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Species interactions shape biodiversity patterns, community assemblage, and the dynamics of wildlife populations. Ecological theory posits that the strength of interspecific interactions is fundamentally underpinned by the population sizes of the involved species. Nonetheless, prevalent approaches for modeling species interactions predominantly center around occupancy states. Here, we use simulations to illuminate the inadequacies of modeling species interactions solely as a function of occupancy, as is common practice in ecology. We demonstrate erroneous inference into species interactions due to error in parameter estimates when considering species occupancy alone. To address this critical issue, we propose, develop, and demonstrate an abundance‐mediated interaction framework designed explicitly for modeling species interactions involving two or more species from detection/non‐detection data. We present Markov chain Monte Carlo (MCMC) samplers tailored for diverse ecological scenarios, including intraguild predation, disease‐ or predator‐mediated competition, and trophic cascades. Illustrating the practical implications of our approach, we compare inference from modeling the interactions in a three‐species network involving coyotes (Canis latrans), fishers (Pekania pennanti), and American marten (Martes americana) in North America as a function of occupancy states and as a function of abundance. When modeling interactions as a function of abundance rather than occupancy, we uncover previously unidentified interactions. Our study emphasizes that accounting for abundance‐mediated interactions rather than simple co‐occurrence patterns can fundamentally alter our comprehension of system dynamics. Through an empirical case study and comprehensive simulations, we demonstrate the importance of accounting for abundance when modeling species interactions, and we present a statistical framework equipped with MCMC samplers to achieve this paradigm shift in ecological research. [ABSTRACT FROM AUTHOR]

In the Neotropical biogeographic region, there are about 290 known species and subspecies of fleas, which have as their main hosts to the rodent subfamily Sigmodontinae. In Peru, more than 22 years have passed since the last list of known flea species was published. This study presents a review and update of the fleas recorded in Peru from 1908 to 2024. This list contains information on the flea species, including their known hosts, the localities in Peru where they were reported, the main references and some comments. In addition, the specificity of flea–host interactions was assessed using an interaction network approach. In the literature review, 86 flea species were found distributed among 9 families, 34 genera and 19 subspecies. These fleas were recorded parasitizing at least71 species of mammals and birds (14 orders, 28 families, 54 genera), 15 reported only at the genera level and seven undetermined ones. The flea–host interaction network exhibited a modular structure, indicating that these interactions tend to be specialized. A sigmodontine rodent (Akodon mollis) and a Rhopalopsyllidae flea (Polygenis litargus) were highly connected across modules and the overall network, and thus were important to maintain the structure. This review contributes to the knowledge of fleas in Peru, synthesizing the scattered information and providing information on the interaction they have with their hosts. [ABSTRACT FROM AUTHOR]

Understanding the behavior of migratory birds can help determine levels of connectivity and inform conservation actions for species of conservation concern. The common tern Sterna hirundo is a long‐distance migratory seabird that is considered a species of conservation concern in the North American Great Lakes region and that has experienced significant declines in breeding numbers across large lakes in Manitoba. To better understand the movement ecology of common terns, we used data from multiple tracking technologies (solar geolocation, GPS tracking, and Motus radio tracking) obtained from individuals (n = 83) across five breeding colonies on four inland lakes in North America. We identified key stopover regions used during southward migration and explored how demographics and social interactions influence connectivity. We identified three key stopover regions (Lake Erie, the southern Atlantic Coast, and Florida) and documented, for the first time, differences in post‐natal and post‐breeding migration for inland nesting terns. Juveniles arrived, on average, three weeks later than unrelated adults to their first major staging area. Although adult female arrival to and departure from Lake Erie was similar to adult males, female schedules became significantly earlier than males as southward migration progressed. Using a graph network to describe the spatiotemporal associations among adults from the same inland lake, individuals appeared to be highly connected, meeting up in different regions throughout the non‐breeding season, suggesting that social interactions may play an important role in maintaining spatial connectivity. Despite differences in migration schedules by sex and arrival to the first major staging area by age class, birds appeared to rely on the same key stopover regions during southward migration. The stopover regions identified in this study can help identify potential bottlenecks and guide future research aimed at assessing the impacts of climate change and human disturbance on common terns breeding in North America. [ABSTRACT FROM AUTHOR]

Background Cytoscape is an open-source software to visualize and analyze networks. However, large networks, such as protein interaction networks, are still difficult to analyze as a whole. Methods Here, we propose Clust&See3.0, a novel version of a Cytoscape app that has been developed to identify, visualize and manipulate network clusters and modules. It is now enriched with functionalities allowing custom annotations of nodes and computation of their statistical enrichments. Results As the wealth of multi-omics data is growing, such functionalities are highly valuable for a better understanding of biological module composition, as illustrated by the presented use case. Conclusions In summary, the originality of Clust&See3.0 lies in providing users with a complete tool for network clusters analyses: from cluster identification, visualization, node and cluster annotations to annotation statistical analyses.

The separation of macro-level and microbial food webs is typical but has important limits. A multilayered food web conceptual model is needed because microbial food webs are nested within macro-organisms. These multilayered microbial food webs likely influence the network dynamics of macro-level food webs. A multilayered food webs model opens new avenues for empirical investigations into the complexity of ecological networks. The model can provide a new lens through which to view a network's response to ecosystem changes. Food webs are typically defined as being macro-organism-based (e.g., plants, mammals, birds) or microbial (e.g., bacteria, fungi, viruses). However, these characterizations have limits. We propose a multilayered food web conceptual model where microbial food webs are nested within food webs composed of macro-organisms. Nesting occurs through host–microbe interactions, which influence the health and behavior of host macro-organisms, such that host microbiomes likely alter population dynamics of interacting macro-organisms and vice versa. Here, we explore the theoretical underpinnings of multilayered food webs and the implications of this new conceptual model on food web ecology. Our framework opens avenues for new empirical investigations into complex ecological networks and provides a new lens through which to view a network's response to ecosystem changes. [ABSTRACT FROM AUTHOR]

Background: Cardiovascular diseases (CVDs) are major causes of mortality and morbidity worldwide; yet the understanding of their molecular basis is incomplete. Multi-omics studies have significant potential to uncover these mechanisms, but such studies are challenged by genetic and environmental confounding—a problem that can be effectively reduced by investigating intrapair differences in twins. Here, we linked data on all diagnoses of the circulatory system from the nationwide Danish Patient Registry (spanning 1977–2022) to a study population of 835 twins holding genome-wide DNA methylation and gene expression data. CVD diagnoses were divided into prevalent or incident cases (i.e., occurring before or after blood sample collection (2007–2011)). The diagnoses were classified into four groups: cerebrovascular diseases, coronary artery disease (CAD), arterial and other cardiovascular diseases (AOCDs), and diseases of the veins and lymphatic system. Statistical analyses were performed by linear (prevalent cases) or cox (incident cases) regression analyses at both the individual-level and twin pair-level. Significant genes (p < 0.05) in both types of biological data and at both levels were inspected by bioinformatic analyses, including gene set enrichment analysis and interaction network analysis. Results: In general, more genes were found for prevalent than for incident cases, and bioinformatic analyses primarily found pathways of the immune system, signal transduction and diseases for prevalent cases, and pathways of cell–cell communication, metabolisms of proteins and RNA, gene expression, and chromatin organization groups for incident cases. This potentially reflects biology related to response to CVD (prevalent cases) and mechanisms related to regulation and development of disease (incident cases). Of specific genes, Myosin 1E was found to be central for CAD, and DEAD-Box Helicase 5 for AOCD. These genes were observed in both the prevalent and the incident analyses, potentially reflecting that their DNA methylation and gene transcription levels change both because of disease (prevalent cases) and prior disease (incident cases). Conclusion: We present novel biomarkers for CVD by performing multi-omics analysis in twins, hereby lowering the confounding due to shared genetics and early life environment—a study design that is surprisingly rare in the field of CVD, and where additional studies are highly needed. [ABSTRACT FROM AUTHOR]

The advancement of mechanization in forestry has increased productivity in the forestry sector, bringing positive and negative impacts that require a deeper understanding for sustainable forest management. This study aimed to apply a simplified instrument for assessing damage and environmental impacts in forest harvesting of commercial eucalyptus plantations, using a combination of methodologies. The methodology used combined interaction networks and impact assessment matrices, carrying out field surveys, transposing them to interaction networks and weighting them through assessment matrices, resulting in environmental indices (ES) for prioritizing actions. The study was conducted on a commercial eucalyptus plantation in the municipality of São Pedro, São Paulo, Brazil. The mechanized harvesting of the area consists of the structure of a module with a mobile unit consisting of a harvester and forwarder. The results indicated that wood transport presented the highest ES, both positive and negative. The most significant negative impacts (ES) were the depletion of water resources and erosion, while the positive impacts included regional development and job creation. The most notable changes, positive and negative, were observed in the physical and anthropic environment, with a lesser impact on the biotic environment. [ABSTRACT FROM AUTHOR]

Background Cytoscape is an open-source software to visualize and analyze networks. However, large networks, such as protein interaction networks, are still difficult to analyze as a whole. Methods Here, we propose Clust&See3.0, a novel version of a Cytoscape app that has been developed to identify, visualize and manipulate network clusters and modules. It is now enriched with functionalities allowing custom annotations of nodes and computation of their statistical enrichments. Results As the wealth of multi-omics data is growing, such functionalities are highly valuable for a better understanding of biological module composition, as illustrated by the presented use case. Conclusions In summary, the originality of Clust&See3.0 lies in providing users with a complete tool for network clusters analyses: from cluster identification, visualization, node and cluster annotations to annotation statistical analyses.

Behaviour, morphology and responses to stimuli in biological systems are determined by the genetic information of different types of biomolecules and the interactions between them. Comparative interactomics, the discipline devoted in comparing two or more interaction networks that happen in different species or under different cellular conditions, is a powerful tool for understanding systems evolution and the complex relationships that control cellular processes. This review provides an overview of data sources and research methods for comparative interactomics and the current directions in the application of comparative interactomics are summarised in brief. We also highlight the potential challenges of comparative interactomics in terms of interaction detection, noise delineation, alignment algorithms and quantitative network upgrading. We provide insights for future studies of network evolution using more accurate experimental and informative methodologies, with the hope that comparative interactomics to be further developed and build the study bridges from micromolecules to biological phenotypes.

Background Cytoscape is an open-source software to visualize and analyze networks. However, large networks, such as protein interaction networks, are still difficult to analyze as a whole. Methods Here, we propose Clust&See3.0, a novel version of a Cytoscape app that has been developed to identify, visualize and manipulate network clusters and modules. It is now enriched with functionalities allowing custom annotations of nodes and computation of their statistical enrichments. Results As the wealth of multi-omics data is growing, such functionalities are highly valuable for a better understanding of biological module composition, as illustrated by the presented use case. Conclusions In summary, the originality of Clust&See3.0 lies in providing users with a complete tool for network clusters analyses: from cluster identification, visualization, node and cluster annotations to annotation statistical analyses.

Simple Summary: This research aimed to identify, through an in silico approach using interaction networks, a potential biomarker associated with HPV 16 integration in cervical cancer. MAGI-1 was selected, and the expression profiles and changes in subcellular localization in cell lines and samples were evaluated in patients with premalignant lesions and invasive squamous carcinoma with HPV 16 in an integrated state. MAGI-1 is a potential biomarker that differentiates a normal cell with integrated HPV 16 from early cervical lesions. HPV 16 integration is crucial for the onset and progression of premalignant lesions to invasive squamous cell carcinoma (ISCC) because it promotes the amplification of proto-oncogenes and the silencing of tumor suppressor genes; some of these are proteins with PDZ domains involved in homeostasis and cell polarity. Through a bioinformatics approach based on interaction networks, a group of proteins associated with HPV 16 infection, PDZ domains, and direct physical interaction with E6 and related to different hallmarks of cancer were identified. MAGI-1 was selected to evaluate the expression profile and subcellular localization changes in premalignant lesions and ISCC with HPV 16 in an integrated state in cervical cytology; the profile expression of MAGI-1 diminished according to lesion grade. Surprisingly, in cell lines CaSki and SiHa, the protein localization was cytoplasmic and nuclear. In contrast, in histological samples, a change in subcellular localization from the cytoplasm in low-grade squamous intraepithelial lesions (LSIL) to the nucleus in the high-grade squamous intraepithelial lesion (HSIL) was observed; in in situ carcinomas and ISCC, MAGI-1 expression was absent. In conclusion, MAGI-1 expression could be a potential biomarker for distinguishing those cells with normal morphology but with HPV 16 integrated from those showing morphology-related uterine cervical lesions associated with tumor progression. [ABSTRACT FROM AUTHOR]

Promoting urban green spaces is an effective strategy to increase biodiversity in cities. However, our understanding of how local and landscape factors influence trophic interactions in these urban contexts remains limited. Here, we sampled cavity-nesting bees and wasps and their natural enemies within 85 urban gardens in Zurich (Switzerland) to identify factors associated with the diversity and dissimilarity of antagonistic interactions in these communities. The proportions of built-up area and urban green area at small landscape scales (50 m radius), as well as the management intensity, sun exposure, plant richness and proportion of agricultural land at the landscape scale (250 m radius), were key drivers of interaction diversity. This increased interaction diversity resulted not only from the higher richness of host and natural enemy species, but also from species participating in more interactions. Furthermore, dissimilarity in community structure and interactions across gardens (beta-diversity) were primarily influenced by differences in built-up areas and urban green areas at the landscape scale, as well as by management intensity. Our study offers crucial insights for urban planning and conservation strategies, supporting sustainability goals by helping to understand the factors that shape insect communities and their trophic interactions in urban gardens. [ABSTRACT FROM AUTHOR]

Bats are the second‐most diverse group of mammals in the world, and bat flies are their main parasites. However, significant knowledge gaps remain regarding these antagonistic interactions, especially since diverse factors such as seasonality and host sex can affect their network structures. Here, we explore the influence of such factors by comparing species richness and composition of bat flies on host bats, as well as specialization and modularity of bat–bat fly interaction networks between seasons and adult host sexes. We captured bats and collected their ectoparasitic flies at 10 sampling sites in the savannahs of Amapá State, northeastern region of the Brazilian Amazon. Despite female bats being more parasitized and recording greater bat fly species richness in the wet season, neither relationship was statistically significant. The pooled network could be divided into 15 compartments with 54 links, and all subnetworks comprised >12 compartments. The total number of links ranged from 27 to 48 (for the dry and wet seasons, respectively), and female and male subnetworks had 44 and 41 links, respectively. Connectance values were very low for the pooled network and for all subnetworks. Our results revealed higher bat fly species richness and abundance in the wet season, whereas specialization and modularity were higher in the dry season. Moreover, the subnetwork for female bats displayed higher specialization and modularity than the male subnetwork. Therefore, both seasonality and host sex contribute in different ways to bat–bat fly network structure. Future studies should consider these factors when evaluating bat–bat fly interaction networks. [ABSTRACT FROM AUTHOR]

Background Cytoscape is an open-source software to visualize and analyze networks. However, large networks, such as protein interaction networks, are still difficult to analyze as a whole. Methods Here, we propose Clust&See3.0, a novel version of a Cytoscape app that has been developed to identify, visualize and manipulate network clusters and modules. It is now enriched with functionalities allowing custom annotations of nodes and computation of their statistical enrichments. Results As the wealth of multi-omics data is growing, such functionalities are highly valuable for a better understanding of biological module composition, as illustrated by the presented use case. Conclusions In summary, the originality of Clust&See3.0 lies in providing users with a complete tool for network clusters analyses: from cluster identification, visualization, node and cluster annotations to annotation statistical analyses.

Abstract Background The caffeoyl-CoA-O methyltransferase (CCoAOMT) family plays a crucial role in the oxidative methylation of phenolic substances and is involved in various plant processes, including growth, development, and stress response. However, there is a limited understanding of the interactions among CCoAOMT protein members in tea plants. Results In this study, we identified 10 members of the CsCCoAOMT family in the genome of Camellia sinensis (cultivar ‘HuangDan’), characterized by conserved gene structures and motifs. These CsCCoAOMT members were located on six different chromosomes (1, 2, 3, 4, 6, and 14). Based on phylogenetic analysis, CsCCoAOMT can be divided into two groups: I and II. Notably, the CsCCoAOMT members of group Ia are likely to be candidate genes involved in lignin biosynthesis. Moreover, through the yeast two-hybrid (Y2H) assay, we established protein interaction networks for the CsCCoAOMT family, revealing 9 pairs of members with interaction relationships. Conclusions We identified the CCoAOMT gene family in Camellia sinensis and conducted a comprehensive analysis of their classifications, phylogenetic and synteny relationships, gene structures, protein interactions, tissue-specific expression patterns, and responses to various stresses. Our findings shed light on the evolution and composition of CsCCoAOMT. Notably, the observed interaction among CCoAOMT proteins suggests the potential formation of the O-methyltransferase (OMT) complex during the methylation modification process, expanding our understanding of the functional roles of this gene family in diverse biological processes.

Gut microbes play a vital role in the health and disease of animals, especially in relation to pathogen infections. Chinchillas, ferrets, and marmots are commonly used as important laboratory animals for infectious disease research. Here, we studied the bacterial and fungal microbiota and discovered that chinchillas had higher alpha diversity and a higher abundance of bacteria compared to marmots and ferrets by using the metabarcoding of 16S rRNA genes and ITS2, coupled with co-occurrence network analysis. The dominant microbes varied significantly among the three animal species, particularly in the gut mycobiota. In the ferrets, the feces were dominated by yeast such as Rhodotorula and Kurtzmaniella, while in the chinchillas, we found Teunomyces and Penicillium dominating, and Acaulium, Piromyces, and Kernia in the marmots. Nevertheless, the dominant bacterial genera shared some similarities, such as Clostridium and Pseudomonas across the three animal species. However, there were significant differences observed, such as Vagococcus and Ignatzschineria in the ferrets, Acinetobacter and Bacteroides in the chinchillas, and Bacteroides and Cellvibrio in the marmots. Additionally, our differential analysis revealed significant differences in classification levels among the three different animal species, as well as variations in feeding habitats that resulted in distinct contributions from the host microbiome. Therefore, our data are valuable for monitoring and evaluating the impacts of the microbiome, as well as considering potential applications. [ABSTRACT FROM AUTHOR]

Background: The caffeoyl-CoA-O methyltransferase (CCoAOMT) family plays a crucial role in the oxidative methylation of phenolic substances and is involved in various plant processes, including growth, development, and stress response. However, there is a limited understanding of the interactions among CCoAOMT protein members in tea plants. Results: In this study, we identified 10 members of the CsCCoAOMT family in the genome of Camellia sinensis (cultivar 'HuangDan'), characterized by conserved gene structures and motifs. These CsCCoAOMT members were located on six different chromosomes (1, 2, 3, 4, 6, and 14). Based on phylogenetic analysis, CsCCoAOMT can be divided into two groups: I and II. Notably, the CsCCoAOMT members of group Ia are likely to be candidate genes involved in lignin biosynthesis. Moreover, through the yeast two-hybrid (Y2H) assay, we established protein interaction networks for the CsCCoAOMT family, revealing 9 pairs of members with interaction relationships. Conclusions: We identified the CCoAOMT gene family in Camellia sinensis and conducted a comprehensive analysis of their classifications, phylogenetic and synteny relationships, gene structures, protein interactions, tissue-specific expression patterns, and responses to various stresses. Our findings shed light on the evolution and composition of CsCCoAOMT. Notably, the observed interaction among CCoAOMT proteins suggests the potential formation of the O-methyltransferase (OMT) complex during the methylation modification process, expanding our understanding of the functional roles of this gene family in diverse biological processes. [ABSTRACT FROM AUTHOR]

Logical modeling is a powerful tool in biology, offering a system-level understanding of the complex interactions that govern biological processes. A gap that hinders the scalability of logical models is the need to specify the update function of every vertex in the network depending on the status of its predecessors. To address this, we introduce in this paper the concept of strong regulation, where a vertex is only updated to active/inactive if all its predecessors agree in their influences; otherwise, it is set to ambiguous. We explore the interplay between active, inactive, and ambiguous influences in a network. We discuss the existence of phenotype attractors in such networks, where the status of some of the variables is fixed to active/inactive, while the others can have an arbitrary status, including ambiguous. [ABSTRACT FROM AUTHOR]

Stingless bees are important pollinators in tropical forests. Yet, we know little about their foraging behavior (e.g., their nutritional requirements or their floral sources visited for resource collection). Many stingless bees not only depend vitally on pollen and nectar for food but also on resin for nest building and/or defense. However, it is unclear whether the large effort devoted to collecting resin as a non‐food resource by certain stingless bees affects their foraging behavior. Therefore, in this study, we analyzed differences in foraging patterns (i.e., foraging activity, proportion of collected resources, and specialization in plants visited) and resource nutritional composition (i.e., sucrose amount in nectar and amino acids in pollen) of seven different stingless bee species (eleven wild colonies) in north‐western Ecuador with a particular focus on the role of resin collection. We found that species with a high resin intake tended to be more active than species with a low resin intake. The foragers per minute invested for pollen collection were similar across all species. Sucrose intake per minute differed between some species but was not affected by increased resin intake. Interestingly, high and low resin collectors partly differed in the plants visited for pollen collection. Pollen amino acid profiles largely, but not completely, overlapped between the two resin collection groups. Our findings show that the foraging patterns and plant choices of stingless bees may vary depending on their resin intake, highlighting the need for more research focusing on resin collection and use by stingless bees. [ABSTRACT FROM AUTHOR]

Participants in mixed-species bird flocks (MSFs) have been shown to associate with species that are similar in body size, diet, and evolutionary history, suggesting that facilitation structures these assemblages. In addition, several studies have suggested that species in MSFs resemble each other in their plumage, but this question has not been systematically investigated for any MSF system. During the nonbreeding season of 2020 and 2021, we sampled 585 MSFs on 14 transects in 2 habitats of Tongbiguang Nature Reserve in western Yunnan Province, China. We performed social network analysis and the Multiple Regression Quadratic Assignment Procedure to evaluate the effect of 4 species traits (body size, overall plumage color, distinctive plumage patterns, and diet) and evolutionary history on species association strength at the whole-MSF and within-MSF levels. All 41 significant relationships showed that species with stronger associations were more similar in their various traits. Body size had the strongest effect on association strength, followed by phylogeny, plumage patterns, and plumage color; diet had the weakest effect. Our results are consistent with the hypotheses that the benefits of associating with phenotypically similar species outweigh the potential costs of interspecific competition, and that trait matching can occur in plumage characteristics, albeit more weakly than in other traits. Several explanations exist as to why similarities in plumage may occur in MSFs, including that they could reduce predators' ability to target phenotypically "odd" individuals. Whether trait matching in plumage occurs through assortative processes in ecological time or is influenced by co-evolution requires further study. [ABSTRACT FROM AUTHOR]

Urban areas act as important shelters to support bee populations, but some guilds, such as generalist species, benefit more than others. We aimed to investigate if the floral preferences of a polylectic species would change throughout the years and if gardening practices such as mowing could affect the females’ floral preferences and, thus, the bee-plant interaction networks in an urban area within a medium- sized city in Brazil. Nesting females of Pseudaugochlora graminea (Fabricius) (Halictidae) were collected and had the pollen grains attached to their scopae removed, acetolyzed, and identified in two different periods: March 2019 and March 2022. Only five plant species were identified in samples from 2019, while 13 species were detected in 2022 despite mowing and plant replacements throughout three years. Among the floral sources observed, both exotic and native species were visited by females for pollen and nectar collection. Despite being a generalist species, all interaction networks between P. graminea females and plant species were highly specialized. Females concentrated their pollen gathering on a few plant species, represented by less than ten individuals in the study area. Mowing led to the destruction of the third most important pollen source in 2019. However, plant replacements may have favored females by some nectar sources seedlings. Our findings demonstrate that gardening practices impacted the floral choices of females of a generalist bee species, whose females established highly specialized interaction networks with plants in an urban area.

Abstract Since its inception, the keystone species concept has become a central theoretical framework in ecology. Among many approaches, keystones have been operationalized in natural and human environments using centrality metrics applied to monolayer networks. Despite the great success of this approach, as species make several types of interactions, recent studies on keystones moved from monolayer to multilayer networks. To help fulfil the need for a centrality metric designed for multilayer networks, here we introduce Gnorm. We tested the performance of our new metric using in silico data in addition to an empirical data set of frugivory and nectarivory interactions between bats and plants in the Neotropics. A comparison between the results obtained with different random and scale‐free networks demonstrates the performance of our new metric. First, a modularity analysis based on the multilayer version of the Louvain algorithm enables the modules to be composed of nodes from different layers. Second, by setting the coupling parameter (ω) and the resolution parameter (γ), module identity changes gradually, from single‐ to multiple‐node modules and from mono‐ to multilayer composition. Third, we check the number of modules from different layers to which a node belongs (G) at different levels of ω and γ. Finally, by observing how average G decreases with ω and γ, it is possible to calculate Gnorm and detect which nodes are most resistant to change in these two parameters. Those resistant nodes are identified as central in the multilayer structure. After applying this new analysis to the bat–plant network, we observed that it identified a different set of potential keystone species compared to previous analyses performed separately for each layer or the aggregated network. In conclusion, our new metric opens a new way of operationalizing the keystone species concept in multilayer networks. It may help identify keystone species involved in different interaction types.

Beyond abiotic conditions, do population dynamics mostly depend on a species' direct predators, preys and conspecifics? Or can indirect feedback that ripples across the whole community be equally important? Determining where ecological communities sit on the spectrum between these two characterizations requires a metric able to capture the difference between them. Here we show that the spectral radius of a community's interaction matrix provides such a metric, thus a measure of ecological collectivity, which is accessible from imperfect knowledge of biotic interactions and related to observable signatures. This measure of collectivity integrates existing approaches to complexity, interaction structure and indirect interactions. Our work thus provides an original perspective on the question of to what degree communities are more than loose collections of species or simple interaction motifs and explains when pragmatic reductionist approaches ought to suffice or fail when applied to ecological communities. [ABSTRACT FROM AUTHOR]

Amyloid transthyretin (ATTR) amyloidosis caused by transthyretin misfolded into amyloid deposits in nerve and heart is a progressive rare disease. The unknown pathogenesis and the lack of therapy make the 5-year survival prognosis extremely poor. Currently available ATTR drugs can only relieve symptoms and slow down progression, but no drug has demonstrated curable effect for this disease. The growing volume of pharmacological data and large-scale genome and transcriptome data bring new opportunities to find potential new ATTR drugs through computational drug repositioning. We collected the ATTR-related in the disease pathogenesis and differentially expressed (DE) genes from five public databases and Gene Expression Omnibus expression profiles, respectively, then screened drug candidates by a corrected protein–protein network analysis of the ATTR-related genes as well as the drug targets from DrugBank database, and then filtered the drug candidates on the basis of gene expression data perturbed by compounds. We collected 139 and 56 ATTR-related genes from five public databases and transcriptome data, respectively, and performed functional enrichment analysis. We screened out 355 drug candidates based on the proximity to ATTR-related genes in the corrected interactome network, refined by graph neural networks. An Inverted Gene Set Enrichment analysis was further applied to estimate the effect of perturbations on ATTR-related and DE genes. High probability drug candidates were discussed. Drug repositioning using systematic computational processes on an interactome network with transcriptome data were performed to screen out several potential new drug candidates for ATTR. [ABSTRACT FROM AUTHOR]

Since its inception, the keystone species concept has become a central theoretical framework in ecology. Among many approaches, keystones have been operationalized in natural and human environments using centrality metrics applied to monolayer networks. Despite the great success of this approach, as species make several types of interactions, recent studies on keystones moved from monolayer to multilayer networks.To help fulfil the need for a centrality metric designed for multilayer networks, here we introduce Gnorm. We tested the performance of our new metric using in silico data in addition to an empirical data set of frugivory and nectarivory interactions between bats and plants in the Neotropics. A comparison between the results obtained with different random and scale‐free networks demonstrates the performance of our new metric.First, a modularity analysis based on the multilayer version of the Louvain algorithm enables the modules to be composed of nodes from different layers. Second, by setting the coupling parameter (ω) and the resolution parameter (γ), module identity changes gradually, from single‐ to multiple‐node modules and from mono‐ to multilayer composition. Third, we check the number of modules from different layers to which a node belongs (G) at different levels of ω and γ. Finally, by observing how average G decreases with ω and γ, it is possible to calculate Gnorm and detect which nodes are most resistant to change in these two parameters. Those resistant nodes are identified as central in the multilayer structure. After applying this new analysis to the bat–plant network, we observed that it identified a different set of potential keystone species compared to previous analyses performed separately for each layer or the aggregated network.In conclusion, our new metric opens a new way of operationalizing the keystone species concept in multilayer networks. It may help identify keystone species involved in different interaction types. [ABSTRACT FROM AUTHOR]

The Diannong River, a valuable river and lake resource of the northern Ningxia Yellow River Irrigation Area, plays an instrumental role in regional flood control, drought resistance, climate regulation, and biodiversity conservation. Phytoplankton and zooplankton, as crucial elements of the aquatic ecosystem, have their distribution patterns evaluated and potential influencing factors identified, thereby enhancing the understanding of community distribution patterns. Nested structures and interspecies interaction relationships bear significant implications for community distribution patterns, functions, and stability. The upstream section of the Diannong River in Yinchuan City was chosen as the study object. Water samples were collected in January, April, July, and October 2021, and the community composition of phytoplankton and zooplankton was analyzed using relative abundance, density, and biomass. The distribution matrix temperature and bipartite network methodologies were deployed to investigate their nested pattern and interaction network seasonal characteristics. The findings indicate that the water environment of the Diannong River's upstream section displays pronounced spatiotemporal heterogeneity, characterized by weak alkalinity and high fluoride content. The plankton community composition and relative abundance showed marked differences among the distinct sampling periods. The temperature of the random distribution matrix shows a significant difference compared to the zero-sum model, revealing a notable nested pattern in plankton in the Diannong River's upstream section. The bipartite network suggests that the plankton composition was the simplest in January and the most complex in July, with the fiercest species competition observed in January and the lowest levels of species specificity, vulnerability, and generality. Water temperature (WT), dissolved oxygen (DO), total phosphorus (TP), available phosphorus (AP), CODCr, F−, and Cl− constitute the environmental parameters influencing the overall structure of the phytoplankton community in the Diannong River's upstream section, whereas zooplankton did not present a significant correlation with water environmental factors. [ABSTRACT FROM AUTHOR]

Budapesten kora rézkori temetkezések csak településekről vagy elszórtan ismertek. Jelenleg egyedülálló a XVII. ker. Rákoscsaba-Majorhegy, észak lelőhelyen előkerült több sírt magában foglaló, önálló temetkezési hely. A temetkezések két területileg is elkülönülő csoportot alkotnak, közöttük a mellékletadásban és a halottakkal való bánásmódban is eltérések mutatkoznak. E jelenség mögött a térség összekötő és közvetítő szerepe, de társadalmi, identitás béli tényezők is meghúzódhatnak. Early Copper Age burials in the territory of Budapest had primarily been known from the contemporary settlements or were discovered as lone graves. The burial ground investigated at Rákoscsaba, Major-hegy north, in Budapest, District XVII., consisting of several inhumations is still unique in this regard. The discovered graves formed two separate groups; this spatial distinction was also reflected by the treatment of the deceased and the variety of grave goods present at the site. The distinction between burials could be explained either by the location and the role the site played in the network of interactions, or by social, economic factors, but it may also be considered as expressions of local identities. [ABSTRACT FROM AUTHOR]

Aim: As species' ranges shift poleward in response to anthropogenic change, they may lose antagonistic interactions if they move into less diverse communities, fail to interact with novel populations or species effectively, or if ancestral interacting populations or species fail to shift synchronously. We leveraged a poleward range expansion in a tractable insect host–enemy community to uncover mechanisms by which altered antagonistic interactions between native and recipient communities contributed to 'high niche opportunities' (limited biotic resistance) for a range‐expanding insect. Location: North America, Pacific Northwest. Methods: We created quantitative insect host–enemy interaction networks by sampling oak gall wasps on 400 trees of a dominant oak species in the native and expanded range of a range‐expanding gall wasp species. We compared host–enemy network structure between regions. We measured traits (phenology, morphology) of galls and interacting parasitoids, predicting greater trait divergence in the expanded range. We measured function relating to host control and explored if altered interactions and traits contributed to reduced function, or biotic resistance. Results: Interaction networks had fewer species in the expanded range and lower complementarity of parasitoid assemblages among host species. While networks were more generalized, interactions with the range‐expanding species were more specialized in the expanded range. Specialist enemies effectively tracked the range‐expanding host, and there was reduced apparent competition with co‐occurring hosts by shared generalist enemies. Phenological divergence of enemy assemblages interacting with the range‐expanding and co‐occurring hosts was greater in the expanded range, potentially contributing to weak apparent competition. Biotic resistance was lower in the expanded range, where fewer parasitoids emerged from galls of the range‐expanding host. Main Conclusions: Changes in interactions with generalist enemies created high niche opportunities, and limited biotic resistance, suggesting weak apparent competition may be a mechanism of enemy release for range‐expanding insects embedded within generalist enemy networks. [ABSTRACT FROM AUTHOR]

The current biodiversity crisis requires efficient approaches to address the ongoing impoverishment of natural communities and the depletion of ecosystem services and functions. In this sense, identifying key species that promote the functioning of ecological processes can be strategic to guide actions aiming at the conservation and restoration of biodiversity. Node‐level metrics in interaction networks can be helpful to identify those key species, as they measure the role each species plays in organizing the interactions. Moreover, ecological correlates of species structural roles may vary between local and global networks of interactions, reflecting distinct mechanisms acting at different spatial scales. By studying local seed dispersal networks and one global meta‐network combining those local networks, Moulatlet et al. identified the most important traits explaining bird species centrality at varying spatial scales. They found that body mass was the main trait explaining centrality at the local scale, whereas range size was the main predictor of species centrality at the global scale. In this contribution, besides assessing local interaction networks, Moulatlet et al. adopt a biogeographical perspective to seed dispersal systems, extending our knowledge about the possible mechanisms that underlie the organization of interacting assemblages when changing the spatial scale of observation. Future efforts on this field could include an intermediate scale, comprising the level of metacommunities, shedding light on the interplay between local and spatial processes, both embedded in biogeographical realms, when determining the organization of interactions and the ecological correlates of species roles. [ABSTRACT FROM AUTHOR]

In the present study, we investigated the effect of habitat heterogeneity, elevation gradient, and phylogenetic distance of host species on the abundance and richness of anuran endoparasites, assuming that parasites follow the distribution of their hosts independently of environmental variation. We collected 192 anurans distributed in three altitude ranges: 100–200 m, 400–500 m, and 700–800 m. We performed discriminant principal component analysis to analyze the interrelationships between environmental heterogeneity and the distribution of parasite and host species in the formation of species groups in each altitude range. We estimated the niche width and parasite overlap, using host species as a variable, and assessed whether parasite abundance is more influenced by historical (distance host phylogeny) or ecological effects in each altitude category and overall. Finally, we use network analyses to understand how interactions between parasites and hosts are formed along the altitude gradient. We found 22 parasite species, and the overall prevalence of infection was 74%. In our study, we did not identify environmental (altitude gradients and heterogeneity) or phylogenetic effects acting on the parasite species diversity. Overall, our results suggest that the parasites are distributed following the dispersal of their hosts and are dispersed among most anuran species. [ABSTRACT FROM AUTHOR]

Moral foundations theory proposes that individuals with conflicting political views base their behavior on different principles chosen from a small group of universal moral foundations. This study proposes using a set of widely accepted moral foundations (fairness, in-group loyalty, authority, and purity) as proxies to determine the degree of radicalization of online communities. A fifth principle, care, is generally surpassed by others that are higher in the radicalized groups’ moral hierarchy. Moreover, the presented data-driven methodological framework proposes an alternative way to measure whether a community complies with a certain moral principle or foundation: not evaluating its speech, but its behavior through the interactions of its individuals, establishing a bridge between the structural features of the interaction network and the intensity of communities’ radicalization regarding the considered moral foundations. Two foundations were assessed using the network’s structural characteristics: in-group loyalty measured by group-level modularity, and authority evaluated using group domination, for detecting potential hierarchical substructures within the network. By analyzing a set of Pareto-optimal groups regarding a multidimensional moral relevance scale, the most radicalized communities were identified among those considered extreme in some of their attitudes or views. An application of the proposed framework is illustrated using real-world datasets. The radicalized communities’ behavior exhibited increasing isolation, and their authorities and leaders showed growing domination over their audience. Differences were also detected between users’ behavior and speech, showing that individuals tended to share more “extreme” in-group content than they publish: extreme views get more likes on social media.

The extracellular-matrix (ECM) is a complex interconnected three-dimensional network that provides structural support for the cells and tissues and defines organ architecture as key for their healthy functioning. However, the intimate mechanisms by which ECM acquire their three-dimensional architecture are still largely unknown. In this paper, we study this question by means of a simple three-dimensional individual based model of interacting fibres able to spontaneously crosslink or unlink to each other and align at the crosslinks. We show that such systems are able to spontaneously generate different types of architectures. We provide a thorough analysis of the emerging structures by an exhaustive parametric analysis and the use of appropriate visualization tools and quantifiers in three dimensions. The most striking result is that the emergence of ordered structures can be fully explained by a single emerging variable: the number of links per fibre in the network. If validated on real tissues, this simple variable could become an important putative target to control and predict the structuring of biological tissues, to suggest possible new therapeutic strategies to restore tissue functions after disruption, and to help in the development of collagen-based scaffolds for tissue engineering. Moreover, the model reveals that the emergence of architecture is a spatially homogeneous process following a unique evolutionary path, and highlights the essential role of dynamical crosslinking in tissue structuring.

Listeria monocytogenes is a Gram positive foodborne pathogen that regularly causes outbreaks of systemic infectious diseases. The bacterium maintains a facultative intracellular lifestyle; it thrives under a variety of environmental conditions and is able to infect human host cells. L. monocytogenes is genetically tractable and therefore has become an attractive model system to study the mechanisms employed by facultative intracellular bacteria to invade eukaryotic cells and to replicate in their cytoplasm. Besides its importance for basic research, L. monocytogenes also serves as a paradigmatic pathogen in genomic epidemiology, where the relative stability of its genome facilitates successful outbreak detection and elucidation of transmission chains in genomic pathogen surveillance systems. In both terms, it is necessary to keep the annotation of the L. monocytogenes genome up to date. Therefore, we have created the database ListiWiki (http://listiwiki.uni-goettingen.de/) which stores comprehensive information on the widely used L. monocytogenes reference strain EDG-e. ListiWiki is designed to collect information on genes, proteins and RNAs and their relevant functional characteristics, but also further information such as mutant phenotypes, available biological material, and publications. In its present form, ListiWiki combines the most recent annotation of the EDG-e genome with published data on gene essentiality, gene expression and subcellular protein localization. ListiWiki also predicts protein-protein interactions networks based on protein homology to Bacillus subtilis proteins, for which detailed interaction maps have been compiled in the sibling database SubtiWiki. Furthermore, crystallographic information of proteins is made accessible through integration of Protein Structure Database codes and AlphaFold structure predictions. ListiWiki is an easy-to-use web interface that has been developed with a focus on an intuitive access to all information. Use of ListiWiki is free of charge and its content can be edited by all members of the scientific community after registration. In our labs, ListiWiki has already become an important and easy to use tool to quickly access genome annotation details that we can keep updated with advancing knowledge. It also might be useful to promote the comprehensive understanding of the physiology and virulence of an important human pathogen.

Aim: Most biodiversity studies have considered species to be isolated entities, neglecting the fact that their biotic interactions and spatial variation are fundamental to their persistence across elevational gradients. Here, using a standardized sampling methodology, we evaluated how and why the composition of flower–visitor interactions (i.e. beta diversity) varies over an extensive elevational gradient. Specifically, we aimed to identify which biotic (species turnover) and abiotic factors (temperature, precipitation and primary productivity) inherent to elevational gradients can explain the distribution of floral visitor–plant interactions. Location: Mexican Transition Zone. Taxon: Angiosperms, Hymenoptera, Lepidoptera, Diptera, Hemiptera and Coleoptera. Methods: We sampled ecological interactions between floral visitors and flowering plants at 10 sites along an elevational gradient from 4 to 3425 m.a.s.l. We measured the additive partitioning of the beta diversity of species interactions and used generalized dissimilarity modelling to assess how spatial and environmental factors can explain the observed dissimilarity. Results: We found that the composition of interactions between floral visitors and plant species differs from lowlands to highlands mainly due to differences in temperature across the studied elevation gradient, rather than geographical distance or other environmental factors (i.e. mean annual precipitation and net primary productivity). We also observed that the main component of the beta diversity of interactions was interaction turnover driven by the turnover of both plants and floral visitors along the elevation gradient studied, which may be influenced by both temperature and the biogeographical affinity of biotas. Main Conclusions: We conclude that environmental filters play a crucial role in the establishment of novel interactions, as temperature can filter species and impact the behaviour and traits of floral visitors and plants across an elevational gradient. These findings underscore the importance of considering the role of abiotic factors in predicting and explaining the distribution of species interactions across different elevational gradients. [ABSTRACT FROM AUTHOR]

We present a framework called the Reasoning Engine, which implements Satisfiability Modulo Theories (SMT)-based methods within a unified computational environment to address diverse biological analysis problems. The Reasoning Engine was used to reproduce results from key scientific studies, as well as supporting new research in stem cell biology. The framework utilizes an intermediate language for encoding partially specified discrete dynamical systems, which bridges the gap between high-level domain-specific languages and low-level SMT solvers. We provide this framework as open source together with various biological case studies, illustrating the synthesis, enumeration, optimization, and reasoning over models consistent with experimental observations to reveal novel biological insights. [ABSTRACT FROM AUTHOR]

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Frugivory and seed dispersal by fish is an important mutualistic interaction in complex and species-rich tropical rivers. The local ecological knowledge (LEK) held by fishers can provide new information on relationships between fishes and plants in less studied rivers. This study aims to investigate the feeding interactions between frugivorous fish and plants through interaction networks based on the fishers' LEK in three rivers in the Brazilian Amazon (Negro, Tapajós and Tocantins). A total of 418 fishers were interviewed in 24 communities (eight in each river). The studied fishes were tambaqui (Colossoma macropomum), matrinxã (Brycon spp.), pacu (Myloplus spp.), pacu manteiga (Mylossoma duriventre), pirapitinga (Piaractus brachypomus), and jaraqui (Semaprochilodus spp.). The interviewed fishers cited a total of 92 plants consumed by the six frugivorous fishes in the three rivers. The interaction networks showed a higher nestedness in the Tocantins, greater connectance and modularity in the Tapajós and more specialization in the Negro, where the protected areas may have contributed to a more complex and specialized interaction network. The more nested network in the Tocantins River indicated the loss of specialized interactions in disturbed communities. The Tapajós River network showed the highest number of interactions between fish and plants, but this river has been threatened by environmental changes. Fishers' LEK associated to network analyses can advance our understanding on ecological interactions. This approach can be also useful to evaluate and mitigate ecological effects from anthropic changes in the Amazon and other high diverse tropical rivers. [ABSTRACT FROM AUTHOR]

Arbuscular mycorrhizas are one of the most frequent mutualisms in terrestrial ecosystems. Although studies on plant mutualistic interaction networks suggest that they may leave their imprint on plant community structure and dynamics, this has not been explicitly assessed. Thus, in the context of plant‐fungi interactions, studies explicitly linking plant‐mycorrhizal fungi interaction networks with key ecological functions of plant communities, such as recruitment, are lacking.In this study, we analyse, in two Mediterranean forest communities of southern Iberian Peninsula, how plant‐arbuscular mycorrhizal fungi (AMF) networks modulate plant‐plant recruitment interaction networks. We use a new approach integrating plant‐AMF and plant recruitment networks into a single multilayer structure. We also develop a new metric (Interlayer Node Neighbourhood Integration, INNI) to explore the impact of a given node on the structure across layers.The similarity of plant species in their AMF communities is positively related to the observed frequency of recruitment interactions in the field. Results reveal that properties of plant‐AMF networks, such as plant degree and centrality, can explain about the properties of plant recruitment network, such as in‐ and out‐degree (i.e. sapling bank and canopy service) and its modular structure. However, these relationships differed between the two forest communities. Finally, we identify particular AMF that contribute to integrate the neighbourhood of recruitment interactions between plants.This multilayer network approach is useful to explore the role of plant‐AMF interactions on recruitment, a key ecosystem function enhanced by fungi. Results provide evidence that the complex structure of plant‐AMF interactions impacts functional and structurally plant‐plant interactions, which in turn may potentially influence plant community dynamics, through their effects on the structure of the recruitment network. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Citizen science has the potential to increase the efficiency of scientific data collection. However, such initiatives often focus on unique taxa for each record, not necessarily involving interspecific interactions. Moreover, whether openly available unstructured citizen science data can contribute to better understand ecological patterns is still not well understood. Here, we identify hummingbird-plant interactions recorded by amateur birdwatchers in the most popular online platform in Brazil, Wikiaves. Then, we evaluated how this information can benefit our understanding of interactions in a large Tropical country by comparing with data generated by experts. We also constructed a nation-wide meta-network to identify the structural roles of hummingbirds and plants. In total, 3210 interactions were compiled, with better hummingbirds and geographic coverage of citizen data in relation to expert data. The interaction network showed a modular pattern, and some plant species found as most frequently interacting here were similar to those found by experts. Nevertheless, when comparing the plant partners for hummingbirds featured in both expert and citizen data, the proportion of plants in common were generally low (usually less than 40%), indicating that amateur birdwatchers are mostly recording interactions not captured by scientists. Finally, as in other cases of compilation of interaction data, we found that sampling intensity (here, number of photographs) is a strong driver of interaction records, highlighting the unique challenge of separating biologically meaningful patterns from sampling artifacts in citizen science data. Our study illustrates the richness of citizen-gathered biodiversity data available in a megadiverse country, which show great potential to complement expert collected data.

Liver cancer is a high mortality cancer, and its increasing prevalence is a concern worldwide. Current treatment modalities for liver cancer include chemotherapy and immunotherapy. These therapies provide symptomatic relief and help prolong the lives of patients but are not an absolute cure. In this paper we have explored an alternative approach, drug repurposing, to identify drugs for treating liver cancer. Databases like PubMed, ScienceDirect, and JSTOR were used for literature mining, and the PRISMA 2020 systemic review guidelines were followed to identify drugs that have been trialed for repurposing in liver cancer. The protein receptors and target protein classes of all the drugs were identified using the Swiss Target Prediction tool. Further, the biological interactions and pathways followed by the drugs were studied via protein interaction networks using Cytoscape. Molecular pathways such as Bile acid receptor activity, Inosine-5′-monophosphate (IMP) dehydrogenase activity, JUN kinase activity, Nitric-oxide synthase activity, and Mitogen-activated protein (MAP) kinase activity were observed to be influenced by these drugs. The fact that the genes targeted by these repurposed drugs are common with the differentially expressed genes in liver cancer is an excellent starting point to verify the current hypothesis.

The emergence of graph theory allowed using the complex network approach to aggregate detailed information about interactions between species. Although the use of the complex network approach has improved the understanding about community structuring, few aspects such as the temporal variation in the species’ activity pattern in the networks’ topology were explored so far. The current study used the ecological network approach to investigate ants interacting in the extrafloral nectary (EFN) of plants in order to test the hypothesis that the temporal variation in the foraging behavior of these animals affects the networks’ topology. In order to assess the temporal effect on the interaction networks, 24-hour collections divided in two 12-hour shifts (day and night) were performed in 20 plots, thus totaling 288 collection hours over 6 months. The ant-plant interaction networks presented similarity among the topological metrics assessed throughout the day. Different ant species presented distinct foraging times. Thus, two modules referring to the day and night shifts emerged from the network and presented specific species at each foraging shift. On the other hand, the plants kept on providing the resource (active EFNs) throughout the day. The results found in the current study have shown that ecological networks keep their structures constant; however, the ecological processes ruling these networks can better respond to the effects caused, for example, by the temporal variation in species’ activity. Therefore, it is worth always taking into consideration the importance of ecological processes at the time to analyze interactions in the nature.

It is not clear if mature secondary growth coniferous forests can support similar pollinator communities as old growth coniferous forests, or how active management (e.g., retention forestry) in mature secondary growth forests may affect pollinator communities. We compare the native bee community and plant‐bee interaction networks of old growth, naturally regenerating and actively managed (retention forestry) mature secondary growth forests of similar stand age. Old growth forests had a higher bee species richness and Shannon's diversity index, but not Simpson's diversity index, than both actively managed and naturally regenerating mature secondary forests. Forest type (old‐growth, naturally regenerating mature secondary growth, and actively managed mature secondary growth) had a significant effect on bee community composition. Redwood forest bee‐plant interaction networks were small in size and had lower complexity than expected and few connector species. While studies suggest that small‐scale timber harvest may increase bee biodiversity in the short‐term in other coniferous forest habitats, our study suggests that there may be long‐term negative effects of clear‐cutting that lower bee biodiversity in mature secondary growth forests as compared to mature old‐growth forests. [ABSTRACT FROM AUTHOR]

Flower‐vising bats are important components of tropical pollinator communities, yet little is known about the structure of their pollination networks and how resource availability through time (seasons) and space (habitat heterogeneity) affects the extent to which bats interact with plants within a community‐wide context. This information is key for the conservation of threatened nectarivore species, such as the Cerrado‐endemic Lonchophylla dekeyseri, for which data on its specialization on floral‐resources is scarce.Within a seasonal and heterogeneous savanna in the central Brazilian Cerrado, we performed a year‐round assessment of an inclusive assemblage of flower‐visiting bats (both nectarivores and other guilds that can also feed on nectar) within a savanna‐edge‐forest gradient, the phenological trends and spatial distribution of bat and their resource plants, and the resultant temporal and spatial interaction networks between bats and plants in order to associate network structure to resource availability.Clear spatiotemporal trends emerged in the community. Nectarivores dominated the flower‐visiting niche outside forests and were prolific floral visitors, resulting in networks with lower specialization and modularity. These bats diverged into savanna foragers active during the wet season and the wet‐dry transition, and edge foragers active mostly during the dry season. The latter group encompassed L. dekeyseri, which visited mostly Bauhinia species. Frugivores took over as main floral visitors within forests, as well as during peak dry season, when fewer fruits were available, resulting in more specialized and modular networks.Our work shows that the turnover of floral resources across seasons and vegetation types has a defining role in bat–plant interactions and relates to network structure, as bat trophic guilds interact with plants in distinct habitats and times of the year. Frugivores dominate the flower‐visiting niche in certain temporal and spatial subsets of the network, which calls for the inclusion of this guild in future studies. Moreover, the high visitation to Bauhinia species by L. dekeyseri during the dry season might reduce competition with other nectarivores and is relevant to the management of the species, although more data is needed on its resource consumption on a larger time frame and across its geographic range. [ABSTRACT FROM AUTHOR]