William Edington Armit

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.

Risk analysis plays a crucial role in regulating and managing alien and invasive species but can be time-consuming and costly. Alternatively, combining invasion and impact history with species distribution models offers a cost-effective and time-efficient approach to assess invasion risk and identify species for which a comprehensive risk analysis should take precedence. We conducted such an assessment for six traded alien fern species, determining their invasion risk in countries where they are traded. Four of the species (Dicksonia antarctica, Dryopteris erythrosora, Lygodium japonicum, and Phlebodium aureum) showed limited global distributions, while Adiantum raddianum and Sphaeropteris cooperi had broader distributions. A. raddianum, however, was the only species found to pose a high invasion risk in two known trade countries – the USA and Australia – and requires a complete risk analysis to determine the appropriate regulatory responses. Dicksonia antarctica, Phlebodium aureum (for New Zealand), and Dryopteris erythrosora (for the USA) posed a medium risk of invasion due to the lack of evidence of impacts, and a complete risk analysis is thus deemed less crucial for these species in these countries. For other species, suitable environments were not predicted in the countries where they are traded, thus the risk of invasion is low, and a complete risk analysis is not required. For species in countries where suitable environments are predicted but no trade information or presence data are available, risk assessments are recommended to better determine the risk posed. Despite the relatively limited potential global distribution of the studied ferns relative to other major plant invaders (e.g., Pinus spp. and Acacia spp.), their history of invasion, documented impacts in pristine environments, and high propagule pressure from trade warrants concern, possibly necessitating legislative and regulatory measures in environmentally suitable regions.

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.

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.

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.

Paleoclimate reconstructions can provide a window into the environmental conditions in Earth history when atmospheric carbon dioxide concentrations were higher than today. In the eastern USA, paleoclimate reconstructions are sparse, because terrestrial sedimentary deposits are rare. Despite this, the eastern USA has the largest population and population density in North America, and understanding the effects of current and future climate change is of vital importance. Here, we provide terrestrial paleoclimate reconstructions of the eastern USA from Miocene fossil floras. Additionally, we compare proxy paleoclimate reconstructions from the warmest period in the Miocene, the Miocene Climatic Optimum (MCO), to those of an MCO Earth System Model. Reconstructed Miocene temperatures and precipitation north of 35°N are higher than modern. In contrast, south of 35°N, temperatures and precipitation are similar to today, suggesting a poleward amplification effect in eastern North America. Reconstructed Miocene rainfall seasonality was predominantly higher than modern, regardless of latitude, indicating greater variability in intra-annual moisture transport. Reconstructed climates are almost uniformly in the temperate seasonal forest biome, but heterogeneity of specific forest types is evident. Reconstructed Miocene terrestrial temperatures from the eastern USA are lower than modeled temperatures and coeval Atlantic sea surface temperatures. However, reconstructed rainfall is consistent with modeled rainfall. Our results show that during the Miocene, climate was most different from modern in the northeastern states, and may suggest a drastic reduction in the meridional temperature gradient along the North American east coast compared to today.

Striga asiatica (dicot), an obligate hemiparasitic of monocots, is a potential threat to South America. Determining the ecological factors that explain the occurrence and predicting suitable areas for S. asiatica are fundamental for designing prevention strategies. We developed a Spatio-temporal dynamics model and evaluated Brazil's Weekly Growth Index (GIW) for S. asiatica. We analyzed four Brazilian regions (Central-West, South, Southeast, and Northeast) to verify the local seasonal variation of the species in climatic data. Our results indicated areas with favorable climatic suitability for the species in part of South America. Seasonal assessment models showed that high rainfall and the dry and cold periods common in tropical regions affect the GIW for S. asiatica. When we associate periods with maximum rainfall of 53 mm per week and temperature above 20 °C, the GIW approaches the optimal index for the regions evaluated, indicating the influence of soil moisture and air temperature. Our risk assessment indicated that the Southeast and Northeast are at the most significant risk of S. asiatica invasion. Projections for climate change between 2040–2059 showed expansions in areas suitable for S. asiatica compared to the current climate of South America.

Climate change has significantly affected global agricultural production, particularly in arid zones of Central Asia. Thus, we analyzed changes in the habitat suitability of cotton in Central Asia under various shared socioeconomic pathway (SSP) scenarios during 2021–2060. The results showed that the average minimum temperature in April, precipitation seasonality, and distance to rivers were the main environmental factors influencing the suitable distribution of cotton. Suitable habitats expanded toward the north and east, reaching a maximum net increase of 10.85 × 104 km2 under the SSP5–8.5 scenario during 2041–2060, while habitats in the southwestern area showed a contracting trend. The maximum decreased and increased habitats were concentrated at approximately 68°E and 87°E, respectively. In addition, their latitudinal distributions were concentrated at approximately 40°N and 44°N. The longitudinal and latitudinal dividing lines of increased and decreased habitats were 69°E and 41°N, respectively. Habitats at the same altitude showed an increasing trend, excluding the elevation range of 125–325 m. Habitat shifts could exacerbate spatial conflicts with forest/grassland and natural reserves. The maximum spatial overlap between them was observed under the SSP5–8.5 scenario during 2041–2060. These findings could provide scientific evidence for rational cotton cultivation planning in global arid zones.