Aim This study has three broad aims: to (a) develop genus-specific primers for High Resolution Melt analysis (HRM) of members of Cyclopia Vent., (b) test the haplotype discrimination of HRM compared to Sanger sequencing, and (c) provide an example of using HRM to detect novel haplotype variation in wild C. subternata Vogel. populations. Location The Cape Floristic Region (CFR), located along the southern Cape of South Africa. Methods Polymorphic loci were detected through a screening process of sequencing 12 non-coding chloroplast DNA segments across 14 Cyclopia species. Twelve genus-specific primer combinations were designed around variable cpDNA loci, four of which failed to amplify under PCR; the eight remaining were applied to test the specificity, sensitivity and accuracy of HRM. The three top performing HRM Primer combinations were then applied to detect novel haplotypes in wild C. subternata populations, and phylogeographic patterns of C. subternata were explored. Results We present a framework for applying HRM to non-model systems. HRM accuracy varied across the PCR products screened using the genus-specific primers developed, ranging between 56 and 100%. The nucleotide variation failing to produce distinct melt curves is discussed. The top three performing regions, having 100% specificity (i.e. different haplotypes were never grouped into the same cluster, no false negatives), were able to detect novel haplotypes in wild C. subternata populations with high accuracy (96%). Sensitivity below 100% (i.e. a single haplotype being clustered into multiple unique groups during HRM curve analysis, false positives) was resolved through sequence confirmation of each cluster resulting in a final accuracy of 100%. Phylogeographic analyses revealed that wild C. subternata populations tend to exhibit phylogeographic structuring across mountain ranges (accounting for 73.8% of genetic variation base on an AMOVA), and genetic differentiation between populations increases with distance (p < 0.05 for IBD analyses). Conclusions After screening for regions with high HRM clustering specificity—akin to the screening process associated with most PCR based markers—the technology was found to be a high throughput tool for detecting genetic variation in non-model plants.

Background The current cultivation and plant breeding of Honeybush tea (produced from members of CyclopiaVent.) do not consider the genetic diversity nor structuring of wild populations. Thus, wild populations may be at risk of genetic contamination if cultivated plants are grown in the same landscape. Here, we investigate the spatial distribution of genetic diversity within Cyclopia intermedia E. Mey.—this species is widespread and endemic in the Cape Floristic Region (CFR) and used in the production of Honeybush tea. Methods We applied High Resolution Melt analysis (HRM), with confirmation Sanger sequencing, to screen two non-coding chloroplast DNA regions (two fragments from the atpI-aptH intergenic spacer and one from the ndhA intron) in wild C. intermedia populations. A total of 156 individuals from 17 populations were analyzed for phylogeographic structuring. Statistical tests included analyses of molecular variance and isolation-by-distance, while relationships among haplotypes were ascertained using a statistical parsimony network. Results Populations were found to exhibit high levels of genetic structuring, with 62.8% of genetic variation partitioned within mountain ranges. An additional 9% of genetic variation was located amongst populations within mountains, suggesting limited seed exchange among neighboring populations. Despite this phylogeographic structuring, no isolation-by-distance was detected (p > 0.05) as nucleotide variation among haplotypes did not increase linearly with geographic distance; this is not surprising given that the configuration of mountain ranges dictates available habitats and, we assume, seed dispersal kernels. Conclusions Our findings support concerns that the unmonitored redistribution of Cyclopia genetic material may pose a threat to the genetic diversity of wild populations, and ultimately the genetic resources within the species. We argue that ‘duty of care’ principles be used when cultivating Honeybush and that seed should not be translocated outside of the mountain range of origin. Secondarily, given the genetic uniqueness of wild populations, cultivated populations should occur at distance from wild populations that is sufficient to prevent unintended gene flow; however, further research is needed to assess gene flow within mountain ranges.

Aim The evolutionary forces that gave rise to the exceptional plant species richness of the Cape Floristic Region (CFR) have also likely played a role at the intraspecific level (i.e. plant populations)—and thereby generating shared phylogeographic patterns among taxa. Here we test whether plant populations in the CFR exhibit phylogeographic breaks across the boundaries between Centres of Endemism (CoEs). The boundaries between CoEs (derived from the distribution ranges of endemic taxa and currently mapped at a coarse, Quarter Degree Square scale) represent a spatial proxy for the evolutionary diversifying drivers acting on plant taxa in the CFR. Location The CFR, located along the southern Cape of South Africa. Methods Published phylogeographic literature were compiled and spatial patterns of genetic divergence re-analysed to assess the frequency at which CFR plant taxa exhibit phylogeographic breaks either (1) across or (2) within CoE boundaries. Population pairs from each study were compared across and within CoEs and scored as either exhibiting a phylogeographic break or not. Results Phylogeographic breaks in Cape plants were found to occur across the boundaries of CoEs more often than not. Significantly more population pairs exhibited phylogeographic breaks across CoE boundaries (506 of the 540, χ2 = 886, p < 0.001) and fewer breaks within CoEs (94 of 619, χ2 = 300, p < 0.001) than would be expected if there was equal probability of a genetic break occurring across CoE boundaries. Main conclusions The evolutionary forces that have produced and maintained the exceptional plant diversity in the CFR appear to have operated at the population level, producing similar patterns of phylogeographic structuring of plant lineages regardless of life history or taxonomy. This tendency for Cape plants to exhibit shared patterns of spatially structured genetic diversity that match the distribution of endemic taxa may assist CFR phylogeographers to streamline sampling efforts and test novel hypotheses pertaining to the distribution of genetic diversity among CFR plant taxa. Additionally, the resolution at which CoEs are mapped should be refined, which may provide a valuable tool for future conservation planning and the development of precautionary guidelines for the translocation of genetic material during species reintroductions and commercial cultivation of Cape endemic crops. Thus, to answer the question ‘Do Centres of Endemism provide a spatial context for predicting and preserving plant phylogeographic patterns in the Cape Floristic Region, South Africa?’—yes, CoEs do appear to be an important tool for Cape phylogeographers. However, the data is limited and more plant phylogeography work is needed in the CFR.

Ecosystem restoration and reforestation often operate at large scales, whereas monitoring practices are usually limited to spatially restricted field measurements that are (i) time- and labour-intensive, and (ii) unable to accurately quantify restoration success over hundreds to thousands of hectares. Recent advances in remote sensing technologies paired with deep learning algorithms provide an unprecedented opportunity for monitoring changes in vegetation cover at spatial and temporal scales. Such data can feed directly into adaptive management practices and provide insights into restoration and regeneration dynamics. Here, we demonstrate that convolutional neural network (CNN) segmentation algorithms can accurately classify the canopy cover of Portulacaria afra Jacq. in imagery acquired using different models of unoccupied aerial vehicles (UAVs) and under variable light intensities. Portulacaria afra is the target species for the restoration of Albany Subtropical Thicket vegetation, endemic to South Africa, where canopy cover is challenging to measure due to the dense, tangled structure of this vegetation. The automated classification strategy presented here is widely transferable to restoration monitoring as its application does not require any knowledge of the CNN model or specialist training, and can be applied to imagery generated by a range of UAV models. This will reduce the sampling effort required to track restoration trajectories in space and time, contributing to more effective management of restoration sites, and promoting collaboration between scientists, practitioners and landowners.

Drought prone, arid and semi-arid ecosystems are challenging to restore once degraded due to low levels of natural recruitment and survival of reintroduced plants. This is evident in the restoration of degraded succulent thicket habitats in the Albany Subtropical Thicket Biome located in South Africa. The current restoration practice for this ecosystem focuses predominantly on reintroducing Portulacaria afra L. Jacq., which is naturally dominant in terms of cover and biomass, but largely absent in regions degraded by domestic livestock. This has been achieved by planting unrooted cuttings with limited consideration of soil water availability in a drought-prone ecosystem. This study tests the effects of the timing of water availability after planting on the root development of P. afra cuttings. Cuttings were harvested from seven individual plants and grown in a glasshouse setting. Eighty four cuttings were taken from each individual, twelve for each of the seven watering treatments per individual plant. The treatments represented a time-staggered initial watering after planting, including: on the day of planting, 4 days, 7 days, 14 days, 21 days, and 28 days after planting. After 32 days, all treatments were watered on a bi-weekly basis for two weeks; a control treatment with no watering throughout the experiment was included. The proportion of rooted cuttings per treatment and dry root mass were determined at the end of the experimental period (day 42). The early onset of watering was associated with a higher percentage of rooting (X2(5) = 11.352, p = 0.045) and had a weak, but non-significant, impact on the final dry root mass (F5,36 = 2.109, p = 0.0631). Importantly, no clear rooting window within 28 days was detected as the majority of cuttings exhibited root development (greater than 50% of cuttings rooted for each individual parent-plant); this suggests that watering at the time of planting P. afra cuttings in-field for restoration may not be necessary. An unexpected, but important, result was that parent-plant identity had a strong interaction with the accumulation of root mass (F36,460 = 5.026, p < 0.001; LR7 = 122.99, p < 0.001). The control treatment, which had no water throughout the experiment, had no root development. These findings suggest that water availability is required for the onset of rooting in P. afra cutting. However, the duration of the experiment was insufficient to detect the point at which P. afra cuttings could no longer initiate rooting once exposed to soil moisture, and thus no rooting window could be defined. Despite harvesting material from the same source population, parent-plant identity strongly impacted root development. Further work is required to characterise the rooting window, and to explore the effect of parent-plant condition on in-field and experimental restoration results; we urge that experiments using P. afra closely track the parent-source at the individual level as this may be a factor that may have a major impact on results.