Shedding new light on the origin and spread of the brinjal eggplant (Solanum melongena L.) and its wild relatives.

PREMISE OF THE STUDY: While brinjal eggplant (Solanum melongena L.) is the second most important solanaceous fruit crop, we lack firm knowledge of its evolutionary relationships. This in turn limits efficient use of crop wild relatives in eggplant improvement. Here, we examine the hypothesis of linear step-wise expansion of the eggplant group from Africa to Asia. METHODS: We use museum collections to generate nuclear and full-plastome data for all species of the Eggplant clade. We combine a phylogenomic approach with distribution data to infer a biogeographic scenario for the clade. KEY RESULTS: The Eggplant clade has Pleistocene origins in northern Africa. Dispersals to tropical Asia gave rise to Solanum insanum, the wild progenitor of the eggplant, and to African distinct lineages of widespread and southern African species. Results suggest that spread of the species to southern Africa has been recent and likely facilitated by large mammalian herbivores, such as the African elephant and impala feeding on Solanum fruit. CONCLUSIONS: Rather than a linear 'Out Of Africa' sequence, our results are more consistent with an initial dispersal event into Asia, and subsequent wide dispersal and differentiation across Africa driven by large mammalian herbivores. Our evolutionary results will affect future work on eggplant domestication and affect the use of wild relatives in breeding of this increasingly important solanaceous crop.

Crop wild relatives of the brinjal eggplant (Solanum melongena): Poorly represented in genebanks and many species at risk of extinction.

PREMISE OF THE STUDY: Crop wild relatives (CWR) provide important traits for plant breeding, including pest, pathogen, and abiotic stress resistance. Therefore, their conservation and future availability are essential for food security. Despite this need, the world's genebanks are currently thought to conserve only a small fraction of the total diversity of CWR. METHODS: We define the eggplant genepool using the results of recent taxonomic and phylogenetic studies. We identify the gaps in germplasm accessions for eggplant (Solanum melongena L.) CWR by comparing georeferenced herbarium records and germplasm accessions using a gap analysis methodology implementing species distribution models (SDM). Preliminary conservation assessments using IUCN criteria were done for all species and were combined with the gap analysis to pinpoint where under-collected and threatened CWR species coincide with high human disturbance and occur outside of protected areas. KEY RESULTS: We show that many eggplant CWR are poorly represented in genebanks compared to their native ranges. Priority areas for future collecting are concentrated in Africa, especially along the Kenya-Tanzania border. Fourteen species of eggplant CWR are assessed as threatened or near-threatened; these are also concentrated in eastern Africa. CONCLUSIONS: The knowledge base upon which conservation of wild relative germplasm depends must take into account both taxonomic and phylogenetic advances. Beyond traditional research focus on close relatives of crops, we emphasize the benefits of defining a broad CWR genepool, and the importance of assessing threats to wild species when targeting localities for future collection of CWR to improve crop breeding in the face of environmental change.

Emerging New Crop Pests: Ecological Modelling and Analysis of the South American Potato Psyllid Russelliana solanicola (Hemiptera: Psylloidea) and Its Wild Relatives.

Food security is threatened by newly emerging pests with increased invasive potential accelerated through globalization. The Neotropical jumping plant louse Russelliana solanicola Tuthill is currently a localized potato pest and probable vector of plant pathogens. It is an unusually polyphagous species and is widely distributed in and along the Andes. To date, introductions have been detected in eastern Argentina, southern Brazil and Uruguay. Species distribution models (SDMs) and trait comparisons based on contemporary and historical collections are used to estimate the potential spread of R. solanicola worldwide. We also extend our analyses to all described species in the genus Russelliana in order to assess the value of looking beyond pest species to predict pest spread. We investigate the extent to which data on geographical range and environmental niche can be effectively extracted from museum collections for comparative analyses of pest and non-pest species in Russelliana. Our results indicate that R. solanicola has potential for invasion in many parts of the world with suitable environmental conditions that currently have or are anticipated to increase potato cultivation. Large geographical ranges are characteristic of a morphological subgeneric taxon group that includes R. solanicola; this same group also has a larger environmental breadth than other groups within the genus. Ecological modelling using museum collections provides a useful tool for identifying emerging pests and developing integrated pest management programs.

The potato pest Russelliana solanicola Tuthill (Hemiptera: Psylloidea): taxonomy and host-plant patterns.

The Neotropical jumping plant-louse Russelliana solanicola Tuthill is a potato pest and a probable vector of plant pathogens. Populations morphologically similar to those found on potatoes have been collected on plants of at least ten different families, four of which have been confirmed as hosts by the presence of immatures. This suggests that R. solanicola is either a single polyphagous species or a complex of closely related, monophagous species (host races/cryptic species). Results of our analyses of multiple morphometric characters show for both sexes a grouping of the populations of R. solanicola and a clear separation of the latter from other Russelliana species. On the other hand, within R. solanicola, there is an overlap of populations from different host-plants as well as from different geographical regions. The results of the present study strongly suggest that R. solanicola is a single, polyphagous species and the known distribution indicates that it is native to the Andes. It is likely that R. solanicola has been introduced into eastern Argentina, Brazil and Uruguay. The polyphagy together with the ability to disperse and transmit plant pathogens potentially make this species an economically important pest of potato and other crop species.

The sampled Red List Index for plants, phase II: ground-truthing specimen-based conservation assessments.

The IUCN Sampled Red List Index (SRLI) is a policy response by biodiversity scientists to the need to estimate trends in extinction risk of the world's diminishing biological diversity. Assessments of plant species for the SRLI project rely predominantly on herbarium specimen data from natural history collections, in the overwhelming absence of accurate population data or detailed distribution maps for the vast majority of plant species. This creates difficulties in re-assessing these species so as to measure genuine changes in conservation status, which must be observed under the same Red List criteria in order to be distinguished from an increase in the knowledge available for that species, and thus re-calculate the SRLI. However, the same specimen data identify precise localities where threatened species have previously been collected and can be used to model species ranges and to target fieldwork in order to test specimen-based range estimates and collect population data for SRLI plant species. Here, we outline a strategy for prioritizing fieldwork efforts in order to apply a wider range of IUCN Red List criteria to assessments of plant species, or any taxa with detailed locality or natural history specimen data, to produce a more robust estimation of the SRLI.

The effects of sampling bias and model complexity on the predictive performance of MaxEnt species distribution models.

Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.