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opencc-zeroDec 2016View details →

FIGURE 28 in Leaf-mining Nepticulidae (Lepidoptera) from record high altitudes: documenting an entire new fauna in the Andean páramo and puna

FIGURE 28. Details of adult morphology of high-Andean Stigmella, Nepticulidae.

opencc-zeroDec 2016View details →

FIGURE 27 in Leaf-mining Nepticulidae (Lepidoptera) from record high altitudes: documenting an entire new fauna in the Andean páramo and puna

FIGURE 27. Distribution map of the high-Andean Nepticulidae with height records.

opencc-by-4.0Jul 2017View details →

A dataset of atmospheric ozone above the Mexico City basin retrieved from FTIR remote sensing observations made at two different ground altitudes

This dataset of atmospheric ozone (O3) has been generated from solar absorption spectra measured in central Mexico using ground-based Fourier-Transform Infrared (FTIR) spectrometers. The FTIR experiments have been operated by the “Spectroscopy and Remote Sensing” Research Group of the Centro de Ciencias de la Atmósfera of the Universidad Nacional Autónoma de México (http://www.atmosfera.unam.mx/espectroscopia/index.html). The dataset covers measurements made between November 2012 and February 2014 applying two different FTIR spectrometers. The first instrument offers very high resolution spectra and contributes to NDACC (Network for the Detection of Atmospheric Composition Change). It is located at the mountain observatory of Altzomoni (ALTZ) about 1700m above the Mexico City basin. The second instrument has a medium spectral resolution and is located inside of Mexico City at the Universidad Nacional Autónoma de México (UNAM) at a horizontal distance of about 60km to the mountain observatory. The here provided dataset consists of two NETCDF data-files for each station and a MATLAB script for reading the NETCDF files. The files “ALTZ_IFS125_O3.nc” and “UNAM_IFS125_O3.nc” contain the retrieved O3 state vectors, the O3 averaging kernels and the O3 a priori profiles, together with auxiliary data: observation time, observation geometry, instrumental settings, atmospheric temperature and humidity profiles. The data as well as the method for combining the two different observations are presented in Plaza-Medina et al. (2017), which should be consulted for more details. The files “ALTZ_IFS125_O3_Jac+Gain.nc” and “UNAM_IFS125_O3_Jac+Gain.nc” contain the Jacobians (for O3 as well as for error sources) and the Gain matrix, together with the auxiliary data. The MATLAB script “readNETCDF_and_combine2FTIR.m” reads the NETCDF files and performs the operations needed for the generation of a combined product, thereby exploiting the synergetic effects of two observations made in coincidence but at different ground altitudes. A related dataset with Altzomoni O3 profiles obtained by applying slightly different retrieval settings is available at the NDACC database (ftp://ftp.cpc.ncep.noaa.gov/ndacc/station/altzomoni/hdf/ftir/). Further datasets of atmospheric parameters as measured by different techniques are available at the webpage of the Red Universitario de Observaciones Atmosfericas (www.ruoa.unam.mx).

opencc-by-4.0Dec 2023View details →

Data Set: Radio Frequency Senser (RFS) example waveforms, altitudes, and density plot

This data set contains data for the paper entitled "Radio Frequency Sensor: radio frequency lightning detection in geostationary orbit", submitted to Radio Science in December 2023. This data set contains three types of RFS data. 1) The first are time domain waveforms of three lightning events, in both the RFS high band (116 – 142 MHz) and the RFS low band (10-60 MHz), sampled at 155 MHz. The waveforms are right-hand circularly polarized waveforms. 2) The second type of data is altitudes and locations of trans-ionospheric pulse pairs (TIPPs) over time. The locations were determined by time coincidence with geolocated World Wide Lightning Location Network strokes. 3) The third type is RFS events per square kilometer per year in latitude and longitude. The RFS event were located by time correlation to Earth Networks Global Lightning Network lightning strokes. Data set 1: Consists of six ASCII files – 3 high band & 3 low band example RFS right-hand circularly polarized waveforms. Each ascii file contains a header with the RFS event time in UTC, the label of “RFS high band (77.5 – 155 MHz)” or “low band (0 – 77.5 MHz)”, and sample rate (155 MHz). Data following the header are time samples of electric field in uV/m sampled at 155 MHz. Filenames are: RFS_waveform_HighBand_20230607_010803.txt RFS_waveform_HighBand_20230607_015553.txt RFS_waveform_HighBand_20230607_034055.txt RFS_waveform_LowBand_20230607_010803.txt RFS_waveform_LowBand_20230607_015553.txt RFS_waveform_LowBand_20230607_034055.txt   Data set 2: Filename = ‘RFS_TIPPs_20230607_0100-0500_UTC.txt’ 1 ASCII comma separated value (CSV) file. Columns are: 1.     UTC date yyyy/mm/dd 2.     UTC seconds of day 3.     WWLLN-determined latitude (degrees, wwlln_latitude in header) 4.     WWLLN-determined longitude (degrees, wwlln_longitude in header) 5.     TIPP-estimated height (km, height in header)   Data set 3: Filename = ‘RFS_map.csv’ 1 CSV file of a 2-dimensional data set. 1.     Row 1, Longitude (degrees, in 0.25-degree steps) 2.     Column 1, Latitude (degrees, in 0.5-degree steps) 3.     2-D grid in latitude and longitude: events per square kilometer per year Notes: Since the RFS coverage range goes across longitude = -180/180 degrees, longitudes go from 147.75 to 180, then start at -180 to -12.75. Latitude range goes from -58.5 to 68.5, as there were no detected RFS events outside these latitudes. The three examples given in data set 1 are those shown in LA-UR-23-32419, Figure 2. The TIPP data in data set 1 is shown in LA-UR-23-32419, Figure 4, and comprises data from 07 June 2023 between 01:00-05:00 UTC. Data set 3 contains RFS event rates per sq. km per year for data from 1 March 2022 – 1 March 2023, with the caveats described in LA-UR-23-32419.

opencc-by-4.0Mar 2024View details →

India Onshore Wind Energy Atlas Accounting for Altitude and Land Use Restrictions and Co-Located Solar

India faces the simultaneous challenges of meeting rising energy demand and reducing carbon emissions. To address these, India must transition to renewable energy sources. These high-resolution maps are used to quantify available areas for wind farms, after accounting for restrictions, including airports, buildings, protected land use, military zones, railways, roads, water bodies, waterways, wildlife and nature, high elevation and slope, and existing solar farms, to which policy-informed setback distances are applied. This study finds the wind and solar potential within available areas considering three altitudes (100 m, 150 m, 200 m) and four wind speed thresholds (5-8 m/s), and modern wind turbine and solar array dimensions. The raster files included here indicate available areas after aggregating restrictions for different combinations of altitude and wind speed threshold. Availability is indicated with a binary system in which available land is designated with a value of zero and restricted land is designated with a value of one.

opencc-by-4.0Jun 2024View details →

Abiotic conditions along altitude shape plant-fungal associations by influencing both fungal availability and association strength

These files contains the description of the data and scripts to reproduce the analyses of: "Abiotic conditions along altitude shape plant-fungal associations by influencing both fungal availability and association strength" which can be found here: <a href="https://doi.org/10.1111/1365-2745.70075">https://doi.org/10.1111/1365-2745.70075</a> As detailed in the study, the data consist of fungal DNA data from ten high and low Bistorta vivipara populations across Fennoscandia. Species-level fungal OTUs have been identified applying ITS2-based metabarcoding to the different parts of the focal plant B. vivipara (bulbils, leaves and roots) and its surrounding soil and leaves of surrounding plants. In total, the data contains data on 253 fungal OTUs across 641 sampling units. The README file describes the contents of the metadata and explains how the scripts are to be run in order to reproduce the results of the study.

opencc-zeroJan 2022View details →

A predictive flight-altitude model for avoiding future conflicts between an emblematic raptor and wind energy development in the Swiss Alps

Deployment of wind energy is proposed as a mechanism to reduce greenhouse gas emissions. Yet, wind energy and large birds, notably soaring raptors, both depend on suitable wind conditions. Conflicts in airspace use may thus arise between wind energy development and wildlife protection due to the risks of collisions of birds with the blades of wind turbines. Using locations of GPS-tagged bearded vultures, a rare scavenging raptor reintroduced into the Alps, we built a spatially-explicit model to predict potential areas of conflict with future wind turbines deployments in the Swiss Alps. We modelled the probability of bearded vultures flying within or below the rotor-swept zone of wind turbines as a function of wind and environmental conditions, including food supply (presence of wild ungulates). Flight activity at potential risk of collision was generally high, concentrating on south-exposed mountainsides, especially in areas where ibex carcasses have a high occurrence probability, with critical areas covering vast expanses throughout the Swiss Alps. Our model provides a spatially-explicit decision tool that will guide authorities and energy companies for planning the deployment of wind farms in a proactive manner to reduce risk to emblematic Alpine wildlife.

opencc-zeroApr 2022View details →

Data on bird communities and vegetation in relation to altitude and habitat alteration in the Kalakad - Mundanthurai Tiger Reserve, Tamil Nadu, India

The dataset contains data on bird communities and habitat collected between 1997 and 1999 from Kalakad Mundanthurai Tiger Reserve, Tamil Nadu, India, related to the following two publications: <ol> <li>Raman, T. R. S., Joshi, N. V. & Sukumar, R. 2005. Tropical rainforest bird community structure in relation to altitude, tree species composition, and null models in the Western Ghats, India. Journal of the Bombay Natural History Society 102: 145-157. <a href="https://archive.org/details/journalofbomb10222005bomb/page/145/mode/2up">https://archive.org/details/journalofbomb10222005bomb/page/145/mode/2up</a> </li> <li>Raman, T. R. S. & Sukumar, R. 2002. Responses of tropical rainforest birds to abandoned plantations, edges, and logged forest in the Western Ghats, India. Animal Conservation 5: 201-216. <a href="http://dx.doi.org/10.1017/S1367943002002251">http://dx.doi.org/10.1017/S1367943002002251 </a> </li> </ol> GEOGRAPHICAL AREA: Kalakad-Mundathurai Tiger Reserve (KMTR), 895 km² sanctuary located between 8°25′ to 8°53′ N and 77°10′ to 77°35′ E in Tamil Nadu state in the Western Ghats mountain range of India. TAXONOMIC SCOPE: Birds, trees Supplementary information The Appendix of Raman and Sukumar (2002) is included in the dataset as an open document format word (ODT) file. Three Tables from Raman et al. (2005) are included in the dataset as an open document format worksheet (ODS) file.

Figure 5 in Fish fauna of moderate altitude from first order stream in upper Rio Machado, Rondônia, Brazil

Figure 5. Richness per family (A) and relative abundance of species (B) registered in the upper Rio Machado basin.

Figure 4 in Fish fauna of moderate altitude from first order stream in upper Rio Machado, Rondônia, Brazil

Figure 4. Relative diversity of species (A), and relative abundance of specimens (B) per order registered in the upper Rio Machado basin.

Figure 2 in Fish fauna of moderate altitude from first order stream in upper Rio Machado, Rondônia, Brazil

Figure 2. Habitats of the sampled station in the upper Rio Machado, Rio Madeira basin, Rondônia, Brazil.

Figure 1 in Fish fauna of moderate altitude from first order stream in upper Rio Machado, Rondônia, Brazil

Figure 1. Map of the study area from the upper Rio Machado, Rio Madeira basin, Rondônia, Brazil. The sampled station is indicated by the red plus symbol.

Figure 3 in Fish fauna of moderate altitude from first order stream in upper Rio Machado, Rondônia, Brazil

Figure 3. Fishes registered from the tributary of Igarapé Piracolina, upper Rio Machado, Vilhena, Rondônia. Bryconops piracolina (1-2); Creagrutus petilus (3); Hyphessobrycon aff. notidanos (4-5); H. lucenorum (6-7); Hyphessobrycon cf. melanostichos (8); Moenkhausia parecis (9); M. cambacica (10); Erythrinus erythrinus (11); Pyrrhulina sp. nov. (12-13); Ancistrus verecundus (14-15); Tatia intermedia (16); Corydoras hephaestus (17); Megalechis thoracata (18); Cetopsorhamdia clathrata (19); Rhamdia quelen (20); Aequidens aff. rondoni (21); Brachyhypopomus degy (22); Hoplias malabaricus not represented herein.

opencc-zeroApr 2024View details →

Data from: Influences of ski-runs, meadow management and climate on the occupancy of reptiles and amphibians in a high-altitude environment of Italy

Alpine ecosystems harbour a rich and highly-specialized biodiversity which is particularly susceptible to anthropogenic disturbances such as habitat loss and fragmentation as well as to climate change. Combined with other forms of land-use conversion, construction and maintenance of ski resorts can have severe consequences on alpine biodiversity. In this study, we show how one amphibian and two reptile species, namely Rana temporaria, Zootoca vivipara and Vipera berus, respond to such impacts by means of a multi-season occupancy analysis. We found all three species both in and outside ski-runs, showing that these habitats do not necessarily preclude their occurrence. Contrarily, this is influenced more by microhabitat availability, such as ground vegetation, humid areas, and rock cover, rather than by macro-characteristics like elevation or habitat type. Moreover, we found a climatic influence on the year-to-year occupancy change of the species, with activity-months conditions being more relevant than overwintering ones. Our results demonstrate how, in the specific case of reptiles and amphibians, ski resorts do not necessarily limit species' occurrence and that a mild series of management actions might secure the species' persistence in the area.

opencc-by-4.0Feb 2014View details →

Data from: Admixture facilitates genetic adaptations to high altitude in Tibet

Genotype data for the 69 high altitude Sherpa individuals from   Jeong C, Alkorta-Aranburu G, Basnyat B, Neupane M, Witonsky DB, Pritchard JK, Beall CM, Di Rienzo A. Admixture facilitates genetic adaptations to high altitude in Tibet. Nat Commun. 2014;5:3281. doi: 10.1038/ncomms4281. PMID: 24513612; PMCID: PMC4643256.   Files are in PLINK binary format.

opencc-zeroMay 2024View details →

Changes in ventilatory responses at high altitude measured using rebreathing

Ventilatory responses to hypoxia and hypercapnia play a vital role in maintaining gas exchange homeostasis, and in adaptation to high-altitude environments. This study investigates the mechanisms underlying sensitization of hypoxic and hypercapnic ventilatory responses (HVR and HCVR, respectively) in individuals acclimatized to moderate high altitude (3800 m). Thirty-one participants underwent chemoreflex testing using the Duffin modified rebreathing technique. Measures were taken at sea level and after 2 days of acclimatization to high altitude. Ventilatory recruitment thresholds (VRT), HCVR-Hyperoxia, HCVR-Hypoxia, and HVR were quantified. Acclimatization to high altitude resulted in increased HVR (p<0.001) and HCVR-Hyperoxia (p<0.001), as expected. We also observed that the decrease in VRT under hypoxic test conditions significantly contributed to the elevated HVR at high altitude since the change in VRT across hyperoxic and hypoxic test conditions was greater at high altitude compared to baseline sea level tests (p=0.043). Pre-VRT, or basal, ventilation also increased at high altitude (p<0.001), but the change did not differ between oxygen conditions. Taken together, this data suggests that the increase in HVR at high altitude is at least partially driven by a larger decrease in the VRT in hypoxia versus hyperoxia at high altitude compared to sea level. This study highlights the intricacies of respiratory adaptations during acclimatization to moderate high altitude, shedding light on the roles of the VRT, baseline respiratory drive, and two-slope HCVR in this process. These findings contribute to our understanding of how the human respiratory control responds to hypoxic and hypercapnic challenges at high altitude.

Fig 8 in First report of the high altitude cladoceran species Streblocerus serricaudatus (Fischer, 1849) S.LAT from the Western Ghats of India, Tamil Nadu

Fig 8: Antennule with 3 spines at the tip.

Fig 1 in First report of the high altitude cladoceran species Streblocerus serricaudatus (Fischer, 1849) S.LAT from the Western Ghats of India, Tamil Nadu

Fig 1: Posterior part of the body of Streblocerrus serricaudatus showing protuberances.

Fig 5 in First report of the high altitude cladoceran species Streblocerus serricaudatus (Fischer, 1849) S.LAT from the Western Ghats of India, Tamil Nadu

Fig 5: Carapace. Fig 6: Bilobed Post abdomen.

Fig 2 in First report of the high altitude cladoceran species Streblocerus serricaudatus (Fischer, 1849) S.LAT from the Western Ghats of India, Tamil Nadu

Fig 2: Kanyakumari district map showing Pechiparai dam