Genetic diversity and structure of the Australian flora

Aim To investigate the relationships between species attributes and genetic parameters in Australian plant species and to determine the associations in relation to predictions from population theory and previous global analyses. Location Continent of Australia. Methods We assembled a dataset of all known population genetic analyses of Australian plants based on neutral markers and catalogued them according to key species attributes, including range, abundance, range disjunction, biome and growth form; and genetic parameters, mean number of alleles per locus, observed and expected heterozygosity and population differentiation. We determined relationships between species attributes and genetic parameters using a maximum‐likelihood, multimodel inference approach. Results We found many associations that were consistent with predictions. Species attributes with greatest effect on genetic diversity were range size, growth form, abundance and biome. The most important attributes influencing genetic differentiation were range disjunction and abundance. We found unexpected results in the effects of biome and growth form on genetic diversity, with greater diversity in the eastern biome of Australia, and lower diversity in shrubs compared to trees. Main conclusions Our analysis of genetic diversity of Australian plants showed associations consistent with predictions based on population genetics theory, with strong effects of range size, abundance and growth form. We identified a striking effect of range disjunction on population genetic differentiation, an effect that has received little attention in the literature. We also found some notable differences to global predictions, which were most likely explained by confounding effects across variables. This highlights that caution is needed when extrapolating trends from global analyses to regional floras. Identifying associations between species attributes and patterns of genetic diversity enables broadscale predictions to facilitate the inclusion of genetic considerations into conservation decision‐making.This research was supported by the joint resources of CSIRO and the Western Australian Department of Parks and Wildlif

Introducing BASE: the Biomes of Australian Soil Environments soil microbial diversity database

Background: Microbial inhabitants of soils are important to ecosystem and planetary functions, yet there are large gaps in our knowledge of their diversity and ecology. The 'Biomes of Australian Soil Environments' (BASE) project has generated a database of microbial diversity with associated metadata across extensive environmental gradients at continental scale. As the characterisation of microbes rapidly expands, the BASE database provides an evolving platform for interrogating and integrating microbial diversity and function. Findings: BASE currently provides amplicon sequences and associated contextual data for over 900 sites encompassing all Australian states and territories, a wide variety of bioregions, vegetation and land-use types. Amplicons target bacteria, archaea and general and fungal-specific eukaryotes. The growing database will soon include metagenomics data. Data are provided in both raw sequence (FASTQ) and analysed OTU table formats and are accessed via the project's data portal, which provides a user-friendly search tool to quickly identify samples of interest. Processed data can be visually interrogated and intersected with other Australian diversity and environmental data using tools developed by the 'Atlas of Living Australia'. Conclusions: Developed within an open data framework, the BASE project is the first Australian soil microbial diversity database. The database will grow and link to other global efforts to explore microbial, plant, animal, and marine biodiversity. Its design and open access nature ensures that BASE will evolve as a valuable tool for documenting an often overlooked component of biodiversity and the many microbe-driven processes that are essential to sustain soil function and ecosystem services

Introducing BASE: the Biomes of Australian Soil Environments soil microbial diversity database

Microbial inhabitants of soils are important to ecosystem and planetary functions, yet there are large gaps in our knowledge of their diversity and ecology. The ‘Biomes of Australian Soil Environments’ (BASE) project has generated a database of microbial diversity with associated metadata across extensive environmental gradients at continental scale. As the characterisation of microbes rapidly expands, the BASE database provides an evolving platform for interrogating and integrating microbial diversity and function

Global genetic diversity status and trends: towards a suite of Essential Biodiversity Variables (EBVs) for genetic composition

Biodiversity underlies ecosystem resilience, ecosystem function, sustainable economies, and human well-being. Understanding how biodiversity sustains ecosystems under anthropogenic stressors and global environmental change will require new ways of deriving and applying biodiversity data. A major challenge is that biodiversity data and knowledge are scattered, biased, collected with numerous methods, and stored in inconsistent ways. The Group on Earth Observations Biodiversity Observation Network (GEO BON) has developed the Essential Biodiversity Variables (EBVs) as fundamental metrics to help aggregate, harmonize, and interpret biodiversity observation data from diverse sources. Mapping and analyzing EBVs can help to evaluate how aspects of biodiversity are distributed geographically and how they change over time. EBVs are also intended to serve as inputs and validation to forecast the status and trends of biodiversity, and to support policy and decision making. Here, we assess the feasibility of implementing Genetic Composition EBVs (Genetic EBVs), which are metrics of within-species genetic variation. We review and bring together numerous areas of the field of genetics and evaluate how each contributes to global and regional genetic biodiversity monitoring with respect to theory, sampling logistics, metadata, archiving, data aggregation, modeling, and technological advances. We propose four Genetic EBVs: (i) Genetic Diversity; (ii) Genetic Differentiation; (iii) Inbreeding; and (iv) Effective Population Size (Ne). We rank Genetic EBVs according to their relevance, sensitivity to change, generalizability, scalability, feasibility and data availability. We outline the workflow for generating genetic data underlying the Genetic EBVs, and review advances and needs in archiving genetic composition data and metadata. We discuss how Genetic EBVs can be operationalized by visualizing EBVs in space and time across species and by forecasting Genetic EBVs beyond current observations using various modeling approaches. Our review then explores challenges of aggregation, standardization, and costs of operationalizing the Genetic EBVs, as well as future directions and opportunities to maximize their uptake globally in research and policy. The collection, annotation, and availability of genetic data has made major advances in the past decade, each of which contributes to the practical and standardized framework for large-scale genetic observation reporting. Rapid advances in DNA sequencing technology present new opportunities, but also challenges for operationalizing Genetic EBVs for biodiversity monitoring regionally and globally. With these advances, genetic composition monitoring is starting to be integrated into global conservation policy, which can help support the foundation of all biodiversity and species' long-term persistence in the face of environmental change. We conclude with a summary of concrete steps for researchers and policy makers for advancing operationalization of Genetic EBVs. The technical and analytical foundations of Genetic EBVs are well developed, and conservation practitioners should anticipate their increasing application as efforts emerge to scale up genetic biodiversity monitoring regionally and globally

Cumulative human impacts on marine predators

Stressors associated with human activities interact in complex ways to affect marine ecosystems, yet we lack spatially explicit assessments of cumulative impacts on ecologically and economically key components such as marine predators. Here we develop a metric of cumulative utilization and impact (CUI) on marine predators by combining electronic tracking data of eight protected predator species (n=685 individuals) in the California Current Ecosystem with data on 24 anthropogenic stressors. We show significant variation in CUI with some of the highest impacts within US National Marine Sanctuaries. High variation in underlying species and cumulative impact distributions means that neither alone is sufficient for effective spatial management. Instead, comprehensive management approaches accounting for both cumulative human impacts and trade-offs among multiple stressors must be applied in planning the use of marine resources

Prediction by a neural network of outer membrane beta-strand protein topology

An artificial neural network (NN) was trained to predict the topology of bacterial outer membrane (OM) β-strand proteins. Specifically, the NN predicts the z-coordinate of Cα atoms in a coordinate frame with the outer membrane in the xy-plane, such that low z-values indicate periplasmic turns, medium z-values indicate transmembrane β-strands, and high z-values indicate extracellular loops. To obtain a training set, seven OM proteins (porins) with structures known to high resolution were aligned with their pores along the z-axis. The relationship between Cα z-values and topology was thereby established. To predict the topology of other OM proteins, all seven porins were used for the training set. Z-values (topologies) were predicted for two porins with hitherto unknown structure and for OM proteins not belonging to the porin family, all with insignificant sequence homology to the training set. The results of topology prediction compare favorably with experimental topology data

Comparison of in vivo and in vitro phosphorylation of the exocytosis-sensitive protein PP63/Parafusin by differential MALDI mass spectrometric peptide mapping

PP63 (parafusin) is a 63 kDa phosphoprotein, which exists in at least two different isoforms. It is very rapidly (80 ms) dephosphorylated during triggered trichocyst exocytosis. This occurs selectively in exocytosis-competent Paramecium tetraurelia strains. At least two protein kinases isolated from Paramecium, casein kinase type II kinase and cGMP-dependent kinase, are able to phosphorylate the two recombinant PP63/parafusin isoforms, both with phosphoglucomutase activity, in vitro. By performing mass spectrometric peptide mapping, we have investigated in vitro phosphorylation of recombinant PP63/ parafusin by these kinases in comparison to in vivo phosphorylation of native PP63/parafusin isolated from Paramecium homogenates. Low picomolar quantities of proteolytic digests of recombinant and native PP63/parafusin, prior to and following alkaline phosphatase treatment, were directly analyzed by MALDI mass spectrometry. In native PP63-1/parafusin-1, six of 64 serine and threonine residues (S-196, T-205, T-280, T-371, T-373, and T-469) were found definitely, 27 were found possibly phosphorylated, 28 were identified as nonphosphorylated, and three were not covered by mapping. Three of the six certainly phosphorylated amino acids represent consensus phosphorylation sites for casein kinase II or cGMPdependent protein kinase. In vitro phosphorylation studies of recombinant PP63/parafusin confirm that some of the sites found were used in vivo; however, also significant differences with respect to in vivo phosphorylation of native PP63/parafusin were observed. The two Paramecium protein kinases that were used do not preferably phosphorylate expected consensus sites in vitro. Homology structure modeling of PP63/parafusin with rabbit phosphoglucomutase revealed that the majority of residues found phosphorylated is located on the surface of the molecule