japanese map, were shown to be very effective for Korean samples. These results demonstrate that the HapMap variation maps are robust in related populations and will serve as an important resource for the studies of the Korean population in particular. PMID:16702437

Genetic recombination is targeted towards gene promoter regions in dogs.

PubMed

Auton, Adam; Rui Li, Ying; Kidd, Jeffrey; Oliveira, Kyle; Nadel, Julie; Holloway, J Kim; Hayward, Jessica J; Cohen, Paula E; Greally, John M; Wang, Jun; Bustamante, Carlos D; Boyko, Adam R

2013-01-01

The identification of the H3K4 trimethylase, PRDM9, as the gene responsible for recombination hotspot localization has provided considerable insight into the mechanisms by which recombination is initiated in mammals. However, uniquely amongst mammals, canids appear to lack a functional version of PRDM9 and may therefore provide a model for understanding recombination that occurs in the absence of PRDM9, and thus how PRDM9 functions to shape the recombination landscape. We have constructed a fine-scale genetic map from patterns of linkage disequilibrium assessed using high-throughput sequence data from 51 free-ranging dogs, Canis lupus familiaris. While broad-scale properties of recombination appear similar to other mammalian species, our fine-scale estimates indicate that canine highly elevated recombination rates are observed in the vicinity of CpG rich regions including gene promoter regions, but show little association with H3K4 trimethylation marks identified in spermatocytes. By comparison to genomic data from the Andean fox, Lycalopex culpaeus, we show that biased gene conversion is a plausible mechanism by which the high CpG content of the dog genome could have occurred.

A database of global marine commercial, small-scale, illegal and unreported fisheries catch 1950-2014

NASA Astrophysics Data System (ADS)

Watson, Reg A.

2017-04-01

Global fisheries landings data from a range of public sources was harmonised and mapped to 30-min spatial cells based on the distribution of the reported taxa and the fishing fleets involved. This data was extended to include the associated fishing gear used, as well as estimates of illegal, unregulated and unreported catch (IUU) and discards at sea. Expressed as catch rates, these results also separated small-scale fisheries from other fishing operations. The dataset covers 1950 to 2014 inclusive. Mapped catch allows study of the impacts of fisheries on habitats and fauna, on overlap with the diets of marine birds and mammals, and on the related use of fuels and release of greenhouse gases. The fine-scale spatial data can be aggregated to the exclusive economic zone claims of countries and will allow study of the value of landed marine products to their economies and food security, and to those of their trading partners.

A database of global marine commercial, small-scale, illegal and unreported fisheries catch 1950-2014.

PubMed

Watson, Reg A

2017-04-11

Global fisheries landings data from a range of public sources was harmonised and mapped to 30-min spatial cells based on the distribution of the reported taxa and the fishing fleets involved. This data was extended to include the associated fishing gear used, as well as estimates of illegal, unregulated and unreported catch (IUU) and discards at sea. Expressed as catch rates, these results also separated small-scale fisheries from other fishing operations. The dataset covers 1950 to 2014 inclusive. Mapped catch allows study of the impacts of fisheries on habitats and fauna, on overlap with the diets of marine birds and mammals, and on the related use of fuels and release of greenhouse gases. The fine-scale spatial data can be aggregated to the exclusive economic zone claims of countries and will allow study of the value of landed marine products to their economies and food security, and to those of their trading partners.

A database of global marine commercial, small-scale, illegal and unreported fisheries catch 1950–2014

PubMed Central

Watson, Reg A.

2017-01-01

Global fisheries landings data from a range of public sources was harmonised and mapped to 30-min spatial cells based on the distribution of the reported taxa and the fishing fleets involved. This data was extended to include the associated fishing gear used, as well as estimates of illegal, unregulated and unreported catch (IUU) and discards at sea. Expressed as catch rates, these results also separated small-scale fisheries from other fishing operations. The dataset covers 1950 to 2014 inclusive. Mapped catch allows study of the impacts of fisheries on habitats and fauna, on overlap with the diets of marine birds and mammals, and on the related use of fuels and release of greenhouse gases. The fine-scale spatial data can be aggregated to the exclusive economic zone claims of countries and will allow study of the value of landed marine products to their economies and food security, and to those of their trading partners. PMID:28398351

Combination of AUV high resolution mapping and submersible visual observations on the Guaymas Hydrothermal Fields (Southern Trough Ridge)

NASA Astrophysics Data System (ADS)

Ondreas, H.; Fouquet, Y.; Normand, A.; Rouxel, O.; Godfroy, A.

2011-12-01

The BIG cruise -leg I- was carried out on the Guaymas basin in June 2010 on board the French research vessel L'Atalante. An AUV high-resolution survey was made on the southern trough ridge to gather fine-scale bathymetry and acoustic imagery data. The results of the high resolution survey were used, the next days, to explore the vent's area during several Nautile dives. The southern trough hydrothermal fields of the Guaymas basin have often been studied. However, the local geological context was not really well-defined. During the AUV surveys, maps at 70 m above the seafloor were done over the hydrothermal area. The data were gridded at 2 m spacing. During the same cruise, Nautile dives help us to compare the field observations and the geological features revealed by the high resolution mapping and to investigate the fine-scale relationships between the vents and their geological environment. Integration of these data is made easier by the use of the GIS software technology. It helps us perpetuate data, undertake comparisons, combine different types of data, realize fine-scale geological mapping. Even if some problems are recurrent (precision of positioning, integration of old data...), such combinations of high resolution mapping and visual observations and sampling have changed our vision of hydrothermal geological context. In the Guaymas sedimented spreading axis, our new data show that major hydrothermal sites, in the south part of the southern trough only, are located inside or at the border of 100 to 250 m long, 60 to 150 m wide, 6 to 12 m deep small collapsed sub-circular depressions. The direction of the collapse is variable. Curved faults at the outer border of these depressions control the largest and mature edifices. Smaller, possibly younger, immature chimneys are located at the centre of some depressions. The mature hydrothermal structures appear as mounds up to 80 m in diameter, 20 m in high, each hydrothermal edifice being very-well identified on the 2 m resolution map. Classical high temperature chimneys are present but also areas of high temperature fluids percolating through the petroleum-rich sediment. Echosounder profiles, realized near the bottom with the AUV, show the root of some hydrothermal edifice 40 m down in the sediment and their link with the small depressions. The profiles also show normal faults buried in the sediment and the collapsed depression controlling the hydrothermal edifices. The bordering curved-faults appear as superficial features. To explain the local features seen on high resolution data, we propose a succession of process: i) collapse related to deep recent fissuration in the volcanic basement, ii) discharge controlled along the border of the sub-circular collapse structures and starting of chimneys construction, iii) maturation of the external edifices and collapse of the depression enhanced by mobilisation of sediment out of the depression by fluid discharge.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir

PubMed Central

Burnet, Jean-Baptiste; Ogorzaly, Leslie; Penny, Christian; Cauchie, Henry-Michel

2015-01-01

Background: The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Methods: Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Results: Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. Conclusion: This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies. PMID:26404350

Tracking fine-scale seasonal evolution of surface water extent in Central Alaska and the Canadian Shield

NASA Astrophysics Data System (ADS)

Cooley, S. W.; Smith, L. C.; Pitcher, L. H.; Pavelsky, T.; Topp, S.

2017-12-01

Quantifying spatial and temporal variability in surface water storage at high latitudes is critical for assessing environmental sensitivity to climate change. Traditionally the tradeoff between high spatial and high temporal resolution space-borne optical imagery has limited the ability to track fine-scale changes in surface water extent. However, the recent launch of hundreds of earth-imaging CubeSats by commercial satellite companies such as Planet opens up new possibilities for monitoring surface water from space. In this study we present a comparison of seasonal evolution of surface water extent in two study areas with differing geologic, hydrologic and permafrost regimes, namely, the Yukon Flats in Central Alaska and the Canadian Shield north of Yellowknife, N.W.T. Using near-daily 3m Planet CubeSat imagery, we track individual lake surface area from break-up to freeze-up during summer 2017 and quantify the spatial and temporal variability in inundation extent. We validate our water delineation method and inundation extent time series using WorldView imagery, coincident in situ lake shoreline mapping and pressure transducer data for 19 lakes in the Northwest Territories and Alaska collected during the NASA Arctic Boreal Vulnerability Experiment (ABoVE) 2017 field campaign. The results of this analysis demonstrate the value of CubeSat imagery for dynamic surface water research particularly at high latitudes and illuminate fine-scale drivers of cold regions surface water extent.

Map based navigation for autonomous underwater vehicles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tuohy, S.T.; Leonard, J.J.; Bellingham, J.G.

1995-12-31

In this work, a map based navigation algorithm is developed wherein measured geophysical properties are matched to a priori maps. The objectives is a complete algorithm applicable to a small, power-limited AUV which performs in real time to a required resolution with bounded position error. Interval B-Splines are introduced for the non-linear representation of two-dimensional geophysical parameters that have measurement uncertainty. Fine-scale position determination involves the solution of a system of nonlinear polynomial equations with interval coefficients. This system represents the complete set of possible vehicle locations and is formulated as the intersection of contours established on each map frommore » the simultaneous measurement of associated geophysical parameters. A standard filter mechanisms, based on a bounded interval error model, predicts the position of the vehicle and, therefore, screens extraneous solutions. When multiple solutions are found, a tracking mechanisms is applied until a unique vehicle location is determined.« less

Depth image super-resolution via semi self-taught learning framework

NASA Astrophysics Data System (ADS)

Zhao, Furong; Cao, Zhiguo; Xiao, Yang; Zhang, Xiaodi; Xian, Ke; Li, Ruibo

2017-06-01

Depth images have recently attracted much attention in computer vision and high-quality 3D content for 3DTV and 3D movies. In this paper, we present a new semi self-taught learning application framework for enhancing resolution of depth maps without making use of ancillary color images data at the target resolution, or multiple aligned depth maps. Our framework consists of cascade random forests reaching from coarse to fine results. We learn the surface information and structure transformations both from a small high-quality depth exemplars and the input depth map itself across different scales. Considering that edge plays an important role in depth map quality, we optimize an effective regularized objective that calculates on output image space and input edge space in random forests. Experiments show the effectiveness and superiority of our method against other techniques with or without applying aligned RGB information

Mapping the Active Vents of Stromboli Volcano with an Unmanned Aerial Vehicle

NASA Astrophysics Data System (ADS)

Turner, N.; Houghton, B. F.; von der Lieth, J.; Hort, M. K.; Taddeucci, J.; Kueppers, U.; Ricci, T.; Gaudin, D.

2016-12-01

We present a new detailed map of the active vents of Stromboli volcano obtained from UAV flights in May 2016, when the active NE and SW craters were repeatedly mapped. Due to high levels of gas emissions and frequent explosions, fine-scale measurements of vent geometry from single flights were challenging. However, the compilation of data acquired over 12 flights used with Structure from Motion software allowed us to create a 10 cm Digital Elevation Model (DEM) offering a non-obstructed view into the active craters. Such direct observations permits us to constrain parameters such as vent geometry and depth with an unprecedented precision, thus potentially reducing the uncertainty of models depending on such inputs (e.g. conduit and acoustic models). Furthermore, the low-cost and safety of UAVs allows mapping changes at small temporal and spatial resolutions, making this technique complementary to monitoring efforts at active volcanoes.

STarlight Absorption Reduction through a Survey of Multiple Occulting Galaxies (STARSMOG)

NASA Astrophysics Data System (ADS)

Holwerda, Benne

2014-10-01

Dust absorption remains the poorest constrained parameter in both Cosmological distances and multi-wavelength studies of galaxy populations. A galaxy's dust distribution can be measured to great accuracy in the case of an overlapping pair of galaxies, i.e., when a foreground spiral galaxy accidentally overlaps a more distant, preferably elliptical galaxy. We have identified over 300 bona-fide overlapping pairs --well separated in redshift but close on the sky-- in the GAMA spectroscopic survey, taking advantage of its high completeness (98%) on small scales. We propose to map the fine-scale (~50pc) dust structure in these occulting galaxies, using HST/WFC3 SNAP observations. The resulting dust maps will (1) serve as an extinction probability for supernova lightcurve fits in similar type host galaxies, (2) strongly constrain the role of ISM structure in Spectral Energy Distribution models of spiral galaxies, and (3) map the level of ISM turbulence (through the spatial power-spectrum). We ask for SNAP observations with a parent list of 355 targets to ensure a complete and comprehensive coverage of each foreground galaxy mass, radius and inclination. The resulting extinction maps will serve as a library for SNIa measurements, galaxy SED modelling and ISM turbulence measurements.

Geology of Holden Crater and the Holden and Ladon Multi-Ring Impact Basins, Margaritifer Terra, Mars

NASA Technical Reports Server (NTRS)

Irwin, R. P., III; Grant, J. A.

2008-01-01

Geologic mapping at 1:500K scale of Mars quads 15s027, 20s027, 25s027, and 25s032 (Fig. 1) is in progress to constrain the geologic and geomorphic history of southwestern Margaritifer Terra. This work builds on earlier maps at 1:5M [1] and 1:15M scales [2], recent to concurrent 1:500Kscale mapping of adjacent areas to the east [3-5], and studies of drainage basin evolution along the Uzboi-Ladon-M (ULM; the third valley in the sequence has no formal name) Valles basin overflow system and nearby watersheds [6-9]. Two of the six landing sites under consideration for the Mars Science Laboratory rover are in this map area, targeting finely layered, phyllosilicate-rich strata and alluvial fans in Holden crater [10-12] (26degS, 34degW, 150 km diameter) or deposits southeast of a likely delta in Eberswalde crater [13-16] (24degS, 33degW, 50 km in diameter). Diverse processes including larger and smaller impacts, a wide range in fluvial activity, and local to regional structural influences have all affected the surface morphology.

Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

PubMed

Gogol-Prokurat, Melanie

2011-01-01

If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables were not available at large extents. No single model met all habitat prioritization criteria, and the best models were overlaid to identify consensus areas of high suitability. Although the four species modeled here co-occur and are treated together for conservation planning, model accuracy and predicted suitable areas varied among species.

Integrating population dynamics into mapping human exposure to seismic hazard

NASA Astrophysics Data System (ADS)

Freire, S.; Aubrecht, C.

2012-11-01

Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.

Heritability maps of human face morphology through large-scale automated three-dimensional phenotyping

NASA Astrophysics Data System (ADS)

Tsagkrasoulis, Dimosthenis; Hysi, Pirro; Spector, Tim; Montana, Giovanni

2017-04-01

The human face is a complex trait under strong genetic control, as evidenced by the striking visual similarity between twins. Nevertheless, heritability estimates of facial traits have often been surprisingly low or difficult to replicate. Furthermore, the construction of facial phenotypes that correspond to naturally perceived facial features remains largely a mystery. We present here a large-scale heritability study of face geometry that aims to address these issues. High-resolution, three-dimensional facial models have been acquired on a cohort of 952 twins recruited from the TwinsUK registry, and processed through a novel landmarking workflow, GESSA (Geodesic Ensemble Surface Sampling Algorithm). The algorithm places thousands of landmarks throughout the facial surface and automatically establishes point-wise correspondence across faces. These landmarks enabled us to intuitively characterize facial geometry at a fine level of detail through curvature measurements, yielding accurate heritability maps of the human face (www.heritabilitymaps.info).

Individual Brain Charting, a high-resolution fMRI dataset for cognitive mapping.

PubMed

Pinho, Ana Luísa; Amadon, Alexis; Ruest, Torsten; Fabre, Murielle; Dohmatob, Elvis; Denghien, Isabelle; Ginisty, Chantal; Becuwe-Desmidt, Séverine; Roger, Séverine; Laurier, Laurence; Joly-Testault, Véronique; Médiouni-Cloarec, Gaëlle; Doublé, Christine; Martins, Bernadette; Pinel, Philippe; Eger, Evelyn; Varoquaux, Gaël; Pallier, Christophe; Dehaene, Stanislas; Hertz-Pannier, Lucie; Thirion, Bertrand

2018-06-12

Functional Magnetic Resonance Imaging (fMRI) has furthered brain mapping on perceptual, motor, as well as higher-level cognitive functions. However, to date, no data collection has systematically addressed the functional mapping of cognitive mechanisms at a fine spatial scale. The Individual Brain Charting (IBC) project stands for a high-resolution multi-task fMRI dataset that intends to provide the objective basis toward a comprehensive functional atlas of the human brain. The data refer to a cohort of 12 participants performing many different tasks. The large amount of task-fMRI data on the same subjects yields a precise mapping of the underlying functions, free from both inter-subject and inter-site variability. The present article gives a detailed description of the first release of the IBC dataset. It comprises a dozen of tasks, addressing both low- and high- level cognitive functions. This openly available dataset is thus intended to become a reference for cognitive brain mapping.

Non-coding genomic regions possessing enhancer and silencer potential are associated with healthy aging and exceptional survival.

PubMed

Kim, Sangkyu; Welsh, David A; Myers, Leann; Cherry, Katie E; Wyckoff, Jennifer; Jazwinski, S Michal

2015-02-28

We have completed a genome-wide linkage scan for healthy aging using data collected from a family study, followed by fine-mapping by association in a separate population, the first such attempt reported. The family cohort consisted of parents of age 90 or above and their children ranging in age from 50 to 80. As a quantitative measure of healthy aging, we used a frailty index, called FI34, based on 34 health and function variables. The linkage scan found a single significant linkage peak on chromosome 12. Using an independent cohort of unrelated nonagenarians, we carried out a fine-scale association mapping of the region suggestive of linkage and identified three sites associated with healthy aging. These healthy-aging sites (HASs) are located in intergenic regions at 12q13-14. HAS-1 has been previously associated with multiple diseases, and an enhancer was recently mapped and experimentally validated within the site. HAS-2 is a previously uncharacterized site possessing genomic features suggestive of enhancer activity. HAS-3 contains features associated with Polycomb repression. The HASs also contain variants associated with exceptional longevity, based on a separate analysis. Our results provide insight into functional genomic networks involving non-coding regulatory elements that are involved in healthy aging and longevity.

Non-coding genomic regions possessing enhancer and silencer potential are associated with healthy aging and exceptional survival

PubMed Central

Kim, Sangkyu; Welsh, David A.; Myers, Leann; Cherry, Katie E.; Wyckoff, Jennifer; Jazwinski, S. Michal

2015-01-01

We have completed a genome-wide linkage scan for healthy aging using data collected from a family study, followed by fine-mapping by association in a separate population, the first such attempt reported. The family cohort consisted of parents of age 90 or above and their children ranging in age from 50 to 80. As a quantitative measure of healthy aging, we used a frailty index, called FI34, based on 34 health and function variables. The linkage scan found a single significant linkage peak on chromosome 12. Using an independent cohort of unrelated nonagenarians, we carried out a fine-scale association mapping of the region suggestive of linkage and identified three sites associated with healthy aging. These healthy-aging sites (HASs) are located in intergenic regions at 12q13–14. HAS-1 has been previously associated with multiple diseases, and an enhancer was recently mapped and experimentally validated within the site. HAS-2 is a previously uncharacterized site possessing genomic features suggestive of enhancer activity. HAS-3 contains features associated with Polycomb repression. The HASs also contain variants associated with exceptional longevity, based on a separate analysis. Our results provide insight into functional genomic networks involving non-coding regulatory elements that are involved in healthy aging and longevity. PMID:25682868

Rapid Fine Conformational Epitope Mapping Using Comprehensive Mutagenesis and Deep Sequencing*

PubMed Central

Kowalsky, Caitlin A.; Faber, Matthew S.; Nath, Aritro; Dann, Hailey E.; Kelly, Vince W.; Liu, Li; Shanker, Purva; Wagner, Ellen K.; Maynard, Jennifer A.; Chan, Christina; Whitehead, Timothy A.

2015-01-01

Knowledge of the fine location of neutralizing and non-neutralizing epitopes on human pathogens affords a better understanding of the structural basis of antibody efficacy, which will expedite rational design of vaccines, prophylactics, and therapeutics. However, full utilization of the wealth of information from single cell techniques and antibody repertoire sequencing awaits the development of a high throughput, inexpensive method to map the conformational epitopes for antibody-antigen interactions. Here we show such an approach that combines comprehensive mutagenesis, cell surface display, and DNA deep sequencing. We develop analytical equations to identify epitope positions and show the method effectiveness by mapping the fine epitope for different antibodies targeting TNF, pertussis toxin, and the cancer target TROP2. In all three cases, the experimentally determined conformational epitope was consistent with previous experimental datasets, confirming the reliability of the experimental pipeline. Once the comprehensive library is generated, fine conformational epitope maps can be prepared at a rate of four per day. PMID:26296891

[Fine mapping of complex disease susceptibility loci].

PubMed

Song, Qingfeng; Zhang, Hongxing; Ma, Yilong; Zhou, Gangqiao

2014-01-01

Genome-wide association studies (GWAS) using single nucleotide polymorphism (SNP) markers have identified more than 3800 susceptibility loci for more than 660 diseases or traits. However, the most significantly associated variants or causative variants in these loci and their biological functions have remained to be clarified. These causative variants can help to elucidate the pathogenesis and discover new biomarkers of complex diseases. One of the main goals in the post-GWAS era is to identify the causative variants and susceptibility genes, and clarify their functional aspects by fine mapping. For common variants, imputation or re-sequencing based strategies were implemented to increase the number of analyzed variants and help to identify the most significantly associated variants. In addition, functional element, expression quantitative trait locus (eQTL) and haplotype analyses were performed to identify functional common variants and susceptibility genes. For rare variants, fine mapping was carried out by re-sequencing, rare haplotype analysis, family-based analysis, burden test, etc.This review summarizes the strategies and problems for fine mapping.

High Resolution Insights into Snow Distribution Provided by Drone Photogrammetry

NASA Astrophysics Data System (ADS)

Redpath, T.; Sirguey, P. J.; Cullen, N. J.; Fitzsimons, S.

2017-12-01

Dynamic in time and space, New Zealand's seasonal snow is largely confined to remote alpine areas, complicating ongoing in situ measurement and characterisation. Improved understanding and modeling of the seasonal snowpack requires fine scale resolution of snow distribution and spatial variability. The potential of remotely piloted aircraft system (RPAS) photogrammetry to resolve spatial and temporal variability of snow depth and water equivalent in a New Zealand alpine catchment is assessed in the Pisa Range, Central Otago. This approach yielded orthophotomosaics and digital surface models (DSM) at 0.05 and 0.15 m spatial resolution, respectively. An autumn reference DSM allowed mapping of winter (02/08/2016) and spring (10/09/2016) snow depth at 0.15 m spatial resolution, via DSM differencing. The consistency and accuracy of the RPAS-derived surface was assessed by comparison of snow-free regions of the spring and autumn DSMs, while accuracy of RPAS retrieved snow depth was assessed with 86 in situ snow probe measurements. Results show a mean vertical residual of 0.024 m between DSMs acquired in autumn and spring. This residual approximated a Laplace distribution, reflecting the influence of large outliers on the small overall bias. Propagation of errors associated with successive DSMs saw snow depth mapped with an accuracy of ± 0.09 m (95% c.l.). Comparing RPAS and in situ snow depth measurements revealed the influence of geo-location uncertainty and interactions between vegetation and the snowpack on snow depth uncertainty and bias. Semi-variogram analysis revealed that the RPAS outperformed systematic in situ measurements in resolving fine scale spatial variability. Despite limitations accompanying RPAS photogrammetry, this study demonstrates a repeatable means of accurately mapping snow depth for an entire, yet relatively small, hydrological basin ( 0.5 km2), at high resolution. Resolving snowpack features associated with re-distribution and preferential accumulation and ablation, snow depth maps provide geostatistically robust insights into seasonal snow processes, with unprecedented detail. Such data may enhance understanding of physical processes controlling spatial and temporal distribution of seasonal snow, and their relative importance at varying spatial and temporal scales.

An Integrated Genomic Approach for Rapid Delineation of Candidate Genes Regulating Agro-Morphological Traits in Chickpea

PubMed Central

Saxena, Maneesha S.; Bajaj, Deepak; Das, Shouvik; Kujur, Alice; Kumar, Vinod; Singh, Mohar; Bansal, Kailash C.; Tyagi, Akhilesh K.; Parida, Swarup K.

2014-01-01

The identification and fine mapping of robust quantitative trait loci (QTLs)/genes governing important agro-morphological traits in chickpea still lacks systematic efforts at a genome-wide scale involving wild Cicer accessions. In this context, an 834 simple sequence repeat and single-nucleotide polymorphism marker-based high-density genetic linkage map between cultivated and wild parental accessions (Cicer arietinum desi cv. ICC 4958 and Cicer reticulatum wild cv. ICC 17160) was constructed. This inter-specific genetic map comprising eight linkage groups spanned a map length of 949.4 cM with an average inter-marker distance of 1.14 cM. Eleven novel major genomic regions harbouring 15 robust QTLs (15.6–39.8% R2 at 4.2–15.7 logarithm of odds) associated with four agro-morphological traits (100-seed weight, pod and branch number/plant and plant hairiness) were identified and mapped on chickpea chromosomes. Most of these QTLs showed positive additive gene effects with effective allelic contribution from ICC 4958, particularly for increasing seed weight (SW) and pod and branch number. One robust SW-influencing major QTL region (qSW4.2) has been narrowed down by combining QTL mapping with high-resolution QTL region-specific association analysis, differential expression profiling and gene haplotype-based association/LD mapping. This enabled to delineate a strong SW-regulating ABI3VP1 transcription factor (TF) gene at trait-specific QTL interval and consequently identified favourable natural allelic variants and superior high seed weight-specific haplotypes in the upstream regulatory region of this gene showing increased transcript expression during seed development. The genes (TFs) harbouring diverse trait-regulating QTLs, once validated and fine-mapped by our developed rapid integrated genomic approach and through gene/QTL map-based cloning, can be utilized as potential candidates for marker-assisted genetic enhancement of chickpea. PMID:25335477

Scattering - a probe to Earth's small scale structure

NASA Astrophysics Data System (ADS)

Rost, S.; Earle, P.

2009-05-01

Much of the short-period teleseismic wavefield shows strong evidence for scattered waves in extended codas trailing the main arrivals predicted by ray theory. This energy mainly originates from high-frequency body waves interacting with fine-scale volumetric heterogeneities in the Earth. Studies of this energy revealed much of what we know about Earth's structure at scale lengths around 10 km throughout the Earth from crust to core. From these data we can gain important information about the mineral-physical and geochemical constitution of the Earth that is inaccessible to many other seismic imaging techniques. Previous studies used scattered energy related to PKP, PKiKP, and Pdiff to identify and map the small-scale structure of the mantle and core. We will present observations related to the core phases PKKP and P'P' to study fine-scale mantle heterogeneities. These phases are maximum travel-time phases with respect to perturbations at their reflection points. This allows observation of the scattered energy as precursors to the main phase avoiding common problems with traditional coda phases which arrive after the main pulse. The precursory arrival of the scattered energy allows the separation between deep Earth and crustal contributions to the scattered wavefield for certain source-receiver configurations. Using the information from these scattered phases we identify regions of the mantle that shows increased scattering potential likely linked to larger scale mantle structure identified in seismic tomography and geodynamical models.

On the ecological relevance of landscape mapping and its application in the spatial planning of very large marine protected areas.

PubMed

Hogg, Oliver T; Huvenne, Veerle A I; Griffiths, Huw J; Linse, Katrin

2018-06-01

In recent years very large marine protected areas (VLMPAs) have become the dominant form of spatial protection in the marine environment. Whilst seen as a holistic and geopolitically achievable approach to conservation, there is currently a mismatch between the size of VLMPAs, and the data available to underpin their establishment and inform on their management. Habitat mapping has increasingly been adopted as a means of addressing paucity in biological data, through use of environmental proxies to estimate species and community distribution. Small-scale studies have demonstrated environmental-biological links in marine systems. Such links, however, are rarely demonstrated across larger spatial scales in the benthic environment. As such, the utility of habitat mapping as an effective approach to the ecosystem-based management of VLMPAs remains, thus far, largely undetermined. The aim of this study was to assess the ecological relevance of broadscale landscape mapping. Specifically we test the relationship between broad-scale marine landscapes and the structure of their benthic faunal communities. We focussed our work at the sub-Antarctic island of South Georgia, site of one of the largest MPAs in the world. We demonstrate a statistically significant relationship between environmentally derived landscape mapping clusters, and the composition of presence-only species data from the region. To demonstrate this relationship required specific re-sampling of historical species occurrence data to balance biological rarity, biological cosmopolitism, range-restricted sampling and fine-scale heterogeneity between sampling stations. The relationship reveals a distinct biological signature in the faunal composition of individual landscapes, attributing ecological relevance to South Georgia's environmentally derived marine landscape map. We argue therefore, that landscape mapping represents an effective framework for ensuring representative protection of habitats in management plans. Such scientific underpinning of marine spatial planning is critical in balancing the needs of multiple stakeholders whilst maximising conservation payoff. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

The potential for LiDAR technology to map fire fuel hazard over large areas of Australian forest.

PubMed

Price, Owen F; Gordon, Christopher E

2016-10-01

Fuel load is a primary determinant of fire spread in Australian forests. In east Australian forests, litter and canopy fuel loads and hence fire hazard are thought to be highest at and beyond steady-state fuel loads 15-20 years post-fire. Current methods used to predict fuel loads often rely on course-scale vegetation maps and simple time-since-fire relationships which mask fine-scale processes influencing fuel loads. Here we use Light Detecting and Remote Sensing technology (LiDAR) and field surveys to quantify post-fire mid-story and crown canopy fuel accumulation and fire hazard in Dry Sclerophyll Forests of the Sydney Basin (Australia) at fine spatial-scales (20 × 20 m cell resolution). Fuel cover was quantified in three strata important for crown fire propagation (0.5-4 m, 4-15 m, >15 m) over a 144 km(2) area subject to varying fire fuel ages. Our results show that 1) LiDAR provided a precise measurement of fuel cover in each strata and a less precise but still useful predictor of surface fuels, 2) cover varied greatly within a mapped vegetation class of the same fuel age, particularly for elevated fuel, 3) time-since-fire was a poor predictor of fuel cover and crown fire hazard because fuel loads important for crown fire propagation were variable over a range of fire fuel ages between 2 and 38 years post-fire, and 4) fuel loads and fire hazard can be high in the years immediately following fire. Our results show the benefits of spatially and temporally specific in situ fuel sampling methods such as LiDAR, and are widely applicable for fire management actions which aim to decrease human and environmental losses due to wildfire. Copyright © 2016 Elsevier Ltd. All rights reserved.

Correspondence between solar fine-scale structures in the corona, transition region, and lower atmosphere from collaborative observations

NASA Technical Reports Server (NTRS)

Moses, J. Daniel; Cook, J. W.; Bartoe, J.-D. F.; Brueckner, G. E.; Dere, K. P.; Webb, D. F.; Davis, John M.; Recely, F.; Martin, S. F.; Zirin, H.

1989-01-01

The Soft X-Ray Imaging Payload and the High Resolution Telescope and Spectrograph (HRTS) instrument were launched from White Sands on 11 December 1987 in coordinated sounding rocket flights to investigate the correspondence of coronal and transition region structures, especially the relationship between X-ray bright points (XBPs) and transition region small spatial scale energetic events. The coaligned data from X-ray images are presented along with maps of sites of transition region energetic events observed in C IV (100,000 K), HRTS 1600 A spectroheliograms of the T sub min region and ground based magnetogram and He I 10830 A images.

Small-Scale Tropopause Dynamics and TOMS Total Ozone

NASA Technical Reports Server (NTRS)

Stanford, John L.

2002-01-01

This project used Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) along-track ozone retrievals, in conjunction with ancillary meteorological fields and modeling studies, for high resolution investigations of upper troposphere and lower stratosphere dynamics. Specifically, high resolution along-track (Level 2) EP TOMS data were used to investigate the beautiful fine-scale structure in constituent and meteorological fields prominent in the evolution of highly non-linear baroclinic storm systems. Comparison was made with high resolution meteorological models. The analyses provide internal consistency checks and validation of the EP TOMS data which are vital for monitoring ozone depletion in both polar and midlatitude regions.

Compiling and Mapping Global Permeability of the Unconsolidated and Consolidated Earth: GLobal HYdrogeology MaPS 2.0 (GLHYMPS 2.0)

NASA Astrophysics Data System (ADS)

Huscroft, Jordan; Gleeson, Tom; Hartmann, Jens; Börker, Janine

2018-02-01

The spatial distribution of subsurface parameters such as permeability are increasingly relevant for regional to global climate, land surface, and hydrologic models that are integrating groundwater dynamics and interactions. Despite the large fraction of unconsolidated sediments on Earth's surface with a wide range of permeability values, current global, high-resolution permeability maps distinguish solely fine-grained and coarse-grained unconsolidated sediments. Representative permeability values are derived for a wide variety of unconsolidated sediments and applied to a new global map of unconsolidated sediments to produce the first geologically constrained, two-layer global map of shallower and deeper permeability. The new mean logarithmic permeability of the Earth's surface is -12.7 ± 1.7 m2 being 1 order of magnitude higher than that derived from previous maps, which is consistent with the dominance of the coarser sediments. The new data set will benefit a variety of scientific applications including the next generation of climate, land surface, and hydrology models at regional to global scales.

Evaluation of seabed mapping methods for fine-scale classification of extremely shallow benthic habitats - Application to the Venice Lagoon, Italy

NASA Astrophysics Data System (ADS)

Montereale Gavazzi, G.; Madricardo, F.; Janowski, L.; Kruss, A.; Blondel, P.; Sigovini, M.; Foglini, F.

2016-03-01

Recent technological developments of multibeam echosounder systems (MBES) allow mapping of benthic habitats with unprecedented detail. MBES can now be employed in extremely shallow waters, challenging data acquisition (as these instruments were often designed for deeper waters) and data interpretation (honed on datasets with resolution sometimes orders of magnitude lower). With extremely high-resolution bathymetry and co-located backscatter data, it is now possible to map the spatial distribution of fine scale benthic habitats, even identifying the acoustic signatures of single sponges. In this context, it is necessary to understand which of the commonly used segmentation methods is best suited to account for such level of detail. At the same time, new sampling protocols for precisely geo-referenced ground truth data need to be developed to validate the benthic environmental classification. This study focuses on a dataset collected in a shallow (2-10 m deep) tidal channel of the Lagoon of Venice, Italy. Using 0.05-m and 0.2-m raster grids, we compared a range of classifications, both pixel-based and object-based approaches, including manual, Maximum Likelihood Classifier, Jenks Optimization clustering, textural analysis and Object Based Image Analysis. Through a comprehensive and accurately geo-referenced ground truth dataset, we were able to identify five different classes of the substrate composition, including sponges, mixed submerged aquatic vegetation, mixed detritic bottom (fine and coarse) and unconsolidated bare sediment. We computed estimates of accuracy (namely Overall, User, Producer Accuracies and the Kappa statistic) by cross tabulating predicted and reference instances. Overall, pixel based segmentations produced the highest accuracies and the accuracy assessment is strongly dependent on the number of classes chosen for the thematic output. Tidal channels in the Venice Lagoon are extremely important in terms of habitats and sediment distribution, particularly within the context of the new tidal barrier being built. However, they had remained largely unexplored until now, because of the surveying challenges. The application of this remote sensing approach, combined with targeted sampling, opens a new perspective in the monitoring of benthic habitats in view of a knowledge-based management of natural resources in shallow coastal areas.

Using Moss to Detect Fine-Scaled Deposition of Heavy Metals in Urban Environments

NASA Astrophysics Data System (ADS)

Jovan, S.; Donovan, G.; Demetrios, G.; Monleon, V. J.; Amacher, M. C.

2017-12-01

Mosses are commonly used as bio-indicators of heavy metal deposition to forests. Their application in urban airsheds is relatively rare. Our objective was to develop fine-scaled, city-wide maps for heavy metals in Portland, Oregon, to identify pollution "hotspots" and serve as a screening tool for more effective placement of air quality monitoring instruments. In 2013 we measured twenty-two elements in epiphytic moss sampled on a 1km x1km sampling grid (n = 346). We detected large hotspots of cadmium and arsenic in two neighborhoods associated with stained glass manufacturers. Air instruments deployed by local regulators measured cadmium concentrations 49 times and arsenic levels 155 times the state health benchmarks. Moss maps also detected a large nickel hotspot in a neighborhood near a forge where air instruments later measured concentrations 4 times the health benchmark. In response, the facilities implemented new pollution controls, air quality improved in all three affected neighborhoods, revision of regulations for stained glass furnace emissions are underway, and Oregon's governor launched an initiative to develop health-based (vs technology-based) regulations for air toxics in the state. The moss maps also indicated a couple dozen smaller hotspots of heavy metals, including lead, chromium, and cobalt, in Portland neighborhoods. Ongoing follow-up work includes: 1) use of moss sampling by local regulators to investigate source and extent of the smaller hotspots, 2) use of lead isotopes to determine origins of higher lead levels observed in moss collected from the inner city, and 3) co-location of air instruments and moss sampling to determine accuracy, timeframe represented, and seasonality of heavy metals in moss.

A generic method for improving the spatial interoperability of medical and ecological databases.

PubMed

Ghenassia, A; Beuscart, J B; Ficheur, G; Occelli, F; Babykina, E; Chazard, E; Genin, M

2017-10-03

The availability of big data in healthcare and the intensive development of data reuse and georeferencing have opened up perspectives for health spatial analysis. However, fine-scale spatial studies of ecological and medical databases are limited by the change of support problem and thus a lack of spatial unit interoperability. The use of spatial disaggregation methods to solve this problem introduces errors into the spatial estimations. Here, we present a generic, two-step method for merging medical and ecological databases that avoids the use of spatial disaggregation methods, while maximizing the spatial resolution. Firstly, a mapping table is created after one or more transition matrices have been defined. The latter link the spatial units of the original databases to the spatial units of the final database. Secondly, the mapping table is validated by (1) comparing the covariates contained in the two original databases, and (2) checking the spatial validity with a spatial continuity criterion and a spatial resolution index. We used our novel method to merge a medical database (the French national diagnosis-related group database, containing 5644 spatial units) with an ecological database (produced by the French National Institute of Statistics and Economic Studies, and containing with 36,594 spatial units). The mapping table yielded 5632 final spatial units. The mapping table's validity was evaluated by comparing the number of births in the medical database and the ecological databases in each final spatial unit. The median [interquartile range] relative difference was 2.3% [0; 5.7]. The spatial continuity criterion was low (2.4%), and the spatial resolution index was greater than for most French administrative areas. Our innovative approach improves interoperability between medical and ecological databases and facilitates fine-scale spatial analyses. We have shown that disaggregation models and large aggregation techniques are not necessarily the best ways to tackle the change of support problem.

Multi-scale functional mapping of tidal marsh vegetation for restoration monitoring

NASA Astrophysics Data System (ADS)

Tuxen Bettman, Karin

2007-12-01

Nearly half of the world's natural wetlands have been destroyed or degraded, and in recent years, there have been significant endeavors to restore wetland habitat throughout the world. Detailed mapping of restoring wetlands can offer valuable information about changes in vegetation and geomorphology, which can inform the restoration process and ultimately help to improve chances of restoration success. I studied six tidal marshes in the San Francisco Estuary, CA, US, between 2003 and 2004 in order to develop techniques for mapping tidal marshes at multiple scales by incorporating specific restoration objectives for improved longer term monitoring. I explored a "pixel-based" remote sensing image analysis method for mapping vegetation in restored and natural tidal marshes, describing the benefits and limitations of this type of approach (Chapter 2). I also performed a multi-scale analysis of vegetation pattern metrics for a recently restored tidal marsh in order to target the metrics that are consistent across scales and will be robust measures of marsh vegetation change (Chapter 3). Finally, I performed an "object-based" image analysis using the same remotely sensed imagery, which maps vegetation type and specific wetland functions at multiple scales (Chapter 4). The combined results of my work highlight important trends and management implications for monitoring wetland restoration using remote sensing, and will better enable restoration ecologists to use remote sensing for tidal marsh monitoring. Several findings important for tidal marsh restoration monitoring were made. Overall results showed that pixel-based methods are effective at quantifying landscape changes in composition and diversity in recently restored marshes, but are limited in their use for quantifying smaller, more fine-scale changes. While pattern metrics can highlight small but important changes in vegetation composition and configuration across years, scientists should exercise caution when using metrics in their studies or to validate restoration management decisions, and multi-scale analyses should be performed before metrics are used in restoration science for important management decisions. Lastly, restoration objectives, ecosystem function, and scale can each be integrated into monitoring techniques using remote sensing for improved restoration monitoring.

Frontiers in Sedimentary Geology: Microstructure of Fine-Grained Sediments from Mud to Shale

DTIC Science & Technology

1990-01-01

observations at the East Pacific cal Society of America Bulletin. v. 92. p. 212-218. Rise , 8°45’ N , and some interpretations. In: Rosendahl. BR.. R...in the basin east of Shatski Rise . Scale = t Pm. Burial diagenesis processes involve (I) postdepositional/mech- enables the investigator to determine...commonly used in the field. 50N Figure 15.1. Map of the eastern equatorial North Pacific Ocean showing the Results kation of Site H The East Pacific Rise

Fine-scale population structure of Malays in Peninsular Malaysia and Singapore and implications for association studies.

PubMed

Hoh, Boon-Peng; Deng, Lian; Julia-Ashazila, Mat Jusoh; Zuraihan, Zakaria; Nur-Hasnah, Ma'amor; Nur-Shafawati, Ab Rajab; Hatin, Wan Isa; Endom, Ismail; Zilfalil, Bin Alwi; Khalid, Yusoff; Xu, Shuhua

2015-07-22

Fine scale population structure of Malays - the major population in Malaysia, has not been well studied. This may have important implications for both evolutionary and medical studies. Here, we investigated the population sub-structure of Malay involving 431 samples collected from all states from peninsular Malaysia and Singapore. We identified two major clusters of individuals corresponding to the north and south peninsular Malaysia. On an even finer scale, the genetic coordinates of the geographical Malay populations are in correlation with the latitudes (R(2) = 0.3925; P = 0.029). This finding is further supported by the pairwise FST of Malay sub-populations, of which the north and south regions showed the highest differentiation (FST [North-south] = 0.0011). The collective findings therefore suggest that population sub-structure of Malays are more heterogenous than previously expected even within a small geographical region, possibly due to factors like different genetic origins, geographical isolation, could result in spurious association as demonstrated in our analysis. We suggest that cautions should be taken during the stage of study design or interpreting the association signals in disease mapping studies which are expected to be conducted in Malay population in the near future.

Genetic Recombination Is Targeted towards Gene Promoter Regions in Dogs

PubMed Central

Auton, Adam; Rui Li, Ying; Kidd, Jeffrey; Oliveira, Kyle; Nadel, Julie; Holloway, J. Kim; Hayward, Jessica J.; Cohen, Paula E.; Greally, John M.; Wang, Jun; Bustamante, Carlos D.; Boyko, Adam R.

2013-01-01

The identification of the H3K4 trimethylase, PRDM9, as the gene responsible for recombination hotspot localization has provided considerable insight into the mechanisms by which recombination is initiated in mammals. However, uniquely amongst mammals, canids appear to lack a functional version of PRDM9 and may therefore provide a model for understanding recombination that occurs in the absence of PRDM9, and thus how PRDM9 functions to shape the recombination landscape. We have constructed a fine-scale genetic map from patterns of linkage disequilibrium assessed using high-throughput sequence data from 51 free-ranging dogs, Canis lupus familiaris. While broad-scale properties of recombination appear similar to other mammalian species, our fine-scale estimates indicate that canine highly elevated recombination rates are observed in the vicinity of CpG rich regions including gene promoter regions, but show little association with H3K4 trimethylation marks identified in spermatocytes. By comparison to genomic data from the Andean fox, Lycalopex culpaeus, we show that biased gene conversion is a plausible mechanism by which the high CpG content of the dog genome could have occurred. PMID:24348265

A coarse-to-fine approach for pericardial effusion localization and segmentation in chest CT scans

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Chellamuthu, Karthik; Lu, Le; Bagheri, Mohammadhadi; Summers, Ronald M.

2018-02-01

Pericardial effusion on CT scans demonstrates very high shape and volume variability and very low contrast to adjacent structures. This inhibits traditional automated segmentation methods from achieving high accuracies. Deep neural networks have been widely used for image segmentation in CT scans. In this work, we present a two-stage method for pericardial effusion localization and segmentation. For the first step, we localize the pericardial area from the entire CT volume, providing a reliable bounding box for the more refined segmentation step. A coarse-scaled holistically-nested convolutional networks (HNN) model is trained on entire CT volume. The resulting HNN per-pixel probability maps are then threshold to produce a bounding box covering the pericardial area. For the second step, a fine-scaled HNN model is trained only on the bounding box region for effusion segmentation to reduce the background distraction. Quantitative evaluation is performed on a dataset of 25 CT scans of patient (1206 images) with pericardial effusion. The segmentation accuracy of our two-stage method, measured by Dice Similarity Coefficient (DSC), is 75.59+/-12.04%, which is significantly better than the segmentation accuracy (62.74+/-15.20%) of only using the coarse-scaled HNN model.

Fine-scale mapping of the 4q24 locus identifies two independent loci associated with breast cancer risk.

PubMed

Guo, Xingyi; Long, Jirong; Zeng, Chenjie; Michailidou, Kyriaki; Ghoussaini, Maya; Bolla, Manjeet K; Wang, Qin; Milne, Roger L; Shu, Xiao-Ou; Cai, Qiuyin; Beesley, Jonathan; Kar, Siddhartha P; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Beeghly-Fadiel, Alicia; Benitez, Javier; Blot, William; Bogdanova, Natalia; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Brinton, Louise; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Cai, Hui; Canisius, Sander; Chang-Claude, Jenny; Choi, Ji-Yeob; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Darabi, Hatef; Devilee, Peter; Droit, Arnaud; Dörk, Thilo; Fasching, Peter A; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gaborieau, Valerie; García-Closas, Montserrat; Giles, Graham G; Grip, Mervi; Guénel, Pascal; Haiman, Christopher A; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L; Hsiung, Chia-Ni; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kabisch, Maria; Kang, Daehee; Khan, Sofia; Knight, Julia A; Kosma, Veli-Matti; Lambrechts, Diether; Le Marchand, Loic; Li, Jingmei; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Marme, Frederik; Matsuo, Keitaro; McLean, Catriona A; Meindl, Alfons; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Nord, Silje; Olson, Janet E; Orr, Nick; Peterlongo, Paolo; Putti, Thomas Choudary; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Shen, Chen-Yang; Shi, Jiajun; Shrubsole, Martha J; Southey, Melissa C; Swerdlow, Anthony; Teo, Soo Hwang; Thienpont, Bernard; Toland, Amanda Ewart; Tollenaar, Robert A E M; Tomlinson, Ian P M; Truong, Thérèse; Tseng, Chiu-Chen; van den Ouweland, Ans; Wen, Wanqing; Winqvist, Robert; Wu, Anna; Yip, Cheng Har; Zamora, M Pilar; Zheng, Ying; Hall, Per; Pharoah, Paul D P; Simard, Jacques; Chenevix-Trench, Georgia; Dunning, Alison M; Easton, Douglas F; Zheng, Wei

2015-11-01

A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10(-4); OR, 1.04; 95% confidence interval (CI), 1.02-1.07] and rs77928427 (P = 1.86 × 10(-4); OR, 1.04; 95% CI, 1.02-1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r(2) ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor-binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk. ©2015 American Association for Cancer Research.

Fine-scale mapping of the 4q24 locus identifies two independent loci associated with breast cancer risk

PubMed Central

Guo, Xingyi; Long, Jirong; Zeng, Chenjie; Michailidou, Kyriaki; Ghoussaini, Maya; Bolla, Manjeet K.; Wang, Qin; Milne, Roger L.; Shu, Xiao-Ou; Cai, Qiuyin; Beesley, Jonathan; Kar, Siddhartha P.; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W.; Beeghly-Fadiel, Alicia; Benitez, Javier; Blot, William; Bogdanova, Natalia; Bojesen, Stig E.; Brauch, Hiltrud; Brenner, Hermann; Brinton, Louise; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Cai, Hui; Canisius, Sander; Chang-Claude, Jenny; Choi, Ji-Yeob; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Darabi, Hatef; Devilee, Peter; Droit, Arnaud; Dörk, Thilo; Fasching, Peter A.; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gaborieau, Valerie; García-Closas, Montserrat; Giles, Graham G.; Grip, Mervi; Guénel, Pascal; Haiman, Christopher A.; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L.; Hsiung, Chia-Ni; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kabisch, Maria; Kang, Daehee; Khan, Sofia; Knight, Julia A.; Kosma, Veli-Matti; Lambrechts, Diether; Marchand, Loic Le; Li, Jingmei; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Marme, Frederik; Matsuo, Keitaro; McLean, Catriona A.; Meindl, Alfons; Muir, Kenneth; Neuhausen, Susan L.; Nevanlinna, Heli; Nord, Silje; Olson, Janet E.; Orr, Nick; Peterlongo, Paolo; Putti, Thomas Choudary; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Marjanka K.; Schmutzler, Rita K.; Shen, Chen-Yang; Shi, Jiajun; Shrubsole, Martha J; Southey, Melissa C.; Swerdlow, Anthony; Teo, Soo Hwang; Thienpont, Bernard; Toland, Amanda Ewart; Tollenaar, Robert A.E.M.; Tomlinson, Ian P.M.; Truong, Thérèse; Tseng, Chiu-chen; van den Ouweland, Ans; Wen, Wanqing; Winqvist, Robert; Wu, Anna; Yip, Cheng Har; Zamora, M. Pilar; Zheng, Ying; Hall, Per; Pharoah, Paul D.P.; Simard, Jacques; Chenevix-Trench, Georgia; Dunning, Alison M.; Easton, Douglas F.; Zheng, Wei

2015-01-01

Background A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 (conditional p = 2.51 × 10−4; OR = 1.04; 95% CI 1.02–1.07) and rs77928427 (p = 1.86 × 10−4; OR = 1.04; 95% CI 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk. PMID:26354892

Evaluation of soil and vegetation response to drought using SMOS soil moisture satellite observations

NASA Astrophysics Data System (ADS)

Piles, Maria; Sánchez, Nilda; Vall-llossera, Mercè; Ballabrera, Joaquim; Martínez, Justino; Martínez-Fernández, José; Camps, Adriano; Font, Jordi

2014-05-01

Soil moisture plays an important role in determining the likelihood of droughts and floods that may affect an area. Knowledge of soil moisture distribution as a function of time and space is highly relevant for hydrological, ecological and agricultural applications, especially in water-limited or drought-prone regions. However, measuring soil moisture is challenging because of its high variability; point-scale in-situ measurements are scarce being remote sensing the only practical means to obtain regional- and global-scale soil moisture estimates. The ESA's Soil Moisture and Ocean Salinity (SMOS) is the first satellite mission ever designed to measuring the Earth's surface soil moisture at near daily time scales with levels of accuracy previously not attained. Since its launch in November 2009, significant efforts have been dedicated to validate and fine-tune the retrieval algorithms so that SMOS-derived soil moisture estimates meet the standards required for a wide variety of applications. In this line, the SMOS Barcelona Expert Center (BEC) is distributing daily, monthly, and annual temporal averages of 0.25-deg global soil moisture maps, which have proved useful for assessing drought and water-stress conditions. In addition, a downscaling algorithm has been developed to combine SMOS and NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) data into fine-scale (< 1km) soil moisture estimates, which permits extending the applicability of the data to regional and local studies. Fine-scale soil moisture maps are currently limited to the Iberian Peninsula but the algorithm is dynamic and can be transported to any region. Soil moisture maps are generated in a near real-time fashion at BEC facilities and are used by Barcelona's fire prevention services to detect extremely dry soil and vegetation conditions posing a risk of fire. Recently, they have been used to explain drought-induced tree mortality episodes and forest decline in the Catalonia region. These soil moisture products can also be a useful tool to monitor the effectiveness of land restoration management practices. The aim of this work is to demonstrate the feasibility of using SMOS soil moisture maps for monitoring drought and water-stress conditions. In previous research, SMOS-derived Soil Moisture Anomalies (SSMA), calculated in a ten-day basis, were shown to be in close relationship with well-known drought indices (the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index). In this work, SSMA have been calculated for the period 2010-2013 in representative arid, semi-arid, sub-humid and humid areas across global land biomes. The SSMA reflect the cumulative precipitation anomalies and is known to provide 'memory' in the climate and hydrological system; the water retained in the soil after a rainfall event is temporally more persistent than the rainfall event itself, and has a greater persistence during periods of low precipitation. Besides, the Normalized Difference Vegetation Index (NDVI) from MODIS is used as an indicator of vegetation activity and growth. The NDVI time series are expected to reflect the changes in surface vegetation density and status induced by water-deficit conditions. Understanding the relationships between SSMA and NDVI concurrent time series should provide new insight about the sensitivity of land biomes to drought.

A VS30 map for California with geologic and topographic constraints

USGS Publications Warehouse

Thompson, Eric; Wald, David J.; Worden, Charles

2014-01-01

For many earthquake engineering applications, site response is estimated through empirical correlations with the time‐averaged shear‐wave velocity to 30 m depth (VS30). These applications therefore depend on the availability of either site‐specific VS30 measurements or VS30 maps at local, regional, and global scales. Because VS30 measurements are sparse, a proxy frequently is needed to estimate VS30 at unsampled locations. We present a new VS30 map for California, which accounts for observational constraints from multiple sources and spatial scales, such as geology, topography, and site‐specific VS30measurements. We apply the geostatistical approach of regression kriging (RK) to combine these constraints for predicting VS30. For the VS30 trend, we start with geology‐based VS30 values and identify two distinct trends between topographic gradient and the residuals from the geology VS30 model. One trend applies to deep and fine Quaternary alluvium, whereas the second trend is slightly stronger and applies to Pleistocene sedimentary units. The RK framework ensures that the resulting map of California is locally refined to reflect the rapidly expanding database of VS30 measurements throughout California. We compare the accuracy of the new mapping method to a previously developed map of VS30 for California. We also illustrate the sensitivity of ground motions to the new VS30 map by comparing real and scenario ShakeMaps with VS30 values from our new map to those for existingVS30 maps.

A multi-scale approach to monitor urban carbon-dioxide emissions in the atmosphere over Vancouver, Canada

NASA Astrophysics Data System (ADS)

Christen, A.; Crawford, B.; Ketler, R.; Lee, J. K.; McKendry, I. G.; Nesic, Z.; Caitlin, S.

2015-12-01

Measurements of long-lived greenhouse gases in the urban atmosphere are potentially useful to constrain and validate urban emission inventories, or space-borne remote-sensing products. We summarize and compare three different approaches, operating at different scales, that directly or indirectly identify, attribute and quantify emissions (and uptake) of carbon dioxide (CO2) in urban environments. All three approaches are illustrated using in-situ measurements in the atmosphere in and over Vancouver, Canada. Mobile sensing may be a promising way to quantify and map CO2 mixing ratios at fine scales across heterogenous and complex urban environments. We developed a system for monitoring CO2 mixing ratios at street level using a network of mobile CO2 sensors deployable on vehicles and bikes. A total of 5 prototype sensors were built and simultaneously used in a measurement campaign across a range of urban land use types and densities within a short time frame (3 hours). The dataset is used to aid in fine scale emission mapping in combination with simultaneous tower-based flux measurements. Overall, calculated CO2 emissions are realistic when compared against a spatially disaggregated scale emission inventory. The second approach is based on mass flux measurements of CO2 using a tower-based eddy covariance (EC) system. We present a continuous 7-year long dataset of CO2 fluxes measured by EC at the 28m tall flux tower 'Vancouver-Sunset'. We show how this dataset can be combined with turbulent source area models to quantify and partition different emission processes at the neighborhood-scale. The long-term EC measurements are within 10% of a spatially disaggregated scale emission inventory. Thirdly, at the urban scale, we present a dataset of CO2 mixing ratios measured using a tethered balloon system in the urban boundary layer above Vancouver. Using a simple box model, net city-scale CO2 emissions can be determined using measured rate of change of CO2 mixing ratios, estimated CO2 advection and entrainment fluxes. Daily city-scale emissions totals predicted by the model are within 32% of a spatially scaled municipal greenhouse gas inventory. In summary, combining information from different approaches and scales is a promising approach to establish long-term emission monitoring networks in cities.

GWAS and fine-mapping of 35 production, reproduction and conformation traits with imputed sequences of 27K Holstein bulls

USDA-ARS?s Scientific Manuscript database

Fine-mapping of causal variants is becoming feasible for complex traits in livestock GWAS, as an increasing number of animals are sequenced. Imputation has been routinely applied to ascertain sequence variants in large genotyped populations based on small reference populations of sequenced animals. ...

GWAS and fine-mapping of 35 production, reproduction, and conformation traits with imputed sequences of 27K Holstein bulls

USDA-ARS?s Scientific Manuscript database

Imputation has been routinely applied to ascertain sequence variants in large genotyped populations based on reference populations of sequenced animals. With the implementation of the 1000 Bull Genomes Project and increasing numbers of animals sequenced, fine-mapping of causal variants is becoming f...

Fine mapping implicates two immunity genes in larval resistance to the honey bee brood fungal disease, Chalkbrood

USDA-ARS?s Scientific Manuscript database

Chalkbrood infection of honey bee (Apis mellifera) brood by the fungus Ascosphaera apis results in fatal encapsulation of susceptible larvae with a mycelial coat. Recent QTL analysis indicates that some level of physiological resistance exists in individual larvae. We performed a fine mapping anal...

Far Sidelobe Effects from Panel Gaps of the Atacama Cosmology Telescope

NASA Technical Reports Server (NTRS)

Fluxa, Pedro R.; Duenner, Rolando; Maurin, Loiec; Choi, Steve K.; Devlin, Mark J.; Gallardo, Patricio A.; Shuay-Pwu, P. Ho; Koopman, Brian J.; Louis, Thibaut; Wollack, Edward J.

2016-01-01

The Atacama Cosmology Telescope is a 6 meter diameter CMB telescope located at 5200 meters in the Chilean desert. ACT has made arc-minute scale maps of the sky at 90 and 150 GHz which have led to precise measurements of the fine angular power spectrum of the CMB fluctuations in temperature and polarization. One of the goals of ACT is to search for the B-mode polarization signal from primordial gravity waves, and thus extending ACT's data analysis to larger angular scales. This goal introduces new challenges in the control of systematic effects, including better understanding of far sidelobe effects that might enter the power spectrum at degree angular scales. Here we study the effects of the gaps between panels of the ACT primary and secondary reflectors in the worst case scenario in which the gaps remain open. We produced numerical simulations of the optics using GRASP up to 8 degrees away from the main beam and simulated timestreams for observations with this beam using real pointing information from ACT data. Maps from these simulated timestreams showed leakage from the sidelobes, indicating that this effect must be taken into consideration at large angular scales.

High-resolution tree canopy mapping for New York City using LIDAR and object-based image analysis

NASA Astrophysics Data System (ADS)

MacFaden, Sean W.; O'Neil-Dunne, Jarlath P. M.; Royar, Anna R.; Lu, Jacqueline W. T.; Rundle, Andrew G.

2012-01-01

Urban tree canopy is widely believed to have myriad environmental, social, and human-health benefits, but a lack of precise canopy estimates has hindered quantification of these benefits in many municipalities. This problem was addressed for New York City using object-based image analysis (OBIA) to develop a comprehensive land-cover map, including tree canopy to the scale of individual trees. Mapping was performed using a rule-based expert system that relied primarily on high-resolution LIDAR, specifically its capacity for evaluating the height and texture of aboveground features. Multispectral imagery was also used, but shadowing and varying temporal conditions limited its utility. Contextual analysis was a key part of classification, distinguishing trees according to their physical and spectral properties as well as their relationships to adjacent, nonvegetated features. The automated product was extensively reviewed and edited via manual interpretation, and overall per-pixel accuracy of the final map was 96%. Although manual editing had only a marginal effect on accuracy despite requiring a majority of project effort, it maximized aesthetic quality and ensured the capture of small, isolated trees. Converting high-resolution LIDAR and imagery into usable information is a nontrivial exercise, requiring significant processing time and labor, but an expert system-based combination of OBIA and manual review was an effective method for fine-scale canopy mapping in a complex urban environment.

Geological Features Mapping Using PALSAR-2 Data in Kelantan River Basin, Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Pour, A. B.; Hashim, M.

2016-09-01

In this study, the recently launched Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), remote sensing data were used to map geologic structural and topographical features in the Kelantan river basin for identification of high potential risk and susceptible zones for landslides and flooding areas. A ScanSAR and two fine mode dual polarization level 3.1 images cover Kelantan state were processed for comprehensive analysis of major geological structures and detailed characterizations of lineaments, drainage patterns and lithology at both regional and district scales. Red-Green-Blue (RGB) colour-composite was applied to different polarization channels of PALSAR-2 data to extract variety of geological information. Directional convolution filters were applied to the data for identifying linear features in particular directions and edge enhancement in the spatial domain. Results derived from ScanSAR image indicate that lineament occurrence at regional scale was mainly linked to the N-S trending of the Bentong-Raub Suture Zone (BRSZ) in the west and Lebir Fault Zone in the east of the Kelantan state. Combination of different polarization channels produced image maps contain important information related to water bodies, wetlands and lithological units for the Kelantan state using fine mode observation data. The N-S, NE-SW and NNE-SSW lineament trends were identified in the study area using directional filtering. Dendritic, sub-dendritic and rectangular drainage patterns were detected in the Kelantan river basin. The analysis of field investigations data indicate that many of flooded areas were associated with high potential risk zones for hydro-geological hazards such as wetlands, urban areas, floodplain scroll, meander bend, dendritic and sub-dendritic drainage patterns, which are located in flat topograghy regions. Numerous landslide points were located in rectangular drainage system that associated with topographic slope of metamorphic and Quaternary rock units. Some large landslides were associated with N-S, NNE-SSW and NE-SW trending fault zones. Consequently, structural and topographical geology maps were produced for Kelantan river basin using PALSAR-2 data, which could be broadly applicable for landslide hazard mapping and identification of high potential risk zone for hydro-geological hazards.

Variants for HDL-C, LDL-C and Triglycerides Identified from Admixture Mapping and Fine-Mapping Analysis in African-American Families

PubMed Central

Shetty, Priya B.; Tang, Hua; Feng, Tao; Tayo, Bamidele; Morrison, Alanna C.; Kardia, Sharon L.R.; Hanis, Craig L.; Arnett, Donna K.; Hunt, Steven C.; Boerwinkle, Eric; Rao, D.C.; Cooper, R.S.; Risch, Neil; Zhu, Xiaofeng

2015-01-01

Background Admixture mapping of lipids was followed-up by family-based association analysis to identify variants for cardiovascular disease in African-Americans. Methods and Results The present study conducted admixture mapping analysis for total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglycerides. The analysis was performed in 1,905 unrelated African-American subjects from the National Heart, Lung and Blood Institute’s Family Blood Pressure Program. Regions showing admixture evidence were followed-up with family-based association analysis in 3,556 African-American subjects from the FBPP. The admixture mapping and family-based association analyses were adjusted for age, age2, sex, body-mass-index, and genome-wide mean ancestry to minimize the confounding due to population stratification. Regions that were suggestive of local ancestry association evidence were found on chromosomes 7 (LDL-C), 8 (HDL-C), 14 (triglycerides) and 19 (total cholesterol and triglycerides). In the fine-mapping analysis, 52,939 SNPs were tested and 11 SNPs (8 independent SNPs) showed nominal significant association with HDL-C (2 SNPs), LDL-C (4 SNPs) and triglycerides (5 SNPs). The family data was used in the fine-mapping to identify SNPs that showed novel associations with lipids and regions including genes with known associations for cardiovascular disease. Conclusions This study identified regions on chromosomes 7, 8, 14 and 19 and 11 SNPs from the fine-mapping analysis that were associated with HDL-C, LDL-C and triglycerides for further studies of cardiovascular disease in African-Americans. PMID:25552592

A multiscale restriction-smoothed basis method for high contrast porous media represented on unstructured grids

DOE Office of Scientific and Technical Information (OSTI.GOV)

Møyner, Olav, E-mail: olav.moyner@sintef.no; Lie, Knut-Andreas, E-mail: knut-andreas.lie@sintef.no

2016-01-01

A wide variety of multiscale methods have been proposed in the literature to reduce runtime and provide better scaling for the solution of Poisson-type equations modeling flow in porous media. We present a new multiscale restricted-smoothed basis (MsRSB) method that is designed to be applicable to both rectilinear grids and unstructured grids. Like many other multiscale methods, MsRSB relies on a coarse partition of the underlying fine grid and a set of local prolongation operators (multiscale basis functions) that map unknowns associated with the fine grid cells to unknowns associated with blocks in the coarse partition. These mappings are constructedmore » by restricted smoothing: Starting from a constant, a localized iterative scheme is applied directly to the fine-scale discretization to compute prolongation operators that are consistent with the local properties of the differential operators. The resulting method has three main advantages: First of all, both the coarse and the fine grid can have general polyhedral geometry and unstructured topology. This means that partitions and good prolongation operators can easily be constructed for complex models involving high media contrasts and unstructured cell connections introduced by faults, pinch-outs, erosion, local grid refinement, etc. In particular, the coarse partition can be adapted to geological or flow-field properties represented on cells or faces to improve accuracy. Secondly, the method is accurate and robust when compared to existing multiscale methods and does not need expensive recomputation of local basis functions to account for transient behavior: Dynamic mobility changes are incorporated by continuing to iterate a few extra steps on existing basis functions. This way, the cost of updating the prolongation operators becomes proportional to the amount of change in fluid mobility and one reduces the need for expensive, tolerance-based updates. Finally, since the MsRSB method is formulated on top of a cell-centered, conservative, finite-volume method, it is applicable to any flow model in which one can isolate a pressure equation. Herein, we only discuss single and two-phase incompressible models. Compressible flow, e.g., as modeled by the black-oil equations, is discussed in a separate paper.« less

Efficient design of nanoplasmonic waveguide devices using the space mapping algorithm.

PubMed

Dastmalchi, Pouya; Veronis, Georgios

2013-12-30

We show that the space mapping algorithm, originally developed for microwave circuit optimization, can enable the efficient design of nanoplasmonic waveguide devices which satisfy a set of desired specifications. Space mapping utilizes a physics-based coarse model to approximate a fine model accurately describing a device. Here the fine model is a full-wave finite-difference frequency-domain (FDFD) simulation of the device, while the coarse model is based on transmission line theory. We demonstrate that simply optimizing the transmission line model of the device is not enough to obtain a device which satisfies all the required design specifications. On the other hand, when the iterative space mapping algorithm is used, it converges fast to a design which meets all the specifications. In addition, full-wave FDFD simulations of only a few candidate structures are required before the iterative process is terminated. Use of the space mapping algorithm therefore results in large reductions in the required computation time when compared to any direct optimization method of the fine FDFD model.

Mapping invasive aquatic vegetation in the Sacramento-San Joaquin Delta using hyperspectral imagery.

PubMed

Underwood, E C; Mulitsch, M J; Greenberg, J A; Whiting, M L; Ustin, S L; Kefauver, S C

2006-10-01

The ecological and economic impacts associated with invasive species are of critical concern to land managers. The ability to map the extent and severity of invasions would be a valuable contribution to management decisions relating to control and monitoring efforts. We investigated the use of hyperspectral imagery for mapping invasive aquatic plant species in the Sacramento-San Joaquin Delta in the Central Valley of California, at two spatial scales. Sixty-four flightlines of HyMap hyperspectral imagery were acquired over the study region covering an area of 2,139 km(2) and field work was conducted to acquire GPS locations of target invasive species. We used spectral mixture analysis to classify two target invasive species; Brazilian waterweed (Egeria densa), a submerged invasive, and water hyacinth (Eichhornia crassipes), a floating emergent invasive. At the relatively fine spatial scale for five sites within the Delta (average size 51 ha) average classification accuracies were 93% for Brazilian waterweed and 73% for water hyacinth. However, at the coarser, Delta-wide scale (177,000 ha) these accuracy results were 29% for Brazilian waterweed and 65% for water hyacinth. The difference in accuracy is likely accounted for by the broad range in water turbidity and tide heights encountered across the Delta. These findings illustrate that hyperspectral imagery is a promising tool for discriminating target invasive species within the Sacramento-San Joaquin Delta waterways although more work is needed to develop classification tools that function under changing environmental conditions.

High-Throughput Sequencing and Linkage Mapping of a Clownfish Genome Provide Insights on the Distribution of Molecular Players Involved in Sex Change.

PubMed

Casas, Laura; Saenz-Agudelo, Pablo; Irigoien, Xabier

2018-03-06

Clownfishes are an excellent model system for investigating the genetic mechanism governing hermaphroditism and socially-controlled sex change in their natural environment because they are broadly distributed and strongly site-attached. Genomic tools, such as genetic linkage maps, allow fine-mapping of loci involved in molecular pathways underlying these reproductive processes. In this study, a high-density genetic map of Amphiprion bicinctus was constructed with 3146 RAD markers in a full-sib family organized in 24 robust linkage groups which correspond to the haploid chromosome number of the species. The length of the map was 4294.71 cM, with an average marker interval of 1.38 cM. The clownfish linkage map showed various levels of conserved synteny and collinearity with the genomes of Asian and European seabass, Nile tilapia and stickleback. The map provided a platform to investigate the genomic position of genes with differential expression during sex change in A. bicinctus. This study aims to bridge the gap of genome-scale information for this iconic group of species to facilitate the study of the main gene regulatory networks governing social sex change and gonadal restructuring in protandrous hermaphrodites.

BAC sequencing using pooled methods.

PubMed

Saski, Christopher A; Feltus, F Alex; Parida, Laxmi; Haiminen, Niina

2015-01-01

Shotgun sequencing and assembly of a large, complex genome can be both expensive and challenging to accurately reconstruct the true genome sequence. Repetitive DNA arrays, paralogous sequences, polyploidy, and heterozygosity are main factors that plague de novo genome sequencing projects that typically result in highly fragmented assemblies and are difficult to extract biological meaning. Targeted, sub-genomic sequencing offers complexity reduction by removing distal segments of the genome and a systematic mechanism for exploring prioritized genomic content through BAC sequencing. If one isolates and sequences the genome fraction that encodes the relevant biological information, then it is possible to reduce overall sequencing costs and efforts that target a genomic segment. This chapter describes the sub-genome assembly protocol for an organism based upon a BAC tiling path derived from a genome-scale physical map or from fine mapping using BACs to target sub-genomic regions. Methods that are described include BAC isolation and mapping, DNA sequencing, and sequence assembly.

Surficial Geologic Map of the Worcester North-Oxford- Wrentham-Attleboro Nine-Quadrangle Area in South- Central Massachusetts

USGS Publications Warehouse

Stone, Byron D.; Stone, Janet R.; DiGiacomo-Cohen, Mary L.

2008-01-01

The surficial geologic map layer shows the distribution of nonlithified earth materials at land surface in an area of nine 7.5-minute quadrangles (417 mi2 total) in south-central Massachusetts (fig. 1). Across Massachusetts, these materials range from a few feet to more than 500 ft in thickness. They overlie bedrock, which crops out in upland hills and in resistant ledges in valley areas. The geologic map differentiates surficial materials of Quaternary age on the basis of their lithologic characteristics (such as grain size and sedimentary structures), constructional geomorphic features, stratigraphic relationships, and age. Surficial materials also are known in engineering classifications as unconsolidated soils, which include coarse-grained soils, fine-grained soils, or organic fine-grained soils. Surficial materials underlie and are the parent materials of modern pedogenic soils, which have developed in them at the land surface. Surficial earth materials significantly affect human use of the land, and an accurate description of their distribution is particularly important for water resources, construction aggregate resources, earth-surface hazards assessments, and land-use decisions. The mapped distribution of surficial materials that lie between the land surface and the bedrock surface is based on detailed geologic mapping of 7.5-minute topographic quadrangles, produced as part of an earlier (1938-1982) cooperative statewide mapping program between the U.S. Geological Survey and the Massachusetts Department of Public Works (now Massachusetts Highway Department) (Page, 1967; Stone, 1982). Each published geologic map presents a detailed description of local geologic map units, the genesis of the deposits, and age correlations among units. Previously unpublished field compilation maps exist on paper or mylar sheets and these have been digitally rendered for the present map compilation. Regional summaries based on the Massachusetts surficial geologic mapping studies discuss the ages of multiple glaciations, the nature of glaciofluvial, glaciolacustrine, and glaciomarine deposits, and the processes of ice advance and retreat across Massachusetts (Koteff and Pessl, 1981; papers in Larson and Stone, 1982; Oldale and Barlow, 1986; Stone and Borns, 1986; Warren and Stone, 1986). This compilation of surficial geologic materials is an interim product that defines the areas of exposed bedrock and the boundaries between glacial till, glacial stratified deposits, and overlying postglacial deposits. This work is part of a comprehensive study to produce a statewide digital map of the surficial geology at a 1:24,000-scale level of accuracy. This surficial geologic map layer covering nine quadrangles revises previous digital surficial geologic maps (Stone and others, 1993; MassGIS, 1999) that were compiled on base maps at regional scales of 1:125,000 and 1:250,000. The purpose of this study is to provide fundamental geologic data for the evaluation of natural resources, hazards, and land information within the Commonwealth of Massachusetts.

Life on the Edge - Improved Forest Cover Mapping in Mixed-Use Tropical Regions

NASA Astrophysics Data System (ADS)

Anderson, C.; Mendenhall, C. D.; Daily, G.

2016-12-01

Tropical ecosystems and biodiversity are experiencing rapid change, primarily due to conversion of forest habitat to agriculture. Protected areas, while effective for conservation, only manage 15% of terrestrial area, whereas approximately 58% is privately owned. To incentivize private forest management and slow the loss of biodiversity, payments for ecosystem services (PES) programs were established in Costa Rica that pay landowners who maintain trees on their property. While this program is effective in improving livelihoods and preventing forest conversion, it is only managing payments to landowners on 1% of eligible, non-protected forested land.A major bottleneck for this program is access to accurate, national-scale tree cover maps. While the remote sensing community has made great progress in global-scale tree cover mapping, these maps are not sufficient to guide investments for PES programs. The major limitations of current global-scale tree-cover maps are that they a) do not distinguish between forest and agriculture and b) overestimate tree cover in mixed land-use areas (e.g. Global Forest Change overestimates by 20% on average in this region). This is especially problematic in biodiversity-rich Costa Rica, where small patches of forest intermix with agricultural production, and where the conservation value of tree-cover is high. To address this problem, we are developing a new forest cover mapping method that a) performs a least-squares spectral mixture analysis (SMA) using repeat Landsat imagery and canopy radiative transfer modeling: b) combines Landsat data, SMA results, and radar backscatter data using multi-sensor fusion techniques and: c) trains tree-cover classification models using high resolution data sets along a land use-intensity gradient. Our method predicted tree cover with 85% accuracy when compared to a fine-scale map of tree cover in a tropical, agricultural landscape, whereas the next-best method, the Global Forest Change map, predicted tree cover with 72% accuracy. Next steps will aim to test, improve, and apply this method globally to guide investments in nature in agricultural landscapes where forest stewardship will sustain biodiversity.

Indirect quantification of fine root production in a near tropical wet mountainous region

NASA Astrophysics Data System (ADS)

Lu, X.; Zhang, J.; Huang, C.

2016-12-01

The main functions of fine root (defined as diameter <= 2 mm) are water and nutrient transports. Besides being a carbon (C) storage pool, it also provides a C flux pathway through soil and plant. Fine root takes up a small portion, normally 5%, of biomass in forest ecosystems, but 30% to 70% of total net primary production. Therefore, quantifying fine root productivity is important to study the forest C budget. Presumably, belowground growth can be indirectly estimated by the more accessible aboveground vegetation structure dynamics. To verify the relationship with fine root productivity, we take internal (floristic) and external (environmental) factors into account, including litter production, canopy density (leaf area index), leaf nutrients (N, K, Ca, Mg, P), weather and/or soil physical conditions (air temperature, humidity, precipitation, solar radiation and soil moisture). The study was conducted in near tropical broadleaf (700 m asl) and conifer (1700 m asl) forests in northeastern Taiwan, generally receiving more than 4000 mm of precipitation per year. For each site, 16 50-cm long minirhizotron tubes were installed. Fine root images were acquired every three weeks. Growth and decline, newly presence and absence of fine roots were delineated by image processing algorithms to derive fine-root productivity through time. Aforementioned internal and external attributes were simultaneously collected as well. Some of these variables were highly correlated and were detrended using principal component analysis. We found that these transformed variables (mainly associated with litter production, precipitation and solar radiation) can delineate the spatiotemporal dynamics of root production well (r2 = 0.87, p = 0.443). In conclusion, this study demonstrated the feasibility of utilized aboveground variables to indirectly assess fine root growth, which could be further developed for the regional scale mapping with aid of remote sensing.

Fine mapping and characterization of BPH27, a brown planthopper resistance gene from wild rice (Oryza rufipogon Griff.).

PubMed

Huang, D; Qiu, Y; Zhang, Y; Huang, F; Meng, J; Wei, S; Li, R; Chen, B

2013-01-01

The brown planthopper (Nilaparvata lugens Stål; BPH) is one of the most serious rice pests worldwide. Growing resistant varieties is the most effective way to manage this insect, and wild rice species are a valuable source of resistance genes for developing resistant cultivars. BPH27 derived from an accession of Guangxi wild rice, Oryza rufipogon Griff. (Accession no. 2183, hereafter named GX2183), was primarily mapped to a 17-cM region on the long arm of the chromosome four. In this study, fine mapping of BPH27 was conducted using two BC(1)F(2) populations derived from introgression lines of GX2183. Insect resistance was evaluated in the BC(1)F(2) populations with 6,010 individual offsprings, and 346 resistance extremes were obtained and employed for fine mapping of BPH27. High-resolution linkage analysis defined the BPH27 locus to an 86.3-kb region in Nipponbare. Regarding the sequence information of rice cultivars, Nipponbare and 93-11, all predicted open reading frames (ORFs) in the fine-mapping region have been annotated as 11 types of proteins, and three ORFs encode disease-related proteins. Moreover, the average BPH numbers showed significant differences in 96-120 h after release in comparisons between the preliminary near-isogenic lines (pre-NILs, lines harboring resistance genes) and BaiR54. BPH growth and development were inhibited and survival rates were lower in the pre-NIL plants compared with the recurrent parent BaiR54. The pre-NIL exhibited 50.7% reductions in population growth rates (PGR) compared to BaiR54. The new development in fine mapping of BPH27 will facilitate the efforts to clone this important resistant gene and to use it in BPH-resistance rice breeding.

Fine mapping and introgressing qFIS1-2, a major QTL for kernel fissure resistance in rice (Oryza sativa L.)

USDA-ARS?s Scientific Manuscript database

Rice (Oryza sativa L.) kernel fissuring increases breakage during milling and decreases the value of processed rice. This study employed molecular gene tagging methods to fine-map a fissure resistance (FR) locus in ‘Cybonnet’, a semidwarf tropical japonica cultivar, as well as transfer this trait to...

Global Regolith Thermophysical Properties of the Moon From the Diviner Lunar Radiometer Experiment

NASA Astrophysics Data System (ADS)

Hayne, Paul O.; Bandfield, Joshua L.; Siegler, Matthew A.; Vasavada, Ashwin R.; Ghent, Rebecca R.; Williams, Jean-Pierre; Greenhagen, Benjamin T.; Aharonson, Oded; Elder, Catherine M.; Lucey, Paul G.; Paige, David A.

2017-12-01

We used infrared data from the Lunar Reconnaissance Orbiter (LRO) Diviner Lunar Radiometer Experiment to globally map thermophysical properties of the Moon's regolith fines layer. Thermal conductivity varies from 7.4 × 10-4 W m-1 K-1 at the surface to 3.4 × 10-3 W m-1 K-1 at depths of 1 m, given density values of 1,100 kg m-3 at the surface to 1,800 kg m-3 at 1 m depth. On average, the scale height of these profiles is 7 cm, corresponding to a thermal inertia of 55 ± 2 J m-2 K-1 s-1/2 at 273 K, relevant to the diurnally active near-surface layer, 4-7 cm. The temperature dependence of thermal conductivity and heat capacity leads to an 2 times diurnal variation in thermal inertia at the equator. On global scales, the regolith fines are remarkably uniform, implying rapid homogenization by impact gardening of this layer on timescales <1 Gyr. Regional- and local-scale variations show prominent impact features <1 Gyr old, including higher thermal inertia (> 100 J m-2 K-1 s-1/2) in the interiors and ejecta of Copernican-aged impact craters and lower thermal inertia (< 50 J m-2 K-1 s-1/2) within the lunar cold spots identified by Bandfield et al. (2014). Observed trends in ejecta thermal inertia provide a potential tool for age dating craters of previously unknown age, complementary to the approach suggested by Ghent et al. (2014). Several anomalous regions are identified in the global 128 pixels per degree maps presented here, including a high-thermal inertia deposit near the antipode of Tycho crater.

Comparing orbiter and rover image-based mapping of an ancient sedimentary environment, Aeolis Palus, Gale crater, Mars

NASA Astrophysics Data System (ADS)

Stack, K. M.; Edwards, C. S.; Grotzinger, J. P.; Gupta, S.; Sumner, D. Y.; Calef, F. J.; Edgar, L. A.; Edgett, K. S.; Fraeman, A. A.; Jacob, S. R.; Le Deit, L.; Lewis, K. W.; Rice, M. S.; Rubin, D.; Williams, R. M. E.; Williford, K. H.

2016-12-01

This study provides the first systematic comparison of orbital facies maps with detailed ground-based geology observations from the Mars Science Laboratory (MSL) Curiosity rover to examine the validity of geologic interpretations derived from orbital image data. Orbital facies maps were constructed for the Darwin, Cooperstown, and Kimberley waypoints visited by the Curiosity rover using High Resolution Imaging Science Experiment (HiRISE) images. These maps, which represent the most detailed orbital analysis of these areas to date, were compared with rover image-based geologic maps and stratigraphic columns derived from Curiosity's Mast Camera (Mastcam) and Mars Hand Lens Imager (MAHLI). Results show that bedrock outcrops can generally be distinguished from unconsolidated surficial deposits in high-resolution orbital images and that orbital facies mapping can be used to recognize geologic contacts between well-exposed bedrock units. However, process-based interpretations derived from orbital image mapping are difficult to infer without known regional context or observable paleogeomorphic indicators, and layer-cake models of stratigraphy derived from orbital maps oversimplify depositional relationships as revealed from a rover perspective. This study also shows that fine-scale orbital image-based mapping of current and future Mars landing sites is essential for optimizing the efficiency and science return of rover surface operations.

Comparing orbiter and rover image-based mapping of an ancient sedimentary environment, Aeolis Palus, Gale crater, Mars

USGS Publications Warehouse

Stack, Kathryn M.; Edwards, Christopher; Grotzinger, J. P.; Gupta, S.; Sumner, D.; Edgar, Lauren; Fraeman, A.; Jacob, S.; LeDeit, L.; Lewis, K.W.; Rice, M.S.; Rubin, D.; Calef, F.; Edgett, K.; Williams, R.M.E.; Williford, K.H.

2016-01-01

This study provides the first systematic comparison of orbital facies maps with detailed ground-based geology observations from the Mars Science Laboratory (MSL) Curiosity rover to examine the validity of geologic interpretations derived from orbital image data. Orbital facies maps were constructed for the Darwin, Cooperstown, and Kimberley waypoints visited by the Curiosity rover using High Resolution Imaging Science Experiment (HiRISE) images. These maps, which represent the most detailed orbital analysis of these areas to date, were compared with rover image-based geologic maps and stratigraphic columns derived from Curiosity’s Mast Camera (Mastcam) and Mars Hand Lens Imager (MAHLI). Results show that bedrock outcrops can generally be distinguished from unconsolidated surficial deposits in high-resolution orbital images and that orbital facies mapping can be used to recognize geologic contacts between well-exposed bedrock units. However, process-based interpretations derived from orbital image mapping are difficult to infer without known regional context or observable paleogeomorphic indicators, and layer-cake models of stratigraphy derived from orbital maps oversimplify depositional relationships as revealed from a rover perspective. This study also shows that fine-scale orbital image-based mapping of current and future Mars landing sites is essential for optimizing the efficiency and science return of rover surface operations.

Spatial consistency of chinook salmon redd distribution within and among years in the Cowlitz River, Washington

USGS Publications Warehouse

Klett, Katherine J.C.; Torgersen, Christian E.; Henning, Julie A.; Murray, Christopher J.

2013-01-01

We investigated the spawning patterns of Chinook Salmon Oncorhynchus tshawytscha on the lower Cowlitz River, Washington, using a unique set of fine- and coarse-scale temporal and spatial data collected during biweekly aerial surveys conducted in 1991–2009 (500 m to 28 km resolution) and 2008–2009 (100–500 m resolution). Redd locations were mapped from a helicopter during 2008 and 2009 with a hand-held GPS synchronized with in-flight audio recordings. We examined spatial patterns of Chinook Salmon redd reoccupation among and within years in relation to segment-scale geomorphic features. Chinook Salmon spawned in the same sections each year with little variation among years. On a coarse scale, 5 years (1993, 1998, 2000, 2002, and 2009) were compared for reoccupation. Redd locations were highly correlated among years. Comparisons on a fine scale (500 m) between 2008 and 2009 also revealed a high degree of consistency among redd locations. On a finer temporal scale, we observed that Chinook Salmon spawned in the same sections during the first and last week. Redds were clustered in both 2008 and 2009. Regression analysis with a generalized linear model at the 500-m scale indicated that river kilometer and channel bifurcation were positively associated with redd density, whereas sinuosity was negatively associated with redd density. Collecting data on specific redd locations with a GPS during aerial surveys was logistically feasible and cost effective and greatly enhanced the spatial precision of Chinook Salmon spawning surveys.

Groundwater sensitivity mapping in Kentucky using GIS and digitally vectorized geologic quadrangles

NASA Astrophysics Data System (ADS)

Croskrey, Andrea; Groves, Chris

2008-05-01

Groundwater sensitivity (Ray and O’dell in Environ Geol 22:345 352, 1993a) refers to the inherent ease with which groundwater can be contaminated based on hydrogeologic characteristics. We have developed digital methods for identifying areas of varying groundwater sensitivity for a ten county area of south central Kentucky at a scale of 1:100,000. The study area includes extensive limestone karst sinkhole plains, with groundwater extremely sensitive to contamination. Digitally vectorized geologic quadrangles (DVGQs) were combined with elevation data to identify both hydrogeologic groundwater sensitivity regions and zones of “high risk runoff” where contaminants could be transported in runoff from less sensitive to higher sensitivity (particularly karst) areas. While future work will fine-tune these maps with additional layers of data (soils for example) as digital data have become available, using DVGQs allows a relatively rapid assessment of groundwater sensitivity for Kentucky at a more useful scale than previously available assessment methods, such as DRASTIC and DIVERSITY.

Progressive simplification and transmission of building polygons based on triangle meshes

NASA Astrophysics Data System (ADS)

Li, Hongsheng; Wang, Yingjie; Guo, Qingsheng; Han, Jiafu

2010-11-01

Digital earth is a virtual representation of our planet and a data integration platform which aims at harnessing multisource, multi-resolution, multi-format spatial data. This paper introduces a research framework integrating progressive cartographic generalization and transmission of vector data. The progressive cartographic generalization provides multiple resolution data from coarse to fine as key scales and increments between them which is not available in traditional generalization framework. Based on the progressive simplification algorithm, the building polygons are triangulated into meshes and encoded according to the simplification sequence of two basic operations, edge collapse and vertex split. The map data at key scales and encoded increments between them are stored in a multi-resolution file. As the client submits requests to the server, the coarsest map is transmitted first and then the increments. After data decoding and mesh refinement the building polygons with more details will be visualized. Progressive generalization and transmission of building polygons is demonstrated in the paper.

Fine-grained sediment spatial distribution on the basis of a geostatistical analysis: Example of the eastern Bay of the Seine (France)

NASA Astrophysics Data System (ADS)

Méar, Y.; Poizot, E.; Murat, A.; Lesueur, P.; Thomas, M.

2006-12-01

The eastern Bay of the Seine (English Channel) was the subject in 1991 of a sampling survey of superficial sediments. Geostatistic tools were used to examine the complexity of the spatial distribution of the fine-grained fraction (<50 μm). A central depocentre of fine sediments (i.e. content up to 50%) oriented in a NW-SE direction in a muddy coastal strip, in a very high energy hydrodynamical situation due to storm swells and its megatidal setting, is for the first time recognised and discussed. Within this sedimentary unit, the distribution of the fine fraction is very heterogeneous, with mud patches of less than 4000 m diameter; the boundary between these mud patches and their substratum is very sharp. The distribution of this fine fraction appears to be controlled by an anticyclonic eddy located off the Pays de Caux. Under the influence of this, the suspended material expelled from the Seine estuary moves along the coast and swings off Antifer harbour, towards the NW. It is trapped within this eddy because of the settling of suspended particulate matter. Both at a general scale and a local scale the morphology (whether inherited or due to modern processes) has a strong influence on the spatial distribution of the fine fraction. At the general scale, the basin-like shape of the area facilitates the silting, and the presence of the submarine dunes, called "Ridins d'Antifer", clearly determines the northern limit of the muddy zone. At a local scale, the same influence is obvious: paleovalleys trap the fine sediments, whereas isolated sand dunes and ripples limit the silting. This duality of role of the morphology is therefore one of the reasons why the muddy surface is extremely heterogeneous spatially. The presence of an important population of suspension feeding echinoderm, the brittle-star Ophiothrix fragilis Abildgaard, has led to a local increase in the silting, and to the modification of the physicochemical and sedimentological parameters. A complex relationship is shown to occur between the amount of fine fraction and the number of brittle-stars (ind. m -2). Classical statistical methods are not appropriate to study the spatial distribution of the mud fraction, because the spatial component of the percentage of the distribution is not integrated in the analysis. On the other hand, this is the main property of the geostatistic concepts. The use of geostatistic tools within a strict and clearly identified procedure enables the proposal of an accurate cartography. Further application of the proposed protocol (based on a semivariographic study and a conditional simulation interpolation) for surficial sediments mapping will help explain spatial and temporal variations of fine-grained fraction. Then assessments of sedimentation and erosion stages allow highlighting signature of environmental processes.

Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci

PubMed Central

Zubair, Niha; Luis Ambite, Jose; Bush, William S.; Kichaev, Gleb; Lu, Yingchang; Manichaikul, Ani; Sheu, Wayne H-H.; Absher, Devin; Assimes, Themistocles L.; Bielinski, Suzette J.; Bottinger, Erwin P.; Buzkova, Petra; Chuang, Lee-Ming; Chung, Ren-Hua; Cochran, Barbara; Dumitrescu, Logan; Gottesman, Omri; Haessler, Jeffrey W.; Haiman, Christopher; Heiss, Gerardo; Hsiung, Chao A.; Hung, Yi-Jen; Hwu, Chii-Min; Juang, Jyh-Ming J.; Le Marchand, Loic; Lee, I-Te; Lee, Wen-Jane; Lin, Li-An; Lin, Danyu; Lin, Shih-Yi; Mackey, Rachel H.; Martin, Lisa W.; Pasaniuc, Bogdan; Peters, Ulrike; Predazzi, Irene; Quertermous, Thomas; Reiner, Alex P.; Robinson, Jennifer; Rotter, Jerome I.; Ryckman, Kelli K.; Schreiner, Pamela J.; Stahl, Eli; Tao, Ran; Tsai, Michael Y.; Waite, Lindsay L.; Wang, Tzung-Dau; Buyske, Steven; Ida Chen, Yii-Der; Cheng, Iona; Crawford, Dana C.; Loos, Ruth J.F.; Rich, Stephen S.; Fornage, Myriam; North, Kari E.; Kooperberg, Charles; Carty, Cara L.

2016-01-01

Abstract Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies. PMID:28426890

Fine resolution mapping of population age-structures for health and development applications.

PubMed

Alegana, V A; Atkinson, P M; Pezzulo, C; Sorichetta, A; Weiss, D; Bird, T; Erbach-Schoenberg, E; Tatem, A J

2015-04-06

The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings.

Variants for HDL-C, LDL-C, and triglycerides identified from admixture mapping and fine-mapping analysis in African American families.

PubMed

Shetty, Priya B; Tang, Hua; Feng, Tao; Tayo, Bamidele; Morrison, Alanna C; Kardia, Sharon L R; Hanis, Craig L; Arnett, Donna K; Hunt, Steven C; Boerwinkle, Eric; Rao, Dabeeru C; Cooper, Richard S; Risch, Neil; Zhu, Xiaofeng

2015-02-01

Admixture mapping of lipids was followed-up by family-based association analysis to identify variants for cardiovascular disease in African Americans. The present study conducted admixture mapping analysis for total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides. The analysis was performed in 1905 unrelated African American subjects from the National Heart, Lung and Blood Institute's Family Blood Pressure Program (FBPP). Regions showing admixture evidence were followed-up with family-based association analysis in 3556 African American subjects from the FBPP. The admixture mapping and family-based association analyses were adjusted for age, age(2), sex, body mass index, and genome-wide mean ancestry to minimize the confounding caused by population stratification. Regions that were suggestive of local ancestry association evidence were found on chromosomes 7 (low-density lipoprotein cholesterol), 8 (high-density lipoprotein cholesterol), 14 (triglycerides), and 19 (total cholesterol and triglycerides). In the fine-mapping analysis, 52 939 single-nucleotide polymorphisms (SNPs) were tested and 11 SNPs (8 independent SNPs) showed nominal significant association with high-density lipoprotein cholesterol (2 SNPs), low-density lipoprotein cholesterol (4 SNPs), and triglycerides (5 SNPs). The family data were used in the fine-mapping to identify SNPs that showed novel associations with lipids and regions, including genes with known associations for cardiovascular disease. This study identified regions on chromosomes 7, 8, 14, and 19 and 11 SNPs from the fine-mapping analysis that were associated with high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides for further studies of cardiovascular disease in African Americans. © 2014 American Heart Association, Inc.

The Eagle Nebula: a spectral template for star forming regions

NASA Astrophysics Data System (ADS)

Flagey, Nicolas; Boulanger, Francois; Carey, Sean; Compiegne, Mathieu; Dwek, Eli; Habart, Emilie; Indebetouw, Remy; Montmerle, Thierry; Noriega-Crespo, Alberto

2008-03-01

IRAC and MIPS have revealed spectacular images of massive star forming regions in the Galaxy. These vivid illustrations of the interaction between the stars, through their winds and radiation, and their environment, made of gas and dust, still needs to be explained. The large scale picture of layered shells of gas components, is affected by the small scale interaction of stars with the clumpy medium that surrounds them. To understand spatial variations of physical conditions and dust properties on small scales, spectroscopic imaging observations are required on a nearby object. The iconic Eagle Nebula (M16) is one of the nearest and most observed star forming region of our Galaxy and as such, is a well suited template to obtain this missing data set. We thus propose a complete spectral map of the Eagle Nebula (M16) with the IRS/Long Low module (15-38 microns) and MIPS/SED mode (55-95 microns). Analysis of the dust emission, spectral features and continuum, and of the H2 and fine-structure gas lines within our models will provide us with constraints on the physical conditions (gas ionization state, pressure, radiation field) and dust properties (temperature, size distribution) at each position within the nebula. Only such a spatially and spectrally complete map will allow us to characterize small scale structure and dust evolution within the global context and understand the impact of small scale structure on the evolution of dusty star forming regions. This project takes advantage of the unique ability of IRS at obtaining sensitive spectral maps covering large areas.

Mapping by sequencing in cotton (Gossypium hirsutum) line MD52ne identified candidate genes for fiber strength and its related quality attributes

USDA-ARS?s Scientific Manuscript database

Fiber strength, length, maturity and fineness determine the market value of cotton fibers and the quality of spun yarn. Cotton fiber strength has been recognized as a critical quality attribute in the modern textile industry. Fine mapping along with quantitative trait loci (QTL) validation and candi...

A note on the efficiencies of sampling strategies in two-stage Bayesian regional fine mapping of a quantitative trait.

PubMed

Chen, Zhijian; Craiu, Radu V; Bull, Shelley B

2014-11-01

In focused studies designed to follow up associations detected in a genome-wide association study (GWAS), investigators can proceed to fine-map a genomic region by targeted sequencing or dense genotyping of all variants in the region, aiming to identify a functional sequence variant. For the analysis of a quantitative trait, we consider a Bayesian approach to fine-mapping study design that incorporates stratification according to a promising GWAS tag SNP in the same region. Improved cost-efficiency can be achieved when the fine-mapping phase incorporates a two-stage design, with identification of a smaller set of more promising variants in a subsample taken in stage 1, followed by their evaluation in an independent stage 2 subsample. To avoid the potential negative impact of genetic model misspecification on inference we incorporate genetic model selection based on posterior probabilities for each competing model. Our simulation study shows that, compared to simple random sampling that ignores genetic information from GWAS, tag-SNP-based stratified sample allocation methods reduce the number of variants continuing to stage 2 and are more likely to promote the functional sequence variant into confirmation studies. © 2014 WILEY PERIODICALS, INC.

High-Density Genetic Linkage Map Construction and Quantitative Trait Locus Mapping for Hawthorn (Crataegus pinnatifida Bunge).

PubMed

Zhao, Yuhui; Su, Kai; Wang, Gang; Zhang, Liping; Zhang, Jijun; Li, Junpeng; Guo, Yinshan

2017-07-14

Genetic linkage maps are an important tool in genetic and genomic research. In this study, two hawthorn cultivars, Qiujinxing and Damianqiu, and 107 progenies from a cross between them were used for constructing a high-density genetic linkage map using the 2b-restriction site-associated DNA (2b-RAD) sequencing method, as well as for mapping quantitative trait loci (QTL) for flavonoid content. In total, 206,411,693 single-end reads were obtained, with an average sequencing depth of 57× in the parents and 23× in the progeny. After quality trimming, 117,896 high-quality 2b-RAD tags were retained, of which 42,279 were polymorphic; of these, 12,951 markers were used for constructing the genetic linkage map. The map contained 17 linkage groups and 3,894 markers, with a total map length of 1,551.97 cM and an average marker interval of 0.40 cM. QTL mapping identified 21 QTLs associated with flavonoid content in 10 linkage groups, which explained 16.30-59.00% of the variance. This is the first high-density linkage map for hawthorn, which will serve as a basis for fine-scale QTL mapping and marker-assisted selection of important traits in hawthorn germplasm and will facilitate chromosome assignment for hawthorn whole-genome assemblies in the future.

GWASeq: targeted re-sequencing follow up to GWAS.

PubMed

Salomon, Matthew P; Li, Wai Lok Sibon; Edlund, Christopher K; Morrison, John; Fortini, Barbara K; Win, Aung Ko; Conti, David V; Thomas, Duncan C; Duggan, David; Buchanan, Daniel D; Jenkins, Mark A; Hopper, John L; Gallinger, Steven; Le Marchand, Loïc; Newcomb, Polly A; Casey, Graham; Marjoram, Paul

2016-03-03

For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called "missing" heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS. We investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called 'SNP-set' tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer. Here we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.

Genomic correlates of recombination rate and its variability across eight recombination maps in the western honey bee (Apis mellifera L.).

PubMed

Ross, Caitlin R; DeFelice, Dominick S; Hunt, Greg J; Ihle, Kate E; Amdam, Gro V; Rueppell, Olav

2015-02-21

Meiotic recombination has traditionally been explained based on the structural requirement to stabilize homologous chromosome pairs to ensure their proper meiotic segregation. Competing hypotheses seek to explain the emerging findings of significant heterogeneity in recombination rates within and between genomes, but intraspecific comparisons of genome-wide recombination patterns are rare. The honey bee (Apis mellifera) exhibits the highest rate of genomic recombination among multicellular animals with about five cross-over events per chromatid. Here, we present a comparative analysis of recombination rates across eight genetic linkage maps of the honey bee genome to investigate which genomic sequence features are correlated with recombination rate and with its variation across the eight data sets, ranging in average marker spacing ranging from 1 Mbp to 120 kbp. Overall, we found that GC content explained best the variation in local recombination rate along chromosomes at the analyzed 100 kbp scale. In contrast, variation among the different maps was correlated to the abundance of microsatellites and several specific tri- and tetra-nucleotides. The combined evidence from eight medium-scale recombination maps of the honey bee genome suggests that recombination rate variation in this highly recombining genome might be due to the DNA configuration instead of distinct sequence motifs. However, more fine-scale analyses are needed. The empirical basis of eight differing genetic maps allowed for robust conclusions about the correlates of the local recombination rates and enabled the study of the relation between DNA features and variability in local recombination rates, which is particularly relevant in the honey bee genome with its exceptionally high recombination rate.

Spatial characterization of the meltwater field from icebergs in the Weddell Sea.

PubMed

Helly, John J; Kaufmann, Ronald S; Vernet, Maria; Stephenson, Gordon R

2011-04-05

We describe the results from a spatial cyberinfrastructure developed to characterize the meltwater field around individual icebergs and integrate the results with regional- and global-scale data. During the course of the cyberinfrastructure development, it became clear that we were also building an integrated sampling planning capability across multidisciplinary teams that provided greater agility in allocating expedition resources resulting in new scientific insights. The cyberinfrastructure-enabled method is a complement to the conventional methods of hydrographic sampling in which the ship provides a static platform on a station-by-station basis. We adapted a sea-floor mapping method to more rapidly characterize the sea surface geophysically and biologically. By jointly analyzing the multisource, continuously sampled biological, chemical, and physical parameters, using Global Positioning System time as the data fusion key, this surface-mapping method enables us to examine the relationship between the meltwater field of the iceberg to the larger-scale marine ecosystem of the Southern Ocean. Through geospatial data fusion, we are able to combine very fine-scale maps of dynamic processes with more synoptic but lower-resolution data from satellite systems. Our results illustrate the importance of spatial cyberinfrastructure in the overall scientific enterprise and identify key interfaces and sources of error that require improved controls for the development of future Earth observing systems as we move into an era of peta- and exascale, data-intensive computing.

Spatial characterization of the meltwater field from icebergs in the Weddell Sea

PubMed Central

Helly, John J.; Kaufmann, Ronald S.; Vernet, Maria; Stephenson, Gordon R.

2011-01-01

We describe the results from a spatial cyberinfrastructure developed to characterize the meltwater field around individual icebergs and integrate the results with regional- and global-scale data. During the course of the cyberinfrastructure development, it became clear that we were also building an integrated sampling planning capability across multidisciplinary teams that provided greater agility in allocating expedition resources resulting in new scientific insights. The cyberinfrastructure-enabled method is a complement to the conventional methods of hydrographic sampling in which the ship provides a static platform on a station-by-station basis. We adapted a sea-floor mapping method to more rapidly characterize the sea surface geophysically and biologically. By jointly analyzing the multisource, continuously sampled biological, chemical, and physical parameters, using Global Positioning System time as the data fusion key, this surface-mapping method enables us to examine the relationship between the meltwater field of the iceberg to the larger-scale marine ecosystem of the Southern Ocean. Through geospatial data fusion, we are able to combine very fine-scale maps of dynamic processes with more synoptic but lower-resolution data from satellite systems. Our results illustrate the importance of spatial cyberinfrastructure in the overall scientific enterprise and identify key interfaces and sources of error that require improved controls for the development of future Earth observing systems as we move into an era of peta- and exascale, data-intensive computing. PMID:21444769

Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

NASA Astrophysics Data System (ADS)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.

Genetic fine-mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

PubMed Central

Mahajan, Anubha; Locke, Adam; Rayner, N William; Robertson, Neil; Scott, Robert A; Prokopenko, Inga; Scott, Laura J; Green, Todd; Sparso, Thomas; Thuillier, Dorothee; Yengo, Loic; Grallert, Harald; Wahl, Simone; Frånberg, Mattias; Strawbridge, Rona J; Kestler, Hans; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Li, Man; Chen, Han; Fuchsberger, Christian; Kwan, Phoenix; Ma, Clement; Linderman, Michael; Lu, Yingchang; Thomsen, Soren K; Rundle, Jana K; Beer, Nicola L; van de Bunt, Martijn; Chalisey, Anil; Kang, Hyun Min; Voight, Benjamin F; Abecasis, Goncalo R; Almgren, Peter; Baldassarre, Damiano; Balkau, Beverley; Benediktsson, Rafn; Blüher, Matthias; Boeing, Heiner; Bonnycastle, Lori L; Borringer, Erwin P; Burtt, Noël P; Carey, Jason; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn C; Couper, David J; Crenshaw, Andrew T; van Dam, Rob M; Doney, Alex SF; Dorkhan, Mozhgan; Edkins, Sarah; Eriksson, Johan G; Esko, Tonu; Eury, Elodie; Fadista, João; Flannick, Jason; Fontanillas, Pierre; Fox, Caroline; Franks, Paul W; Gertow, Karl; Gieger, Christian; Gigante, Bruna; Gottesman, Omri; Grant, George B; Grarup, Niels; Groves, Christopher J; Hassinen, Maija; Have, Christian T; Herder, Christian; Holmen, Oddgeir L; Hreidarsson, Astradur B; Humphries, Steve E; Hunter, David J; Jackson, Anne U; Jonsson, Anna; Jørgensen, Marit E; Jørgensen, Torben; Kerrison, Nicola D; Kinnunen, Leena; Klopp, Norman; Kong, Augustine; Kovacs, Peter; Kraft, Peter; Kravic, Jasmina; Langford, Cordelia; Leander, Karin; Liang, Liming; Lichtner, Peter; Lindgren, Cecilia M; Lindholm, Eero; Linneberg, Allan; Liu, Ching-Ti; Lobbens, Stéphane; Luan, Jian’an; Lyssenko, Valeriya; Männistö, Satu; McLeod, Olga; Meyer, Julia; Mihailov, Evelin; Mirza, Ghazala; Mühleisen, Thomas W; Müller-Nurasyid, Martina; Navarro, Carmen; Nöthen, Markus M; Oskolkov, Nikolay N; Owen, Katharine R; Palli, Domenico; Pechlivanis, Sonali; Perry, John RB; Platou, Carl GP; Roden, Michael; Ruderfer, Douglas; Rybin, Denis; van der Schouw, Yvonne T; Sennblad, Bengt; Sigurðsson, Gunnar; Stančáková, Alena; Steinbach, Gerald; Storm, Petter; Strauch, Konstantin; Stringham, Heather M; Sun, Qi; Thorand, Barbara; Tikkanen, Emmi; Tonjes, Anke; Trakalo, Joseph; Tremoli, Elena; Tuomi, Tiinamaija; Wennauer, Roman; Wood, Andrew R; Zeggini, Eleftheria; Dunham, Ian; Birney, Ewan; Pasquali, Lorenzo; Ferrer, Jorge; Loos, Ruth JF; Dupuis, Josée; Florez, Jose C; Boerwinkle, Eric; Pankow, James S; van Duijn, Cornelia; Sijbrands, Eric; Meigs, James B; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Lakka, Timo A; Rauramaa, Rainer; Stumvoll, Michael; Pedersen, Nancy L; Lind, Lars; Keinanen-Kiukaanniemi, Sirkka M; Korpi-Hyövälti, Eeva; Saaristo, Timo E; Saltevo, Juha; Kuusisto, Johanna; Laakso, Markku; Metspalu, Andres; Erbel, Raimund; Jöckel, Karl-Heinz; Moebus, Susanne; Ripatti, Samuli; Salomaa, Veikko; Ingelsson, Erik; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Koistinen, Heikki; Tuomilehto, Jaakko; Hveem, Kristian; Njølstad, Inger; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; de Faire, Ulf; Hamsten, Anders; Illig, Thomas; Peters, Annette; Cauchi, Stephane; Sladek, Rob; Froguel, Philippe; Hansen, Torben; Pedersen, Oluf; Morris, Andrew D; Palmer, Collin NA; Kathiresan, Sekar; Melander, Olle; Nilsson, Peter M; Groop, Leif C; Barroso, Inês; Langenberg, Claudia; Wareham, Nicholas J; O’Callaghan, Christopher A; Gloyn, Anna L; Altshuler, David; Boehnke, Michael; Teslovich, Tanya M; McCarthy, Mark I; Morris, Andrew P

2015-01-01

We performed fine-mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in/near KCNQ1. “Credible sets” of variants most likely to drive each distinct signal mapped predominantly to non-coding sequence, implying that T2D association is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine-mapping implicated rs10830963 as driving T2D association. We confirmed that this T2D-risk allele increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D-risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease. PMID:26551672

Construction of an SNP-based high-density linkage map for flax (Linum usitatissimum L.) using specific length amplified fragment sequencing (SLAF-seq) technology.

PubMed

Yi, Liuxi; Gao, Fengyun; Siqin, Bateer; Zhou, Yu; Li, Qiang; Zhao, Xiaoqing; Jia, Xiaoyun; Zhang, Hui

2017-01-01

Flax is an important crop for oil and fiber, however, no high-density genetic maps have been reported for this species. Specific length amplified fragment sequencing (SLAF-seq) is a high-resolution strategy for large scale de novo discovery and genotyping of single nucleotide polymorphisms. In this study, SLAF-seq was employed to develop SNP markers in an F2 population to construct a high-density genetic map for flax. In total, 196.29 million paired-end reads were obtained. The average sequencing depth was 25.08 in male parent, 32.17 in the female parent, and 9.64 in each F2 progeny. In total, 389,288 polymorphic SLAFs were detected, from which 260,380 polymorphic SNPs were developed. After filtering, 4,638 SNPs were found suitable for genetic map construction. The final genetic map included 4,145 SNP markers on 15 linkage groups and was 2,632.94 cM in length, with an average distance of 0.64 cM between adjacent markers. To our knowledge, this map is the densest SNP-based genetic map for flax. The SNP markers and genetic map reported in here will serve as a foundation for the fine mapping of quantitative trait loci (QTLs), map-based gene cloning and marker assisted selection (MAS) for flax.

Mapping local and global variability in plant trait distributions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Butler, Ethan E.; Datta, Abhirup; Flores-Moreno, Habacuc

2017-12-01

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusingmore » on a set of plant traits closely coupled to photosynthesis and foliar respiration—specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen (N m) and phosphorus (P m), we characterize how traits vary within and among over 50,000 ~50×50-km cells across the entire vegetated land surface. We do this in several ways—without defining the PFT of each grid cell and using 4 or 14 PFTs; each model’s predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps further reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.« less

Mapping local and global variability in plant trait distributions.

PubMed

Butler, Ethan E; Datta, Abhirup; Flores-Moreno, Habacuc; Chen, Ming; Wythers, Kirk R; Fazayeli, Farideh; Banerjee, Arindam; Atkin, Owen K; Kattge, Jens; Amiaud, Bernard; Blonder, Benjamin; Boenisch, Gerhard; Bond-Lamberty, Ben; Brown, Kerry A; Byun, Chaeho; Campetella, Giandiego; Cerabolini, Bruno E L; Cornelissen, Johannes H C; Craine, Joseph M; Craven, Dylan; de Vries, Franciska T; Díaz, Sandra; Domingues, Tomas F; Forey, Estelle; González-Melo, Andrés; Gross, Nicolas; Han, Wenxuan; Hattingh, Wesley N; Hickler, Thomas; Jansen, Steven; Kramer, Koen; Kraft, Nathan J B; Kurokawa, Hiroko; Laughlin, Daniel C; Meir, Patrick; Minden, Vanessa; Niinemets, Ülo; Onoda, Yusuke; Peñuelas, Josep; Read, Quentin; Sack, Lawren; Schamp, Brandon; Soudzilovskaia, Nadejda A; Spasojevic, Marko J; Sosinski, Enio; Thornton, Peter E; Valladares, Fernando; van Bodegom, Peter M; Williams, Mathew; Wirth, Christian; Reich, Peter B

2017-12-19

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means.

Robust visual object tracking with interleaved segmentation

NASA Astrophysics Data System (ADS)

Abel, Peter; Kieritz, Hilke; Becker, Stefan; Arens, Michael

2017-10-01

In this paper we present a new approach for tracking non-rigid, deformable objects by means of merging an on-line boosting-based tracker and a fast foreground background segmentation. We extend an on-line boosting- based tracker, which uses axes-aligned bounding boxes with fixed aspect-ratio as tracking states. By constructing a confidence map from the on-line boosting-based tracker and unifying this map with a confidence map, which is obtained from a foreground background segmentation algorithm, we build a superior confidence map. For constructing a rough confidence map of a new frame based on on-line boosting, we employ the responses of the strong classifier as well as the single weak classifier responses that were built before during the updating step. This confidence map provides a rough estimation of the object's position and dimension. In order to refine this confidence map, we build a fine, pixel-wisely segmented confidence map and merge both maps together. Our segmentation method is color-histogram-based and provides a fine and fast image segmentation. By means of back-projection and the Bayes' rule, we obtain a confidence value for every pixel. The rough and the fine confidence maps are merged together by building an adaptively weighted sum of both maps. The weights are obtained by utilizing the variances of both confidence maps. Further, we apply morphological operators in the merged confidence map in order to reduce the noise. In the resulting map we estimate the object localization and dimension via continuous adaptive mean shift. Our approach provides a rotated rectangle as tracking states, which enables a more precise description of non-rigid, deformable objects than axes-aligned bounding boxes. We evaluate our tracker on the visual object tracking (VOT) benchmark dataset 2016.

Accuracy of mapping the Earth's gravity field fine structure with a spaceborne gravity gradiometer mission

NASA Technical Reports Server (NTRS)

Kahn, W. D.

1984-01-01

The spaceborne gravity gradiometer is a potential sensor for mapping the fine structure of the Earth's gravity field. Error analyses were performed to investigate the accuracy of the determination of the Earth's gravity field from a gravity field satellite mission. The orbital height of the spacecraft is the dominating parameter as far as gravity field resolution and accuracies are concerned.

A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

EPA Science Inventory

Fine-scale Computational Fluid Dynamics (CFD) simulation of pollutant concentrations within roadway and building microenvironments is feasible using high performance computing. Unlike currently used regulatory air quality models, fine-scale CFD simulations are able to account rig...

Fine-mapping of qGW4.05, a major QTL for kernel weight and size in maize.

PubMed

Chen, Lin; Li, Yong-xiang; Li, Chunhui; Wu, Xun; Qin, Weiwei; Li, Xin; Jiao, Fuchao; Zhang, Xiaojing; Zhang, Dengfeng; Shi, Yunsu; Song, Yanchun; Li, Yu; Wang, Tianyu

2016-04-12

Kernel weight and size are important components of grain yield in cereals. Although some information is available concerning the map positions of quantitative trait loci (QTL) for kernel weight and size in maize, little is known about the molecular mechanisms of these QTLs. qGW4.05 is a major QTL that is associated with kernel weight and size in maize. We combined linkage analysis and association mapping to fine-map and identify candidate gene(s) at qGW4.05. QTL qGW4.05 was fine-mapped to a 279.6-kb interval in a segregating population derived from a cross of Huangzaosi with LV28. By combining the results of regional association mapping and linkage analysis, we identified GRMZM2G039934 as a candidate gene responsible for qGW4.05. Candidate gene-based association mapping was conducted using a panel of 184 inbred lines with variable kernel weights and kernel sizes. Six polymorphic sites in the gene GRMZM2G039934 were significantly associated with kernel weight and kernel size. The results of linkage analysis and association mapping revealed that GRMZM2G039934 is the most likely candidate gene for qGW4.05. These results will improve our understanding of the genetic architecture and molecular mechanisms underlying kernel development in maize.

Dusty Dwarfs Galaxies Occulting A Bright Background Spiral

NASA Astrophysics Data System (ADS)

Holwerda, Benne

2017-08-01

The role of dust in shaping the spectral energy distributions of low mass disk galaxies remains poorly understood. Recent results from the Herschel Space Observatory imply that dwarf galaxies contain large amounts of cool (T 20K) dust, coupled with very modest optical extinctions. These seemingly contradictory conclusions may be resolved if dwarfs harbor a variety of dust geometries, e.g., dust at larger galactocentric radii or in quiescent dark clumps. We propose HST observations of six truly occulting dwarf galaxies drawn from the Galaxy Zoo catalog of silhouetted galaxy pairs. Confirmed, true occulting dwarfs are rare as most low-mass disks in overlap are either close satellites or do not have a confirmed redshift. Dwarf occulters are the key to determining the spatial extent of dust, the small scale structure introduced by turbulence, and the prevailing dust attenuation law. The recent spectroscopic confirmation of bona-fide low mass occulting dwarfs offers an opportunity to map dust in these with HST. What is the role of dust in the SED of these dwarf disk galaxies? With shorter feedback scales, how does star-formation affect their morphology and dust composition, as revealed from their attenuation curve? The resolution of HST allows us to map the dust disks down to the fine scale structure of molecular clouds and multi-wavelength imaging maps the attenuation curve and hence dust composition in these disks. We therefore ask for 2 orbits on each of 6 dwarf galaxies in F275W, F475W, F606W, F814W and F125W to map dust from UV to NIR to constrain the attenuation curve.

From Google Maps to a fine-grained catalog of street trees

NASA Astrophysics Data System (ADS)

Branson, Steve; Wegner, Jan Dirk; Hall, David; Lang, Nico; Schindler, Konrad; Perona, Pietro

2018-01-01

Up-to-date catalogs of the urban tree population are of importance for municipalities to monitor and improve quality of life in cities. Despite much research on automation of tree mapping, mainly relying on dedicated airborne LiDAR or hyperspectral campaigns, tree detection and species recognition is still mostly done manually in practice. We present a fully automated tree detection and species recognition pipeline that can process thousands of trees within a few hours using publicly available aerial and street view images of Google MapsTM. These data provide rich information from different viewpoints and at different scales from global tree shapes to bark textures. Our work-flow is built around a supervised classification that automatically learns the most discriminative features from thousands of trees and corresponding, publicly available tree inventory data. In addition, we introduce a change tracker that recognizes changes of individual trees at city-scale, which is essential to keep an urban tree inventory up-to-date. The system takes street-level images of the same tree location at two different times and classifies the type of change (e.g., tree has been removed). Drawing on recent advances in computer vision and machine learning, we apply convolutional neural networks (CNN) for all classification tasks. We propose the following pipeline: download all available panoramas and overhead images of an area of interest, detect trees per image and combine multi-view detections in a probabilistic framework, adding prior knowledge; recognize fine-grained species of detected trees. In a later, separate module, track trees over time, detect significant changes and classify the type of change. We believe this is the first work to exploit publicly available image data for city-scale street tree detection, species recognition and change tracking, exhaustively over several square kilometers, respectively many thousands of trees. Experiments in the city of Pasadena, California, USA show that we can detect >70% of the street trees, assign correct species to >80% for 40 different species, and correctly detect and classify changes in >90% of the cases.

A matter of scale: apparent niche differentiation of diploid and tetraploid plants may depend on extent and grain of analysis.

PubMed

Kirchheimer, Bernhard; Schinkel, Christoph C F; Dellinger, Agnes S; Klatt, Simone; Moser, Dietmar; Winkler, Manuela; Lenoir, Jonathan; Caccianiga, Marco; Guisan, Antoine; Nieto-Lugilde, Diego; Svenning, Jens-Christian; Thuiller, Wilfried; Vittoz, Pascal; Willner, Wolfgang; Zimmermann, Niklaus E; Hörandl, Elvira; Dullinger, Stefan

2016-03-22

Emerging polyploids may depend on environmental niche shifts for successful establishment. Using the alpine plant Ranunculus kuepferi as a model system, we explore the niche shift hypothesis at different spatial resolutions and in contrasting parts of the species range. European Alps. We sampled 12 individuals from each of 102 populations of R. kuepferi across the Alps, determined their ploidy levels, derived coarse-grain (100 × 100 m) environmental descriptors for all sampling sites by downscaling WorldClim maps, and calculated fine-scale environmental descriptors (2 × 2 m) from indicator values of the vegetation accompanying the sampled individuals. Both coarse and fine-scale variables were further computed for 8239 vegetation plots from across the Alps. Subsequently, we compared niche optima and breadths of diploid and tetraploid cytotypes by combining principal components analysis and kernel smoothing procedures. Comparisons were done separately for coarse and fine-grain data sets and for sympatric, allopatric and the total set of populations. All comparisons indicate that the niches of the two cytotypes differ in optima and/or breadths, but results vary in important details. The whole-range analysis suggests differentiation along the temperature gradient to be most important. However, sympatric comparisons indicate that this climatic shift was not a direct response to competition with diploid ancestors. Moreover, fine-grained analyses demonstrate niche contraction of tetraploids, especially in the sympatric range, that goes undetected with coarse-grained data. Although the niche optima of the two cytotypes differ, separation along ecological gradients was probably less decisive for polyploid establishment than a shift towards facultative apomixis, a particularly effective strategy to avoid minority cytotype exclusion. In addition, our results suggest that coarse-grained analyses overestimate niche breadths of widely distributed taxa. Niche comparison analyses should hence be conducted at environmental data resolutions appropriate for the organism and question under study.

Ecology and space: A case study in mapping harmful invasive species

USGS Publications Warehouse

David T. Barnett,; Jarnevich, Catherine S.; Chong, Geneva W.; Stohlgren, Thomas J.; Sunil Kumar,; Holcombe, Tracy R.; Brunn, Stanley D.; Dodge, Martin

2017-01-01

The establishment and invasion of non-native plant species have the ability to alter the composition of native species and functioning of ecological systems with financial costs resulting from mitigation and loss of ecological services. Spatially documenting invasions has applications for management and theory, but the utility of maps is challenged by availability and uncertainty of data, and the reliability of extrapolating mapped data in time and space. The extent and resolution of projections also impact the ability to inform invasive species science and management. Early invasive species maps were coarse-grained representations that underscored the phenomena, but had limited capacity to direct management aside from development of watch lists for priorities for prevention and containment. Integrating mapped data sets with fine-resolution environmental variables in the context of species-distribution models allows a description of species-environment relationships and an understanding of how, why, and where invasions may occur. As with maps, the extent and resolution of models impact the resulting insight. Models of cheatgrass (Bromus tectorum) across a variety of spatial scales and grain result in divergent species-environment relationships. New data can improve models and efficiently direct further inventories. Mapping can target areas of greater model uncertainty or the bounds of modeled distribution to efficiently refine models and maps. This iterative process results in dynamic, living maps capable of describing the ongoing process of species invasions.

Construction of a high-density, high-resolution genetic map and its integration with BAC-based physical map in channel catfish

PubMed Central

Li, Yun; Liu, Shikai; Qin, Zhenkui; Waldbieser, Geoff; Wang, Ruijia; Sun, Luyang; Bao, Lisui; Danzmann, Roy G.; Dunham, Rex; Liu, Zhanjiang

2015-01-01

Construction of genetic linkage map is essential for genetic and genomic studies. Recent advances in sequencing and genotyping technologies made it possible to generate high-density and high-resolution genetic linkage maps, especially for the organisms lacking extensive genomic resources. In the present work, we constructed a high-density and high-resolution genetic map for channel catfish with three large resource families genotyped using the catfish 250K single-nucleotide polymorphism (SNP) array. A total of 54,342 SNPs were placed on the linkage map, which to our knowledge had the highest marker density among aquaculture species. The estimated genetic size was 3,505.4 cM with a resolution of 0.22 cM for sex-averaged genetic map. The sex-specific linkage maps spanned a total of 4,495.1 cM in females and 2,593.7 cM in males, presenting a ratio of 1.7 : 1 between female and male in recombination fraction. After integration with the previously established physical map, over 87% of physical map contigs were anchored to the linkage groups that covered a physical length of 867 Mb, accounting for ∼90% of the catfish genome. The integrated map provides a valuable tool for validating and improving the catfish whole-genome assembly and facilitates fine-scale QTL mapping and positional cloning of genes responsible for economically important traits. PMID:25428894

Fine mapping and characterization of candidate genes that control resistance to Cercospora Sojina K. Hara in two soybean germplasm accessions

USDA-ARS?s Scientific Manuscript database

In order to fine map the novel FLS resistance gene(s) in two PIs, PI 594891 and PI 594774, F2:3 seeds from the crosses Blackhawk (FLS susceptible genotype) ×PI 594891, and Blackhawk ×PI 594774 were genotyped with KASP markers that were designed based on the SoySNP 50k Infinium Chip data to identi...

Fine-scale variation of historical fire regimes in sagebrush-steppe and juniper woodland: An example from California, USA

Treesearch

Richard F. Miller; Emily K. Heyerdahl

2008-01-01

Coarse-scale estimates of fire intervals across the mountain big sagebrush (Artemisia tridentata spp. vaseyana (Rydb.) Beetle) alliance range from decades to centuries. However, soil depth and texture can affect the abundance and continuity of fine fuels and vary at fine spatial scales, suggesting fire regimes may vary at similar scales. We explored...

Fine-scale structure in the far-infrared Milky-Way

NASA Technical Reports Server (NTRS)

Waller, William H.; Wall, William F.; Reach, William T.; Varosi, Frank; Ebert, Rick; Laughlin, Gaylin; Boulanger, Francois

1995-01-01

This final report summarizes the work performed and which falls into five broad categories: (1) generation of a new data product (mosaics of the far-infrared emission in the Milky Way); (2) acquisition of associated data products at other wavelengths; (3) spatial filtering of the far-infrared mosaics and resulting images of the FIR fine-scale structure; (4) evaluation of the spatially filtered data; (5) characterization of the FIR fine-scale structure in terms of its spatial statistics; and (6) identification of interstellar counterparts to the FIR fine-scale structure.

Assessing and mapping spatial associations among oral cancer mortality rates, concentrations of heavy metals in soil, and land use types based on multiple scale data.

PubMed

Lin, Wei-Chih; Lin, Yu-Pin; Wang, Yung-Chieh; Chang, Tsun-Kuo; Chiang, Li-Chi

2014-02-21

In this study, a deconvolution procedure was used to create a variogram of oral cancer (OC) rates. Based on the variogram, area-to-point (ATP) Poisson kriging and p-field simulation were used to downscale and simulate, respectively, the OC rate data for Taiwan from the district scale to a 1 km × 1 km grid scale. Local cluster analysis (LCA) of OC mortality rates was then performed to identify OC mortality rate hot spots based on the downscaled and the p-field-simulated OC mortality maps. The relationship between OC mortality and land use was studied by overlapping the maps of the downscaled OC mortality, the LCA results, and the land uses. One thousand simulations were performed to quantify local and spatial uncertainties in the LCA to identify OC mortality hot spots. The scatter plots and Spearman's rank correlation yielded the relationship between OC mortality and concentrations of the seven metals in the 1 km cell grid. The correlation analysis results for the 1 km scale revealed a weak correlation between OC mortality rate and concentrations of the seven studied heavy metals in soil. Accordingly, the heavy metal concentrations in soil are not major determinants of OC mortality rates at the 1 km scale at which soils were sampled. The LCA statistical results for local indicator of spatial association (LISA) revealed that the sites with high probability of high-high (high value surrounded by high values) OC mortality at the 1 km grid scale were clustered in southern, eastern, and mid-western Taiwan. The number of such sites was also significantly higher on agricultural land and in urban regions than on land with other uses. The proposed approach can be used to downscale and evaluate uncertainty in mortality data from a coarse scale to a fine scale at which useful additional information can be obtained for assessing and managing land use and risk.

A low-cost drone based application for identifying and mapping of coastal fish nursery grounds

NASA Astrophysics Data System (ADS)

Ventura, Daniele; Bruno, Michele; Jona Lasinio, Giovanna; Belluscio, Andrea; Ardizzone, Giandomenico

2016-03-01

Acquiring seabed, landform or other topographic data in the field of marine ecology has a pivotal role in defining and mapping key marine habitats. However, accessibility for this kind of data with a high level of detail for very shallow and inaccessible marine habitats has been often challenging, time consuming. Spatial and temporal coverage often has to be compromised to make more cost effective the monitoring routine. Nowadays, emerging technologies, can overcome many of these constraints. Here we describe a recent development in remote sensing based on a small unmanned drone (UAVs) that produce very fine scale maps of fish nursery areas. This technology is simple to use, inexpensive, and timely in producing aerial photographs of marine areas. Both technical details regarding aerial photos acquisition (drone and camera settings) and post processing workflow (3D model generation with Structure From Motion algorithm and photo-stitching) are given. Finally by applying modern algorithm of semi-automatic image analysis and classification (Maximum Likelihood, ECHO and Object-based Image Analysis) we compared the results of three thematic maps of nursery area for juvenile sparid fishes, highlighting the potential of this method in mapping and monitoring coastal marine habitats.

High-Resolution Thermal Inertia Mapping from the Mars Global Surveyor Thermal Emission Spectrometer

USGS Publications Warehouse

Mellon, M.T.; Jakosky, B.M.; Kieffer, H.H.; Christensen, P.R.

2000-01-01

High-resolution thermal inertia mapping results are presented, derived from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) observations of the surface temperature of Mars obtained during the early portion of the MGS mapping mission. Thermal inertia is the key property controlling the diurnal surface temperature variations, and is dependent on the physical character of the top few centimeters of the surface. It represents a complex combination of particle size, rock abundance, exposures of bedrock, and degree of induration. In this work we describe the derivation of thermal inertia from TES data, present global scale analysis, and place these results into context with earlier work. A global map of nighttime thermal-bolometer-based thermal inertia is presented at 14?? per pixel resolution, with approximately 63% coverage between 50??S and 70??N latitude. Global analysis shows a similar pattern of high and low thermal inertia as seen in previous Viking low-resolution mapping. Significantly more detail is present in the high-resolution TES thermal inertia. This detail represents horizontal small-scale variability in the nature of the surface. Correlation with albedo indicates the presence of a previously undiscovered surface unit of moderate-to-high thermal inertia and intermediate albedo. This new unit has a modal peak thermal inertia of 180-250 J m-2 K-1 s-12 and a narrow range of albedo near 0.24. The unit, covering a significant fraction of the surface, typically surrounds the low thermal inertia regions and may comprise a deposit of indurated fine material. Local 3-km-resolution maps are also presented as examples of eolian, fluvial, and volcanic geology. Some impact crater rims and intracrater dunes show higher thermal inertias than the surrounding terrain; thermal inertia of aeolian deposits such as intracrater dunes may be related to average particle size. Outflow channels and valleys consistently show higher thermal inertias than the surrounding terrain. Generally, correlations between spatial variations in thermal inertia and geologic features suggest a relationship between the hundred-meter-scale morphology and the centimeter-scale surface layer. ?? 2000 Academic Press.

A large QTL for fear and anxiety mapped using an F2 cross can be dissected into multiple smaller QTLs.

PubMed

Parker, C C; Sokoloff, G; Leung, E; Kirkpatrick, S L; Palmer, A A

2013-10-01

Using chromosome substitution strains (CSS), we previously identified a large quantitative trait locus (QTL) for conditioned fear (CF) on mouse chromosome 10. Here, we used an F2 cross between CSS-10 and C57BL/6J (B6) to localize that QTL to distal chromosome 10. That QTL accounted for all the difference between CSS-10 and B6. We then produced congenic strains to fine-map that interval. We identified two congenic strains that captured some or all the QTL. The larger congenic strain (Line 1: 122.387121-129.068 Mb; build 37) appeared to account for all the difference between CSS-10 and B6. The smaller congenic strain (Line 2: 127.277-129.068 Mb) was intermediate between CSS-10 and B6. We used haplotype mapping followed by quantitative polymerase chain reaction to identify one gene that was differentially expressed in both lines relative to B6 (Rnf41) and one that was differentially expressed between only Line 1 and B6 (Shmt2). These cis-eQTLs may cause the behavioral QTLs; however, further studies are required to validate these candidate genes. More generally, our observation that a large QTL mapped using CSS and F2 crosses can be dissected into multiple smaller QTLs shows a weaknesses of two-stage approaches that seek to use coarse mapping to identify large regions followed by fine-mapping. Indeed, additional dissection of these congenic strains might result in further subdivision of these QTL regions. Despite these limitations, we have successfully fine-mapped two QTLs to small regions and identified putative candidate genes, showing that the congenic approach can be effective for fine-mapping QTLs. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.

PubMed

Gaulton, Kyle J; Ferreira, Teresa; Lee, Yeji; Raimondo, Anne; Mägi, Reedik; Reschen, Michael E; Mahajan, Anubha; Locke, Adam; Rayner, N William; Robertson, Neil; Scott, Robert A; Prokopenko, Inga; Scott, Laura J; Green, Todd; Sparso, Thomas; Thuillier, Dorothee; Yengo, Loic; Grallert, Harald; Wahl, Simone; Frånberg, Mattias; Strawbridge, Rona J; Kestler, Hans; Chheda, Himanshu; Eisele, Lewin; Gustafsson, Stefan; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Qi, Lu; Karssen, Lennart C; van Leeuwen, Elisabeth M; Willems, Sara M; Li, Man; Chen, Han; Fuchsberger, Christian; Kwan, Phoenix; Ma, Clement; Linderman, Michael; Lu, Yingchang; Thomsen, Soren K; Rundle, Jana K; Beer, Nicola L; van de Bunt, Martijn; Chalisey, Anil; Kang, Hyun Min; Voight, Benjamin F; Abecasis, Gonçalo R; Almgren, Peter; Baldassarre, Damiano; Balkau, Beverley; Benediktsson, Rafn; Blüher, Matthias; Boeing, Heiner; Bonnycastle, Lori L; Bottinger, Erwin P; Burtt, Noël P; Carey, Jason; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn C; Couper, David J; Crenshaw, Andrew T; van Dam, Rob M; Doney, Alex S F; Dorkhan, Mozhgan; Edkins, Sarah; Eriksson, Johan G; Esko, Tonu; Eury, Elodie; Fadista, João; Flannick, Jason; Fontanillas, Pierre; Fox, Caroline; Franks, Paul W; Gertow, Karl; Gieger, Christian; Gigante, Bruna; Gottesman, Omri; Grant, George B; Grarup, Niels; Groves, Christopher J; Hassinen, Maija; Have, Christian T; Herder, Christian; Holmen, Oddgeir L; Hreidarsson, Astradur B; Humphries, Steve E; Hunter, David J; Jackson, Anne U; Jonsson, Anna; Jørgensen, Marit E; Jørgensen, Torben; Kao, Wen-Hong L; Kerrison, Nicola D; Kinnunen, Leena; Klopp, Norman; Kong, Augustine; Kovacs, Peter; Kraft, Peter; Kravic, Jasmina; Langford, Cordelia; Leander, Karin; Liang, Liming; Lichtner, Peter; Lindgren, Cecilia M; Lindholm, Eero; Linneberg, Allan; Liu, Ching-Ti; Lobbens, Stéphane; Luan, Jian'an; Lyssenko, Valeriya; Männistö, Satu; McLeod, Olga; Meyer, Julia; Mihailov, Evelin; Mirza, Ghazala; Mühleisen, Thomas W; Müller-Nurasyid, Martina; Navarro, Carmen; Nöthen, Markus M; Oskolkov, Nikolay N; Owen, Katharine R; Palli, Domenico; Pechlivanis, Sonali; Peltonen, Leena; Perry, John R B; Platou, Carl G P; Roden, Michael; Ruderfer, Douglas; Rybin, Denis; van der Schouw, Yvonne T; Sennblad, Bengt; Sigurðsson, Gunnar; Stančáková, Alena; Steinbach, Gerald; Storm, Petter; Strauch, Konstantin; Stringham, Heather M; Sun, Qi; Thorand, Barbara; Tikkanen, Emmi; Tonjes, Anke; Trakalo, Joseph; Tremoli, Elena; Tuomi, Tiinamaija; Wennauer, Roman; Wiltshire, Steven; Wood, Andrew R; Zeggini, Eleftheria; Dunham, Ian; Birney, Ewan; Pasquali, Lorenzo; Ferrer, Jorge; Loos, Ruth J F; Dupuis, Josée; Florez, Jose C; Boerwinkle, Eric; Pankow, James S; van Duijn, Cornelia; Sijbrands, Eric; Meigs, James B; Hu, Frank B; Thorsteinsdottir, Unnur; Stefansson, Kari; Lakka, Timo A; Rauramaa, Rainer; Stumvoll, Michael; Pedersen, Nancy L; Lind, Lars; Keinanen-Kiukaanniemi, Sirkka M; Korpi-Hyövälti, Eeva; Saaristo, Timo E; Saltevo, Juha; Kuusisto, Johanna; Laakso, Markku; Metspalu, Andres; Erbel, Raimund; Jöcke, Karl-Heinz; Moebus, Susanne; Ripatti, Samuli; Salomaa, Veikko; Ingelsson, Erik; Boehm, Bernhard O; Bergman, Richard N; Collins, Francis S; Mohlke, Karen L; Koistinen, Heikki; Tuomilehto, Jaakko; Hveem, Kristian; Njølstad, Inger; Deloukas, Panagiotis; Donnelly, Peter J; Frayling, Timothy M; Hattersley, Andrew T; de Faire, Ulf; Hamsten, Anders; Illig, Thomas; Peters, Annette; Cauchi, Stephane; Sladek, Rob; Froguel, Philippe; Hansen, Torben; Pedersen, Oluf; Morris, Andrew D; Palmer, Collin N A; Kathiresan, Sekar; Melander, Olle; Nilsson, Peter M; Groop, Leif C; Barroso, Inês; Langenberg, Claudia; Wareham, Nicholas J; O'Callaghan, Christopher A; Gloyn, Anna L; Altshuler, David; Boehnke, Michael; Teslovich, Tanya M; McCarthy, Mark I; Morris, Andrew P

2015-12-01

We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.

SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

PubMed

Pauli, Benjamin P; McCann, Nicholas P; Zollner, Patrick A; Cummings, Robert; Gilbert, Jonathan H; Gustafson, Eric J

2013-01-01

Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH's capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of SEARCH for a variety of applications and illustrate benefits it can provide for conservation planning.

Principles for problem aggregation and assignment in medium scale multiprocessors

NASA Technical Reports Server (NTRS)

Nicol, David M.; Saltz, Joel H.

1987-01-01

One of the most important issues in parallel processing is the mapping of workload to processors. This paper considers a large class of problems having a high degree of potential fine grained parallelism, and execution requirements that are either not predictable, or are too costly to predict. The main issues in mapping such a problem onto medium scale multiprocessors are those of aggregation and assignment. We study a method of parameterized aggregation that makes few assumptions about the workload. The mapping of aggregate units of work onto processors is uniform, and exploits locality of workload intensity to balance the unknown workload. In general, a finer aggregate granularity leads to a better balance at the price of increased communication/synchronization costs; the aggregation parameters can be adjusted to find a reasonable granularity. The effectiveness of this scheme is demonstrated on three model problems: an adaptive one-dimensional fluid dynamics problem with message passing, a sparse triangular linear system solver on both a shared memory and a message-passing machine, and a two-dimensional time-driven battlefield simulation employing message passing. Using the model problems, the tradeoffs are studied between balanced workload and the communication/synchronization costs. Finally, an analytical model is used to explain why the method balances workload and minimizes the variance in system behavior.

Modelling the Risk Posed by the Zebra Mussel Dreissena polymorpha: Italy as a Case Study

NASA Astrophysics Data System (ADS)

Bosso, Luciano; De Conno, Carmelina; Russo, Danilo

2017-08-01

We generated a risk map to forecast the potential effects of the spreading of zebra mussels Dreissena polymorpha across the Italian territory. We assessed the invader's potential impact on rivers, lakes, watersheds and dams at a fine-grained scale and detected those more at risk that should be targeted with appropriate monitoring. We developed a MaxEnt model and employed weighted overlay analyses to detect the species' potential distribution and generate risk maps for Italy. D. polymorpha has a greater probability of occurring at low to medium altitudes in areas characterised by fluviatile deposits of major streams. Northern and central Italy appear more at risk. Some hydroelectric power dams are at high risk, while most dams for irrigation, drinkable water reservoirs and other dam types are at medium to low risk. The lakes and rivers reaches (representing likely expansion pathways) at medium-high or high risk mostly occur in northern and central Italy. We highlight the importance of modelling potential invasions on a country scale to achieve the sufficient resolution needed to develop appropriate monitoring plans and prevent the invader's harmful effects. Further high-resolution risk maps are needed for other regions partly or not yet colonised by the zebra mussel.

15 years of zooming in and zooming out: Developing a new single scale national active fault database of New Zealand

NASA Astrophysics Data System (ADS)

Ries, William; Langridge, Robert; Villamor, Pilar; Litchfield, Nicola; Van Dissen, Russ; Townsend, Dougal; Lee, Julie; Heron, David; Lukovic, Biljana

2014-05-01

In New Zealand, we are currently reconciling multiple digital coverages of mapped active faults into a national coverage at a single scale (1:250,000). This seems at first glance to be a relatively simple task. However, methods used to capture data, the scale of capture, and the initial purpose of the fault mapping, has produced datasets that have very different characteristics. The New Zealand digital active fault database (AFDB) was initially developed as a way of managing active fault locations and fault-related features within a computer-based spatial framework. The data contained within the AFDB comes from a wide range of studies, from plate tectonic (1:500,000) to cadastral (1:2,000) scale. The database was designed to allow capture of field observations and remotely sourced data without a loss in data resolution. This approach has worked well as a method for compiling a centralised database for fault information but not for providing a complete national coverage at a single scale. During the last 15 years other complementary projects have used and also contributed data to the AFDB, most notably the QMAP project (a national series of geological maps completed over 19 years that include coverage of active and inactive faults at 1:250,000). AFDB linework and attributes was incorporated into this series but simplification of linework and attributes has occurred to maintain map clarity at 1:250,000 scale. Also, during this period on-going mapping of active faults has improved upon these data. Other projects of note that have used data from the AFDB include the National Seismic Hazard Model of New Zealand and the Global Earthquake Model (GEM). The main goal of the current project has been to provide the best digital spatial representation of a fault trace at 1:250,000 scale and combine this with the most up to date attributes. In some areas this has required a simplification of very fine detailed data and in some cases new mapping to provide a complete coverage. Where datasets have conflicting line work and/or attributes, data was reviewed through consultation with authors or review of published research to ensure the most to date representation was maintained. The current project aims to provide a coverage that will be consistent between the AFDB and QMAP digital and provide a free download of these data on the AFDB website (http://data.gns.cri.nz/af/).

Fine-mapping of lipid regions in global populations discovers ethnic-specific signals and refines previously identified lipid loci.

PubMed

Zubair, Niha; Graff, Mariaelisa; Luis Ambite, Jose; Bush, William S; Kichaev, Gleb; Lu, Yingchang; Manichaikul, Ani; Sheu, Wayne H-H; Absher, Devin; Assimes, Themistocles L; Bielinski, Suzette J; Bottinger, Erwin P; Buzkova, Petra; Chuang, Lee-Ming; Chung, Ren-Hua; Cochran, Barbara; Dumitrescu, Logan; Gottesman, Omri; Haessler, Jeffrey W; Haiman, Christopher; Heiss, Gerardo; Hsiung, Chao A; Hung, Yi-Jen; Hwu, Chii-Min; Juang, Jyh-Ming J; Le Marchand, Loic; Lee, I-Te; Lee, Wen-Jane; Lin, Li-An; Lin, Danyu; Lin, Shih-Yi; Mackey, Rachel H; Martin, Lisa W; Pasaniuc, Bogdan; Peters, Ulrike; Predazzi, Irene; Quertermous, Thomas; Reiner, Alex P; Robinson, Jennifer; Rotter, Jerome I; Ryckman, Kelli K; Schreiner, Pamela J; Stahl, Eli; Tao, Ran; Tsai, Michael Y; Waite, Lindsay L; Wang, Tzung-Dau; Buyske, Steven; Ida Chen, Yii-Der; Cheng, Iona; Crawford, Dana C; Loos, Ruth J F; Rich, Stephen S; Fornage, Myriam; North, Kari E; Kooperberg, Charles; Carty, Cara L

2016-12-15

Genome-wide association studies have identified over 150 loci associated with lipid traits, however, no large-scale studies exist for Hispanics and other minority populations. Additionally, the genetic architecture of lipid-influencing loci remains largely unknown. We performed one of the most racially/ethnically diverse fine-mapping genetic studies of HDL-C, LDL-C, and triglycerides to-date using SNPs on the MetaboChip array on 54,119 individuals: 21,304 African Americans, 19,829 Hispanic Americans, 12,456 Asians, and 530 American Indians. The majority of signals found in these groups generalize to European Americans. While we uncovered signals unique to racial/ethnic populations, we also observed systematically consistent lipid associations across these groups. In African Americans, we identified three novel signals associated with HDL-C (LPL, APOA5, LCAT) and two associated with LDL-C (ABCG8, DHODH). In addition, using this population, we refined the location for 16 out of the 58 known MetaboChip lipid loci. These results can guide tailored screening efforts, reveal population-specific responses to lipid-lowering medications, and aid in the development of new targeted drug therapies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Integration of ALOS/PALSAR backscatter with a LiDAR-derived canopy height map to quantify forest fragmentation

NASA Astrophysics Data System (ADS)

Pinto, N.; Dubayah, R.; Simard, M.; Fatoyinbo, T. E.

2011-12-01

Habitat loss is the main predictor of species extinctions and must be characterized in high-biodiversity ecosystems where land cover change is pervasive. Forests' ability to support viable animal populations is typically modeled as a function of the presence of linkages or corridors, and quantified with fragmentation metrics. In this scenario, small forest patches and linear (e.g. riparian) zones can act as keystone structures. Fine-resolution, all-weather Synthetic Aperture Radar (SAR) data from ALOS/PALSAR is well-suited to resolve forest fragments in tropical sites. This study summarizes a technique for integrating fragmentation metrics from ALOS/PALSAR with vertical structure data from ICESat/GLAS to produce fine-resolution (30 m) forest habitat metrics that capture both local quality (canopy height) as well as spatial context and multi-scale connectivity. We illustrate our approach with backscatter images acquired over the Brazilian Atlantic Forest, a biodiversity hotspot. ALOS/PALSAR 1.1 images acquired over the dry season were calibrated to calculate gamma naught and map forest cover via tresholding. We employ network algorithms to locate dispersal bottlenecks between conservation units. The location of keystone structures is compared against a model that uses coarse (500m) percent tree cover as an input.

Fine resolution mapping of population age-structures for health and development applications

PubMed Central

Alegana, V. A.; Atkinson, P. M.; Pezzulo, C.; Sorichetta, A.; Weiss, D.; Bird, T.; Erbach-Schoenberg, E.; Tatem, A. J.

2015-01-01

The age-group composition of populations varies considerably across the world, and obtaining accurate, spatially detailed estimates of numbers of children under 5 years is important in designing vaccination strategies, educational planning or maternal healthcare delivery. Traditionally, such estimates are derived from population censuses, but these can often be unreliable, outdated and of coarse resolution for resource-poor settings. Focusing on Nigeria, we use nationally representative household surveys and their cluster locations to predict the proportion of the under-five population in 1 × 1 km using a Bayesian hierarchical spatio-temporal model. Results showed that land cover, travel time to major settlements, night-time lights and vegetation index were good predictors and that accounting for fine-scale variation, rather than assuming a uniform proportion of under 5 year olds can result in significant differences in health metrics. The largest gaps in estimated bednet and vaccination coverage were in Kano, Katsina and Jigawa. Geolocated household surveys are a valuable resource for providing detailed, contemporary and regularly updated population age-structure data in the absence of recent census data. By combining these with covariate layers, age-structure maps of unprecedented detail can be produced to guide the targeting of interventions in resource-poor settings. PMID:25788540

Prospects of Fine-Mapping Trait-Associated Genomic Regions by Using Summary Statistics from Genome-wide Association Studies.

PubMed

Benner, Christian; Havulinna, Aki S; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ripatti, Samuli; Pirinen, Matti

2017-10-05

During the past few years, various novel statistical methods have been developed for fine-mapping with the use of summary statistics from genome-wide association studies (GWASs). Although these approaches require information about the linkage disequilibrium (LD) between variants, there has not been a comprehensive evaluation of how estimation of the LD structure from reference genotype panels performs in comparison with that from the original individual-level GWAS data. Using population genotype data from Finland and the UK Biobank, we show here that a reference panel of 1,000 individuals from the target population is adequate for a GWAS cohort of up to 10,000 individuals, whereas smaller panels, such as those from the 1000 Genomes Project, should be avoided. We also show, both theoretically and empirically, that the size of the reference panel needs to scale with the GWAS sample size; this has important consequences for the application of these methods in ongoing GWAS meta-analyses and large biobank studies. We conclude by providing software tools and by recommending practices for sharing LD information to more efficiently exploit summary statistics in genetics research. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Fine and distributed subcellular retinotopy of excitatory inputs to the dendritic tree of a collision-detecting neuron

PubMed Central

Zhu, Ying

2016-01-01

Individual neurons in several sensory systems receive synaptic inputs organized according to subcellular topographic maps, yet the fine structure of this topographic organization and its relation to dendritic morphology have not been studied in detail. Subcellular topography is expected to play a role in dendritic integration, particularly when dendrites are extended and active. The lobula giant movement detector (LGMD) neuron in the locust visual system is known to receive topographic excitatory inputs on part of its dendritic tree. The LGMD responds preferentially to objects approaching on a collision course and is thought to implement several interesting dendritic computations. To study the fine retinotopic mapping of visual inputs onto the excitatory dendrites of the LGMD, we designed a custom microscope allowing visual stimulation at the native sampling resolution of the locust compound eye while simultaneously performing two-photon calcium imaging on excitatory dendrites. We show that the LGMD receives a distributed, fine retinotopic projection from the eye facets and that adjacent facets activate overlapping portions of the same dendritic branches. We also demonstrate that adjacent retinal inputs most likely make independent synapses on the excitatory dendrites of the LGMD. Finally, we show that the fine topographic mapping can be studied using dynamic visual stimuli. Our results reveal the detailed structure of the dendritic input originating from individual facets on the eye and their relation to that of adjacent facets. The mapping of visual space onto the LGMD's dendrites is expected to have implications for dendritic computation. PMID:27009157

Mapping, fine mapping, and molecular dissection of quantitative trait Loci in domestic animals.

PubMed

Georges, Michel

2007-01-01

Artificial selection has created myriad breeds of domestic animals, each characterized by unique phenotypes pertaining to behavior, morphology, physiology, and disease. Most domestic animal populations share features with isolated founder populations, making them well suited for positional cloning. Genome sequences are now available for most domestic species, and with them a panoply of tools including high-density single-nucleotide polymorphism panels. As a result, domestic animal populations are becoming invaluable resources for studying the molecular architecture of complex traits and of adaptation. Here we review recent progress and issues in the positional identification of genes underlying complex traits in domestic animals. As many phenotypes studied in animals are quantitative, we focus on mapping, fine mapping, and cloning of quantitative trait loci.

a Structure of Experienced Time

NASA Astrophysics Data System (ADS)

Havel, Ivan M.

2005-10-01

The subjective experience of time will be taken as a primary motivation for an alternative, essentially discontinuous conception of time. Two types of such experience will be discussed, one based on personal episodic memory, the other on the theoretical fine texture of experienced time below the threshold of phenomenal awareness. The former case implies a discrete structure of temporal episodes on a large scale, while the latter case suggests endowing psychological time with a granular structure on a small scale, i.e. interpreting it as a semi-ordered flow of smeared (not point-like) subliminal time grains. Only on an intermediate temporal scale would the subjectively felt continuity and fluency of time emerge. Consequently, there is no locally smooth mapping of phenomenal time onto the real number continuum. Such a model has certain advantages; for instance, it avoids counterintuitive interpretations of some neuropsychological experiments (e.g. Libet's measurement) in which the temporal order of events is crucial.

Sinking Maps: A Conceptual Tool for Visual Metaphor

ERIC Educational Resources Information Center

Giampa, Joan Marie

2012-01-01

Sinking maps, created by Northern Virginia Community College professor Joan Marie Giampa, are tools that teach fine art students how to construct visual metaphor by conceptually mapping sensory perceptions. Her dissertation answers the question, "Can visual metaphor be conceptually mapped in the art classroom?" In the Prologue, Giampa…

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

Saturation of an Intra-Gene Pool Linkage Map: Towards a Unified Consensus Linkage Map for Fine Mapping and Synteny Analysis in Common Bean

PubMed Central

Galeano, Carlos H.; Fernandez, Andrea C.; Franco-Herrera, Natalia; Cichy, Karen A.; McClean, Phillip E.; Vanderleyden, Jos; Blair, Matthew W.

2011-01-01

Map-based cloning and fine mapping to find genes of interest and marker assisted selection (MAS) requires good genetic maps with reproducible markers. In this study, we saturated the linkage map of the intra-gene pool population of common bean DOR364×BAT477 (DB) by evaluating 2,706 molecular markers including SSR, SNP, and gene-based markers. On average the polymorphism rate was 7.7% due to the narrow genetic base between the parents. The DB linkage map consisted of 291 markers with a total map length of 1,788 cM. A consensus map was built using the core mapping populations derived from inter-gene pool crosses: DOR364×G19833 (DG) and BAT93×JALO EEP558 (BJ). The consensus map consisted of a total of 1,010 markers mapped, with a total map length of 2,041 cM across 11 linkage groups. On average, each linkage group on the consensus map contained 91 markers of which 83% were single copy markers. Finally, a synteny analysis was carried out using our highly saturated consensus maps compared with the soybean pseudo-chromosome assembly. A total of 772 marker sequences were compared with the soybean genome. A total of 44 syntenic blocks were identified. The linkage group Pv6 presented the most diverse pattern of synteny with seven syntenic blocks, and Pv9 showed the most consistent relations with soybean with just two syntenic blocks. Additionally, a co-linear analysis using common bean transcript map information against soybean coding sequences (CDS) revealed the relationship with 787 soybean genes. The common bean consensus map has allowed us to map a larger number of markers, to obtain a more complete coverage of the common bean genome. Our results, combined with synteny relationships provide tools to increase marker density in selected genomic regions to identify closely linked polymorphic markers for indirect selection, fine mapping or for positional cloning. PMID:22174773

Fine Mapping for Identification of Citrus Alternaria Brown Spot Candidate Resistance Genes and Development of New SNP Markers for Marker-Assisted Selection

PubMed Central

Cuenca, Jose; Aleza, Pablo; Garcia-Lor, Andres; Ollitrault, Patrick; Navarro, Luis

2016-01-01

Alternaria brown spot (ABS) is a serious disease affecting susceptible citrus genotypes, which is a strong concern regarding citrus breeding programs. Resistance is conferred by a recessive locus (ABSr) previously located by our group within a 3.3 Mb genome region near the centromere in chromosome III. This work addresses fine-linkage mapping of this region for identifying candidate resistance genes and develops new molecular markers for ABS-resistance effective marker-assisted selection (MAS). Markers closely linked to ABSr locus were used for fine mapping using a 268-segregating diploid progeny derived from a heterozygous susceptible × resistant cross. Fine mapping limited the genomic region containing the ABSr resistance gene to 366 kb, flanked by markers at 0.4 and 0.7 cM. This region contains nine genes related to pathogen resistance. Among them, eight are resistance (R) gene homologs, with two of them harboring a serine/threonine protein kinase domain. These two genes along with a gene encoding a S-adenosyl-L-methionine-dependent-methyltransferase protein, should be considered as strong candidates for ABS-resistance. Moreover, the closest SNP was genotyped in 40 citrus varieties, revealing very high association with the resistant/susceptible phenotype. This new marker is currently used in our citrus breeding program for ABS-resistant parent and cultivar selection, at diploid, triploid and tetraploid level. PMID:28066498

Satellite Remote Sensing of Cropland Characteristics in 30m Resolution: The First North American Continental-Scale Classification on High Performance Computing Platforms

NASA Astrophysics Data System (ADS)

Massey, Richard

Cropland characteristics and accurate maps of their spatial distribution are required to develop strategies for global food security by continental-scale assessments and agricultural land use policies. North America is the major producer and exporter of coarse grains, wheat, and other crops. While cropland characteristics such as crop types are available at country-scales in North America, however, at continental-scale cropland products are lacking at fine sufficient resolution such as 30m. Additionally, applications of automated, open, and rapid methods to map cropland characteristics over large areas without the need of ground samples are needed on efficient high performance computing platforms for timely and long-term cropland monitoring. In this study, I developed novel, automated, and open methods to map cropland extent, crop intensity, and crop types in the North American continent using large remote sensing datasets on high-performance computing platforms. First, a novel method was developed in this study to fuse pixel-based classification of continental-scale Landsat data using Random Forest algorithm available on Google Earth Engine cloud computing platform with an object-based classification approach, recursive hierarchical segmentation (RHSeg) to map cropland extent at continental scale. Using the fusion method, a continental-scale cropland extent map for North America at 30m spatial resolution for the nominal year 2010 was produced. In this map, the total cropland area for North America was estimated at 275.2 million hectares (Mha). This map was assessed for accuracy using randomly distributed samples derived from United States Department of Agriculture (USDA) cropland data layer (CDL), Agriculture and Agri-Food Canada (AAFC) annual crop inventory (ACI), Servicio de Informacion Agroalimentaria y Pesquera (SIAP), Mexico's agricultural boundaries, and photo-interpretation of high-resolution imagery. The overall accuracies of the map are 93.4% with a producer's accuracy for crop class at 85.4% and user's accuracy of 74.5% across the continent. The sub-country statistics including state-wise and county-wise cropland statistics derived from this map compared well in regression models resulting in R2 > 0.84. Secondly, an automated phenological pattern matching (PPM) method to efficiently map cropping intensity was also developed in this study. This study presents a continental-scale cropping intensity map for the North American continent at 250m spatial resolution for 2010. In this map, the total areas for single crop, double crop, continuous crop, and fallow were estimated to be 123.5 Mha, 11.1 Mha, 64.0 Mha, and 83.4 Mha, respectively. This map was assessed using limited country-level reference datasets derived from United States Department of Agriculture cropland data layer and Agriculture and Agri-Food Canada annual crop inventory with overall accuracies of 79.8% and 80.2%, respectively. Third, two novel and automated decision tree classification approaches to map crop types across the conterminous United States (U.S.) using MODIS 250 m resolution data: 1) generalized, and 2) year-specific classification were developed. The classification approaches use similarities and dissimilarities in crop type phenology derived from NDVI time-series data for the two approaches. Annual crop type maps were produced for 8 major crop types in the United States using the generalized classification approach for 2001-2014 and the year-specific approach for 2008, 2010, 2011 and 2012. The year-specific classification had overall accuracies greater than 78%, while the generalized classifier had accuracies greater than 75% for the conterminous U.S. for 2008, 2010, 2011, and 2012. The generalized classifier enables automated and routine crop type mapping without repeated and expensive ground sample collection year after year with overall accuracies > 70% across all independent years. Taken together, these cropland products of extent, cropping intensity, and crop types, are significantly beneficial in agricultural and water use planning and monitoring to formulate policies towards global and North American food security issues.

Fine-scale habitat modeling of a top marine predator: do prey data improve predictive capacity?

PubMed

Torres, Leigh G; Read, Andrew J; Halpin, Patrick

2008-10-01

Predators and prey assort themselves relative to each other, the availability of resources and refuges, and the temporal and spatial scale of their interaction. Predictive models of predator distributions often rely on these relationships by incorporating data on environmental variability and prey availability to determine predator habitat selection patterns. This approach to predictive modeling holds true in marine systems where observations of predators are logistically difficult, emphasizing the need for accurate models. In this paper, we ask whether including prey distribution data in fine-scale predictive models of bottlenose dolphin (Tursiops truncatus) habitat selection in Florida Bay, Florida, U.S.A., improves predictive capacity. Environmental characteristics are often used as predictor variables in habitat models of top marine predators with the assumption that they act as proxies of prey distribution. We examine the validity of this assumption by comparing the response of dolphin distribution and fish catch rates to the same environmental variables. Next, the predictive capacities of four models, with and without prey distribution data, are tested to determine whether dolphin habitat selection can be predicted without recourse to describing the distribution of their prey. The final analysis determines the accuracy of predictive maps of dolphin distribution produced by modeling areas of high fish catch based on significant environmental characteristics. We use spatial analysis and independent data sets to train and test the models. Our results indicate that, due to high habitat heterogeneity and the spatial variability of prey patches, fine-scale models of dolphin habitat selection in coastal habitats will be more successful if environmental variables are used as predictor variables of predator distributions rather than relying on prey data as explanatory variables. However, predictive modeling of prey distribution as the response variable based on environmental variability did produce high predictive performance of dolphin habitat selection, particularly foraging habitat.

SNP discovery by high-throughput sequencing in soybean

PubMed Central

2010-01-01

Background With the advance of new massively parallel genotyping technologies, quantitative trait loci (QTL) fine mapping and map-based cloning become more achievable in identifying genes for important and complex traits. Development of high-density genetic markers in the QTL regions of specific mapping populations is essential for fine-mapping and map-based cloning of economically important genes. Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variation existing between any diverse genotypes that are usually used for QTL mapping studies. The massively parallel sequencing technologies (Roche GS/454, Illumina GA/Solexa, and ABI/SOLiD), have been widely applied to identify genome-wide sequence variations. However, it is still remains unclear whether sequence data at a low sequencing depth are enough to detect the variations existing in any QTL regions of interest in a crop genome, and how to prepare sequencing samples for a complex genome such as soybean. Therefore, with the aims of identifying SNP markers in a cost effective way for fine-mapping several QTL regions, and testing the validation rate of the putative SNPs predicted with Solexa short sequence reads at a low sequencing depth, we evaluated a pooled DNA fragment reduced representation library and SNP detection methods applied to short read sequences generated by Solexa high-throughput sequencing technology. Results A total of 39,022 putative SNPs were identified by the Illumina/Solexa sequencing system using a reduced representation DNA library of two parental lines of a mapping population. The validation rates of these putative SNPs predicted with low and high stringency were 72% and 85%, respectively. One hundred sixty four SNP markers resulted from the validation of putative SNPs and have been selectively chosen to target a known QTL, thereby increasing the marker density of the targeted region to one marker per 42 K bp. Conclusions We have demonstrated how to quickly identify large numbers of SNPs for fine mapping of QTL regions by applying massively parallel sequencing combined with genome complexity reduction techniques. This SNP discovery approach is more efficient for targeting multiple QTL regions in a same genetic population, which can be applied to other crops. PMID:20701770

Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats

PubMed Central

Holl, Katie L.; Oreper, Daniel; Xie, Yuying; Tsaih, Shirng-Wern; Valdar, William

2012-01-01

Type 2 diabetes (T2D) is a disease of relative insulin deficiency resulting from both insulin resistance and beta cell failure. We have previously used heterogeneous stock (HS) rats to fine-map a locus for glucose tolerance. We show here that glucose intolerance in the founder strains of the HS colony is mediated by different mechanisms: insulin resistance in WKY and an insulin secretion defect in ACI, and we demonstrate a high degree of variability for measures of insulin resistance and insulin secretion in HS rats. As such, our goal was to use HS rats to fine-map several diabetes-related traits within a region on rat chromosome 1. We measured blood glucose and plasma insulin levels after a glucose tolerance test in 782 male HS rats. Using 97 SSLP markers, we genotyped a 68 Mb region on rat chromosome 1 previously implicated in glucose and insulin regulation. We used linkage disequilibrium mapping by mixed model regression with inferred descent to identify a region from 198.85 to 205.9 that contains one or more quantitative trait loci (QTL) for fasting insulin and a measure of insulin resistance, the quantitative insulin sensitivity check index. This region also encompasses loci identified for fasting glucose and Insulin_AUC (area under the curve). A separate <3 Mb QTL was identified for body weight. Using a novel penalized regression method we then estimated effects of alternative haplotype pairings under each locus. These studies highlight the utility of HS rats for fine-mapping genetic loci involved in the underlying causes of T2D. PMID:22947656

Large-Scale CTRW Analysis of Push-Pull Tracer Tests and Other Transport in Heterogeneous Porous Media

NASA Astrophysics Data System (ADS)

Hansen, S. K.; Berkowitz, B.

2014-12-01

Recently, we developed an alternative CTRW formulation which uses a "latching" upscaling scheme to rigorously map continuous or fine-scale stochastic solute motion onto discrete transitions on an arbitrarily coarse lattice (with spacing potentially on the meter scale or more). This approach enables model simplification, among many other things. Under advection, for example, we see that many relevant anomalous transport problems may be mapped into 1D, with latching to a sequence of successive, uniformly spaced planes. On this formulation (which we term RP-CTRW), the spatial transition vector may generally be made deterministic, with CTRW waiting time distributions encapsulating all the stochastic behavior. We demonstrate the excellent performance of this technique alongside Pareto-distributed waiting times in explaining experiments across a variety of scales using only two degrees of freedom. An interesting new application of the RP-CTRW technique is the analysis of radial (push-pull) tracer tests. Given modern computational power, random walk simulations are a natural fit for the inverse problem of inferring subsurface parameters from push-pull test data, and we propose them as an alternative to the classical type curve approach. In particular, we explore the visibility of heterogeneity through non-Fickian behavior in push-pull tests, and illustrate the ability of a radial RP-CTRW technique to encapsulate this behavior using a sparse parameterization which has predictive value.

Spatial consistency of Chinook salmon redd distribution within and among years in the Cowlitz River, Washington

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klett, Katherine J.; Torgersen, Christian; Henning, Julie

2013-04-28

We investigated the spawning patterns of Chinook salmon Oncorhynchus tshawytscha on the lower Cowlitz River, Washington (USA) using a unique set of fine- and coarse-scale 35 temporal and spatial data collected during bi-weekly aerial surveys conducted in 1991-2009 (500 m to 28 km resolution) and 2008-2009 (100-500 m resolution). Redd locations were mapped from a helicopter during 2008 and 2009 with a hand-held global positioning system (GPS) synchronized with in-flight audio recordings. We examined spatial patterns of Chinook salmon redd reoccupation among and within years in relation to segment-scale geomorphic features. Chinook salmon spawned in the same sections each yearmore » with little variation among years. On a coarse scale, five years (1993, 1998, 2000, 2002, and 2009) were compared for reoccupation. Redd locations were highly correlated among years resulting in a minimum correlation coefficient of 0.90 (adjusted P = 0.002). Comparisons on a fine scale (500 m) between 2008 and 2009 also revealed a high degree of consistency among redd locations (P < 0.001). On a finer temporal scale, we observed that salmon spawned in the same sections during the first and last week (2008: P < 0.02; and 2009: P < 0.001). Redds were clustered in both 2008 and 2009 (P < 0.001). Regression analysis with a generalized linear model at the 500-m scale indicated that river kilometer and channel bifurcation were positively associated with redd density, whereas sinuosity was negatively associated with redd density. Collecting data on specific redd locations with a GPS during aerial surveys was logistically feasible and cost effective and greatly enhanced the spatial precision of Chinook salmon spawning surveys.« less

Linkage disequilibrium fine mapping of quantitative trait loci: A simulation study

PubMed Central

Abdallah, Jihad M; Goffinet, Bruno; Cierco-Ayrolles, Christine; Pérez-Enciso, Miguel

2003-01-01

Recently, the use of linkage disequilibrium (LD) to locate genes which affect quantitative traits (QTL) has received an increasing interest, but the plausibility of fine mapping using linkage disequilibrium techniques for QTL has not been well studied. The main objectives of this work were to (1) measure the extent and pattern of LD between a putative QTL and nearby markers in finite populations and (2) investigate the usefulness of LD in fine mapping QTL in simulated populations using a dense map of multiallelic or biallelic marker loci. The test of association between a marker and QTL and the power of the test were calculated based on single-marker regression analysis. The results show the presence of substantial linkage disequilibrium with closely linked marker loci after 100 to 200 generations of random mating. Although the power to test the association with a frequent QTL of large effect was satisfactory, the power was low for the QTL with a small effect and/or low frequency. More powerful, multi-locus methods may be required to map low frequent QTL with small genetic effects, as well as combining both linkage and linkage disequilibrium information. The results also showed that multiallelic markers are more useful than biallelic markers to detect linkage disequilibrium and association at an equal distance. PMID:12939203

The Importance of Measurement Errors for Deriving Accurate Reference Leaf Area Index Maps for Validation of Moderate-Resolution Satellite LAI Products

NASA Technical Reports Server (NTRS)

Huang, Dong; Yang, Wenze; Tan, Bin; Rautiainen, Miina; Zhang, Ping; Hu, Jiannan; Shabanov, Nikolay V.; Linder, Sune; Knyazikhin, Yuri; Myneni, Ranga B.

2006-01-01

The validation of moderate-resolution satellite leaf area index (LAI) products such as those operationally generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data requires reference LAI maps developed from field LAI measurements and fine-resolution satellite data. Errors in field measurements and satellite data determine the accuracy of the reference LAI maps. This paper describes a method by which reference maps of known accuracy can be generated with knowledge of errors in fine-resolution satellite data. The method is demonstrated with data from an international field campaign in a boreal coniferous forest in northern Sweden, and Enhanced Thematic Mapper Plus images. The reference LAI map thus generated is used to assess modifications to the MODIS LAI/fPAR algorithm recently implemented to derive the next generation of the MODIS LAI/fPAR product for this important biome type.

High-density genetic map construction and comparative genome analysis in asparagus bean.

PubMed

Huang, Haitao; Tan, Huaqiang; Xu, Dongmei; Tang, Yi; Niu, Yisong; Lai, Yunsong; Tie, Manman; Li, Huanxiu

2018-03-19

Genetic maps are a prerequisite for quantitative trait locus (QTL) analysis, marker-assisted selection (MAS), fine gene mapping, and assembly of genome sequences. So far, several asparagus bean linkage maps have been established using various kinds of molecular markers. However, these maps were all constructed by gel- or array-based markers. No maps based on sequencing method have been reported. In this study, an NGS-based strategy, SLAF-seq, was applied to create a high-density genetic map for asparagus bean. Through SLAF library construction and Illumina sequencing of two parents and 100 F2 individuals, a total of 55,437 polymorphic SLAF markers were developed and mined for SNP markers. The map consisted of 5,225 SNP markers in 11 LGs, spanning a total distance of 1,850.81 cM, with an average distance between markers of 0.35 cM. Comparative genome analysis with four other legume species, soybean, common bean, mung bean and adzuki bean showed that asparagus bean is genetically more related to adzuki bean. The results will provide a foundation for future genomic research, such as QTL fine mapping, comparative mapping in pulses, and offer support for assembling asparagus bean genome sequence.

Exploiting sequence similarity to validate the sensitivity of SNP arrays in detecting fine-scaled copy number variations.

PubMed

Wong, Gerard; Leckie, Christopher; Gorringe, Kylie L; Haviv, Izhak; Campbell, Ian G; Kowalczyk, Adam

2010-04-15

High-density single nucleotide polymorphism (SNP) genotyping arrays are efficient and cost effective platforms for the detection of copy number variation (CNV). To ensure accuracy in probe synthesis and to minimize production costs, short oligonucleotide probe sequences are used. The use of short probe sequences limits the specificity of binding targets in the human genome. The specificity of these short probeset sequences has yet to be fully analysed against a normal reference human genome. Sequence similarity can artificially elevate or suppress copy number measurements, and hence reduce the reliability of affected probe readings. For the purpose of detecting narrow CNVs reliably down to the width of a single probeset, sequence similarity is an important issue that needs to be addressed. We surveyed the Affymetrix Human Mapping SNP arrays for probeset sequence similarity against the reference human genome. Utilizing sequence similarity results, we identified a collection of fine-scaled putative CNVs between gender from autosomal probesets whose sequence matches various loci on the sex chromosomes. To detect these variations, we utilized our statistical approach, Detecting REcurrent Copy number change using rank-order Statistics (DRECS), and showed that its performance was superior and more stable than the t-test in detecting CNVs. Through the application of DRECS on the HapMap population datasets with multi-matching probesets filtered, we identified biologically relevant SNPs in aberrant regions across populations with known association to physical traits, such as height, covered by the span of a single probe. This provided empirical confirmation of the existence of naturally occurring narrow CNVs as well as the sensitivity of the Affymetrix SNP array technology in detecting them. The MATLAB implementation of DRECS is available at http://ww2.cs.mu.oz.au/ approximately gwong/DRECS/index.html.

Assessment of Acacia koa forest health across environmental gradients in Hawai'i using fine resolution remote sensing and GIS.

PubMed

Morales, Rodolfo Martinez; Idol, Travis; Friday, James B

2011-01-01

Koa (Acacia koa) forests are found across broad environmental gradients in the Hawai'ian Islands. Previous studies have identified koa forest health problems and dieback at the plot level, but landscape level patterns remain unstudied. The availability of high-resolution satellite images from the new GeoEye1 satellite offers the opportunity to conduct landscape-level assessments of forest health. The goal of this study was to develop integrated remote sensing and geographic information systems (GIS) methodologies to characterize the health of koa forests and model the spatial distribution and variability of koa forest dieback patterns across an elevation range of 600-1,000 m asl in the island of Kaua'i, which correspond to gradients of temperature and rainfall ranging from 17-20 °C mean annual temperature and 750-1,500 mm mean annual precipitation. GeoEye1 satellite imagery of koa stands was analyzed using supervised classification techniques based on the analysis of 0.5-m pixel multispectral bands. There was clear differentiation of native koa forest from areas dominated by introduced tree species and differentiation of healthy koa stands from those exhibiting dieback symptoms. The area ratio of healthy koa to koa dieback corresponded linearly to changes in temperature across the environmental gradient, with koa dieback at higher relative abundance in warmer areas. A landscape-scale map of healthy koa forest and dieback distribution demonstrated both the general trend with elevation and the small-scale heterogeneity that exists within particular elevations. The application of these classification techniques with fine spatial resolution imagery can improve the accuracy of koa forest inventory and mapping across the islands of Hawai'i. Such findings should also improve ecological restoration, conservation and silviculture of this important native tree species.

The wildland fuel cell concept: an approach to characterize fine-scale variation in fuels and fire in frequently burned longleaf pine forests

Treesearch

J. Kevin Hiers; Joseph J. O’Brien; R. J. Mitchell; John M. Grego; E. Louise Loudermilk

2009-01-01

In ecosystems with frequent surface fire regimes, fire and fuel heterogeneity has been largely overlookedowing to the lack of unburned patches and the difficulty in measuring fire behavior at fine scales (0.1–10 m). The diversevegetation in these ecosystems varies at these fine scales. This diversity could be...

Towards a Near Real-Time Satellite-Based Flux Monitoring System for the MENA Region

NASA Astrophysics Data System (ADS)

Ershadi, A.; Houborg, R.; McCabe, M. F.; Anderson, M. C.; Hain, C.

2013-12-01

Satellite remote sensing has the potential to offer spatially and temporally distributed information on land surface characteristics, which may be used as inputs and constraints for estimating land surface fluxes of carbon, water and energy. Enhanced satellite-based monitoring systems for aiding local water resource assessments and agricultural management activities are particularly needed for the Middle East and North Africa (MENA) region. The MENA region is an area characterized by limited fresh water resources, an often inefficient use of these, and relatively poor in-situ monitoring as a result of sparse meteorological observations. To address these issues, an integrated modeling approach for near real-time monitoring of land surface states and fluxes at fine spatio-temporal scales over the MENA region is presented. This approach is based on synergistic application of multiple sensors and wavebands in the visible to shortwave infrared and thermal infrared (TIR) domain. The multi-scale flux mapping and monitoring system uses the Atmosphere-Land Exchange Inverse (ALEXI) model and associated flux disaggregation scheme (DisALEXI), and the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in conjunction with model reanalysis data and multi-sensor remotely sensed data from polar orbiting (e.g. Landsat and MODerate resolution Imaging Spectroradiometer (MODIS)) and geostationary (MSG; Meteosat Second Generation) satellite platforms to facilitate time-continuous (i.e. daily) estimates of field-scale water, energy and carbon fluxes. Within this modeling system, TIR satellite data provide information about the sub-surface moisture status and plant stress, obviating the need for precipitation input and a detailed soil surface characterization (i.e. for prognostic modeling of soil transport processes). The STARFM fusion methodology blends aspects of high frequency (spatially coarse) and spatially fine resolution sensors and is applied directly to flux output fields to facilitate daily mapping of fluxes at sub-field scales. A complete processing infrastructure to automatically ingest and pre-process all required input data and to execute the integrated modeling system for near real-time agricultural monitoring purposes over targeted MENA sites is being developed, and initial results from this concerted effort will be discussed.

How BenMAP-CE Estimates the Health and Economic Effects of Air Pollution

EPA Pesticide Factsheets

The BenMAP-CE tool estimates the number and economic value of health impacts resulting from changes in air quality - specifically, ground-level ozone and fine particles. Learn what data BenMAP-CE uses and how the estimates are calculated.

Quantifying and communicating the uncertainty of mineral resource evaluations

NASA Astrophysics Data System (ADS)

Mee, Katy; Marchant, Ben; Mankelow, Joseph; Deady, Eimear

2015-04-01

Three-dimensional subsurface models are increasingly being used to assess the value of sand and gravel mineral deposits. Planners might use this information to decide when deposits should be protected from new developments. The models are generally based on interpretations of relatively sparse boreholes and are therefore uncertain. This uncertainty propagates into the predictions of the value of the deposit and must be quantified and communicated to planners in a manner which permits informed decision-making. We discuss these issues in relation to a 60 km by 40 km study area in the south of England. We use the interpretations of 630 boreholes to build statistical models of the subsurface. Mineral deposit categories are defined in terms of the ratio of mineral depth to overburden depth and the proportion of fine particles within the mineral. We use a linear model of coregionalization to model the spatial distribution of these parameters. Furthermore, we use stochastic simulation methods to produce maps of the probability of each category of mineral deposit occurring at each location in the study area. These maps indicate where deposits of suitable sand and gravel might be expected to occur. However, they are only telling us the probability that if a borehole was to be drilled at a location that its contents would satisfy the criteria of each mineral category. Planners require information for areas much larger than a single borehole. Therefore, we demonstrate how the model can be up-scaled to a 1 km2 site. We again use a stochastic simulation method to produce box-whisker plots which illustrate the proportions of gravels, sands, fine sands and fine material that are predicted to occur in the region and the uncertainty associated with the predictions.

Using DNase Hi-C techniques to map global and local three-dimensional genome architecture at high resolution.

PubMed

Ma, Wenxiu; Ay, Ferhat; Lee, Choli; Gulsoy, Gunhan; Deng, Xinxian; Cook, Savannah; Hesson, Jennifer; Cavanaugh, Christopher; Ware, Carol B; Krumm, Anton; Shendure, Jay; Blau, C Anthony; Disteche, Christine M; Noble, William S; Duan, ZhiJun

2018-06-01

The folding and three-dimensional (3D) organization of chromatin in the nucleus critically impacts genome function. The past decade has witnessed rapid advances in genomic tools for delineating 3D genome architecture. Among them, chromosome conformation capture (3C)-based methods such as Hi-C are the most widely used techniques for mapping chromatin interactions. However, traditional Hi-C protocols rely on restriction enzymes (REs) to fragment chromatin and are therefore limited in resolution. We recently developed DNase Hi-C for mapping 3D genome organization, which uses DNase I for chromatin fragmentation. DNase Hi-C overcomes RE-related limitations associated with traditional Hi-C methods, leading to improved methodological resolution. Furthermore, combining this method with DNA capture technology provides a high-throughput approach (targeted DNase Hi-C) that allows for mapping fine-scale chromatin architecture at exceptionally high resolution. Hence, targeted DNase Hi-C will be valuable for delineating the physical landscapes of cis-regulatory networks that control gene expression and for characterizing phenotype-associated chromatin 3D signatures. Here, we provide a detailed description of method design and step-by-step working protocols for these two methods. Copyright © 2018 Elsevier Inc. All rights reserved.

Fine-mapping inflammatory bowel disease loci to single variant resolution

PubMed Central

Huang, Hailiang; Fang, Ming; Jostins, Luke; Mirkov, Maša Umićević; Boucher, Gabrielle; Anderson, Carl A; Andersen, Vibeke; Cleynen, Isabelle; Cortes, Adrian; Crins, François; D'Amato, Mauro; Deffontaine, Valérie; Dimitrieva, Julia; Docampo, Elisa; Elansary, Mahmoud; Farh, Kyle Kai-How; Franke, Andre; Gori, Ann-Stephan; Goyette, Philippe; Halfvarson, Jonas; Haritunians, Talin; Knight, Jo; Lawrance, Ian C; Lees, Charlie W; Louis, Edouard; Mariman, Rob; Meuwissen, Theo; Mni, Myriam; Momozawa, Yukihide; Parkes, Miles; Spain, Sarah L; Théâtre, Emilie; Trynka, Gosia; Satsangi, Jack; van Sommeren, Suzanne; Vermeire, Severine; Xavier, Ramnik J; Weersma, Rinse K; Duerr, Richard H; Mathew, Christopher G; Rioux, John D; McGovern, Dermot PB; Cho, Judy H; Georges, Michel; Daly, Mark J; Barrett, Jeffrey C

2017-01-01

Summary The inflammatory bowel diseases (IBD) are chronic gastrointestinal inflammatory disorders that affect millions worldwide. Genome-wide association studies have identified 200 IBD-associated loci, but few have been conclusively resolved to specific functional variants. Here we report fine-mapping of 94 IBD loci using high-density genotyping in 67,852 individuals. We pinpointed 18 associations to a single causal variant with >95% certainty, and an additional 27 associations to a single variant with >50% certainty. These 45 variants are significantly enriched for protein-coding changes (n=13), direct disruption of transcription factor binding sites (n=3) and tissue specific epigenetic marks (n=10), with the latter category showing enrichment in specific immune cells among associations stronger in CD and in gut mucosa among associations stronger in UC. The results of this study suggest that high-resolution fine-mapping in large samples can convert many GWAS discoveries into statistically convincing causal variants, providing a powerful substrate for experimental elucidation of disease mechanisms. PMID:28658209

System and method for the detection of anomalies in an image

DOEpatents

Prasad, Lakshman; Swaminarayan, Sriram

2013-09-03

Preferred aspects of the present invention can include receiving a digital image at a processor; segmenting the digital image into a hierarchy of feature layers comprising one or more fine-scale features defining a foreground object embedded in one or more coarser-scale features defining a background to the one or more fine-scale features in the segmentation hierarchy; detecting a first fine-scale foreground feature as an anomaly with respect to a first background feature within which it is embedded; and constructing an anomalous feature layer by synthesizing spatially contiguous anomalous fine-scale features. Additional preferred aspects of the present invention can include detecting non-pervasive changes between sets of images in response at least in part to one or more difference images between the sets of images.

A highly efficient approach to protein interactome mapping based on collaborative filtering framework.

PubMed

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-09

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

PubMed Central

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-01

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly. PMID:25572661

A Highly Efficient Approach to Protein Interactome Mapping Based on Collaborative Filtering Framework

NASA Astrophysics Data System (ADS)

Luo, Xin; You, Zhuhong; Zhou, Mengchu; Li, Shuai; Leung, Hareton; Xia, Yunni; Zhu, Qingsheng

2015-01-01

The comprehensive mapping of protein-protein interactions (PPIs) is highly desired for one to gain deep insights into both fundamental cell biology processes and the pathology of diseases. Finely-set small-scale experiments are not only very expensive but also inefficient to identify numerous interactomes despite their high accuracy. High-throughput screening techniques enable efficient identification of PPIs; yet the desire to further extract useful knowledge from these data leads to the problem of binary interactome mapping. Network topology-based approaches prove to be highly efficient in addressing this problem; however, their performance deteriorates significantly on sparse putative PPI networks. Motivated by the success of collaborative filtering (CF)-based approaches to the problem of personalized-recommendation on large, sparse rating matrices, this work aims at implementing a highly efficient CF-based approach to binary interactome mapping. To achieve this, we first propose a CF framework for it. Under this framework, we model the given data into an interactome weight matrix, where the feature-vectors of involved proteins are extracted. With them, we design the rescaled cosine coefficient to model the inter-neighborhood similarity among involved proteins, for taking the mapping process. Experimental results on three large, sparse datasets demonstrate that the proposed approach outperforms several sophisticated topology-based approaches significantly.

Linking in situ LAI and fine resolution remote sensing data to map reference LAI over cropland and grassland using geostatistical regression method

NASA Astrophysics Data System (ADS)

He, Yaqian; Bo, Yanchen; Chai, Leilei; Liu, Xiaolong; Li, Aihua

2016-08-01

Leaf Area Index (LAI) is an important parameter of vegetation structure. A number of moderate resolution LAI products have been produced in urgent need of large scale vegetation monitoring. High resolution LAI reference maps are necessary to validate these LAI products. This study used a geostatistical regression (GR) method to estimate LAI reference maps by linking in situ LAI and Landsat TM/ETM+ and SPOT-HRV data over two cropland and two grassland sites. To explore the discrepancies of employing different vegetation indices (VIs) on estimating LAI reference maps, this study established the GR models for different VIs, including difference vegetation index (DVI), normalized difference vegetation index (NDVI), and ratio vegetation index (RVI). To further assess the performance of the GR model, the results from the GR and Reduced Major Axis (RMA) models were compared. The results show that the performance of the GR model varies between the cropland and grassland sites. At the cropland sites, the GR model based on DVI provides the best estimation, while at the grassland sites, the GR model based on DVI performs poorly. Compared to the RMA model, the GR model improves the accuracy of reference LAI maps in terms of root mean square errors (RMSE) and bias.

A high-resolution cat radiation hybrid and integrated FISH mapping resource for phylogenomic studies across Felidae.

PubMed

Davis, Brian W; Raudsepp, Terje; Pearks Wilkerson, Alison J; Agarwala, Richa; Schäffer, Alejandro A; Houck, Marlys; Chowdhary, Bhanu P; Murphy, William J

2009-04-01

We describe the construction of a high-resolution radiation hybrid (RH) map of the domestic cat genome, which includes 2662 markers, translating to an estimated average intermarker distance of 939 kilobases (kb). Targeted marker selection utilized the recent feline 1.9x genome assembly, concentrating on regions of low marker density on feline autosomes and the X chromosome, in addition to regions flanking interspecies chromosomal breakpoints. Average gap (breakpoint) size between cat-human ordered conserved segments is less than 900 kb. The map was used for a fine-scale comparison of conserved syntenic blocks with the human and canine genomes. Corroborative fluorescence in situ hybridization (FISH) data were generated using 129 domestic cat BAC clones as probes, providing independent confirmation of the long-range correctness of the map. Cross-species hybridization of BAC probes on divergent felids from the genera Profelis (serval) and Panthera (snow leopard) provides further evidence for karyotypic conservation within felids, and demonstrates the utility of such probes for future studies of chromosome evolution within the cat family and in related carnivores. The integrated map constitutes a comprehensive framework for identifying genes controlling feline phenotypes of interest, and to aid in assembly of a higher coverage feline genome sequence.

A High-Resolution Cat Radiation Hybrid and Integrated FISH Mapping Resource for Phylogenomic Studies across Felidae

PubMed Central

Davis, Brian W.; Raudsepp, Terje; Wilkerson, Alison J. Pearks; Agarwala, Richa; Schäffer, Alejandro A.; Houck, Marlys; Ryder, Oliver A.; Chowdhdary, Bhanu P.; Murphy, William J.

2008-01-01

We describe the construction of a high-resolution radiation hybrid (RH) map of the domestic cat genome, which includes 2,662 markers, translating to an estimated average intermarker distance of 939 kilobases (Kb). Targeted marker selection utilized the recent feline 1.9x genome assembly, concentrating on regions of low marker density on feline autosomes and the X chromosome, in addition to regions flanking interspecies chromosomal breakpoints. Average gap (breakpoint) size between cat-human ordered conserved segments is less than 900 Kb. The map was used for a fine-scale comparison of conserved syntenic blocks with the human and canine genomes. Corroborative fluorescence in situ hybridization (FISH) data were generated using 129 domestic cat BAC-clones as probes, providing independent confirmation of the long-range correctness of the map. Cross-species hybridization of BAC probes on divergent felids from the genera Profelis (serval) and Panthera (snow leopard) provides further evidence for karyotypic conservation within felids, and demonstrates the utility of such probes for future studies of chromosome evolution within the cat family and in related carnivores. The integrated map constitutes a comprehensive framework for identifying genes controlling feline phenotypes of interest, and to aid in assembly of a higher coverage feline genome sequence. PMID:18951970

Seabed maps showing topography, ruggedness, backscatter intensity, sediment mobility, and the distribution of geologic substrates in Quadrangle 6 of the Stellwagen Bank National Marine Sanctuary Region offshore of Boston, Massachusetts

USGS Publications Warehouse

Valentine, Page C.; Gallea, Leslie B.

2015-11-10

The U.S. Geological Survey (USGS), in cooperation with the National Oceanic and Atmospheric Administration's National Marine Sanctuary Program, has conducted seabed mapping and related research in the Stellwagen Bank National Marine Sanctuary (SBNMS) region since 1993. The area is approximately 3,700 square kilometers (km2) and is subdivided into 18 quadrangles. Seven maps, at a scale of 1:25,000, of quadrangle 6 (211 km2) depict seabed topography, backscatter, ruggedness, geology, substrate mobility, mud content, and areas dominated by fine-grained or coarse-grained sand. Interpretations of bathymetric and seabed backscatter imagery, photographs, video, and grain-size analyses were used to create the geology-based maps. In all, data from 420 stations were analyzed, including sediment samples from 325 locations. The seabed geology map shows the distribution of 10 substrate types ranging from boulder ridges to immobile, muddy sand to mobile, rippled sand. Mapped substrate types are defined on the basis of sediment grain-size composition, surface morphology, sediment layering, the mobility or immobility of substrate surfaces, and water depth range. This map series is intended to portray the major geological elements (substrates, topographic features, processes) of environments within quadrangle 6. Additionally, these maps will be the basis for the study of the ecological requirements of invertebrate and vertebrate species that utilize these substrates and guide seabed management in the region.

Polygamy and an absence of fine-scale structure in Dendroctonus ponderosae (Hopk.) (Coleoptera: Curcilionidae) confirmed using molecular markers

PubMed Central

Janes, J K; Roe, A D; Rice, A V; Gorrell, J C; Coltman, D W; Langor, D W; Sperling, F A H

2016-01-01

An understanding of mating systems and fine-scale spatial genetic structure is required to effectively manage forest pest species such as Dendroctonus ponderosae (mountain pine beetle). Here we used genome-wide single-nucleotide polymorphisms to assess the fine-scale genetic structure and mating system of D. ponderosae collected from a single stand in Alberta, Canada. Fine-scale spatial genetic structure was absent within the stand and the majority of genetic variation was best explained at the individual level. Relatedness estimates support previous reports of pre-emergence mating. Parentage assignment tests indicate that a polygamous mating system better explains the relationships among individuals within a gallery than the previously reported female monogamous/male polygynous system. Furthermore, there is some evidence to suggest that females may exploit the galleries of other females, at least under epidemic conditions. Our results suggest that current management models are likely to be effective across large geographic areas based on the absence of fine-scale genetic structure. PMID:26286666

Spatial adaptive sampling in multiscale simulation

NASA Astrophysics Data System (ADS)

Rouet-Leduc, Bertrand; Barros, Kipton; Cieren, Emmanuel; Elango, Venmugil; Junghans, Christoph; Lookman, Turab; Mohd-Yusof, Jamaludin; Pavel, Robert S.; Rivera, Axel Y.; Roehm, Dominic; McPherson, Allen L.; Germann, Timothy C.

2014-07-01

In a common approach to multiscale simulation, an incomplete set of macroscale equations must be supplemented with constitutive data provided by fine-scale simulation. Collecting statistics from these fine-scale simulations is typically the overwhelming computational cost. We reduce this cost by interpolating the results of fine-scale simulation over the spatial domain of the macro-solver. Unlike previous adaptive sampling strategies, we do not interpolate on the potentially very high dimensional space of inputs to the fine-scale simulation. Our approach is local in space and time, avoids the need for a central database, and is designed to parallelize well on large computer clusters. To demonstrate our method, we simulate one-dimensional elastodynamic shock propagation using the Heterogeneous Multiscale Method (HMM); we find that spatial adaptive sampling requires only ≈ 50 ×N0.14 fine-scale simulations to reconstruct the stress field at all N grid points. Related multiscale approaches, such as Equation Free methods, may also benefit from spatial adaptive sampling.

Schaffer Collateral Inputs to CA1 Excitatory and Inhibitory Neurons Follow Different Connectivity Rules.

PubMed

Kwon, Osung; Feng, Linqing; Druckmann, Shaul; Kim, Jinhyun

2018-05-30

Neural circuits, governed by a complex interplay between excitatory and inhibitory neurons, are the substrate for information processing, and the organization of synaptic connectivity in neural network is an important determinant of circuit function. Here, we analyzed the fine structure of connectivity in hippocampal CA1 excitatory and inhibitory neurons innervated by Schaffer collaterals (SCs) using mGRASP in male mice. Our previous study revealed spatially structured synaptic connectivity between CA3 and CA1 pyramidal cells (PCs). Surprisingly, parvalbumin-positive interneurons (PVs) showed a significantly more random pattern spatial structure. Notably, application of Peters' rule for synapse prediction by random overlap between axons and dendrites enhanced structured connectivity in PCs, but, by contrast, made the connectivity pattern in PVs more random. In addition, PCs in a deep sublayer of striatum pyramidale appeared more highly structured than PCs in superficial layers, and little or no sublayer specificity was found in PVs. Our results show that CA1 excitatory PCs and inhibitory PVs innervated by the same SC inputs follow different connectivity rules. The different organizations of fine scale structured connectivity in hippocampal excitatory and inhibitory neurons provide important insights into the development and functions of neural networks. SIGNIFICANCE STATEMENT Understanding how neural circuits generate behavior is one of the central goals of neuroscience. An important component of this endeavor is the mapping of fine-scale connection patterns that underlie, and help us infer, signal processing in the brain. Here, using our recently developed synapse detection technology (mGRASP and neuTube), we provide detailed profiles of synaptic connectivity in excitatory (CA1 pyramidal) and inhibitory (CA1 parvalbumin-positive) neurons innervated by the same presynaptic inputs (CA3 Schaffer collaterals). Our results reveal that these two types of CA1 neurons follow different connectivity patterns. Our new evidence for differently structured connectivity at a fine scale in hippocampal excitatory and inhibitory neurons provides a better understanding of hippocampal networks and will guide theoretical and experimental studies. Copyright © 2018 the authors 0270-6474/18/385140-13$15.00/0.

Water availability drives signatures of local adaptation in whitebark pine (Pinus albicaulis Engelm.) across fine spatial scales of the Lake Tahoe Basin, USA

Treesearch

Brandon M. Lind; Christopher J. Friedline; Jill L. Wegrzyn; Patricia E. Maloney; Detlev R. Vogler; David B. Neale; Andrew J. Eckert

2017-01-01

Patterns of local adaptation at fine spatial scales are central to understanding how evolution proceeds, and are essential to the effective management of economically and ecologically important forest tree species. Here, we employ single and multilocus analyses of genetic data (n = 116 231 SNPs) to describe signatures of fine-scale...

Using fine-scale fuel measurements to assess wildland fuels, potential fire behavior and hazard mitigation treatments in the southeastern USA

Treesearch

Roger D. Ottmar; John I. Blake; William T. Crolly

2012-01-01

The inherent spatial and temporal heterogeneity of fuel beds in forests of the southeastern United States may require fine scale fuel measurements for providing reliable fire hazard and fuel treatment effectiveness estimates. In a series of five papers, an intensive, fine scale fuel inventory from the Savanna River Site in the southeastern United States is used for...

Fine-Scale Habitat Segregation between Two Ecologically Similar Top Predators.

PubMed

Palomares, Francisco; Fernández, Néstor; Roques, Severine; Chávez, Cuauhtemoc; Silveira, Leandro; Keller, Claudia; Adrados, Begoña

2016-01-01

Similar, coexisting species often segregate along the spatial ecological axis. Here, we examine if two top predators (jaguars and pumas) present different fine-scale habitat use in areas of coexistence, and discuss if the observed pattern can be explained by the risk of interference competition between them. Interference competition theory predicts that pumas should avoid habitats or areas used by jaguars (the dominant species), and as a consequence should present more variability of niche parameters across study areas. We used non-invasive genetic sampling of faeces in 12 different areas and sensor satellite fine-scale habitat indices to answer these questions. Meta-analysis confirmed differences in fine-scale habitat use between jaguars and pumas. Furthermore, average marginality of the realized niches of pumas was more variable than those of jaguars, and tolerance (a measure of niche breadth) was on average 2.2 times higher in pumas than in jaguars, as expected under the interference competition risk hypothesis. The use of sensor satellite fine-scale habitat indices allowed the detection of subtle differences in the environmental characteristics of the habitats used by these two similar top predators, which, as a rule, until now were recorded using the same general habitat types. The detection of fine spatial segregation between these two top predators was scale-dependent.

Incorporating Functional Annotations for Fine-Mapping Causal Variants in a Bayesian Framework Using Summary Statistics.

PubMed

Chen, Wenan; McDonnell, Shannon K; Thibodeau, Stephen N; Tillmans, Lori S; Schaid, Daniel J

2016-11-01

Functional annotations have been shown to improve both the discovery power and fine-mapping accuracy in genome-wide association studies. However, the optimal strategy to incorporate the large number of existing annotations is still not clear. In this study, we propose a Bayesian framework to incorporate functional annotations in a systematic manner. We compute the maximum a posteriori solution and use cross validation to find the optimal penalty parameters. By extending our previous fine-mapping method CAVIARBF into this framework, we require only summary statistics as input. We also derived an exact calculation of Bayes factors using summary statistics for quantitative traits, which is necessary when a large proportion of trait variance is explained by the variants of interest, such as in fine mapping expression quantitative trait loci (eQTL). We compared the proposed method with PAINTOR using different strategies to combine annotations. Simulation results show that the proposed method achieves the best accuracy in identifying causal variants among the different strategies and methods compared. We also find that for annotations with moderate effects from a large annotation pool, screening annotations individually and then combining the top annotations can produce overly optimistic results. We applied these methods on two real data sets: a meta-analysis result of lipid traits and a cis-eQTL study of normal prostate tissues. For the eQTL data, incorporating annotations significantly increased the number of potential causal variants with high probabilities. Copyright © 2016 by the Genetics Society of America.

Construction and Annotation of a High Density SNP Linkage Map of the Atlantic Salmon (Salmo salar) Genome.

PubMed

Tsai, Hsin Y; Robledo, Diego; Lowe, Natalie R; Bekaert, Michael; Taggart, John B; Bron, James E; Houston, Ross D

2016-07-07

High density linkage maps are useful tools for fine-scale mapping of quantitative trait loci, and characterization of the recombination landscape of a species' genome. Genomic resources for Atlantic salmon (Salmo salar) include a well-assembled reference genome, and high density single nucleotide polymorphism (SNP) arrays. Our aim was to create a high density linkage map, and to align it with the reference genome assembly. Over 96,000 SNPs were mapped and ordered on the 29 salmon linkage groups using a pedigreed population comprising 622 fish from 60 nuclear families, all genotyped with the 'ssalar01' high density SNP array. The number of SNPs per group showed a high positive correlation with physical chromosome length (r = 0.95). While the order of markers on the genetic and physical maps was generally consistent, areas of discrepancy were identified. Approximately 6.5% of the previously unmapped reference genome sequence was assigned to chromosomes using the linkage map. Male recombination rate was lower than females across the vast majority of the genome, but with a notable peak in subtelomeric regions. Finally, using RNA-Seq data to annotate the reference genome, the mapped SNPs were categorized according to their predicted function, including annotation of ∼2500 putative nonsynonymous variants. The highest density SNP linkage map for any salmonid species has been created, annotated, and integrated with the Atlantic salmon reference genome assembly. This map highlights the marked heterochiasmy of salmon, and provides a useful resource for salmonid genetics and genomics research. Copyright © 2016 Tsai et al.

High-density genetic map using whole-genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanut.

PubMed

Agarwal, Gaurav; Clevenger, Josh; Pandey, Manish K; Wang, Hui; Shasidhar, Yaduru; Chu, Ye; Fountain, Jake C; Choudhary, Divya; Culbreath, Albert K; Liu, Xin; Huang, Guodong; Wang, Xingjun; Deshmukh, Rupesh; Holbrook, C Corley; Bertioli, David J; Ozias-Akins, Peggy; Jackson, Scott A; Varshney, Rajeev K; Guo, Baozhu

2018-04-10

Whole-genome resequencing (WGRS) of mapping populations has facilitated development of high-density genetic maps essential for fine mapping and candidate gene discovery for traits of interest in crop species. Leaf spots, including early leaf spot (ELS) and late leaf spot (LLS), and Tomato spotted wilt virus (TSWV) are devastating diseases in peanut causing significant yield loss. We generated WGRS data on a recombinant inbred line population, developed a SNP-based high-density genetic map, and conducted fine mapping, candidate gene discovery and marker validation for ELS, LLS and TSWV. The first sequence-based high-density map was constructed with 8869 SNPs assigned to 20 linkage groups, representing 20 chromosomes, for the 'T' population (Tifrunner × GT-C20) with a map length of 3120 cM and an average distance of 1.45 cM. The quantitative trait locus (QTL) analysis using high-density genetic map and multiple season phenotyping data identified 35 main-effect QTLs with phenotypic variation explained (PVE) from 6.32% to 47.63%. Among major-effect QTLs mapped, there were two QTLs for ELS on B05 with 47.42% PVE and B03 with 47.38% PVE, two QTLs for LLS on A05 with 47.63% and B03 with 34.03% PVE and one QTL for TSWV on B09 with 40.71% PVE. The epistasis and environment interaction analyses identified significant environmental effects on these traits. The identified QTL regions had disease resistance genes including R-genes and transcription factors. KASP markers were developed for major QTLs and validated in the population and are ready for further deployment in genomics-assisted breeding in peanut. © 2018 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery

NASA Astrophysics Data System (ADS)

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms (R2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

Mapping paddy rice planting area in cold temperate climate region through analysis of time series Landsat 8 (OLI), Landsat 7 (ETM+) and MODIS imagery.

PubMed

Qin, Yuanwei; Xiao, Xiangming; Dong, Jinwei; Zhou, Yuting; Zhu, Zhe; Zhang, Geli; Du, Guoming; Jin, Cui; Kou, Weili; Wang, Jie; Li, Xiangping

2015-07-01

Accurate and timely rice paddy field maps with a fine spatial resolution would greatly improve our understanding of the effects of paddy rice agriculture on greenhouse gases emissions, food and water security, and human health. Rice paddy field maps were developed using optical images with high temporal resolution and coarse spatial resolution (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) or low temporal resolution and high spatial resolution (e.g., Landsat TM/ETM+). In the past, the accuracy and efficiency for rice paddy field mapping at fine spatial resolutions were limited by the poor data availability and image-based algorithms. In this paper, time series MODIS and Landsat ETM+/OLI images, and the pixel- and phenology-based algorithm are used to map paddy rice planting area. The unique physical features of rice paddy fields during the flooding/open-canopy period are captured with the dynamics of vegetation indices, which are then used to identify rice paddy fields. The algorithm is tested in the Sanjiang Plain (path/row 114/27) in China in 2013. The overall accuracy of the resulted map of paddy rice planting area generated by both Landsat ETM+ and OLI is 97.3%, when evaluated with areas of interest (AOIs) derived from geo-referenced field photos. The paddy rice planting area map also agrees reasonably well with the official statistics at the level of state farms ( R 2 = 0.94). These results demonstrate that the combination of fine spatial resolution images and the phenology-based algorithm can provide a simple, robust, and automated approach to map the distribution of paddy rice agriculture in a year.

Acoustic mapping and classification of benthic habitat using unsupervised learning in artificial reef water

NASA Astrophysics Data System (ADS)

Li, Dong; Tang, Cheng; Xia, Chunlei; Zhang, Hua

2017-02-01

Artificial reefs (ARs) are effective means to maintain fishery resources and to restore ecological environment in coastal waters. ARs have been widely constructed along the Chinese coast. However, understanding of benthic habitats in the vicinity of ARs is limited, hindering effective fisheries and aquacultural management. Multibeam echosounder (MBES) is an advanced acoustic instrument capable of efficiently generating large-scale maps of benthic environments at fine resolutions. The objective of this study is to develop a technical approach to characterize, classify, and map shallow coastal areas with ARs using an MBES. An automated classification method is designed and tested to process bathymetric and backscatter data from MBES and transform the variables into simple, easily visualized maps. To reduce the redundancy in acoustic variables, a principal component analysis (PCA) is used to condense the highly collinear dataset. An acoustic benthic map of bottom sediments is classified using an iterative self-organizing data analysis technique (ISODATA). The approach is tested with MBES surveys in a 1.15 km2 fish farm with a high density of ARs off the Yantai coast in northern China. Using this method, 3 basic benthic habitats (sandy bottom, muddy sediments, and ARs) are distinguished. The results of the classification are validated using sediment samples and underwater surveys. Our study shows that the use of MBES is an effective method for acoustic mapping and classification of ARs.

Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium.

PubMed

Ng, Maggie C Y; Graff, Mariaelisa; Lu, Yingchang; Justice, Anne E; Mudgal, Poorva; Liu, Ching-Ti; Young, Kristin; Yanek, Lisa R; Feitosa, Mary F; Wojczynski, Mary K; Rand, Kristin; Brody, Jennifer A; Cade, Brian E; Dimitrov, Latchezar; Duan, Qing; Guo, Xiuqing; Lange, Leslie A; Nalls, Michael A; Okut, Hayrettin; Tajuddin, Salman M; Tayo, Bamidele O; Vedantam, Sailaja; Bradfield, Jonathan P; Chen, Guanjie; Chen, Wei-Min; Chesi, Alessandra; Irvin, Marguerite R; Padhukasahasram, Badri; Smith, Jennifer A; Zheng, Wei; Allison, Matthew A; Ambrosone, Christine B; Bandera, Elisa V; Bartz, Traci M; Berndt, Sonja I; Bernstein, Leslie; Blot, William J; Bottinger, Erwin P; Carpten, John; Chanock, Stephen J; Chen, Yii-Der Ida; Conti, David V; Cooper, Richard S; Fornage, Myriam; Freedman, Barry I; Garcia, Melissa; Goodman, Phyllis J; Hsu, Yu-Han H; Hu, Jennifer; Huff, Chad D; Ingles, Sue A; John, Esther M; Kittles, Rick; Klein, Eric; Li, Jin; McKnight, Barbara; Nayak, Uma; Nemesure, Barbara; Ogunniyi, Adesola; Olshan, Andrew; Press, Michael F; Rohde, Rebecca; Rybicki, Benjamin A; Salako, Babatunde; Sanderson, Maureen; Shao, Yaming; Siscovick, David S; Stanford, Janet L; Stevens, Victoria L; Stram, Alex; Strom, Sara S; Vaidya, Dhananjay; Witte, John S; Yao, Jie; Zhu, Xiaofeng; Ziegler, Regina G; Zonderman, Alan B; Adeyemo, Adebowale; Ambs, Stefan; Cushman, Mary; Faul, Jessica D; Hakonarson, Hakon; Levin, Albert M; Nathanson, Katherine L; Ware, Erin B; Weir, David R; Zhao, Wei; Zhi, Degui; Arnett, Donna K; Grant, Struan F A; Kardia, Sharon L R; Oloapde, Olufunmilayo I; Rao, D C; Rotimi, Charles N; Sale, Michele M; Williams, L Keoki; Zemel, Babette S; Becker, Diane M; Borecki, Ingrid B; Evans, Michele K; Harris, Tamara B; Hirschhorn, Joel N; Li, Yun; Patel, Sanjay R; Psaty, Bruce M; Rotter, Jerome I; Wilson, James G; Bowden, Donald W; Cupples, L Adrienne; Haiman, Christopher A; Loos, Ruth J F; North, Kari E

2017-04-01

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations.

Fine Mapping of Resistance Genes from Five Brown Stem Rot Resistance Sources in Soybean.

PubMed

Rincker, Keith; Hartman, Glen L; Diers, Brian W

2016-03-01

Brown stem rot (BSR) of soybean [ (L.) Merr.] caused by (Allington & Chamb.) T.C. Harr. & McNew can be controlled effectively with genetic host resistance. Three BSR resistance genes , , and , have been identified and mapped to a large region on chromosome 16. Marker-assisted selection (MAS) will be more efficient and gene cloning will be facilitated with a narrowed genomic interval containing an gene. The objective of this study was to fine map the positions of genes from five sources. Mapping populations were developed by crossing the resistant sources 'Bell', PI 84946-2, PI 437833, PI 437970, L84-5873, and PI 86150 with either the susceptible cultivar Colfax or Century 84. Plants identified as having a recombination event near genes were selected and individually harvested to create recombinant lines. Progeny from recombinant lines were tested in a root-dip assay and evaluated for foliar and stem BSR symptom development. Overall, 4878 plants were screened for recombination, and progeny from 52 recombinant plants were evaluated with simple-sequence repeat (SSR) genetic markers and assessed for symptom development. Brown stem rot resistance was mapped to intervals ranging from 0.34 to 0.04 Mb in the different sources. In all sources, resistance was fine mapped to intervals inclusive of BARCSOYSSR_16_1114 and BARCSOYSSR_16_1115, which provides further evidence that one locus provides BSR resistance in soybean. Copyright © 2016 Crop Science Society of America.

Ecosystem services of boreal forests - Carbon budget mapping at high resolution.

PubMed

Akujärvi, Anu; Lehtonen, Aleksi; Liski, Jari

2016-10-01

The carbon (C) cycle of forests produces ecosystem services (ES) such as climate regulation and timber production. Mapping these ES using simple land cover -based proxies might add remarkable inaccuracy to the estimates. A framework to map the current status of the C budget of boreal forested landscapes was developed. The C stocks of biomass and soil and the annual change in these stocks were quantified in a 20 × 20 m resolution at the regional level on mineral soils in southern Finland. The fine-scale variation of the estimates was analyzed geo-statistically. The reliability of the estimates was evaluated by comparing them to measurements from the national multi-source forest inventory. The C stocks of forests increased slightly from the south coast to inland whereas the changes in these stocks were more uniform. The spatial patches of C stocks were larger than those of C stock changes. The patch size of the C stocks reflected the spatial variation in the environmental conditions, and that of the C stock changes the typical area of forest management compartments. The simulated estimates agreed well with the measurements indicating a good mapping framework performance. The mapping framework is the basis for evaluating the effects of forest management alternatives on C budget at high resolution across large spatial scales. It will be coupled with the assessment of other ES and biodiversity to study their relationships. The framework integrated a wide suite of simulation models and extensive inventory data. It provided reliable estimates of the human influence on C cycle in forested landscapes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Advanced Ecosystem Mapping Techniques for Large Arctic Study Domains Using Calibrated High-Resolution Imagery

NASA Astrophysics Data System (ADS)

Macander, M. J.; Frost, G. V., Jr.

2015-12-01

Regional-scale mapping of vegetation and other ecosystem properties has traditionally relied on medium-resolution remote sensing such as Landsat (30 m) and MODIS (250 m). Yet, the burgeoning availability of high-resolution (<=2 m) imagery and ongoing advances in computing power and analysis tools raises the prospect of performing ecosystem mapping at fine spatial scales over large study domains. Here we demonstrate cutting-edge mapping approaches over a ~35,000 km² study area on Alaska's North Slope using calibrated and atmospherically-corrected mosaics of high-resolution WorldView-2 and GeoEye-1 imagery: (1) an a priori spectral approach incorporating the Satellite Imagery Automatic Mapper (SIAM) algorithms; (2) image segmentation techniques; and (3) texture metrics. The SIAM spectral approach classifies radiometrically-calibrated imagery to general vegetation density categories and non-vegetated classes. The SIAM classes were developed globally and their applicability in arctic tundra environments has not been previously evaluated. Image segmentation, or object-based image analysis, automatically partitions high-resolution imagery into homogeneous image regions that can then be analyzed based on spectral, textural, and contextual information. We applied eCognition software to delineate waterbodies and vegetation classes, in combination with other techniques. Texture metrics were evaluated to determine the feasibility of using high-resolution imagery to algorithmically characterize periglacial surface forms (e.g., ice-wedge polygons), which are an important physical characteristic of permafrost-dominated regions but which cannot be distinguished by medium-resolution remote sensing. These advanced mapping techniques provide products which can provide essential information supporting a broad range of ecosystem science and land-use planning applications in northern Alaska and elsewhere in the circumpolar Arctic.

Sonic Kayaks: Environmental monitoring and experimental music by citizens.

PubMed

Griffiths, Amber G F; Kemp, Kirsty M; Matthews, Kaffe; Garrett, Joanne K; Griffiths, David J

2017-11-01

The Sonic Kayak is a musical instrument used to investigate nature and developed during open hacklab events. The kayaks are rigged with underwater environmental sensors, which allow paddlers to hear real-time water temperature sonifications and underwater sounds, generating live music from the marine world. Sensor data is also logged every second with location, time and date, which allows for fine-scale mapping of water temperatures and underwater noise that was previously unattainable using standard research equipment. The system can be used as a citizen science data collection device, research equipment for professional scientists, or a sound art installation in its own right.

Sonic Kayaks: Environmental monitoring and experimental music by citizens

PubMed Central

Kemp, Kirsty M.; Matthews, Kaffe; Garrett, Joanne K.; Griffiths, David J.

2017-01-01

The Sonic Kayak is a musical instrument used to investigate nature and developed during open hacklab events. The kayaks are rigged with underwater environmental sensors, which allow paddlers to hear real-time water temperature sonifications and underwater sounds, generating live music from the marine world. Sensor data is also logged every second with location, time and date, which allows for fine-scale mapping of water temperatures and underwater noise that was previously unattainable using standard research equipment. The system can be used as a citizen science data collection device, research equipment for professional scientists, or a sound art installation in its own right. PMID:29190283

What does physics have to do with cancer?

PubMed Central

Michor, Franziska; Liphardt, Jan; Ferrari, Mauro; Widom, Jonathan

2013-01-01

Large-scale cancer genomics, proteomics and RNA-sequencing efforts are currently mapping in fine detail the genetic and biochemical alterations that occur in cancer. However, it is becoming clear that it is difficult to integrate and interpret these data and to translate them into treatments. This difficulty is compounded by the recognition that cancer cells evolve, and that initiation, progression and metastasis are influenced by a wide variety of factors. To help tackle this challenge, the US National Cancer Institute Physical Sciences-Oncology Centers initiative is bringing together physicists, cancer biologists, chemists, mathematicians and engineers. How are we beginning to address cancer from the perspective of the physical sciences? PMID:21850037

Downscaling climate model output for water resources impacts assessment (Invited)

NASA Astrophysics Data System (ADS)

Maurer, E. P.; Pierce, D. W.; Cayan, D. R.

2013-12-01

Water agencies in the U.S. and around the globe are beginning to wrap climate change projections into their planning procedures, recognizing that ongoing human-induced changes to hydrology can affect water management in significant ways. Future hydrology changes are derived using global climate model (GCM) projections, though their output is at a spatial scale that is too coarse to meet the needs of those concerned with local and regional impacts. Those investigating local impacts have employed a range of techniques for downscaling, the process of translating GCM output to a more locally-relevant spatial scale. Recent projects have produced libraries of publicly-available downscaled climate projections, enabling managers, researchers and others to focus on impacts studies, drawing from a shared pool of fine-scale climate data. Besides the obvious advantage to data users, who no longer need to develop expertise in downscaling prior to examining impacts, the use of the downscaled data by hundreds of people has allowed a crowdsourcing approach to examining the data. The wide variety of applications employed by different users has revealed characteristics not discovered during the initial data set production. This has led to a deeper look at the downscaling methods, including the assumptions and effect of bias correction of GCM output. Here new findings are presented related to the assumption of stationarity in the relationships between large- and fine-scale climate, as well as the impact of quantile mapping bias correction on precipitation trends. The validity of these assumptions can influence the interpretations of impacts studies using data derived using these standard statistical methods and help point the way to improved methods.

Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer

PubMed Central

Zheng, Wei; Michailidou, Kyriaki; Ghoussaini, Maya; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Lush, Michael; Milne, Roger L.; Shu, Xiao-Ou; Beesley, Jonathan; Kar, Siddhartha; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W.; Zhao, Zhiguo; Guo, Xingyi; Benitez, Javier; Beeghly-Fadiel, Alicia; Blot, William; Bogdanova, Natalia V.; Bojesen, Stig E.; Brauch, Hiltrud; Brenner, Hermann; Brinton, Louise; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Cai, Hui; Canisius, Sander; Chang-Claude, Jenny; Choi, Ji-Yeob; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Darabi, Hatef; Devilee, Peter; Droit, Arnaud; Dork, Thilo; Fasching, Peter A.; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gaborieau, Valerie; García-Closas, Montserrat; Giles, Graham G.; Guenel, Pascal; Haiman, Christopher A.; Hamann, Ute; Hartman, Mikael; Miao, Hui; Hollestelle, Antoinette; Hopper, John L.; Hsiung, Chia-Ni; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Torres, Diana; Kabisch, Maria; Kang, Daehee; Khan, Sofia; Knight, Julia A.; Kosma, Veli-Matti; Lambrechts, Diether; Li, Jingmei; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Le Marchand, Loic; Margolin, Sara; Marme, Frederik; Matsuo, Keitaro; McLean, Catriona; Meindl, Alfons; Muir, Kenneth; Neuhausen, Susan L.; Nevanlinna, Heli; Nord, Silje; Børresen-Dale, Anne-Lise; Olson, Janet E.; Orr, Nick; van den Ouweland, Ans M.W.; Peterlongo, Paolo; Putti, Thomas Choudary; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Marjanka K.; Schmutzler, Rita K.; Shen, Chen-Yang; Hou, Ming-Feng; Shrubsole, Matha J; Southey, Melissa C.; Swerdlow, Anthony; Teo, Soo Hwang; Thienpont, Bernard; Toland, Amanda E.; Tollenaar, Robert A.E.M.; Tomlinson, Ian; Truong, Therese; Tseng, Chiu-chen; Wen, Wanqing; Winqvist, Robert; Wu, Anna H.; Yip, Cheng Har; Zamora, Pilar M.; Zheng, Ying; Floris, Giuseppe; Cheng, Ching-Yu; Hooning, Maartje J.; Martens, John W.M.; Seynaeve, Caroline; Kristensen, Vessela N.; Hall, Per; Pharoah, Paul D.P.; Simard, Jacques; Chenevix-Trench, Georgia; Dunning, Alison M.; Antoniou, Antonis C.; Easton, Douglas F.; Cai, Qiuyin; Long, Jirong

2016-01-01

Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. We conducted a fine-mapping study across 2.06 Mb (chr8:127,561,724 −129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium. We found three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional P = 5.8 × 10−6), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional P = 1.1 × 10−6), and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional P = 1.1 × 10−4). Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas, and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r2 = 0.77), were putatively functional variants for two of the five independent association signals. Our results highlight multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry. PMID:27087578

Fine-scale mapping of 8q24 locus identifies multiple independent risk variants for breast cancer.

PubMed

Shi, Jiajun; Zhang, Yanfeng; Zheng, Wei; Michailidou, Kyriaki; Ghoussaini, Maya; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Lush, Michael; Milne, Roger L; Shu, Xiao-Ou; Beesley, Jonathan; Kar, Siddhartha; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Zhao, Zhiguo; Guo, Xingyi; Benitez, Javier; Beeghly-Fadiel, Alicia; Blot, William; Bogdanova, Natalia V; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Brinton, Louise; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Cai, Hui; Canisius, Sander; Chang-Claude, Jenny; Choi, Ji-Yeob; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Darabi, Hatef; Devilee, Peter; Droit, Arnaud; Dork, Thilo; Fasching, Peter A; Fletcher, Olivia; Flyger, Henrik; Fostira, Florentia; Gaborieau, Valerie; García-Closas, Montserrat; Giles, Graham G; Guenel, Pascal; Haiman, Christopher A; Hamann, Ute; Hartman, Mikael; Miao, Hui; Hollestelle, Antoinette; Hopper, John L; Hsiung, Chia-Ni; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Torres, Diana; Kabisch, Maria; Kang, Daehee; Khan, Sofia; Knight, Julia A; Kosma, Veli-Matti; Lambrechts, Diether; Li, Jingmei; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Le Marchand, Loic; Margolin, Sara; Marme, Frederik; Matsuo, Keitaro; McLean, Catriona; Meindl, Alfons; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Nord, Silje; Børresen-Dale, Anne-Lise; Olson, Janet E; Orr, Nick; van den Ouweland, Ans M W; Peterlongo, Paolo; Putti, Thomas Choudary; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Shen, Chen-Yang; Hou, Ming-Feng; Shrubsole, Matha J; Southey, Melissa C; Swerdlow, Anthony; Teo, Soo Hwang; Thienpont, Bernard; Toland, Amanda E; Tollenaar, Robert A E M; Tomlinson, Ian; Truong, Therese; Tseng, Chiu-Chen; Wen, Wanqing; Winqvist, Robert; Wu, Anna H; Yip, Cheng Har; Zamora, Pilar M; Zheng, Ying; Floris, Giuseppe; Cheng, Ching-Yu; Hooning, Maartje J; Martens, John W M; Seynaeve, Caroline; Kristensen, Vessela N; Hall, Per; Pharoah, Paul D P; Simard, Jacques; Chenevix-Trench, Georgia; Dunning, Alison M; Antoniou, Antonis C; Easton, Douglas F; Cai, Qiuyin; Long, Jirong

2016-09-15

Previous genome-wide association studies among women of European ancestry identified two independent breast cancer susceptibility loci represented by single nucleotide polymorphisms (SNPs) rs13281615 and rs11780156 at 8q24. A fine-mapping study across 2.06 Mb (chr8:127,561,724-129,624,067, hg19) in 55,540 breast cancer cases and 51,168 controls within the Breast Cancer Association Consortium was conducted. Three additional independent association signals in women of European ancestry, represented by rs35961416 (OR = 0.95, 95% CI = 0.93-0.97, conditional p = 5.8 × 10(-6) ), rs7815245 (OR = 0.94, 95% CI = 0.91-0.96, conditional p = 1.1 × 10(-6) ) and rs2033101 (OR = 1.05, 95% CI = 1.02-1.07, conditional p = 1.1 × 10(-4) ) were found. Integrative analysis using functional genomic data from the Roadmap Epigenomics, the Encyclopedia of DNA Elements project, the Cancer Genome Atlas and other public resources implied that SNPs rs7815245 in Signal 3, and rs1121948 in Signal 5 (in linkage disequilibrium with rs11780156, r(2)  = 0.77), were putatively functional variants for two of the five independent association signals. The results highlighted multiple 8q24 variants associated with breast cancer susceptibility in women of European ancestry. © 2016 UICC.

Fine mapping of powdery mildew resistance genes PmTb7A.1 and PmTb7A.2 in Triticum boeoticum (Boiss.) using the shotgun sequence assembly of chromosome 7AL.

PubMed

Chhuneja, Parveen; Yadav, Bharat; Stirnweis, Daniel; Hurni, Severine; Kaur, Satinder; Elkot, Ahmed Fawzy; Keller, Beat; Wicker, Thomas; Sehgal, Sunish; Gill, Bikram S; Singh, Kuldeep

2015-10-01

A novel powdery mildew resistance gene and a new allele of Pm1 were identified and fine mapped. DNA markers suitable for marker-assisted selection have been identified. Powdery mildew caused by Blumeria graminis is one of the most important foliar diseases of wheat and causes significant yield losses worldwide. Diploid A genome species are an important genetic resource for disease resistance genes. Two powdery mildew resistance genes, identified in Triticum boeoticum (A(b)A(b)) accession pau5088, PmTb7A.1 and PmTb7A.2 were mapped on chromosome 7AL. In the present study, shotgun sequence assembly data for chromosome 7AL were utilised for fine mapping of these Pm resistance genes. Forty SSR, 73 resistance gene analogue-based sequence-tagged sites (RGA-STS) and 36 single nucleotide polymorphism markers were designed for fine mapping of PmTb7A.1 and PmTb7A.2. Twenty-one RGA-STS, 8 SSR and 13 SNP markers were mapped to 7AL. RGA-STS markers Ta7AL-4556232 and 7AL-4426363 were linked to the PmTb7A.1 and PmTb7A.2, at a genetic distance of 0.6 and 6.0 cM, respectively. The present investigation established that PmTb7A.1 is a new powdery mildew resistance gene that confers resistance to a broad range of Bgt isolates, whereas PmTb7A.2 most probably is a new allele of Pm1 based on chromosomal location and screening with Bgt isolates showing differential reaction on lines with different Pm1 alleles. The markers identified to be linked to the two Pm resistance genes are robust and can be used for marker-assisted introgression of these genes to hexaploid wheat.

A Closer Look at Holden Crater

NASA Image and Video Library

2017-03-15

Holden Crater in southern Margaritifer Terra displays a series of finely layered deposits on its floor. The layered deposits are especially well exposed in the southwestern section of the crater where erosion by water flowing through a breach in the crater rim created spectacular outcrops. In this location, the deposits appear beneath a cap of alluvial fan materials (tan to brown in this image). Within the deposits, individual layers are nearly flat-lying and can be traced for hundreds of meters to kilometers. Information from the CRISM instrument on the Mars Reconnaissance Orbiter suggests that at least some of these beds contain clays. By contrast, the beds in the overlying alluvial fan are less continuous and dip in varying directions, showing less evidence for clays. Collectively, the characteristics of the finely bedded deposits suggest they may have been deposited into a lake on the crater floor, perhaps fed by runoff related to formation of the overlying fans. The map is projected here at a scale of 25 centimeters (9.8 inches) per pixel. [The original image scale is 25.9 centimeters (10.2 inches) per pixel (with 1 x 1 binning); objects on the order of 78 centimeters (30.7 inches) across are resolved.] North is up. http://photojournal.jpl.nasa.gov/catalog/PIA21561

Fine-scale habitat use of reintroduced black-footed ferrets on prairie dog colonies in New Mexico

USGS Publications Warehouse

Chipault, Jennifer G.; Biggins, Dean E.; Detling, James K.; Long, Dustin H.; Reich, Robin M.

2012-01-01

Black-footed ferrets (Mustela nigripes) are among the most endangered animals in North America. Reintroductions of captive-born ferrets onto prairie dog (Cynomys spp.) colonies are crucial to the conservation of the species. In September 2007, captive-born ferrets were released on a black-tailed prairie dog (Cynomys ludovicianus) colony at the Vermejo Park Ranch, New Mexico. Ferret kits experimentally released in areas of comparatively low and high prairie dog burrow densities were located via spotlight surveys. Some maturing ferret kits were subsequently translocated to areas of low and high burrow densities on nearby prairie dog colonies. For 2 months, fine-scale habitat use was quantified by mapping all burrow openings within a 30-m radius of each ferret location. Spatial statistics accounted for autocorrelation in the burrow densities in areas used by ferrets. It was hypothesized that ferrets would select areas of high burrow densities within colonies; however, burrow densities in areas used by ferrets were generally similar to the available burrow densities. Because ferrets used areas with burrow densities similar to densities available at the colony level and because of the potential energetic benefits for ferrets using areas with high burrow densities, releasing ferrets on colonies with high burrow densities might increase reintroduction success.

Improving Geologic Mapping of Mid-ocean Ridges by Integrating sonar and Visual Observations through Seafloor Classification by Machine-learning Systems

NASA Astrophysics Data System (ADS)

White, S. M.; McClinton, J. T.

2011-12-01

Beyond the ability of modern near-bottom sonar systems to deliver air-photo-like images of the seafloor to help guide fieldwork, there is a tremendous amount of information hidden within sonar data that is rarely exploited for geologic mapping. Seafloor texture, backscatter amplitude, seafloor slope and roughness data can provide clues about seafloor geology but not straightforward to interpret. We present techniques for seafloor classification in volcanic terrains that integrate the capability of high-resolution, near-bottom sonar instruments to cover extensive areas of seafloor with the ability of visual mapping to discriminate differences in volcanic terrain. These techniques are adapted from the standard practices of terrestrial remote-sensing for use in the deep seafloor volcanic environment. A combination of sonar backscatter and bathymetry is used to supplement the direct seafloor visual observations by geologists to make quasi-geologic thematic maps that are consistent, objective, and most importantly spatially complete. We have taken two approaches to producing thematic maps of the seafloor for the accurate mapping of fine-scale lava morphology (e.g. pillow, lobate and sheet lava) and for the differentiation of distinct seafloor terrain types on a larger scale (e.g. hummocky or smooth). Mapping lava morphology is most accurate using fuzzy logic capable of making inferences between similar morphotypes (e.g. pillow and lobate) and where high-resolution side-scan and bathymetry data coexist. We present examples of lava morphology maps from the Galápagos Spreading Center that show the results from several analyses using different types of input data. Lava morphology is an important source of information on volcanic emplacement and eruptive dynamics. Terrain modeling can be accomplished at any resolution level, depending on the desired use of the model. For volcanic processes, input data needs to be at the appropriate scale to resolve individual volcanic features on the seafloor (e.g. small haystacks and lava channels). We present examples from the East Pacific Rise, which shows that the number of volcanic terrains differs from the tectonic provinces defined by following the spreading axis. Our terrain modeling suggests that differences in ocean crust construction and evolution can be meaningfully identified and explored without a priori assumptions about the geologic processes in a given region.

Holocene debris flows on the Colorado Plateau: The influence of clay mineralogy and chemistry

USGS Publications Warehouse

Webb, R.H.; Griffiths, P.G.; Rudd, L.P.

2008-01-01

Holocene debris flows do not occur uniformly on the Colorado Plateau province of North America. Debris flows occur in specific areas of the plateau, resulting in general from the combination of steep topography, intense convective precipitation, abundant poorly sorted material not stabilized by vegetation, and the exposure of certain fine-grained bedrock units in cliffs or in colluvium beneath those cliffs. In Grand and Cataract Canyons, fine-grained bedrock that produces debris flows contains primarily single-layer clays - notably illite and kaolinite - and has low multilayer clay content. This clay-mineral suite also occurs in the colluvium that produces debris flows as well as in debris-flow deposits, although unconsolidated deposits have less illite than the source bedrock. We investigate the relation between the clay mineralogy and major-cation chemistry of fine-grained bedrock units and the occurrence of debris flows on the entire Colorado Plateau. We determined that 85 mapped fine-grained bedrock units potentially could produce debris flows, and we analyzed clay mineralogy and major-cation concentration of 52 of the most widely distributed units, particularly those exposed in steep topography. Fine-grained bedrock units that produce debris flows contained an average of 71% kaolinite and illite and 5% montmorillonite and have a higher concentration of potassium and magnesium than nonproducing units, which have an average of 51% montmorillonite and a higher concentration of sodium. We used multivariate statistics to discriminate fine-grained bedrock units with the potential to produce debris flows, and we used digital-elevation models and mapped distribution of debris-flow producing units to derive a map that predicts potential occurrence of Holocene debris flows on the Colorado Plateau. ?? 2008 Geological Society of America.

Galactic Abundance Gradients fro IR Fine Strucuture LInes in Compact H II regions

NASA Technical Reports Server (NTRS)

Afflerbach, A.; Churchwell, E.; Werner, M. W.

1996-01-01

We present observations of the [S III]19(micro)m, [O III]52 and 88(micro)m, and [N III]57(micro)m lines toward 18 compact and ultracompact (UC) H II regions. These data were combined with data from the literature and high-resolution radio continuum maps to construct detailed statistical equilibrium and ionization equilibrium models of 34 compact H II regions located at galactocentric distances (Dg)0-12kpc. Our models simultaneously fit the observed IR fine-structure lines and high-resolution radio continuum maps.

Impact of human mobility on the emergence of dengue epidemics in Pakistan

PubMed Central

Wesolowski, Amy; Qureshi, Taimur; Boni, Maciej F.; Sundsøy, Pål Roe; Johansson, Michael A.; Rasheed, Syed Basit; Engø-Monsen, Kenth; Buckee, Caroline O.

2015-01-01

The recent emergence of dengue viruses into new susceptible human populations throughout Asia and the Middle East, driven in part by human travel on both local and global scales, represents a significant global health risk, particularly in areas with changing climatic suitability for the mosquito vector. In Pakistan, dengue has been endemic for decades in the southern port city of Karachi, but large epidemics in the northeast have emerged only since 2011. Pakistan is therefore representative of many countries on the verge of countrywide endemic dengue transmission, where prevention, surveillance, and preparedness are key priorities in previously dengue-free regions. We analyze spatially explicit dengue case data from a large outbreak in Pakistan in 2013 and compare the dynamics of the epidemic to an epidemiological model of dengue virus transmission based on climate and mobility data from ∼40 million mobile phone subscribers. We find that mobile phone-based mobility estimates predict the geographic spread and timing of epidemics in both recently epidemic and emerging locations. We combine transmission suitability maps with estimates of seasonal dengue virus importation to generate fine-scale dynamic risk maps with direct application to dengue containment and epidemic preparedness. PMID:26351662

High resolution wetland mapping in West Siberian taiga zone for methane emission inventory

NASA Astrophysics Data System (ADS)

Terentieva, I. E.; Glagolev, M. V.; Lapshina, E. D.; Sabrekov, A. F.; Maksyutov, S. S.

2015-12-01

High latitude wetlands are important for understanding climate change risks because these environments sink carbon and emit methane. Fine scale heterogeneity of wetland landscapes pose challenges for producing the greenhouse gas flux inventories based on point observations. To reduce uncertainties at the regional scale, we mapped wetlands and water bodies in the taiga zone of West Siberia on a scene-by-scene basis using a supervised classification of Landsat imagery. The training dataset was based on high-resolution images and field data that were collected at 28 test areas. Classification scheme was aimed at methane inventory applications and included 7 wetland ecosystem types composing 9 wetland complexes in different proportions. Accuracy assessment based on 1082 validation polygons of 10 × 10 pixels indicated an overall map accuracy of 79 %. The total area of the wetlands and water bodies was estimated to be 52.4 Mha or 4-12 % of the global wetland area. Ridge-hollow complexes prevail in WS's taiga, occupying 33 % of the domain, followed by forested bogs or "ryams" (23 %), ridge-hollow-lake complexes (16 %), open fens (8 %), palsa complexes (7 %), open bogs (5 %), patterned fens (4 %), and swamps (4 %). Various oligotrophic environments are dominant among the wetland ecosystems, while fens cover only 14 % of the area. Because of the significant update in the wetland ecosystem coverage, a considerable revaluation of the total CH4 emissions from the entire region is expected. A new Landsat-based map of WS's taiga wetlands provides a benchmark for validation of coarse-resolution global land cover products and wetland datasets in high latitudes.

Global patterns of terrestrial vertebrate diversity and conservation

PubMed Central

Jenkins, Clinton N.; Pimm, Stuart L.; Joppa, Lucas N.

2013-01-01

Identifying priority areas for biodiversity is essential for directing conservation resources. Fundamentally, we must know where individual species live, which ones are vulnerable, where human actions threaten them, and their levels of protection. As conservation knowledge and threats change, we must reevaluate priorities. We mapped priority areas for vertebrates using newly updated data on >21,000 species of mammals, amphibians, and birds. For each taxon, we identified centers of richness for all species, small-ranged species, and threatened species listed with the International Union for the Conservation of Nature. Importantly, all analyses were at a spatial grain of 10 × 10 km, 100 times finer than previous assessments. This fine scale is a significant methodological improvement, because it brings mapping to scales comparable with regional decisions on where to place protected areas. We also mapped recent species discoveries, because they suggest where as-yet-unknown species might be living. To assess the protection of the priority areas, we calculated the percentage of priority areas within protected areas using the latest data from the World Database of Protected Areas, providing a snapshot of how well the planet’s protected area system encompasses vertebrate biodiversity. Although the priority areas do have more protection than the global average, the level of protection still is insufficient given the importance of these areas for preventing vertebrate extinctions. We also found substantial differences between our identified vertebrate priorities and the leading map of global conservation priorities, the biodiversity hotspots. Our findings suggest a need to reassess the global allocation of conservation resources to reflect today’s improved knowledge of biodiversity and conservation. PMID:23803854

Seeding method influences warm-season grass abundance and distribution but not local diversity in grassland restoration

USGS Publications Warehouse

Yurkonis, Kathryn A.; Wilsey, Brian J.; Moloney, Kirk A.; Drobney, Pauline; Larson, Diane L.

2010-01-01

Ecological theory predicts that the arrangement of seedlings in newly restored communities may influence future species diversity and composition. We test the prediction that smaller distances between neighboring seeds in drill seeded grassland plantings would result in lower species diversity, greater weed abundance, and larger conspecific patch sizes than otherwise similar broadcast seeded plantings. A diverse grassland seed mix was either drill seeded, which places seeds in equally spaced rows, or broadcast seeded, which spreads seeds across the ground surface, into 24 plots in each of three sites in 2005. In summer 2007, we measured species abundance in a 1 m2 quadrat in each plot and mapped common species within the quadrat by recording the most abundant species in each of 64 cells. Quadrat-scale diversity and weed abundance were similar between drilled and broadcast plots, suggesting that processes that limited establishment and controlled invasion were not affected by such fine-scale seed distribution. However, native warm-season (C4) grasses were more abundant and occurred in less compact patches in drilled plots. This difference in C4 grass abundance and distribution may result from increased germination or vegetative propagation of C4 grasses in drilled plots. Our findings suggest that local plant density may control fine-scale heterogeneity and species composition in restored grasslands, processes that need to be further investigated to determine whether seed distributions can be manipulated to increase diversity in restored grasslands.

Seeding Method Influences Warm-Season Grass Abundance and Distribution but not Local Diversity in Grassland Restoration

USGS Publications Warehouse

Yurkonis, K.A.; Wilsey, B.J.; Moloney, K.A.; Drobney, P.; Larson, D.L.

2010-01-01

Ecological theory predicts that the arrangement of seedlings in newly restored communities may influence future species diversity and composition. We test the prediction that smaller distances between neighboring seeds in drill seeded grassland plantings would result in lower species diversity, greater weed abundance, and larger conspecific patch sizes than otherwise similar broadcast seeded plantings. A diverse grassland seed mix was either drill seeded, which places seeds in equally spaced rows, or broadcast seeded, which spreads seeds across the ground surface, into 24 plots in each of three sites in 2005. In summer 2007, we measured species abundance in a 1 m2 quadrat in each plot and mapped common species within the quadrat by recording the most abundant species in each of 64 cells. Quadrat-scale diversity and weed abundance were similar between drilled and broadcast plots, suggesting that processes that limited establishment and controlled invasion were not affected by such fine-scale seed distribution. However, native warm-season (C4) grasses were more abundant and occurred in less compact patches in drilled plots. This difference in C4 grass abundance and distribution may result from increased germination or vegetative propagation of C4 grasses in drilled plots. Our findings suggest that local plant density may control fine-scale heterogeneity and species composition in restored grasslands, processes that need to be further investigated to determine whether seed distributions can be manipulated to increase diversity in restored grasslands. ?? 2010 Society for Ecological Restoration International.

Assessing species habitat using Google Street View: a case study of cliff-nesting vultures.

PubMed

Olea, Pedro P; Mateo-Tomás, Patricia

2013-01-01

The assessment of a species' habitat is a crucial issue in ecology and conservation. While the collection of habitat data has been boosted by the availability of remote sensing technologies, certain habitat types have yet to be collected through costly, on-ground surveys, limiting study over large areas. Cliffs are ecosystems that provide habitat for a rich biodiversity, especially raptors. Because of their principally vertical structure, however, cliffs are not easy to study by remote sensing technologies, posing a challenge for many researches and managers working with cliff-related biodiversity. We explore the feasibility of Google Street View, a freely available on-line tool, to remotely identify and assess the nesting habitat of two cliff-nesting vultures (the griffon vulture and the globally endangered Egyptian vulture) in northwestern Spain. Two main usefulness of Google Street View to ecologists and conservation biologists were evaluated: i) remotely identifying a species' potential habitat and ii) extracting fine-scale habitat information. Google Street View imagery covered 49% (1,907 km) of the roads of our study area (7,000 km²). The potential visibility covered by on-ground surveys was significantly greater (mean: 97.4%) than that of Google Street View (48.1%). However, incorporating Google Street View to the vulture's habitat survey would save, on average, 36% in time and 49.5% in funds with respect to the on-ground survey only. The ability of Google Street View to identify cliffs (overall accuracy = 100%) outperformed the classification maps derived from digital elevation models (DEMs) (62-95%). Nonetheless, high-performance DEM maps may be useful to compensate Google Street View coverage limitations. Through Google Street View we could examine 66% of the vultures' nesting-cliffs existing in the study area (n = 148): 64% from griffon vultures and 65% from Egyptian vultures. It also allowed us the extraction of fine-scale features of cliffs. This World Wide Web-based methodology may be a useful, complementary tool to remotely map and assess the potential habitat of cliff-dependent biodiversity over large geographic areas, saving survey-related costs.

Assessing Species Habitat Using Google Street View: A Case Study of Cliff-Nesting Vultures

PubMed Central

Olea, Pedro P.; Mateo-Tomás, Patricia

2013-01-01

The assessment of a species’ habitat is a crucial issue in ecology and conservation. While the collection of habitat data has been boosted by the availability of remote sensing technologies, certain habitat types have yet to be collected through costly, on-ground surveys, limiting study over large areas. Cliffs are ecosystems that provide habitat for a rich biodiversity, especially raptors. Because of their principally vertical structure, however, cliffs are not easy to study by remote sensing technologies, posing a challenge for many researches and managers working with cliff-related biodiversity. We explore the feasibility of Google Street View, a freely available on-line tool, to remotely identify and assess the nesting habitat of two cliff-nesting vultures (the griffon vulture and the globally endangered Egyptian vulture) in northwestern Spain. Two main usefulness of Google Street View to ecologists and conservation biologists were evaluated: i) remotely identifying a species’ potential habitat and ii) extracting fine-scale habitat information. Google Street View imagery covered 49% (1,907 km) of the roads of our study area (7,000 km2). The potential visibility covered by on-ground surveys was significantly greater (mean: 97.4%) than that of Google Street View (48.1%). However, incorporating Google Street View to the vulture’s habitat survey would save, on average, 36% in time and 49.5% in funds with respect to the on-ground survey only. The ability of Google Street View to identify cliffs (overall accuracy = 100%) outperformed the classification maps derived from digital elevation models (DEMs) (62–95%). Nonetheless, high-performance DEM maps may be useful to compensate Google Street View coverage limitations. Through Google Street View we could examine 66% of the vultures’ nesting-cliffs existing in the study area (n = 148): 64% from griffon vultures and 65% from Egyptian vultures. It also allowed us the extraction of fine-scale features of cliffs. This World Wide Web-based methodology may be a useful, complementary tool to remotely map and assess the potential habitat of cliff-dependent biodiversity over large geographic areas, saving survey-related costs. PMID:23355880

A major gene controls mimicry and crypsis in butterflies and moths

PubMed Central

Nadeau, Nicola J.; Pardo-Diaz, Carolina; Whibley, Annabel; Supple, Megan; Saenko, Suzanne V.; Wallbank, Richard W. R.; Wu, Grace C.; Maroja, Luana; Ferguson, Laura; Hanly, Joseph J.; Hines, Heather; Salazar, Camilo; Merrill, Richard; Dowling, Andrea; ffrench-Constant, Richard; Llaurens, Violaine; Joron, Mathieu; McMillan, W. Owen; Jiggins, Chris D.

2016-01-01

The wing patterns of butterflies and moths (Lepidoptera) are diverse and striking examples of evolutionary diversification by natural selection1,2. Lepidopteran wing colour patterns are a key innovation, consisting of arrays of coloured scales. We still lack a general understanding of how these patterns are controlled and if there is any commonality across the 160,000 moth and 17,000 butterfly species. Here, we identify a gene, cortex, through fine-scale mapping using population genomics and gene expression analyses, which regulates pattern switches in multiple species across the mimetic radiation in Heliconius butterflies. cortex belongs to a fast evolving subfamily of the otherwise highly conserved fizzy family of cell cycle regulators3, suggesting that it most likely regulates pigmentation patterning through regulation of scale cell development. In parallel with findings in the peppered moth (Biston betularia)4, our results suggest that this mechanism is common within Lepidoptera and that cortex has become a major target for natural selection acting on colour and pattern variation in this group of insects. PMID:27251285

Fine-scale analysis of genetic structure in the brooding coral Seriatopora hystrix from the Red Sea

NASA Astrophysics Data System (ADS)

Maier, E.; Tollrian, R.; Nürnberger, B.

2009-09-01

The dispersal of gametes and larvae plays a key role in the population dynamics of sessile marine invertebrates. Species with internal fertilisation are often associated with very localised larval dispersal, which may cause small-scale patterns of neutral genetic variation. This study on the brooding coral Seriatopora hystrix from the Red Sea focused on the smallest possible scale: Two S. hystrix stands (~100 colonies each) near Dahab were completely sampled, mapped and analysed at five microsatellite markers. The sexual mode of reproduction, the likely occurrence of selfing and the level of immigration were in agreement with previous studies on this species. Contrary to previous findings, both stands were in Hardy-Weinberg proportions. Also, no evidence for spatially restricted larval dispersal within the sampled areas was found. Differences between this and previous studies on S. hystrix could reflect variation in life history or varying environmental conditions, which opens intriguing questions for future research.

Scaling field data to calibrate and validate moderate spatial resolution remote sensing models

USGS Publications Warehouse

Baccini, A.; Friedl, M.A.; Woodcock, C.E.; Zhu, Z.

2007-01-01

Validation and calibration are essential components of nearly all remote sensing-based studies. In both cases, ground measurements are collected and then related to the remote sensing observations or model results. In many situations, and particularly in studies that use moderate resolution remote sensing, a mismatch exists between the sensor's field of view and the scale at which in situ measurements are collected. The use of in situ measurements for model calibration and validation, therefore, requires a robust and defensible method to spatially aggregate ground measurements to the scale at which the remotely sensed data are acquired. This paper examines this challenge and specifically considers two different approaches for aggregating field measurements to match the spatial resolution of moderate spatial resolution remote sensing data: (a) landscape stratification; and (b) averaging of fine spatial resolution maps. The results show that an empirically estimated stratification based on a regression tree method provides a statistically defensible and operational basis for performing this type of procedure. 

Enhancement of fine-scale mixing for fuel-rich plume combustion

NASA Astrophysics Data System (ADS)

Schadow, K. C.; Gutmark, E.; Parr, T. P.; Parr, D. M.; Wilson, K. J.; Ferrell, G. B.

1987-01-01

The effect of enhancing small-scale turbulent structures on the combustion intensity and flame stability was studied in nonreacting and reacting flows. Hot-wire anemometry was used to map the mean and turbulent flow fields of the nonreacting flows. Reacting flows were studied in a free flame and in a ducted gas-generator fuel-rich plume using Planar Laser Induced Fluorescence, a rake of thermocouples and high speed photography. A modified circular nozzle having several backward facing steps upstream of its exit was used to introduce numerous inflection points in the initial mean velocity profiles, thus producing multiple corresponding sources of small-scale turbulence generators. Cold flow tests showed turbulence increases of up to six times the initial turbulence level relative to a circular nozzle. The ensuing result was that the flame of this nozzle was more intense with a homogeneous heat release. The fuel-rich plume was stable even in supersonic speeds, and secondary ignition was obtained under conditions that prevented sustained afterburning using the circular nozzle.

The gene cortex controls mimicry and crypsis in butterflies and moths.

PubMed

Nadeau, Nicola J; Pardo-Diaz, Carolina; Whibley, Annabel; Supple, Megan A; Saenko, Suzanne V; Wallbank, Richard W R; Wu, Grace C; Maroja, Luana; Ferguson, Laura; Hanly, Joseph J; Hines, Heather; Salazar, Camilo; Merrill, Richard M; Dowling, Andrea J; ffrench-Constant, Richard H; Llaurens, Violaine; Joron, Mathieu; McMillan, W Owen; Jiggins, Chris D

2016-06-02

The wing patterns of butterflies and moths (Lepidoptera) are diverse and striking examples of evolutionary diversification by natural selection. Lepidopteran wing colour patterns are a key innovation, consisting of arrays of coloured scales. We still lack a general understanding of how these patterns are controlled and whether this control shows any commonality across the 160,000 moth and 17,000 butterfly species. Here, we use fine-scale mapping with population genomics and gene expression analyses to identify a gene, cortex, that regulates pattern switches in multiple species across the mimetic radiation in Heliconius butterflies. cortex belongs to a fast-evolving subfamily of the otherwise highly conserved fizzy family of cell-cycle regulators, suggesting that it probably regulates pigmentation patterning by regulating scale cell development. In parallel with findings in the peppered moth (Biston betularia), our results suggest that this mechanism is common within Lepidoptera and that cortex has become a major target for natural selection acting on colour and pattern variation in this group of insects.

Detailed maps of tropical forest types are within reach: forest tree communities for Trinidad and Tobago mapped with multiseason Landsat and multiseason fine-resolution imagery

Treesearch

Eileen H. Helmer; Thomas S. Ruzycki; Jay Benner; Shannon M. Voggesser; Barbara P. Scobie; Courtenay Park; David W. Fanning; Seepersad Ramnarine

2012-01-01

Tropical forest managers need detailed maps of forest types for REDD+, but spectral similarity among forest types; cloud and scan-line gaps; and scarce vegetation ground plots make producing such maps with satellite imagery difficult. How can managers map tropical forest tree communities with satellite imagery given these challenges? Here we describe a case study of...

Three-dimensional mapping of soil chemical characteristics at micrometric scale: Statistical prediction by combining 2D SEM-EDX data and 3D X-ray computed micro-tomographic images

NASA Astrophysics Data System (ADS)

Hapca, Simona

2015-04-01

Many soil properties and functions emerge from interactions of physical, chemical and biological processes at microscopic scales, which can be understood only by integrating techniques that traditionally are developed within separate disciplines. While recent advances in imaging techniques, such as X-ray computed tomography (X-ray CT), offer the possibility to reconstruct the 3D physical structure at fine resolutions, for the distribution of chemicals in soil, existing methods, based on scanning electron microscope (SEM) and energy dispersive X-ray detection (EDX), allow for characterization of the chemical composition only on 2D surfaces. At present, direct 3D measurement techniques are still lacking, sequential sectioning of soils, followed by 2D mapping of chemical elements and interpolation to 3D, being an alternative which is explored in this study. Specifically, we develop an integrated experimental and theoretical framework which combines 3D X-ray CT imaging technique with 2D SEM-EDX and use spatial statistics methods to map the chemical composition of soil in 3D. The procedure involves three stages 1) scanning a resin impregnated soil cube by X-ray CT, followed by precision cutting to produce parallel thin slices, the surfaces of which are scanned by SEM-EDX, 2) alignment of the 2D chemical maps within the internal 3D structure of the soil cube, and 3) development, of spatial statistics methods to predict the chemical composition of 3D soil based on the observed 2D chemical and 3D physical data. Specifically, three statistical models consisting of a regression tree, a regression tree kriging and cokriging model were used to predict the 3D spatial distribution of carbon, silicon, iron and oxygen in soil, these chemical elements showing a good spatial agreement between the X-ray grayscale intensities and the corresponding 2D SEM-EDX data. Due to the spatial correlation between the physical and chemical data, the regression-tree model showed a great potential in predicting chemical composition in particular for iron, which is generally sparsely distributed in soil. For carbon, silicon and oxygen, which are more densely distributed, the additional kriging of the regression tree residuals improved significantly the prediction, whereas prediction based on co-kriging was less consistent across replicates, underperforming regression-tree kriging. The present study shows a great potential in integrating geo-statistical methods with imaging techniques to unveil the 3D chemical structure of soil at very fine scales, the framework being suitable to be further applied to other types of imaging data such as images of biological thin sections for characterization of microbial distribution. Key words: X-ray CT, SEM-EDX, segmentation techniques, spatial correlation, 3D soil images, 2D chemical maps.

Giant polygons and mounds in the lowlands of Mars: signatures of an ancient ocean?

PubMed

Oehler, Dorothy Z; Allen, Carlton C

2012-06-01

This paper presents the hypothesis that the well-known giant polygons and bright mounds of the martian lowlands may be related to a common process-a process of fluid expulsion that results from burial of fine-grained sediments beneath a body of water. Specifically, we hypothesize that giant polygons and mounds in Chryse and Acidalia Planitiae are analogous to kilometer-scale polygons and mud volcanoes in terrestrial, marine basins and that the co-occurrence of masses of these features in Chryse and Acidalia may be the signature of sedimentary processes in an ancient martian ocean. We base this hypothesis on recent data from both Earth and Mars. On Earth, 3-D seismic data illustrate kilometer-scale polygons that may be analogous to the giant polygons on Mars. The terrestrial polygons form in fine-grained sediments that have been deposited and buried in passive-margin, marine settings. These polygons are thought to result from compaction/dewatering, and they are commonly associated with fluid expulsion features, such as mud volcanoes. On Mars, in Chryse and Acidalia Planitiae, orbital data demonstrate that giant polygons and mounds have overlapping spatial distributions. There, each set of features occurs within a geological setting that is seemingly analogous to that of the terrestrial, kilometer-scale polygons (broad basin of deposition, predicted fine-grained sediments, and lack of significant horizontal stress). Regionally, the martian polygons and mounds both show a correlation to elevation, as if their formation were related to past water levels. Although these observations are based on older data with incomplete coverage, a similar correlation to elevation has been established in one local area studied in detail with newer higher-resolution data. Further mapping with the latest data sets should more clearly elucidate the relationship(s) of the polygons and mounds to elevation over the entire Chryse-Acidalia region and thereby provide more insight into this hypothesis.

Fractures system within Qusaiba shale outcrop and its relationship to the lithological properties, Qasim area, Central Saudi Arabia

NASA Astrophysics Data System (ADS)

Ibrahim, Mohamed I. M.; Hariri, Mustafa M.; Abdullatif, Osman M.; Makkawi, Mohammad H.; Elzain, Hussam

2017-09-01

The basal Qusaiba hot shale member of Qalibah Formation is considered to be an important source rock in the Paleozoic petroleum system of Saudi Arabia and an exploration target for tight shale as one of the Unconventional resources of petroleum. This work has been carried out to understand the fractures network of Qusaiba shale member in outcrops located to the west of Qusayba' village in Al-Qasim area, Central Saudi Arabia. The main objective of this study is to understand the distribution of natural fractures over different lithological units. Description data sheets were used for the detailed lithological description of Qusaiba shale member on two outcrops. Spot-7 and Landsat ETM+ satellite images were used for lineament mapping and analyses on a regional scale in a GIS environment. Fractures characterization in outcrop-scale was conducted by using linear scanline method. Qusaiba shale member in the study area consists of 5 main lithofacies, divided based on their sedimentary structures and petrographical properties, from base to top in the outcrops, the lithofacies are; fissile shale, very fine-grained micaceous siltstone, bioturbated mudstone, very fine to fine-grained hummocky cross-stratified sandstone, and fine to medium-grained low/high angle cross-stratified sandstone lithofacies. Lineaments interpretation of the Spot-7 and Landsat ETM+ satellite images showed two major directions in the study area; 320° that could be related to Najd fault system and 20° that could be related to the extensional activities which took place after Amar collision. Fractures are much denser in the fissile shale and mudstone lithofacies than sandstones lithofacies, and average spacing is smaller in the fissile shale and mudstone lithofacies than sandstones lithofacies. Lineaments and large-scale fractures are Non-Stratabound fractures and they deal with the area as one big mechanical unit, but small-scale fractures are Stratabound fractures that propose different mechanical units within Qusaiba shale member in the study area. The fractures network in the study area has a wide range of properties related to fractures density, length, spacing, height, and termination degree. The conceptual multi-scale model divides the fractures in the study area into 4 orders depending on the available data that have been observed from satellite images and field. The multi-scale fractures model that was generated in this study could help to understand the distribution of stratigraphically controlled fractures when integrated with flow simulation models. Overall, this work could have a significant contribution to tight shale exploration plans in the subsurface by providing some knowledge about the fractures mechanical behavior of the lower part of Qusaiba shale member of Qalibah Formation.

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

PubMed

Dadaev, Tokhir; Saunders, Edward J; Newcombe, Paul J; Anokian, Ezequiel; Leongamornlert, Daniel A; Brook, Mark N; Cieza-Borrella, Clara; Mijuskovic, Martina; Wakerell, Sarah; Olama, Ali Amin Al; Schumacher, Fredrick R; Berndt, Sonja I; Benlloch, Sara; Ahmed, Mahbubl; Goh, Chee; Sheng, Xin; Zhang, Zhuo; Muir, Kenneth; Govindasami, Koveela; Lophatananon, Artitaya; Stevens, Victoria L; Gapstur, Susan M; Carter, Brian D; Tangen, Catherine M; Goodman, Phyllis; Thompson, Ian M; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L J; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; Hakansson, Niclas; West, Catharine; Dunning, Alison M; Burnet, Neil; Mucci, Lorelei; Giovannucci, Edward; Andriole, Gerald; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Freeman, Laura E Beane; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Martin, Richard M; Travis, Ruth C; Key, Tim J; Hamilton, Robert J; Fleshner, Neil E; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C; Rosenstein, Barry; Kerns, Sarah; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G; Southey, Melissa C; MacInnis, Robert J; FitzGerald, Liesel M; Kibel, Adam S; Drake, Bettina F; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn L; Stampfer, Meir; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Stanford, Janet L; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A; Geybels, Milan S; Nordestgaard, Børge G; Nielsen, Sune F; Weisher, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J; John, Esther M; Teixeira, Manuel R; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W; Newcomb, Lisa F; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Singhal, Sandeep; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A; Aukim-Hastie, Claire; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J; Jenster, Guido; van Schaik, Ron H N; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David J; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Kraft, Peter; Freedman, Matthew; Wiklund, Fredrik; Chanock, Stephen; Henderson, Brian E; Easton, Douglas F; Haiman, Christopher A; Eeles, Rosalind A; Conti, David V; Kote-Jarai, Zsofia

2018-06-11

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

Fine-mapping inflammatory bowel disease loci to single-variant resolution.

PubMed

Huang, Hailiang; Fang, Ming; Jostins, Luke; Umićević Mirkov, Maša; Boucher, Gabrielle; Anderson, Carl A; Andersen, Vibeke; Cleynen, Isabelle; Cortes, Adrian; Crins, François; D'Amato, Mauro; Deffontaine, Valérie; Dmitrieva, Julia; Docampo, Elisa; Elansary, Mahmoud; Farh, Kyle Kai-How; Franke, Andre; Gori, Ann-Stephan; Goyette, Philippe; Halfvarson, Jonas; Haritunians, Talin; Knight, Jo; Lawrance, Ian C; Lees, Charlie W; Louis, Edouard; Mariman, Rob; Meuwissen, Theo; Mni, Myriam; Momozawa, Yukihide; Parkes, Miles; Spain, Sarah L; Théâtre, Emilie; Trynka, Gosia; Satsangi, Jack; van Sommeren, Suzanne; Vermeire, Severine; Xavier, Ramnik J; Weersma, Rinse K; Duerr, Richard H; Mathew, Christopher G; Rioux, John D; McGovern, Dermot P B; Cho, Judy H; Georges, Michel; Daly, Mark J; Barrett, Jeffrey C

2017-07-13

Inflammatory bowel diseases are chronic gastrointestinal inflammatory disorders that affect millions of people worldwide. Genome-wide association studies have identified 200 inflammatory bowel disease-associated loci, but few have been conclusively resolved to specific functional variants. Here we report fine-mapping of 94 inflammatory bowel disease loci using high-density genotyping in 67,852 individuals. We pinpoint 18 associations to a single causal variant with greater than 95% certainty, and an additional 27 associations to a single variant with greater than 50% certainty. These 45 variants are significantly enriched for protein-coding changes (n = 13), direct disruption of transcription-factor binding sites (n = 3), and tissue-specific epigenetic marks (n = 10), with the last category showing enrichment in specific immune cells among associations stronger in Crohn's disease and in gut mucosa among associations stronger in ulcerative colitis. The results of this study suggest that high-resolution fine-mapping in large samples can convert many discoveries from genome-wide association studies into statistically convincing causal variants, providing a powerful substrate for experimental elucidation of disease mechanisms.

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms

PubMed Central

Horikoshi, Momoko; Pasquali, Lorenzo; Wiltshire, Steven; Huyghe, Jeroen R.; Mahajan, Anubha; Asimit, Jennifer L.; Ferreira, Teresa; Locke, Adam E.; Robertson, Neil R.; Wang, Xu; Sim, Xueling; Fujita, Hayato; Hara, Kazuo; Young, Robin; Zhang, Weihua; Choi, Sungkyoung; Chen, Han; Kaur, Ismeet; Takeuchi, Fumihiko; Fontanillas, Pierre; Thuillier, Dorothée; Yengo, Loic; Below, Jennifer E.; Tam, Claudia H.T.; Wu, Ying; Abecasis, Gonçalo; Altshuler, David; Bell, Graeme I.; Blangero, John; Burtt, Noél P.; Duggirala, Ravindranath; Florez, Jose C.; Hanis, Craig L.; Seielstad, Mark; Atzmon, Gil; Chan, Juliana C.N.; Ma, Ronald C.W.; Froguel, Philippe; Wilson, James G.; Bharadwaj, Dwaipayan; Dupuis, Josee; Meigs, James B.; Cho, Yoon Shin; Park, Taesung; Kooner, Jaspal S.; Chambers, John C.; Saleheen, Danish; Kadowaki, Takashi; Tai, E. Shyong; Mohlke, Karen L.; Cox, Nancy J.; Ferrer, Jorge; Zeggini, Eleftheria; Kato, Norihiro; Teo, Yik Ying; Boehnke, Michael; McCarthy, Mark I.; Morris, Andrew P.

2016-01-01

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci. PMID:26911676

Spatial Variability of Sources and Mixing State of Atmospheric Particles in a Metropolitan Area.

PubMed

Ye, Qing; Gu, Peishi; Li, Hugh Z; Robinson, Ellis S; Lipsky, Eric; Kaltsonoudis, Christos; Lee, Alex K Y; Apte, Joshua S; Robinson, Allen L; Sullivan, Ryan C; Presto, Albert A; Donahue, Neil M

2018-05-30

Characterizing intracity variations of atmospheric particulate matter has mostly relied on fixed-site monitoring and quantifying variability in terms of different bulk aerosol species. In this study, we performed ground-based mobile measurements using a single-particle mass spectrometer to study spatial patterns of source-specific particles and the evolution of particle mixing state in 21 areas in the metropolitan area of Pittsburgh, PA. We selected sampling areas based on traffic density and restaurant density with each area ranging from 0.2 to 2 km 2 . Organics dominate particle composition in all of the areas we sampled while the sources of organics differ. The contribution of particles from traffic and restaurant cooking varies greatly on the neighborhood scale. We also investigate how primary and aged components in particles mix across the urban scale. Lastly we quantify and map the particle mixing state for all areas we sampled and discuss the overall pattern of mixing state evolution and its implications. We find that in the upwind and downwind of the urban areas, particles are more internally mixed while in the city center, particle mixing state shows large spatial heterogeneity that is mostly driven by emissions. This study is to our knowledge, the first study to perform fine spatial scale mapping of particle mixing state using ground-based mobile measurement and single-particle mass spectrometry.

Characterising and modelling regolith stratigraphy using multiple geophysical techniques

NASA Astrophysics Data System (ADS)

Thomas, M.; Cremasco, D.; Fotheringham, T.; Hatch, M. A.; Triantifillis, J.; Wilford, J.

2013-12-01

Regolith is the weathered, typically mineral-rich layer from fresh bedrock to land surface. It encompasses soil (A, E and B horizons) that has undergone pedogenesis. Below is the weathered C horizon that retains at least some of the original rocky fabric and structure. At the base of this is the lower regolith boundary of continuous hard bedrock (the R horizon). Regolith may be absent, e.g. at rocky outcrops, or may be many 10's of metres deep. Comparatively little is known about regolith, and critical questions remain regarding composition and characteristics - especially deeper where the challenge of collecting reliable data increases with depth. In Australia research is underway to characterise and map regolith using consistent methods at scales ranging from local (e.g. hillslope) to continental scales. These efforts are driven by many research needs, including Critical Zone modelling and simulation. Pilot research in South Australia using digitally-based environmental correlation techniques modelled the depth to bedrock to 9 m for an upland area of 128 000 ha. One finding was the inability to reliably model local scale depth variations over horizontal distances of 2 - 3 m and vertical distances of 1 - 2 m. The need to better characterise variations in regolith to strengthen models at these fine scales was discussed. Addressing this need, we describe high intensity, ground-based multi-sensor geophysical profiling of three hillslope transects in different regolith-landscape settings to characterise fine resolution (i.e. < 1 m) regolith stratigraphy. The geophysics included: ground penetrating radar collected at a number of frequencies; multiple frequency, multiple coil electromagnetic induction; and high resolution resistivity. These were accompanied by georeferenced, closely spaced deep cores to 9 m - or to core refusal. The intact cores were sub-sampled to standard depths and analysed for regolith properties to compile core datasets consisting of: water content; texture; electrical conductivity; and weathered state. After preprocessing (filtering, geo-registration, depth correction, etc.) each geophysical profile was evaluated by matching the core data. Applying traditional geophysical techniques, the best profiles were inverted using the core data creating two-dimensional (2-D) stratigraphic regolith models for each transect, and evaluated using independent validation. Next, in a test of an alternative method borrowed from digital soil mapping, the best preprocessed geophysical profiles were co-registered and stratigraphic models for each property created using multivariate environmental correlation. After independent validation, the qualities of the latest models were compared to the traditionally derived 2-D inverted models. Finally, the best overall stratigraphic models were used in conjunction with local environmental data (e.g. geology, geochemistry, terrain, soils) to create conceptual regolith hillslope models for each transect highlighting important features and processes, e.g. morphology, hydropedology and weathering characteristics. Results are presented with recommendations regarding the use of geophysics in modelling regolith stratigraphy at fine scales.

Sample-based synthesis of two-scale structures with anisotropy

DOE PAGES

Liu, Xingchen; Shapiro, Vadim

2017-05-19

A vast majority of natural or synthetic materials are characterized by their anisotropic properties, such as stiffness. Such anisotropy is effected by the spatial distribution of the fine-scale structure and/or anisotropy of the constituent phases at a finer scale. In design, proper control of the anisotropy may greatly enhance the efficiency and performance of synthesized structures. In this paper, we propose a sample-based two-scale structure synthesis approach that explicitly controls anisotropic effective material properties of the structure on the coarse scale by orienting sampled material neighborhoods at the fine scale. We first characterize the non-uniform orientations distribution of the samplemore » structure by showing that the principal axes of an orthotropic material may be determined by the eigenvalue decomposition of its effective stiffness tensor. Such effective stiffness tensors can be efficiently estimated based on the two-point correlation functions of the fine-scale structures. Then we synthesize the two-scale structure by rotating fine-scale structures from the sample to follow a given target orientation field. Finally, the effectiveness of the proposed approach is demonstrated through examples in both 2D and 3D.« less

Sample-based synthesis of two-scale structures with anisotropy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Xingchen; Shapiro, Vadim

A vast majority of natural or synthetic materials are characterized by their anisotropic properties, such as stiffness. Such anisotropy is effected by the spatial distribution of the fine-scale structure and/or anisotropy of the constituent phases at a finer scale. In design, proper control of the anisotropy may greatly enhance the efficiency and performance of synthesized structures. In this paper, we propose a sample-based two-scale structure synthesis approach that explicitly controls anisotropic effective material properties of the structure on the coarse scale by orienting sampled material neighborhoods at the fine scale. We first characterize the non-uniform orientations distribution of the samplemore » structure by showing that the principal axes of an orthotropic material may be determined by the eigenvalue decomposition of its effective stiffness tensor. Such effective stiffness tensors can be efficiently estimated based on the two-point correlation functions of the fine-scale structures. Then we synthesize the two-scale structure by rotating fine-scale structures from the sample to follow a given target orientation field. Finally, the effectiveness of the proposed approach is demonstrated through examples in both 2D and 3D.« less

An operational methodology for riparian land cover fine scale regional mapping for the study of landscape influence on river ecological status

NASA Astrophysics Data System (ADS)

Tormos, T.; Kosuth, P.; Souchon, Y.; Villeneuve, B.; Durrieu, S.; Chandesris, A.

2010-12-01

Preservation and restoration of river ecosystems require an improved understanding of the mechanisms through which they are influenced by landscape at multiple spatial scales and particularly at river corridor scale considering the role of riparian vegetation for regulating and protecting river ecological status and the relevance of this specific area for implementing efficient and realistic strategies. Assessing correctly this influence over large river networks involves accurate broad scale (i.e. at least regional) information on Land Cover within Riparian Areas (LCRA). As the structure of land cover along rivers is generally not accessible using moderate-scale satellite imagery, finer spatial resolution imagery and specific mapping techniques are needed. For this purpose we developed a generic multi-scale Object Based Image Analysis (OBIA) scheme able to produce LCRA maps in different geographic context by exploiting information available from very high spatial resolution imagery (satellite or airborne) and/or metric to decametric spatial thematic data on a given study zone thanks to fuzzy expert knowledge classification rules. A first experimentation was carried out on the Herault river watershed (southern of France), a 2650 square kilometers basin that presents a contrasted landscape (different ecoregions) and a total stream length of 1150 Km, using high and very high multispectral remotely-sensed images (10m Spot5 multispectral images and 0.5m aerial photography) and existing spatial thematic data. Application of the OBIA scheme produced a detailed (22 classes) LCRA map with an overall accuracy of 89% and a Kappa index of 83% according to a land cover pressures typology (six categories). A second experimentation (using the same data sources) was carried out on a larger test zone, a part of the Normandy river network (25 000 square kilometers basin; 6000 km long river network; 155 ecological stations). This second work aimed at elaborating a robust statistical eco-regional model to study links between land cover spatial indicators calculated at local and watershed scales, and river ecological status assessed with macroinvertebrate indicators. Application of the OBIA scheme produced a detailed (62 classes) LCRA map which allowed the model to highlight influence of specific land use patterns: (i) the significant beneficial effect of 20-m riparian tree vegetation strip near a station and 20-m riparian grassland strip along the upstream network of a station and (ii) the negative impact on river ecological status of urban areas and roads on the upstream flood plain of a station. Results of these two experimentations highlight that (i) the application of an OBIA scheme using multi-source spatial data provides an efficient approach for mapping and monitoring LCRA that can be implemented operationally at regional or national scale and (ii) and the interest of using LCRA-maps derived from very high spatial resolution imagery (satellite or airborne) and/or metric spatial thematic data to study landscape influence on river ecological status and support managers in the definition of optimized riparian preservation and restoration strategies.

Reliability of biomass burning estimates from savanna fires: Biomass burning in northern Australia during the 1999 Biomass Burning and Lightning Experiment B field campaign

NASA Astrophysics Data System (ADS)

Russell-Smith, Jeremy; Edwards, Andrew C.; Cook, Garry D.

2003-02-01

This paper estimates the two-daily extent of savanna burning and consumption of fine (grass and litter) fuels from an extensive 230,000 km2 region of northern Australia during August-September 1999 encompassing the Australian continental component of the Biomass Burning and Lightning Experiment B (BIBLE B) campaign [, 2002]. The extent of burning for the study region was derived from fire scar mapping of imagery from the advanced very high resolution radiometer (AVHRR) on board the National Oceanic and Atmospheric Administration (NOAA) satellite. The mapping was calibrated and verified with reference to one Landsat scene and associated aerial transect validation data. Fine fuel loads were estimated using published fuel accumulation relationships for major regional fuel types. It is estimated that more than 43,000 km2 was burnt during the 25 day study period, with about 19 Mt of fine (grass and litter) fuels. This paper examines assumptions and errors associated with these estimates. It is estimated from uncalibrated fire mapping derived from AVHRR imagery that 417,500 km2 of the northern Australian savanna was burnt in 1999, of which 136,405 km2, or 30%, occurred in the Northern Territory study region. Using generalized fuel accumulation equations, such biomass burning consumed an estimated 212.3 Mt of fine fuels, but no data are available for consumption of coarse fuels. This figure exceeds a recent estimate, based on fine fuels only, for the combined Australian savanna and temperate grassland biomass burning over the period 1990-1999 but is lower than past estimates derived from classification approaches. We conclude that (1) fire maps derived from coarse-resolution optical imagery can be applied relatively reliably to estimate the extent of savanna fires, generally with 70-80% confidence using the approach adopted here, over the major burning period in northern Australia and (2) substantial further field assessment and associated modeling of fuel accumulation, especially of coarse fuels, is required.

Evaluating rapid ground sampling and scaling estimated plant cover using UAV imagery up to Landsat for mapping arctic vegetation

NASA Astrophysics Data System (ADS)

Nelson, P.; Paradis, D. P.

2017-12-01

The small stature and spectral diversity of arctic plant taxa presents challenges in mapping arctic vegetation. Mapping vegetation at the appropriate scale is needed to visualize effects of disturbance, directional vegetation change or mapping of specific plant groups for other applications (eg. habitat mapping). Fine spatial grain of remotely sensed data (ca. 10 cm pixels) is often necessary to resolve patches of many arctic plant groups, such as bryophytes and lichens. These groups are also spectrally different from mineral, litter and vascular plants. We sought to explore method to generate high-resolution spatial and spectral data to explore better mapping methods for arctic vegetation. We sampled ground vegetation at seven sites north or west of tree-line in Alaska, four north of Fairbanks and three northwest of Bethel, respectively. At each site, we estimated cover of plant functional types in 1m2 quadrats spaced approximately every 10 m along a 100 m long transect. Each quadrat was also scanned using a field spectroradiometer (PSR+ Spectral Evolution, 400-2500 nm range) and photographed from multiple perspectives. We then flew our small UAV with a RGB camera over the transect and at least 50 m on either side collecting on imagery of the plot, which were used to generate a image mosaic and digital surface model of the plot. We compare plant functional group cover ocular estimated in situ to post-hoc estimation, either automated or using a human observer, using the quadrat photos. We also compare interpolated lichen cover from UAV scenes to estimated lichen cover using a statistical models using Landsat data, with focus on lichens. Light and yellow lichens are discernable in the UAV imagery but certain lichens, especially dark colored lichens or those with spectral signatures similar to graminoid litter, present challenges. Future efforts will focus on integrating UAV-upscaled ground cover estimates to hyperspectral sensors (eg. AVIRIS ng) for better combined spectral and spatial resolution.

Impact of extrinsic factors on fine motor performance of children attending day care.

PubMed

Corsi, Carolina; Santos, Mariana Martins Dos; Marques, Luísa de Andrade Perez; Rocha, Nelci Adriana Cicuto Ferreira

2016-12-01

To assess the impact of extrinsic factors on fine motor performance of children aged two years old. 73 children attending public and 21 private day care centers were assessed. Day care environment was evaluated using the Infant/Toddler Environment Rating Scale - Revised Edition (ITERS-R), fine motor performance was assessed through the Bayley Scales of Infant and Toddler Development - III (BSITD-III), socioeconomic data, maternal education and time of start at the day care were collected through interviews. Spearman's correlation coefficient was calculated to assess the association between the studied variables. The time at the day care was positively correlated with the children's performance in some fine motor tasks of the BSITD-III, showing that the activities developed in day care centers were important for the refinement of specific motor skills, while the overall fine motor performance by the scale was associated with maternal education and the ITERS-R scale sub-item "language and understanding". Extrinsic factors such as higher maternal education and quality of day care centers are associated with fine motor performance in children attending day care. Copyright © 2016 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

The utility of satellite observations for constraining fine-scale and transient methane sources

NASA Astrophysics Data System (ADS)

Turner, A. J.; Jacob, D.; Benmergui, J. S.; Brandman, J.; White, L.; Randles, C. A.

2017-12-01

Resolving differences between top-down and bottom-up emissions of methane from the oil and gas industry is difficult due, in part, to their fine-scale and often transient nature. There is considerable interest in using atmospheric observations to detect these sources. Satellite-based instruments are an attractive tool for this purpose and, more generally, for quantifying methane emissions on fine scales. A number of instruments are planned for launch in the coming years from both low earth and geostationary orbit, but the extent to which they can provide fine-scale information on sources has yet to be explored. Here we present an observation system simulation experiment (OSSE) exploring the tradeoffs between pixel resolution, measurement frequency, and instrument precision on the fine-scale information content of a space-borne instrument measuring methane. We use the WRF-STILT Lagrangian transport model to generate more than 200,000 column footprints at 1.3×1.3 km2 spatial resolution and hourly temporal resolution over the Barnett Shale in Texas. We sub-sample these footprints to match the observing characteristics of the planned TROPOMI and GeoCARB instruments as well as different hypothetical observing configurations. The information content of the various observing systems is evaluated using the Fisher information matrix and its singular values. We draw conclusions on the capabilities of the planned satellite instruments and how these capabilities could be improved for fine-scale source detection.

Coexistence between wildlife and humans at fine spatial scales.

PubMed

Carter, Neil H; Shrestha, Binoj K; Karki, Jhamak B; Pradhan, Narendra Man Babu; Liu, Jianguo

2012-09-18

Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal's Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger-human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge-meeting human needs while sustaining wildlife.

Multielement mapping of alpha-SiC by scanning Auger microscopy

NASA Technical Reports Server (NTRS)

Browning, Ray; Smialek, James L.; Jacobson, Nathan S.

1987-01-01

Fine second-phase particles, numerous in sintered alpha-SiC, were analyzed by scanning Auger microscopy and conventional techniques. The Auger analysis utilized computer-controlled data acquisition, multielement correlation diagrams, and a high spatial resolution of 100 nm. This procedure enabled construction of false color maps and the detection of fine compositional details within these particles. Carbon, silicon oxide, and boron-rich particles (qualitatively as BN or B4C) predominated. The BN particles, sometimes having a carbon core, are believed to result from reaction between B4C additives and nitrogen sintering atmospheres.

Beyond Solar-B: MTRAP, the Magnetic Transition Region Probe

NASA Technical Reports Server (NTRS)

Davis, John M.; Moore, Ronald L.; Hathaway, David H.

2003-01-01

The next generation of solar missions will reveal and measure fine-scale solar magnetic fields and their effects in the solar atmosphere at heights, small scales, sensitivities, and fields of view well beyond the reach of Solar-B. The necessity for, and potential of, such observations for understanding solar magnetic fields, their generation in and below the photosphere, and their control of the solar atmosphere and heliosphere, were the focus of a science definition workshop, 'High-Resolution Solar Magnetography from Space: Beyond Solar-B,' held in Huntsville Alabama in April 2001. Forty internationally prominent scientists active in solar research involving fine-scale solar magnetism participated in this Workshop and reached consensus that the key science objective to be pursued beyond Solar-B is a physical understanding of the fine-scale magnetic structure and activity in the magnetic transition region, defined as the region between the photosphere and corona where neither the plasma nor the magnetic field strongly dominates the other. The observational objective requires high cadence (less than 10s) vector magnetic field maps, and spatially resolved spectra from the IR, visible, vacuum UV, to the EUV at high resolution (less than 50km) over a large FOV (approximately 140,000 km). A polarimetric resolution of one part in ten thousand is required to measure transverse magnetic fields of less than 30G. The latest SEC Roadmap includes a mission identified as MTRAP to meet these requirements. Enabling technology development requirements include large, lightweight, reflecting optics, large format sensors (16K x 16K pixels) with high QE at 150 nm, and extendable spacecraft structures. The Science Organizing Committee of the Beyond Solar-B Workshop recommends that: (1) Science and Technology Definition Teams should be established in FY04 to finalize the science requirements and to define technology development efforts needed to ensure the practicality of MTRAP's observational goals; (2) The necessary technology development funding should be included in Code S budgets for FY06 and beyond to prepare MTRAP for a new start no later than the nominal end of the Solar-B mission, around 2010.

Beyond Solar-B: MTRAP, the Magnetic TRAnsition Region Probe

NASA Astrophysics Data System (ADS)

Davis, J. M.; Moore, R. L.; Hathaway, D. H.; Science Definition CommitteeHigh-Resolution Solar Magnetography Beyond Solar-B Team

2003-05-01

The next generation of solar missions will reveal and measure fine-scale solar magnetic fields and their effects in the solar atmosphere at heights, small scales, sensitivities, and fields of view well beyond the reach of Solar-B. The necessity for, and potential of, such observations for understanding solar magnetic fields, their generation in and below the photosphere, and their control of the solar atmosphere and heliosphere, were the focus of a science definition workshop, "High-Resolution Solar Magnetography from Space: Beyond Solar-B," held in Huntsville Alabama in April 2001. Forty internationally prominent scientists active in solar research involving fine-scale solar magnetism participated in this Workshop and reached consensus that the key science objective to be pursued beyond Solar-B is a physical understanding of the fine-scale magnetic structure and activity in the magnetic transition region, defined as the region between the photosphere and corona where neither the plasma nor the magnetic field strongly dominates the other. The observational objective requires high cadence (< 10s) vector magnetic field maps, and spatially resolved spectra from the IR, visible, vacuum UV, to the EUV at high resolution (< 50km) over a large FOV ( 140,000 km). A polarimetric resolution of one part in ten thousand is required to measure transverse magnetic fields of < 30G. The latest SEC Roadmap includes a mission identified as MTRAP to meet these requirements. Enabling technology development requirements include large, lightweight, reflecting optics, large format sensors (16K x 16K pixels) with high QE at 150 nm, and extendable spacecraft structures. The Science Organizing Committee of the Beyond Solar-B Workshop recommends that: 1. Science and Technology Definition Teams should be established in FY04 to finalize the science requirements and to define technology development efforts needed to ensure the practicality of MTRAP's observational goals. 2. The necessary technology development funding should be included in Code S budgets for FY06 and beyond to prepare MTRAP for a new start no later than the nominal end of the Solar-B mission, around 2010.

Spherical Harmonic Analyses of Intensity Mapping Power Spectra

NASA Astrophysics Data System (ADS)

Liu, Adrian; Zhang, Yunfan; Parsons, Aaron R.

2016-12-01

Intensity mapping is a promising technique for surveying the large-scale structure of our universe from z = 0 to z ˜ 150, using the brightness temperature field of spectral lines to directly observe previously unexplored portions of our cosmic timeline. Examples of targeted lines include the 21 cm hyperfine transition of neutral hydrogen, rotational lines of carbon monoxide, and fine-structure lines of singly ionized carbon. Recent efforts have focused on detections of the power spectrum of spatial fluctuations, but have been hindered by systematics such as foreground contamination. This has motivated the decomposition of data into Fourier modes perpendicular and parallel to the line of sight, which has been shown to be a particularly powerful way to diagnose systematics. However, such a method is well-defined only in the limit of a narrow-field, flat-sky approximation. This limits the sensitivity of intensity mapping experiments, as it means that wide surveys must be separately analyzed as a patchwork of smaller fields. In this paper, we develop a framework for analyzing intensity mapping data in a spherical Fourier-Bessel basis, which incorporates curved sky effects without difficulty. We use our framework to generalize a number of techniques in intensity mapping data analysis from the flat sky to the curved sky. These include visibility-based estimators for the power spectrum, treatments of interloper lines, and the “foreground wedge” signature of spectrally smooth foregrounds.

A FRAMEWORK FOR FINE-SCALE COMPUTATIONAL FLUID DYNAMICS AIR QUALITY MODELING AND ANALYSIS

EPA Science Inventory

This paper discusses a framework for fine-scale CFD modeling that may be developed to complement the present Community Multi-scale Air Quality (CMAQ) modeling system which itself is a computational fluid dynamics model. A goal of this presentation is to stimulate discussions on w...

Multi-scale graph-cut algorithm for efficient water-fat separation.

PubMed

Berglund, Johan; Skorpil, Mikael

2017-09-01

To improve the accuracy and robustness to noise in water-fat separation by unifying the multiscale and graph cut based approaches to B 0 -correction. A previously proposed water-fat separation algorithm that corrects for B 0 field inhomogeneity in 3D by a single quadratic pseudo-Boolean optimization (QPBO) graph cut was incorporated into a multi-scale framework, where field map solutions are propagated from coarse to fine scales for voxels that are not resolved by the graph cut. The accuracy of the single-scale and multi-scale QPBO algorithms was evaluated against benchmark reference datasets. The robustness to noise was evaluated by adding noise to the input data prior to water-fat separation. Both algorithms achieved the highest accuracy when compared with seven previously published methods, while computation times were acceptable for implementation in clinical routine. The multi-scale algorithm was more robust to noise than the single-scale algorithm, while causing only a small increase (+10%) of the reconstruction time. The proposed 3D multi-scale QPBO algorithm offers accurate water-fat separation, robustness to noise, and fast reconstruction. The software implementation is freely available to the research community. Magn Reson Med 78:941-949, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Prediction of near-surface soil moisture at large scale by digital terrain modeling and neural networks.

PubMed

Lavado Contador, J F; Maneta, M; Schnabel, S

2006-10-01

The capability of Artificial Neural Network models to forecast near-surface soil moisture at fine spatial scale resolution has been tested for a 99.5 ha watershed located in SW Spain using several easy to achieve digital models of topographic and land cover variables as inputs and a series of soil moisture measurements as training data set. The study methods were designed in order to determining the potentials of the neural network model as a tool to gain insight into soil moisture distribution factors and also in order to optimize the data sampling scheme finding the optimum size of the training data set. Results suggest the efficiency of the methods in forecasting soil moisture, as a tool to assess the optimum number of field samples, and the importance of the variables selected in explaining the final map obtained.

Logarithmic profile mapping multi-scale Retinex for restoration of low illumination images

NASA Astrophysics Data System (ADS)

Shi, Haiyan; Kwok, Ngaiming; Wu, Hongkun; Li, Ruowei; Liu, Shilong; Lin, Ching-Feng; Wong, Chin Yeow

2018-04-01

Images are valuable information sources for many scientific and engineering applications. However, images captured in poor illumination conditions would have a large portion of dark regions that could heavily degrade the image quality. In order to improve the quality of such images, a restoration algorithm is developed here that transforms the low input brightness to a higher value using a modified Multi-Scale Retinex approach. The algorithm is further improved by a entropy based weighting with the input and the processed results to refine the necessary amplification at regions of low brightness. Moreover, fine details in the image are preserved by applying the Retinex principles to extract and then re-insert object edges to obtain an enhanced image. Results from experiments using low and normal illumination images have shown satisfactory performances with regard to the improvement in information contents and the mitigation of viewing artifacts.

Need for improved methods to collect and present spatial epidemiologic data for vectorborne diseases.

PubMed

Eisen, Lars; Eisen, Rebecca J

2007-12-01

Improved methods for collection and presentation of spatial epidemiologic data are needed for vectorborne diseases in the United States. Lack of reliable data for probable pathogen exposure site has emerged as a major obstacle to the development of predictive spatial risk models. Although plague case investigations can serve as a model for how to ideally generate needed information, this comprehensive approach is cost-prohibitive for more common and less severe diseases. New methods are urgently needed to determine probable pathogen exposure sites that will yield reliable results while taking into account economic and time constraints of the public health system and attending physicians. Recent data demonstrate the need for a change from use of the county spatial unit for presentation of incidence of vectorborne diseases to more precise ZIP code or census tract scales. Such fine-scale spatial risk patterns can be communicated to the public and medical community through Web-mapping approaches.

Assumption-versus data-based approaches to summarizing species' ranges.

PubMed

Peterson, A Townsend; Navarro-Sigüenza, Adolfo G; Gordillo, Alejandro

2018-06-01

For conservation decision making, species' geographic distributions are mapped using various approaches. Some such efforts have downscaled versions of coarse-resolution extent-of-occurrence maps to fine resolutions for conservation planning. We examined the quality of the extent-of-occurrence maps as range summaries and the utility of refining those maps into fine-resolution distributional hypotheses. Extent-of-occurrence maps tend to be overly simple, omit many known and well-documented populations, and likely frequently include many areas not holding populations. Refinement steps involve typological assumptions about habitat preferences and elevational ranges of species, which can introduce substantial error in estimates of species' true areas of distribution. However, no model-evaluation steps are taken to assess the predictive ability of these models, so model inaccuracies are not noticed. Whereas range summaries derived by these methods may be useful in coarse-grained, global-extent studies, their continued use in on-the-ground conservation applications at fine spatial resolutions is not advisable in light of reliance on assumptions, lack of real spatial resolution, and lack of testing. In contrast, data-driven techniques that integrate primary data on biodiversity occurrence with remotely sensed data that summarize environmental dimensions (i.e., ecological niche modeling or species distribution modeling) offer data-driven solutions based on a minimum of assumptions that can be evaluated and validated quantitatively to offer a well-founded, widely accepted method for summarizing species' distributional patterns for conservation applications. © 2016 Society for Conservation Biology.

Fine mapping on chromosome 13q32-34 and brain expression analysis implicates MYO16 in schizophrenia.

PubMed

Rodriguez-Murillo, Laura; Xu, Bin; Roos, J Louw; Abecasis, Gonçalo R; Gogos, Joseph A; Karayiorgou, Maria

2014-03-01

We previously reported linkage of schizophrenia and schizoaffective disorder to 13q32-34 in the European descent Afrikaner population from South Africa. The nature of genetic variation underlying linkage peaks in psychiatric disorders remains largely unknown and both rare and common variants may be contributing. Here, we examine the contribution of common variants located under the 13q32-34 linkage region. We used densely spaced SNPs to fine map the linkage peak region using both a discovery sample of 415 families and a meta-analysis incorporating two additional replication family samples. In a second phase of the study, we use one family-based data set with 237 families and independent case-control data sets for fine mapping of the common variant association signal using HapMap SNPs. We report a significant association with a genetic variant (rs9583277) within the gene encoding for the myosin heavy-chain Myr 8 (MYO16), which has been implicated in neuronal phosphoinositide 3-kinase signaling. Follow-up analysis of HapMap variation within MYO16 in a second set of Afrikaner families and additional case-control data sets of European descent highlighted a region across introns 2-6 as the most likely region to harbor common MYO16 risk variants. Expression analysis revealed a significant increase in the level of MYO16 expression in the brains of schizophrenia patients. Our results suggest that common variation within MYO16 may contribute to the genetic liability to schizophrenia.

Use of single nucleotide polymorphisms (SNP) to fine-map quantitative trait loci (QTL) in swine

USDA-ARS?s Scientific Manuscript database

Mapping quantitative trait loci (QTL) in swine at the US Meat Animal Research Center has relied heavily on linkage mapping in either F2 or Backcross families. QTL identified in the initial scans typically have very broad confidence intervals and further refinement of the QTL’s position is needed bef...

Parcel-scale urban coastal flood mapping: Leveraging the multi-scale CoSMoS model for coastal flood forecasting

NASA Astrophysics Data System (ADS)

Gallien, T.; Barnard, P. L.; Sanders, B. F.

2011-12-01

California coastal sea levels are projected to rise 1-1.4 meters in the next century and evidence suggests mean tidal range, and consequently, mean high water (MHW) is increasing along portions of Southern California Bight. Furthermore, emerging research indicates wind stress patterns associated with the Pacific Decadal Oscillation (PDO) have suppressed sea level rise rates along the West Coast since 1980, and a reversal in this pattern would result in the resumption of regional sea level rise rates equivalent to or exceeding global mean sea level rise rates, thereby enhancing coastal flooding. Newport Beach is a highly developed, densely populated lowland along the Southern California coast currently subject to episodic flooding from coincident high tides and waves, and the frequency and intensity of flooding is expected to increase with projected future sea levels. Adaptation to elevated sea levels will require flood mapping and forecasting tools that are sensitive to the dominant factors affecting flooding including extreme high tides, waves and flood control infrastructure. Considerable effort has been focused on the development of nowcast and forecast systems including Scripps Institute of Oceanography's Coastal Data Information Program (CDIP) and the USGS Multi-hazard model, the Southern California Coastal Storm Modeling System (CoSMoS). However, fine scale local embayment dynamics and overtopping flows are needed to map unsteady flooding effects in coastal lowlands protected by dunes, levees and seawalls. Here, a recently developed two dimensional Godunov non-linear shallow water solver is coupled to water level and wave forecasts from the CoSMoS model to investigate the roles of tides, waves, sea level changes and flood control infrastructure in accurate flood mapping and forecasting. The results of this study highlight the important roles of topographic data, embayment hydrodynamics, water level uncertainties and critical flood processes required for meaningful prediction of sea level rise impacts and coastal flood forecasting.

Mapping of West Siberian taiga wetland complexes using Landsat imagery: implications for methane emissions

NASA Astrophysics Data System (ADS)

Evgenievna Terentieva, Irina; Vladimirovich Glagolev, Mikhail; Dmitrievna Lapshina, Elena; Faritovich Sabrekov, Alexandr; Maksyutov, Shamil

2016-08-01

High-latitude wetlands are important for understanding climate change risks because these environments sink carbon dioxide and emit methane. However, fine-scale heterogeneity of wetland landscapes poses a serious challenge when generating regional-scale estimates of greenhouse gas fluxes from point observations. In order to reduce uncertainties at the regional scale, we mapped wetlands and water bodies in the taiga zone of The West Siberia Lowland (WSL) on a scene-by-scene basis using a supervised classification of Landsat imagery. Training data consist of high-resolution images and extensive field data collected at 28 test areas. The classification scheme aims at supporting methane inventory applications and includes seven wetland ecosystem types comprising nine wetland complexes distinguishable at the Landsat resolution. To merge typologies, mean relative areas of wetland ecosystems within each wetland complex type were estimated using high-resolution images. Accuracy assessment based on 1082 validation polygons of 10 × 10 pixel size indicated an overall map accuracy of 79 %. The total area of the WSL wetlands and water bodies was estimated to be 52.4 Mha or 4-12 % of the global wetland area. Ridge-hollow complexes prevail in WSL's taiga zone accounting for 33 % of the total wetland area, followed by pine bogs or "ryams" (23 %), ridge-hollow-lake complexes (16 %), open fens (8 %), palsa complexes (7 %), open bogs (5 %), patterned fens (4 %), and swamps (4 %). Various oligotrophic environments are dominant among wetland ecosystems, while poor fens cover only 14 % of the area. Because of the significant change in the wetland ecosystem coverage in comparison to previous studies, a considerable reevaluation of the total CH4 emissions from the entire region is expected. A new Landsat-based map of WSL's taiga wetlands provides a benchmark for validation of coarse-resolution global land cover products and wetland data sets in high latitudes.

Genome structure and primitive sex chromosome revealed in Populus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tuskan, Gerald A; Yin, Tongming; Gunter, Lee E

We constructed a comprehensive genetic map for Populus and ordered 332 Mb of sequence scaffolds along the 19 haploid chromosomes in order to compare chromosomal regions among diverse members of the genus. These efforts lead us to conclude that chromosome XIX in Populus is evolving into a sex chromosome. Consistent segregation distortion in favor of the sub-genera Tacamahaca alleles provided evidence of divergent selection among species, particularly at the proximal end of chromosome XIX. A large microsatellite marker (SSR) cluster was detected in the distorted region even though the genome-wide distribute SSR sites was uniform across the physical map. Themore » differences between the genetic map and physical sequence data suggested recombination suppression was occurring in the distorted region. A gender-determination locus and an overabundance of NBS-LRR genes were also co-located to the distorted region and were put forth as the cause for divergent selection and recombination suppression. This hypothesis was verified by using fine-scale mapping of an integrated scaffold in the vicinity of the gender-determination locus. As such it appears that chromosome XIX in Populus is in the process of evolving from an autosome into a sex chromosome and that NBS-LRR genes may play important role in the chromosomal diversification process in Populus.« less

High resolution population distribution maps for Southeast Asia in 2010 and 2015.

PubMed

Gaughan, Andrea E; Stevens, Forrest R; Linard, Catherine; Jia, Peng; Tatem, Andrew J

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org.

High Resolution Population Distribution Maps for Southeast Asia in 2010 and 2015

PubMed Central

Gaughan, Andrea E.; Stevens, Forrest R.; Linard, Catherine; Jia, Peng; Tatem, Andrew J.

2013-01-01

Spatially accurate, contemporary data on human population distributions are vitally important to many applied and theoretical researchers. The Southeast Asia region has undergone rapid urbanization and population growth over the past decade, yet existing spatial population distribution datasets covering the region are based principally on population count data from censuses circa 2000, with often insufficient spatial resolution or input data to map settlements precisely. Here we outline approaches to construct a database of GIS-linked circa 2010 census data and methods used to construct fine-scale (∼100 meters spatial resolution) population distribution datasets for each country in the Southeast Asia region. Landsat-derived settlement maps and land cover information were combined with ancillary datasets on infrastructure to model population distributions for 2010 and 2015. These products were compared with those from two other methods used to construct commonly used global population datasets. Results indicate mapping accuracies are consistently higher when incorporating land cover and settlement information into the AsiaPop modelling process. Using existing data, it is possible to produce detailed, contemporary and easily updatable population distribution datasets for Southeast Asia. The 2010 and 2015 datasets produced are freely available as a product of the AsiaPop Project and can be downloaded from: www.asiapop.org. PMID:23418469

Experimental philosophy leading to a small scale digital data base of the conterminous United States for designing experiments with remotely sensed data

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Masuoka, E. J.; Broderick, P. W.; Garman, T. R.; Ludwig, R. W.; Beltran, G. N.; Heyman, P. J.; Hooker, L. K.

1983-01-01

Research using satellite remotely sensed data, even within any single scientific discipline, often lacked a unifying principle or strategy with which to plan or integrate studies conducted over an area so large that exhaustive examination is infeasible, e.g., the U.S.A. However, such a series of studies would seem to be at the heart of what makes satellite remote sensing unique, that is the ability to select for study from among remotely sensed data sets distributed widely over the U.S., over time, where the resources do not exist to examine all of them. Using this philosophical underpinning and the concept of a unifying principle, an operational procedure for developing a sampling strategy and formal testable hypotheses was constructed. The procedure is applicable across disciplines, when the investigator restates the research question in symbolic form, i.e., quantifies it. The procedure is set within the statistical framework of general linear models. The dependent variable is any arbitrary function of remotely sensed data and the independent variables are values or levels of factors which represent regional climatic conditions and/or properties of the Earth's surface. These factors are operationally defined as maps from the U.S. National Atlas (U.S.G.S., 1970). Eighty-five maps from the National Atlas, representing climatic and surface attributes, were automated by point counting at an effective resolution of one observation every 17.6 km (11 miles) yielding 22,505 observations per map. The maps were registered to one another in a two step procedure producing a coarse, then fine scale registration. After registration, the maps were iteratively checked for errors using manual and automated procedures. The error free maps were annotated with identification and legend information and then stored as card images, one map to a file. A sampling design will be accomplished through a regionalization analysis of the National Atlas data base (presently being conducted). From this analysis a map of homogeneous regions of the U.S.A. will be created and samples (LANDSAT scenes) assigned by region.

Self Consistent Bathymetric Mapping Using Sub-maps: Survey Results From the TAG Hydrothermal Structure

NASA Astrophysics Data System (ADS)

Roman, C. N.; Reves-Sohn, R.; Singh, H.; Humphris, S.

2005-12-01

The spatial resolution of microbathymetry maps created using robotic vehicles such as ROVs, AUVs and manned submersibles in the deep ocean is currently limited by the accuracy of the vehicle navigation data. Errors in the vehicle position estimate commonly exceed the ranging errors of the acoustic mapping sensor itself, which creates inconsistency in the map making process and produces artifacts that lower resolution and distort map integrity. We present a methodology for producing self-consistent maps and improving vehicle position estimation by exploiting accurate local navigation and utilizing terrain relative measurements. The complete map is broken down into individual "sub-maps'', which are generated using short term Doppler based navigation. The sub-maps are pairwise registered to constrain the vehicle position estimates by matching terrain that has been imaged multiple times. This procedure is implemented using a delayed state Kalman filter to incorporate the sub-map registrations as relative position measurements between previously visited vehicle locations. Archiving of previous positions in a filter state vector allows for continual adjustment of the sub-map locations. The terrain registration is accomplished using a two dimensional correlation and a six degree of freedom point cloud alignment method tailored to bathymetric data. This registration procedure is applicable to fully 3 dimensional complex underwater environments. The complete bathymetric map is then created from the union of all sub-maps that have been aligned in a consistent manner. The method is applied to an SM2000 multibeam survey of the TAG hydrothermal structure on the Mid-Atlantic Ridge at 26(°)N using the Jason II ROV. The survey included numerous crossing tracklines designed to test this algorithm, and the final gridded bathymetry data is sub-meter accurate. The high-resolution map has allowed for the identification of previously unrecognized fracture patterns associated with flow focusing at TAG, as well as imaging of fine-scale features such as individual sulfide talus blocks and ODP re-entry cones.

Breed locally, disperse globally: Fine-scale genetic structure despite landscape-scale panmixia in a fire-specialist

Treesearch

Jennifer C. Pierson; Fred W. Allendorf; Pierre Drapeau; Michael K. Schwartz

2013-01-01

An exciting advance in the understanding of metapopulation dynamics has been the investigation of how populations respond to ephemeral patches that go 'extinct' during the lifetime of an individual. Previous research has shown that this scenario leads to genetic homogenization across large spatial scales. However, little is known about fine-scale genetic...

Downscaling future climate scenarios to fine scales for hydrologic and ecological modeling and analysis

USGS Publications Warehouse

Flint, Lorraine E.; Flint, Alan L.

2012-01-01

The methodology, which includes a sequence of rigorous analyses and calculations, is intended to reduce the addition of uncertainty to the climate data as a result of the downscaling while providing the fine-scale climate information necessary for ecological analyses. It results in new but consistent data sets for the US at 4 km, the southwest US at 270 m, and California at 90 m and illustrates the utility of fine-scale downscaling to analyses of ecological processes influenced by topographic complexity.

A reduced-order modeling approach to represent subgrid-scale hydrological dynamics for land-surface simulations: application in a polygonal tundra landscape

DOE PAGES

Pau, G. S. H.; Bisht, G.; Riley, W. J.

2014-09-17

Existing land surface models (LSMs) describe physical and biological processes that occur over a wide range of spatial and temporal scales. For example, biogeochemical and hydrological processes responsible for carbon (CO 2, CH 4) exchanges with the atmosphere range from the molecular scale (pore-scale O 2 consumption) to tens of kilometers (vegetation distribution, river networks). Additionally, many processes within LSMs are nonlinearly coupled (e.g., methane production and soil moisture dynamics), and therefore simple linear upscaling techniques can result in large prediction error. In this paper we applied a reduced-order modeling (ROM) technique known as "proper orthogonal decomposition mapping method" thatmore » reconstructs temporally resolved fine-resolution solutions based on coarse-resolution solutions. We developed four different methods and applied them to four study sites in a polygonal tundra landscape near Barrow, Alaska. Coupled surface–subsurface isothermal simulations were performed for summer months (June–September) at fine (0.25 m) and coarse (8 m) horizontal resolutions. We used simulation results from three summer seasons (1998–2000) to build ROMs of the 4-D soil moisture field for the study sites individually (single-site) and aggregated (multi-site). The results indicate that the ROM produced a significant computational speedup (> 10 3) with very small relative approximation error (< 0.1%) for 2 validation years not used in training the ROM. We also demonstrate that our approach: (1) efficiently corrects for coarse-resolution model bias and (2) can be used for polygonal tundra sites not included in the training data set with relatively good accuracy (< 1.7% relative error), thereby allowing for the possibility of applying these ROMs across a much larger landscape. By coupling the ROMs constructed at different scales together hierarchically, this method has the potential to efficiently increase the resolution of land models for coupled climate simulations to spatial scales consistent with mechanistic physical process representation.« less

Verifying mapping, monitoring and modeling of fine sediment pollution sources in West Maui, Hawai'i, USA

NASA Astrophysics Data System (ADS)

Cerovski-Darriau, C.; Stock, J. D.

2017-12-01

Coral reef ecosystems, and the fishing and tourism industries they support, depend on clean waters. Fine sediment pollution from nearshore watersheds threatens these enterprises in West Maui, Hawai'i. To effectively mitigate sediment pollution, we first have to know where the sediment is coming from, and how fast it erodes. In West Maui, we know that nearshore sediment plumes originate from erosion of fine sand- to silt-sized air fall deposits where they are exposed by grazing, agriculture, or other disturbances. We identified and located these sediment sources by mapping watershed geomorphological processes using field traverses, historic air photos, and modern orthophotos. We estimated bank lowering rates using erosion pins, and other surface erosion rates were extrapolated from data collected elsewhere on the Hawaiian Islands. These measurements and mapping led to a reconnaissance sediment budget which showed that annual loads are dominated by bank erosion of legacy terraces. Field observations during small storms confirm that nearshore sediment plumes are sourced from bank erosion of in-stream, legacy agricultural deposits. To further verify this sediment budget, we used geochemical fingerprinting to uniquely identify each potential source (e.g. stream banks, agricultural fields, roads, other human modified soils, and hillslopes) from the Wahikuli watershed (10 km2) and analyzed the fine fraction using ICP-MS for elemental geochemistry. We propose to apply this the fingerprinting results to nearshore suspended sediment samples taken during storms to identify the proportion of sediment coming from each source. By combining traditional geomorphic mapping, monitoring and geochemistry, we hope to provide a powerful tool to verify the primary source of sediment reaching the nearshore.

Fine-Mapping of Common Genetic Variants Associated with Colorectal Tumor Risk Identified Potential Functional Variants

PubMed Central

Gala, Manish; Abecasis, Goncalo; Bezieau, Stephane; Brenner, Hermann; Butterbach, Katja; Caan, Bette J.; Carlson, Christopher S.; Casey, Graham; Chang-Claude, Jenny; Conti, David V.; Curtis, Keith R.; Duggan, David; Gallinger, Steven; Haile, Robert W.; Harrison, Tabitha A.; Hayes, Richard B.; Hoffmeister, Michael; Hopper, John L.; Hudson, Thomas J.; Jenkins, Mark A.; Küry, Sébastien; Le Marchand, Loic; Leal, Suzanne M.; Newcomb, Polly A.; Nickerson, Deborah A.; Potter, John D.; Schoen, Robert E.; Schumacher, Fredrick R.; Seminara, Daniela; Slattery, Martha L.; Hsu, Li; Chan, Andrew T.; White, Emily; Berndt, Sonja I.; Peters, Ulrike

2016-01-01

Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) associated with colorectal cancer risk. These SNPs may tag correlated variants with biological importance. Fine-mapping around GWAS loci can facilitate detection of functional candidates and additional independent risk variants. We analyzed 11,900 cases and 14,311 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. To fine-map genomic regions containing all known common risk variants, we imputed high-density genetic data from the 1000 Genomes Project. We tested single-variant associations with colorectal tumor risk for all variants spanning genomic regions 250-kb upstream or downstream of 31 GWAS-identified SNPs (index SNPs). We queried the University of California, Santa Cruz Genome Browser to examine evidence for biological function. Index SNPs did not show the strongest association signals with colorectal tumor risk in their respective genomic regions. Bioinformatics analysis of SNPs showing smaller P-values in each region revealed 21 functional candidates in 12 loci (5q31.1, 8q24, 11q13.4, 11q23, 12p13.32, 12q24.21, 14q22.2, 15q13, 18q21, 19q13.1, 20p12.3, and 20q13.33). We did not observe evidence of additional independent association signals in GWAS-identified regions. Our results support the utility of integrating data from comprehensive fine-mapping with expanding publicly available genomic databases to help clarify GWAS associations and identify functional candidates that warrant more onerous laboratory follow-up. Such efforts may aid the eventual discovery of disease-causing variant(s). PMID:27379672

HAPRAP: a haplotype-based iterative method for statistical fine mapping using GWAS summary statistics.

PubMed

Zheng, Jie; Rodriguez, Santiago; Laurin, Charles; Baird, Denis; Trela-Larsen, Lea; Erzurumluoglu, Mesut A; Zheng, Yi; White, Jon; Giambartolomei, Claudia; Zabaneh, Delilah; Morris, Richard; Kumari, Meena; Casas, Juan P; Hingorani, Aroon D; Evans, David M; Gaunt, Tom R; Day, Ian N M

2017-01-01

Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data require the pairwise correlation coefficients ([Formula: see text]) of the variants. However, haplotypes rather than pairwise [Formula: see text], are the true biological representation of linkage disequilibrium (LD) among multiple loci. In this article, we present an empirical iterative method, HAPlotype Regional Association analysis Program (HAPRAP), that enables fine mapping using summary statistics and haplotype information from an individual-level reference panel. Simulations with individual-level genotypes show that the results of HAPRAP and multiple regression are highly consistent. In simulation with summary-level data, we demonstrate that HAPRAP is less sensitive to poor LD estimates. In a parametric simulation using Genetic Investigation of ANthropometric Traits height data, HAPRAP performs well with a small training sample size (N < 2000) while other methods become suboptimal. Moreover, HAPRAP's performance is not affected substantially by single nucleotide polymorphisms (SNPs) with low minor allele frequencies. We applied the method to existing quantitative trait and binary outcome meta-analyses (human height, QTc interval and gallbladder disease); all previous reported association signals were replicated and two additional variants were independently associated with human height. Due to the growing availability of summary level data, the value of HAPRAP is likely to increase markedly for future analyses (e.g. functional prediction and identification of instruments for Mendelian randomization). The HAPRAP package and documentation are available at http://apps.biocompute.org.uk/haprap/ CONTACT: : jie.zheng@bristol.ac.uk or tom.gaunt@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Lack of sex-biased dispersal promotes fine-scale genetic structure in alpine ungulates

Treesearch

Gretchen H. Roffler; Sandra L. Talbot; Gordon Luikart; George K. Sage; Kristy L. Pilgrim; Layne G. Adams; Michael K. Schwartz

2014-01-01

Identifying patterns of fine-scale genetic structure in natural populations can advance understanding of critical ecological processes such as dispersal and gene flow across heterogeneous landscapes. Alpine ungulates generally exhibit high levels of genetic structure due to female philopatry and patchy configuration of mountain habitats. We assessed the spatial scale...

Fine-scale habitat characteristics related to occupancy of the Yosemite Toad, Anaxyrus canorus

Treesearch

Christina T. Liang; Robert L. Grasso; Julie J. Nelson-Paul; Kim E. Vincent; Amy J. Lind

2017-01-01

Fine-scale habitat information can provide insight into species occupancy and persistence that is not apparent at the landscape-scale. Such information is particularly important for rare species that are experiencing population declines, such as the threatened Yosemite Toad (Anaxyrus canorus). Our study examined differences in physical...

RESOLVING FINE SCALE IN AIR TOXICS MODELING AND THE IMPORTANCE OF ITS SUB-GRID VARIABILITY FOR EXPOSURE ESTIMATES

EPA Science Inventory

This presentation explains the importance of the fine-scale features for air toxics exposure modeling. The paper presents a new approach to combine local-scale and regional model results for the National Air Toxic Assessment. The technique has been evaluated with a chemical tra...

The managed clearing: An overlooked land-cover type in urbanizing regions?

PubMed Central

Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K.

2018-01-01

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type–semi-natural, vegetated land surfaces with varying degrees of management practices–for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area– 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems. PMID:29432442

The managed clearing: An overlooked land-cover type in urbanizing regions?

PubMed

Singh, Kunwar K; Madden, Marguerite; Gray, Josh; Meentemeyer, Ross K

2018-01-01

Urban ecosystem assessments increasingly rely on widely available map products, such as the U.S. Geological Service (USGS) National Land Cover Database (NLCD), and datasets that use generic classification schemes to detect and model large-scale impacts of land-cover change. However, utilizing existing map products or schemes without identifying relevant urban class types such as semi-natural, yet managed land areas that account for differences in ecological functions due to their pervious surfaces may severely constrain assessments. To address this gap, we introduce the managed clearings land-cover type-semi-natural, vegetated land surfaces with varying degrees of management practices-for urbanizing landscapes. We explore the extent to which managed clearings are common and spatially distributed in three rapidly urbanizing areas of the Charlanta megaregion, USA. We visually interpreted and mapped fine-scale land cover with special attention to managed clearings using 2012 U.S. Department of Agriculture (USDA) National Agriculture Imagery Program (NAIP) images within 150 randomly selected 1-km2 blocks in the cities of Atlanta, Charlotte, and Raleigh, and compared our maps with National Land Cover Database (NLCD) data. We estimated the abundance of managed clearings relative to other land use and land cover types, and the proportion of land-cover types in the NLCD that are similar to managed clearings. Our study reveals that managed clearings are the most common land cover type in these cities, covering 28% of the total sampled land area- 6.2% higher than the total area of impervious surfaces. Managed clearings, when combined with forest cover, constitutes 69% of pervious surfaces in the sampled region. We observed variability in area estimates of managed clearings between the NAIP-derived and NLCD data. This suggests using high-resolution remote sensing imagery (e.g., NAIP) instead of modifying NLCD data for improved representation of spatial heterogeneity and mapping of managed clearings in urbanizing landscapes. Our findings also demonstrate the need to more carefully consider managed clearings and their critical ecological functions in landscape- to regional-scale studies of urbanizing ecosystems.

Development of fine-resolution analyses and expanded large-scale forcing properties. Part I: Methodology and evaluation

DOE PAGES

Li, Zhijin; Vogelmann, Andrew M.; Feng, Sha; ...

2015-01-20

We produce fine-resolution, three-dimensional fields of meteorological and other variables for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS-DA) framework that is used within the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. The MS-DA algorithm uses existing reanalysis products and constrains fine-scale atmospheric properties by assimilating high-resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system.more » Evaluations also show that the large-scale forcing derived from the fine-resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine-resolution fields are used to characterize the contribution of subgrid variability to the large-scale forcing and to derive hydrometeor forcing, which are presented in companion papers.« less

Geologic map of the Mound Spring quadrangle, Nye and Clark Counties, Nevada, and Inyo County, California

USGS Publications Warehouse

Lundstrom, Scott C.; Mahan, Shannon; Blakely, Richard J.; Paces, James B.; Young, Owen D.; Workman, Jeremiah B.; Dixon, Gary L.

2003-01-01

The Mound Spring quadrangle, the southwestern-most 7.5' quadrangle of the area of the Las Vegas 1:100,000-scale quadrangle, is entirely within the Pahrump Valley, spanning the Nevada/California State line. New geologic mapping of the predominantly Quaternary materials is combined with new studies of gravity and geochronology in this quadrangle. Eleven predominantly fine-grained units are delineated, including playa sediment, dune sand, and deposits associated with several cycles of past groundwater discharge and distal fan sedimentation. These units are intercalated with 5 predominantly coarse-grained alluvial-fan and wash gravel units mainly derived from the Spring Mountains. The gravel units are distinguished on the basis of soil development and associated surficial characteristics. Thermoluminescence and U-series geochronology constrain most of the units to the Holocene and late and middle Pleistocene. Deposits of late Pleistocene groundwater discharge in the northeast part of the quadrangle are associated with a down-to-the-southwest fault zone that is expressed by surface fault scarps and a steep gravity gradient. The gravity field also defines a northwest-trending uplift along the State line, in which the oldest sediments are poorly exposed. About 2 km to the northeast a prominent southwest-facing erosional escarpment is formed by resistant beds in middle Pleistocene fine-grained sediments that dip northeast away from the uplift. These sediments include cycles of groundwater discharge that were probably caused by upwelling of southwesterly groundwater flow that encountered the horst.

Robust, Efficient Depth Reconstruction With Hierarchical Confidence-Based Matching.

PubMed

Sun, Li; Chen, Ke; Song, Mingli; Tao, Dacheng; Chen, Gang; Chen, Chun

2017-07-01

In recent years, taking photos and capturing videos with mobile devices have become increasingly popular. Emerging applications based on the depth reconstruction technique have been developed, such as Google lens blur. However, depth reconstruction is difficult due to occlusions, non-diffuse surfaces, repetitive patterns, and textureless surfaces, and it has become more difficult due to the unstable image quality and uncontrolled scene condition in the mobile setting. In this paper, we present a novel hierarchical framework with multi-view confidence-based matching for robust, efficient depth reconstruction in uncontrolled scenes. Particularly, the proposed framework combines local cost aggregation with global cost optimization in a complementary manner that increases efficiency and accuracy. A depth map is efficiently obtained in a coarse-to-fine manner by using an image pyramid. Moreover, confidence maps are computed to robustly fuse multi-view matching cues, and to constrain the stereo matching on a finer scale. The proposed framework has been evaluated with challenging indoor and outdoor scenes, and has achieved robust and efficient depth reconstruction.

The environment of south-central Tunisia as observed on Landsat scene 206/036

USGS Publications Warehouse

Grolier, M.J.; Schultejann, P.A.

1982-01-01

One Landsat image in south-central Tunisia was analyzed to demonstrate the application of remote-sensing technology to regional development. A preliminary analysis included I) major landscape features; 2) gypsum-encrusted soils; and 3) phosphate-bearing beds exposed in the Gafsa mining district. The products specifically used for this report include: 1) A false-color composite (FCC), which had been linearly stretched to enhance contrast, and to which a modulation transfer function correction (a high-pass filter 3 pixels by 3 pixels wide) had been applied to enhance fine topographic relief. 2) A sinusoidally stretched false-color composite, on which mappable gypsum-encrusted soils and saline soils are detectable in greater detail than on the existing soil map of Tunisia at 1:500,000 scale. 3) A sinusoidally stretched band-ratio false-color composite, from which a thematic map of most phosphate-bearing beds in the Gafsa mining district was prepared. Recommendations for future Landsat image interpretation in Tunisia are offered.

An ultra-high density linkage map and QTL mapping for sex and growth-related traits of common carp (Cyprinus carpio)

PubMed Central

Peng, Wenzhu; Xu, Jian; Zhang, Yan; Feng, Jianxin; Dong, Chuanju; Jiang, Likun; Feng, Jingyan; Chen, Baohua; Gong, Yiwen; Chen, Lin; Xu, Peng

2016-01-01

High density genetic linkage maps are essential for QTL fine mapping, comparative genomics and high quality genome sequence assembly. In this study, we constructed a high-density and high-resolution genetic linkage map with 28,194 SNP markers on 14,146 distinct loci for common carp based on high-throughput genotyping with the carp 250 K single nucleotide polymorphism (SNP) array in a mapping family. The genetic length of the consensus map was 10,595.94 cM with an average locus interval of 0.75 cM and an average marker interval of 0.38 cM. Comparative genomic analysis revealed high level of conserved syntenies between common carp and the closely related model species zebrafish and medaka. The genome scaffolds were anchored to the high-density linkage map, spanning 1,357 Mb of common carp reference genome. QTL mapping and association analysis identified 22 QTLs for growth-related traits and 7 QTLs for sex dimorphism. Candidate genes underlying growth-related traits were identified, including important regulators such as KISS2, IGF1, SMTLB, NPFFR1 and CPE. Candidate genes associated with sex dimorphism were also identified including 3KSR and DMRT2b. The high-density and high-resolution genetic linkage map provides an important tool for QTL fine mapping and positional cloning of economically important traits, and improving common carp genome assembly. PMID:27225429

Mapping Migratory Bird Prevalence Using Remote Sensing Data Fusion

PubMed Central

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G.; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Background Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. Methodology and Principal Findings A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy (“fusion”) models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Conclusion and Significance Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level. PMID:22235254

Mapping migratory bird prevalence using remote sensing data fusion.

PubMed

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.

Autosomal dominant hereditary spastic paraplegia with axonal sensory motor polyneuropathy maps to chromosome 21q 22.3.

PubMed

Peddareddygari, Leema Reddy; Hanna, Philip A; Igo, Robert P; Luo, Yuqun A; Won, Sungho; Hirano, Michio; Grewal, Raji P

2016-01-01

Hereditary spastic paraplegia (HSP) are a genetically and clinically heterogeneous group of disorders. At present, 19 autosomal dominant loci for HSP have been mapped. We ascertained an American family of European descent segregating an autosomal dominant HSP associated with peripheral neuropathy. A genome wide scan was performed with 410 microsatellite repeat marker (Weber lab screening set 16) and following linkage and haplotype analysis, fine mapping was performed. Established genes or loci for HSP were excluded by direct sequencing or haplotype analysis. All established loci for HSP were excluded. Fine mapping suggested a locus on chromosome 21q22.3 flanked by markers D21S1411 and D21S1446 with a maximum logarithm of odds score of 2.05 and was supported by haplotype analysis. A number of candidate genes in this region were analyzed and no disease-producing mutations were detected. We present the clinical and genetic analysis of an American family with autosomal dominant HSP with axonal sensory motor polyneuropathy mapping to a novel locus on chromosome 21q22.3 designated SPG56.

A map of human impacts to a ``pristine'' coral reef ecosystem, the Papahānaumokuākea Marine National Monument

NASA Astrophysics Data System (ADS)

Selkoe, K. A.; Halpern, B. S.; Ebert, C. M.; Franklin, E. C.; Selig, E. R.; Casey, K. S.; Bruno, J.; Toonen, R. J.

2009-09-01

Effective and comprehensive regional-scale marine conservation requires fine-grained data on the spatial patterns of threats and their overlap. To address this need for the Papahānaumokuākea Marine National Monument (Monument) in Hawaii, USA, spatial data on 14 recent anthropogenic threats specific to this region were gathered or created, including alien species, bottom fishing, lobster trap fishing, ship-based pollution, ship strike risks, marine debris, research diving, research equipment installation, research wildlife sacrifice, and several anthropogenic climate change threats i.e., increase in ultraviolet (UV) radiation, seawater acidification, the number of warm ocean temperature anomalies relevant to disease outbreaks and coral bleaching, and sea level rise. These data were combined with habitat maps and expert judgment on the vulnerability of different habitat types in the Monument to estimate spatial patterns of current cumulative impact at 1 ha (0.01 km2) resolution. Cumulative impact was greatest for shallow reef areas and peaked at Maro Reef, where 13 of the 14 threats overlapped in places. Ocean temperature variation associated with disease outbreaks was found to have the highest predicted impact overall, followed closely by other climate-related threats, none of which have easily tractable management solutions at the regional scale. High impact threats most tractable to regional management relate to ship traffic. Sensitivity analyses show that the results are robust to both data availability and quality. Managers can use these maps to (1) inform management and surveillance priorities based on the ranking of threats and their distributions, (2) guide permitting decisions based on cumulative impacts, and (3) choose areas to monitor for climate change effects. Furthermore, this regional analysis can serve as a case study for managers elsewhere interested in assessing and mapping region-specific cumulative human impacts.

Mapping the patent landscape of synthetic biology for fine chemical production pathways.

PubMed

Carbonell, Pablo; Gök, Abdullah; Shapira, Philip; Faulon, Jean-Loup

2016-09-01

A goal of synthetic biology bio-foundries is to innovate through an iterative design/build/test/learn pipeline. In assessing the value of new chemical production routes, the intellectual property (IP) novelty of the pathway is important. Exploratory studies can be carried using knowledge of the patent/IP landscape for synthetic biology and metabolic engineering. In this paper, we perform an assessment of pathways as potential targets for chemical production across the full catalogue of reachable chemicals in the extended metabolic space of chassis organisms, as computed by the retrosynthesis-based algorithm RetroPath. Our database for reactions processed by sequences in heterologous pathways was screened against the PatSeq database, a comprehensive collection of more than 150M sequences present in patent grants and applications. We also examine related patent families using Derwent Innovations. This large-scale computational study provides useful insights into the IP landscape of synthetic biology for fine and specialty chemicals production. © 2016 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Genetic analysis and fine mapping of a rice brown planthopper (Nilaparvata lugens Stål) resistance gene bph19(t).

PubMed

Chen, J W; Wang, L; Pang, X F; Pan, Q H

2006-04-01

Genetic analysis and fine mapping of a resistance gene against brown planthopper (BPH) biotype 2 in rice was performed using two F(2) populations derived from two crosses between a resistant indica cultivar (cv.), AS20-1, and two susceptible japonica cvs., Aichi Asahi and Lijiangxintuanheigu. Insect resistance was evaluated using F(1) plants and the two F(2) populations. The results showed that a single recessive gene, tentatively designated as bph19(t), conditioned the resistance in AS20-1. A linkage analysis, mainly employing microsatellite markers, was carried out in the two F(2) populations through bulked segregant analysis and recessive class analysis (RCA), in combination with bioinformatics analysis (BIA). The resistance gene locus bph19(t) was finely mapped to a region of about 1.0 cM on the short arm of chromosome 3, flanked by markers RM6308 and RM3134, where one known marker RM1022, and four new markers, b1, b2, b3 and b4, developed in the present study were co-segregating with the locus. To physically map this locus, the bph19(t)-linked markers were landed on bacterial artificial chromosome or P1 artificial chromosome clones of the reference cv., Nipponbare, released by the International Rice Genome Sequencing Project. Sequence information of these clones was used to construct a physical map of the bph19(t) locus, in silico, by BIA. The bph19(t) locus was physically defined to an interval of about 60 kb. The detailed genetic and physical maps of the bph19(t) locus will facilitate marker-assisted gene pyramiding and cloning.

Estimating daily surface NO2 concentrations from satellite data - a case study over Hong Kong using land use regression models

NASA Astrophysics Data System (ADS)

Anand, Jasdeep S.; Monks, Paul S.

2017-07-01

Land use regression (LUR) models have been used in epidemiology to determine the fine-scale spatial variation in air pollutants such as nitrogen dioxide (NO2) in cities and larger regions. However, they are often limited in their temporal resolution, which may potentially be rectified by employing the synoptic coverage provided by satellite measurements. In this work a mixed-effects LUR model is developed to model daily surface NO2 concentrations over the Hong Kong SAR during the period 2005-2015. In situ measurements from the Hong Kong Air Quality Monitoring Network, along with tropospheric vertical column density (VCD) data from the OMI, GOME-2A, and SCIAMACHY satellite instruments were combined with fine-scale land use parameters to provide the spatiotemporal information necessary to predict daily surface concentrations. Cross-validation with the in situ data shows that the mixed-effects LUR model using OMI data has a high predictive power (adj. R2 = 0. 84), especially when compared with surface concentrations derived using the MACC-II reanalysis model dataset (adj. R2 = 0. 11). Time series analysis shows no statistically significant trend in NO2 concentrations during 2005-2015, despite a reported decline in NOx emissions. This study demonstrates the utility in combining satellite data with LUR models to derive daily maps of ambient surface NO2 for use in exposure studies.

Coexistence between wildlife and humans at fine spatial scales

PubMed Central

Carter, Neil H.; Shrestha, Binoj K.; Karki, Jhamak B.; Pradhan, Narendra Man Babu; Liu, Jianguo

2012-01-01

Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal’s Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger–human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge—meeting human needs while sustaining wildlife. PMID:22949642

Multi-scale monitoring of landscape change after the 2011 tsunami

NASA Astrophysics Data System (ADS)

Hara, K.; Zhao, Y.; Harada, I.; Tomita, M.; Park, J.; Jung, E.; Kamagata, N.; Hirabuki, Y.

2015-04-01

The Great East Japan Earthquake (magnitude 9.0; occurred on 11th March 2011) and subsequent huge tsunami caused widespread damage along the Pacific Ocean coast of eastern Honshu, Japan. This research utilizes multi-resolution remote sensing images to clarify the impact on landscapes caused by this disaster, and also to monitor the subsequent survival and recovery process in the Sendai Bay region. The coastal landscape in the target area features a narrow strip of coastal sand barrier, historically stabilized by planted pine groves; backed by a low-lying plain that has traditionally been diked and converted to irrigated rice paddies. Farmsteads on the flat alluvial plain are surrounded by groves called "Igune", consisting primarily of conifers. MODIS data (250 m resolution) were employed to map the overall extent of inundation and damage on the regional landscape scale. The major damage caused by the tsunami, destruction of coastal pine forests and inundation or rice paddies on the plain, was identified at this level. Progressively finer scale analysis were then implemented using SPOT/HRG-2 (10 m resolution) data; GeoEye-1 fine resolution data (0.5 m) and very fine resolution aerial photographs (10 cm) and LiDAR. These results demonstrated the minute details of the damage and recovery process. Some patches of pine forest, for example, were seen to have survived, and some coastal plant communities were already recovering only a year after the disaster. Continuous monitoring using field work and remote sensing is required for balanced regional strategies that provide for economic and social recovery and as well as restoration of vegetation, biodiversity and vital ecosystem services.

Spatial and Temporal Characteristics of Insulator Contaminations Revealed by Daily Observations of Equivalent Salt Deposit Density

PubMed Central

Ruan, Ling; Han, Ge; Zhu, Zhongmin; Zhang, Miao; Gong, Wei

2015-01-01

The accurate estimation of deposits adhering on insulators is of great significance to prevent pollution flashovers which cause huge costs worldwide. Researchers have developed sensors using different technologies to monitor insulator contamination on a fine time scale. However, there is lack of analysis of these data to reveal spatial and temporal characteristics of insulator contamination, and as a result the scheduling of periodical maintenance of power facilities is highly dependent on personal experience. Owing to the deployment of novel sensors, daily Equivalent Salt Deposit Density (ESDD) observations of over two years were collected and analyzed for the first time. Results from 16 sites distributed in four regions of Hubei demonstrated that spatial heterogeneity can be seen at both the fine and coarse geographical scales, suggesting that current polluted area maps are necessary but are not sufficient conditions to guide the maintenance of power facilities. Both the local emission and the regional air pollution condition exert evident influences on deposit accumulation. A relationship between ESDD and PM10 was revealed by using regression analysis, proving that air pollution exerts influence on pollution accumulations on insulators. Moreover, the seasonality of ESDD was discovered for the first time by means of time series analysis, which could help engineers select appropriate times to clean the contamination. Besides, the trend component shows that the ESDD increases in a negative exponential fashion with the accumulation date (ESDD = a − b × exp(−time)) at a long time scale in real environments. PMID:25643058

Understanding the climate-included variations in the seasonal water demands of irrigated crops in Northern India

NASA Astrophysics Data System (ADS)

Bhattarai, N.; Jain, M.

2016-12-01

Expected changes in temperature and precipitation patterns in the rice-wheat belt of Northern India have implications for balancing crop water demand and available water resources. Because the impacts of water scarcity and reduced crop production are realized at a local scale, water-saving interventions are most effective when implemented locally. However, a paucity of fine-scale studies on the relationship between variations in climate and crop water demand has limited our ability to effectively implement such interventions. In an effort to better understand the responses of irrigated crops to changing climate in Northern India at finer-scales, we propose a remote sensing based semi-empirical approach. First, we employ a multi-model surface energy balance (SEB) approach to map seasonal evapotranspiration (ET)/water use (1995-2015) at 30 to 100 m resolution from space and investigate how seasonal and inter-annual variations in temperature and precipitation are associated with regional surface-energy budgets. Second, using remote estimates of ET and other biophysical variables, such as vegetation indices, land surface temperature, and albedo, we will explain the possible relationships between climate change and seasonal water demands of crops. Our estimates of high/moderate resolution (30 to 100 m) seasonal ET maps can make clear distinctions between impacts of climate variations on crop water demand at field, plot, and regional scales in Northern India. Finally, by improving our ability to identify targeted area for water-saving interventions, this study supports agricultural resiliency of Northern India in the face of climate change.

Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium

PubMed Central

Lu, Yingchang; Justice, Anne E.; Mudgal, Poorva; Liu, Ching-Ti; Young, Kristin; Feitosa, Mary F.; Rand, Kristin; Dimitrov, Latchezar; Duan, Qing; Guo, Xiuqing; Lange, Leslie A.; Nalls, Michael A.; Okut, Hayrettin; Tayo, Bamidele O.; Vedantam, Sailaja; Bradfield, Jonathan P.; Chen, Guanjie; Chesi, Alessandra; Irvin, Marguerite R.; Padhukasahasram, Badri; Zheng, Wei; Allison, Matthew A.; Ambrosone, Christine B.; Bandera, Elisa V.; Berndt, Sonja I.; Blot, William J.; Bottinger, Erwin P.; Carpten, John; Chanock, Stephen J.; Chen, Yii-Der Ida; Conti, David V.; Cooper, Richard S.; Fornage, Myriam; Freedman, Barry I.; Garcia, Melissa; Goodman, Phyllis J.; Hsu, Yu-Han H.; Hu, Jennifer; Huff, Chad D.; Ingles, Sue A.; John, Esther M.; Kittles, Rick; Klein, Eric; Li, Jin; McKnight, Barbara; Nayak, Uma; Nemesure, Barbara; Olshan, Andrew; Salako, Babatunde; Sanderson, Maureen; Shao, Yaming; Siscovick, David S.; Stanford, Janet L.; Strom, Sara S.; Witte, John S.; Yao, Jie; Zhu, Xiaofeng; Ziegler, Regina G.; Zonderman, Alan B.; Ambs, Stefan; Cushman, Mary; Faul, Jessica D.; Hakonarson, Hakon; Levin, Albert M.; Nathanson, Katherine L.; Weir, David R.; Zhi, Degui; Arnett, Donna K.; Kardia, Sharon L. R.; Oloapde, Olufunmilayo I.; Rao, D. C.; Williams, L. Keoki; Becker, Diane M.; Borecki, Ingrid B.; Evans, Michele K.; Harris, Tamara B.; Hirschhorn, Joel N.; Psaty, Bruce M.; Wilson, James G.; Bowden, Donald W.; Cupples, L. Adrienne; Haiman, Christopher A.; Loos, Ruth J. F.; North, Kari E.

2017-01-01

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10−8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (<5%). In the trans-ethnic fine mapping of 47 BMI loci and 27 WHRadjBMI loci that were locus-wide significant (P < 0.05 adjusted for effective number of variants per locus) from the African ancestry sex-combined and sex-stratified analyses, 26 BMI loci and 17 WHRadjBMI loci contained ≤ 20 variants in the credible sets that jointly account for 99% posterior probability of driving the associations. The lead variants in 13 of these loci had a high probability of being causal. As compared to our previous HapMap imputed GWAS for BMI and WHRadjBMI including up to 71,412 and 27,350 African ancestry individuals, respectively, our results suggest that 1000 Genomes imputation showed modest improvement in identifying GWAS loci including low frequency variants. Trans-ethnic meta-analyses further improved fine mapping of putative causal variants in loci shared between the African and European ancestry populations. PMID:28430825

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

NASA Astrophysics Data System (ADS)

Altaf, Muhammad U.; Jana, Raghavendra B.; Hoteit, Ibrahim; McCabe, Matthew F.

2016-10-01

Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model's large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.

2003-12-01

The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.

Review of 3d GIS Data Fusion Methods and Progress

NASA Astrophysics Data System (ADS)

Hua, Wei; Hou, Miaole; Hu, Yungang

2018-04-01

3D data fusion is a research hotspot in the field of computer vision and fine mapping, and plays an important role in fine measurement, risk monitoring, data display and other processes. At present, the research of 3D data fusion in the field of Surveying and mapping focuses on the 3D model fusion of terrain and ground objects. This paper summarizes the basic methods of 3D data fusion of terrain and ground objects in recent years, and classified the data structure and the establishment method of 3D model, and some of the most widely used fusion methods are analysed and commented.

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

PubMed

Horikoshi, Momoko; Pasquali, Lorenzo; Wiltshire, Steven; Huyghe, Jeroen R; Mahajan, Anubha; Asimit, Jennifer L; Ferreira, Teresa; Locke, Adam E; Robertson, Neil R; Wang, Xu; Sim, Xueling; Fujita, Hayato; Hara, Kazuo; Young, Robin; Zhang, Weihua; Choi, Sungkyoung; Chen, Han; Kaur, Ismeet; Takeuchi, Fumihiko; Fontanillas, Pierre; Thuillier, Dorothée; Yengo, Loic; Below, Jennifer E; Tam, Claudia H T; Wu, Ying; Abecasis, Gonçalo; Altshuler, David; Bell, Graeme I; Blangero, John; Burtt, Noél P; Duggirala, Ravindranath; Florez, Jose C; Hanis, Craig L; Seielstad, Mark; Atzmon, Gil; Chan, Juliana C N; Ma, Ronald C W; Froguel, Philippe; Wilson, James G; Bharadwaj, Dwaipayan; Dupuis, Josee; Meigs, James B; Cho, Yoon Shin; Park, Taesung; Kooner, Jaspal S; Chambers, John C; Saleheen, Danish; Kadowaki, Takashi; Tai, E Shyong; Mohlke, Karen L; Cox, Nancy J; Ferrer, Jorge; Zeggini, Eleftheria; Kato, Norihiro; Teo, Yik Ying; Boehnke, Michael; McCarthy, Mark I; Morris, Andrew P

2016-05-15

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci. © The Author 2016. Published by Oxford University Press.

Hot deformation behavior of uniform fine-grained GH4720Li alloy based on its processing map

NASA Astrophysics Data System (ADS)

Yu, Qiu-ying; Yao, Zhi-hao; Dong, Jian-xin

2016-01-01

The hot deformation behavior of uniform fine-grained GH4720Li alloy was studied in the temperature range from 1040 to 1130°C and the strain-rate range from 0.005 to 0.5 s-1 using hot compression testing. Processing maps were constructed on the basis of compression data and a dynamic materials model. Considerable flow softening associated with superplasticity was observed at strain rates of 0.01 s-1 or lower. According to the processing map and observations of the microstructure, the uniform fine-grained microstructure remains intact at 1100°C or lower because of easily activated dynamic recrystallization (DRX), whereas obvious grain growth is observed at 1130°C. Metallurgical instabilities in the form of non-uniform microstructures under higher and lower Zener-Hollomon parameters are induced by local plastic flow and primary γ' local faster dissolution, respectively. The optimum processing conditions at all of the investigated strains are proposed as 1090-1130°C with 0.08-0.5 s-1 and 0.005-0.008 s-1 and 1040-1085°C with 0.005-0.06 s-1.

Restricted cross-scale habitat selection by American beavers.

PubMed

Francis, Robert A; Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-12-01

Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection.

Restricted cross-scale habitat selection by American beavers

PubMed Central

Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-01-01

Abstract Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection. PMID:29492032

Mapping and predictive variations of soil bacterial richness across France

PubMed Central

Dequietd, Samuel; Saby, Nicolas P. A.; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition. PMID:29059218

Mapping and predictive variations of soil bacterial richness across France.

PubMed

Terrat, Sébastien; Horrigue, Walid; Dequiedt, Samuel; Saby, Nicolas P A; Lelièvre, Mélanie; Nowak, Virginie; Tripied, Julie; Régnier, Tiffanie; Jolivet, Claudy; Arrouays, Dominique; Wincker, Patrick; Cruaud, Corinne; Karimi, Battle; Bispo, Antonio; Maron, Pierre Alain; Chemidlin Prévost-Bouré, Nicolas; Ranjard, Lionel

2017-01-01

Although numerous studies have demonstrated the key role of bacterial diversity in soil functions and ecosystem services, little is known about the variations and determinants of such diversity on a nationwide scale. The overall objectives of this study were i) to describe the bacterial taxonomic richness variations across France, ii) to identify the ecological processes (i.e. selection by the environment and dispersal limitation) influencing this distribution, and iii) to develop a statistical predictive model of soil bacterial richness. We used the French Soil Quality Monitoring Network (RMQS), which covers all of France with 2,173 sites. The soil bacterial richness (i.e. OTU number) was determined by pyrosequencing 16S rRNA genes and related to the soil characteristics, climatic conditions, geomorphology, land use and space. Mapping of bacterial richness revealed a heterogeneous spatial distribution, structured into patches of about 111km, where the main drivers were the soil physico-chemical properties (18% of explained variance), the spatial descriptors (5.25%, 1.89% and 1.02% for the fine, medium and coarse scales, respectively), and the land use (1.4%). Based on these drivers, a predictive model was developed, which allows a good prediction of the bacterial richness (R2adj of 0.56) and provides a reference value for a given pedoclimatic condition.

Fine-Scale Mapping at 9p22.2 Identifies Candidate Causal Variants That Modify Ovarian Cancer Risk in BRCA1 and BRCA2 Mutation Carriers

PubMed Central

Vigorito, Elena; Kuchenbaecker, Karoline B.; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A.; Andrulis, Irene L.; Arun, Banu K.; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A.; Campbell, Ian; Chan, Salina B.; Claes, Kathleen B. M.; Cohn, David E.; Cook, Jackie; Daly, Mary B.; Damiola, Francesca; Davidson, Rosemarie; de Pauw, Antoine; Delnatte, Capucine; Diez, Orland; Domchek, Susan M.; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F.; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D. Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D.; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A.; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K.; Goldgar, David E.; Hake, Christopher R.; Hansen, Thomas V. O.; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B. L.; Houdayer, Claude; Hulick, Peter J.; Imyanitov, Evgeny N.; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M.; Vijai, Joseph; Karlan, Beth Y.; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L.; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R.; Montagna, Marco; Nathanson, Katherine L.; Neuhausen, Susan L.; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I.; Ong, Kai-ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M.; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C.; Rookus, Matti A.; Ross, Eric A.; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F.; Slavin, Thomas P.; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I.; Tea, Muy-Kheng; Teixeira, Manuel R.; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J.; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N.; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J.; Greene, Mark H.; Couch, Fergus J.; Offit, Kenneth; Pharoah, Paul D. P.; Chenevix-Trench, Georgia; Antoniou, Antonis C.

2016-01-01

Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10−16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10−6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population. PMID:27463617

Fine-Scale Mapping at 9p22.2 Identifies Candidate Causal Variants That Modify Ovarian Cancer Risk in BRCA1 and BRCA2 Mutation Carriers.

PubMed

Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A; Andrulis, Irene L; Arun, Banu K; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A; Campbell, Ian; Chan, Salina B; Claes, Kathleen B M; Cohn, David E; Cook, Jackie; Daly, Mary B; Damiola, Francesca; Davidson, Rosemarie; Pauw, Antoine de; Delnatte, Capucine; Diez, Orland; Domchek, Susan M; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K; Goldgar, David E; Hake, Christopher R; Hansen, Thomas V O; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B L; Houdayer, Claude; Hulick, Peter J; Imyanitov, Evgeny N; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M; Vijai, Joseph; Karlan, Beth Y; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R; Montagna, Marco; Nathanson, Katherine L; Neuhausen, Susan L; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I; Ong, Kai-Ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C; Rookus, Matti A; Ross, Eric A; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F; Slavin, Thomas P; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I; Tea, Muy-Kheng; Teixeira, Manuel R; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J; Greene, Mark H; Couch, Fergus J; Offit, Kenneth; Pharoah, Paul D P; Chenevix-Trench, Georgia; Antoniou, Antonis C

2016-01-01

Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10-16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10-6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population.

Assessment of Acacia Koa Forest Health across Environmental Gradients in Hawai‘i Using Fine Resolution Remote Sensing and GIS

PubMed Central

Morales, Rodolfo Martinez; Idol, Travis; Friday, James B.

2011-01-01

Koa (Acacia koa) forests are found across broad environmental gradients in the Hawai‘ian Islands. Previous studies have identified koa forest health problems and dieback at the plot level, but landscape level patterns remain unstudied. The availability of high-resolution satellite images from the new GeoEye1 satellite offers the opportunity to conduct landscape-level assessments of forest health. The goal of this study was to develop integrated remote sensing and geographic information systems (GIS) methodologies to characterize the health of koa forests and model the spatial distribution and variability of koa forest dieback patterns across an elevation range of 600–1,000 m asl in the island of Kaua‘i, which correspond to gradients of temperature and rainfall ranging from 17–20 °C mean annual temperature and 750–1,500 mm mean annual precipitation. GeoEye1 satellite imagery of koa stands was analyzed using supervised classification techniques based on the analysis of 0.5-m pixel multispectral bands. There was clear differentiation of native koa forest from areas dominated by introduced tree species and differentiation of healthy koa stands from those exhibiting dieback symptoms. The area ratio of healthy koa to koa dieback corresponded linearly to changes in temperature across the environmental gradient, with koa dieback at higher relative abundance in warmer areas. A landscape-scale map of healthy koa forest and dieback distribution demonstrated both the general trend with elevation and the small-scale heterogeneity that exists within particular elevations. The application of these classification techniques with fine spatial resolution imagery can improve the accuracy of koa forest inventory and mapping across the islands of Hawai‘i. Such findings should also improve ecological restoration, conservation and silviculture of this important native tree species. PMID:22163920

Determining the factors affecting the distribution of Muscari latifolium, an endemic plant of Turkey, and a mapping species distribution model.

PubMed

Yilmaz, Hatice; Yilmaz, Osman Yalçın; Akyüz, Yaşar Feyza

2017-02-01

Species distribution modeling was used to determine factors among the large predictor candidate data set that affect the distribution of Muscari latifolium , an endemic bulbous plant species of Turkey, to quantify the relative importance of each factor and make a potential spatial distribution map of M. latifolium . Models were built using the Boosted Regression Trees method based on 35 presence and 70 absence records obtained through field sampling in the Gönen Dam watershed area of the Kazdağı Mountains in West Anatolia. Large candidate variables of monthly and seasonal climate, fine-scale land surface, and geologic and biotic variables were simplified using a BRT simplifying procedure. Analyses performed on these resources, direct and indirect variables showed that there were 14 main factors that influence the species' distribution. Five of the 14 most important variables influencing the distribution of the species are bedrock type, Quercus cerris density, precipitation during the wettest month, Pinus nigra density, and northness. These variables account for approximately 60% of the relative importance for determining the distribution of the species. Prediction performance was assessed by 10 random subsample data sets and gave a maximum the area under a receiver operating characteristic curve (AUC) value of 0.93 and an average AUC value of 0.8. This study provides a significant contribution to the knowledge of the habitat requirements and ecological characteristics of this species. The distribution of this species is explained by a combination of biotic and abiotic factors. Hence, using biotic interaction and fine-scale land surface variables in species distribution models improved the accuracy and precision of the model. The knowledge of the relationships between distribution patterns and environmental factors and biotic interaction of M. latifolium can help develop a management and conservation strategy for this species.

High-Resolution Synchrotron Radiation Imaging of Trace Metal Elemental Concentrations in Porites Coral

NASA Astrophysics Data System (ADS)

Cirino, M.; Dunbar, R. B.; Tangri, N.; Mehta, A.

2014-12-01

We investigated the use of synchrotron radiation for elemental imaging within the skeleton of a Porites coral from American Samoa to explore the fine-scale structure of strontium to calcium (Sr/Ca) variability. The use of a synchrotron for coral paleoclimate analysis is relatively new. The method provides a high resolution, two-dimensional elemental map of a coral surface. The aragonitic skeleton of Porites sp. colonies has been widely used for paleoclimate reconstruction as the oxygen isotope ratio (δ18O) signal varies with both sea surface temperature (SST) and sea surface salinity (SSS). Sr/Ca has been used in previous studies in conjunction with δ18O to deconvolve SST from SSS, as Sr/Ca in the coral skeleton varies with SST, but not SSS. However, recent studies suggest that in some cases Sr/Ca variability in coral does not reliably reflect changes in SST. We sought to address this puzzle by investigating Sr/Ca variability in Porites corals at a very fine spatial scale while also demonstrating the suitability of the synchrotron as a coral analysis tool. We also considered Sr/Ca variability as it pertains to the coral's structural elements. The Stanford Linear Accelerator Center synchrotron station generates collimated x-rays in the energy range of 4500-45000 eV with beam diameters as small as 20 μm. Synchrotron imaging allows faster and higher-resolution Sr/Ca analysis than does inductively coupled plasma mass spectrometry (ICP-MS). It also is capable of mapping spatial distributions of many elements, which aids in the development of a multiproxy approach to paleoclimate reconstruction. Imaging and analysis of the Porites coral using synchrotron radiation revealed an intricate sub-seasonal Sr/Ca signal, possibly correlating to a sub-monthly resolution. This signal, which seems unrelated to SST, dominates the annual signal.

Fine Scale Baleen Whale Behavior Observed Via Tagging Over Daily Time Scales

DTIC Science & Technology

2015-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Fine Scale Baleen Whale Behavior Observed Via Tagging...followed over time scales of days from an oceanographic vessel so that environmental sampling can be conducted in proximity to the tagged whale ...characterize the relationship between diel variability in the foraging behavior of baleen whales (North Atlantic right whales and sei whales ) and the

Susceptibility and triggering scenarios at a regional scale for shallow landslides

NASA Astrophysics Data System (ADS)

Gullà, G.; Antronico, L.; Iaquinta, P.; Terranova, O.

2008-07-01

The work aims at identifying susceptible areas and pluviometric triggering scenarios at a regional scale in Calabria (Italy), with reference to shallow landsliding events. The proposed methodology follows a statistical approach and uses a database linked to a GIS that has been created to support the various steps of spatial data management and manipulation. The shallow landslide predisposing factors taken into account are derived from (i) the 40-m digital terrain model of the region, an ˜ 15,075 km 2 extension; (ii) outcropping lithology; (iii) soils; and (iv) land use. More precisely, a map of the slopes has been drawn from the digital terrain model. Two kinds of covers [prevalently coarse-grained (CG cover) or fine-grained (FG cover)] were identified, referring to the geotechnical characteristics of geomaterial covers and to the lithology map; soilscapes were drawn from soil maps; and finally, the land use map was employed without any prior processing. Subsequently, the inventory maps of some shallow landsliding events, totaling more than 30,000 instabilities of the past and detected by field surveys and photo aerial restitution, were employed to calibrate the relative importance of these predisposing factors. The use of single factors (first level analysis) therefore provides three different susceptibility maps. Second level analysis, however, enables better location of areas susceptible to shallow landsliding events by crossing the single susceptibility maps. On the basis of the susceptibility map obtained by the second level analysis, five different classes of susceptibility to shallow landsliding events have been outlined over the regional territory: 8.9% of the regional territory shows very high susceptibility, 14.3% high susceptibility, 15% moderate susceptibility, 3.6% low susceptibility, and finally, about 58% very low susceptibility. Finally, the maps of two significant shallow landsliding events of the past and their related rainfalls have been utilized to identify the relevant pluviometric triggering scenarios. By using 205 daily rainfall series, different triggering pluviometric scenarios have been identified with reference to CG and FG covers: a value of 365 mm of the total rainfall of the event and/or 170 mm/d of the rainfall maximum intensity and a value of 325 mm of the total rainfall of the event and/or 158 mm/d of the rainfall maximum intensity are able to trigger shallow landsliding events for CG and FG covers, respectively. The results obtained from this study can help administrative authorities to plan future development activities and mitigation measures in shallow landslide-prone areas. In addition, the proposed methodology can be useful in managing emergency situations at a regional scale for shallow landsliding events triggered by intense rainfalls; through this approach, the susceptibility and the pluviometric triggering scenario maps will be improved by means of finer calibration of the involved factors.

Doubly stochastic Poisson process models for precipitation at fine time-scales

NASA Astrophysics Data System (ADS)

Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

2012-09-01

This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

Potential for using regional and global datasets for national scale ecosystem service modelling

NASA Astrophysics Data System (ADS)

Maxwell, Deborah; Jackson, Bethanna

2016-04-01

Ecosystem service models are increasingly being used by planners and policy makers to inform policy development and decisions about national-level resource management. Such models allow ecosystem services to be mapped and quantified, and subsequent changes to these services to be identified and monitored. In some cases, the impact of small scale changes can be modelled at a national scale, providing more detailed information to decision makers about where to best focus investment and management interventions that could address these issues, while moving toward national goals and/or targets. National scale modelling often uses national (or local) data (for example, soils, landcover and topographical information) as input. However, there are some places where fine resolution and/or high quality national datasets cannot be easily obtained, or do not even exist. In the absence of such detailed information, regional or global datasets could be used as input to such models. There are questions, however, about the usefulness of these coarser resolution datasets and the extent to which inaccuracies in this data may degrade predictions of existing and potential ecosystem service provision and subsequent decision making. Using LUCI (the Land Utilisation and Capability Indicator) as an example predictive model, we examine how the reliability of predictions change when national datasets of soil, landcover and topography are substituted with coarser scale regional and global datasets. We specifically look at how LUCI's predictions of where water services, such as flood risk, flood mitigation, erosion and water quality, change when national data inputs are replaced by regional and global datasets. Using the Conwy catchment, Wales, as a case study, the land cover products compared are the UK's Land Cover Map (2007), the European CORINE land cover map and the ESA global land cover map. Soils products include the National Soil Map of England and Wales (NatMap) and the European Soils Database. NEXTmap elevation data, which covers the UK and parts of continental Europe, are compared to global AsterDEM and SRTM30 topographical products. While the regional and global datasets can be used to fill gaps in data requirements, the coarser resolution of these datasets means that there is greater aggregation of information over larger areas. This loss of detail impacts on the reliability of model output, particularly where significant discrepancies between datasets exist. The implications of this loss of detail in terms of spatial planning and decision making is discussed. Finally, in the context of broader development the need for better nationally and globally available data to allow LUCI and other ecosystem models to become more globally applicable is highlighted.

Post-LHC7 fine-tuning in the minimal supergravity/CMSSM model with a 125 GeV Higgs boson

NASA Astrophysics Data System (ADS)

Baer, Howard; Barger, Vernon; Huang, Peisi; Mickelson, Dan; Mustafayev, Azar; Tata, Xerxes

2013-02-01

The recent discovery of a 125 GeV Higgs-like resonance at LHC, coupled with the lack of evidence for weak scale supersymmetry (SUSY), has severely constrained SUSY models such as minimal supergravity (mSUGRA)/CMSSM. As LHC probes deeper into SUSY model parameter space, the little hierarchy problem—how to reconcile the Z and Higgs boson mass scale with the scale of SUSY breaking—will become increasingly exacerbated unless a sparticle signal is found. We evaluate two different measures of fine-tuning in the mSUGRA/CMSSM model. The more stringent of these, ΔHS, includes effects that arise from the high-scale origin of the mSUGRA parameters while the second measure, ΔEW, is determined only by weak scale parameters: hence, it is universal to any model with the same particle spectrum and couplings. Our results incorporate the latest constraints from LHC7 sparticle searches, LHCb limits from Bs→μ+μ- and also require a light Higgs scalar with mh˜123-127GeV. We present fine-tuning contours in the m0 vs m1/2 plane for several sets of A0 and tan⁡β values. We also present results for ΔHS and ΔEW from a scan over the entire viable model parameter space. We find a ΔHS≳103, or at best 0.1%, fine-tuning. For the less stringent electroweak fine-tuning, we find ΔEW≳102, or at best 1%, fine-tuning. Two benchmark points are presented that have the lowest values of ΔHS and ΔEW. Our results provide a quantitative measure for ascertaining whether or not the remaining mSUGRA/CMSSM model parameter space is excessively fine-tuned and so could provide impetus for considering alternative SUSY models.

Parameterizing a Large-scale Water Balance Model in Regions with Sparse Data: The Tigris-Euphrates River Basins as an Example

NASA Astrophysics Data System (ADS)

Flint, A. L.; Flint, L. E.

2010-12-01

The characterization of hydrologic response to current and future climates is of increasing importance to many countries around the world that rely heavily on changing and uncertain water supplies. Large-scale models that can calculate a spatially distributed water balance and elucidate groundwater recharge and surface water flows for large river basins provide a basis of estimates of changes due to future climate projections. Unfortunately many regions in the world have very sparse data for parameterization or calibration of hydrologic models. For this study, the Tigris and Euphrates River basins were used for the development of a regional water balance model at 180-m spatial scale, using the Basin Characterization Model, to estimate historical changes in groundwater recharge and surface water flows in the countries of Turkey, Syria, Iraq, Iran, and Saudi Arabia. Necessary input parameters include precipitation, air temperature, potential evapotranspiration (PET), soil properties and thickness, and estimates of bulk permeability from geologic units. Data necessary for calibration includes snow cover, reservoir volumes (from satellite data and historic, pre-reservoir elevation data) and streamflow measurements. Global datasets for precipitation, air temperature, and PET were available at very large spatial scales (50 km) through the world scale databases, finer scale WorldClim climate data, and required downscaling to fine scales for model input. Soils data were available through world scale soil maps but required parameterization on the basis of textural data to estimate soil hydrologic properties. Soil depth was interpreted from geomorphologic interpretation and maps of quaternary deposits, and geologic materials were categorized from generalized geologic maps of each country. Estimates of bedrock permeability were made on the basis of literature and data on driller’s logs and adjusted during calibration of the model to streamflow measurements where available. Results of historical water balance calculations throughout the Tigris and Euphrates River basins will be shown along with details of processing input data to provide spatial continuity and downscaling. Basic water availability analysis for recharge and runoff is readily available from a determinisitic solar radiation energy balance model and a global potential evapotranspiration model and global estimates of precipitation and air temperature. Future climate estimates can be readily applied to the same water and energy balance models to evaluate future water availability for countries around the globe.

Breed relationships facilitate fine-mapping studies: A 7.8-kb deletion cosegregates with Collie eye anomaly across multiple dog breeds

PubMed Central

Parker, Heidi G.; Kukekova, Anna V.; Akey, Dayna T.; Goldstein, Orly; Kirkness, Ewen F.; Baysac, Kathleen C.; Mosher, Dana S.; Aguirre, Gustavo D.; Acland, Gregory M.; Ostrander, Elaine A.

2007-01-01

The features of modern dog breeds that increase the ease of mapping common diseases, such as reduced heterogeneity and extensive linkage disequilibrium, may also increase the difficulty associated with fine mapping and identifying causative mutations. One way to address this problem is by combining data from multiple breeds segregating the same trait after initial linkage has been determined. The multibreed approach increases the number of potentially informative recombination events and reduces the size of the critical haplotype by taking advantage of shortened linkage disequilibrium distances found across breeds. In order to identify breeds that likely share a trait inherited from the same ancestral source, we have used cluster analysis to divide 132 breeds of dog into five primary breed groups. We then use the multibreed approach to fine-map Collie eye anomaly (cea), a complex disorder of ocular development that was initially mapped to a 3.9-cM region on canine chromosome 37. Combined genotypes from affected individuals from four breeds of a single breed group significantly narrowed the candidate gene region to a 103-kb interval spanning only four genes. Sequence analysis revealed that all affected dogs share a homozygous deletion of 7.8 kb in the NHEJ1 gene. This intronic deletion spans a highly conserved binding domain to which several developmentally important proteins bind. This work both establishes that the primary cea mutation arose as a single disease allele in a common ancestor of herding breeds as well as highlights the value of comparative population analysis for refining regions of linkage. PMID:17916641

Fine Mapping on Chromosome 13q32–34 and Brain Expression Analysis Implicates MYO16 in Schizophrenia

PubMed Central

Rodriguez-Murillo, Laura; Xu, Bin; Roos, J Louw; Abecasis, Gonçalo R; Gogos, Joseph A; Karayiorgou, Maria

2014-01-01

We previously reported linkage of schizophrenia and schizoaffective disorder to 13q32–34 in the European descent Afrikaner population from South Africa. The nature of genetic variation underlying linkage peaks in psychiatric disorders remains largely unknown and both rare and common variants may be contributing. Here, we examine the contribution of common variants located under the 13q32–34 linkage region. We used densely spaced SNPs to fine map the linkage peak region using both a discovery sample of 415 families and a meta-analysis incorporating two additional replication family samples. In a second phase of the study, we use one family-based data set with 237 families and independent case–control data sets for fine mapping of the common variant association signal using HapMap SNPs. We report a significant association with a genetic variant (rs9583277) within the gene encoding for the myosin heavy-chain Myr 8 (MYO16), which has been implicated in neuronal phosphoinositide 3-kinase signaling. Follow-up analysis of HapMap variation within MYO16 in a second set of Afrikaner families and additional case–control data sets of European descent highlighted a region across introns 2–6 as the most likely region to harbor common MYO16 risk variants. Expression analysis revealed a significant increase in the level of MYO16 expression in the brains of schizophrenia patients. Our results suggest that common variation within MYO16 may contribute to the genetic liability to schizophrenia. PMID:24141571

Visualizing Single Cell Biology: Nanosims Studies of Carbon and Nitrogen Metabolism in Diazotrophic Cyanobacteria

NASA Astrophysics Data System (ADS)

Pett-Ridge, J.; Finzi, J. A.; Capone, D. G.; Popa, R.; Nealson, K. H.; Ng, W.; Spormann, A. M.; Hutcheon, I. D.; Weber, P. K.

2007-12-01

Filamentous nitrogen fixing (diazotrophic) cyanobacteria are key players in global nutrient cycling, but the relationship between CO2- and N2-fixation and intercellular exchange of these elements remains poorly understood in many genera. These bacteria are faced with the challenge of isolating regions of N-fixation (O2 inhibited) and photosynthetic (O2 producing) activity. We used isotope labeling in conjunction with a high-resolution isotope and elemental mapping technique (NanoSIMS) to quantitatively describe 13C and 15N uptake and transport in two aquatic cyanobacteria grown on NaH13CO3 and 15N2. The technical challenges of tracing isotopes within individual bacteria can be overcome with high resolution Secondary Ion Mass Spectrometry (NanoSIMS). In NanoSIMS analysis, samples are sputtered with an energetic primary beam (Cs+, O-) liberating secondary ions that are separated by the mass spectrometer and detected in a suite of electron multipliers. Five isotopic species may be analyzed concurrently with spatial resolution as fine as 50nm. A high sensitivity isotope ratio 'map' can then be generated for the analyzed area. Using sequentially harvested cyanobacteria in conjunction with enriched H13CO3 and 15N2 incubations, we measured temporal enrichment patterns that evolve over the course of a day's growth and suggest tightly regulated changes in fixation kinetics. With a combination of TEM, SEM and NanoSIMS analyses, we also mapped the distribution of C, N and Mo (a critical nitrogenase co-factor) isotopes in intact cells. Our results suggest that NanoSIMS mapping of metal enzyme co-factors may be a powerful method of identifying physiological and morphological characteristics within individual bacterial cells, and could be used to provide a 3-dimensional context for more traditional analyses such as immunogold labeling. Finally, we resolved patterns of isotope enrichment at multiple spatial scales: sub-cellular variation, cell-cell differences along filaments, inter-species transfers (with Rhizobium epibionts), and within-cell depth profiles. Spatial enrichment patterns were correlated with morphological features evidenced in TEM images of microtomed filaments. These features indicate how 15N and 13C "hotspots" are dispersed throughout individual cells in different species, and may indicate isolated locations of increased N2 fixation, sites of amino acid/protein synthesis, or cyanophycin storage granules. This combination of Nano-Secondary Ion Mass Spectrometry (NanoSIMS) analysis and high resolution microscopy allows isotopic analysis to be linked to morphological features and holds great promise for fine-scale studies of bacteria metabolism.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images.

PubMed

Hapca, Simona; Baveye, Philippe C; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution.

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images

PubMed Central

Hapca, Simona; Baveye, Philippe C.; Wilson, Clare; Lark, Richard Murray; Otten, Wilfred

2015-01-01

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R2 value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution. PMID:26372473

Fostering Creativity: A Multiple Intelligences Approach to Designing Learning in Undergraduate Fine Art

ERIC Educational Resources Information Center

Clarke, Angela; Cripps, Peter

2012-01-01

Curriculum and pedagogy in undergraduate fine art can promote an approach to learning creativity that is more about being an artist than knowing about art. Lecturers can provide a road map for developing particular dispositions, in relation to student ideas and perceptions, to foster personalised creativity. This requires that lecturers have an…

A Method to Reveal Fine-Grained and Diverse Conceptual Progressions during Learning

ERIC Educational Resources Information Center

Lombard, François; Merminod, Marie; Widmer, Vincent; Schneider, Daniel K.

2018-01-01

Empirical data on learners' conceptual progression is required to design curricula and guide students. In this paper, we present the Reference Map Change Coding (RMCC) method for revealing students' progression at a fine-grained level. The method has been developed and tested through the analysis of successive versions of the productions of eight…

Assessment of fine-scale parameterizations of turbulent dissipation rates in the Southern Ocean

NASA Astrophysics Data System (ADS)

Takahashi, A.; Hibiya, T.

2016-12-01

To sustain the global overturning circulation, more mixing is required in the ocean than has been observed. The most likely candidates for this missing mixing are breaking of wind-induced near-inertial waves and bottom-generated internal lee waves in the sparsely observed Southern Ocean. Nevertheless, there is a paucity of direct microstructure measurements in the Southern Ocean where energy dissipation rates have been estimated mostly using fine-scale parameterizations. In this study, we assess the validity of the existing fine-scale parameterizations in the Antarctic Circumpolar Current (ACC) region using the data obtained from simultaneous full-depth measurements of micro-scale turbulence and fine-scale shear/strain carried out south of Australia during January 17 to February 2, 2016. Although the fine-scale shear/strain ratio (Rω) is close to the Garrett-Munk (GM) value at the station north of Subtropical Front, the values of Rω at the stations south of Subantarctic Front well exceed the GM value, suggesting that the local internal wave spectra are significantly biased to lower frequencies. We find that not all of the observed energy dissipation rates at these locations are well predicted using Gregg-Henyey-Polzin (GHP; Gregg et al., 2003) and Ijichi-Hibiya (IH; Ijichi and Hibiya, 2015) parameterizations, both of which take into account the spectral distortion in terms of Rω; energy dissipation rates at some locations are obviously overestimated by GHP and IH, although only the strain-based Wijesekera (Wijesekera et al., 1993) parameterization yields fairly good predictions. One possible explanation for this result is that a significant portion of the observed shear variance at these locations might be attributed to kinetic-energy-dominant small-scale eddies associated with the ACC, so that fine-scale strain rather than Rω becomes a more appropriate parameter to characterize the actual internal wave field.

Genetic dissection and fine mapping of a novel dt gene associated with determinate growth habit in sesame.

PubMed

Zhang, Yanxin; Wang, Linhai; Gao, Yuan; Li, Donghua; Yu, Jingyin; Zhou, Rong; Zhang, Xiurong

2018-06-14

As an important oil crop, growth habit of sesame (Sesamum indicum L.) is naturally indeterminate, which brings about asynchronous maturity of capsules and causes loss of yield. The genetic basis of determinate growth habit in sesame was investigated by classical genetic analysis through multiple populations, results revealed that it was controlled by an unique recessive gene. The genotyping by sequencing (GBS) approach was employed for high-throughput SNP identification and genotyping in the F 2 population, then a high density bin map was constructed, the map was 1086.403 cM in length, which consisted of 1184 bins (13,679 SNPs), with an average of 0.918 cM between adjacent bins. Based on bin mapping in conjunction with SSR markers analysis in targeted region, the novel sesame determinacy gene was mapped on LG09 in a genome region of 41 kb. This study dissected genetic basis of determinate growth habit in sesame, constructed a new high-density bin map and mapped a novel determinacy gene. Results of this study demonstrate that we employed an optimized approach to get fine-accuracy, high-resolution and high-efficiency mapping result in sesame. The findings provided important foundation for sesame determinacy gene cloning and were expected to be applied in breeding for cultivars suited to mechanized production.

Enhancing genomic prediction with genome-wide association studies in multiparental maize populations

USDA-ARS?s Scientific Manuscript database

Genome-wide association mapping using dense marker sets has identified some nucleotide variants affecting complex traits which have been validated with fine-mapping and functional analysis. Many sequence variants associated with complex traits in maize have small effects and low repeatability, howev...

Identifying grain-size dependent errors on global forest area estimates and carbon studies

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2008-01-01

Satellite-derived coarse-resolution data are typically used for conducting global analyses. But the forest areas estimated from coarse-resolution maps (e.g., 1 km) inevitably differ from a corresponding fine-resolution map (such as a 30-m map) that would be closer to ground truth. A better understanding of changes in grain size on area estimation will improve our...

Methods for Improving Fine-Scale Applications of the WRF-CMAQ Modeling System

EPA Science Inventory

Presentation on the work in AMAD to improve fine-scale (e.g. 4km and 1km) WRF-CMAQ simulations. Includes iterative analysis, updated sea surface temperature and snow cover fields, and inclusion of impervious surface information (urban parameterization).

Coarse-Scale Biases for Spirals and Orientation in Human Visual Cortex

PubMed Central

Heeger, David J.

2013-01-01

Multivariate decoding analyses are widely applied to functional magnetic resonance imaging (fMRI) data, but there is controversy over their interpretation. Orientation decoding in primary visual cortex (V1) reflects coarse-scale biases, including an over-representation of radial orientations. But fMRI responses to clockwise and counter-clockwise spirals can also be decoded. Because these stimuli are matched for radial orientation, while differing in local orientation, it has been argued that fine-scale columnar selectivity for orientation contributes to orientation decoding. We measured fMRI responses in human V1 to both oriented gratings and spirals. Responses to oriented gratings exhibited a complex topography, including a radial bias that was most pronounced in the peripheral representation, and a near-vertical bias that was most pronounced near the foveal representation. Responses to clockwise and counter-clockwise spirals also exhibited coarse-scale organization, at the scale of entire visual quadrants. The preference of each voxel for clockwise or counter-clockwise spirals was predicted from the preferences of that voxel for orientation and spatial position (i.e., within the retinotopic map). Our results demonstrate a bias for local stimulus orientation that has a coarse spatial scale, is robust across stimulus classes (spirals and gratings), and suffices to explain decoding from fMRI responses in V1. PMID:24336733

Admixture mapping of serum vitamin D and parathyroid hormone concentrations in the African American-Diabetes Heart Study

PubMed Central

Palmer, Nicholette D.; Divers, Jasmin; Lu, Lingyi; Register, Thomas C.; Carr, J. Jeffrey; Hicks, Pamela J.; Smith, S. Carrie; Xu, Jianzhao; Judd, Suzanne E.; Irvin, Marguerite R.; Gutierrez, Orlando M.; Bowden, Donald W.; Wagenknecht, Lynne E.; Langefeld, Carl D.; Freedman, Barry I.

2016-01-01

Vitamin D and intact parathyroid hormone (iPTH) concentrations differ between individuals of African and European descent and may play a role in observed racial differences in bone mineral density (BMD). These findings suggest that mapping by admixture linkage disequilibrium (MALD) may be informative for identifying genetic variants contributing to these ethnic disparities. Admixture mapping was performed for serum 25-hydroxyvitamin D, 1,25-dihydroxyvitamin D, vitamin D-binding protein (VDBP), bioavailable vitamin D, and iPTH concentrations and computed tomography measured thoracic and lumbar vertebral volumetric BMD in 552 unrelated African Americans with type 2 diabetes from the African American-Diabetes Heart Study. Genotyping was performed using a custom Illumina ancestry informative marker (AIM) panel. For each AIM, the probability of inheriting 0, 1, or 2 copies of a European-derived allele was determined. Non-parametric linkage analysis was performed by testing for association between each AIM using these probabilities among phenotypes, accounting for global ancestry, age, and gender. Fine-mapping of MALD peaks was facilitated by genome-wide association study (GWAS) data. VDBP levels were significantly linked in proximity to the protein coding locus (rs7689609, LOD=11.05). Two loci exhibited significant linkage signals for 1,25-dihydroxyvitamin D on 13q21.2 (rs1622710, LOD=3.20) and 12q13.2 (rs11171526, LOD=3.10). iPTH was significantly linked on 9q31.3 (rs7854368, LOD=3.14). Fine-mapping with GWAS data revealed significant known (rs7041 with VDBP, P=1.38×10−82) and novel (rs12741813 and rs10863774 with VDBP, P<6.43×10−5) loci with plausible biological roles. Admixture mapping in combination with fine-mapping has focused efforts to identify loci contributing to ethnic differences in vitamin D-related traits. PMID:27032714

Analytical SuperSTEM for extraterrestrial materials research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, J P; Dai, Z R

2009-09-08

Electron-beam studies of extraterrestrial materials with significantly improved spatial resolution, energy resolution and sensitivity are enabled using a 300 keV SuperSTEM scanning transmission electron microscope with a monochromator and two spherical aberration correctors. The improved technical capabilities enable analyses previously not possible. Mineral structures can be directly imaged and analyzed with single-atomic-column resolution, liquids and implanted gases can be detected, and UV-VIS optical properties can be measured. Detection limits for minor/trace elements in thin (<100 nm thick) specimens are improved such that quantitative measurements of some extend to the sub-500 ppm level. Electron energy-loss spectroscopy (EELS) can be carried outmore » with 0.10-0.20 eV energy resolution and atomic-scale spatial resolution such that variations in oxidation state from one atomic column to another can be detected. Petrographic mapping is extended down to the atomic scale using energy-dispersive x-ray spectroscopy (EDS) and energy-filtered transmission electron microscopy (EFTEM) imaging. Technical capabilities and examples of the applications of SuperSTEM to extraterrestrial materials are presented, including the UV spectral properties and organic carbon K-edge fine structure of carbonaceous matter in interplanetary dust particles (IDPs), x-ray elemental maps showing the nanometer-scale distribution of carbon within GEMS (glass with embedded metal and sulfides), the first detection and quantification of trace Ti in GEMS using EDS, and detection of molecular H{sub 2}O in vesicles and implanted H{sub 2} and He in irradiated mineral and glass grains.« less

Mapping Brazilian savanna vegetation gradients with Landsat time series

NASA Astrophysics Data System (ADS)

Schwieder, Marcel; Leitão, Pedro J.; da Cunha Bustamante, Mercedes Maria; Ferreira, Laerte Guimarães; Rabe, Andreas; Hostert, Patrick

2016-10-01

Global change has tremendous impacts on savanna systems around the world. Processes related to climate change or agricultural expansion threaten the ecosystem's state, function and the services it provides. A prominent example is the Brazilian Cerrado that has an extent of around 2 million km2 and features high biodiversity with many endemic species. It is characterized by landscape patterns from open grasslands to dense forests, defining a heterogeneous gradient in vegetation structure throughout the biome. While it is undisputed that the Cerrado provides a multitude of valuable ecosystem services, it is exposed to changes, e.g. through large scale land conversions or climatic changes. Monitoring of the Cerrado is thus urgently needed to assess the state of the system as well as to analyze and further understand ecosystem responses and adaptations to ongoing changes. Therefore we explored the potential of dense Landsat time series to derive phenological information for mapping vegetation gradients in the Cerrado. Frequent data gaps, e.g. due to cloud contamination, impose a serious challenge for such time series analyses. We synthetically filled data gaps based on Radial Basis Function convolution filters to derive continuous pixel-wise temporal profiles capable of representing Land Surface Phenology (LSP). Derived phenological parameters revealed differences in the seasonal cycle between the main Cerrado physiognomies and could thus be used to calibrate a Support Vector Classification model to map their spatial distribution. Our results show that it is possible to map the main spatial patterns of the observed physiognomies based on their phenological differences, whereat inaccuracies occurred especially between similar classes and data-scarce areas. The outcome emphasizes the need for remote sensing based time series analyses at fine scales. Mapping heterogeneous ecosystems such as savannas requires spatial detail, as well as the ability to derive important phenological parameters for monitoring habitats or ecosystem responses to climate change. The open Landsat and Sentinel-2 archives provide the satellite data needed for improved analyses of savanna ecosystems globally.

Advancing UAS methods for monitoring coastal environments

NASA Astrophysics Data System (ADS)

Ridge, J.; Seymour, A.; Rodriguez, A. B.; Dale, J.; Newton, E.; Johnston, D. W.

2017-12-01

Utilizing fixed-wing Unmanned Aircraft Systems (UAS), we are working to improve coastal monitoring by increasing the accuracy, precision, temporal resolution, and spatial coverage of habitat distribution maps. Generally, multirotor aircraft are preferred for precision imaging, but recent advances in fixed-wing technology have greatly increased their capabilities and application for fine-scale (decimeter-centimeter) measurements. Present mapping methods employed by North Carolina coastal managers involve expensive, time consuming and localized observation of coastal environments, which often lack the necessary frequency to make timely management decisions. For example, it has taken several decades to fully map oyster reefs along the NC coast, making it nearly impossible to track trends in oyster reef populations responding to harvesting pressure and water quality degradation. It is difficult for the state to employ manned flights for collecting aerial imagery to monitor intertidal oyster reefs, because flights are usually conducted after seasonal increases in turbidity. In addition, post-storm monitoring of coastal erosion from manned platforms is often conducted days after the event and collects oblique aerial photographs which are difficult to use for accurately measuring change. Here, we describe how fixed wing UAS and standard RGB sensors can be used to rapidly quantify and assess critical coastal habitats (e.g., barrier islands, oyster reefs, etc.), providing for increased temporal frequency to isolate long-term and event-driven (storms, harvesting) impacts. Furthermore, drone-based approaches can accurately image intertidal habitats as well as resolve information such as vegetation density and bathymetry from shallow submerged areas. We obtain UAS imagery of a barrier island and oyster reefs under ideal conditions (low tide, turbidity, and sun angle) to create high resolution (cm scale) maps and digital elevation models to assess habitat condition. Concurrently, we test the accuracy of UAS platforms and image analysis tools against traditional high-resolution mapping equipment (GPS and terrestrial lidar) and in situ sampling (density quadrats) to conduct error analysis of UAS orthoimagery and data processing.

Introducing close-range photogrammetry for characterizing forest understory plant diversity and surface fuel structure at fine scales

Treesearch

Benjamin C. Bright; E. Louise Loudermilk; Scott M. Pokswinski; Andrew T. Hudak; Joseph J. O' Brien

2016-01-01

Methods characterizing fine-scale fuels and plant diversity can advance understanding of plant-fire interactions across scales and help in efforts to monitor important ecosystems such as longleaf pine (Pinus palustris Mill.) forests of the southeastern United States. Here, we evaluate the utility of close-range photogrammetry for measuring fuels and plant...

Fine-scale multi-species aggregations of oceanic zooplankton

NASA Astrophysics Data System (ADS)

Haury, L. R.; Wiebe, P. H.

1982-07-01

Sixteen Longhurst-Hardy Plankton Recorder tows were taken at different depths in the northwest Atlantic for analysis of fine-scale horizontal patchiness. Abundant species were non-randomly distributed in patches with scales of tens to hundreds of meters. Positive correlations between species abundances dominated, indicating that the patches were multi-species associations. Most horizontal pattern appeared to be of biological origin.

Stream gradient Hotspot and Cluster Analysis (SL-HCA) for improving the longitudinal profiles metrics

NASA Astrophysics Data System (ADS)

Troiani, Francesco; Piacentini, Daniela; Seta Marta, Della

2016-04-01

Many researches successfully focused on stream longitudinal profiles analysis through Stream Length-gradient (SL) index for detecting, at different spatial scales, either tectonic structures or hillslope processes. The analysis and interpretation of spatial variability of SL values, both at a regional and local scale, is often complicated due to the concomitance of different factors generating SL anomalies, including the bedrock composition. The creation of lithologically-filtered SL maps is often problematic in areas where homogeneously surveyed geological maps, with a sufficient resolution are unavailable. Moreover, both the SL map classification and the unbiased anomaly detection are rather difficult. For instance, which is the best threshold to define the anomalous SL values? Further, is there a minimum along-channel extent of anomalous SL values for objectively defining over-steeped segments on long-profiles? This research investigates the relevance and potential of a new approach based on Hotspot and Cluster Analysis of SL values (SL-HCA) for detecting knickzones on long-profiles at a regional scale and for fine-tuning the interpretation of their geological-geomorphological meaning. We developed this procedure within a 2800 km2-wide area located in the mountainous sector of the Northern Apennines of Italy. The Getis-Ord Gi∗ statistic is applied for the SL-HCA approach. The value of SL, calculated starting from a 5x5 m Digital Elevation Model, is used as weighting factor and the Gi∗ index is calculated for each 50 m-long channel segment for the whole fluvial system. The outcomes indicate that high positive Gi∗ values imply the clustering of SL anomalies, thus the occurrence of knickzones on the stream long-profiles. Results show that high and very high Gi* values (i.e. values beyond two standard deviations from the mean) correlate well with the principal knickzones detected with existent lithologically-filtered SL maps. Field checks and remote sensing analysis conducted on 52 clusters of high and very high Gi* values indicate that mass movement of slope material represents the dominant process producing over-steeped long-profiles along connected streams, whereas the litho-structure accounts for the main anomalies along disconnected steams. Tectonic structures generally provide to the largest clusters. Our results demonstrate that SL-HCA maps have the same potential of lithologically-filtered SL maps for detecting knickzones due to hillslope processes and/or tectonic structures. The reduced-complexity model derived from SL-HCA approach highly improve the readability of the morphometric outcomes, thus the interpretation at a regional scale of the geological-geomorphological meaning of over-steeped segments on long-profiles. SL-HCA maps are useful to investigate and better interpret knickzones within regions poorly covered by geological data and where field surveys are difficult to be performed.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pau, G. S. H.; Bisht, G.; Riley, W. J.

Existing land surface models (LSMs) describe physical and biological processes that occur over a wide range of spatial and temporal scales. For example, biogeochemical and hydrological processes responsible for carbon (CO 2, CH 4) exchanges with the atmosphere range from the molecular scale (pore-scale O 2 consumption) to tens of kilometers (vegetation distribution, river networks). Additionally, many processes within LSMs are nonlinearly coupled (e.g., methane production and soil moisture dynamics), and therefore simple linear upscaling techniques can result in large prediction error. In this paper we applied a reduced-order modeling (ROM) technique known as "proper orthogonal decomposition mapping method" thatmore » reconstructs temporally resolved fine-resolution solutions based on coarse-resolution solutions. We developed four different methods and applied them to four study sites in a polygonal tundra landscape near Barrow, Alaska. Coupled surface–subsurface isothermal simulations were performed for summer months (June–September) at fine (0.25 m) and coarse (8 m) horizontal resolutions. We used simulation results from three summer seasons (1998–2000) to build ROMs of the 4-D soil moisture field for the study sites individually (single-site) and aggregated (multi-site). The results indicate that the ROM produced a significant computational speedup (> 10 3) with very small relative approximation error (< 0.1%) for 2 validation years not used in training the ROM. We also demonstrate that our approach: (1) efficiently corrects for coarse-resolution model bias and (2) can be used for polygonal tundra sites not included in the training data set with relatively good accuracy (< 1.7% relative error), thereby allowing for the possibility of applying these ROMs across a much larger landscape. By coupling the ROMs constructed at different scales together hierarchically, this method has the potential to efficiently increase the resolution of land models for coupled climate simulations to spatial scales consistent with mechanistic physical process representation.« less

High-resolution (SIMS) versus bulk sulfur isotope patterns of pyrite in Proterozoic microbialites with diverse mat textures

NASA Astrophysics Data System (ADS)

Gomes, M. L.; Fike, D. A.; Bergmann, K.; Knoll, A. H.

2015-12-01

Sulfur (S) isotope signatures of sedimentary pyrite preserved in marine rocks provide a rich suite of information about changes in biogeochemical cycling associated with the evolution of microbial metabolisms and oxygenation of Earth surface environments. Conventionally, these S isotope records are based on bulk rock measurements. Yet, in modern microbial mat environments, S isotope compositions of sulfide can vary by up to 40‰ over a spatial range of ~ 1 mm. Similar ranges of S isotope variability have been found in Archean pyrite grains using both Secondary Ion Mass Spectrometry and other micro-analytical techniques. These micron-scale patterns have been linked to changes in rates of microbial sulfate reduction and/or sulfide oxidation, isotopic distillation of the sulfate reservoir due to microbial sulfate reduction, and post-depositional alteration. Fine-scale mapping of S isotope compositions of pyrite can thus be used to differentiate primary environmental signals from post-depositional overprinting - improving our understanding of both. Here, we examine micron-scale S isotope patterns of pyrite in microbialites from the Mesoproterozoic-Neoproterozoic Sukhaya Tunguska Formation and Neoproterozoic Draken Formation in order to explore S isotope variability associated with different mat textures and pyrite grain morphologies. A primary goal is to link modern observations of how sulfide spatial isotope distributions reflect active microbial communities present at given depths in the mats to ancient processes driving fine-sale pyrite variability in microbialites. We find large (up to 60‰) S isotope variability within a spatial range of less than 2.5cm. The micron-scale S isotope measurements converge around the S isotope composition of pyrite extracted from bulk samples of the same microbialites. These micron-scale pyrite S isotope patterns have the potential to reveal important information about ancient biogeochemical cycling in Proterozoic mat environments with implications for interpreting S isotope signatures from the geological record.

MODELING TOOLS FOR ASSESSING LANDSCAPE-LEVEL DETERMINANTS OF FISH PRODUCTION: EXAMPLES FROM WESTERN OREGON

EPA Science Inventory

Most studies addressing relationships between salmonids and factors that affect their freshwater production have focused on small areas and short time frames. Limits of understanding gained at fine spatiotemporal scales have become obvious, and aggregating fine-scale information ...

IMPLEMENTATION OF AN URBAN CANOPY PARAMETERIZATION FOR FINE-SCALE SIMULATIONS

EPA Science Inventory

The Pennsylvania State University/National Center for Atmospheric Research Mesoscale Model (MM5) (Grell et al. 1994) has been modified to include an urban canopy parameterization (UCP) for fine-scale urban simulations ( 1 - km horizontal grid spacing ). The UCP accounts for dr...

Satellite data based method for general survey of forest insect disturbance in British Columbia

NASA Astrophysics Data System (ADS)

Ranson, J.; Montesano, P.

2008-12-01

Regional forest disturbances caused by insects are important to monitor and quantify because of their influence on local ecosystems and the global carbon cycle. Local damage to forest trees disrupts food supplies and shelter for a variety of organisms. Changes in the global carbon budget, its sources and its sinks affect the way the earth functions as a whole, and has an impact on global climate. Furthermore, the ability to detect nascent outbreaks and monitor the spread of regional infestations helps managers mitigate the damage done by catastrophic insect outbreaks. While detection is needed at a fine scale to support local mitigation efforts, detection at a broad regional scale is important for carbon flux modeling on the landscape scale, and needed to direct the local efforts. This paper presents a method for routinely detecting insect damage to coniferous forests using MODIS vegetation indices, thermal anomalies and land cover. The technique is validated using insect outbreak maps and accounts for fire disturbance effects. The range of damage detected may be used to interpret and quantify possible forest damage by insects.

Does soil compaction increase floods? A review

NASA Astrophysics Data System (ADS)

Alaoui, Abdallah; Rogger, Magdalena; Peth, Stephan; Blöschl, Günter

2018-02-01

Europe has experienced a series of major floods in the past years which suggests that flood magnitudes may have increased. Land degradation due to soil compaction from crop farming or grazing intensification is one of the potential drivers of this increase. A literature review suggests that most of the experimental evidence was generated at plot and hillslope scales. At larger scales, most studies are based on models. There are three ways in which soil compaction affects floods at the catchment scale: (i) through an increase in the area affected by soil compaction; (ii) by exacerbating the effects of changes in rainfall, especially for highly degraded soils; and (iii) when soil compaction coincides with soils characterized by a fine texture and a low infiltration capacity. We suggest that future research should focus on better synthesising past research on soil compaction and runoff, tailored field experiments to obtain a mechanistic understanding of the coupled mechanical and hydraulic processes, new mapping methods of soil compaction that combine mechanical and remote sensing approaches, and an effort to bridge all disciplines relevant to soil compaction effects on floods.

End of the chain? Rugosity and fine-scale bathymetry from existing underwater digital imagery using structure-from-motion (SfM) technology

USGS Publications Warehouse

Storlazzi, Curt; Dartnell, Peter; Hatcher, Gerry; Gibbs, Ann E.

2016-01-01

The rugosity or complexity of the seafloor has been shown to be an important ecological parameter for fish, algae, and corals. Historically, rugosity has been measured either using simple and subjective manual methods such as ‘chain-and-tape’ or complicated and expensive geophysical methods. Here, we demonstrate the application of structure-from-motion (SfM) photogrammetry to generate high-resolution, three-dimensional bathymetric models of a fringing reef from existing underwater video collected to characterize the seafloor. SfM techniques are capable of achieving spatial resolution that can be orders of magnitude greater than large-scale lidar and sonar mapping of coral reef ecosystems. The resulting data provide finer-scale measurements of bathymetry and rugosity that are more applicable to ecological studies of coral reefs than provided by the more expensive and time-consuming geophysical methods. Utilizing SfM techniques for characterizing the benthic habitat proved to be more effective and quantitatively powerful than conventional methods and thus might portend the end of the ‘chain-and-tape’ method for measuring benthic complexity.

Automated mapping of impervious surfaces in urban and suburban areas: Linear spectral unmixing of high spatial resolution imagery

NASA Astrophysics Data System (ADS)

Yang, Jian; He, Yuhong

2017-02-01

Quantifying impervious surfaces in urban and suburban areas is a key step toward a sustainable urban planning and management strategy. With the availability of fine-scale remote sensing imagery, automated mapping of impervious surfaces has attracted growing attention. However, the vast majority of existing studies have selected pixel-based and object-based methods for impervious surface mapping, with few adopting sub-pixel analysis of high spatial resolution imagery. This research makes use of a vegetation-bright impervious-dark impervious linear spectral mixture model to characterize urban and suburban surface components. A WorldView-3 image acquired on May 9th, 2015 is analyzed for its potential in automated unmixing of meaningful surface materials for two urban subsets and one suburban subset in Toronto, ON, Canada. Given the wide distribution of shadows in urban areas, the linear spectral unmixing is implemented in non-shadowed and shadowed areas separately for the two urban subsets. The results indicate that the accuracy of impervious surface mapping in suburban areas reaches up to 86.99%, much higher than the accuracies in urban areas (80.03% and 79.67%). Despite its merits in mapping accuracy and automation, the application of our proposed vegetation-bright impervious-dark impervious model to map impervious surfaces is limited due to the absence of soil component. To further extend the operational transferability of our proposed method, especially for the areas where plenty of bare soils exist during urbanization or reclamation, it is still of great necessity to mask out bare soils by automated classification prior to the implementation of linear spectral unmixing.

Warm Temperature Deformation Behavior and Processing Maps of 5182 and 7075 Aluminum Alloy Sheets with Fine Grains

NASA Astrophysics Data System (ADS)

Jang, D. H.; Kim, W. J.

2018-05-01

The tensile deformation behavior and processing maps of commercial 5182 and 7075 aluminum alloy sheets with similarly fine grain sizes (about 8 μm) were examined and compared over the temperature range of 423-723 K. The 5182 aluminum alloy with equiaxed grains exhibited larger strain rate sensitivity exponent ( m) values than the 7075 aluminum alloy with elongated grains under most of the testing conditions. The fracture strain behaviors of the two alloys as a function of strain rate and temperature followed the trend in their m values. In the processing maps, the power dissipation parameter values of the 5182 aluminum alloy were larger than those of the 7075 aluminum alloy and the instability domains of the 5182 aluminum alloy were smaller compared to that of the 7075 aluminum alloy, implying that the 5182 aluminum alloy had a better hot workability than the 7075 aluminum alloy.

High-resolution EPMA X-ray images of mother liquid inclusions in a Pd2Ga single crystal

NASA Astrophysics Data System (ADS)

Müller, D.; Schwerin, J.; Gille, P.; Fehr, K. T.

2014-03-01

During crystal growth from solution inclusions of different compositions were trapped at the rim of a Pd2Ga single crystal. Their fine-grained (< 5 μm) internal structure demands special requirements for electron microprobe analysis, realized by low-voltage (5 keV) element mapping applying a step size of 0.138 μm for each pixel. It can be shown, that these inclusions represent an isolated chemical system, and that crystallisation upon cooling follows the expected thermodynamic phase relations. Thus the final composition in the centre of the inclusion consists of a small-scale mixture of PdGa and Pd5Ga3 evolved out of a solid-solid decomposition of Pd5Ga4.

Trans-ancestral studies fine map the SLE-susceptibility locus TNFSF4.

PubMed

Manku, Harinder; Langefeld, Carl D; Guerra, Sandra G; Malik, Talat H; Alarcon-Riquelme, Marta; Anaya, Juan-Manuel; Bae, Sang-Cheol; Boackle, Susan A; Brown, Elizabeth E; Criswell, Lindsey A; Freedman, Barry I; Gaffney, Patrick M; Gregersen, Peter A; Guthridge, Joel M; Han, Sang-Hoon; Harley, John B; Jacob, Chaim O; James, Judith A; Kamen, Diane L; Kaufman, Kenneth M; Kelly, Jennifer A; Martin, Javier; Merrill, Joan T; Moser, Kathy L; Niewold, Timothy B; Park, So-Yeon; Pons-Estel, Bernardo A; Sawalha, Amr H; Scofield, R Hal; Shen, Nan; Stevens, Anne M; Sun, Celi; Gilkeson, Gary S; Edberg, Jeff C; Kimberly, Robert P; Nath, Swapan K; Tsao, Betty P; Vyse, Tim J

2013-01-01

We previously established an 80 kb haplotype upstream of TNFSF4 as a susceptibility locus in the autoimmune disease SLE. SLE-associated alleles at this locus are associated with inflammatory disorders, including atherosclerosis and ischaemic stroke. In Europeans, the TNFSF4 causal variants have remained elusive due to strong linkage disequilibrium exhibited by alleles spanning the region. Using a trans-ancestral approach to fine-map the locus, utilising 17,900 SLE and control subjects including Amerindian/Hispanics (1348 cases, 717 controls), African-Americans (AA) (1529, 2048) and better powered cohorts of Europeans and East Asians, we find strong association of risk alleles in all ethnicities; the AA association replicates in African-American Gullah (152,122). The best evidence of association comes from two adjacent markers: rs2205960-T (P=1.71 × 10(-34) , OR=1.43[1.26-1.60]) and rs1234317-T (P=1.16 × 10(-28) , OR=1.38[1.24-1.54]). Inference of fine-scale recombination rates for all populations tested finds the 80 kb risk and non-risk haplotypes in all except African-Americans. In this population the decay of recombination equates to an 11 kb risk haplotype, anchored in the 5' region proximal to TNFSF4 and tagged by rs2205960-T after 1000 Genomes phase 1 (v3) imputation. Conditional regression analyses delineate the 5' risk signal to rs2205960-T and the independent non-risk signal to rs1234314-C. Our case-only and SLE-control cohorts demonstrate robust association of rs2205960-T with autoantibody production. The rs2205960-T is predicted to form part of a decameric motif which binds NF-κBp65 with increased affinity compared to rs2205960-G. ChIP-seq data also indicate NF-κB interaction with the DNA sequence at this position in LCL cells. Our research suggests association of rs2205960-T with SLE across multiple groups and an independent non-risk signal at rs1234314-C. rs2205960-T is associated with autoantibody production and lymphopenia. Our data confirm a global signal at TNFSF4 and a role for the expressed product at multiple stages of lymphocyte dysregulation during SLE pathogenesis. We confirm the validity of trans-ancestral mapping in a complex trait.

Trans-Ancestral Studies Fine Map the SLE-Susceptibility Locus TNFSF4

PubMed Central

Manku, Harinder; Langefeld, Carl D.; Guerra, Sandra G.; Malik, Talat H.; Alarcon-Riquelme, Marta; Anaya, Juan-Manuel; Bae, Sang-Cheol; Boackle, Susan A.; Brown, Elizabeth E.; Criswell, Lindsey A.; Freedman, Barry I.; Gaffney, Patrick M.; Gregersen, Peter A.; Guthridge, Joel M.; Han, Sang-Hoon; Harley, John B.; Jacob, Chaim O.; James, Judith A.; Kamen, Diane L.; Kaufman, Kenneth M.; Kelly, Jennifer A.; Martin, Javier; Merrill, Joan T.; Moser, Kathy L.; Niewold, Timothy B.; Park, So-Yeon; Pons-Estel, Bernardo A.; Sawalha, Amr H.; Scofield, R. Hal; Shen, Nan; Stevens, Anne M.; Sun, Celi; Gilkeson, Gary S.; Edberg, Jeff C.; Kimberly, Robert P.; Nath, Swapan K.; Tsao, Betty P.; Vyse, Tim J.

2013-01-01

We previously established an 80 kb haplotype upstream of TNFSF4 as a susceptibility locus in the autoimmune disease SLE. SLE-associated alleles at this locus are associated with inflammatory disorders, including atherosclerosis and ischaemic stroke. In Europeans, the TNFSF4 causal variants have remained elusive due to strong linkage disequilibrium exhibited by alleles spanning the region. Using a trans-ancestral approach to fine-map the locus, utilising 17,900 SLE and control subjects including Amerindian/Hispanics (1348 cases, 717 controls), African-Americans (AA) (1529, 2048) and better powered cohorts of Europeans and East Asians, we find strong association of risk alleles in all ethnicities; the AA association replicates in African-American Gullah (152,122). The best evidence of association comes from two adjacent markers: rs2205960-T (P = 1.71×10−34, OR = 1.43[1.26–1.60]) and rs1234317-T (P = 1.16×10−28, OR = 1.38[1.24–1.54]). Inference of fine-scale recombination rates for all populations tested finds the 80 kb risk and non-risk haplotypes in all except African-Americans. In this population the decay of recombination equates to an 11 kb risk haplotype, anchored in the 5′ region proximal to TNFSF4 and tagged by rs2205960-T after 1000 Genomes phase 1 (v3) imputation. Conditional regression analyses delineate the 5′ risk signal to rs2205960-T and the independent non-risk signal to rs1234314-C. Our case-only and SLE-control cohorts demonstrate robust association of rs2205960-T with autoantibody production. The rs2205960-T is predicted to form part of a decameric motif which binds NF-κBp65 with increased affinity compared to rs2205960-G. ChIP-seq data also indicate NF-κB interaction with the DNA sequence at this position in LCL cells. Our research suggests association of rs2205960-T with SLE across multiple groups and an independent non-risk signal at rs1234314-C. rs2205960-T is associated with autoantibody production and lymphopenia. Our data confirm a global signal at TNFSF4 and a role for the expressed product at multiple stages of lymphocyte dysregulation during SLE pathogenesis. We confirm the validity of trans-ancestral mapping in a complex trait. PMID:23874208

Application of a predator-prey overlap metric to determine the impact of sub-grid scale feeding dynamics on ecosystem productivity

NASA Astrophysics Data System (ADS)

Greer, A. T.; Woodson, C. B.

2016-02-01

Because of the complexity and extremely large size of marine ecosystems, research attention has a strong focus on modelling the system through space and time to elucidate processes driving ecosystem state. One of the major weaknesses of current modelling approaches is the reliance on a particular grid cell size (usually 10's of km in the horizontal & water column mean) to capture the relevant processes, even though empirical research has shown that marine systems are highly structured on fine scales, and this structure can persist over relatively long time scales (days to weeks). Fine-scale features can have a strong influence on the predator-prey interactions driving trophic transfer. Here we apply a statistic, the AB ratio, used to quantify increased predator production due to predator-prey overlap on fine scales in a manner that is computationally feasible for larger scale models. We calculated the AB ratio for predator-prey distributions throughout the scientific literature, as well as for data obtained with a towed plankton imaging system, demonstrating that averaging across a typical model grid cell neglects the fine-scale predator-prey overlap that is an essential component of ecosystem productivity. Organisms from a range of trophic levels and oceanographic regions tended to overlap with their prey both in the horizontal and vertical dimensions. When predator swimming over a diel cycle was incorporated, the amount of production indicated by the AB ratio increased substantially. For the plankton image data, the AB ratio was higher with increasing sampling resolution, especially when prey were highly aggregated. We recommend that ecosystem models incorporate more fine-scale information both to more accurately capture trophic transfer processes and to capitalize on the increasing sampling resolution and data volume from empirical studies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Adrian; Zhang, Yunfan; Parsons, Aaron R., E-mail: acliu@berkeley.edu

Intensity mapping is a promising technique for surveying the large-scale structure of our universe from z  = 0 to z  ∼ 150, using the brightness temperature field of spectral lines to directly observe previously unexplored portions of our cosmic timeline. Examples of targeted lines include the 21 cm hyperfine transition of neutral hydrogen, rotational lines of carbon monoxide, and fine-structure lines of singly ionized carbon. Recent efforts have focused on detections of the power spectrum of spatial fluctuations, but have been hindered by systematics such as foreground contamination. This has motivated the decomposition of data into Fourier modes perpendicular and parallel tomore » the line of sight, which has been shown to be a particularly powerful way to diagnose systematics. However, such a method is well-defined only in the limit of a narrow-field, flat-sky approximation. This limits the sensitivity of intensity mapping experiments, as it means that wide surveys must be separately analyzed as a patchwork of smaller fields. In this paper, we develop a framework for analyzing intensity mapping data in a spherical Fourier–Bessel basis, which incorporates curved sky effects without difficulty. We use our framework to generalize a number of techniques in intensity mapping data analysis from the flat sky to the curved sky. These include visibility-based estimators for the power spectrum, treatments of interloper lines, and the “foreground wedge” signature of spectrally smooth foregrounds.« less

Application of PALSAR-2 Remote Sensing Data for Landslide Hazard Mapping in Kelantan River Basin, Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Beiranvand Pour, Amin; Hashim, Mazlan

2016-06-01

Yearly, several landslides ensued during heavy monsoons rainfall in Kelantan river basin, peninsular Malaysia, which are obviously connected to geological structures and topographical features of the region. In this study, the recently launched Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) onboard the Advanced Land Observing Satellite-2 (ALOS-2), remote sensing data were used to map geological structural and topographical features in the Kelantan river basin for identification of high potential risk and susceptible zones for landslides. Adaptive Local Sigma filter was selected and applied to accomplish speckle reduction and preserving both edges and features in PALSAR-2 fine mode observation images. Different polarization images were integrated to enhance geological structures. Additionally, directional filters were applied to the PALSAR-2 Local Sigma resultant image for edge enhancement and detailed identification of linear features. Several faults, drainage patterns and lithological contact layers were identified at regional scale. In order to assess the results, fieldwork and GPS survey were conducted in the landslide affected zones in the Kelantan river basin. Results demonstrate the most of the landslides were associated with N-S, NNW-SSE and NE-SW trending faults, angulated drainage pattern and metamorphic and Quaternary units. Consequently, structural and topographical geology maps were produced for Kelantan river basin using PALSAR-2 data, which could be broadly applicable for landslide hazard mapping.

Development of a remote sensing network for time-sensitive detection of fine scale damage to transportation infrastructure : [final report].

DOT National Transportation Integrated Search

2015-09-23

This research project aimed to develop a remote sensing system capable of rapidly identifying fine-scale damage to critical transportation infrastructure following hazard events. Such a system must be pre-planned for rapid deployment, automate proces...

Fine-structure mapping of the firA gene, a locus involved in the phenotypic expression of rifampin resistance in Escherichia.

PubMed

Lathe, R

1977-09-01

The firA (Ts)200 mutation not only eliminates the resistance to rifampin of certain genetically resistant strains, but, moreover, renders ribonucleic acid synthesis thermolabile. The firA gene has been mapped by P1 tranduction and is located extremely close to the structural gene for deoxyribonucleic acid polymerase III at 4 min on the Escherichia coli linkage map.

MROrchestrator: A Fine-Grained Resource Orchestration Framework for MapReduce Clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharma, Bikash; Prabhakar, Ramya; Kandemir, Mahmut

2012-01-01

Efficient resource management in data centers and clouds running large distributed data processing frameworks like MapReduce is crucial for enhancing the performance of hosted applications and boosting resource utilization. However, existing resource scheduling schemes in Hadoop MapReduce allocate resources at the granularity of fixed-size, static portions of nodes, called slots. In this work, we show that MapReduce jobs have widely varying demands for multiple resources, making the static and fixed-size slot-level resource allocation a poor choice both from the performance and resource utilization standpoints. Furthermore, lack of co-ordination in the management of mul- tiple resources across nodes prevents dynamic slotmore » reconfigura- tion, and leads to resource contention. Motivated by this, we propose MROrchestrator, a MapReduce resource Orchestrator framework, which can dynamically identify resource bottlenecks, and resolve them through fine-grained, co-ordinated, and on- demand resource allocations. We have implemented MROrches- trator on two 24-node native and virtualized Hadoop clusters. Experimental results with a suite of representative MapReduce benchmarks demonstrate up to 38% reduction in job completion times, and up to 25% increase in resource utilization. We further show how popular resource managers like NGM and Mesos when augmented with MROrchestrator can hike up their performance.« less

Altered fish community and feeding behaviour in close proximity to boat moorings in an urban estuary.

PubMed

Lanham, Brendan S; Vergés, Adriana; Hedge, Luke H; Johnston, Emma L; Poore, Alistair G B

2018-04-01

Coastal urbanization has led to large-scale transformation of estuaries, with artificial structures now commonplace. Boat moorings are known to reduce seagrass cover, but little is known about their effect on fish communities. We used underwater video to quantify abundance, diversity, composition and feeding behaviour of fish assemblages on two scales: with increasing distance from moorings on fine scales, and among locations where moorings were present or absent. Fish were less abundant in close proximity to boat moorings, and the species composition varied on fine scales, leading to lower predation pressure near moorings. There was no relationship at the location with seagrass. On larger scales, we detected no differences in abundance or community composition among locations where moorings were present or absent. These findings show a clear impact of moorings on fish and highlight the importance of fine-scale assessments over location-scale comparisons in the detection of the effects of artificial structures. Copyright © 2018 Elsevier Ltd. All rights reserved.

A fine structure genomic map of the region of 12q13 containing SAS and CDK4

DOE Office of Scientific and Technical Information (OSTI.GOV)

Linder, C.Y.; Elkahloun, A.G.; Su, Y.A.

1994-09-01

We have recently adapted a method, originally described by Rackwitz, to the rapid restriction mapping of multiple cosmid DNA samples. Linearization of the cosmids at the lambda cohesive site using lambda terminase is followed by partial digestion with selected restriction enzymes and hybridization to oligonucleotides specific for the right or left hand termini. Partial digestions are performed in a microtiter plate thus allowing up to 12 cosmid clones to be digested with one restriction enzyme. We have applied this rapid restriction mapping method to cosmids derived from a region of chromosome 12q13 that has recently been shown to be amplifiedmore » in a variety of cancers including malignant fibrous histiocytoma, fibrosarcoma, liposarcoma, osteosarcoma and brain tumors. A small segment of this amplification unit containing three genes, SAS (a membrane protein), CDK4 (a cyclin dependent kinase) and OS-9 (a recently described cDNA) has been analyzed with the system described above. This fine structure genomic map will be useful for completing the expression map of this region as well as characterizing its pattern of amplification in tumor specimens.« less

Scanning electron microscopy/energy dispersive spectrometry fixedbeam or overscan x-ray microanalysis of particles can miss the real structure: x-ray spectrum image mapping reveals the true nature

NASA Astrophysics Data System (ADS)

Newbury, Dale E.; Ritchie, Nicholas W. M.

2013-05-01

The typical strategy for analysis of a microscopic particle by scanning electron microscopy/energy dispersive spectrometry x-ray microanalysis (SEM/EDS) is to use a fixed beam placed at the particle center or to continuously overscan to gather an "averaged" x-ray spectrum. While useful, such strategies inevitably concede any possibility of recognizing microstructure within the particle, and such fine scale structure is often critical for understanding the origins, behavior, and fate of particles. Elemental imaging by x-ray mapping has been a mainstay of SEM/EDS analytical practice for many years, but the time penalty associated with mapping with older EDS technology has discouraged its general use and reserved it more for detailed studies that justified the time investment. The emergence of the high throughput, high peak stability silicon drift detector (SDD-EDS) has enabled a more effective particle mapping strategy: "flash" x-ray spectrum image maps can now be recorded in seconds that capture the spatial distribution of major (concentration, C > 0.1 mass fraction) and minor (0.01 <= C <= 0.1) constituents. New SEM/SDD-EDS instrument configurations feature multiple SDDs that view the specimen from widely spaced azimuthal angles. Multiple, simultaneous measurements from different angles enable x-ray spectrometry and mapping that can minimize the strong geometric effects of particles. The NIST DTSA-II software engine is a powerful aid for quantitatively analyzing EDS spectra measured individually as well as for mapping information (available free for Java platforms at: http://www.cstl.nist.gov/div837/837.02/epq/dtsa2/index.html).

Deficiency mapping of quantitative trait loci affecting longevity in Drosophila melanogaster.

PubMed Central

Pasyukova, E G; Vieira, C; Mackay, T F

2000-01-01

In a previous study, sex-specific quantitative trait loci (QTL) affecting adult longevity were mapped by linkage to polymorphic roo transposable element markers, in a population of recombinant inbred lines derived from the Oregon and 2b strains of Drosophila melanogaster. Two life span QTL were each located on chromosomes 2 and 3, within sections 33E-46C and 65D-85F on the cytological map, respectively. We used quantitative deficiency complementation mapping to further resolve the locations of life span QTL within these regions. The Oregon and 2b strains were each crossed to 47 deficiencies spanning cytological regions 32F-44E and 64C-76B, and quantitative failure of the QTL alleles to complement the deficiencies was assessed. We initially detected a minimum of five and four QTL in the chromosome 2 and 3 regions, respectively, illustrating that multiple linked factors contribute to each QTL detected by recombination mapping. The QTL locations inferred from deficiency mapping did not generally correspond to those of candidate genes affecting oxidative and thermal stress or glucose metabolism. The chromosome 2 QTL in the 35B-E region was further resolved to a minimum of three tightly linked QTL, containing six genetically defined loci, 24 genes, and predicted genes that are positional candidates corresponding to life span QTL. This region was also associated with quantitative variation in life span in a sample of 10 genotypes collected from nature. Quantitative deficiency complementation is an efficient method for fine-scale QTL mapping in Drosophila and can be further improved by controlling the background genotype of the strains to be tested. PMID:11063689

Predicting and mapping soil available water capacity in Korea.

PubMed

Hong, Suk Young; Minasny, Budiman; Han, Kyung Hwa; Kim, Yihyun; Lee, Kyungdo

2013-01-01

The knowledge on the spatial distribution of soil available water capacity at a regional or national extent is essential, as soil water capacity is a component of the water and energy balances in the terrestrial ecosystem. It controls the evapotranspiration rate, and has a major impact on climate. This paper demonstrates a protocol for mapping soil available water capacity in South Korea at a fine scale using data available from surveys. The procedures combined digital soil mapping technology with the available soil map of 1:25,000. We used the modal profile data from the Taxonomical Classification of Korean Soils. The data consist of profile description along with physical and chemical analysis for the modal profiles of the 380 soil series. However not all soil samples have measured bulk density and water content at -10 and -1500 kPa. Thus they need to be predicted using pedotransfer functions. Furthermore, water content at -10 kPa was measured using ground samples. Thus a correction factor is derived to take into account the effect of bulk density. Results showed that Andisols has the highest mean water storage capacity, followed by Entisols and Inceptisols which have loamy texture. The lowest water retention is Entisols which are dominated by sandy materials. Profile available water capacity to a depth of 1 m was calculated and mapped for Korea. The western part of the country shows higher available water capacity than the eastern part which is mountainous and has shallower soils. The highest water storage capacity soils are the Ultisols and Alfisols (mean of 206 and 205 mm, respectively). Validation of the maps showed promising results. The map produced can be used as an indication of soil physical quality of Korean soils.

Maps and grids of hydrogeologic information created from standardized water-well drillers’ records of the glaciated United States

USGS Publications Warehouse

Bayless, E. Randall; Arihood, Leslie D.; Reeves, Howard W.; Sperl, Benjamin J.S.; Qi, Sharon L.; Stipe, Valerie E.; Bunch, Aubrey R.

2017-01-18

As part of the National Water Availability and Use Program established by the U.S. Geological Survey (USGS) in 2005, this study took advantage of about 14 million records from State-managed collections of water-well drillers’ records and created a database of hydrogeologic properties for the glaciated United States. The water-well drillers’ records were standardized to be relatively complete and error-free and to provide consistent variables and naming conventions that span all State boundaries.Maps and geospatial grids were developed for (1) total thickness of glacial deposits, (2) total thickness of coarse-grained deposits, (3) specific-capacity based transmissivity and hydraulic conductivity, and (4) texture-based estimated equivalent horizontal and vertical hydraulic conductivity and transmissivity. The information included in these maps and grids is required for most assessments of groundwater availability, in addition to having applications to studies of groundwater flow and transport. The texture-based estimated equivalent horizontal and vertical hydraulic conductivity and transmissivity were based on an assumed range of hydraulic conductivity values for coarse- and fine-grained deposits and should only be used with complete awareness of the methods used to create them. However, the maps and grids of texture-based estimated equivalent hydraulic conductivity and transmissivity may be useful for application to areas where a range of measured values is available for re-scaling.Maps of hydrogeologic information for some States are presented as examples in this report but maps and grids for all States are available electronically at the project Web site (USGS Glacial Aquifer System Groundwater Availability Study, http://mi.water.usgs.gov/projects/WaterSmart/Map-SIR2015-5105.html) and the Science Base Web site, https://www.sciencebase.gov/catalog/item/58756c7ee4b0a829a3276352.

Molecular mapping and breeding with microsatellite markers.

PubMed

Lightfoot, David A; Iqbal, Muhammad J

2013-01-01

In genetics databases for crop plant species across the world, there are thousands of mapped loci that underlie quantitative traits, oligogenic traits, and simple traits recognized by association mapping in populations. The number of loci will increase as new phenotypes are measured in more diverse genotypes and genetic maps based on saturating numbers of markers are developed. A period of locus reevaluation will decrease the number of important loci as those underlying mega-environmental effects are recognized. A second wave of reevaluation of loci will follow from developmental series analysis, especially for harvest traits like seed yield and composition. Breeding methods to properly use the accurate maps of QTL are being developed. New methods to map, fine map, and isolate the genes underlying the loci will be critical to future advances in crop biotechnology. Microsatellite markers are the most useful tool for breeders. They are codominant, abundant in all genomes, highly polymorphic so useful in many populations, and both economical and technically easy to use. The selective genotyping approaches, including genotype ranking (indexing) based on partial phenotype data combined with favorable allele data and bulked segregation event (segregant) analysis (BSA), will be increasingly important uses for microsatellites. Examples of the methods for developing and using microsatellites derived from genomic sequences are presented for monogenic, oligogenic, and polygenic traits. Examples of successful mapping, fine mapping, and gene isolation are given. When combined with high-throughput methods for genotyping and a genome sequence, the use of association mapping with microsatellite markers will provide critical advances in the analysis of crop traits.

FINE SCALE AIR QUALITY MODELING USING DISPERSION AND CMAQ MODELING APPROACHES: AN EXAMPLE APPLICATION IN WILMINGTON, DE

EPA Science Inventory

Characterization of spatial variability of air pollutants in an urban setting at fine scales is critical for improved air toxics exposure assessments, for model evaluation studies and also for air quality regulatory applications. For this study, we investigate an approach that su...

CFD MODELING OF FINE SCALE FLOW AND TRANSPORT IN THE HOUSTON METROPOLITAN AREA, TEXAS

EPA Science Inventory

Fine scale modeling of flows and air quality in Houston, Texas is being performed; the use of computational fluid dynamics (CFD) modeling is being applied to investigate the influence of morphologic structures on the within-grid transport and dispersion of sources in grid models ...

Fine scale mapping of the 17q22 breast cancer locus using dense SNPs, genotyped within the Collaborative Oncological Gene-Environment Study (COGs)

PubMed Central

Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud; Kar, Siddhartha; Nord, Silje; Moradi Marjaneh, Mahdi; Soucy, Penny; Michailidou, Kyriaki; Ghoussaini, Maya; Fues Wahl, Hanna; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Alonso, M. Rosario; Andrulis, Irene L.; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W.; Benitez, Javier; Bogdanova, Natalia V.; Bojesen, Stig E.; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Choi, Ji-Yeob; Conroy, Don M.; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Easton, Douglas F.; Fasching, Peter A.; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G.; Goldberg, Mark S.; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A.; Hallberg, Emily; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L.; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kang, Daehee; Khan, Sofia; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Lambrechts, Diether; Le Marchand, Loic; Lee, Soo Chin; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Matsuo, Keitaro; Mayes, Rebecca; McKay, James; Meindl, Alfons; Milne, Roger L.; Muir, Kenneth; Neuhausen, Susan L.; Nevanlinna, Heli; Olswold, Curtis; Orr, Nick; Peterlongo, Paolo; Pita, Guillermo; Pylkäs, Katri; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J.; Schmidt, Marjanka K.; Schmutzler, Rita K.; Seynaeve, Caroline; Shah, Mitul; Shen, Chen-Yang; Shu, Xiao-Ou; Southey, Melissa C.; Stram, Daniel O.; Surowy, Harald; Swerdlow, Anthony; Teo, Soo H.; Tessier, Daniel C.; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine M.; Vincent, Daniel; Winqvist, Robert; Wu, Anna H.; Wu, Pei-Ei; Yip, Cheng Har; Zheng, Wei; Pharoah, Paul D. P.; Hall, Per; Edwards, Stacey L.; Simard, Jacques; French, Juliet D.; Chenevix-Trench, Georgia; Dunning, Alison M.

2016-01-01

Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90–0.94; P = 8.96 × 10−15)) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10−09, r2 = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10−11, r2 = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus. PMID:27600471

Mechanisms of Transmission Ratio Distortion at Hybrid Sterility Loci Within and Between Mimulus Species

PubMed Central

Kerwin, Rachel E.; Sweigart, Andrea L.

2017-01-01

Hybrid incompatibilities are a common correlate of genomic divergence and a potentially important contributor to reproductive isolation. However, we do not yet have a detailed understanding of how hybrid incompatibility loci function and evolve within their native species, or why they are dysfunctional in hybrids. Here, we explore these issues for a well-studied, two-locus hybrid incompatibility between hybrid male sterility 1 (hms1) and hybrid male sterility 2 (hms2) in the closely related yellow monkeyflower species Mimulus guttatus and M. nasutus. By performing reciprocal backcrosses with introgression lines (ILs), we find evidence for gametic expression of the hms1-hms2 incompatibility. Surprisingly, however, hybrid transmission ratios at hms1 do not reflect this incompatibility, suggesting that additional mechanisms counteract the effects of gametic sterility. Indeed, our backcross experiment shows hybrid transmission bias toward M. guttatus through both pollen and ovules, an effect that is particularly strong when hms2 is homozygous for M. nasutus alleles. In contrast, we find little evidence for hms1 transmission bias in crosses within M. guttatus, providing no indication of selfish evolution at this locus. Although we do not yet have sufficient genetic resolution to determine if hybrid sterility and transmission ratio distortion (TRD) map to the same loci, our preliminary fine-mapping uncovers a genetically independent hybrid lethality system involving at least two loci linked to hms1. This fine-scale dissection of TRD at hms1 and hms2 provides insight into genomic differentiation between closely related Mimulus species and reveals multiple mechanisms of hybrid dysfunction. PMID:28935753

Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species.

PubMed

Rödder, Dennis; Nekum, Sven; Cord, Anna F; Engler, Jan O

2016-07-01

Climate change and anthropogenic habitat fragmentation are considered major threats for global biodiversity. As a direct consequence, connectivity is increasingly disrupted in many species, which might have serious consequences that could ultimately lead to the extinction of populations. Although a large number of reserves and conservation sites are designated and protected by law, potential habitats acting as inter-population connectivity corridors are, however, mostly ignored in the common practice of environmental planning. In most cases, this is mainly caused by a lack of quantitative measures of functional connectivity available for the planning process. In this study, we highlight the use of fine-scale potential connectivity models (PCMs) derived from multispectral satellite data for the quantification of spatially explicit habitat corridors for matrix-sensitive species of conservation concern. This framework couples a species distribution model with a connectivity model in a two-step framework, where suitability maps from step 1 are transformed into maps of landscape resistance in step 2 filtered by fragmentation thresholds. We illustrate the approach using the sand lizard (Lacerta agilis L.) in the metropolitan area of Cologne, Germany, as a case study. Our model proved to be well suited to identify connected as well as completely isolated populations within the study area. Furthermore, due to its fine resolution, the PCM was also able to detect small linear structures known to be important for sand lizards' inter-population connectivity such as railroad embankments. We discuss the applicability and possible implementation of PCMs to overcome shortcomings in the common practice of environmental impact assessments.

Mechanisms of Transmission Ratio Distortion at Hybrid Sterility Loci Within and Between Mimulus Species.

PubMed

Kerwin, Rachel E; Sweigart, Andrea L

2017-11-06

Hybrid incompatibilities are a common correlate of genomic divergence and a potentially important contributor to reproductive isolation. However, we do not yet have a detailed understanding of how hybrid incompatibility loci function and evolve within their native species, or why they are dysfunctional in hybrids. Here, we explore these issues for a well-studied, two-locus hybrid incompatibility between hybrid male sterility 1 ( hms1 ) and hybrid male sterility 2 ( hms2 ) in the closely related yellow monkeyflower species Mimulus guttatus and M. nasutus By performing reciprocal backcrosses with introgression lines (ILs), we find evidence for gametic expression of the hms1-hms2 incompatibility. Surprisingly, however, hybrid transmission ratios at hms1 do not reflect this incompatibility, suggesting that additional mechanisms counteract the effects of gametic sterility. Indeed, our backcross experiment shows hybrid transmission bias toward M. guttatus through both pollen and ovules, an effect that is particularly strong when hms2 is homozygous for M. nasutus alleles. In contrast, we find little evidence for hms1 transmission bias in crosses within M. guttatus , providing no indication of selfish evolution at this locus. Although we do not yet have sufficient genetic resolution to determine if hybrid sterility and transmission ratio distortion (TRD) map to the same loci, our preliminary fine-mapping uncovers a genetically independent hybrid lethality system involving at least two loci linked to hms1 This fine-scale dissection of TRD at hms1 and hms2 provides insight into genomic differentiation between closely related Mimulus species and reveals multiple mechanisms of hybrid dysfunction. Copyright © 2017 Kerwin and Sweigart.

Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species

NASA Astrophysics Data System (ADS)

Rödder, Dennis; Nekum, Sven; Cord, Anna F.; Engler, Jan O.

2016-07-01

Climate change and anthropogenic habitat fragmentation are considered major threats for global biodiversity. As a direct consequence, connectivity is increasingly disrupted in many species, which might have serious consequences that could ultimately lead to the extinction of populations. Although a large number of reserves and conservation sites are designated and protected by law, potential habitats acting as inter-population connectivity corridors are, however, mostly ignored in the common practice of environmental planning. In most cases, this is mainly caused by a lack of quantitative measures of functional connectivity available for the planning process. In this study, we highlight the use of fine-scale potential connectivity models (PCMs) derived from multispectral satellite data for the quantification of spatially explicit habitat corridors for matrix-sensitive species of conservation concern. This framework couples a species distribution model with a connectivity model in a two-step framework, where suitability maps from step 1 are transformed into maps of landscape resistance in step 2 filtered by fragmentation thresholds. We illustrate the approach using the sand lizard ( Lacerta agilis L.) in the metropolitan area of Cologne, Germany, as a case study. Our model proved to be well suited to identify connected as well as completely isolated populations within the study area. Furthermore, due to its fine resolution, the PCM was also able to detect small linear structures known to be important for sand lizards' inter-population connectivity such as railroad embankments. We discuss the applicability and possible implementation of PCMs to overcome shortcomings in the common practice of environmental impact assessments.

Fine scale mapping of the 17q22 breast cancer locus using dense SNPs, genotyped within the Collaborative Oncological Gene-Environment Study (COGs).

PubMed

Darabi, Hatef; Beesley, Jonathan; Droit, Arnaud; Kar, Siddhartha; Nord, Silje; Moradi Marjaneh, Mahdi; Soucy, Penny; Michailidou, Kyriaki; Ghoussaini, Maya; Fues Wahl, Hanna; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Alonso, M Rosario; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Beckmann, Matthias W; Benitez, Javier; Bogdanova, Natalia V; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Brüning, Thomas; Burwinkel, Barbara; Chang-Claude, Jenny; Choi, Ji-Yeob; Conroy, Don M; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Devilee, Peter; Dörk, Thilo; Easton, Douglas F; Fasching, Peter A; Figueroa, Jonine; Fletcher, Olivia; Flyger, Henrik; Galle, Eva; García-Closas, Montserrat; Giles, Graham G; Goldberg, Mark S; González-Neira, Anna; Guénel, Pascal; Haiman, Christopher A; Hallberg, Emily; Hamann, Ute; Hartman, Mikael; Hollestelle, Antoinette; Hopper, John L; Ito, Hidemi; Jakubowska, Anna; Johnson, Nichola; Kang, Daehee; Khan, Sofia; Kosma, Veli-Matti; Kriege, Mieke; Kristensen, Vessela; Lambrechts, Diether; Le Marchand, Loic; Lee, Soo Chin; Lindblom, Annika; Lophatananon, Artitaya; Lubinski, Jan; Mannermaa, Arto; Manoukian, Siranoush; Margolin, Sara; Matsuo, Keitaro; Mayes, Rebecca; McKay, James; Meindl, Alfons; Milne, Roger L; Muir, Kenneth; Neuhausen, Susan L; Nevanlinna, Heli; Olswold, Curtis; Orr, Nick; Peterlongo, Paolo; Pita, Guillermo; Pylkäs, Katri; Rudolph, Anja; Sangrajrang, Suleeporn; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Seynaeve, Caroline; Shah, Mitul; Shen, Chen-Yang; Shu, Xiao-Ou; Southey, Melissa C; Stram, Daniel O; Surowy, Harald; Swerdlow, Anthony; Teo, Soo H; Tessier, Daniel C; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine M; Vincent, Daniel; Winqvist, Robert; Wu, Anna H; Wu, Pei-Ei; Yip, Cheng Har; Zheng, Wei; Pharoah, Paul D P; Hall, Per; Edwards, Stacey L; Simard, Jacques; French, Juliet D; Chenevix-Trench, Georgia; Dunning, Alison M

2016-09-07

Genome-wide association studies have found SNPs at 17q22 to be associated with breast cancer risk. To identify potential causal variants related to breast cancer risk, we performed a high resolution fine-mapping analysis that involved genotyping 517 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of genotypes for 3,134 SNPs in more than 89,000 participants of European ancestry from the Breast Cancer Association Consortium (BCAC). We identified 28 highly correlated common variants, in a 53 Kb region spanning two introns of the STXBP4 gene, that are strong candidates for driving breast cancer risk (lead SNP rs2787486 (OR = 0.92; CI 0.90-0.94; P = 8.96 × 10(-15))) and are correlated with two previously reported risk-associated variants at this locus, SNPs rs6504950 (OR = 0.94, P = 2.04 × 10(-09), r(2) = 0.73 with lead SNP) and rs1156287 (OR = 0.93, P = 3.41 × 10(-11), r(2) = 0.83 with lead SNP). Analyses indicate only one causal SNP in the region and several enhancer elements targeting STXBP4 are located within the 53 kb association signal. Expression studies in breast tumor tissues found SNP rs2787486 to be associated with increased STXBP4 expression, suggesting this may be a target gene of this locus.

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data

PubMed Central

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-01-01

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification. PMID:28025525

Surrogate based wind farm layout optimization using manifold mapping

NASA Astrophysics Data System (ADS)

Kaja Kamaludeen, Shaafi M.; van Zuijle, Alexander; Bijl, Hester

2016-09-01

High computational cost associated with the high fidelity wake models such as RANS or LES serves as a primary bottleneck to perform a direct high fidelity wind farm layout optimization (WFLO) using accurate CFD based wake models. Therefore, a surrogate based multi-fidelity WFLO methodology (SWFLO) is proposed. The surrogate model is built using an SBO method referred as manifold mapping (MM). As a verification, optimization of spacing between two staggered wind turbines was performed using the proposed surrogate based methodology and the performance was compared with that of direct optimization using high fidelity model. Significant reduction in computational cost was achieved using MM: a maximum computational cost reduction of 65%, while arriving at the same optima as that of direct high fidelity optimization. The similarity between the response of models, the number of mapping points and its position, highly influences the computational efficiency of the proposed method. As a proof of concept, realistic WFLO of a small 7-turbine wind farm is performed using the proposed surrogate based methodology. Two variants of Jensen wake model with different decay coefficients were used as the fine and coarse model. The proposed SWFLO method arrived at the same optima as that of the fine model with very less number of fine model simulations.

Object-Based Paddy Rice Mapping Using HJ-1A/B Data and Temporal Features Extracted from Time Series MODIS NDVI Data.

PubMed

Singha, Mrinal; Wu, Bingfang; Zhang, Miao

2016-12-22

Accurate and timely mapping of paddy rice is vital for food security and environmental sustainability. This study evaluates the utility of temporal features extracted from coarse resolution data for object-based paddy rice classification of fine resolution data. The coarse resolution vegetation index data is first fused with the fine resolution data to generate the time series fine resolution data. Temporal features are extracted from the fused data and added with the multi-spectral data to improve the classification accuracy. Temporal features provided the crop growth information, while multi-spectral data provided the pattern variation of paddy rice. The achieved overall classification accuracy and kappa coefficient were 84.37% and 0.68, respectively. The results indicate that the use of temporal features improved the overall classification accuracy of a single-date multi-spectral image by 18.75% from 65.62% to 84.37%. The minimum sensitivity (MS) of the paddy rice classification has also been improved. The comparison showed that the mapped paddy area was analogous to the agricultural statistics at the district level. This work also highlighted the importance of feature selection to achieve higher classification accuracies. These results demonstrate the potential of the combined use of temporal and spectral features for accurate paddy rice classification.

Fine root dynamics and trace gas fluxes in two lowland tropical forest soils.

Treesearch

WHENDEE L. SILVER; ANDREW W. THOMPSON; MEGAN E . MCGRODDY; RUTH K. VARNER; JADSON D. DIAS; HUDSON SILVA; CRILL PATRICK M.; MICHAEL KELLER

2005-01-01

Fine root dynamics have the potential to contribute significantly to ecosystem-scale biogeochemical cycling, including the production and emission of greenhouse gases. This is particularly true in tropical forests which are often characterized as having large fine root biomass and rapid rates of root production and decomposition. We examined patterns in fine root...

Comparative fine mapping of the Wax 1 (W1) locus in hexaploid wheat.

PubMed

Lu, Ping; Qin, Jinxia; Wang, Guoxin; Wang, Lili; Wang, Zhenzhong; Wu, Qiuhong; Xie, Jingzhong; Liang, Yong; Wang, Yong; Zhang, Deyun; Sun, Qixin; Liu, Zhiyong

2015-08-01

By applying comparative genomics analyses, a high-density genetic linkage map of the Wax 1 ( W1 ) locus was constructed as a framework for map-based cloning. Glaucousness is described as the scattering effect of visible light from wax deposited on the cuticle of plant aerial organs. In wheat, the wax on leaves and stems is mainly controlled by two sets of genes: glaucousness loci (W1 and W2) and non-glaucousness loci (Iw1 and Iw2). Bulked segregant analysis (BSA) and simple sequence repeat (SSR) mapping showed that Wax1 (W1) is located on chromosome arm 2BS between markers Xgwm210 and Xbarc35. By applying comparative genomics analyses, colinearity genomic regions of the W1 locus on wheat 2BS were identified in Brachypodium distachyon chromosome 5, rice chromosome 4 and sorghum chromosome 6, respectively. Four STS markers were developed using the Triticum aestivum cv. Chinese Spring 454 contig sequences and the International Wheat Genome Sequencing Consortium (IWGSC) survey sequences. W1 was mapped into a 0.93 cM genetic interval flanked by markers XWGGC3197 and XWGGC2484, which has synteny with genomic regions of 56.5 kb in Brachypodium, 390 kb in rice and 31.8 kb in sorghum. The fine genetic map can serve as a framework for chromosome landing, physical mapping and map-based cloning of the W1 in wheat.

Identification of rare recombinants leads to tightly linked markers for nematode resistance in peanut

USDA-ARS?s Scientific Manuscript database

Strong host resistance to root-knot nematode (RKN; Meloidogyne arenaria) introgressed from a wild diploid species to cultivated peanut was previously shown to be located on a large chromosomal region of linkage group A09. Little to no recombination in mapping populations has hindered fine mapping o...

Enhanced Resolution Maps of Energetic Neutral Atoms from IBEX

NASA Astrophysics Data System (ADS)

Teodoro, L. A.; Elphic, R. C.; Janzen, P.; Reisenfeld, D.; Wilson, J. T.

2017-12-01

The discovery by the Interstellar Boundary Explorer (IBEX) of a "Ribbon" in the measurements of Energetic Neutral Particles (ENA) was a major surprise that lead to the re-thinking of the Physics underpinning the heliosphere-intergalactic medium boundary dynamics. Several physical models have been proposed and tested in their ability to mimic the IBEX observations. Some of the ENA IBEX's include the following features: 1) The presence of fine structure within the ribbon suggests that the physical properties of it exhibit small-scale spacial structure and possibly rapid small-scale variations. 2) The ribbon is a fairly narrow feature at low energies and broadens with increasing energy;The IBEX detectors were designed to maximize count rate by incorporating wide angular and broad energy acceptance. Thus far, the existing mapping software used by the IBEX Science Operation Center has not been design with the "Ribbon" ( 20o wide) in mind: the current generation of maps are binned in 6o longitude pixels by 6o latitude pixels (so the pixels are all of the same size in angle and are quite "blocky"). Furthermore, the instrumental point spread function has not been deconvolved, making any potential narrow features broader than they are. An improvement in the spatial resolution of the IBEX maps would foster a better understanding of the Ribbon and its substructure, and thus reply to some of the basic and profound questions related to its origin, the nature of the outer boundaries of the our solar system and the surrounding interstellar Galactic medium.Here we report on the application of the Bayesian image reconstruction algorithm "Speedy Pixons" to the ENA data with the aim to sharpen the ENA IBEX maps. A preliminary application allow us to conclude that: The peaks in the count rate do appear to be more enhanced in the reconstruction; The reconstruction is clearly denoised; The "Ribbon" is better defined in the reconstruction. We are currently studying the implications of our preliminary results in the current generation of models. Potentially, our results can also be used in the design and planning of future missions whose aim is to produce higher resolution maps of the interstellar medium (e.g. IMAP).

Sub-micron Raman Mapping of Ultramafic Fault Rock Textures

NASA Astrophysics Data System (ADS)

Tarling, M. S.; Rooney, J. S.; Smith, S. A. F.; Gordon, K. C.

2016-12-01

Deciphering the often complex temporal and microstructural relationships between the serpentine group minerals - antigorite, chrysotile, lizardite and polygonal serpentine - is essential for a proper understanding of the serpentinization process in a range of geodynamic settings. Conventional techniques such as optical microscopy, quantitative XRD and SEM-EDS often fail to correctly identify the four varieties of serpentine. Transmission electron microscopy can be used to successfully identify these minerals, but complex sample preparation and very small sample sizes (1-10's microns) means that microstructural context is difficult to maintain. Building on previous work (Petriglieri et al. 2015, J. Raman Spectrosc.) that introduced a methodology for Raman mapping on thin sections, we present the initial results of large-area and high-resolution (at the optical limit) Raman mapping that allows us to unambiguously distinguish and contextualise the serpentine minerals within their microstructural context. Measurements were performed on flat, SYTON-polished petrographic thin sections using a Witec Raman microscope equipped with a piezoelectric nano-positioning x-y stage. With a laser wavelength of 532 nm and a 100x dry objective, spatial resolution approaching 360 nm, as predicted by the Abbe equation, can readily be achieved. Minerals are primarily discerned by examining the Raman peaks in the high wavenumber spectral range of 3600-3710 cm-1, corresponding to OH-stretching vibrations. To illustrate the technique, Raman maps were acquired on several samples from the Livingstone Fault, a major terrane boundary in New Zealand that is localized in a mélange of ultramafic rocks including harzburgite and serpentinite. The maps highlight fine-scale intergrowths of antigorite, lizardite, chrysotile and related minerals (e.g. brucite, magnetite) at a sub-micron level over large areas (10's of microns to mm scale), features that are inaccessible or not visible using other techniques. In addition, the high-resolution mapping of discrete magnetite-bearing serpentinite slip surfaces has revealed the presence of 10-50 μm patches of nano-crystalline forsterite and enstatite, which may be the result of localized, faulting-induced, serpentinite dehydration.

Inversion of Acoustic and Electromagnetic Recordings for Mapping Current Flow in Lightning Strikes

NASA Astrophysics Data System (ADS)

Anderson, J.; Johnson, J.; Arechiga, R. O.; Thomas, R. J.

2012-12-01

Acoustic recordings can be used to map current-carrying conduits in lightning strikes. Unlike stepped leaders, whose very high frequency (VHF) radio emissions have short (meter-scale) wavelengths and can be located by lightning-mapping arrays, current pulses emit longer (kilometer-scale) waves and cannot be mapped precisely by electromagnetic observations alone. While current pulses are constrained to conductive channels created by stepped leaders, these leaders often branch as they propagate, and most branches fail to carry current. Here, we present a method to use thunder recordings to map current pulses, and we apply it to acoustic and VHF data recorded in 2009 in the Magdalena mountains in central New Mexico, USA. Thunder is produced by rapid heating and expansion of the atmosphere along conductive channels in response to current flow, and therefore can be used to recover the geometry of the current-carrying channel. Toward this goal, we use VHF pulse maps to identify candidate conductive channels where we treat each channel as a superposition of finely-spaced acoustic point sources. We apply ray tracing in variable atmospheric structures to forward model the thunder that our microphone network would record for each candidate channel. Because multiple channels could potentially carry current, a non-linear inversion is performed to determine the acoustic source strength of each channel. For each combination of acoustic source strengths, synthetic thunder is modeled as a superposition of thunder signals produced by each channel, and a power envelope of this stack is then calculated. The inversion iteratively minimizes the misfit between power envelopes of recorded and modeled thunder. Because the atmospheric sound speed structure through which the waves propagate during these events is unknown, we repeat the procedure on many plausible atmospheres to find an optimal fit. We then determine the candidate channel, or channels, that minimizes residuals between synthetic and acoustic recordings. We demonstrate the usefulness of this method on both intracloud and cloud-to-ground strikes, and discuss factors affecting our ability to replicate recorded thunder.

Low incidence of clonality in cold water corals revealed through the novel use of standardized protocol adapted to deep sea sampling

USGS Publications Warehouse

Becheler, Ronan; Cassone, Anne-Laure; Noel, Philippe; Mouchel, Olivier; Morrison, Cheryl L.; Arnaud-Haond, Sophie

2017-01-01

Sampling in the deep sea is a technical challenge, which has hindered the acquisition of robust datasets that are necessary to determine the fine-grained biological patterns and processes that may shape genetic diversity. Estimates of the extent of clonality in deep-sea species, despite the importance of clonality in shaping the local dynamics and evolutionary trajectories, have been largely obscured by such limitations. Cold-water coral reefs along European margins are formed mainly by two reef-building species, Lophelia pertusa and Madrepora oculata. Here we present a fine-grained analysis of the genotypic and genetic composition of reefs occurring in the Bay of Biscay, based on an innovative deep-sea sampling protocol. This strategy was designed to be standardized, random, and allowed the georeferencing of all sampled colonies. Clonal lineages discriminated through their Multi-Locus Genotypes (MLG) at 6–7 microsatellite markers could thus be mapped to assess the level of clonality and the spatial spread of clonal lineages. High values of clonal richness were observed for both species across all sites suggesting a limited occurrence of clonality, which likely originated through fragmentation. Additionally, spatial autocorrelation analysis underlined the possible occurrence of fine-grained genetic structure in several populations of both L. pertusa and M. oculata. The two cold-water coral species examined had contrasting patterns of connectivity among canyons, with among-canyon genetic structuring detected in M. oculata, whereas L. pertusa was panmictic at the canyon scale. This study exemplifies that a standardized, random and georeferenced sampling strategy, while challenging, can be applied in the deep sea, and associated benefits outlined here include improved estimates of fine grained patterns of clonality and dispersal that are comparable across sites and among species.

Evaluating process origins of sand-dominated fluvial stratigraphy

NASA Astrophysics Data System (ADS)

Chamberlin, E.; Hajek, E. A.

2015-12-01

Sand-dominated fluvial stratigraphy is often interpreted as indicating times of relatively slow subsidence because of the assumption that fine sediment (silt and clay) is reworked or bypassed during periods of low accommodation. However, sand-dominated successions may instead represent proximal, coarse-grained reaches of paleo-river basins and/or fluvial systems with a sandy sediment supply. Differentiating between these cases is critical for accurately interpreting mass-extraction profiles, basin-subsidence rates, and paleo-river avulsion and migration behavior from ancient fluvial deposits. We explore the degree to which sand-rich accumulations reflect supply-driven progradation or accommodation-limited reworking, by re-evaluating the Castlegate Sandstone (Utah, USA) and the upper Williams Fork Formation (Colorado, USA) - two Upper Cretaceous sandy fluvial deposits previously interpreted as having formed during periods of relatively low accommodation. Both units comprise amalgamated channel and bar deposits with minor intra-channel and overbank mudstones. To constrain relative reworking, we quantify the preservation of bar deposits in each unit using detailed facies and channel-deposit mapping, and compare bar-deposit preservation to expected preservation statistics generated with object-based models spanning a range of boundary conditions. To estimate the grain-size distribution of paleo-sediment input, we leverage results of experimental work that shows both bed-material deposits and accumulations on the downstream side of bars ("interbar fines") sample suspended and wash loads of active flows. We measure grain-size distributions of bar deposits and interbar fines to reconstruct the relative sandiness of paleo-sediment supplies for both systems. By using these novel approaches to test whether sand-rich fluvial deposits reflect river systems with accommodation-limited reworking and/or particularly sand-rich sediment loads, we can gain insight into large-scale downstream-fining and mass-extraction trends in basins with limited exposure.

Low incidence of clonality in cold water corals revealed through the novel use of a standardized protocol adapted to deep sea sampling

NASA Astrophysics Data System (ADS)

Becheler, Ronan; Cassone, Anne-Laure; Noël, Philippe; Mouchel, Olivier; Morrison, Cheryl L.; Arnaud-Haond, Sophie

2017-11-01

Sampling in the deep sea is a technical challenge, which has hindered the acquisition of robust datasets that are necessary to determine the fine-grained biological patterns and processes that may shape genetic diversity. Estimates of the extent of clonality in deep-sea species, despite the importance of clonality in shaping the local dynamics and evolutionary trajectories, have been largely obscured by such limitations. Cold-water coral reefs along European margins are formed mainly by two reef-building species, Lophelia pertusa and Madrepora oculata. Here we present a fine-grained analysis of the genotypic and genetic composition of reefs occurring in the Bay of Biscay, based on an innovative deep-sea sampling protocol. This strategy was designed to be standardized, random, and allowed the georeferencing of all sampled colonies. Clonal lineages discriminated through their Multi-Locus Genotypes (MLG) at 6-7 microsatellite markers could thus be mapped to assess the level of clonality and the spatial spread of clonal lineages. High values of clonal richness were observed for both species across all sites suggesting a limited occurrence of clonality, which likely originated through fragmentation. Additionally, spatial autocorrelation analysis underlined the possible occurrence of fine-grained genetic structure in several populations of both L. pertusa and M. oculata. The two cold-water coral species examined had contrasting patterns of connectivity among canyons, with among-canyon genetic structuring detected in M. oculata, whereas L. pertusa was panmictic at the canyon scale. This study exemplifies that a standardized, random and georeferenced sampling strategy, while challenging, can be applied in the deep sea, and associated benefits outlined here include improved estimates of fine grained patterns of clonality and dispersal that are comparable across sites and among species.

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Coarse- and fine-scale patterns of distribution and habitat selection places an Amazonian floodplain curassow in double jeopardy.

PubMed

Leite, Gabriel A; Farias, Izeni P; Gonçalves, André L S; Hawes, Joseph E; Peres, Carlos A

2018-01-01

Patterns of habitat selection are influenced by local productivity, resource availability, and predation risk. Species have taken millions of years to hone the macro- and micro-habitats they occupy, but these may now overlap with contemporary human threats within natural species ranges. Wattled Curassow ( Crax globulosa ), an endemic galliform species of the western Amazon, is threatened by both hunting and habitat loss, and is restricted to white-water floodplain forests of major Amazonian rivers. In this study conducted along the Juruá River, Amazonas, Brazil, we quantified the ranging ecology and fine-scale patterns of habitat selection of the species. We estimated the home range size of C. globulosa using conventional VHF telemetry. To estimate patterns of habitat selection, we used geo-locations of day ranges to examine the extent and intensity of use across the floodplain, which were then compared to a high-resolution flood map of the study area. We captured two females and one male, which we monitored for 13 months between September 2014 and September 2015. Average home range size was 283 ha, based on the 95% aLoCoH estimator. Wattled Curassows selected areas of prolonged flood pulses (six to eight months/year) and had a consistent tendency to be near open water, usually in close proximity to river banks and lakes, especially during the dry season. Amazonian floodplains are densely settled, and the small portions of floodplain habitat used by Wattled Curassows are both the most accessible to hunters and most vulnerable to deforestation. As a result, the geographic and ecological distribution of Wattled Curassows places them at much higher extinction risk at multiple spatial scales, highlighting the need to consider habitat preferences within their conservation strategy.

Separating the effects of environment and space on tree species distribution: from population to community.

PubMed

Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang

2013-01-01

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.

Multiple Objects Fusion Tracker Using a Matching Network for Adaptively Represented Instance Pairs

PubMed Central

Oh, Sang-Il; Kang, Hang-Bong

2017-01-01

Multiple-object tracking is affected by various sources of distortion, such as occlusion, illumination variations and motion changes. Overcoming these distortions by tracking on RGB frames, such as shifting, has limitations because of material distortions caused by RGB frames. To overcome these distortions, we propose a multiple-object fusion tracker (MOFT), which uses a combination of 3D point clouds and corresponding RGB frames. The MOFT uses a matching function initialized on large-scale external sequences to determine which candidates in the current frame match with the target object in the previous frame. After conducting tracking on a few frames, the initialized matching function is fine-tuned according to the appearance models of target objects. The fine-tuning process of the matching function is constructed as a structured form with diverse matching function branches. In general multiple object tracking situations, scale variations for a scene occur depending on the distance between the target objects and the sensors. If the target objects in various scales are equally represented with the same strategy, information losses will occur for any representation of the target objects. In this paper, the output map of the convolutional layer obtained from a pre-trained convolutional neural network is used to adaptively represent instances without information loss. In addition, MOFT fuses the tracking results obtained from each modality at the decision level to compensate the tracking failures of each modality using basic belief assignment, rather than fusing modalities by selectively using the features of each modality. Experimental results indicate that the proposed tracker provides state-of-the-art performance considering multiple objects tracking (MOT) and KITTIbenchmarks. PMID:28420194

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology.

PubMed

Tompkins, Adrian M; Ermert, Volker

2013-02-18

The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions.

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology

PubMed Central

2013-01-01

Background The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. Methods A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Results Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. Conclusions A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions. PMID:23419192

Topographic gravity modeling for global Bouguer maps to degree 2160: Validation of spectral and spatial domain forward modeling techniques at the 10 microGal level

NASA Astrophysics Data System (ADS)

Hirt, Christian; Reußner, Elisabeth; Rexer, Moritz; Kuhn, Michael

2016-09-01

Over the past years, spectral techniques have become a standard to model Earth's global gravity field to 10 km scales, with the EGM2008 geopotential model being a prominent example. For some geophysical applications of EGM2008, particularly Bouguer gravity computation with spectral techniques, a topographic potential model of adequate resolution is required. However, current topographic potential models have not yet been successfully validated to degree 2160, and notable discrepancies between spectral modeling and Newtonian (numerical) integration well beyond the 10 mGal level have been reported. Here we accurately compute and validate gravity implied by a degree 2160 model of Earth's topographic masses. Our experiments are based on two key strategies, both of which require advanced computational resources. First, we construct a spectrally complete model of the gravity field which is generated by the degree 2160 Earth topography model. This involves expansion of the topographic potential to the 15th integer power of the topography and modeling of short-scale gravity signals to ultrahigh degree of 21,600, translating into unprecedented fine scales of 1 km. Second, we apply Newtonian integration in the space domain with high spatial resolution to reduce discretization errors. Our numerical study demonstrates excellent agreement (8 μGgal RMS) between gravity from both forward modeling techniques and provides insight into the convergence process associated with spectral modeling of gravity signals at very short scales (few km). As key conclusion, our work successfully validates the spectral domain forward modeling technique for degree 2160 topography and increases the confidence in new high-resolution global Bouguer gravity maps.

Porphyry copper deposit tract definition - A global analysis comparing geologic map scales

USGS Publications Warehouse

Raines, G.L.; Connors, K.A.; Chorlton, L.B.

2007-01-01

Geologic maps are a fundamental data source used to define mineral-resource potential tracts for the first step of a mineral resource assessment. Further, it is generally believed that the scale of the geologic map is a critical consideration. Previously published research has demonstrated that the U.S. Geological Survey porphyry tracts identified for the United States, which are based on 1:500,000-scale geology and larger scale data and published at 1:1,000,000 scale, can be approximated using a more generalized 1:2,500,000-scale geologic map. Comparison of the USGS porphyry tracts for the United States with weights-of-evidence models made using a 1:10,000,000-scale geologic map, which was made for petroleum applications, and a 1:35,000,000-scale geologic map, which was created as context for the distribution of porphyry deposits, demonstrates that, again, the USGS US porphyry tracts identified are similar to tracts defined on features from these small scale maps. In fact, the results using the 1:35,000,000-scale map show a slightly higher correlation with the USGS US tract definition, probably because the conceptual context for this small-scale map is more appropriate for porphyry tract definition than either of the other maps. This finding demonstrates that geologic maps are conceptual maps. The map information shown in each map is selected and generalized for the map to display the concepts deemed important for the map maker's purpose. Some geologic maps of small scale prove to be useful for regional mineral-resource tract definition, despite the decrease in spatial accuracy with decreasing scale. The utility of a particular geologic map for a particular application is critically dependent on the alignment of the intention of the map maker with the application. ?? International Association for Mathematical Geology 2007.

Estimating forest and woodland aboveground biomass using active and passive remote sensing

USGS Publications Warehouse

Wu, Zhuoting; Dye, Dennis G.; Vogel, John M.; Middleton, Barry R.

2016-01-01

Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1. Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States.

Need for Improved Methods to Collect and Present Spatial Epidemiologic Data for Vectorborne Diseases

PubMed Central

Eisen, Rebecca J.

2007-01-01

Improved methods for collection and presentation of spatial epidemiologic data are needed for vectorborne diseases in the United States. Lack of reliable data for probable pathogen exposure site has emerged as a major obstacle to the development of predictive spatial risk models. Although plague case investigations can serve as a model for how to ideally generate needed information, this comprehensive approach is cost-prohibitive for more common and less severe diseases. New methods are urgently needed to determine probable pathogen exposure sites that will yield reliable results while taking into account economic and time constraints of the public health system and attending physicians. Recent data demonstrate the need for a change from use of the county spatial unit for presentation of incidence of vectorborne diseases to more precise ZIP code or census tract scales. Such fine-scale spatial risk patterns can be communicated to the public and medical community through Web-mapping approaches. PMID:18258029

Fine-scale acoustic telemetry reveals unexpected lake trout, Salvelinus namaycush, spawning habitats in northern Lake Huron, North America

USGS Publications Warehouse

Binder, Thomas; Farha, Steve A.; Thompson, Henry T.; Holbrook, Christopher; Bergstedt, Roger A.; Riley, Stephen; Bronte, Charles R.; He, Ji; Krueger, Charles C.

2018-01-01

Previous studies of lake trout, Salvelinus namaycush, spawning habitat in the Laurentian Great Lakes have used time- and labour-intensive survey methods and have focused on areas with historic observations of spawning aggregations and on habitats prejudged by researchers to be suitable for spawning. As an alternative, we used fine-scale acoustic telemetry to locate, describe and compare lake trout spawning habitats. Adult lake trout were implanted with acoustic transmitters and tracked during five consecutive spawning seasons in a 19–27 km2 region of the Drummond Island Refuge, Lake Huron, using the VEMCO Positioning System. Acoustic telemetry revealed discrete areas of aggregation on at least five reefs in the study area, subsequently confirmed by divers to contain deposited eggs. Notably, several identified spawning sites would likely not have been discovered using traditional methods because either they were too small and obscure to stand out on a bathymetric map or because they did not conform to the conceptual model of spawning habitat held by many biologists. Our most unique observation was egg deposition in gravel and rubble substrates located at the base of and beneath overhanging edges of large boulders. Spawning sites typically comprised <10% of the reef area and were used consistently over the 5-year study. Evaluation of habitat selection from the perspective of fish behaviour through use of acoustic transmitters offers potential to expand current conceptual models of critical spawning habitat.

Integrating Climate Change Resilience Features into the Incremental Refinement of an Existing Marine Park

PubMed Central

Beckley, Lynnath E.; Kobryn, Halina T.; Lombard, Amanda T.; Radford, Ben; Heyward, Andrew

2016-01-01

Marine protected area (MPA) designs are likely to require iterative refinement as new knowledge is gained. In particular, there is an increasing need to consider the effects of climate change, especially the ability of ecosystems to resist and/or recover from climate-related disturbances, within the MPA planning process. However, there has been limited research addressing the incorporation of climate change resilience into MPA design. This study used Marxan conservation planning software with fine-scale shallow water (<20 m) bathymetry and habitat maps, models of major benthic communities for deeper water, and comprehensive human use information from Ningaloo Marine Park in Western Australia to identify climate change resilience features to integrate into the incremental refinement of the marine park. The study assessed the representation of benthic habitats within the current marine park zones, identified priority areas of high resilience for inclusion within no-take zones and examined if any iterative refinements to the current no-take zones are necessary. Of the 65 habitat classes, 16 did not meet representation targets within the current no-take zones, most of which were in deeper offshore waters. These deeper areas also demonstrated the highest resilience values and, as such, Marxan outputs suggested minor increases to the current no-take zones in the deeper offshore areas. This work demonstrates that inclusion of fine-scale climate change resilience features within the design process for MPAs is feasible, and can be applied to future marine spatial planning practices globally. PMID:27529820

Using IKONOS Imagery to Estimate Surface Soil Property Variability in Two Alabama Physiographies

NASA Technical Reports Server (NTRS)

Sullivan, Dana; Shaw, Joey; Rickman, Doug

2005-01-01

Knowledge of surface soil properties is used to assess past erosion and predict erodibility, determine nutrient requirements, and assess surface texture for soil survey applications. This study was designed to evaluate high resolution IKONOS multispectral data as a soil- mapping tool. Imagery was acquired over conventionally tilled fields in the Coastal Plain and Tennessee Valley physiographic regions of Alabama. Acquisitions were designed to assess the impact of surface crusting, roughness and tillage on our ability to depict soil property variability. Soils consisted mostly of fine-loamy, kaolinitic, thermic Plinthic Kandiudults at the Coastal Plain site and fine, kaolinitic, thermic Rhodic Paleudults at the Tennessee Valley site. Soils were sampled in 0.20 ha grids to a depth of 15 cm and analyzed for % sand (0.05 - 2 mm), silt (0.002 -0.05 mm), clay (less than 0.002 mm), citrate dithionite extractable iron (Fe(sub d)) and soil organic carbon (SOC). Four methods of evaluating variability in soil attributes were evaluated: 1) kriging of soil attributes, 2) co-kriging with soil attributes and reflectance data, 3) multivariate regression based on the relationship between reflectance and soil properties, and 4) fuzzy c-means clustering of reflectance data. Results indicate that co-kriging with remotely sensed data improved field scale estimates of surface SOC and clay content compared to kriging and regression methods. Fuzzy c-means worked best using RS data acquired over freshly tilled fields, reducing soil property variability within soil zones compared to field scale soil property variability.

HYSPLIT SMOKE/DUST GRAPHICS

Science.gov Websites

HYSPLIT SMOKE/DUST Forecasts 03 06 09 12 15 18 21 24 27 30 33 36 39 42 45 48 Select speed: normal 28 29 30 31 Select Cycle: 06Z 12Z Select Field: Smoke Fine Particulate matter (ug/m3) Dust Fine Particulate matter (ug/m3) Select vertical level: Surface Column Average Get map NAQFC NCEP Home NOAA Home

a Model Study of Small-Scale World Map Generalization

NASA Astrophysics Data System (ADS)

Cheng, Y.; Yin, Y.; Li, C. M.; Wu, W.; Guo, P. P.; Ma, X. L.; Hu, F. M.

2018-04-01

With the globalization and rapid development every filed is taking an increasing interest in physical geography and human economics. There is a surging demand for small scale world map in large formats all over the world. Further study of automated mapping technology, especially the realization of small scale production on a large scale global map, is the key of the cartographic field need to solve. In light of this, this paper adopts the improved model (with the map and data separated) in the field of the mapmaking generalization, which can separate geographic data from mapping data from maps, mainly including cross-platform symbols and automatic map-making knowledge engine. With respect to the cross-platform symbol library, the symbol and the physical symbol in the geographic information are configured at all scale levels. With respect to automatic map-making knowledge engine consists 97 types, 1086 subtypes, 21845 basic algorithm and over 2500 relevant functional modules.In order to evaluate the accuracy and visual effect of our model towards topographic maps and thematic maps, we take the world map generalization in small scale as an example. After mapping generalization process, combining and simplifying the scattered islands make the map more explicit at 1 : 2.1 billion scale, and the map features more complete and accurate. Not only it enhance the map generalization of various scales significantly, but achieve the integration among map-makings of various scales, suggesting that this model provide a reference in cartographic generalization for various scales.

Fine-structure mapping of the firA gene, a locus involved in the phenotypic expression of rifampin resistance in Escherichia.

PubMed Central

Lathe, R

1977-01-01

The firA (Ts)200 mutation not only eliminates the resistance to rifampin of certain genetically resistant strains, but, moreover, renders ribonucleic acid synthesis thermolabile. The firA gene has been mapped by P1 tranduction and is located extremely close to the structural gene for deoxyribonucleic acid polymerase III at 4 min on the Escherichia coli linkage map. PMID:330494

Predictive Modelling to Identify Near-Shore, Fine-Scale Seabird Distributions during the Breeding Season

PubMed Central

Warwick-Evans, Victoria C.; Atkinson, Philip W.; Robinson, Leonie A.; Green, Jonathan A.

2016-01-01

During the breeding season seabirds are constrained to coastal areas and are restricted in their movements, spending much of their time in near-shore waters either loafing or foraging. However, in using these areas they may be threatened by anthropogenic activities such as fishing, watersports and coastal developments including marine renewable energy installations. Although many studies describe large scale interactions between seabirds and the environment, the drivers behind near-shore, fine-scale distributions are not well understood. For example, Alderney is an important breeding ground for many species of seabird and has a diversity of human uses of the marine environment, thus providing an ideal location to investigate the near-shore fine-scale interactions between seabirds and the environment. We used vantage point observations of seabird distribution, collected during the 2013 breeding season in order to identify and quantify some of the environmental variables affecting the near-shore, fine-scale distribution of seabirds in Alderney’s coastal waters. We validate the models with observation data collected in 2014 and show that water depth, distance to the intertidal zone, and distance to the nearest seabird nest are key predictors in the distribution of Alderney’s seabirds. AUC values for each species suggest that these models perform well, although the model for shags performed better than those for auks and gulls. While further unexplained underlying localised variation in the environmental conditions will undoubtedly effect the fine-scale distribution of seabirds in near-shore waters we demonstrate the potential of this approach in marine planning and decision making. PMID:27031616

Operational data products to support phenological research and applications at local to continental scales

NASA Astrophysics Data System (ADS)

Weltzin, J. F.

2017-12-01

Phenological data from a variety of platforms - across a range of spatial and temporal scales - are required to support research, natural resource management, and policy- and decision-making in a changing world. Observational and modeled phenological data, especially when integrated with associated biophysical data (e.g., climate, land-use/land-cover, hydrology) has great potential to provide multi-faceted information critical to decision support systems, vulnerability and risk assessments, change detection applications, and early-warning and forecasting systems for natural and modified ecosystems. The USA National Phenology Network (USA-NPN; www.usanpn.org) is a national-scale science and monitoring initiative focused on understanding the drivers and feedback effects of phenological variation in changing environments. The Network maintains a centralized database of over 10M ground-based observations of plants and animals for 1954-present, and leverages these data to produce operational data products for use by a variety of audiences, including researchers and resource managers. This presentation highlights our operational data products, including the tools, maps, and services that facilitate discovery, accessibility and usability of integrated phenological information. We describe (1) the data download tool, a customizable GUI that provides geospatially referenced raw, bounded or summarized organismal and climatological data and associated metadata (including calendars, time-series curves, and XY graphs), (2) the visualization tool, which provides opportunities to explore, visualize and export or download both organismal and modeled (gridded) products at daily time-steps and relatively fine spatial resolutions ( 2.5 km to 4 km) for the period 1980 to 6 days into the future, and (3) web services that enable custom query and download of map, feature and cover services in a variety of standard formats. These operational products facilitate scaling of integrated phenological and associated data to landscapes and regions, and enable novel investigations of biophysical interactions at unprecedented scales, e.g., continental-scale migrations.

Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

NASA Astrophysics Data System (ADS)

Kearney, Michael R.; Maino, James L.

2018-06-01

Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0.085 m3 m-3). Comparisons at the continental scale to 0-2 cm satellite data (ASCAT) showed that the SLGA/SG datasets increased model fit over simulations using the DAAS soil properties (r ∼ 0.63 &rmse 15% vs. r 0.48 &rmse 18%, respectively). Overall, our results demonstrate the advantages of using GlobalSoilMap.net products in combination with gridded weather data for modelling soil moisture at fine spatial and temporal resolution at the continental scale.

Dissociative Experiences, Creative Imagination, and Artistic Production in Students of Fine Arts

ERIC Educational Resources Information Center

Perez-Fabello, Maria Jose; Campos, Alfredo

2011-01-01

The current research was designed to assess the influence of dissociative experiences and creative imagination on the artistic production of Fine Arts students of the University of Vigo (Spain). The sample consisted of 81 students who were administered the Creative Imagination Scale and The Dissociative Experiences Scale. To measure artistic…

Parallelization of fine-scale computation in Agile Multiscale Modelling Methodology

NASA Astrophysics Data System (ADS)

Macioł, Piotr; Michalik, Kazimierz

2016-10-01

Nowadays, multiscale modelling of material behavior is an extensively developed area. An important obstacle against its wide application is high computational demands. Among others, the parallelization of multiscale computations is a promising solution. Heterogeneous multiscale models are good candidates for parallelization, since communication between sub-models is limited. In this paper, the possibility of parallelization of multiscale models based on Agile Multiscale Methodology framework is discussed. A sequential, FEM based macroscopic model has been combined with concurrently computed fine-scale models, employing a MatCalc thermodynamic simulator. The main issues, being investigated in this work are: (i) the speed-up of multiscale models with special focus on fine-scale computations and (ii) on decreasing the quality of computations enforced by parallel execution. Speed-up has been evaluated on the basis of Amdahl's law equations. The problem of `delay error', rising from the parallel execution of fine scale sub-models, controlled by the sequential macroscopic sub-model is discussed. Some technical aspects of combining third-party commercial modelling software with an in-house multiscale framework and a MPI library are also discussed.

Synchrotron imaging reveals bone healing and remodelling strategies in extinct and extant vertebrates

PubMed Central

Anné, Jennifer; Edwards, Nicholas P.; Wogelius, Roy A.; Tumarkin-Deratzian, Allison R.; Sellers, William I.; van Veelen, Arjen; Bergmann, Uwe; Sokaras, Dimosthenis; Alonso-Mori, Roberto; Ignatyev, Konstantin; Egerton, Victoria M.; Manning, Phillip L.

2014-01-01

Current understanding of bone healing and remodelling strategies in vertebrates has traditionally relied on morphological observations through the histological analysis of thin sections. However, chemical analysis may also be used in such interpretations, as different elements are known to be absorbed and used by bone for different physiological purposes such as growth and healing. These chemical signatures are beyond the detection limit of most laboratory-based analytical techniques (e.g. scanning electron microscopy). However, synchrotron rapid scanning–X-ray fluorescence (SRS–XRF) is an elemental mapping technique that uniquely combines high sensitivity (ppm), excellent sample resolution (20–100 µm) and the ability to scan large specimens (decimetre scale) approximately 3000 times faster than other mapping techniques. Here, we use SRS–XRF combined with microfocus elemental mapping (2–20 µm) to determine the distribution and concentration of trace elements within pathological and normal bone of both extant and extinct archosaurs (Cathartes aura and Allosaurus fragilis). Results reveal discrete chemical inventories within different bone tissue types and preservation modes. Chemical inventories also revealed detail of histological features not observable in thin section, including fine structures within the interface between pathological and normal bone as well as woven texture within pathological tissue. PMID:24806709

Integration of Satellite Tracking Data and Satellite Images for Detailed Characteristics of Wildlife Habitats

NASA Astrophysics Data System (ADS)

Dobrynin, D. V.; Rozhnov, V. V.; Saveliev, A. A.; Sukhova, O. V.; Yachmennikova, A. A.

2017-12-01

Methods of analysis of the results got from satellite tracking of large terrestrial mammals differ in the level of their integration with additional geographic data. The reliable fine-scale cartographic basis for assessing specific wildlife habitats can be developed through the interpretation of multispectral remote sensing data and extrapolation of the results to the entire estimated species range. Topographic maps were ordinated according to classified features using self-organizing maps (Kohonen's SOM). The satellite image of the Ussuriiskyi Nature Reserve area was interpreted for the analysis of movement conditions for seven wild Amur tigers ( Panthera tigris altaica) equipped with GPS collars. 225 SOM classes for cartographic visualization are sufficient for the detailed mapping of all natural complexes that were identified as a result of interpretation. During snow-free periods, tigers preferred deciduous and shrub associations at lower elevations, as well as mixed forests in the valleys of streams that are adjacent to sparse forests and shrub watershed in the mountain ranges; during heavy snow periods, the animals preferred the entire range of plant communities in different relief types, except for open sites in meadows and abandoned fields at foothills. The border zones of different biotopes were typically used by the tigers during all seasons. Amur tigers preferred coniferous forests for long-term movements.

High-resolution mapping based on an Unmanned Aerial Vehicle (UAV) to capture paleoseismic offsets along the Altyn-Tagh fault, China.

PubMed

Gao, Mingxing; Xu, Xiwei; Klinger, Yann; van der Woerd, Jerome; Tapponnier, Paul

2017-08-15

The recent dramatic increase in millimeter- to centimeter- resolution topographic datasets obtained via multi-view photogrammetry raises the possibility of mapping detailed offset geomorphology and constraining the spatial characteristics of active faults. Here, for the first time, we applied this new method to acquire high-resolution imagery and generate topographic data along the Altyn Tagh fault, which is located in a remote high elevation area and shows preserved ancient earthquake surface ruptures. A digital elevation model (DEM) with a resolution of 0.065 m and an orthophoto with a resolution of 0.016 m were generated from these images. We identified piercing markers and reconstructed offsets based on both the orthoimage and the topography. The high-resolution UAV data were used to accurately measure the recent seismic offset. We obtained the recent offset of 7 ± 1 m. Combined with the high resolution satellite image, we measured cumulative offsets of 15 ± 2 m, 20 ± 2 m, 30 ± 2 m, which may be due to multiple paleo-earthquakes. Therefore, UAV mapping can provide fine-scale data for the assessment of the seismic hazards.