Non-random Structure Research Articles

Mobile genetic elements define the non-random structure of the Salmonella enterica serovar Typhi pangenome.

Bacterial relatedness measured using select chromosomal loci forms the basis of public health genomic surveillance. While approximating vertical evolution through this approach has proven exceptionally valuable for understanding pathogen dynamics, it excludes a fundamental dimension of bacterial evolution-horizontal gene transfer. Incorporating the accessory genome is the logical remediation and has recently shown promise in expanding epidemiological resolution for enteric pathogens. Employing k-mer-based Jaccard index analysis, and a novel genome length distance metric, we computed pangenome (i.e., core and accessory) relatedness for the globally important pathogen Salmonella enterica serotype Typhi (Typhi), and graphically express both vertical (homology-by-descent) and horizontal (homology-by-admixture) evolutionary relationships in a reticulate network of over 2,200 U.S. Typhi genomes. This analysis revealed non-random structure in the Typhi pangenome that is driven predominantly by the gain and loss of mobile genetic elements, confirming and expanding upon known epidemiological patterns, revealing novel plasmid dynamics, and identifying avenues for further genomic epidemiological exploration. With an eye to public health application, this work adds important biological context to the rapidly improving ways of analyzing bacterial genetic data and demonstrates the value of the accessory genome to infer pathogen epidemiology and evolution.IMPORTANCEGiven bacterial evolution occurs in both vertical and horizontal dimensions, inclusion of both core and accessory genetic material (i.e., the pangenome) is a logical step toward a more thorough understanding of pathogen dynamics. With an eye to public, and indeed, global health relevance, we couple contemporary tools for genomic analysis with decades of research on mobile genetic elements to demonstrate the value of the pangenome, known and unknown, annotated, and hypothetical, for stratification of Salmonella enterica serovar Typhi (Typhi) populations. We confirm and expand upon what is known about Typhi epidemiology, plasmids, and antimicrobial resistance dynamics, and offer new avenues of exploration to further deduce Typhi ecology and evolution, and ultimately to reduce the incidence of human disease.

Comparative phylogeography informs community structure and assembly during and after Pleistocene Lake Bonneville

Abstract Dispersal is one of the major processes controlling both genetic diversity and species diversity and is frequently studied in both phylogeography and community ecology. As such, integrating these fields to uncover how both historical and contemporary dispersal have affected local community structure can provide greater insights into community assembly. We used comparative phylogeography to determine if freshwater fish species in the Bonneville Basin show evidence of geologically recent dispersal and gene flow, which would probably have occurred when the basin was inundated by Lake Bonneville in the late Pleistocene. We then used museum records to uncover patterns of contemporary community structure and relate them to the results of the phylogeographical analyses. We found evidence for late Pleistocene dispersal throughout the Bonneville Basin in most of the fish species studied, which would have homogenized ancient communities. However, modern communities show evidence of non-random community structure and dispersal limitation between major sub-basins and habitats. Together, these results suggest that the Bonneville Basin fish fauna assembled due to a combination of historical dispersal and contemporary habitat filtering and extinction dynamics following isolation. Further work should continue to combine different data types to achieve more accurate inferences regarding contemporary community assembly.

Phylogenetic Partitioning of Gansu Flora: Unveiling the Core Transitional Zone of Chinese Flora.

Floristic regions, conventionally established using species distribution patterns, have often overlooked the phylogenetic relationships among taxa. However, how phylogenetic relationships influence the historical interconnections within and among biogeographic regions remains inadequately understood. In this research, we compiled distribution data for seed plants in Gansu, a region of significant biogeographic diversity located in northwestern China.We proposed a novel framework for floristic regions within Gansu, integrating distribution data and phylogenetic relationships of genera-level native seed plants, aiming to explore the relationship between phylogenetic relatedness, taxonomic composition, and regional phylogenetic delineation. We found that (1) phylogenetic relatedness was strongly correlated with the taxonomic composition among floras in Gansu. (2) The southeastern Gansu region showed the lowest level of spatial turnover in both phylogenetic relationships and the taxonomic composition of floristic assemblages across the Gansu region. (3) Null model analyses indicated nonrandom phylogenetic structure across the region, where most areas showed higher phylogenetic turnover than expected given the underlying taxonomic composition between sites. (4) Our results demonstrated a consistent pattern across various regionalization schemes and highlighted the preference for employing the phylogenetic dissimilarity approach in biogeographical regionalization investigations. (5) Employing the phylogenetic dissimilarity approach, we identified nine distinct floristic regions in Gansu that are categorized into two broader geographical units, namely the northwest and southeast. (6) Based on the phylogenetic graphic regions of China across this area.

Sequential analysis reveals use of mutual assessment in contests between wild New Zealand giraffe weevils

ABSTRACT When resources such as mates or mating sites are limited, selection drives the evolution of complex and frequently violent fighting behaviour. Contest outcome is determined by an individual’s resource holding potential (RHP) in comparison to that of their opponent. During contests individuals may assess only their own RHP, or they may mutually assess both their own and their opponent’s RHP to determine the effort they allocate to a contest. Male giraffe weevils (Lasiorhynchus barbicornis) bear an elongated rostrum used as a weapon during intense fights over access to females. We used sequential analysis to target the fine-scale structure of contests and phases of contest escalation to determine the assessment strategy used by rival male giraffe weevils in the wild. We found significant non-random temporal structure in behavioural transitions in all transition matrices, and winner and loser transition matrices were significantly different. Contest de-escalation was extremely rare compared to escalation and winners and losers used very different behaviours during contests overall. This study provides support for the sequential assessment model of mutual assessment by male giraffe weevils during competitive interactions. It also demonstrates the utility of sequential analysis in making sense of the often complex interactions occurring in wild insect populations.

Decoupled functional and phylogenetic diversity provide complementary information about community assembly mechanisms: A case study of Greek forests

Understanding the mechanisms of community assembly is of great importance to biogeography and ecology. Simultaneous investigation of the functional and phylogenetic facets of diversity has been proposed as a useful approach that allows inferences about such mechanisms. This study applies such an approach to explore diversity and structure within and among the main plant community types of mountainous forests in northern and central Greece. Functional and phylogenetic diversity and structure were measured in 25 community types of broadleaved deciduous and mountainous coniferous forests. Functional richness and Faith’s phylogenetic diversity were used to assess diversity, while mean pairwise functional and phylogenetic distances were used to investigate structure. Relationships between both facets of diversity and structure, as well as community types, were tested using boosted regression trees separately for all vascular plant taxa and taxa occurring in the forest understorey. Phylogenetic diversity was positively correlated with functional diversity, but phylogenetic structure was not a good predictor of functional structure. The understorey dataset revealed non-random structure for more vegetation plots than the dataset with all taxa. Habitat effects, represented by community types, were found to be better predictors of functional structure than phylogenetic structure, highlighting the need to account for habitat variability in studies of community assembly. In our study system, the two diversity facets provide complementary information on the structure of community types since most of the vegetation plots studied were found statistically significantly structured for one diversity facet (functionally clustered or phylogenetically overdispersed) and random for the other. Our results indicate that functional and phylogenetic measures provide different insights into the mechanisms driving the assembly of the forest community types studied.

Strong interactions between highly dynamic lamina-associated domains and the nuclear envelope stabilize the 3D architecture of Drosophila interphase chromatin

BackgroundInteractions among topologically associating domains (TADs), and between the nuclear envelope (NE) and lamina-associated domains (LADs) are expected to shape various aspects of three-dimensional (3D) chromatin structure and dynamics; however, relevant genome-wide experiments that may provide statistically significant conclusions remain difficult.ResultsWe have developed a coarse-grained dynamical model of D. melanogaster nuclei at TAD resolution that explicitly accounts for four distinct epigenetic classes of TADs and LAD–NE interactions. The model is parameterized to reproduce the experimental Hi-C map of the wild type (WT) nuclei; it describes time evolution of the chromatin over the G1 phase of the interphase. The simulations include an ensemble of nuclei, corresponding to the experimentally observed set of several possible mutual arrangements of chromosomal arms. The model is validated against multiple structural features of chromatin from several different experiments not used in model development. Predicted positioning of all LADs at the NE is highly dynamic—the same LAD can attach, detach and move far away from the NE multiple times during interphase. The probabilities of LADs to be in contact with the NE vary by an order of magnitude, despite all having the same affinity to the NE in the model. These probabilities are mostly determined by a highly variable local linear density of LADs along the genome, which also has the same strong effect on the predicted positioning of individual TADs -- higher probability of a TAD to be near NE is largely determined by a higher linear density of LADs surrounding this TAD. The distribution of LADs along the chromosome chains plays a notable role in maintaining a non-random average global structure of chromatin. Relatively high affinity of LADs to the NE in the WT nuclei substantially reduces sensitivity of the global radial chromatin distribution to variations in the strength of TAD–TAD interactions compared to the lamin depleted nuclei, where a small (0.5 kT) increase of cross-type TAD–TAD interactions doubles the chromatin density in the central nucleus region.ConclusionsA dynamical model of the entire fruit fly genome makes multiple genome-wide predictions of biological interest. The distribution of LADs along the chromatin chains affects their probabilities to be in contact with the NE and radial positioning of highly mobile TADs, playing a notable role in creating a non-random average global structure of the chromatin. We conjecture that an important role of attractive LAD–NE interactions is to stabilize global chromatin structure against inevitable cell-to-cell variations in TAD–TAD interactions.

Anomalous entropic effects in physical systems associated with collective consciousness

Beginning in 1998, a network of electronic random number generators located around the world has continuously recorded samples of truly random bits. The resulting data were used to explore a hypothesis that predicts the emergence of anomalous structure in randomness correlated with events that attract widespread human attention. A formal experiment testing this hypothesis from 1998 to 2015 found a highly significant deviation from chance expectation. However, the duration of the selected events comprised less than 5% of all data available through 2022, so the present analysis examined the full database to see if emergence of nonrandom structure was limited to those events, or if it was reflective of a persistent, if subtle, relationship between collective mind and matter. Two analytical methods were used to study emergent structure in time-series data: Multiscale entropy and a novel deconvolution technique. Both methods provided evidence consistent with the hypothesis, suggesting that some aspect of collective consciousness appears to be anomalously associated with aspects of the physical world.

Scaling migrations to communities: An empirical case of migration network in the Arctic

Seasonal migrants transport energy, nutrients, contaminants, parasites and diseases, while also connecting distant food webs between communities and ecosystems, which contributes to structuring meta-communities and meta-ecosystems. However, we currently lack a framework to characterize the structure of the spatial connections maintained by all migratory species reproducing or wintering in a given community. Here, we use a network approach to represent and characterize migratory pathways at the community level and provide an empirical description of this pattern from a High-Arctic terrestrial community. We define community migration networks as multipartite networks representing different biogeographic regions connected with a focal community through the seasonal movements of its migratory species. We focus on the Bylot Island High-Arctic terrestrial community, a summer breeding ground for several migratory species. We define the non-breeding range of each species using tracking devices, or range maps refined by flyways and habitat types. We show that the migratory species breeding on Bylot Island are found across hundreds of ecoregions on several continents during the non-breeding period and present a low spatial overlap. The migratory species are divided into groups associated with different sets of ecoregions. The non-random structure observed in our empirical community migration network suggests evolutionary and geographic constraints as well as ecological factors act to shape migrations at the community level. Overall, our study provides a simple and generalizable framework as a starting point to better integrate migrations at the community level. Our framework is a far-reaching tool that could be adapted to address the seasonal transport of energy, contaminants, parasites and diseases in ecosystems, as well as trophic interactions in communities with migratory species.

Spatial field reconstruction with INLA

Aims. Monte Carlo radiative transfer (MCRT) simulations are a powerful tool for understanding the role of dust in astrophysical systems and its influence on observations. However, due to the strong coupling of the radiation field and medium across the whole computational domain, the problem is non-local and non-linear, and such simulations are computationally expensive in the case of realistic 3D inhomogeneous dust distributions. We explore a novel technique for post-processing MCRT output to reduce the total computational run time by enhancing the output of computationally less expensive simulations of lower-quality. Methods. We combined principal component analysis (PCA) and non-negative matrix factorisation (NMF) as dimensionality reduction techniques together with Gaussian Markov random fields and the integrated nested Laplace approximation (INLA), an approximate method for Bayesian inference, to detect and reconstruct the non-random spatial structure in the images of lower signal-to-noise ratios or with missing data. Results. We tested our methodology using synthetic observations of a galaxy from the SKIRT Auriga project - a suite of high-resolution magnetohydrodynamic Milky Way-sized galaxies simulated in cosmological environment using a ‘zoom-in' technique. With this approach, we are able to reproduce high-photon-number reference images ~5 times faster with median residuals below ~20%.

Landscape or local? Distinct responses of flower visitor diversity and interaction networks to different land use scales in agricultural tropical highlands

Land use change has been identified as a cause for biodiversity loss and has significant effects on pollinators and their interactions with plants. Interaction network analyses complement diversity estimators by providing information on the stability and functionality of the plant-pollinator community in an ecosystem. However, how land use changes affect insect diversity, and the structure of their plant-insect interaction networks, could depend on the intensity of the disturbance but also may be a matter of scale. Our study was carried out in a tropical highland landscape dominated by intense, yet diverse, small-scale agriculture. We studied the effects of land use, at a landscape scale, and local cover and plant ecological descriptors, at a local scale; on diversity descriptors of insect pollinator communities, the abundance of the most frequent flower visitors, and their interaction networks. Seminatural vegetation favored insect flower visitors at both scales. At the landscape scale, human settlements positively influenced bee diversity, and seminatural areas favored the abundance of frequent hoverfly and bumblebee species. At the local scale, bare soil cover negatively influenced honeybee abundance while flower-rich covers positively related to bumblebee abundance. Only local scale variables had influence on network metrics. Bare soil cover was related to higher network specialization, probably due to a low rate of honeybee interactions. Flower-rich covers negatively influenced network connectance but favored modularity. These results suggest that flower resources, provided by weed areas and flowering crops, promote a high rate of interactions between trophic levels and a non-random structure in the interaction networks that may be helping to sustain network stability. Our results highlight the role of seminatural vegetation, at both scales, in maintaining stable insect pollinator communities and interactions in heterogeneous agricultural landscapes of the tropics.

Identification of multiplicatively acting modulatory mutational signatures in cancer

BackgroundA deep understanding of carcinogenesis at the DNA level underpins many advances in cancer prevention and treatment. Mutational signatures provide a breakthrough conceptualisation, as well as an analysis framework, that can be used to build such understanding. They capture somatic mutation patterns and at best identify their causes. Most studies in this context have focused on an inherently additive analysis, e.g. by non-negative matrix factorization, where the mutations within a cancer sample are explained by a linear combination of independent mutational signatures. However, other recent studies show that the mutational signatures exhibit non-additive interactions.ResultsWe carefully analysed such additive model fits from the PCAWG study cataloguing mutational signatures as well as their activities across thousands of cancers. Our analysis identified systematic and non-random structure of residuals that is left unexplained by the additive model. We used hierarchical clustering to identify cancer subsets with similar residual profiles to show that both systematic mutation count overestimation and underestimation take place. We propose an extension to the additive mutational signature model—multiplicatively acting modulatory processes—and develop a maximum-likelihood framework to identify such modulatory mutational signatures. The augmented model is expressive enough to almost fully remove the observed systematic residual patterns.ConclusionWe suggest the modulatory processes biologically relate to sample specific DNA repair propensities with cancer or tissue type specific profiles. Overall, our results identify an interesting direction where to expand signature analysis.

Polymicrobial Biofilm Organization of Staphylococcus aureus and Pseudomonas aeruginosa in a Chronic Wound Environment.

Biofilm on the skin surface of chronic wounds is an important step that involves difficulties in wound healing. The polymicrobial nature inside this pathogenic biofilm is key to understanding the chronicity of the lesion. Few in vitro models have been developed to study bacterial interactions inside this chronic wound. We evaluated the biofilm formation and the evolution of bacteria released from this biofilm on the two main bacteria isolated in this condition, Staphylococcus aureus and Pseudomonas aeruginosa, using a dynamic system (BioFlux™ 200) and a chronic wound-like medium (CWM) that mimics the chronic wound environment. We observed that all species constituted a faster biofilm in the CWM compared to a traditional culture medium (p < 0.01). The percentages of biofilm formation were significantly higher in the mixed biofilm compared to those determined for the bacterial species alone (p < 0.01). Biofilm organization was a non-random structure where S. aureus aggregates were located close to the wound surface, whereas P. aeruginosa was located deeper in the wound bed. Planktonic biofilm-detached bacteria showed decreased growth, overexpression of genes encoding biofilm formation, and an increase in the mature biofilm biomass formed. Our data confirmed the impact of the chronic wound environment on biofilm formation and on bacterial lifecycle inside the biofilm.

Unmasking the perching effect of the pioneer Mediterranean dwarf palm Chamaerops humilis L.

Although farmlands are the most extensive terrestrial biomes, the abandonment of traditional agriculture in many parts of the world has brought opportunities and challenges for the restoration of such human-disturbed habitats. Seed arrival is a crucial necessary ecological process during plant recolonization that can be enhanced by the use of the so-called "perch plants". Little is known, however, about whether the seed arrival via frugivorous birds is affected by the spatial distribution of the perch plants in disturbed habitats. To evaluate several spatial aspects of "perching" effect, we used a spatially explicit approach in two disturbed plots within the Doñana National Park (SW Spain). Specifically, we chose as study system the pioneer Mediterranean dwarf palm Chamaerops humilis L., which is often used as a perch by a variety of frugivorous bird species. A total of 289 C. humilis individuals were sampled in search of bird feces (N = 2998) and dispersed seeds (N = 529). Recorded seeds belonged to six different woody species from five different families. Nine bird species from six different families were recorded using C. humilis as perches. GLMs analyses indicated that taller C. humilis males with higher numbers of spatially associated woody species received more dispersed seeds. We detected a random spatial structure of bird feces and dispersed seeds in one study plot, while a nonrandom spatial structure was found in the other one, where isolated C. humilis received a higher number of bird feces and dispersed seeds than expected under spatial null models. The difference in spatial patterns between both study plots could relate, among other factors, to their different state of development in the ecological succession. Most of dispersed seeds were concentrated in a small number of C. humilis individuals, usually male and large ones, that acted as "hotspots" of seed arrival. The fact that frugivorous birds in one study site visited most often isolated C. humilis questions the aggregated spatial structure of revegetation designs typically used in restoration projects. This study reveals novel spatial aspects of the "perching" effect which could be helpful in the restoration of human-disturbed habitats worldwide.

Structured sampling of olfactory input by the fly mushroom body

Associative memory formation and recall in the fruit fly Drosophila melanogaster is subserved by the mushroom body (MB). Upon arrival in the MB, sensory information undergoes a profound transformation from broadly tuned and stereotyped odorant responses in the olfactory projection neuron (PN) layer to narrowly tuned and nonstereotyped responses in the Kenyon cells (KCs). Theory and experiment suggest that this transformation is implemented by random connectivity between KCs and PNs. However, this hypothesis has been challenging to test, given the difficulty of mapping synaptic connections between large numbers of brain-spanning neurons. Here, we used a recent whole-brain electron microscopy volume of the adult fruit fly to map PN-to-KC connectivity at synaptic resolution. The PN-KC connectome revealed unexpected structure, with preponderantly food-responsive PN types converging at above-chance levels on downstream KCs. Axons of the overconvergent PN types tended to arborize near one another in the MB main calyx, making local KC dendrites more likely to receive input from those types. Overconvergent PN types preferentially co-arborize and connect with dendrites of αβ and α'β' KC subtypes. Computational simulation of the observed network showed degraded discrimination performance compared with a random network, except when all signal flowed through the overconvergent, primarily food-responsive PN types. Additional theory and experiment will be needed to fully characterize the impact of the observed non-random network structure on associative memory formation and recall.

The role of population structure in computations through neural dynamics.

Neural computations are currently investigated using two separate approaches: sorting neurons into functional subpopulations or examining the low-dimensional dynamics of collective activity. Whether and how these two aspects interact to shape computations is currently unclear. Using a novel approach to extract computational mechanisms from networks trained on neuroscience tasks, here we show that the dimensionality of the dynamics and subpopulation structure play fundamentally complementary roles. Although various tasks can be implemented by increasing the dimensionality in networks with fully random population structure, flexible input-output mappings instead require a non-random population structure that can be described in terms of multiple subpopulations. Our analyses revealed that such a subpopulation structure enables flexible computations through a mechanism based on gain-controlled modulations that flexibly shape the collective dynamics. Our results lead to task-specific predictions for the structure of neural selectivity, for inactivation experiments and for the implication of different neurons in multi-tasking.

Shuffle the Decks: Children Are Sensitive to Incidental Nonrandom Structure in a Sequential-Choice Task

As children age, they can learn increasingly complex features of environmental structure—a key prerequisite for adaptive decision-making. Yet when we tested children (N = 304, 4–13 years old) in the Children’s Gambling Task, an age-appropriate variant of the Iowa Gambling Task, we found that age was negatively associated with performance. However, this paradoxical effect of age was found only in children who exhibited a maladaptive deplete-replenish bias, a tendency to shift choices after positive outcomes and repeat choices after negative outcomes. We found that this bias results from sensitivity to incidental nonrandom structure in the canonical, deterministic forms of these tasks—and that it would actually lead to optimal outcomes if the tasks were not deterministic. Our results illustrate that changes in decision-making across early childhood reflect, in part, increasing sensitivity to environmental structure.

Uncovering fundamental features of biological networks

Many biological networks are truly complex systems, displaying highly irregular yet significantly non-random structure. Extracting the statistical regularities of a biological network is a challenging inverse problem since one often has access to only a single experimental realization. In this case the analysis necessarily relies on a statistical model, typically a random graph null model against which statistical significance is defined. Results of the analysis may crucially depend on the choice of null model, leading to possible uncontrolled biases when this choice is ambiguous.

Local stability properties of complex, species-rich soil food webs with functional block structure.

Ecologists have long debated the properties that confer stability to complex, species‐rich ecological networks. Species‐level soil food webs are large and structured networks of central importance to ecosystem functioning. Here, we conducted an analysis of the stability properties of an up‐to‐date set of theoretical soil food web models that account both for realistic levels of species richness and the most recent views on the topological structure (who is connected to whom) of these food webs. The stability of the network was best explained by two factors: strong correlations between interaction strengths and the blocked, nonrandom trophic structure of the web. These two factors could stabilize our model food webs even at the high levels of species richness that are typically found in soil, and that would make random systems very unstable. Also, the stability of our soil food webs is well‐approximated by the cascade model. This result suggests that stability could emerge from the hierarchical structure of the functional organization of the web. Our study shows that under the assumption of equilibrium and small perturbations, theoretical soil food webs possess a topological structure that allows them to be complex yet more locally stable than their random counterpart. In particular, results strongly support the general hypothesis that the stability of rich and complex soil food webs is mostly driven by correlations in interaction strength and the organization of the soil food web into functional groups. The implication is that in real‐world food web, any force disrupting the functional structure and distribution pattern of interaction strengths (i.e., energy fluxes) of the soil food webs will destabilize the dynamics of the system, leading to species extinction and major changes in the relative abundances of species.

Permutation tests for hypothesis testing with animal social network data: Problems and potential solutions.

Permutation tests are widely used to test null hypotheses with animal social network data, but suffer from high rates of type I and II error when the permutations do not properly simulate the intended null hypothesis.Two common types of permutations each have limitations. Pre‐network (or datastream) permutations can be used to control ‘nuisance effects’ like spatial, temporal or sampling biases, but only when the null hypothesis assumes random social structure. Node (or node‐label) permutation tests can test null hypotheses that include nonrandom social structure, but only when nuisance effects do not shape the observed network.We demonstrate one possible solution addressing these limitations: using pre‐network permutations to adjust the values for each node or edge before conducting a node permutation test. We conduct a range of simulations to estimate error rates caused by confounding effects of social or non‐social structure in the raw data.Regressions on simulated datasets suggest that this ‘double permutation’ approach is less likely to produce elevated error rates relative to using only node permutations, pre‐network permutations or node permutations with simple covariates, which all exhibit elevated type I errors under at least one set of simulated conditions. For example, in scenarios where type I error rates from pre‐network permutation tests exceed 30%, the error rates from double permutation remain at 5%.The double permutation procedure provides one potential solution to issues arising from elevated type I and type II error rates when testing null hypotheses with social network data. We also discuss alternative approaches that can provide robust inference, including fitting mixed effects models, restricted node permutations, testing multiple null hypotheses and splitting large datasets to generate replicated networks. Finally, we highlight ways that uncertainty can be explicitly considered and carried through the analysis.

Social Network Analysis Reveals the Subtle Impacts of Tourist Provisioning on the Social Behavior of a Generalist Marine Apex Predator

Shark dive ecotourism is a lucrative industry in many regions around the globe. In some cases, sharks are provisioned using bait, prompting increased research on how baited dives influence shark behavior and yielding mixed results. Effects on patterns of habitat use and movement seemly vary across species and locations. It is unknown, however, whether wide-ranging, marine apex predators respond to provisioning by changing their patterns of grouping or social behavior. We applied a tiered analytical approach (aggregation-gregariousness-social preferences) examining the impact of provisioning on the putative social behavior of tiger sharks (Galeocerdo cuvier) at a dive tourism location in The Bahamas. Using network inference on three years of acoustic tracking data from 48 sharks, we tested for non-random social structure between non-provisioned and provisioned monitoring sites resulting in 12 distinct networks. Generally considered a solitary nomadic predator, we found evidence of sociality in tiger sharks, which varied spatiotemporally. We documented periods of both random (n = 7 networks) and non-random aggregation (n = 5 networks). Three of five non-random aggregations were at locations unimpacted by provisioning regardless of season, one occurred at an active provisioning site during the dry season and one at the same receivers during the wet season when provision activity is less prevalent. Aggregations lasted longer and occurred more frequently at provisioning sites, where gregariousness was also more variable. While differences in gregariousness among individuals was generally predictive of non-random network structure, individual site preferences, size and sex were not. Within five social preference networks, constructed using generalized affiliation indices, network density was lower at provisioning sites, indicating lower connectivity at these locations. We found no evidence of size assortment on preferences. Our data suggest that sociality may occur naturally within the Tiger Beach area, perhaps due to the unusually high density of individuals there. This study demonstrates the existence of periodic social behavior, but also considerable variation in association between tiger sharks, which we argue may help to mitigate any long-term impacts of provisioning on this population. Finally, we illustrate the utility of combining telemetry and social network approaches for assessing the impact of human disturbance on wildlife behavior.