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Fig. 1 in Rancho La Brea Fossil Indicates Native Nearctic Status for Necrobia violacea (Linnaeus) (Coleoptera: Cleridae), a Species Previously Considered a Synanthropic Introduction to North America
Fig. 1. Stacked photographs of the heads and pronota of Necrobia species. A) Modern, British N. violacea from the British Collection in the Natural History Museum, London, photographed by RBA, B) Fossil N. violacea from the Rancho La Brea Tar Pits, photographed by ARH, C) Modern, British N. rufipes from the British Collection in the Natural History Museum, London, photographed by RBA.
Figure 4 in Molecular phylogeny and divergence times of Hormaphidinae (Hemiptera: Aphididae) indicate Late Cretaceous tribal diversification
Figure 4. Simplified phylogenetic tree with information on host associations of sampled in-group genera. The phylogenetic pattern of host associations and dating might imply a coincidence between tribal diversifications within Hormaphidinae and the appearance of their primary hosts.
Figure 2 in Molecular phylogeny and divergence times of Hormaphidinae (Hemiptera: Aphididae) indicate Late Cretaceous tribal diversification
Figure 2. Phylogeny of Hormaphidinae based on combined data of nuclear EF-1a and mitochondrial COI sequences. The tree obtained from Bayesian analysis is shown. Bootstrap values (> 50) from maximum-parsimony/maximum-likelihood analyses are shown above the branches, and the Bayesian posterior probabilities (> 0.90) are shown below the branches.
Figure 1 in Molecular phylogeny and divergence times of Hormaphidinae (Hemiptera: Aphididae) indicate Late Cretaceous tribal diversification
Figure 1. Phylogeny of Hormaphidinae based on nuclear EF-1a sequences. The tree obtained from Bayesian analysis is shown. Numbers above the branches are bootstrap values (> 50) from maximum-parsimony/maximum-likelihood analyses, and the Bayesian posterior probabilities (> 0.90) are shown below the branches. Species including more than one sample are represented by species names with voucher numbers.
Figure 4 in Horn scaling relationships in three species of Bledius Leach 1819 (Insecta: Coleoptera: Staphylinidae) show no indication of fitting non-linear allometric models
Figure 4. Scaling relationship between log pronotum width and log horn length in Bledius tricornis (Herbst, 1784). The slope is 1.166 (SE = 0.093) and the linear model has an R2 of 0.78.
Figure 3 in Horn scaling relationships in three species of Bledius Leach 1819 (Insecta: Coleoptera: Staphylinidae) show no indication of fitting non-linear allometric models
Figure 3. Scaling relationship between log pronotum width and log horn length in Bledius frisius Lohse, 1978. The slope is 1.816 (SE = 0.136) and the linear model has an R2 of 0.78.
Figure 1 in Horn scaling relationships in three species of Bledius Leach 1819 (Insecta: Coleoptera: Staphylinidae) show no indication of fitting non-linear allometric models
Figure 1. (a) Bledius spectabilis Kraatz, 1857 schematic diagram of pronotal measurements taken and habitus. (b) Bledius spectabilis at Chesil Fleet, Dorset, UK (photograph by Steve Trewhella). HL = horn length; PW = pronotum width.
Figure 2 in Horn scaling relationships in three species of Bledius Leach 1819 (Insecta: Coleoptera: Staphylinidae) show no indication of fitting non-linear allometric models
Figure 2. Scaling relationship between log pronotum width and log horn length in Bledius spectabilis Kraatz, 1857. The slope is 1.447 (SE = 0.096) and the linear model has an R2 of 0.68.
Use of synthetic aperture radar data for the determination of vegetation indices
<p>Database for the article "Use of synthetic aperture radar data for the determination of vegetation indices"</p>
FIGURE. Map of Mexico, indicating the number of families, genera, and species of Mexican Vascular Epiphytes by state. in Mexican Vascular Epiphytes: Richness and Distribution
FIGURE. Map of Mexico, indicating the number of families, genera, and species of Mexican Vascular Epiphytes by state.
FIGURE. Inflorescence of Hylaeaicum. A. H. myrmecophilum (Leme 2555). B. H. levianum (Leme 5639-A). C–D. H. wurdackii (Leme 2567). C. Top view. D. Outer primary fascicle, with secondary fascicles indicated by an arrow. E–G. H. eleutheropetalum var. eleutheropetalum (Leme 4491). E. Top view. F. Secondary fascicles indicated by an arrow. G. Outer primary fascicles, with secondary fascicles indicated by an arrow. H. H. margaretae (Leme 2331). I. H. tarapotoense (Leme 1977). J. H. aff. myrmecophilum (Leme 3487). K. H. pendulum (Leme 1979). in Re-evaluation of the Amazonian Hylaeaicum (Bromeliaceae: Bromelioideae) based on neglected morphological traits and molecular evidence
FIGURE. Inflorescence of Hylaeaicum. A. H. myrmecophilum (Leme 2555). B. H. levianum (Leme 5639-A). C–D. H. wurdackii (Leme 2567). C. Top view. D. Outer primary fascicle, with secondary fascicles indicated by an arrow. E–G. H. eleutheropetalum var. eleutheropetalum (Leme 4491). E. Top view. F. Secondary fascicles indicated by an arrow. G. Outer primary fascicles, with secondary fascicles indicated by an arrow. H. H. margaretae (Leme 2331). I. H. tarapotoense (Leme 1977). J. H. aff. myrmecophilum (Leme 3487). K. H. pendulum (Leme 1979).
Text-fig. 15. Lightly worn molars of Sayimys hintoni n. sp. (f, g, h) and S. cf. minor (e and i) from locality H.-GSP81.14a and S. chinjiensis from H.-GSP82.24 (a, b, c, d). Upper molars: occlusal surfaces and labial sides, lower molars occlusal surfaces and lingual sides. Side views horizontally-mirrored, anterior indicated by arrows. in An Exceptional Large Sample Of The Early Miocene Ctenodactyline Rodent Sayimys Giganteus, Specific Variation And Taxonomic Implications
Text-fig. 15. Lightly worn molars of Sayimys hintoni n. sp. (f, g, h) and S. cf. minor (e and i) from locality H.-GSP81.14a and S. chinjiensis from H.-GSP82.24 (a, b, c, d). Upper molars: occlusal surfaces and labial sides, lower molars occlusal surfaces and lingual sides. Side views horizontally-mirrored, anterior indicated by arrows.
Text-fig. 11. Cheek teeth of Sayimys giganteus from Keseköy. Anterior sides are indicated by arrows. Top row: labial sides of M3, M2, M1 and DP4, images horizontally-mirrored. Second row: occlusal surfaces of M3, M2, M1 and DP4 of the same specimens. Third row: lingual sides of m3, m2, m1 and dp4, images horizontally-mirrored. Lower row: occlusal surfaces of m3, m2, m1 and dp4 of the same specimens. in An Exceptional Large Sample Of The Early Miocene Ctenodactyline Rodent Sayimys Giganteus, Specific Variation And Taxonomic Implications
Text-fig. 11. Cheek teeth of Sayimys giganteus from Keseköy. Anterior sides are indicated by arrows. Top row: labial sides of M3, M2, M1 and DP4, images horizontally-mirrored. Second row: occlusal surfaces of M3, M2, M1 and DP4 of the same specimens. Third row: lingual sides of m3, m2, m1 and dp4, images horizontally-mirrored. Lower row: occlusal surfaces of m3, m2, m1 and dp4 of the same specimens.
Text-fig. 12. Ranges of the length of the dp4 based on data from the literature. Vertical scale in Ma, the samples are from the Siwaliks (black) and Turkey, Greece and Arabia (red). Type localities of species are indicated with an asterisk. The Y and Z sites are from Baskin (1996), its size ranges are composed of data from several localities and the vertical arrowed broken line indicates the age range of these sites. in An Exceptional Large Sample Of The Early Miocene Ctenodactyline Rodent Sayimys Giganteus, Specific Variation And Taxonomic Implications
Text-fig. 12. Ranges of the length of the dp4 based on data from the literature. Vertical scale in Ma, the samples are from the Siwaliks (black) and Turkey, Greece and Arabia (red). Type localities of species are indicated with an asterisk. The Y and Z sites are from Baskin (1996), its size ranges are composed of data from several localities and the vertical arrowed broken line indicates the age range of these sites.
Immunological indices and parasites in blackbirds
<p>1. Despite the intensive use of immune indices in immunoecology, whether to interpret the results of immune indices in terms of actual immune competence (i.e., ability to control and clear parasite infections as indicated by high values of immune indices associated with low parasite loads) or current immune activation (pathogenic infection being associated with high parasite load and high values of immune indices) is still an open question. Most studies to date have produced contrasting results focused on the effect of a single parasite species despite the fact that hosts usually harbour a community of parasites that influence one another's impact on host immune response.</p> <p>2. We simultaneously assessed blood parasites, intestinal parasites and ectoparasite loads in male blackbirds and compared these measures to several immune indices to investigate how parasites explain the variation around the mean of these immune indices.</p> <p>3. Parasite loads covaried within hosts. Immune indices better reflected the interacting effects of these parasites than the independent effect of each parasite. Immune indices may therefore be better indicators of ongoing pathogenic infections than immune competence. Furthermore, intestinal parasites explained a significant part of the variance in most immune indices through their interactions with other parasites, suggesting that they have a strong influence in modulating immune function.</p> <p>4. Taking the parasite community into account in immunoecology studies will certainly help increase our understanding of immune indices.</p>
C:N:P stoichiometric indicator of net primary production of Cynodon dactylon (Linn.) Pers. in the riparian zone of a Three Gorges tributary
<p>Net primary production (NPP) was strongly influenced by the flooding stress, which is closely related to carbon (C), nitrogen (N) and phosphorus (P) allocation in plant aboveground (leaf-stem) and belowground (root) biomass. However, the relationship of NPP with the C:N:P stoichiometric ratio in plant tissues remains unknown, especially in the riparian zone of the Three Gorges Reservoir (TGR). In this study, the leaf-stem and root C, N, P content and biomass of <i>Cynodon dactylon (Linn.) Pers. </i>(<i>C. dactylon</i>) were investigated at the 145-155m, 155-165m and 165-175m altitudes of the riparian zone in TGR tributary-Pengxi River. The results showed that the biomass and NPP of <i>C. dactylon</i> had a similar trend along the riparian zone altitudes. The root showed much lower N and P content, but much higher N and P use efficiency with higher C:N and C:P ratio than that of leaf-stem under N limitation condition. Hydrological and C:N:P stoichiometric variables could predict 68% of the NPP variance. NPP was positively directly correlated to C:N in the stem-leaf to root ratio (C:N<sub>stem-leaf/root</sub>) and C:P ratio in the root<sub> </sub>(C:P<sub>root </sub>ratio ), thus could be regarded as the indicators of NPP in the riparian zone of the TGR.</p>
Data from: Multi-generation genomic prediction of maize yield using parametric and non-parametric sparse selection indices
<p>Genomic prediction models are often calibrated using multi-generation data. Over time, as data accumulates, training data sets become increasingly heterogeneous. Differences in allele frequency and linkage disequilibrium patterns between the training and prediction genotypes may limit prediction accuracy. This leads to the question of whether all available data or a subset of it should be used to calibrate genomic prediction models. Previous research on training set optimization has focused on identifying a subset of the available data that is optimal for a given prediction set. However, this approach does not contemplate the possibility that different training sets may be optimal for different prediction genotypes. To address this problem, we recently introduced a sparse selection index (SSI) that identifies an optimal training set for each individual in a prediction set. Using additive genomic relationships, the SSI can provide increased accuracy relative to genomic-BLUP (GBLUP). Non-parametric genomic models using Gaussian kernels (KBLUP) have, in some cases, yielded higher prediction accuracies than standard additive models. Therefore, here we studied whether combining SSIs and kernel methods could further improve prediction accuracy when training genomic models using multi-generation data. Using four years of doubled haploid maize data from the International Maize and Wheat Improvement Center (CIMMYT), we found that when predicting grain yield the KBLUP outperformed the GBLUP, and that using SSI with additive relationships (GSSI) lead to 5-17% increases in accuracy, relative to the GBLUP. However, differences in prediction accuracy between the KBLUP and the kernel-based SSI were smaller and not always significant.</p>
Data from: Effectiveness of signs of activity as relative abundance indices for wild boar
<p><span>Population growth in wild boars and feral pigs (</span><i><span>Sus scrofa</span></i><span>) has negative environmental and economic implications worldwide. Accordingly, it is necessary to monitor population trends for appropriate management. Despite the potential for bias, relative abundance indices based on signs of activity </span><span><span>have the potential to be </span></span><span>practical, low-cost monitoring tools for data collection at a local scale and over large areas. However, few studies have examined the effectiveness of specific signs as measures of relative wild boar abundance </span><span><span>in comparison with reliable density estimates.</span></span><span> In this study, we examined whether three activity signs (digging marks, rubbing marks, and fecal pellet groups) could be used as relative abundance indices for wild boar. In particular, we conducted transect surveys for signs of activity as well as camera trap surveys from September 2017 to January 2018 at six sites in Hyogo Prefecture and eight sites in Chiba Prefecture, Japan. We modeled the relations between the number of activity signs and wild boar densities or </span><span><span>abundances</span></span><span> estimated from camera trap data </span><span><span>in a hierarchical framework</span></span><span>. Fecal pellet counts are a well-established method for estimating the abundance of herbivores, including wild boar; however, we found few fecal pellet groups in our study area, and the counts were not related to wild boar densities. Instead, we found that digging marks were strongly associated with estimates of wild boar density. Although fluctuations in the number of digging marks may be affected by factors other than boar density, including environmental conditions and seasonality, our results suggest that digging marks are an effective relative abundance index for evaluations of the spatial patterns of wild boar in Japan.</span></p>
FIGURE. Median network analyses (MNA) of a subset of the C. trilobus aggregate (i.e. those in the clade A from Fig. 11) based on concatenated DNA sequence data from ITS, trnL-trnF and psbJ-petA. Stars and arrow indicate accessions discussed in the text. NI: North Island, SI: South Island. in Five new species of Corybas (Diurideae, Orchidaceae) endemic to New Zealand and phylogeny of the Nematoceras clade
FIGURE. Median network analyses (MNA) of a subset of the C. trilobus aggregate (i.e. those in the clade A from Fig. 11) based on concatenated DNA sequence data from ITS, trnL-trnF and psbJ-petA. Stars and arrow indicate accessions discussed in the text. NI: North Island, SI: South Island.
FIGURE. Bayesian tree of New Zealand spider orchids (Corybas) based on DNA sequence data from ITS, trnL-trnF and psbJ-petA. Major clades are indicated by open bars and capital letters, members of the C. trilobus aggregate are shaded, and posterior probabilities/ bootstrap percentages (≥50) indicated by numbers near each node. NI: North Island, SI: South Island, MCQI: Macquarie Island, CHI: Chatham Island in Five new species of Corybas (Diurideae, Orchidaceae) endemic to New Zealand and phylogeny of the Nematoceras clade
FIGURE. Bayesian tree of New Zealand spider orchids (Corybas) based on DNA sequence data from ITS, trnL-trnF and psbJ-petA. Major clades are indicated by open bars and capital letters, members of the C. trilobus aggregate are shaded, and posterior probabilities/ bootstrap percentages (≥50) indicated by numbers near each node. NI: North Island, SI: South Island, MCQI: Macquarie Island, CHI: Chatham Island
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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.