Species absences can provide meaningful insights for ecological restoration. This ‘dark diversity’ can reveal species pools, the number and characteristics of suitable yet absent species, and the proportion of potential diversity realised (community completeness). Here, patterns in species richness, dark diversity, species pools and community completeness were assessed along a 25-year chronosequence of jarrah ( Eucalyptus marginata ) forest under restoration in southwestern Australia. Species were classified into plant functional types (PFTs) using a multi-trait approach to assess the functional analogues of the same metrics. A decline in species and functional richness over time corresponded with increased dark diversity and lower community completeness, and the composition of species and functional pools changed over time; however, whether these short-term trends are consistent with long-term succession patterns in the jarrah forest warrants further investigation. Variability detected among plots of the same age indicated that site and year effects influence the diversity and composition of species and functional pools. Restoration practices driving dark diversity affinity—the likelihood of species and PFTs being absent from suitable sites—were then assessed. Topsoil handling, fertilisation, the species richness of the applied seed mix and the timing of seeding emerged as influential. Species and PFTs absent from restoration plots remained members of the species and functional pools as dark diversity, suggesting that those plots maintain the potential to recruit missing species. This research exemplifies how dark diversity coupled with functional approaches can advance the monitoring and management of restoration.

Understanding what makes a community vulnerable to invasion is integral to the successful management of invasive species. Our understanding of how characteristics of resident plant interactions, such as the network architecture of interactions, can affect the invasibility of plant communities is limited. Using a simulation model, we tested how successfully a new plant invader established in communities with different network architectures of species interactions. We also investigated whether species interaction networks lead to relationships between invasibility and other community properties also affected by species interaction networks, such as diversity, species dominance, compositional stability and the productivity of the resident community. We found that higher invasibility strongly related with a lower productivity of the resident community. Plant interaction networks influenced diversity and invasibility in ways that led to complex but clear relationships between the two. Heterospecific interactions that increased diversity tended to decrease invasibility. Negative conspecific interactions always increased diversity and invasibility, but increased invasibility more when they increased diversity less. This study provides new theoretical insights into the effects of plant interaction networks on community invasibility and relationships between diversity and invasibility. Combined with increasing empirical evidence, these insights could have useful implications for the management of invasive plant species.

The restoration of diverse self-sustaining ecosystems requires re-establishment of functional interactions among species. For plant communities, pollinators are usually essential for pollination, seed set and seed quality. A common assumption in ecological restoration for plants pollinated by animals is one of 'build it and they will come', which is rarely tested. Beyond seed set, there may be negative genetic consequences for seed quality if pollinators and their behaviour do not reflect those in reference populations. Here, we conduct an ecological genetic assessment of seed quality via mating system parameters in Lambertia multiflora (Proteaceae), a species dependent on nectar-feeding birds for pollination. Four populations of L. multiflora in disturbed sites that were rehabilitated following mineral sands mining were compared with four native reference populations, near Eneabba, Western Australia. In each population, approximately 10 offspring from each of 10 maternal plants were genotyped with 11 highly polymorphic microsatellite markers. From these data, genetic diversity and mating system parameters were assessed, and found to be equivalent across all populations. Mean allelic diversity and heterozygosity across loci were very high. All populations were completely outcrossing with no bi-parental inbreeding. Mean correlated paternity, sibship and effective population size estimates for restored and natural populations were not significantly different and reflected uniformly high paternal diversity and wide outcrossing. Equivalent genetic results for restored and natural reference populations indicate successful restitution of bird-pollinator services for L. multiflora in these post-mining rehabilitation sites. Synthesis and applications. Reviewing our results with other published studies to date suggests a resilience of bird-pollinator services in restored plant communities. These findings provide some reassurance to restoration practitioners working in these global south systems where bird pollination is a feature, at least for similar landscape scenarios. Our study also highlights the global contribution of ecological genetics to the objective assessment of functional species interactions in ecological restoration, an increasingly important goal of land managers and regulators seeking to improve restoration standards. Reviewing our results with other published studies to date suggests a resilience of bird-pollinator services in restored plant communities. These findings provide some reassurance to restoration practitioners working in these global south systems where bird pollination is a feature, at least for similar landscape scenarios. Our study also highlights the global contribution of ecological genetics to the objective assessment of functional species interactions in ecological restoration, an increasingly important goal of land managers and regulators seeking to improve restoration standards.image

Post‐mining scenarios present challenges for restoration in a wide range of environments, especially in the context of climate change. The source of seed for restoration has been an issue of intense focus, as seed provenance can impact plant fitness and restoration outcomes. However, post‐mining landscapes require substrate reconstruction prior to vegetation re‐establishment. Critically, the relative importance of provenance and substrate in ecosystem recovery has been rarely quantified in a statistically rigorous framework. We established a large provenance trial with Banksia attenuata and Eucalyptus todtiana at two Western Australian mine sites in post‐mining reconstructed and adjoining un‐mined substrates. We show that site and substrate were 4 and 26 times more important than provenance in explaining survival for B. attenuata and E. todtiana , respectively. At one site, there was 100% mortality in the post‐mining substrate but high survival and no clear provenance effect in the un‐mined substrate. At the second site, there was again no clear provenance effect, but E. todtiana survival was higher in the post‐mining than un‐mined substrate. Our results show that post‐mining substrate changes can overwhelm provenance issues. Consequently, where substrates are highly impacted, alternative restoration targets and/or greater investment in substrate research are needed to improve restoration outcomes. Due to the thousands of mines across the world, this is an internationally relevant finding with important implications for investment into global ecosystem recovery.

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.

1. Negative conspecific interactions have been shown to promote diversity in plant communities, as have some heterospecific interactions such as intransitive competition and facilitation. However, it is unclear whether combinations of conspecific and other heterospecific interactions can also promote diversity in plant communities. We therefore investigated the effects of heterospecific plant interaction network architecture with and without conspecific interactions on alpha diversity, beta diversity and long-term diversity. 2. We simulated long-term plant community dynamics for theoretical plant interaction scenarios with modular, ring and nested networks of positive or negative heterospecific interactions and conspecific interactions, using a spatially explicit cellular automaton model that accounted for stochastic effects. Throughout the simulations several measures of diversity were recorded. 3. The way that heterospecific interactions affected diversity depended strongly on various characteristics of the architecture of the interaction network. Negative conspecific interactions generally promoted alpha diversity and reduced beta diversity, with a few key exceptions. Positive heterospecific ring interactions that resulted in cyclic appearance and disappearance of species groups led to the greatest long-term diversity (a measure of the total diversity over time). 4. This study provides new theoretical insights into how the network architecture of heterospecific plant interactions can affect the diversity of plant communities over time and provides the first evidence that heterospecific plant interactions can increase long-term diversity more than negative conspecific interactions alone.

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.

Long‐term studies of vegetation recovery following post‐mining restoration in low‐productivity, high‐stress areas are limited, but essential for understanding underlying ecological processes and evaluating management practices. This study's goal was to describe temporal patterns of recovery (up to 37 years) in vegetation structure, floristic diversity, and composition following post‐mining restoration at two sites, and identify potential drivers of restoration outcomes, in the nutrient‐poor, seasonally dry, species‐rich, fire‐prone kwongan vegetation of southwest Western Australia. Vegetation development is progressing and restoration measures are within range of native reference values, but there is large variation in both patterns observed and restoration outcomes. Several patterns described share similarities with post‐fire recovery of kwongan, and post‐disturbance recovery of other low‐productivity, high‐stress, fire‐prone systems. However, differences in some patterns between sites indicate differences in the underlying mechanisms of recovery. Many management and environmental variables emerge as significant drivers of restoration outcomes but age, fire, and the planting of seedlings account for the largest amount of variation. Adaptive management at both sites appears to be facilitating improved restoration outcomes over time. Using a combination of space‐for‐time, plot level, and linear mixed effects modeling perspectives to examine patterns provides greater insights into restoration recovery than a chronosequence perspective alone. This study will inform restoration practices and outcomes not only in kwongan but in other comparable systems also.

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.

Seedling emergence from broadcast seed is notoriously low in mining rehabilitation. At Iluka Resources’ Eneabba mine in the Mid West of Western Australia, eight-fold more seedlings emerged under ideal nursery conditions in 2015 than when that seed was broadcast in the field. Unlocking this potential in broadcast seed is critical to establish the desired plant density and species diversity of restored kwongan shrubland vegetation. Erosion, both wind and water, is a major factor affecting seedling emergence in newly rehabilitated mines sites. To control wind erosion at Eneabba, Iluka applies a crust of dilute, non-toxic bitumen emulsion to the sandy soil surface. This crust degrades over a few years but does not inhibit germination. It allows seedlings to emerge and establish under windy conditions, common at Eneabba, holding the seed in the soil matrix for germination to occur and eliminating the sand-blasting that kills newly emerged seedlings. Combining this crust application with ripping-mounding to prevent water erosion in 2016 increased seedling establishment almost two-fold. Land imprinting, a technique developed in the 1970s, reduces rainfall runoff and increases infiltration and nutrient/organic matter accumulation thereby improving seedling emergence and establishment. However, the imprints erode too quickly in sandy soils like those at Eneabba. A trial in 2017, combining land imprinting and bitumen emulsion crust increased seedling emergence more than two-fold for broadcast seed and three-fold for topsoil-derived seed. Burial of the diverse sized and shaped seed, for improved germination, was achieved in 2018. This combined with land imprinting and crust application increased seedling emergence from broadcast seed by 50% on the 2017 trial. Data from large-scale field trials of these rehabilitation practices and their innovative combination will be presented to illustrate their effectiveness and applicability in other projects. New, custom-built seeding, land imprinting and crust application equipment used in 2019 Eneabba rehabilitation will be unveiled.

The nature of community patterns and environmental drivers in kwongan mediterranean-type shrubland on nutrient-poor soils occurring in Western Australia remain poorly examined. We aimed to determine whether (i) classification of the kwongan vegetation of the northern Swan Coastal Plain would be ecologically informative and (ii) which environmental drivers underpin the plant community patterns. The study area was positioned on the northern Swan Coastal Plain, locality of Cooljarloo (30 degrees 39 ' S, 115 degrees 22 ' E), situated 170 km north of Perth, Western Australia. Compositional (518 species x 337 releves) and environmental data set (29 variables x 87 releves) describing time since last fire, soil chemical and physical properties, and terrain characteristics were analysed using classification and ordination techniques. OptimClass assisted in the selection of a robust data transformation, resemblance function and clustering algorithm to identify the vegetation patterns. Major ecological drivers of the vegetation patterns were detected using distance-based redundancy analysis (db-RDA). Classification revealed major groupings of Wet Heath and Banksia Woodland distinguishable by the high prevalence of myrtyoid and proteoid taxa, respectively. On floristic-sociological grounds, we recognised four Wet Heath and two Banksia Woodland communities. The Wet Heath was constrained to areas of higher litter depth (db-RDA axis 1: 9%). Soil chemical and physical properties explained the highest proportion (17%) of the compositional variance, while the terrain- and fire-related variables explained 2% and <0.001%, respectively. While fire explained little compositional variance overall, a separate db-RDA analysis found that it may play an important pattern-structuring role within Banksia Woodlands. Fine-scale compositional patterns correspond only to a small extent to environmental data; the substantial unexplained variance may be due to slow-acting neutral and stochastic processes.

The concepts of traits, plant functional types (PFT), and functional communities are effective tools for the study of complex phenomena such as plant community assembly. Here, we (1) suggest a procedure formalising the classification of response traits to construct a PFT system; (2) integrate the PFT, and species compositional data to formally define functional communities; and, (3) identify environmental drivers that underpin the functional-community patterns. A species-trait data set featuring species pooled from two study sites (Eneabba and Cooljarloo, Western Australia), both supporting kwongan vegetation (sclerophyllous scrub and woodland communities), was subjected to classification to define PFTs. Species of both study sites were replaced with the newly derived PFTs and projected cover abundance-weighted means calculated for every plot. Functional communities were defined by classifications of the abundance-weighted PFT data in the respective sites. Distance-based redundancy analysis (using the abundance-weighted community and environmental data) was used to infer drivers of the functional community patterns for each site. A classification based on trait data assisted in reducing trait-space complexity in the studied vegetation and revealed 26 PFTs shared across the study sites. In total, seven functional communities were identified. We demonstrate a putative functional-community pattern-driving effect of soil-texture (clay-sand) gradients at Eneabba (42% of the total inertia explained) and that of water repellence at Cooljarloo (36%). Synthesis. This paper presents a procedure formalising the classification of multiple response traits leading to the delineation of PFTs and functional communities. This step captures plant responses to stresses and disturbance characteristic of kwongan vegetation, including low nutrient status, water stress, and fire (a landscape-level disturbance factor). Our study is the first to introduce a formal procedure assisting their formal recognition. Our results support the role of short-term abiotic drivers structuring the formation of fine-scale functional community patterns in a complex, species-rich vegetation of Western Australia.

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.

Questions: The community patterns in kwongan, a mediterranean-type scrub on nutrient-poor soils occurring in Western Australia, are poorly understood due to only few, focused studies using disparate sampling designs. We aimed to determine whether (a) classification of the kwongan vegetation of the Eneabba Sandplains leads to an ecologically informative classification scheme, and (b) we could identify environmental drivers underpinning the plant community patterns. Location: Township of Eneabba (29 degrees 82 ' S, 115 degrees 27 ' E), approximately 250 km north of Perth, Western Australia, covering 1,210 km(2). Methods: We used a data set consisting of 512 releves, collected following the standard field methodology of the Braun-Blanquet approach, and accompanied by an extensive set of environmental data consisting of 94 variables representing climate, fire, soil and terrain properties across 189 releves. The data were classified and ordinated by a series of multivariate analyses. OptimClass assisted in the selection of the most robust classification procedure. Distance-based redundancy analysis (db-RDA) inferred the major ecological drivers of the vegetation patterns. Results: Numerical classification, nonmetric multidimensional scaling, and syntaxonomic tabular analysis revealed two major community groups (MCG A and B), eight community groups, and 17 communities in the kwongan vegetation of the study area. All vegetation units are characterised in terms of floristic composition and position along major ecological gradients in the studied area. The MCGs separated along a composite gradient of soil-texture and exchangeable cations. The first two db-RDA axes explained 21% of the total variance which is very low, considering the high number of environmental variables used. Conclusions: Our study provides a comprehensive insight into the high variability of vegetation types in hyper-diverse kwongan scrub at a landscape spatial scale; it is the first syntaxonomic account of the Western Australian kwongan vegetation, presenting a complete tabular comparative analysis. The studied major community groups segregate along a soil-texture and an exchangeable-cation content gradient. At a community scale, environmental filtering explained a small fraction of the vegetation-environment relationship. We suggest that the unexplained portion of the vegetation-environment relationship might be a product of slow-acting neutral processes in this hyper-diverse system; this assertion is amenable to rigorous future testing.

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.

Asexual fungal endophytes of the genus Epichloë form mutually beneficial associations with cool-season pasture grasses such as ryegrasses (Lolium spp.). Alkaloid production by the fungus confers both beneficial (deterrence of invertebrate herbivory) and detrimental (toxicity to mammalian livestock) attributes. A few novel strains with desirable metabolite profiles have been advanced into commercial production by inoculation of perennial ryegrass cultivars. In the present study, an integrated process for discovery of novel endophytes based on exploitation of genotypic information has been designed and implemented. A survey of genetic diversity was performed on a large-scale, customised germplasm collection (containing 244 accessions) in order to identify previously uncharacterised endophyte genotypes. Preliminary qualitative metabolic profiling in the endogenous genetic background permitted elimination of undesirable combinations, and definition of a subset of priority candidates. A novel method was developed for inoculation of endophytes into meristem-culture-derived callus tissue of single genotypes from multiple perennial ryegrass cultivars, in order to allow isogenic comparisons with respect to both host and endophyte genotype. Beneficial toxin profiles were confirmed for associations formed with the grass genotypic panel, and semi-quantitative metabolite analysis provided evidence for genotype-specific effects of both host and genotype on levels of alkaloid production. Vegetative stability was also assessed over both shorter and longer terms. A final set of three prioritised candidates was obtained, two of which (belonging to the known taxa E. festucae var. lolii and LpTG-2) produce the alkaloids ergovaline and peramine. The third candidate endophyte, belonging to a putative novel taxon, solely produces representatives of an additional alkaloid class, the epoxy-janthitrems.

Abstract. Due to the complex genetic architecture of perennial ryegrass, based on an obligate outbreeding reproductive habit, association-mapping approaches to genetic dissection offer the potential for effective identification of genetic marker–trait linkages. Associations with genes for agronomic characters, such as components of herbage nutritive quality, may then be utilised for accelerated cultivar improvement using advanced molecular breeding practices. The objective of the present study was to evaluate the presence of such associations for a broad range of candidate genes involved in pathways of cell wall biosynthesis and carbohydrate metabolism. An association-mapping panel composed from a broad range of non-domesticated and varietal sources was assembled and assessed for genome-wide sequence polymorphism. Removal of significant population structure obtained a diverse meta-population (220 genotypes) suitable for association studies. The meta-population was established with replication as a spaced-plant field trial. All plants were genotyped with a cohort of candidate gene-derived single nucleotide polymorphism (SNP) markers. Herbage samples were harvested at both vegetative and reproductive stages and were measured for a range of herbage quality traits using near infrared reflectance spectroscopy. Significant associations were identified for ∼50% of the genes, accounting for small but significant components of phenotypic variance. The identities of genes with associated SNPs were largely consistent with detailed knowledge of ryegrass biology, and they are interpreted in terms of known biochemical and physiological processes. Magnitudes of effect of observed marker–trait gene association were small, indicating that future activities should focus on genome-wide association studies in order to identify the majority of causal mutations for complex traits such as forage quality.