John Medley Wood

In this study, we documented and compared similarities of the alien plant species richness between South Africa represented by three provinces: Free State (FS), Eastern Cape (EC), and KwaZulu-Natal (KZN), and Lesotho—an important water source area for southern Africa. We tested the prediction that alien plant species in Lesotho are a subset of South Africa’s species partly because of the short geographical distances between the provinces and Lesotho, and environmental similarity. Overall, 7124 records containing 1040 individual alien plant species belonging to 147 families were documented. South Africa had significantly greater alien plant species records than Lesotho. Of 147 plant families, 44 were represented in both countries, and 101 families did not occur in Lesotho. Against the study prediction, the Geraniaceae and Orobanchaceae families occurred in Lesotho but not in three provinces. KwaZulu-Natal had a significantly greater number of species than Lesotho but not the other provinces, and 49% of species in three provinces originated from the Americas (i.e. South and North), Europe, and Asia. A similar pattern was observed in Lesotho. Woody and herbaceous alien plants, habitat transformers, dominated three provinces, while herbaceous species dominated Lesotho. The 62% of 1040 alien species were not listed in the South African national regulations, indicating their negative impacts are also unknown in the study region. Plant nurseries were a dominant species dispersal pathway in South Africa, while home gardens were prominent in Lesotho. We conclude that invasive plant species constitute a future threat to the Lesotho Drakensberg highlands water catchments and recommend prioritising their management and improving cross-border biosecurity between Lesotho and South Africa.

The use of non-pollen palynomorphs (NPP), particularly fossil fungi and algae, as palaeobiological proxies for Late Cretaceous palaeoenvironmental and palaeoclimatic reconstructions of warm-to-hot greenhouse conditions, can enhance our understanding of climate change impacts on modern Patagonian environments. This study aimed to reconstruct the Maastrichtian palaeoenvironment and palaeoclimate in the Cañadón Asfalto Basin (CAB, Chubut Province) by testing these NPPs as proxies using the Nearest Living Relative method (NLR). Moreover, using modern ecological requirements from open-source databases, such as GBIF and processing it with an open-source, cross-platform tool like QGIS, linked with Köppen-Geiger shapefiles, provided evidence of climate-driven palaeo-distribution patterns of fungal and algal diversity at CAB. Applying modern ecological requirements and biogeographic distribution data, we reconstructed the palaeoclimate as temperate with evenly distributed precipitation and warm summers, corresponding to the Cfb climate zone in Köppen-Geiger classifications. Additionally, our methodology produced reliable results regarding Cenozoic floras’ physiognomies based on fossil fungi, revealing a transition from sparsely wooded areas with palms and prairies to complex forest ecosystems with palms, deciduous trees, and shrubland. Furthermore, testing Cretaceous algae with the NLR method, for the first time, provided comprehensive insights into past water body characteristics, including trophic state and water quality.

Premise Cleomaceae is an important model clade for studies of evolutionary processes including genome evolution, floral form diversification, and photosynthetic pathway evolution. Diversification and divergence patterns in Cleomaceae remain tangled as research has been restricted by its worldwide distribution, limited genetic sampling and species coverage, and a lack of definitive fossil calibration points.MethodsWe used target sequence capture and the Angiosperms353 probe set to perform a phylogenetic study of Cleomaceae. We estimated divergence times and biogeographic analyses to explore the origin and diversification of the family. Seed morphology across extant taxa was documented with multifocal image‐stacking techniques and morphological characters were extracted, analyzed, and compared to fossil records.ResultsWe recovered a well‐supported and resolved phylogenetic tree of Cleomaceae generic relationships that includes 236 (~86%) species. We identified 11 principal clades and confidently placed Cleomella as sister to the rest of the family. Our analyses suggested that Cleomaceae and Brassicaceae diverged ~56 mya, and Cleomaceae began to diversify ~53 mya in the Palearctic and Africa. Multiple transatlantic disjunct distributions were identified. Seeds were imaged from 218 (~80%) species in the family and compared to all known fossil species.ConclusionsOur results represent the most comprehensive phylogenetic study of Cleomaceae to date. We identified transatlantic disjunctions and proposed explanations for these patterns, most likely either long‐distance dispersals or contractions in latitudinal distributions caused by climate change over geological timescales. We found that seed morphology varied considerably but mostly mirrored generic relationships.

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.

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.

Dense branching and spines are common features of plant species in ecosystems with high mammalian herbivory pressure. While dense branching and spines can inhibit herbivory independently, when combined, they form a powerful defensive cage architecture. However, how cage architecture evolved under mammalian pressure has remained unexplored. Here we show how dense branching and spines emerged during the age of mammalian radiation in the Combretaceae family and diversified in herbivore-driven ecosystems in the tropics. Phylogenetic comparative methods revealed that modern plant architectural strategies defending against large mammals evolved via a stepwise process. First, dense branching emerged under intermediate herbivory pressure, followed by the acquisition of spines that supported higher speciation rates under high herbivory pressure. Our study highlights the adaptive value of dense branching as part of a herbivore defence strategy and identifies large mammal herbivory as a major selective force shaping the whole plant architecture of woody plants. This study explores the evolution of two traits, branching density and spine presence, in the globally distributed plant family Combretaceae. These traits were found to have appeared in a two-step process in response to mammalian herbivory pressure, revealing the importance of large mammals in the evolution of plant architecture diversity.

Background and aims Quantifying spatial species richness is useful to describe biodiversity patterns across broad geographic areas, especially in large, poorly known plant groups. We explore patterns and predictors of species richness across Africa in one such group; the paleotropical genus Grewia L. (Malvaceae). Methods Grewia species richness was quantified by extracting herbarium records from GBIF and Tropicos and creating geographic grids at varying spatial scales. We assessed predictors of species richness using spatial regression models with 30 environmental variables. We explored species co-occurrence in Madagascar at finer resolutions using Schoener's index, and compared species’ range sizes and IUCN status among ecoregions. Lastly, we derived a trait matrix for a subset of species found in Madagascar to characterize morphological diversity across space. Key Results Grewia species occur in 50 countries in Africa, with the highest number of species in Madagascar (93, with 80 species endemic). Species richness is highest in Madagascar, with up to 23 Grewia species in a grid cell, followed by coastal Tanzania/Kenya (up to 13 species), and northern South Africa and central Angola (11 species each). Across Africa, higher species richness was predicted by variables related to aridity. In Madagascar, a greater range in environmental variables best predicted species richness, consistent with geographic grid cells of highest species richness occurring near biome/ecoregion transitions. In Madagascar we also observe increasing dissimilarity in species composition with increasing geographic distance. Conclusions The spatial patterns and underlying environmental predictors that we uncover in Grewia represent an important step in our understanding of plant distribution and diversity patterns across Africa. Madagascar boasts nearly twice the Grewia species richness, compared to the second most species-rich country in Africa, which might be explained by complex topography and environmental conditions across small spatial scales.

Aim The aim of this study was to further advance our understanding of the species-rich, and ecologically important angiosperm family Combretaceae to provide new insights into their evolutionary history. We assessed phylogenetic relationships in the family using target capture data and produced a dated phylogenetic tree to assess fruit dispersal modes and patterns of distribution. Location Tropical and subtropical regions. Time Period Cretaceous to present. Major Taxa Studied Family Combretaceae is a member of the rosid clade and comprises 10 genera and more than 500 species, predominantly assigned to genera Combretum and Terminalia, and occurring on all continents and in a wide range of ecosystems. Methods We use a target capture approach and the Angiosperms353 universal probes to reconstruct a robust dated phylogenetic tree for the family. This phylogenetic framework, combined with seed dispersal traits, biome data and biogeographic ranges, allows the reconstruction of the biogeographical history of the group. Results Ancestral range reconstructions suggest a Gondwanan origin (Africa/South America), with several intercontinental dispersals within the family and few transitions between biomes. Relative abundance of fruit dispersal types differed by both continent and biome. However, intercontinental colonizations were only significantly enhanced by water dispersal (drift fruit), and there was no evidence that seed dispersal modes influenced biome shifts. Main Conclusions Our analysis reveals a paradox as drift fruit greatly enhanced dispersal distances at intercontinental scale but did not affect the strong biome conservatism observed.

Designing multispecies systems with suitable climatic affinity and identifying species' vulnerability under human‐driven climate change are current challenges to achieve successful adaptation of natural systems. To address this problem, we need to (1) identify groups of species with climatic similarity under climate scenarios and (2) identify areas with high conservation value under predicted climate change.To recognize species with similar climatic niche requirements that can be grouped for mixed cropping in Brazil, we employed ecological niche models (ENMs) and Spearman's ρ for overlap. We also used prioritization algorithms to map areas of high conservation value using two Shared Socioeconomic Pathways (SSP2‐4.5 and SSP5‐8.5) to assess mid‐term (2041–2060) and long‐term (2061–2080) climate change impacts.We identified 15 species groups with finer climatic affinities at different times depicted on hierarchical clustering dendrograms, which can be combined into agroecological agroforestry systems. Furthermore, we highlight the climatically suitable areas for these groups of species, thus providing an outlook of where different species will need to be planted over time to be conserved. In addition, we observed that climate change is predicted to modify the spatial association of these groups under different future climate scenarios, causing a mean negative change in species climatic similarity of 9.5% to 13.7% under SSP2‐4.5 scenario and 9.5% to 10.5% under SSP5‐8.5, for 2041–2060 and 2061–2080, respectively.Synthesis and applications. Our findings provide a framework for agroforestry conservation. The groups of species with finer climatic affinities identified and the climatically suitable areas can be combined into agroecological productive systems, and provide an outlook of where different species may be planted over time. In addition, the conservation priority zones displaying high climate stability for each species individually and all at once can be incorporated into Brazil's conservation plans by policymakers to prioritize specific sites. Lastly, we urge policymakers, conservation organizations and donors to promote interventions involving farmers and local communities, since the species' evaluated have proven to maintain landscapes with productive forest fragments and can be conserved in different Brazilian ecosystems.

Plants are a rich source of bioactive compounds and a number of plant-derived antiplasmodial compounds have been developed into pharmaceutical drugs for the prevention and treatment of malaria, a major public health challenge. However, identifying plants with antiplasmodial potential can be time-consuming and costly. One approach for selecting plants to investigate is based on ethnobotanical knowledge which, though having provided some major successes, is restricted to a relatively small group of plant species. Machine learning, incorporating ethnobotanical and plant trait data, provides a promising approach to improve the identification of antiplasmodial plants and accelerate the search for new plant-derived antiplasmodial compounds. In this paper we present a novel dataset on antiplasmodial activity for three flowering plant families – Apocynaceae, Loganiaceae and Rubiaceae (together comprising c. 21,100 species) – and demonstrate the ability of machine learning algorithms to predict the antiplasmodial potential of plant species. We evaluate the predictive capability of a variety of algorithms – Support Vector Machines, Logistic Regression, Gradient Boosted Trees and Bayesian Neural Networks – and compare these to two ethnobotanical selection approaches – based on usage as an antimalarial and general usage as a medicine. We evaluate the approaches using the given data and when the given samples are reweighted to correct for sampling biases. In both evaluation settings each of the machine learning models have a higher precision than the ethnobotanical approaches. In the bias-corrected scenario, the Support Vector classifier performs best – attaining a mean precision of 0.67 compared to the best performing ethnobotanical approach with a mean precision of 0.46. We also use the bias correction method and the Support Vector classifier to estimate the potential of plants to provide novel antiplasmodial compounds. We estimate that 7677 species in Apocynaceae, Loganiaceae and Rubiaceae warrant further investigation and that at least 1300 active antiplasmodial species are highly unlikely to be investigated by conventional approaches. While traditional and Indigenous knowledge remains vital to our understanding of people-plant relationships and an invaluable source of information, these results indicate a vast and relatively untapped source in the search for new plant-derived antiplasmodial compounds.