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9,152 results for “Networking”
Data from: Predicting species occurrences with habitat network models
1. Biodiversity conservation requires modelling tools capable of predicting the presence or absence (i.e. occurrence-state) of species in habitat patches. Local habitat characteristics of a patch (lh), the cost of traversing the landscape matrix between patches (weighted connectivity; (wc), and the position of the patch in the habitat network topology (nt) all influence occurrence-state. Existing models are data demanding or consider only local habitat characteristics. We address these shortcomings and present a network-based modelling approach, which aims to predict species occurrence-state in habitat patches using readily available presence-only records. 2. For the tree frog Hyla arborea on the Swiss Plateau, we delineated habitat network nodes from an ensemble habitat suitability model, and used different cost surfaces to generate the edges of three networks: one limited only by dispersal distance (Uniform), another incorporating traffic, and a third based on inverse habitat suitability. For each network, we calculated explanatory variables representing the three categories (lh, wc and nt). The response variable, occurrence-state, was parametrized by a sampling-intensity procedure assessing observations of comparable species over a threshold of patch visits. The explanatory variables from the three networks and an additional non-topological model were related to the response variable with boosted regression trees. 3. The habitat network models had a similar fit; they all outperformed the non-topological model. Habitat suitability index ((lh) was the most important predictor in all networks, followed by third-order neighborhood (nt). Patch size (lh) was unimportant in all three networks. 4. We found that topological variables of habitat networks are relevant for the prediction of species occurrence-state, a step-forward from models considering only local habitat characteristics. For any habitat patch, occurrence-state is most prominently influenced by its habitat suitability, and then by the number of patches in a wide neighborhood. Our approach is generic and can be applied to multiple species in different habitats.
Double attention recurrent convolution neural network for answer selection
<p>Answer selection is one of the key steps in many Question Answering (QA) applications. In this paper, a new deep model with two kinds of attention is proposed for answer selection: the Double Attention Recurrent Convolution Neural Network (DARCNN). Double attention means self-attention and cross-attention. The design inspiration of this model came from the Transformer in the domain of machine translation. Self-attention can directly calculate dependencies between words regardless of the distance. However, self-attention ignores the distinction between its surrounding words and other words. Thus, we design a decay self-attention that prioritizes local words in a sentence. In addition, cross-attention is established to achieve interaction between question and candidate answer. With the outputs of self-attention and decay self-attention, we can get two kinds of interactive information via cross-attention. Finally, using the feature vectors of the question and answer, elementwise multiplication is used to combine with them and multi-layer perceptron (MLP) is used to predict the matching score. Experimental results on four QA datasets containing Chinese and English show that DARCNN performs better than other answer selection models, thereby demonstrating the effectiveness of self-attention, decay self-attention and cross-attention in answer-selection tasks.</p>
Data from: Gene coexpression networks reveal key drivers of phenotypic divergence in lake whitefish
BACKGROUND: A functional understanding of processes involved in adaptive divergence is one of the awaiting opportunities afforded by high throughput transcriptomic technologies. Functional analysis of co-expressed genes has succeeded in the biomedical field in identifying key drivers of disease pathways. However, in ecology and evolutionary biology, functional interpretation of transcriptomic data is still limited. RESULTS: Here we used Weighted Gene Co-Expression Network Analysis (WGCNA) to identify modules of co-expressed genes in muscle and brain tissue of a lake whitefish backcross progeny. Modules were connected to gradients of known adaptive traits involved in the ecological speciation process between benthic and limnetic ecotypes. Key drivers, i.e. hub genes of functional modules related to reproduction, growth, and behavior were identified, and module preservation was assessed in natural populations. Using this approach, we identified modules of co-expressed genes involved in phenotypic divergence and their key drivers, and further identified a module part specifically rewired in the backcross progeny. CONCLUSIONS: Functional analysis of transcriptomic data can significantly contribute to the understanding of the mechanisms underlying ecological speciation. Our findings point to BMP and Calcium signaling as common pathways involved in coordinated evolution of trophic behavior, trophic morphology (gill rakers), and reproduction. Results also point to pathways implicating hemoglobins and constitutive stress response (HSP70) governing growth in lake whitefish.
Data from: The multilayer temporal network of public transport in Great Britain
Despite the widespread availability of information concerning public transport coming from different sources, it is extremely hard to have a complete picture, in particular at a national scale. Here, we integrate timetable data obtained from the United Kingdom open-data program together with timetables of domestic flights, and obtain a comprehensive snapshot of the temporal characteristics of the whole UK public transport system for a week in October 2010. In order to focus on multi-modal aspects of the system, we use a coarse graining procedure and define explicitly the coupling between different transport modes such as connections at airports, ferry docks, rail, metro, coach and bus stations. The resulting weighted, directed, temporal and multilayer network is provided in simple, commonly used formats, ensuring easy access and the possibility of a straightforward use of old or specifically developed methods on this new and extensive dataset.
Data from: Genetic specificity of a plant-insect food web: implications for linking genetic variation to network complexity
Theory predicts that intraspecific genetic variation can increase the complexity of an ecological network. To date, however, we are lacking empirical knowledge of the extent to which genetic variation determines the assembly of ecological networks, as well as how the gain or loss of genetic variation will affect network structure. To address this knowledge gap, we used a common garden experiment to quantify the extent to which heritable trait variation in a host plant determines the assembly of its associated insect food web (network of trophic interactions). We then used a resampling procedure to simulate the additive effects of genetic variation on overall food-web complexity. We found that trait variation among host-plant genotypes was associated with resistance to insect herbivores, which indirectly affected interactions between herbivores and their insect parasitoids. Direct and indirect genetic effects resulted in distinct compositions of trophic interactions associated with each host-plant genotype. Moreover, our simulations suggest that food-web complexity would increase by 20% over the range of genetic variation in the experimental population of host plants. Taken together, our results indicate that intraspecific genetic variation can play a key role in structuring ecological networks, which may in turn affect network persistence.
Data from: Dissecting nutrient-related co-expression networks in phosphate starved poplars
Phosphorus (P) is an essential plant nutrient, but its availability is often limited in soil. Here, we studied changes in the transcriptome and in nutrient element concentrations in leaves and roots of poplars (Populus × canescens) in response to P deficiency. P starvation resulted in decreased concentrations of S and major cations (K, Mg, Ca), in increased concentrations of N, Zn and Al, while C, Fe and Mn were only little affected. In roots and leaves >4,000 and >9,000 genes were differently expressed upon P starvation. These genes clustered in eleven co-expression modules of which seven were correlated with distinct elements in the plant tissues. One module (4.7% of all differentially expressed genes) was strongly correlated with changes in the P concentration in the plant. In this module the GO term "response to P starvation" was enriched with phosphoenolpyruvate carboxylase kinases, phosphatases and pyrophosphatases as well as regulatory domains such as SPX, but no phosphate transporters. The P-related module was also enriched in genes of the functional category "galactolipid synthesis". Galactolipids substitute phospholipids in membranes under P limitation. Two modules, one correlated with C and N and the other with biomass, S and Mg, were connected with the P-related module by co-expression. In these modules GO terms indicating "DNA modification" and "cell division" as well as "defense" and "RNA modification" and "signaling" were enriched; they contained phosphate transporters. Bark storage proteins were among the most strongly upregulated genes in the growth-related module suggesting that N, which could not be used for growth, accumulated in typical storage compounds. In conclusion, weighted gene coexpression network analysis revealed a hierarchical structure of gene clusters, which separated phosphate starvation responses correlated with P tissue concentrations from other gene modules, which most likely represented transcriptional adjustments related to down-stream nutritional changes and stress.
Data from: Building genetic networks using relatedness information: a novel approach for the estimation of dispersal and characterization of group structure in social animals
Natal dispersal is an important life history trait driving variation in individual fitness and, therefore, a proper understanding of the factors underlying dispersal behaviour is critical to many fields including population dynamics, behavioural ecology and conservation biology. However, individual dispersal patterns remain difficult to quantify despite many years of research using direct and indirect methods. Here, we quantify dispersal in a single intensively-studied population of the cooperatively breeding chestnut-crowned babbler (Pomatostomus ruficeps) using genetic networks created from the combination of pairwise relatedness data and social networking methods and compare this to dispersal estimates from re-sighting data. Not only does this novel approach identify movements between social groups within our study sites but also provides an estimation of immigration rates of individuals originating outside the study site. Both genetic and re-sighting data indicated that dispersal was strongly female-biased, but the magnitude of dispersal estimates was much greater using genetic data. This suggests that many previous studies relying on mark-recapture data may have significantly underestimated dispersal. An analysis of spatial genetic structure within the sampled population also supports the idea that females are more dispersive, with females having no structure beyond the bounds of their own social group while male genetic structure expands for 750 meters from their social group. Although the genetic network approach we have used is an excellent tool for visualising the social and genetic microstructure of social animals and identifying dispersers, our results also indicate the importance of applying them in parallel with behavioural and life history data.
Data from: Conservation under uncertainty: optimal network protection strategies for worst-case disturbance events
1. Conservation goals are ideally set after a thorough understanding of potential threats; however, predicting future spatial patterns of threats, such as disturbance, remains challenging. Here, we develop a novel extension of network fortification-interdiction models (NFIM) that deals with uncertainty in future spatial patterns of disturbance by optimally selecting sites that will best mitigate a worst-case scenario for a given magnitude of disturbance. 2. This approach uses information on between-patch movement probabilities and patch-specific survival, which can be estimated from mark-recapture data, to optimize life expectancy. Optimization occurs in three interrelated stages: protection, followed by disturbance, and then assessment. 3. We applied the modeling approach to two mark-recapture data sets: Roseate terns Sterna dougallii in the northeastern United States and the Everglade snail kite Rostrhamus sociabilis plumbeus in Florida. We contrasted the results to a more conventional approach of protecting sites that maximize connectivity (by minimizing the distances among protected sites) and a bi-objective model that maximizes connectivity and the number of individuals under protection. 4. Protecting sites that best mitigate future worst-case disturbance scenarios consistently resulted in higher predicted life expectancies than protecting patches that minimize dispersal distance. Predicted life expectancy was similar between NFIM and the biobjective model for the small roseate tern network, yet, the NFIM predicted higher life expectancy than any of the scenarios in the bi-objective model in the snail kite network. 5. Synthesis and applications. This application of interdiction models prescribed a combination of patches for protection that results in the least possible decrease in life expectancy. Our analyses of the snail kite and roseate tern networks suggest that managing to protect these prescribed patches by the network fortification interdiction model (i.e. protecting against the worst-case disturbance scenario) is more beneficial than managing patches that minimize dispersal distance or maximize the number of individuals under protection if the conservation goal is to ensure the long term persistence of a species.
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.
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.