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9,152 results for “Networking”
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.
Data from: Landscape simplification shapes pathogen prevalence in plant-pollinator networks
Species interaction networks, which play an important role in determining pathogen transmission and spread in ecological communities, can shift in response to agricultural landscape simplification. However, we know surprisingly little about how landscape simplification-driven changes in network structure impact epidemiological patterns. Here, we combine mathematical modeling and data from eleven bipartite plant-pollinator networks observed along a landscape simplification gradient to elucidate how changes in network structure shape disease dynamics. Our empirical data show that landscape simplification reduces pathogen prevalence in bee communities via increased diet breadth of the dominant species. Furthermore, our empirical data and theoretical model indicate that increased connectance reduces the likelihood of a disease outbreak and decreases variance in prevalence among bee species in the community, resulting in a dilution effect. Because infectious diseases are implicated in pollinator declines worldwide, a better understanding of how land use change impacts species interactions is therefore critical for conserving pollinator health.
Data from: Plant life history stage and nurse age change the development of ecological networks in an arid ecosystem
Understanding how ecological networks are organised over the course of an organism's lifetime is crucial for predicting the dynamics of interacting populations and communities across temporal scales. However, most studies so far considered only one life history stage at a time, such as adult, when studying networks of interacting species. Therefore, knowledge about how multiple life history stages affect the development and stability of plant–plant association networks is lacking. We measured the understory adult plant community and the soil seed bank across a plant age gradient of the nurse shrub Retama sphaerocarpa in an arid ecosystem in Spain. Using a multilayer network approach, we built adult understory–nurse and seed bank–nurse networks and analysed how network nestedness, species' role, and species specificity varied between them and with nurse plant age. We found that seed bank and adult understory networks changed depending on nurse plant age in two different ways. With increasing nurse plant age, adult understory networks became significantly more nested than seed bank networks. The nested architecture of seed bank networks was therefore a poor predictor of adult understory network nestedness. The contribution and specificity of species to network nestedness increased with increasing nurse plant age more in the adult understory than in seed bank networks, despite high species turnover. Our data show that life history and ontogeny affect the development of plant–plant association networks. Niche construction and environmental filtering along nurse ontogeny seem pivotal mechanisms structuring adult understory networks while the assembly of seed bank networks seems rather stochastic. We highlight the importance of mature plant communities for maintaining rare species populations and supporting the stability of ecological communities through time.
Data from: High-resolution contact networks of free-ranging domestic dogs Canis familiaris and implications for transmission of infection
Contact patterns strongly influence the dynamics of disease transmission in both human and non-human animal populations. Domestic dogs Canis familiaris are a social species and are a reservoir for several zoonotic infections, yet few studies have empirically determined contact patterns within dog populations. Using high-resolution proximity logging technology, we characterised the contact networks of free-ranging domestic dogs from two settlements (n = 108 dogs, covering >80% of the population in each settlement) in rural Chad. We used these data to simulate the transmission of an infection comparable to rabies and investigated the effects of including observed contact heterogeneities on epidemic outcomes. We found that dog contact networks displayed considerable heterogeneity, particularly in the duration of contacts and that the network had communities that were highly correlated with household membership. Simulations using observed contact networks had smaller epidemic sizes than those that assumed random mixing, demonstrating the unsuitability of homogenous mixing models in predicting epidemic outcomes. When contact heterogeneities were included in simulations, the network position of the individual initially infected had an important effect on epidemic outcomes. The risk of an epidemic occurring was best predicted by the initially infected individual's ranked degree, while epidemic size was best predicted by the individual's ranked eigenvector centrality. For dogs in one settlement, we found that ranked eigenvector centrality was correlated with range size. Our results demonstrate that observed heterogeneities in contacts are important for the prediction of epidemiological outcomes in free-ranging domestic dogs. We show that individuals presenting a higher risk for disease transmission can be identified by their network position and provide evidence that observable traits hold potential for informing targeted disease management strategies.
Predicting barrier effects of transportation networks on Asian elephants: Implications for environmental impact assessment
<p>The rapid proliferation of transportation networks (TNs) is a threat to wide–ranged animals through habitat erosion, road–kill, and indirect socio–ecological interaction. In most cases, environmental impact assessments of TNs about animals are descriptive and targeted to direct impacts of the "linear features", while indirect and cumulative impacts are relatively neglected. Using spatially explicit data of elephant–caused damage during 2012–2015 in China, we quantified barrier effects of TN on Asian elephants and predicted the effects under a TN expansion scenario using maximum entropy algorithms. We found that TN acted as a strong barrier even for the elephants that have inhabited highly fragmented landscapes for years, with only 18% of the damage occurred on the crossed side of roads. Also, the TN expansion will reduce elephant habitats, exacerbating herd isolation and human–elephant conflict locally. Thus, we suggest that mitigation of the conflicts should be integrated into future environmental impact assessments.</p>
Data from: Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants
Correlations among plant traits often reflect important trade‐offs or allometric relationships in biological functions like carbon gain, support, water uptake, and reproduction that are associated with different plant organs. Whether trait correlations can be aggregated to "spectra" or "leading dimensions," whether these dimensions are consistent across plant organs, spatial scale, and growth forms are still open questions. To illustrate the current state of knowledge, we constructed a network of published trait correlations associated with the "leaf economics spectrum," "biomass allocation dimension," "seed dimension," and carbon and nitrogen concentrations. This literature‐based network was compared to a network based on a dataset of 23 traits from 2,530 individuals of 126 plant species from 381 plots in Northwest Europe. The observed network comprised more significant correlations than the literature‐based network. Network centrality measures showed that size traits such as the mass of leaf, stem, below‐ground, and reproductive tissues and plant height were the most central traits in the network, confirming the importance of allometric relationships in herbaceous plants. Stem mass and stem‐specific length were "hub" traits correlated with most traits. Environmental selection of hub traits may affect the whole phenotype. In contrast to the literature‐based network, SLA and leaf N were of minor importance. Based on cluster analysis and subsequent PCAs of the resulting trait clusters, we found a "size" module, a "seed" module, two modules representing C and N concentrations in plant organs, and a "partitioning" module representing organ mass fractions. A module representing the plant economics spectrum did not emerge. Synthesis. Although we found support for several trait dimensions, the observed trait network deviated significantly from current knowledge, suggesting that previous studies have overlooked trait coordination at the whole‐plant level. Furthermore, network analysis suggests that stem traits have a stronger regulatory role in herbaceous plants than leaf traits.
Data from: Interaction networks of macrofungi and mycophagous beetles reflect diurnal variation and the size and spatial arrangement of resources
Ecological networks are useful for characterizing interspecific associations and predicting the resilience of ecological communities. We evaluated how such networks vary with the size, spatial distribution, and timing of availability of resources, with a focus on beetle-macrofungal associations. We used 2 y of field experiments to construct ecological networks based on manipulated sporocarp baits (resources; Pleurotus ostreatus) and natural communities of beetles (consumers) in a temperate forest. Centrality and interaction strength increased with resource size, but were associated weakly with resource density and isolation, and not at all with position within patches. Whole-network connectance was greater in mornings (when beetle richness and abundance were high) than evenings. Interannual differences in networks were consistent with differences in beetle communities between years. The capacity of networks to vary temporally, spatially, and as a function of resource traits is examined in light of understanding beetle-macrofungal associations, which are important components of fungal ecology.
Data from: Invariant antagonistic network structure despite high spatial and temporal turnover of interactions
Recent work has suggested that emergent ecological network structure exhibits very little spatial or temporal variance despite changes in community composition. However, the changes in network interactions associated with turnover in community composition have seldom been assessed. Here we examine whether changes in ecological networks are best detected by standard emergent network metrics or by assessing internal network changes (i.e. interaction and composition turnover). To eliminate possible spatial or phylogenetic effects, that in large-scale studies may obscure mechanisms structuring networks and interactions, we sampled multiple antagonistic (plant-herbivore) networks for a single diverse plant family (the Restionaceae) in the hyperdiverse Cape Floristic Region. These are the first plant-herbivore networks constructed for this global biodiversity hotspot. We found invariant emergent network structure despite considerable changes in insect and plant composition across communities over time and space. In contrast, there was high interaction turnover between networks. Seasonally, this was driven by turnover in insect species and insect host switching. Spatially, this was driven by simultaneous turnover in plant and insect species, suggesting that many insects are host specific or that both groups exhibit parallel responses to environmental gradients. Spatial interaction turnover was also driven by turnover in plants, showing that many insects can utilise multiple (possibly closely related) hosts and this may create divergent selection gradients that promote insect speciation. Thus we show highly variable interaction fidelity, despite invariant emergent network structure. We suggest that evaluating internal network changes may be more effective at elucidating the processes structuring networks, and many fine-scale changes may be obscured when only calculating emergent network metrics.
Data from: Integrated genome-scale analysis identifies novel genes and networks underlying senescence in maize
Premature senescence in annual crops reduces yield while delayed senescence, termed stay-green, is known to impose both positive and negative impact on yield and nutrition quality. Despite the importance, scant information is available on the genetic architecture of senescence in maize (Zea mays L.) and other cereals. We combined a systematic characterization of natural diversity for senescence in maize and co-expression networks derived from transcriptome analysis of normally senescing and stay-green lines. Sixty-four candidate genes were identified by GWAS, and 14 of these are supported by additional evidence for involvement in senescence-related processes including proteolysis, sugar transport and signaling, and sink activity. Eight of the GWAS candidates, independently supported by a co-expression network underlying stay-green, include a trehalose-6-phosphate synthase, a NAC transcription factor, and two xylan biosynthetic enzymes. Source-sink communication and the activity of cell walls as a secondary sink emerge as key determinants of stay-green. Mutant analysis supports the role of a candidate encoding cysteine protease in stay-green in Arabidopsis (Arabidopsis thaliana), and analysis of natural alleles suggest a similar role in maize. This study provides a foundation for enhanced understanding and manipulation of senescence for increasing carbon yield, nutritional quality, and stress tolerance of maize and other cereals.
Data from: Inferring species networks from gene trees in high-polyploid North American and Hawaiian violets (Viola, Violaceae)
The phylogenies of allopolyploids take the shape of networks and cannot be adequately represented as bifurcating trees. Especially for high-polyploids (i.e., organisms with more than six sets of nuclear chromosomes), the signatures of gene homoeolog loss, deep coalescence and polyploidy may become confounded, with the result that gene trees may be congruent with more than one species network. Herein, we obtained the most parsimonious species network by objective comparison of competing scenarios involving polyploidization and homoeolog loss in a high-polyploid lineage of violets (Viola, Violaceae) mostly or entirely restricted to North America, Central America, or Hawaii. We amplified homoeologs of the low-copy nuclear gene GPI by single-molecule PCR and the chloroplast trnL-F region by conventional PCR for 51 species and subspecies. Topological incongruence among GPI homoeolog subclades, owing to deep coalescence and two instances of putative loss (or lack of detection) of homoeologs, were reconciled by applying the maximum tree topology for each subclade. The most parsimonious species network and the fossil-based calibration of the homoeolog tree favored monophyly of the high-polyploids, which has resulted from allodecaploidization 9–14 Ma ago, involving sympatric ancestors from the extant Viola sections Chamaemelanium (diploid), Plagiostigma (paleotetraploid), and Viola (paleotetraploid). While two of the high-polyploid lineages (Boreali-Americanae, Pedatae) remained decaploid, recurrent polyploidization with tetraploids of section Plagiostigma within the last 5 Ma has resulted in two 14-ploid lineages (Mexicanae, Nosphinium) and one 18-ploid lineage (Langsdorffianae). This implies a more complex phylogenetic and biogeographic origin of the Hawaiian violets (Nosphinium) than that previously inferred from rDNA data and illustrates the necessity of considering polyploidy in phylogenetic and biogeographic reconstruction.
Data from: Ecological divergence among colour morphs mediated by changes in spatial network structure associated with disturbance
1. Differences in individual behaviour affect social interactions and contribute to the spatial structuring of animal populations. However, disturbance should also affect spatial networks by altering habitat heterogeneity and resource availability. Variation in resource availability should perturb the frequency and nature of social and ecological interactions within a population by affecting the spatial distribution of individuals. 2. In disturbed habitats where resources are limiting, spatial relationships should reflect behavioural differences among individuals, with higher-quality resources controlled by dominant individuals. In contrast, all individuals may exploit preferred resources in resource-rich habitats. Environmental variation and population reorganisation may also result in variation in morphological, behavioural, and ecological traits, which ultimately affect fitness. 3. We addressed these considerations for male tree lizards (Urosaurus ornatus) at three sites that differ in levels of disturbance. The habitats at these localities differed in the availability of live trees, the preferred microhabitat of U. ornatus. In addition, male U. ornatus exhibit a polymorphism in dewlap colour linked with differences in aggression, which should influence their position in a network and access to resources. We applied a network framework to characterise the spatial organisation of male morphs at each site and quantified male aggressive behaviour in the laboratory. We also compared body size, body condition, number of bite marks, parasite load, and the microhabitat use and diet, of males among the sites. 4. We detected no significant differences in spatial network structure between unburned and infrequently burned sites. However, at a frequently-burned site, the network shifted towards geographically closer, heteromorphic male neighbour associations. Males at this site were also larger, more aggressive, and had more bite marks but fewer parasites than males at the other sites. Moreover, we detected divergence in microhabitat use and diet among the morphs at the frequently-burned site that reflected the shift in spatial network structure and differences in morph behaviour. That is, only more-aggressive morphs usurped trees and consumed prey from higher trophic levels. 5. We conclude that environmental variation may influence animal spatial network structure. Jointly, behavioural and environmental variation may promote despotic social dynamics and ecological divergence in resource-limited habitats.
Data from: Beta diversity and specialization in plant-pollinator networks along an elevational gradient
Aim: To assess whether the reduced nutritional resources available for pollinators due to plant community simplification along an elevational plant-diversity gradient changes pollinator niche breadth and richness. Additionally, we evaluated how body size and proboscis length of pollinators shifted along the gradient, and whether these changes were related to pollinator niche breadth. Location: An elevational gradient (2,350-3,520 m a.s.l.) on the oceanic high-mountain strato-volcano of El Teide (Tenerife, Canary Islands). Taxon: Flowering plant and pollinator species. Methods: We compared quantitative plant–pollinator networks along the plant-diversity gradient. We calculated a set of niche-based topological metrics that capture the degree of specialization, niche breadth and niche overlap. Furthermore, we obtained β-diversity measures and the proportion of replacement and richness components. Results: There was an overall decline in species richness of pollinators with increasing elevation. This decline was mainly driven by the loss of species along the elevational gradient, which conformed a nested subset pattern. The whole network showed less specialization, greater connectance and lower modularity towards the summit. At high elevations, pollinators were more generalized and less selective in their flower choice, showing a greater trophic niche breadth compared to pollinators at lower elevations. Mean body size of pollinators increased with elevation, and species body size and proboscis length were positively associated with the number of plant species visited. Main conclusions. Overall, results indicated that the elevational gradient filters pollinator species, probably according to their thermal tolerance and ability to exploit a wide range of trophic resources. The finding that pollinators become more generalized and opportunistic at higher elevations is a novel result, which may have implications for new research into how ecological networks vary over environmental gradients. From an applied perspective, our results highlight the importance of considering the spatial variation of species assemblages when aiming to construct functionally reliable interaction networks along environmental gradients.
Data from: Knockouts of high-ranking males have limited impact on baboon social networks
Social network structures can crucially impact complex social processes such as collective behaviour or the transmission of information and diseases. However, currently it is poorly understood how social networks change over time. Previous studies on primates suggest that 'knockouts' (due to death or dispersal) of high-ranking individuals might be important drivers for structural changes in animal social networks. Here we test this hypothesis using long-term data on a natural population of baboons, examining the effects of 29 natural knockouts of alpha or beta males on adult female social networks. We investigated whether and how knockouts affected (1) changes in grooming and association rates among adult females, and (2) changes in mean degree and global clustering coefficient in these networks. The only significant effect that we found was a decrease in mean degree in grooming networks in the first month after knockouts, but this decrease was rather small, and grooming networks rebounded to baseline levels by the second month after knockouts. Taken together our results indicate that the removal of high-ranking males has only limited or no lasting effects on social networks of adult female baboons. This finding calls into question the hypothesis that the removal of high-ranking individuals has a destabilizing effect on social network structures in social animals.
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.