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Biological invasions are a major threat to biodiversity and as such understanding their impacts is a research priority. Ecological networks provide a valuable tool to explore such impacts at the community level, and can be particularly insightful for planning and monitoring biocontrol programmes, including the potential for their seldom evaluated indirect non-target effects. Acacia longifolia is among the worst invasive species in Portugal, and has been recently targeted for biocontrol by a highly specific gall-wasp. Here we use an ambitious replicated network approach to: (1) identify the mechanisms by which direct and indirect impacts of A. longifolia can cascade from plants to higher trophic levels, including gallers, their parasitoids and inquilines; (2) reveal the structure of the interaction networks between plants, gallers, parasitoids and inquilines before the biocontrol; and (3) explore the potential for indirect interactions among gallers, including those established with the biocontrol agent, via apparent competition. Over a 15-month period, we collected 31,737 galls from native plants and identified all emerging insects, quantifying the interactions between 219 plant-, 49 galler-, 65 parasitoid- and 87 inquiline-species—one of the largest ecological networks to date. No galls were found on any of the 16 alien plant species. Invasion by A. longifolia caused an alarming simplification of plant communities, with cascading effects to higher trophic levels, namely: a decline of overall gall biomass, and on the richness, abundance and biomass of galler insects, their parasitoids, and inquilines. Correspondingly, we detected a significant decline in the richness of interactions between plants and galls. The invasion tended to increase overall interaction evenness by promoting the local extinction of the native plants that sustained more gall species. However, highly idiosyncratic responses hindered the detection of further consistent changes in network topology. Predictions of indirect effects of the biocontrol on native gallers via apparent competition ranged from negligible to highly significant. Such scenarios are incredibly hard to predict, but even if there are risks of indirect effects it is critical to weigh them carefully against the consequences of inaction and invasive species spread.

Gene tree discordance in large genomic data sets can be caused by evolutionary processes such as incomplete lineage sorting and hybridization, as well as model violation, and errors in data processing, orthology inference, and gene tree estimation. Species tree methods that identify and accommodate all sources of conflict are not available, but a combination of multiple approaches can help tease apart alternative sources of conflict. Here, using a phylotranscriptomic analysis in combination with reference genomes, we test a hypothesis of ancient hybridization events within the plant family Amaranthaceae s.l. thatwas previously supported bymorphological, ecological, and Sanger-based molecular data. The data set included seven genomes and 88 transcriptomes, 17 generated for this study. We examined gene-tree discordance using coalescent-based species trees and network inference, gene tree discordance analyses, site pattern tests of introgression, topology tests, synteny analyses, and simulations. We found that a combination of processes might have generated the high levels of gene tree discordance in the backbone of Amaranthaceae s.l. Furthermore, we found evidence that three consecutive short internal branches produce anomalous trees contributing to the discordance. Overall, our results suggest that Amaranthaceae s.l. might be a product of an ancient and rapid lineage diversification, and remains, and probably will remain, unresolved. This work highlights the potential problems of identifiability associated with the sources of gene tree discordance including, in particular, phylogenetic network methods. Our results also demonstrate the importance of thoroughly testing for multiple sources of conflict in phylogenomic analyses, especially in the context of ancient, rapid radiations. We provide several recommendations for exploring conflicting signals in such situations.

1. Most plant–pollinator network studies are conducted at species level, whereas little is known about network patterns at the individual level. In fact, nodes in traditional species-based interaction networks are aggregates of individuals establishing the actual links observed in nature. Thus, emergent properties of interaction networks might be the result of mechanisms acting at the individual level. 2. Pollen loads carried by insect flower visitors from two mountain communities were studied to construct pollen–transport networks. For the first time, these community-wide pollen–transport networks were downscaled from species–species (sp–sp) to individuals–species (i–sp) in order to explore specialization, network patterns and niche variation at both interacting levels. We used a null model approach to account for network size differences inherent to the downscaling process. Specifically, our objectives were (i) to investigate whether network structure changes with downscaling, (ii) to evaluate the incidence and magnitude of individual specialization in pollen use and (iii) to identify potential ecological factors influencing the observed degree of individual specialization. 3. Network downscaling revealed a high specialization of pollinator individuals, which was masked and unexplored in sp–sp networks. The average number of interactions per node, connectance, interaction diversity and degree of nestedness decreased in i–sp networks, because generalized pollinator species were composed of specialized and idiosyncratic conspecific individuals. An analysis with 21 pollinator species representative of two communities showed that mean individual pollen resource niche was only c. 46% of the total species niche. 4. The degree of individual specialization was associated with inter- and intraspecific overlap in pollen use, and it was higher for abundant than for rare species. Such niche heterogeneity depends on individual differences in foraging behaviour and likely has implications for community dynamics and species stability. 5. Our findings highlight the importance of taking interindividual variation into account when studying higher-order structures such as interaction networks. We argue that exploring individual-based networks will improve our understanding of species-based networks and will enhance the link between network analysis, foraging theory and evolutionary biology.

Genomic data have had a profound impact on nearly every biological discipline. In systematics and phylogenetics, the thousands of loci that are now being sequenced can be analyzed under the multispecies coalescent model (MSC) to explicitly account for gene tree discordance due to incomplete lineage sorting (ILS). However, the MSC assumes no gene flow post divergence, calling for additional methods that can accommodate this limitation. Explicit phylogenetic network methods have emerged, which can simultaneously account for ILS and gene flow by representing evolutionary history as a directed acyclic graph. In this point of view, we highlight some of the strengths and limitations ofphylogenetic networks and argue that tree-based inference should not be blindly abandoned in favor of networks simply because they represent more parameter rich models. Attention should be given to model selection of reticulation complexity, and the most robust conclusions regarding evolutionary history are likely obtained when combining tree- and network-based inference.

Adaptive radiation is thought to be responsible for the evolution of a great portion of the past and present diversity of life. Instances of adaptive radiation, characterized by the rapid emergence of an array of species as a consequence to their adaptation to distinct ecological niches, are important study systems in evolutionary biology. However, because of the rapid lineage formation in these groups, and occasional gene flow between the participating species, it is often difficult to reconstruct the phylogenetic history of species that underwent an adaptive radiation. In this study, we present a novel approach for species-tree estimation in rapidly diversifying lineages, where introgression is known to occur, and apply it to a multimarker data set containing up to 16 specimens per species for a set of 45 species of East African cichlid fishes (522 individuals in total), with a main focus on the cichlid species flock of Lake Tanganyika. We first identified, using age distributions of most recent common ancestors in individual gene trees, those lineages in our data set that show strong signatures of past introgression. This led us to formulate three hypotheses of introgression between different lineages of Tanganyika cichlids: the ancestor of Boulengerochromini (or of Boulengerochromini and Bathybatini) received genomic material from the derived H-lineage; the common ancestor of Cyprichromini and Perissodini experienced, in turn, introgression from Boulengerochromini and/or Bathybatini; and the Lake Tanganyika Haplochromini and closely related riverine lineages received genetic material from Cyphotilapiini. We then applied the multispecies coalescent model to estimate the species tree of Lake Tanganyika cichlids, but excluded the lineages involved in these introgression events, as the multispecies coalescent model does not incorporate introgression. This resulted in a robust species tree, in which the Lamprologini were placed as sister lineage to the H-lineage (including the Eretmodini), and we identify a series of rapid splitting events at the base of the H-lineage. Divergence ages estimated with the multispecies coalescent model were substantially younger than age estimates based on concatenation, and agree with the geological history of the Great Lakes of East Africa. Finally, we formally tested the three hypotheses of introgression using a likelihood framework, and find strong support for introgression between some of the cichlid tribes of Lake Tanganyika.

Abstract This study explores the relationship between microbial diversity and disease status in human lung cancer tissue microbiomes, using a sample size of 1212. Analysis divided the data into primary tumour (PT) and normal tissue (NT) categories. Differences in microbial diversity between PT and NT were significant in 57% of comparisons, although dataset dependence was a factor in the diversity levels. Shared species analysis (SSA) indicated no significant differences between PT and NT in over 90% of comparisons. Network diversity assessments revealed significant differences between NT and PT regarding species relative abundances and network link abundances for q = 0–3. Additionally, significant variations were found between NT and lung squamous cell carcinoma (LUSC) at q = 0. in network link probabilities, illustrating the diversity in species interactions. Our findings suggest a stable overall microbiome diversity and composition in lung cancer patients’ lung tissues despite patients with diagnosed lung tumours, indicating modified microbial interactions within the tumour. These results highlight an association between altered microbiome interaction patterns and lung tumours, offering new insights into the ecological dynamics of lung cancer microbiomes. Our findings suggest a stable overall microbiome diversity and composition in lung cancer patients’ lung tissues, despite tumour growth, but indicate modified microbial interactions within the tumour.

Background: Equine strongyles encompass more than 64 species of nematode worms that are responsible for growth retardation and the death of animals. The factors underpinning variation in the structure of the equine strongyle community remain unknown. Methods: Using horse-based strongyle community data collected after horse deworming (48 horses in Poland, 197 horses in Ukraine), we regressed species richness and the Gini-Simpson index upon the horse’s age, faecal egg count, sex and operation of origin. Using the Ukrainian observations, we applied a hierarchical diversity partitioning framework to estimate how communities were remodelled across operations, age groups and horses. Lastly, strongyle species counts collected after necropsy (46 horses in France, 150 in Australia) were considered for analysis of their co-occurrences across intestinal compartments using a joint species distribution modelling approach.Results: First, inter-operation variation accounted for > 45% of the variance in species richness or the Gini-Simpson index (which relates to species dominance in communities). Species richness decreased with horse’s age ( P = 0.01) and showed a mild increase with parasite egg excretion ( P < 0.1), but the Gini-Simpson index was neither associated with parasite egg excretion ( P = 0.8) nor with horse age ( P = 0.37). Second, within-host diversity represented half of the overall diversity across Ukrainian operations. While this is expected to erase species diversity across communities, community dissimilarity between horse age classes was the second most important contributor to overall diversity (25.8%). Third, analysis of species abundance data quantified at necropsy defined a network of positive co-occurrences between the four most prevalent strongyle genera. This pattern was common to necropsies performed in France and Australia. Conclusions: Taken together, these results show a pattern of β-diversity maintenance across age classes combined with positive co-occurrences that might be grounded by priority effects between the major species.

Aim Mutualistic interactions between plants and animals are fundamental for the maintenance of natural communities and the ecosystem services they provide. However, particularly in human‐dominated island ecosystems, introduced species may alter mutualistic interactions. Based on an extensive dataset of plant–frugivore interactions, we mapped and analysed a meta‐network across the Caribbean archipelago. Specifically, we searched for subcommunity structure (modularity) and identified the types of species facilitating the integration of introduced species in the Caribbean meta‐network. Location Caribbean archipelago (Lucayan archipelago, Greater Antilles, Lesser Antilles). Methods We reviewed published scientific literature, unpublished theses and other nonpeer‐reviewed sources to compile an extensive dataset of plant–frugivore interactions. We visualized spatial patterns and conducted a modularity analysis of the cross‐island meta‐network. We also examined which species were most likely to interact with introduced species: (1) endemic, nonendemic native or introduced species, and (2) generalized or specialized species. Results We reported 3060 records of interactions between 486 plant and 178 frugivore species. The Caribbean meta‐network was organized in 13 modules, driven by a combination of functional or taxonomic (modules dominated by certain groups of frugivores) and biogeographical (island‐specific modules) mechanisms. Few introduced species or interaction pairs were shared across islands, suggesting little homogenization of the plant–frugivore meta‐network at the regional scale. However, we found evidence of “invader complexes,” as introduced frugivores were more likely to interact with introduced plants than expected at random. Moreover, we found generalist species more likely to interact with introduced species than were specialized species. Main conclusions These results demonstrate that generalist species and “invader complexes” may facilitate the incorporation of introduced species into plant–frugivore communities. Despite the influx of introduced species, the meta‐network was structured into modules related to biogeographical and functional or taxonomic affinities. These findings reveal how introduced species become an integral part of mutualistic systems on tropical islands.

Species networks generalize the notion of species trees to allow for hybridization or other lateral gene transfer. Under the network multispecies coalescent model, individual gene trees arising from a network can have any topology, but arise with frequencies dependent on the network structure and numerical parameters. We propose a new algorithm for statistical inference of a level-1 species network under this model, from data consisting of gene tree topologies, and provide the theoretical justification for it. The algorithm is based on an analysis of quartets displayed on gene trees, combining several statistical hypothesis tests with combinatorial ideas such as a quartet-based intertaxon distance appropriate to networks, the NeighborNet algorithm for circular split systems, and the Circular Network algorithm for constructing a splits graph.

Difficulties in generating nuclear data for polyploids have impeded phylogenetic study of these groups. We describe a high-throughput protocol and an associated bioinformatics pipeline (Pipeline for Untangling Reticulate Complexes (PURC)) that is able to generate these data quickly and conveniently, and demonstrate its efficacy on accessions from the fern family Cystopteridaceae. We conclude with a demonstration of the downstream utility of these data by inferring a multi-labeled species tree for a subset of our accessions. We amplified four c. 1-kb-long nuclear loci and sequenced them in a parallel-tagged amplicon sequencing approach using the PacBio platform. PURC infers the final sequences from the raw reads via an iterative approach that corrects PCR and sequencing errors and removes PCR-mediated recombinant sequences (chimeras). We generated data for all gene copies (homeologs, paralogs, and segregating alleles) present in each of three sets of 50 mostly polyploid accessions, for four loci, in three PacBio runs (one run per set). From the raw sequencing reads, PURC was able to accurately infer the underlying sequences. This approach makes it easy and economical to study the phylogenetics of polyploids, and, in conjunction with recent analytical advances, facilitates investigation of broad patterns of polyploid evolution.