Plant clonality in a soil-impoverished open ecosystem: insights from southwest Australian shrublands.

BACKGROUND AND AIMS: Clonality is a key life-history strategy promoting on-spot persistence, space occupancy, resprouting after disturbance, and resource storage, sharing and foraging. These functions provided by clonality can be advantageous under different environmental conditions, including resource-paucity and fire-proneness, which define most mediterranean-type open ecosystems, such as southwest Australian shrublands. Studying clonality-environment links in underexplored mediterranean shrublands could therefore deepen our understanding of the role played by this essential strategy in open ecosystems globally. METHODS: We created a new dataset including 463 species, six traits related to clonal growth organs (CGOs; lignotubers, herbaceous and woody rhizomes, stolons, tubers, stem fragments), and edaphic predictors of soil water availability, nitrogen (N) and phosphorus (P) from 138 plots. Within two shrubland communities, we explored multivariate clonal patterns and how the diversity of CGOs, and abundance-weighted and unweighted proportions .of clonality in plots changed along with the edaphic gradients. KEY RESULTS: We found clonality in 65 % of species; the most frequent were those with lignotubers (28 %) and herbaceous rhizomes (26 %). In multivariate space, plots clustered into two groups, one distinguished by sandy plots and plants with CGOs, the other by clayey plots and non-clonal species. CGO diversity did not vary along the edaphic gradients (only marginally with water availability). The abundance-weighted proportion of clonal species increased with N and decreased with P and water availability, yet these results were CGO-specific. We revealed almost no relationships for unweighted clonality. CONCLUSIONS: Clonality is more widespread in shrublands than previously thought, and distinct plant communities are distinguished by specific suites (or lack) of CGOs. We show that weighting belowground traits by aboveground abundance affects the results, with implications for trait-based ecologists using abundance-weighting. We suggest unweighted approaches for belowground organs in open ecosystems until belowground abundance is quantifiable.

Next generation restoration metrics: Using soil eDNA bacterial community data to measure trajectories towards rehabilitation targets.

In post-mining rehabilitation, successful mine closure planning requires specific, measurable, achievable, relevant and time-bound (SMART) completion criteria, such as returning ecological communities to match a target level of similarity to reference sites. Soil microbiota are fundamentally linked to the restoration of degraded ecosystems, helping to underpin ecological functions and plant communities. High-throughput sequencing of soil eDNA to characterise these communities offers promise to help monitor and predict ecological progress towards reference states. Here we demonstrate a novel methodology for monitoring and evaluating ecological restoration using three long-term (>25 year) case study post-mining rehabilitation soil eDNA-based bacterial community datasets. Specifically, we developed rehabilitation trajectory assessments based on similarity to reference data from restoration chronosequence datasets. Recognising that numerous alternative options for microbiota data processing have potential to influence these assessments, we comprehensively examined the influence of standard versus compositional data analyses, different ecological distance measures, sequence grouping approaches, eliminating rare taxa, and the potential for excessive spatial autocorrelation to impact on results. Our approach reduces the complexity of information that often overwhelms ecologically-relevant patterns in microbiota studies, and enables prediction of recovery time, with explicit inclusion of uncertainty in assessments. We offer a step change in the development of quantitative microbiota-based SMART metrics for measuring rehabilitation success. Our approach may also have wider applications where restorative processes facilitate the shift of microbiota towards reference states.

Optimising the conservation of genetic diversity of the last remaining population of a critically endangered shrub.

An understanding of genetic diversity and the population genetic processes that impact future population viability is vital for the management and recovery of declining populations of threatened species. Styphelia longissima (Ericaceae) is a critically endangered shrub, restricted to a single fragmented population near Eneabba, 250 km north of Perth, Western Australia. For this population, we sought to characterize population genetic variation and its spatial structure, and aspects of the mating portfolio, from which strategies that optimize the conservation of this diversity are identified. A comprehensive survey was carried out and 220 adults, and 106 seedlings from 14 maternal plants, were genotyped using 13 microsatellite markers. Levels of genetic variation and its spatial structure were assessed, and mating system parameters were estimated. Paternity was assigned to the offspring of a subsection of plants, which allowed for the calculation of realized pollen dispersal. Allelic richness and levels of expected heterozygosity were higher than predicted for a small isolated population. Spatial autocorrelation analysis identified fine-scale genetic structure at a scale of 20 m, but no genetic structure was found at larger scales. Mean outcrossing rate (t m = 0.66) reflects self-compatibility and a mixed-mating system. Multiple paternity was low, where 61 % of maternal siblings shared the same sire. Realized pollen dispersal was highly restricted, with 95 % of outcrossing events occurring at 7 m or less, and a mean pollen dispersal distance of 3.8 m. Nearest-neighbour matings were common (55 % of all outcross events), and 97 % of mating events were between the three nearest-neighbours. This study has provided critical baseline data on genetic diversity, mating system and pollen dispersal for future monitoring of S. longissima. Broadly applicable conservation strategies such as implementing a genetic monitoring plan, diluting spatial genetic structure in the natural population, genetically optimizing ex situ collections and incorporating genetic knowledge into translocations will help to manage the future erosion of the high genetic variation detected.

Impact of ecological redundancy on the performance of machine learning classifiers in vegetation mapping.

Vegetation maps are models of the real vegetation patterns and are considered important tools in conservation and management planning. Maps created through traditional methods can be expensive and time-consuming, thus, new more efficient approaches are needed. The prediction of vegetation patterns using machine learning shows promise, but many factors may impact on its performance. One important factor is the nature of the vegetation-environment relationship assessed and ecological redundancy. We used two datasets with known ecological redundancy levels (strength of the vegetation-environment relationship) to evaluate the performance of four machine learning (ML) classifiers (classification trees, random forests, support vector machines, and nearest neighbor). These models used climatic and soil variables as environmental predictors with pretreatment of the datasets (principal component analysis and feature selection) and involved three spatial scales. We show that the ML classifiers produced more reliable results in regions where the vegetation-environment relationship is stronger as opposed to regions characterized by redundant vegetation patterns. The pretreatment of datasets and reduction in prediction scale had a substantial influence on the predictive performance of the classifiers. The use of ML classifiers to create potential vegetation maps shows promise as a more efficient way of vegetation modeling. The difference in performance between areas with poorly versus well-structured vegetation-environment relationships shows that some level of understanding of the ecology of the target region is required prior to their application. Even in areas with poorly structured vegetation-environment relationships, it is possible to improve classifier performance by either pretreating the dataset or reducing the spatial scale of the predictions.

Isolation and characterization of microsatellite primers for the critically endangered shrub Styphelia longissima (Ericaceae).

PREMISE OF THE STUDY: Microsatellite markers were developed for population genetic analysis in the rare shrub Styphelia longissima (Ericaceae). METHODS AND RESULTS: We generated ca. 2.5 million sequence reads using a Personal Genome Machine semiconductor sequencer. Using the QDD pipeline, we designed primers for >12,000 sequences with PCR product lengths of 80-480 bp. From these, 30 primer pairs were selected and screened using PCR; of these, 16 loci were found to be polymorphic, four loci were monomorphic, and 10 loci did not amplify reliably for S. longissima. For a sample of 57 plants from the only known population, the number of alleles observed for these 16 loci ranged from two to 21 and expected heterozygosity ranged from 0.49 to 0.91. These markers were also amplified in Astroloma xerophyllum, a closely related species. CONCLUSIONS: These markers will be used to characterize population genetic variation, spatial genetic structure, mating system parameters, and dispersal to aid in the management and conservation of the rare shrub S. longissima.

SNP discovery, validation, haplotype structure and linkage disequilibrium in full-length herbage nutritive quality genes of perennial ryegrass (Lolium perenne L.).

Development of accurate high-throughput molecular marker systems such as SNPs permits evaluation and selection of favourable gene variants to accelerate elite varietal production. SNP discovery in perennial ryegrass has been based on PCR amplification and sequencing of multiple amplicons designed to scan all components of the transcriptional unit. Full-length genes (with complete intron-exon structure and promoter information) corresponding to well-defined biochemical functions such as lignin biosynthesis and oligosaccharide metabolism are ideal for complete SNP haplotype determination. Multiple SNPs at regular intervals across the transcriptional unit were detected within and between the heterozygous parents and validated in the progeny of the F (1)(NA(6) x AU(6)) genetic mapping family. Haplotype structures in the parental genotypes were defined and haplotypic abundance, structure and variation were assessed in diverse germplasm sources. Decay of LD to r (2) values of c. 0.2 typically occurs over 500-3,000 bp, comparable with gene length and with little apparent variation between diverse, ecotypic and varietal population sub-groups. Similar patterns were revealed as limited blocks of intragenic LD. The results are compatible with the reproductive biology of perennial ryegrass and the effects of large ancestral population size. This analysis provides crucial information to validate strategies for correlation of haplotypic diversity and phenotypic variation through association mapping.

Assessment of genetic diversity in cultivars of white clover (Trifolium repens L.) detected by SSR polymorphisms.

White clover (Trifolium repens L.) is an important temperate pasture legume that plays a key role as a companion to grass species, such as perennial ryegrass (Lolium perenne L.). Due to the outbreeding nature of white clover, cultivars are highly heterogeneous. Genetic diversity was assessed using 16 elite cultivars from Europe, North and South America, Australia, and New Zealand. Fifteen simple sequence repeat markers that detect single, codominant polymorphic genetic loci were selected for the study. The genetic relationships among individuals were compared using phenetic clustering, and those among cultivars were compared using nonmetric multidimensional scaling. Intrapopula tion variability exceeded interpopulation variability, with substantial overlap among populations and weak interpopula tion differentiation. No obvious or significant differentiation was observed on the basis of morphology or geographic origin of the cultivars. The number of parental genotypes used to derive each cultivar was not a major determinant of genome-wide genetic diversity. The outcomes of this assessment of genetic variation in elite white clover germplasm pools have important implications for the feasibility of molecular marker-based cultivar discrimination, and will be used to assist the design of linkage disequilibrium mapping strategies for marker-trait association.

Development and characterization of EST-SSR markers for the crown rust pathogen of ryegrass (Puccinia coronata f.sp. lolii).

The causative organism of crown rust in ryegrasses (Puccinia coronata f.sp. lolii) is an obligate biotroph that causes significant economic losses within the temperate grazing industries of dairy, meat, and wool production. This study reports on the development, transferability, and utility of gene-associated simple sequence repeat (SSR) molecular markers for crown rust. Analysis of 1,100 expressed sequence tag (EST) sequences from a urediniospore-derived cDNA library detected 55 SSR loci. The majority of EST-SSR arrays contained perfect trinucleotide repeats with consistently low repeat numbers, and the motifs (ACC)n and (CAT)n were most commonly represented. DNA extraction from single pustules, in conjunction with multiple displacement amplification, provided the basis for PCR-based screening to evaluate genetic marker performance. An example of the identification of intraspecific genetic diversity was obtained from the analysis of 16 P. coronata isolates originating from the United Kingdom, Australia, New Zealand, and Japan. A subset of 12 robust EST-SSR markers was informative for determination of pathogen diversity within and between these localities. It was also demonstrated that crown rust EST-SSR markers were capable of cross-amplification in closely related fungal taxa (Puccinia spp.) and filamentous fungi within the Ascomycota.

Gene-associated single nucleotide polymorphism discovery in perennial ryegrass (Lolium perenne L.).

Molecular genetic marker development in perennial ryegrass has largely been dependent on anonymous sequence variation. The availability of a large-scale EST resource permits the development of functionally-associated genetic markers based on SNP variation in candidate genes. Genic SNP loci and associated haplotypes are suitable for implementation in molecular breeding of outbreeding forage species. Strategies for in vitro SNP discovery through amplicon cloning and sequencing have been designed and implemented. Putative SNPs were identified within and between the parents of the F(1)(NA(6) x AU(6)) genetic mapping family and were validated among progeny individuals. Proof-of-concept for the process was obtained using the drought tolerance-associated LpASRa2 gene. SNP haplotype structures were determined and correlated with predicted amino acid changes. Gene-length LD was evaluated across diverse germplasm collections. A survey of SNP variation across 100 candidate genes revealed a high frequency of SNP incidence (c. 1 per 54 bp), with similar proportions in exons and introns. A proportion (c. 50%) of the validated genic SNPs were assigned to the F(1)(NA(6) x AU(6)) genetic map, showing high levels of coincidence with previously mapped RFLP loci. The perennial ryegrass SNP resource will enable genetic map integration, detailed LD studies and selection of superior allele content during varietal development.

Non-Mendelian inheritance revealed in a genetic analysis of sexual progeny of Phytophthora cinnamomi with microsatellite markers.

We report the development of four microsatellite loci into genetic markers for the diploid oomycete plant pathogen Phytophthora cinnamomi and that (AC)(n) and (AG)(n) microsatellites are significantly less frequent than in plant and mammal genomes. A minisatellite motif 14 bp long was also discovered. The four microsatellite loci were used to analyze sexual progeny from four separate crosses of P. cinnamomi. A large proportion of non-Mendelian inheritance was observed across all loci in all four crosses, including inheritance of more than two alleles at a locus and noninheritance of alleles from either parent at a locus. The aberrant inheritance is best explained by nondisjunction at meiosis in both the A1 parent and the A2 trisomic parents, resulting in aneuploid progeny. Two loci on the putative trisomic chromosome showed linkage and no loci were linked to mating type. One aneuploid offspring was shown to have lost alleles at two loci following subculture over 4 years, indicating that aneuploid progeny may not be mitotically stable.