The roles of divergent and parallel molecular evolution contributing to thermal adaptive strategies in trees

Local adaptation is a driver of biological diversity, and species may develop analogous (parallel evolution) or alternative (divergent evolution) solutions to similar ecological challenges. We expect these adaptive solutions would culminate in both phenotypic and genotypic signals. Using two Eucalyptus species (Eucalyptus grandis and Eucalyptus tereticornis) with overlapping distributions grown under contrasting ‘local’ temperature conditions to investigate the independent contribution of adaptation and plasticity at molecular, physiological and morphological levels. The link between gene expression and traits markedly differed between species. Divergent evolution was the dominant pattern driving adaptation (91% of all significant genes); but overlapping gene (homologous) responses were dependent on the determining factor (plastic, adaptive or genotype by environment interaction). Ninety-eight percent of the plastic homologs were similarly regulated, while 50% of the adaptive homologs and 100% of the interaction homologs were antagonistical. Parallel evolution for the adaptive effect in homologous genes was greater than expected but not in favour of divergent evolution. Heat shock proteins for E. grandis were almost entirely driven by adaptation, and plasticity in E. tereticornis. These results suggest divergent molecular evolutionary solutions dominated the adaptive mechanisms among species, even in similar ecological circumstances. Suggesting that tree species with overlapping distributions are unlikely to equally persist in the future

Plant functional traits differ in adaptability and are predicted to be differentially affected by climate change

1. Climate change is testing the resilience of forests worldwide pushing physiological tolerance to climatic extremes. Plant functional traits have been shown to be adapted to climate and have evolved patterns of trait correlations (similar patterns of distribution) and coordinations (mechanistic trade-off). We predicted that traits would differentiate between populations associated with climatic gradients, suggestive of adaptive variation, and correlated traits would adapt to future climate scenarios in similar ways. 2. We measured genetically determined trait variation and described patterns of correlation for seven traits: photochemical reflectance index (PRI), normalized difference vegetation index (NDVI), leaf size (LS), specific leaf area (SLA), δ13C (integrated water-use efficiency, WUE), nitrogen concentration (NCONC), and wood density (WD). All measures were conducted in an experimental plantation on 960 trees sourced from 12 populations of a key forest canopy species in southwestern Australia. 3. Significant differences were found between populations for all traits. Narrow sense heritability was significant for five traits (0.15–0.21), indicating that natural selection can drive differentiation; however, SLA (0.08) and PRI (0.11) were not significantly heritable. Generalized additive models predicted trait values across the landscape for current and future climatic conditions (>90% variance). The percent change differed markedly among traits between current and future predictions (differing as little as 1.5% (δ13C) or as much as 30% (PRI)). Some trait correlations were predicted to break down in the future (SLA:NCONC, δ13C:PRI, and NCONC:WD). 4. Synthesis: Our results suggest that traits have contrasting genotypic patterns and will be subjected to different climate selection pressures, which may lower the working optimum for functional traits. Further, traits are independently associated with different climate factors, indicating that some trait correlations may be disrupted in the future. Genetic constraints and trait correlations may limit the ability for functional traits to adapt to climate change

Aridity drives clinal patterns in leaf traits and responsiveness to precipitation in a broadly distributed Australian tree species

Aridity shapes species distributions and plant growth and function worldwide. Yet, plant traits often show complex relationships with aridity, challenging our understanding of aridity as a driver of evolutionary adaptation. We grew nine genotypes of Eucalyptus camaldulensis subsp. camaldulensis sourced from an aridity gradient together in the field for ~650 days under low and high precipitation treatments. Eucalyptus camaldulesis is considered a phreatophyte (deep-rooted species that utilizes groundwater), so we hypothesized that genotypes from more arid environments would show lower aboveground productivity, higher leaf gas-exchange rates, and greater tolerance/avoidance of dry surface soils (indicated by lower responsiveness) than genotypes from less arid environments. Aridity predicted genotype responses to precipitation, with more arid genotypes showing lower responsiveness to reduced precipitation and dry surface conditions than less arid genotypes. Under low precipitation, genotype net photosynthesis and stomatal conductance increased with home-climate aridity. Across treatments, genotype intrinsic water-use efficiency and osmotic potential declined with increasing aridity while photosynthetic capacity (Rubisco carboxylation and RuBP regeneration) increased with aridity. The observed clinal patterns indicate that E. camaldulensis genotypes from extremely arid environments possess a unique strategy defined by lower responsiveness to dry surface soils, low water-use efficiency, and high photosynthetic capacity. This strategy could be underpinned by deep rooting and could be adaptive under arid conditions where heat avoidance is critical and water demand is high

TRY plant trait database - enhanced coverage and open access

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

Community Preferences for the Allocation &Donation of Organs - The PAraDOx Study

<p>Abstract</p> <p>Background</p> <p>Transplantation is the treatment of choice for people with severe organ failure. However, demand substantially exceeds supply of suitable organs; consequently many people wait months, or years to receive an organ. Reasons for the chronic shortage of deceased organ donations are unclear; there appears to be no lack of 'in principle' public support for organ donation.</p> <p>Methods/Design</p> <p>The PAraDOx Study examines community preferences for organ donation policy in Australia. The aims are to 1) determine which factors influence decisions by individuals to offer their organs for donation and 2) determine the criteria by which the community deems the allocation of donor organs to be fair and equitable. Qualitative and quantitative methods will be used to assess community preferences for organ donation and allocation.</p> <p>Focus group participants from the general community, aged between 18-80, will be purposively sampled to ensure a variety of cultural backgrounds and views on organ donation. Each focus group will include a ranking exercise using a modified nominal group technique. Focus groups of organ recipients, their families, and individuals on a transplant waiting list will also be conducted.</p> <p>Using the qualitative work, a discrete choice study will be designed to quantitatively assess community preferences. Discrete choice methods are based on the premise that goods and services can be described in terms of a number of separate attributes. Respondents are presented with a series of choices where levels of attributes are varied, and a mathematical function is estimated to describe numerically the value respondents attach to different options. Two community surveys will be conducted in approximately 1000 respondents each to assess community preferences for organ donation and allocation. A mixed logit model will be used; model results will be expressed as parameter estimates (β) and the odds of choosing one option over an alternative. Trade-offs between attributes will also be calculated.</p> <p>Discussion</p> <p>By providing a better understanding of current community preferences in relation to organ donation and allocation, the PAraDOx study will highlight options for firstly, increasing the rate of organ donation and secondly, allow for more transparent and equitable policies in relation to organ allocation.</p

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe

TRY plant trait database – enhanced coverage and open access

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

TRY plant trait database - enhanced coverage and open access

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