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opencc-by-4.0Jun 2020View details →

Digital Elevation Models for use with Fogpy

Digital Elevation Models (DEMs) in geotiff format.  One for central Europe and one for northeast USA.  Data sources Central Europe: <a href="https://land.copernicus.eu/imagery-in-situ/eu-dem/eu-dem-v1.1">EU-DEM v1.1 (Copernicus Land Monitoring Service)</a> USA: <a href="https://viewer.nationalmap.gov/datasets/">USGS National Map</a> Data processing Data were processed with GDAL.  After collecting the required source files in geotiff, the final file was produced with two steps: <pre>gdal_merge.py -o merged.tif */*.tif</pre> <pre>gdalwarp -r bilinear -t_srs '+proj=eqc +lat_ts=0 +lat_0=0 +lon_0=0 +x_0=0 +y_0=0 +ellps=WGS84 +units=m +no_defs +type=crs' -tr 500 500 merged.tif merged-2-500.tif</pre> Context These elevation models are needed by <a href="https://github.com/pytroll/fogpy">Fogpy</a>, a satellite fog retrieval package within the Pytroll satellite processing set of tools.

Elevation Models for Reproducible Evaluation of Terrain Representation – Multiscale Models – Valdez ASCII

Multiscale elevation models centered on Valdez, Alaska, USA Resolutions: 3.3, 7.5, 15, 30, 90, 250, 500, 1,000, and 2,000 meters, 1500 x 1,500 height samples each File format: Esri ASCII grid When using these elevation models in an academic publication, please cite the following article, which describes the process and rationale for compiling these models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

Elevation Models for Reproducible Evaluation of Terrain Representation – Archetypal Landforms – Massanutten Mountain GeoTIFF

An elevation model of Massanutten Mountain, Virginia, USA Landform features: folded ridges, hogback, water gap, meander Resolution: 10 meter, 3,900 x 3,900 height samples File format: GeoTIFF This is one model of a set of elevation models: <a href="https://doi.org/10.5281/zenodo.3938020">https://doi.org/10.5281/zenodo.3938020</a>. Please cite the entire set of models. When using this elevation model in an academic publication, please cite the following article, which describes the process and rationale for compiling elevation models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

Elevation Models for Reproducible Evaluation of Terrain Representation – Multiscale Models – Gore Range GeoTIFF

Multiscale elevation models centered on Gore Range, Colorado, USA Resolutions: 1, 5, 15, 30, 90, 250, 500, 1,000, 2,000, 2,500, and 5,000 meters, 1500 x 1,500 height samples each File format: GeoTIFF When using these elevation models in an academic publication, please cite the following article, which describes the process and rationale for compiling these models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

Elevation Models for Reproducible Evaluation of Terrain Representation – Archetypal Landforms – Sandhills GeoTIFF

An elevation model of Sandhills, Nebraska, USA Landform features: stabilized dune field Resolution: 10 meter, 4,500 x 4,500 height samples File format: GeoTIFF This is one model of a set of elevation models: <a href="https://doi.org/10.5281/zenodo.3938020">https://doi.org/10.5281/zenodo.3938020</a>. Please cite the entire set of models. When using this elevation model in an academic publication, please cite the following article, which describes the process and rationale for compiling elevation models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

Elevation Models for Reproducible Evaluation of Terrain Representation – Archetypal Landforms – Jackson Hole (riverbed) GeoTIFF

An elevation model of Jackson Hole, Wyoming, USA Landform features: braided river, fluvial terrace Resolution: 2 meter, 4,200 x 4,200height samples File format: GeoTIFF This is one model of a set of elevation models: <a href="https://doi.org/10.5281/zenodo.3938020">https://doi.org/10.5281/zenodo.3938020</a>. Please cite the entire set of models. When using this elevation model in an academic publication, please cite the following article, which describes the process and rationale for compiling elevation models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

Elevation Models for Reproducible Evaluation of Terrain Representation – Archetypal Landforms – Sandhills ASCII

An elevation model of Sandhills, Nebraska, USA Landform features: stabilized dune field Resolution: 10 meter, 4,500 x 4,500 height samples File format: Esri ASCII grid This is one model of a set of elevation models: <a href="https://doi.org/10.5281/zenodo.3938020">https://doi.org/10.5281/zenodo.3938020</a>. Please cite the entire set of models. Version 1.0.1 removes empty space characters from the file header, which prevented the file from being opened by some software. When using this elevation model in an academic publication, please cite the following article, which describes the process and rationale for compiling elevation models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

Elevation Models for Reproducible Evaluation of Terrain Representation – Multiscale Models – Gore Range ASCII

Multiscale elevation models centered on Gore Range, Colorado, USA Resolutions: 1, 5, 15, 30, 90, 250, 500, 1,000, 2,000, 2,500, and 5,000 meters, 1500 x 1,500 height samples each File format: Esri ASCII grid Version 1.1.0 does not contain GeoTIFF files that were included by mistake in version 1.0.0. When using these elevation models in an academic publication, please cite the following article, which describes the process and rationale for compiling these models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

Elevation Models for Reproducible Evaluation of Terrain Representation – Archetypal Landforms – Crater Lake ASCII

An elevation model of Crater Lake, Oregon, USA Landform features: caldera, cinder cone, lava flow Resolution: 3.33 meter, 5,200 x 5,200 height samples File format: Esri ASCII grid This is one model of a set of elevation models: <a href="https://doi.org/10.5281/zenodo.3938020">https://doi.org/10.5281/zenodo.3938020</a>. Please cite the entire set of models. Version 1.0.1 removes empty space characters from the file header, which prevented the file from being opened by some software. When using this elevation model in an academic publication, please cite the following article, which describes the process and rationale for compiling elevation models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

Water Management Panel Data (1985-2018) of California's Western Sierra Nevada High-Elevation Basins

This is 34 years of water data from 14 high-elevation basins on the western slope of California's Sierra Nevada. All data originates from the California Data Exchange Center (CDEC: <a href="http://cdec.water.ca.gov/">http://cdec.water.ca.gov/</a>). The data were cleaned and aggregated between the years 2013-2019. The panel data table includes records of April-July runoff forecasts (the 50% exceedance forecast), forecast uncertainty (as measured by the difference between the 90% and 10% exceedance forecasts), available reservoir space to store runoff on March 31st, April-July releases, and the interaction term forecastXuncertainty. The data are organized as an unbalanced panel data table (N=416) for 34 years of records for 14 basins. All water volumes are reported in cubic kilometers. This data set includes a key that details the common names of each basins, each of their aggregated surface reservoir storage capacity, the measurement location where the data are aggregated in reference to, and a three letter code that links the key to the panel data table. This is the same three letter key used to query some of these data within CDEC. Detailed information on the project is available in the companion open-access publication (DOI available upon publication). The description of this data is in progress and will be fully updated upon acceptance of accompanying peer-reviewed journal article.

Elevation Models for Reproducible Evaluation of Terrain Representation – Archetypal Landforms – Jackson Hole (riverbed) ASCII

An elevation model of Jackson Hole, Wyoming, USA Landform features: braided river, fluvial terrace Resolution: 2 meter, 4,200 x 4,200 height samples File format: Esri ASCII grid This is one model of a set of elevation models: <a href="https://doi.org/10.5281/zenodo.3938020">https://doi.org/10.5281/zenodo.3938020</a>. Please cite the entire set of models. Version 1.0.1 removes empty space characters from the file header, which prevented the file from being opened by some software. When using this elevation model in an academic publication, please cite the following article, which describes the process and rationale for compiling elevation models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

Elevation Models for Reproducible Evaluation of Terrain Representation – Archetypal Landforms – Great Sand Dunes ASCII

An elevation model of Great Sand Dunes, Colorado, USA Landform features: active dune field, sand sheet, sabkha Resolution: 3.3 meter, 5,300 x 5,300 height samples File format: Esri ASCII grid This is one model of a set of elevation models: <a href="https://doi.org/10.5281/zenodo.3938020">https://doi.org/10.5281/zenodo.3938020</a>. Please cite the entire set of models. Version 1.0.1 removes empty space characters from the file header, which prevented the file from being opened by some software. When using this elevation model in an academic publication, please cite the following article, which describes the process and rationale for compiling elevation models: Kennelly, P. J., Patterson, T., Jenny, B., Huffman, D. P., Marston, B. E., Bell, S. and Tait, A. M. (2021). Elevation models for reproducible evaluation of terrain representation. Cartography and Geographic Information Science, 48:1, 63–77. DOI: <a href="http://doi.org/10.1080/15230406.2020.1830856">10.1080/15230406.2020.1830856</a>

opennotspecifiedMay 2017View details →

FIG. 7 in Comparative chromosomal studies in Rhinolophus formosae and R. luctus from China and Vietnam: elevation of R. l. lanosus to species rank

FIG. 7. Metaphase spreads of R. formosae after CBG-banding (A, B) and silver-staining (C). A — Centromeric heterochromatin is clearly visible at acrocentric chromosomes but only faintly stained at the metacentric ones. The arrows point to the smallest autosomal pair no. 25 which is presumably bi-armed. B — The C-banded X chromosomes of the female R. formosae showed the usual appearance for the family without a large hetero-chromatic block. The arrows indicate pair 25. C — Silver-stained metaphase plate with arrows indicating the NORs

opennotspecifiedMay 2017View details →

FIG. 3 in Comparative chromosomal studies in Rhinolophus formosae and R. luctus from China and Vietnam: elevation of R. l. lanosus to species rank

FIG. 3. FISH examples showing the hybridization patterns of A. stoliczkanus (AST) chromosome-specific painting probes onto metaphase spreads of R. cf. luctoides (A, D), R. lanosus (B, E) and R. formosae (C, F). A–C — hybridization signals of AST1 (red) and AST8 (green) meet in chromosome 5 in R. cf. luctoides (A) and R. lanosus (B) but not in R. formosae (C). In B and C AST X (yellow) was applied in addition. D, E — hybridization signals of AST2 (green) and AST5 (red) meet in chromosome 3 of R. cf. luctoides (D), but not in R. lanosus (E), where AST2 (green) is found in combination with AST1 (red) on chromosome 4 instead.

Data from: Forest structure determines spatial changes in avian community along an elevational gradient in tropical Africa

Aim To test if tree species richness and forest structure drive spatial variation in avian communities along a tropical elevation gradient and to present information about the role of detailed forest parameters. Location A 2000-m long elevational gradient of tropical forest on Mt. Cameroon, west-central Africa. Taxon Birds and trees. Methods We performed bird censuses and vegetation mapping at the same plots across six forested sites at elevations of 350, 650, 1,100, 1,500, 1,850, and 2,200 m a.s.l., with 16 plots per elevation. We tested the effects of elevation, forest structure and tree diversity on the species richness, functional diversity and β-diversity of birds (Bray-Curtis dissimilarity). We used conditional inference trees based on random forests (RF) to investigate these relationships across all elevation sites as well as within elevations. Results Both tree and bird species richness declined monotonically with elevation. Vegetation structure correlated with elevation, and all vegetation attributes significantly differed among elevations. The RF explained 70% of the variance in avian species richness, with the most important predictors being elevation, proportion of dead trees, tree species richness and herb layer coverage. We found that elevation (and shrub layerE2) was a particularly important predictor of avian functional diversity. We identified no important predictor of bird species richness after standardization within elevations, and the proportion of dead trees was the sole important predictor of functional diversity. Within-elevation β-diversity in avian community composition was determined by the dissimilarity of the tree community and differences in leaf area index, solar radiation and spatial distance. The functional dissimilarity was best explained by leaf area index. Main conclusions Apart from elevation itself, spatial distance even within elevations correlated with compositional and functional variation among avian assemblages. Forest structural traits can have a significant influence on distribution of birds. Thus, gaps in the spatial distribution of species such as along elevations might be caused by fine-scale recognition of suitable habitats.

Data from: Environmental context determines the limiting demographic processes for plant recruitment across a species' elevational range

Plant recruitment is a multi-stage process determining population dynamics and species distributions. Still, we have limited understanding of how the successive demographic processes depend on the environmental context across species' distributional ranges. We conducted a large-scale transplant experiment to study recruitment of Pinus cembra over six years. We quantified the effects of environmental conditions on four demographic processes and identified the most limiting across and beyond the pines' elevational range over several years. Realized transition probabilities of the demographic processes varied substantially across the species' distributional range. Seed deposition decreased from the lower to the upper elevational range margin by 90 %, but this reduction was offset by increased seed germination and seedling survival. Dispersal limitation at the upper range margin potentially stems from unsuitable seed caching conditions for the animal seed disperser, whereas increased seed germination might result from enemy escape from fungal pathogens and favourable abiotic conditions at the upper range margin. Our multi-year experiment demonstrates that environmental context is decisive for the local relevance of particular demographic processes. We conclude that experimental studies identifying the limiting demographic processes controlling species distributions are key for projecting future range dynamics of plants.

Data from: Evolutionary constraint on low elevation range expansion: defense-abiotic stress tolerance tradeoff in crosses of the ecological model Boechera stricta

Most transplant experiments across species geographic range boundaries indicate that adaptation to stressful environments outside the range is often constrained. However, the mechanisms of these constraints remain poorly understood. We used extended generation crosses from diverged high and low elevation populations. In experiments across low elevation range boundaries, there was selection on the parental lines for abiotic stress tolerance and resistance to herbivores. However, in support of a defense-tolerance tradeoff, extended generation crosses showed non-independent segregation of these traits in the lab across a drought-stress gradient and in the field across the low elevation range boundary. Genotypic variation in a marker from a region of the genome containing a candidate gene (MYC2) was associated with change in the genetic tradeoff. Thus, using crosses and forward genetics, we found experimental genetic and molecular evidence for a pleiotropic tradeoff that could constrain the evolution of range expansion.

The elevated mist-net frame - Supporting Information: Appendices S1-S4

Summary <ol> <li>Classic standard mist-netting limits sampling to understory birds flying <3 m above ground-level. Methodological innovations targeting higher strata birds (and bats) are important for ecological studies, particularly in tropical forests.</li> <li>I present and evaluate a method of applying elevated mist-net frames (EMF) up to ~25-30 m. I designed detachable mobile alloy frames for standard-sized 3×6 m mist-nets, weighing ~11 kg including fittings, and suspended by 3-point cable-wire mounting. State-of-the-art archery and fishing gear are employed for securing anchor-lines, with hoisting applied by pulley, ropes and guys. </li> <li>EMF is assembled and detached by 2-3 team members within 15-20 minutes, and up-down hoisting lasts 1-3 minutes. EMF excludes tree-climbing and arboreal platforms, through versatile manoeuvring in lightly-cluttered naturally open corridors. EMF costs are source and quantity dependent, and feasible to institutions and grant beneficiaries. </li> <li>EMF is a workable alternative or supplement to existing elevated mist-netting applying poles, ropes and pulleys, owing to strength and durability, replicable construction, and versatile manoeuvrability in upper strata. The EMF-design demonstrates favourable prospects for high-tech development, thus further innovations are recommended. </li> </ol>

Data from: Factors determining species richness patterns of breeding birds along an elevational gradient in the Horn of Africa region

Aim: To document the species richness patterns of breeding birds along elevational gradients and explore its drivers in the Horn of Africa Region. Location: Horn of Africa Region Taxon: Breeding species of birds Methods: Distributional data for breeding birds were collected. Elevational distribution data were extracted, interpolated, and assembled for all birds, passerines and non-passerines. In order to tease apart how different environmental factors contributed to the variation in species richness, we found it necessary to divide the area into four subregions with different climatic regimes and topographic structure. Then, the species richness in each 100 m elevational band was counted along the elevational gradients of each subregion. Pearson's correlation analyses and ordinary least squares (OLS) regressions were used to examine the relationships between species richness and factors Results: The variation in species richness followed hump-shaped patterns for all subregions, although with peak values at different elevations. The bird species groups on the western and eastern slopes showed low and high plateaus with mid-elevational peaks, respectively, but very low species diversities at the highest elevations. Species richness was significantly correlated with temperature range and productivity in each subregion. The temperature range, area and productivity explained 82% of the species richness variations for all birds on the western slope. Main conclusions: The separate analyses of four area subdivisions provide strong indications of how various factors interact. Productivity and temperature range were the best driving factors for shaping the richness patterns, but deviations from expected patterns suggest modifying roles of mist formation zones in the valleys that deeply intersect the large highlands in the west and rich riparian vegetation where water from cool and humid environments at high elevation reaches lower elevations in the arid east. Conservation is recommended in each subregion based on the elevational richness scenarios.

Intracellular sodium elevation reprograms cardiac metabolism: Metabolomics data

Intracellular Na elevation in the heart is a hallmark of pathologies where both acute and chronic metabolic remodeling occurs. We assessed whether acute (75μM ouabain 100nM blebbistatin) and chronic myocardial Naiload (PLM3SA mouse) are causally linked to metabolic remodeling and whether the hypertrophied failing heart shares a common Na-mediated metabolic 'fingerprint'. Control (PLMWT), transgenic (PLM3SA), ouabain treated and hypertrophied Langendorff-perfused mouse hearts were studied by 23Na, 31P, 13C NMR followed by 1H NMR metabolomic profiling. Elevated Nai leads to common adaptive metabolic alterations preceding energetic impairment: a switch from fatty acid to carbohydrate metabolism and changes in steady-state metabolite concentrations (glycolytic, anaplerotic, Krebs cycle intermediates). Inhibition of mitochondrial Na/Ca exchanger by CGP37157 ameliorated the metabolic changes. In silico modelling indicated altered metabolic fluxes (Krebs cycle, fatty acid, carbohydrate, amino acid metabolism). Prevention of Nai overload or inhibition of Na/Camitomay be a new approach to ameliorate metabolic dysregulation in heart failure.