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Australia’s 2019–2020 ‘Black Summer’ bushfires burnt more than 8 million hectares of vegetation across the south-east of the continent, an event unprecedented in the last 200 years. Here we report the impacts of these fires on vascular plant species and communities. Using a map of the fires generated from remotely sensed hotspot data we show that, across 11 Australian bioregions, 17 major native vegetation groups were severely burnt, and up to 67–83% of globally significant rainforests and eucalypt forests and woodlands. Based on geocoded species occurrence data we estimate that >50% of known populations or ranges of 816 native vascular plant species were burnt during the fires, including more than 100 species with geographic ranges more than 500 km across. Habitat and fire response data show that most affected species are resilient to fire. However, the massive biogeographic, demographic and taxonomic breadth of impacts of the 2019–2020 fires may leave some ecosystems, particularly relictual Gondwanan rainforests, susceptible to regeneration failure and landscape-scale decline. Fires triggered by climate change threaten plant diversity in many biomes. Here the authors investigate how the catastrophic fires of 2019–2020 affected the vascular flora of SE Australia. They report that 816 species were highly impacted, including taxa of biogeographic and conservation interest.

Bioregions are an important concept in biogeography, and are key to our understanding of biodiversity patterns across the world. The use of networks in biogeography to produce bioregions is a relatively novel approach that has been proposed to improve upon current methods. However, it remains unclear if they may be used in place of current methods and/or offer additional biogeographic insights. We compared two network methods to detect bioregions (modularity and map equation) with the conventional distance‐based clustering method. We also explored the relationship between network and biodiversity metrics. For the analysis we used two datasets of iconic Australian plant groups at a continental scale, Acacia and eucalypts, as example groups. The modularity method detected fewer large bioregions produced the most succinct bioregionalisation for both plant groups corresponding to Australian biomes, while map equation detected many small bioregions including interzones at a natural scale of one. The clustering method was less sensitive than network methods in detecting bioregions. The network metric called participation coefficient from both network partition methods identified interzones or transition zones between bioregions. Furthermore, another network metric (betweenness) was highly correlated to richness and endemism. We conclude that the application of networks to biogeography offers a number of advantages and provides novel insights. More specifically, our study showed that these network partition methods were more efficient than the clustering method for bioregionalisation of continental‐scale data in: 1) the identification of bioregions and 2) the quantification of biogeographic transition zones using the participation coefficient metric. The use of network methods and especially the participation coefficient metric adds to bioregionalisation by identifying transition zones which could be useful for conservation purposes and identifying biodiversity hotspots.

Aim The goal of this study was to investigate the invasion history of the weed Sonchus oleraceus in Australia by comparing the population genetic structure of individuals at different locations in Australia, and in the most likely areas of origin in the native range. Location Samples were collected in Europe and Morocco, North Africa (27 locations), and Australia (17 locations). Methods We performed population genetic analyses using a large dataset comprising 2883 single nucleotide polymorphism markers from 547 plant samples and investigated the invasion history of S. oleraceus with Approximate Bayesian Computation and Random Forest classification algorithms. We compared single and multiple invasion scenarios considering admixture having occurred before and after introduction. Results Our results revealed high levels of inbreeding within sampling locations in the two ranges. Analyses also showed that S. oleraceus was possibly introduced to Australia at least twice: a first introduction around 1000 years ago before British settlement and a more recent introduction (~65 years ago) from Europe and North Africa. We also found evidence of post‐introduction admixture and a potential reintroduction of S. oleraceus from Australia back to its native range. Main conclusions We conclude that the invasion history of S. oleraceus into Australia is probably historic (i.e. prior to British settlements) and complex showing recent evidence of post‐introduction admixture. The complex invasion history of S. oleraceus in Australia poses challenges for the search of potential biological control agents.

Transitions from self-incompatibility to self-compatibility in angiosperms may be frequently driven by selection for reproductive assurance when mates or pollinators are rare, and are often succeeded by loss of inbreeding depression by purging. Here, we use experimental evolution to investigate the spread of self-compatibility from one such population of the perennial plant Linaria cavanillesii into self-incompatible (SI) populations that still have high inbreeding depression. We introduced self-compatible (SC) individuals at different frequencies into replicate experimental populations of L. cavanillesii that varied in access to pollinators. Our experiment revealed a rapid shift to self-compatibility in all replicates, driven by both greater seed set and greater outcross siring success of SC individuals. We discuss our results in the light of computer simulations that confirm the tendency of self-compatibility to spread into SI populations under the observed conditions. Our study illustrates the ease with which self-compatibility can spread among populations, a requisite for species-wide transitions from self-incompatibility to self-compatibility.

Accurate identification of the botanical components of honey can be used to establish its geographical provenance, while also providing insights into honeybee (Apis mellifera L.) diet and foraging preferences. DNA metabarcoding has been demonstrated as a robust method to identify plant species from pollen and pollen‐based products, including honey. We investigated the use of pollen metabarcoding to identify the floral sources and local foraging preferences of honeybees using 15 honey samples from six bioregions from eastern and western Australia. We used two plant metabarcoding markers, ITS2 and the trnL P6 loop. Both markers combined identified a total of 55 plant families, 67 genera, and 43 species. The trnL P6 loop marker provided significantly higher detection of taxa, detecting an average of 15.6 taxa per sample, compared to 4.6 with ITS2. Most honeys were dominated by Eucalyptus and other Myrtaceae species, with a few honeys dominated by Macadamia (Proteaceae) and Fabaceae. Metabarcoding detected the nominal primary source provided by beekeepers among the top five most abundant taxa for 85% of samples. We found that eastern and western honeys could be clearly differentiated by their floral composition, and clustered into bioregions with the trnL marker. Comparison with previous results obtained from melissopalynology shows that metabarcoding can detect similar numbers of plant families and genera, but provides significantly higher resolution at species level. Our results show that pollen DNA metabarcoding is a powerful and robust method for detecting honey provenance and examining the diet of honeybees. This is particularly relevant for hives foraging on the unique and diverse flora of the Australian continent, with the potential to be used as a novel monitoring tool for honeybee floral resources. We used pollen DNA metabarcoding to identify the botanical content of 15 honey samples from six Australian biogeographical regions. We sequenced ITS2 and trnL P6 loop, which in combination identified 55 plant families, 67 genera, and 43 species. The trnL marker was able to differentiate between eastern and western Australian honeys and cluster samples into biogeographical regions. ​

ABSTRACT Habitat fragmentation and the acceleration of environmental change threaten the survival of many plant species. The problem is especially pronounced for plant species with self‐incompatibility mating systems, which are obligate outcrossers, thus requiring high mate availability to persist. In such situations, plant populations suffering decreased fitness could be rescued by: (a) improving local habitat conditions (habitat rescue), (b) increasing the number of individuals (demographic rescue), or (c) introducing new genetic variation (genetic rescue). In this study, we used a spatially and genetically explicit individual‐based model to approximate the demography of a small (N = 250) isolated self‐incompatible population using a timescale of 500 years. Using this model, we quantified the effectiveness of the different types of rescues described above, singly and in combination. Our results show that individual genetic rescue is the most effective type of rescue with respect to improving fitness and population viability. However, we found that introducing a high number of individuals (N > 30) to a small population (N = 50) at the brink of extinction through demographic rescue can also have a positive effect on viability, improving average fitness by 55% compared to introducing a low number of individuals (N = 10) over a long timescale (> 500 years). By itself, habitat rescue showed the lowest effects on viability. However, combining genetic and habitat rescue provided the best results overall, increasing both persistence (> 30%) and mate availability (> 50%). Interestingly, we found that the addition of even a small number of new S alleles (20%) can be highly beneficial to increase mate availability and persistence. We conclude that genetic rescue through the introduction of new S alleles and an increase in habitat suitability is the best management strategy to improve mate availability and population viability of small isolated SI plant populations to overcome the effects of demographic stochasticity and positive density dependence.

Monitoring biodiversity is a growing and pressing challenge, particularly as climate change threatens species with extinction and leads to widespread shifts in plant distribution and phenology. Tracking changes via ground vegetation surveys is costly and time‐consuming, hence monitoring of complex and heterogenous communities remains an ongoing challenge. Molecular DNA methods are rapidly being developed to provide fast and reproducible results for environmental monitoring, including diet and ecosystem assessments. Here, we used DNA metabarcoding of pollen foraged by European honey bees (Apis mellifera) to investigate their floral resource use in an urban reserve. We collected three different pollen samples from hives: individual bees, raw honey and pollen traps, and identified plants using two metabarcoding markers (ITS2 and trnL). We then compared the results to a ground vegetation survey of surrounding flowering taxa. Pollen DNA metabarcoding detected 74 taxa (48.6% identified to species) across all pollen sources, compared to 44 taxa recorded by the survey (93% identified to species). Within the metabarcoding results, we identified 25% of the genera and 9% of the species found during the survey, with three of the top 10 flowering genera represented. While honey was the most taxon‐rich pollen source (mean = 8.5, SD = 3.5), followed by honey bees (mean = 5.8, SD = 6.1) and pollen traps (mean = 4.2, SD = 1.7), combining the results of six individual bees could detect similar taxa numbers to honey, while 20 bees were required to detect as many taxa as the survey. We demonstrate how DNA metabarcoding of the pollen foraged by honey bees can detect more flowering taxa than traditional survey methods, and how different pollen sources and genetic markers affect the level of detection of plant taxa. The foraging choices of honey bees matched few species detected by the vegetation survey, therefore pollen metabarcoding is recommended as a complementary approach to ground surveys. Rigorous validation and stringent filtering of metabarcoding results were also required to exclude potential false positives. Altogether, this molecular approach can be used to augment vegetation surveys, while tracking the floral resources used by bees. Pollen DNA metabarcoding, a novel method for monitoring honey bee floral resources, shows potential as a tool for the rapid bioassessment of flowering vegetation, complementary to ground surveys. Here, we compare three pollen sources taken from honey bees to a botanical survey. While honey was the most taxon‐rich source of plant identifications, pooling six individual bees could detect similar numbers of taxa to honey, with twenty bees required to match the numbers of taxa detected by the survey.

Aim In recent years biogeography has been transformed by the increased availability of large‐scale distributional data, phylogenies, and novel quantitative analysis methods and models. More case studies, however, are needed to test the performance of various approaches, in particular at global scales and in species‐rich groups. In this study, we inferred bioregionalization and estimated ancestral areas for the largest plant family, the Asteraceae. Location Global. Methods We used the Global Compositae Checklist data to infer Asteraceae bioregions with cluster and modularity analysis. We reconstructed a phylogeny of genus‐terminals for the Asteraceae family from a supermatrix of nuclear ribosomal internal transcribed spacer and chloroplast data. Combining areas based on the bioregions from modularity analysis and the phylogeny, we then estimated ancestral ranges across the Asteraceae phylogeny under 12 biogeographic models. Results Cluster analysis resulted in several small bioregions from areas with low taxon numbers and linear and disjunct bioregions between Eurasia and Africa. Modularity analysis produced larger and compact bioregions, and we based downstream analysis on its results. The favoured model for ancestral area estimation was BAYAREALIKE+j+x, demonstrating the importance of long distance dispersal in the biogeographic history of the Asteraceae and a strong distance‐dependence of dispersal. Main conclusions Differences between cluster and modularity analysis suggest that the latter may be more robust to incomplete data and produces less disjunct and thus presumably biologically more realistic bioregions. With few exceptions, results of ancestral area estimation confirmed the results of previous studies, in particular South America as the ancestral area of the family, subsequent dispersal to and a secondary radiation from Africa, and the ancestral areas of individual tribes of the family.

Plant-pollinator associations are often seen as purely mutualistic, while in reality they can be more complex. Indeed they may also display a diverse array of antagonistic interactions, such as competition and victim-exploiter interactions. In some cases mutualistic and antagonistic interactions are carried-out by the same species but at different life-stages. As a consequence, population structure affects the balance of inter-specific associations, a topic that is receiving increased attention. In this paper, we developed a model that captures the basic features of the interaction between a flowering plant and an insect with a larval stage that feeds on the plant's vegetative tissues (e.g. leaves) and an adult pollinator stage. Our model is able to display a rich set of dynamics, the most remarkable of which involves victim-exploiter oscillations that allow plants to attain abundances above their carrying capacities and the periodic alternation between states dominated by mutualism or antagonism. Our study indicates that changes in the insect's life cycle can modify the balance between mutualism and antagonism, causing important qualitative changes in the interaction dynamics. These changes in the life cycle could be caused by a variety of external drivers, such as temperature, plant nutrients, pesticides and changes in the diet of adult pollinators.

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 alíeles 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.