Lucy Beatrice Moore

ABSTRACTAimFerns are globally distributed, yet the number of studies examining the historical evolution of African taxa is relatively low. Investigation of the evolution of African fern diversity is critical in order to understand patterns and processes that have global relevance (e.g., the pantropical diversity disparity [PDD] pattern). This study aims to examine when and from where a globally distributed fern lineage arrived in sub‐Saharan Africa, to obtain a better understanding of potential processes contributing to patterns of diversity across the region.LocationGlobal, sub‐Saharan Africa.TaxonAsplenium (Aspleniaceae).MethodsWe analysed five loci from 537 Asplenium taxa using a maximum likelihood (IQ‐Tree) phylogenetic framework. For age estimation, we performed penalised likelihood as implemented in treePL, and executed a Bayesian analysis using BEAST. Biogeographical analyses were carried out using BioGeoBEARS.ResultsMost dispersals into Africa occurred within the last ~55 myr, with the highest diversity of sub‐Saharan African taxa concentrated in two clades, each of which descended from an Asian ancestor. Additional dispersals to sub‐Saharan Africa can be found throughout the phylogeny. Lastly, potential cryptic species diversity exists within Asplenium as evidenced by several polyphyletic taxa.Main ConclusionsWe recover multiple dispersals of Asplenium to sub‐Saharan Africa, with two major lineages likely diversifying after arrival.

The Khanka Lowland forest-steppe is the most eastern outpost of the Eurasian steppe biome. It includes unique grassland plant communities with rare steppe species. These coenosis have changed under the influence of anthropogenic activity, especially during the last 100 years and included both typical steppe species and nemoral mesophytic species. To distinguish these ecological groups of plants the random forest method with three datasets of environmental variables was applied. Specifically, a model of classification with the most important bioindices to predict a mesophytic ecological group of plants with a sensitivity greater than 80% was constructed. The data demonstrated the presence of steppe species that arrived at different times in the Primorye Territory. Most of these species are associated with the Mongolian-Daurian relict steppe complex and habit in the Khanka Lowland. Other species occur only in mountains in Primorye Territory and do not persist in the Khanka Lowland. These findings emphasize the presence of relict steppe communities with a complex of true steppe species in the Khanka Lowland. Steppe communities exhibit features of anthropogenic influence definitely through the long land use period but are not anthropogenic in origin. The most steppe species are located at the eastern border of distribution in the Khanka Lowlands and are valuable in terms of conservation and sources of information about steppe species origin and the emergence of the steppe biome as a whole.

Persicae Semen (Taoren), the seed of mature peaches consumed as both food and medicine, is native to the temperate regions of China, distributed in the provinces of North and East China, and currently cultivated worldwide. The primary components of Persicae Semen include volatile oil, protein, amino acids, amygdalin, and prunasin, all of which have pharmacological properties, such as anti-inflammatory, antioxidant, and immune regulatory effects, and are clinically used in the treatment of gynecological, cardiovascular, cerebrovascular, orthopedic, and digestive system diseases. This review provides a comprehensive perspective on the resource status, ethnopharmacology, phytochemistry, pharmacology, and toxicology, as well as the trend of Persicae Semen patent, global distribution, and clinical applications. This review will help facilitate the development and utilization of Persicae Semen in clinical settings.

Parasitic weeds in the genera Orobanche, Phelipanche (broomrapes) and Striga (witchweeds) have a devastating impact on food security across much of Africa, Asia and the Mediterranean Basin. Yet, how climatic factors might affect the range expansion of these weeds in the context of global environmental change remains unexplored. We examined satellite‐based environmental variables such as surface temperature, root zone soil moisture, and elevation, in relation to parasitic weed distribution and environmental conditions over time, in combination with observational data from the Global Biodiversity Information Facility (GBIF). Our analysis reveals contrasting environmental and altitude preferences in the genera Striga and Orobanche. Asiatic witchweed (Striga asiatica), which infests corn, rice, sorghum, and sugar cane crops, appears to be expanding its range in high elevation habitats. It also shows a significant association with heat‐moisture coupling events, the frequency of which is rising in such environments. These results point to geographical shifts in distribution and abundance in parasitic weeds due to climate change.

Species occurrence-based climate niche models (CNMs) serve as valuable tools for predicting the future ranges of species’ suitable habitats, aiding the development of climate change adaptation strategies. However, these models do not address an essential aspect - productivity, which holds economic significance for timber production and ecological importance for carbon sequestration and ecosystem services. In this study, we investigated the potential to extend the CNMs to predict species productivity under various climate conditions. Lodgepole pine (Pinus contorta Dougl. ex Loud.) and Douglas-fir (Pseudotsuga menziesii Franco.) were selected as our model species due to their comprehensive range-wide occurrence data and measurement of site productivity. To achieve this, we compared and optimized the performance of four individual modeling algorithms (Random Forest (RF), Maxent, Generalized Boosted Models (GBM), and Generalized Additive Model (GAM)) in reflecting site productivity by evaluating the effect of spatial filtering, and the ratio of presence to absence (p/a ratio) observations. Additionally, we applied a binning process to capture the overarching trend of climatic effects while minimizing the impact of other factors. We observed consistency in optimal performance across both species when using the unfiltered data and a 1:1.5 p/a ratio, which could potentially be extended to other species. Among the modeling algorithms explored, we selected the ensemble model combining RF and Maxent as the final model to predict the range-wide site productivity for both species. The predicted range-wide site productivity was validated with an independent dataset for each species and yielded promising results (R2 above 0.7), affirming our model’s credibility. Our model introduced an innovative approach for predicting species productivity with high accuracy using only species occurrence data, and significantly advanced the application of CNMs. It provided crucial tools and insights for evaluating climate change's impact on productivity and holds a better potential for informed forest management and conservation decisions.

Aim Species occurrence data are valuable information that enables one to estimate geographical distributions, characterize niches and their evolution, and guide spatial conservation planning. Rapid increases in species occurrence data stem from increasing digitization and aggregation efforts, and citizen science initiatives. However, persistent quality issues in occurrence data can impact the accuracy of scientific findings, underscoring the importance of filtering erroneous occurrence records in biodiversity analyses.InnovationWe introduce an R package, occTest, that synthesizes a growing open‐source ecosystem of biodiversity cleaning workflows to prepare occurrence data for different modelling applications. It offers a structured set of algorithms to identify potential problems with species occurrence records by employing a hierarchical organization of multiple tests. The workflow has a hierarchical structure organized in testPhases (i.e. cleaning vs. testing) that encompass different testBlocks grouping different testTypes (e.g. environmental outlier detection), which may use different testMethods (e.g. Rosner test, jacknife,etc.). Four different testBlocks characterize potential problems in geographic, environmental, human influence and temporal dimensions. Filtering and plotting functions are incorporated to facilitate the interpretation of tests. We provide examples with different data sources, with default and user‐defined parameters. Compared to other available tools and workflows, occTest offers a comprehensive suite of integrated tests, and allows multiple methods associated with each test to explore consensus among data cleaning methods. It uniquely incorporates both coordinate accuracy analysis and environmental analysis of occurrence records. Furthermore, it provides a hierarchical structure to incorporate future tests yet to be developed.Main conclusionsoccTest will help users understand the quality and quantity of data available before the start of data analysis, while also enabling users to filter data using either predefined rules or custom‐built rules. As a result, occTest can better assess each record's appropriateness for its intended application.

Myoporum is a genus of trees and shrubs native to the Northern Hemisphere that has been introduced to many parts of the world, mainly for ornamental purposes. We assessed the introduction history, distribution, and extent of naturalization/invasion for Myoporum species in South Africa.Information was collated to determine key events associated with the introduction, establishment, and naturalization of Myoporum in South Africa. Data were collated to determine the current distribution of the genus in South Africa. Twenty sites in the Western Cape were sampled to determine correlates of naturalization. Myoporum was first recorded in South Africa in 1934. Three species were confirmed to be present in South Africa: M. insulare, M. laetum and M. montanum (37 %, 25 % and 24 % of all iNaturalist records respectively). Most records are from the Western Cape (91 %) and small parts of the Eastern Cape; isolated populations occur in Gauteng and the Northern Cape. We could not confirm the presence M. petiolatum, M. tenuifolium or M. tetrandrum. Field surveys revealed widespread naturalization of M. insulare (46 % of all Research Grade observations in iNaturalist); this species was categorized code D1 in the introduction-naturalization-invasion continuum. Myoporum laetum (C3) and M. montanum (C2) are also widely naturalized but over smaller areas. Naturalized populations comprised predominantly juvenile M. insulare plants occurring in highly disturbed (transformed) habitats. Formal risk analyses for all Myoporum species in South Africa are needed as the basis for re-evaluation of their status in national legislation.

Present-day geographic and phylogenetic patterns often reflect the geological and climatic history of the planet. Neontological distribution data are often sufficient to unravel a lineage’s biogeographic history, yet ancestral range inferences can be at odds with fossil evidence. Here, I use the fossilized birth–death process and the dispersal–extinction cladogenesis model to jointly infer the dated phylogeny and range evolution of the tree fern order Cyatheales. I use data for 101 fossil and 442 extant tree ferns to reconstruct the biogeographic history of the group over the last 220 million years. Fossil-aware reconstructions evince a prolonged occupancy of Laurasia over the Triassic–Cretaceous by Cyathealean tree ferns, which is evident in the fossil record but hidden from analyses relying on neontological data alone. Nonetheless, fossil-aware reconstructions are affected by uncertainty in fossils’ phylogenetic placement, taphonomic biases, and specimen sampling and are sensitive to interpretation of paleodistributions and how these are scored. The present results highlight the need and challenges of incorporating fossils into joint inferences of phylogeny and biogeography to improve the reliability of ancestral geographic range estimation.

Aim Species severely under‐represented in fossil pollen records leave gaps in interpretations and reconstructions of past vegetation. These ‘silent taxa’ leave little or no trace due to low pollen production, dispersal, preservation and taxonomic resolution. An approach for including them is through associating them with other species with reliable pollen representation. Here, we demonstrate a method for selecting such a proxy species for the Holocene using modern vegetation data.LocationNew Zealand.TaxonBeilschmiedia tawa (A.Cunn.) Benth. & Hook. F. ex Kirk (Lauraceae).MethodsWe used vegetation plot data to perform a pairwise co‐occurrence analysis of the New Zealand indigenous forest metacommunity to identify species with a strong positive association with Beilschmiedia tawa (tawa), a common tree severely under‐recorded in the pollen record. For those species, we then modelled their realised climatic niches to identify species with high niche overlap. We discuss how well those species could be interpreted from the Holocene fossil pollen record based on the representation of their pollen taxa.ResultsKnightia excelsa (rewarewa; Proteaceae) is a potential proxy for B. tawa in Holocene fossil pollen records, and other, range‐limited species may provide community‐specific proxies. We show combining resampling with sub‐sampling is a robust method for reducing the high false positive rate associated with large co‐occurrence analyses (1000+ sites) by limiting the sample size to 100 sites.Main ConclusionsWe show that the palaeoecology of silent taxa can be studied via proxy species, allowing their past distributions to be better understood. We highlight the importance of modelling many aspects of the realised niche to understand the usefulness and limitations of the silent–proxy association. Future research should focus on testing the underlying assumptions of the silent–proxy relationship so that models built on modern data can confidently be applied to palaeoecological data.

Invasive plant species can suppress local biodiversity, affect soil properties and modify the landscape. However, an additional concern of plant invasions that has been more disregarded is their impact on environmental human health. Here, we discuss the case of Cortaderia selloana (Schult. & Schult.f.) Asch. & Graebn, as an example of a worldwide invasive species with a strong environmental impact. We summarise the main facts regarding the C. selloana invasion, the recent clinical evidence of its impact on human health and the great potential expansion of the species in the context of climate change. C. selloana constitutes a clear example to boost demands from policy makers for urgent and efficient measures to control or eradicate invasive species, also in ruderal areas. This aggressive invader is still out of relevant binding international invasive species catalogues, including the European List of Invasive Alien Species of Union concern (Union list), and is still subjected to extensive trading in some European countries. Therefore, including C. selloana in the Union list becomes mandatory to impose full restrictions on keeping, importing, selling, breeding and cultivating the species.