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831 results for “Partition”
Brighter Ocean: Arctic sea ice solar partitioning
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Anatomical partitioning has little influence in topologies from Bayesian phylogenetic analyses of morphological data
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Niche partitioning between planktivorous fish in the pelagic Baltic Sea assessed by DNA metabarcoding, qPCR and microscopy: Data and Analyses
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Data from: Resource partitioning among pelagic predators remains stable despite annual variability in diet composition
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Data from: Seasonal diet partition among top predators of a small island, Iriomotejima island in the Ryukyu Archipelago, Japan
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Supplement to: Electron energy partition across interplanetary shocks: III. Analysis
<p><strong>Quick Summary:</strong></p> <p>The PDF file herein provides additional example superposed epoch analysis (SEA) plots in addition to reference tables of the upstream values used to normalize the SEA data in this file and those in the paper this supplement supports. This is a supplement to Part 3 of a three-part study of the electron velocity distribution functions (VDFs) observed near interplanetary (IP) shocks by the <em>Wind</em> spacecraft. Paper I [<a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab22bd"><em>Wilson et al.</em>, 2019a</a>] introduced the methodology and data products [<a href="https://doi.org/10.5281/zenodo.2875806"><em>Wilson et al.</em>, 2019c</a>] for fitting the electron VDFs to the sum of three model functions. Paper II [<a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab5445"><em>Wilson et al.</em>, 2019b</a>] presents the statistics of the fit parameters produced and provided in the data products from Paper I. Paper III presents and summarizes the analysis of the fit parameters. The papers share the title <strong><em>Electron energy partition across interplanetary shocks</em></strong>.</p> <p><strong><em>Wind</em> Spacecraft:</strong></p> <p>The <em>Wind</em> spacecraft (<a href="http://wind.nasa.gov/">https://wind.nasa.gov</a>) was launched on November 1, 1994 and currently orbits the first Lagrange point between the Earth and sun. It holds a suite of instruments from gamma ray detectors to quasi-static magnetic field instruments, <strong>B</strong><sub>o</sub>. The instruments used in this study and these datasets are the fluxgate magnetometer (<a href="https://doi.org/10.1007/BF00751330">MFI</a>), the radio receivers (<a href="https://doi.org/10.1007/BF00751331">WAVES</a>), ion Faraday cups (<a href="https://doi.org/10.1007/BF00751326">SWE</a>), and the electron and ion electrostatic analyzers (<a href="https://doi.org/10.1007/BF00751328">3DP</a>). The MFI measures 3-vector <strong>B</strong><sub>o</sub> at ~11 samples per second (sps); the SWE measures reduced VDFs of the thermal proton and alpha-particle populations from which velocity moments are derived and used herein; WAVES observes electromagnetic radiation from ~4 kHz to >12 MHz which provides an observation of the upper hybrid line (also called the plasma line) used to define the total electron density; and 3DP observes full 4π steradian VDFs of electrons and ions from a few eV to ~30 keV which provide both ion velocity moments and the electron VDFs modeled herein.</p> <p><strong>PDF Supplement Description:</strong></p> <p>Definitions:</p> <ul> <li>VDF = velocity distribution function</li> <li>Electron Components/Populations [taken from <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab22bd"><em>Wilson et al.</em>, 2019a</a>,<a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab5445">b</a>] <ul> <li>Core (<em>s</em> = ec): cold, dense population with energies <span class="math-tex">\(E_{ec} \lesssim \text{15 eV}\)</span></li> <li>Halo (<em>s</em> = eh): hot, tenuous population with energies <span class="math-tex">\(E_{eh} \gtrsim \text{20 eV}\)</span></li> <li>Beam/Strahl (<em>s</em> = eb): anti-sunward propagating, magnetic field-aligned beam (or strahl) with <span class="math-tex">\(E_{eb} \sim \text{a few tens of eV}\)</span></li> <li>Effective (<em>s</em> = eff): effective total electron population, i.e., used for approximate moments rather than integrating entire VDF</li> </ul> </li> <li>Ion Components/Populations [taken from <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab22bd"><em>Wilson et al.</em>, 2019a</a>,<a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab5445">b</a>] <ul> <li>Proton (<em>s</em> = p): core solar wind proton beam, i.e., main proton population streaming away from sun</li> <li>Alpha-particles (<em>s</em> = <span class="math-tex">\(\alpha\)</span>): alpha-particle magnetic field-aligned beam</li> </ul> </li> <li><span class="math-tex">\(k_{B}\)</span> = the Boltzmann constant [J K<sup>-1</sup>]</li> <li><span class="math-tex">\(\mu_{o}\)</span> = permeability of free space [T m A<sup>-1</sup>]</li> <li><span class="math-tex">\(n_{s}\)</span>= number density of species <em>s</em> [cm<sup>-3</sup>] (s = ec for core, eh for halo, eb for beam/strahl, p for proton, etc.)</li> <li><span class="math-tex">\(B_{o, j}\)</span>= j<sup>th</sup> component (GSE coordinate basis) of quasi-static magnetic field vector [nT]</li> <li><span class="math-tex">\(V_{Ts, j}\)</span> = j<sup>th</sup> component (relative to <strong>B</strong><sub>o</sub>) of thermal speed of species <em>s</em> [km/s] <ul> <li><span class="math-tex">\(V_{Ts, j} = \sqrt{ \tfrac{ 2 \ k_{B} \ T_{s, j} }{ m_{s} }}\)</span>, where <span class="math-tex">\(T_{s, j}\)</span> is the j<sup>th</sup> component (relative to <strong>B</strong><sub>o</sub>) of the temperature of species <em>s</em> [eV]</li> </ul> </li> <li><span class="math-tex">\(V_{os, j}\)</span> = j<sup>th</sup> component (relative to <strong>B</strong><sub>o</sub>) of drift speed of species <em>s</em> [km/s] in ion rest frame</li> <li><span class="math-tex">\(V_{s, j}\)</span> = j<sup>th</sup> component (GSE coordinate basis) bulk velocity of species <em>s</em> [km/s] in spacecraft frame</li> <li><span class="math-tex">\(T_{s, tot} = {1 \over 3} (T_{s, \parallel} + 2 \ T_{s, \perp})\)</span>, where <span class="math-tex">\(\parallel(\perp)\)</span> is the parallel(perpendicular) component relative to <strong>B</strong><sub>o</sub></li> <li><span class="math-tex">\(P_{s, j} = n_{s} \ k_{B} \ T_{s, j}\)</span> = partial thermal pressure [eV cm<sup>-3</sup>] of the <em>j</em><sup>th</sup> component of species <em>s</em></li> <li><span class="math-tex">\(P_{t, j} = \sum_{s} \ P_{s, j}\)</span> = total thermal pressure [eV cm<sup>-3</sup>] of the <em>j</em><sup>th</sup> component summed over all species including ions</li> <li><span class="math-tex">\(\mathcal{A}_{s} = \left(\tfrac{ T_{\perp} }{ T_{\parallel} } \right)_{s}\)</span> = temperature anisotropy [N/A] of species <em>s</em></li> <li><span class="math-tex">\(\xi_{s, j} = \tfrac{1}{2} m_{s} \ n_{s} \ V_{os, j}^{2}\)</span> = ram energy density [eV cm<sup>-3</sup>] <em>j</em><sup>th</sup> component of species <em>s</em></li> <li><span class="math-tex">\(\epsilon_{j} = \tfrac{ B_{o}^{2} }{ 2 \ \mu_{o} } + \sum_{s} \left[ P_{s, j} + \xi_{s, j} \right]\)</span> = total energy density [eV cm<sup>-3</sup>] of the <em>j</em><sup>th</sup> component of the system in the plasma bulk flow rest frame</li> <li><span class="math-tex">\(\zeta_{s, j} = \tfrac{ \xi_{s, j} }{ \epsilon_{j} }\)</span> = ratio of the ram energy density of the <em>j</em><sup>th</sup> component of species <em>s</em> to the total energy density [N/A]</li> <li><span class="math-tex">\(\psi_{s, j} = \tfrac{ P_{s, j} }{ \epsilon_{j} }\)</span> = ratio of the thermal energy density of the <em>j</em><sup>th</sup> component of species <em>s</em> to the total energy density [N/A]</li> <li><span class="math-tex">\(\Pi_{s, j} = \tfrac{ P_{s, j} }{ P_{t, j} }\)</span> = ratio of the partial thermal pressure of the <em>j</em><sup>th</sup> component of species <em>s</em> to the total thermal pressure [N/A]</li> <li><span class="math-tex">\(s_{es}\)</span> = exponent for the symmetric self-similar model VDF of species <em>s</em></li> <li><span class="math-tex">\(\kappa_{es}\)</span> = kappa value for the bi-kappa VDF of species <em>s</em></li> <li><span class="math-tex">\(p_{es}(q_{es})\)</span> = parallel(perpendicular) exponent for the asymmetric self-similar model VDF of species <em>s</em></li> <li><span class="math-tex">\(n_{eff} = \sum_{s} \ n_{s}\)</span> = effective number density of all electron populations</li> <li><span class="math-tex">\(T_{eff, j} = \tfrac{ \sum_{s} \ n_{s} \ T_{s, j} }{ n_{eff} }\)</span> = effective temperature of the <em>j</em><sup>th</sup> component of all electrons populations</li> <li><span class="math-tex">\(\beta_{s, j} = \tfrac{ 2 \ \mu_{o} \ n_{s} \ k_{B} \ T_{s, j} }{ B_{o}^{2} }\)</span> = plasma beta [N/A] of the <em>j</em><sup>th</sup> component of species <em>s</em></li> </ul> <p> </p> <p>This PDF supplement contains the following SEA plots:</p> <ul> <li><span class="math-tex">\(T_{s, j}\)</span> vs <span class="math-tex">\(\Delta\)</span>t (for <em>s</em> = ec, eh, and eb and <em>j</em> = <span class="math-tex">\(\parallel \text{ or } \perp \text{ or tot}\)</span>)</li> <li><span class="math-tex">\(\mathcal{A}_{s}\)</span> vs <span class="math-tex">\(\Delta\)</span>t (for <em>s</em> = ec, eh, and eb)</li> <li><span class="math-tex">\(\left( \tfrac{ T_{s} }{ T_{eff} } \right)_{j}\)</span> vs <span class="math-tex">\(\Delta\)</span>t (for <em>s</em> = ec, eh, and eb and j = <span class="math-tex">\(\parallel \text{ or } \perp \text{ or tot}\)</span>)</li> <li> <p><span class="math-tex">\(\psi_{s, j}\)</span> vs <span class="math-tex">\(\Delta\)</span>t (for <em>s</em> = ec, eh, eb, p, and <span class="math-tex">\(\alpha\)</span> and j = <span class="math-tex">\(\parallel \text{ or } \perp \text{ or tot}\)</span>)</p> </li> <li> <p><span class="math-tex">\(\Pi_{s, j}\)</span> vs <span class="math-tex">\(\Delta\)</span>t (for <em>s</em> = ec, eh, eb, p, and <span class="math-tex">\(\alpha\)</span> and j = <span class="math-tex">\(\parallel \text{ or } \perp \text{ or tot}\)</span>)</p> </li> </ul> <p>The PDF supplement contains tables of upstream median values for each shock used for normalizing the SEA plots, where the parameters listed include:</p> <ul> <li><span class="math-tex">\(T_{s, j}\)</span> (for <em>s</em> = ec, eh, and eb and j = <span class="math-tex">\(\parallel \text{ or } \perp \text{ or tot}\)</span>)</li> <li><span class="math-tex">\(n_{s}\)</span> (for <em>s</em> = ec, eh, eb, and eff and j = <span class="math-tex">\(\parallel \text{ or } \perp \text{ or tot}\)</span>)</li> <li><span class="math-tex">\(\tfrac{ n_{s} }{ n_{eff} }\)</span> (for <em>s</em> = ec, eh, and eb and j = <span class="math-tex">\(\parallel \text{ or } \perp \text{ or tot}\)</span>)</li> <li><span class="math-tex">\(\beta_{s, j}\)</span> (for <em>s</em> = ec, eh, and eb and j = <span class="math-tex">\(\parallel \text{ or } \perp \text{ or tot}\)</span>)</li> <li><span class="math-tex">\(s_{ec}\text{, }\kappa_{eh}\text{, and }\kappa_{eb}\)</span></li> <li><span class="math-tex">\(\mathcal{A}_{s}\)</span> (for <em>s</em> = ec, eh, eb, and eff)</li> <li><span class="math-tex">\(\left( \tfrac{ T_{s} }{ T_{eff} } \right)_{j}\)</span> (for <em>s</em> = ec, eh, and eb and j = <span class="math-tex">\(\parallel \text{ or } \perp \text{ or tot}\)</span>)</li> </ul>
Data: Assessing year-round habitat use by migratory sea ducks in a multi-species context reveals seasonal variation in habitat selection and partitioning
<p>This data file consists of state-space model-derived locations and individual data used to analyze transmitter effects for sea ducks in Eastern North America and is associated with the manuscript "Assessing year-round habitat use by migratory sea ducks in a multi-species context reveals seasonal variation in habitat selection and partitioning" published in Ecography. Columns are organized as follows:</p> <p>id - unique identifier</p> <p>species - species from which the centroid was obtained (BLSC = black scoter, COEI = common eider, LTDU = long-tailed duck, SUSC = surf scoter, WWSC = white-winged scoter)</p> <p>date - date of location (mm/dd/yy)</p> <p>jday - Julian date of location</p> <p>year - calendar year of location</p> <p>lon - longitude of location</p> <p>lat - latitude of location</p> <p>b - average assignment of location to either migrant (1) or resident (2) across all runs of the state-space model</p> <p>b.5 - most probable behavioral category based on average state assignment (1 = b ≤ 1.5 ; 2 = b > 1.5)</p> <p>sex - sex of individual (M = male, F = female)</p> <p>age - age of individual (HY = hatch year, SY = second year, TY = third year, ASY = after second year, ATY = after third year, AHY = after hatch year</p> <p>capture_reg - general area where individual was captured</p> <p>capture_subreg - specific region within capture region where individual was captured</p> <p>stage - period of the annual cycle to which the centroid belongs (W = winter, B = breeding, S = spring staging, M = fall staging and molt, WM = winter migration, BM = breeding migration, MM = molt migration, SM = spring migration)</p> <p>site - position of centroid within season (i.e., W1 = first site occupied during winter, W2 = second site occupied, etc.)</p> <p>cycle - number of annual cycles following transmitter attachment (1 = first cycle after attachment, 2 = second cycle after attachment, etc.)</p> <p>season - season of annual cycle in which centroid occurred (W = winter, F = fall, B = breeding, S = spring)</p>
Data from: Plasticity versus evolutionary divergence: what causes habitat partitioning in urban-adapted birds?
<p>Habitat partitioning can facilitate the coexistence of closely related species, and often results from competitive interference inducing plastic shifts of subordinate species in response to aggressive, dominant species (plasticity), or the evolution of ecological differences in subordinate species that reduce their ability to occupy habitats where the dominant species occurs (evolutionary divergence). Evidence consistent with both plasticity and evolutionary divergence exist, but the relative contributions of each to habitat partitioning have been difficult to discern. Here we use a global dataset on the breeding occurrence of birds in cities to test predictions of these alternative hypotheses to explain previously described habitat partitioning associated with competitive interference. Consistent with plasticity, the presence of behaviorally dominant congeners in a city was associated with a 65% reduction in occurrence of subordinate species, but only when the dominant was a widespread breeder in urban habitats. Consistent with evolutionary divergence, increased range-wide overlap with dominant congeners was associated with a 56% reduction in occurrence of subordinates in cities, even when the dominant was absent from the city. Overall, our results suggest that both plasticity and evolutionary divergence play important, concurrent roles in habitat partitioning among closely related species in urban environments.</p>
R code for Snyder, Ellner, and Hooker, "Time and chance: using age partitioning to understand how luck drives variation in reproductive success"
<p>Over the course of individual lifetimes, luck usually explains a large fraction of the between- individual variation in lifespan or lifetime reproductive output (LRO) within a population, while variation in individual traits or "quality" explains much less. To understand how, where in the life cycle, and through which demographic processes luck trumps trait variation, we show how to partition by age the contributions of luck and trait variation to LRO variance, and how to quantify three distinct components of luck. We apply these tools to several empirical case studies.</p> <p>We find that luck swamps effects of trait variation at all ages, primarily due to randomness in individual state dynamics ("state trajectory luck"). Luck early in life is most important. Very early state trajectory luck generally determines whether or not an individual ever breeds, likely by ensuring that they are not dead or doomed quickly. Less early luck drives variation in success among those breeding at least once. Consequently, the importance of luck often has a sharp peak early in life, or two peaks. We suggest that ages/stages where the importance luck peaks are potential targets for interventions to benefit a population of concern, different from those identified by eigenvalue elasticity analysis.</p>
Data from: Partitioning between atmospheric deposition and canopy microbial nitrification into throughfall nitrate fluxes in a Mediterranean forest
1. Microbial activity plays a central role in nitrogen (N) cycling, with effects on forest productivity. Though N bio-transformations, such as nitrification, are known to occur in the soil, here we investigate whether nitrifiers are present in tree canopies and actively process atmospheric N. 2. This study was conducted in a Mediterranean holm oak (Quercus ilex L.) forest in Spain during the transition from hot dry summer to cool wet winter. We quantified NH4+—N and NO3-—N fluxes for rainfall (RF) and throughfall (TF) and used δ15N, δ18O, and Δ17O to elucidate sources of NO3-. Finally, we characterized microbial communities and abundance of nitrifiers on foliage, RF and TF water through metabarcoding and quantitative Polymerase Chain Reaction, respectively. 3. NO3—N fluxes at the site were larger in TF than RF, suggesting a contribution from dry deposition, as also supported by δ15N and δ18O. However, Δ17O indicated that about 20% of NO3- in TF derived from canopies nitrification in August, after a severe drought, with a lower proportion in September (≈ 8%). This seasonal partitioning between biologically and atmospherically derived NO3- coincided with a decreasing trend of the abundance of archaeal nitrifiers. Tree canopies and TF had more diverse microbial communities than RF. Yet, RF showed higher variability in microbial composition, likely associated to the origin of air masses. 4. Synthesis. Atmospheric N deposition is significantly altered after passing through tree canopies. While nitrification has been proposed as one of the mechanisms responsible for these changes, very few studies directly investigate its occurrence. Here, we showed that nitrification by epiphytic leaf microbes contributed to increasing NO3 in TF and that nitrifiers' activity was reduced going from the dry and hot summer to the cool winter. Overall, these results highlight the power of coupling microbial community analysis, functional gene amplification and stable isotope approaches to examine ecosystem-scale processes.
Supplementary material for "A Partitioned Finite Element Method for power-preserving discretization of open systems of conservation laws"
<p>This archive contains supplementary material for the paper "A Partitioned Finite Element Method for power-preserving discretization of open systems of conservation laws", containing the source codes for the numerial results presented in the paper. An arXiv pre-print version of the paper is available <a href="https://arxiv.org/abs/1906.05965">here</a>.</p> <p>The following codes are provided:</p> <ul> <li> <p><code>codes/simulation1D_small.jl</code>: small amplitudes (linear) 1D simulation</p> </li> <li> <p><code>codes/simulation1D_large.jl</code>: large amplitudes (nonlinear) 1D simulation</p> </li> <li> <p><code>codes/simulation1D_analytical_gradient</code>: large amplitudes 1D simulation, but using an analytical nonlinear Hamiltonian gradient expression</p> </li> <li> <p><code>codes/simulation2D.jl</code>: large amplitudes (nonlinear) 2D simulation</p> </li> <li> <p><code>codes/convergence1D.jl</code>: convergence analysis of the 1D linear case</p> </li> <li> <p><code>codes/convergence2D.m</code>: convergence analysis of the 2D linear case</p> </li> </ul> <p>A GitHub with the codes and a few instructions on usage is available <a href="http://github.com/flavioluiz/PFEM-article-supplementary-material">here</a>.</p> <p><strong>Acknowledgements</strong></p> <p>This work has been performed in the frame of the Collaborative Research DFG and ANR project INFIDHEM, entitled "Interconnected of Infinite-Dimensional systems for Heterogeneous Media", nº ANR-16-CE92-0028. Further information is available <a href="http://websites.isae-supaero.fr/infidhem/the-project">here</a>.</p>
Data from: Carbonate shelf development and early Paleozoic benthic diversity in Baltica: A hierarchical diversity partitioning approach using brachiopod data
<p class="Text">The Ordovician–Silurian (~485–419 Ma) was a time of considerable evolutionary upheaval, encompassing both the largest evolutionary diversification and one of the first major mass extinctions. The Ordovician diversification coincided with global climatic cooling and paleocontinental collision, the ecological impacts of which were mediated by region-specific processes including substrate changes, biotic invasions, and tectonic movements. From the Sandbian–Katian (~453 Ma) onward, an extensive carbonate shelf developed in the eastern Baltic paleobasin in response to a tectonic shift to tropical latitudes and an increase in the abundance of calcareous macroorganisms. We quantify the contributions of environmental differentiation and temporal turnover to regional diversity through the Ordovician and Silurian, using brachiopod occurrences from the more shallow-water facies belts of the eastern Baltic paleobasin, an epicontinental sea on the Baltica paleocontinent. The results are consistent with carbonate shelf development as a driver of Ordovician regional diversification, both by enhancing broadscale differentiation between shallow- and deep-marine environments and by generating heterogeneous carbonate environments that allowed increasing numbers of brachiopod genera to coexist. However, temporal turnover also contributed significantly to apparent regional diversity, particularly in the Middle–Late Ordovician.</p>
Niche partitioning among three snail-eating snakes revealed by dentition asymmetry and prey specialisation
<p>1. The level of dentition asymmetry in snail-eating snakes may reflect their prey choice and feeding efficiency on asymmetric land snails. The three species of Pareas snakes (Squamata: Pareidae) in Taiwan, which are partially sympatric distribution on the island, provide a potential case to test the hypothesis of niche partitioning and character displacement with regard to dentition asymmetry and specialisation in feeding behaviour.</p> <p>2. In this study, behavioural experiments confirmed that P. formosensis feeds exclusively on slugs, whereas P. atayal and P. komaii consumed both. However, P. atayal more efficiently preys on land snails than P. komaii, exhibiting a shorter handling time and fewer mandibular retractions.</p> <p>3. Micro-CT and ancestral character reconstruction demonstrated the lowest asymmetry in P. formosensis (the slug specialist), the highest dentition asymmetry in P. atayal (the land snail specialist), and flexibility in P. komaii (the niche switcher): increased dentition asymmetry when sympatrically distributed with the slug eater (character displacement), and decreased asymmetry when living alone (ecological niche release).</p> <p>4. Ecological niche modelling showed that the distribution P. formosensis is associated with the presence of slugs, while that of P. atayal could be explained by the land snails.<br> Combining the results from morphology, phylogeny, behavioural experiments and ecological niche modelling, we showed that competition in the sympatric region might have facilitated character displacement among congeners, while absence of competition in allopatric region has led to ecological niche release.</p>
Data from: Selfish partners: resource partitioning in male coalitions of Asiatic lions
Behavioral plasticity within species is adaptive which directs survival traits to take multiple pathways under varying conditions. Male-male cooperation is an evolutionary strategy often exhibiting an array of alternatives between and within species. African male lions coalesce to safeguard territories and mate-acquisition. Unique to these coalitions is lack of strict hierarchies between partners, who have similar resource-securities possibly because of many mating-opportunities within large female-groups. Skewed mating and feeding rights have only been documented in large coalitions where males were related. However, smaller modal prey coupled with less simultaneous mating-opportunities for male Asiatic lions in Gir forests, India would likely result in a different coalition-structure. Observations on mating-events (n=127) and feeding-incidents (n=44) were made on 11 male-coalitions and 9 female-prides in Gir, to assess resource distribution within- and among- different sized male-coalitions. Information from 39 males were used to estimate annual tenure-holding probabilities. Single-males had smaller tenures and appropriated fewer matings than coalition-males. Pronounced dominance-hierarchies were observed within coalitions, with one partner getting >70% of all matings and 47% more food. Competition between coalition-partners at kills increased with decline in prey-size, increase in coalition-size and the appetite-states of the males. However, immediate subordinates in coalitions had higher reproductive fitness than single-males. Declining benefits to partners with increasing coalition-size, with individuals below the immediate subordinates having fitness comparable to single-males, suggest to an optimal coalition-size of two lions. Lions under higher competitive selection in Gir show behavioral plasticity to form hierarchical-coalitions, wherein partners utilize resources asymmetrically, yet coalesce for personal gains.
Data from: Effects of soil type and light on height growth, biomass partitioning, and nitrogen dynamics on 22 species of tropical dry forest tree seedlings: comparisons between legumes and nonlegumes
PREMISE OF THE STUDY: The seedling stage is particularly vulnerable to resource limitation, with potential consequences for community composition. We investigated how light and soil variation affected early growth, biomass partitioning, morphology, and physiology of 22 tree species common in tropical dry forest, including eight legumes. Our hypothesis was that legume seedlings are better at taking advantage of increased resource availability, which contributes to their successful regeneration in tropical dry forests. METHODS: We grew seedlings in a full-factorial design under two light levels in two soil types that differed in nutrient concentrations and soil moisture. We measured height biweekly and, at final harvest, biomass partitioning, internode segments, leaf carbon, nitrogen, δ 13 C, and δ 15 N. KEY RESULTS: Legumes initially grew taller and maintained that height advantage over time under all experimental conditions. Legumes also had the highest final total biomass and water-use efficiency in the high-light and high-resource soil. For nitrogen-fixing legumes, the amount of nitrogen derived from fixation was highest in the richer soil. Although seed mass tended to be larger in legumes, seed size alone did not account for all the differences between legumes and nonlegumes. Both belowground and aboveground resources were limiting to early seedling growth and function. CONCLUSIONS: Legumes may have a different regeneration niche, in that they germinate rapidly and grow taller than other species immediately after germination, maximizing their performance when light and belowground resources are readily available, and potentially permitting them to take advantage of high light, nutrient, and water availability at the beginning of the wet season.
A Benchmark Set for Multilevel Hypergraph Partitioning Algorithms
<p>DESCRIPTION<br> -------------------------------------------------------------------------------------------------------<br> This archive contains a large benchmark set for hypergraph partitioning algorithms.<br> All hypergraphs are unweighted (i.e., have unit edge and vertex weights) and use<br> the hMetis hypergraph input file format [1].</p> <p>BENCHMARK SETS<br> -------------------------------------------------------------------------------------------------------<br> Hypergraphs are derived from the following benchmark sets:<br> - The ISPD98 Circuit Benchmark Suite [2]<br> - The DAC 2012 Routability-Driven Placement Contest [3]<br> - The international SAT Competition 2014 [4]<br> - The University of Florida Sparse Matrix Collection (UF-SPM) [5]</p> <p>The benchmark set contains all ISPD98 and DAC2012 instances. Furthermore,<br> it contains 92 randomly selected instances from the application track of the SAT Competition 2014.<br> The Sparse Matrix Collection is organized into 172 groups and each group contains<br> matrices of different application areas. From each group, we chose one matrix for each application <br> area that has between 10 000 and 10.000.000 columns. In case multiple matrices fulfill<br> our criteria, we randomly selected one. In total, we include 192 matrices.</p> <p><br> HYPERGRAPH REPRESENTATION<br> -------------------------------------------------------------------------------------------------------<br> VLSI instances [2,3] are transformed into hypergraphs by converting the netlist into a<br> set of hyperedges. Sparse Matrices are translated into hypergraphs using the row-net model [6],<br> i.e. each row is treated as a net and each column as a vertex. SAT instances are converted into<br> three different hypergraph representations: In the literal model, each boolean literal is mapped to one<br> vertex and each clause constitutes a net [7]. In the primal model each variable is represented by a vertex<br> and each clause is represented by a net, whereas in the dual model the opposite is the case [8].</p> <p>FILE NAMES<br> -------------------------------------------------------------------------------------------------------<br> The origin of each hypergraph (and for SAT instances the hypergraph model) is encoded<br> into the file names as follows:<br> - Sparse Matrices : *.mtx.hgr<br> - DAC2012 : dac2012_superblue*.hgr<br> - ISPD98 : ISPD98_ibm*.hgr<br> - SAT-14 primal : sat14_*.cnf.primal.hgr<br> - SAT-14 dual : sat14_*.cnf.dual.hgr<br> - SAT-14 literal : sat14_*.cnf.hgr</p> <p>REFERENCES<br> -------------------------------------------------------------------------------------------------------<br> [1] http://glaros.dtc.umn.edu/gkhome/fetch/sw/hmetis/manual.pdf<br> [2] C. J. Alpert. The ISPD98 Circuit Benchmark Suite. In Proc. of the 1998 Int. Symp. on Physical Design, pages 80–85, New York, 1998. ACM.<br> [3] N. Viswanathan, C. Alpert, C. Sze, Z. Li, and Y/ Wei. The dac 2012 routability-driven placement contest and benchmark suite. In Proceedings of the 49th Annual Design Automation Conference, DAC ’12, pages 774–782<br> [4] A. Belov, D. Diepold, M. Heule, and M. Järvisalo. The SAT Competition 2014. http://www.satcompetition.org/2014/, 2014.<br> [5] T. A. Davis and Y. Hu. The University of Florida Sparse Matrix Collection. ACM Trans. Math. Softw.,38(1):1:1–1:25, 2011.<br> [6] Ü. V. Catalyürek and C. Aykanat. Hypergraph-partitioning-based decomposition for parallel sparse-matrix vector multiplication. IEEE Transactions on Parallel and Distributed Systems, 10(7):673–693, Jul 1999.<br> [7] D. A. Papa and I. L. Markov. Hypergraph Partitioning and Clustering. In T. F. Gonzalez, editor, Handbook of Approximation Algorithms and Metaheuristics. Chapman and Hall/CRC, 2007.<br> [8] Zoltan Mann and Pal Papp. Formula partitioning revisited. In Daniel Le Berre, editor, POS-14. Fifth Pragmatics of SAT workshop, volume 27 of EPiC Series in Computing, pages 41–56. EasyChair, 2014.</p>
Data for: Seasonally mediated niche partitioning in a vertically compressed pelagic predator guild
<p>Niche partitioning among closely related, sympatric species is a fundamental concept in ecology, and its mechanisms are of broad interest for understanding ecosystem functioning and predicting the impacts of human-driven environmental change. However, identifying mechanisms by which top marine predators partition available resources has been especially challenging given the difficulty of quantifying resource use of large pelagic animals. In the eastern tropical Pacific (ETP), three large, highly mobile and ecologically similar pelagic predators (blue marlin (<em>Makaira</em> <em>nigricans</em>), black marlin (<em>Istiompax</em> <em>indica</em>) and sailfish (<em>Istiophorus platypterus))</em> coexist in a vertically compressed habitat. To evaluate each species' ecological niche, we leveraged a decade of recreational fisheries data, multi-year satellite tracking with high-resolution dive data, and stable isotope analysis. Fishery interaction and telemetry-based three-dimensional seasonal utilization distributions suggested high spatial and temporal overlap among species; however, seasonal and diel variability in diving behaviour produced spatial partitioning, leading to low trophic overlap among species. Expanding oxygen minimum zones will reduce the available vertical habitat within predator guilds, likely leading to increases in interspecific competition. Thus, understanding the mechanisms of habitat partitioning among predators in the vertically compressed ETP can provide insight into how predators in other ocean regions may respond to vertically limited habitats.</p>
Data from: Nitrogen niche partitioning between tropical legumes and grasses conditionally weakens under elevated CO2
<p>Plant community biodiversity can be maintained, at least partially, by shifts in species interactions between facilitation and competition for resources as environmental conditions change. These interactions also drive ecosystem functioning, including productivity, and can promote over-yielding- an ecosystem service prioritized in agro-ecosystems, such as pastures, that occurs when multiple species together are more productive than the component species alone. Importantly, species interactions that can result in over-yielding may shift in response to rising CO<sub>2</sub> concentrations and changes in resource availability, and the consequences these shifts have on production is uncertain especially in the context of tropical mixed-species grasslands.</p> <p>We examined the relative performance of two species pairs of tropical pasture grasses and legumes growing in monoculture and mixtures in a glasshouse experiment manipulating CO<sub>2</sub>. We investigated how over-yielding can arise from nitrogen (N) niche partitioning and biotic facilitation using stable isotopes to differentiate soil N from biological N fixation (BNF) within N acquisition into aboveground biomass for these two-species mixtures.</p> <p>We found that N niche partitioning in species-level use of soil N vs. BNF drove species interactions in mixtures. Importantly partitioning and overyielding were generally reduced under elevated CO<sub>2</sub>. However, this finding was mixture-dependent based on biomass of dominant species in mixtures and the strength of selection effects for the dominant species.</p> <p>This study demonstrates that rising atmospheric CO<sub>2</sub> may alter niche partitioning between co-occurring species, with negative implications for the over-yielding benefits predicted for legume-grass mixtures in working landscapes with tropical species. Furthermore, these changes in inter-species interactions may have consequences for grassland composition that are not yet considered in larger-scale projections for impacts of climate change and species distributions. </p>
Spatial partitioning of terrestrial precipitation and corresponding dataset agreement
<p>The study of the water cycle at planetary scale is crucial for our understanding of large-scale climatic processes. However, very little is known about how terrestrial precipitation is distributed across different environments. In this study, we address this gap by employing a 17-dataset ensemble to provide, for the first time, precipitation estimates over a suite of land cover types, biomes, elevation zones, and precipitation intensity classes. We estimate annual terrestrial precipitation at approximately 114,000 ± 9,400 km3, with about 70% falling over tropical, subtropical and temperate regions. Our results highlight substantial inconsistencies, mainly, over the arid and the mountainous areas. To quantify the overall discrepancies, we utilize the concept of dataset agreement and then explore the pairwise relationships among the datasets in terms of "genealogy", concurrency, and distance. The resulting uncertainty-based partitioning demonstrates how precipitation is distributed over a wide range of environments and improves our understanding on how their conditions influence observational fidelity.</p>
Data for umbrella sampling windows for polyleucine partitioning in thickness gradient
<p>Water removed from trajectories</p> <p>30 microseconds per window</p> <p>Martini 2.2</p> <p>https://www.biorxiv.org/content/10.1101/2024.02.02.578561v1.abstract</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.