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34 results for “bobcat”
Figure 1 in First attraction record of Trox plicatus Robinson, 1940 (Coleoptera: Trogidae) to feces of bobcat Lynx rufus Schreber, 1777 (Carnivora: Felidae)
Figure 1. Dorsal habitus of Trox plicatus Robinson. Scale barr: 5 mm. / Hábito dorsal de Trox plicatus. Escala: 5 mm.
Figure 5 in First attraction record of Trox plicatus Robinson, 1940 (Coleoptera: Trogidae) to feces of bobcat Lynx rufus Schreber, 1777 (Carnivora: Felidae)
Figure 5. Temperate forest where the specimens of Trox plicatus were found. / Bosque templado donde se encontraron los ejemplares de Trox plicatus.
Figure 4 in First attraction record of Trox plicatus Robinson, 1940 (Coleoptera: Trogidae) to feces of bobcat Lynx rufus Schreber, 1777 (Carnivora: Felidae)
Figure 4. Study region (Las Derrumbadas, Puebla, Mexico) encompassed by a couple of volcanic domes. / Región de estudio (Las Derrumbadas, Puebla, México) conformada por un par de domos volcánicos.
Sonora Bobcat: cloud-free, substellar atmosphere models, spectra, photometry, evolution, and chemistry
<p><strong>OVERVIEW</strong></p> <p>Presented here are models for non-irradiated, substellar mass objects belonging to the Sonora model series, described in Marley et al. (2021). The files presented here are model temperature-pressure structures ("structure"), emergent spectra from the top of the atmosphere ("spectra"), thermal evolution and photometry ("evolution_and_photometry"), and rainout chemical equilibrium tables used to compute the models ("chemistry"). </p> <p>Atmospheric structure and spectra .tar file names specify metallicity [M/H] and carbon-to-oxygen ratio (C/O) relative to solar. For example, "structures+0.0_co1.5<a href="../api/files/2e9ce76a-67fc-4fd6-ae5c-f88f16c610ea/structures%2B0.0_co1.5.tar.gz">.</a>tar.gz" contains the set of radiative-convective equilibrium atmospheric structures for solar metallicity ("+0.0") with C/O=1.5 times the solar abundance. The _co*.* is omitted for solar C/O, or co_1.0. The individual file naming convention is described below. All stated abundances and ratios are relative to Lodders (2010) abundances, see Marley et al. (2021) for details and use caution when referring to other abundance tabulations.</p> <p>This particular set of model atmosphere structures and associated spectra, photometry, and evolution, which we name <strong>Sonora Bobcat</strong>, are for cloudless objects with 3.25 ≤ log g (cgs) ≤ 5.5 and 200 ≤ Teff ≤ 2400K. Steps in T<sub>eff</sub> vary from 25K to 1000K and steps in log g are 0.25 or 0.5. Some combinations of model grid parameters include additional values of the gravity. Models are provided for [M/H] = -0.5, 0.0, and +0.5 and "rainout" chemical equilibrium. A limited set of models with carbon-to-oxygen ratio of 0.5 and 1.5 times solar abundance are also included. For the convenience of having a rectangular table in (T<sub>eff</sub>, gravity) space, models are calculated in regimes that are not reached by the evolution, such as very high gravity and very low T<sub>eff</sub>. Refer to the companion evolution tables to identify combinations of T<sub>eff</sub> and log g outside the bounds covered by the evolution.</p> <p><strong>ATMOSPHERIC STRUCTURE</strong></p> <p>Atmospheric structure and spectra filenames specify Teff and gravity (in mks units) along with [M/H] and (C/O) relative to solar. "co1.5" in version and spectra header nomenclature refers to 1.5 times the solar C/O ratio. _co*.* is generally omitted for 1.0, the solar value. For example, the file t1000g316nc_m-0.5.dat contains the structure of a model with T<sub>eff</sub>=1000K, g=316m/s<sup>2</sup> (the exact value of the gravity is given<sup> </sup>in the first line of the file, see below) , [Fe/H]=-0.5, and C/O=1.0 times the solar value. </p> <p>Temperature structure and spectra files have a one line header giving "Teff, grav(MKS), Y, f_sed, kz_min, [Fe/H], C/O, f_hole". Teff and grav are the effective temperature (K) and gravity (MKS), Y is the He mass fraction. f_sed is a cloud parameterization which is not relevant for these cloudless models and is arbitrarily given as 0.0. Likewise kz_min relates to the atmospheric eddy diffusion coefficient, which is also not relevant for these chemical equilibrium models and is arbitrarily set equal to a placeholder value that is not used in these models. [Fe/H] and C/O are the metallicity and C/O ratios as described above. [Fe/H] is identical to [M/H]. f_hole is another cloud parameter for cloudy models, not relevant to these cloudless models.</p> <p>Columns in the atmosphere structure files describe the atmosphere at discrete levels. Columns give: level index, P(bar), T(K), internally used check parameter, adiabatic temperature gradient (d ln T / d ln P), local temperature gradient (d ln T / d ln P), atmospheric density (g / cm<sup>3</sup>).</p> <p><strong>EVOLUTION AND PHOTOMETRY</strong></p> <p>Evolution and Photometry tables are described in detail in a README file included in that tar file. Evolution files connect mass, effective temperature, radius, age, gravity, and moment of inertia for these model sets. Each set of model spectra is complemented with tables of fluxes and of absolute magnitudes in a number of photometric systems commonly used in brown dwarf and exoplanet research (MKO, Keck, 2MASS, SDSS, WISE, Spitzer IRAC, etc). Fluxes and magnitudes for the full set of JWST filters is also included in separate tables. Magnitudes are computed on the Vega system (using the Vega spectrum of Bohlin & Gilliland 2004) or on the AB system (e.g. for SDSS).</p> <p><strong>SPECTRA</strong></p> <p>The model spectra each contain close to 362000 wavelength points. The resolving power varies with wavelength and ranges from R=6000 to 200000 but is otherwise the same for all spectra. The first line gives the model parameters in the same format as the structure files described above. This is followed by the spectrum</p> <p>Column 1: wavelength in µm</p> <p>Column 2: <strong>Radiation flux <em>F<sub>ν</sub></em></strong><sub> </sub>= \(4\pi\) x Eddington flux <em>H</em><sub>ν</sub>, in erg/cm<sup>2</sup>/s/Hz (always exercise caution with factors of \(4\pi\) when comparing to the radiation and Eddington flux, e.g., see Section 3.3 of Hubeny & Mihalas, "Theory of Stellar Atmospheres")</p> <p>The spectral fluxes are given at the top of the atmosphere and are strictly monochromatic. The model spectrum provides no information in the wavelength range between two tabulated points. Unless a spectral line or feature is well resolved,<em> interpolation in wavelength is not advised</em>. For comparison with data, the model spectra need to be convolved and binned to the instrumental resolution and sampling. In our experience, a minimum of 10 wavelength points is necessary to obtain a reasonable average flux over a wavelength interval. This is a rule of thumb and caution is advised, especially when comparing with high resolution data. The flux received at Earth is that given in the table scaled by (R/D)<sup>2</sup> where R is the radius of the object (given in the companion evolution tables) and D its distance. </p> <p>The solar spectra and photometry are the same as those archived at https://zenodo.org/record/1309035#.YOyz4S1h2X0, which did not provide the T(P) profiles available here.</p> <p><strong>CHEMISTRY</strong></p> <p>We also separately include rainout chemical equilibrium tables for these same atmospheric bulk abundances. These chemistry files are described in detail by their own README file. Additional chemistry tables, beyond those used for the models presented here, are also included for completeness. Users interested in the chemical abundances of the structure models must interpolate within the matching chemistry file for the atmospheric species of interest.</p> <p><strong>CREDITS</strong></p> <p>If you use these tables in your research, please cite Marley et al. (2021, Astrophysical Journal, Volume 920, Issue 2, id.85.)</p> <p>16 Feb 2024: Error corrected in Column 2 heading. Column 2 is the Radiation flux, not the Eddington flux as previously stated. Citation updated.</p> <p> </p>
Data from: Climate connectivity of the bobcat in the Great Lakes region
<p>The Great Lakes and the St. Lawrence River are imposing barriers for wildlife and the additive effect of urban and agricultural development that dominates the lower Great Lakes region likely further reduces functional connectivity for many terrestrial species. As the climate warms species will need to track climate across these barriers. It is important, therefore, to investigate land cover and bioclimatic hypotheses that may explain the northward expansion of species through the Great Lakes. We investigated the functional connectivity of a vagile generalist, the bobcat, as a representative generalist forest species common to the region. We genotyped tissue samples collected across the region at 14 microsatellite loci and compared different landscape hypotheses that might explain the observed gene flow or functional connectivity. We found that the Great Lakes and the additive influence of forest stands with either low or high canopy cover and deep lake-effect snow have disrupted gene flow, whereas intermediate forest cover has facilitated gene flow. Functional connectivity in southern Ontario is relatively low and was limited in part by the low amount of forest cover. Pathways across the Great Lakes were through the Niagara region and through the Lower Peninsula of Michigan over the Straits of Mackinac and the St. Mary's River. These pathways are important routes for bobcat range expansion north of the Great Lakes and are also likely pathways that many other mobile habitat generalists must navigate to track the changing climate. The extent to which species can navigate these routes will be important for determining the future biodiversity of areas north of the Great Lakes.</p>
Genetic diversity in two insular populations of bobcats (Lynx rufus)
<p>We documented changes in genetic diversity in an isolated, reintroduced population of bobcats on Cumberland Island (CUIS), Georgia, USA, compared to another bobcat population on Kiawah Island, South Carolina, USA, that was naturally established and experiences limited immigration from the mainland. We compared the predictions of a novel population viability analysis (PVA) to empirical estimates of abundance and genetic diversity on CUIS and used our PVA to identify management actions that are likely to support long-term viability.</p>
Figure 2 in First attraction record of Trox plicatus Robinson, 1940 (Coleoptera: Trogidae) to feces of bobcat Lynx rufus Schreber, 1777 (Carnivora: Felidae)
Figure 2. Footprint of the bobcat Lynx rufus Schreber. / Huella de lince rojo Lynx rufus Schreber.
Genetic diversity in two insular populations of bobcats (Lynx rufus)
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Data from: Evidence of extensive home range sharing among mother-daughter bobcat pairs in the wildland-urban interface of the Tucson Mountains
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Data from: Co-occurrence of bobcats, coyotes, and ocelots in Texas
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Data from: History matters: contemporary versus historic population structure of bobcats in the New England region, USA
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Data from: Climate connectivity of the bobcat in the Great Lakes region
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Data from: Spatial segregation and habitat partitioning of bobcat and Canada lynx
<p>Harvest records suggest that the abundance of bobcats (<i>Lynx rufus</i>) has increased and the leading edge of their distribution has spread northward, while the trailing edge of the Canada lynx (<i>Lynx canadensis</i>) range has contracted in Ontario, Canada. There has been a debate about whether these closely related felids might compete in areas of sympatry, but there is little research on sympatric populations of bobcat and lynx. Both species are found on the north shore of Lake Huron in Ontario, Canada, which provided an opportunity to investigate their spatial patterns and habitat use. We surveyed snowmobile routes for snow tracks over 3 winters and estimated probability of occupancy for the two felid species while accounting for detectability. Bobcat and lynx tracks were never found on the same survey route. Bobcat occupancy increased with habitat heterogeneity whereas lynx occupancy increased with homogeneity. Our results fit with the common assumption of the generalist and specialist natures of bobcat and lynx, respectively. Our findings suggest that bobcats invaded former lynx territory after these areas became vacant. The story of the bobcat and the lynx is one of the loss of a unique, boreal specialist due to anthropogenic change, and eventual replacement by an adaptable generalist.</p>
Data from: Effects of sun angle, lunar illumination, and diurnal temperature on temporal movement rates of sympatric ocelots and bobcats in South Texas
<p>Sympatric ocelots (<i>Leopardus pardalis</i>) and bobcats (<i>Lynx rufus</i>) in South Texas show substantial overlap in body size, food habits, and habitat use. Consequently, we explore whether temporal niche partitioning may explain ocelot and bobcat coexistence. We investigated the influence of sun angle, lunar illumination, and maximum diurnal temperature on temporal movement rates of sympatric ocelots (n = 8) and bobcats (n = 6) using a combination of high-frequency GPS locations and bi-axial accelerometer data. We demonstrated that accelerometer data could be used to predict movement rates, providing a nearly continuous measure of animal activity and supplementing GPS locations. Ocelots showed a strong nocturnal activity pattern with the highest movement rates at night whereas bobcats showed a crepuscular activity pattern with the highest movement rates occurring around sunrise and sunset. Although bobcat activity levels were lower during the day, bobcat diurnal activity was higher than ocelot diurnal activity. During warmer months, bobcats were more active on nights with high levels of lunar illumination. In contrast, ocelots showed the highest nocturnal activity levels during periods of low lunar illumination. Ocelots showed reduced diurnal activity on hotter days. Our results indicate that ocelot and bobcat coexistence in South Texas can be partially explained by temporal niche partitioning, although both felids showed periods of overlapping activity during nocturnal and crepuscular periods.</p>
Data from: Disease and freeways drive genetic change in urban bobcat populations
Urbanization profoundly impacts animal populations by causing isolation, increased susceptibility to disease, and exposure to toxicants. Genetic effects include reduced effective population size, increased population substructure, and decreased adaptive potential. We investigated the influence that urbanization and a disease epizootic had on the population genetics of bobcats (Lynx rufus) distributed across a highly fragmented urban landscape. We genotyped more than 300 bobcats, sampled from 1996-2012, for variation at nine neutral and seven immune gene-linked microsatellite loci. We found that two freeways are significant barriers to gene flow. Further, a 3-year disease epizootic, associated with secondary anticoagulant rodenticide exposure, caused a population bottleneck that led to significant genetic differentiation between pre- and post-disease populations that was greater than that between populations separated by major freeways for > 60 years. However, balancing selection acted on immune-linked loci during the epizootic, maintaining variation at functional regions. Conservation assessments need to assay loci that are potentially under selection in order to better preserve the adaptive potential of populations at the urban-wildland interface. Further, inter-connected regions that contain appropriate habitat for wildlife will be critical to the long-term viability of animal populations in urban landscapes.
2013 BoBcat Currents
<p>These are the 1m and 5m depth near-surface currents for the year 2013 in the Bay of Bengal produced using the BoBcat algorithm.</p>
Data from: Fine-scale habitat selection by sympatric Canada lynx and bobcat
<p>The Canada lynx (<em>Lynx canadensis</em>) and the bobcat (<em>Lynx rufus</em>) are closely related species with overlap at their range peripheries, but the factors that limit each species and the interactions between them are not well understood. Habitat selection is a hierarchical process, in which selection at higher orders (geographic range, home range) may constrain selection at lower orders (within the home range). Habitat selection at a very fine scale within the home range has been less studied for both lynx and bobcat compared to selection at broader spatio-temporal scales. To compare this fourth-order habitat selection by the two species in an area of sympatry, we tracked lynx and bobcat during the winters of 2017 and 2018 on the north shore of Lake Huron, Ontario. We found that both lynx and bobcat selected shallower snow, higher snowshoe hare abundance, and higher amounts of coniferous forest at the fourth order. However, the two species were spatially segregated at the second order, and lynx were found in areas with deeper snow, more snowshoe hare, and more coniferous forest. Taken together, our findings demonstrate that the lynx and bobcat select different resources at the second order, assorting along an environmental gradient in the study area, and that competition is unlikely to be occurring between the two species at finer scales.</p>
Urbanization reduces genetic connectivity in bobcats (Lynx rufus) at both intra- and inter-population spatial scales
<p>Urbanization is a major factor driving habitat fragmentation and connectivity loss in wildlife. However, the impacts of urbanization on connectivity can vary among species and even populations due to differences in local landscape characteristics, and our ability to detect these relationships may depend on the spatial scale at which they are measured. Bobcats (<i>Lynx rufus</i>) are relatively sensitive to urbanization and the status of bobcat populations is an important indicator of connectivity in urban coastal southern California. We genotyped 271 bobcats at 13,520 SNP loci to conduct a replicated landscape resistance analysis in five genetically distinct populations. We tested urban and natural factors potentially influencing individual connectivity in each population separately, as well as study-wide. Overall, landscape genomic effects were most frequently detected at the study-wide spatial scale, with urban land cover (measured as impervious surface) having negative effects and topographic roughness having positive effects on gene flow. The negative effect of urban land cover on connectivity was also evident when populations were analyzed separately despite varying substantially in spatial area and the proportion of urban development, confirming a pervasive impact of urbanization largely independent of spatial scale. The effect of urban development was strongest in one population where stream habitat had been lost to development, suggesting that riparian corridors may help mitigate reduced connectivity in urbanizing areas. Our results demonstrate the importance of replicating landscape genetic analyses across populations and considering how landscape genetic effects may vary with spatial scale and local landscape structure.</p>
Data and code for: Insights into the spatial ecology of severely injured free-living felids: Iberian lynx, bobcat, and snow leopard.
<p>Data and code for: Insights into the spatial ecology of severely injured free-living felids: Iberian lynx, bobcat, and snow leopard.</p> <p>To protect the endangered Iberian lynx, data for this species is not provided. Iberian lynx data may be provided upon reasonable request to the authors.</p>
Data from: Population and genetic outcomes 20 years after reintroducing bobcats (Lynx rufus) to Cumberland Island, Georgia USA
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