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1,721 results for “network data”
Data from: Learning and robustness to catch-and-release fishing in a shark social network
Individuals can play different roles in maintaining connectivity and social cohesion in animal populations and thereby influence population robustness to perturbations. We performed a social network analysis in a reef shark population to assess the vulnerability of the global network to node removal under different scenarios. We found that the network was generally robust to the removal of nodes with high centrality. The network appeared also highly robust to experimental fishing. Individual shark catchability decreased as a function of experience, as revealed by comparing capture frequency and site presence. Altogether, these features suggest that individuals learnt to avoid capture, which ultimately increased network robustness to experimental catch-and-release. Our results also suggest that some caution must be taken when using capture–recapture models often used to assess population size as assumptions (such as equal probabilities of capture and recapture) may be violated by individual learning to escape recapture.
Data from: Downscaling pollen-transport networks to the level of individuals
1. Most plant-pollinator network studies are conducted at species level whereas little is known about network patterns at the individual level. In fact, nodes in traditional species-based interaction networks are aggregates of individuals establishing the actual links observed in nature. Thus, emergent properties of interaction networks might be the result of mechanisms acting at the individual level. 2. Pollen loads carried by insect flower-visitors from two mountain communities were studied to construct pollen-transport networks. For the first time, these community-wide pollen-transport networks were downscaled from species-species (sp-sp) to individuals-species (i-sp) in order to explore specialization, network patterns and niche variation at both interacting levels. We used a null model approach to account for network size differences inherent to the downscaling process. Specifically, our objectives were: (i) to investigate whether network structure changes with downscaling, (ii) to evaluate the incidence and magnitude of individual specialization in pollen use, and (iii) to identify potential ecological factors influencing the observed degree of individual specialization. 3. Network downscaling revealed a high specialization of pollinator individuals, which was masked and unexplored in sp-sp networks. The average number of interactions per node, connectance, interaction diversity and degree of nestedness decreased in i-sp networks, because generalized pollinator species were composed of specialized and idiosyncratic conspecific individuals. An analysis with 21 pollinator species representative of two communities showed that mean individual pollen resource niche was only c. 46% of the total species niche. 4.The degree of individual specialization was associated to inter- and intraspecific overlap in pollen use and it was higher for abundant than for rare species. Such niche heterogeneity depends on individual differences in foraging behaviour and likely has implications for community dynamics and species stability. 5. Our findings highlight the importance of taking inter-individual variation into account when studying higher–order structures such as interaction networks. We argue that exploring individual-based networks will improve our understanding of species-based networks and will enhance the link between network analysis, foraging theory and evolutionary biology.
Data from: Temporal variation in plant-pollinator networks from seasonal tropical environments: higher specialization when resources are scarce
The temporal dynamics of plant phenology and pollinator abundance across seasons should influence the structure of plant-pollinator interaction networks. Nevertheless, such dynamics are seldom considered, especially for diverse tropical networks. Here, we evaluated the temporal variation of four plant-pollinator networks in two seasonal ecosystems in Central Brazil (Cerrado and Pantanal). Data were gathered on a monthly basis over one year for each network. We characterized seasonal and temporal shifts in plant-pollinator interactions, using temporally discrete networks. We predicted that the greater floral availability in the rainy season would allow for finer partitioning of the floral niche by the pollinators, i.e., higher specialization patterns as previously described across large spatial gradients. Contrary to these expectations, we found that dry season networks, although characterized by lower floral resource richness and abundance, showed higher levels of network-wide interaction partitioning (complementary specialization and modularity). For nestedness and species level indices, though, this between-seasons difference was not consistent. Reduced resource availability in the dry season may promote higher interspecific competition among pollinators leading to reduced niche overlap, thus explaining the increase in specialization. Importantly, we also show that targeted data collection during peak flowering generates higher estimates of network specialization. Hence, depending on the period of data collection, different structural values for the networks of interactions may be found. Synthesis: Our study suggests that networks of tropical environments have structural properties that vary according to seasons, which should be taken into account in the description of the complex systems of interactions between plants and their pollinators in these areas.
Data from: Detailed food web networks of three Greater Antillean coral reef systems: the Cayman Islands, Cuba, and Jamaica
Food webs represent one of the most complex aspects of community biotic interactions. Complex food webs are represented as networks of interspecific interactions, where nodes represent species or groups of species, and links are predator-prey interactions. This paper presents reconstructions of coral reef food webs in three Greater Antillean regions of the Caribbean: the Cayman Islands, Cuba, and Jamaica. Though not taxonomically comprehensive, each food web nevertheless comprises producers and consumers, single-celled and multicellular organisms, and species foraging on reefs and adjacent seagrass beds. Species are grouped into trophic guilds if their prey and predator links are indistinguishable. The data list guilds, taxonomic composition, prey guilds/species, and predators. Primary producer and invertebrate richness are regionally uniform, but vertebrate richness varies on the basis of more detailed occurrence data. Each region comprises 169 primary producers, 513 protistan and invertebrate consumer species, and 159, 178, and 170 vertebrate species in the Cayman Islands, Cuba, and Jamaica, respectively. Caribbean coral reefs are among the world's most endangered by anthropogenic activities. The datasets presented here will facilitate comparisons of historical and regional variation, the assessment of impacts of species loss and invasion, and the application of food webs to ecosystem analyses.
Data from: Functional outcomes of mutualistic network interactions: a community-scale study of frugivore gut passage on germination
1. Current understanding of mutualistic networks is grounded largely in data on interaction frequency, yet mutualistic network dynamics are also shaped by interaction quality—the functional outcomes of individual interactions on reproduction and survival. The difficulty of obtaining data on functional outcomes has resulted in limited understanding of functional variation among a network's pairwise species interactions, of the study designs that are necessary to capture major sources of functional variation, and of predictors of functional variation that may allow generalization across networks. 2. In this community-scale study, we targeted a key functional outcome in plant-frugivore networks: the impact of frugivore gut passage on seed germination. We used captive frugivore feeding trials and germination experiments in an island ecosystem, attaining species-level coverage across all extant native frugivores and the plants they consume to 1) assess sources of functional variation, 2) separate effects of pulp removal from those of scarification via gut passage, and 3) test trait-based correlates of gut passage effect sizes. 3. We found antagonistic seed predation effects of a frugivore previously assumed to be a seed disperser, highlighting the need to consider functional outcomes rather than interaction frequency alone. The other frugivores each exhibited similar impacts for individual plant species, with benefits primarily caused by pulp removal rather than scarification, supporting the use of animal functional groups in this context. In contrast, plant species varied widely in impacts of gut passage on germination. Species with smaller seeds and more frugivore partners had larger benefits of gut passage, showing promise for network metrics and functional traits to predict functional variation among plants. 4. Synthesis. Combining network and demographic approaches, we assessed the degree and sources of variation in a key functional outcome of plant-frugivore interactions across an entire network. Using a detailed study design, our work shows how simpler study designs can capture primary sources of functional variation and that functional traits and network metrics may allow generalization across networks. Efficiently measuring and generalizing sources of functional variation within mutualistic networks will strengthen our ability to model network dynamics and predict mutualist responses to global change.
Data from: Social network analysis of psychological morbidity in an urban slum of Bangladesh: a cross-sectional study based on a community census
Background Social ties are believed to play important roles in mitigating depression and anxiety, as well as fostering mental health in the population. We test this association for young urban men in Bangladesh. Methods Using a locally adapted GHQ-12 instrument, we enumerate self-reported mental health outcomes for 824 post-adolescent young men between the ages of 18 and 29 in a low-income urban community in Dhaka, Bangladesh. We further measure the social network for all our subjects and estimate the association of social network of the respondents with self-reported mental health outcomes controlling for possible confounders. Results We find there are considerable variations in both the mental health outcomes and social network across respondents. The GHQ scores (mean = 9.2, SD = 4.9) suggest significant psychological morbidity among the respondents. However, our findings imply better social ties and connections can potentially mitigate negative mental health outcomes (0.05-0.65 lower standardized GHQ score). Among other factors, being married and a recent migrant are also associated with better mental health status (0.17-0.20 and 0.16-0.17 lower standardized GHQ scores respectively). Conclusion Our results underscore the importance of social connection in providing buffer against stress and anxiety through psychosocial support from one's peer in a resource constraint urban setting. Our findings also suggest incorporating social network and ties in designing mental health policies and interventions.
Data from: Argentine ants (Linepithema humile) use adaptable transportation networks to track changes in resource quality
Transportation networks play a crucial role in human and animal societies. For a transportation network to be efficient, it must have adequate capacity to meet traffic demand. Network design becomes increasingly difficult in situations where traffic demand can change unexpectedly. In humans, network design is often constrained by path dependency because it is difficult to move a road once it is built. A similar issue theoretically faces pheromone-trail-laying social insects; once a trail has been laid, positive feedback makes re-routing difficult because new trails cannot compete with continually reinforced pre-existing trails. In the present study, we examined the response of Argentine ant colonies and their trail networks to variable environments where resources differ in quality and change unexpectedly. We found that Argentine ant colonies effectively tracked changes in food quality such that colonies allocated the highest proportion of foragers to the most rewarding feeder. Ant colonies maximised access to high concentration feeders by building additional trails and routes connecting the nest to the feeder. Trail networks appeared to form via a pruning process in which lower traffic trails were gradually removed from the network. At the same time, we observed several instances where new trails appear to have been built to accommodate a surge in demand. The combination of trail building when traffic demand is high and trail pruning when traffic demand is low results in a demand-driven network formation system that allows ants to monopolise multiple dynamic resources.
Data from: From gene trees to a dated allopolyploid network: insights from the angiosperm genus Viola (Violaceae)
Allopolyploidisation acounts for a significant fraction of speciation events in many eukaryotic lineages. However, existing phylogenetic and dating methods require tree-like topologies and are unable to handle the network-like phylogenetic relationships of lineages containing allopolyploids. No explicit framework has so far been established for evaluating competing network topologies, and few attempts have been made to date phylogenetic networks. We used a four-step approach to generate a dated polyploid species network for the cosmopolitan angiosperm genus Viola L. (Violaceae Batch.). The genus contains ca 600 species and both recent (neo-) and more ancient (meso-) polyploid lineages distributed over 16 sections. First, we obtained DNA sequences of three low-copy nuclear genes and one chloroplast region, from 42 species representing all 16 sections. Second, we obtained fossil-calibrated chronograms for each nuclear gene marker. Third, we determined the most parsimonious multilabelled genome tree and its corresponding network, resolved at the section (not the species) level. Reconstructing the 'correct' network for a set of polyploids depends on recovering all homoeologs, i.e. all subgenomes, in these polyploids. Assuming the presence of Viola subgenome lineages that were not detected by the nuclear gene phylogenies ('ghost subgenome lineages'), significantly reduced the number of inferred polyploidisation events. We identified the most parsimonious network topology from a set of five competing scenarios differing in the interpretation of homoeolog extinctions and lineage sorting, based on (1) fewest possible ghost subgenome lineages, (2) fewest possible polyploidisation events, and (3) least possible deviation from expected ploidy as inferred from available chromosome counts of the involved polyploid taxa. Finally, we estimated the homoploid and polyploid speciation times of the most parsimonious network. Homoploid speciation times were estimated by coalescent analysis of gene tree node ages. Polyploid speciation times were estimated by comparing branch lengths and speciation rates of lineages with and without ploidy shifts. Our analyses recognise Viola as an old genus (crown age 31 Ma) whose evolutionary history has been profoundly affected by allopolyploidy. Between 16 and 21 allopolyploidisations are necessary to explain the diversification of the 16 major lineages (sections) of Viola, suggesting that allopolyploidy has accounted for a high percentage – between 67% and 88% – of the speciation events at this level. The theoretical and methodological approaches presented here for (1) constructing networks and (2) dating speciation events within a network, have general applicability for phylogenetic studies of groups where allopolyploidisation has occurred. They make explicit use of a hitherto underexplored source of ploidy information from chromosome counts to help resolve phylogenetic cases where incomplete sequence data hampers network inference. Importantly, the coalescent-based method used herein circumvents the assumption of tree-like evolution required by most techniques for dating speciation events.
Data from: Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees.
Claims of culture in animals have been stimulated by studies on a wide range of taxa revealing group-specific behavior patterns that remain stable through generations, consistent with different behavioral innovations spreading within groups by social transmission in a manner similar to human culture. In chimpanzees, 39 behaviors have been identified as 'cultural', because alternative genetic and environmental explanations for the observed regional variation appear less plausible. This interpretation is supported by experimental data from captive chimpanzee groups. However, there is no experimental evidence for social learning in the wild, nor has there been direct observation of social diffusion of spontaneously occurring behavioral innovations. Here, we document the spread of two novel tool-use variants, 'moss-sponging' and 'leaf-sponge re-use', in the Sonso chimpanzee community of Budongo Forest, Uganda. We use traditional network-based diffusion analysis (NBDA) to test whether these novel behaviors spread by social learning, as well as a newly developed dynamic version of NBDA, capable of capturing temporal aspects of acquisition, i.e. how each successive personal observations impact the subsequent acquisition of behavior. Both models provide strong evidence that diffusion patterns of moss-sponging, but not leaf-sponge re-use, are significantly better explained by social than asocial learning, therefore showing that wild chimpanzees socially learned moss-sponging from each other. The most conservative estimate of social transmission accounts for 85% of observed events with an estimated 11-fold increase in learning rate for each time a novice observed an informed individual performing moss-sponging. We conclude that group-specific behavioral variants in chimpanzees can be socially learned, suggesting this prerequisite for culture originated in a common ancestor of great apes and humans, long before the advent of modern humans.
Data from: Loss of functional connectivity in migration networks induces population decline in migratory birds
Migratory birds rely on a habitat network along their migration routes by temporarily occupying stopover sites between breeding and non-breeding grounds. Removal or degradation of stopover sites in a network might impede movement, and thereby reduce migration success and survival. The extent to which the breakdown of migration networks, due to changes in land use, impacts the population sizes of migratory birds is poorly understood. We measured the functional connectivity of migration networks of waterfowl species that migrate over the East Asian-Australasian Flyway from 1992-2015. We analysed the relationship between changes in non-breeding population sizes and changes in functional connectivity, while taking into account other commonly-considered species traits, using a Phylogenetic Linear Mixed Model. We found that population sizes significantly declined with a reduction in the functional connectivity of migration networks; no other predictor variables were important. We conclude that the current decrease in functional connectivity, due to habitat loss and degradation in migration networks, can negatively and crucially impact population sizes of migratory birds. Our findings provide new insights into the underlying mechanisms that affect population trends of migratory birds under environmental changes. Establishment of international agreements leading to the creation of systematic conservation networks associated with migratory species' distributions and stopover sites may safeguard migratory bird populations.
Data from: Infection-induced behavioural changes reduce connectivity and the potential for disease spread in wild mice contact networks
Infection may modify the behaviour of the host and of its conspecifics in a group, potentially altering social connectivity. Because many infectious diseases are transmitted through social contact, social connectivity changes can impact transmission dynamics. Previous approaches to understanding disease transmission dynamics in wild populations were limited in their ability to disentangle different factors that determine the outcome of disease outbreaks. Here we ask how social connectivity is affected by infection and how this relationship impacts disease transmission dynamics. We experimentally manipulated disease status of wild house mice using an immune challenge and monitored social interactions within this free-living population before and after manipulation using automated tracking. The immune-challenged animals showed reduced connectivity to their social groups, which happened as a function of their own behaviour, rather than through conspecific avoidance. We incorporated these disease-induced changes of social connectivity among individuals into models of disease outbreaks over the empirically-derived networks. The models revealed that changes in host behaviour frequently resulted in the disease being contained to very few animals, as opposed to becoming widespread. Our results highlight the importance of considering the role that behavioural alterations during infection can have on social dynamics when evaluating the potential for disease outbreaks.
Data from: Wild birds respond to flockmate loss by increasing their social network associations to others
Understanding the consequences of losing individuals from wild populations is a current and pressing issue, yet how such loss influences the social behaviour of the remaining animals is largely unexplored. Through combining the automated tracking of winter flocks of over 500 wild great tits (Parus major) with removal experiments, we assessed how individuals' social network positions responded to the loss of their social associates. We found that the extent of flockmate loss that individuals experienced correlated positively with subsequent increases in the number of their social associations, the average strength of their bonds and their overall connectedness within the social network (defined as summed edge weights). Increased social connectivity was not driven by general disturbance or changes in foraging behaviour, but by modifications to fine-scale social network connections in response to losing their associates. Therefore, the reduction in social connectedness expected by individual loss may be mitigated by increases in social associations between remaining individuals. Given that these findings demonstrate rapid adjustment of social network associations in response to the loss of previous social ties, future research should examine the generality of the compensatory adjustment of social relations in ways that maintain the structure of social organization.
Data from: Contact networks structured by sex underpin sex-specific epidemiology of infection
Contact networks are fundamental to the transmission of infection and host sex often affects the acquisition and progression of infection. However, the epidemiological impacts of sex-related variation in animal contact networks have rarely been investigated. We test the hypothesis that sex-biases in infection are related to variation in multilayer contact networks structured by sex in a population of European badgers Meles meles naturally infected with Mycobacterium bovis. Our key results are that male-male and between-sex networks are structured at broader spatial scales than female-female networks and that in male-male and between-sex contact networks, but not female-female networks, there is a significant relationship between infection and contacts with individuals in other groups. These sex differences in social behaviour may underpin male-biased acquisition of infection and may result in males being responsible for more between-group transmission. This highlights the importance of sex-related variation in host behaviour when managing animal diseases.
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.
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.
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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.