AusTraits, a curated plant trait database for the Australian flora

We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge. © 2021, The Author(s). **Please note that there are multiple authors for this article therefore only the name of the first 5 including Federation University Australia affiliate “David Cheal" is provided in this record*

Unstable DNA Repair Genes Shaped by Their Own Sequence Modifying Phenotypes

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

Climate shapes community flowering periods across biomes

Aim: Climate 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. Location: Australia. Taxon: Flowering plants. Methods: We 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 2983 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. Results: Combined, 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 conclusions: Current climate conditions shape flowering periods across biomes, with implications for phenology 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 for pollinators across the landscape

Patterns and drivers of plant diversity across Australia

Biodiversity analyses across continental extents are important in providing comprehensive information on patterns and likely drivers of diversity. For vascular plants in Australia, community-level diversity analyses have been restricted by the lack of a consistent plot-based survey dataset across the continent. To overcome these challenges, we collated and harmonised plot-based vegetation survey data from the major data sources across Australia and used them as the basis for modelling species richness (α-diversity) and community compositional dissimilarity (β-diversity), standardised to 400 m2, with the aim of mapping diversity patterns and identifying potential environmental drivers. The harmonised Australian vegetation plot (HAVPlot) dataset includes 219 552 plots, of which we used 115 083 to analyse plant diversity. Models of species richness and compositional dissimilarity both explained approximately one-third of the variation in plant diversity across Australia (D2 = 33.0% and 32.7%, respectively). The strongest environmental predictors for both aspects of diversity were a combination of temperature and precipitation, with soil texture and topographic heterogeneity also important. The fine-resolution (≈ 90 m) spatial predictions of species richness and compositional dissimilarity identify areas expected to be of particular importance for plant diversity, including south-western Australia, rainforests of eastern Australia and the Australian Alps. Arid areas of central and western Australia are predicted to support assemblages that are less speciose or unique; however, these areas are most in need of additional survey data to fill the spatial, environmental and taxonomic gaps in the HAVPlot dataset. The harmonised data and model predictions presented here provide new insight into plant diversity patterns across Australia, enabling a wide variety of future research, such as exploring changes in species abundances, linking compositional patterns to functional traits or undertaking conservation assessments for selected components of the flora

Cumulative incidence of child protection system contacts among a cohort of Western Australian Aboriginal children born 2000 to 2013

Background: Reducing the over-representation of Aboriginal children in the child protection system is a key target for the Australian government. Objective: We aimed to provide more recent evidence on the population-level cumulative incidence of contacts for Aboriginal children with child protective services (CPS) in Western Australia (WA). Participants and Setting: Linked administrative data was provided for WA CPS between 2000 and 2015 for 33,709 Aboriginal children born in WA between 2000 and 2013. Methods: Descriptive summaries and cumulative incidence estimates were used to examine changes in CPS contact trends over time and within sibling groups. Results: There was an increase in early-childhood contacts for children born more recently, with 7.6 % and 2.3 % of children born in 2000–2001 having a notification and placement in out-of-home care by age one, respectively, compared to 15.1 % and 4.3 % of children born in 2012–2013. Among sibling groups where at least one sibling had a CPS contact, approximately half of children had their first contacts on the same date as another sibling. For children born after one of their siblings had been placed in out-of-home care, 31.9 % had themselves been placed in out-of-home care by age one. Conclusions: Multiple children tend to be placed into out-of-home care when at least one sibling is, which is likely to have a significant impact on families affected. The additional risk of placement also carries over to children born after the first removal in a sibling group, highlighting the need for further support to prevent future removals

BAAD: a Biomass And Allometry Database for woody plants

Understanding how plants are constructed—i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals—is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among species adapted to different environments. While a variety of models dealing with biomass allocation exist, we lack a synthetic understanding of the underlying processes. This is partly due to the lack of suitable data sets for validating and parameterizing models. To that end, we present the Biomass And Allometry Database (BAAD) for woody plants. The BAAD contains 259 634 measurements collected in 176 different studies, from 21 084 individuals across 678 species. Most of these data come from existing publications. However, raw data were rarely made public at the time of publication. Thus, the BAAD contains data from different studies, transformed into standard units and variable names. The transformations were achieved using a common workflow for all raw data files. Other features that distinguish the BAAD are: (i) measurements were for individual plants rather than stand averages; (ii) individuals spanning a range of sizes were measured; (iii) plants from 0.01–100 m in height were included; and (iv) biomass was estimated directly, i.e., not indirectly via allometric equations (except in very large trees where biomass was estimated from detailed sub‐sampling). We included both wild and artificially grown plants. The data set contains the following size metrics: total leaf area; area of stem cross‐section including sapwood, heartwood, and bark; height of plant and crown base, crown area, and surface area; and the dry mass of leaf, stem, branches, sapwood, heartwood, bark, coarse roots, and fine root tissues. We also report other properties of individuals (age, leaf size, leaf mass per area, wood density, nitrogen content of leaves and wood), as well as information about the growing environment (location, light, experimental treatment, vegetation type) where available. It is our hope that making these data available will improve our ability to understand plant growth, ecosystem dynamics, and carbon cycling in the world\u27s vegetation

Tallo: A global tree allometry and crown architecture database

Data capturing multiple axes of tree size and shape, such as a tree's stem diameter, height and crown size, underpin a wide range of ecological research—from developing and testing theory on forest structure and dynamics, to estimating forest carbon stocks and their uncertainties, and integrating remote sensing imagery into forest monitoring programmes. However, these data can be surprisingly hard to come by, particularly for certain regions of the world and for specific taxonomic groups, posing a real barrier to progress in these fields. To overcome this challenge, we developed the Tallo database, a collection of 498,838 georeferenced and taxonomically standardized records of individual trees for which stem diameter, height and/or crown radius have been measured. These data were collected at 61,856 globally distributed sites, spanning all major forested and non-forested biomes. The majority of trees in the database are identified to species (88%), and collectively Tallo includes data for 5163 species distributed across 1453 genera and 187 plant families. The database is publicly archived under a CC-BY 4.0 licence and can be access from: https://doi.org/10.5281/zenodo.6637599. To demonstrate its value, here we present three case studies that highlight how the Tallo database can be used to address a range of theoretical and applied questions in ecology—from testing the predictions of metabolic scaling theory, to exploring the limits of tree allometric plasticity along environmental gradients and modelling global variation in maximum attainable tree height. In doing so, we provide a key resource for field ecologists, remote sensing researchers and the modelling community working together to better understand the role that trees play in regulating the terrestrial carbon cycle.EEA Santa CruzFil: Jucker, Tommaso. University of Bristol. School of Biological Sciences; Reino UnidoFil: Fischer, Fabian Jörg. University of Bristol. School of Biological Sciences; Reino UnidoFil: Chave, Jérôme. Laboratoire Évolution et Diversité Biologique (EDB); FranciaFil: Chave, Jérôme. Université Toulouse; FranciaFil: Coomes, David A. University of Cambridge. Conservation Research Institute; Reino UnidoFil: Caspersen, John. University of Toronto. Institute of Forestry and Conservation; Canadá.Fil: Ali, Arshad. Hebei University. College of Life Sciences. Forest Ecology Research Group; China.Fil: Loubota Panzou, Grace Jopaul. Université de Liège, Gembloux Agro-Bio Tech; BélgicaFil: Loubota Panzou, Grace Jopaul. Université Marien Ngouabi. Faculté des Sciences et Techniques. Laboratoire de Biodiversité, de Gestion des Ecosystèmes et de l'Environnement (LBGE); Republica del CongoFil: Feldpausch, Ted R. University of Exeter. College of Life and Environmental Sciences; Reino UnidoFil: Falster, Daniel. University of New South Wales Sydney. Evolution & Ecology Research Centre; Australia.Fil: Usoltsev, Vladimir A. Ural State Forest Engineering University. Department of Forestry; Rusia.Fil: Usoltsev, Vladimir A. Botanical Garden of the Ural Branch of Russian Academy of Sciences. Department of Forest Dynamics; Rusia.Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: Xiang, Wenhua. Central South University of Forestry and Technology. Faculty of Life Science and Technology; China

BAAD: A biomass and allometry database for woody plants.

Understanding how plants are constructed—i.e., how key size dimensions and the amount of mass invested in different tissues varies among individuals—is essential for modeling plant growth, carbon stocks, and energy fluxes in the terrestrial biosphere. Allocation patterns can differ through ontogeny, but also among coexisting species and among species adapted to different environments. While a variety of models dealing with biomass allocation exist, we lack a synthetic understanding of the underlying processes. This is partly due to the lack of suitable data sets for validating and parameterizing models. To that end, we present the Biomass And Allometry Database (BAAD) for woody plants. The BAAD contains 259 634 measurements collected in 176 different studies, from 21 084 individuals across 678 species. Most of these data come from existing publications. However, raw data were rarely made public at the time of publication. Thus, the BAAD contains data from different studies, transformed into standard units and variable names. The transformations were achieved using a common workflow for all raw data files. Other features that distinguish the BAAD are: (i) measurements were for individual plants rather than stand averages; (ii) individuals spanning a range of sizes were measured; (iii) plants from 0.01– 100 m in height were included; and (iv) biomass was estimated directly, i.e., not indirectly via allometric equations (except in very large trees where biomass was estimated from detailed sub-sampling). We included both wild and artificially grown plants. The data set contains the following size metrics: total leaf area; area of stem cross-section including sapwood, heartwood, and bark; height of plant and crown base, crown area, and surface area; and the dry mass of leaf, stem, branches, sapwood, heartwood, bark, coarse roots, and fine root tissues. We also report other properties of individuals (age, leaf size, leaf mass per area, wood density, nitrogen content of leaves and wood), as well as information about the growing environment (location, light, experimental treatment, vegetation type) where available. It is our hope that making these data available will improve our ability to understand plant growth, ecosystem dynamics, and carbon cycling in the world’s vegetation.EEA Santa CruzFil: Falster, Daniel S. Macquarie University. Biological Sciences; Australia.Fil: Duursma, Remko A. University of Western Sydney. Hawkesbury Insitute for the Environment; Australia.Fil: Ishihara, Masae I. Hiroshima University. Graduate School for International Development and Cooperation; Japón.Fil: Barneche, Diego R. Macquarie University. Biological Sciences; Australia.Fil: FitzJohn, Richard G. Macquarie University. Biological Sciences; Australia.Fil: Vårhammar, Angelica. University of Western Sydney. Hawkesbury Insitute for the Environment; Australia.Fil: Aiba, Masahiro. Tohoku University. Graduate School of Life Sciences; Japón.Fil: Ando, Makoto. Kyoto University. Field Science Education and Research Center; JapónFil: Anten, Niels. Centre for Crop Systems Analysis; Países BajosFil: Aspinwall, Michael J. University of Western Sydney. Hawkesbury Insitute for the Environment; Australia.Fil: Gargaglione Verónica Beatriz. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Gargaglione Verónica Beatriz. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina.Fil: Peri, Pablo Luis. Universidad Nacional de la Patagonia Austral; Argentina.Fil: Peri, Pablo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.Fil: York, Robert A. University of California Berkeley. Center for Forestry; Estados Unido

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 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.SRKZ and ML were supported by the Australian (ARC) Discovery Grant (DP180100818) awarded to SN. JM was supported by EMBL core funding and the NIH Common Fund (UM1-H G006370). AMS was supported by an ARC fellowship (DE180101520)

Open Science Principles for Accelerating Trait-Based Science Across the Tree of Life

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