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9,152 results for “Networking”
Data from: Genetics of gene expression responses to temperature stress in a sea urchin gene network
Stress responses play an important role in shaping species distributions and robustness to climate change. We investigated how stress responses alter the contribution of additive genetic variation to gene expression during development of the purple sea urchin, Strongylocentrotus purpuratus, under increased temperatures that model realistic climate change scenarios. We first measured gene expression responses in the embryos by RNA-seq to characterize molecular signatures of mild, chronic temperature stress. We found that an increase from 12 °C to 18 °C caused widespread alterations in gene expression including in genes involved in protein folding, RNA processing, and development. To understand the quantitative genetic architecture of this response, we then focused on a well-characterized gene network involved in endomesoderm and ectoderm specification. Using a breeding design with wild-caught individuals, we measured genetic and gene-environment interaction effects on 72 genes within this network. We found genetic or maternal effects in 33 of these genes, and that the genetic effects were correlated in the network. 14 network genes also responded to higher temperatures, but we found no significant genotype-environment interactions in any of the genes. This absence may be due to an effective buffering of the temperature perturbations within the network. In support of this hypothesis, perturbations to regulatory genes did not affect the expression of the genes that they regulate. Together, these results provide novel insights into the relationship between environmental change and developmental evolution and suggest that climate change may not expose large amounts of cryptic genetic variation to selection in this species.
Data from: Approaches to integrating genetic data into ecological networks
As molecular tools for assessing trophic interactions become common, research is increasingly focused on the construction of interaction networks. Here we demonstrate three key methods for incorporating DNA data into network ecology and discuss analytical considerations using a model consisting of plants, insects, bats and their parasites from the Costa Rican dry forest. The simplest method involves the use of Sanger sequencing to acquire long sequences to validate or refine field identifications, for example of bats and their parasites, where one specimen yields one sequence and one identification. This method can be fully quantified and resolved and these data resemble traditional ecological networks. For more complex taxonomic identifications, we target multiple DNA loci e.g. from a seed or fruit pulp sample in faeces. These networks are also well resolved but gene targets vary in resolution and quantification is difficult. Finally for mixed templates such as faecal contents of insectivorous bats we use DNA metabarcoding targeting two sequence lengths (157bp, 407bp) of one gene region and a MOTU, BLAST and BIN association approach to resolve nodes. This network type is complex to generate and analyse and we discuss the implications of this type of resolution on network analysis. Using these data we construct the first molecular-based network of networks containing 3304 interactions between 762 nodes of 8 trophic functions and involving parasitic, mutualistic, and predatory interactions. We provide a comparison of the relative strengths and weaknesses of these data types in network ecology.
Data from: Network-scale effects of invasive species on spatially-structured amphibian populations
<p>Understanding the factors affecting the dynamics of spatially-structured populations (SSP) is a central topic of conservation and landscape ecology. Invasive alien species are increasingly important drivers of the dynamics of native species. However, the impacts of invasives are often assessed at the patch scale, while their effects on SSP dynamics are rarely considered. We used long-term abundance data to test whether the impact of invasive crayfish on subpopulations can also affect the whole SSP dynamics, through their influence on source populations. From 2010 to 2018, we surveyed a network of 58 ponds and recorded the abundance of Italian agile frog clutches, the occurrence of an invasive crayfish, and environmental features. Using Bayesian hierarchical models, we assessed relationships between frog abundance in ponds and a) environmental features; b) connectivity within the SSP; c) occurrence of invasive species at both the patch- and the SSP-levels. If spatial relationships between ponds were overlooked, we did not detect effects of crayfish presence on frog abundance or trends. When we jointly considered habitat, subpopulation, and SSP features, processes acting at all these levels affected frog abundance. At the subpopulation scale, frog abundance in a year was related to habitat features, but was unrelated to crayfish occurrence at that site during the previous year. However, when we considered the SSP level, we found a strong negative relationship between frog abundance in a given site and crayfish frequency in surrounding wetlands during the previous year. Hence, SSP-level analyses can identify effects that would remain unnoticed when focussing on single patches. Invasive species can affect population dynamics even in not invaded patches, through the degradation of subpopulation networks. Patch-scale assessments of the impact of invasive species can thus be insufficient: predicting the long-term interplay between invasive and native populations requires landscape-level approaches accounting for the complexity of spatial interactions.</p>
Data from: The robustness and restoration of a network of ecological networks
Understanding species' interactions and the robustness of interaction networks to species loss is essential to understand the effects of species' declines and extinctions. In most studies, different types of networks (such as food webs, parasitoid webs, seed dispersal networks, and pollination networks) have been studied separately. We sampled such multiple networks simultaneously in an agroecosystem. We show that the networks varied in their robustness; networks including pollinators appeared to be particularly fragile. We show that, overall, networks did not strongly covary in their robustness, which suggests that ecological restoration (for example, through agri-environment schemes) benefitting one functional group will not inevitably benefit others. Some individual plant species were disproportionately well linked to many other species. This type of information can be used in restoration management, because it identifies the plant taxa that can potentially lead to disproportionate gains in biodiversity.
Data from: Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks
The network architecture of streams and rivers constrains evolutionary, demographic, and ecological processes of freshwater organisms. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examined genetic structure and gene flow in the facultatively paedomorphic Idaho giant salamander, Dicamptodon aterrimus, in stream networks of Idaho and Montana, USA. We used microsatellite data to test population structure models by (1) examining hierarchical partitioning of genetic variation in stream networks and (2) testing for genetic isolation by distance along stream corridors versus overland pathways. Replicated sampling of streams within catchments within three river basins revealed that hierarchical scale had strong effects on genetic structure and gene flow. AMOVA identified significant structure at all hierarchical scales (among streams, among catchments, among basins), but divergence among catchments had the greatest structural influence. Isolation by distance was detected within catchments, and in-stream distance was a strong predictor of genetic divergence. Patterns of genetic divergence suggest that differentiation among streams within catchments was driven by limited migration, consistent with a stream hierarchy model of population structure. However, there was no evidence of migration among catchments within basins, or among basins, indicating that gene flow only counters the effects of genetic drift at smaller scales (within rather than among catchments). These results show the strong influence of stream networks on population structure and genetic divergence of a salamander, with contrasting effects at different hierarchical scales.
Network analysis reveals underlying syntactic features in a vocally learnt mammalian display, humpback whale song
<p>Vocal communication systems have a set of rules that govern the arrangement of acoustic signals, broadly defined as 'syntax'. However, there is a limited understanding of potentially shared or analogous rules across vocal displays in different taxa. Recent work on songbirds has investigated syntax using network-based modelling. This technique quantifies features such as connectivity (adjacent signals in a sequence) and recurring patterns. Here, we apply network-based modelling to the complex, hierarchically structured songs of humpback whales (Megaptera novaeangliae) from east Australia. Given the song's annual evolving pattern and the cultural conformity of males within a population, network modelling captured the patterns of multiple song types over 13 consecutive years. Song arrangements in each year displayed clear "small-world" network structure, characterised by clusters of highly connected sounds. Transitions between these connected sounds further suggested a combination of both structural stability and variability. Small-world network structure within humpback songs may facilitate the characteristic and persistent vocal learning observed. Similar small-world structures and transition patterns are found in several birdsong displays, indicating common syntactic patterns among vocal learning in multiple taxa. Understanding the syntactic rules governing vocal displays in multiple, independently evolving lineages may indicate what rules or structural features are important to the evolution of complex communication, including human language. </p>
Data from: Plant-mycorrhizal fungus co-occurrence network lacks substantial structure
The interactions between plants and arbuscular mycorrhizal fungi (AMF) maintain a crucial link between macroscopic organisms and the soil microbial world. These interactions are of extreme importance for the diversity of plant communities and ecosystem functioning. Despite this importance, only recently has the structure of plant–AMF interaction networks been studied. These recent studies, which used genetic data, suggest that these networks are highly structured, very similar to plant–animal mutualistic networks. However, the assembly process of plant–AMF communities is still largely unknown, and an important feature of plant–AMF interactions has not been incorporated: they occur at an extremely localized scale. Studying plant–AMF networks in a spatial context seems therefore a crucial step. This paper studies a plant–AMF spatial co-occurrence network using novel methodology based on information theory and a unique set of spatially explicit species-level data. We apply three null models of which only one accounts for spatial effects. We find that the data show substantial departures from null expectations for the two non-spatial null models. However, for the null model considering spatial effects, there are few significant co-occurrences compared with the other two null models. Thus, plant–AMF spatial co-occurrences seem to be mostly explained by stochasticity, with a small role for other factors related to plant–AMF specialization. Furthermore, we find that the network is not significantly nested or modular. We conclude that this plant–AMF spatial co-occurrence network lacks substantial structure and, therefore, plants and AMF species do not track each other over space. Thus, random encounters seem more important in the first step of the assembly of plant–AMF communities.
Data from: Rate of inter-sex interactions affects injury likelihood in Tasmanian devil contact networks
Identifying the types of contacts that result in disease transmission is important for accurately modelling and predicting transmission dynamics and disease spread in wild populations. We investigated contacts within a population of adult Tasmanian devils (Sarcophilus harrisii) over a six-month period and tested whether individual-level contact patterns were correlated with accumulation of bite wounds. Bite wounds are important in the spread of devil facial tumour disease (DFTD), a clonal cancer cell line transmitted through direct inoculation of tumour cells when susceptible and infected individuals bite each other. We used multi-model inference and network autocorrelation models to investigate the effects of individual-level contact patterns, identities of interacting partners, and position within the social network on the propensity to be involved in bite-inducing contacts. We found that males were more likely to receive potentially disease-transmitting bite wounds than females, particularly during the mating season when males spend extended periods mate-guarding females. The number of bite wounds individuals received during the mating season was unrelated to any of the network metrics examined. Our approach illustrates the necessity for understanding which contact types spread disease in different systems to assist the management of this and other infectious wildlife diseases.
Data from: The contribution of land tenure diversity to the spatial resilience of protected area networks
1. The relationship between diversity and resilience is relatively well-established for ecological systems, but remains much less explored for socioeconomic systems. Institutional diversity may have particular relevance for protected areas, whose managerial responses to environmental change depend on their legal basis, ability to make and enforce rules, and socio-political acceptance and endorsement. 2. Protected area expansion strategies are increasingly turning to private land conservation to increase the configuration and connectivity of national protected area networks. Yet we know little about the relative role of privately-owned protected areas in protecting threatened and poorly protected (under-represented) habitats, and in the overall connectivity of the national protected area network. 3. We present an empirical assessment of protected area tenure diversity across South Africa. 4. Privately-owned protected areas comprise 25.58% (2878422.26 ha) of the area of the total protected area estate. 5. Private nature reserves emerged as the dominant protected area type in under-represented and threatened habitats, protecting, on average, 32%, 38%, and 41%, respectively, of poorly protected, threatened and endangered vegetation classes. 6. Private nature reserves had the largest overall effect, compared to other protected area types, on connectivity within the national network. A spatially randomised comparison showed that privately-owned protected areas are over-dispersed and more strategically positioned to connect other types of protected areas than would be expected by chance from their extent and abundance. 7. Our results suggest that privately-owned protected areas enhance the resilience of the national protected area network, making it more extensive and better-connected, with greater levels of habitat redundancy. More generally, our analysis highlights the potentially valuable role of institutional diversity in building resilient habitat networks for biodiversity conservation.
Data from: Dynamic species co-occurrence networks require dynamic biodiversity surrogates
In conservation it is inevitable that surrogates be selected to represent the occurrence of hard–to–find species and find priority locations for management. However, species co–occurrence can vary over time. Here we demonstrate how temporal dynamics in species co–occurrence influence the ability of managers to choose the best surrogate species. We develop an efficient optimisation formulation that selects the optimal set of complementary surrogate species from any co–occurrence network. We apply it to two Australian datasets on successional bird responses to disturbances of revegetation and fire. We discover that a surprisingly small number of species are required to represent the majority of species co–occurrences at any one time. Because co–occurrence patterns are temporally dynamic, the optimal set of surrogates, and the number of surrogates required to achieve a desired surrogacy power, depend on sampling effort and the successional state of a system. Overlap in optimal sets of surrogates for representing 70% of co–occurring species ranges from zero to 57% depending on when the surrogacy decision is made. Surrogate sets representing early successional communities over–estimate the power of surrogacy decisions at later times. Our results show that in dynamic systems, optimal surrogates might be selected in different ways: (1) use short–term monitoring to choose a larger number of static less–informative surrogates; (2) use long–term monitoring to choose a smaller number of static high–power surrogates that may poorly represent early successional co–occurrence; (3) develop adaptive surrogate selection frameworks with high short–term and long–term surrogacy power that update surrogate sets and capture temporal dynamics in species co–occurrence. Our results suggest vigilance is needed when selecting surrogates for other co–occurring species in dynamic landscapes, as selected surrogates from one time may have reduced effectiveness at a different time. Ultimately, decisions that fail to acknowledge dynamic species co–occurrence will lead to uninformative or redundant surrogates.
Data from: A dedicated network for social interaction processing in the primate brain
Primate cognition requires interaction processing. Interactions can reveal otherwise hidden properties of intentional agents, such as thoughts and feelings, and of inanimate objects, such as mass and material. Where and how interaction analyses are implemented in the brain is unknown. Using whole-brain functional magnetic resonance imaging in macaque monkeys, we discovered a network centered in the medial and ventrolateral prefrontal cortex that is exclusively engaged in social interaction analysis. Exclusivity of specialization was found for no other function anywhere in the brain. Two additional networks, a parieto-premotor and a temporal one, exhibited both social and physical interaction preference, which, in the temporal lobe, mapped onto a fine-grain pattern of object, body, and face selectivity. Extent and location of a dedicated system for social interaction analysis suggest that this function is an evolutionary forerunner of human mind-reading capabilities.
Neural network weights for the xrv.baseline_models.chexpert.DenseNet model for torchxrayvision
<p>https://github.com/mlmed/torchxrayvision</p> <p>xrv.baseline_models.chexpert.DenseNet</p>
Data from: Does detection range matter for inferring social networks in a benthic shark using acoustic telemetry?
Accurately estimating contacts between animals can be critical in ecological studies such as examining social structure, predator–prey interactions or transmission of information and disease. While biotelemetry has been used successfully for such studies in terrestrial systems, it is still under development in the aquatic environment. Acoustic telemetry represents an attractive tool to investigate spatio-temporal behaviour of marine fish and has recently been suggested for monitoring underwater animal interactions. To evaluate the effectiveness of acoustic telemetry in recording interindividual contacts, we compared co-occurrence matrices deduced from three types of acoustic receivers varying in detection range in a benthic shark species. Our results demonstrate that (i) associations produced by acoustic receivers with a large detection range (i.e. Vemco VR2W) were significantly different from those produced by receivers with smaller ranges (i.e. Sonotronics miniSUR receivers and proximity loggers) and (ii) the position of individuals within their network, or centrality, also differed. These findings suggest that acoustic receivers with a large detection range may not be the best option to represent true social networks in the case of a benthic marine animal. While acoustic receivers are increasingly used by marine ecologists, we recommend users first evaluate the influence of detection range to depict accurate individual interactions before using these receivers for social or predator–prey studies. We also advocate for combining multiple receiver types depending on the ecological question being asked and the development of multi-sensor tags or testing of new automated proximity loggers, such as the Encounternet system, to improve the precision and accuracy of social and predator–prey interaction studies.
Data from: Speciation network in Laurasiatheria: retrophylogenomic signals
Rapid species radiation due to adaptive changes or occupation of new ecospaces challenges our understanding of ancestral speciation and the relationships of modern species. At the molecular level, rapid radiation with successive speciations over short time periods—too short to fix polymorphic alleles—is described as incomplete lineage sorting. Incomplete lineage sorting leads to random fixation of genetic markers and hence, random signals of relationships in phylogenetic reconstructions. The situation is further complicated when you consider that the genome is a mosaic of ancestral and modern incompletely sorted sequence blocks that leads to reconstructed affiliations to one or the other relative, depending on the fixation of their shared ancestral polymorphic alleles. The laurasiatherian relationships among Chiroptera, Perissodactyla, Cetartiodactyla, and Carnivora present a prime example for such enigmatic affiliations. We performed whole-genome screenings for phylogenetically diagnostic retrotransposon insertions involving the representatives bat (Chiroptera), horse (Perissodactyla), cow (Cetartiodactyla), and dog (Carnivora), and extracted among 162,000 preselected cases 102 virtually homoplasy-free, phylogenetically informative retroelements to draw a complete picture of the highly complex evolutionary relations within Laurasiatheria. All possible evolutionary scenarios received considerable retrotransposon support, leaving us with a network of affiliations. However, the Cetartiodactyla–Carnivora relationship as well as the basal position of Chiroptera and an ancestral laurasiatherian hybridization process did exhibit some very clear, distinct signals. The significant accordance of retrotransposon presence/absence patterns and flanking nucleotide changes suggest an important influence of mosaic genome structures in the reconstruction of species histories.
Asperge Cavity full 3D network
* Topo Data: https://ipvsmn.org/ * DEM: Jaxa ALOS World 3D * Imagery: MapBox Satellite Source: Objaverse 1.0 / Sketchfab
Reproducibility and robustness of graph measures of the Associative-Semantic Network
<p>Matfiles and matlab scripts used to study the reproducibility and robustness of graph measures of the Associative-Semantic Network.</p>
Irradiance monitoring network data
<p>The data.tar.gz archive contains data from an irradiance monitoring network in Tucson, Arizona for the period 2014-04-05 to 2014-06-30. It includes a sensor metadata csv, csv files for the measurements on each day, and csv files for the clearsky-profiles for each sensor on each day. This data was used to make short-term forecasts of solar irradiance.</p>
Irradiance monitoring network data and wind motion vectors
<p>The data.tar.gz archive contains data from an irradiance monitoring network in Tucson, Arizona for the period 2014-04-05 to 2014-06-30. It includes a sensor metadata csv, csv files for the measurements on each day, csv files for the clearsky-profiles for each sensor on each day, and a time-series of the expected wind motion vectors obtained from a numerical weather model. This data was used to make short-term forecasts of solar irradiance.</p>
Foraging Networks of the Leaf-Cutting Ant Atta bisphaerica
<p>This dataset describes the foraging network of four nests of the leaf-cutting ant Atta bisphaerica over an 8-month period covering the whole humid season and part of the dry season. All nests were in a pasture located in the southern part of the Brazilian state of Minas Gerais, near the municipality of Coronel Pacheco( 21° 39'S, 43° 21'W, altitude: 800m). The networks consist of underground tunnels connecting the nests to distant foraging holes from which one or several foraging trails depart to reach resource patches. The dataset gives the positions and status (active, inactive, close) of the foraging holes as well as the number, length and terminal position of each trail departing from these holes.</p>
Video Figure: Intelligent Agents and Networked Buttons Improve Free-Improvised Ensemble Music-Making on Touch-Screens
<p>This video figure is an overview of our study comparing two designs for network communications between touch-screen musical instruments played in free-improvised ensemble performances.</p> <p>The video shows an overview of the touch-screen app (PhaseRings) used in the study and each of the interface conditions.</p> <p>The abstract of the paper relating to this figure is as follows:</p> <p>We present the results of two controlled studies of free-improvised ensemble music-making on touch-screens. In our system, updates to an interface of harmonically-selected pitches are broadcast to every touch-screen in response to either a performer pressing a GUI button, or to interventions from an intelligent agent. In our first study, analysis of survey results and performance data indicated significant effects of the button on performer preference, but of the agent on performance length. In the second follow-up study, a mixed-initiative interface, where the presence of the button was interlaced with agent interventions, was developed to leverage both approaches. Comparison of this mixed-initiative interface with the always-on button-plus-agent condition of the first study demonstrated significant preferences for the former. The different approaches were found to shape the creative interactions that take place. Overall, this research offers evidence that an intelligent agent and a networked GUI both improve aspects of improvised ensemble music-making.</p>
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.