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Abstract Population genetics and understanding of mating systems provide fundamental information for conservation planning. Pairing these methods is a powerful tool in the study of threatened species, however, they are rarely applied in concert. We examined the mating system and used molecular genetics to measure pairwise kinship and the potential for inbreeding in Hibbertia spanantha, a critically endangered long‐lived shrub endemic to the Sydney Basin, Australia, as a model for conservation planning of species in highly fragmented populations. In situ hand pollination experiments demonstrated that the species is preferentially outcrossing, with limited ability to self‐pollinate (either autogamously or geitonogamously). Although population genetics confirmed high levels of kinship and clonality, there is currently enough population heterozygosity for successful open pollination, primarily through buzz pollination by Sweat Bees (Lasioglossum [Chilalictus]). High levels of clonality and population kinship in one population may be the cause of reduced fitness, identified because our outcrossing pollination treatment produced significantly more seeds with greater viability and seed mass than the open treatments. Differences in weight of filled (viable) seeds were identified between populations, although not treatments, where clonal dominance may be swamping pollinator foraging activities. Identification of species mating system, population reproductive capacity, and impacts of fragmentation on population genetic health provides a robust basis for strategic planning and conservation of this critically endangered species, including establishment of an ex situ population and genetic rescue through population augmentation. These methods are easily applicable and particularly relevant to other plant species with small populations or those occurring in fragmented systems.

Measurement(s) plant trait Technology Type(s) digital curation Sample Characteristic - Organism Viridiplantae Sample Characteristic - Location Australia Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.14545755

Owing to decreasing costs and increased efficiency, it is now conceivable that conservation genomic information can be used to improve the effectiveness of recovery programs for many, if not most, threatened plants. We suggest that a simple genomic study be viewed as an initial step in conservation decision-making, as it informs long-term recovery efforts in various ways. We present biodiversity managers and conservation biologists with a simple, standardized workflow for genomic research that can guide efficient collection, analysis and application of genomic information across disparate threatened plants. Using two case studies, ‘Banksia vincentia’ and Daphnandra johnsonii, we demonstrate how a single round of genotyping by sequencing – a one-time cost – produces multiple directly applicable benefits, and how generating genomic information as early as possible can enhance conservation outcomes. We argue for a shift away from asking whether genomic information is needed or justified, and a shift towards consideration of the questions that need to be addressed. Such questions should aimed at cost-effectively guiding multiple practical aspects of a threatened plant’s management plan. The workflow presented here should help relevant stakeholders design a sampling strategy that directly suits their questions and needs.

We present a model of the growth rate and elemental stoichiometry of phytoplankton as a function of resource allocation between and within broad macromolecular pools under a variety of resource supply conditions. The model is based on four, empirically-supported, cornerstone assumptions: that there is a saturating relationship between light and photosynthesis, a linear relationship between RNA/protein and growth rate, a linear relationship between biosynthetic proteins and growth rate, and a constant macromolecular composition of the light-harvesting machinery. We combine these assumptions with statements of conservation of carbon, nitrogen, phosphorus, and energy. The model can be solved algebraically for steady state conditions and constrained with data on elemental stoichiometry from published laboratory chemostat studies. It interprets the relationships between macromolecular and elemental stoichiometry and also provides quantitative predictions of the maximum growth rate at given light intensity and nutrient supply rates. The model is compatible with data sets from several laboratory studies characterizing both prokaryotic and eukaryotic phytoplankton from marine and freshwater environments. It is conceptually simple, yet mechanistic and quantitative. Here, the model is constrained only by elemental stoichiometry, but makes predictions about allocation to measurable macromolecular pools, which could be tested in the laboratory.

Ecological restoration requires balancing levels of genetic diversity to achieve present-day establishment as well as long-term sustainability. Assumptions based on distributional, taxonomic or functional generalizations are often made when deciding how to source plant material for restoration. We investigate this assumption and ask whether species-specific data is required to optimize provenancing strategies. We use population genetic and environmental data from five congeneric and largely co-distributed species of Acacia to specifically ask how different species-specific genetic provenancing strategies are based on empirical data and how well a simple, standardized collection strategy would work when applied to the same species. We find substantial variability in terms of patterns of genetic diversity and differentiation across the landscape among these five co-distributed Acacia species. This variation translates into substantial differences in genetic provenancing recommendations among species (ranging from 100% to less than 1% of observed genetic variation across species) that could not have been accurately predicted a priori based on simple observation or overall distributional patterns. Furthermore, when a common provenancing strategy was applied to each species, the recommended collection areas and the evolutionary representativeness of such artificially standardized areas were substantially different (smaller) from those identified based on environmental and genetic data. We recommend the implementation of the increasingly accessible array of evolutionary-based methodologies and information to optimize restoration efforts.

Nitrogen fixation provides bioavailable nitrogen, supporting global ecosystems and influencing global cycles of other elements. It provides an additional source of nitrogen to organisms at a cost of lower growth efficiency, largely due to respiratory control of intra-cellular oxygen. Nitrogen-fixing bacteria can, however, utilize both dinitrogen gas and fixed nitrogen, decreasing energetic costs. Here we present an idealized metabolic model of the heterotrophic nitrogen fixer Azotobacter vinelandii which, constrained by laboratory data, provides quantitative predictions for conditions under which the organism uses either ammonium or nitrogen fixation, or both, as a function of the relative supply rates of carbohydrate, fixed nitrogen as well as the ambient oxygen concentration. The model reveals that the organism respires carbohydrate in excess of energetic requirements even when nitrogen fixation is inhibited and respiratory protection is not essential. The use of multiple nitrogen source expands the potential niche and range for nitrogen fixation. The model provides a quantitative framework which can be employed in ecosystem and biogeochemistry models.