Mixed-species flock sizes and compositions influence flock members' success in three field experiments with novel feeders.

Mixed-species groups and aggregations are quite common and may provide substantial fitness-related benefits to group members. Individuals may benefit from the overall size of the mixed-species group or from the diversity of species present, or both. Here we exposed mixed-species flocks of songbirds (Carolina chickadees, Poecile carolinensis, tufted titmice, Baeolophus bicolor, and the satellite species attracted to these two species) to three different novel feeder experiments to assess the influence of mixed-species flock size and composition on ability to solve the feeder tasks. We also assessed the potential role of habitat density and traffic noise on birds' ability to solve these tasks. We found that likelihood of solving a novel feeder task was associated with mixed-species flock size and composition, though the specific social factor involved depended on the particular species and on the novel feeder. We did not find an influence of habitat density or background traffic noise on likelihood of solving novel feeder tasks. Overall, our results reveal the importance of variation in mixed-species group size and diversity on foraging success in these songbirds.

Influence of social and physical environmental variation on antipredator behavior in mixed-species parid flocks.

Carolina chickadees (Poecile carolinensis) and tufted titmice (Baeolophus bicolor) regularly form flocks with multiple species through the winter months, including white-breasted nuthatches (Sitta carolinensis). Earlier studies found that behavior of both chickadees and titmice was sensitive to mixed-species flock composition. Little is known about the influence of background noise level and vegetation density on the antipredator behaviors of individuals within these flocks, however. We tested for the effects of vegetation density, traffic noise, and flock composition (conspecific number, flock diversity, and flock size) on antipredator behavioral responses following an alarm call playback (Study 1) and an owl model presentation (Study 2) at feeders. We recorded background traffic noise and performed lidar scans to quantify vegetation density at each site. After a feeder had been stocked with seed and a flock was present, we recorded calls produced, and we identified flock composition metrics. We coded seed-taking latency, call latency, mob latency, and mob duration following the respective stimulus presentation and tested for effects of flock composition metrics, vegetation density, and background noise on these responses. For the alarm call playback study, flock composition drove behaviors in chickadees and titmice, and vegetation density drove behaviors in chickadees and nuthatches. For the owl model study, conspecific number predicted behavior in chickadees, and mob duration was predicted by nuthatch number. The results reveal individual sensitivity to group composition in anti-predatory and foraging behavior in simulated risky contexts. Additionally, our data suggest that the modality of perceived simulated risk (acoustic vs. visual) and the density of vegetation influence behavior in these groups.

Flow similarity model predicts the allometry and allometric covariation of petiole dimensions.

Allometric relationships for plants, plant organs and plant parts, have long generated interest among biologists. Several prominent theoretical models based on biomechanical and/or hydraulic arguments have been introduced with mixed support. Here, I test a more recent offering, flow similarity, which is based on the conservation of volumetric flow rate and velocity. Using dimensional data for 935 petioles from 43 angiosperm species, I show that both the intraspecific and interspecific petiole allometries are more closely aligned with the predictions of the flow similarity model than that of elastic or geometric similarity. Further, allometric covariation among empirical scaling exponents falls along predicted functions with clustering around the flow similarity predictions. This work adds to the body of literature highlighting the importance of hydraulics in understanding the physiological basis of plant allometries, identifies previously unknown central tendencies in petiole allometry, and helps to delineate the scope within which the flow similarity model may be applicable.

Considering humans as habitat reveals evidence of successional disease ecology among human pathogens.

The realization that ecological principles play an important role in infectious disease dynamics has led to a renaissance in epidemiological theory. Ideas from ecological succession theory have begun to inform an understanding of the relationship between the individual microbiome and health but have not yet been applied to investigate broader, population-level epidemiological dynamics. We consider human hosts as habitat and apply ideas from succession to immune memory and multi-pathogen dynamics in populations. We demonstrate that ecologically meaningful life history characteristics of pathogens and parasites, rather than epidemiological features alone, are likely to play a meaningful role in determining the age at which people have the greatest probability of being infected. Our results indicate the potential importance of microbiome succession in determining disease incidence and highlight the need to explore how pathogen life history traits and host ecology influence successional dynamics. We conclude by exploring some of the implications that inclusion of successional theory might have for understanding the ecology of diseases and their hosts.

Flow similarity, stochastic branching, and quarter-power scaling in plants.

The origin of allometric scaling patterns that are multiples of one-fourth has long fascinated biologists. While not universal, quarter-power scaling relationships are common and have been described in all major clades. Several models have been advanced to explain the origin of such patterns, but questions regarding the discordance between model predictions and empirical data have limited their widespread acceptance. Notable among these is a fractal branching model that predicts power-law scaling of both metabolism and physical dimensions. While a power law is a useful first approximation to some data sets, nonlinear data compilations suggest the possibility of alternative mechanisms. Here, we show that quarter-power scaling can be derived using only the preservation of volume flow rate and velocity as model constraints. Applying our model to land plants, we show that incorporating biomechanical principles and allowing different parts of plant branching networks to be optimized to serve different functions predicts nonlinearity in allometric relationships and helps explain why interspecific scaling exponents covary along a fractal continuum. We also demonstrate that while branching may be a stochastic process, due to the conservation of volume, data may still be consistent with the expectations for a fractal network when one examines sub-trees within a tree. Data from numerous sources at the level of plant shoots, stems, and petioles show strong agreement with our model predictions. This theoretical framework provides an easily testable alternative to current general models of plant metabolic allometry.

When do children avoid infection risks: Lessons for schools during the COVID-19 pandemic.

The physical closing of schools because of COVID-19 has disrupted both student learning and family logistics. There is significant pressure for in-person learning to remain open for all children. However, as is expected with outbreaks of novel infections, vaccines and other pharmaceutical therapeutics may not be instantly available. This raises serious public health questions about the risks to children and society at large. The best protective measures for keeping young children in school focus on behaviors that limit transmission. It is therefore critical to understand how we can engage children in age-appropriate ways that will best support their ability to adhere to protocols effectively. Here, we synthesize published studies with new results to investigate the earliest ages at which children form an understanding of infection risk and when they can translate that understanding effectively to protective action.

Morphological Plant Modeling: Unleashing Geometric and Topological Potential within the Plant Sciences.

The geometries and topologies of leaves, flowers, roots, shoots, and their arrangements have fascinated plant biologists and mathematicians alike. As such, plant morphology is inherently mathematical in that it describes plant form and architecture with geometrical and topological techniques. Gaining an understanding of how to modify plant morphology, through molecular biology and breeding, aided by a mathematical perspective, is critical to improving agriculture, and the monitoring of ecosystems is vital to modeling a future with fewer natural resources. In this white paper, we begin with an overview in quantifying the form of plants and mathematical models of patterning in plants. We then explore the fundamental challenges that remain unanswered concerning plant morphology, from the barriers preventing the prediction of phenotype from genotype to modeling the movement of leaves in air streams. We end with a discussion concerning the education of plant morphology synthesizing biological and mathematical approaches and ways to facilitate research advances through outreach, cross-disciplinary training, and open science. Unleashing the potential of geometric and topological approaches in the plant sciences promises to transform our understanding of both plants and mathematics.

Apparent Overinvestment in Leaf Venation Relaxes Leaf Morphological Constraints on Photosynthesis in Arid Habitats.

Leaf veins supply the mesophyll with water that evaporates when stomata are open to allow CO2 uptake for photosynthesis. Theoretical analyses suggest that water is optimally distributed in the mesophyll when the lateral distance between veins (dx) is equal to the distance from these veins to the epidermis (dy), expressed as dx:dy ≈ 1. Although this theory is supported by observations of many derived angiosperms, we hypothesize that plants in arid environments may reduce dx:dy below unity owing to climate-specific functional adaptations of increased leaf thickness and increased vein density. To test our hypothesis, we assembled leaf hydraulic, morphological, and photosynthetic traits of 68 species from the Eucalyptus and Corymbia genera (termed eucalypts) along an aridity gradient in southwestern Australia. We inferred the potential gas-exchange advantage of reducing dx beyond dy using a model that links leaf morphology and hydraulics to photosynthesis. Our observations reveal that eucalypts in arid environments have thick amphistomatous leaves with high vein densities, resulting in dx:dy ratios that range from 1.6 to 0.15 along the aridity gradient. Our model suggests that, as leaves become thicker, the effect of reducing dx beyond dy is to offset the reduction in leaf gas exchange that would result from maintaining dx:dy at unity. This apparent overinvestment in leaf venation may be explained from the selective pressure of aridity, under which traits associated with long leaf life span, high hydraulic and thermal capacitances, and high potential rates of leaf water transport confer a competitive advantage.

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.

Optimal allocation of leaf epidermal area for gas exchange.

A long-standing research focus in phytology has been to understand how plants allocate leaf epidermal space to stomata in order to achieve an economic balance between the plant's carbon needs and water use. Here, we present a quantitative theoretical framework to predict allometric relationships between morphological stomatal traits in relation to leaf gas exchange and the required allocation of epidermal area to stomata. Our theoretical framework was derived from first principles of diffusion and geometry based on the hypothesis that selection for higher anatomical maximum stomatal conductance (gsmax ) involves a trade-off to minimize the fraction of the epidermis that is allocated to stomata. Predicted allometric relationships between stomatal traits were tested with a comprehensive compilation of published and unpublished data on 1057 species from all major clades. In support of our theoretical framework, stomatal traits of this phylogenetically diverse sample reflect spatially optimal allometry that minimizes investment in the allocation of epidermal area when plants evolve towards higher gsmax . Our results specifically highlight that the stomatal morphology of angiosperms evolved along spatially optimal allometric relationships. We propose that the resulting wide range of viable stomatal trait combinations equips angiosperms with developmental and evolutionary flexibility in leaf gas exchange unrivalled by gymnosperms and pteridophytes.

Evaluating general allometric models: interspecific and intraspecific data tell different stories due to interspecific variation in stem tissue density and leaf size.

The ability of general scaling models to capture the central tendency or dispersion in biological data has been questioned. In fact, the appropriate domain of such models has never been clearly articulated and they have been supported and challenged using both interspecific and/or intraspecific data. Here, we evaluate several simplifying assumptions and predictions of two prominent scaling models: West, Brown and Enquist's fractal model (WBE) and a null model of geometric similarity (GEOM). Using data for 53 herbaceous angiosperm species from the Songnen Grasslands of Northern China, we compared both the interspecific and intraspecific scaling relationships for plant geometry and biomass partitioning. Specifically, we considered biomass investment in shoots and leaves as well as related several traits not commonly collected in plant allometric analyses: shoot volume, leaf number, and mean leaf mass. At the interspecific level, we find substantial variation in regression slopes, and the simplifying assumptions of WBE and predictions of both the WBE and GEOM models do not hold. In contrast, we find substantial support for the WBE model at the intraspecific level, and to a lesser extent for GEOM. The differences between our results at interspecific and intraspecific levels are due to the fact that leaf size and stem tissue density vary considerably across species in contrast to the simplifying assumptions of WBE. These results highlight the domain within which simplifying model assumptions might be most appropriate, and suggest allometric models may be useful points of departure within some species, growth forms or taxonomic groups.

Isometric partitioning of hydraulic conductance between leaves and stems: balancing safety and efficiency in different growth forms and habitats.

Recent advances in modelling the architecture and function of the plant hydraulic network have led to improvements in predicting and interpreting the consequences of functional trait variation on CO2 uptake and water loss. We build upon one such model to make novel predictions for scaling of the total specific hydraulic conductance of leaves and shoots (kL and kSH , respectively) and variation in the partitioning of hydraulic conductance. Consistent with theory, we observed isometric (slope = 1) scaling between kL and kSH across several independently collected datasets and a lower ratio of kL and kSH , termed the leaf-to-shoot conductance ratio (CLSCR ), in arid environments and in woody species. Isometric scaling of kL and kSH supports the concept that hydraulic design is coordinated across the plant. We propose that CLSCR is an important adaptive trait that represents the trade-off between efficiency and safety at the scale of the whole plant.

Costs and benefits of reticulate leaf venation.

BACKGROUND: Recent theoretical and empirical work has identified redundancy as one of the benefits of the reticulate form in the evolution of leaf vein networks. However, we know little about the costs of redundancy or how those costs depend on vein network geometry or topology. Here, we examined both costs and benefits to redundancy in 339 individual reticulate leaf networks comprising over 3.5 million vein segments. We compared levels of costs and benefits within reticulate networks to those within analogous networks without loops known as Maximum Spanning Trees (MSTs). RESULTS: We show that network robustness to varying degrees of simulated damage is positively correlated with structural indices of redundancy. We further show that leaf vein networks are topologically, geometrically and functionally more redundant than are MSTs. However, increased redundancy comes with minor costs in terms of increases in material allocation or decreases in conductance. We also show that full networks do not markedly decrease the distance to non-vein tissue in comparison to MSTs. CONCLUSIONS: These results suggest the evolutionary transition to the reticulate type of networks found in modern Angiosperm flora involved a relatively minor increase in material and conductance costs with significant benefits in terms of network redundancy.

Reading the leaves: A comparison of leaf rank and automated areole measurement for quantifying aspects of leaf venation.

The reticulate venation that is characteristic of a dicot leaf has excited interest from systematists for more than a century, and from physiological and developmental botanists for decades. The tools of digital image acquisition and computer image analysis, however, are only now approaching the sophistication needed to quantify aspects of the venation network found in real leaves quickly, easily, accurately, and reliably enough to produce biologically meaningful data. In this paper, we examine 120 leaves distributed across vascular plants (representing 118 genera and 80 families) using two approaches: a semiquantitative scoring system called "leaf ranking," devised by the late Leo Hickey, and an automated image-analysis protocol. In the process of comparing these approaches, we review some methodological issues that arise in trying to quantify a vein network, and discuss the strengths and weaknesses of automatic data collection and human pattern recognition. We conclude that subjective leaf rank provides a relatively consistent, semiquantitative measure of areole size among other variables; that modal areole size is generally consistent across large sections of a leaf lamina; and that both approaches-semiquantitative, subjective scoring; and fully quantitative, automated measurement-have appropriate places in the study of leaf venation.

ClearedLeavesDB: an online database of cleared plant leaf images.

BACKGROUND: Leaf vein networks are critical to both the structure and function of leaves. A growing body of recent work has linked leaf vein network structure to the physiology, ecology and evolution of land plants. In the process, multiple institutions and individual researchers have assembled collections of cleared leaf specimens in which vascular bundles (veins) are rendered visible. In an effort to facilitate analysis and digitally preserve these specimens, high-resolution images are usually created, either of entire leaves or of magnified leaf subsections. In a few cases, collections of digital images of cleared leaves are available for use online. However, these collections do not share a common platform nor is there a means to digitally archive cleared leaf images held by individual researchers (in addition to those held by institutions). Hence, there is a growing need for a digital archive that enables online viewing, sharing and disseminating of cleared leaf image collections held by both institutions and individual researchers. DESCRIPTION: The Cleared Leaf Image Database (ClearedLeavesDB), is an online web-based resource for a community of researchers to contribute, access and share cleared leaf images. ClearedLeavesDB leverages resources of large-scale, curated collections while enabling the aggregation of small-scale collections within the same online platform. ClearedLeavesDB is built on Drupal, an open source content management platform. It allows plant biologists to store leaf images online with corresponding meta-data, share image collections with a user community and discuss images and collections via a common forum. We provide tools to upload processed images and results to the database via a web services client application that can be downloaded from the database. CONCLUSIONS: We developed ClearedLeavesDB, a database focusing on cleared leaf images that combines interactions between users and data via an intuitive web interface. The web interface allows storage of large collections and integrates with leaf image analysis applications via an open application programming interface (API). The open API allows uploading of processed images and other trait data to the database, further enabling distribution and documentation of analyzed data within the community. The initial database is seeded with nearly 19,000 cleared leaf images representing over 40 GB of image data. Extensible storage and growth of the database is ensured by using the data storage resources of the iPlant Discovery Environment. ClearedLeavesDB can be accessed at http://clearedleavesdb.org.

Estimates of leaf vein density are scale dependent.

Leaf vein density (LVD) has garnered considerable attention of late, with numerous studies linking it to the physiology, ecology, and evolution of land plants. Despite this increased attention, little consideration has been given to the effects of measurement methods on estimation of LVD. Here, we focus on the relationship between measurement methods and estimates of LVD. We examine the dependence of LVD on magnification, field of view (FOV), and image resolution. We first show that estimates of LVD increase with increasing image magnification and resolution. We then demonstrate that estimates of LVD are higher with higher variance at small FOV, approaching asymptotic values as the FOV increases. We demonstrate that these effects arise due to three primary factors: (1) the tradeoff between FOV and magnification; (2) geometric effects of lattices at small scales; and; (3) the hierarchical nature of leaf vein networks. Our results help to explain differences in previously published studies and highlight the importance of using consistent magnification and scale, when possible, when comparing LVD and other quantitative measures of venation structure across leaves.

The role of root exuded low molecular weight organic anions in facilitating petroleum hydrocarbon degradation: current knowledge and future directions.

Rhizoremediation is a bioremediation technique whereby enhanced microbial degradation of organic contaminants occurs within the plant root zone (rhizosphere). It is considered an effective and affordable 'green technology' for remediating soils contaminated with petroleum hydrocarbons (PHCs). This paper critically reviews the potential role of root exuded compounds in rhizoremediation, with emphasis on commonly exuded low molecular weight aliphatic organic acid anions (carboxylates). The extent to which remediation is achieved shows wide disparity among plant species. Therefore, plant selection is crucial for the advancement and widespread adoption of this technology. Root exudation is speculated to be one of the predominant factors leading to microbial changes in the rhizosphere and thus the potential driver behind enhanced petroleum biodegradation. Carboxylates can form a significant component of the root exudate mixture and are hypothesised to enhance petroleum biodegradation by: i) providing an easily degradable energy source; ii) increasing phosphorus supply; and/or iii) enhancing the contaminant bioavailability. These differing hypotheses, which are not mutually exclusive, require further investigation to progress our understanding of plant-microbe interactions with the aim to improve plant species selection and the efficacy of rhizoremediation.

The influence of branch order on optimal leaf vein geometries: Murray's law and area preserving branching.

Models that predict the form of hierarchical branching networks typically invoke optimization based on biomechanical similitude, the minimization of impedance to fluid flow, or construction costs. Unfortunately, due to the small size and high number of vein segments found in real biological networks, complete descriptions of networks needed to evaluate such models are rare. To help address this we report results from the analysis of the branching geometry of 349 leaf vein networks comprising over 1.5 million individual vein segments. In addition to measuring the diameters of individual veins before and after vein bifurcations, we also assign vein orders using the Horton-Strahler ordering algorithm adopted from the study of river networks. Our results demonstrate that across all leaves, both radius tapering and the ratio of daughter to parent branch areas for leaf veins are in strong agreement with the expectation from Murray's law. However, as veins become larger, area ratios shift systematically toward values expected under area-preserving branching. Our work supports the idea that leaf vein networks differentiate roles of leaf support and hydraulic supply between hierarchical orders.

Testing the metabolic theory of ecology.

The metabolic theory of ecology (MTE) predicts the effects of body size and temperature on metabolism through considerations of vascular distribution networks and biochemical kinetics. MTE has also been extended to characterise processes from cellular to global levels. MTE has generated both enthusiasm and controversy across a broad range of research areas. However, most efforts that claim to validate or invalidate MTE have focused on testing predictions. We argue that critical evaluation of MTE also requires strong tests of both its theoretical foundations and simplifying assumptions. To this end, we synthesise available information and find that MTE's original derivations require additional assumptions to obtain the full scope of attendant predictions. Moreover, although some of MTE's simplifying assumptions are well supported by data, others are inconsistent with empirical tests and even more remain untested. Further, although many predictions are empirically supported on average, work remains to explain the often large variability in data. We suggest that greater effort be focused on evaluating MTE's underlying theory and simplifying assumptions to help delineate the scope of MTE, generate new theory and shed light on fundamental aspects of biological form and function.

LEAF GUI: analyzing the geometry of veins and areoles using image segmentation algorithms.

The Leaf Extraction and Analysis Framework Graphical User Interface (LEAF GUI) software is designed for biologists who wish to analyze the structure of vessel bundles (veins) in leaves. The software enables users to extract descriptive statistics on the dimensions and positions of leaf veins and areoles by utilizing a series of thresholding, cleaning, and segmentation algorithms applied to images of leaf veins. The resulting statistics for the dimensions of individual veins and the areoles they surround can then be used to evaluate numerous hypotheses regarding the structure and function of leaf veins.