Consistently high heat tolerance acclimation in response to a simulated heatwave across species from the broadly distributed Acacia genus.

When leaves exceed their thermal threshold during heatwaves, irreversible damage to the leaf can accumulate. However, few studies have explored short-term acclimation of leaves to heatwaves that could help plants to prevent heat damage with increasing heatwave intensity. Here, we studied the heat tolerance of PSII (PHT) in response to a heatwave in Acacia species from across a strong environmental gradient in Australia. We compared PHT metrics derived from temperature-dependent chlorophyll fluorescence response curves (T-F 0 ) before and during a 4-day 38°C heatwave in a controlled glasshouse experiment. We found that the 15 Acacia species displayed surprisingly large and consistent PHT acclimation responses with a mean tolerance increase of 12°C (range, 7.7-19.1°C). Despite species originating from diverse climatic regions, neither maximum temperature of the warmest month nor mean annual precipitation at origin were clear predictors of PHT. To our knowledge, these are some of the largest measured acclimation responses of PHT from a controlled heatwave experiment. This remarkable capacity could partially explain why this genus has become more diverse and common as the Australian continent became more arid and suggests that the presence of Acacia in Australian ecosystems will remain ubiquitous with climate change.

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.

Areas of global importance for conserving terrestrial biodiversity, carbon and water.

To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature's contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally. We found that selecting the top-ranked 30% and 50% of terrestrial land area would conserve respectively 60.7% and 85.3% of the estimated total carbon stock and 66% and 89.8% of all clean water, in addition to meeting conservation targets for 57.9% and 79% of all species considered. Our data and prioritization further suggest that adequately conserving all species considered (vertebrates and plants) would require giving conservation attention to ~70% of the terrestrial land surface. If priority was given to biodiversity only, managing 30% of optimally located land area for conservation may be sufficient to meet conservation targets for 81.3% of the terrestrial plant and vertebrate species considered. Our results provide a global assessment of where land could be optimally managed for conservation. We discuss how such a spatial prioritization framework can support the implementation of the biodiversity and climate conventions.

The Atlantic salmon whole blood transcriptome and how it relates to major locus maturation genotypes and other tissues.

The Atlantic salmon (Salmo salar) is important to many ecosystems and local economies and has therefore become the focus of a broad range of research questions that have benefited from the availability of high-quality genomic resources. Albeit gene expression studies have been extensive for this species, the transcriptome information for Atlantic salmon whole blood has been lacking. A transcriptome of Atlantic salmon blood would be a valuable resource for future studies, especially those wishing to take non-lethal samples. Here, we report a whole blood transcriptome for Atlantic salmon constructed from twelve 8-month old salmon parr using RNA-seq. We identify transcriptomic proxies for the genotype at the major maturation timing locus vestigial-like 3 (vgll3). Differentially expressed genes between the early and late maturing genotypes showed overrepresented Gene Ontology (GO) terms with the strongest result linked to 13 ribosomal subunit genes. To assess how the whole blood gene expression profile relates to other tissues, we compare the blood transcriptome to the reference transcriptome of fourteen other tissue types using both a common PCA method and a novel method. The novel method compares transcriptomes when gene expression is visualised as a layer using thin-plate spline smoothers. Both methods found similar patterns with the blood transcriptome being quite unique compared to the transcription profiles of other tissues.

Publisher Correction: Open Science principles for accelerating trait-based science across the Tree of Life.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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.

Signs of adaptation to trace metal contamination in a common urban bird.

Metals and metalloids at elevated concentrations can be toxic to both humans and wildlife. In particular, lead exposure can act as a stressor to wildlife and cause negative effects on fitness. Any ability to adapt to stress caused by the negative effects of trace metal exposure would be beneficial for species living in contaminated environments. However, mechanisms for responding adaptively to metal contamination are not fully understood in free-living organisms. The Australian populations of the house sparrow (Passer domesticus) provides an excellent opportunity to study potential adaptation to environmental lead contamination because they have a commensal relationship with humans and are distributed broadly across Australian settlements including many long-term mining and smelting communities. To examine the potential for an evolutionary response to long-term lead exposure, we collected genomic SNP data using the house sparrow 200 K SNP array, from 11 localities across the Australian distribution including two mining sites (Broken Hill and Mount Isa, which are two genetically independent populations) that have well-established elevated levels of lead contamination as well as trace metals and metalloids. We contrast these known contaminated locations to other lesser-contaminated environments. Using an ecological association genome scan method to identify genomic differentiation associated with estimates of lead contamination we identified 60 outlier loci across three tests. A total of 39 genes were found to be physically linked (within 20 kbps) of all outliers in the house sparrow reference genome. The linked candidate genes included 12 genes relevant to lead exposure, such as two metal transporters that can transport metals including lead and zinc across cell membranes. These candidate genes provide targets for follow up experiments comparing resilience to lead exposure between populations exposed to varied levels of lead contamination.

Signatures of genetic adaptation to extremely varied Australian environments in introduced European house sparrows.

Due to its history of multiple introductions to novel environments worldwide, the house sparrow has been used as a model species to study local adaption in invasive avian species. New genomic resources such as a custom 200K SNP array and a house sparrow reference genome provide great prospects for studying rapid local adaptation in this invasive species. Here, we analyse high-density genomewide genetic data collected across an extensive range of temperate, arid and tropical climates, in Australian populations that were introduced from Europe 150 years ago. We used two population differentiation (PD) and two ecological association (EA) methods to identify putative loci subject to selection across these varied climates. A majority of the outlier SNPs were identified through the use of the latent factor mixed models (LFMM) EA method, but the BayeScEnv EA method had the strongest overlap with the outliers from the two PD methods. Out of all the 971 outliers identified across the different methods, 38.3% were physically linked (within 20 kbps) to 575 known protein-coding regions in the house sparrow reference genome. Interestingly, some outlier genes had been previously identified in genome scan studies of broadly distributed species or had strong links to traits that are expected to be important to local adaptation, for example, heat-shock proteins, immune response and HOX genes. However, many outliers still have unknown relevance and some outliers can be false positives. Our results identify an opportunity to use the house sparrow model to further study local adaptation in an invasive species.

Peak shift in honey bee olfactory learning.

If animals are trained with two similar stimuli such that one is rewarding (S+) and one punishing (S-), then following training animals show a greatest preference not for the S+, but for a novel stimulus that is slightly more different from the S- than the S+ is. This peak shift phenomenon has been widely reported for vertebrates and has recently been demonstrated for bumblebees and honey bees. To explore the nature of peak shift in invertebrates further, here we examined the properties of peak shift in honey bees trained in a free-flight olfactory learning assay. Hexanal and heptanol were mixed in different ratios to create a continuum of odour stimuli. Bees were trained to artificial flowers such that one odour mixture was rewarded with 2 molar sucrose (S+), and one punished with distasteful quinine (S-). After training, bees were given a non-rewarded preference test with five different mixtures of hexanal and heptanol. Following training bees' maximal preference was for an odour mixture slightly more distinct from the S- than the trained S+. This effect was not seen if bees were initially trained with two distinct odours, replicating the classic features of peak shift reported for vertebrates. We propose a conceptual model of how peak shift might occur in honey bees. We argue that peak shift does not require any higher level of processing than the known olfactory learning circuitry of the bee brain and suggest that peak shift is a very general feature of discrimination learning.