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FIGURE 35. Pterygosoma sinaita Jack, 1961, female. A in A systematic revision of the scale mite genus Pterygosoma Peters, 1849 (Acariformes: Pterygosomatidae)
FIGURE 35. Pterygosoma sinaita Jack, 1961, female. A, dorsal view; B, ventral view; C, postero-lateral seta.
FIGURE 26 in A systematic revision of the scale mite genus Pterygosoma Peters, 1849 (Acariformes: Pterygosomatidae)
FIGURE 26. Pterygosoma inermis (Trägårdh, 1905), female. A, gnathosoma in dorsal view, B, tarsi I in lateral view.
FIGURE 30 in A systematic revision of the scale mite genus Pterygosoma Peters, 1849 (Acariformes: Pterygosomatidae)
FIGURE 30. Pterygosoma parasiniatum Fajfer, Melnikov and Dabert, 2016, male. A, dorsal view; B, ventral view (after Fajfer et al. 2016).
FIGURE 19. Pterygosoma balochistani Fajfer, 2016, male. A in A systematic revision of the scale mite genus Pterygosoma Peters, 1849 (Acariformes: Pterygosomatidae)
FIGURE 19. Pterygosoma balochistani Fajfer, 2016, male. A, dorsal view; B, ventral view (after Fajfer 2016).
FIGURE 23. Pterygosoma dhofarensis Fajfer and Melnikov 2014, female. A in A systematic revision of the scale mite genus Pterygosoma Peters, 1849 (Acariformes: Pterygosomatidae)
FIGURE 23. Pterygosoma dhofarensis Fajfer and Melnikov 2014, female. A, dorsal view; B, ventral view (after Fajfer and Melnikov 2014).
FIGURE 8. A in A mid-Cretaceous female scale insect (Hemiptera: Sternorrhyncha: Coccomorpha) in Burmese amber
FIGURE 8. A Rostrum (arrows) of Paleolepidotus macrocolus gen. et sp. n. in Burmese amber; B duplicate image with overlaid dotted outline of rostrum and interpretation of segmentation adopted in description. Scale bar = 560 µm.
FIGURE 4 in A mid-Cretaceous female scale insect (Hemiptera: Sternorrhyncha: Coccomorpha) in Burmese amber
FIGURE 4. Detail of terminal antennomere of Paleolepidotus macrocolus gen. et sp. n. in Burmese amber; image and illustration of claw. Arrow shows constricted "knob" at tip. Scale bar = 57 µm.
Raw Data of "Runoff and erosive responses to different land-cover types in semiarid environment: Scale effects and controlling factors"
<p>The raw data of manuscript "Runoff and erosive responses to different land-cover types in semiarid environment: Scale effects and controlling factors" </p>
Broad-scale patterns of the Afro-Palearctic landbird migration
Aim: Animal migration strategies balance trade-offs between mortality and reproduction in seasonal environments. Knowledge of broad-scale biogeographical patterns of animal migration is important for understanding ecological drivers of migratory behaviours. Here we present a flyway-scale assessment of the spatial structure and seasonal dynamics of the Afro-Palearctic bird migration system and explore how phenology of the environment guides long-distance migration. Location: Europe and Africa. Time period: 2009–2017. Major taxa studied: Birds. Methods: We compiled an individual-based dataset comprising 23 passerine and near-passerine species of 55 European breeding populations where a total of 564 individuals were tracked migrating between Europe and sub-Saharan Africa. In addition, we used remote sensed observations on primary productivity (NDVI) to estimate the timing of vegetation green-up in spring and senescence in autumn across Europe. First, we described how individual breeding and non-breeding sites and the migratory flyways link geographically. Second, we examined how migration timing along the two major Afro-Palearctic flyways is tuned with vegetation phenology en route and at the breeding sites. Results: While we found the longitudes of individual breeding and non-breeding sites to be strongly positively related, the latitudes of breeding and non-breeding sites were negatively related. In autumn, timing of migration was similar along the Western and the Eastern flyways and happened ahead of the autumnal senescence of vegetation. In spring, migration timing was approximately two weeks later along the Eastern flyway than on the Western flyway which coincided with the later spring green-up in Eastern Europe. Main Conclusions: Migration of the Afro-Palearctic landbirds follows a longitudinally parallel leap-frog migration pattern where migrants track vegetation green-up in spring and depart before vegetation senescence in autumn. However, the ongoing global change have the potential to disrupt this spatiotemporal synchronization between migration timing and spring green-up with variable effects on different migrant populations.
Data from: Genetic structure at three spatial scales is consistent with limited philopatry in Ricord's Rock Iguanas (Cyclura ricordii)
Cyclura ricordii is an endemic iguana from Hispaniola Island and is threatened on the IUCN Red List. The main threats are predation by introduced mammals, habitat destruction, and hunting pressure. The present study focused on two nesting sites from Pedernales Province in the Dominican Republic. The hypothesis that natal philopatry influences dispersal and nest site selection was tested. Monitoring and sampling took place in 2012 and 2013. Polymorphic markers were used to evaluate whether natal philopatry limits dispersal at multiple spatial scales. Ripley's K revealed that nests were significantly clustered at multiple scales, when both nesting sites were considered and within each nesting site. This suggests a patchy, non-random distribution of nests within nest sites. Hierarchical AMOVA revealed that nest site aggregations did not explain a significant portion of genetic variation within nesting sites. However, a small but positive correlation between geographic and genetic distance was detected using a Mantel's test. Hence, the relationship between geographic distance and genetic distance among hatchlings within nest sites, while detectable, was not strong enough to have a marked effect on fine scale genetic structure. Spatial and genetic data combined determined that the nesting sites included nesting females from multiple locations, and the hypothesis of 'natal philopatry', was not supported because females nesting in the same cluster were no more closely related to each other than to other females from the same nesting site. These findings imply that nesting aggregations are more likely associated with cryptic habitat variables contributing to optimal nesting conditions.
Data from: Multiple scales of spatial heterogeneity control soil respiration responses to precipitation across a dryland rainfall gradient
<p><i>Aims –</i> Soil respiration (R<sub>s</sub>) is a major pathway for releasing fixed carbon back to the atmosphere. However, controls over R<sub>s</sub> are poorly understood in arid and hyper-arid systems where microbial activity is frequently constrained by moisture. We addressed key uncertainties in R<sub>s</sub>: 1) How do short-term rainfall pulses affect R<sub>s</sub> at sites that differ in long-term precipitation inputs?, 2) how do R<sub>s</sub> responses to short and long-term rainfall differ across soil surfaces?, and 3) how are R<sub>s</sub> responses affected by local-scale attributes?</p> <p><i>Methods – </i>We measured R<sub>s</sub> responses to rainfall pulses over a 48 h period. Working across a climate gradient, we compared R<sub>s </sub>responses on two contrasting soil surfaces which both had two vegetation/soil morphology patch types that differed in organic matter inputs and accumulation.</p> <p><i>Results – </i>Rates of R<sub>s </sub>were low, but highly responsive to rainfall pulses. Stimulation of R<sub>s </sub>by rainfall was generally greater in areas with higher annual rainfall. However, patterns for R<sub>s </sub>responses to rainfall differed greatly on the two soil surfaces and among patch types.</p> <p><i>Conclusions – </i>The strong role of patch type and soil surface in controlling R<sub>s</sub> points to the need to carefully consider small-scale spatial and temporal variation when interpreting dryland biogeochemical fluxes.</p>
Data from: Geographic scale and disturbance influence intraspecific trait variability in leaves and roots of North American understory plants
1. Considering intraspecific trait variability (ITV) in ecological studies has improved our understanding of species persistence and coexistence. These advances are based on the growing number of leaf ITV studies over local gradients, but logistical constraints have prevented a solid examination of ITV in root traits or at scales reflecting species' geographic ranges. 2. We compared the magnitude of ITV in above- and below-ground plant organs across three spatial scales (biophysical region, locality, plot). We focused on six understory species (four herbs, two shrubs) that occur both in disturbed and undisturbed habitats across boreal and temperate Canadian forests. We aimed to document ITV structure over wide ecological and geographical scales by asking: 1) What is the breadth of ITV across species range-scale?; 2) What proportion of ITV is captured at different spatial scales, particularly when local scale disturbances are considered? and 3) Is the variance structure consistent between leaf and analogous root traits, and between morphological and chemical traits? 3. Following standardized methods, we sampled 818 populations across 79 forest plots simultaneously, including disturbed and undisturbed stands, spanning four biophysical regions (~5200 km). Traits measured included specific leaf area (SLA), specific root length (SRL), and leaf and root nutrient concentrations (N, P, K, Mg, Ca). We used variance decomposition techniques to characterize ITV structure across scales. 4. Our results show that an important proportion of ITV occurred at the local scale when sampling includes contrasting environmental conditions resulting from local disturbance. A certain proportion of the variability in both leaf and root traits remained unaccounted for by the three sampling scales included in the design (36% on average) and a largest amount for SRL (54%). Substantial differences in magnitude of ITV were found among the six species, and between analogous traits, suggesting that trait distribution was influenced by species strategy and reflects the extent of understory environment heterogeneity. 5. Even for species with broad geographical distributions, a large proportion of within-species trait variability can be captured by sampling locally across ecological gradients. This has practical implications for sampling design and trait selection for both local studies and continental scale modeling.
Large-scale metabolic interaction network of the mouse and human gut microbiota
<p>The role of our gut microbiota in health and disease is largely attributed to the collective metabolic activities of the inhabitant microbes. A system-level framework of the microbial community structure, mediated through metabolite transport, would provide important insights into the complex microbe-microbe and host-microbe chemical interactions. This framework, if adaptable to both mouse and human systems, would be useful for mechanistic interpretations of the vast amounts of experimental data from gut microbiomes in murine animal models, whether humanized or not. Here, we constructed a literature-curated, interspecies network of the mammalian gut microbiota for mouse and human hosts, called NJC19. This network is an extensive data resource, encompassing 838 microbial species (766 bacteria, 53 archaea, and 19 eukaryotes) and 6 host cell types, interacting through 8,224 small-molecule transport and macromolecule degradation events. Moreover, we compiled 912 negative associations between organisms and metabolic compounds that are not transportable or degradable by those organisms. Our network may facilitate experimental and computational endeavors for the mechanistic investigations of host-associated microbial communities.</p>
Data from: Specialization and niche overlap across spatial scales: revealing ecological factors shaping species richness and coexistence in Australian songbirds
1. Ecological specialization enables the partitioning of resources and thus can facilitate the coexistence of species and promote higher species richness. Specialization and niche partitioning are expected to exert a decisive influence on local spatial scales, while species richness at regional scales should be shaped mostly by historical factors and abiotic conditions. Moreover, specialization is expected to be particularly important in communities that are exceptionally species rich for their environmental conditions. Concurrently, niche overlap in these communities should be minimized to enable species coexistence. 2. We tested these hypotheses by studying specialization-richness relationship and niche overlap in assemblages of 298 species of songbirds (Passeriformes) across Australia. We used local (2-6 ha) to regional (bioregions) spatial scales, and detailed data on habitat, diet, and foraging behaviour (method, substrate, and stratum). 3. We expected the richness-specialization relationship to be particularly strong i) on local spatial scales and ii) in communities exceptionally species rich for given environmental conditions (approximated by moisture and vegetation complexity). We also expected iii) low niche overlap in assemblages with specialized species. 4. Only the third prediction was partly supported. First, while the specialization and species richness were often positively related, the strength and the direction of the relationship changed between traits and across spatial scales. The strength of the specialization-richness relationship was consistently positive only in foraging stratum, and it increased towards smaller spatial scales only in case of habitat and diet. Simultaneously, species in local communities demonstrated high overlap in habitat and diet. Second, we did not find particularly strong specialization-richness relationships in exceptionally species rich communities. Third, we found the expected negative relationship between specialization and overlap in foraging stratum and substrate (in local communities), suggesting that species partition ecological space locally in terms of where they find food. 5. Our expectations were only weakly supported. Specialization on foraging stratum was probably important in facilitating species co-existence. Conversely, although species were often specialized on habitat and diet, high overlap in these traits did not preclude their local coexistence. Overall, specialization and overlap in foraging traits were more important for species coexistence than habitat or diet.
Predicting Phenotype from Multi-Scale Genomic and Environment Data using Neural Networks and Knowledge Graphs
<p><strong>Background: To mitigate the effects of climate change on public health and conservation, we need to better understand the dynamic interplay between biological processes and environmental effects. Machine learning (ML) methods in general, and Deep Learning (DL) methods in particular, are a potential way forward because they are able to cope with the nonlinearity of natural systems. However, there are several barriers that exist, including the absence of ML-ready data. We propose to develop a machine learning framework capable of predicting phenotypes based on multi-scale data about genes and environments. A critical part of this framework are data transformation methods that map the heterogeneous input data into formats that are consumable by the ML techniques. The central hypothesis of this research is that deep learning algorithms and biological knowledge graphs will predict phenotypes more accurately across more taxa and more ecosystems than do current numerical and traditional statistical modeling methods. Our long term goal is to develop predictive analytics for organismal response to environmental perturbations using innovative data science approaches. This pilot project on predicting emergent properties of complex systems and multidimensional interactions is funded by the NSF (Award # 1939945, 1940059, 1940062, 1940330). </strong></p> <p> </p> <p><strong>Results: We have established shared project governance, communication channels, project timeline, and data and computing environment across four universities. We have successfully reached out to three other projects for broader collaboration.</strong></p>
Data from: Chromosome-scale inference of hybrid speciation and admixture with convolutional neural networks
<p>Inferring the frequency and mode of hybridization among closely related organisms is an important step for understanding the process of speciation and can help to uncover reticulated patterns of phylogeny more generally. Phylogenomic methods to test for the presence of hybridization come in many varieties and typically operate by leveraging expected patterns of genealogical discordance in the absence of hybridization. An important assumption made by these tests is that the data (genes or SNPs) are independent given the species tree. However, when the data are closely linked, it is especially important to consider their non-independence. Recently, deep learning techniques such as convolutional neural networks (CNNs) have been used to perform population genetic inferences with linked SNPs coded as binary images. Here we use CNNs for selecting among candidate hybridization scenarios using the tree topology (((P<sub>1</sub>,P<sub>2</sub>),P<sub>3</sub>),Out) and a matrix of pairwise nucleotide divergence (d<sub>XY</sub>) calculated in windows across the genome. Using coalescent simulations to train and independently test a neural network showed that our method, HyDe-CNN, was able to accurately perform model selection for hybridization scenarios across a wide-breath of parameter space. We then used HyDe-CNN to test models of admixture in <em>Heliconius</em> butterflies, as well as comparing it to a random forest classifier trained on introgression-based statistics. Given the flexibility of our approach, the dropping cost of long-read sequencing, and the continued improvement of CNN architectures, we anticipate that inferences of hybridization using deep learning methods like ours will help researchers to better understand patterns of admixture in their study organisms.</p>
Data from: How characteristic is the species characteristic selection scale?
The importance of framing investigations of organism-environment relationships to interpret patterns at relevant spatial scales is increasingly recognized. However, most research related to environmental relationships is single-scaled, implicitly or explicitly assuming that a 'species characteristic selection scale' exists. We tested the premise that a single characteristic scale exists to understand species-environment relationships within species by asking 1) what are the characteristic scales of species' relationships with environmental predictors, and 2) is within-species, cross-predictor consistency in characteristic scales a general phenomenon. Nebraska, USA. 2016 Birds We used data from 86 species at >500 locations to build hierarchical N-mixture models relating species abundance to landcover variables. By incorporating Bayesian latent indicator scale selection, we identified the spatial scales that best explain species-environment relationships with each landcover predictor. We quantify the extent of cross-predictor consistency in characteristic scales, and contrast this to the expectation given a single species' characteristic scale. We found no evidence for a characteristic spatial scale explaining all abundance-environment relationships within species, rather we found substantial variation in scale-dependence across multiple environmental attributes. Furthermore, 33% of species displayed evidence of multiple important scales within environmental attributes. Within species there is little evidence for a single characteristic scale of environmental relationships and considerable variation in species' scale–dependencies. Because species may respond to multiple environmental attributes at different spatial scales, or single environmental attributes at multiple scales, we caution against any unoptimized single-scale studies. Our results demonstrate that until a framework is developed to predict the scales at which species respond to environmental characteristics, multi-scale investigations must be performed to identify and account for multiscale dependencies. Natural selection acting on species' response to distinct environmental attributes, rather than natural selection acting on species' perception of spatial scales per se, may have shaped patterns of scale-dependency and is an area ripe for investigation.
A narrow ear canal reduces sound velocity to 1 create additional acoustic inputs in a micro-scale insect ear
<p><span><span><span><span><span><span><span><span><span><span><span>Located in the forelegs, katydid ears are unique among arthropods in having outer, middle and inner component, analogous to the mammalian ear. Unlike mammals, sound is received externally, and internally via a narrow ear canal (EC) derived from the respiratory tracheal system. Inside the EC sound travels slower than in free air, causing temporal and pressure differences between external and internal inputs. The delay is suspected to arise as sound propagation changes from adiabatic to isothermal, imposed by EC geometry. If true, a reduction in sound velocity should persist independently of the gas composition in the EC. Integrating experimental (laser Doppler vibrometry, micro-CT) and numerical methods, we demonstrate that the narrow radius of the EC is the major cause of the signal time delay. Results imply that the EC is asymmetrically bifurcated, creating four notable auditory paths for each ear. Implication of methods and findings in avian hearing are discussed.</span></span></span></span></span></span></span></span></span></span></span></p>
Strong Scaling Tools 2 Additive manufacturing case study
<p>All data, results, and scripts from the Al-Si-Sc additive manufacturing alloy design high-throughput case study.</p> <p>All data, results, and scripts from Al-Zn-Mg-Cu high-throughput case study.</p> <p><strong>*.zip</strong> are the specimen-specific PARAPROBE results and POS rawdata.</p> <p><strong>*.pdf</strong> are the PDF reports that were created with the automation of paraprobe-autoreporter.</p> <p><strong>src.zip</strong> contains the source code of the paraprobe-autoreporter Python classes with which the results were computed. This source code is meant as a documentation of the results only!<br> <strong>Instead, all users should always use the latest versions of the PARAPROBE tools from the GitLab repository https://gitlab.mpcdf.mpg.de/mpie-aptfim-toolbox</strong>/<strong>paraprobe</strong><br> <strong>https://paraprobe-toolbox.readthedocs.org</strong></p>
Generation of a chromosome-scale genome assembly of the insect-repellant terpenoid-producing Lamiaceae species, Callicarpa americana
<p>Background: Plants exhibit wide chemical diversity due to production of specialized metabolites which function as pollinator attractants, defensive compounds, and signaling molecules. Lamiaceae (mints) are known for their chemodiversity and have been cultivated for use as culinary herbs and as sources of insect repellents, health-promoting compounds, and fragrance. Findings: We report the chromosome-scale genome assembly of <em>Callicarpa americana</em> L. (American beautyberry), a species within the early diverging Callicarpoideae clade of the Lamiaceae, known for its metallic purple fruits and use as an insect repellent due to its production of terpenoids. Using long reads and Hi-C scaffolding, we generated a 506.1 Mb assembly spanning 17 pseudomolecules with an N50 contig and N50 scaffold size of 7.5 Mb and 29.0 Mb, respectively. A total of 32,164 genes was annotated including 53 candidate terpene synthases and 47 putative clusters of specialized metabolite biosynthetic pathways. Whole genome duplication analyses revealed three putative events, which together with local tandem duplication events, contributed to gene family expa, American beautyberransion of terpene synthases. Kolavenyl diphosphate is a gateway to many of <em>C. americana</em>'s bioactive terpenoids; experimental validation confirmed that CamTPS2 encodes kolavenyl diphosphate synthase. Syntenic analyses with <em>Tectona grandis</em> L. f. (teak), a member of the Tectonoideae clade of Lamiaceae known for exceptionally strong wood resistant to insects, revealed 963 collinear blocks and 21,297 <em>C. americana</em> syntelogs. Conclusions: Access to the <em>C. americana</em> genome provides a roadmap for rapid discovery of genes encoding plant-derived agrichemicals and a key resource to understand the evolution of chemical diversity in Lamiaceae. </p> <p> </p>
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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.