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Data from: Validation of an algorithm for identifying MS cases in administrative health claims datasets
Objective: To develop a valid algorithm for identifying multiple sclerosis (MS) cases in administrative health claims (AHC) datasets. Methods: We used 4 AHC datasets from the Veterans Administration (VA), Kaiser Permanente Southern California (KPSC), Manitoba (Canada), and Saskatchewan (Canada). In the VA, KPSC, and Manitoba, we tested the performance of candidate algorithms based on inpatient, outpatient, and disease-modifying therapy (DMT) claims compared to medical records review using sensitivity, specificity, positive and negative predictive values, and interrater reliability (Youden J statistic) both overall and stratified by sex and age. In Saskatchewan, we tested the algorithms in a cohort randomly selected from the general population. Results: The preferred algorithm required ≥3 MS-related claims from any combination of inpatient, outpatient, or DMT claims within a 1-year time period; a 2-year time period provided little gain in performance. Algorithms including DMT claims performed better than those that did not. Sensitivity (86.6%–96.0%), specificity (66.7%–99.0%), positive predictive value (95.4%–99.0%), and interrater reliability (Youden J = 0.60–0.92) were generally stable across datasets and across strata. Some variation in performance in the stratified analyses was observed but largely reflected changes in the composition of the strata. In Saskatchewan, the preferred algorithm had a sensitivity of 96%, specificity of 99%, positive predictive value of 99%, and negative predictive value of 96%. Conclusions: The performance of each algorithm was remarkably consistent across datasets. The preferred algorithm required ≥3 MS-related claims from any combination of inpatient, outpatient, or DMT use within 1 year. We recommend this algorithm as the standard AHC case definition for MS.
Data from: Biotic and climatic velocity identify contrasting areas of vulnerability to climate change
Metrics that synthesize the complex effects of climate change are essential tools for mapping future threats to biodiversity and predicting which species are likely to adapt in place to new climatic conditions, disperse and establish in areas with newly suitable climate, or face the prospect of extirpation. The most commonly used of such metrics is the velocity of climate change, which estimates the speed at which species must migrate over the earth's surface to maintain constant climatic conditions. However, "analog-based" velocities, which represent the actual distance to where analogous climates will be found in the future, may provide contrasting results to the more common form of velocity based on local climate gradients. Additionally, whereas climatic velocity reflects the exposure of organisms to climate change, resultant biotic effects are dependent on the sensitivity of individual species as reflected in part by their climatic niche width. This has motivated development of biotic velocity, a metric which uses data on projected species range shifts to estimate the velocity at which species must move to track their climatic niche. We calculated climatic and biotic velocity for the Western Hemisphere for 1961–2100, and applied the results to example ecological and conservation planning questions, to demonstrate the potential of such analog-based metrics to provide information on broad-scale patterns of exposure and sensitivity. Geographic patterns of biotic velocity for 2954 species of birds, mammals, and amphibians differed from climatic velocity in north temperate and boreal regions. However, both biotic and climatic velocities were greatest at low latitudes, implying that threats to equatorial species arise from both the future magnitude of climatic velocities and the narrow climatic tolerances of species in these regions, which currently experience low seasonal and interannual climatic variability. Biotic and climatic velocity, by approximating lower and upper bounds on migration rates, can inform conservation of species and locally-adapted populations, respectively, and in combination with backward velocity, a function of distance to a source of colonizers adapted to a site's future climate, can facilitate conservation of diversity at multiple scales in the face of climate change.
Data from: Local and landscape metrics identify opportunities for conserving cavity-nesting birds in a rapidly urbanizing ecoregion
Urban centers are rapidly expanding globally, resulting in regional forest-cover transformations that shift from temperate forest biomes to a heterogeneous mix of urban development, forest patches, and agriculture. Data on habitat use within remaining forest patches embedded across land use types, particularly in urban land use, are needed to optimize conservation strategies as urban growth continues. In the rapidly urbanizing southern Piedmont, USA, small pine patches have become more frequent across the landscape and are found embedded within second-growth forest, agricultural, and urban land use matrices. We used point-count surveys and N-mixture models to determine the effect of patch- and landscape-scale drivers on cavity-nesting bird abundance, including the threatened Brown-headed Nuthatch (Sitta pusilla), in pine forest patches. Model-averaged estimates suggest Brown-headed Nuthatches are more abundant in large patches in a heterogeneous matrix that includes urban residential development. Three other cavity-nesting species declined in abundance as a function of reduced canopy cover. White-breasted Nuthatches increased and Tufted Titmice decreased in abundance in response to patch area. By identifying factors that predict abundance at local and landscape scales for ecologically sensitive and generalist species, we can more effectively contribute to regional conservation efforts in urban ecosystems, extending conservation in practice beyond protected areas.
Data from: On the origin of a domesticated species: identifying the parent population of Russian silver foxes (Vulpes vulpes)
The foxes at Novosibirsk, Russia, are the only population of domesticated foxes in the world. These domesticated foxes originated from farm-bred silver foxes (Vulpes vulpes), whose genetic source is unknown. In the present study, we examined the origin of the domesticated strain of foxes and two other farm-bred fox populations (aggressive and unselected) maintained in Novosibirsk. To identify the phylogenetic origin of these populations we sequenced two regions of mitochondrial DNA, cytochrome b and d-loop, from 24 Novosibirsk foxes (eight foxes from each population) and compared them with corresponding sequences of native red foxes from Europe, Asia, Alaska and Western Canada, Eastern Canada, and the Western Mountains of the USA. We identified seven cytochrome b–d-loop haplotypes in Novosibirsk populations, four of which were previously observed in Eastern Canada. The three remaining haplotypes differed by one or two base change from the most common haplotype in Eastern Canada. ΦST analysis showed significant differentiation between Novosibirsk populations and red fox populations from all geographic regions except Eastern Canada. No haplotypes of Eurasian origin were identified in the Novosibirsk populations. These results are consistent with historical records indicating that the original breeding stock of farm-bred foxes originated from Prince Edward Island, Canada. Mitochondrial DNA data together with historical records indicate two stages in the selection of domesticated foxes: the first includes captive breeding for approximately 50 years with unconscious selection for behaviour; the second corresponds to > 50 years of additional intensive selection for tame behaviour.
Data from: "Diagnostic SNPs for inferring population structure in American mink (Neovison vison) identified through RAD sequencing" in Genomic Resources Notes accepted 1 October 2014 to 30 November 2014
The article documents the public availability of RAD sequencing data and generated SNPs for the American mink (Neovison vison). 224,095 polymorphic loci were identified from 14 mink from which primers were designed for a subset of 380 SNPs. The panel was tested on 211 mink. Fisher's F-statistics (Fis, FIT and FST) as well as observed (HO), expected (HE) and unbiased expected (uHE) heterozygosity was calculated for the SNPs and 194 SNPs was validated as being useful for population genetic studies.
Identifying and characterizing stress pathways of concern for consumer safety in next generation risk assessment
<p>Many substances for which consumer safety risk assessments need to be conducted are not associated with specific toxicity modes of action, but rather exhibit non-specific toxicity leading to cell stress. In this work, a cellular stress panel is described, consisting of 36 biomarkers representing mitochondrial toxicity, cell stress and cell health, measured predominantly using high content imaging. To evaluate the panel, data were generated for thirteen substances at exposures consistent with typical use-case scenarios. These included some that have been shown to cause adverse effects in a proportion of exposed humans and have a toxicological mode-of-action associated with cellular stress (e.g. doxorubicin, troglitazone, diclofenac), and some that are not associated with adverse effects due to cellular stress at human-relevant exposures (e.g. caffeine, niacinamide and phenoxyethanol). For each substance, concentration response data were generated for each biomarker at three timepoints. A Bayesian model was then developed to quantify the evidence for a biological response, and if present, a credibility range for the estimated point of departure (PoD) was determined. PoDs were compared with the plasma C<sub>max</sub> associated with the typical substance exposures, and indicated a clear differentiation between 'low' risk and 'high' risk chemical exposure scenarios. </p> <p>Developing robust methods to characterize the in vitro bioactivity of xenobiotics is an important part of non-animal safety assessment. The results presented show that the cellular stress panel can be used, together with other new approach methodologies, to identify chemical exposures that are protective of consumer health.</p>
Data from: Genetic mapping identifies a major locus spanning P450 clusters associated with pyrethroid resistance in kdr-free Anopheles arabiensis from Chad
Prevention of malaria transmission throughout much of Africa is dependent on bednets that are impregnated with pyrethroid insecticides. Anopheles arabiensis is the major malaria vector in Chad and efforts to control this vector are threatened by the emergence of pyrethroid resistance. WHO bioassays revealed that An. arabiensis from Ndjamena is resistant to pyrethroids and dichlorodiphenyltrichloroethane (DDT) but fully susceptible to carbamates and organophosphates. No 1014F or 1014S kdr alleles were detected in this population. To determine the mechanisms that are responsible for resistance, genetic crosses were established between the Ndja strain and an insecticide susceptible population from Mozambique. Resistance was inherited as an autosomal trait and quantitative trait locus (QTL) mapping identified a single major locus on chromosome 2R, which explained 24.4% of the variance in resistance. This QTL is enriched in P450 genes including 25 cytochrome P450s in total. One of these, Cyp6p4 is 22-fold upregulated in the Ndja strain compared with the susceptible. Piperonyl butoxide (PBO) synergist and biochemical assays further support a role for P450s in conferring pyrethroid resistance in this population.
Data from: Geometric morphometric analyses of worn cheek teeth help identify extant and extinct gophers (Rodentia: Geomyidae)
Studies of the biostratigraphy and palaeoecology of fossil vertebrate assemblages require large samples of accurately identified specimens. Such analyses can be hampered by the inability to assign isolated and worn remains to specific taxa. Entoptychine gophers are a diverse group of burrowing rodents found in Oligo-Miocene deposits of the western United States. In both entoptychines and their extant relatives the geomyines, diagnostic characters of the occlusal surface of the teeth are modified with wear, making difficult the identification of many isolated fossil teeth. We use geometric morphometrics to test the hypothesis that tooth shape informs taxonomic affinities and expected levels of morphological variation across gopher taxa. We also incorporate data from microcomputer tomography to investigate changes in occlusal surface shape through wear within individuals. Our analyses demonstrate the usefulness of our approach in identifying extant geomyines to the genus, subgenus and species levels, and fossil entoptychines to the genus and, in some cases, the species level. Our results cast doubt on the validity of some species within Entoptychus and suggest future revisions to entoptychine taxonomy. The amounts of morphological divergence observed among fossil and extant genera are similar. Fossil species do not differ greatly from extant ones in that regard either. Further work evaluating the morphological variation within and across entoptychine species, including unworn teeth and osteological material, will allow revised analyses of the biostratigraphy and palaeoecology of important Oligo-Miocene mammalian assemblages of the western United States and help to infer the phylogenetic relationships and evolution of gophers.
Data from: QTL mapping identifies candidate alleles involved in adaptive introgression and range expansion in a wild sunflower
The wild North American sunflowers Helianthus annuus and H. debilis are participants in one of the earliest identified examples of adaptive trait introgression, and the exchange is hypothesized to have triggered a range expansion in H. annuus. However, the genetic basis of the adaptive exchange has not been examined. Here, we combine quantitative trait locus (QTL) mapping with field measurements of fitness to identify candidate H. debilis QTL alleles likely to have introgressed into H. annuus to form the natural hybrid lineage H. a. texanus. Two 500-individual BC1 mapping populations were grown in central Texas, genotyped for 384 single nucleotide polymorphism (SNP) markers and then phenotyped in the field for two fitness and 22 herbivore resistance, ecophysiological, phenological and architectural traits. We identified a total of 110 QTL, including at least one QTL for 22 of the 24 traits. Over 75% of traits exhibited at least one H. debilis QTL allele that would shift the trait in the direction of the wild hybrid H. a. texanus. We identified three chromosomal regions where H. debilis alleles increased both female and male components of fitness; these regions are expected to be strongly favoured in the wild. QTL for a number of other ecophysiological, phenological and architectural traits colocalized with these three regions and are candidates for the actual traits driving adaptive shifts. G × E interactions played a modest role, with 17% of the QTL showing potentially divergent phenotypic effects between the two field sites. The candidate adaptive chromosomal regions identified here serve as explicit hypotheses for how the genetic architecture of the hybrid lineage came into existence.
Data from: Managing more than the mean: using quantile regression to identify factors related to large elk groups
1. Animal group size distributions are often right-skewed, whereby most groups are small, but most individuals occur in larger groups that may also disproportionately affect ecology and policy. In this case, examining covariates associated with upper quantiles of the group size distribution could facilitate better understanding and management of large animal groups. 2. We studied wintering elk groups in Wyoming, where group sizes span several orders of magnitude, and issues of disease, predation and property damage are affected by larger group sizes. We used quantile regression to evaluate relationships between the group size distribution and variables of land use, habitat, elk density and wolf abundance to identify conditions important to larger elk groups. 3. We recorded 1263 groups ranging from 1 to 1952 elk and found that across all quantiles of group size, group sizes were larger in open habitat and on private land, but the largest effect occurred between irrigated and non-irrigated land [e.g. the 90th quantile group size increased by 135 elk (95% CI = 42, 227) on irrigation]. 4. Only upper quantile group sizes were positively related to broad-scale measures of elk density and wolf abundance. For wolf abundance, this effect was greater on elk groups found in open habitats and private land than those in closed habitats or public land. If we had limited our analysis to mean or median group sizes, we would not have detected these effects. 5. Synthesis and applications. Our analysis of elk group size distributions using quantile regression suggests that private land, irrigation, open habitat, elk density and wolf abundance can affect large elk group sizes. Thus, to manage larger groups by removal or dispersal of individuals, we recommend incentivizing hunting on private land (particularly if irrigated) during the regular and late hunting seasons, promoting tolerance of wolves on private land (if elk aggregate in these areas to avoid wolves) and creating more winter range and varied habitats. Relationships to the variables of interest also differed by quantile, highlighting the importance of using quantile regression to examine response variables more completely to uncover relationships important to conservation and management.
Data from: SNP genotyping identifies new signatures of selection in a deep sample of West African P. falciparum malaria parasites
We used a high density SNP array to genotype 75 P. falciparum isolates recently collected from Senegal and The Gambia in order to search for signals of selection in this malaria endemic region. We found little geographic or temporal stratification of the genetic diversity among the sampled parasites. Through application of the iHS and REHH haplotype-based tests for positive selection, we found evidence of recent selective sweeps at a known drug resistance locus, at several known antigenic loci, and at several genomic regions not previously identified as sites of recent selection. We discuss the value of deep population-specific genomic analyses for identifying selection signals within sampled endemic populations of parasites, which may correspond to local selection pressures such as distinctive therapeutic regimes or mosquito vectors.
Data from: From animal tracks to fine-scale movement modes: a straightforward approach for identifying multiple, spatial movement patterns
1. Thanks to developments in animal tracking technology, detailed data on the movement tracks of individual animals are now attainable for many species. However, straightforward methods to decompose individual tracks into high-resolution, spatial modes are lacking but are essential to understand what an animal is doing. 2. We developed an analytical approach that combines separately-validated methods into a straightforward tool for converting animal GPS tracks to short-range movement modes. Our three-step analytical process comprises: (1) decomposing data into separate movement segments using behavioural change point analysis; (2) defining candidate movement modes and translating them into non-linear or linear equations between net squared displacement (NSD) and time; and (3) fitting each candidate equation to NSD segments and determining the best-fitting modes using Concordance Criteria, Akaike's Information Criteria and other fine-scale segment characteristics. We illustrate our approach for three sub-adults, male wild boar Sus scrofa tracked at 15 min intervals over 4 months using GPS collars. We defined five candidate movement modes based on previously published studies of short-term movements: encamped, ranging, round trips (complete and partial), and wandering. 3. Our approach successfully classified over 80% of the tracks into these movement modes lasting between 5 and 54 hours and covering between 300 m to 20 km. Repeated analyses of GPS data resampled at different rates indicated that one positional fix every 3-4 h was sufficient for >70% classification success. Classified modes were consistent with published observations of wild boar movement, further validating our method. 4. The proposed approach advances the status quo by permitting classification into multiple movement modes (where these are adequately discernable from spatial fixes) facilitating analyses at high temporal and spatial resolutions, and is straightforward, largely objective, and without restrictive assumptions, necessary parameterizations or visual interpretation. Thus, it should capture the complexity and variability of tracked animal movement mode for a variety of taxa across a wide range of spatial and temporal scales.
Data from: Missing the people for the trees: identifying coupled natural-human system feedbacks driving the ecology of Lyme disease
1. Infectious diseases are rapidly emerging and many are increasing in incidence across the globe. Processes of land-use change, notably habitat loss and fragmentation, have been widely implicated in emergence and spread of zoonoses such as Lyme disease, yet evidence remains equivocal. 2. Here we discuss and apply an innovative approach from the social sciences, instrumental variables, that seeks to tease out causality from observational data. Using this approach, we revisit the effect of forest fragmentation on Lyme disease incidence, focusing on human interaction with fragmented landscapes. Though human interaction with infected ticks is of clear and fundamental importance to human disease incidence, human activities that influence exposure have been nearly universally overlooked in the ecology literature. 3. Using county-level land-use and Lyme disease incidence data for ~800 counties from the northeastern United States over the span of a decade, we illustrate (1) human interaction with fragmented forest landscapes reliably predicts Lyme disease incidence, while ecological measures of forest fragmentation alone are unreliable predictors and (2) that identifying the effect of forest fragmentation on human disease requires addressing the feedback between Lyme disease risk and human decisions to avoid interaction with high-risk landscapes. 4. Synthesis and applications. The innovative approach and novel results help to clarify the equivocal literature on forest fragmentation and Lyme disease, and illustrate the key role that human behavior may be playing in the ecology of Lyme disease in North America. Accounting for human activity and behavior in the ecology of disease more broadly may result in improved understanding of both the ecological drivers of disease, as well as actionable intervention strategies to reduce disease burden in a changing world. For example, our model results have practical implications for land-use policy aimed at disease reduction. Our model suggests land use regulations that reduce parcel size would be an actionable approach for policy makers concerned about increasing Lyme disease incidence in the northeastern US.10-Oct-2018
Data from: Genome-wide exon-capture approach identifies genetic variants of Norway spruce genes associated with susceptibility to Heterobasidion parviporum infection
Root and butt rot caused by members of the Heterobasidion annosum species complex is the most economically important disease of conifer trees in boreal forests. Wood decay in the infected trees dramatically decreases their value and causes considerable losses to forest owners. Trees vary in their susceptibility to Heterobasidion infection, but the genetic determinants underlying the variation in the susceptibility are not well-understood. We performed the identification of Norway spruce genes associated with the resistance to Heterobasidion parviporum infection using genome-wide exon-capture approach. Sixty-four clonal Norway spruce lines were phenotyped, and their responses to H. parviporum inoculation were determined by lesion length measurements. Afterwards, the spruce lines were genotyped by targeted resequencing and identification of genetic variants (SNPs). Genome-wide association analysis identified 10 SNPs located within 8 genes as significantly associated with the larger necrotic lesions in response to H. parviporum inoculation. The genetic variants identified in our analysis are potential marker candidates for future screening programs aiming at the differentiation of disease-susceptible and resistant trees.
Data from: Patterns of genetic differentiation at MHC class I genes and microsatellites identify conservation units in the giant panda
Background: Evaluating patterns of genetic variation is important to identify conservation units (i.e., evolutionarily significant units [ESUs], management units [MUs], and adaptive units [AUs]) in endangered species. While neutral markers could be used to infer population history, their application in the estimation of adaptive variation is limited. The capacity to adapt to various environments is vital for the long-term survival of endangered species. Hence, analysis of adaptive loci, such as the major histocompatibility complex (MHC) genes, is critical for conservation genetics studies. Here, we investigated 4 classical MHC class I genes (Aime-C, Aime-F, Aime-I, and Aime-L) and 8 microsatellites to infer patterns of genetic variation in the giant panda (Ailuropoda melanoleuca) and to further define conservation units. Results: Overall, we identified 24 haplotypes (9 for Aime-C, 1 for Aime-F, 7 for Aime-I, and 7 for Aime-L) from 218 individuals obtained from 6 populations of giant panda. We found that the Xiaoxiangling population had the highest genetic variation at microsatellites among the 6 giant panda populations and higher genetic variation at Aime-MHC class I genes than other larger populations (Qinling, Qionglai, and Minshan populations). Differentiation index (FST)-based phylogenetic and Bayesian clustering analyses for Aime-MHC-I and microsatellite loci both supported that most populations were highly differentiated. The Qinling population was the most genetically differentiated. Conclusions: The giant panda showed a relatively higher level of genetic diversity at MHC class I genes compared with endangered felids. Using all of the loci, we found that the 6 giant panda populations fell into 2 ESUs: Qinling and non-Qinling populations. We defined 3 MUs based on microsatellites: Qinling, Minshan-Qionglai, and Daxiangling-Xiaoxiangling-Liangshan. We also recommended 3 possible AUs based on MHC loci: Qinling, Minshan-Qionglai, and Daxiangling-Xiaoxiangling-Liangshan. Furthermore, we recommend that a captive breeding program be considered for the Qinling panda population.
Data from: Admixture mapping identifies introgressed genomic regions in North American canids
Hybrid zones typically contain novel gene combinations that can be tested by natural selection in a unique genetic context. Parental haplotypes that increase fitness can introgress beyond the hybrid zone, into the range of parental species. We used the Affymetrix canine SNP genotyping array to identify genomic regions tagged by multiple ancestry informative markers that are more frequent in an admixed population than expected. We surveyed a hybrid zone formed in the last 100 years as coyotes expanded their range into eastern North America. Concomitant with expansion, coyotes hybridized with wolves and some populations became more wolflike, such that coyotes in the northeast have the largest body size of any coyote population. Using a set of 3102 ancestry informative markers, we identified 60 differentially introgressed regions in 44 canines across this admixture zone. These regions are characterized by an excess of exogenous ancestry and, in northeastern coyotes, are enriched for genes affecting body size and skeletal proportions. Further, introgressed wolf-derived alleles have penetrated into Southern US coyote populations. Because no wolves currently exist in this area, these alleles are unlikely to have originated from recent hybridization. Instead, they probably originated from intraspecific gene flow or ancient admixture. We show that grey wolf and coyote admixture has far-reaching effects and, in addition to phenotypically transforming admixed populations, allows for the differential movement of alleles from different parental species to be tested in new genomic backgrounds.
Data from: An integrated framework to identify wildlife populations under threat from climate change
Climate change is a major threat to global biodiversity that will produce a range of new selection pressures. Understanding species responses to climate change requires an interdisciplinary perspective, combining ecological, molecular and environmental approaches. We propose an applied integrated framework to identify populations under threat from climate change based on their extent of exposure, inherent sensitivity due to adaptive and neutral genetic variation and range shift potential. We consider intraspecific vulnerability and population-level responses, an important but often neglected conservation research priority. We demonstrate how this framework can be applied to vertebrates with limited dispersal abilities using empirical data for the bat Plecotus austriacus. We use ecological niche modelling and environmental dissimilarity analysis to locate areas at high risk of exposure to future changes. Combining outlier tests with genotype-environment association analysis we identify potential climate-adaptive SNPs in our genomic dataset and differences in the frequency of adaptive and neutral variation between populations. We assess landscape connectivity and show that changing environmental suitability may limit the future movement of individuals, thus affecting both the ability of populations to shift their distribution to climatically suitable areas and the probability of evolutionary rescue through the spread of adaptive genetic variation among populations. Therefore a better understanding of movement ecology and landscape connectivity is needed for predicting population persistence under climate change. Our study highlights the importance of incorporating genomic data to determine sensitivity, adaptive potential and range shift potential, instead of relying solely on exposure to guide species vulnerability assessments and conservation planning.
Data from: Identifying patterns and drivers of coral diversity in the Central Indo-Pacific marine biodiversity hotspot
Biodiversity hotspots are increasingly recognized as areas of high taxonomic and functional diversity. These hotspots are dynamic and shift geographically over time in response to environmental change. To identify drivers of the origin, evolution, and persistence of diversity hotspots, we investigated the diversity patterns of reef-building corals (Scleractinia) in the Central Indo-Pacific, a marine biodiversity hotspot for the last 25 Myr. We used the scleractinian fossil record (based on literature and a newly acquired fossil collection) to examine the taxonomic and functional diversity of corals from the Eocene to Pliocene. Our data identify potential drivers of coral diversity through time (and space) in the Central Indo-Pacific by constraining the timing of taxonomic turnover events and correlating them with known environmental changes. Increases in taxonomic diversity, high origination rates, and changes in abundance of functional character states indicate that the origin of the Central Indo-Pacific hotspot occurred during the Oligocene, initially through proliferation of pre-existing taxa and then by origination of new taxa. In contrast to taxonomic diversity, overall functional diversity of Central Indo-Pacific reef-building corals remained constant from the Eocene to the Pliocene. Our results identify global sea level as a main driver of diversity increase that, together with local tectonics, regulates availability of suitable habitats. Moreover, marine biodiversity hotspots develop from both the accumulation of taxa from older biodiversity hotspots and origination of new taxa. Our study demonstrates the utility of a combined literature-based and new collection approach for gaining new insights into the timing, drivers, and development of tropical biodiversity hotspots.
Data from: Cluster analysis successfully identifies clinically meaningful knee valgus moment patterns: frequency of early peaks reflects sex-specific ACL injury incidence
Background: Biomechanical studies of ACL injury risk factors frequently analyze only a fraction of the relevant data, and typically not in accordance with the injury mechanism. Extracting a peak value within a time series of relevance to ACL injuries is challenging due to differences in the relative timing and size of the peak value of interest. Aims/hypotheses: The aim was to cluster analyze the knee valgus moment time series curve shape in the early stance phase. We hypothesized that 1a) There would be few discrete curve shapes, 1b) there would be a shape reflecting an early peak of the knee valgus moment, 2a) youth athletes of both sexes would show similar frequencies of early peaks, 2b) adolescent girls would have greater early peak frequencies. Methods: N = 213 (39% boys) youth soccer and team handball athletes (phase 1) and N = 35 (45% boys) with 5 year follow-up data (phase 2) were recorded performing a change of direction task with 3D motion analysis and a force plate. The time series of the first 30% of stance phase were cluster analyzed based on Euclidean distances in two steps; shape-based main clusters with a transformed time series, and magnitude based sub-clusters with body weight normalized time series. Group differences (sex, phase) in curve shape frequencies, and shape-magnitude frequencies were tested with chi-squared tests. Results: Six discrete shape-clusters and 14 magnitude based sub-clusters were formed. Phase 1 boys had greater frequency of early peaks than phase 1 girls (38% vs 25% respectively, P < 0.001 for full test). Phase 2 girls had greater frequency of early peaks than phase 2 boys (42% vs 21% respectively, P < 0.001 for full test). Conclusions: Cluster analysis can reveal different patterns of curve shapes in biomechanical data, which likely reflect different movement strategies. The early peak shape is relatable to the ACL injury mechanism as the timing of its peak moment is consistent with the timing of injury. Greater frequency of early peaks demonstrated by Phase 2 girls is consistent with their higher risk of ACL injury in sports.
Data from: Identifying native plants for coordinated habitat management of arthropod pollinators, herbivores and natural enemies
1. Providing non-crop flowering resources in agricultural landscapes is widely promoted as a strategy to support arthropods that deliver pollination and pest control services. However, management options have largely been developed separately for pollinators and natural enemies, whereas possible effects on insect herbivores, such as crop pests, have often been overlooked. A first critical step for design and implementation of multifunctional plantings that promote beneficial arthropods while controlling insect pests is to identify suitable plant species to use. 2. We aimed to identify California native plants and, more generally, plant traits suitable for the coordinated management of pollinators (wild bees and honey bees), insect herbivores and arthropod natural enemies (predators and parasitic wasps). We established 43 plant species in a common garden experiment and sampled arthropods by weekly netting (wild bees), observations (honey bees) or vacuum sampling (insect herbivores, arthropod predators and parasitic wasps) during peak bloom of each plant species over two years. 3. Plant species differed in attractiveness for each arthropod functional group. Floral area of the focal plant species positively affected honey bee, predator and parasitic wasp attractiveness. Later bloom period was associated with lower numbers of parasitic wasps. Flower type (actinomorphic, composite or zygomorphic) predicted attractiveness for honey bees, which preferred actinomorphic over composite flowers and for parasitic wasps, which preferred composite flowers over actinomorphic flowers. 4. Across plant species, herbivore, predator and parasitic wasp abundances were positively correlated, and honey bee abundance correlated negatively to herbivore abundance. 5. Synthesis and applications. We use data from our common garden experiment to inform evidence-based selection of plants that support pollinators and natural enemies without enhancing potential pests. We recommend selecting plant species with a high floral area per ground area unit, as this metric predicts the abundances of several groups of beneficial arthropods. Multiple correlations between functionally important arthropod groups across plant species stress the importance of a multifunctional approach to arthropod habitat management.
ScienceDex guides
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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.