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1,855 results for “Framework”
Data from: A phylogenomic framework, evolutionary timeline and genomic resources for comparative studies of decapod crustaceans
Comprising over 15 000 living species, decapods (crabs, shrimp and lobsters) are the most instantly recognizable crustaceans, representing a considerable global food source. Although decapod systematics have received much study, limitations of morphological and Sanger sequence data have yet to produce a consensus for higher-level relationships. Here, we introduce a new anchored hybrid enrichment kit for decapod phylogenetics designed from genomic and transcriptomic sequences that we used to capture new high-throughput sequence data from 94 species, including 58 of 179 extant decapod families, and 11 of 12 major lineages. The enrichment kit yields 410 loci (greater than 86 000 bp) conserved across all lineages of Decapoda, more clade-specific molecular data than any prior study. Phylogenomic analyses recover a robust decapod tree of life strongly supporting the monophyly of all infraorders, and monophyly of each of the reptant, 'lobster' and 'crab' groups, with some results supporting pleocyemate monophyly. We show that crown decapods diverged in the Late Ordovician and most crown lineages diverged in the Triassic–Jurassic, highlighting a cryptic Palaeozoic history, and post-extinction diversification. New insights into decapod relationships provide a phylogenomic window into morphology and behaviour, and a basis to rapidly and cheaply expand sampling in this economically and ecologically significant invertebrate clade.
Data from: Applying a dryland degradation framework for rangelands: the case of Mongolia
Livestock-caused rangeland degradation remains a major policy concern globally and the subject of widespread scientific study. This concern persists in part because it is difficult to isolate the effects of livestock from climate and other factors that influence ecosystem conditions. Further, degradation studies seldom use multiple plant and soil indicators linked to a clear definition of and ecologically-grounded framework for degradation assessment that distinguishes different levels of degradation. Here, we integrate two globally applicable rangeland degradation frameworks and apply them to a broad-scale empirical dataset for the country of Mongolia. We compare our assessment results with two other recent national rangeland degradation assessments in Mongolia to gauge consistency of findings across assessments and evaluate the utility of our framework. We measured livestock-use impacts across Mongolia's major ecological zones: mountain and forest steppe, eastern steppe, steppe, and desert steppe. At 143 sites in 36 counties, we measured livestock-use and degradation indicators at increasing distances from livestock corrals in winter-grazed pastures. At each site, we measured multiple indicators linked to our degradation framework, including plant cover, standing biomass, palatability, species richness, forage quality, vegetation gaps and soil surface characteristics. Livestock use had no effect on soils, plant species richness or standing crop biomass in any ecological zone, but subtly affected plant cover and palatable plant abundance. Livestock effects were strongest in the steppe zone, moderate in the desert steppe and limited in the mountain/forest and eastern steppes. Our results aligned closely with those of two other recent country-wide assessments, suggesting that our framework may have widespread application. All three assessments found that very severe and irreversible degradation is rare in Mongolia (1-18% of land area), with most rangelands only slightly (33-53%) or moderately (25-40%) degraded. We conclude that very severe livestock-induced rangeland degradation is overstated in Mongolia. However, targeted rangeland restoration coupled with monitoring, adaptive management and stronger rangeland governance are needed to prevent further degradation where heavy grazing could cause irreversible change. Given the broad applicability of our degradation framework for Mongolia, we suggest it be tested for application in other temperate grasslands throughout Central Asia and North America.
A unifying framework for analyzing temporal changes in functional and taxonomic diversity along disturbance gradients
<p>Frameworks exclusively considering functional diversity are gaining popularity, as they complement and extend the information provided by taxonomic diversity metrics, particularly in response to disturbance. Taxonomic diversity should be included in functional diversity frameworks to uncover the functional mechanisms causing species loss following disturbance events. We present and test a predictive framework that considers temporal functional and taxonomic diversity responses along disturbance gradients. Our proposed framework allows us to test different multidimensional metrics of taxonomic diversity that can be directly compared to calculated multidimensional functional diversity metrics. It builds on existing functional diversity-disturbance frameworks both by using a gradient approach and by jointly considering taxonomic and functional diversity. We used previously unpublished stream insect community data collected prior to, and for the two years following, an extreme flood event that occurred in 2013. Using 14 northern Colorado mountain streams, we tested our framework and determined that taxonomic diversity metrics calculated using multidimensional methods resulted in concordance between taxonomic and functional diversity responses. By considering functional and taxonomic diversity together and using a gradient approach, we were able to identify some of the mechanisms driving species losses following this extreme disturbance event.</p>
Data from: A framework for simultaneous tests of abiotic, biotic, and historical drivers of species distributions: empirical tests for North American wood warblers based on climate and pollen
Understanding how abiotic, biotic and historical factors shape species distributions remains a central question in ecology, but studies linking biotic factors to continental-scale patterns remain scarce. Here, we present a novel framework for simultaneously testing patterns expected when abiotic, biotic or historical factors drive species range limits. We use ecological niche models to produce empirical estimates of the "Biotic, Abiotic, and Movement" paradigm (BAM diagrams), which previously had only been used theoretically. Based on climatic and pollen data, as well as explicit consideration of dispersal limitations, we implement the framework for a group of North American birds (Oreothlypis warblers) with clear habitat associations. Because the pollen-based predictor variables characterize vegetation, they represent biotic factors needed by each bird species. Although continental-scale patterns of distribution traditionally are attributed to abiotic factors, only one species matched the hypothesis of solely abiotic drivers. In contrast, pollen-based models indicate biotic drivers for two species, correctly predicting their absence in climatically suitable areas. These results highlight the feasibility of considering and quantifying potential effects of biotic interactions on species ranges, especial when interactions can be decoupled from abiotic factors. Furthermore, the availability of pollen data now and in the Holocene highlights the potential of these data to be used to predict range shifts of other organisms tightly dependent on particular vegetation types.
Data from: When are extinctions simply bad luck? rarefaction as a framework for disentangling selective and stochastic extinctions
1. A key challenge in conservation biology is that not all species are equally likely to go extinct when faced with a disturbance. Traditionally, differences in species extinction risk are considered a form of extinction selectivity, a nanrondom process by which species' extinction risks are associated with their traits. While selectivity clearly contributes to varation in extinction among taxa, it is also clear that rare species are more likely to go extinct than are common species. While obvious, this law of extinction suggests that random chance, operating on species abundance, plays an important role in the extinction process. Unless ecologists and conservation biologists can disentangle random and nonrandom extinction processes, then the prediction and prevention of future extinctions will continue to be an elusive challenge. 2. We suggest that a modified version of a common null model procedure, rarefaction, can be used to disentangle the influence of stochastic species loss from selective nonrandom processes. To this end we applied a rarefaction based null model to three published data sets to characterize the influence of species rarity in driving biodiversity loss following three disturbance events: i) disease-associated bat declines; ii) disease-associated amphibian declines; and iii) habitat loss and invasive species-associated gastropod declines. For each case study, we used rarefaction to generate null expectations of stochastic biodiversity loss and species-specific extinction probabilities. 3. In each of our case studies we find evidence for random and nonrandom (selective) extinctions. Our findings highlight the importance of explicitly considering that some species extinctions are the result of stochastic processes, i.e., bad luck. 4. Policy Implications If there is a first law of extinction, it is that rare species are most likely than common species to go extinct. We suggest that taking this law into account in analyses of extinction risk is critical to the identification of selective extinctions. Our results suggest that rarefaction can be used to identify nonrandom decline, extirpation, and extinction events and provide an important baseline comparison point for future extinction analyses.12-Jul-2019
Data from: A framework for linking competitor ecological differences to coexistence
1. Not all ecological differences among competing species affect their ability to locally coexist. Rather, the differences that promote stable coexistence can be those which cause each species to experience stronger intraspecific than interspecific competition. Recent approaches have established how to detect the demographic signature of these competitive effects, but alone they cannot elucidate the ecological differences among species that yield these patterns. 2. Here, we present a unifying experimental and observational framework that identifies potential ecological differences among species shaping their responses to intra- and interspecific competition. We first describe a conceptual model establishing why the strength of intra- and interspecific competitive interactions should vary along environmental gradients related to species ecological differences. We then show how to apply the framework using Enallagma damselflies, a diverse group of predatory aquatic insects. 3. To determine how species responded to intra- and interspecific competition along environmental gradients, we experimentally manipulated the relative abundances of three species and replicated this across five lakes which varied in environmental conditions affecting larval damselfly per capita growth and mortality rates – key vital rates regulating their populations. 4. Results suggest Enallagma are ecologically differentiated in ways that in some communities can result in intraspecific competition exceeding interspecific competition. However, in many cases the opposite was true, or the effects of intra- and interspecific competition were equivalent via growth and mortality responses. Moreover, these effects tended to be weak and asymmetrical among competitors, which suggests that differential responses of larval growth and mortality to intra- and interspecific competition may not contribute strongly to the maintenance of Enallagma diversity. Different environmental factors appear to shape these demographic responses to competition, providing insight into the ecological mechanisms regulating damselfly assemblages. 5. This framework can be broadly applied to identify the ecological differences among species that may promote coexistence, advancing knowledge of the mechanisms underlying coexistence, and overcoming some limitations of purely phenomenological approaches.
Data from: A trait-based framework for discerning drivers of species co-occurrence across heterogeneous landscapes
Null model analysis of species co-occurrence patterns has long been used to gain insight into community assembly but is often limited to identifying non-random patterns without providing clarity about underlying ecological mechanisms. This challenge is especially apparent when sampling units are spread across a heterogeneous landscape or along an environmental gradient because multiple mechanisms can produce similar co-occurrence patterns. We developed a trait-based approach for discriminating between environmental filtering and biotic interactions as the probable driver of co-occurrence patterns across environmentally heterogeneous sites. We demonstrate our framework by analyzing the co-occurrence of small mammals over elevation in three independent mountain ranges in the Great Basin of the western United States. Our sampling design accounts for landscape scale environmental variability and within-site habitat heterogeneity. We identified 52 non-random species pairs, of which 36 were aggregated and 16 were segregated. For each pair, we determined which mechanism was the likely ecological explanation using a hypothesis-testing framework based on functional trait similarity. Expectations of biotic interactions were based on similarity of diet and body size whereas habitat affinity and geographic range were used for environmental filtering. Only four pairs were consistent with expectations under biotic interactions, including pairs for which competitive exclusion has previously been documented. In addition to analyzing individual pairs, we used binomial tests of observed versus expected totals of intra- and inter-guild pairs to determine assemblage-wide deviations from random community structure. Signatures of environmental filtering were consistent across mountain ranges and scales. Despite differences in species composition and significant pairs among data sets, our approach revealed consistent mechanistic conclusions, emphasizing the value of trait-based methods to co-occurrence and community assembly.
Assessing the benefits and risks of translocations in depauperate species: a theoretical framework with an empirical validation
<p>1. Conservation translocations are becoming more common to assist in the management of threatened native species. While many translocation programs focus on maximizing survival in newly established populations, consideration is also required for the persistence of source populations. 2. Here, we present and test a theoretical framework that assesses the translocation trade-off between increasing a species probability of survival and decreasing a species' overall genetic diversity. We anticipate that i) the genetic diversity of translocated populations will be reduced compared to the source due to a failure to capture and retain genetic diversity, and ii) the genetic diversity of the source population will decline due to the removal of founder individuals. 3. We test this framework with an empirical study of redfin blue eye, Scaturiginichthys vermeilipinnis; a critically endangered fish species which has undergone several replicate translocations, established with founders sourced from a single remnant population. Several generations after reintroduction, we show that the predicted survival of the species has improved as a result of these translocations. 4. While the species' genetic diversity has been retained across all populations combined (translocated and source), we show that genetic diversity in each individual population (including the source) is reduced compared to the source population prior to translocation. 5. <i>Synthesis and applications</i>. Conservation translocations can provide great benefits to species survival, enabling extinction risk to be spread across multiple populations. Translocated populations, however, often harbour reduced genetic diversity compared to source populations and initiating translocated populations can decrease the genetic diversity of source populations, placing them at an increased risk of extinction. The framework presented here enables the trade-off between extinction risk and retention of genetic diversity to be established. This will enable the optimal conservation strategy to be employed to increase the long-term persistence and evolutionary potential of a species.</p>
Accreditation Frameworks - conceptual view
<p>A conceptual view of how accreditation frameworks allow members to access content and stop non-members from accessing content.</p>
On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework - accompanying figures
<p>Differential isotropic shielding density isosurfaces (isovalues at +0.53 ppm (red) and -0.53 ppm (blue)) for XH2 - H2O systems X = Se, Te, Po (shield_dens_x_0_01.png) and Hb (shield_dens_h2_0_01.png), calculated as a difference between supermolecule shielding densities and the sum of subsystem shielding densities approximated as: (a) isolated fragments (b) FDE(4)[0] (c) FDE(4)[v] (d) FDE(4)[v+w_u] (e) FDE(4)[v+w_all]. Color of atoms: X (blue), O(red), H(grey).</p> <p> </p>
On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework - supplementary information
<p>Supplementary information to the publication "On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework"</p> <p>The attached 'supplementary_info_fde_mag.zip' unpacks to three directories:</p> <ul> <li>'optimized_structures' directory contains optimized molecular structures in xyz format</li> <li>'results' directory contains all the results obtained in this work, collected in <ul> <li>gnumeric and xlsx spreadsheets with complete results from DIRAC and from ADF</li> <li>csv files (data involving heavy atoms, X, and hydrogen-bonded H atoms, Hb)</li> <li>'supplementary_tables' latex and pdf files</li> </ul> </li> <li>'visualization' directory contains the data for plotting the NMR shielding density and prepared plots; for the explanation of files in this directory open the 'visualization/visualization.html' document in your browser or read the corresponding jupyter notebook (visualization/visualization.ipynb')</li> </ul>
On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework - supplementary information
<p>Supplementary information to the publication "On the calculation of second-order magnetic properties using subsystem approaches in the relativistic framework"</p> <p>The attached 'supplementary_info_fde_mag.tar.gz' unpacks to three directories:</p> <ul> <li>'optimized_structures' directory contains optimized molecular structures in xyz format</li> <li>'results' directory contains all the results obtained in this work, collected in <ul> <li>spreadsheets with complete results from DIRAC and from ADF (in *xlsx and *gnumeric format)</li> <li>csv files (data involving heavy atoms, X, and hydrogen-bonded H atoms, Hb obtained with DC and ZORA Hamiltonians and TZ-type basis sets)</li> <li>'supplementary_tables' latex and pdf files</li> </ul> </li> <li>'visualization' directory contains the data for plotting the NMR shielding density and prepared plots; for the explanation of files in this directory open the 'visualization/visualization.html' document in your browser or read the corresponding jupyter notebook (visualization/visualization.ipynb')</li> </ul>
FUX-Sim: An implementation of a fast universal simulation/reconstruction framework for X-ray systems
<p>This dataset contains the input and output data related to the paper "FUX-Sim: An implementation of a fast universal simulation/reconstruction framework for X-ray systems". </p>
Fully-coupled pressure-based finite-volume framework for the simulation of fluid flows at all speeds in complex geometries (Supporting Data)
<p>This data accompanies the paper "Fully-coupled pressure-based finite-volume framework for the simulation of fluid flows at all speeds in complex geometries", published in Journal of Computational Physics (2017), http://dx.doi.org/10.1016/j.jcp.2017.06.009.</p>
LabbookDB Presentation - A Relational Framework for Laboratory Metadata
<p>LabbookDB is a relational database application framework for life sciences—providing an extendable schema and functions to conveniently add and retrieve information, and generate summaries. The core concept of LabbookDB is that wet work metadata commonly tracked in lab books or spreadsheets is more efficiently and more reliably stored in a relational database, and more flexibly queried. We overcome the flexibility limitations of designed-for-analysis spreadsheets and databases by building our schema around atomized physical object interactions in the laboratory (and providing plotting- and/or analysis-ready dataframes as a compatibility layer). We keep our database schema more easily extendable and adaptable by using joined table inheritance to manage polymorphic objects and their relationships. LabbookDB thus provides a wet work metadata storage model excellently suited for exploratory ex-post reporting and analysis, as well as a potential infrastructure for automated wet work tracking.</p>
Data from a flexible framework to assess patterns and drivers of beta diversity across spatial scales
<p><span>The patterns and underlying ecological (e.g., environmental filtering) and </span><span>historical</span><span> (e.g., priority effects) drivers of beta diversity are scale-dependent but generally difficult to distinguish</span> <span>and rarely explored with a sufficiently broad range of spatial scales. We propose a general scale-explicit framework to assess and contrast the patterns and drivers of beta diversity across hierarchical spatial scales ranging from within fine-scale ecoregion-scale to among broad-scale ecoregion-scale. By applying this framework to aquatic macroinvertebrate datasets, we show that beta diversity generally increases with spatial extent.</span> <span>With an increasing spatial extent, beta diversity shifts from being more influenced by environmental filtering to being more influenced by recent historical factors (i.e., past beta diversity). Such recent historical effects may result from past environmental variation rather than priority effects.</span><span> We also found that the small-scale and large-scale environmental drivers act differently on beta diversity across spatial extents. Our research reveals a complex spatial-scale dependence in beta diversity patterns and their drivers and provides a more holistic understanding of beta diversity dynamics. Our framework represents a flexible way to unravel the internal structure of beta diversity across scales by partitioning of entire beta diversity variation into scale-specific differences and may have broad application in community ecology, landscape planning and biodiversity conservation.</span></p>
Data from: Reactive high-spin iron(IV)-oxo sites through dioxygen activation in a metal–organic framework
<p>In nature, nonheme iron-containing enzymes use dioxygen to generate high-spin iron(IV)=O species for a variety of oxygenation reactions. Although scientists have long sought to mimic this reactivity, the enzyme-like activation of dioxygen to form high-spin iron(IV)=O species remains an unrealized goal in synthetic chemistry. Here, we report a metal–organic framework featuring iron(II) sites with a local structure similar to that in α-ketoglutarate-dependent dioxygenases. The framework reacts with dioxygen at low temperatures to form high-spin iron(IV)=O species that are characterized using in situ diffuse reflectance infrared Fourier transform, in situ and variable-field Mössbauer, Fe Kβ x-ray emission, and nuclear resonance vibrational spectroscopies. In the presence of dioxygen, the framework is competent for catalytic oxygenation of cyclohexane and the stoichiometric conversion of ethane to ethanol.</p>
Application of a Comprehensive Hygroscopicity Framework for Simulating Aerosol Water Uptake in a Large-scale Climate Model
<p>This dataset was generated from 18-month simulations of the NCAR Community Atmosphere Model (CAM); the atmospheric component of the Community Earth System Model version 2 (CESM2). The dataset can be used to reproduce the analysis and figures presented in the upcoming JGR publication.</p>
Solid-state $^{13}$C-NMR spectroscopic determination of sidechain mobilities in zirconium-based metal-organic frameworks
<p>This Dataset contains the raw data contained in the figures of our journal article in <i>Magnetic Resonance</i>: <a href="https://doi.org/10.5194/mr-2023-13">https://doi.org/10.5194/mr-2023-13</a>.</p>
STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer
<p>Scripts generating figures of the paper titled "STmut: a framework for visualizing somatic alterations in spatial transcriptomics data of cancer".</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.