Linkage Rules for Plant–Pollinator Networks: Trait Complementarity or Exploitation Barriers?

Recent attempts to examine the biological processes responsible for the general characteristics of mutualistic networks focus on two types of explanations: nonmatching biological attributes of species that prevent the occurrence of certain interactions (“forbidden links”), arising from trait complementarity in mutualist networks (as compared to barriers to exploitation in antagonistic ones), and random interactions among individuals that are proportional to their abundances in the observed community (“neutrality hypothesis”). We explored the consequences that simple linkage rules based on the first two hypotheses (complementarity of traits versus barriers to exploitation) had on the topology of plant–pollination networks. Independent of the linkage rules used, the inclusion of a small set of traits (two to four) sufficed to account for the complex topological patterns observed in real-world networks. Optimal performance was achieved by a “mixed model” that combined rules that link plants and pollinators whose trait ranges overlap (“complementarity models”) and rules that link pollinators to flowers whose traits are below a pollinator-specific barrier value (“barrier models”). Deterrence of floral parasites (barrier model) is therefore at least as important as increasing pollination efficiency (complementarity model) in the evolutionary shaping of plant–pollinator networks.     

Evolution and Function of Leaf Venation Architecture: A Review

The leaves of extant terrestrial plants show highly diverseand elaborate patterns of leaf venation. One fundamental featureof many leaf venation patterns, especially in the case of angiospermleaves, is the presence of anastomoses. Anastomosing veins distinguisha network topologically from a simple dendritic (tree-like)pattern which represents the primitive venation architecture.The high degree of interspecific variation of entire venationpatterns as well as phenotypic plasticity of some venation properties,such as venation density, indicate the high selective pressureacting on this branching system. Few investigations deal withfunctional properties of the leaf venation system. The interrelationshipsbetween topological or geometric properties of the various leafvenation patterns and functional aspects are far from beingwell understood. In this review we summarize current knowledgeof interrelationships between the form and function of leafvenation and the evolution of leaf venation patterns. Sincethe functional aspects of architectural features of differentleaf venation patterns are considered, the review also refersto the topic of individual and intraspecific variation. Onebasic function of leaf venation is represented by its contributionto the mechanical behaviour of a leaf. Venation geometry anddensity influences mechanical stability and may affect, forexample, susceptibility to herbivory. Transport of water andcarbohydrates is the other basic function of this system andthe transport properties are also influenced by the venationarchitecture. These various functional aspects can be interpretedin an ecophysiological context. Copyright 2001 Annals of BotanyCompany Review, leaves, leaf venation, evolution, network, transport, flow, mechanical stabilization     

叶脉网络功能性状及其生态学意义

叶脉网络结构是叶脉系统在叶片里的分布和排列样式。早期叶脉网络结构研究主要集中在其分类学意义上; 近年来叶脉网络功能性状及其在植物水分利用上的意义已成为植物生态学研究的热点。该文介绍了叶脉网络功能性状的指标体系(包括叶脉密度、叶脉直径、叶脉之间的距离、叶脉闭合度等), 综述了叶脉网络功能性状与叶脉系统功能(包括水分、养分和光合产物等物质运输、机械支撑和虫害防御等)的关系, 叶脉网络功能性状与叶片其他功能性状(包括比叶重、叶寿命、光合速率、叶片大小、气孔密度等)的协同变异和权衡关系, 以及叶脉网络功能性状随环境因子(包括水分、温度、光照等)的变化规律等方面的最新研究进展。此外, 叶脉网络功能性状的研究成果也被应用于古环境重建、城市交通规划、流域规划及全球变化研究中。由于叶脉网络功能性状是环境因子与系统发育共同作用的结果, 未来开展分子—叶片—植物—生态系统等多尺度的叶脉网络功能性状研究, 理清叶脉网络功能性状与气孔失水—茎干导水—根系吸水等植物水分利用的关系, 将为预测植物及生态系统对全球变化的响应提供新的启示。     

Discriminating Different Classes of Biological Networks by Analyzing the Graphs Spectra Distribution

The brain''s structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e.g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a “fingerprint”. Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the “uncertainty” of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.     

Venation networks and the origin of the leaf economics spectrum

The leaf economics spectrum describes biome-invariant scaling functions for leaf functional traits that relate to global primary productivity and nutrient cycling. Here, we develop a comprehensive framework for the origin of this leaf economics spectrum based on venation-mediated economic strategies. We define a standardized set of traits - density, distance and loopiness - that provides a common language for the study of venation. We develop a novel quantitative model that uses these venation traits to model leaf-level physiology, and show that selection to optimize the venation network predicts the mean global trait-trait scaling relationships across 2548 species. Furthermore, using empirical venation data for 25 plant species, we test our model by predicting four key leaf functional traits related to leaf economics: net carbon assimilation rate, life span, leaf mass per area ratio and nitrogen content. Together, these results indicate that selection on venation geometry is a fundamental basis for understanding the diversity of leaf form and function, and the carbon balance of leaves. The model and associated predictions have broad implications for integrating venation network geometry with pattern and process in ecophysiology, ecology and palaeobotany.     

An efficient method for estimating vein density of Glossopteris and its application

Glossopteris-type leaves are the most abundant floristic element from the Gondwanan continent and are recorded throughout the Permian, which was a period of extreme icehouse-to-hothouse climatic global change. Fossil leaf traits can be useful for the reconstruction of palaeoenvironments and identification of climatic changes throughout geological time, but the conservative morphology of Glossopteris leaves has thus far made them difficult to use for this purpose. If the characters of Glossopteris can be better quantified then it should make them useful for tracking environmental changes over a wide geographical area and over a long time interval. Venation density is a highly variable leaf trait that might be useful for this purpose. This trait can be calculated, usually as vein length per centimetre squared, but this can be a time-consuming procedure. In this paper we propose a new rapid method to estimate venation density in a conical sector of Glossopteris leaf lamina using an accurate linear model whose predictors are three linear venation densities, measured as veins per centimetre. In addition to substantially reducing the data collection time, it is less biased and more reproducible than methods applied previously with this leaf type. Using this more robust method, preliminary results significantly distinguish the venation densities of leaves produced in wet and drier ecosystems, matching a pattern similar to modern plants. This is the first survey using a large sample size to reveal that environmental stress controlled the vein architecture of Palaeozoic plants, in a manner similar to plants in modern ecosystems.     

The role of elastic stresses on leaf venation morphogenesis

We explore the possible role of elastic mismatch between epidermis and mesophyll as a driving force for the development of leaf venation. The current prevalent ‘canalization’ hypothesis for the formation of veins claims that the transport of the hormone auxin out of the leaves triggers cell differentiation to form veins. Although there is evidence that auxin plays a fundamental role in vein formation, the simple canalization mechanism may not be enough to explain some features observed in the vascular system of leaves, in particular, the abundance of vein loops. We present a model based on the existence of mechanical instabilities that leads very naturally to hierarchical patterns with a large number of closed loops. When applied to the structure of high-order veins, the numerical results show the same qualitative features as actual venation patterns and, furthermore, have the same statistical properties. We argue that the agreement between actual and simulated patterns provides strong evidence for the role of mechanical effects on venation development.     

Linking leaf veins to growth and mortality rates: an example from a subtropical tree community

A fundamental goal in ecology is to link variation in species function to performance, but functional trait–performance investigations have had mixed success. This indicates that less commonly measured functional traits may more clearly elucidate trait–performance relationships. Despite the potential importance of leaf vein traits, which are expected to be related to resource delivery rates and photosynthetic capacity, there are few studies, which examine associations between these traits and demographic performance in communities. Here, we examined the associations between species traits including leaf venation traits and demographic rates (Relative Growth Rate, RGR and mortality) as well as the spatial distributions of traits along soil environment for 54 co‐occurring species in a subtropical forest. Size‐related changes in demographic rates were estimated using a hierarchical Bayesian approach. Next, Kendall's rank correlations were quantified between traits and estimated demographic rates at a given size and between traits and species‐average soil environment. Species with denser venation, smaller areoles, less succulent, or thinner leaves showed higher RGR for a wide range of size classes. Species with leaves of denser veins, larger area, cheaper construction costs or thinner, or low‐density wood were associated with high mortality rates only in small size classes. Lastly, contrary to our expectations, acquisitive traits were not related to resource‐rich edaphic conditions. This study shows that leaf vein traits are weakly, but significantly related to tree demographic performance together with other species traits. Because leaf traits associated with an acquisitive strategy such as denser venation, less succulence, and thinner leaves showed higher growth rate, but similar leaf traits were not associated with mortality, different pathways may shape species growth and survival. This study suggests that we are still not measuring some of key traits related to resource‐use strategies, which dictate the demography and distributions of species.     

Yeast metabolic innovations emerged via expanded metabolic network and gene positive selection

Yeasts are known to have versatile metabolic traits, while how these metabolic traits have evolved has not been elucidated systematically. We performed integrative evolution analysis to investigate how genomic evolution determines trait generation by reconstructing genome‐scale metabolic models (GEMs) for 332 yeasts. These GEMs could comprehensively characterize trait diversity and predict enzyme functionality, thereby signifying that sequence‐level evolution has shaped reaction networks towards new metabolic functions. Strikingly, using GEMs, we can mechanistically map different evolutionary events, e.g. horizontal gene transfer and gene duplication, onto relevant subpathways to explain metabolic plasticity. This demonstrates that gene family expansion and enzyme promiscuity are prominent mechanisms for metabolic trait gains, while GEM simulations reveal that additional factors, such as gene loss from distant pathways, contribute to trait losses. Furthermore, our analysis could pinpoint to specific genes and pathways that have been under positive selection and relevant for the formulation of complex metabolic traits, i.e. thermotolerance and the Crabtree effect. Our findings illustrate how multidimensional evolution in both metabolic network structure and individual enzymes drives phenotypic variations.     

Performance of Social Network Sensors during Hurricane Sandy

Information flow during catastrophic events is a critical aspect of disaster management. Modern communication platforms, in particular online social networks, provide an opportunity to study such flow and derive early-warning sensors, thus improving emergency preparedness and response. Performance of the social networks sensor method, based on topological and behavioral properties derived from the “friendship paradox”, is studied here for over 50 million Twitter messages posted before, during, and after Hurricane Sandy. We find that differences in users’ network centrality effectively translate into moderate awareness advantage (up to 26 hours); and that geo-location of users within or outside of the hurricane-affected area plays a significant role in determining the scale of such an advantage. Emotional response appears to be universal regardless of the position in the network topology, and displays characteristic, easily detectable patterns, opening a possibility to implement a simple “sentiment sensing” technique that can detect and locate disasters.     

Quercus species divergence is driven by natural selection on evolutionarily less integrated traits

Functional traits are organismal attributes that can respond to environmental cues, thereby providing important ecological functions. In addition, an organism’s potential for adaptation is defined by the patterns of covariation among groups of functionally related traits. Whether an organism is evolutionarily constrained or has the potential for adaptation is based on the phenotypic integration or modularity of these traits. Here, we revisited leaf morphology in two European sympatric white oaks (Quercus petraea (Matt.) Liebl. and Quercus robur L.), sampling 2098 individuals, across much of their geographical distribution ranges. At the phenotypic level, leaf morphology traditionally encompasses discriminant attributes among different oak species. Here, we estimated in situ heritability, genetic correlation, and integration across such attributes. Also, we performed Selection Response Decomposition to test these traits for potential differences in oak species’ evolutionary responses. Based on the uncovered functional units of traits (modules) in our study, the morphological module “leaf size gradient” was highlighted among functionally integrated traits. Equally, this module was defined in both oaks as being under “global regulation” in vegetative bud establishment and development. Lamina basal shape and intercalary veins’ number were not, or, less integrated within the initially defined leaf functional unit, suggesting more than one module within the leaf traits’ ensemble. Since these traits generally show the greatest species discriminatory power, they potentially underwent effective differential response to selection among oaks. Indeed, the selection of these traits could have driven the ecological preferences between the two sympatric oaks growing under different microclimates.Subject terms: Quantitative trait, Evolutionary biology     

The importance of bottlenecks in protein networks: correlation with gene essentiality and expression dynamics

It has been a long-standing goal in systems biology to find relations between the topological properties and functional features of protein networks. However, most of the focus in network studies has been on highly connected proteins (“hubs”). As a complementary notion, it is possible to define bottlenecks as proteins with a high betweenness centrality (i.e., network nodes that have many “shortest paths” going through them, analogous to major bridges and tunnels on a highway map). Bottlenecks are, in fact, key connector proteins with surprising functional and dynamic properties. In particular, they are more likely to be essential proteins. In fact, in regulatory and other directed networks, betweenness (i.e., “bottleneck-ness”) is a much more significant indicator of essentiality than degree (i.e., “hub-ness”). Furthermore, bottlenecks correspond to the dynamic components of the interaction network—they are significantly less well coexpressed with their neighbors than nonbottlenecks, implying that expression dynamics is wired into the network topology.     

Robustness in phenotypic plasticity and heterogeneity patterns enabled by EMT networks

Epithelial-mesenchymal plasticity (EMP) is a key arm of cancer metastasis and is observed across many contexts. Cells undergoing EMP can reversibly switch between three classes of phenotypes: epithelial (E), mesenchymal (M), and hybrid E/M. While a large number of multistable regulatory networks have been identified to be driving EMP in various contexts, the exact mechanisms and design principles that enable robustness in driving EMP across contexts are not yet fully understood. Here, we investigated dynamic and structural robustness in EMP networks with regard to phenotypic heterogeneity and plasticity. We use two different approaches to simulate these networks: a computationally inexpensive, parameter-independent continuous state space Boolean model, and an ODE-based parameter-agnostic framework (RACIPE), both of which yielded similar phenotypic distributions. While the latter approach is useful for measurements of plasticity, the former model enabled us to extensively investigate robustness in phenotypic heterogeneity. Using perturbations to network topology and by varying network parameters, we show that multistable EMP networks are structurally and dynamically more robust compared with their randomized counterparts, thereby highlighting their topological hallmarks. These features of robustness are governed by a balance of positive and negative feedback loops embedded in these networks. Using a combination of the number of negative and positive feedback loops weighted by their lengths, we identified a metric that can explain the structural and dynamical robustness of these networks. This metric enabled us to compare networks across multiple sizes, and the network principles thus obtained can be used to identify fragilities in large networks without simulating their dynamics. Our analysis highlights a network topology-based approach to quantify robustness in the phenotypic heterogeneity and plasticity emergent from EMP networks.     

The expression of light-related leaf functional traits depends on the location of individual leaves within the crown of isolated Olea europaea trees

Background The spatial arrangement and expression of foliar syndromes within tree crowns can reflect the coupling between crown form and function in a given environment. Isolated trees subjected to high irradiance and concomitant stress may adjust leaf phenotypes to cope with environmental gradients that are heterogeneous in space and time within the tree crown. The distinct expression of leaf phenotypes among crown positions could lead to complementary patterns in light interception at the crown scale.Methods We quantified eight light-related leaf traits across 12 crown positions of ten isolated Olea europaea trees in the field. Specifically, we investigated whether the phenotypic expression of foliar traits differed among crown sectors and layers and five periods of the day from sunrise to sunset. We investigated the consequences in terms of the exposed area of the leaves at the tree scale during a single day.Key Results All traits differed among crown positions except the length-to-width ratio of the leaves. We found a strong complementarity in the patterns of the potential exposed area of the leaves among day periods as a result of a non-random distribution of leaf angles across the crown. Leaf exposure at the outer layer was below 60 % of the displayed surface, reaching maximum interception during morning periods. Daily interception increased towards the inner layer, achieving consecutive maximization from east to west positions within the crown, matching the sun’s trajectory.Conclusions The expression of leaf traits within isolated trees of O. europaea varies continuously through the crown in a gradient of leaf morphotypes and leaf angles depending on the exposure and location of individual leaves. The distribution of light-related traits within the crown and the complementarity in the potential exposure patterns of the leaves during the day challenges the assumption of low trait variability within individuals.     

Mechanisms driving plant functional trait variation in a tropical forest

Plant functional trait variation in tropical forests results from taxonomic differences in phylogeny and associated genetic differences, as well as, phenotypic plastic responses to the environment. Accounting for the underlying mechanisms driving plant functional trait variation is important for understanding the potential rate of change of ecosystems since trait acclimation via phenotypic plasticity is very fast compared to shifts in community composition and genetic adaptation. We here applied a statistical technique to decompose the relative roles of phenotypic plasticity, genetic adaptation, and phylogenetic constraints. We examined typically obtained plant functional traits, such as wood density, plant height, specific leaf area, leaf area, leaf thickness, leaf dry mass content, leaf nitrogen content, and leaf phosphorus content. We assumed that genetic differences in plant functional traits between species and genotypes increase with environmental heterogeneity and geographic distance, whereas trait variation due to plastic acclimation to the local environment is independent of spatial distance between sampling sites. Results suggest that most of the observed trait variation could not be explained by the measured environmental variables, thus indicating a limited potential to predict individual plant traits from commonly assessed parameters. However, we found a difference in the response of plant functional traits, such that leaf traits varied in response to canopy‐light regime and nutrient availability, whereas wood traits were related to topoedaphic factors and water availability. Our analysis furthermore revealed differences in the functional response of coexisting neotropical tree species, which suggests that endemic species with conservative ecological strategies might be especially prone to competitive exclusion under projected climate change.     

Rapid Plant Invasion in Distinct Climates Involves Different Sources of Phenotypic Variation

When exotic species spread over novel environments, their phenotype will depend on a combination of different processes, including phenotypic plasticity (PP), local adaptation (LA), environmental maternal effects (EME) and genetic drift (GD). Few attempts have been made to simultaneously address the importance of those processes in plant invasion. The present study uses the well-documented invasion history of Senecio inaequidens (Asteraceae) in southern France, where it was introduced at a single wool-processing site. It gradually invaded the Mediterranean coast and the Pyrenean Mountains, which have noticeably different climates. We used seeds from Pyrenean and Mediterranean populations, as well as populations from the first introduction area, to explore the phenotypic variation related to climatic variation. A reciprocal sowing experiment was performed with gardens under Mediterranean and Pyrenean climates. We analyzed climatic phenotypic variation in germination, growth, reproduction, leaf physiology and survival. Genetic structure in the studied invasion area was characterized using AFLP. We found consistent genetic differentiation in growth traits but no home-site advantage, so weak support for LA to climate. In contrast, genetic differentiation showed a relationship with colonization history. PP in response to climate was observed for most traits, and it played an important role in leaf trait variation. EME mediated by seed mass influenced all but leaf traits in a Pyrenean climate. Heavier, earlier-germinating seeds produced larger individuals that produced more flower heads throughout the growing season. However, in the Mediterranean garden, seed mass only influenced the germination rate. The results show that phenotypic variation in response to climate depends on various ecological and evolutionary processes associated with geographical zone and life history traits. Seeing the relative importance of EME and GD, we argue that a “local adaptation vs. phenotypic plasticity” approach is therefore not sufficient to fully understand what shapes phenotypic variation and genetic architecture of invasive populations.     

Fisher’s Geometrical Model Emerges as a Property of Complex Integrated Phenotypic Networks

Models relating phenotype space to fitness (phenotype–fitness landscapes) have seen important developments recently. They can roughly be divided into mechanistic models (e.g., metabolic networks) and more heuristic models like Fisher’s geometrical model. Each has its own drawbacks, but both yield testable predictions on how the context (genomic background or environment) affects the distribution of mutation effects on fitness and thus adaptation. Both have received some empirical validation. This article aims at bridging the gap between these approaches. A derivation of the Fisher model “from first principles” is proposed, where the basic assumptions emerge from a more general model, inspired by mechanistic networks. I start from a general phenotypic network relating unspecified phenotypic traits and fitness. A limited set of qualitative assumptions is then imposed, mostly corresponding to known features of phenotypic networks: a large set of traits is pleiotropically affected by mutations and determines a much smaller set of traits under optimizing selection. Otherwise, the model remains fairly general regarding the phenotypic processes involved or the distribution of mutation effects affecting the network. A statistical treatment and a local approximation close to a fitness optimum yield a landscape that is effectively the isotropic Fisher model or its extension with a single dominant phenotypic direction. The fit of the resulting alternative distributions is illustrated in an empirical data set. These results bear implications on the validity of Fisher’s model’s assumptions and on which features of mutation fitness effects may vary (or not) across genomic or environmental contexts.     

Hierarchical ordering of reticular networks

The structure of hierarchical networks in biological and physical systems has long been characterized using the Horton-Strahler ordering scheme. The scheme assigns an integer order to each edge in the network based on the topology of branching such that the order increases from distal parts of the network (e.g., mountain streams or capillaries) to the "root" of the network (e.g., the river outlet or the aorta). However, Horton-Strahler ordering cannot be applied to networks with loops because they they create a contradiction in the edge ordering in terms of which edge precedes another in the hierarchy. Here, we present a generalization of the Horton-Strahler order to weighted planar reticular networks, where weights are assumed to correlate with the importance of network edges, e.g., weights estimated from edge widths may correlate to flow capacity. Our method assigns hierarchical levels not only to edges of the network, but also to its loops, and classifies the edges into reticular edges, which are responsible for loop formation, and tree edges. In addition, we perform a detailed and rigorous theoretical analysis of the sensitivity of the hierarchical levels to weight perturbations. In doing so, we show that the ordering of the reticular edges is more robust to noise in weight estimation than is the ordering of the tree edges. We discuss applications of this generalized Horton-Strahler ordering to the study of leaf venation and other biological networks.     

Cheaters in mutualism networks

Mutualism-network studies assume that all interacting species are mutualistic partners and consider that all links are of one kind. However, the influence of different types of links, such as cheating links, on network organization remains unexplored. We studied two flower-visitation networks (Malpighiaceae and Bignoniaceae and their flower visitors), and divide the types of link into cheaters (i.e. robbers and thieves of flower rewards) and effective pollinators. We investigated if there were topological differences among networks with and without cheaters, especially with respect to nestedness and modularity. The Malpighiaceae network was nested, but not modular, and it was dominated by pollinators and had much fewer cheater species than Bignoniaceae network (28% versus 75%). The Bignoniaceae network was mainly a plant–cheater network, being modular because of the presence of pollen robbers and showing no nestedness. In the Malpighiaceae network, removal of cheaters had no major consequences for topology. In contrast, removal of cheaters broke down the modularity of the Bignoniaceae network. As cheaters are ubiquitous in all mutualisms, the results presented here show that they have a strong impact upon network topology.