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1,721 results for “network data”
Data from: Resilient networks of ant-plant mutualists in Amazonian forest fragments
BACKGROUND: The organization of networks of interacting species, such as plants and animals engaged in mutualisms, strongly influences the ecology and evolution of partner communities. Habitat fragmentation is a globally pervasive form of spatial heterogeneity that could profoundly impact the structure of mutualist networks. This is particularly true for biodiversity-rich tropical ecosystems, where the majority of plant species depend on mutualisms with animals and it is thought that changes in the structure of mutualist networks could lead to cascades of extinctions. METHODOLOGY/PRINCIPAL FINDINGS: We evaluated effects of fragmentation on mutualistic networks by calculating metrics of network structure for ant-plant networks in continuous Amazonian forests with those in forest fragments. We hypothesized that networks in fragments would have fewer species and higher connectance, but equal nestedness and resilience compared to forest networks. Only one of the nine metrics we compared differed between continuous forest and forest fragments, indicating that networks were resistant to the biotic and abiotic changes that accompany fragmentation. This is partially the result of the loss of only specialist species with one connection that were lost in forest fragments. CONCLUSIONS/SIGNIFICANCE: We found that the networks of ant-plant mutualists in twenty-five year old fragments are similar to those in continuous forest, suggesting these interactions are resistant to the detrimental changes associated with habitat fragmentation, at least in landscapes that are a mosaic of fragments, regenerating forests, and pastures. However, ant-plant mutualistic networks may have several properties that may promote their persistence in fragmented landscapes. Proactive identification of key mutualist partners may be necessary to focus conservation efforts on the interactions that insure the integrity of network structure and the ecosystems services networks provide.
Data from: Benefits and challenges of scaling up expansion of marine protected area networks in the Verde Island Passage, Central Philippines
Locally-established marine protected areas (MPAs) have been proven to achieve local-scale fisheries and conservation objectives. However, since many of these MPAs were not designed to form ecologically-connected networks, their contributions to broader-scale goals such as complementarity and connectivity can be limited. In contrast, integrated networks of MPAs designed with systematic conservation planning are assumed to be more effective—ecologically, socially, and economically—than collections of locally-established MPAs. There is, however, little empirical evidence that clearly demonstrates the supposed advantages of systematic MPA networks. A key reason is the poor record of implementation of systematic plans attributable to lack of local buy-in. An intermediate scenario for the expansion of MPAs is scaling up of local decisions, whereby locally-driven MPA initiatives are coordinated through collaborative partnerships among local governments and their communities. Coordination has the potential to extend the benefits of individual MPAs and perhaps to approach the potential benefits offered by systematic MPA networks. We evaluated the benefits of scaling up local MPAs to form networks by simulating seven expansion scenarios for MPAs in the Verde Island Passage, central Philippines. The scenarios were: uncoordinated community-based establishment of MPAs; two scenarios reflecting different levels of coordinated MPA expansion through collaborative partnerships; and four scenarios guided by systematic conservation planning with different contexts for governance. For each scenario, we measured benefits through time in terms of achievement of objectives for representation of marine habitats. We found that: in any governance context, systematic networks were more efficient than non-systematic ones; systematic networks were more efficient in broader governance contexts; and, contrary to expectations but with caveats, the uncoordinated scenario was slightly more efficient than the coordinated scenarios. Overall, however, coordinated MPA networks have the potential to be more efficient than the uncoordinated ones, especially when coordinated planning uses systematic methods.
Data from: The importance of delineating networks by activity type in bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida
Network analysis has proved to be a valuable tool for studying the behavioural patterns of complex social animals. Often such studies either do not distinguish between different behavioural states of the organisms or simply focus attention on a single behavioural state to the exclusion of all others. In either of these approaches it is impossible to ascertain how the behavioural patterns of individuals depend on the type of activity they are engaged in. Here we report on a network-based analysis of the behavioural associations in a population of bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida. We consider three distinct behavioural states—socializing, travelling and foraging—and analyse the association networks corresponding to each activity. Moreover, in constructing the different activity networks we do not simply record a spatial association between two individuals as being either present or absent, but rather quantify the degree of any association, thus allowing us to construct weighted networks describing each activity. The results of these weighted activity networks indicate that networks can reveal detailed patterns of bottlenose dolphins at the population level; dolphins socialize in large groups with preferential associations; travel in small groups with preferential associates; and spread out to forage in very small, weakly connected groups. There is some overlap in the socialize and travel networks but little overlap between the forage and other networks. This indicates that the social bonds maintained in other activities are less important as they forage on dispersed, solitary prey. The overall network, not sorted by activity, does not accurately represent any of these patterns.
Data from: Manifold influences of phylogenetic structure on a plant-herbivore network
Ecologists are increasingly aware of the interplay between evolutionary history and ecological processes in shaping current species interaction patterns. The inclusion of phylogenetic relationships in studies of species interaction networks has shown that closely related species commonly interact with sets of similar species. Notably, the degree of phylogenetic conservatism in antagonistic ecological interactions is frequently stronger among species at lower trophic levels than among those at higher trophic levels. One hypothesis that accounts for this asymmetry is that competition among consumer species promotes resource partitioning and offsets the maintenance of dietary similarity by phylogenetic inertia. Here, we used a regional plant-herbivore network comprised of Asteraceae species and flower-head endophagous insects to evaluate how the strength of phylogenetic conservatism in species interactions differs between the two trophic levels. We also addressed whether the asymmetry in the strength of the phylogenetic signal between plants and animals depends on the overall degree of relatedness among the herbivores. We show that, beyond the previously reported compositional similarity, closely related species also share a greater proportion of counterpart phylogenetic history, both for resource and consumer species. Comparison of the patterns found in the entire network with those found in subnetworks composed of more phylogenetically restricted groups of herbivores provides evidence that resource partitioning occurs mostly at deeper phylogenetic levels, so that a positive phylogenetic signal in antagonist similarity is detectable even between closely related consumers in monophyletic subnetworks. The asymmetry in signal strength between trophic levels is most apparent in the way network modules reflect resource phylogeny, both for the entire network and for subnetworks. Taken together, these results suggest that evolutionary processes, such as phylogenetic conservatism and independent colonization history of the insect groups may be the main forces generating the phylogenetic structure observed in this particular plant–herbivore network system.
Data from: Geographical variation in mutualistic networks: similarity, turnover and partner fidelity
Although species and their interactions in unison represent biodiversity and all the ecological and evolutionary processes associated with life, biotic interactions have, contrary to species, rarely been integrated into the concepts of spatial β-diversity. Here, we examine β-diversity of ecological networks by using pollination networks sampled across the Canary Islands. We show that adjacent and distant communities are more and less similar, respectively, in their composition of plants, pollinators and interactions than expected from random distributions. We further show that replacement of species is the major driver of interaction turnover and that this contribution increases with distance. Finally, we quantify that species-specific partner compositions (here called partner fidelity) deviate from random partner use, but vary as a result of ecological and geographical variables. In particular, breakdown of partner fidelity was facilitated by increasing geographical distance, changing abundances and changing linkage levels, but was not related to the geographical distribution of the species. This highlights the importance of space when comparing communities of interacting species and may stimulate a rethinking of the spatial interpretation of interaction networks. Moreover, geographical interaction dynamics and its causes are important in our efforts to anticipate effects of large-scale changes, such as anthropogenic disturbances.
Data from: Identification of migratory bird flyways in North America using community detection on biological networks
Migratory behavior of waterfowl populations in North America has traditionally been broadly characterized by four north-south flyways, and these flyways have been central to the management of waterfowl populations for more than 80 years. However, previous flyway characterizations are not easily updated with current bird movement data and fail to provide assessments of the importance of specific geographical regions to the identification of flyways. Here, we developed a network model of migratory movement for four waterfowl species —mallard (Anas platyrhnchos), northern pintail (A. acuta), American green-winged teal (A. carolinensis), and Canada goose (Branta canadensis) — in North America using bird band and recovery data. We then identified migratory flyways using a community detection algorithm and characterize the importance of smaller geographic regions in identifying flyways using a novel metric, the consolidation factor. We identified four main flyways for mallards, northern pintails, and American green-winged teal with the flyway identification in Canada geese exhibiting higher complexity. For mallards, flyways were relatively consistent through time. However, consolidation factors revealed that for mallards and green-winged teal the presumptive Mississippi flyway was potentially a zone of high mixing between other flyways. Our results demonstrate that the network approach provides a robust method for flyway identification that is widely applicable given the relatively minimal data requirements and is easily updated with future movement data to reflect changes in flyway definitions and management goals.
Data from: NetView P: a network visualization tool to unravel complex population structure using genome-wide SNPs
Network-based approaches are emerging as valuable tools for the analysis of complex genetic structure in both wild and captive populations. NetView P combines data quality control with the construction of population networks based on mutual k-nearest-neighbours thresholds applied to genome-wide SNPs. The program is cross-platform compatible, open-source and efficiently operates on data ranging from hundreds to hundreds of thousands of SNPs through multiprocessing in Python. We used the pipeline for the analysis of pedigree data from simulated (n = 750, SNPs = 1279) and captive Silver-lipped Pearl Oysters (n = 415, SNPs = 1107), wild populations of the European Hake from the Atlantic and Mediterranean (n = 834, SNPs = 380) and Gray Wolves from North America (n = 239, SNPs = 86,103). The population networks effectively visualize large- and fine-scale genetic structure within and between populations, including family-level structure and relationships. NetView P comprises a network-based addition to other population analysis tools and provides user-friendly access to a complex network analysis pipeline through implementation in Python.
Data from: Social networks predict gut microbiome composition in wild baboons
Social relationships have profound effects on health in humans and other primates, but the mechanisms that explain this relationship are not well understood. Using shotgun metagenomic data from wild baboons, we found that social group membership and social network relationships predicted both the taxonomic structure of the gut microbiome and the structure of genes encoded by gut microbial species. Rates of interaction directly explained variation in the gut microbiome, even after controlling for diet, kinship, and shared environments. They therefore strongly implicate direct physical contact among social partners in the transmission of gut microbial species. We identified 51 socially structured taxa, which were significantly enriched for anaerobic and non-spore-forming lifestyles. Our results argue that social interactions are an important determinant of gut microbiome composition in natural animal populations—a relationship with important ramifications for understanding how social relationships influence health, as well as the evolution of group living.
Data from: Network reorganization and breakdown of an ant–plant protection mutualism with elevation
Both the abiotic environment and the composition of animal and plant communities change with elevation. For mutualistic species, these changes are expected to result in altered partner availability, and shifts in context-dependent benefits for partners. To test these predictions, we assessed the network structure of terrestrial ant-plant mutualists and how the benefits to plants of ant inhabitation changed with elevation in tropical forest in Papua New Guinea. At higher elevations, ant-plants were rarer, species richness of both ants and plants decreased, and the average ant or plant species interacted with fewer partners. However, networks became increasingly connected and less specialized, more than could be accounted for by reductions in ant-plant abundance. On the most common ant-plant, ants recruited less and spent less time attacking a surrogate herbivore at higher elevations, and herbivory damage increased. These changes were driven by turnover of ant species rather than by within-species shifts in protective behaviour. We speculate that reduced partner availability at higher elevations results in less specialized networks, while lower temperatures mean that even for ant-inhabited plants, benefits are reduced. Under increased abiotic stress, mutualistic networks can break down, owing to a combination of lower population sizes, and a reduction in context-dependent mutualistic benefits.
Data from: Large frugivores matter: insights from network and seed dispersal effectiveness approaches
1.While large avian frugivores are known to be key dispersers for large‐seeded tree species, their role in community‐wide plant‐disperser networks is still poorly known. Large avian frugivores are also among the most threatened due to anthropogenic impacts. 2.We evaluated the role of large avian frugivores in a plant‐disperser community by a) determining whether the plant‐disperser community was modular, with a distinct community of large frugivores (thereby highlighting their importance), b) determining relative qualitative and quantitative roles played by large‐bodied frugivores vis‐à‐vis other frugivores and c) determining impacts of large‐bodied frugivore loss on the plant‐disperser community. 3.The study was carried at a tropical forest site in north‐east India which is part of the Eastern Himalaya Biodiversity Hotspot. We collected tree watch data (2055 h) from 46 tree species, which represented 85% of tree species that are predominantly bird‐dispersed in the area. 4.We found that the plant‐disperser community was modular, with a distinct module of large‐seeded tree species and large frugivores. Intermediate‐sized frugivores such as barbets and bulbuls were the most connected, while large‐sized frugivores, such as hornbills and imperial‐pigeons were moderately well‐connected. Qualitative and quantitative roles played by different dispersers varied across the gradient of frugivore body size. Hornbills, the largest avian frugivores, consumed a significantly greater number of fruits and swallowed larger proportions of fruits compared to other avian groups. In comparison to similar‐sized frugivores, imperial‐pigeons fed on larger‐sized fruits, highlighting their importance for dispersal of large‐seeded plants. Under simulated extinction scenarios, larger extinction cascades weren't necessarily caused by larger frugivores, however, extinctions of certain large‐bodied frugivores (hornbills, imperial‐pigeons) caused extinction cascades. 5.Integrating information from networks and seed dispersal effectiveness approaches enabled a better understanding of large frugivore role in a plant‐disperser community. While large‐bodied frugivores may not be playing a central role in plant‐disperser communities, they are crucial as seed dispersal service providers for large‐seeded plants. In conjunction with the reported local extinctions of large frugivores like hornbills from the south Asian region, this study's findings highlight the irreplaceable quantitative and qualitative impacts that tropical plant communities are likely to experience in the future.
Data from: Ditch network sustains functional connectivity and influences patterns of gene flow in an intensive agricultural landscape
In intensive agricultural landscapes, plant species previously relying on semi-natural habitats may persist as metapopulations within landscape linear elements. Maintenance of populations' connectivity through pollen and seed dispersal is a key factor in species persistence in the face of substantial habitat loss. The goals of this study were to investigate the potential corridor role of ditches and to identify the landscape components that significantly impact patterns of gene flow among remnant populations. Using microsatellite loci, we explored the spatial genetic structure of two hydrochorous wetland plants exhibiting contrasting local abundance and different habitat requirements: the rare and regionally protected Oenanthe aquatica and the more commonly distributed Lycopus europaeus, in an 83 km2 agricultural lowland located in northern France. Both species exhibited a significant spatial genetic structure, along with substantial levels of genetic differentiation, especially for L. europaeus, which also expressed high levels of inbreeding. Isolation-by-distance analysis revealed enhanced gene flow along ditches, indicating their key role in effective seed and pollen dispersal. Our data also suggested that the configuration of the ditch network and the landscape elements significantly affected population genetic structure, with (i) species-specific scale effects on the genetic neighborhood and (ii) detrimental impact of human ditch management on genetic diversity, especially for O. aquatica. Altogether, these findings highlighted the key role of ditches in the maintenance of plant biodiversity in intensive agricultural landscapes with few remnant wetland habitats.
Data from: Experimental evidence for fundamental, and not realised, niche partitioning in a plant-herbivore community interaction network
Patterns of niche partitioning can result from local ecological interactions (e.g. interspecific competition) occurring within a contemporary time frame (realised niche partitioning). Alternatively they may represent the end-product of historical processes acting over long time frames (fundamental niche partitioning). Niche partitioning is often detected by analysing patterns of resource use within communities, but experiments are rarely conducted to test whether patterns of non-overlapping resource use reflect realised or fundamental niche partitioning. We studied a community of restio leafhoppers from the genus Cephalelus, and their host plants, the Restionaceae (restios). We used network and experimental approaches to determine whether network modularity (a measure of niche partitioning within local communities) reflects fundamental or realised niche partitioning. Using a weighted modularity index for two party networks (e.g. insect - plant) we determined whether the network of this community is modular (i.e. consists of groups of species interacting strongly, with weak interactions between groups). We also aimed to identify specific Cephalelus - restio modules (groups). Using knowledge of module membership to design experiments, we tested whether Cephalelus species from two different modules, C. uncinatus and C. pickeri, prefer and perform better on restios from their own modules versus restios from other modules. These experiments were performed under controlled conditions, eliminating the influences of competition and predation on host choices. The Cephalelus – restio community was modular, implying niche partitioning. Cephalelus also preferred and performed better on restios from their own modules in the absence of local contemporary factors. Most niche partitioning in the investigated Cephalelus community, is not caused by local interactions, and thus host use patterns represent fundamental niches. Our findings highlight the importance of understanding local community structure in the light of processes extrinsic to the local community context.
Data from: Systematic site selection for multispecies monitoring networks
The importance of monitoring biodiversity to detect and understand changes throughout time and to inform management is increasingly recognized. Monitoring schemes should be globally unified, spatially integrated across scales, long term, and cost-efficient. We propose a framework to design optimized multispecies-targeted monitoring networks over large areas. The method builds upon previous developments on systematic conservation planning in terms of optimizing resource allocation in space, and comprises seven steps: (a) determine which questions will be addressed, (b) define species to be monitored, (c) compile occurrence data for all defined species, (d) predict the overall distribution of each species, (e) collect relevant environmental data and identify homogeneous strata, (f) set targets for the minimum number of monitoring sites per species and/or stratum and (g) identify optimal monitoring sites. We tested whether the monitoring networks designed with our framework have increased performance when compared to networks obtained with simple-random or stratified-random sampling by using a set of different indicators. To that end, we designed monitoring networks using optimized and non-optimized sampling schemes, applied to a case study in Portugal, where the goal was to design a monitoring network for amphibians and reptiles, to complement the one currently established in Spain. Results allowed us to conclude that monitoring networks designed with our method tend to outperform the non-optimized ones, in terms of higher species diversity (i.e. higher number of species and equity across monitoring sites), higher representation of environmental strata, and particularly higher coverage of rare species, with less survey effort. Synthesis and applications. We developed a framework to allocate monitoring sites for multiple species at broad scales using predictive models and optimization algorithms currently applied in systematic conservation planning. This framework presents field survey cost-efficiency advantages when compared to other standard sampling designs and can significantly contribute to improving the design of monitoring schemes. Thus, we recommend its application to design new multispecies monitoring networks or to extend existing ones.
Data from: Machine learning-based differential network analysis: a study of stress-responsive transcriptomes in Arabidopsis thaliana
Machine learning (ML) is an intelligent data mining technique that builds a prediction model based on the learning of prior knowledge to recognize patterns in large-scale data sets. We present an ML-based methodology for transcriptome analysis via comparison of gene coexpression networks, implemented as an R package called machine learning–based differential network analysis (mlDNA) and apply this method to reanalyze a set of abiotic stress expression data in Arabidopsis thaliana. The mlDNA first used a ML-based filtering process to remove nonexpressed, constitutively expressed, or non-stress-responsive "noninformative" genes prior to network construction, through learning the patterns of 32 expression characteristics of known stress-related genes. The retained "informative" genes were subsequently analyzed by ML-based network comparison to predict candidate stress-related genes showing expression and network differences between control and stress networks, based on 33 network topological characteristics. Comparative evaluation of the network-centric and gene-centric analytic methods showed that mlDNA substantially outperformed traditional statistical testing–based differential expression analysis at identifying stress-related genes, with markedly improved prediction accuracy. To experimentally validate the mlDNA predictions, we selected 89 candidates out of the 1784 predicted salt stress–related genes with available SALK T-DNA mutagenesis lines for phenotypic screening and identified two previously unreported genes, mutants of which showed salt-sensitive phenotypes.
Data from: The contribution of rare species to community phylogenetic diversity across a global network of forest plots
Niche differentiation has been proposed as an explanation for rarity in species assemblages. Testing this hypothesis requires quantifying the ecological similarity of species. This similarity can potentially be estimated by using phylogenetic relatedness. In this study, we predicted that if niche differentiation does explain the co-occurrence of rare and common species, then rare species should contribute greatly to the overall community phylogenetic diversity (PD), abundance will have phylogenetic signal and that common and rare species will be phylogenetically dissimilar. We tested these predictions by developing a novel method that integrates species rank abundance distributions with phylogenetic trees and trend analyses to examine the relative contribution of individual species to the overall community PD. We then supplement this approach with analyses of phylogenetic signal in abundances and measures of phylogenetic similarity within and between rare and common species groups. We applied this analytical approach to 15 long-term temperate and tropical forest dynamics plots from around the world. We show that the niche differentiation hypothesis is supported in six forests but is rejected in nine forests, and that the three metrics utilized in this study each provide unique but corroborating information regarding the phylogenetic distribution of rarity in communities.
Data from: Integrating plant species contribution to mycorrhizal and seed dispersal mutualistic networks
Mutualistic interactions like those established between plants and mycorrhizal fungi or seed dispersers are key drivers of plant population dynamics and ecosystem functioning, however, these interactions have rarely been explored together. We assembled a tripartite fungi-plant-disperser network in the Gorongosa National Park - Mozambique, to test 1) if the diversity and importance of plant mutualists above- and belowground are correlated, and 2) whether biotically and abiotically dispersed plants are associated with similar or distinct arbuscular mycorrhizal fungi (AMF) communities. We quantified seed dispersal by animals during one year and characterized the community of 26 common plant species. Sixteen plant species were dispersed by 15 animals and colonized by 48 AMF virtual taxa (VT), while the remaining ten plant species were not dispersed by animals and associated with 34 AMF VT. We found no evidence for a correlation between the number of plant partners above- and belowground or on plant specialization on both types of partners. We also found no evidence for differentiation of AMF communities between biotically and abiotically dispersed plants. Altogether, these results suggest that the establishment of plant interactions with seed dispersers and mycorrhizal fungi are largely independent and that both biotically and abiotically dispersed plants seem to associate with similar communities of AM fungi.
Data from: Predicting forest insect flight activity: a Bayesian network approach
Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model's predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways.
Data from: Influence of the honeybee and trait similarity on the effect of a non-native plant on pollination and network rewiring
Introduced entomophilous non-native plants usually become well integrated into the diet of generalist pollinators. This integration can affect the entire recipient plant–pollinator network. Effects vary from facilitative to competitive, and understanding the factors that govern such variability is one of the fundamental goals in invasion ecology. Species traits determine the linking patterns between plant and pollinator species. Therefore, trait similarity among plants or among pollinators might modulate how they affect each other. We conducted a flower removal experiment to investigate the effects of the non-native entomophilous legume Hedysarum coronarium on the pollination patterns of a Mediterranean shrubland plant–pollinator network. Specifically, we explored whether effects were influenced by similarity with the resident plant species in flower morphology (papilionate vs. non-papilionate), and whether effects on the pollinator community were influenced by similarity in functional group with its main visitor species (bees vs. non-bees). In addition, we explored whether Hedysarum had an effect on the identity of interactions. For this purpose, we calculated the interaction rewiring, that is the number of plant–pollinator interactions that were gained or lost after invasion. Hedysarum was well integrated into the diet of 15 generalist pollinators having the honeybee as its main visitor species. Such integration did not affect visitation rates, normalized degree (i.e. proportion of pollinators they are visited by) nor niche overlap (i.e. proportion of plant species they share pollinators with) of plants, irrespective of their flower morphology. Only the proportion of honeybee visits to resident plants decreased with invasion. On the other hand, Hedysarum reduced visitation rates and niche overlap of pollinators, mainly those of bee species. Finally, we observed that changes in the foraging behaviour of the honeybee were positively associated with the interaction rewiring involving the rest (92 taxa) of pollinators. In conclusion, pollinators show a plastic use of floral resources, responding to the presence of non-native plants. When the non-native attracts highly competitive pollinators such as the honeybee, plasticity is especially significant in pollinators that are functionally close to that competitive pollinator. The result is an interaction rewiring, probably due to pollinators avoiding competition with the honeybee. Though this plasticity might not quantitatively affect the pollination of plants, consequences on their reproduction and the functioning of the network can derive from the interaction rewiring.
Data from: The effect of excluding juveniles on apparent adult olive baboons (Papio anubis) social networks
In recent years there has been much interest in investigating the social structure of group living animals using social network analysis. Many studies so far have focused on the social networks of adults, often excluding younger, immature group members. This potentially may lead to a biased view of group social structure as multiple recent studies have shown that younger group members can significantly contribute to group structure. As proof of the concept, we address this issue by investigating social network structure with and without juveniles in wild olive baboons (Papio anubis) at Gashaka Gumti National Park, Nigeria. Two social networks including all independently moving individuals (i.e., excluding dependent juveniles) were created based on aggressive and grooming behaviour. We used knockout simulations based on the random removal of individuals from the network in order to investigate to what extent the exclusion of juveniles affects the resulting network structure and our interpretation of age-sex specific social roles. We found that juvenile social patterns differed from those of adults and that the exclusion of juveniles from the network significantly altered the resulting overall network structure. Moreover, the removal of juveniles from the network affected individuals in specific age-sex classes differently: for example, including juveniles in the grooming network increased network centrality of adult females while decreasing centrality of adult males. These results suggest that excluding juveniles from the analysis may not only result in a distorted picture of the overall social structure but also may mask some of the social roles of individuals belonging to different age-sex classes.
Data from: Disruption of the ascending arousal network in acute traumatic disorders of consciousness
Objective: To determine whether ascending arousal network (AAN) connectivity is reduced in patients presenting with traumatic coma. Methods: We performed high angular resolution diffusion imaging (HARDI) in 16 patients with acute severe traumatic brain injury who were comatose on admission and in 16 matched controls. We used probabilistic tractography to measure the connectivity probability (CP) of AAN axonal pathways linking the brainstem tegmentum to the hypothalamus, thalamus and basal forebrain. To assess the spatial specificity of CP differences between patients and controls, we also measured CP within four subcortical pathways outside the AAN. Results: Compared to controls, patients showed a reduction in AAN pathways connecting the brainstem tegmentum to a region of interest encompassing the hypothalamus, thalamus, and basal forebrain. Examining each pathway individually, brainstem-hypothalamus and brainstem-thalamus CPs, but not brainstem-forebrain CP, were significantly reduced in patients. Only one subcortical pathway outside the AAN showed reduced CP in patients. Conclusions: We provide initial evidence for the reduced integrity of axonal pathways linking the brainstem tegmentum to the hypothalamus and thalamus in patients presenting with traumatic coma. Our findings support current conceptual models of coma as being caused by subcortical AAN injury. AAN connectivity mapping provides an opportunity to advance the study of human coma and consciousness.
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.