Mark Newman

Predicting the likelihood that non-native species will be introduced into new areas remains one of conservation’s greatest challenges and, consequently, it is necessary to adopt adequate management measures to mitigate the effects of future biological invasions. At present, not much information is available on the areas in which non-native aquatic plant species could establish themselves in the Iberian Peninsula. Species distribution models were used to predict the potential invasion risk of (1) non-native aquatic plant species already established in the peninsula (32 species) and (2) those with the potential to invade the peninsula (40 species). The results revealed that the Iberian Peninsula contains a number of areas capable of hosting non-native aquatic plant species. Areas under anthropogenic pressure are at the greatest risk of invasion, and the variable most related to invasion risk is temperature. The results of this work were used to create the Invasion Risk Atlas for Alien Aquatic Plants in the Iberian Peninsula, a novel online resource that provides information about the potential distribution of non-native aquatic plant species. The atlas and this article are intended to serve as reference tools for the development of public policies, management regimes, and control strategies aimed at the prevention, mitigation, and eradication of non-native aquatic plant species.

Paleogene flower-insect interactions and paleo-pollination processes are, in general, poorly understood and fossil evidence for such floral and faunal interactions are rarely reported. To shed light on angiosperm flower-insect interactions, we investigated several hundred fossil flowers and insects from the middle Eocene Fossil Lagerstätte of Eckfeld, Germany. During our work, we discovered a unique fossil Ludwigia flower (bud) with in situ pollen. The ecological preferences (climate, biome, habitat, etc.) of extant Ludwigia and the paleoecological configurations of the fossil plant assemblage support the taxonomic affiliation of the flower bud and an Eocene presence of Ludwigia in the vicinity of the former Lake Eckfeld. Today’s Ludwigia are mostly pollinated by Hymenoptera (bees). Therefore, we screened all currently known hymenopteran fossils from Eckfeld but found no Ludwigia pollen adhering to any of the specimens. On the contrary, we discovered Ludwigia pollen adhering to two different groups of Coleoptera (beetles). Our study suggests that during the Eocene of Europe, Ludwigia flowers were visited and probably pollinated by beetles and over time there was a shift in primary flower visitors/pollinators, from beetles to bees, sometime during the late Paleogene to Neogene.

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.

Understanding the interactions between abiotic (environmental and anthropogenic) factors and species diversity and distribution patterns is fundamental to improving the ecological representativeness of biodiversity management tools such as protected areas (PAs). However, significant knowledge gaps remain about how species’ ecological and evolutionary opportunities are associated with abiotic factors, especially in biodiversity-rich but economically ill-equipped countries such as Kenya. Here, we explored the interactions of terrestrial mammal diversity patterns and abiotic factors across species groups and ecoregions in Kenya. We coupled data on terrestrial mammal occurrences, phylogeny, functional traits, and environmental predictors in Kenya to derive multiple diversity indices, encompassing species richness and phylogenetic and functional richness, and mean pairwise and nearest taxon distances. We explored the interactions of these indices with several abiotic factors using multivariate regression analyses while adjusting for spatial autocorrelation. The results showed weak correlations between species richness versus the phylogenetic and functional diversity indices. The best-fit models explained variable proportions of diversity indices between species groups and ecoregions and consistently retained annual temperature and precipitation averages and seasonality and human footprint as the strongest predictors. Compared to the species-poor xeric northern and eastern Kenya regions, the predictors had weak associations with diversity variances in the species-rich mesic western and central Kenya regions, similar to focal species groups compared to ordinal classifications and the combined species pool. These findings illustrate that climate and human footprint interplay determine multiple facets of terrestrial mammal diversity patterns in Kenya. Accordingly, curbing human activities degrading long-term climatic regimes is vital to ensuring the ecological integrity of terrestrial mammal communities and should be integrated into biodiversity management frameworks. For a holistic representation of critical conservation areas, biodiversity managements should also prioritize terrestrial mammal phylogenetic and functional attributes besides species richness.

Aim Fruit selection by animal dispersers with different mobility directly impacts plant geographical range size, which, in turn, may impact plant diversification. Here, we examine the interaction between fruit colour, range size and diversification rate in palms by testing two hypotheses: (1) species with fruit colours attractive to birds have larger range sizes due to high dispersal ability and (2) disperser mobility affects whether small or large range size has higher diversification, and intermediate range size is expected to lead to the highest diversification rate regardless of disperser. Location Global. Time Period Contemporary (or present). Major Taxa Studied Palms (Arecaceae). Methods Palm species were grouped based on likely animal disperser group for given fruit colours. Range sizes were estimated by constructing alpha convex hull polygons from distribution data. We examined disperser group, range size or an interaction of both as possible drivers of change in diversification rate over time in a likelihood dynamic model (Several Examined State-dependent Speciation and Extinction [SecSSE]). Models were fitted, rate estimates were retrieved and likelihoods were compared to those of appropriate null models. Results Species with fruit colours associated with mammal dispersal had larger ranges than those with colours associated with bird dispersal. The best fitting SecSSE models indicated that the examined traits were not the primary driver of the heterogeneity in diversification rates in the model. Extinction rate complexity had a marked impact on model performance and on diversification rates. Main Conclusions Two traits related to dispersal mobility, range size and fruit colour, were not identified as the main drivers of diversification in palms. Increased model extinction rate complexity led to better performing models, which indicates that net diversification should be estimated rather than speciation alone. However, increased complexity may lead to incorrect SecSSE model conclusions without careful consideration. Finally, we find palms with more mobile dispersers do not have larger range sizes, meaning other factors are more important determinants of range size.

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.

Complex distribution data can be summarized by grouping species with similar or overlapping distributions to unravel spatial patterns and separate trends (e.g., of habitat loss) among spatially unique groups. However, such classifications are often heuristic, lacking the transparency, objectivity, and data‐driven rigor of quantitative methods, which limits their interpretability and utility. Here, we develop and illustrate the clustering of spatially associated species, a methodological framework aimed at statistically classifying species using explicit measures of interspecific spatial association. We investigate several association indices and clustering algorithms and show how these methodological choices drive substantial variations in clustering outcomes and performance. To facilitate robust decision‐making, we provide guidance on choosing methods appropriate to one's study objective(s). As a case study, we apply our framework to modeled tree distributions in Borneo and subsequently evaluate the impact of land‐cover change on separate species groupings. Based on the modeled distribution of 390 tree species prior to anthropogenic land‐cover changes, we identified 11 distinct clusters that unraveled ecologically meaningful patterns in Bornean tree distributions. These clusters then enabled us to quantify trends of habitat loss tied to each of those specific clusters, allowing us to discern particularly vulnerable species clusters and their distributions. This study demonstrates the advantages of adopting quantitatively derived clusters of spatially associated species and elucidates the potential of resultant clusters as a spatially explicit framework for investigating distribution‐related questions in ecology, biogeography, and conservation. By adopting our methodological framework and publicly available codes, practitioners can leverage the ever‐growing abundance of distribution data to better understand complex spatial patterns among species distributions and the disparate effects of global changes on biodiversity.

Many tree genera in the Malesian uplands have Southern Hemisphere origins, often supported by austral fossil records. Weathering the vast bedrock exposures in the everwet Malesian tropics may have consumed sufficient atmospheric CO2 to contribute significantly to global cooling over the past 15 Myr. However, there has been no discussion of how the distinctive regional tree assemblages may have enhanced weathering and contributed to this process. We postulate that Gondwanan‐sourced tree lineages that can dominate higher‐elevation forests played an overlooked role in the Neogene CO2 drawdown that led to the Ice Ages and the current, now‐precarious climate state. Moreover, several historically abundant conifers in Araucariaceae and Podocarpaceae are likely to have made an outsized contribution through soil acidification that increases weathering. If the widespread destruction of Malesian lowland forests continues to spread into the uplands, the losses will threaten unique austral plant assemblages and, if our hypothesis is correct, a carbon sequestration engine that could contribute to cooler planetary conditions far into the future. Immediate effects include the spread of heat islands, significant losses of biomass carbon and forest‐dependent biodiversity, erosion of watershed values, and the destruction of tens of millions of years of evolutionary history.

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.

The debated vegetation response to climate change can be investigated through palynological fossil records from past extreme climate conditions. In this context, the early Eocene (53.3 to 41.2 million years ago (Ma)) is often referred to as a model for a greenhouse Earth. In the Xining Basin, situated on the North-eastern Tibetan Plateau (NETP), this time interval is represented by an extensive and well-dated sedimentary sequence of evaporites and red mudstones. Here we focus on the palynological record of the Early Eocene Climatic Optimum (EECO; 53.3 to 49.1 Ma) and study the fossil gymnosperm pollen composition in these sediments. In addition, we also investigate the nearest living relatives (NLR) or botanical affinity of these genera and the paleobiogeographic implications of their occurrence in the Eocene of the NETP. To reach our objective, we complemented transmitted light microscopy with laser scanning- and electron microscopy techniques, to produce high-resolution images, and illustrate the morphological variation within fossil and extant gymnosperm pollen. Furthermore, a morphometric analysis was carried out to investigate the infra- and intrageneric variation of these and related taxa. To place the data in context we produced paleobiogeographic maps for Phyllocladidites and for other Podocarpaceae, based on data from a global fossil pollen data base, and compare these with modern records from GBIF. We also assessed the climatic envelope of the NLR. Our analyses confirm the presence of Phyllocladidites (NLR Phyllocladus, Podocarpaceae) and Podocarpidites (NLR Podocarpus, Podocarpaceae) in the EECO deposits in the Xining Basin. In addition, a comparative study based on literature suggests that Parcisporites is likely a younger synonym of Phyllocladidites. Our findings further suggest that the Phyllocladidites specimens are derived from a lineage that was much more diverse than previously thought, and which had a much larger biogeographical distribution during the EECO than at present. Based on the climatic envelope of the NLR, we suggest that the paleoclimatic conditions in the Xining Basin were warmer and more humid during the EECO. We conclude that phylloclade-type conifers typical of the southern-temperate podocarp forests, had a northward geographical expansion during the EECO, followed by extirpation.