Structure Of Interaction Networks Research Articles

Network Structure of Bat-Ectoparasitic Interactions in Tropical Dry Forests at Two Different Regions in Brazil

Network analysis has been used for understanding complex systems in biology for decades. However, scant information is available for networks of antagonistic interactions. The aim of this study was to describe and compare bat-ectoparasite interaction networks in tropical dry forests (TFDs) in the Brazilian Cerrado and Caatinga biomes, which have contrasting environmental conditions and surrounding matrix. Bats and ectoparasites were sampled at six sites in northern and central Minas Gerais State, southeast Brazil. Network connectance, nestedness and number of compartments were compared between regions, as well as bat species richness, abundance and centrality, and ectoparasite specialization. The effect of bat phylogenetic relatedness on the similarity of their associated ectoparasite species was also tested. Bat-ectoparasite networks were nested, connected and highly compartmentalized in TDFs from both regions, with no significant differences in network structure. In addition, host species richness negatively influenced nestedness and connectance, but was positively related to compartment number. These findings are likely related to the high specialization observed for bat-fly species (usually one exclusive parasite species per host), resulting in networks with few interactions. Bat abundance positively affected bat-fly richness, indicating that resource availability is important in determining host-parasite relationships. Finally, phylogenetically related species of bats possessed more similar ectoparasite faunas, which may be associated with evolutionary responses of ectoparasites to escape defensive mechanisms of different bat species. Our results suggest that local bat-ectoparasite interactions are influenced by both ecological factors and evolutionary constraints, but the effects of environmental conditions on network topology deserved further detailed studies.

Seasonal trajectories of plant-pollinator interaction networks differ following phenological mismatches along an urbanization gradient

Urbanization may significantly alter the abundance, composition and phenology of natural communities of plants and pollinators. However, how such alterations eventually affect the structure of plant-pollinator interaction networks is still poorly known. Here, we investigate how the structure of plant-pollinator networks changes along an urbanization gradient, which coincides with a phenological mismatch between plants and pollinators. We examined changes in plant-pollinator network structure in 12 sites sown with standardized native flower mixes along an urbanization gradient in a metropolis in Northern France. We used network-level metrics in combination with more detailed methodologies to identify changes in network structure, species clustering, and species roles through urban classes and time. We also evaluated the temporal trajectories of α- and β-diversity of species and interactions along the gradient. Network-level metrics showed limited spatial–temporal variability in the connectance, distribution of interactions and network-level specialization. Finer-scale analyses showed that generalist plant and pollinator species with long phenology were the most central and played key roles in defining the composition of cohesive groups of interacting species in all networks. Network motifs and species positions showed higher temporal variability in less urbanized areas, and interactions were more dissimilar between urbanization classes earlier in the season. We showed evidence of alterations in plant-pollinator network structure across space and time along an urbanization gradient, likely driven by the significant advancement in flowering phenology observed in the more urbanized areas. Our results emphasize the importance of targeted measures to maintain functional plant-pollinator communities, especially early in the season in highly urbanized areas.

Improving Abusive Language Detection with online interaction network

The rapid development of online social media makes Abusive Language Detection (ALD) a hot topic in the field of affective computing. However, most methods for ALD in social networks do not take into account the interactive relationships among user posts, which simply regard ALD as a task of text context representation learning. To solve this problem, we propose a pipeline approach that considers both the context of a post and the characteristics of interaction network in which it is posted. Specifically, our method is divided into pre-training and downstream tasks. First, to capture fine contextual features of the posts, we use Bidirectional Encoder Representation from Transformers (BERT) as Encoder to generate sentence representations. Later, we build a Relation-Special Network according to the semantic similarity between posts as well as the interaction network structural information. On this basis, we design a Relation-Special Graph Neural Network (RSGNN) to spread effective information in the interaction network and learn the classification of texts. The experiment proves that our method can effectively improve the detection effect of abusive posts over three public datasets. The results demonstrate that injecting interaction network structure into the abusive language detection task can significantly improve the detection results.

Use of botanical gardens as arks for conserving pollinators and plant-pollinator interactions: A case study from the United States Northern Great Plains

Botanical gardens have contributed to plant conservation through the maintenance of both living and preserved plant specimens for decades. However, there is still a large gap in the literature about the potential conservation value that botanical gardens could provide to local pollinators. We investigated how plant-pollinator interaction network structure and diversity may differ between botanical gardens and native habitats by sampling and comparing two environments: a restored native grassland patch within a local botanical garden and fifteen native, remnant temperate grassland sites in the Northern Great Plains. We found pollinator diversity within the restored botanical garden’s native grassland patch to be at the high end of the distribution of the remnant temperate grassland sites throughout the entire flowering season. However, plant diversity and network community metrics between the two environments remained similar throughout, except that remnant temperate grasslands have more links (higher connectance) with pollinators than the garden patch. Overall, our findings demonstrate the promising role restored native grassland patches in botanical gardens could play as reservoirs for local pollinator communities by supporting plant-pollinator interactions comparable to those found in native habitat remnants in the same region.

Role of Impoundments Created by Low-Head Dams in Affecting Fish Assemblages in Subtropical Headwater Streams in China

Low-head dams are ubiquitous human disturbances that degrade aquatic ecosystem function worldwide. The localized effects of low-head dams have been relatively well documented; however, most previous studies have ignored the concealed process caused by native-invasive species. Based on fish assemblage data from the first-order streams of four basins in the Wannan Mountains, we used a quantitative approach to assess the effects of low-head dams on fish assemblages by distinguishing between native and native-invasive species using occurrence- and abundance-based data, respectively. Low-head dams significantly decreased native fish alpha diversity while favoring native-invasive fish. The opposite pattern between the two fish types partly masked changes in the whole fish assemblage. Meanwhile, the establishment of widespread native-invasive species and the loss of native species driven by low-head dams influenced the interaction network structure. The degree to which local fish assemblages were altered by low-head dams, i.e., beta diversity (β-diversity) was significantly higher for abundance-based approaches than for occurrence-based ones, suggesting that the latter underestimated the effects of low-head dams. Furthermore, the species contribution to β-diversity of native species was significantly higher than that of native-invasive species in both impoundments and free-flowing segments for abundance-based data. In communities or regions where native fish species are predominant, our results suggest that understanding which species contribute to β-diversity will offer new insights into the development of effective conservation strategies by taking the identities of native and native-invasive species into account.

Signals of Potential Species Associations Offer Clues about Community Organisation of Stream Fish across Seasons

Simple SummarySpecies interactions are one of the main factors affecting community assembly, yet the role of such interactions remains mostly unknown. Here, we investigated roles of potential species associations in fish community assembly in the Qiupu River, China. Our results suggested that potential species associations might have been underestimated in stream fish community assembly. The contribution of potential species associations to fish community assembly can be reflected by interaction network structures. Omnivorous species play an important role in maintaining network structure as they may have more associations with other species. This study highlights the importance of capturing species associations in river ecosystems across different geographical and environmental settings.Environmental filtering, spatial factors and species interactions are fundamental ecological mechanisms for community organisation, yet the role of such interactions across different environmental and spatial settings remains mostly unknown. In this study, we investigated fish community organisation scenarios and seasonal species-to-species associations potentially reflecting biotic associations along the Qiupu River (China). Based on a latent variable approach and a tree-based method, we compared the relative contribution of the abiotic environment, spatial covariates and potential species associations for variation in the community structure, and assessed whether different assembly scenarios were modulated by concomitant changes in the interaction network structure of fish communities across seasons. We found that potential species associations might have been underestimated in community-based assessments of stream fish. Omnivore species, since they have more associations with other species, were found to be key components sustaining fish interaction networks across different stream orders. Hence, we suggest that species interactions, such as predation and competition, likely played a key role in community structure. For instance, indices accounting for network structure, such as connectance and nestedness, were strongly correlated with the unexplained residuals from our latent variable approach, thereby re-emphasising that biotic signals, potentially reflecting species interactions, may be of primary importance in determining stream fish communities across seasons. Overall, our findings indicate that interaction network structures are a powerful tool to reflect the contribution of potential species associations to community assembly. From an applied perspective, this study should encourage freshwater ecologists to empirically capture and manage biotic constraints in stream ecosystems across different geographical and environmental settings, especially in the context of the ever-increasing impacts of human-induced local extinction debts and species invasions.

Removing flowers of a generalist plant changes pollinator visitation, composition, and interaction network structure

AbstractPollination is essential for ecosystem functioning, yet our understanding of the empirical consequences of species loss for plant–pollinator interactions remains limited. It is hypothesized that the loss of abundant and generalized (well‐connected) species from a pollination network will have a large effect on the remaining species and their interactions. However, to date, relatively few studies have experimentally removed species from their natural setting to address this hypothesis. We investigated the consequences of losing an abundant, generalist native species from a series of plant–pollinator networks by experimentally removing the flowers of Helianthella quinquenervis (Asteraceae) from half of a series of 10 paired plots (15 m diameter) within a subalpine ecosystem. We then asked how the localized loss of this species influenced patterns of pollinator visitation, floral visitor composition, and interaction network structure. The experimental removal of Helianthella flowers led to an overall decline in plot‐level pollinator visitation rates and shifts in pollinator composition. Species‐level responses to floral removal differed between the two other abundant, co‐flowering plants in our experiment: Potentilla pulcherrima received higher visitation rates, whereas Erigeron speciosus visitation rates did not change. Experimental floral removal altered the structural properties of the localized plant–pollinator networks such that they were more specialized, less nested, and less robust to further species loss. Such changes to interaction network structure were consistently driven more by species turnover than by interaction rewiring. Our findings suggest that the local loss of an abundant, well‐linked, generalist plant can bring about diverse responses within intact pollination networks, including potential competitive and facilitative effects for individual species, changes to network structure that may render them more sensitive to future change, but also numerous changes to interactions that may also suggest flexibility in response to species loss.

A genetic mammalian proportional–integral feedback control circuit for robust and precise gene regulation

The processes that keep a cell alive are constantly challenged by unpredictable changes in its environment. Cells manage to counteract these changes by employing sophisticated regulatory strategies that maintain a steady internal milieu. Recently, the antithetic integral feedback motif has been demonstrated to be a minimal and universal biological regulatory strategy that can guarantee robust perfect adaptation for noisy gene regulatory networks in Escherichia coli. Here, we present a realization of the antithetic integral feedback motif in a synthetic gene circuit in mammalian cells. We show that the motif robustly maintains the expression of a synthetic transcription factor at tunable levels even when it is perturbed by increased degradation or its interaction network structure is perturbed by a negative feedback loop with an RNA-binding protein. We further demonstrate an improved regulatory strategy by augmenting the antithetic integral motif with additional negative feedback to realize antithetic proportional-integral control. We show that this motif produces robust perfect adaptation while also reducing the variance of the regulated synthetic transcription factor. We demonstrate that the integral and proportional-integral feedback motifs can mitigate the impact of gene expression burden, and we computationally explore their use in cell therapy. We believe that the engineering of precise and robust perfect adaptation will enable substantial advances in industrial biotechnology and cell-based therapeutics.

Intermolecular interactions in binary mixtures of formamide and acetone

Trajectories from molecular dynamics simulations of binary mixtures of formamide (FA) and acetone (AT) have been analyzed across the entire concentration range by means of various pair distributions and topological network analysis techniques to probe the structure of the intermolecular interaction networks existing in these mixtures. Radial pair distributions clearly indicated H-bonding interactions between the two molecule types through acetone oxygen and the cis- and/or trans-hydrogens of formamide. Decomposition of pair energy distributions into possible intermolecular interaction types revealed that the most stable formamide-acetone dimers existing in the binary mixtures interact via an H-bonding. Orientational pair distributions have shown that both the AT-AT and the FA-FA pairs tend to adopt an antiparallel dipole orientation, as their respective pair interaction energies get smaller. And, the FA-AT pairs interacting stronger than −6.3 kcal/mol are found to adopt an orientation such that the angle between the dipole of AT and the C-N bond of FA is larger than 130°. Network neighborhood analysis evidently revealed that the formamides do not show a strong preference for either molecule types. As acetone mole fraction of the mixture is increased, the added ATs are found to be capable of substituting the formamides, to a great extent, in the region spanning their second-order neighborhood. Conversely, as formamide content of the mixture is increased, the added FAs fail to adequately substitute the ATs in the region spanning their second-order neighborhood. Guided by our molecular dynamics based observations regarding the different types of intermolecular interactions existing between formamide and acetone, five FA-AT dimeric structures are highlighted. Their interaction energies are computed with density functional theory at the mPW2PLYP/def2-TZVP level. The most stable dimer is found to have an interaction energy of −7.5 kcal/mol, to involve an O⋯HC hydrogen-bonding, and to have nearly coplanar formamide and acetone. In addition, the DFT structures and interaction energies of trimers of the form AT⋯FA⋯AT and FA⋯AT⋯FA are also reported.

Phylogenetic signals in flea-host interaction networks from four biogeographic realms: differences between interactors and the effects of environmental factors

The structure of ecological interaction networks is associated with evolutionary histories of the interacting species. This is reflected by the phylogenetic signals (PS) in these networks when closely related species interact with similar partners because some traits inherited from the ancestors may determine ecological interactions. We investigated PS for small mammalian hosts and fleas in 80 regional interaction networks from four biogeographic realms (the Palearctic, the Nearctic, the Afrotropics, and the Neotropics). We asked (i) whether the relative strength of PS in host-flea networks is similar between hosts and fleas and/or between realms; (ii) how environmental variation affects the PS of hosts and fleas in their interaction networks; and (iii) whether the PS for hosts or fleas is affected by the phylogenetic diversity of either hosts or fleas, respectively. We found that the PS for hosts was stronger than that for fleas in all realms. An environmental effect on the PS for hosts, but not for fleas, was found in three of the four realms (except the Neotropics). In the Palearctic and the Nearctic, a stronger PS was characteristic for cooler and/or drier regions, whereas the opposite was the case for the Afrotropics in regard to precipitation. The phylogenetic diversity of regional host and flea assemblages was not associated with the values of the respective PS in any realm. We conclude that the pattern of the relative strength of the PS for hosts and fleas in their interaction networks is similar in different biogeographic realms with vastly different host and flea faunas. However, the environmental effects on the PS are geographically variable and might be associated with the history of host-flea associations, as well as the spatial pattern of environmental variation, within a realm.

What plant–pollinator network structure tells us about the mechanisms underlying the bidirectional biodiversity productivity relationship?

The Biodiversity – Ecosystem Functioning (B–EF) relationship remains a topic of ongoing debate with most studies focusing on primary productivity, and documenting that this relationship takes many forms. It remains unclear if biodiversity drives productivity or productivity shapes biodiversity or the relationship is bidirectional. B-EF studies explore almost exclusively the relationship between species richness and ecosystem functioning, while the role of biotic interactions, a key component of ecosystem functioning, has been neglected. Here, using data of 80 local plant–pollinator networks on 20 Aegean islands, and of gross primary productivity (GPP) from the MODIS satellite, we explored the bidirectional relationship between interaction network structure (nestedness and specialization), species richness (plants and pollinators) and mean and inter-annual variability of GPP. We found that nestedness and specialisation of plant–pollinator networks is driven by mean GPP. However, specialisation alone was a significant predictor of mean GPP, implying that networks tend to be more specialised in low-productivity areas. Pollinator species richness exerted a strong effect on mean GPP with the remaining factors playing a minor role, while the effect of mean GPP on pollinator species richness was weaker. Furthermore, the nestedness of plant–pollinator networks drives inter-annual variability of GPP with more nested networks displaying less variability, which is in accordance with the predictions of the insurance hypothesis. Plant and pollinator species richness were also associated with inter-annual variability of GPP.

Identification of lncRNA Biomarkers and LINC01198 Promotes Progression of Chronic Rhinosinusitis with Nasal Polyps through Sponge miR-6776-5p.

Background Chronic sinusitis (CRS) was a chronic inflammation that originated in the nasal mucosa and affected the health of most people around the world. Chronic rhinosinusitis with nasal polyps (CRSwNP) was one kind of chronic sinusitis. Emerging research had suggested that long noncoding RNAs (lncRNAs) played vital parts in inflammatories and inflammation development. Methods We acquired GEO data to analyze the differential expression between the miRNA, immune genes, TF, and lncRNA data in CRSWNP and the corresponding control tissues. Bioinformatic analysis by coexpression of endogenous RNA network and competitive way enrichment, analysis, and forecasting functions of these noncoding RNA. The different pathway expressions in CRSwNP patients were confirmed using GSVA to analyze the differentially expressed immune genes and TF data sets in CRSwNP patients. The differential immune gene and transcription factor data set in CRSwNP perform functional notes and protein-protein interaction (PPI) network structure. We predicted the potential genes and RNAs related to CRSWNP by constructing a ceRNA network. In addition, we also used 19 hub immune genes to predict the potential drugs of CRSWNP. lncRNA biomarkers in CRSwNP were identified by lncRNAs LASSO regression. The CIBERSORT algorithm was used to contrast the divergence in immune infiltrations between CRSwNP and usual inferior turbinate organizations in 22 immunocyte subgroups. Results We identified a total of 48 miRNAs, 304 lncRNAs, 92 TFs, and 525 immune genes as CRSwNP-specific RNAs. GO and KEGG pathways both analyzed differentially expressed immune genes and transcription factor data sets. We predicted the potential genes GNG7, TUSC8, LINC01198, and has-miR-6776-5p by constructing ceRNA and PPI networks. At the same time, we found that the above genes were involved in two important pathways: chemokine signal path and PI3K/AKT signal path. In addition, we predicted 5 small molecule drugs to treat CRSwNP by analyzing 19 central immune genes, namely, danazol, ikarugamycin, semustine, cefamandole, and molindone. Finally, we identified 5 biomarkers in CRSwNP, namely, LINC01198, LINC01094, LINC01798, LINC01829, and LINC01320. Conclusions We had identified CRSwNP-related miRNAs, lncRNAs, TFs, and immune genes, which may be making use of latent therapeutic target for CRSwNP. At the same time, we identified 5 lncRNA biomarkers in CRSwNP. The results of this study showed that LINC01198 promoted the progression of CRSwNPs through spongy miR-6776-5p. Our studies provide a new way for further analyses of the pathogenesis of CRSwNP.

Drivers of plant individual-based pollinator visitation network topology in an arid ecosystem

Interactions with pollinators underlie the structure and function of plant communities. Network analysis is a valuable tool for studying plant-pollinator interactions, but these networks are most frequently built by aggregating interactions at the species level. Interactions are between individuals and an advantage of individual-based networks is the ability to integrate inter-individual variation in traits and environmental context within complex ecological networks. We studied the influence of inter-individual variation on pollinator sharing among foundation shrubs and cactus in a desert ecosystem using plant individual-based pollinator visitation networks. We hypothesized that the traits that alter attractiveness of plants to pollinators will also influence an individual plant's role within the visitation network. Foundation plants growing with higher densities of nearby blooming shrubs had higher pollinator visitation rates and had greater access to the conspecific mating pool, suggesting widespread and diffuse pollination facilitation within this community. Further, shrub density influenced the role of betweenness centrality and the effective number of partners (eH). Floral display size also influenced the effective number of interaction partners but did not directly influence the centrality measures for individual plants or other measures of network structure despite increasing visitation rates. The individual-based visitation networks were significantly modular and module membership was predicted by species identity and pollinator visitation rates. Ecological and individual context mediate the outcome of pollinator-mediated interactions and are fundamental drivers of whole community structure. This study shows that the density of immediate neighbours can influence the overall structure of plant-pollinator interaction networks. Exploring the contribution of intraspecific variation to community interaction networks will improve our understanding of drivers of community-level ecological dynamics.

The structure balance of gene-gene networks beyond pairwise interactions.

Despite its high and direct impact on nearly all biological processes, the underlying structure of gene-gene interaction networks is investigated so far according to pair connections. To address this, we explore the gene interaction networks of the yeast Saccharomyces cerevisiae beyond pairwise interaction using the structural balance theory (SBT). Specifically, we ask whether essential and nonessential gene interaction networks are structurally balanced. We study triadic interactions in the weighted signed undirected gene networks and observe that balanced and unbalanced triads are over and underrepresented in both networks, thus beautifully in line with the strong notion of balance. Moreover, we note that the energy distribution of triads is significantly different in both essential and nonessential networks compared to the shuffled networks. Yet, this difference is greater in the essential network regarding the frequency as well as the energy of triads. Additionally, results demonstrate that triads in the essential gene network are more interconnected through sharing common links, while in the nonessential network they tend to be isolated. Last but not least, we investigate the contribution of all-length signed walks and its impact on the degree of balance. Our findings reveal that interestingly when considering longer cycles, not only, both essential and nonessential gene networks are more balanced compared to their corresponding shuffled networks, but also, the nonessential gene network is more balanced compared to the essential network.

Intensive grazing alters the diversity, composition and structure of plant-pollinator interaction networks in Central European grasslands.

Complex socio-economic, political and demographic factors have driven the increased conversion of Europe’s semi-natural grasslands to intensive pastures. This trend is particularly strong in some of the most biodiverse regions of the continent, such as Central and Eastern Europe. Intensive grazing is known to decrease species diversity and alter the composition of plant and insect communities. Comparatively little is known, however, about how intensive grazing influences plant functional traits related to pollination and the structure of plant-pollinator interactions. In traditional hay meadows and intensive pastures in Central Europe, we contrasted the taxonomic and functional group diversity and composition, the structure of plant-pollinator interactions and the roles of individual species in networks. We found mostly lower taxonomic and functional diversity of plants and insects in intensive pastures, as well as strong compositional differences among the two grassland management types. Intensive pastures were dominated by a single plant with a specialized flower structure that is only accessible to a few pollinator groups. As a result, intensive pastures have lower diversity and specificity of interactions, higher amount of resource overlap, more uniform interaction strength and lower network modularity. These findings stand in contrast to studies in which plants with more generalized flower traits dominated pastures. Our results thus highlight the importance of the functional traits of dominant species in mediating the consequences of intensive pasture management on plant-pollinator networks. These findings could further contribute to strategies aimed at mitigating the impact of intensive grazing on plant and pollinator communities.

SINAPs: A Software Tool for Analysis and Visualization of Interaction Networks of Molecular Dynamics Simulations.

As long as the structural study of molecular mechanisms requires multiple molecular dynamics reflecting contrasted bioactive states, the subsequent analysis of molecular interaction networks remains a bottleneck to be fairly treated and requires a user-friendly 3D view of key interactions. Structural Interaction Network Analysis Protocols (SINAPs) is a proprietary python tool developed to (i) quickly solve key interactions able to distinguish two protein states, either from two sets of molecular dynamics simulations or from two crystallographic structures, and (ii) render a user-friendly 3D view of these key interactions through a plugin of UCSF Chimera, one of the most popular open-source viewing software for biomolecular systems. Through two case studies, glucose transporter-1 (GLUT-1) and A2A adenosine receptor (A2AR), SINAPs easily pinpointed key interactions observed experimentally and relevant for their bioactivities. This very effective tool was thus applied to identify the amino acids involved in the molecular enzymatic mechanisms ruling the activation of an immunomodulator drug candidate, P28 glutathione-S-transferase (P28GST). SINAPs is freely available at https://github.com/ParImmune/SINAPs.

The structure of tropical bat-plant interaction networks during an extreme El Niño-Southern Oscillation event.

Interaction network structure reflects the ecological mechanisms acting within biological communities, which are affected by environmental conditions. In tropical forests, higher precipitation usually increases fruit production, which may lead frugivores to increase specialization, resulting in more modular and less nested animal–plant networks. In these ecosystems, El Niño is a major driver of precipitation, but we still lack knowledge of how species interactions change under this influence. To understand bat–plant network structure during an extreme El Niño‐Southern Oscillation event, we determined the links between plantivorous bat species and the plants they consume by DNA barcoding seeds and pulp in bat faeces. These interactions were recorded in the dry forest and rainforest of Costa Rica, during the dry and the wet seasons of an extreme El Niño year. From these we constructed seasonal and whole‐year bat–plant networks and analysed their structures and dissimilarities. In general, networks had low nestedness, had high modularity, and were dominated by one large compartment which included most species and interactions. Contrary to our expectations, networks were less nested and more modular in drier conditions, both in the comparison between forest types and between seasons. We suggest that increased competition, when resources are scarce during drier seasons and habitats, lead to higher resource partitioning among bats and thus higher modularity. Moreover, we have found similar network structures between dry and rainforests during El Niño and non‐El Niño years. Finally, most interaction dissimilarity among networks occurred due to interaction rewiring among species, potentially driven by seasonal changes in resource availability.

The effect of sea surface temperature on the structure and connectivity of species landings interaction networks in a multispecies recreational fishery

Multispecies fisheries, particularly those that routinely adapt the timing, location, and methods of fishing to prioritize fishery targets, present a challenge to traditional single-species management approaches. Efforts to develop robust management for multispecies fisheries require an understanding of how priorities drive the network of interactions between catch of different species, especially given the added challenges presented by climate change. Using 35 years of landings data from a southern California recreational fishery, we leveraged empirical dynamic modelling methods to construct causal interaction networks among the main species targeted by the fishery. We found strong evidence for dependencies among species landings time series driven by apparent hierarchical catch preference within the fishery. In addition, by parsing the landings time series into anomalously cool, normal, and anomalously warm regimes (the last reflecting ocean temperatures anticipated by 2040), we found that network complexity was highest during warm periods. Our findings suggest that as ocean temperatures continue to rise, so too will the risk of unintended consequences from single-species management in this multispecies fishery.

Contribuição do Programa BIOTA/FAPESP para o conhecimento sobre polinização e reprodução em plantas

Abstract Interactions between plant and pollinators are associated with the origin and maintenance of species diversity, as well as ecosystem functioning. The potential of pollination as an ecosystem service is evidenced by its association with food production. Understanding pollination at the landscape scale is essential for characterizing the pollination service for several crops that depend on pollinators for fruit and seed set that make up the human diet. Our aim was to carry out a literature review of studies and projects funded by BIOTA/FAPESP to illustrate the main research approaches developed in the field of Pollination Biology, especially related to plant-pollinator interactions. Plant-pollinator interactions in the Atlantic forest were leveraged as a result of this long-term research program, during which several papers were published in international journals. Pollination by bees (melittophily) was the most representative pollination system studied. In addition to melittophily, other interactions were studied such as pollination by hawkmoths (sphingophily), by hummingbirds (ornithophily) and by bats (chiropterophily). The specific mutualistic relationships between fig trees and fig wasps were also subject of studies within the Program. At the beginning of the BIOTA/FAPESP Program, there were many gaps in basic information about pollination and breeding systems of Brazilian native plant species. Thus, the Program was fundamental to fuel research on the natural history of plants and pollinators from the Atlantic forest. Overall, the Program funded studies that investigated themes such as functional pollination ecology, pollinator effectiveness, plant population genetics, structure and dynamics of plant-pollinator interaction networks, as well as geographic distribution and macroevolution of pollination systems, as well as genetic and molecular studies of native plant populations focusing on pollen flow and genetic structure of populations. Additionally, studies on pollination in the context of landscape ecology had the aim of assessing the effects of forest fragmentation on the functioning of plant populations and their interactions with pollinators and the relationships between landscape structure and ecological processes, biodiversity, and ecosystem service. Therefore, the Program had a prominent role in producing basic data with great implications for understanding the ecology and promoting the conservation of plant-pollinator interactions.

Fitness effects of plasmids shape the structure of bacteria-plasmid interaction networks

Fitness effects of plasmids shape the structure of bacteria-plasmid interaction networks