Eduard Dämel

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.

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.

We examined the phylogeny and biogeography of the glassperch family Ambassidae (Teleostei), which is widely distributed in the freshwater, brackish and marine coastal habitats across the Indo-West Pacific region. We first built a comprehensive time-calibrated phylogeny of Ambassidae using five genes. We then used this tree to reconstruct the evolution of the salinity preference and ancestral areas. Our results indicate that the two largest genera of Ambassidae, Ambassis and Parambassis, are each not monophyletic. The most recent common ancestor of Ambassidae was freshwater adapted and lived in Australia about 56 million years ago. Three independent freshwater-to-marine transitions are inferred, but no marine-to-freshwater ones. To explain the distribution of ambassids, we hypothesise two long-distance marine dispersal events from Australia. A first event was towards Southeast Asia during the early Cenozoic, followed by a second one towards Africa during mid-Cenozoic. The phylogenetic signal associated with the salinity adaptation of these events was not detected, possibly because of the selective extinction of intermediate marine lineages. The Ambassidae shares two characteristics with other freshwater fish groups distributed in continental regions surrounding the Indian Ocean: They are too young to support the hypothesis that their distribution is the result of the fragmentation of Gondwana, but they did not retain the phylogenetic signal of their marine dispersal.

Many studies have quantified ecological impacts of individual foundation species (FS). However, emerging data suggest that FS often co‐occur, potentially inhibiting or facilitating one another, thereby causing indirect, cascading effects on surrounding communities. Furthermore, global warming is accelerating, but little is known about how interactions between co‐occurring FS vary with temperature.Shallow aquatic sedimentary systems are often dominated by three types of FS: slower‐growing clonal angiosperms, faster‐growing solitary seaweeds, and shell‐forming filter‐ and deposit‐feeding bivalves. Here, we tested the impacts of one FS on another by analyzing manipulative interaction experiments from 148 papers with a global meta‐analysis.We calculated 1,942 (non‐independent) Hedges’ g effect sizes, from 11,652 extracted values over performance responses, such as abundances, growths or survival of FS, and their associated standard deviations and replication levels. Standard aggregation procedures generated 511 independent Hedges’ g that was classified into six types of reciprocal impacts between FS.We found that (i) seaweeds had consistent negative impacts on angiosperms across performance responses, organismal sizes, experimental approaches, and ecosystem types; (ii) angiosperms and bivalves generally had positive impacts on each other (e.g., positive effects of angiosperms on bivalves were consistent across organismal sizes and experimental approaches, but angiosperm effect on bivalve growth and bivalve effect on angiosperm abundance were not significant); (iii) bivalves positively affected seaweeds (particularly on growth responses); (iv) there were generally no net effects of seaweeds on bivalves (except for positive effect on growth) or angiosperms on seaweeds (except for positive effect on ‘other processes’); and (v) bivalve interactions with other FS were typically more positive at higher temperatures, but angiosperm‐seaweed interactions were not moderated by temperature.Synthesis: Despite variations in experimental and spatiotemporal conditions, the stronger positive interactions at higher temperatures suggest that facilitation, particularly involving bivalves, may become more important in a future warmer world. Importantly, addressing research gaps, such as the scarcity of FS interaction experiments from tropical and freshwater systems and for less studied species, as well as testing for density‐dependent effects, could better inform aquatic ecosystem conservation and restoration efforts and broaden our knowledge of FS interactions in the Anthropocene.

AbstractAcacialongifolia (Sydney golden wattle) is considered one of the most problematic plant invaders in Mediterranean-type ecosystems. In this study, we investigate the species’ invasion history by comparing the genetic diversity and structure of native (Australia) and several invasive range (Brazil, Portugal, South Africa, Spain, and Uruguay) populations and by modelling different introduction scenarios using these data. We sampled 272 A.longifolia individuals – 126 from different invasive ranges and 146 from the native range – from 41 populations. We genotyped all individuals at four chloroplast and 12 nuclear microsatellite markers. From these data we calculated diversity metrics, identified chloroplast haplotypes, and estimated population genetic structure based on Bayesian assignment tests. We used Approximate Bayesian Computation (ABC) models to infer the likely introduction history into each invaded country. In Australia, population genetic structure of A.longifolia appears to be strongly shaped by the Bass Strait and we identified two genetic clusters largely corresponding to mainland Australian and Tasmanian populations. We found invasive populations to represent a mixture of these clusters. Similar levels of genetic diversity were present in native and invasive ranges, indicating that invasive populations did not go through a genetic bottleneck. Bayesian assignment tests and chloroplast haplotype frequencies further suggested a secondary introduction event between South Africa and Portugal. However, ABC analyses could not confidently identify the native source(s) of invasive populations in these two countries, probably due to the known high propagule pressure that accompanied these introductions. ABC analyses identified Tasmania as the likely source of invasive populations in Brazil and Uruguay. A definitive native source for Spanish populations could also not be identified. This study shows that tracing the introduction history of A.longifolia is difficult, most likely because of the complexity associated with the extensive movement of the species around the world. Our findings should be considered when planning management and control efforts, such as biological control, in some invaded regions.

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.

Outside humans, true agriculture was previously thought to be restricted to social insects farming fungus. However, obligate farming of plants by ants was recently discovered in Fiji, prompting a re-examination of plant cultivation by ants. Here, we generate a database of plant cultivation by ants, identify three main types, and show that these interactions evolved primarily for shelter rather than food. We find that plant cultivation evolved at least 65 times independently for crops (~200 plant species), and 15 times in farmer lineages (~37 ant taxa) in the Neotropics and Asia/Australasia. Because of their high evolutionary replication, and variation in partner dependence, these systems are powerful models to unveil the steps in the evolution and ecology of insect agriculture.

Our understanding of broad-scale biodiversity and functional trait patterns is largely based on plants, and relatively little information is available on soil arthropods. Here, we investigated the distribution of termite diversity globally and morphological traits and diversity across China. Our analyses showed increasing termite species richness with decreasing latitude at both the globally, and within-China. Additionally, we detected obvious latitudinal trends in the mean community value of termite morphological traits on average, with body size and leg length decreasing with increasing latitude. Furthermore, temperature, NDVI and water variables were the most important drivers controlling the variation in termite richness, and temperature and soil properties were key drivers of the geographic distribution of termite morphological traits. Our global termite richness map is one of the first high resolution maps for any arthropod group and especially given the functional importance of termites, our work provides a useful baseline for further ecological analysis.

The massive influxes of pelagic Sargassum and Physalia physalis have become an increasingly recurrent phenomenon on the Atlantic coasts, affecting the economy and the structure of coastal ecosystems. For the first time, a study assesses the simultaneous arrival of these pelagic organisms. This study was conducted from June/2019 through June/2021 on the littoral of La Habana, one of the circulation points of the currents that form the North Atlantic Subtropical Gyre (NASG) run. Transects of 40 m were located parallel to the shoreline, the biomass of pelagic Sargassum was weighed, and the number of colonies of P. physalis was counted at the intertidal zone. The biomass of pelagic Sargassum was estimated as dry biomass. The simultaneous arrival of pelagic Sargassum and P. physalis was reported. Simultaneous arrivals of these pelagic species were recorded in the winter seasons, with the occurrence of cold fronts, low mean temperatures (22–27 °C), and strong northerly winds. Most months with the arrival of these pelagic species coincided with a negative average magnitude of the Arctic Oscillation Index, which favors the occurrence of cold fronts and northerly winds. The mean landing dry biomass of Sargassum during the peak months was low (0.73 ± 0.54 kg/m2) compared to the Mexican Caribbean. 145 P. physalis colonies over 100 m of coast length per year were reported during the study period. The higher visual occurrence of Sargassum natans I and the higher percentage of left-handed P. physalis colonies (56.16 ± 3.37) may indicate that the NASG area, which encloses the Sargasso Sea, could be the primary source of arrivals to La Habana littoral. As reported, the distribution of sightings of pelagic Sargassum and P. physalis coincided in several regions in the Atlantic Ocean and represents an urgent call for coordinated monitoring and development of predictive forecasting of beach landings. This work suggests that there are Atlantic coastal sites such as La Habana littoral that could host the dangerous simultaneous arrivals of pelagic Sargassum and P. physalis. Finally, the use of remote sensing techniques with in situ observations is considered important for future work, since using remote sensing techniques alone seems to miss important events such as those documented in this study.

The early Eocene (∼56‐48 million years ago) is characterised by high CO2 estimates (1200‐2500 ppmv) and elevated global temperatures (∼10 to 16°C higher than modern). However, the response of the hydrological cycle during the early Eocene is poorly constrained, especially in regions with sparse data coverage (e.g. Africa). Here we present a study of African hydroclimate during the early Eocene, as simulated by an ensemble of state‐of‐the‐art climate models in the Deep‐time Model Intercomparison Project (DeepMIP). A comparison between the DeepMIP pre‐industrial simulations and modern observations suggests that model biases are model‐ and geographically dependent, however these biases are reduced in the model ensemble mean. A comparison between the Eocene simulations and the pre‐industrial suggests that there is no obvious wetting or drying trend as the CO2 increases. The results suggest that changes to the land sea mask (relative to modern) in the models may be responsible for the simulated increases in precipitation to the north of Eocene Africa. There is an increase in precipitation over equatorial and West Africa and associated drying over northern Africa as CO2 rises. There are also important dynamical changes, with evidence that anticyclonic low‐level circulation is replaced by increased south‐westerly flow at high CO2 levels. Lastly, a model‐data comparison using newly‐compiled quantitative climate estimates from palaeobotanical proxy data suggests a marginally better fit with the reconstructions at lower levels of CO2.