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1,709 results for “Reflectivity”
Higher ultraviolet skin reflectance signals submissiveness in the anemonefish, Amphiprion akindynos
<p>Ultraviolet (UV) vision is widespread among teleost fishes, of which many exhibit UV skin colours for communication. However, aside from its role in mate selection, few studies have examined the information UV-signalling conveys in other socio-behavioural contexts. Anemonefishes (subfamily, Amphiprioninae) live in a fascinating dominance hierarchy, in which a large female and male dominate over non-breeding subordinates, and body size is the primary cue for dominance. The iconic orange and white bars of anemonefishes are highly UV-reflective, and their colour vision is well-tuned to perceive the chromatic contrast of skin, which we show here decreases in the amount of UV-reflectance with increasing social rank. To test the function of their UV-skin signals, we compared the outcomes of staged contests over dominance between size-matched Barrier Reef anemonefish (<em>Amphiprion akindynos</em>) in aquarium chambers viewed under different UV-absorbing filters. Fish under UV-blocking filters were more likely to win contests, whereas fish under no-filter or neutral-density filter were more likely to submit. For contests between fish in no-filter and neutral density filter treatments, light treatment had no effect on contest outcome (win/lose). We also show that sub-adults were more aggressive towards smaller juveniles placed under a UV filter than a neutral density filter. Taken together, our results show that UV-reflectance or -contrast in anemonefish can modulate aggression and encode dominant and submissive cues when changes in overall intensity are controlled for.</p>
Temporal stability of polymorphic Arctic charr parasite communities reflect sustained divergent trophic niches
<p>Polymorphic Arctic charr Salvelinus alpinus populations frequently display distinct differences in habitat use, diet and parasite communities. Changes to the relative species densities and composition of the wider fish community have the potential to alter the habitat-niche of sympatric Arctic charr populations. This study evaluated the temporal stability of the parasite community, diet and stable isotopes (δ13C, δ15N) of three sympatric Arctic charr morphs (piscivore, benthivore and planktivore) from Loch Rannoch, Scotland, in relation to changes to the fish community. All Arctic charr morphs displayed distinct differences parasite communities, diet and stable isotope signatures over time, despite the establishment of four new trophically transmitted parasite taxa, and increased fish and zooplankton consumption by the piscivorous and planktivore morphs respectively. Native parasite prevalence also increased in all Arctic charr morphs. Overall, Loch Rannoch polymorphic Arctic charr morph populations have maintained their distinct trophic niches and parasite communities through time despite changes in the fish community. This result indicates that restocking of a native fish species has the potential to induce shifts in the parasite community and diet of Arctic charr morphs.</p>
Data for publication: Nanomechanical and Structural Study of Au38 Nanocluster Langmuir-Blodgett Films Using Bimodal Atomic Force Microscopy and X-Ray Reflectivity
<p>Original data of Figures published in:</p> <p><strong>Nanomechanical and Structural Study of Au<sub>38</sub> Nanocluster Langmuir-Blodgett Films Using Bimodal Atomic Force Microscopy and X-Ray Reflectivity</strong></p> <p>Journal of Colloid and Interface Science, 2022, Michal Swierczewski<sup>,</sup> Alexis Chenneviere, Lay-Theng Lee, Plinio Maroni and Thomas Bürgi*<sup>[</sup></p> <p> </p>
Data for "Multifractal comparison of reflectivity and polarimetric rainfall data from C- and X-band radars and respective hydrological responses of a complex catchment model"
<p>The data files arranged here correspond to the data used in the paper: “Multifractal comparison of reflectivity and polarimetric rainfall data from C- and X-band radars and respective hydrological responses of a complex catchment model”, submitted to <em>Water</em>.</p> <p>The data organized as follows:</p> <ul> <li>Data_type_20150912_time_steps.mat: the rainfall data for 3 different products of the X-band radar (FIR filter, a=200, b=1.6; FIR filter, a=150, b=1.3; simple filter, a=150, b=1.3) for the event of 12-13 September 2015, over an area of 64 km x 64 km.</li> <li>Data_type_Event_time_steps.mat: X-band radar data (FIR filter, a=150, b=1.3) for the events of 16 September 2015 and 5-6 October 2015, over an area of 64 km x 64 km.</li> <li>Sub-catchment_name_Data_type_Event.txt: the rainfall series for each of 26 sub-catchments of the model, for 3 different types of rainfall data (C-band, X-band and rain gauges) for the events of 12-13 September 2015, 16 September 2015 and 5-6 October 2015.</li> <li>X-band_Pixels_Event.txt: the rainfall series for all 6 X-band radar pixels corresponding to the 6 rain gauges for the 3 studied events (12-13 September 2015, 16 September 2015, and 5-6 October 2015).</li> <li>X-Band_Optim 20150916_Measurement_point_name.txt: flow simulated at each of the 4 measurement points with X-band data for the 16 September 2015 event, with the implementation of the tool mimicking the regulation optimization.</li> <li>Data_type_Event_Measurement_point_name.txt: flow simulated at each of the 4 measurement points with 3 different types of rainfall data (C-band, X-band and rain gauges) for the 3 studied events (12-13 September 2015, 16 September 2015, and 5-6 October 2015), without the implementation of the tool mimicking the regulation optimization.</li> </ul> <p>The original C-band radar data remains property of Météo-France and was provided to the authors for this research study, without any possibility of data disclosure.</p> <p>The details on how the rainfall series were generated over each sub-catchment could be found in the paper.</p> <p>The authors greatly acknowledge partial financial supports of the Chair “Hydrology for resilient cities” endowed by Veolia, and of the Department of Science and Technology of the Brazilian Army. The authors are thankful to M Bernard Urban (Météo-France) for providing access to the C-band radar data and documentation in the framework of the INTERREG NWE RainGain project.</p>
Range-wide intraspecific variation reflects past adaptation to climate in a gypsophile Mediterranean shrub
<p>Phenotypic differences among populations stem from the interaction between neutral and adaptive processes, and phenotypic plasticity. Although clinal trait variation along climatic gradients often evolves in widely-distributed species, it is unknown whether substrate specialization, such as that of Mediterranean gypsum plants, has constrained adaptation to climate. Using a common garden experiment with two contrasting watering treatments, we quantified phenotypic plasticity, assessed evidence for footprints of selection using FST - QST comparisons, and identified the ecological factors driving genetically-based phenotypic differentiation of 11 populations encompassing the full environmental range of the gypsum shrub Lepidium subulatum. We found evidence for genetic differentiation among populations related to climatic differences, with populations from warmer and drier sites showing lower specific leaf area (SLA) and leaf N, earlier phenology, greater water use efficiency (WUE) and greater fitness. Multiple lines of evidence suggest that this differentiation was driven by past divergent selection rather than neutral processes. All populations showed high phenotypic plasticity, indicating that plasticity has not been selected against, even in populations from sites with harsher climatic conditions.<br>Synthesis. Our results indicate that, despite strong substrate specialization, adaptive differentiation related to climatic gradients occurs in this species. However, we also found that populations from mesic sites may be particularly vulnerable to future climate change given their relatively lower fitness under both wet and dry conditions.</p>
HyperspectralBlueberries: a dataset of hyperspectral reflectance images of normal and defective blueberries
<p>The <strong>HyperspectralBluberries</strong> dataset consists of hyperspectral datacubes, which were acquired by an in-house assembled benchtop line scanning system, from 420 blueberries of two categories, including 210 sound fruit and 210 samples with various defects. The fruit samples were hand-picked from a commercial orchard. Each scanning event, which was done for an array of 42 samples, yields two files in image formats .bil (band-interleaved-by-line) and .hdr (header), which store the hyperspectral raw data and associated metadata, respectively, and are both necessary for loading hyperspectral data for processing. In addition to sample scanning, a white reference was also scanned, which can be used for standardizing spectral responses. As a result, there are 22 files in the dataset, totaling about 25 GB in file size. The sample file names are descriptive, indicating the blueberry category and number information. The dataset was used for developing machine learning models for differentiating between normal and defective blueberries, achieving an overall accuracy of 96.6%. Software programs for the modeling work are publicly available at: <a href="https://github.com/vicdxxx/Blueberry-Defect-Detection-by-Hyperspectral-Imaging">https://github.com/vicdxxx/Blueberry-Defect-Detection-by-Hyperspectral-Imaging.</a></p> <p>Details about the dataset curation and modeling experiments are described in the journal article: <a href="https://www.sciencedirect.com/science/article/pii/S2772375524000789">Deng, B., Lu, Y., Stafne, E. (2024). </a><a href="https://www.sciencedirect.com/science/article/pii/S2772375524000789">Fusing Spectral and Spatial Features of Hyperspectral Reflectance Imagery for Differentiating between Normal and Defective Blueberries. Smart Agricultural Technology</a>. <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.atech.2024.100473" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.atech.2024.100473</a>. If you use the dataset in published research, please consider citing the dataset or the <a href="https://doi.org/10.1016/j.ecoinf.2024.102546">journal article</a>. Hopefully, you find the dataset useful. </p>
Data from: Environmental DNA metabarcoding reflects spatiotemporal patterns of fish community shifts in the Scheldt estuary
<p>Estuarine ecosystems face increasing anthropogenic pressures, necessitating effective monitoring methods to mitigate their impacts on the biodiversity they harbour. The use of environmental DNA (eDNA) based detection methods is increasingly recognized as a promising tool to complement other, potentially invasive monitoring techniques. Integrating such eDNA analyses into monitoring frameworks for large spatial ecosystems is still challenging and requires a deeper understanding of the scale and resolution at which eDNA patterns may offer insights in species presence and community composition space and time. The Scheldt estuary, characterized by its diverse habitats and complex currents, is one of the largest Western European tidal river systems. Until now, it remains challenging to obtain accurate information on fish communities living in and migrating through this large ecosystem, consequently confining our knowledge to specific locations. To explore the potential of eDNA-based monitoring, we simultaneously combine stow net fishing with eDNA metabarcoding, to assess the Scheldt estuary's fish communities in space and time. In total, we detected 71 fish species in the estuary using eDNA metabarcoding, partly overlapping with historic fish community data gathered at the different study locations and in contrast to only 42 species using stow net fishing during the same survey period. Community compositions found by both detection methods varied amongst sampling locations, driven by a clear correlation to the salinity gradient. Limited effects of sampling depth and tide were observed on the eDNA metabarcoding data, allowing a significant reduction of the eDNA sampling effort for future eDNA fish monitoring campaigns in this study system. Our results further demonstrate that seasonal shifts in fish species occurrence can be detected using eDNA metabarcoding. Combining eDNA metabarcoding and stow net fishing further enhances our understanding of this vital waterway's diverse fish populations, allowing a higher resolution and more efficient monitoring strategy.</p>
Parcel level temporal variance of remotely sensed spectral reflectance predicts plant diversity
<p>Over the last two decades, considerable research has built on remote sensing of spectral diversity to assess plant diversity. The spectral variation hypothesis (SVH) proposes that spatial variation in reflectance data of an area is positively associated with plant diversity. While the SVH has exhibited validity in dense forests, it performs poorly in highly fragmented and temporally dynamic agricultural landscapes covered mainly by grasslands. Such underperformance can be attributed to the mosaic-like spatial structure of human-dominated landscapes with fields in varying phenological and management stages. Therefore, we argued for re-evaluating SVH's flawed window-based spatial analysis and underutilized temporal component. In particular, In particular, we captured the spatial and temporal variation in reflectance and assessed the relationships between spatial and temporal components of spectral diversity and plant diversity at the parcel level as a unit that relates to management patterns. Our investigation spanned three grasslands on two continents covering a wide spectrum of agricultural usage intensities. To calculate different components of spectral diversity, we used multi-temporal spaceborne Sentinel-2 data. We showed that plant diversity was negatively associated with the temporal component of spectral diversity across all sites. In contrast, the spatial component of spectral diversity was related to plant diversity in sites with larger parcels. Our findings highlighted that in agricultural landscapes, the temporal component of spectral diversity drives the spectral diversityplant diversity associations. Consequently, our results offer a novel perspective for remote sensing of plant diversity globally.</p>
Fig.1 in Application Of Near-Infrared Reflectance Spectroscopy For Detection Of Acrylamide Content In Potato Crisps And Bread
Fig.1. Predicted acrylamide vs reference acrylamide in bread samples.
Fig.2 in Application Of Near-Infrared Reflectance Spectroscopy For Detection Of Acrylamide Content In Potato Crisps And Bread
Fig.2. Predicted acrylamide vs reference acrylamide in potato crisp samples.
Key habitat for male Strix nebulosa (Great Gray Owls) varies across the diurnal cycle and reflects sex-specific role, data archive
<p>We used GPS tracking and remotely-sensed environmental data to evaluate whether breeding-season habitat selection by adult male <em>Strix nebulosa </em>(Great Gray Owls) (n = 19) varied across diurnal periods (dawn, day, dusk, and night). To address knowledge gaps related to nocturnal habitat, we also evaluated finer-scale, microhabitat selection by male owls at night. Here, we include both the remotely-sensed habitat data and on-the-ground microhabitat data associated with owl locations. Generally, <em>S. nebulosa </em>are associated with mature forests for nesting and meadows for foraging. Yet, in our study, owls avoided herbaceous wetlands during the day but strongly selected them at dawn, dusk, and at night, indicating context-dependent habitat selection. Moreover, owls avoided dry meadows at all times of the day, suggesting that wet rather than xeric meadows are important for foraging. Owls also preferred nighttime microhabitats that facilitated foraging, such as those with presence of primary prey and open understories dominated by graminoids and forbs. During the daytime, owls preferred higher canopy cover and areas with increased soil moisture, which likely provided suitable roosting habitat. Understanding of habitat preferences across sexes, activity periods, and other contexts can improve the identification and conservation of critical habitat for wildlife.</p>
Geomorphic expressions of active rifting reflect the role of structural inheritance: A new model for the evolution of the Shanxi Rift, North China
<p>A geopackage and associated raster files for the geomorphic indices that were used in this study. Can be opened with the freely available QGIS software. Excel table of fault values used for generation of violin plots in R</p>
Raw data: Stable isotopes of Hawaiian spiders reflect substrate properties along a chronosequence
<p>Data sets used to analyze N and C stable isotope ratios in spider tissues, leaf litter, and plant leaves originating from three sites along a substrate age gradient in Hawaii.</p>
Animation of 24h-metereologic radar data (maximum reflectivity and CFAD) for the Liebenbergvlei, Freestate, South Africa on December 30 2001
<p>The visualisation of metereologic radar data for the Liebenbergvlei, RSA, covers the time between December 30 2001 00:00:00 hours and 23:59:00 hours in five minute steps. The data war recorded by the X-band metereological radar station operated by the South African Weather Service in the Liebenbergvlei in the Freestate, South Africa. For each time step, the maximum reflectitivity is depicted on the left, while the contoured frequency by altitude (CFAD) diagram is shown on the right (derived from plan position indicator (PPI) volume data from 1 to 18km height above ground). The processing of the data based on MDV-files was done in GRASS GIS v5.0.</p>
Seismic interpretation of key stratigraphic and structural surfaces, and crustal faults within the Galicia 3-D reflection survey
<p>This repository contains all the seismic interpretations utilized for the analysis in the article "<em>Origin of serpentinization patterns beneath the S-reflector detachment fault in the Galicia margin, offshore Spain</em>". </p> <p>The "<em>Surfaces</em>" file contains the CPS-3 shape files of the major stratigraphic and structural surfaces (seafloor, base of post-rift sedimentary strata, base of pre/syn-rift sedimentary strata, base of crystalline basement, S-reflector detachment fault, Moho). The "<em>Faults</em>" file contains the interpretations of the major crustal faults overlying the S-reflector detachment. The "<em>Data</em>" file contains the spatial boundary of where the S-reflector is the crust-mantle boundary, the P-wave velocities of Schuba et al. (2019) and calculated degree of serpentinization (Schuba et al., submitted) based on Christensen's (2004) 200 MPa/200<sup>o</sup>C serpentinite compilation study. </p> <p>All seismic interpretations were carried out on Petrel<sup>TM</sup> versions 2015 and 2017. The seismic reflection volume that was interpreted can be found at https://doi.org/10.1594/IEDA/500151.</p> <p> </p> <p>References: </p> <ul> <li>Christensen, N.I. (2004). Serpentinites, Peridotites, and Seismology. <em>International Geology Review</em>, <em>46</em>(9), 795-816. https://doi.org/10.2747/0020-6814.46.9.795</li> <li>Schuba, C.N., Schuba, J.P. Gray, G.G., and Davy, R.G., (2019). Interface targeted velocity estimation using machine learning. <em>Geophysical Journal International</em>, <em>218</em>(1), 45-56. https://doi.org/10.1093/gji/ggz142</li> <li>Schuba, C.N., Gray, G.G., Morgan, J.K., Schuba, J.P., and Sawyer, D.S., (submitted). Interface targeted velocity estimation using machine learning. <em>Geochemistry, Geophysics, Geosystems.</em></li> </ul>
Underlying data of the project "Are CONSORT checklists submitted by authors adequately reflecting what information is actually reported in published papers?"
<p><em><strong>Supplementary file 3.xlsx</strong></em> contains the evaluations for the 12 papers included in the study.</p>
Figure 1 in Is the global decline reflects local declines? A case of the population trend of Far Eastern Curlew Numenius madagascariensis in Banyuasin Peninsula, South Sumatra, Indonesia
Figure 1. Map of Banyuasin Peninsula, South Sumatra, Indonesia.
Mid-Infrared Reflectance and Emissivity Spectra of High Porosity Regoliths
<p>This dataset contains laboratory spectra of olivine and pyroxene in the mid-Infrared (MIR; 5-35 micron) wavelength region as described in Martin et al., (in rev). </p> <p>Files are labeled accordingly: mineral_smallest particle size_largest particle size_regolith porosity_measurement type</p> <p>OLV = olivine, PYX=pyroxene</p> <p>r = ambient reflectance, a = ambient emissivity, sae = simulated asteroid environment</p> <p>Example: The file labeled OLV_45_63_10_a.txt contains spectra of olivine, with 45-63 micron particle sizes, has 10% regolith porosity, and was measured in ambient emissivity. </p>
Dataset for the study: Closed-boundary reflections of shallow water waves as an open challenge for physics-informed neural networks
<p>This dataset supports a study on using Physics-Informed Neural Networks (PINNs) to solve the 1D-Shallow Water Equations. It focuses on closed boundary reflection test cases, which are crucial for accurately modeling geophysical fluid dynamics in coastal regions, particularly for storm surge and flood modeling. Properly representing reflections is also essential for accurately modeling related phenomena, such as Kelvin waves and amphidromic systems, which influence coastal water levels during such events. The individual sub-datasets in NetCDF format provide the results used for one figure each. The data arrays within the datasets are named with reference to the figures for ease of comparison. <br><br>Cite as: Demir, K.T.; Logemann, K.; Greenberg, D.S. Closed-Boundary Reflections of Shallow Water Waves as an Open Challenge for Physics-Informed Neural Networks. <em>Mathematics</em> 2024, <em>12</em>, 3315. <a href="https://doi.org/10.3390/math12213315">https://doi.org/10.3390/math12213315</a></p>
Implementation of Aerosol Mie Scattering in POSEIDON with Application to the hot Jupiter HD 189733 b's Transmission, Emission, and Reflected Light Spectrum - Supplementary Material
<p>Supplementary material to 'Implementation of Aerosol Mie Scattering in POSEIDON with Application to the hot Jupiter HD 189733 b’s Transmission, Emission, and Reflected Light Spectrum'</p> <p>This zenodo repository corresponds to the updates to POSEIDON presented in Mullens et al 2024, as well as the benchmark retrievals preformed on archival HD 189733 b. </p> <p>In the upper level of the repository we have data products mentioned in the paper:</p> <p>aersosol_database.pdf <br>Aerosol-Database-Readme.txt<br>aerosol_database.hdf5</p> <p>There are then three directories (here as zip files): </p> <p>Aerosol-Datbase<br>- This folder contains the aerosol properties for aerosols in Table 1 in the paper. It contains the aerosol-database.hdf5 which contains the precomputed aerosol properties that POSEIDON utilizes in forward models and retrievals, a folder containing the npy files that have individual precomputed aerosol properties (used to generate the hdf5 file), a pdf containing the refractive indices + precomputed aerosol properties for each aerosol in the database (png versions of these figures are available in the Aerosol-Optical-Properties-Pngs folder), the refractive index txt files for each aerosol, and a readme file that contains information on each aerosol in the database (such as aerosol name, polymorph, crystalline or amorphous, crystal shape, information on samples used in refractive index references, and exoplanet/planetary science specific references). </p> <p>HD-189733b-Retrievals<br>- Contains retrieval scripts and retrieval results for the transmission, emission, and emission+reflection retrievals in the paper. Also has the notebooks used to make the figures in the paper.</p> <p>POSEIDO-V1-2<br>- Contains the POSEIDON module used to run retrievals and generate figures, and corresponds to POSEIDON version 1.2. Also contains a folder containing tutorial notebooks for new features introduced into POSEIDON version 1.2. Included in this repository for posterity.</p>
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