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Traits with intuitive names, a clear scope and explicit description are essential for all trait databases. The lack of unified, comprehensive, and machine-readable plant trait definitions limits the utility of trait databases, including reanalysis of data from a single database, or analyses that integrate data across multiple databases. Both can only occur if researchers are confident the trait concepts are consistent within and across sources. Here we describe the AusTraits Plant Dictionary (APD), a new data source of terms that extends the trait definitions included in a recent trait database, AusTraits. The development process of the APD included three steps: review and formalisation of the scope of each trait and the accompanying trait description; addition of trait metadata; and publication in both human and machine-readable forms. Trait definitions include keywords, references, and links to related trait concepts in other databases, enabling integration of AusTraits with other sources. The APD will both improve the usability of AusTraits and foster the integration of trait data across global and regional plant trait databases., (© 2024. The Author(s).)

AbstractIn community ecology, it is widely assumed that organisms with similar traits compete more intensely with one another for resources. This assumption is often encoded into theory and empirical tests via a unimodal competition function, which predicts that per capita competitive effect declines with separation in traits. Yet it remains unknown how well this function represents the true effect of traits on competitive outcomes, especially for long-lived plant communities, where lifetime fitness is difficult to estimate. Here, we evaluate the shape of competition functions embedded in two resource-based (RB) models, wherein plants compete for shared, essential resources. In the first RB model individuals compete for two essential nutrients, and in the second they compete for light in a size-based successional setting. We compared the shapes of the competition functions that emerged from interactions within these RB models to the unimodal function and others shapes commonly applied. In few instances did the trait-based competition function emerging from the RB model even vaguely resemble any of the shapes previously used. The mismatch between these two approaches suggests that theory derived using fixed competition functions based on trait separation may not apply well to plant systems, where individuals compete for shared resources. The more promising path will be to model depletion of resources by populations in relation to their traits, with its consequences for fitness landscapes and competitive exclusion.

Ever since the web began, the number of websites has been growing exponentially. These websites cover an ever-increasing range of online services that fill a variety of social and economic functions across a growing range of industries. Yet the networked nature of the web, combined with the economics of preferential attachment, increasing returns and global trade, suggest that over the long run a small number of competitive giants are likely to dominate each functional market segment, such as search, retail and social media. Here we perform a large scale longitudinal study to quantify the distribution of attention given in the online environment to competing organisations. In two large online social media datasets, containing more than 10 billion posts and spanning more than a decade, we tally the volume of external links posted towards the organisations' main domain name as a proxy for the online attention they receive. We also use the Common Crawl dataset-which contains the linkage patterns between more than a billion different websites-to study the patterns of link concentration over the past three years across the entire web. Lastly, we showcase the linking between economic, financial and market data by exploring the relationships between online attention on social media and the growth in enterprise value in the electric carmaker Tesla. Our analysis shows that despite the fact that we observe consistent growth in all the macro indicators-the total amount of online attention, in the number of organisations with an online presence, and in the functions they perform-we also observe that a smaller number of organisations account for an ever-increasing proportion of total user attention, usually with one large player dominating each function. These results highlight how evolution of the online economy involves innovation, diversity, and then competitive dominance., Competing Interests: The authors have declared that no competing interests exist.

If collecting research data is perceived as poorly rewarded compared to data synthesis and analysis, this can slow overall research progress via two effects. People who have already collected data may be slow to make it openly accessible. Also, researchers may reallocate effort from collecting fresh data to synthesizing and analysing data already accessible. Here, we advocate for a second career currency in the form of data contributions statements embedded within applications for jobs, promotions and research grants. This workable step forward would provide for peer opinion to operate across thousands of selection and promotion committees and granting panels. In this way, fair valuation of data contributions relative to publications could emerge.

Biomedical and clinical sciences are experiencing a renewed interest in the fact that males and females differ in many anatomic, physiological, and behavioural traits. Sex differences in trait variability, however, are yet to receive similar recognition. In medical science, mammalian females are assumed to have higher trait variability due to estrous cycles (the 'estrus-mediated variability hypothesis'); historically in biomedical research, females have been excluded for this reason. Contrastingly, evolutionary theory and associated data support the 'greater male variability hypothesis'. Here, we test these competing hypotheses in 218 traits measured in >26,900 mice, using meta-analysis methods. Neither hypothesis could universally explain patterns in trait variability. Sex bias in variability was trait-dependent. While greater male variability was found in morphological traits, females were much more variable in immunological traits. Sex-specific variability has eco-evolutionary ramifications, including sex-dependent responses to climate change, as well as statistical implications including power analysis considering sex difference in variance., Competing Interests: SZ, FZ, RB, RB, WC, DF, ML, JM, AS, DN, SN No competing interests declared, (© 2020, Zajitschek et al.)

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives., (© 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

The sharing and re-use of data has become a cornerstone of modern science. Multiple platforms now allow easy publication of datasets. So far, however, platforms for data sharing offer limited functions for distributing and interacting with evolving datasets- those that continue to grow with time as more records are added, errors fixed, and new data structures are created. In this article, we describe a workflow for maintaining and distributing successive versions of an evolving dataset, allowing users to retrieve and load different versions directly into the R platform. Our workflow utilizes tools and platforms used for development and distribution of successive versions of an open source software program, including version control, GitHub, and semantic versioning, and applies these to the analogous process of developing successive versions of an open source dataset. Moreover, we argue that this model allows for individual research groups to achieve a dynamic and versioned model of data delivery at no cost., (© The Author(s) 2019. Published by Oxford University Press.)

Plant growth rates drive ecosystem productivity and are a central element of plant ecological strategies. For seedlings grown under controlled conditions, a large literature has firmly identified the functional traits that drive interspecific variation in growth rate. For adult plants, the corresponding knowledge is surprisingly poorly understood. Until recently it was widely assumed that the key trait drivers would be the same (e.g. specific leaf area, or SLA), but an increasing number of papers has demonstrated this not to be the case, or not generally so. New theory has provided a prospective basis for understanding these discrepancies. Here we quantified relationships between stem diameter growth rates and functional traits of adult woody plants for 41 species in an Australian tropical rainforest. From various cost-benefit considerations, core predictions included that: (i) photosynthetic rate would be positively related to growth rate; (ii) SLA would be unrelated to growth rate (unlike in seedlings where it is positively related to growth); (iii) wood density would be negatively related to growth rate; and (iv) leaf mass:sapwood mass ratio (LM:SM) in branches (analogous to a benefit:cost ratio) would be positively related to growth rate. All our predictions found support, particularly those for LM:SM and wood density; photosynthetic rate was more weakly related to stem diameter growth rates. Specific leaf area was convincingly correlated to growth rate, in fact negatively. Together, SLA, wood density and LM:SM accounted for 52 % of variation in growth rate among these 41 species, with each trait contributing roughly similar explanatory power. That low SLA species can achieve faster growth rates than high SLA species was an unexpected result but, as it turns out, not without precedent, and easily understood via cost-benefit theory that considers whole-plant allocation to different tissue types. Branch-scale leaf:sapwood ratio holds promise as an easily measurable variable that may help to understand growth rate variation. Using cost-benefit approaches teamed with combinations of leaf, wood and allometric variables may provide a path towards a more complete understanding of growth rates under field conditions.

Tree death drives population dynamics, nutrient cycling, and evolution within plant communities. Mortality variation across species is thought to be influenced by different factors relative to variation within species. The unified model provided here separates mortality rates into growth-dependent and growth-independent hazards. This model creates the opportunity to simultaneously estimate these hazards both across and within species. Moreover, it provides the ability to examine how species traits affect growth-dependent and growth-independent hazards. We derive this unified mortality model using cross-validated Bayesian methods coupled with mortality data collected over three census intervals for 203 tropical rainforest tree species at Barro Colorado Island (BCI), Panama. We found that growth-independent mortality tended to be higher in species with lower wood density, higher light requirements, and smaller maximum diameter at breast height (dbh). Mortality due to marginal carbon budget as measured by near-zero growth rate tended to be higher in species with lower wood density and higher light demand. The total mortality variation attributable to differences among species was large relative to variation explained by these traits, emphasizing that much remains to be understood. This additive hazards model strengthens our capacity to parse and understand individual-level mortality in highly diverse tropical forests and hence to predict its consequences., Competing Interests: The authors declare no conflict of interest.

Large variations in crown shape are observed across the globe, from plants with wide and deep crowns to those with leaves clustered at the top. While there have been advances in the large-scale monitoring of forests, little is known about factors driving variations in crown shape with environmental conditions. Previous theoretical research suggests a gradient in crown shape with latitude, due to the effects of sun angle. Yet, it remains unclear whether such changes are also predicted under competition. Using a size-structured forest-growth model that incorporates self-shading from plants and competitive shading from their neighbors, we investigate how changes in site productivity and sun angle shape crown evolution. We consider evolution in two traits describing the top-heaviness and width-to-height ratio of crowns, shaped by trade-offs reflecting the costs and benefits of alternative architectures. In top-heavy trees, most of the leaves are at the top half of the trunk. We show that, contrary to common belief, the angle of sun beams per se has only a weak influence on crown shapes, except at low site productivity. By contrast, reduced site productivity has a strong effect, with trees growing in less productive sites keeping their leaves closer to the ground. The crown width-to-height ratio is generally higher at a lower site productivity, but this trait is not strongly influenced by any environmental factor. This theoretical analysis brings into question established beliefs about the effects of latitude on crown shapes. By introducing geometry-related growth constraints caused by shading from both the surrounding forest and the tree on itself, and costs for constructing and maintaining a three-dimensional crown, our analysis suggests crown shapes may vary with latitude, mostly via effects on overall site productivity, and less because of the angle of the sun.

Plant species differ in many functional traits that drive differences in rates of photosynthesis, biomass allocation, and tissue turnover. However, it remains unclear how-and even if-such traits influence whole-plant growth, with the simple linear relationships predicted by existing theory often lacking empirical support. Here, we present a theoretical framework for understanding the effect of diverse functional traits on plant growth and shade tolerance by extending a widely used model, linking growth rate in seedlings with a single leaf trait, to explicitly include influences of size, light environment, and five prominent traits: seed mass, height at maturation, leaf mass per unit leaf area, leaf nitrogen per unit leaf area, and wood density. Based on biomass growth and allocation, this framework explains why the influence of traits on growth rate and shade tolerance often varies with plant size and why the impact of size on growth varies among traits. Specifically, we demonstrate why for height growth the influence of: ( i ) leaf mass per unit leaf area is strong in small plants but weakens with size; ( ii ) leaf nitrogen per unit leaf area does not change with size; ( iii ) wood density is present across sizes; ( iv ) height at maturation strengthens with size; and ( v ) seed mass decreases with size. Moreover, we show how traits moderate plant responses to light environment and also determine shade tolerance, supporting diverse empirical results., Competing Interests: The authors declare no conflict of interest.

Branch formation in trees has an inherent tendency toward exponential growth, but exponential growth in the number of branches cannot continue indefinitely. It has been suggested that trees balance this tendency toward expansion by also losing branches grown in previous growth cycles. Here, we present a model for branch formation and branch loss during ontogeny that builds on the phenomenological assumption of a branch carrying capacity. The model allows us to derive approximate analytical expressions for the number of tips on a branch, the distribution of growth modules within a branch, and the rate and size distribution of tree wood litter produced. Although limited availability of data makes empirical corroboration challenging, we show that our model can fit field observations of red maple (Acer rubrum) and note that the age distribution of discarded branches predicted by our model is qualitatively similar to an empirically observed distribution of dead and abscised branches of balsam poplar (Populus balsamifera). By showing how a simple phenomenological assumption-that the number of branches a tree can maintain is limited-leads directly to predictions on branching structure and the rate and size distribution of branch loss, these results potentially enable more explicit modeling of woody tissues in ecosystems worldwide, with implications for the buildup of flammable fuel, nutrient cycling, and understanding of plant growth.

This corrects the article DOI: 10.1038/sdata.2016.17.

To explain diversity in forests, niche theory must show how multiple plant species coexist while competing for the same resources. Although successional processes are widespread in forests, theoretical work has suggested that differentiation in successional strategy allows only a few species stably to coexist, including only a single shade tolerant. However, this conclusion is based on current niche models, which encode a very simplified view of plant communities, suggesting that the potential for niche differentiation has remained unexplored. Here, we show how extending successional niche models to include features common to all vegetation-height-structured competition for light under a prevailing disturbance regime and two trait-mediated tradeoffs in plant function-enhances the diversity of species that can be maintained, including a diversity of shade tolerants. We identify two distinct axes of potential niche differentiation, corresponding to the traits leaf mass per unit leaf area and height at maturation. The first axis allows for coexistence of different shade tolerances and the second axis for coexistence among species with the same shade tolerance. Addition of this second axis leads to communities with a high diversity of shade tolerants. Niche differentiation along the second axis also generates regions of trait space wherein fitness is almost equalized, an outcome we term "evolutionarily emergent near-neutrality." For different environmental conditions, our model predicts diverse vegetation types and trait mixtures, akin to observations. These results indicate that the outcomes of successional niche differentiation are richer than previously thought and potentially account for mixtures of traits and species observed in forests worldwide.

Here, we aim to understand differences in biomass distribution between major woody plant functional types (PFTs) (deciduous vs evergreen and gymnosperm vs angiosperm) in terms of underlying traits, in particular the leaf mass per area (LMA) and leaf area per unit stem basal area. We used a large compilation of plant biomass and size observations, including observations of 21 084 individuals on 656 species. We used a combination of semiparametric methods and variance partitioning to test the influence of PFT, plant height, LMA, total leaf area, stem basal area and climate on above-ground biomass distribution. The ratio of leaf mass to above-ground woody mass (MF /MS ) varied strongly among PFTs. We found that MF /MS at a given plant height was proportional to LMA across PFTs. As a result, the PFTs did not differ in the amount of leaf area supported per unit above-ground biomass or per unit stem basal area. Climate consistently explained very little additional variation in biomass distribution at a given plant size. Combined, these results demonstrate consistent patterns in above-ground biomass distribution and leaf area relationships among major woody PFTs, which can be used to further constrain global vegetation models., (© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.)

Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures)., (© 2015 John Wiley & Sons Ltd.)

Coral reefs are biologically diverse and ecologically complex ecosystems constructed by stony corals. Despite decades of research, basic coral population biology and community ecology questions remain. Quantifying trait variation among species can help resolve these questions, but progress has been hampered by a paucity of trait data for the many, often rare, species and by a reliance on nonquantitative approaches. Therefore, we propose filling data gaps by prioritizing traits that are easy to measure, estimating key traits for species with missing data, and identifying 'supertraits' that capture a large amount of variation for a range of biological and ecological processes. Such an approach can accelerate our understanding of coral ecology and our ability to protect critically threatened global ecosystems., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Trait-based approaches advance ecological and evolutionary research because traits provide a strong link to an organism's function and fitness. Trait-based research might lead to a deeper understanding of the functions of, and services provided by, ecosystems, thereby improving management, which is vital in the current era of rapid environmental change. Coral reef scientists have long collected trait data for corals; however, these are difficult to access and often under-utilized in addressing large-scale questions. We present the Coral Trait Database initiative that aims to bring together physiological, morphological, ecological, phylogenetic and biogeographic trait information into a single repository. The database houses species- and individual-level data from published field and experimental studies alongside contextual data that provide important framing for analyses. In this data descriptor, we release data for 56 traits for 1547 species, and present a collaborative platform on which other trait data are being actively federated. Our overall goal is for the Coral Trait Database to become an open-source, community-led data clearinghouse that accelerates coral reef research.

A plant's reproductive allocation (RA) schedule describes the fraction of surplus energy allocated to reproduction as it increases in size. While theorists use RA schedules as the connection between life history and energy allocation, little is known about RA schedules in real vegetation. Here we review what is known about RA schedules for perennial plants using studies either directly quantifying RA or that collected data from which the shape of an RA schedule can be inferred. We also briefly review theoretical models describing factors by which variation in RA may arise. We identified 34 studies from which aspects of an RA schedule could be inferred. Within those, RA schedules varied considerably across species: some species abruptly shift all resources from growth to reproduction; most others gradually shift resources into reproduction, but under a variety of graded schedules. Available data indicate the maximum fraction of energy allocated to production ranges from 0.1 to 1 and that shorter lived species tend to have higher initial RA and increase their RA more quickly than do longer-lived species. Overall, our findings indicate, little data exist about RA schedules in perennial plants. Available data suggest a wide range of schedules across species. Collection of more data on RA schedules would enable a tighter integration between observation and a variety of models predicting optimal energy allocation, plant growth rates, and biogeochemical cycles.

Background and Aims: The contemporary relegation of conifers mainly to cold or infertile sites has been ascribed to low competitive ability, as a result of the hydraulic inefficiency of tracheids and their seedlings' initial dependence on small foliage areas. Here it is hypothesized that, in temperate rainforests, the larger leaves of angiosperms also reduce self-shading and thus enable display of larger effective foliage areas than the numerous small leaves of conifers., Methods: This hypothesis was tested using 3-D modelling of plant architecture and structural equation modelling to compare self-shading and light interception potential of seedlings of six conifers and 12 angiosperm trees from temperate rainforests. The ratio of displayed leaf area to plant mass (LAR(d)) was used to indicate plant light interception potential: LAR(d) is the product of specific leaf area, leaf mass fraction, self-shading and leaf angle., Results: Angiosperm seedlings self-shaded less than conifers, mainly because of differences in leaf number (more than leaf size), and on average their LAR(d) was about twice that of conifers. Although specific leaf area was the most pervasive influence on LAR(d), differences in self-shading also significantly influenced LAR(d) of large seedlings., Conclusions: The ability to deploy foliage in relatively few, large leaves is advantageous in minimizing self-shading and enhancing seedling light interception potential per unit of plant biomass. This study adds significantly to evidence that vegetative traits may be at least as important as reproductive innovations in explaining the success of angiosperms in productive environments where vegetation is structured by light competition.

Sapwood cross-sectional area per unit leaf area (SA:LA) is an influential trait that plants coordinate with physical environment and with other traits. We develop theory for SA:LA and also for root surface area per leaf area (RA:LA) on the premise that plants maximizing the surplus of revenue over costs should have competitive advantage. SA:LA is predicted to increase in water-relations environments that reduce photosynthetic revenue, including low soil water potential, high water vapor pressure deficit (VPD), and low atmospheric CO(2). Because sapwood has costs, SA:LA adjustment does not completely offset difficult water relations. Where sapwood costs are large, as in tall plants, optimal SA:LA may actually decline with (say) high VPD. Large soil-to-root resistance caps the benefits that can be obtained from increasing SA:LA. Where a plant can adjust water-absorbing surface area of root per leaf area (RA:LA) as well as SA:LA, optimal RA:SA is not affected by VPD, CO(2) or plant height. If selection favours increased height more so than increased revenue-minus-cost, then height is predicted to rise substantially under improved water-relations environments such as high-CO(2) atmospheres. Evolutionary-attractor theory for SA:LA and RA:LA complements models that take whole-plant conductivity per leaf area as a parameter., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

• Plant light interception efficiency is a crucial determinant of carbon uptake by individual plants and by vegetation. Our aim was to identify whole-plant variables that summarize complex crown architecture, which can be used to predict light interception efficiency. • We gathered the largest database of digitized plants to date (1831 plants of 124 species), and estimated a measure of light interception efficiency with a detailed three-dimensional model. Light interception efficiency was defined as the ratio of the hemispherically averaged displayed to total leaf area. A simple model was developed that uses only two variables, crown density (the ratio of leaf area to total crown surface area) and leaf dispersion (a measure of the degree of aggregation of leaves). • The model explained 85% of variation in the observed light interception efficiency across the digitized plants. Both whole-plant variables varied across species, with differences in leaf dispersion related to leaf size. Within species, light interception efficiency decreased with total leaf number. This was a result of changes in leaf dispersion, while crown density remained constant. • These results provide the basis for a more general understanding of the role of plant architecture in determining the efficiency of light harvesting., (© 2011 The Authors. New Phytologist © 2011 New Phytologist Trust.)

• Co-occurring species often differ in their leaf lifespan (LL) and it remains unclear how such variation is maintained in a competitive context. Here we test the hypothesis that leaves of long-LL species yield a greater return in carbon (C) fixed per unit C or nutrient invested by the plant than those of short-LL species. • For 10 sympatric woodland species, we assessed three-dimensional shoot architecture, canopy openness, leaf photosynthetic light response, leaf dark respiration and leaf construction costs across leaf age sequences. We then used the YPLANT model to estimate light interception and C revenue along the measured leaf age sequences. This was done under a series of simulations that incorporated the potential covariates of LL in an additive fashion. • Lifetime return in C fixed per unit C, N or P invested increased with LL in all simulations. • In contrast to other recent studies, our results show that extended LL confers a fundamental economic advantage by increasing a plant's return on investment in leaves. This suggests that time-discounting effects, that is, the compounding of income that arises from quick reinvestment of C revenue, are key in allowing short-LL species to succeed in the face of this economic handicap., (© 2011 The Authors. New Phytologist © 2011 New Phytologist Trust.)

The question of whether natural selection favors genetic stability or genetic variability is a fundamental problem in evolutionary biology. Bioinformatic analyses demonstrate that selection favors genetic stability by avoiding unstable nucleotide sequences in protein encoding DNA. Yet, such unstable sequences are maintained in several DNA repair genes, thereby promoting breakdown of repair and destabilizing the genome. Several studies have therefore argued that selection favors genetic variability at the expense of stability. Here we propose a new evolutionary mechanism, with supporting bioinformatic evidence, that resolves this paradox. Combining the concepts of gene-dependent mutation biases and meiotic recombination, we argue that unstable sequences in the DNA mismatch repair (MMR) genes are maintained by their own phenotype. In particular, we predict that human MMR maintains an overrepresentation of mononucleotide repeats (monorepeats) within and around the MMR genes. In support of this hypothesis, we report a 31% excess in monorepeats in 250 kb regions surrounding the seven MMR genes compared to all other RefSeq genes (1.75 vs. 1.34%, P = 0.0047), with a particularly high content in PMS2 (2.41%, P = 0.0047) and MSH6 (2.07%, P = 0.043). Based on a mathematical model of monorepeat frequency, we argue that the proposed mechanism may suffice to explain the observed excess of repeats around MMR genes. Our findings thus indicate that unstable sequences in MMR genes are maintained through evolution by the MMR mechanism. The evolutionary paradox of genetically unstable DNA repair genes may thus be explained by an equilibrium in which the phenotype acts back on its own genotype.

Woody stems comprise a large biological carbon fraction and determine water transport between roots and leaves; their structure and function can influence both carbon and hydrological cycles. While angiosperm wood anatomy and density determine hydraulic conductivity and mechanical strength, little is known about interrelations across many species. We compiled a global data set comprising two anatomical traits for 3005 woody angiosperms: mean vessel lumen area (Ā) and number per unit area (N). From these, we calculated vessel lumen fraction (F = ĀN) and size to number ratio (S = Ā/N), a new vessel composition index. We examined the extent to which F and S influenced potential sapwood specific stem conductivity (K(S)) and wood density (D; dry mass/fresh volume). F and S varied essentially independently across angiosperms. Variation in K(S) was driven primarily by S, and variation in D was virtually unrelated to F and S. Tissue density outside vessel lumens (D(N)) must predominantly influence D. High S should confer faster K(S) but incur greater freeze-thaw embolism risk. F should also affect K(S), and both F and D(N) should influence mechanical strength, capacitance, and construction costs. Improved theory and quantification are needed to better understand ecological costs and benefits of these three distinct dimensions.

* Here, we evaluated how increased shading and declining net photosynthetic capacity regulate the decline in net carbon balance with increasing leaf age for 10 Australian woodland species. We also asked whether leaves at the age of their mean life-span have carbon balances that are positive, zero or negative. * The net carbon balances of 2307 leaves on 53 branches of the 10 species were estimated. We assessed three-dimensional architecture, canopy openness, photosynthetic light response functions and dark respiration rate across leaf age sequences on all branches. We used YPLANT to estimate light interception and to model carbon balance along the leaf age sequences. * As leaf age increased to the mean life-span, increasing shading and declining photosynthetic capacity each separately reduced daytime carbon gain by approximately 39% on average across species. Together, they reduced daytime carbon gain by 64% on average across species. * At the age of their mean life-span, almost all leaves had positive daytime carbon balances. These per leaf carbon surpluses were of a similar magnitude to the estimated whole-plant respiratory costs per leaf. Thus, the results suggest that a whole-plant economic framework, including respiratory costs, may be useful in assessing controls on leaf longevity.

Understanding evolutionary coordination among different life-history traits is a key challenge for ecology and evolution. Here we develop a general quantitative model predicting how offspring size should scale with adult size by combining a simple model for life-history evolution with a frequency-dependent survivorship model. The key innovation is that larger offspring are afforded three different advantages during ontogeny: higher survivorship per time, a shortened juvenile phase, and advantage during size-competitive growth. In this model, it turns out that size-asymmetric advantage during competition is the factor driving evolution toward larger offspring sizes. For simplified and limiting cases, the model is shown to produce the same predictions as the previously existing theory on which it is founded. The explicit treatment of different survival advantages has biologically important new effects, mainly through an interaction between total maternal investment in reproduction and the duration of competitive growth. This goes on to explain alternative allometries between log offspring size and log adult size, as observed in mammals (slope = 0.95) and plants (slope = 0.54). Further, it suggests how these differences relate quantitatively to specific biological processes during recruitment. In these ways, the model generalizes across previous theory and provides explanations for some differences between major taxa.

Fitting a line to a bivariate dataset can be a deceptively complex problem, and there has been much debate on this issue in the literature. In this review, we describe for the practitioner the essential features of line-fitting methods for estimating the relationship between two variables: what methods are commonly used, which method should be used when, and how to make inferences from these lines to answer common research questions. A particularly important point for line-fitting in allometry is that usually, two sources of error are present (which we call measurement and equation error), and these have quite different implications for choice of line-fitting method. As a consequence, the approach in this review and the methods presented have subtle but important differences from previous reviews in the biology literature. Linear regression, major axis and standardised major axis are alternative methods that can be appropriate when there is no measurement error. When there is measurement error, this often needs to be estimated and used to adjust the variance terms in formulae for line-fitting. We also review line-fitting methods for phylogenetic analyses. Methods of inference are described for the line-fitting techniques discussed in this paper. The types of inference considered here are testing if the slope or elevation equals a given value, constructing confidence intervals for the slope or elevation, comparing several slopes or elevations, and testing for shift along the axis amongst several groups. In some cases several methods have been proposed in the literature. These are discussed and compared. In other cases there is little or no previous guidance available in the literature. Simulations were conducted to check whether the methods of inference proposed have the intended coverage probability or Type I error. We identified the methods of inference that perform well and recommend the techniques that should be adopted in future work.

Global-scale quantification of relationships between plant traits gives insight into the evolution of the world's vegetation, and is crucial for parameterizing vegetation-climate models. A database was compiled, comprising data for hundreds to thousands of species for the core 'leaf economics' traits leaf lifespan, leaf mass per area, photosynthetic capacity, dark respiration, and leaf nitrogen and phosphorus concentrations, as well as leaf potassium, photosynthetic N-use efficiency (PNUE), and leaf N : P ratio. While mean trait values differed between plant functional types, the range found within groups was often larger than differences among them. Future vegetation-climate models could incorporate this knowledge. The core leaf traits were intercorrelated, both globally and within plant functional types, forming a 'leaf economics spectrum'. While these relationships are very general, they are not universal, as significant heterogeneity exists between relationships fitted to individual sites. Much, but not all, heterogeneity can be explained by variation in sample size alone. PNUE can also be considered as part of this trait spectrum, whereas leaf K and N : P ratios are only loosely related.

•  Architecture can vary widely across species. Both steeper leaf angles and increased self-shading are thought to reduce potential carbon gain by decreasing total light interception. An alternative hypothesis is that steeper leaf angles have evolved to improve day-long carbon gain by emphasising light interception from low angles. •  Here we relate variation in architectural properties (leaf angle and leaf size) to cross-species patterns of leaf display, light capture and simulated carbon gain in branching-units of 38 perennial species occurring at two sites in Australian forest. Architectural comparison was made possible by combining 3D-digitising with the architecture model YPLANT. •  Species with shallow angled leaves had greater daily light interception and potentially greater carbon gain. Self-shading, rather than leaf angle, explained most variance between species in light capture and potential carbon gain. Species average leaf size was the most important determinant of self-shading. •  Our results provide the first cross-species evidence that steeper leaf angles function to reduce exposure to excess light levels during the middle of the day, more than to maximise carbon gain.