Biology subjects

Falster, D. S.

Publications and source records attributed to Falster, D. S..

16 recordsLinked to original sources

bioRxiv2026

Contrasting climate signals between native and introduced annual and perennial floras

Annual versus perennial life histories represent a fundamental axis of plant strategy, with empirical evidence showing that the proportion of annuals is greater in hot, arid, or variable climates. Crucially, introduced species, a group that disproportionately includes annuals, are expanding in number and range across the globe. Whether introduced richness is governed by the same climatic controls as native richness remains untested at continental scales. For 19,299 native (12% annual) and 2,802 introduced (34% annual) Australian plant species, we show that native annual richness tracks climate far more tightly than introduced annual richness. Both floras largely follow the global pattern: the annual fraction rises in dry and seasonal climates. However, hotspots of native and introduced annual richness are completely different. Introduced annuals (28% of all annual species) concentrate in wet, populated areas with low precipitation seasonality, whereas native annual richness is fairly evenly distributed, with the highest diversity in the seasonal tropics. The current continental-scale pattern is thus the sum of a long interaction between the native floras life histories and in situ climate, with dynamic, path-dependent introductions layered on top. As introductions and range expansions continue, they will reshape the annual-to-perennial balance along pathways of human influence.

ecology↗

bioRxiv2026

Nutrient currencies and P resorption greatly amplify the perceived costs of reproductive allocation in perennial heath shrubs

SummaryO_LIIn woody perennials, reproductive allocation considered as a fraction of NPP (RA) has been rarely quantified, especially tracked across plant lifetimes, measured in biologically meaningful currencies, and separated from standing biomass. C_LIO_LIWe addressed this gap by measuring dry mass, nitrogen, and phosphorus for every aboveground tissue type for 14 iteroparous perennial shrubs tracked across their full lifetimes, calculating RA using four accounting schemes and three currencies. C_LIO_LIRA was substantially higher by mid-life than typical estimates from ecosystem-scale studies. Distinguishing standing biomass from yearly production further revised RA upwards. Using a nutrient currency (especially P) increased the perceived costs of reproduction. Propagules were highly nutrient-enriched and reproductive accessory costs consumed more nutrients than did the propagules themselves. Considering N and P resorption from senescing leaves and wood shrank the effective vegetative nutrient budget, further concentrating net annual nutrient demand in reproductive tissues. C_LIO_LIOur results highlight high investment in RA for woody perennials, especially using nutrient currencies. Broadly similar allocation patterns were observed across species with different functional traits and lifespans, suggesting generality that may apply across biomes. Widespread underestimation of RA in forest growth models likely overestimates the proportion of NPP available for vegetative growth, leading to substantial errors in predictions. C_LI

ecology↗

bioRxiv2026

A general framework explaining variation in plant economics traits with environment and through ontogeny

Plant economics traits, such as leaf mass per unit leaf area (LMA) and stem specific density (SSD), capture diversity among plant species in how common tissues (leaf, wood, root) are constructed. These traits are key descriptors of plant strategy, yet it has proven difficult to explain this variation with theory and process-based models. Here we reveal a general explanation on why these economics traits vary with environment, through ontogeny, and with other plant traits. This explanation relies on three core assumptions: 1) plants seek to maximise growth rate, 2) growth rate can be decomposed into a product, and 3) there is a tradeoff between the efficiency of tissue construction and tissue turnover rate. Formulation of growth as a product is essential, as it causes the optimal value of an economics trait to vary with the plants biomass production rate, which means economics traits will naturally covary with the abiotic environment, the competitive context, and other strategical features of the plant. Finally, we show how a modification of the trait into plastic and non-plastic components alters the magnitude of intra-specific responses, aligning model responses with empirical trends. Broadly, our results help explain how plant form and function for a wide diversity of species is shaped to suit their environment and, moreover, they reveal insight into a general fast-slow spectrum (Reich 2014) with coordinated shifts among organs (leaf & stem) through tradeoffs between efficient tissue construction and turnover.

ecology↗

bioRxiv2025

hmde: Hierarchical Methods for Differential Equations

AbstractRepeat observations of size are a common tool for understanding growth across taxa, and are used to estimate parameters for functions that describe growth rates. Recent advances in estimating differential equation parameters with a hierarchical longitudinal model have gone beyond available software. Custom implementation of such models is a barrier to use particularly for people who are not familiar with statistical programming. We introduce a new R package implementing a hierarchical Bayesian longitudinal model for repeat observation data with three growth models from ecological case studies. The package provides tools for model fitting and estimate extraction, example data, and case studies to demonstrate the use-case for each of the example models.

bioinformatics↗

bioRxiv2024

Yes, they're all individuals: Hierarchical models for repeat survey data improve estimates of tree growth and size

AbstractO_LIRepeat measurement surveys of tree size are used in forests to estimate growth be-haviour, biomass, and population dynamics. Although size is measured with error, and individuals vary in their growth trajectories, current size-based growth modelling approaches do not usually or fully account for both of these features, and therefore under-utilise available data. C_LIO_LIWe present a new method that leverages the auto-correlation structure of repeat surveys into a hierarchical Bayesian longitudinal growth model. This new structure allows users to correct for measurement error and capture individual-level variation in growth trajectories and parameters. C_LIO_LITo demonstrate the new method we applied it to a sample of tropical tree survey data from long-term monitoring sites at Barro Colorado Island. We were able to reduce estimated error in size and growth, and extract individual-and population-level growth parameter estimates. We used simulation to evaluate the ability of the new method to improve estimates of growth rate and size, and estimate individual and species-level parameters. Our method substantially improved RMSE for growth by an average of 61% compared to existing approaches using pairwise differences; and reduced RMSE in estimated size RMSE compared to observed values in simulated data. Better numerical integration methods (Runge-Kutta 4th order in comparison to Euler and midpoint) provided better estimates of parameters, but did not improve the estimation of size and growth. The choice of a positive growth function eliminated all negative increments without data exclusion. C_LIO_LIOverall, this study shows how we can gain new and improved insights on growth, using repeat forest surveys. Our new method offers improved biomass dynamics estimation through reduced error in sizes over time, coupled with novel information about within-species variation in growth behaviour that is inaccessible with species average models, such as individual parameters for the growth function which allows for relationships between parameters to be considered for the first time. C_LI

ecology↗

bioRxiv2024

traits.build: a data model, workflow and R package for building harmonised ecological trait databases

Trait databases have proliferated over the past decades, facilitating research on the ecology, evolution, and conservation of taxa across the Tree of Life. Typically, teams of independent researchers build these databases, and each must develop their own workflow and output structure. This divests research hours from downstream tasks such as trait-based analysis and interpretation and the resultant datasets are often difficult to integrate due to disparate database structures. Here we introduce the {traits.build} package, which offers a generalised workflow for building trait databases. {traits.build} contains bespoke functions for propagating metadata files, extensive tutorials, and sample configuration files, allowing researchers to efficiently build a new trait database using open source tools. In addition, the {traits.build} output structure is fully documented by a data model, ensuring the meaning of each variable and sematic relationship between variables is transparent and consistent. The data standard links to terms in previously published data standards, drawing strongly on DarwinCore and the Ecological Trait-data Standard, but also includes the ability to fully map location and context properties absent from these vocabularies., It is the first published database-building workflow that adheres to the Extensible Observation Ontology. Simultaneously developing a generalised workflow and publishing a data standard for the workflow provides {traits.build} users a straightforward pathway to build a new trait database that achieves the FAIR principles. The meaning of all variables in a {traits.build} database are already documented, allowing further integration with either other {traits.build} databases or indeed any other database with a documented data model. This follows the vision of the Open Traits Network to build trait databases whose data can be easily integrated for further analysis.

bioinformatics↗

bioRxiv2024

APCalign: an R package workflow and app for aligning and updating flora names to the Australian Plant Census

Here we present "APCalign", an R package and accompanying browser-sourced application to align and update scientific names for Australian vascular plants to the most likely currently accepted name using the Australian Plant Census (APC) or a name in the Australian Plant Names Index (APNI). Scientific names are the label assigned to unique taxon concepts by the scientific community, but this common terminology is most useful if a taxon concept is consistently referred to by the same name. These links can be broken due to either spelling mistakes or taxonomic changes. Automated tools are required to resolve taxon lists, aligning and updating long lists of possibly erroneous scientific names to the most likely currently accepted names. It is essential that tools specific to the APC/APNI be developed, as these lists specify an endorsed national-level nomenclature used in government legislation and include the uniquely Australian concept of phrase names, absent in global taxonomic datasets. To align input names to names within the APC or APNI, "APCalign" works progressively through a sequence of checks that combine different permutations of the input name, exact versus fuzzy matches, matches that consider the entire name input versus a subset of words, and character strings that indicate a name can only be resolved to a genus or family. The aligned names are then, when possible, updated to a currently accepted taxon concept within the APC. This package should facilitate all research outputs that require diverse scientific name lists to be merged or outdated lists to be updated.

plant biology↗

bioRxiv2024

Explaining plant trait variation in response to soil water availability using an optimal height-growth model

1Climate change is expected to bring about changes in precipitation and temperature regimes that, together with rising atmospheric CO2 concentrations, will likely reorganise the functional trait composition of ecosystems. Predicting plant trait responses to emerging environmental conditions including, in particular, water availability, is a tremendous challenge, but is one that eco-evolutionary optimality theory (EEO) can help us undertake. However, most EEO approaches are based on the hypothesis that traits are selected to maximise carbon assimilation which omits the important role that size growth plays in determining fitness outcomes. Using a height-growth based EEO framework, we predict magnitude and directional shifts in four key traits: leaf mass per area, sapwood area to leaf area ratio (Huber value), wood density and sapwood-specific conductivity in response to variation in soil moisture availability, atmospheric aridity, CO2 and light availability. Consistent with empirical patterns, we predict that trait optima shift from resource-acquisitive strategies characterised by low tissue constructions costs and high rates of tissue turnover and sapwood conductivity to resource-conservative strategies - characterised by low rates of tissue turnover and greater xylem embolism resistance - as conditions become increasingly dry. The EEO model that we use here highlights the important role that both carbon assimilation and tissue construction costs jointly play in predicting the response of trait optima to the environment, laying the groundwork for future height-growth based EEO models aiming to predict shifts in the functional composition of ecosystems in response to global change.

ecology↗

bioRxiv2023

A near-complete dataset of plant growth form, life history, and woodiness for all Australian plants

Tabular records of plant trait data are essential for diverse research purposes. Here we present scorings for a trio of core plant traits, plant growth form, woodiness, and life history, for nearly all accepted taxon concepts included in the Australian Plant Census (APC). This dataset is predominately derived from Australias state and national floras, supplemented by the taxonomic literature and diverse web resources. In total, 29,993 species and infraspecific taxa were scored for plant growth form, 30,279 for woodiness, and 30,056 for life history, with taxa scored as displaying a single or multiple trait values, as appropriate. This resource will enable rapid assessment of plant responses to disturbance events and new biogeographic analyses of trait distributions.

ecology↗

bioRxiv2023

The AusTraits Plant Dictionary

Traits with intuitive names, a clear scope and explicit description are essential for all trait databases. Reanalysis of data from a single database, or analyses that integrate data across multiple databases, can only occur if researchers are confident the trait concepts are consistent within and across sources. The lack of a unified, comprehensive resource for plant trait definitions has previously limited the utility of trait databases. Here we describe the AusTraits Plant Dictionary (APD), which extends the trait definitions included in the new 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 meta-data; and publication in both human and machine-readable forms. Trait definitions include keywords, references and links to related trait concepts in other databases, and the traits are grouped into a hierarchy for easy searching. As well as improving the usability of AusTraits, the Dictionary will foster the integration of trait data across global and regional plant trait databases.

ecology↗

bioRxiv2021

Climate shapes flowering periods across plant communities

AimClimate shapes the composition and function of plant communities globally, but it remains unclear how this influence extends to floral traits. Flowering phenology, or the time period in which a species flowers, has well-studied relationships with climatic signals at the species level but has rarely been explored at a cross-community and continental scale. Here, we characterise the distribution of flowering periods (months of flowering) across continental plant communities encompassing six biomes, and determine the influence of climate on community flowering period lengths. LocationAustralia TaxonFlowering plants MethodsWe combined plant composition and abundance data from 629 standardised floristic surveys (AusPlots) with data on flowering period from the AusTraits database and additional primary literature for 2,983 species. We assessed abundance-weighted community mean flowering periods across biomes and tested their relationship with climatic annual means and the predictability of climate conditions using regression models. ResultsCombined, temperature and precipitation (annual mean and predictability) explain 29% of variation in continental community flowering period. Plant communities with higher mean temperatures and lower mean precipitation have longer mean flowering periods. Moreover, plant communities in climates with predictable temperatures and, to a lesser extent, predictable precipitation have shorter mean flowering periods. Flowering period varies by biome, being longest in deserts and shortest in alpine and montane communities. For instance, desert communities experience low and unpredictable precipitation and high, unpredictable temperatures and have longer mean flowering periods, with desert species typically flowering at any time of year in response to rain. Main conclusionsOur findings demonstrate the role of current climate conditions in shaping flowering periods across biomes, with implications under climate change. Shifts in flowering periods across climatic gradients reflect changes in plant strategies, affecting patterns of plant growth and reproduction as well as the availability of floral resources across the landscape.

ecology↗

bioRxiv2021

AusTraits: a curated plant trait database for the Australian flora

We introduce the AusTraits database - a compilation of measurements of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 375 traits across 29230 taxa from field campaigns, published literature, taxonomic monographs, and individual taxa descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological parameters (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual-, species- and genus-level observations coupled to, where available, contextual information on site properties. This data descriptor provides information on version 2.1.0 of AusTraits which contains data for 937243 trait-by-taxa combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data to increase our collective understanding of the Australian flora.

ecology↗

bioRxiv2020

Sex and Power: sexual dimorphism in trait variability and its eco-evolutionary and statistical implications

Biomedical and clinical sciences are experiencing a renewed interest in the fact that males and females differ in many anatomic, physiological, and behavioral 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.

evolutionary biology↗

bioRxiv2017

Unifying intra- and inter-specific variation in tropical tree mortality

Tree death is a fundamental process driving population dynamics, nutrient cycling, and evolution within plant communities. While past research has identified factors influencing tree mortality across a variety of scales, these distinct drivers are yet to be integrated within a unified predictive framework. In this study, we use a cross-validated Bayesian framework coupled with classic survival analysis techniques to derive instantaneous mortality functions for 203 tropical rainforest tree species at Barro Colorado Island (BCI) Panama. Specifically, we develop mortality functions that not only integrate individual, species, and temporal effects, but also partition the contributions of growth-dependent and growth-independent effects on the overall instantaneous mortality rate. We show that functions that separate mortality rates into growth-dependent and growth-independent hazards, use stem diameter growth rather than basal-area growth, and attribute the effect of wood density to growth-independent mortality outperform alternative formulations. Moreover, we show that the effect of wood density - a prominent trait known to influence tree mortality - explains only 22% of the total variability observed among species. Lastly, our analysis show that growth-dependent processes are the predominant contributor to rates of tree mortality at BCI. Combined, this study provides a framework for predicting individual-level mortality in highly diverse tropical forests. It also highlights how little we know about the causes of species-level and temporal plot-scale effects needed to effectively predict tree mortality.

ecology↗

bioRxiv2017

Coordinated Shifts In Allocation Among Reproductive Tissues Across 14 Coexisting Plant Species

Plant species differ in the amounts of energy allocated to different reproductive tissues, driving differences in their ecology and energy flows within ecosystems. While it is widely agreed that energy allocation is key to reproductive outcomes, few studies have estimated how reproductive effort (RE) is partitioned among different pools, for multiple species in a community. In plants, RE can be partitioned in several meaningful ways: seed versus non-seed tissues; into flowers that form seeds and those that fail to develop; into pre-versus post-pollination tissues, and into successful versus aborted ovules. Evolutionary theory suggests several hypotheses about how these tissues should be coordinated across species. To quantify variation in allocation to different reproductive tissues, we collected detailed RE measurements for a year from 14 perennial species in a recurrent-fire coastal heath community in eastern Australia. Overall we found that total accessory costs - the proportion of RE not directly invested in provisioning the seed - were very large, varying from 95.8% to 99.8% across the study species. These results suggest that studies using seed or fruit production as measures of RE may underestimate it by 10-to 500-fold. We propose a suitable alternative that well-approximates true RE. When comparing species, we found strong support for three evolutionary trade-offs that are predicted to arise when a given energy pool is divided into different tissue masses and counts across species: 1) between successful pollen-attraction costs and mature ovule count, 2) between total reproductive costs and seed count, and 3) between seedset and relative investment in pollen-attraction costs. As a result of these trade-offs, species were also predicted to show coordinated shifts in the amounts invested in floral construction, in seedset and seed size. These shifts in investment were indeed observed, with the amount allocated to discarded tissues increasing with seed size and the amount allocated to pollen-attraction decreasing with seed size. It is already well-established that the seed size axis aligns with the colonization-competition life history spectrum; here we show that relative construction costs of pollen-attraction versus provisioning tissues and seedset are also part of this trajectory, expanding our understanding of the relatives sizes of floral and fruiting structures observed across angiosperms.

ecology↗

bioRxiv2016

Trajectories: how functional traits influence plant growth and shade tolerance across the life-cycle

Plant species differ in many functional traits that drive differences in rates of photosynthesis, biomass allocation, and tissue turnover. Yet, 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 new theoretical framework for understanding the effect of diverse functional traits on plant growth and shade-tolerance, extending a widely-used theoretical model that links growth rate in seedlings with a single leaf trait to explicitly include influences of size, light environment, and five other 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 production and allocation, this framework explains why the influence of prominent traits on growth rate and shade tolerance often varies with plant size and why the impact of size on growth varies among traits. Considering growth rate in height, we find 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 but is strongest at intermediate 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. By disentangling the effects of plant size, light environment and traits on growth rates, our results provide a solid theoretical foundation for trait ecology and thus provide a platform for understanding growth across diverse species around the world.

ecology↗